Academic literature on the topic 'Consensus Based Applications'
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Journal articles on the topic "Consensus Based Applications"
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MOSTEFAOUI, A., and M. RAYNAL. "LEADER-BASED CONSENSUS." Parallel Processing Letters 11, no. 01 (March 2001): 95–107. http://dx.doi.org/10.1142/s0129626401000452.
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It is now well recognized that consensus is a fundamental problem one has to solve to implement reliable applications on top of unreliable asynchronous distributed systems prone to failures. It has been shown that this problem cannot be solved if the underlying asynchronous system does not satisfy additional assumptions. This paper presents a new consensus protocol based on a leader oracle (denoted Ω in the litterature). Although this protocol uses asynchronous rounds, it is not based on the rotating coordinator paradigm. As a consequence, it does not suffer from drawbacks inherent to ♢S-based consensus protocols that explicity use this paradigm. As Ω and ♢S are equivalent, the proposed protocol does not require assumptions stronger or weaker than the ones abstracted in ♢S. Hence, it also requires f < n/2 (where n is the number of processes and f an upper bound on the number of processes that may crash). From a design point of view, the proposed protocol is surprisingly simple. From an efficiency point of view, it allows the processes to agree in a single round when the oracle provides the processes with the same leader (a common case in practice). It is also shown that the time and message costs of the protocol can be reduced when f < n/3. Moreover, when, in addition to the leader oracle, the system is equipped with a random oracle, the proposed protocol can be extended to provide a hybrid consensus protocol at no additional message cost.
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Li, Wenjun, and Huaiyu Dai. "Cluster-based distributed consensus." IEEE Transactions on Wireless Communications 8, no. 1 (January 2009): 28–31. http://dx.doi.org/10.1109/t-wc.2009.071146.
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Uddin, Moin, Muhammad Muzammal, Muhammad Khurram Hameed, Ibrahim Tariq Javed, Bandar Alamri, and Noel Crespi. "CBCIoT: A Consensus Algorithm for Blockchain-Based IoT Applications." Applied Sciences 11, no. 22 (November 20, 2021): 11011. http://dx.doi.org/10.3390/app112211011.
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Internet of things is widely used in the current era to collect data from sensors and perform specific tasks through processing according to the requirements. The data collected can be sent to a blockchain network to create secure and tamper-resistant records of transactions. The combination of blockchain with IoT has huge potential as it can provide decentralized computation, storage, and exchange for IoT data. However, IoT applications require a low-latency consensus mechanism due to its constraints. In this paper, CBCIoT, a consensus algorithm for blockchain-based IoT applications, is proposed. The primary purpose of this algorithm is to improve scalability in terms of validation and verification rate. The algorithm is developed to be compatible with IoT devices where a slight delay is acceptable. The simulation results show the proposed algorithm’s efficiency in terms of block generation time and transactions per second.
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Yang, Tao, Di Wu, Yannan Sun, and Jianming Lian. "Minimum-Time Consensus-Based Approach for Power System Applications." IEEE Transactions on Industrial Electronics 63, no. 2 (February 2016): 1318–28. http://dx.doi.org/10.1109/tie.2015.2504050.
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Stankovic, Srdjan S., Milos S. Stankovic, and Dusan M. Stipanovic. "Consensus Based Overlapping Decentralized Estimator." IEEE Transactions on Automatic Control 54, no. 2 (February 2009): 410–15. http://dx.doi.org/10.1109/tac.2008.2009583.
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Pan, Shin-Hung, and Shu-Ching Wang. "Optimal Consensus with Dual Abnormality Mode of Cellular IoT Based on Edge Computing." Sensors 21, no. 2 (January 19, 2021): 671. http://dx.doi.org/10.3390/s21020671.
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The continuous development of fifth-generation (5G) networks is the main driving force for the growth of Internet of Things (IoT) applications. It is expected that the 5G network will greatly expand the applications of the IoT, thereby promoting the operation of cellular networks, the security and network challenges of the IoT, and pushing the future of the Internet to the edge. Because the IoT can make anything in anyplace be connected together at any time, it can provide ubiquitous services. With the establishment and use of 5G wireless networks, the cellular IoT (CIoT) will be developed and applied. In order to provide more reliable CIoT applications, a reliable network topology is very important. Reaching a consensus is one of the most important issues in providing a highly reliable CIoT design. Therefore, it is necessary to reach a consensus so that even if some components in the system is abnormal, the application in the system can still execute correctly in CIoT. In this study, a protocol of consensus is discussed in CIoT with dual abnormality mode that combines dormant abnormality and malicious abnormality. The protocol proposed in this research not only allows all normal components in CIoT to reach a consensus with the minimum times of data exchange, but also allows the maximum number of dormant and malicious abnormal components in CIoT. In the meantime, the protocol can make all normal components in CIoT satisfy the constraints of reaching consensus: Termination, Agreement, and Integrity.
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Ge, Lina, Jie Wang, and Guifen Zhang. "Survey of Consensus Algorithms for Proof of Stake in Blockchain." Security and Communication Networks 2022 (May 29, 2022): 1–13. http://dx.doi.org/10.1155/2022/2812526.
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As the core of blockchain technology, the consensus algorithm directly affects the security, stability, and decentralisation of the blockchain and numerous other important characteristics. Choosing an appropriate consensus algorithm for different scenarios is currently a challenge in the implementation of blockchain applications. This paper classifies the improvement schemes of proof of stake (PoS) into three categories: PoS-based consensus algorithms, PoS- and PoW-based consensus algorithms, and PoS- and BFT-based consensus algorithms. First, the study introduces the PoS and PoS consensus algorithm variants and then summarises the core ideas, effects, advantages, and disadvantages of these algorithms. Subsequently, the performances of the improved algorithms are compared. Finally, the main improved methods are summarised, and the most common network security attacks are discussed. The study lays a foundation for the main improvement directions of PoS in the future, hoping to provide a reference for researchers to help them select and design consensus algorithms in different application scenarios while also helping the evolution of consensus algorithms and the implementation of blockchain applications.
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Sebbak, Faouzi, and Farid Benhammadi. "Majority-consensus fusion approach for elderly IoT-based healthcare applications." Annals of Telecommunications 72, no. 3-4 (November 4, 2016): 157–71. http://dx.doi.org/10.1007/s12243-016-0550-7.
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Geng, Tieming, Laurent Njilla, and Chin-Tser Huang. "Delegated Proof of Secret Sharing: A Privacy-Preserving Consensus Protocol Based on Secure Multiparty Computation for IoT Environment." Network 2, no. 1 (January 25, 2022): 66–80. http://dx.doi.org/10.3390/network2010005.
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With the rapid advancement and wide application of blockchain technology, blockchain consensus protocols, which are the core part of blockchain systems, along with the privacy issues, have drawn much attention from researchers. A key aspect of privacy in the blockchain is the sensitive content of transactions in the permissionless blockchain. Meanwhile, some blockchain applications, such as cryptocurrencies, are based on low-efficiency and high-cost consensus protocols, which may not be practical and feasible for other blockchain applications. In this paper, we propose an efficient and privacy-preserving consensus protocol, called Delegated Proof of Secret Sharing (DPoSS), which is inspired by secure multiparty computation. Specifically, DPoSS first uses polynomial interpolation to select a dealer group from many nodes to maintain the consensus of the blockchain system, in which the dealers in the dealer group take turns to pack the new block. In addition, since the content of transactions is sensitive, our proposed design utilizes verifiable secret sharing to protect the privacy of transmission and defend against the malicious attacks. Extensive experiments show that the proposed consensus protocol achieves fairness during the process of reaching consensus.
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Onan, Aytuğ. "Consensus Clustering-Based Undersampling Approach to Imbalanced Learning." Scientific Programming 2019 (March 3, 2019): 1–14. http://dx.doi.org/10.1155/2019/5901087.
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Class imbalance is an important problem, encountered in machine learning applications, where one class (named as, the minority class) has extremely small number of instances and the other class (referred as, the majority class) has immense quantity of instances. Imbalanced datasets can be of great importance in several real-world applications, including medical diagnosis, malware detection, anomaly identification, bankruptcy prediction, and spam filtering. In this paper, we present a consensus clustering based-undersampling approach to imbalanced learning. In this scheme, the number of instances in the majority class was undersampled by utilizing a consensus clustering-based scheme. In the empirical analysis, 44 small-scale and 2 large-scale imbalanced classification benchmarks have been utilized. In the consensus clustering schemes, five clustering algorithms (namely, k-means, k-modes, k-means++, self-organizing maps, and DIANA algorithm) and their combinations were taken into consideration. In the classification phase, five supervised learning methods (namely, naïve Bayes, logistic regression, support vector machines, random forests, and k-nearest neighbor algorithm) and three ensemble learner methods (namely, AdaBoost, bagging, and random subspace algorithm) were utilized. The empirical results indicate that the proposed heterogeneous consensus clustering-based undersampling scheme yields better predictive performance.
Dissertations / Theses on the topic "Consensus Based Applications"
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Genta, L. "CONSENSUS-BASED CROWDSOURCING: TECHNIQUES AND APPLICATIONS." Doctoral thesis, Università degli Studi di Milano, 2015. http://hdl.handle.net/2434/263749.
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Crowdsourcing solutions are receiving more and more attention in the recent literature about social computing and distributed problem solving. In general terms, crowdsourcing can be considered as a social-computing model aimed at fostering the autonomous formation and emergence of the so-called wisdom of the crowd. Quality assessment is a crucial issue for the effectiveness of crowdsourcing systems, both for what concerns task and worker management. Another aspect to be considered in crowdsourcing systems is about the kind of contributions workers can make. Usually, crowdsourcing approaches rely only on tasks where workers have to decide among a predefined set of possible solutions. On the other hand, tasks leaving the workers a higher level of freedom in producing their answer (e.g., free-hand drawing) are more difficult to be managed and verified. In the Thesis, we present the LiquidCrowd approach based on consensus and trustworthiness techniques for managing the xecution of collaborative tasks. By collaborative task, we refer to a task for which a factual answer is not possible/appropriate, or a task whose result depends on the personal perception/point-of-view of the worker. We introduce the notion of worker trustworthiness to denote the worker “reliability”, namely her/his capability to foster
the successful completion of tasks. Furthermore, we improve the conventional score-based mechanism by introducing the notion of award that is a bonus provided to those workers that contribute to reach the consensus within groups. This way, groups with certain trustworthiness requirements can be composed on-demand, to deal with complex tasks, like for example tasks where consensus has not been reached during the first execution. In LiquidCrowd , we define a democratic mechanism based on the notion of supermajority to enable the flexible specification of the expected degree of agreement required for obtaining the consensus within a worker group. In LiquidCrowd , three task typologies are provided: choice, where the worker is asked to choose the answer among a list of predefined options; range, where the worker is asked to provide a free-numeric answer; proposition, where the worker is asked to provide a free text answer.
To evaluate the quality of the produced results obtained through LiquidCrowd consensus techniques, we perform a testing against the SQUARE crowdsourcing benchmark. Furthermore, to evaluate the capability of LiquidCrowd to effectively support a real problem, real case studies about web data classification have been selected.
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Del, Favero Simone. "Analysis and Development of Consensus-based Estimation Schemes." Doctoral thesis, Università degli studi di Padova, 2010. http://hdl.handle.net/11577/3427027.
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In the last few decades we assisted to an extraordinary expansion of the Internet and of wireless technologies. These interconnection technologies allow a continuously increasing number of devices to exchange information. This fact, together with the parallel increase in the availability of inexpensive nodes carrying a wide range of sensing capabilities, attracts the interest in developing
large-scale sensing platforms, which could be used to measure a variety of physical phenomena.
However, these huge networks of simple devices are subject to tight energy and bandwidth constraints, making efficient distributed estimation and data fusion algorithms a strong need, to avoid unmanageable computational and communicational burden on network bottleneck nodes.
%In this thesis we address some issues in this research avenue
In this thesis we address some issues in this field, presenting and analyzing distributed algorithms to solve specific distributed estimation problems and carrying out the analysis of some other recently-proposed algorithms.
To perform data fusion in a distributed fashion, we relay on consensus algorithms, namely algorithms that achieve agreement on a common value in the network.
Using consensus as a basic brick to build estimation algorithms we can take advantage of the solid understanding on this problem that many recent contributions deepened and sharpened, and we can leverage for our analysis on powerful and effective tools.
In the thesis we propose a distributed algorithm for offset removal and an algorithm for least-square identification of the wireless-channel parameters, motivated by the application of localization and tracking of a moving object. We present moreover a novel linear algebra inequality, useful in the analysis of randomized algorithms. This result comes into play when we carry out an analysis of a recently-proposed distributed Kalman filtering algorithm. Finally, we look at the intriguing set up of a network cooperation to estimate different but correlated quantities, proposing and analyzing a distributed algorithm that performs inference over a simple Gauss-Markov random field.Gli ultimi decenni sono stati segnati dallo straordinario sviluppo di Internet e dalla pervasiva diffusione della tecnologia wireless, consentendo ad un numero sempre maggiore di dispositivi di scambiare tra loro informazioni. Questo fatto, assieme alla crescente disponibilità, a prezzi modici, di nodi equipaggiati con un'ampia varietà di dispositivi di misura, rende tecnologicamente concretizzabile l'idea di sviluppare grandi piattaforme di sensing, incaricate di monitorare qualsivoglia grandezza fisica. Tuttavia, queste grandi reti di dispositivi estremamente semplici hanno stringenti vincoli sul consumo energetico e sulla banda di comunicazione, che rendono criticamente necessario lo sviluppo di tecniche efficienti per la stima e la data-fusion, così da evitare carichi computazionali e di comunicazione insostenibili ai colli di bottiglia della rete. Questa tesi si propone di contribuire proprio in questo settore, presentando alcuni algoritmi per la soluzione distribuita di specifici problemi di stima ed analizzando le prestazioni di algoritmi recentemente proposti. Strumento chiave nella decentralizzazione della stima è la teoria del consensus, che propone algoritmi in grado di portare l'intera rete a concordare su una specifica quantità. L'utilizzo di algoritmi di consensus come elemento base nella costruzione di algoritmi di stima ci consente di sfruttare la solida comprensione di questo problema, affinata dai molti risultati recentemente proposti in letteratura, e di sfruttare degli strumenti di analisi ben consolidati. Nella tesi, motivati dal problema della localizzazione e del tracking di un oggetto, proponiamo un algoritmo per la compensazione degli offset ed un algoritmo per la stima ai minimi quadrati dei parametri caratterizzanti il canale wireless. Inoltre presentiamo un nuovo risultato di algebra lineare, utile nell'analisi di algoritmi randomizzati. Questo risultato giocherà un ruolo centrale nell'analisi qui proposta di un algoritmo distribuito per la stima alla Kalman. Infine, consideriamo l'interessante caso di una rete di sensori incaricata di stimare quantità diverse ma tra loro correlate e proponiamo un algoritmo per l'inferenza di un semplice campo di Gauss-Markov.
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Saravi, Sara. "Use of Coherent Point Drift in computer vision applications." Thesis, Loughborough University, 2013. https://dspace.lboro.ac.uk/2134/12548.
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This thesis presents the novel use of Coherent Point Drift in improving the robustness of a number of computer vision applications. CPD approach includes two methods for registering two images - rigid and non-rigid point set approaches which are based on the transformation model used. The key characteristic of a rigid transformation is that the distance between points is preserved, which means it can be used in the presence of translation, rotation, and scaling. Non-rigid transformations - or affine transforms - provide the opportunity of registering under non-uniform scaling and skew. The idea is to move one point set coherently to align with the second point set. The CPD method finds both the non-rigid transformation and the correspondence distance between two point sets at the same time without having to use a-priori declaration of the transformation model used. The first part of this thesis is focused on speaker identification in video conferencing. A real-time, audio-coupled video based approach is presented, which focuses more on the video analysis side, rather than the audio analysis that is known to be prone to errors. CPD is effectively utilised for lip movement detection and a temporal face detection approach is used to minimise false positives if face detection algorithm fails to perform. The second part of the thesis is focused on multi-exposure and multi-focus image fusion with compensation for camera shake. Scale Invariant Feature Transforms (SIFT) are first used to detect keypoints in images being fused. Subsequently this point set is reduced to remove outliers, using RANSAC (RANdom Sample Consensus) and finally the point sets are registered using CPD with non-rigid transformations. The registered images are then fused with a Contourlet based image fusion algorithm that makes use of a novel alpha blending and filtering technique to minimise artefacts. The thesis evaluates the performance of the algorithm in comparison to a number of state-of-the-art approaches, including the key commercial products available in the market at present, showing significantly improved subjective quality in the fused images. The final part of the thesis presents a novel approach to Vehicle Make & Model Recognition in CCTV video footage. CPD is used to effectively remove skew of vehicles detected as CCTV cameras are not specifically configured for the VMMR task and may capture vehicles at different approaching angles. A LESH (Local Energy Shape Histogram) feature based approach is used for vehicle make and model recognition with the novelty that temporal processing is used to improve reliability. A number of further algorithms are used to maximise the reliability of the final outcome. Experimental results are provided to prove that the proposed system demonstrates an accuracy in excess of 95% when tested on real CCTV footage with no prior camera calibration.
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Huang, Fengqiong, James A. Macklin, Hong Cui, Heather A. Cole, and Lorena Endara. "OTO: ontology term organizer." BioMed Central, 2015. http://hdl.handle.net/10150/610269.
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BACKGROUND: The need to create controlled vocabularies such as ontologies for knowledge organization and access has been widely recognized in various domains. Despite the indispensable need of thorough domain knowledge in ontology construction, most software tools for ontology construction are designed for knowledge engineers and not for domain experts to use. The differences in the opinions of different domain experts and in the terminology usages in source literature are rarely addressed by existing software. METHODS: OTO software was developed based on the Agile principles. Through iterations of software release and user feedback, new features are added and existing features modified to make the tool more intuitive and efficient to use for small and large data sets. The software is open source and built in Java. RESULTS: Ontology Term Organizer (OTO; http://biosemantics.arizona.edu/OTO/) is a user-friendly, web-based, consensus-promoting, open source application for organizing domain terms by dragging and dropping terms to appropriate locations. The application is designed for users with specific domain knowledge such as biology but not in-depth ontology construction skills. Specifically OTO can be used to establish is_a, part_of, synonym, and order relationships among terms in any domain that reflects the terminology usage in source literature and based on multiple experts' opinions. The organized terms may be fed into formal ontologies to boost their coverage. All datasets organized on OTO are publicly available. CONCLUSION: OTO has been used to organize the terms extracted from thirty volumes of Flora of North America and Flora of China combined, in addition to some smaller datasets of different taxon groups. User feedback indicates that the tool is efficient and user friendly. Being open source software, the application can be modified to fit varied term organization needs for different domains.
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Ouattara, Mory. "Développement et mise en place d'une méthode de classification multi-blocs : application aux données de l'OQAI." Phd thesis, Conservatoire national des arts et metiers - CNAM, 2014. http://tel.archives-ouvertes.fr/tel-01062782.
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La multiplication des sources d'information et le développement de nouvelles technologies ont engendré des bases données complexes, souvent caractérisées par un nombre de variables relativement élevé par rapport aux individus. En particulier, dans les études environnementales sur la pollution de l'air intérieur, la collecte des informations sur les individus se fait au regard de plusieurs thématiques, engendrant ainsi des données de grande dimension avec une structure multi-blocs définie par les thématiques. L'objectif de ce travail a été de développer des méthodes de classification adaptées à ces jeux de données de grande dimension et structurées en blocs de variables. La première partie de ce travail présente un état de l'art des méthodes de classification en général et dans le cas de la grande dimension. Dans la deuxième partie, trois nouvelles approches de classification d'individus décrits par des variables structurées en blocs ont été proposées. La méthode 2S-SOM (Soft Subspace-Self Organizing Map), une approche de type subspace clustering basée sur une modification de la fonction de coût de l'algorithme des cartes topologiques à travers un double système de poids adaptatifs défini sur les blocs et sur les variables. Nous proposons ensuite des approches CSOM (Consensus SOM) et Rv-CSOM de recherche de consensus de cartes auto-organisées basées sur un système de poids déterminés à partir des partitions initiales. Enfin, la troisième partie présente une application de ces méthodes sur le jeu de données réelles de la campagne nationale logement (CNL) menée par l'OQAI afin de définir une typologie des logements au regard des thématiques : qualité de l'air intérieur, structure du bâtiment, composition des ménages et habitudes des occupants.
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Kyrgyzov, Ivan. "Recherche dans les bases de donnees satellitaires des paysages et application au milieu urbain: clustering, consensus et categorisation." Phd thesis, Télécom ParisTech, 2008. http://pastel.archives-ouvertes.fr/pastel-00004084.
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Les images satellitaires ont trouvées une large application pour l'analyse des ressources naturelles et des activités humaines. Les images à haute résolution, e.g., SPOT5, sont très nombreuses. Ceci donne un grand intérêt afin de développer de nouveaux aspects théoriques et des outils pour la fouille d'images. L'objectif de la thèse est la fouille non-supervisée d'images et inclut trois parties principales. Dans la première partie nous démontrons le contenu d'images à haute résolution. Nous décrivons les zones d'images par les caractéristiques texturelles et géométriques. Les algorithmes de clustering sont présentés dans la deuxième partie. Une étude de critères de validité et de mesures d'information est donnée pour estimer la qualité de clustering. Un nouveau critère basé sur la Longueur de Description Minimale (LDM) est proposé pour estimer le nombre optimal de clusters. Par ailleurs, nous proposons un nouveau algorithme hiérarchique basé sur le critère LDM à noyau. Une nouvelle méthode de ''combinaison de clustering'' est présentée dans la thèse pour profiter de différents algorithmes de clustering. Nous développons un algorithme hiérarchique pour optimiser la fonction objective basée sur une matrice de co-association. Une deuxième méthode est proposée qui converge à une solution globale. Nous prouvons que le minimum global peut être trouvé en utilisant l'algorithme de type ''mean shift''. Les avantages de cette méthode sont une convergence rapide et une complexité linéaire. Dans la troisième partie de la thèse un protocole complet de la fouille d'images est proposé. Différents clusterings sont représentés via les relations sémantiques entre les concepts.
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Kyrgyzov, Ivan. "Recherche dans les bases de données satellitaires des paysages et application au milieu urbain : clustering, consensus et catégorisation." Paris, ENST, 2008. http://www.theses.fr/2008ENST0011.
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Les images satellitaires ont trouvé une large application pour l'analyse des ressources naturelles et des activités humaine. Les images à haute résolution, e. G. , SpOT5, sont trés nombreuses. Ceci donne un grand intérêt afin de développer de nouveaux aspects théoriques et des outils pour la fouille d'images. L'objectif de la thèse est la fouille non-supervisée d'images et inclut trois parties principales. Dans la première partie nous démontrons le contenu d'images à haute résolution. Nous décrivons les zones d'images par les caractéristiques texturelles et géométriques. Les algorithmes de clustering sont présentés dans la deuxième partie. Une étude de critères de validité et de mesures d'information est donnée pour estimer la qualité de clustering. Un nouveau critère basé sur la Longueur de Description Minimale (LDM) est proposé pour estimer le nombre optimal de clusters. Par ailleurs, nous proposons un nouveau algorithme hiérarchique basé sur le critère LDM à noyau. Une nouvelle méthode de ''combinaison de clustering'' est présentée dans la thèse pour profiter de différents algorithmes de clustering. Nous développons un algorithme hiérarchique pour optimiser la fonction objective basée sur une matrice de co-association. Une deuxième méthode est proposée qui converge à une solution globale. Nous prouvons que le minimum global peut être trouvé en utilisant l'algorithme de type ''mean shift''. Les avantages de cette méthode sont une convergence rapide et une complexité linéaire. Dans la troisième partie de la thèse un protocole complet de la fouille d'images est proposé. Différents clusterings sont représentés via les relations sémantiques entre les conceptsRemote sensed satellite images have found a wide application for analysing and managing natural resources and human activities. Satellite images of high resolution, e. G. , SPOT5, have large sizes and are very numerous. This gives a large interest to develop new theoretical aspects and practical tools for satellite image mining. The objective of the thesis is unsupervised satellite image mining and includes three main parts. In the first part of the thesiswe demonstrate content of high resolution optical satellite images. We describe image zones by texture and geometrical features. Unsupervised clustering algorithms are presented in the second part of the thesis. A review of validity criteria and information measures is given in order to estimate the quality of clustering solutions. A new criterion based on Minimum Description Length (MDL) is proposed for estimating the optimal number of clusters. In addition, we propose a new kernel hierarchical clustering algorithm based on kernel MDL criterion. A new method of ”clustering combination” is presented in the thesis in order to benefit from several clusterings issued from different algorithms. We develop a hierarchical algorithm to optimise the objective function based on a co-association matrix. A second method is proposed which converges to a global solution. We prove that the global minimum may be found using the gradient density function estimation by the mean shift procedure. Advantages of this method are a fast convergence and a linear complexity. In the third part of the thesis a complete protocol of unsupervised satellite images mining is proposed. Different clustering results are represented via semantic relations between concepts
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Huang, Chang-Min, and 黃昶閔. "A Circuit Implementation of Random Sample Consensus Algorithm for Feature-based Image Registration Applications." Thesis, 2012. http://ndltd.ncl.edu.tw/handle/31620421641171434252.
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碩士國立交通大學
電機工程學系
101
With the camera calibration and image processing development in recent years, image registration has become more important in the image processing increasingly. The application of the image registration is also increasingly widespread. This thesis proposes a circuit implementation of RANdom SAmple Consensus (RANSAC)for feature-based image registration applications. In order to achieve the effect of random sampling, the interleaving and the group shuffling method are adopted to disorder the stored matching feature point coordinates. This thesis uses the systolic array architecture to implement the forward elimination step in the Gaussian elimination. The computational complexity in the forward elimination is reduced by sharing the coefficient matrix. As a result, the area of the hardware cost is reduced by more than 50%.The using of the look-up table for the divider circuit implementation make the calculation can be done in a single clock cycle without any iteration. The proposed architecture is realized by using verilog and achieves real-time calculation on 30fps 1024 * 1024 video stream on 100 MHz clock.
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Venugopalakrishna, Y. R. "Data Fusion Based Physical Layer Protocols for Cognitive Radio Applications." Thesis, 2016. http://etd.iisc.ernet.in/handle/2005/2683.
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This thesis proposes and analyzes data fusion algorithms that operate on the physical layer of a wireless sensor network, in the context of three applications of cognitive radios: 1. Cooperative spectrum sensing via binary consensus; 2. Multiple transmitter localization and communication footprint identification; 3.Target self-localization using beacon nodes.
For the first application, a co-phasing based data combining scheme is studied under imperfect channel knowledge. The evolution of network consensus state is modeled as a Markov chain, and the average transition probability matrix is derived. Using this, the average hitting time and average consensus duration are obtained, which are used to determine and optimize the performance of the consensus procedure.
Second, using the fact that a typical communication footprint map admits a sparse representation, two novel compressed sensing based schemes are proposed to construct the map using 1-bit decisions from sensors deployed in a geographical area. The number of transmitters is determined using the K-means algorithm and a circular fitting technique, and a design procedure is proposed to determine the power thresholds for signal detection at sensors.
Third, an algorithm is proposed for self-localization of a target node using power measurements from beacon nodes transmitting from known locations. The geographical area is overlaid with a virtual grid, and the problem is treated as one of testing overlapping subsets of grid cells for the presence of the target node. The column matching algorithm from group testing literature is considered for devising the target localization algorithm. The average probability of localizing the target within a grid cell is derived using the tools from Poisson point processes and order statistics. This quantity is used to determine the minimum required node density to localize the target within a grid cell with high probability.
The performance of all the proposed algorithms is illustrated through Monte Carlo simulations.
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Bonadio, Alessio. "Mobile Computing and Networking Architectures for the Internet of Vehicles." Doctoral thesis, 2021. http://hdl.handle.net/2158/1259056.
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This thesis starts by considering the problem of data dissemination, investigating several network schemes. Besides, to ensure the consistency of the data collected, a distributed consensus sensing application is designed. Then, a mobile Edge computing system is modeled. This paradigm provides computational capabilities at the edge of the network and is able to fulfill the requirements of the Internet of Mobile Things. The model is used to derive the minimum number of processors to be allocated to obtain a given requests dropping probability. Finally, mobile Edge computing and Cloud computing systems are compared. Two analytical models are developed and validated, considering the total service time as a key metric. The comparison gives some insight on how these systems should be designed to handle a given load.
Books on the topic "Consensus Based Applications"
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Mitchener, Donald K. U.S. Naval Gunfire Support in the Pacific War. University Press of Kentucky, 2021. http://dx.doi.org/10.5810/kentucky/9781949668124.001.0001.
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On November 20, 1943, the U.S. military invaded the Tarawa Atoll of the Gilbert Islands as part of the first American offensive in the Central Pacific region during World War II. This invasion marked more than one first, as it was also the introductory test of a doctrine developed during the interwar years to address problems inherent in situations in which amphibious assaults required support by naval gunfire rather than land-based artillery. In this detailed study, Donald K. Mitchener documents and analyzes the prewar development of this doctrine as well as its application and evolution between the years 1943-1945. The historical consensus is that the test at Tawara was successful and increased the efficiency with which U.S. forces were able to apply the doctrine in the Pacific theater for the remainder of the Second World War. Mitchener challenges this view, arguing that the reality was much more complex. He reveals that strategic concerns often took precedence over the lessons learned in the initial engagement, and that naval planners' failure to stay up to date with the latest doctrinal developments and applications sometimes led them to ignore these lessons altogether. U.S. Naval Gunfire Support in the Pacific War presents an important analysis that highlights the human cost of misinterpreting strategic and tactical realities.
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Bolfing, Andreas. Cryptographic Primitives in Blockchain Technology. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198862840.001.0001.
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Many online applications, especially in the financial industries, are running on blockchain technologies in a decentralized manner, without the use of an authoritative entity or a trusted third party. Such systems are only secured by cryptographic protocols and a consensus mechanism. As blockchain-based solutions will continue to revolutionize online applications in a growing digital market in the future, one needs to identify the principal opportunities and potential risks. Hence, it is unavoidable to learn the mathematical and cryptographic procedures behind blockchain technology in order to understand how such systems work and where the weak points are. The book provides an introduction to the mathematical and cryptographic concepts behind blockchain technologies and shows how they are applied in blockchain-based systems. This includes an introduction to the general blockchain technology approaches that are used to build the so-called immutable ledgers, which are based on cryptographic signature schemes. As future quantum computers will break some of the current cryptographic primitive approaches, the book considers their security and presents the current research results that estimate the impact on blockchain-based systems if some of the cryptographic primitive break. Based on the example of Bitcoin, it shows that weak cryptographic primitives pose a possible danger for the ledger, which can be overcome through the use of the so-called post-quantum cryptographic approaches which are introduced as well.
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Wolfson, Todd, ed. Governance: Democracy All the Way Down. University of Illinois Press, 2017. http://dx.doi.org/10.5406/illinois/9780252038846.003.0006.
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This chapter examines indymedia's multilayered, transnational application of direct democracy, which in many ways anticipates and sets the stage for Occupy Wall Street. It focuses on the ways that democracy is understood and enacted by indymedia activists—from the development of an open media system where anyone can speak (democratizing the media), to the preference for consensus-based decision making (democratic governance), and the belief that activists must develop the structures, processes, and relationships within the movement that they aim to achieve in the world (prefigurative politics). Seen from this vantage, for indymedia activists democracy is multivalent, standing in as the end goal of a new society, a revolutionary tool to remake that society, and the everyday practice that allows for innovation and new forms of collective power.
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Geddes, John R., Nancy C. Andreasen, and Guy M. Goodwin, eds. New Oxford Textbook of Psychiatry. Oxford University Press, 2020. http://dx.doi.org/10.1093/med/9780198713005.001.0001.
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The third edition of the textbook presents psychiatry as a medical specialty. The application of science has transformed much of medicine by providing an understanding of the mechanisms of pathology. The genetic basis of psychiatry guarantees a future for explanation by neuroscience. The book sets the scene for such development by explaining the key issues relating to the patient’s perspective, stigma, the global challenge of mental disorder, practical ethics, and the foundations of psychiatry as phenomenology and a medical discipline. It further explains current controversies around diagnosis, psychopathology, evidence, and drug terminology. The scientific basis of psychiatric aetiology and treatment provide simple introductions to the relevant disciplines that underpin our scientific understanding. Individual disorders are covered in sections that follow the structure of the Diagnostic and Statistical Manual of Mental Disorders, fifth edition (DSM-5). Thus, it follows a clinically led summary of how patients present with psychiatric disorder. There is no denying the current utility of symptom-based diagnoses and the consensus that created the current categories. However, the project of applying neuroscience to psychiatry has not failed, as has sometimes been implied by criticism of DSM-5. For these reasons, chapters have been included on genetics, neurobiological targets, and imaging in the sections of the book focused on specific disorders. Sections have also been included on service provision and forensic psychiatry because these are critical to the context in which psychiatric disorder is managed.
Book chapters on the topic "Consensus Based Applications"
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Caicedo-Núñez, Carlos H., and Miloš Žefran. "Counting and Rendezvous: Two Applications of Distributed Consensus in Robotics." In Wireless Networking Based Control, 175–201. New York, NY: Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-7393-1_8.
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Nguyen, Ngoc Thanh, and Hai Bang Truong. "A Consensus-Based Method for Fuzzy Ontology Integration." In Computational Collective Intelligence. Technologies and Applications, 480–89. Berlin, Heidelberg: Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-16732-4_51.
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Fornasier, Massimo, Timo Klock, and Konstantin Riedl. "Convergence of Anisotropic Consensus-Based Optimization in Mean-Field Law." In Applications of Evolutionary Computation, 738–54. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-02462-7_46.
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Mudumbai, Raghuraman, Soura Dasgupta, and M. Muhammad Mahboob Ur Rahman. "Analysis of a Distributed Consensus Based Economic Dispatch Algorithm." In Systems & Control: Foundations & Applications, 481–500. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-030-04630-9_14.
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Sobecki, Janusz, and Ngoc Thanh Nguyen. "Consensus-Based Adaptive Interface Construction for Multiplatform Web Applications." In Intelligent Data Engineering and Automated Learning, 457–61. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003. http://dx.doi.org/10.1007/978-3-540-45080-1_62.
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Wang, Dong, Chenguang Jin, Han Li, and Marek Perkowski. "Proof of Activity Consensus Algorithm Based on Credit Reward Mechanism." In Web Information Systems and Applications, 618–28. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-60029-7_55.
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Qu, Yaohong, Xu Zhu, and Youmin M. Zhang. "Cooperative Control for UAV Formation Flight Based on Decentralized Consensus Algorithm." In Intelligent Robotics and Applications, 357–66. Berlin, Heidelberg: Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-33509-9_35.
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Jiao, Zilong, and Jae Oh. "Consensus-Based Protocol for Distributed Exploration and Mapping." In Trends in Artificial Intelligence Theory and Applications. Artificial Intelligence Practices, 533–44. Cham: Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-55789-8_46.
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Jung, Jason J., and Geun-Sik Jo. "Consensus-Based Evaluation Framework for Cooperative Information Retrieval Systems." In Agent and Multi-Agent Systems: Technologies and Applications, 169–78. Berlin, Heidelberg: Springer Berlin Heidelberg, 2007. http://dx.doi.org/10.1007/978-3-540-72830-6_18.
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Liu, Xiyu, Yuzhen Zhao, and Wenxing Sun. "K-Medoids-Based Consensus Clustering Based on Cell-Like P Systems with Promoters and Inhibitors." In Bio-inspired Computing – Theories and Applications, 95–108. Singapore: Springer Singapore, 2016. http://dx.doi.org/10.1007/978-981-10-3611-8_11.
Full textConference papers on the topic "Consensus Based Applications"
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Caicedo-Nunez, Carlos H., and Milos Zefran. "Consensus-based rendezvous." In 2008 IEEE International Conference on Control Applications (CCA) part of the IEEE Multi-Conference on Systems and Control. IEEE, 2008. http://dx.doi.org/10.1109/cca.2008.4629611.
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Gong, Bei, Zhenhu Ning, Wenjing Li, and Shanshan Tu. "Consensus Algorithm Based on Subject Credit." In ICSCA 2022: 2022 11th International Conference on Software and Computer Applications. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3524304.3524321.
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Gong, Bei, Zhenhu Ning, Wenjing Li, and Shanshan Tu. "Consensus Algorithm Based on Subject Credit." In ICSCA 2022: 2022 11th International Conference on Software and Computer Applications. New York, NY, USA: ACM, 2022. http://dx.doi.org/10.1145/3524304.3524321.
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Lizzio, Fausto Francesco, Elisa Capello, and Giorgio Guglieri. "A Review of Consensus-based Multi-agent UAV Applications." In 2021 International Conference on Unmanned Aircraft Systems (ICUAS). IEEE, 2021. http://dx.doi.org/10.1109/icuas51884.2021.9476858.
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Mallik, Galib R., Sangeeta Daingade, and Arpita Sinha. "Consensus based deviated cyclic pursuit for target tracking applications." In 2015 European Control Conference (ECC). IEEE, 2015. http://dx.doi.org/10.1109/ecc.2015.7330785.
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Saunois, Geoffrey, Frederique Robin, Emmanuelle Anceaume, and Bruno Sericola. "Permissionless Consensus based on Proof-of-Eligibility." In 2020 IEEE 19th International Symposium on Network Computing and Applications (NCA). IEEE, 2020. http://dx.doi.org/10.1109/nca51143.2020.9306715.
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Mata, Francisco, Pedro Sanchez, Ivan Palomares, J. Quesada Francisco, and Luis Martinez. "COMAS: A consensus multi-agent based system." In 2010 10th International Conference on Intelligent Systems Design and Applications (ISDA). IEEE, 2010. http://dx.doi.org/10.1109/isda.2010.5687223.
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Ilic, Nemanja, Milos S. Stankovic, and Srdjan S. Stankovic. "Adaptive sensor networks for consensus based distributed estimation." In 2012 IEEE International Conference on Control Applications (CCA). IEEE, 2012. http://dx.doi.org/10.1109/cca.2012.6402382.
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La, Hung Manh, and Weihua Sheng. "Cooperative sensing in mobile sensor networks based on distributed consensus." In SPIE Optical Engineering + Applications, edited by Oliver E. Drummond. SPIE, 2011. http://dx.doi.org/10.1117/12.895519.
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Zhang, Xueji, Kristian Hengster-Movric, Michael Sebek, Wim Desmet, and Cassio Faria. "Consensus-based distributed sensor fusion over a network." In 2017 IEEE Conference on Control Technology and Applications (CCTA). IEEE, 2017. http://dx.doi.org/10.1109/ccta.2017.8062540.
Full textReports on the topic "Consensus Based Applications"
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Allende López, Marcos, Diego López, Sergio Cerón, Antonio Leal, Adrián Pareja, Marcelo Da Silva, Alejandro Pardo, et al. Quantum-Resistance in Blockchain Networks. Inter-American Development Bank, June 2021. http://dx.doi.org/10.18235/0003313.
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This paper describes the work carried out by the Inter-American Development Bank, the IDB Lab, LACChain, Cambridge Quantum Computing (CQC), and Tecnológico de Monterrey to identify and eliminate quantum threats in blockchain networks. The advent of quantum computing threatens internet protocols and blockchain networks because they utilize non-quantum resistant cryptographic algorithms. When quantum computers become robust enough to run Shor's algorithm on a large scale, the most used asymmetric algorithms, utilized for digital signatures and message encryption, such as RSA, (EC)DSA, and (EC)DH, will be no longer secure. Quantum computers will be able to break them within a short period of time. Similarly, Grover's algorithm concedes a quadratic advantage for mining blocks in certain consensus protocols such as proof of work. Today, there are hundreds of billions of dollars denominated in cryptocurrencies that rely on blockchain ledgers as well as the thousands of blockchain-based applications storing value in blockchain networks. Cryptocurrencies and blockchain-based applications require solutions that guarantee quantum resistance in order to preserve the integrity of data and assets in their public and immutable ledgers. We have designed and developed a layer-two solution to secure the exchange of information between blockchain nodes over the internet and introduced a second signature in transactions using post-quantum keys. Our versatile solution can be applied to any blockchain network. In our implementation, quantum entropy was provided via the IronBridge Platform from CQC and we used LACChain Besu as the blockchain network.
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Butler, John M. Bitemark Analysis. Gaithersburg, MD: National Institute of Standards and Technology, 2022. http://dx.doi.org/10.6028/nist.ir.8352-draft.
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This report summarizes a review of the scientific foundations of bitemark analysis conducted by the National Institute of Standards and Technology (NIST). Bitemark analysis typically involves examining patterned injuries left on a victim or object at a crime scene, identifying those injuries as bitemarks, and comparing those marks with dental impressions from a person of interest. This review specifically focuses on pattern injuries found on human skin. Over 400 sources were considered via literature searches and input from previous efforts by the National Institute of Justice Forensic Technology Center of Excellence. Our NIST review also utilized input from an October 2019 Bitemark Thinkshop organized by the Center for Statistics and Applications in Forensic Evidence (CSAFE) where experts and stakeholders associated with bitemark analysis were convened to discuss key issues. Based on this input, our study found a lack of support for three key premises of the field: 1) human dentition is unique at the individual level, 2) this uniqueness can be accurately transferred to human skin, and 3) identifying characteristics can be accurately captured and interpreted by analysis techniques. Furthermore, our review noted a lack of consensus among practitioners on the interpretation of bitemark evidence as well as thoughts on how to move the field forward. If the field seeks to advance, the key takeaways provided in this review are starting points for areas needing improvement, not an exhaustive list of specific shortcomings.
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Anderson, Gerald L., and Kalman Peleg. Precision Cropping by Remotely Sensed Prorotype Plots and Calibration in the Complex Domain. United States Department of Agriculture, December 2002. http://dx.doi.org/10.32747/2002.7585193.bard.
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This research report describes a methodology whereby multi-spectral and hyperspectral imagery from remote sensing, is used for deriving predicted field maps of selected plant growth attributes which are required for precision cropping. A major task in precision cropping is to establish areas of the field that differ from the rest of the field and share a common characteristic. Yield distribution f maps can be prepared by yield monitors, which are available for some harvester types. Other field attributes of interest in precision cropping, e.g. soil properties, leaf Nitrate, biomass etc. are obtained by manual sampling of the filed in a grid pattern. Maps of various field attributes are then prepared from these samples by the "Inverse Distance" interpolation method or by Kriging. An improved interpolation method was developed which is based on minimizing the overall curvature of the resulting map. Such maps are the ground truth reference, used for training the algorithm that generates the predicted field maps from remote sensing imagery. Both the reference and the predicted maps are stratified into "Prototype Plots", e.g. 15xl5 blocks of 2m pixels whereby the block size is 30x30m. This averaging reduces the datasets to manageable size and significantly improves the typically poor repeatability of remote sensing imaging systems. In the first two years of the project we used the Normalized Difference Vegetation Index (NDVI), for generating predicted yield maps of sugar beets and com. The NDVI was computed from image cubes of three spectral bands, generated by an optically filtered three camera video imaging system. A two dimensional FFT based regression model Y=f(X), was used wherein Y was the reference map and X=NDVI was the predictor. The FFT regression method applies the "Wavelet Based", "Pixel Block" and "Image Rotation" transforms to the reference and remote images, prior to the Fast - Fourier Transform (FFT) Regression method with the "Phase Lock" option. A complex domain based map Yfft is derived by least squares minimization between the amplitude matrices of X and Y, via the 2D FFT. For one time predictions, the phase matrix of Y is combined with the amplitude matrix ofYfft, whereby an improved predicted map Yplock is formed. Usually, the residuals of Y plock versus Y are about half of the values of Yfft versus Y. For long term predictions, the phase matrix of a "field mask" is combined with the amplitude matrices of the reference image Y and the predicted image Yfft. The field mask is a binary image of a pre-selected region of interest in X and Y. The resultant maps Ypref and Ypred aremodified versions of Y and Yfft respectively. The residuals of Ypred versus Ypref are even lower than the residuals of Yplock versus Y. The maps, Ypref and Ypred represent a close consensus of two independent imaging methods which "view" the same target. In the last two years of the project our remote sensing capability was expanded by addition of a CASI II airborne hyperspectral imaging system and an ASD hyperspectral radiometer. Unfortunately, the cross-noice and poor repeatability problem we had in multi-spectral imaging was exasperated in hyperspectral imaging. We have been able to overcome this problem by over-flying each field twice in rapid succession and developing the Repeatability Index (RI). The RI quantifies the repeatability of each spectral band in the hyperspectral image cube. Thereby, it is possible to select the bands of higher repeatability for inclusion in the prediction model while bands of low repeatability are excluded. Further segregation of high and low repeatability bands takes place in the prediction model algorithm, which is based on a combination of a "Genetic Algorithm" and Partial Least Squares", (PLS-GA). In summary, modus operandi was developed, for deriving important plant growth attribute maps (yield, leaf nitrate, biomass and sugar percent in beets), from remote sensing imagery, with sufficient accuracy for precision cropping applications. This achievement is remarkable, given the inherently high cross-noice between the reference and remote imagery as well as the highly non-repeatable nature of remote sensing systems. The above methodologies may be readily adopted by commercial companies, which specialize in proving remotely sensed data to farmers.
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Daudelin, Francois, Lina Taing, Lucy Chen, Claudia Abreu Lopes, Adeniyi Francis Fagbamigbe, and Hamid Mehmood. Mapping WASH-related disease risk: A review of risk concepts and methods. United Nations University Institute for Water, Environment and Health, December 2021. http://dx.doi.org/10.53328/uxuo4751.
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The report provides a review of how risk is conceived of, modelled, and mapped in studies of infectious water, sanitation, and hygiene (WASH) related diseases. It focuses on spatial epidemiology of cholera, malaria and dengue to offer recommendations for the field of WASH-related disease risk mapping. The report notes a lack of consensus on the definition of disease risk in the literature, which limits the interpretability of the resulting analyses and could affect the quality of the design and direction of public health interventions. In addition, existing risk frameworks that consider disease incidence separately from community vulnerability have conceptual overlap in their components and conflate the probability and severity of disease risk into a single component. The report identifies four methods used to develop risk maps, i) observational, ii) index-based, iii) associative modelling and iv) mechanistic modelling. Observational methods are limited by a lack of historical data sets and their assumption that historical outcomes are representative of current and future risks. The more general index-based methods offer a highly flexible approach based on observed and modelled risks and can be used for partially qualitative or difficult-to-measure indicators, such as socioeconomic vulnerability. For multidimensional risk measures, indices representing different dimensions can be aggregated to form a composite index or be considered jointly without aggregation. The latter approach can distinguish between different types of disease risk such as outbreaks of high frequency/low intensity and low frequency/high intensity. Associative models, including machine learning and artificial intelligence (AI), are commonly used to measure current risk, future risk (short-term for early warning systems) or risk in areas with low data availability, but concerns about bias, privacy, trust, and accountability in algorithms can limit their application. In addition, they typically do not account for gender and demographic variables that allow risk analyses for different vulnerable groups. As an alternative, mechanistic models can be used for similar purposes as well as to create spatial measures of disease transmission efficiency or to model risk outcomes from hypothetical scenarios. Mechanistic models, however, are limited by their inability to capture locally specific transmission dynamics. The report recommends that future WASH-related disease risk mapping research: - Conceptualise risk as a function of the probability and severity of a disease risk event. Probability and severity can be disaggregated into sub-components. For outbreak-prone diseases, probability can be represented by a likelihood component while severity can be disaggregated into transmission and sensitivity sub-components, where sensitivity represents factors affecting health and socioeconomic outcomes of infection. -Employ jointly considered unaggregated indices to map multidimensional risk. Individual indices representing multiple dimensions of risk should be developed using a range of methods to take advantage of their relative strengths. -Develop and apply collaborative approaches with public health officials, development organizations and relevant stakeholders to identify appropriate interventions and priority levels for different types of risk, while ensuring the needs and values of users are met in an ethical and socially responsible manner. -Enhance identification of vulnerable populations by further disaggregating risk estimates and accounting for demographic and behavioural variables and using novel data sources such as big data and citizen science. This review is the first to focus solely on WASH-related disease risk mapping and modelling. The recommendations can be used as a guide for developing spatial epidemiology models in tandem with public health officials and to help detect and develop tailored responses to WASH-related disease outbreaks that meet the needs of vulnerable populations. The report’s main target audience is modellers, public health authorities and partners responsible for co-designing and implementing multi-sectoral health interventions, with a particular emphasis on facilitating the integration of health and WASH services delivery contributing to Sustainable Development Goals (SDG) 3 (good health and well-being) and 6 (clean water and sanitation).