Search results for: Road extraction

Authors: Sakthi Priya Balaji R., Vijayendar G.

Abstract:

This paper proposes a technique to block adult images displayed in websites. The filter is designed so as to perform even in exceptional cases such as, where face detection is not possible or improper face visibility. This is achieved by using an alternative phase to extract the MFC (Most Frequent Color) from the Human Body regions estimated using a biometric of anthropometric distances between fixed rigidly connected body locations. The logical results generated can be protected from overriding by a firewall or intrusion, by encrypting the result in a SSH data packet.

Keywords: Face detection, characteristics extraction andclassification, Component based shape analysis and classification, open source SSH V2 protocol

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Authors: M.R. Osman, F. Abas, M.S. Noh, A. Mohamad Suffian, O. Ilhamah, H.Z. Zarir, A.B. Wahida, P. Noor Faradila, M.F. Siti Atiqah

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Safety Health and Environment Code of Practice (SHE COP) was developed to help road transportation operators to manage its operation in a systematic and safe manner. A study was conducted to determine the effectiveness of SHE COP implementation during non-OPS period. The objective of the study is to evaluate the implementations of SHE COP among bus operators during wee hour operations. The data was collected by completing a set of checklist after observing the activities during pre departure, during the trip, and upon arrival. The results show that there are seven widely practiced SHE COP elements. 22% of the buses have average speed exceeding the maximum permissible speed on the highways (90 km/h), with 13% of the buses were travelling at the speed of more than 100 km/h. The statistical analysis shows that there is only one significant association which relates speeding with prior presence of enforcement officers.

Keywords: Safety practices, speeding, wee hour.

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Authors: Zuzana Dideková, Beata Mikovičová

Abstract:

Characterization of radio communication signals aims at automatic recognition of different characteristics of radio signals in order to detect their modulation type, the central frequency, and the level. Our purpose is to apply techniques used in image processing in order to extract pertinent characteristics. To the single analysis, we add several rules for checking the consistency of hypotheses using fuzzy logic. This allows taking into account ambiguity and uncertainty that may remain after the extraction of individual characteristics. The aim is to improve the process of radio communications characterization.

Keywords: fuzzy classification, fuzzy inference system, radio communication signals, telecommunications

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Authors: Amin Chegenizadeh, Mahdi Keramatikerman, Hamid Nikraz

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Pavement engineering plays a significant role to develop cost effective and efficient highway and road networks. In general, pavement regarding structure is categorized in two core group namely flexible and rigid pavements. There are various benefits in application of rigid pavement. For instance, they have a longer life and lower maintenance costs in compare with the flexible pavement. In rigid pavement designs, temperature and thickness are two effective parameters that could widely affect the total cost of the project. In this study, a numerical modeling using Kenpave-Kenslab was performed to investigate the effect of these two important parameters in the rigid pavement.   

Keywords: Rigid pavement, Kenpave, Kenslab, thickness, temperature.

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Authors: S. M. Khalessizadeh, R. Zaefarian, S.H. Nasseri, E. Ardil

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Today, Genetic Algorithm has been used to solve wide range of optimization problems. Some researches conduct on applying Genetic Algorithm to text classification, summarization and information retrieval system in text mining process. This researches show a better performance due to the nature of Genetic Algorithm. In this paper a new algorithm for using Genetic Algorithm in concept weighting and topic identification, based on concept standard deviation will be explored.

Keywords: Genetic Algorithm, Text Mining, Term Weighting, Concept Extraction, Concept Distribution.

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Authors: Simon Thiel, Stavros Dalakakis, Dieter Roller

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This paper outlines the development of a learning retrieval agent. Task of this agent is to extract knowledge of the Active Semantic Network in respect to user-requests. Based on a reinforcement learning approach, the agent learns to interpret the user-s intention. Especially, the learning algorithm focuses on the retrieval of complex long distant relations. Increasing its learnt knowledge with every request-result-evaluation sequence, the agent enhances his capability in finding the intended information.

Keywords: Reinforcement learning, learning retrieval agent, search in semantic networks.

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Authors: Parvinder S. Sandhu, Iqbaldeep Kaur, Amit Verma, Samriti Jindal, Inderpreet Kaur, Shilpi Kumari

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Face Recognition is a field of multidimensional applications. A lot of work has been done, extensively on the most of details related to face recognition. This idea of face recognition using PCA is one of them. In this paper the PCA features for Feature extraction are used and matching is done for the face under consideration with the test image using Eigen face coefficients. The crux of the work lies in optimizing Euclidean distance and paving the way to test the same algorithm using Matlab which is an efficient tool having powerful user interface along with simplicity in representing complex images.

Keywords: Eigen Face, Multidimensional, Matching, PCA.

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Authors: Shinji Kajiwara

Abstract:

The basic ability of a vehicle is to “run”, “turn” and “stop”. The safeness and comfort during a drive on various road surfaces and speed depends on the performance of these basic abilities of the vehicle. Stability and maneuverability of a vehicle are vital in automotive engineering. The stability of a vehicle is the ability of the vehicle to revert back to a stable state during a drive when faced with crosswinds and irregular road conditions. Maneuverability of a vehicle is the ability of the vehicle to change direction during a drive swiftly based on the steering of the driver. The stability and maneuverability of a vehicle can also be defined as the driving stability of the vehicle. Since the fossil fueled vehicle is the main type of transportation today, the environmental factor in automotive engineering is also vital. By improving the fuel efficiency of the vehicle, the overall carbon emission will be reduced, thus reducing the effect of global warming and greenhouse gas on the Earth. Another main focus of the automotive engineering is the safety performance of the vehicle, especially with the worrying increase of vehicle collision every day. With better safety performance of a vehicle, every driver will be more confident driving every day. Next, let us focus on the “turn” ability of a vehicle. By improving this particular ability of the vehicle, the cornering limit of the vehicle can be improved, thus increasing the stability and maneuverability factor. In order to improve the cornering limit of the vehicle, a study to find the balance between the steering systems, the stability of the vehicle, higher lateral acceleration and the cornering limit detection must be conducted. The aim of this research is to study and develop a new suspension system that will boost the lateral acceleration of the vehicle and ultimately improving the cornering limit of the vehicle. This research will also study environmental factor and the stability factor of the new suspension system. The double wishbone suspension system is widely used in a four-wheel vehicle, especially for high cornering performance sports car and racing car. The double wishbone designs allow the engineer to carefully control the motion of the wheel by controlling such parameters as camber angle, caster angle, toe pattern, roll center height, scrub radius, scuff, and more. The development of the new suspension system will focus on the ability of the new suspension system to optimize the camber control and to improve the camber limit during a cornering motion. The research will be carried out using the CAE analysis tool. Using this analysis tool we will develop a JSAE Formula Machine equipped with the double wishbone system and also the new suspension system and conduct simulation and conduct studies on the performance of both suspension systems.

Keywords: Automobile, Camber Thrust, Cornering force, Suspension.

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Authors: Yaser E. Hawas, Md. Didarul Alam

Abstract:

Rollover crashes are complex events entailing interactions of driver, road, vehicle, and environmental factors. The primary objective of this paper is to present an empirical approach that can be used to characterise the rollover crashes and to identify some of the important factors that may lead to rollovers. Among the studied factors are the vehicle types and the rollover occurrence rate after hitting various barrier types. The carried analysis indicated that 71% of the rollover crashes occurred after impact and the type of rollover initiation is “trip/turn over” (nearly 50%). It was also found that light trucks (LTVs) vehicles are more likely to rollover than the sedan vehicles. Barrier impacts are associated with increased incidence of rollover.

Keywords: Empirical, hitting barrier, in-depth crash investigation, rollover, severe crash.

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Authors: A. R. Vazifedoost, M. Rahgozar, F. Oroumchian

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Knowledge discovery from text and ontology learning are relatively new fields. However their usage is extended in many fields like Information Retrieval (IR) and its related domains. Human Plausible Reasoning based (HPR) IR systems for example need a knowledge base as their underlying system which is currently made by hand. In this paper we propose an architecture based on ontology learning methods to automatically generate the needed HPR knowledge base.

Keywords: Ontology Learning, Human Plausible Reasoning, knowledge extraction, knowledge representation.

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Authors: Sanpachai Huvanandana

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A human verification system is presented in this paper. The system consists of several steps: background subtraction, thresholding, line connection, region growing, morphlogy, star skelatonization, feature extraction, feature matching, and decision making. The proposed system combines an advantage of star skeletonization and simple statistic features. A correlation matching and probability voting have been used for verification, followed by a logical operation in a decision making stage. The proposed system uses small number of features and the system reliability is convincing.

Keywords: Human verification, object recognition, videounderstanding, segmentation.

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Authors: Mohammad Yasrebi, Mehran Mohsenzadeh

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The third phase of web means semantic web requires many web pages which are annotated with metadata. Thus, a crucial question is where to acquire these metadata. In this paper we propose our approach, a semi-automatic method to annotate the texts of documents and web pages and employs with a quite comprehensive knowledge base to categorize instances with regard to ontology. The approach is evaluated against the manual annotations and one of the most popular annotation tools which works the same as our tool. The approach is implemented in .net framework and uses the WordNet for knowledge base, an annotation tool for the Semantic Web.

Keywords: Semantic Annotation, Metadata, Information Extraction, Semantic Web, knowledge base.

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Authors: Mingling Zheng, Zhenlong Song, Ke Xu, Hengzhu Liu

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Scale Invariant Feature Transform (SIFT) has been widely applied, but extracting SIFT feature is complicated and time-consuming. In this paper, to meet the demand of the real-time applications, SIFT is parallelized and optimized on cluster system, which is named pSIFT. Redundancy storage and communication are used for boundary data to improve the performance, and before representation of feature descriptor, data reallocation is adopted to keep load balance in pSIFT. Experimental results show that pSIFT achieves good speedup and scalability.

Keywords: cluster, image matching, parallelization and optimization, SIFT.

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Authors: Safdar Tanweer, Abdul Mobin, Afshar Alam

Abstract:

The performance and analysis of speech recognition system is illustrated in this paper. An approach to recognize the English word corresponding to digit (0-9) spoken by 2 different speakers is captured in noise free environment. For feature extraction, speech Mel frequency cepstral coefficients (MFCC) has been used which gives a set of feature vectors from recorded speech samples. Neural network model is used to enhance the recognition performance. Feed forward neural network with back propagation algorithm model is used. However other speech recognition techniques such as HMM, DTW exist. All experiments are carried out on Matlab.

Keywords: Speech Recognition, MFCC, Neural Network, classifier.

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Authors: Erin Lynne Plettenberg, Jeremy Vickery

Abstract:

In an access-control situation, the role of a user determines whether a data request is appropriate. This paper combines vetted web mining and logic modeling to build a lightweight system for determining the role of a health care provider based only on their prior authorized requests. The model identifies provider roles with 100% recall from very little data. This shows the value of vetted web mining in AI systems, and suggests the impact of the ICD classification on medical practice.

Keywords: Ontology, logic modeling, electronic medical records, information extraction, vetted web mining.

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Authors: Tudor Barbu

Abstract:

We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.

Keywords: Text-independent speaker recognition, mel cepstral analysis, speech feature vector, Hausdorff-based metric, supervised classification.

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Authors: Yoshimoto Kurihara, Tad Gonsalves

Abstract:

Currently, in the field of object posture estimation, there is research on estimating the position and angle of an object by storing a 3D model of the object to be estimated in advance in a computer and matching it with the model. However, in this research, we have succeeded in creating a module that is much simpler, smaller in scale, and faster in operation. Our 6D pose estimation model consists of two different networks – a classification network and a regression network. From a single RGB image, the trained model estimates the class of the object in the image, the coordinates of the object, and its rotation angle in 3D space. In addition, we compared the estimation accuracy of each camera position, i.e., the angle from which the object was captured. The highest accuracy was recorded when the camera position was 75°, the accuracy of the classification was about 87.3%, and that of regression was about 98.9%.

Keywords: AlexNet, Deep learning, image recognition, 6D posture estimation.

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Authors: Nermin Ozgulbas, Ali Serhan Koyuncugil

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One of the biggest problems of SMEs is their tendencies to financial distress because of insufficient finance background. In this study, an Early Warning System (EWS) model based on data mining for financial risk detection is presented. CHAID algorithm has been used for development of the EWS. Developed EWS can be served like a tailor made financial advisor in decision making process of the firms with its automated nature to the ones who have inadequate financial background. Besides, an application of the model implemented which covered 7,853 SMEs based on Turkish Central Bank (TCB) 2007 data. By using EWS model, 31 risk profiles, 15 risk indicators, 2 early warning signals, and 4 financial road maps has been determined for financial risk mitigation.

Keywords: Early Warning Systems, Data Mining, Financial Risk, SMEs.

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Authors: Johanna Anteroinen, Wonjae Kim, Kari Stadius, Juha Riikonen, Harri Lipsanen, Jussi Ryynanen

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Graphene-metal contact resistance limits the performance of graphene-based electrical devices. In this work, we have fabricated both graphene field-effect transistors (GFET) and transfer length measurement (TLM) test devices with titanium contacts. The purpose of this work is to compare the contact resistances that can be numerically extracted from the GFETs and measured from the TLM structures. We also provide a brief review of the work done in the field to solve the contact resistance problem.

Keywords: Contact resistance, graphene, TLM

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Authors: Sven Borén, Henrik Ny

Abstract:

Ambitions within the EU for moving towards sustainable transport include major emission reductions for fossil fuel road vehicles, especially for buses, trucks, and cars. The electric driveline seems to be an attractive solution for such development. This study first applied the Framework for Strategic Sustainable Development to compare sustainability effects of today’s fossil fuel vehicles with electric vehicles that have batteries or hydrogen fuel cells. The study then addressed a scenario were electric vehicles might be in majority in Europe by 2050. The methodology called Strategic Lifecycle Assessment was first used, were each life cycle phase was assessed for violations against sustainability principles. This indicates where further analysis could be done in order to quantify the magnitude of each violation, and later to create alternative strategies and actions that lead towards sustainability. A Life Cycle Assessment of combustion engine cars, plug-in hybrid cars, battery electric cars and hydrogen fuel cell cars was then conducted to compare and quantify environmental impacts. The authors found major violations of sustainability principles like use of fossil fuels, which contribute to the increase of emission related impacts such as climate change, acidification, eutrophication, ozone depletion, and particulate matters. Other violations were found, such as use of scarce materials for batteries and fuel cells, and also for most life cycle phases for all vehicles when using fossil fuel vehicles for mining, production and transport. Still, the studied current battery and hydrogen fuel cell cars have less severe violations than fossil fuel cars. The life cycle assessment revealed that fossil fuel cars have overall considerably higher environmental impacts compared to electric cars as long as the latter are powered by renewable electricity. By 2050, there will likely be even more sustainable alternatives than the studied electric vehicles when the EU electricity mix mainly should stem from renewable sources, batteries should be recycled, fuel cells should be a mature technology for use in vehicles (containing no scarce materials), and electric drivelines should have replaced combustion engines in other sectors. An uncertainty for fuel cells in 2050 is whether the production of hydrogen will have had time to switch to renewable resources. If so, that would contribute even more to a sustainable development. Except for being adopted in the GreenCharge roadmap, the authors suggest that the results can contribute to planning in the upcoming decades for a sustainable increase of EVs in Europe, and potentially serve as an inspiration for other smaller or larger regions. Further studies could map the environmental effects in LCA further, and include other road vehicles to get a more precise perception of how much they could affect sustainable development.

Keywords: Strategic, electric vehicles, fuel cell, LCA, sustainability.

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Authors: N. Behidj-Benyounes, K. Benyounes, T. Dahmene, N. Chebouti, S. Gana

Abstract:

Essential oils have a significant antimicrobial activity. These oils can successfully replace the antibiotics. So, the microorganisms show their inefficiencies resistant for the antibiotics. For this reason, we study the physicochemical analysis and antimicrobial activity of the essential oil of Daucus carota. The extraction is done by steam distillation of water which brought us a very significant return of 4.65%. The analysis of the essential oil is performed by GC / MS and has allowed us to identify 32 compounds in the oil of D. carota flowering tops of Bouira. Three of which are in the majority are the α-Pinene (22.3%), the carotol (21.7%) and the limonene (15.8%).

Keywords: α-Pinene, carotol, Daucus carota, limonene.

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Authors: R. Kaur, Y. B. Pakade, J. K. Katnoria

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Considering the serious health hazards of air pollutants from automobiles, the present study was aimed to estimate the genotoxic/tumor inducing potential of three soil samples collected from junctions of Bus stand (BS), Crystal (CT) and Railway station (RS) of Amritsar, Punjab (India) using Allium cepa root chromosomal aberration assay (AlRCAA) and potato disc tumor assay (PDTA). The genotoxic potential in AlRCAA was 41.27% and 41.26% for BS; 37.89% and 43.38% for RS and 33.76% and 37.83% for CT during in situ and root dip treatments, respectively. The maximum number of tumors were induced in RS sample (64) followed by BS (21) and CT (9) during PDTA. The physicochemical parameters of soil sample were also studied and the concentration of lead was found to be 95.21 mg/Kg in RS, 35.30 mg/Kg in BS and 24.59 mg/Kg in CT samples.

Keywords: Automobiles, genotoxicity, Physicochemical parameters, pollutants.

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Authors: Alexandra Gheorghiu, Marie-Line Félonneau

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Speeding represents one of the main concerns for road safety and it still is a subject for research. The need to address this problem and to understand why drivers over speed increases especially in Romania, where in 2011, speed was the main cause of car accidents. This article addresses this problem by using the theory of planned behaviour. A questionnaire was administered to a sample of young Romanian drivers (18 to 25 years) and several path analyses were made in order to verify if the model proposed by the theory of planned behaviour fits the data. One interesting result is that perceived behavioural control does not predict the intention to speed or self-reported driving speed, but subjective norms do. This implies that peers and social environment have a greater impact on young Romanian drivers than we thought.

Keywords: Speed, traffic safety, theory of planned behaviour, young drivers.

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Authors: H. Al-Baghli

Abstract:

In this investigation, rubberized HMA technology was examined to address the most critical forms of pavement distresses in the State of Kuwait, namely, high temperature rutting, and moisture induced raveling. PelletPAVE™ additive was selected as the preferred technology, since it offered a convenient method of directly modifying the exiting local HMA recipe without having to polymer modify the bitumen. Experimental work, using various Pelletpave contents was carried out at Kuwait Institute for Scientific Research (KISR) to design an optimum rubberized HMA formulation prior to conducting a pilot-scale road trial. With the aid of a gyratory compactor, the compaction and volumetric properties of HMAs containing 2.5% and 3.0% Pelletpave additive were investigated at a range of bitumen contents, all by mass of total mix.

Keywords: Modified bitumen, rubberized hot mix asphalt, gyratory compaction, volumetric properties.

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Authors: S. B. Kotsiantis, D. Kanellopoulos, P. E. Pintelas

Abstract:

Many factors affect the success of Machine Learning (ML) on a given task. The representation and quality of the instance data is first and foremost. If there is much irrelevant and redundant information present or noisy and unreliable data, then knowledge discovery during the training phase is more difficult. It is well known that data preparation and filtering steps take considerable amount of processing time in ML problems. Data pre-processing includes data cleaning, normalization, transformation, feature extraction and selection, etc. The product of data pre-processing is the final training set. It would be nice if a single sequence of data pre-processing algorithms had the best performance for each data set but this is not happened. Thus, we present the most well know algorithms for each step of data pre-processing so that one achieves the best performance for their data set.

Keywords: Data mining, feature selection, data cleaning.

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Authors: Djamila Benhaddouche, Abdelkader Benyettou

Abstract:

In this paper, we used data mining to extract biomedical knowledge. In general, complex biomedical data collected in studies of populations are treated by statistical methods, although they are robust, they are not sufficient in themselves to harness the potential wealth of data. For that you used in step two learning algorithms: the Decision Trees and Support Vector Machine (SVM). These supervised classification methods are used to make the diagnosis of thyroid disease. In this context, we propose to promote the study and use of symbolic data mining techniques.

Keywords: A classifier, Algorithms decision tree, knowledge extraction, Support Vector Machine.

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Authors: S. Banerjee

Abstract:

The paper describes design of an ontology in the financial domain for mutual funds. The design of this ontology consists of four steps, namely, specification, knowledge acquisition, implementation and semantic query. Specification includes a description of the taxonomy and different types mutual funds and their scope. Knowledge acquisition involves the information extraction from heterogeneous resources. Implementation describes the conceptualization and encoding of this data. Finally, semantic query permits complex queries to integrated data, mapping of these database entities to ontological concepts.

Keywords: Ontology, Semantic Web, Mutual Funds.

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Authors: Sanjoy Das, Akash Arya, Rishi Pal Singh

Abstract:

Vehicular Ad hoc Network is basically the solution of several problems associated while vehicles are plying on the road. In this paper, we have focused on the detection of imposter node while it has stolen the ID's of the authenticated vehicle in the network. The purpose is to harm the network through imposter messages. Here, we have proposed a protocol namely Imposter Detection based on Location (IDBL), which will store the location coordinate of the each vehicle as the key of the authenticity of the message so that imposter node can be detected. The imposter nodes send messages from a stolen ID and show that it is from an authentic node ID. So, to detect this anomaly, the first location is checked and observed different from original vehicle location. This node is known as imposter node. We have implemented the algorithm through JAVA and tested various types of node distribution and observed the detection probability of imposter node.

Keywords: Authentication, detection, IDBL protocol, imposter node, node detection.

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Authors: Thiago M. R Dias, Gray F. Moita

Abstract:

The analysis of scientific collaboration networks has contributed significantly to improving the understanding of how does the process of collaboration between researchers and also to understand how the evolution of scientific production of researchers or research groups occurs. However, the identification of collaborations in large scientific databases is not a trivial task given the high computational cost of the methods commonly used. This paper proposes a method for identifying collaboration in large data base of curriculum researchers. The proposed method has low computational cost with satisfactory results, proving to be an interesting alternative for the modeling and characterization of large scientific collaboration networks.

Keywords: Extraction and data integration, Information Retrieval, Scientific Collaboration.

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Authors: Jaouadi Ikram, Machhout Mohsen

Abstract:

The development of a quantum key distribution (QKD) system on a field-programmable gate array (FPGA) platform is the subject of this paper. A quantum cryptographic protocol is designed based on the properties of quantum information and the characteristics of FPGAs. The proposed protocol performs key extraction, reconciliation, error correction, and privacy amplification tasks to generate a perfectly secret final key. We modeled the presence of the spy in our system with a strategy to reveal some of the exchanged information without being noticed. Using an FPGA card with a 100 MHz clock frequency, we have demonstrated the evolution of the error rate as well as the amounts of mutual information (between the two interlocutors and that of the spy) passing from one step to another in the key generation process.

Keywords: QKD, BB84, protocol, cryptography, FPGA, key, security, communication.

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