Search logs in a timely and efficient manner are an important part of SRE (Site Reliability Engineer). Logs help us solve the problems during our development work. In this paper, we will introduce you a way how to bui...Search logs in a timely and efficient manner are an important part of SRE (Site Reliability Engineer). Logs help us solve the problems during our development work. In this paper, we will introduce you a way how to build an efficient logs analysis system based on kafka and Elastic Search. We hope you can learn something through the iteration of the Version and get some inspiration with your own log analysis system.展开更多
Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to e...Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to evaluate numerous diseases such as tumors and vascular lesions. However, speckle noise corrupts the CT images and makes the clinical data analysis ambiguous. Therefore, for accurate diagnosis, medical image enhancement is a must for noise removal and sharp/clear images. In this work, a medical image enhancement algorithm has been proposed using log transform in an optimization framework. In order to achieve optimization, a well-known meta-heuristic algorithm, namely: Cuckoo search (CS) algorithm is used to determine the optimal parameter settings for log transform. The performance of the proposed technique is studied on a low contrast CT image dataset. Besides this, the results clearly show that the CS based approach has superior convergence and fitness values compared to PSO as the CS converge faster that proves the efficacy of the CS based technique. Finally, Image Quality Analysis (IQA) justifies the robustness of the proposed enhancement technique.展开更多
Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behaviora...Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behavioral model.Design/methodology/approach: Forty-two matriculated full-time senior college students with a female-to-male ratio of 1 to 1 who majored in medical science in Jilin University participated in our experiment. The task of the experiment was to search for information about 'the influence of environmental pollution on daily life' in order to write a report about this topic. The research methods include concept map, query log analysis and questionnaire survey.Findings: The results indicate that exploratory search can significantly change the knowledge structure of searchers. As searchers were moving through different stages of the exploratory search process, they experienced cognitive changes, and their search behaviors were characterized by quick browsing, careful browsing and focused searching.Research limitations: The study used only one search topic, and there is no comparision or control group. Although we took search habits, personal thinking habits, personality characteristics and professional background into account, a more detailed study to analyze the effects of these factors on exploratory search behavior is needed in our further research.Practical implications: This study can serve as a reference for other researchers engaged in the same effort to construct the supporting system of exploratory search.Originality/value: Three methods are used to investigate the behavior characteristics during exploratory search.展开更多
文摘Search logs in a timely and efficient manner are an important part of SRE (Site Reliability Engineer). Logs help us solve the problems during our development work. In this paper, we will introduce you a way how to build an efficient logs analysis system based on kafka and Elastic Search. We hope you can learn something through the iteration of the Version and get some inspiration with your own log analysis system.
文摘Medical image enhancement is an essential process for superior disease diagnosis as well as for detection of pathological lesion accurately. Computed Tomography (CT) is considered a vital medical imaging modality to evaluate numerous diseases such as tumors and vascular lesions. However, speckle noise corrupts the CT images and makes the clinical data analysis ambiguous. Therefore, for accurate diagnosis, medical image enhancement is a must for noise removal and sharp/clear images. In this work, a medical image enhancement algorithm has been proposed using log transform in an optimization framework. In order to achieve optimization, a well-known meta-heuristic algorithm, namely: Cuckoo search (CS) algorithm is used to determine the optimal parameter settings for log transform. The performance of the proposed technique is studied on a low contrast CT image dataset. Besides this, the results clearly show that the CS based approach has superior convergence and fitness values compared to PSO as the CS converge faster that proves the efficacy of the CS based technique. Finally, Image Quality Analysis (IQA) justifies the robustness of the proposed enhancement technique.
基金supported by the National Social Science Foundation(Grant No.:11BTQ045)
文摘Purpose: This study attempts to investigate how a user's search behavior changes in the exploratory search process in order to understand the characteristics of the user's search behavior and build a behavioral model.Design/methodology/approach: Forty-two matriculated full-time senior college students with a female-to-male ratio of 1 to 1 who majored in medical science in Jilin University participated in our experiment. The task of the experiment was to search for information about 'the influence of environmental pollution on daily life' in order to write a report about this topic. The research methods include concept map, query log analysis and questionnaire survey.Findings: The results indicate that exploratory search can significantly change the knowledge structure of searchers. As searchers were moving through different stages of the exploratory search process, they experienced cognitive changes, and their search behaviors were characterized by quick browsing, careful browsing and focused searching.Research limitations: The study used only one search topic, and there is no comparision or control group. Although we took search habits, personal thinking habits, personality characteristics and professional background into account, a more detailed study to analyze the effects of these factors on exploratory search behavior is needed in our further research.Practical implications: This study can serve as a reference for other researchers engaged in the same effort to construct the supporting system of exploratory search.Originality/value: Three methods are used to investigate the behavior characteristics during exploratory search.
