Search results for: Character Recognition (OCR)

Authors: Elena Kokkoni, Prasanna Kannappan, Ashkan Zehfroosh, Effrosyni Mavroudi, Kristina Strother-Garcia, James C. Galloway, Jeffrey Heinz, Rene Vidal, Herbert G. Tanner

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Early immobility affects the motor, cognitive, and social development. Current pediatric rehabilitation lacks the technology that will provide the dosage needed to promote mobility for young children at risk. The addition of socially assistive robots in early interventions may help increase the mobility dosage. The aim of this study is to examine the feasibility of an early intervention paradigm where non-walking infants experience independent mobility while socially interacting with robots. A dynamic environment is developed where both the child and the robot interact and learn from each other. The environment involves: 1) a range of physical activities that are goal-oriented, age-appropriate, and ability-matched for the child to perform, 2) the automatic functions that perceive the child’s actions through novel activity recognition algorithms, and decide appropriate actions for the robot, and 3) a networked visual data acquisition system that enables real-time assessment and provides the means to connect child behavior with robot decision-making in real-time. The environment was tested by bringing a two-year old boy with Down syndrome for eight sessions. The child presented delays throughout his motor development with the current being on the acquisition of walking. During the sessions, the child performed physical activities that required complex motor actions (e.g. climbing an inclined platform and/or staircase). During these activities, a (wheeled or humanoid) robot was either performing the action or was at its end point 'signaling' for interaction. From these sessions, information was gathered to develop algorithms to automate the perception of activities which the robot bases its actions on. A Markov Decision Process (MDP) is used to model the intentions of the child. A 'smoothing' technique is used to help identify the model’s parameters which are a critical step when dealing with small data sets such in this paradigm. The child engaged in all activities and socially interacted with the robot across sessions. With time, the child’s mobility was increased, and the frequency and duration of complex and independent motor actions were also increased (e.g. taking independent steps). Simulation results on the combination of the MDP and smoothing support the use of this model in human-robot interaction. Smoothing facilitates learning MDP parameters from small data sets. This paradigm is feasible and provides an insight on how social interaction may elicit mobility actions suggesting a new early intervention paradigm for very young children with motor disabilities. Acknowledgment: This work has been supported by NIH under grant #5R01HD87133.

Keywords: activity recognition, human-robot interaction, machine learning, pediatric rehabilitation

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Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Min-Ah Woo, Min-Cheol Lim, Hyun-Joo Chang, Sung-Wook Choi

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We developed a paper-based colorimetric sensor utilizing magnetic nanoparticles conjugated with aptamers (MNP-Apts) against E. coli O157:H7. The MNP-Apts were applied to a test sample solution containing the target cells, and the solution was simply dropped onto PVDF (polyvinylidene difluoride) membrane. The membrane moves the sample radially to form the sample spots of different compounds as concentric rings, thus the MNP-Apts on the membrane enabled specific recognition of the target cells through a color ring generation by MNP-promoted colorimetric reaction of TMB (3,3',5,5'-tetramethylbenzidine) and H₂O₂. This method could be applied to rapidly and visually detect various bacterial pathogens in less than 1 h without cell culturing.

Keywords: aptamer, colorimetric sensor, E. coli O157:H7, magnetic nanoparticle, polyvinylidene difluoride

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Authors: Nguyen Van Loi, Le Thanh Son, Tran Trung Kien

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The paper deals with the problem of the formation of range profiles (RPs) for an X-band coastal surveillance radar. Two popular methods, the difference operator method, and the window-based method, are reviewed and analyzed via two tests with different datasets. The test results show that although the original window-based method achieves a better performance than the difference operator method, it has three main drawbacks that are the use of 3 or 4 peaks of an RP for creating the windows, the extension of the window size using the power sum of three adjacent cells in the left and the right sides of the windows and the same threshold applied for all types of vessels to finish the formation process of RPs. These drawbacks lead to inaccurate RPs due to the low signal-to-clutter ratio. Therefore, some suggestions are proposed to improve the original window-based method.

Keywords: range profile, difference operator method, window-based method, automatic target recognition

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Authors: Fátima R. Zan, Daniela C. Guimarães, Rosângela O. Soares, Suzana L. Russo

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The wine until it reaches the consumer has a long way to go, from planting the wine to the bottling and the placing on the market, bringing many years of experimentation, and through several generations to have recognition for quality and excellence. The winemaking grew dramatically and are today many brands, including the associated locations, demonstrating their origin and cultural order that is associated with their production. The production, circulation and marketing of wines and products of grape and wine in Brazil is regulated by Law 7.678/88, amended by Law 10970/04, and adjusting the legislation to Regulation Wine Mercosur. This study was based on a retrospective study, and aimed to identify and characterize the modalities of industrial property used in wine production in Brazil. The wineries were selected from the 2014 ranking list, drawn up by the World Association of Journalists and Writers of Wines and Spirits (WAWWJ). The results show that the registration with INPI, regarding Patents, Trademarks, Industrial Designs and Geographical Indications, is not used by the wineries analyzed.

Keywords: counterfeiting, industrial property, protection, wine production

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Authors: Xiaowen Yang

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Violence has been gaining an increasing presence among contemporary Chinese writers, yet scholarship on the representation of violence in contemporary Chinese literature is disappointingly sparse. The violence which took place in the Cultural Revolution attracted the most attention in previous literary work and academic studies. Known as a writer of the quotidian, chi Zijian is one of China’s most prominent and prolific writers. It is noticeable that in her depiction of ordinary people, an overwhelming presence of violence features which embodies one of the on-going characteristics of contemporary Chinese literature. The violence present in her texts are not about graphic and minute depiction of violent acts, But rather about the character’s complex interrelation with violence. Is it an obsession with extreme figures and events to create powerful tensions within the texts? Or is it a necessary tool to achieve criticism about social realities? This paper argues that based on her grassroots writing philosophy which is characterized by her long-standing concern about ordinary and even marginal people, it is necessary for her texts to involve characters related to violence. This endows her texts with great potential for reading their social and political implications. This paper also contends that though a shocking effect could make the criticism of social realities more powerful, an over-reliance on the excessive exterior representation of violence inhibits the writer’s literary innovation.

Keywords: Chi Zijian, contemporary Chinese literature, Violence, grassroots writing philosophy

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Authors: Dinesh Kumar Maurya, Sapan Mohan Saini

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A theoretical formalism to calculate the structural, electronic and optical properties of orthorhombic crystals from first principle calculations is described. This is applied first time to new YNi4Si-type DyNi4Si compound. Calculations are performed using full-potential augmented plane wave (FPLAPW) method in the framework of density functional theory (DFT). The Coulomb corrected local-spin density approximation (LSDA+U) in the self-interaction correction (SIC) has been used for exchange-correlation potential. Our optimized results of lattice parameters show good agreement to the previously reported experimental study. Analysis of the calculated band structure of DyNi4Si compound demonstrates their metallic character. We found Ni-3d states mainly contribute to density of states from -5.0 eV to the Fermi level while the Dy-f states peak stands tall in comparison to the small contributions made by the Ni-d and R-d states above Fermi level, which is consistent with experiment, in DNi4Si compound. Our calculated optical conductivity compares well with the experimental data and the results are analyzed in the light of band-to-band transitions. We also report the frequency-dependent refractive index n(ω) and the extinction coefficient k(ω) of the compound.

Keywords: band structure, density of states, optical properties, LSDA+U approximation, YNi4Si- type DyNi4Si compound

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Authors: Michele L. Dormaier

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The purpose of the research was to design costumes based on historic colors used by artists during the seventeenth century. The researcher investigated European art, primarily paintings and portraiture, as well as the color palettes used by the artists. The methodology examined the artists, their work, the color palettes used in their work, and the practices of color usage within their palettes. By examining portraits of historic figures, as well as paintings of ordinary scenes, subjects, and people, further information about color palettes was revealed. Related to the color palettes, was the use of ‘broken colors’ which was a relatively new practice, dating from the sixteenth century. The color palettes used by the artists of the seventeenth century had their limitations due to available pigments. With an examination of not only their artwork, and with a closer look at their palettes, the researcher discovered the exciting choices they made, despite those restrictions. The research was also initiated with the historical elements of the era’s clothing, as well as that of available materials and dyes. These dyes were also limited in much the same manner as the pigments which the artist had at their disposal. The color palettes of the paintings have much to tell us about the lives, status, conditions, and relationships from the past. From this research, informed decisions regarding color choices for a production on a contemporary stage of a period piece could then be made. The designer’s choices were a historic gesture to the colors which might have been worn by the character’s real-life counterparts of the era.

Keywords: broken color palette, costume color research, costume design, costume history, seventeenth century color palette, sixteenth century color palette

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Authors: Chinmayee Nanda

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In this modern era, India is still chained up with the idea of ‘Heteronormativity’. As a result, homonormativity, transgressions, preconceived notions, and bigotry add to many raised eyebrows, the majority being the norm and overpowering the voices of the minority. In this country an undeniable space is the need of the hour to identify those unheard voices. Media can be considered as the most powerful space for the same. This paper aims to examine the representation as well as transition (if any) of the varied figments of the imagination and alternative facts relating to the LGBTQ+ community in celluloid in Hindi. This paper will also explore the visibility of the queer aspirations through this media. The portrayal of the LGBTQ community as the ‘other’ and ‘not normal’ is a matter of concern about any individual’s sexuality. The years 2014 and 2018 turned out to be remarkable in the Indian Legal System pertaining to the recognition of the ‘Third Gender’ and ‘Decriminalization of Homosexuality,’ respectively. In relation to that, this paper will also explore the impression of these dynamics on the subsequent depiction.

Keywords: sexuality, hindi cinema, gender fluidity, legal framework

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Authors: Kuralay Kenzhekanova, Akmaral Dalelbekkyzy

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The article is devoted to the problem of political discourse and its reflection on mass cognition. This article is dedicated to describe the myth as one of the main features of political discourse. The dominance of an expressional and emotional component in the myth is shown. Precedent phenomenon plays an important role in distinguishing the myth from the linguistic point of view. Precedent phenomena show the linguistic cognition, which is characterized by their fame and recognition. Four types of myths such as master myths, a foundation myth, sustaining myth, eschatological myths are observed. The myths about the national idea are characterized by national specificity. The main aim of the political discourse with the help of myths is to influence on the mass consciousness in order to motivate the addressee to certain actions so that the target purpose is reached owing to unity of forces.

Keywords: cognition, myth, linguistic consciousness, types of myths, political discourse, political myth, precedent phenomena

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Authors: Chen Xi, Liu Xuebing, Lao Xueru, Kuan Sinman, Jiang Yike, Wang Hanwei, Yang Xiaolang, Zhou Junjie, Xie Jinpeng

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To further promote the development of smart cities, the microscopic "nerve endings" of the City Intelligent Model (CIM) are extended to be more sensitive. In this paper, we develop a pedestrian trajectory twin terminal based on the CIM and CNN technology. It also uses 5G networks, architectural and geoinformatics technologies, convolutional neural networks, combined with deep learning networks for human behavior recognition models, to provide empirical data such as 'pedestrian flow data and human behavioral characteristics data', and ultimately form spatial performance evaluation criteria and spatial performance warning systems, to make the empirical data accurate and intelligent for prediction and decision making.

Keywords: urban planning, urban governance, CIM, artificial intelligence, sustainable development

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Authors: Nouredine Benouzza, Ahmed Hamida Boudinar, Azeddine Bendiabdellah

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An algorithm for Eccentricity Fault Detection (EFD) applied to a squirrel cage induction machine is proposed in this paper. This algorithm employs the behavior of the stator current spectral analysis and the localization of the Rotor Slot Harmonic (RSH) frequency to detect eccentricity faults in three phase induction machine. The RHS frequency once obtained is used as a key parameter into a simple developed expression to directly compute the eccentricity fault frequencies in the induction machine. Experimental tests performed for both a healthy motor and a faulty motor with different eccentricity fault severities illustrate the effectiveness and merits of the proposed EFD algorithm.

Keywords: squirrel cage motor, diagnosis, eccentricity faults, current spectral analysis, rotor slot harmonic

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Authors: Tiee-Jian Wu, Chih-Yuan Hsu

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Mode estimation is an important task, because it has applications to data from a wide variety of sources. We propose a semi-parametric approach to estimate the mode of an unknown continuous multivariate density function. Our approach is based on a weighted average of a parametric density estimate using the Box-Cox transform and a non-parametric kernel density estimate. Our semi-parametric mode estimate improves both the parametric- and non-parametric- mode estimates. Specifically, our mode estimate solves the non-consistency problem of parametric mode estimates (at large sample sizes) and reduces the variability of non-parametric mode estimates (at small sample sizes). The performance of our method at practical sample sizes is demonstrated by simulation examples and two real examples from the fields of climatology and image recognition.

Keywords: Box-Cox transform, density estimation, mode seeking, semiparametric method

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Authors: R. K. Chaurasiya, N. D. Londhe, S. Ghosh

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The study of the electrical signals produced by neural activities of human brain is called Electroencephalography. In this paper, we propose an automatic and efficient EEG signal classification approach. The proposed approach is used to classify the EEG signal into two classes: epileptic seizure or not. In the proposed approach, we start with extracting the features by applying Discrete Wavelet Transform (DWT) in order to decompose the EEG signals into sub-bands. These features, extracted from details and approximation coefficients of DWT sub-bands, are used as input to Principal Component Analysis (PCA). The classification is based on reducing the feature dimension using PCA and deriving the support-vectors using Support Vector Machine (SVM). The experimental are performed on real and standard dataset. A very high level of classification accuracy is obtained in the result of classification.

Keywords: discrete wavelet transform, electroencephalogram, pattern recognition, principal component analysis, support vector machine

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Authors: Manel Bouloudenine, Karima Djeddou, Hadjer Ben Manser, Hana Soualah Alila, Mohmed Bououdina

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This survey research involves the elaboration and characterization of silver nanoparticles for therapeutic and environmental applications. The silver nanoparticles "Ag NPs" were synthesized by reducing AgNO3 with microwaves. The characterization of nanoparticles was done by using Transmission Electron Microscopy " TEM ", Energy Dispersive Spectroscopy "EDS", Selected Area Electron Diffraction "SEAD", UV-Visible Spectroscopy and Dynamic Light Scattering "DLS". Transmission Electron Microscopy and Electron Diffraction have confirmed the nanoscale, the shape, and the crystalline quality of as synthesized silver nanoparticles. Elementary analysis has proved the purity of Ag NPs and the presence of the Surface Plasmon Resonance phenomenon "SPR". A strong absorption shift was observed in the visible range of the UV-visible spectrum of as synthesized Ag NPs, which indicates the presence of metallic silver. When the strong absorption in the ultraviolet range of the spectrum has revealed the presence of ionic Ag NPs ionic Ag aggregates species. The autocorrelation function measured by the Dynamic Light Scattering has shown a strong monodispersed character of Ag NPs, which is indicated by the presence of a single size population, with a minima and a maxima laying between 40 and 111 nm. Related to other research, our results confirm the performance properties of as synthesized Ag NPs, which allows them to be performing in many technological applications, including therapeutic and environmental ones.

Keywords: silvers nanoparticles, microwaves, EDS, TEM

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Authors: Chen Xi, Kuan Sinman, LI Haofeng, Huang Hongming, Zeng Chengyu, Tong Zhiyuan

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Stray animals are on the rise in mainland China's cities. There are legal reasons for this, namely the lack of protection for domestic pets in mainland China, where only wildlife protection laws exist. At a social level, the ease with which families adopt pets and the lack of a social view of animal nature has led to the frequent abandonment and loss of stray animals. If left unmanaged, conflicts between humans and stray animals can also increase. This project provides an inexpensive and widely applicable management tool for urban management by collecting videos and pictures of stray animals captured by surveillance or transmitted by humans and using artificial intelligence technology (mainly using YOLOv5 recognition technology) and recording and managing them in a database.

Keywords: urban planning, urban governance, artificial intelligence, convolutional neural network

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Authors: Christine F. Boos, Fernando M. Azevedo

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Electroencephalogram (EEG) is a record of the electrical activity of the brain that has many applications, such as monitoring alertness, coma and brain death; locating damaged areas of the brain after head injury, stroke and tumor; monitoring anesthesia depth; researching physiology and sleep disorders; researching epilepsy and localizing the seizure focus. Epilepsy is a chronic condition, or a group of diseases of high prevalence, still poorly explained by science and whose diagnosis is still predominantly clinical. The EEG recording is considered an important test for epilepsy investigation and its visual analysis is very often applied for clinical confirmation of epilepsy diagnosis. Moreover, this EEG analysis can also be used to help define the types of epileptic syndrome, determine epileptiform zone, assist in the planning of drug treatment and provide additional information about the feasibility of surgical intervention. In the context of diagnosis confirmation the analysis is made using long term EEG recordings with at least 24 hours long and acquired by a minimum of 24 electrodes in which the neurophysiologists perform a thorough visual evaluation of EEG screens in search of specific electrographic patterns called epileptiform discharges. Considering that the EEG screens usually display 10 seconds of the recording, the neurophysiologist has to evaluate 360 screens per hour of EEG or a minimum of 8,640 screens per long term EEG recording. Analyzing thousands of EEG screens in search patterns that have a maximum duration of 200 ms is a very time consuming, complex and exhaustive task. Because of this, over the years several studies have proposed automated methodologies that could facilitate the neurophysiologists’ task of identifying epileptiform discharges and a large number of methodologies used neural networks for the pattern classification. One of the differences between all of these methodologies is the type of input stimuli presented to the networks, i.e., how the EEG signal is introduced in the network. Five types of input stimuli have been commonly found in literature: raw EEG signal, morphological descriptors (i.e. parameters related to the signal’s morphology), Fast Fourier Transform (FFT) spectrum, Short-Time Fourier Transform (STFT) spectrograms and Wavelet Transform features. This study evaluates the application of these five types of input stimuli and compares the classification results of neural networks that were implemented using each of these inputs. The performance of using raw signal varied between 43 and 84% efficiency. The results of FFT spectrum and STFT spectrograms were quite similar with average efficiency being 73 and 77%, respectively. The efficiency of Wavelet Transform features varied between 57 and 81% while the descriptors presented efficiency values between 62 and 93%. After simulations we could observe that the best results were achieved when either morphological descriptors or Wavelet features were used as input stimuli.

Keywords: Artificial neural network, electroencephalogram signal, pattern recognition, signal processing

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Authors: Wentian Shi, Daming Shi, Maysam Orouskhani, Feng Tian

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Whereas currently the most prevalent deep learning methods require a large amount of data for training, few-shot learning tries to learn a model from limited data without extensive retraining. In this paper, we present a loss function based on triplet loss for solving few-shot problem using metric based learning. Instead of setting the margin distance in triplet loss as a constant number empirically, we propose an adaptive margin distance strategy to obtain the appropriate margin distance automatically. We implement the strategy in the deep siamese network for deep metric embedding, by utilizing an optimization approach by penalizing the worst case and rewarding the best. Our experiments on image recognition and co-segmentation model demonstrate that using our proposed triplet loss with adaptive margin distance can significantly improve the performance.

Keywords: few-shot learning, triplet network, adaptive margin, deep learning

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Authors: Sheldon McCall, Miao Yu, Liyun Gong, Shigang Yue, Stefanos Kollias

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Falls are a significant health concern for older adults globally, and prompt identification is critical to providing necessary healthcare support. Our study proposes a new fall detection method using computer vision based on modern deep learning techniques. Our approach involves training a trans- former model on a large 2D pose dataset for general action recognition, followed by transfer learning. Specifically, we freeze the first few layers of the trained transformer model and train only the last two layers for fall detection. Our experimental results demonstrate that our proposed method outperforms both classical machine learning and deep learning approaches in fall/non-fall classification. Overall, our study suggests that our proposed methodology could be a valuable tool for identifying falls.

Keywords: healthcare, fall detection, transformer, transfer learning

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Authors: A. Luft, S. Bremen, N. Balc

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The task of flexibility planning and design, just like factory planning, for example, is to create the long-term systemic framework that constitutes the restriction for short-term operational management. This is a strategic challenge since, due to the decision defect character of the underlying flexibility problem, multiple types of flexibility need to be considered over the course of various scenarios, production programs, and production system configurations. In this context, an evaluation model has been developed that integrates both conventional and additive resources on a basic task level and allows the quantification of flexibility enhancement in terms of mix and volume flexibility, complexity reduction, and machine capacity. The model helps companies to decide in early decision-making processes about the potential gains of implementing additive manufacturing technologies on a strategic level. For companies, it is essential to consider both additive and conventional manufacturing beyond pure unit costs. It is necessary to achieve an integrative view of manufacturing that incorporates both additive and conventional manufacturing resources and quantifies their potential with regard to flexibility and manufacturing complexity. This also requires a structured process for the strategic production systems design that spans the design of various scenarios and allows for multi-dimensional and comparative analysis. A respective guideline for the planning of additive resources on a strategic level is being laid out in this paper.

Keywords: additive manufacturing, production system design, flexibility enhancement, strategic guideline

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Authors: Ibrahim A. Alkali

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There is no reservation on the outstanding contribution of patient families in restoration of hospitalised patients, hence their consideration as essential component of hospital ward regimen. The psychological and emotional support a patient requires has been found to be solely provided by the patient’s family. However, consideration of their presence as one of the major functional requirements of an inpatient setting design have always been a source of disquiet, especially in developing countries where policies, norms and protocols of healthcare administration have no consideration for the patients’ family. This have been a major challenge to the hospital ward facilities, a concern for the hospital administration and patient management. The study therefore is aimed at obtaining a consensus opinion on the best approach for family integration in the design of an inpatient setting.  A one day visioning charrette involving Architects, Nurses, Medical Doctors, Healthcare assistants and representatives from the Patient families was conducted with the aim of arriving at a consensus opinion on practical design approach for sustainable family integration. Patient’s family are found to be decisive character of hospital ward regimen that cannot be undermined. However, several challenges that impede family integration were identified and subsequently a recommendation for an ideal approach. This will serve as a guide to both architects and hospital management in implementing much desired Patient and Family Centred Care.

Keywords: patient's family, inpatient setting, care giving, integration

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Authors: Dayo Samuel Banjo, Connice Trimmingham, Niloofar Yousefi, Nitin Agarwal

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Technological advancement and its omnipresent connection have pushed humans past the boundaries and limitations of a computer screen, physical state, or geographical location. It has provided a depth of avenues that facilitate human-computer interaction that was once inconceivable such as audio and body language detection. Given the complex modularities of emotions, it becomes vital to study human-computer interaction, as it is the commencement of a thorough understanding of the emotional state of users and, in the context of social networks, the producers of multimodal information. This study first acknowledges the accuracy of classification found within multimodal emotion detection systems compared to unimodal solutions. Second, it explores the characterization of multimedia content produced based on their emotions and the coherence of emotion in different modalities by utilizing deep learning models to classify emotion across different modalities.

Keywords: affective computing, deep learning, emotion recognition, multimodal

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Authors: Rui Mao, Heming Ji, Xiaoyu Wang

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Keystroke dynamics are widely used in identity recognition. It has the advantage that the individual typing rhythm is difficult to imitate. It also supports continuous authentication through the keyboard without extra devices. The existing keystroke dynamics authentication methods based on machine learning have a drawback in supporting relatively complex scenarios with massive data. There are drawbacks to both feature extraction and model optimization in these methods. To overcome the above weakness, an authentication model of keystroke dynamics based on deep learning is proposed. The model uses feature vectors formed by keystroke content and keystroke time. It ensures efficient continuous authentication by cooperating attention mechanisms with the combination of CNN and Bi-LSTM. The model has been tested with Open Data Buffalo dataset, and the result shows that the FRR is 3.09%, FAR is 3.03%, and EER is 4.23%. This proves that the model is efficient and accurate on continuous authentication.

Keywords: keystroke dynamics, identity authentication, deep learning, CNN, LSTM

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Authors: Ebenezer Obaloluwa Olaniyi

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In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Amer Rghei

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The Sahara region potentially is one of the most attractive heritage areas in the world. Yet presently, the heritage of the Sahara is currently facing serious planning challenges of underdeveloped and neglected economic and physical potentials. Deterioration of heritage resources has been observed by the author during his several field tours for historic sites has discovered special heritage values such as in Ghadames which combines historic oasis, natural environment along with its exceptional urban fabric and architectural character. Despite the richness of Ghadames with historic significance, it is found that at the present time, Ghadames city, the UNESCO World Heritage site, is facing serious challenges including the abandonment by its tenants and inclusive negligence by its officials. The author believes that Ghadames can illustrate an excellent heritage example in North Africa with cultural pride and socio-economic opportunities that can contribute to overall economic development in the Sahara region. However, the paper deals with the case of Ghadames ‘The World Heritage Site’ in Libya and discusses the current challenges and possible planning for its heritage conservation strategy. The momentous resources in Ghadames with their historical, environmental, economic, social, cultural, and aesthetic values would benefit from a careful heritage planning and management program for its significant values. In this paper an attempt is made to investigate this issue seriously towards building a model of a strategy for heritage conservation planning for Ghadames is proposed.

Keywords: Ghadames, Oasis architecture, Sahara region, heritage environment

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Authors: Adian Fatchur Rochim, Abdul Muis, Riri Fitri Sari

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H-index has been widely used as a performance indicator of researchers around the world especially in Indonesia. The Government uses Scopus and Google scholar as indexing references in providing recognition and appreciation. However, those two indexing services yield to different H-index values. For that purpose, this paper evaluates the difference of the H-index from those services. Researchers indexed by Webometrics, are used as reference’s data in this paper. Currently, Webometrics only uses H-index from Google Scholar. This paper observed and compared corresponding researchers’ data from Scopus to get their H-index score. Subsequently, some researchers with huge differences in score are observed in more detail on their paper’s publisher. This paper shows that the H-index of researchers in Google Scholar is approximately 2.45 times of their Scopus H-Index. Most difference exists due to the existence of uncertified publishers, which is considered in Google Scholar but not in Scopus.

Keywords: Google Scholar, H-index, Scopus, performance indicator

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Authors: Tirtha Raj Dhakal, Brian Davidson, Bob Farquharson

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Institutional design is important if water resources are to be managed efficiently. In Nepal, the supply of water in both farmer- and agency-managed irrigation systems is inefficient because of the weak institutional frameworks. This type of inefficiency is linked with collective problems such as non-excludability of irrigation water, inadequate recognition of property rights and externalities. Irrigation scheme surveys from Nepal as well as existing literature revealed that the Nepalese irrigation sector is facing many issues such as low cost recovery, inadequate maintenance of the schemes and inefficient allocation and utilization of irrigation water. The institutional practices currently in place also fail to create/force any incentives for farmers to use water efficiently and to pay for its use. This, thus, compels the need of refined institutional framework that can address the collective problems and improve irrigation efficiency.

Keywords: agency-managed, cost recovery, farmer-managed, institutional design

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Authors: Kristin Murray

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The proposed paper exams prologues in 20th and 21st century American literature in order to show how Native American writer Tommy Orange’s Prologue in his 2018 novel There, Thereis different. In an interview about his 2018 novel There, There, explains he feels “a kind of burden to catch the general reader up with what really happened, because history has got it so wrong and still continue to” (Laubernds). Orange, thus, includes a “Prologue” in his novel to do this work, catching readers upon Native Americans and their history. Prologues are usually from the narrator’s voice, a character’s voice, or even from a fictionalized version of the author, but the tone of Orange’s “Prologue” is that of a non-fictional first-person essayist. Examining prologues in American literature posits Orange’s prologue outside the norm. This paper also examines other introductory sections, the preface, in particular. The research and examination reveal that Orange is adding his personal voice in the Prologue to the multiple narratorsof the novel, and his is the voice of a writer who knows that his audience comes to his novel with a plethora of misinformation. The truths he tells are horrifying and hopeful. He tells of Thanksgiving as a “land deal” and a “successful massacre,” but he also tellsreaders how urban Indians have found a sense of the land, even through concrete. Native American writers contributed and still contribute to the genre of autobiography in ways that have changed our understanding of this genre. This examination of Orange’s Prologue reveals the new and unexpected way to view this often under-examined introductory section, the prologue.

Keywords: native american literature, prologues, prefaces, 20th century american literature

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Authors: César Oliveira, Ana M. S. Bettencourt, Luciano Vilas Boas, Luís Gonçalves, Carlo Bottaini

Abstract:

Funerary megalithic monuments are probably under the most remarkable remains of the Neolithic period of western Europe. Some monuments are well known for their paintings, sometimes associated with engraved motifs, giving the funerary crypts a character of great symbolic value. The engraved and painted motifs, the colors used in the paintings, and the offerings associated with the deposited corpses are archaeological data that, being part of the funeral rites, also reveal the ideological world of these communities and their way of interacting with the world. In this sense, the choice of colors to be used in the paintings, the pigments collected, and the proceeds for making the paints would also be significant performances. The present study will focus on the characterization of painted art from megalithic monuments located in different areas of North-Western Portugal (coastal and inland). The colorant composition of megalithic barrows decorated with rock art motifs was studied using a multi-analytical approach (XRD, SEM-EDS, FTIR, and GC-MS), allowing the characterization of the painting techniques, pigments, and the organic compounds used as binders. Some analyses revealed that the pigments used for painting were produced using a collection of mined or quarried organic and inorganic substances. The results will be analyzed from the perspective of contingencies and regularity among the different case studies in order to interpret more or less standardized behaviors.

Keywords: funerary megalithic monuments, painting motifs, archaeometrical studies, Northwest Iberia, behaviors

Procedia PDF Downloads 99

Authors: M. E. Silva, I. Brás

Abstract:

To study the influence of different organic amendments on the quality of poultry manure compost, three pilot composting trials were carried out with different mixes: poultry manure/carcasse meal/ashes/grape pomace (Pile 1), poultry manure/ cellulosic sludge (Pile 2) and poultry manure (Pile 3). For all piles, wood chips were applied as bulking agent. The process was monitored, over time, by evaluating standard physical and chemical parameters, such as, pH, electric conductivity, moisture, organic matter and ash content, total carbon and total nitrogen content, carbon/nitrogen ratio (C/N) and content in mineral elements. Piles 1 and 2 reached a thermophilic phase, however having different trends. Pile 1 reached this phase earlier than Pile 2. For both, the pH showed a slight alkaline character and the electric conductivity was lower than 2 mS/cm. Also, the initial C/N value was 22 and reached values lower than 15 at the end of composting process. The total N content of the Pile 1 increased slightly during composting, in contrast with the others piles. At the end of composting process, the phosphorus content ranged between 54 and 236 mg/kg dry matter, for Pile 2 and 3, respectively. Generally, the Piles 1 and 3 exhibited similar heavy metals content. This study showed that organic amendments can be used as carbon source, given that the final composts presented parameters within the range of those recommended in the 2^nd Draft of EU regulation proposal (DG Env.A.2 2001) for compost quality.

Keywords: co-composting, compost quality, organic ammendment, poultry manure

Procedia PDF Downloads 299