Search results for: change detection method

Authors: Layan Moussa, Darine Salam, Samir Mustapha

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Heavy metal contamination in agricultural soils in Lebanon poses serious environmental and health problems. Intensive efforts are employed to improve existing quantification methods of heavy metals in contaminated environments since conventional detection techniques have shown to be time-consuming, tedious, and costly. The implication of hyperspectral remote sensing in this field is possible and promising. However, factors impacting the efficiency of hyperspectral imaging in detecting and quantifying heavy metals in agricultural soils were not thoroughly studied. This study proposes to assess the use of hyperspectral imaging for the detection of Ni in agricultural clay soil collected from the Bekaa Valley, a major agricultural area in Lebanon, under different contamination levels and soil moisture content. Soil samples were contaminated with Ni, with concentrations ranging from 150 mg/kg to 4000 mg/kg. On the other hand, soil with background contamination was subjected to increased moisture levels varying from 5 to 75%. Hyperspectral imaging was used to detect and quantify Ni contamination in the soil at different contamination levels and moisture content. IBM SPSS statistical software was used to develop models that predict the concentration of Ni and moisture content in agricultural soil. The models were constructed using linear regression algorithms. The spectral curves obtained reflected an inverse correlation between both Ni concentration and moisture content with respect to reflectance. On the other hand, the models developed resulted in high values of predicted R2 of 0.763 for Ni concentration and 0.854 for moisture content. Those predictions stated that Ni presence was well expressed near 2200 nm and that of moisture was at 1900 nm. The results from this study would allow us to define the potential of using the hyperspectral imaging (HSI) technique as a reliable and cost-effective alternative for heavy metal pollution detection in contaminated soils and soil moisture prediction.

Keywords: heavy metals, hyperspectral imaging, moisture content, soil contamination

Procedia PDF Downloads 79

Authors: Sandip Suman

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Mechanical defects (cracks, voids, irregularities) in rocket motor propellant are not new and it is induced due to various reasons, which could be an improper manufacturing process, lot-to-lot variation in chemicals or just the natural aging of the products. These defects are normally identified during the examination of radiographic films by quality inspectors. However, a lot of times, these defects are under or over-classified by human inspectors, which leads to unpredictable performance during lot acceptance tests and significant economic loss. The human eye can only visualize larger cracks and defects in the radiographs, and it is almost impossible to visualize every small defect through the human eye. A different artificial intelligence-based machine vision methodology has been proposed in this work to identify and classify the structural defects in the radiographic films of rocket motors with solid propellant. The proposed methodology can extract the features of defects, characterize them, and make intelligent decisions for acceptance or rejection as per the customer requirements. This will automatize the defect detection process during manufacturing with human-like intelligence. It will also significantly reduce production downtime and help to restore processes in the least possible time. The proposed methodology is highly scalable and can easily be transferred to various products and processes.

Keywords: artificial intelligence, machine vision, defect detection, rocket motor propellant grains

Procedia PDF Downloads 77

Authors: Najmeh Abedzadeh, Matthew Jacobs

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An intrusion detection system (IDS) is a software application that monitors malicious activities and generates alerts if any are detected. However, most network activities in IDS datasets are normal, and the relatively few numbers of attacks make the available data imbalanced. Consequently, cyber-attacks can hide inside a large number of normal activities, and machine learning algorithms have difficulty learning and classifying the data correctly. In this paper, a comprehensive literature review is conducted on different types of algorithms for both implementing the IDS and methods in correcting the imbalanced IDS dataset. The most famous algorithms are machine learning (ML), deep learning (DL), synthetic minority over-sampling technique (SMOTE), and reinforcement learning (RL). Most of the research use the CSE-CIC-IDS2017, CSE-CIC-IDS2018, and NSL-KDD datasets for evaluating their algorithms.

Keywords: IDS, imbalanced datasets, sampling algorithms, big data

Procedia PDF Downloads 297

Authors: Sai S. Hari, Shriram Ramanujam, Unnati Trivedi

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The advent of mass transit systems like rail, metro, maglev, and various other rail based transport has pacified the requirement of public transport for the masses to a great extent. However, the abatement of the demand does not necessarily mean it is managed efficiently, eloquently or in an encapsulating manner. The primary problem identified that the one this paper seeks to solve is the dipsomaniac like manner in which the compartments are occupied. This problem is solved by using a comparison of an empty train and an occupied one. The pixel data of an occupied train is compared to the pixel data of an empty train. This is done using canny edge detection technique. After the comparison it intimates the passengers at the consecutive stops which compartments are not occupied or have low occupancy. Thus, redirecting them and preventing overcrowding.

Keywords: canny edge detection, comparison, encapsulation, redirection

Procedia PDF Downloads 311

Authors: Shabnam Dadparvar, Laijin Shen

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This paper focuses on China’s policy in the Middle East and the rivalry with the U.S. The question is that what are the main factors on China’s Middle East policy and its competition with the U.S? The hypothesis regards to three effective factors: 'China’s energy dependency' on the Middle East, 'economy' and support for 'stability' in the Middle East. What is important in China’s competition with the U.S regarding to its Middle East policy is the substantial difference in ways of treating the countries of the region; China is committed to Westphalia model based on non-interference in internal affairs of the countries and respect the sovereignty of the governments. However, after 9/11, the U.S is seeking a balance between stability and change through intervention in the international affairs and in some cases is looking for a regime change. From the other hand, China, due to its dependency on the region’s energy welcomes America’s military presence in the region for providing stability. The authors by using a descriptive analytical method try to explain the situation of rivalry between China and the United States in Middle East. China is an 'emerging power' with high economic growth and in demand of more energy supply. The problem is that a rising power in the region is often a source of concern for hegemony.

Keywords: China's foreign policy, energy, hegemony, the Middle East

Procedia PDF Downloads 331

Authors: Ankit Shai

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CRC or Cyclic Redundancy Check is one of the most common, and one of the most powerful error-detecting codes implemented on modern computers. Most of the modern communication protocols use some error detection algorithms in digital networks and storage devices to detect accidental changes to raw data between transmission and reception. Cyclic Redundancy Check, or CRC, is the most popular one among these error detection codes. CRC properties are defined by the generator polynomial length and coefficients. The aim of this project is to implement an efficient FPGA based CRC-8 that accepts a 32 bit input, taking into consideration optimal chip area and high performance, using VHDL. The proposed architecture is implemented on Xilinx ISE Simulator. It is designed while keeping in mind the hardware design, complexity and cost factor.

Keywords: cyclic redundancy checker, CRC-8, 32-bit input, FPGA, VHDL, ModelSim, Xilinx

Procedia PDF Downloads 278

Authors: Aragorn Joaquin Pineda Dela Cruz

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Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

Procedia PDF Downloads 80

Authors: Drew Fockler

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This research examines how to improve an employee’s experience when transferring between departments within an organization. This research includes a historical review of a Canadian retail organization. Based on this historical review, gaps are identified between current and future visions to show where problems with existing training and development practices need to be resolved to reduce front-line employee turnover within an organization. The strategies within this paper support leaders through the LEAD: Listen, Explore, Act and Develop, Change Management Model. The LEAD Change Management Model supports the change process. This research proposes three possible solutions to improve an employee who is transferring between departments. The best solution to resolve the problem of improving an employee moving between departments experience is creating a Training Manager position within the retail store. A Training Manager position could support both employees and leadership with training and development of staff who are moving between departments. Within this research, an implementation plan using the TransX Model was created. The TransX Model is a hybrid of Leader-Member Exchange Theory and Transformational Leadership Theory to facilitate this organizational change within an organization by creating a common vision. Finally, this research provides the next steps as well as future considerations to enhance the training manager role within an organization.

Keywords: employee transfers, employee engagement, human resources, employee induction, TransX model, lead change management model

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Authors: Lubna Eljabu, Mohammad Etemad, Stan Matwin

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Port authorities have many challenges in congested ports to allocate their resources to provide a safe and secure loading/ unloading procedure for cargo vessels. Selecting a destination port is the decision of a vessel master based on many factors such as weather, wavelength and changes of priorities. Having access to a tool which leverages AIS messages to monitor vessel’s movements and accurately predict their next destination port promotes an effective resource allocation process for port authorities. In this research, we propose a method, namely, Reference Route of Trajectory (RRoT) to assist port authorities in predicting inflow and outflow traffic in their local environment by monitoring Automatic Identification System (AIS) messages. Our RRoT method creates a reference route based on historical AIS messages. It utilizes some of the best trajectory similarity measure to identify the destination of a vessel using their recent movement. We evaluated five different similarity measures such as Discrete Fr´echet Distance (DFD), Dynamic Time Warping (DTW), Partial Curve Mapping (PCM), Area between two curves (Area) and Curve length (CL). Our experiments show that our method identifies the destination port with an accuracy of 98.97% and an fmeasure of 99.08% using Dynamic Time Warping (DTW) similarity measure.

Keywords: spatial temporal data mining, trajectory mining, trajectory similarity, resource optimization

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Authors: Misra Ayse Adsiz, Selim Selvi

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In today's world, technology is competing with time. In order to catch up with the world's companies and adapt quickly to the changes, it is necessary to speed up the processes and keep pace with the rate of change of the technology. The missile system design processes, which are handled with classical methods, keep behind in this race. Because customer requirements are not clear, and demands are changing again and again in the design process. Therefore, in the system design process, a methodology suitable for the missile system design dynamics has been investigated and the processes used for catching up the era are examined. When commonly used design processes are analyzed, it is seen that any one of them is dynamic enough for today’s conditions. So a hybrid design process is established. After a detailed review of the existing processes, it is decided to focus on the Scrum Framework and Agile Philosophy. Scrum is a process framework. It is focused on to develop software and handling change management with rapid methods. In addition, agile philosophy is intended to respond quickly to changes. In this study, it is aimed to integrate Scrum framework and agile philosophy, which are the most appropriate ways for rapid production and change adaptation, into the missile system design process. With this approach, it is aimed that the design team, involved in the system design processes, is in communication with the customer and provide an iterative approach in change management. These methods, which are currently being used in the software industry, have been integrated with the product design process. A team is created for system design process. The roles of Scrum Team are realized with including the customer. A scrum team consists of the product owner, development team and scrum master. Scrum events, which are short, purposeful and time-limited, are organized to serve for coordination rather than long meetings. Instead of the classic system design methods used in product development studies, a missile design is made with this blended method. With the help of this design approach, it is become easier to anticipate changing customer demands, produce quick solutions to demands and combat uncertainties in the product development process. With the feedback of the customer who included in the process, it is worked towards marketing optimization, design and financial optimization.

Keywords: agile, design, missile, scrum

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Authors: Ekrem Erdem, Can Tansel Tugcu

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Improved resource efficiency of production is a key requirement for sustainable growth, worldwide. In this regards, by considering the energy and tourism as the extra inputs to the classical Coub-Douglas production function, this study aims at investigating the efficiency changes in the North African countries. To this end, the study uses panel data for the period 1995-2010 and adopts the Malmquist index based on the data envelopment analysis. Results show that tourism increases technical and scale efficiencies, while it decreases technological and total factor productivity changes. On the other hand, when the production function is augmented by the energy input, technical efficiency change decreases, while the technological change, scale efficiency change and total factor productivity change increase. Thus, in order to satisfy the needs for sustainable growth, North African governments should take some measures for increasing the contribution that the tourism makes to economic growth and some others for efficient use of resources in the energy sector.

Keywords: data envelopment analysis, economic efficiency, North African countries, sustainable growth

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Authors: Jen-Te Pai, Jao-Heng Liu, Shin-En Pai

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The impact of climate change has intensified in recent years, causing Taiwan to face higher frequency and serious natural disasters. Therefore, it is imperative for industrial parks manufacturers to promote adaptation policies in response to climate change. On the other hand, with the rise of the international anti-terrorism situation, once a terrorist attack occurs, it will attract domestic and international media attention, especially the strategic and economic status of the science park. Thus, it is necessary to formulate adaptation and mitigation strategies under climate change and social economic disasters. After reviewed the literature about climate change, urban disaster prevention, vulnerability assessment, and risk communication, the study selected 62 industrial parks compiled by the Industrial Bureau of the Ministry of Economic Affairs of Taiwan as the research object. This study explored the vulnerability and disaster prevention and disaster relief functional assessment of these industrial parks facing of natural and socio-economic disasters. Furthermore, this study explored planned adaptation of industrial parks management section and autonomous adaptation of corporate institutions in the park. The conclusion of this study is that Taiwan industrial parks with a higher vulnerability to natural and socio-economic disasters should employ positive adaptive behaviours.

Keywords: adaptive behaviours, analytic network process, vulnerability, industrial parks

Procedia PDF Downloads 123

Authors: Onu Theresa Chinyere

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The study evaluates the perceived effect of climate change on nutritional status of women in Nigeria. Five research questions and two hypotheses were formulated to guide the study. The study adopted a survey and experimental study research design. One thousand two hundred and fifty one (1,250) respondents were selected from different State in Nigeria using multistage sampling technique. The instruments used to collect data were questionnaire and personal interview on socio economic characteristics of respondents, while Anthropometric data (height and weight) were also used. The data was analyzed using t-test statistic, decided at 50% level of significance. The study found that most states in Nigeria experience high winds, warmer and frequent hot days and night over most land areas, droughts and tides during climate change events. The respondent unanimously agree that climate change causes reduction in food yields, decline in food availability/supply, negatively affecting soil quality, carbon fertilization, decreases flexibilities in technology choices to strengthen food production. The Anthropometric analysis shows that out of 1250 women sampled, 560 (44.8%) maintain normal weight, while 405 (32.40%) women were found to be underweight, since their body mass index is less that 18.5. There were few cases of obesity among the surveyed women since only 80 out of 1250 which represent 6.4% of the women were obese. Bases on the findings, the following recommendations were made-local fertilizer should be encouraged to boost foods yield especially during climate change: women should imbibe the culture of preservation or reservoir that will help in mitigating the effects of climate on food intake and nutritional status, especially during the crisis period, among others.

Keywords: climate change, nutrition anthropometric analysis, obesity culture, environment and women among others

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Authors: Gus Salazar, Jeremy Bekker, Lauren Linford, Jared Warren

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Positive psychology practices allow for its principles to be applied to all people, regardless of their current level of functioning. To increase the dissemination of these practices, interventions are being adapted for use with digital technology, such as mobile apps. However, the research regarding positive psychology mobile app interventions is still in its infancy. In an effort to facilitate progress in this important area, we 1) conducted a qualitative review to summarize the current state of the positive psychology mobile app literature and 2) developed research-supported recommendations for positive psychology app development to maximize behavior change. In our literature review, we found that while positive psychology apps varied widely in content and purpose, there was a near-complete lack of research supporting their effectiveness. Most apps provided no rationale for the behavioral change techniques (BCTs) they employed in their app, and most did not develop their app with specific theoretical frameworks or design models in mind. Given this problem, we recommended four steps for effective positive psychology app design. First, developers must establish their app in a research-supported theory of change. Second, researchers must select appropriate behavioral change techniques which are consistent with their app’s goals. Third, researchers must leverage effective design principles. These steps will help mobile applications use data-driven methods for encouraging behavior change in their users. Lastly, we discuss directions for future research. In particular, researchers must investigate the effectiveness of various BCTs in positive psychology interventions. Although there is some research on this point, we do not yet clearly understand the mechanisms within the apps that lead to behavior change. Additionally, app developers must also provide data on the effectiveness of their mobile apps. As developers follow these steps for effective app development and as researchers continue to investigate what makes these apps most effective, we will provide millions of people in need with access to research-based mental health resources.

Keywords: behavioral change techniques, mobile app, mobile intervention, positive psychology

Procedia PDF Downloads 208

Authors: Glauco M. M. M. Lustosa, João Paulo C. Costa, Sonia M. Zanetti, Mario Cilense, Leinig Antônio Perazolli, Maria Aparecida Zaghete

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The contamination of the environment has been one of the biggest problems of our time, mostly due to developments of many industries. SnO2 is an n-type semiconductor with band gap about 3.5 eV and has its electrical conductivity dependent of type and amount of modifiers agents added into matrix ceramic during synthesis process, allowing applications as sensing of gaseous pollutants on ambient. The chemical synthesis by polymeric precursor method consists in a complexation reaction between tin ion and citric acid at 90 °C/2 hours and subsequently addition of ethyleneglycol for polymerization at 130 °C/2 hours. It also prepared polymeric resin of zinc, cobalt and niobium ions. Stoichiometric amounts of the solutions were mixed to obtain the systems (Zn, Nb)-SnO2 and (Co, Nb) SnO2 . The metal immobilization reduces its segregation during the calcination resulting in a crystalline oxide with high chemical homogeneity. The resin was pre-calcined at 300 °C/1 hour, milled in Atritor Mill at 500 rpm/1 hour, and then calcined at 600 °C/2 hours. X-Ray Diffraction (XDR) indicated formation of SnO2 -rutile phase (JCPDS card nº 41-1445). The characterization by Scanning Electron Microscope of High Resolution showed spherical ceramic powder nanostructured with 10-20 nm of diameter. 20 mg of SnO2 -based powder was kept in 20 ml of isopropyl alcohol and then taken to an electrophoretic deposition (EPD) system. The EPD method allows control the thickness films through the voltage or current applied in the electrophoretic cell and by the time used for deposition of ceramics particles. This procedure obtains films in a short time with low costs, bringing prospects for a new generation of smaller size devices with easy integration technology. In this research, films were obtained in an alumina substrate with interdigital electrodes after applying 2 kV during 5 and 10 minutes in cells containing alcoholic suspension of (Zn, Nb)-SnO2 and (Co, Nb) SnO2 of powders, forming a sensing layer. The substrate has designed integrated micro hotplates that provide an instantaneous and precise temperature control capability when a voltage is applied. The films were sintered at 900 and 1000 °C in a microwave oven of 770 W, adapted by the research group itself with a temperature controller. This sintering is a fast process with homogeneous heating rate which promotes controlled growth of grain size and also the diffusion of modifiers agents, inducing the creation of intrinsic defects which will change the electrical characteristics of SnO2 -based powders. This study has successfully demonstrated a microfabricated system with an integrated micro-hotplate for detection of CO and NO2 gas at different concentrations and temperature, with self-heating SnO2 - based nanoparticles films, being suitable for both industrial process monitoring and detection of low concentrations in buildings/residences in order to safeguard human health. The results indicate the possibility for development of gas sensors devices with low power consumption for integration in portable electronic equipment with fast analysis. Acknowledgments The authors thanks to the LMA-IQ for providing the FEG-SEM images, and the financial support of this project by the Brazilian research funding agencies CNPq, FAPESP 2014/11314-9 and CEPID/CDMF- FAPESP 2013/07296-2.

Keywords: chemical synthesis, electrophoretic deposition, self-heating, gas sensor

Procedia PDF Downloads 262

Authors: Eleonora Di Salvo, Antonio Panebianco, Graziella Ziino

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Background: Vibrio parahaemolyticus is a human pathogen that is widely distributed in marine environments. It is frequently isolated from raw seafood, particularly shellfish. Consumption of raw or undercooked seafood contaminated with V. parahaemolyticus may lead to acute gastroenteritis. Vibrio spp. has excellent resistance to low temperatures so it can be found in frozen products for a long time. Recently, the viable but non-culturable state (VBNC) of bacteria has attracted great attention, and more than 85 species of bacteria have been demonstrated to be capable of entering this state. VBNC cells cannot grow in conventional culture medium but are viable and maintain metabolic activity, which may constitute an unrecognized source of food contamination and infection. Also V. parahaemolyticus could exist in VBNC state under nutrient starvation or low-temperature conditions. Aim: The aim of the present study was to optimize methods and investigate V. parahaemolyticus VBNC cells and their presence in frozen bivalve molluscs, regularly marketed. Materials and Methods: propidium monoazide (PMA) was integrated with real-time polymerase chain reaction (qPCR) targeting the tl gene to detect and quantify V. parahaemolyticus in the VBNC state. PMA-qPCR resulted highly specific to V. parahaemolyticus with a limit of detection (LOD) of 10-1 log CFU/mL in pure bacterial culture. A standard curve for V. parahaemolyticus cell concentrations was established with the correlation coefficient of 0.9999 at the linear range of 1.0 to 8.0 log CFU/mL. A total of 77 samples of frozen bivalve molluscs (35 mussels; 42 clams) were subsequently subjected to the qualitative (on alkaline phosphate buffer solution) and quantitative research of V. parahaemolyticus on thiosulfate-citrate-bile salts-sucrose (TCBS) agar (DIFCO) NaCl 2.5%, and incubation at 30°C for 24-48 hours. Real-time PCR was conducted on homogenate samples, in duplicate, with and without propidium monoazide (PMA) dye, and exposed for 45 min under halogen lights (650 W). Total DNA was extracted from cell suspension in homogenate samples according to bolliture protocol. The Real-time PCR was conducted with species-specific primers for V. parahaemolitycus. The RT-PCR was performed in a final volume of 20 µL, containing 10 µL of SYBR Green Mixture (Applied Biosystems), 2 µL of template DNA, 2 µL of each primer (final concentration 0.6 mM), and H2O 4 µL. The qPCR was carried out on CFX96 TouchTM (Bio-Rad, USA). Results: All samples were negative both to the quantitative and qualitative detection of V. parahaemolyticus by the classical culturing technique. The PMA-qPCR let us individuating VBNC V. parahaemolyticus in the 20,78% of the samples evaluated with a value between the Log 10-1 and Log 10-3 CFU/g. Only clams samples were positive for PMA-qPCR detection. Conclusion: The present research is the first evaluating PMA-qPCR assay for detection of VBNC V. parahaemolyticus in bivalve molluscs samples, and the used method was applicable to the rapid control of marketed bivalve molluscs. We strongly recommend to use of PMA-qPCR in order to identify VBNC forms, undetectable by the classic microbiological methods. A precise knowledge of the V.parahaemolyticus in a VBNC form is fundamental for the correct risk assessment not only in bivalve molluscs but also in other seafood.

Keywords: food safety, frozen bivalve molluscs, PMA dye, Real-time PCR, VBNC state, Vibrio parahaemolyticus

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Authors: Natalia Efremova, Sergey Tarasenko

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We propose a novel neural network architecture for visual saliency detections, which utilizes neuro physiologically plausible mechanisms for extraction of salient regions. The model has been significantly inspired by recent findings from neuro physiology and aimed to simulate the bottom-up processes of human selective attention. Two types of features were analyzed: color and direction of maximum variance. The mechanism we employ for processing those features is PCA, implemented by means of normalized Hebbian learning and the waves of spikes. To evaluate performance of our model we have conducted psychological experiment. Comparison of simulation results with those of experiment indicates good performance of our model.

Keywords: neural network models, visual saliency detection, normalized Hebbian learning, Oja's rule, psychological experiment

Procedia PDF Downloads 328

Authors: Abu Hashan Md Mashud, M. Sharif Uddin, Aminur Rahman Khan

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In this paper, we formulate a new problem as a linear programming and Integer Programming problem and maximize profit within the limited budget and limited resources based on the construction of a tea garden problem. It describes a new idea about how to optimize profit and focuses on the practical aspects of modeling and the challenges of providing a solution to a complex real life problem. Finally, a comparative study is carried out among Graphical method, Simplex method and Branch and bound method.

Keywords: integer programming, tea garden, graphical method, simplex method, branch and bound method

Procedia PDF Downloads 599

Authors: Linjie Zhang, Baifen Ren, Xi Zhang, Genwang Liu

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Ship detection is of great significance for both military and civilian applications. Synthetic aperture radar (SAR) with all-day, all-weather, ultra-long-range characteristics, has been used widely. In view of the low time resolution of low orbit SAR and the needs for high time resolution SAR data, GEO (Geosynchronous orbit) SAR is getting more and more attention. Since GEO SAR has short revisiting period and large coverage area, it is expected to be well utilized in marine ship targets monitoring. However, the height of the orbit increases the time of integration by almost two orders of magnitude. For moving marine vessels, the utility and efficacy of GEO SAR are still not sure. This paper attempts to find the feasibility of GEO SAR by giving a GEO SAR simulator of moving ships. This presented GEO SAR simulator is a kind of geometrical-based radar imaging simulator, which focus on geometrical quality rather than high radiometric. Inputs of this simulator are 3D ship model (.obj format, produced by most 3D design software, such as 3D Max), ship's velocity, and the parameters of satellite orbit and SAR platform. Its outputs are simulated GEO SAR raw signal data and SAR image. This simulating process is accomplished by the following four steps. (1) Reading 3D model, including the ship rotations (pitch, yaw, and roll) and velocity (speed and direction) parameters, extract information of those little primitives (triangles) which is visible from the SAR platform. (2) Computing the radar scattering from the ship with physical optics (PO) method. In this step, the vessel is sliced into many little rectangles primitives along the azimuth. The radiometric calculation of each primitive is carried out separately. Since this simulator only focuses on the complex structure of ships, only single-bounce reflection and double-bounce reflection are considered. (3) Generating the raw data with GEO SAR signal modeling. Since the normal ‘stop and go’ model is not available for GEO SAR, the range model should be reconsidered. (4) At last, generating GEO SAR image with improved Range Doppler method. Numerical simulation of fishing boat and cargo ship will be given. GEO SAR images of different posture, velocity, satellite orbit, and SAR platform will be simulated. By analyzing these simulated results, the effectiveness of GEO SAR for the detection of marine moving vessels is evaluated.

Keywords: GEO SAR, radar, simulation, ship

Procedia PDF Downloads 160

Authors: Ayush Shrivastava, Arpit Chaudhary, Devang Kulshreshtha, Vibhav Prakash Singh, Rajeev Srivastava

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Early diagnosis of breast cancer can improve the survival rate by detecting cancer at an early stage. Breast region segmentation is an essential step in the analysis of digital mammograms. Accurate image segmentation leads to better detection of cancer. It aims at separating out Region of Interest (ROI) from rest of the image. The procedure begins with removal of labels, annotations and tags from the mammographic image using morphological opening method. Pectoral Muscle Sliding Window Algorithm (PMSWA) is used for removal of pectoral muscle from mammograms which is necessary as the intensity values of pectoral muscles are similar to that of ROI which makes it difficult to separate out. After removing the pectoral muscle, Dispersed Region Growing Algorithm (DRGA) is used for segmentation of mammogram which disperses seeds in different regions instead of a single bright region. To demonstrate the validity of our segmentation method, 322 mammographic images from Mammographic Image Analysis Society (MIAS) database are used. The dataset contains medio-lateral oblique (MLO) view of mammograms. Experimental results on MIAS dataset show the effectiveness of our proposed method.

Keywords: CAD, dispersed region growing algorithm (DRGA), image segmentation, mammography, pectoral muscle sliding window algorithm (PMSWA)

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Authors: Gulsen Yilmaz

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Istanbul’s population has jumped by over 1 million in the past four years, to a level surpassing the overall population of 64 provinces in the country, according to data from the Turkish Statistical Institute (TÜİK). In this paper, Istanbul's population change and migration effects can be examined in detail Tarlabasi neighborhood cultural center of the city of Istanbul, Istiklal Street, which is located a few hundred meters away. Tarlabasi the end of the nineteenth century in the historic district with built in the early twentieth century, there are four or five storey historic buildings. Tarlabasi, here come from southeastern Turkey and the illegal African immigrants living in Roma origin by the Kurds as a residential area is used. In this area to improve the quality of life for urban renewal projects have been initiated. The aim of this paper is to explore the spatial effects of demographic change and migration with Tarlabasi example.

Keywords: migration, immigration, Tarlabaşı, urban transformation

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Authors: V. Veeraprathap, G. S. Harish, G. Narendra Kumar

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Uncontrolled growth of abnormal cells in the lung in the form of tumor can be either benign (non-cancerous) or malignant (cancerous). Patients with Lung Cancer (LC) have an average of five years life span expectancy provided diagnosis, detection and prediction, which reduces many treatment options to risk of invasive surgery increasing survival rate. Computed Tomography (CT), Positron Emission Tomography (PET), and Magnetic Resonance Imaging (MRI) for earlier detection of cancer are common. Gaussian filter along with median filter used for smoothing and noise removal, Histogram Equalization (HE) for image enhancement gives the best results without inviting further opinions. Lung cavities are extracted and the background portion other than two lung cavities is completely removed with right and left lungs segmented separately. Region properties measurements area, perimeter, diameter, centroid and eccentricity measured for the tumor segmented image, while texture is characterized by Gray-Level Co-occurrence Matrix (GLCM) functions, feature extraction provides Region of Interest (ROI) given as input to classifier. Two levels of classifications, K-Nearest Neighbor (KNN) is used for determining patient condition as normal or abnormal, while Artificial Neural Networks (ANN) is used for identifying the cancer stage is employed. Discrete Wavelet Transform (DWT) algorithm is used for the main feature extraction leading to best efficiency. The developed technology finds encouraging results for real time information and on line detection for future research.

Keywords: artificial neural networks, ANN, discrete wavelet transform, DWT, gray-level co-occurrence matrix, GLCM, k-nearest neighbor, KNN, region of interest, ROI

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Authors: Mohit Batra, Noel Sarkar, Jayeeta Mitra

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In this study silica nanoparticles were synthesized using different methods and different silica sources namely Tetraethyl ortho silicate (TEOS), Sodium Silicate, Rice husk while chitosan nanoparticles were prepared with ionic gelation method using Sodium tripolyphosphate (TPP). Size and texture of silica nanoparticles were studied using field emission scanning electron microscopy (FESEM) and transmission electron microscopy (TEM) along with the effect of change in concentration of various reagents in different synthesis processes. Size and dispersion of Silica nanoparticles prepared from TEOS using stobber’s method were found better than other methods while nanoparticles prepared using rice husk were cheaper than other ones. Catalyst found to play a very significant role in controlling the size of nanoparticles in all methods.

Keywords: silica nanoparticles, gelatin, bio-nanocomposites, SEM, TEM, chitosan

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Authors: Arian Hosseini, Mahmudul Hasan

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To address the increasing need for efficient and accurate content moderation, we propose an efficient and lightweight deep classification ensemble structure. Our approach is based on a combination of simple visual features, designed for high-accuracy classification of violent content with low false positives. Our ensemble architecture utilizes a set of lightweight models with narrowed-down color features, and we apply it to both images and videos. We evaluated our approach using a large dataset of explosion and blast contents and compared its performance to popular deep learning models such as ResNet-50. Our evaluation results demonstrate significant improvements in prediction accuracy, while benefiting from 7.64x faster inference and lower computation cost. While our approach is tailored to explosion detection, it can be applied to other similar content moderation and violence detection use cases as well. Based on our experiments, we propose a "think small, think many" philosophy in classification scenarios. We argue that transforming a single, large, monolithic deep model into a verification-based step model ensemble of multiple small, simple, and lightweight models with narrowed-down visual features can possibly lead to predictions with higher accuracy.

Keywords: deep classification, content moderation, ensemble learning, explosion detection, video processing

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Authors: Mark Osborn

Abstract:

Clustered, regularly interspaced short palindromic repeat (CRISPR/Cas) proteins can be designed to bind specified DNA and RNA sequences and hold great promise for the accurate detection of nucleic acids for diagnostics. Commercially available reagents were integrated into a CRISPR/Cas9-based lateral flow assay that can detect severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequences with single-base specificity. This approach requires minimal equipment and represents a simplified platform for field-based deployment. A rapid, multiplex fluorescence CRISPR/Cas9 nuclease cleavage assay capable of detecting and differentiating SARS-CoV-2, influenza A and B, and respiratory syncytial virus in a single reaction was also developed. These findings provide proof of principle for CRISPR/Cas9 point-of-care diagnosis that can detect specific SARS-CoV-2 strain(s). Further, Cas9 cleavage allows for a scalable fluorescent platform for identifying respiratory viral pathogens with overlapping symptomology. Collectively, this approach is a facile platform for diagnostics with broad application to user-defined sequence interrogation and detection.

Keywords: CRISPR/Cas9, lateral flow assay, SARS-Co-V2, single-nucleotide resolution

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Authors: Georg Ebner

Abstract:

The National Defence Academy, an element of the Austrian Ministry of Defence, is undergoing a transition process leading the Academy towards a new target structure that is currently being developed. In so doing, in addition to a subject-oriented approach, also an employee-oriented process was introduced. This process was initiated by the Ministry of Defence and should lead the National Defence Academy into a new constellation. During this process, the National Defence Academy worked in very special adapted World Café sessions. The “change manager” dealed with very different issues. They took the data feedback from the sessions and prepared with the feedback and information from the guidance the next session. So they got various information and a very different picture around the academy. It was very helpful to involve most of the employees of the academy during this process and to take their knowledge and wisdom. The process himself started with very different feelings and ended with great consent. A very interesting part of this process was also that the commander and his deputy worked together during all of this sessions and they answered all questions from the employees in time. The adapted World Café phases were necessary to deal with the information of the staff and to implement these absolutely needful data into this process. In cooperation with the responsible Headquarters, the first items resulting from the World Café phases could already be fed back to the employees and be implemented. The staff-oriented process is currently supported via a point of contact, through which the staff can contribute ideas as well, but also by the active information policy on the part of the Headquarters. The described change process makes innovative innovations possible. So far, in the event of change processes staff members have been entrusted only with the concrete implementation plan and tied into the process when the respective workplaces were to be re-staffed. The procedure described here can be seen as food-for-thought for further change processes. The findings of this process are that a staff oriented process can lead an organisation into a new era of thinking and working. This process has shown, that a lot of innovative ideas can also take place in a ministry. This process can be a background for a lot of change management processes in ministries and governmental and non-governmental organisations.

Keywords: both directions approach, change management, knowledge database, transformation process, World Cafe

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Authors: Khuram Nawaz Sadozai, Sonia

Abstract:

The agriculture sector is deemed more vulnerable to climate change as its variation can directly affect the crop’s productivity, but farmers’ adaptation strategies play a vital role in climate change-agriculture relationship. Therefore, this research has been undertaken to assess the Climate Change impact on wheat productivity and farmers’ adaptability strategies in Khyber Pakhtunkhwa province, Pakistan. The panel dataset was analyzed to gauge the impact of changing climate variables (i.e., temperature, rainfall, and humidity) on wheat productivity from 1985 to 2015. Amid the study period, the fixed effect estimates confirmed an inverse relationship of temperature and rainfall on the wheat yield. The impact of temperature is observed to be detrimental as compared to the rainfall, causing 0.07 units reduction in the production of wheat with 1C upsurge in temperature. On the flip side, humidity revealed a positive association with the wheat productivity by confirming that high humidity could be beneficial to the production of the crop over time. Thus, this study ensures significant nexus between agricultural production and climatic parameters. However, the farming community in the underlying study area has limited knowledge about the adaptation strategies to lessen the detrimental impact of changing climate on crop yield. It is recommended that farmers should be well equipped with training and advanced agricultural management practices under the realm of climate change. Moreover, innovative technologies pertinent to the agriculture system should be encouraged to handle the challenges arising due to variations in climate factors.

Keywords: climate change, fixed effect model, panel data, wheat productivity

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Authors: Carlos Gordon, Patricio Encalada, Henry Lema, Diego Leon, Dennis Chicaiza

Abstract:

The following work presents a proposal of autonomous navigation of mobile robots implemented in an omnidirectional robot Kuka Youbot. We have been able to perform the integration of robotic operative system (ROS) and machine learning algorithms. ROS mainly provides two distributions; ROS hydro and ROS Kinect. ROS hydro allows managing the nodes of odometry, kinematics, and path planning with statistical and probabilistic, global and local algorithms based on Adaptive Monte Carlo Localization (AMCL) and Dijkstra. Meanwhile, ROS Kinect is responsible for the detection block of dynamic objects which can be in the points of the planned trajectory obstructing the path of Kuka Youbot. The detection is managed by artificial vision module under a trained neural network based on the single shot multibox detector system (SSD), where the main dynamic objects for detection are human beings and domestic animals among other objects. When the objects are detected, the system modifies the trajectory or wait for the decision of the dynamic obstacle. Finally, the obstacles are skipped from the planned trajectory, and the Kuka Youbot can reach its goal thanks to the machine learning algorithms.

Keywords: autonomous navigation, machine learning, path planning, robotic operative system, open source computer vision library

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Authors: Maha Atout, Pippa Hemingway, Jane Seymour

Abstract:

Background: A mixed method systematic review was undertaken in order to explore issues related to the experiences of health care providers and parents in the care of children with palliative care needs. The aims of this systematic review were to identify existing evidence about the experiences of communication in the care of children with palliative care needs, to appraise the research conducted in this area and to identify gaps in the literature in order to recommend for future related studies. Method: A mixed method systematic review of research on the experience of communication in the care of children with palliative care needs, conducted with parents and health professionals was undertaken. The electronic databases of CINAHL, Cochrane, PubMed, OVID, Social Care Online, Web of Science, Scopus, and ProQuest were searched for the period of 2000-2016. Inclusion was limited to studies of communication experience in the care of children with palliative care needs. Result: Thirty-eight studies were found. The studies were conducted in a variety of countries: Uganda, Jordan, USA, UK, Taiwan, Turkey, Ireland, Poland, Brazil, Australia, Switzerland, Sweden, Netherland, Lebanon, Spain, Greece, and China. The current review shows that parents tend to protect their children when they are discussing their illnesses with them, particularly where they have a life-threatening or life-limiting condition. The approach of parents towards the discussion of sensitive issues concerning death with their children is significantly affected by the cultural background of the families. Conservative cultures encourage collusion behaviours which tend to keep children unaware of the incurable nature of the disease. The major communication challenges reported by health professionals are facing difficulties in judging how much information should be given to parents, responding to difficult questions, conflicts with families and inadequate skills to support grieving families. Conclusion: It is probably significant for the future studies to consider the change of parent-child communication experience over time in order to understand how the parents could change their interaction styles with their children according to the different stages of their children’s disease. Moreover, further studies are required to investigate the experience of communication of parents of children with non-malignant life-threatening and life-limiting illnesses.

Keywords: children with life-threatening or life- limiting illnesses, end of life, experience of communication, healthcare care providers, paediatric palliative care

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Authors: Sejin Jung, Dongho Kang, Byungsik Kim

Abstract:

Assessing the impact of climate change requires the use of a multi-model ensemble (MME) to quantify uncertainties between scenarios and produce downscaled outlines for simulation of climate under the influence of different factors, including topography. This study decreases climate change scenarios from the 13 global climate models (GCMs) to assess the impacts of future climate change. Unlike South Korea, North Korea lacks in studies using climate change scenarios of the CoupledModelIntercomparisonProject (CMIP5), and only recently did the country start the projection of extreme precipitation episodes. One of the main purposes of this study is to predict changes in the average climatic conditions of North Korea in the future. The result of comparing downscaled climate change scenarios with observation data for a reference period indicates high applicability of the Multi-Model Ensemble (MME). Furthermore, the study classifies climatic zones by applying the Köppen-Geiger climate classification system to the MME, which is validated for future precipitation and temperature. The result suggests that the continental climate (D) that covers the inland area for the reference climate is expected to shift into the temperate climate (C). The coefficient of variation (CVs) in the temperature ensemble is particularly low for the southern coast of the Korean peninsula, and accordingly, a high possibility of the shifting climatic zone of the coast is predicted. This research was supported by a grant (MOIS-DP-2015-05) of Disaster Prediction and Mitigation Technology Development Program funded by Ministry of Interior and Safety (MOIS, Korea).

Keywords: MME, North Korea, Koppen–Geiger, climatic zones, coefficient of variation, CV

Procedia PDF Downloads 99