Search results for: network intrusion prevention

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 683

Authors: Deanna Ruano-Meas, Laura Shenkman

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Variances are seen in the way healthcare personnel (HCP) don and doff PPE risking contamination to self and others. By standardizing practice, variances in technique decrease, and so does the risk of contamination. To implement this change, the Model for Improvement will be used. A system change will be developed that will outline the role of the organizational leader’s support of HCP in the proper donning and doffing of PPE. Interventions will include environmental surveys to assess the safety and work situation ensuring a permissible environment, plan audits to confirm consistency, and the assessment of PPE wear for standardization. The change will also include an educational plan that will involve instruction of the current guidelines recommended by the Centers for Disease Control and Prevention (CDC) to all pertinent HCP, and the incorporation of PPE education in yearly educational training. The goal is a standardized practice and a reduced risk of contamination through education and organizational support. Personal protective equipment has had recent attention with the coming of the SARS-CoV-2. The realization that proper technique is important to decreasing contamination of pathogens has led to the revising of current processes.

Keywords: donning and doffing, HAI, infection control, PPE

Procedia PDF Downloads 192

Authors: Ying Han, Yuanxiang Chen, Yongtao Huang, Jia Fu, Kaile Li, Shangjing Lin, Jianguo Yu

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In long-haul and high-speed optical transmission system, the orthogonal frequency division multiplexing (OFDM) signal suffers various linear and non-linear impairments. In recent years, researchers have proposed compensation schemes for specific impairment, and the effects are remarkable. However, different impairment compensation algorithms have caused an increase in transmission delay. With the widespread application of deep neural networks (DNN) in communication, multi-impairment compensation based on DNN will be a promising scheme. In this paper, we propose and apply DNN to compensate multi-impairment of 16-QAM coherent optical OFDM signal, thereby improving the performance of the transmission system. The trained DNN models are applied in the offline digital signal processing (DSP) module of the transmission system. The models can optimize the constellation mapping signals at the transmitter and compensate multi-impairment of the OFDM decoded signal at the receiver. Furthermore, the models reduce the peak to average power ratio (PAPR) of the transmitted OFDM signal and the bit error rate (BER) of the received signal. We verify the effectiveness of the proposed scheme for 16-QAM Coherent Optical OFDM signal and demonstrate and analyze transmission performance in different transmission scenarios. The experimental results show that the PAPR and BER of the transmission system are significantly reduced after using the trained DNN. It shows that the DNN with specific loss function and network structure can optimize the transmitted signal and learn the channel feature and compensate for multi-impairment in fiber transmission effectively.

Keywords: coherent optical OFDM, deep neural network, multi-impairment compensation, optical transmission

Procedia PDF Downloads 139

Authors: Jianwei Qian, Rob Law

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With the expansion of globalization and the increment of market competition, the festival, especially the traditional one, has demonstrated its vitality under the new context. As a new tourist attraction, festivals play a critically important role in promoting the tourism economy, because the organization of a festival can engage more tourists, generate more revenues and win a wider media concern. However, in the current stage of China, traditional festivals as a way to disseminate national culture are undergoing the challenge of foreign festivals and the related culture. Different from those special events created solely for developing economy, traditional festivals have their own culture and connotation. Therefore, it is necessary to conduct a study on not only protecting the tradition, but promoting its development as well. This study conducts a comparative study of the development of China’s Valentine’s Day and Western Valentine’s Day under the Chinese context and centers on newspaper reports in China from 2000 to 2016. Based on the literature, two main research focuses can be established: one is concerned about the festival’s impact and the other is about tourists’ motivation to engage in a festival. Newspaper reports serve as the research discourse and can help cover the two focal points. With the assistance of content mining techniques, semantic networks for both Days are constructed separately to help depict the status quo of these two festivals in China. Based on the networks, two models are established to show the key component system of traditional festivals in the hope of perfecting the positive role festival tourism plays in the promotion of economy and culture. According to the semantic networks, newspaper reports on both festivals have similarities and differences. The difference is mainly reflected in its cultural connotation, because westerners and Chinese may show their love in different ways. Nevertheless, they share more common points in terms of economy, tourism, and society. They also have a similar living environment and stakeholders. Thus, they can be promoted together to revitalize some traditions in China. Three strategies are proposed to realize the aforementioned aim. Firstly, localize international festivals to suit the Chinese context to make it function better. Secondly, facilitate the internationalization process of traditional Chinese festivals to receive more recognition worldwide. Finally, allow traditional festivals to compete with foreign ones to help them learn from each other and elucidate the development of other festivals. It is believed that if all these can be realized, not only the traditional Chinese festivals can obtain a more promising future, but foreign ones are the same as well. Accordingly, the paper can contribute to the theoretical construction of festival images by the presentation of the semantic network. Meanwhile, the identified features and issues of festivals from two different cultures can enlighten the organization and marketing of festivals as a vital tourism activity. In the long run, the study can enhance the festival as a key attraction to keep the sustainable development of both the economy and the society.

Keywords: Chinese context, comparative study, festival tourism, semantic network analysis, valentine’s day

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Authors: Pablo De Macedo Silveira Vallejos

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This article aims to observe autobiographical and visual narrative practices among users on Instagram. In this way, the work proposes to reflect on how image resources are used to develop edited representations of the self in that social network. The research aims to explore the uses of editing and the degrees of fictionalization present on Instagram.

Keywords: autobiography, visual narratives, representation, fiction, social media

Procedia PDF Downloads 70

Authors: Vimal Kumar Dewangan, T. S. Sampath Kumar, Mukesh Doble, Viju Daniel Varghese

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The apatite-based, i.e., calcium-deficient hydroxyapatite (CDHAp) bone cement is well-known potential bone graft/substitute in orthopaedics due to its similar chemical composition with natural bone minerals. Therefore, an easy approach was attempted to fabricate the apatite-based (CDHAp) bone cement with improved injectability, bioresorbability, and macroporosity. In this study, the desired bone cement was developed by mixing the solid phase (consisting of wet chemically synthesized nanocrystalline hydroxyapatite and commercially available (synthetic) tricalcium phosphate) and the liquid phase (consisting of cement binding accelerator with few biopolymers in a dilute acidic solution) along with a liquid porogen as polysorbate or a solid porogen as mannitol (for comparison) in an optimized liquid-to-powder ratio. The fabricated cement sets within clinically preferred setting time (≤20 minutes) are better injectable (>70%) and also stable at ~7.3-7.4 (physiological pH). The CDHAp phased bone cement was resulted by immersing the fabricated after-set cement in phosphate buffer solution and other similar artificial body fluids and incubated at physiological conditions for seven days, confirmed through the X-ray diffraction and Fourier transform-infrared spectroscopy analyses. The so-formed synthetic apatite-based bone cement holds the acceptable compressive strength (within the range of trabecular bone) with average interconnected pores size falls in a macropores range (~50-200μm) inside the cement, verified by scanning electron microscopy (SEM), mercury intrusion porosimetry and micro-CT analysis techniques. Also, it is biodegradable (degrades ~19-22% within 10-12 weeks) when incubated in artificial body fluids under physiological conditions. The biocompatibility study of the bone cement, when incubated with MG63 cells, shows a significant increase in the cell viability after 3rd day of incubation compared with the control, and the cells were well-attached and spread completely on the surface of the bone cement, confirmed through SEM and fluorescence microscopy analyses. With this all, we can conclude that the developed synthetic macroporous apatite-based bone cement may have the potential to become promising material used as a trabecular bone substitute.

Keywords: calcium deficient hydroxyapatite, synthetic apatite-based bone cement, injectability, macroporosity, trabecular bone substitute

Procedia PDF Downloads 82

Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

Procedia PDF Downloads 125

Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: healthcare, settlement strategy, urban health, rural

Procedia PDF Downloads 358

Authors: Maryam Zarabian, Hector Guzman, Pedro Pereira-Almao, Abraham Fapojuwo

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Dry reforming of methane (DRM) has sparked significant industrial and scientific interest not only as a viable alternative for addressing the environmental concerns of two main contributors of the greenhouse effect, i.e., carbon dioxide (CO₂) and methane (CH₄), but also produces syngas, i.e., a mixture of hydrogen (H₂) and carbon monoxide (CO) utilized by a wide range of downstream processes as a feedstock for other chemical productions. In this study, we develop an AI-enable syngas production model to tackle the problem of achieving an equivalent H₂/CO ratio [1:1] with respect to the most efficient conversion. Firstly, the unsupervised density-based spatial clustering of applications with noise (DBSAN) algorithm removes outlier data points from the original experimental dataset. Then, random forest (RF) and deep neural network (DNN) models employ the error-free dataset to predict the DRM results. DNN models inherently would not be able to obtain accurate predictions without a huge dataset. To cope with this limitation, we employ reusing pre-trained layers’ approaches such as transfer learning and greedy layer-wise pretraining. Compared to the other deep models (i.e., pure deep model and transferred deep model), the greedy layer-wise pre-trained deep model provides the most accurate prediction as well as similar accuracy to the RF model with R² values 1.00, 0.999, 0.999, 0.999, 0.999, and 0.999 for the total outlet flow, H₂/CO ratio, H₂ yield, CO yield, CH₄ conversion, and CO₂ conversion outputs, respectively.

Keywords: artificial intelligence, dry reforming of methane, artificial neural network, deep learning, machine learning, transfer learning, greedy layer-wise pretraining

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Authors: Muhammad Hanif Amiri, Edris Sadeqy, Ahmad Freed Osman

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International Conference on Architectural Engineering and Skyscraper (ICAES 2016) on January 18 - 19, 2016 is aimed to exchange new ideas and application experiences face to face, to establish business or research relations and to find global partners for future collaboration. Therefore, we are very keen to participate and share our issues in order to get valuable feedbacks of the conference participants. Urbanization is a controversial issue all around the world. Substandard and unplanned urbanization has many implications on a social, cultural and economic situation of population life. Unplanned and illegal construction has become a critical issue in Afghanistan particularly Kabul city. In addition, lack of municipal bylaws, poor municipal governance, lack of development policies and strategies, budget limitation, low professional capacity of ainvolved private sector in development and poor coordination among stakeholders are the other factors which made the problem more complicated. The main purpose of this research paper is to review urbanization pattern of Kabul city and find out the improvement solutions and to evaluate the increasing of population density which caused vast illegal and unplanned development which finally converts the Kabul city to a slam area as the whole. The Kabul city Master Plan was reviewed in the year 1978 and revised for the planned 2million population. In 2001, the interim administration took place and the city became influx of returnees from neighbor countries and other provinces of Afghanistan mostly for the purpose of employment opportunities, security and better quality of life, therefore, Kabul faced with strange population growth. According to Central Statistics Organization of Afghanistan population of Kabul has been estimated approx. 5 million (2015), however a new Master Plan has been prepared in 2009, but the existing challenges have not been dissolved yet. On the other hand, 70% of Kabul population is living in unplanned (slam) area and facing the shortage of drinking water, inexistence of sewerage and drainage network, inexistence of proper management system for solid waste collection, lack of public transportation and traffic management, environmental degradation and the shortage of social infrastructure. Although there are many problems in Kabul city, but still the development of 22 townships are in progress which caused the great attraction of population. The research is completed with a detailed analysis on four main issues such as elimination of duplicated administrations, Development of regions, Rehabilitation and improvement of infrastructure, and prevention of new townships establishment in Kabul Central Core in order to mitigate the problems and constraints which are the foundation and principal to find the point of departure for an objective based future development of Kabul city. The closure has been defined to reflect the stage-wise development in light of prepared policy and strategies, development of a procedure for the improvement of infrastructure, conducting a preliminary EIA, defining scope of stakeholder’s contribution and preparation of project list for initial development. In conclusion this paper will help the transformation of Kabul city.

Keywords: development of regions, illegal construction, population density, urbanization pattern

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Authors: Matthias Haenisch, Katharina Hermann, Marc Godau, Verena Weidner

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Over the past two decades, international music education has been characterized by a growing interest in informal learning for formal contexts and a "compositional turn" that has moved from closed to open forms of composing. This change occurs under social and technological conditions that permeate 21st-century musical practices. This forms the background of Musical Communities in the (Post)Digital Age (MusCoDA), a four-year joint research project of the University of Erfurt (UE) and the University of Education Karlsruhe (PHK), funded by the German Federal Ministry of Education and Research (BMBF). Both explore songwriting processes as an example of collective creativity in (post)digital communities, one in formal and the other in informal learning contexts. Collective songwriting will be studied from a network perspective, that will allow us to view boundaries between both online and offline as well as formal and informal or hybrid contexts as permeable and to reconstruct musical learning practices. By comparing these songwriting processes, possibilities for a pedagogical-didactic interweaving of different educational worlds are highlighted. Therefore, the subproject of the University of Erfurt investigates school music lessons with the help of interviews, videography, and network maps by analyzing new digital pedagogical and didactic possibilities. In the first step, the international literature on songwriting in the music classroom was examined for design development. The analysis focused on the question of which methods and practices are circulating in the current literature. Results from this stage of the project form the basis for the first instructional design that will help teachers in planning regular music classes and subsequently reconstruct musical learning practices under these conditions. In analyzing the literature, we noticed certain structural methods and concepts that recur, such as the Building Blocks method and the pre-structuring of the songwriting process. From these findings, we developed a deck of cards that both captures the current state of research and serves as a method for design development. With this deck of cards, both teachers and students themselves can plan their individual songwriting lessons by independently selecting and arranging topic, structure, and action cards. In terms of science communication, music educators' interactions with the card game provide us with essential insights for developing the first design. The overall goal of MusCoDA is to develop an empirical model of collective musical creativity and learning and an instructional design for teaching music in the postdigital age.

Keywords: card game, collective songwriting, community of practice, network, postdigital

Procedia PDF Downloads 59

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of cross-linked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: redox enzyme, nanomaterials, biosensors, electrical communication

Procedia PDF Downloads 452

Authors: Gabriela Estrada, Joaquim Lloveras

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Design for error-proofing assembly is a new DFX approach to prevent assembly issues since early design stages. Assembly issues that can happen during the life phases of a system such as: production, installation, operation, and replacement phases. This prevention is possible by designing the product with poka-yoke or error-proofing characteristics. This approach guide designers to make decisions based on poka-yoke assembly design requirements. As a result of applying these requirements designers are able to create solutions to prevent assembly issues for the product in development stage. This paper integrates the needs to design products in an error proofing way into the systematic approach of design process by Pahl and Beitz. A case study is presented applying this approach.

Keywords: poka-yoke, error-proofing, assembly issues, design process, life phases of a system

Procedia PDF Downloads 369

Authors: Gabriela Estrada, Joaquim Lloveras

Abstract:

Design for error-proofing assembly is a new DFX approach to prevent assembly issues since early design stages. Assembly issues that can happen during the life phases of a system such as: production, installation, operation and replacement phases. This prevention is possible by designing the product with poka-yoke or error-proofing characteristics. This approach guide designers to make decisions based on poka-yoke assembly design requirements. As a result of applying these requirements designers are able to create solutions to prevent assembly issues for the product in development stage. This paper integrates the needs to design products in an error proofing way into the systematic approach of design process by Pahl and Beitz. A case study is presented applying this approach.

Keywords: poka-yoke, error-proofing, assembly issues, design process, life phases of a system

Procedia PDF Downloads 317

Authors: Huamin Xu, Wenting Jia, Hong Jiang, Junxia Xie

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Rosmarinic acid (RA) is a natural acid that is found in a variety of herbs, such as rosemary and has multiple biological activities such as antioxidative, anti-inflammatory and antiviral activities. In this study, we investigated the neuroprotective effects of RA on dopaminergic system in 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP) induced mouse model of Parkinson’s disease (PD). The mice received oral administration of RA before MPTP injection. Results showed that the tyrosine hydroxylase expression in SN reduced and the levels of dopamine and its metabolites in the striatum decreased in MPTP intoxicated PD mice. Pretreatment with RA significantly inhibited these changes. Further studies demonstrated that MPTP treatment increased the iron content, which was counteracted by pre-treatment with RA. In addition, RA could restore the decrease of superoxide dismutase (SOD) induced by MPTP. This study provides evidence that RA could suppress MPTP-induced degeneration of the nigrostriatal dopaminergic system by regulating iron content and the expression of SOD. Thus, RA might be clinically evaluated for the prevention of neurodegenerative diseases.

Keywords: rosmarinic acid, Parkinson's disease, MPTP, dopaminergic system

Procedia PDF Downloads 196

Authors: Thitaporn Thoopputra, Tipaporn Pongmesa, Shuchuen Li

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Aims: To evaluate the application of non-invasive diabetes risk assessment tool in community pharmacy setting. Methods: Thai diabetes risk score was applied to assess individuals at risk of developing type 2 diabetes. Interactive computer-based risk screening (IT) and paper-based risk screening (PT) tools were applied. Participants aged over 25 years with no known diabetes were recruited in six participating pharmacies. Results: A total of 187 clients, mean aged (+SD) was 48.6 (+10.9) years. 35% were at high risk. The mean value of willingness-to-pay for the service fee in IT group was significantly higher than PT group (p=0.013). No significant difference observed for the satisfaction between groups. Conclusions: Non-invasive risk assessment tool, whether paper-based or computerized-based can be applied in community pharmacy to support the enhancing role of pharmacists in chronic disease management. Long term follow up is needed to determine the impact of its application in clinical, humanistic and economic outcomes.

Keywords: community pharmacy, intervention, prevention, risk assessment, type 2 diabetes

Procedia PDF Downloads 507

Authors: A. K. M. Kafi, S. N. Nina, Mashitah M. Yusoff

Abstract:

In this work, we have described a new 3-dimensional (3D) network of crosslinked Horseradish Peroxidase/Carbon Nanotube (HRP/CNT) on a thiol-modified Au surface in order to build up the effective electrical wiring of the enzyme units with the electrode. This was achieved by the electropolymerization of aniline-functionalized carbon nanotubes (CNTs) and 4-aminothiophenol -modified-HRP on a 4-aminothiophenol monolayer-modified Au electrode. The synthesized 3D HRP/CNT networks were characterized with cyclic voltammetry and amperometry, resulting the establishment direct electron transfer between the redox active unit of HRP and the Au surface. Electrochemical measurements reveal that the immobilized HRP exhibits high biological activity and stability and a quasi-reversible redox peak of the redox center of HRP was observed at about −0.355 and −0.275 V vs. Ag/AgCl. The electron transfer rate constant, KS and electron transfer co-efficient were found to be 0.57 s-1 and 0.42, respectively. Based on the electrocatalytic process by direct electrochemistry of HRP, a biosensor for detecting H2O2 was developed. The developed biosensor exhibits excellent electrocatalytic activity for the reduction of H2O2. The proposed biosensor modified with HRP/CNT 3D network displays a broader linear range and a lower detection limit for H2O2 determination. The linear range is from 1.0×10−7 to 1.2×10−4M with a detection limit of 2.2.0×10−8M at 3σ. Moreover, this biosensor exhibits very high sensitivity, good reproducibility and long-time stability. In summary, ease of fabrication, a low cost, fast response and high sensitivity are the main advantages of the new biosensor proposed in this study. These obvious advantages would really help for the real analytical applicability of the proposed biosensor.

Keywords: biosensor, nanomaterials, redox enzyme, thiol-modified Au surface

Procedia PDF Downloads 325

Authors: Nasibeh Mohammadpour, Ali Rajabzadeh, Adel Azar, Hamid Zargham Borujeni,

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Generally, various industries development depends on their stakeholders and beneficiaries supports. One of the most important stakeholders in tourism industry ( which has become one of the most important lucrative and employment-generating activities at the international level these days) are host communities in tourist destination which are affected and effect on this industry development. Recognizing host community and its segmentations can be important to get their support for future decisions and policy making. In order to identify these segments, in this study, clustering of the residents has been done by using some tools that are designed to encounter human complexities and have ability to model and generalize complex systems without any needs for the initial clusters’ seeds like classic methods. Neural networks can help to meet these expectations. The research have been planned to design neural networks-based mathematical model for clustering the host community effectively according to multi criteria, and identifies differences among segments. In order to achieve this goal, the residents’ segmentation has been done by demographic characteristics, their attitude towards the tourism development, the level of satisfaction and the type of their support in this field. The applied method is self-organized neural networks and the results have compared with K-means. As the results show, the use of Self- Organized Map (SOM) method provides much better results by considering the Cophenetic correlation and between clusters variance coefficients. Based on these criteria, the host community is divided into five sections with unique and distinctive features, which are in the best condition (in comparison other modes) according to Cophenetic correlation coefficient of 0.8769 and between clusters variance of 0.1412.

Keywords: Artificial Nural Network, Clustering , Resident, SOM, Tourism

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Authors: K. M. G. T. R. Waidyarathna, S. M. Vidanagamachchi

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Public Health System exists in Sri Lanka has a satisfactory complete information flow when compared to other systems in developing countries. The availability of a good health information system contributed immensely to achieve health indices that are in line with the developed countries like US and UK. The health information flow at the moment is completely paper based. In Sri Lanka, the fields like banking, accounting and engineering have incorporated information and communication technology to the same extent that can be observed in any other country. The field of medicine has behind those fields throughout the world mainly due to its complexity, issues like privacy, confidentially and lack of people with knowledge in both fields of Information Technology (IT) and Medicine. Sri Lanka’s situation is much worse and the gap is rapidly increasing with huge IT initiatives by private-public partnerships in all other countries. The major goal of the framework is to support minimizing the spreading diseases. To achieve that a web based framework should be implemented for this application domain with web mapping. The aim of this GIS based public health system is a secure, flexible, easy to maintain environment for creating and maintaining public health records and easy to interact with relevant parties.

Keywords: DHIS2, GIS, public health, Sri Lanka

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Authors: Mohammad Sadeghi

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The subject matter of this article is the efficiency of current knowledge standard to afford the legal integration regarding criteria and approaches to ISP knowledge standards, to shield ISP and copyright, trademark and other parties’ rights in the online information society. The EU recognizes the knowledge-based liability for intermediaries in the European Directive on Electronic Commerce, but the implication of all parties’ responsibility for combating infringement has been immolated by dominating attention on liability due to the lack of the appropriate legal mechanism to devote each party responsibility. Moreover, there is legal challenge on the applicability of knowledge-based liability on hosting services and information location tools service. The aim of this contribution is to discuss the advantages and disadvantages of ECD knowledge standard through case law with a special emphasis on duty of prevention and constructive knowledge role on internet service providers (ISP s’) to achieve fair balance between all parties rights.

Keywords: internet service providers, liability, copyright infringement, hosting, caching, mere conduit service, notice and takedown, E-commerce Directive

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Authors: S. A. Naeini, M. Hamidzadeh

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Today, with the daily advancement of geotechnical engineering on soil improvement and modification of the physical properties and shear strength of soil, it is now possible to construct structures with high-volume and high service load on loose sandy soils. One of such methods is using micropiles, which are mostly used to control asymmetrical subsidence, increase bearing capacity, and prevent soil liquefaction. This study examined the improvement of Anzali's saturated loose silty sand using 192 micropiles with a length of 8 meters and diameter of 75 mm. Bandar-e Anzali is one of Iran's coastal populated cities which are located in a high-seismicity region. The effects of the insertion of micropiles on prevention of liquefaction and improvement of subsidence were examined through comparison of the results of Standard Penetration Test (SPT) and Plate Load Test (PLT) before and after implementation of the micropiles. The results show that the SPT values and the ultimate bearing capacity of silty sand increased after the implementation of the micropiles. Therefore, the installation of micropiles increases the strength of silty sand improving the resistance of soil against liquefaction.

Keywords: soil improvement, silty sand, micropiles, SPT, PLT, strength

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Authors: Van-Thanh Ho, Jaiyoung Ryu

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In soft robotics, the optimization of fluid dynamics through pneumatic methods plays a pivotal role in enhancing operational efficiency and reducing energy loss. This is particularly crucial when replacing conventional techniques such as cable-driven electromechanical systems. The pneumatic model employed in this study represents a sophisticated framework designed to efficiently channel pressure from a high-pressure reservoir to various muscle locations on the robot's body. This intricate network involves a branching system of tubes. The study introduces a comprehensive pneumatic model, encompassing the components of a reservoir, tubes, and Pneumatically Actuated Muscles (PAM). The development of this model is rooted in the principles of shock tube theory. Notably, the study leverages experimental data to enhance the understanding of the interplay between the PAM structure and the surrounding fluid. This improved interactive approach involves the use of morphing motion, guided by a contraction function. The study's findings demonstrate a high degree of accuracy in predicting pressure distribution within the PAM. The model's predictive capabilities ensure that the error in comparison to experimental data remains below a threshold of 10%. Additionally, the research employs a machine learning model, specifically a surrogate model based on the Kriging method, to assess and quantify uncertainty factors related to the initial reservoir pressure and tube diameter. This comprehensive approach enhances our understanding of pneumatic soft robotics and its potential for improved operational efficiency.

Keywords: pneumatic artificial muscles, pressure drop, morhing motion, branched network, surrogate model

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Authors: Peng Liu, Maria Justo Alonso, Hans Martin Mathisen

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A theoretical model is developed to evaluate the performance and energy saving potential of an air handling unit integrated with a membrane energy exchanger in cold climates. The recovered sensible and latent heat, fan preheating use for frost prevention and heating energy consumed by heating coil after the ventilator is compared for the air handling unit combined heat and energy exchanger respectively. A concept of coefficient of performance of air handling unit is presented and applied to assess the energy use of air handling unit (AHU) in cold climates. The analytic results indicate downsizing of the preheating coil before exchanger and heating coils after exchanger are expected since the required power to preheat and condition the air is reduced compared to heat exchanger when the MEE is integrated with AHU. Simultaneously, a superior ratio of energy recovered (RER) is obtained from AHU build-in a counter-flow MEE. The AHU with sensible-only heat exchanger has noticeably low RER, around 1 at low outdoor air temperature where the maximum energy rate is desired to condition the severe cold and dry air.

Keywords: membrane energy exchanger, cold climate, energy efficient building, HVAC

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Authors: Manasse Elusma, Thung-Hong Lin, Chun-yin Lee

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The relationship between hunger and war or conflict remains to be discussed. Do wars or conflicts cause hunger and food scarcity, or is the reverse relationship is true? As the world becomes more peaceful and wealthier, some countries are still suffered from hunger and food shortage. So, eradicating hunger calls for a more comprehensive understanding of the relationship between conflict and hunger. Several studies are carried out to detect the importance of conflict or war on food security. Most of these studies, however, perform only descriptive analysis and largely use food security indicators instead of the global hunger index. Few studies have employed cross-country panel data to explicitly analyze the association between conflict and chronic hunger, including hidden hunger. Herein, this study addresses this issue and the knowledge gap. We combine global datasets to build a new panel dataset including 143 countries from 1989 to 2020. This study examines the effect of conflict on hunger with fixed effect models, and the results show that the increase of conflict frequency deteriorates hunger. Peacebuilding efforts and war prevention initiative are required to eradicate global hunger.

Keywords: armed conflict, food scarcity, hidden hunger, hunger, malnutrition

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Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

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Authors: Vanda Božić, Željko Nikač

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Trafficking in children, especially vulnerable victims, is a qualified form of committing the crime of human trafficking, and a special form of abuse and violation of children's rights. Given that trafficking in children is dangerous, but also a specific form of crime in relation to trafficking in human beings, this paper will in the first part indicate the forms of trafficking in children (trafficking in children for sexual exploitation, child pornography, and pedophilia, exploitation of labor, begging, performance of criminal acts, adoption, marriage and participation in armed conflicts). The second part references the international documents which regulate this matter as well as the solutions in national criminal legislations of Republic of Croatia and Republic of Serbia. It points to the essential features and characteristics of the victims, according to sex, age, and citizenship, as well as the age of children at the stage of solicitation and recruitment and the status of the family from which the child comes from. The work includes a special emphasis on international police cooperation in the fight against trafficking in children. Concluding remarks set out proposals de lege ferenda that can be of significant impact, particularly on prevention, and then also on repression in combating this serious crime.

Keywords: trafficking in children, trafficking in human beings, child as a victim of human trafficking, children’s rights

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Authors: Jessica J. Gillies

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Awareness of the tragedy that is human trafficking has increased exponentially over the past two decades. The four pillars widely recognised as global solutions to the problem are prevention, prosecution, protection, and partnership between government and non-government organisations. While ‘sex-trafficking’ initially received major attention, this focus has shifted to other industries that conceal broader experiences of exploitation. However, within the regions of focus for this study, namely Australia and Thailand, trafficking for the purpose of sexual exploitation remains the commonly uncovered narrative of criminal justice investigations. In these regions anti-trafficking action is characterised by government-led prevention and prosecution efforts; whereas protection and reintegration practices have received criticism. Typically, non-government organisations straddle the critical chasm between policy and practice; therefore, they are perfectly positioned to contribute valuable experiential knowledge toward understanding how both sectors can support survivors in the post-trafficking experience. The aim of this research is to inform improved partnerships throughout government and non-government post-trafficking services by illuminating gaps in protection and reintegration initiatives. This research will explore government and non-government responses to human trafficking in Thailand and Australia, in order to understand how meaning is constructed in this context and how the construction of meaning effects survivors in the post-trafficking experience. A qualitative, three-stage methodology was adopted for this study. The initial stage of enquiry consisted of a discursive analysis, in order to deconstruct the broader discourses surrounding human trafficking. The data included empirical papers, grey literature such as publicly available government and non-government reports, and anti-trafficking policy documents. The second and third stages of enquiry will attempt to further explore the findings of the discourse analysis and will focus more specifically on protection and reintegration in Australia and Thailand. Stages two and three will incorporate process observations in government and non-government survivor support services, and semi-structured interviews with employees and volunteers within these settings. Two key findings emerged from the discursive analysis. The first exposed conflicting feminist arguments embedded throughout anti-trafficking discourse. Informed by conflicting feminist discourses on sex-work, a discursive relationship has been constructed between sex-industry policy and anti-trafficking policy. In response to this finding, data emerging from the process observations and semi-structured interviews will be interpreted using a feminist theoretical framework. The second finding progresses from the construction in the first. The discursive construction of sex-trafficking appears to have had influence over perceptions of the legitimacy of survivors, and therefore the support they receive in the post-trafficking experience. For example; women who willingly migrate for employment in the sex-industry, and on arrival are faced with exploitative conditions, are not perceived to be deserving of the same support as a woman who is not coerced, but rather physically forced, into such circumstances, yet both meet the criteria for a victim of human trafficking. The forthcoming study is intended to contribute toward building knowledge and understanding around the implications of the construction of legitimacy; and contextualise this in reference to government led protection and reintegration support services for survivors in the post-trafficking experience.

Keywords: Australia, government, human trafficking, non-government, reintegration, Thailand

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Authors: S. W. Liu, J. H. Lv, W. Z. Wang

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In recent years, the failure accidents in petrochemical industry have been frequent, and have posed great security problems in personnel and property. The improvement of petrochemical safety is highly requested in order to prevent re-occurrence of severe accident. This study focuses on surveying the failure cases occurred in petrochemical field, which were extracted from journals of engineering failure, including engineering failure analysis and case studies in engineering failure analysis. The relation of failure mode, failure mechanism, type of components, and type of materials was analyzed in this study. And the analytical results showed that failures occurred more frequently in vessels and piping among the petrochemical equipment. Moreover, equipment made of carbon steel and stainless steel accounts for the majority of failures compared to other materials. This may be related to the application of the equipment and the performance of the material. In addition, corrosion failures were the largest in number of occurrence in the failure of petrochemical equipment, in which stress corrosion cracking accounts for a large proportion. This may have a lot to do with the service environment of the petrochemical equipment. Therefore, it can be concluded that the corrosion prevention of petrochemical equipment is particularly important.

Keywords: cases analysis, corrosion, failure, petrochemical industry

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Authors: V. Saccà, A. Sarica, F. Novellino, S. Barone, T. Tallarico, E. Filippelli, A. Granata, P. Valentino, A. Quattrone

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The work aim was to evaluate how well Random Forest (RF) and Support Vector Machine (SVM) algorithms could support the early diagnosis of Multiple Sclerosis (MS) from resting-state functional connectivity data. In particular, we wanted to explore the ability in distinguishing between controls and patients of mean signals extracted from ICA components corresponding to 15 well-known networks. Eighteen patients with early-MS (mean-age 37.42±8.11, 9 females) were recruited according to McDonald and Polman, and matched for demographic variables with 19 healthy controls (mean-age 37.55±14.76, 10 females). MRI was acquired by a 3T scanner with 8-channel head coil: (a)whole-brain T1-weighted; (b)conventional T2-weighted; (c)resting-state functional MRI (rsFMRI), 200 volumes. Estimated total lesion load (ml) and number of lesions were calculated using LST-toolbox from the corrected T1 and FLAIR. All rsFMRIs were pre-processed using tools from the FMRIB's Software Library as follows: (1) discarding of the first 5 volumes to remove T1 equilibrium effects, (2) skull-stripping of images, (3) motion and slice-time correction, (4) denoising with high-pass temporal filter (128s), (5) spatial smoothing with a Gaussian kernel of FWHM 8mm. No statistical significant differences (t-test, p < 0.05) were found between the two groups in the mean Euclidian distance and the mean Euler angle. WM and CSF signal together with 6 motion parameters were regressed out from the time series. We applied an independent component analysis (ICA) with the GIFT-toolbox using the Infomax approach with number of components=21. Fifteen mean components were visually identified by two experts. The resulting z-score maps were thresholded and binarized to extract the mean signal of the 15 networks for each subject. Statistical and machine learning analysis were then conducted on this dataset composed of 37 rows (subjects) and 15 features (mean signal in the network) with R language. The dataset was randomly splitted into training (75%) and test sets and two different classifiers were trained: RF and RBF-SVM. We used the intrinsic feature selection of RF, based on the Gini index, and recursive feature elimination (rfe) for the SVM, to obtain a rank of the most predictive variables. Thus, we built two new classifiers only on the most important features and we evaluated the accuracies (with and without feature selection) on test-set. The classifiers, trained on all the features, showed very poor accuracies on training (RF:58.62%, SVM:65.52%) and test sets (RF:62.5%, SVM:50%). Interestingly, when feature selection by RF and rfe-SVM were performed, the most important variable was the sensori-motor network I in both cases. Indeed, with only this network, RF and SVM classifiers reached an accuracy of 87.5% on test-set. More interestingly, the only misclassified patient resulted to have the lowest value of lesion volume. We showed that, with two different classification algorithms and feature selection approaches, the best discriminant network between controls and early MS, was the sensori-motor I. Similar importance values were obtained for the sensori-motor II, cerebellum and working memory networks. These findings, in according to the early manifestation of motor/sensorial deficits in MS, could represent an encouraging step toward the translation to the clinical diagnosis and prognosis.

Keywords: feature selection, machine learning, multiple sclerosis, random forest, support vector machine

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Authors: Burra Vijitha

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A prospective randomized comparative study for the prevention of postoperative nausea and vomiting in the patients undergoing general anesthesia ,for elective laparoscopic surgeries with respect to efficacy and side effects of granisetron and palonosetron. Sixty adult patients of class ASA 1,2 of either sex in age group between 20-70 yrs,scheduled for elective laparoscopic surgeries were selected for the study.Patients were randomly divided into two groups 30 each. Group G: Granisetron group (n=30), 40µg/kg; Group P: Palonosetron group (n=30), 0.075 mg. at end of surgery before extubation group G patients 40 µg/kg of inj.granisetron and group P patients received 0.075 mg of inj.palonosetron slow iv over 30 sec.In post anesthesia care unit, episodes of nausea and vomiting experienced by each patient was recorded by direct questioning the patient .study medication was assessed in terms of incidence of nausea and vomiting during periods of 0-4 hrs,4-12 hrs,12-24 hrs,24-48hrs.our study demonstrated that complete response for those patients who received granisetron were 86.66%,80% and 66.66% ,while those received palonosetron were 100%,86.6%,90% between 0-4hrs,4-12hrs,12-24 hrs. It shows no statistically signidficant differences between the baseline values of hemodynamic variables beween two groups during study. Keywords: Granisetron, nausea, palonosetron, vomiting.

Keywords: granisetron, palonosetron, nausea, vomiting

Procedia PDF Downloads 232