Learning Complex Recursive Rules.

We consider the problem of learning complex recursive rules which involve new concepts other than those given in the input relations and which must be discovered by the learning algorithm in the course of finding rules. The existing learning methods (FOIL, FORGE, and etc.) create rules based on the given concepts or relations but they cannot create new concepts. However, in many cases one must use new intermediate concepts in order to form the recursive rules. We give a new technique for constructing such intermediate concepts and learning rules based on those concepts. We illustrate the new technique with several examples, none of which can be handled by the existing methods. We have implemented the new technique in Common Lisp and tested many different examples

Modelling users' contextual querying behaviour for web image searching

The rapid growth of visual information on Web has led to immense interest in multimedia information retrieval (MIR). While advancement in MIR systems has achieved some success in specific domains, particularly the content-based approaches, general Web users still struggle to find the images they want. Despite the success in content-based object recognition or concept extraction, the major problem in current Web image searching remains in the querying process. Since most online users only express their needs in semantic terms or objects, systems that utilize visual features (e.g., color or texture) to search images create a semantic gap which hinders general users from fully expressing their needs. In addition, query-by-example (QBE) retrieval imposes extra obstacles for exploratory search because users may not always have the representative image at hand or in mind when starting a search (i.e. the page zero problem). As a result, the majority of current online image search engines (e.g., Google, Yahoo, and Flickr) still primarily use textual queries to search. The problem with query-based retrieval systems is that they only capture users’ information need in terms of formal queries;; the implicit and abstract parts of users’ information needs are inevitably overlooked. Hence, users often struggle to formulate queries that best represent their needs, and some compromises have to be made. Studies of Web search logs suggest that multimedia searches are more difficult than textual Web searches, and Web image searching is the most difficult compared to video or audio searches. Hence, online users need to put in more effort when searching multimedia contents, especially for image searches. Most interactions in Web image searching occur during query reformulation. While log analysis provides intriguing views on how the majority of users search, their search needs or motivations are ultimately neglected. User studies on image searching have attempted to understand users’ search contexts in terms of users’ background (e.g., knowledge, profession, motivation for search and task types) and the search outcomes (e.g., use of retrieved images, search performance). However, these studies typically focused on particular domains with a selective group of professional users. General users’ Web image searching contexts and behaviors are little understood although they represent the majority of online image searching activities nowadays. We argue that only by understanding Web image users’ contexts can the current Web search engines further improve their usefulness and provide more efficient searches. In order to understand users’ search contexts, a user study was conducted based on university students’ Web image searching in News, Travel, and commercial Product domains. The three search domains were deliberately chosen to reflect image users’ interests in people, time, event, location, and objects. We investigated participants’ Web image searching behavior, with the focus on query reformulation and search strategies. Participants’ search contexts such as their search background, motivation for search, and search outcomes were gathered by questionnaires. The searching activity was recorded with participants’ think aloud data for analyzing significant search patterns. The relationships between participants’ search contexts and corresponding search strategies were discovered by Grounded Theory approach. Our key findings include the following aspects: - Effects of users' interactive intents on query reformulation patterns and search strategies - Effects of task domain on task specificity and task difficulty, as well as on some specific searching behaviors - Effects of searching experience on result expansion strategies A contextual image searching model was constructed based on these findings. The model helped us understand Web image searching from user perspective, and introduced a context-aware searching paradigm for current retrieval systems. A query recommendation tool was also developed to demonstrate how users’ query reformulation contexts can potentially contribute to more efficient searching

Microbial Air Contamination in an Intensive Care Unit

Unit layout affects every aspect of intensive care services, including patient safety. A previous study has shown that patients admitted to beds adjacent to the sink and to the door of a large bayroom had the highest number of positive blood cultures and the highest blood culture incidence density, respectively. The present study measures microbial air contamination in a medical intensive care unit of a medical center in central Taiwan. Of the 17 rooms, 8 rooms with distinct physical environmental characteristics were selected. Sampling tests were conducted between December 2013 and February 2014 with a microbial air sampler (MAS-100NT). TSA was used for bacteria collection and DG18 for fungi collection. The overall average bacterial and fungal concentrations were 83CFU/m3 and 69CFU/m3, respectively. The ranges were between 8-354 CFU/m3 and 0-1468 CFU/m3, respectively. A significant difference was found in the bacterial concentration (p=.005) between different room locations. The highest concentration was found in the rooms located at the front end of the circulation (99 CFU/m3), while the lowest was found in the rooms located at the rear end of the circulation (55CFU/m3). Differences in fungal concentrations for different room locations did not reach statistical significance. In addition, differences in bacterial and fungal concentrations for rooms with different sink locations did not reach statistical significance. Even though the microbial concentrations generally complied with standards, the results may help designers and hospital administrators develop a healthier environment for patients

ZnO-Based Electron Transporting Layer for Perovskite Solar Cells

Recently, organic/inorganic hybrid perovskite materials, APbX3 (A = CH3NH3 or HC(NH2)2; X = I, Br or Cl), have attracted much interest for their promising application in solar cells as the light-absorbing component to their broad spectral absorption, strong light-harvesting and long exciton diffusion length. The perovskite solar cells (PSCs) can reduce the production costs and achieve high power conversion efficiency significantly compared to standard silicon cells and other thin film cells. On the other hand, ZnO based materials have been recently investigated in the PSCs devices as electron injection layers for low-temperature, low-cost and flexible devices. This chapter aims to review PSCs using ZnO materials as electron extraction layers. We will discuss the electron transmission and effect of the electron-transporting layer in PSCs and the preparation method of the ZnO. ZnO is a potential material for many applications due to their high electron mobility, transparent and various nanostructure. The ZnO was introduced into the PSCs structure to improve electron extraction efficiency. This chapter summaries the effect and parameters of PSCs based on the ZnO layer/nanostructure prepared by several methods as electron transport layers

Extracting Business Intelligence from Online Product Reviews: An Experiment of Automatic Rule-Induction

Online product reviews are a major source of business intelligence (BI) that helps managers and market researchers make important decisions on product development and promotion. However, the large volume of online product review data creates significant information overload problems, making it difficult to analyze users’ concerns. In this paper, we employ a design science paradigm to develop a new framework for designing BI systems that correlate the textual content and the numerical ratings of online product reviews. Based on the framework, we developed a prototype for extracting the relationship between the user ratings and their textual comments posted on Amazon.com’s Web site. Two data mining algorithms were implemented to extract automatically decision rules that guide the understanding of the relationship. We report on experimental results of using the prototype to extract rules from online reviews of three products and discuss the managerial implications

Towards patient-specific cardiovascular modeling system using the immersed boundary technique

<p>Abstract</p> <p>Background</p> <p>Previous research shows that the flow dynamics in the left ventricle (LV) reveal important information about cardiac health. This information can be used in early diagnosis of patients with potential heart problems. The current study introduces a patient-specific cardiovascular-modelling system (CMS) which simulates the flow dynamics in the LV to facilitate physicians in early diagnosis of patients before heart failure.</p> <p>Methods</p> <p>The proposed system will identify possible disease conditions and facilitates early diagnosis through hybrid computational fluid dynamics (CFD) simulation and time-resolved magnetic resonance imaging (4-D MRI). The simulation is based on the 3-D heart model, which can simultaneously compute fluid and elastic boundary motions using the immersed boundary method. At this preliminary stage, the 4-D MRI is used to provide an appropriate comparison. This allows flexible investigation of the flow features in the ventricles and their responses.</p> <p>Results</p> <p>The results simulate various flow rates and kinetic energy in the diastole and systole phases, demonstrating the feasibility of capturing some of the important characteristics of the heart during different phases. However, some discrepancies exist in the pulmonary vein and aorta flow rate between the numerical and experimental data. Further studies are essential to investigate and solve the remaining problems before using the data in clinical diagnostics.</p> <p>Conclusions</p> <p>The results show that by using a simple reservoir pressure boundary condition (RPBC), we are able to capture some essential variations found in the clinical data. Our approach establishes a first-step framework of a practical patient-specific CMS, which comprises a 3-D CFD model (without involving actual hemodynamic data yet) to simulate the heart and the 4-D PC-MRI system. At this stage, the 4-D PC-MRI system is used for verification purpose rather than input. This brings us closer to our goal of developing a practical patient-specific CMS, which will be pursued next. We anticipate that in the future, this hybrid system can potentially identify possible disease conditions in LV through comprehensive analysis and facilitates physicians in early diagnosis of probable cardiac problems.</p

Microbial Air Contamination in an Intensive Care Unit

Unit layout affects every aspect of intensive care services, including patient safety. A previous study has shown that patients admitted to beds adjacent to the sink and to the door of a large bayroom had the highest number of positive blood cultures and the highest blood culture incidence density, respectively. The present study measures microbial air contamination in a medical intensive care unit of a medical center in central Taiwan. Of the 17 rooms, 8 rooms with distinct physical environmental characteristics were selected. Sampling tests were conducted between December 2013 and February 2014 with a microbial air sampler (MAS-100NT). TSA was used for bacteria collection and DG18 for fungi collection. The overall average bacterial and fungal concentrations were 83CFU/m3 and 69CFU/m3, respectively. The ranges were between 8-354 CFU/m3 and 0-1468 CFU/m3, respectively. A significant difference was found in the bacterial concentration (p=.005) between different room locations. The highest concentration was found in the rooms located at the front end of the circulation (99 CFU/m3), while the lowest was found in the rooms located at the rear end of the circulation (55CFU/m3). Differences in fungal concentrations for different room locations did not reach statistical significance. In addition, differences in bacterial and fungal concentrations for rooms with different sink locations did not reach statistical significance. Even though the microbial concentrations generally complied with standards, the results may help designers and hospital administrators develop a healthier environment for patients