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Case-Based Support Vector Optimization for Medical-Imaging Imbalanced Datasets 13th

Case-Based Support Vector Optimization for Medical-Imaging I...

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Int Joint Conf of the 13th Int Conf on Soft Comp Models in Ind and Environm Applicat (SOCO) / 11th Int Conf on Computat Intelligence in Secur for Informat Syst (CISIS) / 9th Int Conf on European Transnat Educ (ICEUTE)

作者： Illan, I. A. Ramirez, J. Gorriz, J. M. Pinker, K. Meyer-Baese, A. Florida State Univ Sci Comp Dept Tallahassee FL 32306 USA Mem Sloan Kettering Canc Ctr Dept Radiol 1275 York Ave New York NY 10021 USA Med Univ Vienna AKH Wien Dept Biomed Imaging & Image Guided Therapy Div Mol & Gender Imaging Vienna Austria Univ Granada Dept Signal Theory Networking & Commun Granada Spain

ISBN: (纸本)9783319941202;9783319941196

Imbalanced datasets constitute a challenge in medical-image processing and machine learning in general. When the available training data is highly imbalanced, the risk for a classifier to find the trivial solution increases dramatically. To control the risk, an estimate on the prior class probabilities is usually required. In some medical datasets, such as breast cancer imaging techniques, estimates on the priors are intractable. Here we propose a solution to the imbalanced support vector classification problem when prior estimations are absent based on a case-dependent transformation on the decision function.

关键词： Medical image processing Support vector machines DCE-MRI Imbalanced datasets

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Accelerating Fireworks Algorithm with Dynamic Population Size Strategy

Accelerating Fireworks Algorithm with Dynamic Population Siz...

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international Symposium on Soft computing and Intelligent Systems (SCIS)

作者： Jun Yu Hideyuki Takagi Institute of Science and Technology Niigata University Niigata Japan Faculty of Design Kyushu University Fukuoka Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

A dynamic population size strategy is proposed for the fireworks algorithm (FWA) to adjust the population size based to the search results of the current generation. When the currently found optimal individual is updated, a linear decreasing method is activated to maintain an efficient exploitation speed. the population size is reduced by 1 until the minimum preset population size is reached, then the population size remains unchanged. Otherwise, we randomly generate a larger population size than the initial population and expand the explosion amplitudes of all firework individuals artificially, which the expectation that we can escape current local minima. To analyze the effectiveness of the proposed strategy, we combined it with the enhanced FWA (EFWA) together, and run the EFWA and (the EFWA + our proposed strategy) on 28 CEC 2013 benchmark functions in three different dimensions. Each function is run 30 trial times independently, and the Wilcoxon signed-rank test is applied to check significant differences. the statistical results showed that the proposed dynamic population size strategy can not only achieve a faster convergence speed for the FWA but also can jump out of trapped local minima more easily to maintain a higher performance, especially for high-dimensional problems.

关键词： Statistics Sociology Explosions Sparks Optimization Heuristic algorithms Next generation networking

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High-degree noise addition method for the $k$-degree anonymization algorithm

High-degree noise addition method for the $k$-degree anonymi...

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international Symposium on Soft computing and Intelligent Systems (SCIS)

作者： Jana Medková University of Hradec Kralove Hradec Kralove Czech Republic

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

Social network datasets are a valuable source of information for academic researches as well as business and marketing studies. Since social network datasets contain personal and sensitive information of their users, sharing the data with a third party gives rise to many privacy-preserving issues. the k-degree anonymization was developed to protect the users of social networks from the re-identification attack by modifying the network structure with a sequence of edge editing operations. In this paper, we introduce a novel approach for noise addition operation in the well-known k-degree anonymization algorithm k-DA. We propose the high-degree noise addition method that modifies the degree sequence anonymized by the degree anonymization procedure of k-DA before it is processed by the graph construction procedure of k-DA. Our proposed method significantly reduces the number of necessary repetitions of the graph constructing algorithm and positively affects the efficiency and runtime of the whole k-DA algorithm. Moreover, we show that the proposed high-degree noise addition algorithm improves k-DA in terms of data utility. We demonstrate its usability by running experiments on 13 different real-world social network datasets.

关键词： Greedy algorithms Social networking (online) Heuristic algorithms Privacy Usability Publishing Merging

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Leveraging Profanity for Insincere Content Detection - A Neural Network Approach

Leveraging Profanity for Insincere Content Detection - A Neu...

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international conference and Workshop on computing and Communication (IEMCON)

作者： Swapna Gottipati Annabel Tan David Chow Jing Shan Joel Lim Wee Kiat School of Information Systems Singapore Management University

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

Community driven social media sites are rich sources of knowledge and entertainment and at the same vulnerable to the flames or toxic content that can be dangerous to various users of these platforms as well as to the society. therefore, it is crucial to identify and remove such content to have a better and safe online experience. Manually eliminating flames is tedious and hence many research works focus on machine learning or deep learning models for automated methods. In this paper, we primarily focus on detecting the insincere content using neural network-based learning methods. We also integrated the profanity features as profanity is correlated with honesty according to psychology research. We tested our model on the questions datasets from CQA platform to detect the insincere content. Our integrated neural network model enabled us to achieve a high performance of F1-score, 94.01%, compared to the standard machine learning algorithms.

关键词： Deep learning Training Machine learning algorithms Social networking (online) Neural networks Psychology Fires

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Processing of Aggregate Continuous Queries in a distributed Environment 9th

Processing of Aggregate Continuous Queries in a Distributed ...

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9th international Workshop on Business Intelligence for the Real-Time Enterprise, BIRTE 2015, 10th international Workshop on Enabling Real-Time Business Intelligence, BIRTE 2016 and 11th international Workshop on Real-Time Business Intelligence and Analytics, BIRTE 2017 held in conjunction with the international conference on Very Large Data Bases, VLDB 2017

作者： Shein, Anatoli U. Chrysanthis, Panos K. Labrinidis, Alexandros Department of Computer Science University of Pittsburgh PittsburghPA15260 United States

ISBN: (纸本)9783030241230

Data Stream Management Systems (DSMSs) performing online analytics rely on the efficient execution of large numbers of Aggregate Continuous Queries (ACQs). In this paper, we study the problem of generating high quality execution plans of ACQs in DSMSs deployed on multi-node (multi-core and multi-processor) distributed environments. Towards this goal, we classify optimizers based on how they partition the workload among computing nodes and on their usage of the concept of Weavability, which is utilized by the state-of-the-art WeaveShare optimizer to selectively combine ACQs and produce low cost execution plans for single-node environments. For each category, we propose an optimizer, which either adopts an existing strategy or develops a new one for assigning and grouping ACQs to computing nodes. We implement and experimentally compare all of our proposed optimizers in terms of (1) keeping the total cost of the ACQs execution plan low and (2) balancing the load among the computing nodes. Our extensive experimental evaluation shows that our newly developed Weave-Group to Nodes ((Forumala Presented).) and Weave-Group Inserted ((Forumala Presented). optimizers produce plans of significantly higher quality than the rest of the optimizers. (Forumala Presented). minimizes the total cost, making it more suitable from a client perspective, and (Forumala Presented). achieves load balancing, making it more suitable from a system perspective. © Springer Nature Switzerland AG 2019.

关键词： Information management

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Modelling and Analysing Overlay Networks by Ambients with Wormholes 11

Modelling and Analysing Overlay Networks by Ambients with Wo...

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11th international conference on Mobile computing and Ubiquitous Network (ICMU)

作者： Hansen, Rene Rydhof Probst, Christian W. Aalborg Univ Aalborg Denmark Unitec Inst Technol Auckland New Zealand

ISBN: (纸本)9784907626341

Process calculi are a powerful mechanism to formally model distributed systems, and are especially useful for assessing trust, security, and privacy issues in mobile and ubiquitous computing and networking. However, they often only support a single modelling approach and semantics, whereas distributed systems and networks often are a conglomeration of different technologies and functionalities. In this paper we propose a novel approach to model these systems and make them amenable to formal analysis. We enhance the ambient calculus with "wormholes" as a convenient way for ambients to travel between "worlds" representing the different technologies and functionalities by means of different semantic layers. Our approach enables easy and natural modelling and analysis of multi-layer systems for ubiquitous computing and networking.

关键词： Mobile computing Overlay networks Mobile communication architectures

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Realizing Edge computing connectivity with Open Virtual networking 11

Realizing Edge Computing connectivity with Open Virtual Netw...

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11th IEEE/ACM international conference on Utility and Cloud computing (UCC-Companion) / 5th IEEE/ACM international conference on Big Data computing, Applications and Technologies (BDCAT)

作者： Murphy, S. Edmonds, A. Zurcher Hsch Angew Wissensch Winterthur Switzerland

ISBN: (纸本)9781728103594

Edge computing will likely be of significant import to the Smart City context, providing a means to deploy and manage large distributed applications [5] [3]. Although Edge computing is receiving significant attention at present, many issues relating to this paradigm remain unclear. In this paper, we focus specifically on mechanisms required to extend Data Centre networking technologies to edge devices. More specifically, we describe the solution we have developed which enables Open Virtual networking (OVN) to be extended to the edge to support integration with a docker engine located at the edge of the network. the mechanisms consist of a process by which a docker engine can request to join the network, an approval process which leverages Openstack authentication and access control mechanisms, a mechanism by which the remote system can connect to the OVN and finally containers can be initialized on the remote docker engine and interact with entities operating in the Enterprise Data Centre.

关键词： Engines Edge computing Data centers Smart cities Neutrons IP networks Containers

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MESH: A Flexible distributed Hypergraph Processing System 7

MESH: A Flexible Distributed Hypergraph Processing System

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7th IEEE international conference on Cloud Engineering (IEEE IC2E)

作者： Heintz, Benjamin Hong, Rankyung Singh, Shivangi Khandelwal, Gaurav Tesdahl, Corey Chandra, Abhishek Univ Minnesota Minneapolis MN 55455 USA

ISBN: (纸本)9781728102184

With the rapid growth of large online social networks, the ability to analyze large-scale social structure and behavior has become critically important, and this has led to the development of several scalable graph processing systems. In reality, however, social interaction takes place not only between pairs of individuals as in the graph model, but rather in the context of multi-user groups. Research has shown that such group dynamics can be better modeled through a more general hypergraph model, resulting in the need to build scalable hypergraph processing systems. In this paper, we present MESH, a flexible distributed framework for scalable hypergraph processing. MESH provides an easy-to-use and expressive application programming interface that naturally extends the "think like a vertex" model common to many popular graph processing systems. Our framework provides a flexible implementation based on an underlying graph processing system, and enables different design choices for the key implementation issues of partitioning a hypergraph representation. We implement MESH on top of the popular GraphX graph processing framework in Apache Spark. Using a variety of real datasets and experiments conducted on a local 8-node cluster as well as a 65-node Amazon AWS testbed, we demonstrate that MESH provides flexibility based on data and application characteristics, as well as scalability with cluster size. We further show that it is competitive in performance to HyperX, another hypergraph processing system based on Spark, while providing a much simpler implementation (requiring about 5X fewer lines of code), thus showing that simplicity and flexibility need not come at the cost of performance.

关键词： Computational modeling Manganese Cluster computing Scalability Partitioning algorithms Sparks Social networking (online)

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A Low-Power Tapered Matrix distributed Amplifier for Ultra-Wide-Band Applications

A Low-Power Tapered Matrix Distributed Amplifier for Ultra-W...

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international conference and Workshop on computing and Communication (IEMCON)

作者： Mehrdad Harifi-Mood Somayye Abbasi Avval Abolfazl Bijari Nabeeh Kandalaft University of Birjand Birjand Iran Grand Valley State University Grand Rapides Michigan USA

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

A fully integrated tapered matrix distributed amplifier (DA) for broadband applications is presented in this paper. the DA is designed in the TSMC 180 nm CMOS RF process. For the gain improvement, the proposed DA employs a matrix architecture to take advantage of the additive and multiplicative gain mechanisms simultaneously. In addition, tapered transmission line technique is used to mitigate power consumption. Also, the terminating resistor of the input transmission line is replaced with an optimized RL-network to ameliorate the noise curve of the DA. In the first stage, the DA used a tunable cascode amplifier as the gain cells to extend the bandwidth. Based on simulation results, the proposed DA with a 3-dB bandwidth of 19.5 GHz demonstrates a flat power gain (S21) of 12+1 dB. throughout the frequency range, S 11 and S 22 of the DA are below than -10 dB. the noise figure (NF) varies between 5 ~ 6.75 dB and the average third-order input intercept point (IIP3) in the operating band is -3.75 dBm. the proposed DA consumes a DC power of 25 mW from a 1-V supply.

关键词： Resistors Radio frequency distributed amplifiers Transmission line matrix methods Power transmission lines Bandwidth Gain

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11th international conference on Ad Hoc Networks, ADHOCNETS 2019

11th International Conference on Ad Hoc Networks, ADHOCNETS ...

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11th international conference on Ad Hoc Networks, ADHOCNETS 2019

ISBN: (纸本)9783030372613

the proceedings contain 26 papers. the special focus in this conference is on Ad Hoc Networks. the topics include: Medium Access Control for Flying Ad Hoc Networks Using Directional Antennas: Challenges, Research Status, and Open Issues;fair Resource Allocation Based on Deep Reinforcement Learning in Fog Networks;multi-agent Reinforcement Learning for Joint Wireless and Computational Resource Allocation in Mobile Edge computing System;cooperative Transmission with Power Control in the Hyper-cellular Network;energy-Efficient Power Allocation for Fading Device-to-Device Channels in Downlink Resource Sharing Communication;delay Based Wireless Scheduling and Server Assignment for Fog computing Systems;High Precision Indoor Positioning Method Based on UWB;improvement of a Single Node Indoor Localization System;an Efficient Approach for Rigid Body Localization via a Single Base Station Using Direction of Arrive Measurement;Design and Mobile Tracking Performance of a Retro-Directive Array (RDA) Antenna System;EL-CRP: An Energy and Location Aware Clustering Routing Protocol in Large Scale Wireless Sensor Networks;the Effects of Non-line of Sight (NLOS) Channel on a User with Varying Device Orientations;Multiobjective Collaborative Beamforming for a distributed Satellite Cluster via NSGA-II;AMP Inspired Antenna Activity and Signal Detection Algorithm for Generalized Spatial Modulated NOMA;a Filtering Dimension Reduction Decoding Algorithm for Underwater Acoustic Networks;a Homology Based Coverage Optimization Algorithm for Wireless Sensor Networks;rail Vehicle Fire Warning System Based on Gas Vapor Sensor Network;guessing Intrinsic Forwarding Trustworthiness of Wireless Ad Hoc Network Nodes;LEER: Layer-Based and Energy-Efficient Routing Protocol for Underwater Sensor Networks;MBA-DbMAC: A Random-Access MAC Protocol for MBAs.

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