We present a framework for sentiment analysis on tweets related to news items. Given a set of tweets and news items, our framework classifies tweets as positive or negative and links them to the related news items. Fo...
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ISBN:
(纸本)9781509006632
We present a framework for sentiment analysis on tweets related to news items. Given a set of tweets and news items, our framework classifies tweets as positive or negative and links them to the related news items. For the classification of tweets we use three of the most used machine learning methods, namely Naive Bayes, Complementary Naive Bayes, and Logistic Regression, and for linking tweets to news items, Natural Language Processing (NLP) techniques are used, including Zemberek NLP library for stemming and morphological analysis and then bag-of-words method for mapping. To test the framework, we collected 6000 tweets and labeled them manually to build a classifier for sentiment analysis. We considered tweets and news in Turkish language only in this work. Our results show that Naive Bayes performs well on classifying tweets in Turkish.
This paper proposes a new algorithm, which uses the second order information of a Least Absolute Shrinkage and Selection Operator (LASSO) to achieve an active sensing approach driven by minimizing the entropy of spars...
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ISBN:
(纸本)9781509029211
This paper proposes a new algorithm, which uses the second order information of a Least Absolute Shrinkage and Selection Operator (LASSO) to achieve an active sensing approach driven by minimizing the entropy of sparse unknown environments, for the multi agent case. For this, a signal model, which restricts the agent's measurements according to its sensor's view, is introduced into the Distributed LASSO (DLASSO) framework. With the help of Compressed Sensing (CS), the DLASSO is able to estimate the environment with less measurements. After the DLASSO converged to a solution, each agent evaluates the proposed algorithm for choosing new measurement locations.
Regression testing (RT) is an expensive activity. It is applied on a modified program to enhance confidence and reliability by ensuring that the changes are accurately true and have not affected the unmodified portion...
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ISBN:
(纸本)9781479985807
Regression testing (RT) is an expensive activity. It is applied on a modified program to enhance confidence and reliability by ensuring that the changes are accurately true and have not affected the unmodified portions of the SUT. Due to limited resources, it is not practical to re-run each test cases (TC). To improve the regression testing's effectiveness, the TCs should be arranged according to some objective function or criteria. Test case prioritization (TCP) arranges TCs in an order for execution that enhances their effectiveness by satisfying some testing goals. The highest priority assigned to TCs must execute before the TCs with low priority by virtue of some performance goal. Numerous goals are possible to achieve of which one such goal is rate of fault detection (RFT) in which the faults are surfaced as quickly as possible within the testing process. In this paper, a novel technique is suggested to prioritize the TCs that increase its effectiveness in detecting faults. The effectiveness of the proposed method is compared and matched with other prioritization approaches with the help of Average Percentage of Fault Detection (APFD) metric from which charts have been prepared.
Aiming at the problem of low speed of 3D reconstruction of indoor scenes with monocular vision, the color images and depth images of indoor scenes based on ASUS Xtion monocular vision sensor were used for 3D reconstru...
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ISBN:
(纸本)9781509041565
Aiming at the problem of low speed of 3D reconstruction of indoor scenes with monocular vision, the color images and depth images of indoor scenes based on ASUS Xtion monocular vision sensor were used for 3D reconstruction. The image feature extraction using the ORB feature detection algorithm, and compared the efficiency of several kinds of classic feature detection algorithm in image matching, Ransac algorithm and ICP algorithm are used to point cloud fusion. Through experiments, a fast 3D reconstruction method for indoor, simple and small-scale static environment is realized. Have good accuracy, robustness, real-time and flexibility.
This paper is about the fault diagnosis of discrete event systems (DES) under time constraints. The DES contains a series of tasks with well-defined time intervals for each, collected during repetitive runs of the sys...
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This paper is about the fault diagnosis of discrete event systems (DES) under time constraints. The DES contains a series of tasks with well-defined time intervals for each, collected during repetitive runs of the system. The repetitive runs allowed us to calculate average function time for each task. The objective is to propose an algorithm that verifies the correct behavior of each individual task within the system. To illustrate the principal of the algorithm, we will apply it with two concrete examples. This algorithm is easy to implement and operate, and is very useful for all types of systems.
In this paper, we scrutinised an improvement of the Modified Cuckoo Search (MCS), called Modified Cuckoo Search-Markov chain Monte Carlo (MCS-MCMC) algorithm, for solving optimisation problems. The performance of MCS ...
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ISBN:
(纸本)9781509017225
In this paper, we scrutinised an improvement of the Modified Cuckoo Search (MCS), called Modified Cuckoo Search-Markov chain Monte Carlo (MCS-MCMC) algorithm, for solving optimisation problems. The performance of MCS are at least on a par with the standard Cuckoo Search (CS) in terms of high rate of convergence when dealing with true global minimum, although at high number of dimensions. In conjunction with the benefits of MCS, we aim to enhance the MCS algorithm by applying Markov chain Monte Carlo (MCMC) random walk. We validated the proposed algorithm alongside several test functions and later on, we compare its performance with those of MCS-Lévy algorithm. The capability of the MCS-MCMC algorithm in yielding good results is considered as a solution to deal with the downside of those existing algorithm.
Counting the number of triangles in a large graph has many important applications in network analysis. Several frequently computed metrics such as the clustering coefficient and the transitivity ratio need to count th...
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ISBN:
(纸本)9781509052073
Counting the number of triangles in a large graph has many important applications in network analysis. Several frequently computed metrics such as the clustering coefficient and the transitivity ratio need to count the number of triangles. In this paper, we present a randomized framework for expressing and analyzing approximate triangle counting algorithms. We show that many existing approximate triangle counting algorithms can be described in terms of probability distributions given as parameters to the proposed framework. Then, we show that our proposed framework provides a quantitative measure for the quality of different approximate algorithms. Finally, we perform experiments on real-world networks from different domains and show that there is no unique sampling technique outperforming the others for all networks and the quality of sampling techniques depends on different factors such as the structure of the network, the vertex degree-triangle correlation and the number of samples.
Considered the cooperation of the container truck and quayside container crane in the container terminal, this paper constructs the model of the quay cranes operation and trucks scheduling problem in the container ter...
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ISBN:
(纸本)9781509038473
Considered the cooperation of the container truck and quayside container crane in the container terminal, this paper constructs the model of the quay cranes operation and trucks scheduling problem in the container terminal. And the hybrid intelligence swarm algorithm combined the particle swarm optimization algorithm(PSO) with artificial fish swarm algorithm (AFSA) was proposed. The hybrid algorithm (PSO-AFSA) adopt the particle swarm optimization algorithm to produce diverse original paths, optimization of the choice nodes set of the problem, use AFSA's preying and chasing behavior improved the ability of PSO to avoid being premature. the proposed algorithm has more effectiveness, quick convergence and feasibility in solving the problem. The results of stimulation show that the scheduling operation efficiency of container terminal is improved and optimized.
We have proposed new instrumental techniques to quantify human touch feelings by nano tactile sensor array system with 3D 2 processing architecture. In the computation of quantification of human touch feelings, high-...
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ISBN:
(纸本)9781509032204
We have proposed new instrumental techniques to quantify human touch feelings by nano tactile sensor array system with 3D 2 processing architecture. In the computation of quantification of human touch feelings, high-level semantics features are calculated from low-level features which are the result of FFT, wavelet translation, etc. For some application, especially medical application, high reliability is required for the recognition results. Furthermore, real-time processing and low power computing are also required. 3D 2 Processing architecture provides high reliable and low power computing for the accelerator. The architecture has three features: Parallel Computation of Multiple Recognition algorithms for High Reliability, Spatial-Parallel Temporal-Pipeline Streaming Processing for High Energy Efficiency Processing, and Current Reuse Energy Pipeline for Low Power Processing.
With the ubiquity of digital slide scanners, histology image analysis is rapidly emerging as an active area of research. Several histology image analysisalgorithms such as those for mitotic cell detection, nuclei seg...
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ISBN:
(纸本)9781479923519
With the ubiquity of digital slide scanners, histology image analysis is rapidly emerging as an active area of research. Several histology image analysisalgorithms such as those for mitotic cell detection, nuclei segmentation and hormone receptors scoring depend on colour information obtained from images of the scanned slides. However, different standards followed by different labs and the technical variation among different scanners result in stain inconsistency in histology images. Thus, applications that use colour information may fail when they are applied to images with different appearance of stain colours. In this paper, we propose a novel method to estimate the so called stain matrix via independent component analysis in the wavelet domain for stain deconvolution in histology images. Experimental results demonstrate stable and more accurate stain deconvolution results as compared to other recently proposed algorithms.
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