Search results for: regional features

Authors: Xingyu Pan, Laure Tougne

Abstract:

For recognizing coins, the graved release date is important information to identify precisely its monetary type. However, reading characters in coins meets much more obstacles than traditional character recognition tasks in the other fields, such as reading scanned documents or license plates. To address this challenging issue in a numismatic context, we propose a training-free approach dedicated to detection and recognition of the release date of the coin. In the first step, the date zone is detected by comparing histogram features; in the second step, a topology-based algorithm is introduced to recognize coin numbers with various font types represented by binary gradient map. Our method obtained a recognition rate of 92% on synthetic data and of 44% on real noised data.

Keywords: coin, detection, character recognition, topology

Procedia PDF Downloads 240

Authors: Zahra Tolou-Ghamari

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Objective: Health care associated with multiresistant pathogens is rising globally. It is well known that nosocomial infections increase hospital stay, morbidity, mortality, and disability. Therefore, the aim of this study was to define the occurrence of nosocomial infections in a tertiary hospital in Isfahan/Iran. Materials and Methods: The data were extracted from the official database of hospital nosocomial infections records that included 9152 vertical rows. For each patient, the reported infections were coded by number as UTI-SUTI; Code 55, VAE-PVAP; Code 56, BSI-LCBI Code 19, SSI-DIP; Code 14, and so on. For continuous variables, mean ± standard deviation and for categorical variables, the frequency was used. Results: The study population was 5542 patients, comprised of males (n=3282) and females (n=2260). With a minimum of 15 and a maximum of 99, the mean age in 5313 patients was 58.5 ± 19.1 years old. The highest reported nosocomial infections (n= 77%) were associated with the ages 30-80 years old. Sites of nosocomial infections in 87% were as: VAE-PVAP; 27.3%, VAE-IVAC; 7.7, UTI-SUTI; 29.5%, BSI-LCBI; 12.9%, SSI-DIP; 9.5% and other individual infection (13%) with the main pathogens klebsiella pneumonia, acinetobacter baumannii and staphylococcus. Conclusions: For an efficient surveillance system, adopting pharmacotherapy used antibiotics in terms of monotherapy or polypharmacy control policy, in addition to advanced infection control programs at regional and national levels in Iran recommended.

Keywords: infection, nosocomial, ventilator, blood stream, Isfahan, Iran

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Authors: Mohammed Arif, Abdessalam Kifouche

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Speech is a very convenient way of communication between people and machines. It conveys information about the identity of the talker. Since speaker recognition technology is increasingly securing our everyday lives, the objective of this paper is to develop two automatic text-independent speaker verification systems (TI SV) using low-level spectral features and machine learning methods. (i) The first system is based on a support vector machine (SVM), which was widely used in voice signal processing with the aim of speaker recognition involving verifying the identity of the speaker based on its voice characteristics, and (ii) the second is based on Gaussian Mixture Model (GMM) and Universal Background Model (UBM) to combine different functions from different resources to implement the SVM based.

Keywords: speaker verification, text-independent, support vector machine, Gaussian mixture model, cepstral analysis

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Authors: Bandar Alahmadi, Manohar Mareboyana, Lethia Jackson

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Today, there are many applications that are using computer vision models, such as face recognition, image classification, and object detection. The accuracy of these models is very important for the performance of these applications. One challenge that facing the computer vision models is the adversarial examples attack. In computer vision, the adversarial example is an image that is intentionally designed to cause the machine learning model to misclassify it. One of very well-known method that is used to attack the Convolution Neural Network (CNN) is Fast Gradient Sign Method (FGSM). The goal of this method is to find the perturbation that can fool the CNN using the gradient of the cost function of CNN. In this paper, we introduce a novel model that can attack Regional-Convolution Neural Network (R-CNN) that use FGSM. We first extract the regions that are detected by R-CNN, and then we resize these regions into the size of regular images. Then, we find the best perturbation of the regions that can fool CNN using FGSM. Next, we add the resulted perturbation to the attacked region to get a new region image that looks similar to the original image to human eyes. Finally, we placed the regions back to the original image and test the R-CNN with the attacked images. Our model could drop the accuracy of the R-CNN when we tested with Pascal VOC 2012 dataset.

Keywords: adversarial examples, attack, computer vision, image processing

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Authors: Saeid Rabiei Majd, Motahareh Alvandi, Mehrad Rabiei

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The rapid economic and technological development of any country depends on access to cheap sources of energy. Competition for access to petroleum resources is always accompanied by numerous environmental risks. These factors have caused more attention to environmental issues and sustainable development in petroleum contracts and activities. Nowadays, a sign of developed countries is adhering to the principles and rules of international environmental law and sustainable development of commercial contracts. China has entered into play through the massive project plan, One Belt, One Road. China is becoming a new emerging power in the world. China's bilateral investment treaties have an impact on environmental rights and sustainable development through regional and international foreign direct investment. The aim of this research is to examine China's key position to promote and improve environmental principles and international law and sustainable development in the energy sector in the world through the initiative, One Belt, One Road. Based on this hypothesis, it seems that in the near future, China's investment bilateral investment treaties will become popular investment model used in global trade, especially in the field of energy and sustainable development. They will replace the European and American models. The research method is including literature review, analytical and descriptive methods.

Keywords: principles of sustainable development, oil and gas law, Chinas BITs, One Belt One Road, environmental rights

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Authors: Zineb Nougrara

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In this paper, we propose a novel methodology for extracting a road network and its nodes from satellite images of Algeria country. This developed technique is a progress of our previous research works. It is founded on the information theory and the mathematical morphology; the information theory and the mathematical morphology are combined together to extract and link the road segments to form a road network and its nodes. We, therefore, have to define objects as sets of pixels and to study the shape of these objects and the relations that exist between them. In this approach, geometric and radiometric features of roads are integrated by a cost function and a set of selected points of a crossing road. Its performances were tested on satellite images of Algeria country.

Keywords: satellite image, road network, nodes, image analysis and processing

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Authors: Petr Konvalina, Jan Moudry

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As organic farmers are searching foregoing crops for horticultural crops, there is possible to choice neglected wheat species and also have a new market and sale opportunities. Concerning wheat, there are landraces so called hulled wheat species (einkorn, emmer wheat, spelt) comprising parts of collections of the world gene banks. The advantage of this wheat species are small demands on growing conditions and also droughtiness in conditions of changing climate. Our paper aims at presenting the results of the study and the assessment of spring wheat forms, four einkorn cultivars, eight emmer wheat cultivars, seven spelt wheat cultivars in particular, as compared to modern bread wheat variety. Small-plot trials were established at two different localities within the Czech Republic and Austria in 2009 and 2012. The results of the trials show that some varieties were inclined to lodging. On the other hand, they were resistant to common wheat diseases (mildew, brown rust). Hulls served as barriers and obstacles against the DON grain contamination. The yield rate was lower. The grains were characterized by a high proportion of protein in grain (up to 18.1 %). However, they may be difficult to use for common baking. Moreover, new food products demonstrating a different technological quality of the hulled wheat species have to be launched on the market. They will be suitable for regional marketing.

Keywords: organic farming, hulled wheat species, einkorn, emmer, spelt

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Authors: José Anderson Rodrigues de Souza, Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, Jeronimo Silva Rocha

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Mobile devices are increasingly occupying sectors of society and one of its most important features is mobility. However, the use of mobile devices is subject to the lifetime of the batteries. Thus, the use of energy batteries has become an important issue in the study of wireless network technologies. In this context, new solutions that enable aggregate energy efficiency not only through energy saving, and principally they are evaluated from a more realistic model of energy discharge, if easy adaptation to existing protocols. This paper presents a study on the energy needed and the lifetime for Wireless Sensor Networks (WSN) using a heterogeneous network and applying the LEACH protocol.

Keywords: wireless sensor networks, energy efficiency, heterogeneous, LEACH protocol

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Authors: Wike Wike

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The aim of this study is to investigate the experience of mothers of autistic children in Indonesia in raising the children and obtaining services for them through the adequate of information. The study seeks to contribute to the knowledge emerging from the women as a mother of children with autism on health and disability area. There is silence in the Indonesian literature on this perspective, especially about the parents and/or mothers of autistic children that is the focus of this analysis. Therefore, in order to capture the points of view emerging from the mothers, a qualitative study design has been applied. The main data for this qualitative study was collected from interviews (semi-structured interview and focus group discussion) with the mothers of children with autism who are member of parenting group in autistic schools and rehabilitation centers in one of Indonesian regional cities. This study reveals that the mothers’ experience in raising a child who is diagnosed with autism is rooted in limited knowledge on autism, limited knowledge on availability of services and limited knowledge on service options. Compounding this is limited availability and accessibility of the services that are important to their child's development. An important contribution of this study is to show how tapping into the experience of mothers can provide much needed information to policy making and service planners and implementers that can improve the services for children with autism and their families.

Keywords: mothers, children with autism, disability services and policy, services

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Authors: Engin Eyceyurt, Josko Zec

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The current and future cellular mobile communication networks generate enormous amounts of data. Networks have become extremely complex with extensive space of parameters, features and counters. These networks are unmanageable with legacy methods and an enhanced design and optimization approach is necessary that is increasingly reliant on machine learning. This paper proposes that machine learning as a viable approach for uplink throughput prediction. LTE radio metric, such as Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and Signal to Noise Ratio (SNR) are used to train models to estimate expected uplink throughput. The prediction accuracy with high determination coefficient of 91.2% is obtained from measurements collected with a simple smartphone application.

Keywords: drive test, LTE, machine learning, uplink throughput prediction

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Authors: Zhiwei Yan, Jong-Hyouk Lee, Yong-Jin Park, Xiaodong Lee

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In this paper, we analyze NEtwork MObility (NEMO) supporting problems in Content-Centric Networking (CCN), and propose the CCN-NEMO which can well support the deployment of the content-centric paradigm in large-scale mobile Internet. The CCN-NEMO extends the signaling message of the basic CCN protocol, to support the mobility discovery and fast trigger of Interest re-issuing during the network mobility. Besides, the Mobile Router (MR) is extended to optimize the content searching and relaying in the local subnet. These features can be employed by the nested NEMO to maximize the advantages of content retrieving with CCN. Based on the analysis, we compare the performance on handover latency between the basic CCN and our proposed CCN-NEMO. The results show that our scheme can facilitate the content-retrieving in the NEMO scenario with improved performance.

Keywords: NEMO, CCN, mobility, handover latency

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Authors: S. M. Hamidi, M. Afsharnia

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Gas sensors based on magneto-plasmonic (MP) structures have attracted much attention due to the high signal to noise ratio in these type of sensors. In these sensors, both the plasmonic and the MO properties of the resulting MP structure become interrelated because the surface Plasmon resonance (SPR) of the metallic medium. This interconnection can be modified the sensor responses and enhanced the signal to noise ratio. So far the sensor features of multilayered structures made of noble and ferromagnetic metals as Au/Co/Au MP multilayer with TiO2 sensor layer have been extensively studied, but their SPR assisted sensor response need to the krestchmann configuration. Here, we present a systematic study on the new MP structure based on one-dimensional nano-grating Au/ Co/ Au/ TiO2 multilayer to utilize as an inexpensive and easy to use gas sensor.

Keywords: Magneto-plasmonic structures, Gas sensor, nano-garting

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Authors: Tim Farrelly

Abstract:

In recent years, AI-powered object detection systems have opened the doors for innovative new applications and products, especially those operating in the real world or ‘on edge’ – namely, in sport. This paper investigates the viability of an ultra-low parameter convolutional neural network specially designed for the detection of footballs on ‘on the edge’ devices. The main contribution of this paper is the exploration of integrating new design features (depth-wise separable convolutional blocks and squeezed and excitation modules) into an ultra-low parameter network and demonstrating subsequent improvements in performance. The results show that tracking the ball from Full HD images with negligibly high accu-racy is possible in real-time.

Keywords: deep learning, object detection, machine vision applications, sport, network design

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Authors: Feng Guo

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Human brain organoids, 3D brain tissue cultures derived from human pluripotent stem cells, hold promising potential in modeling neuroinflammation for a variety of neurological diseases. However, challenges remain in generating standardized human brain organoids that can recapitulate key physiological features of a human brain. Here, this study presents a series of organoids-on-a-chip systems to generate better human brain organoids and model neuroinflammation. By employing 3D printing and microfluidic 3D cell culture technologies, the study’s systems enable the reliable, scalable, and reproducible generation of human brain organoids. Compared with conventional protocols, this study’s method increased neural progenitor proliferation and reduced heterogeneity of human brain organoids. As a proof-of-concept application, the study applied this method to model substance use disorders.

Keywords: human brain organoids, microfluidics, organ-on-a-chip, neuroinflammation

Procedia PDF Downloads 192

Authors: Kunto Wibowo Agung Prodjonoto

Abstract:

Occasionally, opportunities occur not due to chances but threats. This, however, is often not realized because a greater threat is perceived to be anything that threatens, endangers, or harms, resulting in bad impacts that are also part of the risk and consequence. As a result, more focus tends to direct towards the bad impacts. Risk, in this case, shall be seen rather as something challenging, which can turn to be an opportunity to tackle an obstacle. Therefore, it does not seem exaggerating if later, risk can be considered as a challenge that presents an opportunity. So as in the context of the threat of natural disasters which gives an idea that opportunities exist. Nature referred to in a fashion as 'natural disasters' captured an expression to picture the 'threats' aspect, which instructively implying a chance of opportunity. This is quite logical, as SWOT (strengths, weaknesses, opportunities, threats) analysis can evaluate the situation at hand related to the analysis of various factors in formulating strategies to deal with natural disaster situations. The analytical method created by Albert Humphrey is indeed not an analytical tool to provide solutions, but certainly 'opportunities and challenges' are discussed therein on a vertical line, where opportunities are posited on the positive axis, and threats are posed on the negative axis. Observing this dynamism, the challenges and threats of disasters are having opportunity relevance to moralizing opportunities, that by quality poses universalism populist characteristics, universalism characteristics, and regional characteristics. Here, universalism appears as an opportunity domain underneath the threats and challenges of natural disasters.

Keywords: universality, opportunities, threats, challenges of natural disasters

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Authors: Majdi M. Alomari, Nafesah I. Alshdaifat, Mohammad S. Widyan

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Different countries have introduced different schemes and policies to counter global warming. The rationale behind the proposed policies and the potential barriers to successful implementation of the policies adopted by the countries were analyzed and estimated based on different models. It is argued that these models enhance the transparency and provide a better understanding to the policy makers. However, these models are underpinned with several structural and baseline assumptions. These assumptions, modeling features and future prediction of emission reductions and other implication such as cost and benefits of a transition to a low-carbon economy and its economy wide impacts were discussed. On the other hand, there are potential barriers in the form political, financial, and cultural and many others that pose a threat to the mitigation options.

Keywords: energy models, environmental policy instruments, mitigating CO2 emission, economic wide impact

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Authors: Sukryool Kang, James McConnaughey, Robin Doroshow, Raj Shekhar

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Still’s murmur, a vibratory heart murmur, is the most common normal innocent murmur of childhood. Many children with this murmur are unnecessarily referred for cardiology consultation and testing, which exacts a high cost financially and emotionally on the patients and their parents. Pediatricians to date are not successful at distinguishing Still’s murmur from murmurs of true heart disease. In this paper, we present a new algorithmic approach to distinguish Still’s murmur from pathological murmurs in children. We propose two distinct features, spectral width and signal power, which describe the sharpness of the spectrum and the signal intensity of the murmur, respectively. Seventy pediatric heart sound recordings of 41 Still’s and 29 pathological murmurs were used to develop and evaluate our algorithm that achieved a true positive rate of 97% and false positive rate of 0%. This approach would meet clinical standards in recognizing Still’s murmur.

Keywords: AR modeling, auscultation, heart murmurs, Still's murmur

Procedia PDF Downloads 352

Authors: Onder Yakut, Oguzhan Timus, Emine Dogru Bolat

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Health diseases have a vital significance affecting human being's life and life quality. Sudden death events can be prevented owing to early diagnosis and treatment methods. Electrical signals, taken from the human being's body using non-invasive methods and showing the heart activity is called Electrocardiogram (ECG). The ECG signal is used for following daily activity of the heart by clinicians. Heart Rate Variability (HRV) is a physiological parameter giving the variation between the heart beats. ECG data taken from MITBIH Arrhythmia Database is used in the model employed in this study. The detection of arrhythmic heart beats is aimed utilizing the features extracted from the HRV time domain parameters. The developed model provides a satisfactory performance with ~89% accuracy, 91.7 % sensitivity and 85% specificity rates for the detection of arrhythmic beats.

Keywords: arrhythmic beat detection, ECG, HRV, kNN classifier

Procedia PDF Downloads 341

Authors: Nazia Nazir

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Background: The benefits of regional anesthetic techniques are well established. Use of additives to local anesthetics can prolong these benefits. The aim of this study was to observe the effect of adding dexmedetomidine to bupivacaine for the supraclavicular block. Methods (Design): In this randomized, double-blind study, seventy ASA I & II patients of either sex undergoing elective surgeries on the upper limb were given supraclavicular block under ultrasound guidance. Group C (n=35), received 38 mL 0.25% bupivacaine + 2mL normal saline and group D received 38 mL 0.25% bupivacaine + 1 µg/kg dexmedetomidine (2mL). Patients were observed for onset, duration of motor and sensory block, duration of analgesia, sedation score, hemodynamic changes and any adverse events. Results: In group D the onset was faster (P < 0.001), duration of sensory and motor block, as well as duration of analgesia, was prolonged as compared to group C (P < 0.0001). There was significant drop in heart rate (HR) from the baseline in group D (P < 0.05) at 30, 60, 90 and 120 min, however, none of the patients dropped HR below 50/min. Mean arterial Pressure (MAP) remained unaffected. The patients in group D were effectively sedated than those in group C (P < 0.05). No adverse event was reported in either group. Conclusion: Dexmedetomidine as adjuvant to bupivacaine in supraclavicular block resulted in faster action, prolonged motor and sensory block, prolonged analgesia with hemodynamic stability and adequate sedation.

Keywords: Analgesia, bupivacaine, dexmedetomidine, supraclavicular block

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Authors: David A. Swanson, Lucky M. Tedrow

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Taylor’s Law is a widely observed empirical pattern that relates variances to means in sets of non-negative measurements via an approximate power function, which has found application to human mortality. This study adds to this research by showing that Taylor’s Law leads to a model that reasonably describes the relationship between life expectancy at birth (e0, which also is equal to mean age at death in a life table) and variance at age of death in seven World Bank regional life tables measured at two points in time, 1970 and 2000. Using as a benchmark a non-random sample of four Japanese female life tables covering the period from 1950 to 2004, the study finds that the simple linear model provides reasonably accurate estimates of variance in age at death in a life table from e0, where the latter range from 60.9 to 85.59 years. Employing 2017 life tables from the Human Mortality Database, the simple linear model is used to provide estimates of variance at age in death for six countries, three of which have high e0 values and three of which have lower e0 values. The paper provides a substantive interpretation of Taylor’s Law relative to e0 and concludes by arguing that reasonably accurate estimates of variance in age at death in a period life table can be calculated using this approach, which also can be used where e0 itself is estimated rather than generated through the construction of a life table, a useful feature of the model.

Keywords: empirical pattern, mean age at death in a life table, mean age of a stationary population, stationary population

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Authors: Mariana P. Medeiros, Amanda P. Carvallo, Augusta Isaac, Milos Janecek, Peter Minarik, Mayerling Martinez Celis, Roberto. R. Figueiredo

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The effect of high pressure torsion processing on mechanical properties and corrosion behavior of pure magnesium and Mg-Zn, Mg-Zn-Ca, Mg-Li-Y, and Mg-Y-RE alloys is investigated. Micro-tomography and SEM characterization are used to estimate corrosion rate and evaluate non-uniform corrosion features. The results show the severe plastic deformation processing improves the strength of all magnesium alloys, but deformation localization can take place in the Mg-Zn-Ca and Mg-Y-RE alloys. The occurrence of deformation localization is associated with low strain rate sensitivity in these alloys and with severe corrosion localization. Pure magnesium and Mg-Zn and Mg-Li-Y alloys display good corrosion resistance with low corrosion rate and maintained integrity after 28 days of immersion in Hank`s solution.

Keywords: magnesium alloys, severe plastic deformation, corrosion, biodegradable alloys

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Authors: Fatma Susilawati Mohamad, Azizah Abdul Manaf, Fadhillah Ahmad, Zarina Mohamad, Wan Suryani Wan Awang

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A simple and robust multi-class linear classifier is proposed and implemented. For a pair of classes of the linear boundary, a collection of segments of hyper planes created as perpendicular bisectors of line segments linking centroids of the classes or part of classes. Nearest Neighbor and Linear Discriminant Analysis are compared in the experiments to see the performances of each classifier in discriminating ripeness of oil palm. This paper proposes a multi-class linear classifier using Linear Discriminant Analysis (LDA) for image identification. Result proves that LDA is well capable in separating multi-class features for ripeness identification.

Keywords: multi-class, linear classifier, nearest neighbor, linear discriminant analysis

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Authors: K.Ishii, T. Furuichi, A. Fujiyama, S. Hariya

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Rice straw pellets are a promising fuel as a renewable energy source. Financial analysis is needed to make a utilization system using rise straw pellets financially feasible, considering all regional conditions including stakeholders related to the collection and storage, production, transportation and heat utilization. We conducted the financial analysis of feasibility for a heat utilization system using rice straw pellets which has been developed for the first time in Nanporo, Hokkaido, Japan. Especially, we attempted to clarify the effect of factors required for the system to be financial feasibility, such as the heating energy demand and collection and storage method of rice straw. The financial feasibility was found to improve when increasing the heating energy demand and collecting wheat straw in August separately from collection of rice straw in November because the costs of storing rice straw and producing pellets were reduced. However, the system remained financially unfeasible. This study proposed a contractor program funded by a subsidy from Nanporo local government where a contracted company, instead of farmers, collects and transports rice straw in order to ensure the financial feasibility of the system, contributing to job creation in the region.

Keywords: rice straw, pellets, heating energy demand, collection, storage

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Authors: Gaokai Liu

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Automatic defect detection for nanomaterial images is widely required in industrial scenarios. Deep learning approaches are considered as the most effective solutions for the great majority of image-based tasks. In this paper, an edge guidance network for defect segmentation is proposed. First, the encoder path with multiple convolution and downsampling operations is applied to the acquisition of shared features. Then two decoder paths both are connected to the last convolution layer of the encoder and supervised by the edge and segmentation labels, respectively, to guide the whole training process. Meanwhile, the edge and encoder outputs from the same stage are concatenated to the segmentation corresponding part to further tune the segmentation result. Finally, the effectiveness of the proposed method is verified via the experiments on open nanofibrous datasets.

Keywords: deep learning, defect detection, image segmentation, nanomaterials

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Authors: Hossein Soltani, Zahra Hojati, Seyed Reza Attarzadeh Hossini

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Anxiety levels before and during competition are not clear due to conflicting findings; various athletes have reported different levels of anxiety from much too low. With respect to the fact that every sport field has its own special nature, and the lack of a comprehensive theory in this field made the author to compare competitive state anxiety among team sport and individual sport athletes in Iran. The sample included 120 male athletes, 60 athletes in individual sports (taekwondo, karate, and wrestling) and 60 athletes in team sports (volleyball, basketball, futsal). All participants in this study were regularly competing at the super leagues and regional level. The research instrument employed was the Persian version of the Competitive State Anxiety Inventory-2. This inventory was distributed among the subjects about 30 minutes before the first competition. Finally, using one-way ANOVA data was analyzed. The results indicated that the mean score of cognitive and somatic anxiety among individual sport athletes was higher than that of team sport athletes (P<0.05). Self-confidence levels of individual sports athletes was higher than that of team sports athletes but the difference was not significant (P >0.05). It seems the being part of a team alleviates some of the pressure experienced by those who compete alone. Conclusion: Individual sport athletes may be more exposed to evaluation and more engaged in their own skills and abilities than team sport athletes given that responsibility for performance is not distributed across several performers.

Keywords: competitive state anxiety, cognitive anxiety, somatic anxiety, team sports, individual sports

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Authors: Arthur Thirion

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Auxetic geometries allow the generation of a negative Poisson ratio (NPR) in conventional materials. This behaviour allows materials to have certain improved mechanical properties, including impact resistance and altered synclastic behaviour. This means these structures have significant potential when it comes to applications as chronic wound dressings. To this end, 6 different "perforated sheet" structure types were 3D printed. These structures all had variations of key geometrical features included cell length and angle. These were tested in compression and tension to assess their Poisson ratio. Both a positive and negative Poisson ratio was generated by the structures depending on the loading. The a/b ratio followed by θ has been shown to impact the Poisson ratio significantly. There is still a significant discrepancy between modelled and observed behaviour.

Keywords: auxetic materials, 3D printing, negative Poisson's ratio, tunable Poisson's ratio

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Authors: Mengqi Zhu, Chang Nyung Kim

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This study numerically investigates three-dimensional liquid-metal (LM) magnetohydrodynamic (MHD) flows in a misaligned duct under a uniform magnetic field. The duct consists of two misaligned horizontal channels (one is inflow channel, the other is outflow channel) and one central vertical channel. Computational fluid dynamics simulations are performed to predict the behavior of the MHD flows, using commercial code CFX. In the current study, a case with Hartmann number 1000 is considered. The electromagnetic features of LM MHD flows are elucidated to examine the interdependency of the flow velocity, current density, electric potential, pressure drop and Lorentz force. The results show that pressure decreases linearly along the main flow direction.

Keywords: CFX, liquid-metal magnetohydrodynamic flows, misaligned duct, pressure drop

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Authors: Thomas Roche, Erica Wilson, Elizabeth Goode

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Universities across the globe are considering how to effect meaningful change in their higher education (HE) delivery in the face of increasingly diverse student cohorts and shifting student learning preferences. This paper reports on a descriptive case study of whole-of-institution curriculum reform at one regional Australian university, where more traditional 13-week semesters were replaced with a 6-week immersive block model drawing on active learning pedagogy. Based on a synthesis of literature in best practice HE pedagogy and principles, the case study draws on student performance data and senior management staff interviews (N = 5) to outline the key changes necessary for successful HE transformation to deliver increased student pass rates and retention. The findings from this case study indicate that an institutional transformation to an immersive block model requires both a considered change in institutional policy and process as well as the appropriate resourcing of roles, governance committees, technical solutions, and, importantly, communities of practice. Implications for practice at higher education institutions considering reforming their curriculum model are also discussed.

Keywords: student retention, immersive scheduling, block model, curriculum reform, active learning, higher education pedagogy, higher education policy

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Authors: Ivaylo A. Todorov, Peter S. Boyadzhiev

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A new distinctive species of Stepanovia Kostjukov (Hymenoptera: Eulophidae: Tetrastichinae) was reared in laboratory from mature galls of Diplolepis rosae (Linnaeus) (Cynipidae). The galls were collected from Rosa sp. bushes growing in Osogovo Mt. in Western Bulgaria. The new species is close to Stepanovia rosae Boyadzhiev & Todorov but differs in POL and OOL characteristics, width of antennae, forewings and ovipositor sheaths characteristics, different U-shaped pale stripe above clypeus and the length of the ventral plaque on male antenna. The taxonomically important morphological features are illustrated and compared with the rest species of the genus using Scanning electron microscopy and light reflection by compound microscopy. Images of male genitalia are also prepared.

Keywords: Eulophidae, Diplolepis rosae, galls, Stepanovia osogoviensis, Bulgaria

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Authors: Nidhal K. Azawi, John M. Gauch

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Colorectal cancer is one of the leading causes of cancer death in the US and the world, which is why millions of colonoscopy examinations are performed annually. Unfortunately, noise, specular highlights, and motion artifacts corrupt many images in a typical colonoscopy exam. The goal of our research is to produce automated techniques to detect and correct or remove these noninformative images from colonoscopy videos, so physicians can focus their attention on informative images. In this research, we first automatically extract features from images. Then we use machine learning and deep neural network to classify colonoscopy images as either informative or noninformative. Our results show that we achieve image classification accuracy between 92-98%. We also show how the removal of noninformative images together with image alignment can aid in the creation of image panoramas and other visualizations of colonoscopy images.

Keywords: colonoscopy classification, feature extraction, image alignment, machine learning

Procedia PDF Downloads 239