Search results for: support system
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 22898

Search results for: support system

22268 Spatial Relationship of Drug Smuggling Based on Geographic Information System Knowledge Discovery Using Decision Tree Algorithm

Authors: S. Niamkaeo, O. Robert, O. Chaowalit

Abstract:

In this investigation, we focus on discovering spatial relationship of drug smuggling along the northern border of Thailand. Thailand is no longer a drug production site, but Thailand is still one of the major drug trafficking hubs due to its topographic characteristics facilitating drug smuggling from neighboring countries. Our study areas cover three districts (Mae-jan, Mae-fahluang, and Mae-sai) in Chiangrai city and four districts (Chiangdao, Mae-eye, Chaiprakarn, and Wienghang) in Chiangmai city where drug smuggling of methamphetamine crystal and amphetamine occurs mostly. The data on drug smuggling incidents from 2011 to 2017 was collected from several national and local published news. Geo-spatial drug smuggling database was prepared. Decision tree algorithm was applied in order to discover the spatial relationship of factors related to drug smuggling, which was converted into rules using rule-based system. The factors including land use type, smuggling route, season and distance within 500 meters from check points were found that they were related to drug smuggling in terms of rules-based relationship. It was illustrated that drug smuggling was occurred mostly in forest area in winter. Drug smuggling exhibited was discovered mainly along topographic road where check points were not reachable. This spatial relationship of drug smuggling could support the Thai Office of Narcotics Control Board in surveillance drug smuggling.

Keywords: decision tree, drug smuggling, Geographic Information System, GIS knowledge discovery, rule-based system

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22267 Real-Time Land Use and Land Information System in Homagama Divisional Secretariat Division

Authors: Kumara Jayapathma J. H. M. S. S., Dampegama S. D. P. J.

Abstract:

Lands are valuable & limited resource which constantly changes with the growth of the population. An efficient and good land management system is essential to avoid conflicts associated with lands. This paper aims to design the prototype model of a Mobile GIS Land use and Land Information System in real-time. Homagama Divisional Secretariat Division situated in the western province of Sri Lanka was selected as the study area. The prototype model was developed after reviewing related literature. The methodology was consisted of designing and modeling the prototype model into an application running on a mobile platform. The system architecture mainly consists of a Google mapping app for real-time updates with firebase support tools. Thereby, the method of implementation consists of front-end and back-end components. Software tools used in designing applications are Android Studio with JAVA based on GeoJSON File structure. Android Studio with JAVA in GeoJSON File Synchronize to Firebase was found to be the perfect mobile solution for continuously updating Land use and Land Information System (LIS) in real-time in the present scenario. The mobile-based land use and LIS developed in this study are multiple user applications catering to different hierarchy levels such as basic users, supervisory managers, and database administrators. The benefits of this mobile mapping application will help public sector field officers with non-GIS expertise to overcome the land use planning challenges with land use updated in real-time.

Keywords: Android, Firebase, GeoJSON, GIS, JAVA, JSON, LIS, Mobile GIS, real-time, REST API

Procedia PDF Downloads 229
22266 Annual Water Level Simulation Using Support Vector Machine

Authors: Maryam Khalilzadeh Poshtegal, Seyed Ahmad Mirbagheri, Mojtaba Noury

Abstract:

In this paper, by application of the input yearly data of rainfall, temperature and flow to the Urmia Lake, the simulation of water level fluctuation were applied by means of three models. According to the climate change investigation the fluctuation of lakes water level are of high interest. This study investigate data-driven models, support vector machines (SVM), SVM method which is a new regression procedure in water resources are applied to the yearly level data of Lake Urmia that is the biggest and the hyper saline lake in Iran. The evaluated lake levels are found to be in good correlation with the observed values. The results of SVM simulation show better accuracy and implementation. The mean square errors, mean absolute relative errors and determination coefficient statistics are used as comparison criteria.

Keywords: simulation, water level fluctuation, urmia lake, support vector machine

Procedia PDF Downloads 368
22265 Savinglife®: An Educational Technology for Basic and Advanced Cardiovascular Life Support

Authors: Naz Najma, Grace T. M. Dal Sasso, Maria de Lourdes de Souza

Abstract:

The development of information and communication technologies and the accessibility of mobile devices has increased the possibilities of the teaching and learning process anywhere and anytime. Mobile and web application allows the production of constructive teaching and learning models in various educational settings, showing the potential for active learning in nursing. The objective of this study was to present the development of an educational technology (Savinglife®, an app) for learning cardiopulmonary resuscitation and advanced cardiovascular life support training. Savinglife® is a technological production, based on the concept of virtual learning and problem-based learning approach. The study was developed from January 2016 to November 2016, using five phases (analyze, design, develop, implement, evaluate) of the instructional systems development process. The technology presented 10 scenarios and 12 simulations, covering different aspects of basic and advanced cardiac life support. The contents can be accessed in a non-linear way leaving the students free to build their knowledge based on their previous experience. Each scenario is presented through interactive tools such as scenario description, assessment, diagnose, intervention and reevaluation. Animated ECG rhythms, text documents, images and videos are provided to support procedural and active learning considering real life situation. Accessible equally on small to large devices with or without an internet connection, Savinglife® offers a dynamic, interactive and flexible tool, placing students at the center of the learning process. Savinglife® can contribute to the student’s learning in the assessment and management of basic and advanced cardiac life support in a safe and ethical way.

Keywords: problem-based learning, cardiopulmonary resuscitation, nursing education, advanced cardiac life support, educational technology

Procedia PDF Downloads 305
22264 A Challenge to Acquire Serious Victims’ Locations during Acute Period of Giant Disasters

Authors: Keiko Shimazu, Yasuhiro Maida, Tetsuya Sugata, Daisuke Tamakoshi, Kenji Makabe, Haruki Suzuki

Abstract:

In this paper, we report how to acquire serious victims’ locations in the Acute Stage of Large-scale Disasters, in an Emergency Information Network System designed by us. The background of our concept is based on the Great East Japan Earthquake occurred on March 11th, 2011. Through many experiences of national crises caused by earthquakes and tsunamis, we have established advanced communication systems and advanced disaster medical response systems. However, Japan was devastated by huge tsunamis swept a vast area of Tohoku causing a complete breakdown of all the infrastructures including telecommunications. Therefore, we noticed that we need interdisciplinary collaboration between science of disaster medicine, regional administrative sociology, satellite communication technology and systems engineering experts. Communication of emergency information was limited causing a serious delay in the initial rescue and medical operation. For the emergency rescue and medical operations, the most important thing is to identify the number of casualties, their locations and status and to dispatch doctors and rescue workers from multiple organizations. In the case of the Tohoku earthquake, the dispatching mechanism and/or decision support system did not exist to allocate the appropriate number of doctors and locate disaster victims. Even though the doctors and rescue workers from multiple government organizations have their own dedicated communication system, the systems are not interoperable.

Keywords: crisis management, disaster mitigation, messing, MGRS, military grid reference system, satellite communication system

Procedia PDF Downloads 236
22263 Accounting Management Information System for Convenient Shop in Bangkok Thailand

Authors: Anocha Rojanapanich

Abstract:

The purpose of this research is to develop and design an accounting management information system for convenient shop in Bangkok Thailand. The study applied the System Development Life Cycle (SDLC) for development which began with study and analysis of current data, including the existing system. Then, the system was designed and developed to meet users’ requirements via the internet network by use of application software such as My SQL for database management, Product diversity, Apache HTTP Server for Web Server and PHP Hypertext Preprocessor for an interface between web server, database and users. The system was designed into two subsystems as the main system, or system for head office, and the branch system for branch shops. These consisted of three parts which are classified by user management as shop management, inventory management and Point of Sale (POS) management and importance of cost information for decision making also as well as.

Keywords: accounting management information system, convenient shop, cost information for decision making system, development life cycle

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22262 Under the 'Umbrella' Project: A Volunteer-Mentoring Approach for Socially Disadvantaged University Students

Authors: Evridiki Zachopoulou, Vasilis Grammatikopoulos, Michail Vitoulis, Athanasios Gregoriadis

Abstract:

In the last ten years, the recent economic crisis in Greece has decreased the financial ability and strength of several families when it comes to supporting their children’s studies. As a result, the number of students who are significantly delaying or even dropping out of their university studies is constantly increasing. The students who are at greater risk for academic failure are those who are facing various problems and social disadvantages, like health problems, special needs, family poverty or unemployment, single-parent students, immigrant students, etc. The ‘Umbrella’ project is a volunteer-based initiative to tackle this problem at International Hellenic University. The main purpose of the project is to provide support to disadvantaged students at a socio-emotional, academic, and practical level in order to help them complete their undergraduate studies. More specifically, the ‘Umbrella’ project has the following goals: (a) to develop a consulting-supporting network based on volunteering senior students, called ‘i-mentors’. (b) to train the volunteering i-mentors and create a systematic and consistent support procedure for students at-risk, (c), to develop a service that, parallel to the i-mentor network will be ensuring opportunities for at-risk students to find a job, (d) to support students who are coping with accessibility difficulties, (e) to secure the sustainability of the ‘Umbrella’ project after the completion of the funding of the project. The innovation of the Umbrella project is in its holistic-person-centered approach that will be providing individualized support -via the i-mentors network- to any disadvantaged student that will come ‘under the Umbrella.’

Keywords: peer mentoring, student support, socially disadvantaged students, volunteerism in higher education

Procedia PDF Downloads 235
22261 The Red Persian Carpet: Iran as Semi-Periphery in China's Belt and Road Initiative-Bound World-System

Authors: Toufic Sarieddine

Abstract:

As the belt and road Initiative (henceforth, BRI) enters its 9th year, Iran and China are forging stronger ties on economic and military fronts, a development which has not only caused alarm in Washington but also risks staining China’s relationships with the oil-rich Gulf monarchies. World-systems theory has been used to examine the impact of the BRI on the current world order, with scholarship split on the capacity of China to emerge as a hegemon contending with the US or even usurping it. This paper argues the emergence of a new China-centered world-system comprised of states/areas and processes participating in the BRI and overlapping with the global world-system under (shaky) US hegemony. This world-system centers around China as core and hegemon via economic domination, capable new institutions (Shanghai Cooperation Council), legal modi operandi, the common goal of infrastructure development to rally support among developing states, and other indicators of hegemony outlined in world-systems theory. In this regard, while states like Pakistan could become peripheries to China in the BRI-bound world-system via large-scale projects such as the China-Pakistan Economic Corridor, Iran has greater capacities and influence in the Middle East, making it superior to a periphery. This paper thus argues that the increasing proximity between Iran and China sees the former becoming a semi-periphery with respect to China within the BRI-bound world-system, having economic dependence on its new core and hegemon while simultaneously wielding political and military influence on weaker states such as Iraq, Lebanon, Yemen, and Syria. The indicators for peripheralization as well as the characteristics of a semi-periphery outlined in world-systems theory are used to examine the current economic, political, and militaristic dimensions of Iran and China’s growing relationship, as well as the trajectory of these dimensions as part of the BRI-bound world-system.

Keywords: belt and road initiative, China, China-Middle East relations, Iran, world-systems analysis

Procedia PDF Downloads 155
22260 Cultural Self-Efficacy of Child Protection Social Workers in Norway: Barriers and Opportunities in Working with Migrant Families

Authors: Justyna Mroczkowska

Abstract:

Social worker's ability to provide culturally sensitive assistance in child protection is taken for granted; given limited training opportunities and lack of clear guidance, practitioners report working with migrant families more demanding in comparison to working with native families. In this study, the author developed and factor analyzed the Norwegian Cultural Self-Efficacy Scale to describe the level of cultural capability among Norwegian child protection professionals. The study aimed to determine the main influencing factors to cultural efficacy and examine the relationship between self-efficacy and perceived difficulty in working with migrant families. The scale was administered to child protection workers in Norway (N=251), and the reliability of the scale measured by Cronbach's alpha coefficient was .904. The confirmatory factor analysis of social work cultural self-efficacy found support for four separate but correlated subscales: Assessment, Communication, Support Request, and Teamwork. Regression analyses found the experience in working with migrant families, training and support from external agencies, and colleague support to be significant predictors of cultural self-efficacy. Self-efficacy in assessment skills and self-efficacy in communication skills were moderately related to the perceived difficulty to work with migrant families. The findings conclude with previous research and highlight the need for both professional development programs and institutional resources to be provided to support the practitioner's preparation for multicultural practice in child protection.

Keywords: child protection, cultural self-efficacy, cultural competency, migration, resources

Procedia PDF Downloads 143
22259 An Efficient Data Mining Technique for Online Stores

Authors: Mohammed Al-Shalabi, Alaa Obeidat

Abstract:

In any food stores, some items will be expired or destroyed because the demand on these items is infrequent, so we need a system that can help the decision maker to make an offer on such items to improve the demand on the items by putting them with some other frequent item and decrease the price to avoid losses. The system generates hundreds or thousands of patterns (offers) for each low demand item, then it uses the association rules (support, confidence) to find the interesting patterns (the best offer to achieve the lowest losses). In this paper, we propose a data mining method for determining the best offer by merging the data mining techniques with the e-commerce strategy. The task is to build a model to predict the best offer. The goal is to maximize the profits of a store and avoid the loss of products. The idea in this paper is the using of the association rules in marketing with a combination with e-commerce.

Keywords: data mining, association rules, confidence, online stores

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22258 Development of Risk Management System for Urban Railroad Underground Structures and Surrounding Ground

Authors: Y. K. Park, B. K. Kim, J. W. Lee, S. J. Lee

Abstract:

To assess the risk of the underground structures and surrounding ground, we collect basic data by the engineering method of measurement, exploration and surveys and, derive the risk through proper analysis and each assessment for urban railroad underground structures and surrounding ground including station inflow. Basic data are obtained by the fiber-optic sensors, MEMS sensors, water quantity/quality sensors, tunnel scanner, ground penetrating radar, light weight deflectometer, and are evaluated if they are more than the proper value or not. Based on these data, we analyze the risk level of urban railroad underground structures and surrounding ground. And we develop the risk management system to manage efficiently these data and to support a convenient interface environment at input/output of data.

Keywords: urban railroad, underground structures, ground subsidence, station inflow, risk

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22257 Implementation of a Photo-Curable 3D Additive Manufacturing Technology with Grey Capability by Using Piezo Ink-jets

Authors: Ming-Jong Tsai, Y. L. Cheng, Y. L. Kuo, S. Y. Hsiao, J. W. Chen, P. H. Liu, D. H. Chen

Abstract:

The 3D printing is a combination of digital technology, material science, intelligent manufacturing and control of opto-mechatronics systems. It is called the third industrial revolution from the view of the Economist Journal. A color 3D printing machine may provide the necessary support for high value-added industrial and commercial design, architectural design, personal boutique, and 3D artist’s creation. The main goal of this paper is to develop photo-curable color 3D manufacturing technology and system implementation. The key technologies include (1) Photo-curable color 3D additive manufacturing processes development and materials research (2) Piezo type ink-jet head control and Opto-mechatronics integration technique of the photo-curable color 3D laminated manufacturing system. The proposed system is integrated with single Piezo type ink-jet head with two individual channels for two primary UV light curable color resins which can provide for future colorful 3D printing solutions. The main research results are 16 grey levels and grey resolution of 75 dpi.

Keywords: 3D printing, additive manufacturing, color, photo-curable, Piezo type ink-jet, UV Resin

Procedia PDF Downloads 561
22256 Analysis Rotor Bearing System Dynamic Interaction with Bearing Supports

Authors: V. T. Ngo, D. M. Xie

Abstract:

Frequently, in the design of machines, some of parameters that directly affect the rotor dynamics of the machines are not accurately known. In particular, bearing stiffness support is one such parameter. One of the most basic principles to grasp in rotor dynamics is the influence of the bearing stiffness on the critical speeds and mode shapes associated with a rotor-bearing system. Taking a rig shafting as an example, this paper studies the lateral vibration of the rotor with multi-degree-of-freedom by using Finite Element Method (FEM). The FEM model is created and the eigenvalues and eigenvectors are calculated and analyzed to find natural frequencies, critical speeds, mode shapes. Then critical speeds and mode shapes are analyzed by set bearing stiffness changes. The model permitted to identify the critical speeds and bearings that have an important influence on the vibration behavior.

Keywords: lateral vibration, finite element method, rig shafting, critical speed

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22255 Context Specific E-Transformation Decision-Making Framework

Authors: A. Hol

Abstract:

Nowadays, within quickly changing business environments, companies are often faced with specific problems where knowledge required to make timely decisions is often available however is not always readily accessible by the decision makers, in a required form. To identify if in any way via innovative system development companies could be assisted so that they can make quicker industry specific decisions in a given time and space, researchers conducted in depth case study investigation during which they studied company’s e-transformation recommendations, company’s current issues and problems as well as the nature of company’s pressing decisions. This study utilizes Scenario Based Analysis with the aim to help identify parameters crucial for the development of the system that could support decision making in a given time and space. Based on the findings, Context Specific e-transformation decision making framework is proposed.

Keywords: e-transformation, business context, decision making, e-T Guide, ICT

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22254 Maternal Adverse Childhood Experiences and Preschool Children’s Behavioural Problems: Mediation via Adult Attachment and Moderation by Maternal Mental Health, Social Support, and Child Sex

Authors: Stefan Kurbatfinski, Aliyah Dosani, Andrew F. Hayes, Deborah Dewey, Nicole Letourneau

Abstract:

Background: Maternal adverse childhood experiences (ACEs) have been associated with internalizing and externalizing behavioral problems in preschool children. However, little is known about the influence of maternal adult attachment patterns on this association. Further, potential moderation by maternal mental health, maternal social support, or child sex is poorly understood. Therefore, this study examined associations between 1) maternal ACEs and preschool children’s behavioural problems, with mediation through maternal attachment patterns and moderation by maternal mental health, maternal social support, and child sex; and 2) maternal attachment patterns and children’s behavioural problems, with mediation through maternal mental health and social support and moderation by child sex. Methods: This secondary analysis used data (n=625) from a high socioeconomic, longitudinally prospective cohort (Alberta Pregnancy Outcomes and Nutrition). Child behaviour (BASC-2) and maternal adult attachment (ECR-Q) were measured at five years of child age, maternal ACEs (ACEs Questionnaire) at around 12 months, and maternal mental health (CESD and SCL-90-R) and social support (SSQ) across various prenatal and postnatal time points. All moderation and mediation analyses occurred through RStudio using PROCESS, interpreting significant interactions through Johnson-Neyman plots. Findings: Maternal ACEs interacted with maternal anxiety symptoms to predict both behavioural problems (pexternalizing=0.007; pinternalizing=0.0159). An indirect pathway via dismissive attachment was moderated by maternal social support ([0.0058, 0.0596]). Attachment patterns predicted all behavioural problems (p<0.05) and interacted with maternal anxiety symptoms to predict internalizing behaviours among male children ([0.0321, 0.1307]; [0.0321, 0.1291]). Interpretation: Maternal attachment patterns may predict children’s behavioural problems more than ACEs. Social support interventions may not always be beneficial for highly dismissively attached mothers. Implications for policy and child health include mandatory sex and gender education for teachers; assessing attachment patterns prior to recommending social support as an intervention; and anxiety-focused interventions for mothers in higher socioeconomic populations.

Keywords: maternal adverse childhood experiences, internalizing behaviours, externalizing behaviours, mediators and moderators, attachment patterns, child health

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22253 Adaptability of Steel-Framed Industrialized Building System In Post-Service Life

Authors: Alireza Taghdiri, Sara Ghanbarzade Ghomi

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Existing buildings are permanently subjected to change, continuously renovated and repaired in their long service life. Old buildings are destroyed and their material and components are recycled or reused for constructing new ones. In this process, the importance of sustainability principles for building construction is obviously known and great significance must be attached to the consumption of resources, resulting effects on the environment and economic costs. Utilization strategies for extending buildings service life and delay in destroying have a positive effect on environment protection. In addition, simpler alterability or expandability of buildings’ structures and reducing energy and natural resources consumption have benefits for users, producers and the environment. To solve these problems, by applying theories of open building, structural components of some conventional building systems have been analyzed and then, a new geometry adaptive building system is developed which can transform and support different imposed loads. In order to achieve this goal, various research methods and tools such as professional and scientific literatures review, comparative analysis, case study and computer simulation were applied and data interpretation was implemented using descriptive statistics and logical arguments. Therefore, hypothesis and proposed strategies were evaluated and an adaptable and reusable 2-dimensional building system was presented which can respond appropriately to dwellers and end-users needs and provide reusability of structural components of building system in new construction or function. Investigations showed that this incremental building system can be successfully applied in achieving the architectural design objectives and by small modifications on components and joints, it is easy to obtain different and adaptable load-optimized component alternatives for flexible spaces.

Keywords: adaptability, durability, open building, service life, structural building system

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22252 Distributed Multi-Agent Based Approach on Intelligent Transportation Network

Authors: Xiao Yihong, Yu Kexin, Burra Venkata Durga Kumar

Abstract:

With the accelerating process of urbanization, the problem of urban road congestion is becoming more and more serious. Intelligent transportation system combining distributed and artificial intelligence has become a research hotspot. As the core development direction of the intelligent transportation system, Cooperative Intelligent Transportation System (C-ITS) integrates advanced information technology and communication methods and realizes the integration of humans, vehicle, roadside infrastructure, and other elements through the multi-agent distributed system. By analyzing the system architecture and technical characteristics of C-ITS, the report proposes a distributed multi-agent C-ITS. The system consists of Roadside Sub-system, Vehicle Sub-system, and Personal Sub-system. At the same time, we explore the scalability of the C-ITS and put forward incorporating local rewards in the centralized training decentralized execution paradigm, hoping to add a scalable value decomposition method. In addition, we also suggest introducing blockchain to improve the safety of the traffic information transmission process. The system is expected to improve vehicle capacity and traffic safety.

Keywords: distributed system, artificial intelligence, multi-agent, cooperative intelligent transportation system

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22251 Looking Forward, Looking Back: A Critical Reflection on the Impact of the Special Needs Assistant Scheme on Inclusionary Practices for Children with Significant Care Needs in the Irish Education System

Authors: C. P. Griffin

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This paper seeks to critically review special educational needs (SEN) policy in the Irish education system since the introduction of the Education Act in 1998. In particular, the author seeks to focus on the impact of SEN policy on inclusionary practices for children with significant care needs in light of the introduction on the Special Needs Assistant (SNA) scheme. Following a systematic review of the literature, the growth of the SNA scheme in Ireland will be critically reviewed. Strengths and weaknesses of the scheme will be forwarded and comparisons drawn between contrasting international models of teaching assistant support. Based on this review, avenues for future research will be forwarded, with the aim of supporting effective inclusionary practices for children with SEN based on evidence-based practice.

Keywords: care needs, inclusion, Ireland, special needs assistants

Procedia PDF Downloads 279
22250 Optimized Deep Learning-Based Facial Emotion Recognition System

Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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22249 Preparation of hydrophobic silica membranes supported on alumina hollow fibers for pervaporation applications

Authors: Ami Okabe, Daisuke Gondo, Akira Ogawa, Yasuhisa Hasegawa, Koichi Sato, Sadao Araki, Hideki Yamamoto

Abstract:

Membrane separation draws attention as the energy-saving technology. Pervaporation (PV) uses hydrophobic ceramic membranes to separate organic compounds from industrial wastewaters. PV makes it possible to separate organic compounds from azeotropic mixtures and from aqueous solutions. For the PV separation of low concentrations of organics from aqueous solutions, hydrophobic ceramic membranes are expected to have high separation performance compared with that of conventional hydrophilic membranes. Membrane separation performance is evaluated based on the pervaporation separation index (PSI), which depends on both the separation factor and the permeate flux. Ingenuity is required to increase the PSI such that the permeate flux increases without reducing the separation factor or to increase the separation factor without reducing the flux. A thin separation layer without defects and pinholes is required. In addition, it is known that the flux can be increased without reducing the separation factor by reducing the diffusion resistance of the membrane support. In a previous study, we prepared hydrophobic silica membranes by a molecular templating sol−gel method using cetyltrimethylammonium bromide (CTAB) to form pores suitable for permitting the passage of organic compounds through the membrane. We separated low-concentration organics from aqueous solutions by PV using these membranes. In the present study, hydrophobic silica membranes were prepared on a porous alumina hollow fiber support that is thinner than the previously used alumina support. Ethyl acetate (EA) is used in large industrial quantities, so it was selected as the organic substance to be separated. Hydrophobic silica membranes were prepared by dip-coating porous alumina supports with a -alumina interlayer into a silica sol containing CTAB and vinyltrimethoxysilane (VTMS) as the silica precursor. Membrane thickness increases with the lifting speed of the sol in the dip-coating process. Different thicknesses of the γ-alumina layer were prepared by dip-coating the support into a boehmite sol at different lifting speeds (0.5, 1, 3, and 5 mm s-1). Silica layers were subsequently formed by dip-coating using an immersion time of 60 s and lifting speed of 1 mm s-1. PV measurements of the EA (5 wt.%)/water system were carried out using VTMS hydrophobic silica membranes prepared on -alumina layers of different thicknesses. Water and EA flux showed substantially constant value despite of the change of the lifting speed to form the γ-alumina interlayer. All prepared hydrophobic silica membranes showed the higher PSI compared with the hydrophobic membranes using the previous alumina support of hollow fiber.

Keywords: membrane separation, pervaporation, hydrophobic, silica

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22248 Radiomics: Approach to Enable Early Diagnosis of Non-Specific Breast Nodules in Contrast-Enhanced Magnetic Resonance Imaging

Authors: N. D'Amico, E. Grossi, B. Colombo, F. Rigiroli, M. Buscema, D. Fazzini, G. Cornalba, S. Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of nodules considered non-specific by expert radiologists, recognized in magnetic resonance mammography (MRm) with T1-weighted (T1w) sequences with paramagnetic contrast. Material and Methods: 47 cases out of 1200 undergoing MRm, in which the MRm assessment gave uncertain classification (non-specific nodules), were admitted to the study. The clinical outcome of the non-specific nodules was later found through follow-up or further exams (biopsy), finding 35 benign and 12 malignant. All MR Images were acquired at 1.5T, a first basal T1w sequence and then four T1w acquisitions after the paramagnetic contrast injection. After a manual segmentation of the lesions, done by a radiologist, and the extraction of 150 radiomic features (30 features per 5 subsequent times) a machine learning (ML) approach was used. An evolutionary algorithm (TWIST system based on KNN algorithm) was used to subdivide the dataset into training and validation test and to select features yielding the maximal amount of information. After this pre-processing, different machine learning systems were applied to develop a predictive model based on a training-testing crossover procedure. 10 cases with a benign nodule (follow-up older than 5 years) and 18 with an evident malignant tumor (clear malignant histological exam) were added to the dataset in order to allow the ML system to better learn from data. Results: NaiveBayes algorithm working on 79 features selected by a TWIST system, resulted to be the best performing ML system with a sensitivity of 96% and a specificity of 78% and a global accuracy of 87% (average values of two training-testing procedures ab-ba). The results showed that in the subset of 47 non-specific nodules, the algorithm predicted the outcome of 45 nodules which an expert radiologist could not identify. Conclusion: In this pilot study we identified a radiomic approach allowing ML systems to perform well in the diagnosis of a non-specific nodule at MR mammography. This algorithm could be a great support for the early diagnosis of malignant breast tumor, in the event the radiologist is not able to identify the kind of lesion and reduces the necessity for long follow-up. Clinical Relevance: This machine learning algorithm could be essential to support the radiologist in early diagnosis of non-specific nodules, in order to avoid strenuous follow-up and painful biopsy for the patient.

Keywords: breast, machine learning, MRI, radiomics

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22247 One-Class Support Vector Machine for Sentiment Analysis of Movie Review Documents

Authors: Chothmal, Basant Agarwal

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Sentiment analysis means to classify a given review document into positive or negative polar document. Sentiment analysis research has been increased tremendously in recent times due to its large number of applications in the industry and academia. Sentiment analysis models can be used to determine the opinion of the user towards any entity or product. E-commerce companies can use sentiment analysis model to improve their products on the basis of users’ opinion. In this paper, we propose a new One-class Support Vector Machine (One-class SVM) based sentiment analysis model for movie review documents. In the proposed approach, we initially extract features from one class of documents, and further test the given documents with the one-class SVM model if a given new test document lies in the model or it is an outlier. Experimental results show the effectiveness of the proposed sentiment analysis model.

Keywords: feature selection methods, machine learning, NB, one-class SVM, sentiment analysis, support vector machine

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22246 An Analytical Metric and Process for Critical Infrastructure Architecture System Availability Determination in Distributed Computing Environments under Infrastructure Attack

Authors: Vincent Andrew Cappellano

Abstract:

In the early phases of critical infrastructure system design, translating distributed computing requirements to an architecture has risk given the multitude of approaches (e.g., cloud, edge, fog). In many systems, a single requirement for system uptime / availability is used to encompass the system’s intended operations. However, when architected systems may perform to those availability requirements only during normal operations and not during component failure, or during outages caused by adversary attacks on critical infrastructure (e.g., physical, cyber). System designers lack a structured method to evaluate availability requirements against candidate system architectures through deep degradation scenarios (i.e., normal ops all the way down to significant damage of communications or physical nodes). This increases risk of poor selection of a candidate architecture due to the absence of insight into true performance for systems that must operate as a piece of critical infrastructure. This research effort proposes a process to analyze critical infrastructure system availability requirements and a candidate set of systems architectures, producing a metric assessing these architectures over a spectrum of degradations to aid in selecting appropriate resilient architectures. To accomplish this effort, a set of simulation and evaluation efforts are undertaken that will process, in an automated way, a set of sample requirements into a set of potential architectures where system functions and capabilities are distributed across nodes. Nodes and links will have specific characteristics and based on sampled requirements, contribute to the overall system functionality, such that as they are impacted/degraded, the impacted functional availability of a system can be determined. A machine learning reinforcement-based agent will structurally impact the nodes, links, and characteristics (e.g., bandwidth, latency) of a given architecture to provide an assessment of system functional uptime/availability under these scenarios. By varying the intensity of the attack and related aspects, we can create a structured method of evaluating the performance of candidate architectures against each other to create a metric rating its resilience to these attack types/strategies. Through multiple simulation iterations, sufficient data will exist to compare this availability metric, and an architectural recommendation against the baseline requirements, in comparison to existing multi-factor computing architectural selection processes. It is intended that this additional data will create an improvement in the matching of resilient critical infrastructure system requirements to the correct architectures and implementations that will support improved operation during times of system degradation due to failures and infrastructure attacks.

Keywords: architecture, resiliency, availability, cyber-attack

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22245 Machine Learning Based Digitalization of Validated Traditional Cognitive Tests and Their Integration to Multi-User Digital Support System for Alzheimer’s Patients

Authors: Ramazan Bakir, Gizem Kayar

Abstract:

It is known that Alzheimer and Dementia are the two most common types of Neurodegenerative diseases and their visibility is getting accelerated for the last couple of years. As the population sees older ages all over the world, researchers expect to see the rate of this acceleration much higher. However, unfortunately, there is no known pharmacological cure for both, although some help to reduce the rate of cognitive decline speed. This is why we encounter with non-pharmacological treatment and tracking methods more for the last five years. Many researchers, including well-known associations and hospitals, lean towards using non-pharmacological methods to support cognitive function and improve the patient’s life quality. As the dementia symptoms related to mind, learning, memory, speaking, problem-solving, social abilities and daily activities gradually worsen over the years, many researchers know that cognitive support should start from the very beginning of the symptoms in order to slow down the decline. At this point, life of a patient and caregiver can be improved with some daily activities and applications. These activities include but not limited to basic word puzzles, daily cleaning activities, taking notes. Later, these activities and their results should be observed carefully and it is only possible during patient/caregiver and M.D. in-person meetings in hospitals. These meetings can be quite time-consuming, exhausting and financially ineffective for hospitals, medical doctors, caregivers and especially for patients. On the other hand, digital support systems are showing positive results for all stakeholders of healthcare systems. This can be observed in countries that started Telemedicine systems. The biggest potential of our system is setting the inter-user communication up in the best possible way. In our project, we propose Machine Learning based digitalization of validated traditional cognitive tests (e.g. MOCA, Afazi, left-right hemisphere), their analyses for high-quality follow-up and communication systems for all stakeholders. R. Bakir and G. Kayar are with Gefeasoft, Inc, R&D – Software Development and Health Technologies company. Emails: ramazan, gizem @ gefeasoft.com This platform has a high potential not only for patient tracking but also for making all stakeholders feel safe through all stages. As the registered hospitals assign corresponding medical doctors to the system, these MDs are able to register their own patients and assign special tasks for each patient. With our integrated machine learning support, MDs are able to track the failure and success rates of each patient and also see general averages among similarly progressed patients. In addition, our platform also supports multi-player technology which helps patients play with their caregivers so that they feel much safer at any point they are uncomfortable. By also gamifying the daily household activities, the patients will be able to repeat their social tasks and we will provide non-pharmacological reminiscence therapy (RT – life review therapy). All collected data will be mined by our data scientists and analyzed meaningfully. In addition, we will also add gamification modules for caregivers based on Naomi Feil’s Validation Therapy. Both are behaving positively to the patient and keeping yourself mentally healthy is important for caregivers. We aim to provide a therapy system based on gamification for them, too. When this project accomplishes all the above-written tasks, patients will have the chance to do many tasks at home remotely and MDs will be able to follow them up very effectively. We propose a complete platform and the whole project is both time and cost-effective for supporting all stakeholders.

Keywords: alzheimer’s, dementia, cognitive functionality, cognitive tests, serious games, machine learning, artificial intelligence, digitalization, non-pharmacological, data analysis, telemedicine, e-health, health-tech, gamification

Procedia PDF Downloads 138
22244 Investigation on Morphologies, Forming Mechanism, Photocatalytic and Electronic Properties of Co-Zn Ferrite Nanostructure Grown on the Reduced Graphene Oxide Support

Authors: Qinglei Liu, Ali Charkhesht, Tiva Sharifi, Ashkan Bahadoran

Abstract:

Graphene sheets are promising nanoscale building blocks as a support material for the dispersion of nanoparticles. In this work, a solvothermal method employed to directly grow Co1-xZnxFe2O4 ferrite nanospheres on graphene oxide support that is subsequently reduced to graphene. The samples morphology, structure and crystallography were investigated using field-emission scanning electron microscopy (FE-SEM) and powder X-ray diffraction (XRD). The influences of the Zn2+ content on photocatalytic activity, electrical conductivity and magnetic property of the samples are also investigated. The results showed that Co1-x Znx Fe2 O4 nanoparticles are dispersed on graphene sheets and obtained nanocomposites are soft magnetic materials. In addition the samples showed excellent photocatalytic activity under visible light irradiation.

Keywords: reduced graphene oxide, ferrite, magnetic nanocomposite, photocatalytic activity, solvothermal method

Procedia PDF Downloads 249
22243 HcDD: The Hybrid Combination of Disk Drives in Active Storage Systems

Authors: Shu Yin, Zhiyang Ding, Jianzhong Huang, Xiaojun Ruan, Xiaomin Zhu, Xiao Qin

Abstract:

Since large-scale and data-intensive applications have been widely deployed, there is a growing demand for high-performance storage systems to support data-intensive applications. Compared with traditional storage systems, next-generation systems will embrace dedicated processor to reduce computational load of host machines and will have hybrid combinations of different storage devices. The advent of flash- memory-based solid state disk has become a critical role in revolutionizing the storage world. However, instead of simply replacing the traditional magnetic hard disk with the solid state disk, it is believed that finding a complementary approach to corporate both of them is more challenging and attractive. This paper explores an idea of active storage, an emerging new storage configuration, in terms of the architecture and design, the parallel processing capability, the cooperation of other machines in cluster computing environment, and a disk configuration, the hybrid combination of different types of disk drives. Experimental results indicate that the proposed HcDD achieves better I/O performance and longer storage system lifespan.

Keywords: arallel storage system, hybrid storage system, data inten- sive, solid state disks, reliability

Procedia PDF Downloads 448
22242 Solar Energy for Decontamination of Ricinus communis

Authors: Elmo Thiago Lins Cöuras Ford, Valentina Alessandra Carvalho do Vale

Abstract:

The solar energy was used as a source of heating in Ricinus communis pie with the objective of eliminating or minimizing the percentage of the poison in it, so that it can be used as animal feed. A solar cylinder and plane collector were used as heating system. In the focal area of the solar concentrator a gutter support endowed with stove effect was placed. Parameters that denote the efficiency of the systems for the proposed objective was analyzed.

Keywords: solar energy, concentrate, Ricinus communis, temperature

Procedia PDF Downloads 424
22241 Real Time Activity Recognition Framework for Health Monitoring Support in Home Environments

Authors: Shaikh Farhad Hossain, Liakot Ali

Abstract:

Technology advances accelerate the quality and type of services provided for health care and especially for monitoring health conditions. Sensors have turned out to be more effective to detect diverse physiological signs and can be worn on the human body utilizing remote correspondence modules. An assortment of programming devices have been created to help in preparing a difference rundown of essential signs by examining and envisioning information produced by different sensors. In this proposition, we presented a Health signs and Activity acknowledgment monitoring system. Utilizing off-the-rack sensors, we executed a movement location system for identifying five sorts of action: falling, lying down, sitting, standing, and walking. The framework collects and analyzes sensory data in real-time, and provides different feedback to the users. In addition, it can generate alerts based on the detected events and store the data collected to a medical server.

Keywords: ADL, SVM, TRIL , MEMS

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22240 Patient Service Improvement in Public Emergency Department Using Discrete Event Simulation

Authors: Dana Mohammed, Fatemah Abdullah, Hawraa Ali, Najat Al-Shaer, Rawan Al-Awadhi, , Magdy Helal

Abstract:

We study the patient service performance at the emergency department of a major Kuwaiti public hospital, using discrete simulation and lean concepts. In addition to the common problems in such health care systems (over crowdedness, facilities planning and usage, scheduling and staffing, capacity planning) the emergency department suffered from several cultural and patient behavioural issues. Those contributed significantly to the system problems and constituted major obstacles in maintaining the performance in control. This led to overly long waiting times and the potential of delaying providing help to critical cases. We utilized the visual management tools to mitigate the impact of the patients’ behaviours and attitudes and improve the logistics inside the system. In addition a proposal is made to automate the date collection and communication within the department using RFID-based barcoding system. Discrete event simulation models were developed as decision support systems; to study the operational problems and assess achieved improvements. The simulation analysis resulted in cutting the patient delays to about 35% of their current values by reallocating and rescheduling the medical staff. Combined with the application of the visual management concepts, this provided the basis to improving patient service without any major investments.

Keywords: simulation, visual management, health care system, patient

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22239 Formal Development of Electronic Identity Card System Using Event-B

Authors: Tomokazu Nagata, Jawid Ahmad Baktash

Abstract:

The goal of this paper is to explore the use of formal methods for Electronic Identity Card System. Nowadays, one of the core research directions in a constantly growing distributed environment is the improvement of the communication process. The responsibility for proper verification becomes crucial. Formal methods can play an essential role in the development and testing of systems. The thesis presents two different methodologies for assessing correctness. Our first approach employs abstract interpretation techniques for creating a trace based model for Electronic Identity Card System. The model was used for building a semi decidable procedure for verifying the system model. We also developed the code for the eID System and can cover three parts login to system sending of Acknowledgment from user side, receiving of all information from server side and log out from system. The new concepts of impasse and spawned sessions that we introduced led our research to original statements about the intruder’s knowledge and eID system coding with respect to secrecy. Furthermore, we demonstrated that there is a bound on the number of sessions needed for the analysis of System.Electronic identity (eID) cards promise to supply a universal, nation-wide mechanism for user authentication. Most European countries have started to deploy eID for government and private sector applications. Are government-issued electronic ID cards the proper way to authenticate users of online services? We use the eID project as a showcase to discuss eID from an application perspective. The new eID card has interesting design features, it is contact-less, it aims to protect people’s privacy to the extent possible, and it supports cryptographically strong mutual authentication between users and services. Privacy features include support for pseudonymous authentication and per service controlled access to individual data items. The article discusses key concepts, the eID infrastructure, observed and expected problems, and open questions. The core technology seems ready for prime time and government projects deploy it to the masses. But application issues may hamper eID adoption for online applications.

Keywords: eID, event-B, Pro-B, formal method, message passing

Procedia PDF Downloads 237