Search results for: Event processing system

Authors: S. Vignesh, K. S. Rangasamy

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The paper deals with the device capable of detecting and disabling digital cameras. The system locates the camera and then neutralizes it. Every digital camera has an image sensor known as a CCD, which is retro-reflective and sends light back directly to its original source at the same angle. The device shines infrared LED light, which is invisible to the human eye, at a distance of about 20 feet. It then collects video of these reflections with a camcorder. Then the video of the reflections is transferred to a computer connected to the device, where it is sent through image processing algorithms that pick out infrared light bouncing back. Once the camera is detected, the device would project an invisible infrared laser into the camera's lens, thereby overexposing the photo and rendering it useless. Low levels of infrared laser neutralize digital cameras but are neither a health danger to humans nor a physical damage to cameras. We also discuss the simplified design of the above device that can used in theatres to prevent piracy. The domains being covered here are optics and image processing.

Keywords: CCD, optics, image processing, D3CIP

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Authors: Nor Diana Ahmad, Eric Atwell, Brandon Bennett

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Text processing techniques for English have been developed for several decades. But for the Malay language, text processing methods are still far behind. Moreover, there are limited resources, tools for computational linguistic analysis available for the Malay language. Therefore, this research presents the use of natural language processing (NLP) in processing Malay translated Qur’an text. As the result, a new language resource for Malay translated Qur’an was created. This resource will help other researchers to build the necessary processing tools for the Malay language. This research also develops a simple question-answer prototype to demonstrate the use of the Malay Qur’an resource for text processing. This prototype has been developed using Python. The prototype pre-processes the Malay Qur’an and an input query using a stemming algorithm and then searches for occurrences of the query word stem. The result produced shows improved matching likelihood between user query and its answer. A POS-tagging algorithm has also been produced. The stemming and tagging algorithms can be used as tools for research related to other Malay texts and can be used to support applications such as information retrieval, question answering systems, ontology-based search and other text analysis tasks.

Keywords: language resource, Malay translated Qur'an, natural language processing (NLP), text processing

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Authors: Kyoko Tominaga

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Non-Government Organizations (NGOs), Non-Profit Organizations (NPOs), Social Enterprises and other actors play an important role in political decisions in governments at the international levels. Especially, such organizations’ and activists’ network in civil society is quite important to effect to the global politics. To solve the complex social problems in global era, diverse actors should corporate each other. Moreover, network of protesters is also contributes to diffuse tactics, information and other resources of social movements. Based on the findings from the study of International Trade Fairs (ITFs), the author analyzes the network of activists in anti-globalism movement. This research focuses the transition of 54 activists’ whole network in the “protest event” against 2008 G8 summit in Japan. Their network is examined at the three periods: Before protest event phase, during protest event phase and after event phase. A mixed method is used in this study: the author shows the hypothesis from social network analysis and evaluates that with interview data analysis. This analysis gives the two results. Firstly, the more protesters participate to the various events during the protest event, the more they build the network. After that, active protesters keep their network as well. From interview data, we can understand that the active protesters can build their network and diffuse the information because they communicate with other participants and understand that diverse issues are related. This paper comes to same conclusion with previous researches: protest events activate the network among the political activists. However, some participants succeed to build their network, others do not. “Networked” activists are participated in the various events for short period of time and encourage the diffusion of information and tactics of social movements.

Keywords: social movement, global justice movement, tactics, diffusion

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Authors: Deborah Zelinsky

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The retina filters millions of incoming signals into a smaller amount of exiting optic nerve fibers that travel to different portions of the brain. Most of the signals are for eyesight (called "image-forming" signals). However, there are other faster signals that travel "elsewhere" and are not directly involved with eyesight (called "non-image-forming" signals). This article centers on the neurons of the optic nerve connecting to parts of the limbic system. Eye care providers are currently looking at parvocellular and magnocellular processing pathways without realizing that those are part of an enormous "galaxy" of all the body systems. Lenses are modifying both non-image and image-forming pathways, taking A.M. Skeffington's seminal work one step further. Almost 100 years ago, he described the Where am I (orientation), Where is It (localization), and What is It (identification) pathways. Now, among others, there is a How am I (animation) and a Who am I (inclination, motivation, imagination) pathway. Classic eye testing considers pupils and often assesses posture and motion awareness, but classical prescriptions often overlook limbic involvement in visual processing. The limbic system is composed of the hippocampus, amygdala, hypothalamus, and anterior nuclei of the thalamus. The optic nerve's limbic connections arise from the intrinsically photosensitive retinal ganglion cells (ipRGC) through the "retinohypothalamic tract" (RHT). There are two main hypothalamic nuclei with direct photic inputs. These are the suprachiasmatic nucleus and the paraventricular nucleus. Other hypothalamic nuclei connected with retinal function, including mood regulation, appetite, and glucose regulation, are the supraoptic nucleus and the arcuate nucleus. The retino-hypothalamic tract is often overlooked when we prescribe eyeglasses. Each person is different, but the lenses we choose are influencing this fast processing, which affects each patient's aiming and focusing abilities. These signals arise from the ipRGC cells that were only discovered 20+ years ago and do not address the campana retinal interneurons that were only discovered 2 years ago. As eyecare providers, we are unknowingly altering such factors as lymph flow, glucose metabolism, appetite, and sleep cycles in our patients. It is important to know what we are prescribing as the visual processing evaluations expand past the 20/20 central eyesight.

Keywords: neuromodulation, retinal processing, retinohypothalamic tract, limbic system, visual processing

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Authors: Yili Chen, Xiaokun Liang, Zhicheng Zhang, Yaoqin Xie

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In an effort to restore visual perception in retinal diseases, an electronic retinal prosthesis with thousands of electrodes has been developed. The image processing strategies of retinal prosthesis system converts the original images from the camera to the stimulus pattern which can be interpreted by the brain. Practically, the original images are with more high resolution (256x256) than that of the stimulus pattern (such as 25x25), which causes a technical image processing challenge to do large-capacity image information reduction. In this paper, we focus on developing an efficient image processing stimulus pattern extraction algorithm by using a single cue saliency map for extracting salient objects in the image with an optimal trimming threshold. Experimental results showed that the proposed stimulus pattern extraction algorithm performs quite well for different scenes in terms of the stimulus pattern. In the algorithm performance experiment, our proposed SCSPE algorithm have almost five times of the score compared with Boyle’s algorithm. Through experiment s we suggested that when there are salient objects in the scene (such as the blind meet people or talking with people), the trimming threshold should be set around 0.4max, in other situations, the trimming threshold values can be set between 0.2max-0.4max to give the satisfied stimulus pattern.

Keywords: retinal prosthesis, image processing, region of interest, saliency map, trimming threshold selection

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Authors: Nurul-Akidah M. Yusak, Rahmah Mohamed, Noor Zuhaira Abd Aziz

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The introduction of degradable plastic materials into agricultural sectors has represented a promising alternative to promote green agriculture and environmental friendly of modern farming practices. Major challenges of developing degradable agricultural films are to identify the most feasible types of degradation mechanisms, composition of degradable polymers and related processing techniques. The incorrect choice of degradable mechanisms to be applied during the degradation process will cause premature losses of mechanical performance and strength. In order to achieve controlled process of agricultural film degradation, the compositions of degradable agricultural film also important in order to stimulate degradation reaction at required interval of time and to achieve sustainability of the modern agricultural practices. A set of photodegradable polyethylene based agricultural film was developed and produced, following the selective optimization of processing parameters of the agricultural film manufacturing system. Example of agricultural films application for oil palm seedlings cultivation is presented.

Keywords: photodegradable polyethylene, plasticulture, processing schemes

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Authors: Penn P. Wu

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Recent advances in virtual reality (VR) technologies have made it possible for students to experience a virtual on-the-scene or virtual in-person observation of an educational event. In an experimental class, the author uses VR, particularly 360° videos, to virtually engage students in an event, through a wide spectrum of educational resources, such s a virtual “bystander.” Students were able to observe the event as if they were physically on site, although they could not intervene with the scene. The author will describe the adopted equipment, specification, and cost of building them as well as the quality of VR. The author will discuss (a) feasibility, effectiveness, and efficiency of using VR as a supplemental technology to teach college students and criteria and methodologies used by the authors to evaluate them; (b) barriers and issues of technological implementation; and (c) pedagogical practices learned through this experiment. The author also attempts to explore (a) how VR could provide an interactive virtual in-person learning experience; (b) how VR can possibly change traditional college education and online education; (c) how educators and balance six critical factors: cost, time, technology, quality, result, and content.

Keywords: learning with VR, virtual experience of learning, virtual in-person learning, virtual reality for education

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Manop Tirastittam

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Traceability system is one of the tools which can ensure the product’s confident of the consumer as it can trace the product back to its origin and can reduce the operation cost of recall. Nowadays, there are so many technologies which can be applied to the traceability system and also able to increase the efficiency of the system such as QR Code, barcode, GS1 and GTIN. As the result, this research is aimed to study and design the information technology pattern that suits for the traceability of Thailand’s orchid because Thailand’s orchid is the popular export product for Japan, USA, China, Netherlands and Italy. This study will enhance the value of Thailand’s orchid and able to prevent the unexpected event of the defects or damaged product. The traceability pattern was received IOC test from 12 experts from 4 fields of study which are traceability field, information technology field, information communication technology field and orchid export field. The result of the in-depth interview and questionnaire showed that the technology which most compatibility with the traceability system is the QR code. The mean of the score was 4.25 and the standard deviation was 0.5 as the QR code is the new technology and user-friendly. The traceability system should start from the farm to the consumer in the consuming country as the traceability system will enhance the quality level of the product and increase the value of its as well. The other outcome from this research is the supply chain model of Thailand’s Orchid along with the system architecture and working system diagram.

Keywords: exporting, information technology pattern, orchid, traceability

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Authors: M. Zyczkowski, P. Markowski, M. Karol

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The team from IOE MUT is developing fiber optic sensors for the security systems for 15 years. The conclusions of the work indicate that these sensors are complicated. Moreover, these sensors are expensive to produce and require sophisticated signal processing methods.We present the results of the investigations of three different applications of the modalmetric sensor: • Protection of museum collections and heritage buildings, • Protection of fiber optic transmission lines, • Protection of objects of critical infrastructure. Each of the presented applications involves different requirements for the system. The results indicate that it is possible to developed a fiber optic sensor based on a single fiber. Modification of optoelectronic parts with a change of the length of the sensor and the method of reflections of propagating light at the end of the sensor allows to adjust the system to the specific application.

Keywords: modalmetric fiber optic sensor, security sensor, optoelectronic parts, signal processing

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: Hasan Topacoglu

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The Meiji Restoration was a chain of events that restored Japan in 1868 and considered as the beginning of Japanese Modernization by many scholars. In 1968, to honor its modern incarnation, Japan celebrated Meiji Centennial as one of the biggest Media Events in the country after the World War II. It was celebrated all around the country throughout the year following with a central event in Tokyo. Meanwhile, Japanese scholars started an opposition movement and claimed that Government was using this event to raise nationalism, pointing at Government’s statement on the meaning of Meiji. Most of the scholars, unfortunately, were hooked into the ideological problem of the Government’s way of planning and evaluated it as a failure. However, scholars missed out an important point that apart from the central event in Tokyo, each city planned its own event and celebrated it on a different date, also with a different theme. For example, Kyoto showed a regional characteristic and focused on Kyoto’s own culture, tradition etc., and highlighted a further past than 100 years. This was mainly because some areas/cities had a different ‘memory’ for Meiji Restoration than Tokyo which was reflected through the way they celebrated Meiji Centennial. On the other hand, 2023 will be the year of Turkish Republic Centennial. A year which will be marked by national and maybe even international events. Although an official committee has not been announced yet, The 2023 Vision, a list of goals has been released by the Government to coincide with the centenary of the Republic of Turkey in 2023 and there are some ongoing projects that are planned to be completed by then. By looking at the content of these projects, it is possible to say that Government is aiming to focus on Modernization through the Centennial. However, some of the projects are already showing some interesting characteristics such as the Istanbul New Airport whose design is inspired by Selimiye Mosque’s Islamic-Ottoman figure. It is true that Turkey and Japan have different historical backgrounds and the timeline of the Meiji Restoration and Foundation of Turkish Republic are different. Therefore, a particular comparison between these two events is not justified. However, they may have more in common than we are up to think because, each country marked the start of a new nation conceived on modern principles. For that reason, it is important to understand the similarities or differences between Meiji Centennial and Turkish Republic Centennial as a media event. This study introduces Meiji Centennial as a media event and analyses opposition movement along with the meaning of Meiji Centennial. Additionally, it explains regional characteristic differences and gives Kyoto as an example. Moreover, it introduces some of the ongoing Centennial projects in Turkey and analyses the meaning of the Turkish Republic Centennial through these projects. Without comparing Japan and Turkey, it explains the case of Japan but the discussion centers on deepening our understanding of Centennial as a Media Event and remarks some important aspects for Turkey’s upcoming Centennial events.

Keywords: media events, Meiji centennial, the 2023 vision, Turkish republic centennial

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Authors: Ahd Aljarf, Saad Amin

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Images are important source of information used as evidence during any investigation process. Their clarity and accuracy is essential and of the utmost importance for any investigation. Images are vulnerable to losing blocks and having noise added to them either after alteration or when the image was taken initially, therefore, having a high performance image processing system and it is implementation is very important in a forensic point of view. This paper focuses on improving the quality of the forensic images. For different reasons packets that store data can be affected, harmed or even lost because of noise. For example, sending the image through a wireless channel can cause loss of bits. These types of errors might give difficulties generally for the visual display quality of the forensic images. Two of the images problems: noise and losing blocks are covered. However, information which gets transmitted through any way of communication may suffer alteration from its original state or even lose important data due to the channel noise. Therefore, a developed system is introduced to improve the quality and clarity of the forensic images.

Keywords: image filtering, image reconstruction, image processing, forensic images

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Authors: Maad Kamal Al-Anni

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This study is about an algorithmic dependence of Artificial Neural Network on Multilayer Perceptron (MPL) pertaining to the classification and clustering presentations for Mobile Adhoc Network vulnerabilities. Moreover, mobile ad hoc network (MANET) is ubiquitous intelligent internetworking devices in which it has the ability to detect their environment using an autonomous system of mobile nodes that are connected via wireless links. Security affairs are the most important subject in MANET due to the easy penetrative scenarios occurred in such an auto configuration network. One of the powerful techniques used for inspecting the network packets is Intrusion Detection System (IDS); in this article, we are going to show the effectiveness of artificial neural networks used as a machine learning along with stochastic approach (information gain) to classify the malicious behaviors in simulated network with respect to different IDS techniques. The monitoring agent is responsible for detection inference engine, the audit data is collected from collecting agent by simulating the node attack and contrasted outputs with normal behaviors of the framework, whenever. In the event that there is any deviation from the ordinary behaviors then the monitoring agent is considered this event as an attack , in this article we are going to demonstrate the  signature-based IDS approach in a MANET by implementing the back propagation algorithm over ensemble-based Traffic Table (TT), thus the signature of malicious behaviors or undesirable activities are often significantly prognosticated and efficiently figured out, by increasing the parametric set-up of Back propagation algorithm during the experimental results which empirically shown its effectiveness  for the ratio of detection index up to 98.6 percentage. Consequently it is proved in empirical results in this article, the performance matrices are also being included in this article with Xgraph screen show by different through puts like Packet Delivery Ratio (PDR), Through Put(TP), and Average Delay(AD).

Keywords: Intrusion Detection System (IDS), Mobile Adhoc Networks (MANET), Back Propagation Algorithm (BPA), Neural Networks (NN)

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Authors: Wheyming Tina Song, Chi-Hao Hong

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In this study, we investigate the effect of a new boarding policy - short stay, on the overcrowding efficiency in emergency department (ED). The decision variables are no. of short stay beds for least acuity ED patients. The performance measurements used are national emergency department overcrowding score (NEDOCS) and ED retention rate (the percentage that patients stay in ED over than 48 hours in one month). Discrete event simulation (DES) is used as an analysis tool to evaluate the strategy. Also, common random number (CRN) technique is applied to enhance the simulation precision. The DES model was based on a census of 6 months' patients who were treated in the ED of the National Taiwan University Hospital Yunlin Branch. Our results show that the new short-stay boarding significantly impacts both the NEDOCS and ED retention rate when the no. of short stay beds is more than three.

Keywords: emergency department (ED), common random number (CRN), national emergency department overcrowding score (NEDOCS), discrete event simulation (DES)

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Authors: Mariana T. Teixeira, Joana P. Luz

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This paper is based on assumptions of psycholinguistics and investigates the processing of ambiguous sentences in Brazilian Portuguese. Specifically, it aims to verify if there is a difference in processing time between sentences with lexical ambiguity and sentences with structural (or syntactic) ambiguity. We hypothesize, based on the Garden Path Theory, that the two types of ambiguity entail different cognitive efforts, since sentences with structural ambiguity require that two structures be processed, whereas ambiguous phrases whose root of ambiguity is in a word require the processing of a single structure, which admits a variation of punctual meaning, within the scope of only one lexical item. In order to test this hypothesis, 25 undergraduate students, whose average age was 27.66 years, native speakers of Brazilian Portuguese, performed a self-monitoring reading task of ambiguous sentences, which had lexical and structural ambiguity. The results suggest that unambiguous sentence processing is faster than ambiguous sentence processing, whether it has lexical or structural ambiguity. In addition, participants presented a mean reading time greater for sentences with syntactic ambiguity than for sentences with lexical ambiguity, evidencing a greater cognitive effort in sentence processing with structural ambiguity.

Keywords: Brazilian portuguese, lexical ambiguity, sentence processing, syntactic ambiguity

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Authors: Shiuh-Jer Huang, Chen-Zon Yan, C. K. Huang, Chun-Chien Ting

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Since the vision system application in industrial environment for autonomous purposes is required intensely, the image recognition technique becomes an important research topic. Here, deep learning algorithm is employed in image system to recognize the industrial object and integrate with a 7A6 Series Manipulator for object automatic gripping task. PC and Graphic Processing Unit (GPU) are chosen to construct the 3D Vision Recognition System. Depth Camera (Intel RealSense SR300) is employed to extract the image for object recognition and coordinate derivation. The YOLOv2 scheme is adopted in Convolution neural network (CNN) structure for object classification and center point prediction. Additionally, image processing strategy is used to find the object contour for calculating the object orientation angle. Then, the specified object location and orientation information are sent to robotic controller. Finally, a six-axis manipulator can grasp the specific object in a random environment based on the user command and the extracted image information. The experimental results show that YOLOv2 has been successfully employed to detect the object location and category with confidence near 0.9 and 3D position error less than 0.4 mm. It is useful for future intelligent robotic application in industrial 4.0 environment.

Keywords: deep learning, image processing, convolution neural network, YOLOv2, 7A6 series manipulator

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Authors: Mohammed Kamil, M. M. Rahman, Rosli A. Bakar

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Modeling of hydrogen fueled engine (H₂ICE) injection system is a very important tool that can be used for explaining or predicting the effect of advanced injection strategies on combustion and emissions. In this paper, a common rail injection system (CRIS) is proposed for 4-strokes 4-cylinders hydrogen fueled engine with port injection feeding system (PIH₂ICE). For this system, a numerical one-dimensional gas dynamic model is developed considering single injection event for each injector per a cycle. One-dimensional flow equations in conservation form are used to simulate wave propagation phenomenon throughout the CR (accumulator). Using this model, the effect of common rail on the injection system characteristics is clarified. These characteristics include: rail pressure, sound velocity, rail mass flow rate, injected mass flow rate and pressure drop across injectors. The interaction effects of operational conditions (engine speed and rail pressure) and geometrical features (injector hole diameter) are illustrated; and the required compromised solutions are highlighted. The CRIS is shown to be a promising enhancement for PIH₂ICE.

Keywords: common rail, hydrogen engine, port injection, wave propagation

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Authors: Eva Čáslavová, Andrej Višněvský

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This research focused on the dimensions of brand personality of the Ice Hockey World Championship sporting event. The authors compared the elements in relation to different demographic groups including gender, age, level of education and student status of the population of Prague. Moreover, the differences of opinions of respondents who had experience of visiting a sports event and those who had not were assessed. In the research, the modified brand personality scale was used. This modified scale consists of five dimensions: responsibility, activity, toughness, individuality and emotionality, none of which was previously tested. The authors had an intentional sample of 291 respondents from Prague available, ranging in age from 18 years to 75 years, with either a high school or university education. The respondents rated the characteristic features in a seven-point Likert Scale and the data was collected in November 2012. The results suggest that the Ice Hockey World Championship is most identified with these dimensions: responsibility, emotionality and activity. Men had higher mean scores (4.93) on the Likert Scale in the emotionality dimension, while women had higher mean scores (4.91) in the activity dimension. Those respondents with experience visiting an Ice Hockey World Championship match had the highest mean score (5.10) in the emotionality dimension. This research had expected to show more pronounced mean values (above six) on the Likert scale in the emotionality and activity dimensions that more strongly characterize the brand personality of the Ice Hockey World Championship, however this expectation was not confirmed.

Keywords: dimensions, brand personality, ice hockey, international sports event, marketing

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Authors: Entisar A. Elgmati

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Recurrent infant diarrhea is studied using daily data collected in Salvador, Brazil over one year and three months. A logistic regression model is fitted instead of Aalen's additive model using the same covariates that were used in the analysis with the additive model. The model gives reasonably similar results to that using additive regression model. In addition, the problem with the estimated conditional probabilities not being constrained between zero and one in additive model is solved here. Also martingale residuals that have been used to judge the goodness of fit for the additive model are shown to be useful for judging the goodness of fit of the logistic model.

Keywords: additive model, cumulative probabilities, infant diarrhoea, recurrent event

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Authors: Sehreen Moorat, Mussarat Lakho

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A method of artificial intelligence using digital mammograms data has been proposed in this paper for detection of breast cancer. Many researchers have developed techniques for the early detection of breast cancer; the early diagnosis helps to save many lives. The detection of breast cancer through mammography is effective method which detects the cancer before it is felt and increases the survival rate. In this paper, we have purposed image processing technique for enhancing the image to detect the graphical table data and markings. Texture features based on Gray-Level Co-Occurrence Matrix and intensity based features are extracted from the selected region. For classification purpose, neural network based supervised classifier system has been used which can discriminate between benign and malignant. Hence, 68 digital mammograms have been used to train the classifier. The obtained result proved that automated detection of breast cancer is beneficial for early diagnosis and increases the survival rates of breast cancer patients. The proposed system will help radiologist in the better interpretation of breast cancer.

Keywords: medical imaging, cancer, processing, neural network

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Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

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Authors: Giovanni Forte, Melania De Falco, Antonio Santo

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On 24th August 2016, central Italy was affected by a Mw 6.0 earthquake, representing the main shock of a long seismic sequence, which had a second shock Mw 6.6 on 26th October and lasts still nowadays. After the event, several field survey were carried out in the affected areas, which is made of historical masonry buildings. The post event reconnaissance missions were aimed at collecting information on the damage states of the buildings, the triggering of the landslides and the relationships with site effects. In this paper, the data collected after the event are analyzed considering the role of the geological and geomorphological setting and the ground motion scenario. The buildings displayed an uneven damage distribution, which was affected by both topographic and stratigraphic amplification. As pertains the landslides, which were the most recurrent among the ground failures, consisted mainly of rock falls and subordinately of translational slides. Finally, the collected knowledge showed a strong contribution of the local geological and geomorphological site condition on the resulting damage.

Keywords: Amatrice earthquake, damage states, landslides, site effects

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Authors: W. Ait Ahmed, M. Aggour, M. Naciri

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Extracting energy from biomass is an important alternative to produce different types of energy (heat, electricity, or both) assuring low pollution and better efficiency. It is a new yet reliable approach to reduce green gas emission by extracting methane from industry effluents and use it to power machinery. We focused in our project on using paper and mill effluents, treated in a UASB reactor. The methane produced is used in the factory’s power supply. The aim of this work is to develop an electronic system using Arduino platform connected to a gas sensor, to measure and display the curve of daily methane production on processing. The sensor will send the gas values in ppm to the Arduino board so that the later sends the RS232 hardware protocol. The code developed with processing will transform the values into a curve and display it on the computer screen.

Keywords: biogas, Arduino, processing, code, methane, gas sensor, program

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Authors: Ella Abaev, Shany Segal, Miri Gabay

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Background: Choking is a blockage of airways that prevents efficient breathing and air flow to the lungs. Choking may be partial or full and is an emergency situation. Complete or prolonged choking leads to apnea, lack of oxygen in the tissues of the body and brain, and can cause death. There are three mechanisms of choking: obstruction of internal respiratory tracts by food or object aspiration, any material that blocks or covers external air passages, external pressure on the neck or trapping between objects. Children's airways are narrower than that of adults and therefore the risk of choking is greater, due to the aspiration of food and other foreign bodies into the lungs. In the Child Development Center at Safra Children’s Hospital, Tel Hashomer in Israel are treated infants, toddlers, and children aged 0-18 years with various developmental disabilities. Due to the increase in reports of ‘almost an event’ of choking in the past year and the serious consequences of choking event, it was decided to give an emphasis to the issue. Incidence and methods: The number of reports of ‘almost an event’ or a choking event was examined at the center during the years 2013-2018 and a thorough research work was conducted on the subject in order to build a prevention program. Findings: Between 2013 and 2018 the center reported about ten cases of ‘almost choking events’. In the middle of 2018 alone three cases of ‘almost an event’ were reported. Objective: Providing knowledge leads to awareness raise, change of perception, change in behavior and prevention. The center employs more than 130 staff members from various sectors so that it is the work of multi-professional teams to promote the quality and safety of the treatment. The familiarity of the staff with risk factors, prevention guidelines, identification of choking signs, and treatment are most important and significant in determining the outcome of a choking event. Conclusions and recommendations: After in-depth research work was carried out in cooperation with the Risk Management Unit on the subject of choking, which include a description of the definitions, mechanisms, risk factors, treatment methods and extensive recommendations for prevention (e.g. using treatment and stimulation accessories with standards association stamps and adjustment of the type of food and the way it is served to match to the child's age and the ability to swallow). The expected stages of development and emphasis on the population of children with special needs were taken into account. The research findings will be published by the staff and parents of the patients, professional publications, and lectures and there is an expectation to decrease the number of choking events in the next years.

Keywords: children with special needs, choking, educational system, prevention guidelines

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Authors: Prodipta Bhowmik, Poulami Saha, Preety Mehra, Yogesh Soni, Triloki Nath Jha

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In India, the smart city concept is growing day by day. So, for smart city development, a better traffic management and monitoring system is a very important requirement. Nowadays, road accidents increase due to more vehicles on the road. Reckless driving is mainly responsible for a huge number of accidents. So, an efficient traffic management system is required for all kinds of roads to control the traffic speed. The speed limit varies from road to road basis. Previously, there was a radar system but due to high cost and less precision, the radar system is unable to become favorable in a traffic management system. Traffic management system faces different types of problems every day and it has become a researchable topic on how to solve this problem. This paper proposed a computer vision and machine learning-based automated system for multiple vehicle detection, tracking, and speed estimation of vehicles using image processing. Detection of vehicles and estimating their speed from a real-time video is tough work to do. The objective of this paper is to detect vehicles and estimate their speed as accurately as possible. So for this, a real-time video is first captured, then the frames are extracted from that video, then from that frames, the vehicles are detected, and thereafter, the tracking of vehicles starts, and finally, the speed of the moving vehicles is estimated. The goal of this method is to develop a cost-friendly system that can able to detect multiple types of vehicles at the same time.

Keywords: OpenCV, Haar Cascade classifier, DLIB, YOLOV3, centroid tracker, vehicle detection, vehicle tracking, vehicle speed estimation, computer vision

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Authors: Maryam Heidari, James H. Jones Jr.

Abstract:

Millions of online posts about different topics and products are shared on popular social media platforms. One use of this content is to provide crowd-sourced information about a specific topic, event or product. However, this use raises an important question: what percentage of information available through these services is trustworthy? In particular, might some of this information be generated by a machine, i.e., a bot, instead of a human? Bots can be, and often are, purposely designed to generate enough volume to skew an apparent trend or position on a topic, yet the consumer of such content cannot easily distinguish a bot post from a human post. In this paper, we introduce a model for social media bot detection which uses Bidirectional Encoder Representations from Transformers (Google Bert) for sentiment classification of tweets to identify topic-independent features. Our use of a Natural Language Processing approach to derive topic-independent features for our new bot detection model distinguishes this work from previous bot detection models. We achieve 94\% accuracy classifying the contents of data as generated by a bot or a human, where the most accurate prior work achieved accuracy of 92\%.

Keywords: bot detection, natural language processing, neural network, social media

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Authors: Belén Vinaixa Kinnear, Arturo Hidalgo López, Bernardo Elembo Wilasi, Pablo Fernández Pérez, Cecilia Hernández Fuentealba

Abstract:

The expanded use of risk assessment in legislative and corporate decision-making has increased the role of expert judgement in giving data for security-related decision-making. Expert judgements are required in most steps of risk assessment: danger recognizable proof, hazard estimation, risk evaluation, and examination of choices. This paper presents a fault tree analysis (FTA), which implies a probabilistic failure analysis applied to leakage of oil in a subsea production system. In standard FTA, the failure probabilities of items of a framework are treated as exact values while evaluating the failure probability of the top event. There is continuously insufficiency of data for calculating the failure estimation of components within the drilling industry. Therefore, fuzzy hypothesis can be used as a solution to solve the issue. The aim of this paper is to examine the leaks from the Zafiro West subsea oil facility by using fuzzy fault tree analysis (FFTA). As a result, the research has given theoretical and practical contributions to maritime safety and environmental protection. It has been also an effective strategy used traditionally in identifying hazards in nuclear installations and power industries.

Keywords: expert judgment, probability assessment, fault tree analysis, risk analysis, oil pipelines, subsea production system, drilling, quantitative risk analysis, leakage failure, top event, off-shore industry

Procedia PDF Downloads 181

Authors: Yawei Liang

Abstract:

Threat from cruise missiles is among the most dangerous considerations to a warship in the modern era: anti-ship cruise missiles are fast, accurate, and extremely destructive. In this paper, the goal was to use an object-orientated environment to program a simulation to model a scenario in which a lone frigate is attacked by a wave of missiles fired at given intervals. The parameters of the simulation are modified to examine the relationships between different variables in the situation, and an analysis is performed on various aspects of the defending ship’s equipment. Finally, the results are presented, along with a brief discussion.

Keywords: discrete event simulation, Monte Carlo simulation, naval resource management, weapon-target allocation/assignment

Procedia PDF Downloads 77

Authors: Priyanka Lokhande, Ram P. Sawant, Ganesh Kakad, Avinash Kolhatkar

Abstract:

In order to evaluate the influence of chemical processing on low-stress mechanical properties and fabric hand of worsted cloth, eight worsted suiting fabric samples of balance plain and twill weave were studied. The Kawabata KES-FB system has been used for the measurement of low-stress mechanical properties of before and after chemically processed worsted suiting fabrics. Primary hand values and Total Hand Values (THV) of before and after chemically processed worsted suiting fabrics were calculated using the KES-FB test data. Upon statistical analysis, it is observed that chemical processing has considerable influence on the low-stress mechanical properties and thereby on handle properties of worsted suiting fabrics. Improvement in the Total Hand Values (THV) after chemical processing is experienced in most of fabric samples.

Keywords: low stress mechanical properties, plain and twill weave, total hand value (THV), worsted suiting fabric

Procedia PDF Downloads 275

Authors: Keunsu Han

Abstract:

Sports has been used as a valuable tool for countries to enhance brand image and to pursue higher political interests. Olympic games are one of the best examples as a mega sport event to achieve such nations’ purposes. The term, “soft power,” coined by Nye, refers to country’s ability to persuade and attract foreign audiences through non-coercive ways such as cultural, diplomatic, and economic means. This concept of soft power provides significant answers about why countries are willing to host a mega sport event such as Olympics. This paper reviews the concept of soft power by Nye as a theoretical framework of this study to understand critical motivation for countries to host Olympics and examines the effects of 2016 Rio Olympics as the state’s soft power strategy. Thorough data analysis including media, government and private-sector documents, this research analyzes both negative and positive aspects of the nation’s image created during Rio Olympics and discusses the effects of Rio Olympics as Brazil’s chance to showcase its soft power by highlighting the best the state has to present.

Keywords: country brand, olympics, soft power, sport diplomacy, mega sport event

Procedia PDF Downloads 447