Search results for: real time pest tracking
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 21477

Search results for: real time pest tracking

20937 Achieving Shear Wave Elastography by a Three-element Probe for Wearable Human-machine Interface

Authors: Jipeng Yan, Xingchen Yang, Xiaowei Zhou, Mengxing Tang, Honghai Liu

Abstract:

Shear elastic modulus of skeletal muscles can be obtained by shear wave elastography (SWE) and has been linearly related to muscle force. However, SWE is currently implemented using array probes. Price and volumes of these probes and their driving equipment prevent SWE from being used in wearable human-machine interfaces (HMI). Moreover, beamforming processing for array probes reduces the real-time performance. To achieve SWE by wearable HMIs, a customized three-element probe is adopted in this work, with one element for acoustic radiation force generation and the others for shear wave tracking. In-phase quadrature demodulation and 2D autocorrelation are adopted to estimate velocities of tissues on the sound beams of the latter two elements. Shear wave speeds are calculated by phase shift between the tissue velocities. Three agar phantoms with different elasticities were made by changing the weights of agar. Values of the shear elastic modulus of the phantoms were measured as 8.98, 23.06 and 36.74 kPa at a depth of 7.5 mm respectively. This work verifies the feasibility of measuring shear elastic modulus by wearable devices.

Keywords: shear elastic modulus, skeletal muscle, ultrasound, wearable human-machine interface

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20936 Comparative Analysis of Real and Virtual Garment Fit

Authors: Kristina Ancutiene

Abstract:

The goal of this research is to perform comparative analysis between the virtual fit of the woman's dress and the fit on a real person. The dress fitting was done using mechanical and structural parameters of the 100 % linen fabric and using Modaris_3D_Fit software (CAD Lectra). The dress was also sawn after which garment fit differences of real and virtual dress was researched. Four respondents whose figures were similar were used to evaluate the ease and strain deformations of the real and virtual dress. The scores that were given by the respondents wearing the real dress were compared to the ease and strain results that were given by the software. The main result was that respondents feel similar to the virtual stretch deformations but their ease feeling is not always matching the virtual ones. The results may be influenced by psychological factors and different understanding about purpose of garment.

Keywords: virtual garment, 3D CAD, garment fit, mechanical properties

Procedia PDF Downloads 343
20935 Chassis Level Control Using Proportional Integrated Derivative Control, Fuzzy Logic and Deep Learning

Authors: Atakan Aral Ormancı, Tuğçe Arslantaş, Murat Özcü

Abstract:

This study presents the design and implementation of an experimental chassis-level system for various control applications. Specifically, the height level of the chassis is controlled using proportional integrated derivative, fuzzy logic, and deep learning control methods. Real-time data obtained from height and pressure sensors installed in a 6x2 truck chassis, in combination with pulse-width modulation signal values, are utilized during the tests. A prototype pneumatic system of a 6x2 truck is added to the setup, which enables the Smart Pneumatic Actuators to function as if they were in a real-world setting. To obtain real-time signal data from height sensors, an Arduino Nano is utilized, while a Raspberry Pi processes the data using Matlab/Simulink and provides the correct output signals to control the Smart Pneumatic Actuator in the truck chassis. The objective of this research is to optimize the time it takes for the chassis to level down and up under various loads. To achieve this, proportional integrated derivative control, fuzzy logic control, and deep learning techniques are applied to the system. The results show that the deep learning method is superior in optimizing time for a non-linear system. Fuzzy logic control with a triangular membership function as the rule base achieves better outcomes than proportional integrated derivative control. Traditional proportional integrated derivative control improves the time it takes to level the chassis down and up compared to an uncontrolled system. The findings highlight the superiority of deep learning techniques in optimizing the time for a non-linear system, and the potential of fuzzy logic control. The proposed approach and the experimental results provide a valuable contribution to the field of control, automation, and systems engineering.

Keywords: automotive, chassis level control, control systems, pneumatic system control

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20934 Obstacle Avoidance Using Image-Based Visual Servoing Based on Deep Reinforcement Learning

Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

Abstract:

This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

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20933 Gaze Patterns of Skilled and Unskilled Sight Readers Focusing on the Cognitive Processes Involved in Reading Key and Time Signatures

Authors: J. F. Viljoen, Catherine Foxcroft

Abstract:

Expert sight readers rely on their ability to recognize patterns in scores, their inner hearing and prediction skills in order to perform complex sight reading exercises. They also have the ability to observe deviations from expected patterns in musical scores. This increases the “Eye-hand span” (reading ahead of the point of playing) in order to process the elements in the score. The study aims to investigate the gaze patterns of expert and non-expert sight readers focusing on key and time signatures. 20 musicians were tasked with playing 12 sight reading examples composed for one hand and five examples composed for two hands to be performed on a piano keyboard. These examples were composed in different keys and time signatures and included accidentals and changes of time signature to test this theory. Results showed that the experts fixate more and for longer on key and time signatures as well as deviations in examples for two hands than the non-expert group. The inverse was true for the examples for one hand, where expert sight readers showed fewer and shorter fixations on key and time signatures as well as deviations. This seems to suggest that experts focus more on the key and time signatures as well as deviations in complex scores to facilitate sight reading. The examples written for one appeared to be too easy for the expert sight readers, compromising gaze patterns.

Keywords: cognition, eye tracking, musical notation, sight reading

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20932 Requirements to Establish a Taxi Sharing System in an Urban Area

Authors: Morteza Ahmadpur, Ilgin Gokasar, Saman Ghaffarian

Abstract:

That Transportation system plays an important role in management of societies is an undeniable fact and it is one of the most challenging issues in human beings routine life. But by increasing the population in urban areas, the demand for transportation modes also increase. Accordingly, it is obvious that more flexible and dynamic transportation system is required to satisfy peoples’ requirements. Nowadays, there is significant increase in number of environmental issues all over the world which is because of human activities. New technological achievements bring new horizons for humans and so they changed the life style of humans in every aspect of their life and transportation is not an exception. By using new technology, societies can modernize their transportation system and increase the feasibility of their system. Real–time Taxi sharing systems is one of the novel and most modern systems all over the world. For establishing this kind of system in an urban area it is required to use the most advanced technologies in a transportation system. GPS navigation devices, computers and social networks are just some parts of this kind of system. Like carpooling, real-time taxi sharing is one of the best ways to better utilize the empty seats in most cars and taxis, thus decreasing energy consumption and transport costs. It can serve areas not covered by a public transit system and act as a transit feeder service. Taxi sharing is also capable of serving one-time trips, not only recurrent commute trips or scheduled trips. In this study, we describe the requirements and parameters that we need to establish a useful real-time ride sharing system for an urban area. The parameters and requirements of this study can be used in any urban area.

Keywords: transportation, intelligent transportation systems, ride-sharing, taxi sharing

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20931 A Novel Technological Approach to Maintaining the Cold Chain during Transportation

Authors: Philip J. Purnell

Abstract:

Innovators propose to use the Internet of Things to solve the problem of maintaining the cold chain during the transport of biopharmaceutical products. Sending a data logger with refrigerated goods is only useful to inform the recipient of the goods that they have either breached the cold chain and are therefore potentially spoiled or that they have not breached it and are therefore assumed to be in good condition. Connecting the data logger to the Internet of Things means that the supply chain manager will be informed in real-time of the exact location and the precise temperature of the material at any point on earth. Readable using a simple online interface, the supply chain manager will watch the progress of their material on a Google map together with accurate and crucially real-time temperature readings. The data logger will also send alarms to the supply chain manager if a cold chain breach becomes imminent allowing them time to contact the transporter and restore the cold chain before the material is affected. This development is expected to save billions of dollars in wasted biologics that currently arrive either spoiled or in an unreliable condition.

Keywords: internet of things, cold chain, data logger, transportation

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20930 Studies on Population and Management of Melon Fruit Fly Bactrocera cucurbitae (Coquillett) in Vegetables Agro-Ecosystem in District Hyderabada

Authors: Abro Zain-Ul-Aabdin, Naheed Baloch, Khuhro Niaz Hussain, Waseem Akbar, Noor Abid Saeed

Abstract:

The Melon Fruit Fly Bactrocera cucurbitae (Coq.) belongs to family: Tephritidae order: Diptera and is distributed throughout the vegetable growing areas of Pakistan. The B. cucurbitae is injurious pest of more than 125 species of the vegetables throughout the world. In the present studies we investigated the population of this important pest in cucurbit crops and influence of abiotic parameters such as: temperature, relative humidity and rainfall. The study was carried out at two different locations of District, Hyderabad. The locations were Jeay Shah and Dehli farm where three cucurbit vegetable crops, such as bottle gourd (Lagenaria siceraria), bitter gourd (Momordica charantia) and ridge gourd (Luffa acutangula) were grown. The traps were baited with Cue-lure and deployed at three meter height in the all locations from 01.01.2015 and up to 30.06.2015. Results revealed that overall significantly higher (P < 0.05) population was recorded on L.acutangula, M.charantia and L.siceraria (130.64, 127.21, and 122.91), respectively. However, significantly higher (P < 0.05) population was observed on L. acutangula (339.4±22.59) during the 4th week of May 2015 followed by M. charantia (334.6±22.76) L. siceraria (333.2±20.13). Whereas; lowest population was recorded on L. siceraria (5.8±1.39) followed by L. acutangula and M. charantia (6.8±0.80g, 8.0±1.30) respectively during the 4th week of January. The population of B. cucurbitae was significantly correlated with the temperature while negatively correlated with relative humidity. Meanwhile in the parasitism preference experiment pupal parasitoid Dirhinus giffardii showed significantly higher (P<0.05) parasitization when the pupae of B.cucurbitae were reared on Cucumber (Cucumis sativus) (24.8±0.48) and also female were yielded from pupae reared on C.sativus under no choice experiment. Similarly higher parasitization and female were recovered when pupae were supplied C. sativus under free choice experiment. Results of the present investigation would be useful in developing a sustainable pest management strategy in the vegetable agro-ecosystem.

Keywords: Dirhinus giffardii, Bactrocera cucurbitae Cucumis sativus, diptera, free choice, parasitization

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20929 Short-Term Operation Planning for Energy Management of Exhibition Hall

Authors: Yooncheol Lee, Jeongmin Kim, Kwang Ryel Ryu

Abstract:

This paper deals with the establishment of a short-term operational plan for an air conditioner for efficient energy management of exhibition hall. The short-term operational plan is composed of a time series of operational schedules, which we have searched using genetic algorithms. Establishing operational schedule should be considered the future trends of the variables affecting the exhibition hall environment. To reflect continuously changing factors such as external temperature and occupant, short-term operational plans should be updated in real time. But it takes too much time to evaluate a short-term operational plan using EnergyPlus, a building emulation tool. For that reason, it is difficult to update the operational plan in real time. To evaluate the short-term operational plan, we designed prediction models based on machine learning with fast evaluation speed. This model, which was created by learning the past operational data, is accurate and fast. The collection of operational data and the verification of operational plans were made using EnergyPlus. Experimental results show that the proposed method can save energy compared to the reactive control method.

Keywords: exhibition hall, energy management, predictive model, simulation-based optimization

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20928 Triplex Detection of Pistacia vera, Arachis hypogaea and Pisum sativum in Processed Food Products Using Probe Based PCR

Authors: Ergün Şakalar, Şeyma Özçirak Ergün, Emrah Yalazi̇, Emine Altinkaya, Cengiz Ataşoğlu

Abstract:

In recent years, food allergies which cause serious health problems affect to public health around the world. Foodstuffs which contain allergens are either intentionally used as ingredients or are encased as contaminant in food products. The prevalence of clinical allergy to peanuts and nuts is estimated at about 0.4%-1.1% of the adult population, representing the allergy to pistachio the 7% of the cases of tree nut causing allergic reactions. In order to protect public health and enforce the legislation, methods for sensitive analysis of pistachio and peanut contents in food are required. Pea, pistachio and peanut are used together, to reduce the cost in food production such as baklava, snack foods.DNA technology-based methods in food analysis are well-established and well-roundedtools for species differentiation, allergen detection. Especially, the probe-based TaqMan real-time PCR assay can amplify target DNA with efficiency, specificity, and sensitivity.In this study, pistachio, peanut and pea were finely ground and three separate series of triplet mixtures containing 0.1, 1, 10, 100, 1000, 10,000 and 100,000 mg kg-1 of each sample were prepared for each series, to a final weight of 100 g. DNA from reference samples and industrial products was successfully extracted with the GIDAGEN® Multi-Fast DNA Isolation Kit. TaqMan probes were designed for triplex determination of ITS, Ara h 3 and pea lectin genes which are specific regions for identification pistachio, peanut and pea, respectively.The real-time PCR as quantitative detected pistachio, peanut and pea in these mixtures down to the lowest investigated level of 0.1, 0.1 and 1 mg kg-1, respectively. Also, the methods reported here are capable of detecting of as little as 0.001% level of peanut DNA, 0,000001% level of pistachio DNA and 0.000001% level of pea DNA. We accomplish that the quantitative triplex real-time PCR method developed in this study canbe applied to detect pistachio, peanut and peatraces for three allergens at once in commercial food products.

Keywords: allergens, DNA, real-time PCR, TaqMan probe

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20927 The Impact of Exchange Rate Volatility on Real Total Export and Sub-Categories of Real Total Export of Malaysia

Authors: Wong Hock Tsen

Abstract:

This study aims to investigate the impact of exchange rate volatility on real export in Malaysia. The moving standard deviation with order three (MSD(3)) is used for the measurement of exchange rate volatility. The conventional and partially asymmetric autoregressive distributed lag (ARDL) models are used in the estimations. This study finds exchange rate volatility to have significant impact on real total export and some sub-categories of real total export. Moreover, this study finds that the positive or negative exchange rate volatility tends to have positive or negative impact on real export. Exchange rate volatility can be harmful to export of Malaysia.

Keywords: exchange rate volatility, autoregressive distributed lag, export, Malaysia

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20926 Deep Learning-Based Object Detection on Low Quality Images: A Case Study of Real-Time Traffic Monitoring

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

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20925 Harmonic Mitigation and Total Harmonic Distortion Reduction in Grid-Connected PV Systems: A Case Study Using Real-Time Data and Filtering Techniques

Authors: Atena Tazikeh Lemeski, Ismail Ozdamar

Abstract:

This study presents a detailed analysis of harmonic distortion in a grid-connected photovoltaic (PV) system using real-time data captured from a solar power plant. Harmonics introduced by inverters in PV systems can degrade power quality and lead to increased Total Harmonic Distortion (THD), which poses challenges such as transformer overheating, increased power losses, and potential grid instability. This research addresses these issues by applying Fast Fourier Transform (FFT) to identify significant harmonic components and employing notch filters to target specific frequencies, particularly the 3rd harmonic (150 Hz), which was identified as the largest contributor to THD. Initial analysis of the unfiltered voltage signal revealed a THD of 21.15%, with prominent harmonic peaks at 150 Hz, 250 Hz and 350 Hz, corresponding to the 3rd, 5th, and 7th harmonics, respectively. After implementing the notch filters, the THD was reduced to 5.72%, demonstrating the effectiveness of this approach in mitigating harmonic distortion without affecting the fundamental frequency. This paper provides practical insights into the application of real-time filtering techniques in PV systems and their role in improving overall grid stability and power quality. The results indicate that targeted harmonic mitigation is crucial for the sustainable integration of renewable energy sources into modern electrical grids.

Keywords: grid-connected photovoltaic systems, fast Fourier transform, harmonic filtering, inverter-induced harmonics

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20924 Optimization of Headspace Solid Phase Microextraction (SPME) Technique Coupled with GC MS for Identification of Volatile Organic Compounds Released by Trogoderma Variabile

Authors: Thamer Alshuwaili, Yonglin Ren, Bob Du, Manjree Agarwal

Abstract:

The warehouse beetle, Trogoderma variabile Ballion (Coleoptera: Dermestidae), is a major pest of packaged and processed stored products. Warehouse beetle is the common name which was given by Okumura (1972). This pest has been reported to infest 119 different commodities, and it is distributed throughout the tropical and subtropical parts of the world. Also, it is difficult to control because of the insect's ability to stay without food for long times, and it can survive for years under dry conditions and low-moisture food, and it has also developed resistance to many insecticides. The young larvae of these insects can cause damage to seeds, but older larvae prefer to feed on whole grains. The percentage of damage caused by these insects range between 30-70% in the storage. T. variabile is the species most responsible for causing significant damage in grain stores worldwide. Trogoderma spp. is a huge problem for cereal grains, and there are many countries, such as the USA, Australia, China, Kenya, Uganda and Tanzania who have specific quarantine regulations against possible importation. Also, grain stocks can be almost completely destroyed because of the massive populations the insect may develop. However, the purpose of the current research was to optimize conditions to collect volatile organic compound from Trogoderma variabile at different life stages by using headspace solid phase microextraction (SPME) coupled with gas chromatography-mass spectrometry (GC-MS) and flame ionization detection (FID). Using SPME technique to extract volatile from insects is an efficient, straightforward and nondestructive method. Result of the study shows that 15 insects were optimal number for larvae and adults. Selection of the number of insects depend on the height of the peak area and the number of peaks. Sixteen hours were optimized as the best extraction time for larvae and 8 hours was the optimal number of adults.

Keywords: Trogoderma variabile, warehouse beetle , GC-MS, Solid phase microextraction

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20923 Application of Electro-Optical Hybrid Cables in Horizontal Well Production Logging

Authors: Daofan Guo, Dong Yang

Abstract:

For decades, well logging with coiled tubing has relied solely on surface data such as pump pressure, wellhead pressure, depth counter, and weight indicator readings. While this data serves the oil industry well, modern smart logging utilizes real-time downhole information, which automatically increases operational efficiency and optimizes intervention qualities. For example, downhole pressure, temperature, and depth measurement data can be transmitted through the electro-optical hybrid cable in the coiled tubing to surface operators on a real-time base. This paper mainly introduces the unique structural features and various applications of the electro-optical hybrid cables which were deployed into downhole with the help of coiled tubing technology. Fiber optic elements in the cable enable optical communications and distributed measurements, such as distributed temperature and acoustic sensing. The electrical elements provide continuous surface power for downhole tools, eliminating the limitations of traditional batteries, such as temperature, operating time, and safety concerns. The electrical elements also enable cable telemetry operation of cable tools. Both power supply and signal transmission were integrated into an electro-optical hybrid cable, and the downhole information can be captured by downhole electrical sensors and distributed optical sensing technologies, then travels up through an optical fiber to the surface, which greatly improves the accuracy of measurement data transmission.

Keywords: electro-optical hybrid cable, underground photoelectric composite cable, seismic cable, coiled tubing, real-time monitoring

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20922 The Effect of Different Cucumber (Cucumis sativus L.) Varieties on Growth and Development Time of Aphis gossypii Glover (Hemiptera: Aphididae)

Authors: Rochelyn Dona, Mohamed F. Nur, Serdar Satar

Abstract:

The biological response of Aphis gossypii Glover (Hom. Aphididae) was investigated on the effects of seven cucumber varieties (Cucumis sativus L.) such as Kitir, Muhika, Ayda, Beit, 14-F1, Ruzgar, and Ptk in the laboratory condition at 24±1°C, 65±5% relative humidity (RH) and a photoperiod of 16:8 (L:D) hour. The results were related that the developmental time of A. gossypii at the nymphal stages was presented a significant difference only on the first instar stage. From the lowest to the highest respectively, 0.98 days on ruzgar to 1.18 days on Kitir, the second nymphal stage 0.98 days to Beit alfa, 1.08 days on Muhika, the third from 0.94 days to Kitir, from 1.16 days to 14-F1, and the last instar 1.22 days on Ptk, 1.48 days on Kitir were investigated. The total development time was evaluated at 4.46 days Beit on alfa 4.72 days on Kitir. The offspring number was 60.42 aphids on ayda and 83.72 aphids on muhika, the significant differences between varieties were based on one-way ANOVA (Tukey test). The lifetime of A. gossypii was recorded 19.10 days on Kitir, 27.64 days on Ptk. The results showed that cucumber cultivars were affected by the biological life of A. gossypii. The combination of this study with the other methods of the IPM tactics can serve as the best strategy for controlling this pest on cucumber varieties into the greenhouse.

Keywords: cucumber cultivars, fecundity, intrinsic rate, mortality, resistance

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20921 Applying the Eye Tracking Technique for the Evaluation of Oculomotor System in Patients Survived after Cerebellar Tumors

Authors: Marina Shurupova, Victor Anisimov, Alexander Latanov

Abstract:

Background: The cerebellar lesions inevitably provoke oculomotor impairments in patients of different age. Symptoms of subtentorial tumors, particularly medulloblastomas, include static and dynamic coordination disorders (ataxia, asynergia, imbalance), hypo-muscle tonus, disruption of the cranial nerves, and within the oculomotor system - nystagmus (fine or gross). Subtentorial tumors can also affect the areas of cerebellum that control the oculomotor system. The noninvasive eye-tracking technology allows obtaining multiple oculomotor characteristics such as the number of fixations and their duration, amplitude, latency and velocity of saccades, trajectory and scan path of gaze during the process of the visual field navigation. Eye tracking could be very useful in clinical studies serving as convenient and effective tool for diagnostics. The aim: We studied the dynamics of oculomotor system functioning in patients undergoing remission from cerebellar tumors removal surgeries and following neurocognitive rehabilitation. Methods: 38 children (23 boys, 15 girls, 9-17 years old) that have recovered from the cerebellar tumor-removal surgeries, radiation therapy and chemotherapy and were undergoing course of neurocognitive rehabilitation participated in the study. Two tests were carried out to evaluate oculomotor performance - gaze stability test and counting test. The monocular eye movements were recorded with eye tracker ArringtonResearch (60 Hz). Two experimental sessions with both tests were conducted before and after rehabilitation courses. Results: Within the final session of both tests we observed remarkable improvement in oculomotor performance: 1) in the gaze stability test the spread of gaze positions significantly declined compared to the first session, and 2) the visual path in counting test significantly shortened both compared to the first session. Thus, neurocognitive rehabilitation improved the functioning of the oculomotor system in patients following the cerebellar tumor removal surgeries and subsequent therapy. Conclusions: The experimental data support the effectiveness of the utilization of the eye tracking technique as diagnostic tool in the field of neurooncology.

Keywords: eye tracking, rehabilitation, cerebellar tumors, oculomotor system

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20920 Vision-Based Hand Segmentation Techniques for Human-Computer Interaction

Authors: M. Jebali, M. Jemni

Abstract:

This work is the part of vision based hand gesture recognition system for Natural Human Computer Interface. Hand tracking and segmentation are the primary steps for any hand gesture recognition system. The aim of this paper is to develop robust and efficient hand segmentation algorithm such as an input to another system which attempt to bring the HCI performance nearby the human-human interaction, by modeling an intelligent sign language recognition system based on prediction in the context of dialogue between the system (avatar) and the interlocutor. For the purpose of hand segmentation, an overcoming occlusion approach has been proposed for superior results for detection of hand from an image.

Keywords: HCI, sign language recognition, object tracking, hand segmentation

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20919 Mass Pheromone Trapping on Red Palm Weevil, Rhynchophorus ferrugineus (Coleoptera: Curculionidae) in Oil Palm Plantations of Terengganu

Authors: Wahizatul Afzan Azmi, Nur Ain Farhah Ros Saidon Khudri, Mohamad Haris Hussain, Tse Seng Chuah

Abstract:

Malaysia houses a broad range of palm trees species and some of these palm trees are very crucial for the country’s social and economic development, especially the oil palm trees. However, the destructive pest of the various palms species, Rhynchophorus ferrugineus (Coleoptera: Curculionidae) or known as Red Palm Weevil (RPW) was first detected in Terengganu in 2007. Recently, the pattern of infestation has move from coastal lines toward inland areas. After the coconut plantations, it is presumed that the RPW will be a serious threat to the oil palm plantations in Malaysia. Thus, this study was carried out to detect the presence and distribution of Red Palm Weevil (RPW) in selected oil palm plantations of Terengganu. A total of 42 traps were installed in the three oil palm plantations in Terengganu and were inspected every week for two months. Oil palm plantation A collected significantly higher adults RPW compared to the other locations. Generally, females of RPW were significantly higher than male individuals. Females were collected more as the synthetic aggregation pheromone used, ferrugineol was synthesized from the male aggregation pheromone of adult RPW. Oil palm plantation A collected the highest number of RPW might be due to the abundance of soft part in the host plant as the oil palm trees age ranged between 6 to 10 years old. As a conclusion, RPW presence was detected in some oil palm plantations of Terengganu and immediate action is crucially needed before it is too late.

Keywords: red palm weevil, pest, oil palm, pheromone

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20918 A Gradient Orientation Based Efficient Linear Interpolation Method

Authors: S. Khan, A. Khan, Abdul R. Soomrani, Raja F. Zafar, A. Waqas, G. Akbar

Abstract:

This paper proposes a low-complexity image interpolation method. Image interpolation is used to convert a low dimension video/image to high dimension video/image. The objective of a good interpolation method is to upscale an image in such a way that it provides better edge preservation at the cost of very low complexity so that real-time processing of video frames can be made possible. However, low complexity methods tend to provide real-time interpolation at the cost of blurring, jagging and other artifacts due to errors in slope calculation. Non-linear methods, on the other hand, provide better edge preservation, but at the cost of high complexity and hence they can be considered very far from having real-time interpolation. The proposed method is a linear method that uses gradient orientation for slope calculation, unlike conventional linear methods that uses the contrast of nearby pixels. Prewitt edge detection is applied to separate uniform regions and edges. Simple line averaging is applied to unknown uniform regions, whereas unknown edge pixels are interpolated after calculation of slopes using gradient orientations of neighboring known edge pixels. As a post-processing step, bilateral filter is applied to interpolated edge regions in order to enhance the interpolated edges.

Keywords: edge detection, gradient orientation, image upscaling, linear interpolation, slope tracing

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20917 Trajectory Tracking of a Redundant Hybrid Manipulator Using a Switching Control Method

Authors: Atilla Bayram

Abstract:

This paper presents the trajectory tracking control of a spatial redundant hybrid manipulator. This manipulator consists of two parallel manipulators which are a variable geometry truss (VGT) module. In fact, each VGT module with 3-degress of freedom (DOF) is a planar parallel manipulator and their operational planes of these VGT modules are arranged to be orthogonal to each other. Also, the manipulator contains a twist motion part attached to the top of the second VGT module to supply the missing orientation of the endeffector. These three modules constitute totally 7-DOF hybrid (parallel-parallel) redundant spatial manipulator. The forward kinematics equations of this manipulator are obtained, then, according to these equations, the inverse kinematics is solved based on an optimization with the joint limit avoidance. The dynamic equations are formed by using virtual work method. In order to test the performance of the redundant manipulator and the controllers presented, two different desired trajectories are followed by using the computed force control method and a switching control method. The switching control method is combined with the computed force control method and genetic algorithm. In the switching control method, the genetic algorithm is only used for fine tuning in the compensation of the trajectory tracking errors.

Keywords: computed force method, genetic algorithm, hybrid manipulator, inverse kinematics of redundant manipulators, variable geometry truss

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20916 Toward Indoor and Outdoor Surveillance using an Improved Fast Background Subtraction Algorithm

Authors: El Harraj Abdeslam, Raissouni Naoufal

Abstract:

The detection of moving objects from a video image sequences is very important for object tracking, activity recognition, and behavior understanding in video surveillance. The most used approach for moving objects detection / tracking is background subtraction algorithms. Many approaches have been suggested for background subtraction. But, these are illumination change sensitive and the solutions proposed to bypass this problem are time consuming. In this paper, we propose a robust yet computationally efficient background subtraction approach and, mainly, focus on the ability to detect moving objects on dynamic scenes, for possible applications in complex and restricted access areas monitoring, where moving and motionless persons must be reliably detected. It consists of three main phases, establishing illumination changes in variance, background/foreground modeling and morphological analysis for noise removing. We handle illumination changes using Contrast Limited Histogram Equalization (CLAHE), which limits the intensity of each pixel to user determined maximum. Thus, it mitigates the degradation due to scene illumination changes and improves the visibility of the video signal. Initially, the background and foreground images are extracted from the video sequence. Then, the background and foreground images are separately enhanced by applying CLAHE. In order to form multi-modal backgrounds we model each channel of a pixel as a mixture of K Gaussians (K=5) using Gaussian Mixture Model (GMM). Finally, we post process the resulting binary foreground mask using morphological erosion and dilation transformations to remove possible noise. For experimental test, we used a standard dataset to challenge the efficiency and accuracy of the proposed method on a diverse set of dynamic scenes.

Keywords: video surveillance, background subtraction, contrast limited histogram equalization, illumination invariance, object tracking, object detection, behavior understanding, dynamic scenes

Procedia PDF Downloads 256
20915 Testing of Electronic Control Unit Communication Interface

Authors: Petr Šimek, Kamil Kostruk

Abstract:

This paper deals with the problem of testing the Electronic Control Unit (ECU) for the specified function validation. Modern ECUs have many functions which need to be tested. This process requires tracking between the test and the specification. The technique discussed in this paper explores the system for automating this process. The paper focuses in its chapter IV on the introduction to the problem in general, then it describes the proposed test system concept and its principle. It looks at how the process of the ECU interface specification file for automated interface testing and test tracking works. In the end, the future possible development of the project is discussed.

Keywords: electronic control unit testing, embedded system, test generate, test automation, process automation, CAN bus, ethernet

Procedia PDF Downloads 112
20914 Design and Test a Robust Bearing-Only Target Motion Analysis Algorithm Based on Modified Gain Extended Kalman Filter

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Passive sonar is a method for detecting acoustic signals in the ocean. It detects the acoustic signals emanating from external sources. With passive sonar, we can determine the bearing of the target only, no information about the range of the target. Target Motion Analysis (TMA) is a process to estimate the position and speed of a target using passive sonar information. Since bearing is the only available information, the TMA technique called Bearing-only TMA. Many TMA techniques have been developed. However, until now, there is not a very effective method that could be used to always track an unknown target and extract its moving trace. In this work, a design of effective Bearing-only TMA Algorithm is done. The measured bearing angles are very noisy. Moreover, for multi-beam sonar, the measurements is quantized due to the sonar beam width. To deal with this, modified gain extended Kalman filter algorithm is used. The algorithm is fine-tuned, and many modules are added to improve the performance. A special validation gate module is used to insure stability of the algorithm. Many indicators of the performance and confidence level measurement are designed and tested. A new method to detect if the target is maneuvering is proposed. Moreover, a reactive optimal observer maneuver based on bearing measurements is proposed, which insure converging to the right solution all of the times. To test the performance of the proposed TMA algorithm a simulation is done with a MATLAB program. The simulator program tries to model a discrete scenario for an observer and a target. The simulator takes into consideration all the practical aspects of the problem such as a smooth transition in the speed, a circular turn of the ship, noisy measurements, and a quantized bearing measurement come for multi-beam sonar. The tests are done for a lot of given test scenarios. For all the tests, full tracking is achieved within 10 minutes with very little error. The range estimation error was less than 5%, speed error less than 5% and heading error less than 2 degree. For the online performance estimator, it is mostly aligned with the real performance. The range estimation confidence level gives a value equal to 90% when the range error less than 10%. The experiments show that the proposed TMA algorithm is very robust and has low estimation error. However, the converging time of the algorithm is needed to be improved.

Keywords: target motion analysis, Kalman filter, passive sonar, bearing-only tracking

Procedia PDF Downloads 402
20913 Incorporating Moving Authority Limits Into Driving Advice

Authors: Peng Zhou, Peter Pudney

Abstract:

Driver advice systems are used by many rail operators to help train drivers to improve timekeeping while minimising energy use. These systems typically operate independently of the safeworking system, because information on how far the train is allowed to travel -the “limit of authority"- is usually not available as real-time data that can be used when generating driving advice. This is not an issue when there is sufficient separation between trains. But on systems with low headways, driving advice could conflict with safeworking requirements. We describe a method for generating driving advice that takes into account a moving limit of authority that is communicated to the train in real-time. We illustrate the method with four simulated examples using data from the Zhengzhou Metro. The method will allow driver advice systems to be used more effectively on railways with low headways.

Keywords: railway transportation, energy efficient train operation, optimal train control, safe separation

Procedia PDF Downloads 9
20912 Pion/Muon Identification in a Nuclear Emulsion Cloud Chamber Using Neural Networks

Authors: Kais Manai

Abstract:

The main part of this work focuses on the study of pion/muon separation at low energy using a nuclear Emulsion Cloud Chamber (ECC) made of lead and nuclear emulsion films. The work consists of two parts: particle reconstruction algorithm and a Neural Network that assigns to each reconstructed particle the probability to be a muon or a pion. The pion/muon separation algorithm has been optimized by using a detailed Monte Carlo simulation of the ECC and tested on real data. The algorithm allows to achieve a 60% muon identification efficiency with a pion misidentification smaller than 3%.

Keywords: nuclear emulsion, particle identification, tracking, neural network

Procedia PDF Downloads 506
20911 Mass Rearing and Effects of Gamma Irradiation on the Pupal Mortality and Reproduction of Citrus Leaf Miner Phyllocnistis citrella Stainton (Lepidoptera: Gracillariidae)

Authors: Shiva Osouli, Maryam Atapour, Mehrdad Ahmadi, Shima Shokri

Abstract:

Citrus leaf miner (Phyllocnistis citrella Stainton) is native to Asia and one of the most serious pests of Iran’s citrus nursery stocks. In the present study, the possibility of insect mass rearing on four various citrus hosts and the effects of gamma irradiation on the pupal mortality and reproduction of this pest were studied. Trifoliate orange and grapefruit showed less infection, while the number of pupae in Valencia oranges and sweet lemons cages was so high. There was not any significant difference between weight of male and female pupae among different citrus hosts, but generally the weight of male pupae was less than females. Use of Valencia orange or sweet lemons seedlings in especial dark emergence and oviposition cages could be recommended for mass rearing of this pest. In this study, the effects of gamma radiation at doses 100 to 450 Gy on biological and reproductive parameters of the pest has been determined. The results show that mean percent of pupal mortality increased with increasing doses and reached to 28.67% at 450 Gy for male pupae and 38.367% for female pupae. Also, the mean values of this parameter were higher for irradiated female, which indicated the higher sensitivity of this sex. The gamma ray irradiation from 200 and 300 Gy caused decrease in male and female adult moth longevity, respectively. The eggs were laid by emerged females, and their hatchability was decreased by increasing gamma doses. The fecundity of females in both combinations of crosses (irradiated male × normal female and irradiated female × normal male) did not differ, but fertility of laid eggs by irradiated female × normal male affected seriously and the mean values of this parameter reached to zero at 300 Gy. The hatchability percentage of produced eggs by normal female × irradiated male at 300 Gy was 23.29% and reached to less than 2 % at 450 Gy as the highest tested dose. The results of this test show that females have more radio-sensitivity in comparison to males.

Keywords: citrus leaf miner, Phyllocnistis citrella, citrus hosts, mass rearing, Sterile Insect Technique (SIT)

Procedia PDF Downloads 173
20910 Eco-Drive Predictive Analytics

Authors: Sharif Muddsair, Eisels Martin, Giesbrecht Eugenie

Abstract:

With development of society increase the demand for the movement of people also increases gradually. The various modes of the transport in different extent which expat impacts, which depends on mainly technical-operating conditions. The up-to-date telematics systems provide the transport industry a revolutionary. Appropriate use of these systems can help to substantially improve the efficiency. Vehicle monitoring and fleet tracking are among services used for improving efficiency and effectiveness of utility vehicle. There are many telematics systems which may contribute to eco-driving. Generally, they can be grouped according to their role in driving cycle. • Before driving - eco-route selection, • While driving – Advanced driver assistance, • After driving – remote analysis. Our point of interest is regulated in third point [after driving – remote analysis]. TS [Telematics-system] make it possible to record driving patterns in real time and analysis the data later on, So that driver- classification-specific hints [fast driver, slow driver, aggressive driver…)] are given to imitate eco-friendly driving style. Together with growing number of vehicle and development of information technology, telematics become an ‘active’ research subject in IT and the car industry. Telematics has gone a long way from providing navigation solution/assisting the driver to become an integral part of the vehicle. Today’s telematics ensure safety, comfort and become convenience of the driver.

Keywords: internet of things, iot, connected vehicle, cv, ts, telematics services, ml, machine learning

Procedia PDF Downloads 304
20909 Optimal Linear Quadratic Digital Tracker for the Discrete-Time Proper System with an Unknown Disturbance

Authors: Jason Sheng-Hong Tsai, Faezeh Ebrahimzadeh, Min-Ching Chung, Shu-Mei Guo, Leang-San Shieh, Tzong-Jiy Tsai, Li Wang

Abstract:

In this paper, we first construct a new state and disturbance estimator using discrete-time proportional plus integral observer to estimate the system state and the unknown external disturbance for the discrete-time system with an input-to-output direct-feedthrough term. Then, the generalized optimal linear quadratic digital tracker design is applied to construct a proportional plus integral observer-based tracker for the system with an unknown external disturbance to have a desired tracking performance. Finally, a numerical simulation is given to demonstrate the effectiveness of the new application of our proposed approach.

Keywords: non-minimum phase system, optimal linear quadratic tracker, proportional plus integral observer, state and disturbance estimator

Procedia PDF Downloads 502
20908 Light-Weight Network for Real-Time Pose Estimation

Authors: Jianghao Hu, Hongyu Wang

Abstract:

The effective and efficient human pose estimation algorithm is an important task for real-time human pose estimation on mobile devices. This paper proposes a light-weight human key points detection algorithm, Light-Weight Network for Real-Time Pose Estimation (LWPE). LWPE uses light-weight backbone network and depthwise separable convolutions to reduce parameters and lower latency. LWPE uses the feature pyramid network (FPN) to fuse the high-resolution, semantically weak features with the low-resolution, semantically strong features. In the meantime, with multi-scale prediction, the predicted result by the low-resolution feature map is stacked to the adjacent higher-resolution feature map to intermediately monitor the network and continuously refine the results. At the last step, the key point coordinates predicted in the highest-resolution are used as the final output of the network. For the key-points that are difficult to predict, LWPE adopts the online hard key points mining strategy to focus on the key points that hard predicting. The proposed algorithm achieves excellent performance in the single-person dataset selected in the AI (artificial intelligence) challenge dataset. The algorithm maintains high-precision performance even though the model only contains 3.9M parameters, and it can run at 225 frames per second (FPS) on the generic graphics processing unit (GPU).

Keywords: depthwise separable convolutions, feature pyramid network, human pose estimation, light-weight backbone

Procedia PDF Downloads 154