Search results for: feature fusion

Authors: Reza Gheisari, Paulo J. Bartolo, Nicholas Goddard

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Polymeric micro-cantilevers (Cs) are rapidly becoming popular for MEMS applications such as chemo- and bio-sensing as well as purely electromechanical applications such as microrelays. Polymer materials present suitable physical and chemical properties combined with low-cost mass production. Hence, micro-cantilevers made of polymers indicate much more biocompatibility and adaptability of rapid prototyping along with mechanical properties. This research studies the effects of three process and one size factors on the filling behaviour in micro cavity, and the role of each in the replication of micro parts using different polymer materials i.e. polypropylene (PP) SABIC 56M10 and acrylonitrile butadiene styrene (ABS) Magnum 8434. In particular, the following factors are considered: barrel temperature, mould temperature, injection speed and the thickness of micro features. The study revealed that the barrel temperature and the injection speed are the key factors affecting the flow length of micro features replicated in PP and ABS. For both materials, an increase of feature sizes improves the melt flow. However, the melt fill of micro features does not increase linearly with the increase of their thickness.

Keywords: flow length, micro cantilevers, micro injection moulding, microfabrication

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Authors: Sajed Sarabandi, Mostafa Rostampour Vajari

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Breast cancer is the most frequent form of cancer among women and the fifth-leading cause of cancer-related deaths. A common feature of cancer cells is their ability to survive and evade apoptosis. Understanding the mechanisms of these pathways and their regulatory factors can lead to the development of effective treatment strategies. In this study, we aim to model the effect of key miRNAs, which are significant regulatory factors in breast cancer. We designed a Petri net focusing on two crucial pathways, proliferation, and apoptosis, and identified the role of miRNAs in these pathways. Our analysis indicates that the upregulation of miRNAs 99a and 372 can effectively increase apoptosis and decrease proliferation. Moreover, we demonstrate that miRNA-600, previously reported as a potential candidate for treatment, may not be a suitable target due to its dual activity in proliferation. Therefore, further research is required to investigate the potential of this miRNA in cancer treatment. Our model shows that a combination of miRNA upregulation and knockdown can efficiently influence key genes such as MDM2 and PTEN, leading to the activation of apoptosis in cancer cells. Ultimately, our model successfully simulates the connection between regulatory miRNAs and key genes in breast cancer.

Keywords: breast cancer, microRNAs, bio-modeling, Petri net

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Authors: Luo Jin China, Jin Fang

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Countryside has been generally recognized and regarded as a characteristic symbol which presents in human memory for a long time. As a result of the change of times, because of it’s failure to meet the growing needs of the growing life and mental decline, the vast rural area began to decline. But their history feature image which accumulated by the ancient tradition provides people with the origins of existence on the spiritual level, such as "identity" and "belonging", makes people closer to the others in the spiritual and psychological aspects of a common experience about the past, thus the sense of a lack of culture caused by the losing of memory symbols is weakened. So, in the modernization process, how to repair its vitality and transform and planning it in a sustainable way has become a hot topics in architectural and urban planning. This paper aims to break the constraints of disciplines, from the perspective of interdiscipline, using the research methods of systems science to analyze and discuss the theories and methods of rural form factors, which based on the viewpoint of memory in psychology. So, we can find a right way to transform the Rural to give full play to the role of the countryside in the actual use and the shape of history spirits.

Keywords: rural, sustainable renovation, restoration, psychology, memory

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Mahima Thakur

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Trauma rehabilitation requires both repairing physical injury and reconstructing broken narrative systems. The trauma's aftereffects entwine the broken patterns, allowing a cohesive narrative to emerge. In this article, the book Extremely Loud and Incredibly Close by Jonathan Safran Foer is discussed from a psychoanalytic perspective. The paper discusses the 9/11 attacks and their effects on those who suffered and lost family members during the catastrophe. The primary character of the novel, Oskar, along with his grandfather and grandmother, each have unique trauma escape stories that will be examined in light of Cathy Caruth and Geoffery H. Hartman‘s study. The text's numerous horrifying repetitions function as a narration strategy that not only captures the awareness of trauma but also gives the reader the psychological feature to overcome its deadening effects. This article explores the role that communication may have in assisting individuals in overcoming trauma. In addition to more research on traumatic memories, Dominick LaCapra's trauma theory's notions of "working through" and "acting out" highlight the need of communication in overcoming trauma and attempting to live outside of it.

Keywords: trauma theory, Cathy Caruth, memories, escapes, communication

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Authors: Michelangelo Sofo, Giuseppe Labianca

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In recent years, the scientific community's interest in the exploratory analysis of biomedical data has increased exponentially. Considering the field of research of nutritional biologists, the curative process, based on the analysis of clinical data, is a very delicate operation due to the fact that there are multiple solutions for the management of pathologies in the food sector (for example can recall intolerances and allergies, management of cholesterol metabolism, diabetic pathologies, arterial hypertension, up to obesity and breathing and sleep problems). In this regard, in this research work a system was created capable of evaluating various dietary regimes for specific patient pathologies. The system is founded on a mathematical-numerical model and has been created tailored for the real working needs of an expert in human nutrition using the human-centered design (ISO 9241-210), therefore it is in step with continuous scientific progress in the field and evolves through the experience of managed clinical cases (machine learning process). DietAdhoc® is a decision support system nutrition specialists for patients of both sexes (from 18 years of age) developed with an agile methodology. Its task consists in drawing up the biomedical and clinical profile of the specific patient by applying two algorithmic optimization approaches on nutritional data and a symbolic solution, obtained by transforming the relational database underlying the system into a deductive database. For all three solution approaches, particular emphasis has been given to the explainability of the suggested clinical decisions through flexible and customizable user interfaces. Furthermore, the system has multiple software modules based on time series and visual analytics techniques that allow to evaluate the complete picture of the situation and the evolution of the diet assigned for specific pathologies.

Keywords: medical decision support, physiological data extraction, data driven diagnosis, human centered AI, symbiotic AI paradigm

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Authors: Asma A. Alsufyani, Maram A. Alharthi, Maha J. Althobaiti, Manal S. Alharthi, Huda Rizq

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Twitter is one of the most popular microblogging sites that allows users to publish short text messages called 'tweets'. Increasing the number of accounts to follow (followings) increases the number of tweets that will be displayed from different topics in an unclassified manner in the timeline of the user. Therefore, it can be a vital solution for many Twitter users to have their tweets in a timeline classified into general categories to save the user’s time and to provide easy and quick access to tweets based on topics. In this paper, we developed a classifier for timeline tweets trained on a dataset consisting of 3600 tweets in total, which were collected from Saudi Twitter and annotated manually. We experimented with the well-known Bag-of-Words approach to text classification, and we used support vector machines (SVM) in the training process. The trained classifier performed well on a test dataset, with an average F1-measure equal to 92.3%. The classifier has been integrated into an application, which practically proved the classifier’s ability to classify timeline tweets of the user.

Keywords: corpus creation, feature extraction, machine learning, short text classification, social media, support vector machine, Twitter

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Authors: Yunbin Deng

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Most existing applications of automatic speech recognition relies on cooperative subjects at a short distance to a microphone. Standoff speech recognition using microphone arrays can extend the subject to sensor distance somewhat, but it is still limited to only a few feet. As such, most deployed applications of standoff speech recognitions are limited to indoor use at short range. Moreover, these applications require air passway between the subject and the sensor to achieve reasonable signal to noise ratio. This study reports long range (50 feet) automatic speech recognition experiments using a Laser Doppler Vibrometer (LDV) sensor. This study shows that the LDV sensor modality can extend the speech acquisition standoff distance far beyond microphone arrays to hundreds of feet. In addition, LDV enables 'listening' through the windows for uncooperative subjects. This enables new capabilities in automatic audio and speech intelligence, surveillance, and reconnaissance (ISR) for law enforcement, homeland security and counter terrorism applications. The Polytec LDV model OFV-505 is used in this study. To investigate the impact of different vibrating materials, five parallel LDV speech corpora, each consisting of 630 speakers, are collected from the vibrations of a glass window, a metal plate, a plastic box, a wood slate, and a concrete wall. These are the common materials the application could encounter in a daily life. These data were compared with the microphone counterpart to manifest the impact of various materials on the spectrum of the LDV speech signal. State of the art deep neural network modeling approaches is used to conduct continuous speaker independent speech recognition on these LDV speech datasets. Preliminary phoneme recognition results using time-delay neural network, bi-directional long short term memory, and model fusion shows great promise of using LDV for long range speech recognition. To author’s best knowledge, this is the first time an LDV is reported for long distance speech recognition application.

Keywords: covert speech acquisition, distant speech recognition, DSR, laser Doppler vibrometer, LDV, speech intelligence surveillance and reconnaissance, ISR

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Authors: Girma Yohannis Bade, Olga Kolesnikova, Grigori Sidorov

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Named entity recognition (NER) is a building block for information extraction. Though the information extraction process has been automated using a variety of techniques to find and extract a piece of relevant information from unstructured documents, the discovery of targeted knowledge still poses a number of research difficulties because of the variability and lack of structure in Web data. NER, a subtask of information extraction (IE), came to exist to smooth such difficulty. It deals with finding the proper names (named entities), such as the name of the person, country, location, organization, dates, and event in a document, and categorizing them as predetermined labels, which is an initial step in IE tasks. This survey paper presents the roles and importance of NER to IE from the perspective of different algorithms and application area domains. Thus, this paper well summarizes how researchers implemented NER in particular application areas like finance, medicine, defense, business, food science, archeology, and so on. It also outlines the three types of sequence labeling algorithms for NER such as feature-based, neural network-based, and rule-based. Finally, the state-of-the-art and evaluation metrics of NER were presented.

Keywords: the role of NER, named entity recognition, information extraction, sequence labeling algorithms, named entity application area

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Authors: Fung Sze Wai Veera, Peter W. Ferretto

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Gender functions as a principle in organizing society based on the cultural meanings given to males and females. It is an essential component in constructing the spatial reality, one that is in most cases in favor of men’s needs and disregards that of women’s. Similar to other minorities in China, men of the Dong community hold the primary position in policymaking, moral standards, social values, and, furthermore, the building of the physical environment. This study, therefore, aims to investigate the residential architecture of Dong through the lens of gender. Specifically, it examines how the patriarchal practice of Dong is manifested in terms of the spatial organization, the architectural feature, and the construction process of Dong houses in the southern dialect areas. While the residential architecture of Dong has been extensively researched, the role of gender culture in designing and constructing it deserves more research attention. Ultimately, the objective of this study is to challenge the notion of gender-inclusive design in the rural China context while opening up a cross-disciplinary discussion concerning Chinese minority architecture and gender studies.

Keywords: Dong minority residential architecture, gender study, built environment, male-dominated society, gender-inclusive design

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Authors: Azzam Alosaimi

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Different countries attempt to reduce energy demands and Greenhouse Gas (GHG) emissions to mitigate global warming potential. They set different building codes to regulate excessive building’s energy losses. Energy losses occur due to pressure difference between the indoor and outdoor environments, and thus, heat transfers from one region to another. One major sources of energy loss is known as building airtightness. Building airtightness is the fundamental feature of the building envelope that directly impacts infiltration. Most of international building codes require minimum performance for new construction to ensure acceptable airtightness. The execution of airtightness required standards has become more challenging in recent years due to a lack of expertise and equipment, making it costly and time-consuming. Hence, researchers have developed predictive models to predict buildings infiltration rates to meet building codes and to reduce energy and cost. This research applies a theoretical modeling approach using Matlab software to predict mean infiltration rate distributions and total heat loss of Saudi Arabia’s housing stock.

Keywords: infiltration rate, energy demands, heating loss, cooling loss, carbon emissions

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Authors: Heeyoung Lee, Woosung Bin, Kangseog Seo, Hyojeong Yun, Zuog An

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Recently, a new continuous bridge system has been proposed to increase the space under the bridge and to improve aesthetic aspect of the urban area. The main feature of the proposed bridge is to connect steel I-girders and coping by means of prestressed high-strength steel bars and steel plate. The proposed bridge is able to lower the height of the bridge to ensure the workability and efficiency through a reduction of the cost of road construction. This study presents the experimental result of the full-scale connection between steel I-girders and coping under the negative bending moment. The composite behavior is thoroughly examined and discussed under the specific load levels such as service load, factored load and crack load. Structural response showed full composite action until the final load level because no relative displacement between coping and girder was observed. It was also found prestressing force into high-strength bars was able to control tensile stresses of deck slab. This indicated that cracks in deck slab can be controlled by above-mentioned prestressing force.

Keywords: coping, crack, integrated bridge, full-scale test

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Authors: Haziyah Hussin, Syazwan Abdul Samad, Rosnani Jusoh

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This study is aimed towards the automisation of basic patternmaking for traditional clothes for the purpose of mass production using AutoCAD to apply AutoLISP feature under software Hazi Attire. A standard dress form (industrial form) with the size of small (S), medium (M) and large (L) size is measured using full body scanning machine. Later, the pattern for the clothes is designed parametrically based on the measured dress form. Hazi Attire program is used within the framework of AutoCAD to generate the basic pattern of front bodice, back bodice, front skirt, back skirt and sleeve block (sloper). The generation of pattern is based on the parameters inputted by user, whereby in this study, the parameters were determined based on the measured size of dress form. The finalized pattern parameter shows that the pattern fit perfectly on the dress form. Since the pattern is generated almost instantly, these proved that using the AutoLISP programming, the manufacturing lead time for the mass production of the traditional clothes can be decreased.

Keywords: apparel, AutoLISP, Malay traditional clothes, pattern ganeration

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Authors: Pankaj Kumar Jha, Mahendra Singh Hada, Brijendra Singh

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Protection system is an essential feature of the electrical system which helps in detection and removal of faults. Protection system consists of many subsystems like relays, circuit breakers, instrument transformers, auxiliary DC system, auxiliary relays etc. Although the fundamental protective and relay operating concepts are similar throughout the world, there are very significant differences in their implementation. These differences arise through different traditions, operating philosophies, experiences and national standards. Protection system mis-operation due to problem in one or more of its subsystem or inadequate knowledge of numerical relay settings and configuration are very common throughout the world. Protection system mis-operation leads to unstable and unreliable grid operation. In this paper we will discuss about the fundamental concepts of protective relaying and the reasons for protection system mis-operation due to one or more of its subsystems. Many real-world case studies of protection system mis-operation from Indian power sector are discussed in detail in this paper.

Keywords: auxiliary trip relays, bus zone, check zone, CT saturation, dead zone protection, DC ground faults, DMT, DR, end fault protection, instrument transformer, SOTF, STUB

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Authors: Emi Yuda, Yutaka Yoshida, Junichiro Hayano

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Distinct circadian rhythm of activity, i.e., high activity during the day and deep rest at night are a typical feature of a healthy lifestyle. Exposure to the skylight is thought to be an important factor to increase arousal level and maintain normal circadian rhythm. To examine whether sunshine hours influence the day-night contract of activity, we analyzed the relationship between 24-hour heart rate (HR) and weather data of the recording day. We analyzed data in 36,500 males and 49,854 females of Allostatic State Mapping by Ambulatory ECG Repository (ALLSTAR) database in Japan. Median (IQR) sunshine duration was 5.3 (2.8-7.9) hr. While sunshine hours had only modest effects of increasing 24-hour average HR in either gender (P=0.0282 and 0.0248 for male and female) and no significant effects on nighttime HR in either gender, it increased daytime HR (P = 0.0007 and 0.0015) and day-night HF difference in both genders (P < 0.0001 for both) even after adjusting for the effects of average temperature, atmospheric pressure, and humidity. Our observations support for the hypothesis that longer sunshine hours enhance circadian rhythm of activity.

Keywords: big data, circadian rhythm, heart rate, sunshine

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Authors: Dan Frederick Orcherton

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This research explores the fusion of "Critical Pedagogy of Place" and "Indigenous Education Philosophy" to create a holistic pedagogical framework within Instructional Theory, focusing on its application in Distance Education, specifically within two Pacific Island cultures. The study's objectives included investigating culturally relevant instructional techniques, strategies, and technologies for the Itaukei (Indigenous Fijian) and ni-Vanuatu cultures, enhancing appreciation for culturally sensitive pedagogical methods. Methodologically, a qualitative inquiry phenomenological approach was employed within a constructivist paradigm, utilizing a comprehensive qualitative scoping review and online literature search. Key findings include the prioritization of cultural inclusivity and indigenous knowledge integration in both indigenous education philosophies and various instructional approaches. Learner-centered methods like constructivist andragogy and the learning cycle are applicable and effective in distance education within these cultures, aligning with indigenous learners' values and preferences. Place-based education and critical pedagogy of place are particularly pertinent, fostering a deeper connection between education, local environments, and social justice. Integrating digital technologies in culturally responsive education bridges geographical gaps and preserves cultural knowledge. Lastly, blending Western and Indigenous Science, influenced by a Two-Eyed Seeing approach, informs pedagogy by combining Western and Indigenous Science. This research underscores the importance of acknowledging cultural diversity and respecting indigenous knowledge in distance education. It highlights the value of learner-centered approaches, place-based education, and technology integration. The study enriches the educational experience within the Itaukei and niVanuatu cultures and provides insights for educators and policymakers aiming to bridge cultural gaps in distance education.

Keywords: critical pedegory of place, Itaukei (indigenous Fijian) and ni-Vanuatu cultures, placed-based education, indigenous knowledge, distance education

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Authors: Kawalpreet Kalra, Alpana Goel

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The behaviour of the rotational bands should be smooth but due to large amount of inertia and decreased pairing it is not so. Many experiments have been done in the last few decades, and a large amount of data is available for comprehensive study in this region. Peculiar features like signature dependence, signature inversion, and signature reversal are observed in many two quasiparticle rotational bands of doubly odd and doubly even nuclei. At high rotational frequencies, signature and parity are the only two good quantum numbers available to label a state. Signature quantum number is denoted by α. Even-angular momentum states of a rotational band have α =0, and the odd-angular momentum states have α =1. It has been observed that the odd-spin members lie lower in energy up to a certain spin Ic; the normal signature dependence is restored afterwards. This anomalous feature is termed as signature inversion. The systematic of signature inversion in high-j orbitals for doubly odd rare earth nuclei have been done. Many unusual features like signature dependence, signature inversion and signature reversal are observed in rotational bands of even-even/odd-odd nuclei. Attempts have been made to understand these phenomena using several models. These features have been analyzed within the framework of the Two Quasiparticle Plus Rotor Model (TQPRM).

Keywords: rotational bands, signature dependence, signature quantum number, two quasiparticle

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Authors: Randy Price, Harbir Antil, Rainald Löhner, Fumiya Togashi

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Chemically reacting flows are common in engineering applications such as hypersonic flow, combustion, explosions, manufacturing process, and environmental assessments. The number of reactions in combustion simulations can exceed 100, making a large number of flow and combustion problems beyond the capabilities of current supercomputers. Motivated by this, deep neural networks (DNNs) will be introduced with the goal of eventually replacing the existing chemistry software packages with DNNs. The DNNs used in this paper are motivated by the Residual Neural Network (ResNet) architecture. In the continuum limit, ResNets become an optimization problem constrained by an ODE. Such a feature allows the use of ODE control techniques to enhance the DNNs. In this work, DNNs are constructed, which update the species un at the nᵗʰ timestep to uⁿ⁺¹ at the n+1ᵗʰ timestep. Parallel DNNs are trained for each species, taking in uⁿ as input and outputting one component of uⁿ⁺¹. These DNNs are applied to multiple species and reactions common in chemically reacting flows such as H₂-O₂ reactions. Experimental results show that the DNNs are able to accurately replicate the dynamics in various situations and in the presence of errors.

Keywords: chemical reacting flows, computational fluid dynamics, ODEs, residual neural networks, ResNets

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Authors: Piyush Sharma, Devi Prasad Sharma, Sulabh Bansal

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Diseases are fairly common in fruits and vegetables because of the changing climatic and environmental circumstances. Crop diseases, which are frequently difficult to control, interfere with the growth and output of the crops. Accurate disease detection and timely disease control measures are required to guarantee high production standards and good quality. In India, apples are a common crop that may be afflicted by a variety of diseases on the fruit, stem, and leaves. It is fungi, bacteria, and viruses that trigger the early symptoms of leaf diseases. In order to assist farmers and take the appropriate action, it is important to develop an automated system that can be used to detect the type of illnesses. Machine learning-based image processing can be used to: this research suggested a system that can automatically identify diseases in apple fruit and apple plants. Hence, this research utilizes the hybrid SVM-RBN model. As a consequence, the model may produce results that are more effective in terms of accuracy, precision, recall, and F1 Score, with respective values of 96%, 99%, 94%, and 93%.

Keywords: fruit plant disease, crop disease, machine learning, image processing, SVM-RBN

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Authors: Jungho Moon, Lae Jeong Park

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This paper introduces the development of a firmware downloader for students attending microcontroller-related courses taught by the authors In the courses, AVR microcontroller experiment kits are used for programming exercise and the AVR microcontroller is programmed through a serial communication interface using a bootloader preinstalled on it. To use the bootloader, a matching firmware downloader that runs on a host computer and communicates with the bootloader is also required. When firmware downloading is completed, the serial port used for it needs to be closed. If the downloaded firmware uses serial communication, the serial port needs to be reopened in a serial terminal. As a result, the programmer of the AVR board switches from the downloader program and the serial terminal and vice versa. It is a simple task but quite a hassle to do each time new firmware needs downloading. To provide a more convenient programming environment for the courses, the authors developed a downloader program that includes a serial terminal in it. The program operates in downloader or terminal mode and the mode switching is performed automatically; therefore manual mode switching is not necessary. The feature provides a more convenient development environment by eliminating the need for manual mode switching each time firmware downloading is required.

Keywords: bootloader, firmware downloader, microcontroller, serial communication

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Authors: James Q. Feng

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Pneumatic nebulizers (as variations based on the Collison nebulizer) have been widely used for producing fine aerosol droplets from a liquid material. As qualitatively described by many authors, the basic working principle of those nebulizers involves utilization of the negative pressure associated with an expanding gas jet to syphon liquid into the jet stream, then to blow and shear into liquid sheets, filaments, and eventually droplets. But detailed quantitative analysis based on fluid mechanics theory has been lacking in the literature. The purpose of present work is to investigate the nature of negative pressure distribution associated with compressible gas jet flow in the Collison nebulizer by a computational fluid dynamics (CFD) analysis, using an OpenFOAM® compressible flow solver. The value of the negative pressure associated with a gas jet flow is examined by varying geometric parameters of the jet expansion channel adjacent to the jet orifice outlet. Such an analysis can provide valuable insights into fundamental mechanisms in liquid aspiration process, helpful for effective design of the pneumatic atomizer in the Aerosol Jet® direct-write system for micro-feature, high-aspect-ratio material deposition in additive manufacturing.

Keywords: collison nebulizer, compressible gas jet flow, liquid aspiration, pneumatic atomization

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Authors: Erhan Ayas, Buse Katipoğlu, Eda Metin, Rifat Yılmaz

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The search for new materials has begun to be used even higher than the service temperature (~1150ᵒC) where nickel-based superalloys are currently used. This search should also meet the increasing demands for energy efficiency improvements. The materials studied for aerospace applications are expected to have good oxidation resistance. Mo-Si-B alloys, which have higher operating temperatures than nickel-based superalloys, are candidates for ultra-high temperature materials used in gas turbine and jet engines. Because the Moss and Mo₅SiB₂ (T2) phases exhibit high melting temperature, excellent high-temperature creep strength and oxidation resistance properties, however, low fracture toughness value at room temperature is a disadvantage for these materials, but this feature can be improved with optimum Moss phase and microstructure control. High-density value is also a problem for structural parts. For example, in turbine rotors, the higher the weight, the higher the centrifugal force, which reduces the creep life of the material. The density value of the nickel-based superalloys and the T2 phase, which is the Mo-Si-B alloy phase, is in the range of 8.6 - 9.2 g/cm³. But under these conditions, T2 phase Moss (density value 10.2 g/cm³), this value is above the density value of nickel-based superalloys. So, with some ceramic-based contributions, this value is enhanced by optimum values.

Keywords: molybdenum, composites, in-situ, mmc

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Authors: M. Sorahi Nobar, V. Niknam, H. Ebrahimzadeh, H. Soltanloo

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Fusarium graminearum is one of the most destructive crop diseases in the world. Infection occurs during the flowering period in warm and humid conditions. It causes reduction in yield. Moreover, harvested grain is often contaminated with mycotoxins and its acetylated derivatives. Fusarium mycotoxines are potent inhibitor of protein synthesis, and thereby presents hazards for both human and animal health. A rapid production of reactive oxygen intermediates, primarily superoxide and hydrogen peroxide at the site of attempted infection considered as key feature underlying successful pathogen recognition. Here, we compared the time course activity of superoxide dismutase (SOD) as a first line of defenses against ROS- induced oxidative burst between FHB- resistant Sumai3 and susceptible Falat at 48, 96 and 144 hours after infection. Our results showed that Sumai3 SOD activity increased with time and reached the highest-level 4 days after infection while in susceptible cultivar Falat, SOD activity decreased during the first 96 h. after infection. Decreased was followed by an increased at 6 days after infection. According to our results rapid induction of SOD activity in resistant cultivar may play an important role in resistance against FHB in wheat.

Keywords: Fusarium graminearum, mycotoxins, resistant cultivar, superoxide dismutase

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Authors: Farha Mizana Shamsudin, Shahidan Radiman, Yusof Abdullah, Nasri Abdul Hamid

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Oxide dispersion strengthened (ODS) ferritic steels are amongst the most promising candidates for large scale structural materials to be applied in next generation fission and fusion nuclear power reactors. This kind of material is relatively stable at high temperature, possess remarkable mechanical properties and comparatively good resistance from neutron radiation damage. The superior performance of ODS ferritic steels over their conventional properties is attributed to the high number density of nano-sized dispersoids that act as nucleation sites and stable sinks for many small helium bubbles resulting from irradiation, and also as pinning points to dislocation movement and grain growth. ODS ferritic steels are usually produced by powder metallurgical routes involving mechanical alloying (MA) process of Y2O3 and pre-alloyed or elemental metallic powders, and then consolidated by hot isostatic pressing (HIP) or hot extrusion (HE) techniques. In this study, Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (designated as 14YWT) was produced by mechanical alloying process and followed by hot isostatic pressing (HIP) technique. Crystal structure and morphology of this sample were identified and characterized by using X-ray Diffraction (XRD) and field emission scanning electron microscope (FESEM) respectively. The magnetic measurement of this sample at room temperature was carried out by using a vibrating sample magnetometer (VSM). FESEM micrograph revealed a homogeneous microstructure constituted by fine grains of less than 650 nm in size. The ultra-fine dispersoids of size between 5 nm to 19 nm were observed homogeneously distributed within the BCC matrix. The EDS mapping reveals that the dispersoids contain Y-Ti-O nanoclusters and from the magnetization curve plotted by VSM, this sample approaches the behavior of soft ferromagnetic materials. In conclusion, ODS Fe-14Cr-3W-0.5Ti-0.3Y₂O₃ (14YWT) ferritic steel was successfully produced by HIP technique in this present study.

Keywords: hot isostatic pressing, magnetization, microstructure, ODS ferritic steel

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Authors: M. Jazouli, S. Elhoufi, A. Majda, A. Zarghili, R. Aalouane

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Autism spectrum disorder is a complex developmental disability. It is defined by a certain set of behaviors. Persons with Autism Spectrum Disorders (ASD) frequently engage in stereotyped and repetitive motor movements. The objective of this article is to propose a method to automatically detect this unusual behavior. Our study provides a clinical tool which facilitates for doctors the diagnosis of ASD. We focus on automatic identification of five repetitive gestures among autistic children in real time: body rocking, hand flapping, fingers flapping, hand on the face and hands behind back. In this paper, we present a gesture recognition system for children with autism, which consists of three modules: model-based movement tracking, feature extraction, and gesture recognition using artificial neural network (ANN). The first one uses the Microsoft Kinect sensor, the second one chooses points of interest from the 3D skeleton to characterize the gestures, and the last one proposes a neural connectionist model to perform the supervised classification of data. The experimental results show that our system can achieve above 93.3% recognition rate.

Keywords: ASD, artificial neural network, kinect, stereotypical motor movements

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Authors: Billy Moore, Izaiah Smith, Dominic Mckinney, Andrew Cisco, Mehdi Kabir

Abstract:

Phase-change materials (PCMs) are considered one of the most promising substances to be engaged passively in thermal management and storage systems for spacecraft, where it is critical to diminish the overall mass of the onboard thermal storage system while minimizing temperature fluctuations upon drastic changes in the environmental temperature within the orbit stage. This makes the development of effective thermal management systems more challenging since there is no atmosphere in outer space to take advantage of natural and forced convective heat transfer. PCM can store or release a tremendous amount of thermal energy within a small volume in the form of latent heat of fusion in the phase-change processes of melting and solidification from solid to liquid or, conversely, during which temperature remains almost constant. However, the existing PCMs pose very low thermal conductivity, leading to an undesirable increase in total thermal resistance and, consequently, a slow thermal response time. This often turns into a system bottleneck from the thermal performance perspective. To address the above-mentioned drawback, the present study aims to design and develop various heat sinks featured by nano-structured graphitic foams (i.e., carbon foam), expanded graphite (EG), and open-cell copper foam (OCCF) infiltrated with a conventional paraffin wax PCM with a melting temperature of around 35 °C. This study focuses on the use of passive thermal management techniques to develop efficient heat sinks to maintain the electronics circuits’ and battery module’s temperature within the thermal safety limit for small spacecraft and satellites such as the Pumpkin and OPTIMUS battery modules designed for CubeSats with a cross-sectional area of approximately 4˝×4˝. Thermal response times for various heat sinks are assessed in a vacuum chamber to simulate space conditions.

Keywords: heat sink, porous foams, phase-change material (PCM), spacecraft thermal management

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Authors: Seo-Hee Kim, Kee-Won Kim, Seung-Hoon Kim

Abstract:

The most important elements of a novel are the characters, events and background. The background represents the time, place and situation that character appears, and conveys event and atmosphere more realistically. If readers have the proper knowledge about background of novels, it may be helpful for understanding the atmosphere of a novel and choosing a novel that readers want to read. In this paper, we are targeting Korean historical novels because spatio-temporal background especially performs an important role in historical novels among the genre of Korean novels. To the best of our knowledge, we could not find previous study that was aimed at Korean novels. In this paper, we build a Korean historical national dictionary. Our dictionary has historical places and temple names of kings over many generations as well as currently existing spatial words or temporal words in Korean history. We also present a method for recognizing spatio-temporal background based on patterns of phrasal words in Korean sentences. Our rules utilize postposition for spatial background recognition and temple names for temporal background recognition. The knowledge of the recognized background can help readers to understand the flow of events and atmosphere, and can use to visualize the elements of novels.

Keywords: data mining, Korean historical novels, Korean linguistic feature, spatio-temporal background

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Authors: Anita Kéri

Abstract:

Recent developments in the field of education have led to a renewed interest in teaching methodologies and practices. Gamification is fast becoming a key instrument in the education of new generations and besides other methods, serious games have become the center of attention. Ready-built serious games are available for most higher education institutions to buy and implement. However, monetary restraints and the unalterable nature of the games might deter most higher education institutions from the application of these serious games. Therefore, there is a continuously growing need for a customizable serious game that has been developed based on a concrete need analysis and experts’ opinion. There has been little evidence so far of serious games that have been created based on relevant and current need analysis from higher education institution teachers, professional practitioners and students themselves. Therefore, the aim of this current paper is to analyze the needs of higher education institution educators with special emphasis on their needs, the applicability of serious games in their classrooms, and exploring options for the development of a customizable serious game framework. The paper undertakes to analyze workshop discussions on implementing serious games in education and propose a customizable serious game framework applicable in the education of the new generation. Research results show that the most important feature of a serious game is its customizability. The fact that practitioners are able to manage different scenarios and upload their own content to a game seems to be a key to the increasingly widespread application of serious games in the classroom.

Keywords: education, gamification, game-based learning, serious games

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Authors: Arash Ghahraman, Gyula Bene

Abstract:

The object of this study is to investigate the effect of viscosity on the propagation of free-surface waves in an incompressible viscous fluid layer of arbitrary depth. While we provide a more detailed study of properties of linear surface waves, the description of fully nonlinear waves in terms of KdV-like (Korteweg-de Vries) equations is discussed. In the linear case, we find that in shallow enough fluids, no surface waves can propagate. Even in any thicker fluid layers, propagation of very short and very long waves is forbidden. When wave propagation is possible, only a single propagating mode exists for any given horizontal wave number. The numerical results show that there can be two types of non-propagating modes. One type is always present, and there exist still infinitely many of such modes at the same parameters. In contrast, there can be zero, one or two modes belonging to the other type. Another significant feature is that KdV-like equations. They describe propagating nonlinear viscous surface waves. Since viscosity gives rise to a new wavenumber that cannot be small at the same time as the original one, these equations may not exist. Nonetheless, we propose a reasonable nonlinear description in terms of 1+1 variate functions that make possible successive approximations.

Keywords: free surface wave, water waves, KdV equation, viscosity

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Authors: S. R. M. Krishna, R. Santosh Kumar, V. Kamakshi Prasad

Abstract:

Machine learning techniques are applied for the analysis of the impact of mental illness on the burden of disease. It is calculated using the disability-adjusted life year (DALY). DALYs for a disease is the sum of years of life lost due to premature mortality (YLLs) + No of years of healthy life lost due to disability (YLDs). The critical analysis is done based on the Data sources, machine learning techniques and feature extraction method. The reviewing is done based on major databases. The extracted data is examined using statistical analysis and machine learning techniques were applied. The prediction of the impact of mental illness on the population using machine learning techniques is an alternative approach to the old traditional strategies, which are time-consuming and may not be reliable. The approach makes it necessary for a comprehensive adoption, innovative algorithms, and an understanding of the limitations and challenges. The obtained prediction is a way of understanding the underlying impact of mental illness on the health of the people and it enables us to get a healthy life expectancy. The growing impact of mental illness and the challenges associated with the detection and treatment of mental disorders make it necessary for us to understand the complete effect of it on the majority of the population.

Keywords: ML, DAL, YLD, YLL

Procedia PDF Downloads 45