Search results for: named entity recognition natural

Authors: Silvia Boschetti, Jakub Binter, Robin Kopecký, Lenka PříPlatová, Jaroslav Flegr

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A strict dichotomy was present between religion and science, but recently, cognitive science focusses on the impact of supernatural beliefs on cognitive processes such as pattern recognition. It has been hypothesized that cognitive and perceptual processes have been under evolutionary pressures that ensured amplified perception of patterns, especially when in stressful and harsh conditions. The pattern detection in religious and non-religious individuals after induction of negative, anxious mood shall constitute a cornerstone of the general role of anxiety, cognitive bias, leading towards or against the by-product hypothesis, one of the main theories on the evolutionary studies of religion. The apophenia (tendencies to perceive connection and meaning on unrelated events) and perception of visual patterns (or pateidolia) are of utmost interest. To capture the impact of culture and upbringing, a comparative study of two European countries, the Czech Republic (low organized religion participation, high esoteric belief) and Italy (high organized religion participation, low esoteric belief), are currently in the data collection phase. Outcomes will be presented at the conference. A battery of standardized questionnaires followed by pattern recognition tasks (the patterns involve color, shape, and are of artificial and natural origin) using an experimental method involving the conditioning of (controlled, laboratory-induced) stress is taking place. We hypothesize to find a difference between organized religious belief and personal (esoteric) belief that will be alike in both of the cultural environments.

Keywords: culture, esoteric belief, pattern perception, religiosity

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Authors: Annop Jaewisorn

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This study explores the relationship between natural disasters and inequalities -both income and expenditure inequality- at a micro-level of Thailand as the first study of this nature for this country. The analysis uses a unique panel and remote-sensing dataset constructed for the purpose of this research. It contains provincial inequality measures and other economic and social indicators based on the Thailand Household Survey during the period between 1992 and 2019. Meanwhile, the data on natural disasters, which are remote-sensing data, are received from several official geophysical or meteorological databases. Employing a panel fixed effects, the results show that natural disasters significantly reduce household income and expenditure inequality as measured by the Gini index, implying that rich people in Thailand bear a higher cost of natural disasters when compared to poor people. The effect on income inequality is mainly driven by droughts, while the effect on expenditure inequality is mainly driven by flood events. The results are robust across heterogeneity of the samples, lagged effects, outliers, and an alternative inequality measure.

Keywords: inequality, natural disasters, remote-sensing data, Thailand

Procedia PDF Downloads 107

Authors: Megan Weisbart

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Background/Significance: The Intensive Care Unit (ICU) environment contributes to nurse burnout. Burnout costs include decreased employee compassion, missed workdays, worse patient outcomes, diminished job performance, high turnover, and higher organizational cost. Meaningful recognition, nurturing of interpersonal connections, and mindfulness-based interventions are associated with decreased burnout. The purpose of this quality improvement project was to decrease Neonatal ICU (NICU) nurse burnout using a Wellness Bundle that fosters meaningful recognition, interpersonal connections and includes mindfulness-based interventions. Methods: The Professional Quality of Life Scale Version 5 (ProQOL5) was used to measure burnout before Wellness Bundle implementation, after six months, and will be given yearly for three years. Meaningful recognition bundle items include Online submission and posting of staff shoutouts, recognition events, Nurses Week and Unit Practice Council member gifts, and an employee recognition program. Fostering of interpersonal connections bundle items include: Monthly staff games with prizes, social events, raffle fundraisers, unit blog, unit wellness basket, and a wellness resource sheet. Quick coherence techniques were implemented at staff meetings and huddles as a mindfulness-based intervention. Findings: The mean baseline burnout score of 14 NICU nurses was 20.71 (low burnout). The baseline range was 13-28, with 11 nurses experiencing low burnout, three nurses experiencing moderate burnout, and zero nurses experiencing high burnout. After six months of the Wellness Bundle Implementation, the mean burnout score of 39 NICU nurses was 22.28 (low burnout). The range was 14-31, with 22 nurses experiencing low burnout, 17 nurses experiencing moderate burnout, and zero nurses experiencing high burnout. Conclusion: A NICU Wellness Bundle that incorporated meaningful recognition, fostering of interpersonal connections, and mindfulness-based activities was implemented to improve work environments and decrease nurse burnout. Participation bias and low baseline response rate may have affected the reliability of the data and necessitate another comparative measure of burnout in one year.

Keywords: burnout, NICU, nurse, wellness

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Authors: Umair Rashid

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Normally softmax loss is used as the supervision signal in face recognition (FR) system, and it boosts the separability of features. In the last two years, a number of techniques have been proposed by reformulating the original softmax loss to enhance the discriminating power of Deep Convolutional Neural Networks (DCNNs) for FR system. To learn angularly discriminative features Cosine-Margin based softmax has been adjusted as monotonically decreasing angular function, that is the main challenge for angular based softmax. On that issue, we propose monotonically decreasing element for Cosine-Margin based softmax and also, we discussed the effect of different monotonically decreasing parameters on angular Margin softmax for FR system. We train the model on publicly available dataset CASIA- WebFace via our proposed monotonically decreasing parameters for cosine function and the tests on YouTube Faces (YTF, Labeled Face in the Wild (LFW), VGGFace1 and VGGFace2 attain the state-of-the-art performance.

Keywords: deep convolutional neural networks, cosine margin face recognition, softmax loss, monotonically decreasing parameter

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Authors: Subir Gupta, Subhas Ganguly

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In this paper, we demonstrate the new area of application of image processing in metallurgical images to develop the more opportunity for structure-property correlation based approaches of alloy design. The present exercise focuses on the development of image processing tools suitable for phrase segmentation, grain boundary detection and recognition of micro-constituents in SEM micrographs of ferrite and pearlite steels. A comprehensive data of micrographs have been experimentally developed encompassing the variation of ferrite and pearlite volume fractions and taking images at different magnification (500X, 1000X, 15000X, 2000X, 3000X and 5000X) under scanning electron microscope. The variation in the volume fraction has been achieved using four different plain carbon steel containing 0.1, 0.22, 0.35 and 0.48 wt% C heat treated under annealing and normalizing treatments. The obtained data pool of micrographs arbitrarily divided into two parts to developing training and testing sets of micrographs. The statistical recognition features for ferrite and pearlite constituents have been developed by learning from training set of micrographs. The obtained features for microstructure pattern recognition are applied to test set of micrographs. The analysis of the result shows that the developed strategy can successfully detect the micro constitutes across the wide range of magnification and variation of volume fractions of the constituents in the structure with an accuracy of about +/- 5%.

Keywords: SEM micrograph, metallurgical image processing, ferrite pearlite steel, microstructure

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Authors: Ratna Sharma, Kaveri Dutta

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Assam (India), the gate way to the Northeast India is mainly known for its exquisite silks, the art and craft. The state has a rich collection of traditional jewellery which is unique and exclusive to the state. These jewelleries hold a special place in the heart of the Assamese women. Similarly handloom industry of Assam is basically silk oriented. Among the wild silk, Eri silk fabric has remained as “the poor man’s silk” but it is closely attached to the assamese society, dress for it's warm quality. In view of the changing market trends, fashion and consumer demands, Silk is emerging as a fashion fabric both in India and abroad. In case of Eri silk fabric it has limited use in clothing and accessories. Hence the restructured and redesigned traditional jewellery motifs of Assam (India) over Eri silk products will have greater potential in reviving the decline of art, generate revenue, self employment towards craftsmen and also recognition of the art. The information incorporated in the paper is primary and the data have been collected by purposive sampling method. This work of art was expressed on Eri silk fabric in the form of traditional hand embroidery as it is closely connected with the era of the individual in history of mankind and reflects the personal expression of an entity. For this study selected traditional motifs of Assamese ornaments was used. Some of the popular traditional Assamese jewellery include earrings with exquisite Lokaparo, Keru, Thuriya, Jangphai, etc. An array of necklaces including Golpata, Satsori, Jon biri, Bena, Gejera, Dhol biri, Doog doogi, Biri Moni, Mukuta Moni, Poalmoni, Silikha Moni and Magardana and diversified rings including Senpata, Horinsakua, Jethinejia, bakharpata and others. Selected two motifs each from necklace, earring and finger ring designs. Selected motifs were further developed into 3 categories- the border, the main motif and all over butta followed by placement of developed patterns on products. Products developed were stoles, scarf’s, purses, brooch pins, skirts for women and ties, handkerchief, jackets for men. The developed products were surveyed by selected respondents. From the present study it can be observed that the embellished traditional jewellery motifs resulted in fresh and colourful pattern on developed Eri silk products. Moreover the motifs which were gradually fading among the community itself showed a very good recognition towards art. The embroidered Eri silk fabric also created a huge change in a positive way among craftsman.

Keywords: Art and craft of Assam, eri silk, hand embroidery, traditional Assamese jewellery motifs

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Authors: Samaneh Khalili

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Natural law theory, in moral philosophy, refers to a system of unchanging values held to be mutual to all humans and can be discovered through reason. The natural law theory is commonly associated with western Philosophers. In contrast, discussions on notions of natural law in Islamic intellectual history were relatively rare. This paper aims to show that the moral theory developed by the Mu'tazilite thinkers can be classified in the ideas of natural law. In doing so, this study will demonstrate that the objective and unchanging values, according to Mu'tazilite theologians, provide the guidelines for assessing the Islamic law rules in the field of human coexistence. The focus of the paper lies on ʿAbd al-Ğabbār, who was the most influential thinker in the late epoch of the Muʿtazila. Although ʿAbd al-Ǧabbār did not leave a text with a systematic discussion of natural law, his teaching of nature, human reason, and the moral values of actions are all scattered throughout his work -'al-Muġnī fī abwāb at-tawḥīd wa-l-'adl'. It is necessary to focus on ʿAbd al-Ǧabbār's theories on reason, nature, and ethics since natural law revolves around the basic concepts of nature, reason, and moral value. While analyzing the concept of the Nature, it will attempt to answer how he explains the world's physical structure and God's relationship to natural events. Moreover, from ʿAbd al-Ǧabbār's point of view, is nature a self-determined system that follows its inner principle in every kind of change, or is nature guided by an external power? Does causality govern natural events? About the concept of reason, an attempt is made to examine how human reason, according to ʿAbd al-Ǧabbār, conceives moral attributes. Finally, the Autor will discuss the concepts of objective values and the place of rights and duties derived from Islamic law in ʿAbd al-Ǧabbār's thought.

Keywords: Islamic law, Mu'tazilite theology, natural law in Islamic theology, objective and unchanging values.

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Authors: Mohammadreza Sedighi, Mohammad Said Saidi, Hesamoddin Salarian

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A numerical study has been performed to investigate the effect of using different turbulent models on natural convection flow field and temperature distributions in partially heated square cavity compare to benchmark. The temperature of the right vertical wall is lower than that of heater while other walls are insulated. The commercial CFD codes are used to model. Standard k-w model provided good agreement with the experimental data.

Keywords: Buoyancy, Cavity, CFD, Heat Transfer, Natural Convection, Turbulence

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Authors: John Benedict Bernardo

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Crowdsourcing is a way of collecting information provided by the volunteers. This crowdsourced information has the capacity to increase the people’s situational awareness in times of disasters. The research reflected in this paper strives to demonstrate the benefits of crowdsourcing during natural disasters and the ways of utilizing it for disaster response. Shared information regarding natural disasters from social media is often scattered as the inputs from these media are uncategorized. For this reason, the study aims to equip the citizens a medium that is solely intended for sharing and/or obtaining natural disaster-related information. Ergo, an android application was developed to gather and publicize this volunteered information. The capability of crowdsourcing and the effectiveness of the application were evaluated and the result shows overwhelming agreement that this study is indeed efficient in increasing the awareness and response initiatives of the citizens during natural disasters.

Keywords: crowdsourcing, natural disasters, mobile application, social media

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Authors: Yishu Gong, Liangliang Yang, Jianyu Zhang, Zhengyu Chen, Sihong He, Xusheng Zhang, Wei Zhang

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Alzheimer’s disease (AD) is a progressive neurodegenerative disorder that affects millions of people worldwide and is characterized by cognitive decline and behavioral changes. People living with Alzheimer’s disease often find it hard to complete routine tasks. However, there are limited objective assessments that aim to quantify the difficulty of certain tasks for AD patients compared to non-AD people. In this study, we propose to use speech emotion recognition (SER), especially the frustration level, as a potential biomarker for quantifying the difficulty patients experience when describing a picture. We build an SER model using data from the IEMOCAP dataset and apply the model to the DementiaBank data to detect the AD/non-AD group difference and perform longitudinal analysis to track the AD disease progression. Our results show that the frustration level detected from the SER model can possibly be used as a cost-effective tool for objective tracking of AD progression in addition to the Mini-Mental State Examination (MMSE) score.

Keywords: Alzheimer’s disease, speech emotion recognition, longitudinal biomarker, machine learning

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Authors: Juhi Pandya, Elekes Zsuzsanna

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Health is related to every aspect of human being. Even a quintal change leads to ill-health of an individual. Gender plays an eminent role in determining an individual health exposure. Political implications on health have implicit effects on the individual, societal and economical. The inclusion of gender perspective into policies have plunged enormous attention globally, nationally and locally to detract inequalities and achieve economic growth. Simultaneously, there is an initiation of policies with gender perspective which are named differently but hold similar meaning or objective. They are named gender mainstreaming policies or gender sensitization policies. Gender budgeting acts as a tool for the application of gender mainstreaming policies. It incorporates gender perspective into the budgetary process by restricting the revenues and expenditures at all level of the budget. The current study takes into account the analysis of Gender Budgeting reports in terms of healthcare from the 2014-16 year of Gujarat State, India. The expenditures and literature under the heading of gender budgeting reports named “Health and Family Welfare Department” are discussed in the paper. The data analytics is done with the help of reports published by the Gujarat government on Gender Budgeting. The results discuss upon the expenditure and initiation of new policies as a roadmap for the promotion of gender equality from the path of gender budgeting. It states with the escalation of the budgetary numbers for the health expenditure. Additionally, the paper raises the questions on the hypothetical loopholes pertaining to the gender budgeting in Gujarat. The budget reports do not show a specify explanation to the expenditure use of budget for the schemes mentioned in healthcare. It also does not clarify that how many beneficiaries are benefited through gender budget. The explanation just provides an overlook of theory for healthcare Schemes/Yojana or Abhiyan.

Keywords: gender, gender budgeting, gender equality, healthcare

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Authors: Jeansou Moun

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This study argues that constructivism and structuralism, which have been the two important schools of mathematical philosophy since the mid-19th century, can and should be synthesized into structure-constructivism. In fact, the philosophy of mathematics is divided into more than ten schools depending on the point of view. However, the biggest trend is Platonism which claims that mathematical objects are "abstract entities" that exists independently of the human mind and material objects. Its opposite is constructivism. According to the latter, mathematical objects are products of the construction of the human mind. However, whether the basis of the construction is a logical device, a symbolic system, or an empirical perception, it is subdivided into logicism, formalism, and intuitionism. However, these three schools themselves are further subdivided into various variants, and among them, structuralism, which emerged in the mid-20th century, is receiving the most attention. On the other hand, structuralism which emphasizes structure instead of individual objects, is divided into non-eliminative structuralism, which supports the a priori of structure, and non-eliminative structuralism, which rejects any abstract entity. In this context, it is believed that the structure itself is not an a priori entity but a result of the construction of the cognitive subject and that no object has ever been given to us in its full meaning from the outset. In other words, concepts are progressively structured through a dialectical cycle between sensory perception, imagination (abstraction), concepts, judgments, and reasoning. Symbols are needed for formal operation. However, without concrete manipulation, the formal operation cannot have any meaning. However, when formal structurization is achieved, the reality (object) itself is also newly structured. This is the "structure-constructivism".

Keywords: philosophy of mathematics, platonism, logicism, formalism, constructivism, structuralism, structure-constructivism

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Authors: Bo-Gaun Chen, Chiung-Hui Huang, Mei-Ching Chiang, Kuo-Hsing Lee, Chia-Chen Ho, Chin-Ping Huang, Chin-Heng Tien

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It is known that the natural dyeing of cloth results moderate color, but with poor color fastness. This study points out the correlation between the macroscopic color fastness of natural dye to the cotton fiber and the microscopic binding energy of dye molecule to the cellulose. With the additive metallic mordant, the new-formed coordination bond bridges the dye to the fiber surface and thus affects the color fastness as well as the color appearance. The density functional theory (DFT) calculation is therefore used to explore the most possible mechanism during the dyeing process. Finally, the experimental results reflect the strong effect of three different metal ions on the natural dyeing clothes.

Keywords: binding energy, color fastness, density functional theory (DFT), natural dyeing, metallic mordant

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Authors: Bushra

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This paper explores the historical significance, ecological benefits, and contemporary applications of natural dyes in textile dyeing, aiming to provide a comprehensive overview of their potential to contribute to a sustainable fashion industry while minimizing ecological footprints. This research explores the potential of natural dyes as a sustainable alternative to synthetic dyes in the textile industry, examining their historical context, sources, and environmental benefits. Natural dyes come from plants, animals, and minerals, including roots, leaves, bark, fruits, flowers, insects, and metal salts, used as mordants to fix dyes to fabrics. Natural dyeing involves extraction, mordanting, and dyeing techniques. Optimizing these processes can enhance the performance of natural dyes, making them viable for contemporary textile applications based on experimental research. Natural dyes offer eco-friendly benefits like biodegradability, non-toxicity, and resource renewables, reducing pollution, promoting biodiversity, and reducing reliance on petrochemicals. Natural dyes offer benefits but face challenges in color consistency, scalability, and performance, requiring industrial production to meet modern consumer standards for durability and colorfastness. Contemporary initiatives in the textile industry include fashion brands like Eileen Fisher and Patagonia incorporating natural dyes, artisans like India Flint's Botanical Alchemy promoting traditional dyeing techniques, and research projects like the European Union's Horizon 2020 program. Natural dyes offer a sustainable textile industry solution, reducing environmental impact and promoting harmony with nature. Research and innovation are paving the way for widespread adoption, transforming textile dyeing.

Keywords: historical significance, textile industry, natural dyes, sustainability

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Authors: Albatool Al Abdulwahid, Bayan Shakally, Mariam Mohamed, Wed Almokri

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Artificial intelligence has infiltrated every part of our life and every field we can think of. With technical developments, artificial intelligence applications are becoming more prevalent. We chose ELSA speak because it is a magnificent example of Artificial intelligent applications, ELSA speak is a smartphone application that is free to download on both IOS and Android smartphones. ELSA speak utilizes artificial intelligence to help non-native English speakers pronounce words and phrases similar to a native speaker, as well as enhance their English skills. It employs speech-recognition technology that aids the application to excel the pronunciation of its users. This remarkable feature distinguishes ELSA from other voice recognition algorithms and increase the efficiency of the application. This study focused on evaluating ELSA speak application, by testing the degree of effectiveness based on survey questions. The results of the questionnaire were variable. The generality of the participants strongly agreed that ELSA has helped them enhance their pronunciation skills. However, a few participants were unconfident about the application’s ability to assist them in their learning journey.

Keywords: ELSA speak application, artificial intelligence, speech-recognition technology, language learning, english pronunciation

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Authors: Kothuri Sriraman, Mattupalli Komal Teja

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In this paper, a novel algorithm is proposed for the recognition of hulls in a hand written images that might be irregular or digit or character shape. Identification of objects and internal objects is quite difficult to extract, when the structure of the image is having bulk of clusters. The estimation results are easily obtained while going through identifying the sub-regional objects by using the SASK algorithm. Focusing mainly to recognize the number of internal objects exist in a given image, so as it is shadow-free and error-free. The hard clustering and density clustering process of obtained image rough set is used to recognize the differentiated internal objects, if any. In order to find out the internal hull regions it involves three steps pre-processing, Boundary Extraction and finally, apply the Hull Detection system. By detecting the sub-regional hulls it can increase the machine learning capability in detection of characters and it can also be extend in order to get the hull recognition even in irregular shape objects like wise black holes in the space exploration with their intensities. Layered hulls are those having the structured layers inside while it is useful in the Military Services and Traffic to identify the number of vehicles or persons. This proposed SASK algorithm is helpful in making of that kind of identifying the regions and can useful in undergo for the decision process (to clear the traffic, to identify the number of persons in the opponent’s in the war).

Keywords: chain code, Hull regions, Hough transform, Hull recognition, Layered Outline Extraction, SASK algorithm

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Authors: António J. R. Neves, Rui Garcia, Paulo Dias, Alina Trifan

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With the aging of the world population and the continuous growth in technology, service robots are more and more explored nowadays as alternatives to healthcare givers or personal assistants for the elderly or disabled people. Any service robot should be capable of interacting with the human companion, receive commands, navigate through the environment, either known or unknown, and recognize objects. This paper proposes an approach for object recognition based on the use of depth information and color images for a service robot. We present a study on two of the most used methods for object detection, where 3D data is used to detect the position of objects to classify that are found on horizontal surfaces. Since most of the objects of interest accessible for service robots are on these surfaces, the proposed 3D segmentation reduces the processing time and simplifies the scene for object recognition. The first approach for object recognition is based on color histograms, while the second is based on the use of the SIFT and SURF feature descriptors. We present comparative experimental results obtained with a real service robot.

Keywords: object detection, feature, descriptors, SIFT, SURF, depth images, service robots

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Authors: Vishwanath Pethri Kamath, Jayantha Gowda Sarapanahalli, Vishal Mishra, Siddhesh Balwant Bandgar

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Recognition of emotional information is essential in any form of communication. Growing HCI (Human-Computer Interaction) in recent times indicates the importance of understanding of emotions expressed and becomes crucial for improving the system or the interaction itself. In this research work, textual data for emotion recognition is used. The text being the least expressive amongst the multimodal resources poses various challenges such as contextual information and also sequential nature of the language construction. In this research work, the proposal is made for a neural architecture to resolve not less than 8 emotions from textual data sources derived from multiple datasets using google pre-trained word2vec word embeddings and a Multi-head attention-based bidirectional LSTM model with a one-vs-all Multi-Level Classification. The emotions targeted in this research are Anger, Disgust, Fear, Guilt, Joy, Sadness, Shame, and Surprise. Textual data from multiple datasets were used for this research work such as ISEAR, Go Emotions, Affect datasets for creating the emotions’ dataset. Data samples overlap or conflicts were considered with careful preprocessing. Our results show a significant improvement with the modeling architecture and as good as 10 points improvement in recognizing some emotions.

Keywords: text emotion recognition, bidirectional LSTM, multi-head attention, multi-level classification, google word2vec word embeddings

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Authors: Aref Aasi, Sadegh Mehdi Aghaei, Balaji Panchapakesan

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This work aims to evaluate the free and forced vibration of a beam with two end joints subjected to a concentrated moving mass and a load using the Euler-Bernoulli method. The natural frequency is calculated for different locations of the concentrated mass and load on the beam. The analytical results are verified by the experimental data. The variations of natural frequency as a function of the location of the mass, the effect of the forced frequency on the vibrational amplitude, and the displacement amplitude versus time are investigated. It is discovered that as the concentrated mass moves toward the center of the beam, the natural frequency of the beam and the relative error between experimental and analytical data decreases. There is a close resemblance between analytical data and experimental observations.

Keywords: Euler-Bernoulli beam, natural frequency, forced vibration, experimental setup

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Authors: Mohammed S. Al-Rawi, J. Bastos, J. Rodriguez

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Object detection and object recognition are essential components of every computer vision system. Despite the high computational complexity and other problems related to numerical stability and accuracy, Zernike moments of 2D images (ZMs) have shown resilience when used in object recognition and have been used in various image analysis applications. In this work, we propose a novel method for computing ZMs via Fast Fourier Transform (FFT). Notably, this is the first algorithm that can generate ZMs up to extremely high orders accurately, e.g., it can be used to generate ZMs for orders up to 1000 or even higher. Furthermore, the proposed method is also simpler and faster than the other methods due to the availability of FFT software and/or hardware. The accuracies and numerical stability of ZMs computed via FFT have been confirmed using the orthogonality property. We also introduce normalizing ZMs with Neumann factor when the image is embedded in a larger grid, and color image reconstruction based on RGB normalization of the reconstructed images. Astonishingly, higher-order image reconstruction experiments show that the proposed methods are superior, both quantitatively and subjectively, compared to the q-recursive method.

Keywords: Chebyshev polynomial, fourier transform, fast algorithms, image recognition, pseudo Zernike moments, Zernike moments

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Authors: Alaa Sarhan, Rania Abd El Gelil, Hana Awad

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Through the last decades, the impact of thermal comfort on the working performance of users and occupants of an indoor space has been a concern. Research papers concluded that natural ventilation quality directly impacts the levels of thermal comfort. Natural ventilation must be put into account during the design process in order to improve the inhabitant's efficiency and productivity. One example of daily long-term occupancy spaces is educational facilities. Many individuals spend long times receiving a considerable amount of knowledge, and it takes additional time to apply this knowledge. Thus, this research is concerned with user's level of thermal comfort in design studios of educational facilities. The natural ventilation quality in spaces is affected by a number of parameters including orientation, opening design, and many other factors. This research aims to investigate the conscious manipulation of the physical parameters of the spaces and its impact on natural ventilation performance which subsequently affects thermal comfort of users. The current research uses inductive and deductive methods to define natural ventilation design considerations, which are used in a field study in a studio in the university building in Alexandria (AAST) to evaluate natural ventilation performance through analyzing and comparing the current case to the developed framework and conducting computational fluid dynamics simulation. Results have proved that natural ventilation performance is successful by only 50% of the natural ventilation design framework; these results are supported by CFD simulation.

Keywords: educational buildings, natural ventilation, , mediterranean climate, thermal comfort

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Authors: Valentina Zhang

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While facial expression is a complex and individualized behavior, all facial emotion recognition (FER) systems known to us rely on a single facial representation and are trained on universal data. We conjecture that: (i) different facial representations can provide different, sometimes complementing views of emotions; (ii) when employed collectively in a discussion group setting, they enable more accurate emotion reading which is highly desirable in autism care and other applications context sensitive to errors. In this paper, we first study FER using pixel-based DL vs semantics-based DL in the context of deepfake videos. Our experiment indicates that while the semantics-trained model performs better with articulated facial feature changes, the pixel-trained model outperforms on subtle or rare facial expressions. Armed with these findings, we have constructed an adaptive FER system learning from both types of models for dyadic or small interacting groups and further leveraging the synthesized group emotions as the ground truth for individualized FER training. Using a collection of group conversation videos, we demonstrate that FER accuracy and personalization can benefit from such an approach.

Keywords: neurodivergence care, facial emotion recognition, deep learning, ground truth for supervised learning

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Authors: B. Afsharipoor, E. Nazemi

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Artificial neural networks (ANNs) are powerful tool for prediction which can be trained based on a set of examples and thus, it would be useful for nonlinear image processing. The present paper reviews several paper regarding applications of ANN in image processing to shed the light on advantage and disadvantage of ANNs in this field. Different steps in the image processing chain including pre-processing, enhancement, segmentation, object recognition, image understanding and optimization by using ANN are summarized. Furthermore, results on using multi artificial neural networks are presented.

Keywords: neural networks, image processing, segmentation, object recognition, image understanding, optimization, MANN

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Authors: Anahita Aris

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Geometry always plays a key role in natural structures, which can be a source of inspiration for architects and urban designers to create spaces. By understanding formative principles in nature, a variety of options can be provided that lead to freedom of formation. The main purpose of this paper is to analyze the geometrical order found in pomegranate to find formative principles explaining its complex structure. The point is how spherical arils of pomegranate pressed together inside the fruit and filled the space as they expand in the growing process, which made a self-organized system leads to the formation of each of the arils are unique in size, topology and shape. The main challenge of this paper would be using advanced architectural modeling techniques to discover these principles.

Keywords: advanced modeling techniques, architectural modeling, computational design, the geometry of natural formation, geometrical analysis, the natural order of pomegranate, voronoi diagrams

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Authors: Rubin Dan, Xingcai Wang, Ziyang Chen

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A chaotic time series noise reduction method based on the fusion of the local projection method, wavelet transform, and particle swarm algorithm (referred to as the LW-PSO method) is proposed to address the problem of false recognition due to noise in the recognition process of chaotic time series containing noise. The method first uses phase space reconstruction to recover the original dynamical system characteristics and removes the noise subspace by selecting the neighborhood radius; then it uses wavelet transform to remove D1-D3 high-frequency components to maximize the retention of signal information while least-squares optimization is performed by the particle swarm algorithm. The Lorenz system containing 30% Gaussian white noise is simulated and verified, and the phase space, SNR value, RMSE value, and K value of the 0-1 test method before and after noise reduction of the Schreiber method, local projection method, wavelet transform method, and LW-PSO method are compared and analyzed, which proves that the LW-PSO method has a better noise reduction effect compared with the other three common methods. The method is also applied to the classical system to evaluate the noise reduction effect of the four methods and the original system identification effect, which further verifies the superiority of the LW-PSO method. Finally, it is applied to the Chengdu rainfall chaotic sequence for research, and the results prove that the LW-PSO method can effectively reduce the noise and improve the chaos recognition rate.

Keywords: Schreiber noise reduction, wavelet transform, particle swarm optimization, 0-1 test method, chaotic sequence denoising

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Authors: Yeliz Sarı Nayim, B. N. Nayim

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Vertical natural gardens encountered in urban ecosystems are important elements contributing to urban ecology by raising the quality of urban life. This research covers the investigation of the semi-natural plant walls of Bartın city which is located on the western Black Sea coast of Turkey. Landscape analysis and evaluation as a result of land and office work have resulted in vertical garden ecosystems that have been processed in the urban habitat map, mostly in natural stone walls, wooden garden fences, garden entrance doors, historical buildings and building walls. Structural surfaces on old building facades, especially with abandoned or still in use with natural stone walls, have been found to have many natural vertical gardens over time. Parietaria judaica, Cymbalaria longipes and Hedera helix species were dominant, and other types of content were recorded, providing information on the current biotope potential, human activities and effects on them. It has been emphasized that the described vertical gardens together with the species they contain should be protected in terms of Bartin urban ecology and biodiversity. It has been stated that sustainable urban planning, design and management should be considered as a compensation for open and green area losses.

Keywords: semi-natural vertical gardens, urban ecology, sustainable urban planning and design, Bartın

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Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi

Abstract:

In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.

Keywords: Iot, activity recognition, automatic classification, unconstrained environment

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Authors: Reza Shakoori

Abstract:

This paper presents a structural correction of Arabic and Persian strokes using manipulation of their chain codes in order to improve the rate and performance of Persian and Arabic handwritten word recognition systems. It collects pure and effective features to represent a character with one consolidated feature vector and reduces variations in order to decrease the number of training samples and increase the chance of successful classification. Our results also show that how the proposed approaches can simplify classification and consequently recognition by reducing variations and possible noises on the chain code by keeping orientation of characters and their backbone structures.

Keywords: Arabic, chain code normalization, OCR systems, image processing

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Authors: Jamshaid ul Rahman, Akhter Ali, Adnan Manzoor

Abstract:

Learning-based systems have received increasing interest in recent years; recognition structures, including end-to-end speak recognition, are one of the hot topics in this area. A famous work on end-to-end speaker verification by using Angular Softmax Loss gained significant importance and is considered useful to directly trains a discriminative model instead of the traditional adopted i-vector approach. The margin-based strategy in angular softmax is beneficial to learn discriminative speaker embeddings where the random selection of margin values is a big issue in additive angular margin and multiplicative angular margin. As a better solution in this matter, we present an alternative approach by introducing a bit similar form of an additive parameter that was originally introduced for face recognition, and it has a capacity to adjust automatically with the corresponding margin values and is applicable to learn more discriminative features than the Softmax. Experiments are conducted on the part of Fisher dataset, where it observed that the additive parameter with angular softmax to train the front-end and probabilistic linear discriminant analysis (PLDA) in the back-end boosts the performance of the structure.

Keywords: additive parameter, angular softmax, speaker verification, PLDA

Procedia PDF Downloads 82

Authors: Engin Eroğlu, Oktay Yıldız, Necmi Aksoy, Akif Keten, Mehmet Kıvanç Ak, Şeref Keskin, Elif Atmaca, Sertaç Kaya

Abstract:

Nowadays, green spaces in urban areas are under threat and decreasing their percentages in the urban areas because of increasing population, urbanization, migration, and some cultural changes in quality. An important element of the natural landscape water and water-related natural ecosystems are exposed to corruption due to these pressures. A landscape has owned many different types of elements or units, a more dominant structure than other landscapes as good or bad perceptible extent different direction and variable reveals a unique structure and character of the landscape. Whereas landscapes deal with two main groups as urban and rural according to their location on the world, especially intersection areas of urban and rural named semi-urban or semi-rural present variety landscape features. The main components of the landscape are defined as patch-matrix-corridor. The corridors include quite various vegetation types such as riparian, wetland and the others. In urban areas, natural water corridors are an important elements of the diversity of the riparian vegetation cover. In particular, water corridors attract attention with a natural diversity and lack of fragmentation, degradation and artificial results. Thanks to these features, without a doubt, water corridors are the important component of all cities in the world. These corridors not only divide the city into two separate sides, but also assured the ecological connectivity between the two sides of the city. The main objective of this study is to determine the vegetation and habitat features of urban stream corridor according to environmental interactions. Within this context, this study will be realized that 'Asar Suyu' is an important component of the city of Düzce. Moreover, the riparian zone touched contiguous area borders of the city and overlaid the urban development limits of the city, determining of characteristics of the corridor will be carried out as floristic and habitat analysis. Consequently, vegetation structure and habitat features which play an important role between riparian zone vegetation covers and environmental interaction will be determined. This study includes first results of The Scientific and Technological Research Council of Turkey (TUBITAK-116O596; 'Determining of Landscape Character of Urban Water Corridors as Visual and Ecological; A Case Study of Asar Suyu in Duzce').

Keywords: corridor, Duzce, landscape ecology, riparian vegetation

Procedia PDF Downloads 326