[신간의 별자리x] 우리/미술, 그리고 ‘슬픔의 박물관’

Data Mining Practical Machine Learning Tools and Techniques

From the Publisher: 
The accessible presentation of this book gives both a general view of the entire computer vision enterprise and also offers sufficient detail to be able to build useful applications. Users learn techniques that have proven to be useful by first-hand experience and a wide range of mathematical methods. A CD-ROM with every copy of the text contains source code for programming practice, color images, and illustrative movies. Comprehensive and up-to-date, this book includes essential topics that either reflect practical significance or are of theoretical importance. Topics are discussed in substantial and increasing depth. Application surveys describe numerous important application areas such as image based rendering and digital libraries. Many important algorithms broken down and illustrated in pseudo code. Appropriate for use by engineers as a comprehensive reference to the computer vision enterprise.

Computer vision : a modern approach = 计算机视觉 : 一种现代的方法

비만아 부모의 돌봄 경험: q 방법론

Executive Summary Introduction Methodology Used to Prepare the Guideline Epidemiology Incidence Etiology Major Epidemiologic Points Pathogenesis Major Points for Pathogenesis Modifiable Risk Factors Intubation and Mechanical Ventilation Aspiration, Body Position, and Enteral Feeding Modulation of Colonization: Oral Antiseptics and Antibiotics Stress Bleeding Prophylaxis, Transfusion, and Glucose Control Major Points and Recommendations for Modifiable Risk Factors Diagnostic Testing Major Points and Recommendations for Diagnosis Diagnostic Strategies and Approaches Clinical Strategy Bacteriologic Strategy Recommended Diagnostic Strategy Major Points and Recommendations for Comparing Diagnostic Strategies Antibiotic Treatment of Hospital-acquired Pneumonia General Approach Initial Empiric Antibiotic Therapy Appropriate Antibiotic Selection and Adequate Dosing Local Instillation and Aerosolized Antibiotics Combination versus Monotherapy Duration of Therapy Major Points and Recommendations for Optimal Antibiotic Therapy Specific Antibiotic Regimens Antibiotic Heterogeneity and Antibiotic Cycling Response to Therapy Modification of Empiric Antibiotic Regimens Defining the Normal Pattern of Resolution Reasons for Deterioration or Nonresolution Evaluation of the Nonresponding Patient Major Points and Recommendations for Assessing Response to Therapy Suggested Performance Indicators

Guidelines for the management of adults with hospital-acquired, ventilator-associated, and healthcare-associated pneumonia the official statement of the American Thoracic Society and the Infectious Disease Society of America (特集 救急診療ガイドライン) -- (海外のガイドライン)

https://www.techscience.com/cmc/v66n3/41049/pdf

Fully Automatic Segmentation of Gynaecological Abnormality Using a New Viola-Jones Model

Wireless Sensor Networks (WSNs) have attracted intensive interest from both academia and industry due to their wide application in civil and military scenarios. Recently, there is a great interest related to routing process in WSNs. Security aspects in routing protocols have not been given enough attention, since most of the routing protocols in WSNs have not been designed with security requirements in mind. This paper surveys the current challenges of WSN. It will focus on the attempts of building an Artificial Intelligence (AI) based routing protocols in WSNs. This paper also identifies the WSN security trends and threats. The paper also addresses some examples of how to use artificial intelligence in the routing algorithms and shows the advantages and the drawbacks of each. A proposed framework also has been introduced. Finally, the future directions of WSNs have been declared.

/pdf/secure-routing-in-wireless-sensor-networks-a-state-of-the-424zm8hz1r.pdf

Secure Routing in Wireless Sensor Networks: A State of the Art

https://www.techscience.com/cmc/v66n3/41059/pdf

A New Decision-Making Model based on Plithogenic Set for Supplier Selection

Generally, WSN consists of thousands of inexpensive devices, called sensor nodes, capable of computation, communication and sensing events in a specific environment [1, 2, 3]. WSNs have attracted intensive interest from both academia and industry due to their wide application in civil and military scenarios [4, 5, 6]. Enormous advances that are emerging in WSNs act as a revolution in all aspects of our life. WSNs have unique specifications describe it and different from other networks. Sensor nodes have energy and computational challenges. Moreover, WSNs may be prone to software failure, unreliable wireless connections, malicious attacks, and hardware faults; that make the network performance may degrade significantly over time. Recently, there is a great interest related to routing process in WSNs using intelligent and machine learning algorithms such as Genetic Algorithms [7, 8, 9]. Security aspects in routing protocols have not been given enough attention, since most of the routing protocols in WSNs have not been designed with security requirements in mind [10, 11, 12, 13, 14]. In this chapter, the main models of WSN with their advantages and limitations are discussed, specially the clustering model. In addition, it provides a literature of the existing clustering methods of WSN that aims to increase the network lifetime. After that, the security aspects are explained in details. Finally, the existing secure clustering methods are discussed and evaluated based on a set of criteria.

Hierarchical and Clustering WSN Models: Their Requirements for Complex Applications

The design of Two-Dimensional Infinite Input Response Filters (2D IIR) is an important task in the field of signal processing. These filters are widely used in several areas of engineering as an important tool to eliminate undesired frequencies in high-noised signals. However, 2D IIR filters have parameters that need to be calibrated in order to obtain the best output, and finding these optimal values is not an easy task. On the other hand, Electro-magnetism Optimization (EMO) is a population-based technique which possess interesting convergence properties, it works following the electro-magnetism principles for solving complex optimization problems. This paper introduces an algorithm for the automatic parameter identification of 2D IIR filters using EMO, a process that is regarded as a multidimensional optimization problem. Experimental results are included to validate the efficiency of the proposed technique regarding accuracy, speed, and robustness.

Mohamed Elhoseny

Papers

Fully Automatic Segmentation of Gynaecological Abnormality Using a New Viola-Jones Model

Secure Routing in Wireless Sensor Networks: A State of the Art

A New Decision-Making Model based on Plithogenic Set for Supplier Selection

Hierarchical and Clustering WSN Models: Their Requirements for Complex Applications

Parameter identification of two dimensional digital filters using electro-magnetism optimization