Search results for: adaptive robust rbf neural network approximation
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 7819

Search results for: adaptive robust rbf neural network approximation

4519 Fake Accounts Detection in Twitter Based on Minimum Weighted Feature Set

Authors: Ahmed ElAzab, Amira M. Idrees, Mahmoud A. Mahmoud, Hesham Hefny

Abstract:

Social networking sites such as Twitter and Facebook attracts over 500 million users across the world, for those users, their social life, even their practical life, has become interrelated. Their interaction with social networking has affected their life forever. Accordingly, social networking sites have become among the main channels that are responsible for vast dissemination of different kinds of information during real time events. This popularity in Social networking has led to different problems including the possibility of exposing incorrect information to their users through fake accounts which results to the spread of malicious content during life events. This situation can result to a huge damage in the real world to the society in general including citizens, business entities, and others. In this paper, we present a classification method for detecting fake accounts on Twitter. The study determines the minimized set of the main factors that influence the detection of the fake accounts on Twitter, then the determined factors have been applied using different classification techniques, a comparison of the results for these techniques has been performed and the most accurate algorithm is selected according to the accuracy of the results. The study has been compared with different recent research in the same area, this comparison has proved the accuracy of the proposed study. We claim that this study can be continuously applied on Twitter social network to automatically detect the fake accounts, moreover, the study can be applied on different Social network sites such as Facebook with minor changes according to the nature of the social network which are discussed in this paper.

Keywords: fake accounts detection, classification algorithms, twitter accounts analysis, features based techniques

Procedia PDF Downloads 416
4518 Institutional Quality and Tax Compliance: A Cross-Country Regression Evidence

Authors: Debi Konukcu Onal, Tarkan Cavusoglu

Abstract:

In modern societies, the costs of public goods and services are shared through taxes paid by citizens. However, taxation has always been a frictional issue, as tax obligations are perceived to be a financial burden for taxpayers rather than being merit that fulfills the redistribution, regulation and stabilization functions of the welfare state. The tax compliance literature evolves into discussing why people still pay taxes in systems with low costs of legal enforcement. Related empirical and theoretical works show that a wide range of socially oriented behavioral factors can stimulate voluntary compliance and subversive effects as well. These behavioral motivations are argued to be driven by self-enforcing rules of informal institutions, either independently or through interactions with legal orders set by formal institutions. The main focus of this study is to investigate empirically whether institutional particularities have a significant role in explaining the cross-country differences in the tax noncompliance levels. A part of the controversy about the driving forces behind tax noncompliance may be attributed to the lack of empirical evidence. Thus, this study aims to fill this gap through regression estimates, which help to trace the link between institutional quality and noncompliance on a cross-country basis. Tax evasion estimates of Buehn and Schneider is used as the proxy measure for the tax noncompliance levels. Institutional quality is quantified by three different indicators (percentile ranks of Worldwide Governance Indicators, ratings of the International Country Risk Guide, and the country ratings of the Freedom in the World). Robust Least Squares and Threshold Regression estimates based on the sample of the Organization for Economic Co-operation and Development (OECD) countries imply that tax compliance increases with institutional quality. Moreover, a threshold-based asymmetry is detected in the effect of institutional quality on tax noncompliance. That is, the negative effects of tax burdens on compliance are found to be more pronounced in countries with institutional quality below a certain threshold. These findings are robust to all alternative indicators of institutional quality, supporting the significant interaction of societal values with the individual taxpayer decisions.

Keywords: institutional quality, OECD economies, tax compliance, tax evasion

Procedia PDF Downloads 134
4517 Development of a Secured Telemedical System Using Biometric Feature

Authors: O. Iyare, A. H. Afolayan, O. T. Oluwadare, B. K. Alese

Abstract:

Access to advanced medical services has been one of the medical challenges faced by our present society especially in distant geographical locations which may be inaccessible. Then the need for telemedicine arises through which live videos of a doctor can be streamed to a patient located anywhere in the world at any time. Patients’ medical records contain very sensitive information which should not be made accessible to unauthorized people in order to protect privacy, integrity and confidentiality. This research work focuses on a more robust security measure which is biometric (fingerprint) as a form of access control to data of patients by the medical specialist/practitioner.

Keywords: biometrics, telemedicine, privacy, patient information

Procedia PDF Downloads 289
4516 Numerical Methods versus Bjerksund and Stensland Approximations for American Options Pricing

Authors: Marasovic Branka, Aljinovic Zdravka, Poklepovic Tea

Abstract:

Numerical methods like binomial and trinomial trees and finite difference methods can be used to price a wide range of options contracts for which there are no known analytical solutions. American options are the most famous of that kind of options. Besides numerical methods, American options can be valued with the approximation formulas, like Bjerksund-Stensland formulas from 1993 and 2002. When the value of American option is approximated by Bjerksund-Stensland formulas, the computer time spent to carry out that calculation is very short. The computer time spent using numerical methods can vary from less than one second to several minutes or even hours. However to be able to conduct a comparative analysis of numerical methods and Bjerksund-Stensland formulas, we will limit computer calculation time of numerical method to less than one second. Therefore, we ask the question: Which method will be most accurate at nearly the same computer calculation time?

Keywords: Bjerksund and Stensland approximations, computational analysis, finance, options pricing, numerical methods

Procedia PDF Downloads 456
4515 Scheduling in a Single-Stage, Multi-Item Compatible Process Using Multiple Arc Network Model

Authors: Bokkasam Sasidhar, Ibrahim Aljasser

Abstract:

The problem of finding optimal schedules for each equipment in a production process is considered, which consists of a single stage of manufacturing and which can handle different types of products, where changeover for handling one type of product to the other type incurs certain costs. The machine capacity is determined by the upper limit for the quantity that can be processed for each of the products in a set up. The changeover costs increase with the number of set ups and hence to minimize the costs associated with the product changeover, the planning should be such that similar types of products should be processed successively so that the total number of changeovers and in turn the associated set up costs are minimized. The problem of cost minimization is equivalent to the problem of minimizing the number of set ups or equivalently maximizing the capacity utilization in between every set up or maximizing the total capacity utilization. Further, the production is usually planned against customers’ orders, and generally different customers’ orders are assigned one of the two priorities – “normal” or “priority” order. The problem of production planning in such a situation can be formulated into a Multiple Arc Network (MAN) model and can be solved sequentially using the algorithm for maximizing flow along a MAN and the algorithm for maximizing flow along a MAN with priority arcs. The model aims to provide optimal production schedule with an objective of maximizing capacity utilization, so that the customer-wise delivery schedules are fulfilled, keeping in view the customer priorities. Algorithms have been presented for solving the MAN formulation of the production planning with customer priorities. The application of the model is demonstrated through numerical examples.

Keywords: scheduling, maximal flow problem, multiple arc network model, optimization

Procedia PDF Downloads 402
4514 Magnetohydrodynamic Couette Flow of Fractional Burger’s Fluid in an Annulus

Authors: Sani Isa, Ali Musa

Abstract:

Burgers’ fluid with a fractional derivatives model in an annulus was analyzed. Combining appropriately the basic equations, with the fractionalized fractional Burger’s fluid model allow us to determine the velocity field, temperature and shear stress. The governing partial differential equation was solved using the combine Laplace transformation method and Riemann sum approximation to give velocity field, temperature and shear stress on the fluid flow. The influence of various parameters like fractional parameters, relaxation time and retardation time, are drawn. The results obtained are simulated using Mathcad software and presented graphically. From the graphical results, we observed that the relaxation time and time helps the flow pattern, on the other hand, other material constants resist the fluid flow while fractional parameters effect on fluid flow is opposite to each other.

Keywords: sani isa, Ali musaburger’s fluid, Laplace transform, fractional derivatives, annulus

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4513 Microbiological Analysis, Cytotoxic and Genotoxic Effects from Material Captured in PM2.5 and PM10 Filters Used in the Aburrá Valley Air Quality Monitoring Network (Colombia)

Authors: Carmen E. Zapata, Juan Bautista, Olga Montoya, Claudia Moreno, Marisol Suarez, Alejandra Betancur, Duvan Nanclares, Natalia A. Cano

Abstract:

This study aims to evaluate the diversity of microorganisms in filters PM2.5 and PM10; and determine the genotoxic and cytotoxic activity of the complex mixture present in PM2.5 filters used in the Aburrá Valley Air Quality Monitoring Network (Colombia). The research results indicate that particulate matter PM2.5 of different monitoring stations are bacteria; however, this study of detection of bacteria and their phylogenetic relationship is not complete evidence to connect the microorganisms with pathogenic or degrading activities of compounds present in the air. Additionally, it was demonstrated the damage induced by the particulate material in the cell membrane, lysosomal and endosomal membrane and in the mitochondrial metabolism; this damage was independent of the PM2.5 concentrations in almost all the cases.

Keywords: cytotoxic, genotoxic, microbiological analysis, PM10, PM2.5

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4512 Data, Digital Identity and Antitrust Law: An Exploratory Study of Facebook’s Novi Digital Wallet

Authors: Wanjiku Karanja

Abstract:

Facebook has monopoly power in the social networking market. It has grown and entrenched its monopoly power through the capture of its users’ data value chains. However, antitrust law’s consumer welfare roots have prevented it from effectively addressing the role of data capture in Facebook’s market dominance. These regulatory blind spots are augmented in Facebook’s proposed Diem cryptocurrency project and its Novi Digital wallet. Novi, which is Diem’s digital identity component, shall enable Facebook to collect an unprecedented volume of consumer data. Consequently, Novi has seismic implications on internet identity as the network effects of Facebook’s large user base could establish it as the de facto internet identity layer. Moreover, the large tracts of data Facebook shall collect through Novi shall further entrench Facebook's market power. As such, the attendant lock-in effects of this project shall be very difficult to reverse. Urgent regulatory action is therefore required to prevent this expansion of Facebook’s data resources and monopoly power. This research thus highlights the importance of data capture to competition and market health in the social networking industry. It utilizes interviews with key experts to empirically interrogate the impact of Facebook’s data capture and control of its users’ data value chains on its market power. This inquiry is contextualized against Novi’s expansive effect on Facebook’s data value chains. It thus addresses the novel antitrust issues arising at the nexus of Facebook’s monopoly power and the privacy of its users’ data. It also explores the impact of platform design principles, specifically data portability and data portability, in mitigating Facebook’s anti-competitive practices. As such, this study finds that Facebook is a powerful monopoly that dominates the social media industry to the detriment of potential competitors. Facebook derives its power from its size, annexure of the consumer data value chain, and control of its users’ social graphs. Additionally, the platform design principles of data interoperability and data portability are not a panacea to restoring competition in the social networking market. Their success depends on the establishment of robust technical standards and regulatory frameworks.

Keywords: antitrust law, data protection law, data portability, data interoperability, digital identity, Facebook

Procedia PDF Downloads 123
4511 Study of Gait Stability Evaluation Technique Based on Linear Inverted Pendulum Model

Authors: Kang Sungjae

Abstract:

This research proposes a gait stability evaluation technique based on the linear inverted pendulum model and moving support foot Zero Moment Point. With this, an improvement towards the gait analysis of the orthosis walk is validated. The application of Lagrangian mechanics approximation to the solutions of the dynamics equations for the linear inverted pendulum does not only simplify the solution, but it provides a smooth Zero Moment Point for the double feet support phase. The Zero Moment Point gait analysis techniques mentioned above validates reference trajectories for the center of mass of the gait orthosis, the timing of the steps and landing position references for the swing feet. The stability evaluation technique are tested with a 6 DOF powered gait orthosis. The results obtained are promising for implementations.

Keywords: locomotion, center of mass, gait stability, linear inverted pendulum model

Procedia PDF Downloads 517
4510 Structural and Electronic Properties of Cd0.75V0.25S Alloy

Authors: H. Baltache, M. El Amine. Monir, R. Khenata, D. Rached, T. Seddik

Abstract:

The first principles calculations based on the density functional theory (DFT) by using the full-potential linearized augmented plane wave (FP-LAPW) method within the generalized gradient approximation (GGA) in order to investigate the structural and electronic properties of Cd1-xVxS alloy at x = 0.25 in zincblende structure. For the structural properties, we have calculated the equilibrium lattice parameters, such as lattice constant, bulk modulus and first pressure derivatives of the bulk modulus. From the electronic structure, we obtain that Cd0.75V0.25S alloy is nearly half-metallic. The analysis of the density of states (DOS) curves allow to evaluate the spin-exchange splitting energies Δx(d) and Δx(pd) that are generated by V-3d states, where the effective potential for spin-down case is attractive than for spin-up case. Calculations of the exchange constants N0α (valence band) and N0β (conduction band) are served to describe the magnetic behavior of the compounds.

Keywords: first-principles calculations, structural properties, electronic properties

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4509 Integration of Wireless Sensor Networks and Radio Frequency Identification (RFID): An Assesment

Authors: Arslan Murtaza

Abstract:

RFID (Radio Frequency Identification) and WSN (Wireless sensor network) are two significant wireless technologies that have extensive diversity of applications and provide limitless forthcoming potentials. RFID is used to identify existence and location of objects whereas WSN is used to intellect and monitor the environment. Incorporating RFID with WSN not only provides identity and location of an object but also provides information regarding the condition of the object carrying the sensors enabled RFID tag. It can be widely used in stock management, asset tracking, asset counting, security, military, environmental monitoring and forecasting, healthcare, intelligent home, intelligent transport vehicles, warehouse management, and precision agriculture. This assessment presents a brief introduction of RFID, WSN, and integration of WSN and RFID, and then applications related to both RFID and WSN. This assessment also deliberates status of the projects on RFID technology carried out in different computing group projects to be taken on WSN and RFID technology.

Keywords: wireless sensor network, RFID, embedded sensor, Wi-Fi, Bluetooth, integration, time saving, cost efficient

Procedia PDF Downloads 334
4508 Message Framework for Disaster Management: An Application Model for Mines

Authors: A. Baloglu, A. Çınar

Abstract:

Different tools and technologies were implemented for Crisis Response and Management (CRM) which is generally using available network infrastructure for information exchange. Depending on type of disaster or crisis, network infrastructure could be affected and it could not be able to provide reliable connectivity. Thus any tool or technology that depends on the connectivity could not be able to fulfill its functionalities. As a solution, a new message exchange framework has been developed. Framework provides offline/online information exchange platform for CRM Information Systems (CRMIS) and it uses XML compression and packet prioritization algorithms and is based on open source web technologies. By introducing offline capabilities to the web technologies, framework will be able to perform message exchange on unreliable networks. The experiments done on the simulation environment provide promising results on low bandwidth networks (56kbps and 28.8 kbps) with up to 50% packet loss and the solution is to successfully transfer all the information on these low quality networks where the traditional 2 and 3 tier applications failed.

Keywords: crisis response and management, XML messaging, web services, XML compression, mining

Procedia PDF Downloads 339
4507 Distribution Planning with Renewable Energy Units Based on Improved Honey Bee Mating Optimization

Authors: Noradin Ghadimi, Nima Amjady, Oveis Abedinia, Roza Poursoleiman

Abstract:

This paper proposed an Improved Honey Bee Mating Optimization (IHBMO) for a planning paradigm for network upgrade. The proposed technique is a new meta-heuristic algorithm which inspired by mating of the honey bee. The paradigm is able to select amongst several choices equi-cost one assuring the optimum in terms of voltage profile, considering various scenarios of DG penetration and load demand. The distributed generation (DG) has created a challenge and an opportunity for developing various novel technologies in power generation. DG prepares a multitude of services to utilities and consumers, containing standby generation, peaks chopping sufficiency, base load generation. The proposed algorithm is applied over the 30 lines, 28 buses power system. The achieved results demonstrate the good efficiency of the DG using the proposed technique in different scenarios.

Keywords: distributed generation, IHBMO, renewable energy units, network upgrade

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4506 Design and Implementation of Security Middleware for Data Warehouse Signature, Framework

Authors: Mayada Al Meghari

Abstract:

Recently, grid middlewares have provided large integrated use of network resources as the shared data and the CPU to become a virtual supercomputer. In this work, we present the design and implementation of the middleware for Data Warehouse Signature, DWS Framework. The aim of using the middleware in our DWS framework is to achieve the high performance by the parallel computing. This middleware is developed on Alchemi.Net framework to increase the security among the network nodes through the authentication and group-key distribution model. This model achieves the key security and prevents any intermediate attacks in the middleware. This paper presents the flow process structures of the middleware design. In addition, the paper ensures the implementation of security for DWS middleware enhancement with the authentication and group-key distribution model. Finally, from the analysis of other middleware approaches, the developed middleware of DWS framework is the optimal solution of a complete covering of security issues.

Keywords: middleware, parallel computing, data warehouse, security, group-key, high performance

Procedia PDF Downloads 119
4505 Improve Divers Tracking and Classification in Sonar Images Using Robust Diver Wake Detection Algorithm

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

Procedia PDF Downloads 238
4504 Personalizing Human Physical Life Routines Recognition over Cloud-based Sensor Data via AI and Machine Learning

Authors: Kaushik Sathupadi, Sandesh Achar

Abstract:

Pervasive computing is a growing research field that aims to acknowledge human physical life routines (HPLR) based on body-worn sensors such as MEMS sensors-based technologies. The use of these technologies for human activity recognition is progressively increasing. On the other hand, personalizing human life routines using numerous machine-learning techniques has always been an intriguing topic. In contrast, various methods have demonstrated the ability to recognize basic movement patterns. However, it still needs to be improved to anticipate the dynamics of human living patterns. This study introduces state-of-the-art techniques for recognizing static and dy-namic patterns and forecasting those challenging activities from multi-fused sensors. Further-more, numerous MEMS signals are extracted from one self-annotated IM-WSHA dataset and two benchmarked datasets. First, we acquired raw data is filtered with z-normalization and denoiser methods. Then, we adopted statistical, local binary pattern, auto-regressive model, and intrinsic time scale decomposition major features for feature extraction from different domains. Next, the acquired features are optimized using maximum relevance and minimum redundancy (mRMR). Finally, the artificial neural network is applied to analyze the whole system's performance. As a result, we attained a 90.27% recognition rate for the self-annotated dataset, while the HARTH and KU-HAR achieved 83% on nine living activities and 90.94% on 18 static and dynamic routines. Thus, the proposed HPLR system outperformed other state-of-the-art systems when evaluated with other methods in the literature.

Keywords: artificial intelligence, machine learning, gait analysis, local binary pattern (LBP), statistical features, micro-electro-mechanical systems (MEMS), maximum relevance and minimum re-dundancy (MRMR)

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4503 Data Compression in Ultrasonic Network Communication via Sparse Signal Processing

Authors: Beata Zima, Octavio A. Márquez Reyes, Masoud Mohammadgholiha, Jochen Moll, Luca de Marchi

Abstract:

This document presents the approach of using compressed sensing in signal encoding and information transferring within a guided wave sensor network, comprised of specially designed frequency steerable acoustic transducers (FSATs). Wave propagation in a damaged plate was simulated using commercial FEM-based software COMSOL. Guided waves were excited by means of FSATs, characterized by the special shape of its electrodes, and modeled using PIC255 piezoelectric material. The special shape of the FSAT, allows for focusing wave energy in a certain direction, accordingly to the frequency components of its actuation signal, which makes available a larger monitored area. The process begins when a FSAT detects and records reflection from damage in the structure, this signal is then encoded and prepared for transmission, using a combined approach, based on Compressed Sensing Matching Pursuit and Quadrature Amplitude Modulation (QAM). After codification of the signal is in binary chars the information is transmitted between the nodes in the network. The message reaches the last node, where it is finally decoded and processed, to be used for damage detection and localization purposes. The main aim of the investigation is to determine the location of detected damage using reconstructed signals. The study demonstrates that the special steerable capabilities of FSATs, not only facilitate the detection of damage but also permit transmitting the damage information to a chosen area in a specific direction of the investigated structure.

Keywords: data compression, ultrasonic communication, guided waves, FEM analysis

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4502 A Digital Twin Approach to Support Real-time Situational Awareness and Intelligent Cyber-physical Control in Energy Smart Buildings

Authors: Haowen Xu, Xiaobing Liu, Jin Dong, Jianming Lian

Abstract:

Emerging smart buildings often employ cyberinfrastructure, cyber-physical systems, and Internet of Things (IoT) technologies to increase the automation and responsiveness of building operations for better energy efficiency and lower carbon emission. These operations include the control of Heating, Ventilation, and Air Conditioning (HVAC) and lighting systems, which are often considered a major source of energy consumption in both commercial and residential buildings. Developing energy-saving control models for optimizing HVAC operations usually requires the collection of high-quality instrumental data from iterations of in-situ building experiments, which can be time-consuming and labor-intensive. This abstract describes a digital twin approach to automate building energy experiments for optimizing HVAC operations through the design and development of an adaptive web-based platform. The platform is created to enable (a) automated data acquisition from a variety of IoT-connected HVAC instruments, (b) real-time situational awareness through domain-based visualizations, (c) adaption of HVAC optimization algorithms based on experimental data, (d) sharing of experimental data and model predictive controls through web services, and (e) cyber-physical control of individual instruments in the HVAC system using outputs from different optimization algorithms. Through the digital twin approach, we aim to replicate a real-world building and its HVAC systems in an online computing environment to automate the development of building-specific model predictive controls and collaborative experiments in buildings located in different climate zones in the United States. We present two case studies to demonstrate our platform’s capability for real-time situational awareness and cyber-physical control of the HVAC in the flexible research platforms within the Oak Ridge National Laboratory (ORNL) main campus. Our platform is developed using adaptive and flexible architecture design, rendering the platform generalizable and extendable to support HVAC optimization experiments in different types of buildings across the nation.

Keywords: energy-saving buildings, digital twins, HVAC, cyber-physical system, BIM

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4501 Self in Networks: Public Sphere in the Era of Globalisation

Authors: Sanghamitra Sadhu

Abstract:

A paradigm shift from capitalism to information technology is discerned in the era globalisation. The idea of public sphere, which was theorized in terms of its decline in the wake of the rise of commercial mass media has now emerged as a transnational or global sphere with the discourse being dominated by the ‘network society’. In other words, the dynamic of globalisation has brought about ‘a spatial turn’ in the social and political sciences which is also manifested in the public sphere, Especially the global public sphere. The paper revisits the Habermasian concept of the public sphere and focuses on the various social networking sites with their plausibility to create a virtual global public sphere. Situating Habermas’s notion of the bourgeois public sphere in the present context of global public sphere, it considers the changing dimensions of the public sphere across time and examines the concept of the ‘public’ with its shifting transformation from the concrete collective to the fluid ‘imagined’ category. The paper addresses the problematic of multimodal self-portraiture in the social networking sites as well as various online diaries/journals with an attempt to explore the nuances of the networked self.

Keywords: globalisation, network society, public sphere, self-fashioning, identity, autonomy

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4500 Blockchain’s Feasibility in Military Data Networks

Authors: Brenden M. Shutt, Lubjana Beshaj, Paul L. Goethals, Ambrose Kam

Abstract:

Communication security is of particular interest to military data networks. A relatively novel approach to network security is blockchain, a cryptographically secured distribution ledger with a decentralized consensus mechanism for data transaction processing. Recent advances in blockchain technology have proposed new techniques for both data validation and trust management, as well as different frameworks for managing dataflow. The purpose of this work is to test the feasibility of different blockchain architectures as applied to military command and control networks. Various architectures are tested through discrete-event simulation and the feasibility is determined based upon a blockchain design’s ability to maintain long-term stable performance at industry standards of throughput, network latency, and security. This work proposes a consortium blockchain architecture with a computationally inexpensive consensus mechanism, one that leverages a Proof-of-Identity (PoI) concept and a reputation management mechanism.

Keywords: blockchain, consensus mechanism, discrete-event simulation, fog computing

Procedia PDF Downloads 138
4499 State of the Art on the Recommendation Techniques of Mobile Learning Activities

Authors: Nassim Dennouni, Yvan Peter, Luigi Lancieri, Zohra Slama

Abstract:

The objective of this article is to make a bibliographic study on the recommendation of mobile learning activities that are used as part of the field trip scenarios. Indeed, the recommendation systems are widely used in the context of mobility because they can be used to provide learning activities. These systems should take into account the history of visits and teacher pedagogy to provide adaptive learning according to the instantaneous position of the learner. To achieve this objective, we review the existing literature on field trip scenarios to recommend mobile learning activities.

Keywords: mobile learning, field trip, mobile learning activities, collaborative filtering, recommendation system, point of interest, ACO algorithm

Procedia PDF Downloads 446
4498 Breast Cancer Detection Using Machine Learning Algorithms

Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

Abstract:

In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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4497 Analysis of Anti-Tuberculosis Immune Response Induced in Lungs by Intranasal Immunization with Mycobacterium indicus pranii

Authors: Ananya Gupta, Sangeeta Bhaskar

Abstract:

Mycobacterium indicus pranii (MIP) is a saprophytic mycobacterium. It is a predecessor of M. avium complex (MAC). Whole genome analysis and growth kinetics studies have placed MIP in between pathogenic and non-pathogenic species. It shares significant antigenic repertoire with M. tuberculosis and have unique immunomodulatory properties. MIP provides better protection than BCG against pulmonary tuberculosis in animal models. Immunization with MIP by aerosol route provides significantly higher protection as compared to immunization by subcutaneous (s.c.) route. However, mechanism behind differential protection has not been studied. In this study, using mice model we have evaluated and compared the M.tb specific immune response in lung compartments (airway lumen / lung interstitium) as well as spleen following MIP immunization via nasal (i.n.) and s.c. route. MIP i.n. vaccination resulted in increased seeding of memory T cells (CD4+ and CD8+ T-cells) in the airway lumen. Frequency of CD4+ T cells expressing Th1 migratory marker (CXCR3) and activation marker (CD69) were also high in airway lumen of MIP i.n. group. Significantly high ex vivo secretion of cytokines- IFN-, IL-12, IL-17 and TNF- from cells of airway luminal spaces provides evidence of antigen-specific lung immune response, besides generating systemic immunity comparable to MIP s.c. group. Analysis of T cell response on per cell basis revealed that antigen specific T-cells of MIP i.n. group were functionally superior as higher percentage of these cells simultaneously secreted IFN-gamma, IL-2 and TNF-alpha cytokines as compared to MIP s.c. group. T-cells secreting more than one of the cytokines simultaneously are believed to have robust effector response and crucial for protection, compared with single cytokine secreting T-cells. Adoptive transfer of airway luminal T-cells from MIP i.n. group into trachea of naive B6 mice revealed that MIP induced CD8 T-cells play crucial role in providing long term protection. Thus the study demonstrates that MIP intranasal vaccination induces M.tb specific memory T-cells in the airway lumen that results in an early and robust recall response against M.tb infection.

Keywords: airway lumen, Mycobacterium indicus pranii, Th1 migratory markers, vaccination

Procedia PDF Downloads 187
4496 Design an Architectural Model for Deploying Wireless Sensor Network to Prevent Forest Fire

Authors: Saurabh Shukla, G. N. Pandey

Abstract:

The fires have become the most serious disasters to forest resources and the human environment. In recent years, due to climate change, human activities and other factors the frequency of forest fires has increased considerably. The monitoring and prevention of forest fires have now become a global concern for forest fire prevention organizations. Currently, the methods for forest fire prevention largely consist of patrols, observation from watch towers. Thus, software like deployment of the wireless sensor network to prevent forest fire is being developed to get a better estimate of the temperature and humidity prospects. Now days, wireless sensor networks are beginning to be deployed at an accelerated pace. It is not unrealistic to expect that in coming years the world will be covered with wireless sensor networks. This new technology has lots of unlimited potentials and can be used for numerous application areas including environmental, medical, military, transportation, entertainment, crisis management, homeland defense, and smart spaces.

Keywords: deployment, sensors, wireless sensor networks, forest fires

Procedia PDF Downloads 436
4495 Automatic Classification Using Dynamic Fuzzy C Means Algorithm and Mathematical Morphology: Application in 3D MRI Image

Authors: Abdelkhalek Bakkari

Abstract:

Image segmentation is a critical step in image processing and pattern recognition. In this paper, we proposed a new robust automatic image classification based on a dynamic fuzzy c-means algorithm and mathematical morphology. The proposed segmentation algorithm (DFCM_MM) has been applied to MR perfusion images. The obtained results show the validity and robustness of the proposed approach.

Keywords: segmentation, classification, dynamic, fuzzy c-means, MR image

Procedia PDF Downloads 478
4494 Privacy Policy Prediction for Uploaded Image on Content Sharing Sites

Authors: Pallavi Mane, Nikita Mankar, Shraddha Mazire, Rasika Pashankar

Abstract:

Content sharing sites are very useful in sharing information and images. However, with the increasing demand of content sharing sites privacy and security concern have also increased. There is need to develop a tool for controlling user access to their shared content. Therefore, we are developing an Adaptive Privacy Policy Prediction (A3P) system which is helpful for users to create privacy settings for their images. We propose the two-level framework which assigns the best available privacy policy for the users images according to users available histories on the site.

Keywords: online information services, prediction, security and protection, web based services

Procedia PDF Downloads 358
4493 Fault Diagnosis in Induction Motors Using Discrete Wavelet Transform

Authors: K. Yahia, A. Titaouine, A. Ghoggal, S. E. Zouzou, F. Benchabane

Abstract:

This paper deals with the problem of stator faults diagnosis in induction motors. Using the discrete wavelet transform (DWT) for the current Park’s vector modulus (CPVM) analysis, the inter-turn short-circuit faults diagnosis can be achieved. This method is based on the decomposition of the CPVM signal, where wavelet approximation and detail coefficients of this signal have been extracted. The energy evaluation of a known bandwidth detail permits to define a fault severity factor (FSF). This method has been tested through the simulation of an induction motor using a mathematical model based on the winding-function approach. Simulation, as well as experimental, results show the effectiveness of the used method.

Keywords: Induction Motors (IMs), inter-turn short-circuits diagnosis, Discrete Wavelet Transform (DWT), Current Park’s Vector Modulus (CPVM)

Procedia PDF Downloads 553
4492 Physical Properties of Uranium Dinitride UN2 by Using Density Functional Theory (DFT and DFT+U)

Authors: T. Zergoug, S. E. H. Abaidia, A. Nedjar, M. Y. Mokeddem

Abstract:

Physical properties of uranium di-nitride (UN2) were investigated in detail using first principles calculations based on density functional theory. To treat the strong correlation effects caused by 5f Uranium valence electrons, on-site Coulomb interaction correction via the Hubbard-like term, U (DFT+U) was employed. The UN2 structural, mechanical and thermodynamic properties were calculated within DFT and Various U of DFT+U approach. The Perdew–Burke–Ernzerhof (PBE.5.2) version of the generalized gradient approximation (GGA) is used to describe the exchange-correlation with the projector-augmented wave (PAW) pseudo potentials. A comparative study shows that results are improved by using the Hubbard formalism for a certain U value correction like the structural parameter. For some physical properties the variation versus Hubbard U is strong like Young modulus but for others it is weakly noticeable such as the density of state (DOS) or bulk modulus. We noticed also that up from U=7.5 eV, elastic results become not conform to the cubic cell elastic criteria since the C44 values turn out to be negative.

Keywords: uranium diNitride, UN2, DFT+U, elastic properties

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4491 Network Impact of a Social Innovation Initiative in Rural Areas of Southern Italy

Authors: A. M. Andriano, M. Lombardi, A. Lopolito, M. Prosperi, A. Stasi, E. Iannuzzi

Abstract:

In according to the scientific debate on the definition of Social Innovation (SI), the present paper identifies SI as new ideas (products, services, and models) that simultaneously meet social needs and create new social relationships or collaborations. This concept offers important tools to unravel the difficult condition for the agricultural sector in marginalized areas, characterized by the abandonment of activities, low level of farmer education, and low generational renewal, hampering new territorial strategies addressed at and integrated and sustainable development. Models of SI in agriculture, starting from bottom up approach or from the community, are considered to represent the driving force of an ecological and digital revolution. A system based on SI may be able to grasp and satisfy individual and social needs and to promote new forms of entrepreneurship. In this context, Vazapp ('Go Hoeing') is an emerging SI model in southern Italy that promotes solutions for satisfying needs of farmers and facilitates their relationships (creation of network). The Vazapp’s initiative, considered in this study, is the Contadinners ('Farmer’s dinners'), a dinner held at farmer’s house where stakeholders living in the surrounding area know each other and are able to build a network for possible future professional collaborations. The aim of the paper is to identify the evolution of farmers’ relationships, both quantitatively and qualitatively, because of the Contadinner’s initiative organized by Vazapp. To this end, the study adopts the Social Network Analysis (SNA) methodology by using UCINET (Version 6.667) software to analyze the relational structure. Data collection was realized through a questionnaire distributed to 387 participants in the twenty 'Contadinners', held from February 2016 to June 2018. The response rate to the survey was about 50% of farmers. The elaboration data was focused on different aspects, such as: a) the measurement of relational reciprocity among the farmers using the symmetrize method of answers; b) the measurement of the answer reliability using the dichotomize method; c) the description of evolution of social capital using the cohesion method; d) the clustering of the Contadinners' participants in followers and not-followers of Vazapp to evaluate its impact on the local social capital. The results concern the effectiveness of this initiative in generating trustworthy relationships within the rural area of southern Italy, typically affected by individualism and mistrust. The number of relationships represents the quantitative indicator to define the dimension of the network development; while the typologies of relationships (from simple friendship to formal collaborations, for branding new cooperation initiatives) represents the qualitative indicator that offers a diversified perspective of the network impact. From the analysis carried out, Vazapp’s initiative represents surely a virtuous SI model to catalyze the relationships within the rural areas and to develop entrepreneurship based on the real needs of the community.

Keywords:

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4490 Generation Transcritical Flow Influenced by Dissipation over a Hole

Authors: Mohammed Daher Albalwi

Abstract:

The transcritical flow of a stratified fluid over an obstacle for negative forcing amplitude (hole) that generation upstream and downstream, connected by an unsteady solution, is examined. In the weakly nonlinear, weakly dispersive regime, the problem is formulated in the forced Korteweg-de Vries–Burgers framework. This is done by including the influence of the viscosity of the fluid beyond the Korteweg–de Vries approximation. The results show that the influence of viscosity is crucial in determining various wave properties, including the amplitudes of solitary waves in the upstream and downstream directions, as well as the widths of the bores. We focused here on weak damping, and the results are presented for transcritical, supercritical, and subcritical flows. In general, the outcomes are not qualitatively similar to those from the forced Korteweg-de–Vries equation when the value of the viscous is small, interesting differences emerge as the magnitude of the value of viscous increases.

Keywords: Korteweg–de Vries–Burgers equation, soliton, transcritical flow, viscous flow

Procedia PDF Downloads 51