Search results for: distant named entity recognition

Authors: Yusri Yusof, Chen Wong Keong

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This paper presents the implementation details of a Relational Database Management System of a STEP-technology product model repository. It is able support the implementation of any EXPRESS language schema, although it has been primarily implemented to support mechanical product life cycle applications. This database support the input of STEP part 21 file format from CAD in geometrical and topological data format and support a range of queries for mechanical product life cycle applications. This proposed relational database management system uses entity-to-table method (R1) rather than type-to-table method (R4). The two mapping methods have their own strengths and drawbacks.

Keywords: RDBMS, CAD, ISO 10303, part-21 file

Procedia PDF Downloads 536

Authors: Leah Lee

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This paper examines the correlation between deep learning models and emotions with noises to see whether or not noises mask emotions. The deep learning models used are plain convolutional neural networks (CNN), auto-encoder, long short-term memory (LSTM), and Visual Geometry Group-16 (VGG-16). Emotion datasets used are Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS), Crowd-sourced Emotional Multimodal Actors Dataset (CREMA-D), Toronto Emotional Speech Set (TESS), and Surrey Audio-Visual Expressed Emotion (SAVEE). To make it four times bigger, audio set files, stretch, and pitch augmentations are utilized. From the augmented datasets, five different features are extracted for inputs of the models. There are eight different emotions to be classified. Noise variations are white noise, dog barking, and cough sounds. The variation in the signal-to-noise ratio (SNR) is 0, 20, and 40. In summation, per a deep learning model, nine different sets with noise and SNR variations and just augmented audio files without any noises will be used in the experiment. To compare the results of the deep learning models, the accuracy and receiver operating characteristic (ROC) are checked.

Keywords: auto-encoder, convolutional neural networks, long short-term memory, speech emotion recognition, visual geometry group-16

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Authors: K. Bresilla, L. Manfrini, B. Morandi, A. Boini, G. Perulli, L. C. Grappadelli

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Image/video processing for fruit in the tree using hard-coded feature extraction algorithms have shown high accuracy during recent years. While accurate, these approaches even with high-end hardware are computationally intensive and too slow for real-time systems. This paper details the use of deep convolution neural networks (CNNs), specifically an algorithm (YOLO - You Only Look Once) with 24+2 convolution layers. Using deep-learning techniques eliminated the need for hard-code specific features for specific fruit shapes, color and/or other attributes. This CNN is trained on more than 5000 images of apple and pear fruits on 960 cores GPU (Graphical Processing Unit). Testing set showed an accuracy of 90%. After this, trained data were transferred to an embedded device (Raspberry Pi gen.3) with camera for more portability. Based on correlation between number of visible fruits or detected fruits on one frame and the real number of fruits on one tree, a model was created to accommodate this error rate. Speed of processing and detection of the whole platform was higher than 40 frames per second. This speed is fast enough for any grasping/harvesting robotic arm or other real-time applications.

Keywords: artificial intelligence, computer vision, deep learning, fruit recognition, harvesting robot, precision agriculture

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Authors: Assem El-Ansary

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This paper illustrates the event-oriented Behavioral Pattern Analysis (BPA) modeling approach in developing an Multi-Agent TeleRobotic Security Control System (MTSCS). The event defined in BPA is a real-life conceptual entity that is unrelated to any implementation. The major contributions of this research are the Behavioral Pattern Analysis (BPA) modeling methodology, and the development of an interactive software tool (DECISION), which is based on a combination of the Analytic Hierarchy Process (AHP) and the ELECTRE Multi-Criteria Decision Making (MCDM) methods.

Keywords: analysis, multi-agent, TeleRobotics control, security, modeling methodology, software modeling, event-oriented, behavioral pattern, use cases

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Authors: Vesa Salminen, Esa Santakallio, Heikki Ruohomaa

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Introduction: The city of Riihimäki has decided robotics on well-being, service and industry as the main focus area on their ecosystem strategy. Robotics is going to be an important part of the everyday life of citizens and present in the working day of the average citizen and employee in the future. For that reason, also education system and education programs on all levels of education from diaper age to doctorate have been directed to fulfill this ecosystem strategy. Goal: The objective of this activity has been to develop education continuity from diaper age to doctorate. The main target of the development activity is to create a unique robotics study entity that enables ongoing robotics studies from preprimary education to university. The aim is also to attract students internationally and supply a skilled workforce to the private sector, capable of the challenges of the future. Methodology: Education instances (high school, second grade, Universities on all levels) in a large area of Tavastia Province have gradually directed their education programs to support this goal. On the other hand, applied research projects have been created to make proof of concept- phases on areal real environment field labs to test technology opportunities and digitalization to change business processes by applying robotic solutions. Customer-oriented applied research projects offer for students in robotics education learning environments to learn new knowledge and content. That is also a learning environment for education programs to adapt and co-evolution. New content and problem-based learning are used in future education modules. Major findings: Joint robotics education entity is being developed in cooperation with the city of Riihimäki (primary education), Syria Education (secondary education) and HAMK (bachelor and master education). The education modules have been developed to enable smooth transitioning from one institute to another. This article is introduced a case study of the change of education of wellbeing education because of digitalization and robotics. Riihimäki's Elderly citizen's service house, Riihikoti, has been working as a field lab for proof-of-concept phases on testing technology opportunities. According to successful case studies also education programs on various levels of education have been changing. Riihikoti has been developed as a physical learning environment for home care and robotics, investigating and developing a variety of digital devices and service opportunities and experimenting and learn the use of equipment. The environment enables the co-development of digital service capabilities in the authentic environment for all interested groups in transdisciplinary cooperation.

Keywords: ecosystem strategy, digitalization and robotics, education continuity, learning environment, transdisciplinary co-operation

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Authors: Dimitrios Binas, Marianna Konidari, Charis Bourgioti, Lia Angela Moulopoulou, Theodore Economopoulos, George Matsopoulos

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High grade ovarian epithelial cancer (OEC) is fatal gynecological cancer and the poor prognosis of this entity is closely related to considerable intratumoral genetic heterogeneity. By examining imaging data, it is possible to assess the heterogeneity of tumorous tissue. This study proposes a methodology for aligning, segmenting and finally visualizing information from various magnetic resonance imaging series in order to construct 3D models of heterogeneity maps from the same tumor in OEC patients. The proposed system may be used as an adjunct digital tool by health professionals for personalized medicine, as it allows for an easy visual assessment of the heterogeneity of the examined tumor.

Keywords: image segmentation, ovarian epithelial cancer, quantitative characteristics, image registration, tumor visualization

Procedia PDF Downloads 211

Authors: Sajeesh Sulaiman, Gomathisankar A., Aravind Devaraj, Aswin R., Vijay Kumar G., Rachana Raj

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Wind turbines are the next big answer to the emerging and ever-growing demand for electricity, and this need is increasing day by day. These high mast structures, whether on land or on the sea, has also become one of the big sources of electromagnetic interferences (EMI) in the not so distant past. With the emergence of the AC-AC converter and drawing of large power cables through the wind turbine towers has made this clean and efficient source of renewable energy to become one of the culprits in creating electromagnetic interference. This paper will present the sources of such EMIs, a comparison of radiated emissions (both electric and magnetic field) patterns in wind turbine towers for both onshore and offshore wind turbines and close look into the IEC 61400-40 (new standard for EMC design on wind turbine). At present, offshore wind turbines are tested in onshore facilities. This paper will present the anomaly in results for offshore wind turbines when tested in onshore, which the existing standards and the upcoming standards have failed to address.

Keywords: emissions, electric field, magnetic field, wind turbine, tower, standards and regulations

Procedia PDF Downloads 247

Authors: Vladimir Kulyukin, Tanwir Zaman, Sarat Kiran Andhavarapu

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Research on nutrition label use identifies four factors that impede comprehension and retention of nutrition information by consumers: label’s location on the package, presentation of information within the label, label’s surface size, and surrounding visual clutter. In this paper, a system is presented that makes nutrition label use more effective for nutrition information comprehension and retention. The system’s front end is a smartphone application. The system’s back end is a four node Linux cluster for image recognition and data storage. Image frames captured on the smartphone are sent to the back end for skewed or aligned barcode recognition. When barcodes are recognized, corresponding nutrition labels are retrieved from a cloud database and presented to the user on the smartphone’s touchscreen. Each displayed nutrition label is positioned centrally on the touchscreen with no surrounding visual clutter. Wikipedia links to important nutrition terms are embedded to improve comprehension and retention of nutrition information. Standard touch gestures (e.g., zoom in/out) available on mainstream smartphones are used to manipulate the label’s surface size. The nutrition label database currently includes 200,000 nutrition labels compiled from public web sites by a custom crawler. Stress test experiments with the node cluster are presented. Implications for proactive nutrition management and food policy are discussed.

Keywords: mobile computing, cloud computing, nutrition label use, nutrition management, barcode scanning

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Authors: Susan P. Teru, Jerome Nyameh

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Many contemporary organizations are placing a greater emphasis on business enterprise systems as a means of generating higher levels of economic development. Many business research and literature has also concur that enterprise drive economic development, giving little or no credit to social enterprise, whose profit is reinvest to the community development compare to the business enterprise that share their profit to shareholders. Economic development includes economic policies that affect the beneficiaries of the economic entity. We suggest that producing social enterprise increments may be best achieved by orienting social enterprise entrepreneurs system to promote economic development. To this end, we describe a new approach to the social enterprise process that includes social entrepreneur and the key drivers of economic development at each stage. We present a model of social enterprise that incorporates the main ideas of the paper and suggests a new perspective for thinking about how to foster and manage social enterprise to achieve high levels of economic development.

Keywords: social enterprise, economic development, Nigeria, business and management

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Authors: Xiang Shijie, Zhou Dong, Tian Dan

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This paper focuses on the application of real-time semantic segmentation technology in complex road condition recognition, aiming to address the critical issue of how to improve segmentation accuracy while ensuring real-time performance. Semantic segmentation technology has broad application prospects in fields such as autonomous vehicle navigation and remote sensing image recognition. However, current real-time semantic segmentation networks face significant technical challenges and optimization gaps in balancing speed and accuracy. To tackle this problem, this paper conducts an in-depth study and proposes an innovative Guided Image Reconstruction Module. By resampling high-resolution images into a set of low-resolution images, this module effectively reduces computational complexity, allowing the network to more efficiently extract features within limited resources, thereby improving the performance of real-time segmentation tasks. In addition, a dual-branch network structure is designed in this paper to fully leverage the advantages of different feature layers. A novel Hybrid Attention Mechanism is also introduced, which can dynamically capture multi-scale contextual information and effectively enhance the focus on important features, thus improving the segmentation accuracy of the network in complex road condition. Compared with traditional methods, the proposed model achieves a better balance between accuracy and real-time performance and demonstrates competitive results in road condition segmentation tasks, showcasing its superiority. Experimental results show that this method not only significantly improves segmentation accuracy while maintaining real-time performance, but also remains stable across diverse and complex road conditions, making it highly applicable in practical scenarios. By incorporating the Guided Image Reconstruction Module, dual-branch structure, and Hybrid Attention Mechanism, this paper presents a novel approach to real-time semantic segmentation tasks, which is expected to further advance the development of this field.

Keywords: hybrid attention mechanism, image reconstruction, real-time, road status recognition

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Authors: Ziling Chen

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Within six days in June 1967, Israeli armies defeated the combined forces of Egypt, Syria, and Jordan. This war was later named the Six-Day War, or Third Arab-Israeli War. This paper examines the lasting legacy of the Six-Day War in the life of Palestinians and Israelis economically, politically, and religiously. The long-term Israeli occupation resulted in Palestinian displacement, impeded the development of the Palestinian economy, as well as a created division within Israeli society. Although the war ended, the conflicts persist, most notably in the Old City of Jerusalem. Due to its sacred nature, the Old City became the center of religious conflicts after the Six-Day War.

Keywords: Israelis, Jerusalem, Palestinians, Six-Day War

Procedia PDF Downloads 123

Authors: Besma Khalfoun

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In many current Human Activity Recognition (HAR) applications, users' data is frequently shared and centrally stored by third parties, posing a significant privacy risk. This practice makes these entities attractive targets for extracting sensitive information about users, including their identity, health status, and location, thereby directly violating users' privacy. To tackle the issue of centralized data storage, a relatively recent paradigm known as federated learning has emerged. In this approach, users' raw data remains on their smartphones, where they train the HAR model locally. However, users still share updates of their local models originating from raw data. These updates are vulnerable to several attacks designed to extract sensitive information, such as determining whether a data sample is used in the training process, recovering the training data with inversion attacks, or inferring a specific attribute or property from the training data. In this paper, we first introduce PUR-Attack, a parameter-based user re-identification attack developed for HAR applications within a federated learning setting. It involves associating anonymous model updates (i.e., local models' weights or parameters) with the originating user's identity using background knowledge. PUR-Attack relies on a simple yet effective machine learning classifier and produces promising results. Specifically, we have found that by considering the weights of a given layer in a HAR model, we can uniquely re-identify users with an attack success rate of almost 100%. This result holds when considering a small attack training set and various data splitting strategies in the HAR model training. Thus, it is crucial to investigate protection methods to mitigate this privacy threat. Along this path, we propose SAFER, a privacy-preserving mechanism based on adaptive local differential privacy. Before sharing the model updates with the FL server, SAFER adds the optimal noise based on the re-identification risk assessment. Our approach can achieve a promising tradeoff between privacy, in terms of reducing re-identification risk, and utility, in terms of maintaining acceptable accuracy for the HAR model.

Keywords: federated learning, privacy risk assessment, re-identification risk, privacy preserving mechanisms, local differential privacy, human activity recognition

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Authors: Rodolfo Lorbieski, Silvia Modesto Nassar

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Many supervised machine learning tasks require decision making across numerous different classes. Multi-class classification has several applications, such as face recognition, text recognition and medical diagnostics. The objective of this article is to analyze an adapted method of Stacking in multi-class problems, which combines ensembles within the ensemble itself. For this purpose, a training similar to Stacking was used, but with three levels, where the final decision-maker (level 2) performs its training by combining outputs from the tree-based pair of meta-classifiers (level 1) from Bayesian families. These are in turn trained by pairs of base classifiers (level 0) of the same family. This strategy seeks to promote diversity among the ensembles forming the meta-classifier level 2. Three performance measures were used: (1) accuracy, (2) area under the ROC curve, and (3) time for three factors: (a) datasets, (b) experiments and (c) levels. To compare the factors, ANOVA three-way test was executed for each performance measure, considering 5 datasets by 25 experiments by 3 levels. A triple interaction between factors was observed only in time. The accuracy and area under the ROC curve presented similar results, showing a double interaction between level and experiment, as well as for the dataset factor. It was concluded that level 2 had an average performance above the other levels and that the proposed method is especially efficient for multi-class problems when compared to binary problems.

Keywords: stacking, multi-layers, ensemble, multi-class

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Authors: Yasser M. Abd-elrhman, Mohamed A. Gepreel, Kiochi Nakamura, Ahmed Abd El-Moneim, Sengo Kobayashi, Mervat M. Ibrahim

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Titanium alloys are known as highly bio compatible metallic materials due to their high strength, low elastic modulus, and high corrosion resistance in biological media. Besides other important material features, the corrosion parameters and corrosion products are responsible for limiting the biological and chemical bio compatibility of metallic materials that produce undesirable reactions in implant-adjacent and/or more distant tissues. Electrochemical corrosion behaviors of novel beta titanium alloys, Ti-4.7Mo-4.5Fe, Ti-3Mo-0.5Fe, and Ti-2Mo-0.5Fe were characterized in naturally aerated Ringer’s solution at room temperature compared with common used biomedical titanium alloy, Ti-6Al-4V. The corrosion resistance of titanium alloys were investigated through open circuit potential (OCP), potentiodynamic polarization measurements and optical microscope (OM). A high corrosion resistance was obtained for all alloys due to the stable passive film formed on their surfaces. The new present alloys are promising metallic biomaterials for the future, owing to their very low elastic modulus and good corrosion resistance capabilities.

Keywords: titanium alloys, corrosion resistance, Ringer’s solution, electrochemical corrosion

Procedia PDF Downloads 658

Authors: Milena M. Melo, Jane M. Santos, Severine Frere, Valderio A. Reisen, Neyval C. Reis Jr., Mariade Fátima S. Leite

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Although there had been a many studies that shows the impact of air pollution on physical health, comparatively less was known of human behavioral responses and annoyance impacts. Annoyance caused by air pollution is a public health problem because it can be an ambient stressor causing stress and disease and can affect quality of life. The objective of this work is to evaluate the annoyance caused by air pollution in two different industrialized urban areas, Dunkirk (France) and Vitoria (Brazil). The populations of these cities often report feeling annoyed by dust. Surveys were conducted, and the collected data were analyzed using statistical analyses. The results show that sociodemographic variables, importance of air quality, perceived industrial risk, perceived air pollution and occurrence of health problems play important roles in the perceived annoyance. These results show the existence of a common problem in geographically distant areas and allow stakeholders to develop prevention strategies.

Keywords: air pollution, annoyance, industrial risks, public health, perception of pollution, settled dust

Procedia PDF Downloads 691

Authors: Sunny Ewankhiwimen Aigbomian

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Time, is a scarce resource and in everything we do, time is required to accomplish any given task. The need for this presentation is predicated on the way majority of Nigerian especially in the public sector operators see “Time Management”. Time as resources cannot be regained if lost or managed badly. As a significant aspect of human life it should be handled with diligence and utmost seriousness if the public sector is to function as a coordinated entity. In our homes, private life and offices, we schedule different things to ensure that some things do not go the unexpected. When it comes to service delivery on the part of government, it ought to be more serious because government is all about effect and efficient service delivery and “Time” is a significant variable necessary to successful accomplishment. The need for Nigerian government to re-examine time management in her public sector with a view of repositioning the sector to be able to compete well with other public sectors in the world. The peculiarity of Time management in Public Sector in Nigerian context as examined and some useful recommendations of immerse assistance proffered.

Keywords: Nigeria, public sector, time management, task

Procedia PDF Downloads 99

Authors: Noorlizawati Abd Rahim, Zainai Mohamed, Zaidatun Tasir, Astuty Amrin, Haliyana Khalid, Nina Diana Nawi

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Entrepreneurial leaders have been sought as in-demand talents to lead profit-driven organizations during turbulent and unprecedented times. However, research regarding the pertinence of their roles in the public sector has been limited. This paper examined the characteristics of the challenging experiences encountered by senior leaders in public universities that require them to embrace entrepreneurialism in their leadership. Through a focus group interview with five Malaysian university top senior leaders with experience being Vice-Chancellor, we explored and developed a framework of institutional adversity characteristics and exemplary entrepreneurial leadership competency in the face of adversity. Complexity of diverse stakeholders, multiplicity of academic disciplines, unfamiliarity to lead different and broader roles, leading new directions, and creating change in high velocity and uncertain environment are among the dimensions that characterise institutional adversities. Our findings revealed that learning agility, opportunity recognition capacity, and bridging capability are among the characteristics of entrepreneurial university leaders. The findings reinforced that the presence of specific attributes in institutional adversity and experiences in overcoming those challenges may contribute to the development of entrepreneurial leadership capabilities.

Keywords: bridging capability, entrepreneurial leadership, leadership development, learning agility, opportunity recognition, university leaders

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Authors: Mina Dabirinezhad, Mohsen Bayat Pour, Amin Dabirinejad

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This paper is intended to introduce the technology to solve some of the deficiencies of the direct digital radiology. Nowadays, digital radiology is the latest progression in dental imaging, which has become an essential part of dentistry. There are two main parts of the direct digital radiology comprised of an intraoral X-ray machine and a sensor (digital image receptor). The dentists and the dental nurses experience afflictions during the taking image process by the direct digital X-ray machine. For instance, sometimes they need to readjust the sensor in the mouth of the patient to take the X-ray image again due to the low quality of that. Another problem is, the position of the sensor may move in the mouth of the patient and it triggers off an inappropriate image for the dentists. It means that it is a time-consuming process for dentists or dental nurses. On the other hand, taking several the X-ray images brings some problems for the patient such as being harmful to their health and feeling pain in their mouth due to the pressure of the sensor to the jaw. The author provides a technology to solve the above-mentioned issues that is called “Self-Recognition Direct Digital Radiology” (SDDR). This technology is based on the principle that the intraoral X-ray machine is capable to diagnose the location of the sensor in the mouth of the patient automatically. In addition, to solve the aforementioned problems, SDDR technology brings out fewer environmental impacts in comparison to the previous version.

Keywords: Dental direct digital imaging, digital image receptor, digital x-ray machine, and environmental impacts

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Authors: Saleem Abuleil, Khalid S. Alsamara

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Events represent a significant source of information on the web; they deliver information about events that occurred around the world in all kind of subjects and areas. These events can be collected and organized to provide valuable and useful information for decision makers, researchers, as well as any person seeking knowledge. In this paper, we discuss an ongoing research to target stock markets domain to observe and record changes (events) when they happen, collect them, understand the meaning of each one of them, and organize the information along with meaning in a well-structured format. By using Semantic Role Labeling (SRL) technique, we identified four factors for each event in this paper: verb of action and three roles associated with it, entity name, attribute, and attribute value. We have generated a set of rules and techniques to support our approach to analyze and understand the meaning of the events taking place in stock markets.

Keywords: natuaral language processing, Arabic language, event extraction and understanding, sematic role labeling, stock market

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Authors: Mwamba Mwamini Ruth

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For many authors,the percentage of married or in union persons using family planning methods has increased significantly since the 1960s, despite this progress, important differences across régions are observer.These différences become even greater,to present a paradox,when studying the issue in smallest territorial entities in developing countries.In line with the above,the general objective of this research is to investigate into "knowledge , attitude and practice"of households from a basic territorial entity,here in"Murara Sector"(in the city of Goma, province of North Kivu,Democratic Republic of Congo,Africa)on family planning (as defined and provisioned by the four World Health Organization-WHO key texts on the matter)

Keywords: DRC, family planning methods, information technology, Murara

Procedia PDF Downloads 139

Authors: Sandra Tapin-Lingua, Katia Ruel, Jean-Paul Joseleau, Daouia Messaoudi, Olivier Fahy, Michel Petit-Conil

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The preservative efficacy of organic biocides is strongly related to their capacity of penetration and retention within wood tissues. The specific detection of the pyrethroid insecticide is currently obtained after extraction followed by chemical analysis by chromatography techniques. However visualizing the insecticide molecule within the wood structure requires specific probes together with microscopy techniques. Therefore, the aim of the present work was to apply a new methodology based on antibody-antigen recognition and electronic microscopy to visualize directly pyrethroids in the wood material. A polyclonal antibody directed against cypermethrin was developed and implement it on Pinus sylvestris wood samples coated with technical cypermethrin. The antibody was tested on impregnated wood and the specific recognition of the insecticide was visualized in transmission electron microscopy (TEM). The immunogold-TEM assay evidenced the capacity of the synthetic biocide to penetrate in the wood. The depth of penetration was measured on sections taken at increasing distances from the coated surface of the wood. Such results correlated with chemical analyzes carried out by GC-ECD after extraction. In addition, the immuno-TEM investigation allowed visualizing, for the first time at the ultrastructure scale of resolution, that cypermethrin was able to diffuse within the secondary wood cell walls.

Keywords: cypermethrin, insecticide, wood penetration, wood retention, immuno-transmission electron microscopy, polyclonal antibody

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Authors: A. Degale Desta, Cheng Jian

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Deep learning application in computer vision is rapidly advancing, giving it the ability to monitor the public and quickly identify potentially anomalous behaviour from crowd scenes. Therefore, the purpose of the current work is to improve the performance of safety of people in crowd events from panic behaviour through introducing the innovative idea of Aggregation of Ensembles (AOE), which makes use of the pre-trained ConvNets and a pool of classifiers to find anomalies in video data with packed scenes. According to the theory of algorithms that applied K-means, KNN, CNN, SVD, and Faster-CNN, YOLOv5 architectures learn different levels of semantic representation from crowd videos; the proposed approach leverages an ensemble of various fine-tuned convolutional neural networks (CNN), allowing for the extraction of enriched feature sets. In addition to the above algorithms, a long short-term memory neural network to forecast future feature values and a handmade feature that takes into consideration the peculiarities of the crowd to understand human behavior. On well-known datasets of panic situations, experiments are run to assess the effectiveness and precision of the suggested method. Results reveal that, compared to state-of-the-art methodologies, the system produces better and more promising results in terms of accuracy and processing speed.

Keywords: action recognition, computer vision, crowd detecting and tracking, deep learning

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Authors: Sonia Bernardo Correia

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This paper is part of ongoing research that aims to understand the role of gender in the composition of the Portuguese contemporary art world and the possibilities and limits to the success of the professional paths of women and men artists. The field of visual arts is gender-sensitive as it differentiates the positions occupied by artists in terms of visibility and recognition. Women artists occupy a peripheral space, which may hinder the progression of their professional careers. Based on the collection of data on the participation of artists in Portuguese exhibitions, art fairs, auctions, and art awards between 2012 and 2019, the goal of this study is to portray female artists’ participation as a condition of professional, social, and cultural visibility. From the analysis of a significant sample of institutions from the artistic field, it was possible to observe that the works of female authors are under exhibited, never exceeding one-third of the total of exhibitions. Male artists also enjoy a comfortable majority as gallery artists (around 70%) and as part of institutional collections (around 80%). However, when analysing the younger age cohorts of artists by gender, it appears that there is representation parity, which may be a good sign of change. The data shows that there are persistent gender inequalities in accessing the artist profession. Women are not yet occupying positions of exposure, recognition, and legitimation in the market similar to those of their male counterparts, suggesting that they may face greater obstacles in experiencing successful professional trajectories.

Keywords: inequalities, invisibility of the woman artist, gender, visual arts

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Authors: Aptin Rahnavard, Ghavamaldin Asadian, Khalil Pourshamsian, Mariamalsadat Taghavi

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Dog rose is one of the important rose species in Iran that the distant past had been considered due to nutritional value and medicinal. Despite its long history of use, due to poor information on the genetic modification of plants has been done resources inheritance. In this study was to assess the genetic diversity. Total of 30 genotypes Dog rose from areas of northern Iran in the Caspian region (provinces of Guilan and Mazandaran) were evaluated using 25 RAPD primers. The number of bands produced total of 202 and for each primer were measured in a bands with an average 8-band .The number of polymorphic bands per primer ranged from 1 to 13 and the bands were in the range of 300 to 3000 bp. Based on the results OPA-04 primer with 13 bands and PRA-1, E-09 and A-04 with 5-band were created maximum and minimum number of amplified fragments. Molecular marker genotypes showed a high degree of polymorphism. Studied genotypes based on RAPD results were divided into 2 groups and 2 subgroups. Most similar in subgroups A2 and B group was the lowest.

Keywords: rosa canina spp., RAPD marker, genetic variation, caspian climate

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Authors: Geum Yeon Sim, Jasal Patel, Anand Kumthekar, Stanley Wainapel

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A 65-year-old right-hand dominant African-American man, formerly employed as a security guard, was referred to Rehabilitation Medicine with bilateral hand stiffness and weakness. His past medical history was only significant for myelofibrosis, diagnosed 4 years earlier, for which he was receiving scheduled blood transfusions. Approximately 2 years ago, he began to notice stiffness and swelling in his non-dominant hand that progressed to pain and decreased strength, limiting his hand function. Similar but milder symptoms developed in his right hand several months later. There was no history of prior injury or exposure to cold. Physical examination showed enlargement of metacarpophalangeal (MCP) and proximal interphalangeal (PIP) joints with finger flexion contractures, Swan-neck and Boutonniere deformities, and associated joint tenderness. Changes were more prominent in the left hand. X-rays showed mild osteoarthritis of several bilateral PIP joints. Anti-nuclear antibodies, rheumatoid factor, and cyclic citrullinated peptide antibodies were negative. MRI of the hand showed no erosions or synovitis. A rheumatology consultation was obtained, and the cause of his symptoms was attributed to myelofibrosis-related arthropathy with secondary osteoarthritis. The patient was tried on diclofenac cream and received a few courses of Occupational Therapy with limited functional improvement. Primary myelofibrosis (PMF) is a rare myeloproliferative neoplasm characterized by clonal proliferation of myeloid cells with variable morphologic maturity and hematopoietic efficiency. Rheumatic manifestations of malignancies include direct invasion, paraneoplastic presentations, secondary gout, or hypertrophic osteoarthropathy. PMF causes gradual bone marrow fibrosis with extramedullary metaplastic hematopoiesis in the liver, spleen, or lymph nodes. Musculoskeletal symptoms are not common and are not well described in the literature. The first reported case of myelofibrosis related arthritis was seronegative arthritis due to synovial invasion of myeloproliferative elements. Myelofibrosis has been associated with autoimmune diseases such as systemic lupus erythematosus, progressive systemic sclerosis, and rheumatoid arthritis. Gout has been reported in patients with myelofibrosis, and the underlying mechanism is thought to be related to the high turnover of nucleic acids that is greatly augmented in this disease. X-ray findings in these patients usually include erosive arthritis with synovitis. Treatment of underlying PMF is the treatment of choice, along with anti-inflammatory medications. Physicians should be cognizant of recognizing this rare entity in patients with PMF while maintaining clinical suspicion for more common causes of joint deformities, such as rheumatic diseases.

Keywords: myelofibrosis, arthritis, arthralgia, malignancy

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Authors: C. Ramamoorthy, R. Ranga Raj

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In olden days the Ramayana epic depicts the usage of invisible and fuel less aircraft named pushpavimana. The change of color in the reptile family chameleon paves way for the concept of color change phenomenon available in nature. In present scenario the aircrafts are visible so it is easily identified. So there are too many problems from the threatening. Research is still going on about this problem by using Liquid Crystal Display (LCD). Objective of this paper is to find much better to use the concept of invisible aircraft using plasma display through Couple Charged Device camera (CCD), which has a high resolution and can be used for many purposes like spying, defense, etc. Moreover it is cost wise cheap then, escaping the foe viewing.

Keywords: CCD camera, chameleon, invisible, plasma display

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Authors: Karima Sifi, Noureddine Soltani

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Annaba gulf is the most important touristic and economic area located on the east coast of Algeria. However, these fishery resources are threatened by the pollution due to the progress of economic activity. As part of a biomonitoring program on the quality of waters of the Gulf of Annaba, the specific activity of two biomarkers, acetylcholinesterase (AChE) and glutathion S-transferase (GST) has been measured in edible bivalve Donax trunculus. The samples have been collected during the year 2013 in two sites: El Battah, distant from polluted sources, and Sidi Salem, located near the harbor and different industrial waste. The results showed a significant inhibition of AChE activity and a significant increase in the activity of the GST in samples collected from Sidi Salem as compared to El Battah. The inhibition of the AChE and the increase of the GST in Sidi Salem are in relation with the level of exposition of this site to the pollution.

Keywords: Donax trunculus, annaba gulf, acetylcholinesterase, glutathion s-transferase, biomonitoring, pollution

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Authors: Rohit Semwal, Shivam Arora, Saurav, Sangita Roy

Abstract:

This work proposes a supervised framework with deep convolutional neural networks (CNNs) for vision-based sign language recognition of static gestures. Our approach addresses the acquisition and segmentation of correct inputs for the CNN-based classifier. Microsoft Kinect™ sensor, despite complex environmental conditions, can track hands efficiently. Skin Colour based segmentation is applied on cropped images of hands in different poses, used to depict different sign language gestures. The segmented hand images are used as an input for our classifier. The CNN classifier proposed in the paper is able to classify the input images with a high degree of accuracy. The system was trained and tested on 39 static sign language gestures, including 26 letters of the alphabet and 13 commonly used words. This paper includes a problem definition for building the proposed system, which acts as a sign language translator between deaf/mute and the rest of the society. It is then followed by a focus on reviewing existing knowledge in the area and work done by other researchers. It also describes the working principles behind different components of CNNs in brief. The architecture and system design specifications of the proposed system are discussed in the subsequent sections of the paper to give the reader a clear picture of the system in terms of the capability required. The design then gives the top-level details of how the proposed system meets the requirements.

Keywords: sign language, CNN, HCI, segmentation

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Authors: Christian Arcos, Marley Vellasco, Abraham Alcaim

Abstract:

In this paper, we present a wavelet coefficients masking based on Local Binary Patterns (WLBP) approach to enhance the temporal spectra of the wavelet coefficients for speech enhancement. This technique exploits the wavelet denoising scheme, which splits the degraded speech into pyramidal subband components and extracts frequency information without losing temporal information. Speech enhancement in each high-frequency subband is performed by binary labels through the local binary pattern masking that encodes the ratio between the original value of each coefficient and the values of the neighbour coefficients. This approach enhances the high-frequency spectra of the wavelet transform instead of eliminating them through a threshold. A comparative analysis is carried out with conventional speech enhancement algorithms, demonstrating that the proposed technique achieves significant improvements in terms of PESQ, an international recommendation of objective measure for estimating subjective speech quality. Informal listening tests also show that the proposed method in an acoustic context improves the quality of speech, avoiding the annoying musical noise present in other speech enhancement techniques. Experimental results obtained with a DNN based speech recognizer in noisy environments corroborate the superiority of the proposed scheme in the robust speech recognition scenario.

Keywords: binary labels, local binary patterns, mask, wavelet coefficients, speech enhancement, speech recognition

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Authors: Ardawan Mustafa Ismail, Rebaz Sdiq Ismail

Abstract:

The subject of minorities takes an exceptional importance at all levels, around the world, especially those whose population is composed of many nationalities, and this subject became a very affective part in every country for its security, entity and stability, such as the nationality, religion or culture, as a result of internal factors and external influences, and at the same time it became clear that enslaving minorities had become a matter of reality. Which made the rights of minorities one of the legal, political and geographical issues, many attempts emerged that specialists and non-specialists have given the minorities ’problems their realistic solutions away from theorizing and assumption. On this chosen topic, there are many researches that are written in general places, but… It is believed did not see any in-depth studies dealing with the protection of minority rights of the Region of Kurdistan/ Iraq, because in the Region of Kurdistan/ Iraq there are many minorities living in this area, such as: Muslims, Yazidi, Assyrian, Christian, Chaldeans, and others.

Keywords: minority, international law, protection, Kurdistan, people

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