Matrix- and tensor-based recommender systems for the discovery of currently unknown inorganic compounds

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Kashima, Hisashi; Tanaka, Isao

2018-01-01

Chemically relevant compositions (CRCs) and atomic arrangements of inorganic compounds have been collected as inorganic crystal structure databases. Machine learning is a unique approach to search for currently unknown CRCs from vast candidates. Herein we propose matrix- and tensor-based recommender system approaches to predict currently unknown CRCs from database entries of CRCs. Firstly, the performance of the recommender system approaches to discover currently unknown CRCs is examined. A Tucker decomposition recommender system shows the best discovery rate of CRCs as the majority of the top 100 recommended ternary and quaternary compositions correspond to CRCs. Secondly, systematic density functional theory (DFT) calculations are performed to investigate the phase stability of the recommended compositions. The phase stability of the 27 compositions reveals that 23 currently unknown compounds are newly found to be stable. These results indicate that the recommender system has great potential to accelerate the discovery of new compounds.

Promoting Cold-Start Items in Recommender Systems

PubMed Central

Liu, Jin-Hu; Zhou, Tao; Zhang, Zi-Ke; Yang, Zimo; Liu, Chuang; Li, Wei-Min

2014-01-01

As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs. PMID:25479013

Promoting cold-start items in recommender systems.

PubMed

Liu, Jin-Hu; Zhou, Tao; Zhang, Zi-Ke; Yang, Zimo; Liu, Chuang; Li, Wei-Min

2014-01-01

As one of the major challenges, cold-start problem plagues nearly all recommender systems. In particular, new items will be overlooked, impeding the development of new products online. Given limited resources, how to utilize the knowledge of recommender systems and design efficient marketing strategy for new items is extremely important. In this paper, we convert this ticklish issue into a clear mathematical problem based on a bipartite network representation. Under the most widely used algorithm in real e-commerce recommender systems, the so-called item-based collaborative filtering, we show that to simply push new items to active users is not a good strategy. Interestingly, experiments on real recommender systems indicate that to connect new items with some less active users will statistically yield better performance, namely, these new items will have more chance to appear in other users' recommendation lists. Further analysis suggests that the disassortative nature of recommender systems contributes to such observation. In a word, getting in-depth understanding on recommender systems could pave the way for the owners to popularize their cold-start products with low costs.

Hybrid attacks on model-based social recommender systems

NASA Astrophysics Data System (ADS)

Yu, Junliang; Gao, Min; Rong, Wenge; Li, Wentao; Xiong, Qingyu; Wen, Junhao

2017-10-01

With the growing popularity of the online social platform, the social network based approaches to recommendation emerged. However, because of the open nature of rating systems and social networks, the social recommender systems are susceptible to malicious attacks. In this paper, we present a certain novel attack, which inherits characteristics of the rating attack and the relation attack, and term it hybrid attack. Furtherly, we explore the impact of the hybrid attack on model-based social recommender systems in multiple aspects. The experimental results show that, the hybrid attack is more destructive than the rating attack in most cases. In addition, users and items with fewer ratings will be influenced more when attacked. Last but not the least, the findings suggest that spammers do not depend on the feedback links from normal users to become more powerful, the unilateral links can make the hybrid attack effective enough. Since unilateral links are much cheaper, the hybrid attack will be a great threat to model-based social recommender systems.

A Hybrid Approach using Collaborative filtering and Content based Filtering for Recommender System

NASA Astrophysics Data System (ADS)

Geetha, G.; Safa, M.; Fancy, C.; Saranya, D.

2018-04-01

In today’s digital world, it has become an irksome task to find the content of one's liking in an endless variety of content that are being consumed like books, videos, articles, movies, etc. On the other hand there has been an emerging growth among the digital content providers who want to engage as many users on their service as possible for the maximum time. This gave birth to the recommender system comes wherein the content providers recommend users the content according to the users’ taste and liking. In this paper we have proposed a movie recommendation system. A movie recommendation is important in our social life due to its features such as suggesting a set of movies to users based on their interest, or the popularities of the movies. In this paper we are proposing a movie recommendation system that has the ability to recommend movies to a new user as well as the other existing users. It mines movie databases to collect all the important information, such as, popularity and attractiveness, which are required for recommendation. We use content-based and collaborative filtering and also hybrid filtering, which is a combination of the results of these two techniques, to construct a system that provides more precise recommendations concerning movies.

Semantically Enhanced Recommender Systems

NASA Astrophysics Data System (ADS)

Ruiz-Montiel, Manuela; Aldana-Montes, José F.

Recommender Systems have become a significant area in the context of web personalization, given the large amount of available data. Ontologies can be widely taken advantage of in recommender systems, since they provide a means of classifying and discovering of new information about the items to recommend, about user profiles and even about their context. We have developed a semantically enhanced recommender system based on this kind of ontologies. In this paper we present a description of the proposed system.

An effective trust-based recommendation method using a novel graph clustering algorithm

NASA Astrophysics Data System (ADS)

Moradi, Parham; Ahmadian, Sajad; Akhlaghian, Fardin

2015-10-01

Recommender systems are programs that aim to provide personalized recommendations to users for specific items (e.g. music, books) in online sharing communities or on e-commerce sites. Collaborative filtering methods are important and widely accepted types of recommender systems that generate recommendations based on the ratings of like-minded users. On the other hand, these systems confront several inherent issues such as data sparsity and cold start problems, caused by fewer ratings against the unknowns that need to be predicted. Incorporating trust information into the collaborative filtering systems is an attractive approach to resolve these problems. In this paper, we present a model-based collaborative filtering method by applying a novel graph clustering algorithm and also considering trust statements. In the proposed method first of all, the problem space is represented as a graph and then a sparsest subgraph finding algorithm is applied on the graph to find the initial cluster centers. Then, the proposed graph clustering algorithm is performed to obtain the appropriate users/items clusters. Finally, the identified clusters are used as a set of neighbors to recommend unseen items to the current active user. Experimental results based on three real-world datasets demonstrate that the proposed method outperforms several state-of-the-art recommender system methods.

Machine learning algorithms for the creation of clinical healthcare enterprise systems

NASA Astrophysics Data System (ADS)

Mandal, Indrajit

2017-10-01

Clinical recommender systems are increasingly becoming popular for improving modern healthcare systems. Enterprise systems are persuasively used for creating effective nurse care plans to provide nurse training, clinical recommendations and clinical quality control. A novel design of a reliable clinical recommender system based on multiple classifier system (MCS) is implemented. A hybrid machine learning (ML) ensemble based on random subspace method and random forest is presented. The performance accuracy and robustness of proposed enterprise architecture are quantitatively estimated to be above 99% and 97%, respectively (above 95% confidence interval). The study then extends to experimental analysis of the clinical recommender system with respect to the noisy data environment. The ranking of items in nurse care plan is demonstrated using machine learning algorithms (MLAs) to overcome the drawback of the traditional association rule method. The promising experimental results are compared against the sate-of-the-art approaches to highlight the advancement in recommendation technology. The proposed recommender system is experimentally validated using five benchmark clinical data to reinforce the research findings.

Personalized Recommender System for Digital Libraries

ERIC Educational Resources Information Center

Omisore, M. O.; Samuel, O. W.

2014-01-01

The huge amount of information available online has given rise to personalization and filtering systems. Recommender systems (RS) constitute a specific type of information filtering technique that present items according to user's interests. In this research, a web-based personalized recommender system capable of providing learners with books that…

Recommendation System for Adaptive Learning.

PubMed

Chen, Yunxiao; Li, Xiaoou; Liu, Jingchen; Ying, Zhiliang

2018-01-01

An adaptive learning system aims at providing instruction tailored to the current status of a learner, differing from the traditional classroom experience. The latest advances in technology make adaptive learning possible, which has the potential to provide students with high-quality learning benefit at a low cost. A key component of an adaptive learning system is a recommendation system, which recommends the next material (video lectures, practices, and so on, on different skills) to the learner, based on the psychometric assessment results and possibly other individual characteristics. An important question then follows: How should recommendations be made? To answer this question, a mathematical framework is proposed that characterizes the recommendation process as a Markov decision problem, for which decisions are made based on the current knowledge of the learner and that of the learning materials. In particular, two plain vanilla systems are introduced, for which the optimal recommendation at each stage can be obtained analytically.

CROSS-DISCIPLINARY PHYSICS AND RELATED AREAS OF SCIENCE AND TECHNOLOGY: Diffusion-Based Recommendation in Collaborative Tagging Systems

NASA Astrophysics Data System (ADS)

Shang, Ming-Sheng; Zhang, Zi-Ke

2009-11-01

Recently, collaborative tagging systems have attracted more and more attention and have been widely applied in web systems. Tags provide highly abstracted information about personal preferences and item content, and therefore have the potential to help in improving better personalized recommendations. We propose a diffusion-based recommendation algorithm considering the personal vocabulary and evaluate it in a real-world dataset: Del.icio.us. Experimental results demonstrate that the usage of tag information can significantly improve the accuracy of personalized recommendations.

Recommendation advertising method based on behavior retargeting

NASA Astrophysics Data System (ADS)

Zhao, Yao; YIN, Xin-Chun; CHEN, Zhi-Min

2011-10-01

Online advertising has become an important business in e-commerce. Ad recommended algorithms are the most critical part in recommendation systems. We propose a recommendation advertising method based on behavior retargeting which can avoid leakage click of advertising due to objective reasons and can observe the changes of the user's interest in time. Experiments show that our new method can have a significant effect and can be further to apply to online system.

Weighted hybrid technique for recommender system

NASA Astrophysics Data System (ADS)

Suriati, S.; Dwiastuti, Meisyarah; Tulus, T.

2017-12-01

Recommender system becomes very popular and has important role in an information system or webpages nowadays. A recommender system tries to make a prediction of which item a user may like based on his activity on the system. There are some familiar techniques to build a recommender system, such as content-based filtering and collaborative filtering. Content-based filtering does not involve opinions from human to make the prediction, while collaborative filtering does, so collaborative filtering can predict more accurately. However, collaborative filtering cannot give prediction to items which have never been rated by any user. In order to cover the drawbacks of each approach with the advantages of other approach, both approaches can be combined with an approach known as hybrid technique. Hybrid technique used in this work is weighted technique in which the prediction score is combination linear of scores gained by techniques that are combined.The purpose of this work is to show how an approach of weighted hybrid technique combining content-based filtering and item-based collaborative filtering can work in a movie recommender system and to show the performance comparison when both approachare combined and when each approach works alone. There are three experiments done in this work, combining both techniques with different parameters. The result shows that the weighted hybrid technique that is done in this work does not really boost the performance up, but it helps to give prediction score for unrated movies that are impossible to be recommended by only using collaborative filtering.

Solving the stability-accuracy-diversity dilemma of recommender systems

NASA Astrophysics Data System (ADS)

Hou, Lei; Liu, Kecheng; Liu, Jianguo; Zhang, Runtong

2017-02-01

Recommender systems are of great significance in predicting the potential interesting items based on the target user's historical selections. However, the recommendation list for a specific user has been found changing vastly when the system changes, due to the unstable quantification of item similarities, which is defined as the recommendation stability problem. To improve the similarity stability and recommendation stability is crucial for the user experience enhancement and the better understanding of user interests. While the stability as well as accuracy of recommendation could be guaranteed by recommending only popular items, studies have been addressing the necessity of diversity which requires the system to recommend unpopular items. By ranking the similarities in terms of stability and considering only the most stable ones, we present a top- n-stability method based on the Heat Conduction algorithm (denoted as TNS-HC henceforth) for solving the stability-accuracy-diversity dilemma. Experiments on four benchmark data sets indicate that the TNS-HC algorithm could significantly improve the recommendation stability and accuracy simultaneously and still retain the high-diversity nature of the Heat Conduction algorithm. Furthermore, we compare the performance of the TNS-HC algorithm with a number of benchmark recommendation algorithms. The result suggests that the TNS-HC algorithm is more efficient in solving the stability-accuracy-diversity triple dilemma of recommender systems.

Decision-Guided Recommenders with Composite Alternatives

ERIC Educational Resources Information Center

Alodhaibi, Khalid

2011-01-01

Recommender systems aim to support users in their decision-making process while interacting with large information spaces and recommend items of interest to users based on preferences they have expressed, either explicitly or implicitly. Recommender systems are increasingly used with product and service selection over the Internet. Although…

How to translate therapeutic recommendations in clinical practice guidelines into rules for critiquing physician prescriptions? Methods and application to five guidelines

PubMed Central

2010-01-01

Background Clinical practice guidelines give recommendations about what to do in various medical situations, including therapeutical recommendations for drug prescription. An effective way to computerize these recommendations is to design critiquing decision support systems, i.e. systems that criticize the physician's prescription when it does not conform to the guidelines. These systems are commonly based on a list of "if conditions then criticism" rules. However, writing these rules from the guidelines is not a trivial task. The objective of this article is to propose methods that (1) simplify the implementation of guidelines' therapeutical recommendations in critiquing systems by automatically translating structured therapeutical recommendations into a list of "if conditions then criticize" rules, and (2) can generate an appropriate textual label to explain to the physician why his/her prescription is not recommended. Methods We worked on the therapeutic recommendations in five clinical practice guidelines concerning chronic diseases related to the management of cardiovascular risk. We evaluated the system using a test base of more than 2000 cases. Results Algorithms for automatically translating therapeutical recommendations into "if conditions then criticize" rules are presented. Eight generic recommendations are also proposed; they are guideline-independent, and can be used as default behaviour for handling various situations that are usually implicit in the guidelines, such as decreasing the dose of a poorly tolerated drug. Finally, we provide models and methods for generating a human-readable textual critique. The system was successfully evaluated on the test base. Conclusion We show that it is possible to criticize physicians' prescriptions starting from a structured clinical guideline, and to provide clear explanations. We are now planning a randomized clinical trial to evaluate the impact of the system on practices. PMID:20509903

Personalized Recommendation of Learning Material Using Sequential Pattern Mining and Attribute Based Collaborative Filtering

ERIC Educational Resources Information Center

Salehi, Mojtaba; Nakhai Kamalabadi, Isa; Ghaznavi Ghoushchi, Mohammad Bagher

2014-01-01

Material recommender system is a significant part of e-learning systems for personalization and recommendation of appropriate materials to learners. However, in the existing recommendation algorithms, dynamic interests and multi-preference of learners and multidimensional-attribute of materials are not fully considered simultaneously. Moreover,…

Recommendation System Based On Association Rules For Distributed E-Learning Management Systems

NASA Astrophysics Data System (ADS)

Mihai, Gabroveanu

2015-09-01

Traditional Learning Management Systems are installed on a single server where learning materials and user data are kept. To increase its performance, the Learning Management System can be installed on multiple servers; learning materials and user data could be distributed across these servers obtaining a Distributed Learning Management System. In this paper is proposed the prototype of a recommendation system based on association rules for Distributed Learning Management System. Information from LMS databases is analyzed using distributed data mining algorithms in order to extract the association rules. Then the extracted rules are used as inference rules to provide personalized recommendations. The quality of provided recommendations is improved because the rules used to make the inferences are more accurate, since these rules aggregate knowledge from all e-Learning systems included in Distributed Learning Management System.

Long-term effects of user preference-oriented recommendation method on the evolution of online system

NASA Astrophysics Data System (ADS)

Shi, Xiaoyu; Shang, Ming-Sheng; Luo, Xin; Khushnood, Abbas; Li, Jian

2017-02-01

As the explosion growth of Internet economy, recommender system has become an important technology to solve the problem of information overload. However, recommenders are not one-size-fits-all, different recommenders have different virtues, making them be suitable for different users. In this paper, we propose a novel personalized recommender based on user preferences, which allows multiple recommenders to exist in E-commerce system simultaneously. We find that output of a recommender to each user is quite different when using different recommenders, the recommendation accuracy can be significantly improved if each user is assigned with his/her optimal personalized recommender. Furthermore, different from previous works focusing on short-term effects on recommender, we also evaluate the long-term effect of the proposed method by modeling the evolution of mutual feedback between user and online system. Finally, compared with single recommender running on the online system, the proposed method can improve the accuracy of recommendation significantly and get better trade-offs between short- and long-term performances of recommendation.

Personalized Location-Based Recommendation Services for Tour Planning in Mobile Tourism Applications

NASA Astrophysics Data System (ADS)

Yu, Chien-Chih; Chang, Hsiao-Ping

Travel and tour planning is a process of searching, selecting, grouping and sequencing destination related products and services including attractions, accommodations, restaurants, and activities. Personalized recommendation services aim at suggesting products and services to meet users’ preferences and needs, while location-based services focus on providing information based on users’ current positions. Due to the fast growing of user needs in the mobile tourism domain, how to provide personalized location-based tour recommendation services becomes a critical research and practical issue. The objective of this paper is to propose a system architecture and design methods for facilitating the delivery of location-based recommendation services to support personalized tour planning. Based on tourists’ current location and time, as well as personal preferences and needs, various recommendations regarding sightseeing spots, hotels, restaurants, and packaged tour plans can be generated efficiently. An application prototype is also implemented to illustrate and test the system feasibility and effectiveness.

Coarse cluster enhancing collaborative recommendation for social network systems

NASA Astrophysics Data System (ADS)

Zhao, Yao-Dong; Cai, Shi-Min; Tang, Ming; Shang, Min-Sheng

2017-10-01

Traditional collaborative filtering based recommender systems for social network systems bring very high demands on time complexity due to computing similarities of all pairs of users via resource usages and annotation actions, which thus strongly suppresses recommending speed. In this paper, to overcome this drawback, we propose a novel approach, namely coarse cluster that partitions similar users and associated items at a high speed to enhance user-based collaborative filtering, and then develop a fast collaborative user model for the social tagging systems. The experimental results based on Delicious dataset show that the proposed model is able to dramatically reduce the processing time cost greater than 90 % and relatively improve the accuracy in comparison with the ordinary user-based collaborative filtering, and is robust for the initial parameter. Most importantly, the proposed model can be conveniently extended by introducing more users' information (e.g., profiles) and practically applied for the large-scale social network systems to enhance the recommending speed without accuracy loss.

Multimodal hybrid reasoning methodology for personalized wellbeing services.

PubMed

Ali, Rahman; Afzal, Muhammad; Hussain, Maqbool; Ali, Maqbool; Siddiqi, Muhammad Hameed; Lee, Sungyoung; Ho Kang, Byeong

2016-02-01

A wellness system provides wellbeing recommendations to support experts in promoting a healthier lifestyle and inducing individuals to adopt healthy habits. Adopting physical activity effectively promotes a healthier lifestyle. A physical activity recommendation system assists users to adopt daily routines to form a best practice of life by involving themselves in healthy physical activities. Traditional physical activity recommendation systems focus on general recommendations applicable to a community of users rather than specific individuals. These recommendations are general in nature and are fit for the community at a certain level, but they are not relevant to every individual based on specific requirements and personal interests. To cover this aspect, we propose a multimodal hybrid reasoning methodology (HRM) that generates personalized physical activity recommendations according to the user׳s specific needs and personal interests. The methodology integrates the rule-based reasoning (RBR), case-based reasoning (CBR), and preference-based reasoning (PBR) approaches in a linear combination that enables personalization of recommendations. RBR uses explicit knowledge rules from physical activity guidelines, CBR uses implicit knowledge from experts׳ past experiences, and PBR uses users׳ personal interests and preferences. To validate the methodology, a weight management scenario is considered and experimented with. The RBR part of the methodology generates goal, weight status, and plan recommendations, the CBR part suggests the top three relevant physical activities for executing the recommended plan, and the PBR part filters out irrelevant recommendations from the suggested ones using the user׳s personal preferences and interests. To evaluate the methodology, a baseline-RBR system is developed, which is improved first using ranged rules and ultimately using a hybrid-CBR. A comparison of the results of these systems shows that hybrid-CBR outperforms the modified-RBR and baseline-RBR systems. Hybrid-CBR yields a 0.94% recall, a 0.97% precision, a 0.95% f-score, and low Type I and Type II errors. Copyright © 2015 Elsevier Ltd. All rights reserved.

Vote Stuffing Control in IPTV-based Recommender Systems

NASA Astrophysics Data System (ADS)

Bhatt, Rajen

Vote stuffing is a general problem in the functioning of the content rating-based recommender systems. Currently IPTV viewers browse various contents based on the program ratings. In this paper, we propose a fuzzy clustering-based approach to remove the effects of vote stuffing and consider only the genuine ratings for the programs over multiple genres. The approach requires only one authentic rating, which is generally available from recommendation system administrators or program broadcasters. The entire process is automated using fuzzy c-means clustering. Computational experiments performed over one real-world program rating database shows that the proposed approach is very efficient for controlling vote stuffing.

Hot news recommendation system from heterogeneous websites based on bayesian model.

PubMed

Xia, Zhengyou; Xu, Shengwu; Liu, Ningzhong; Zhao, Zhengkang

2014-01-01

The most current news recommendations are suitable for news which comes from a single news website, not for news from different heterogeneous news websites. Previous researches about news recommender systems based on different strategies have been proposed to provide news personalization services for online news readers. However, little research work has been reported on utilizing hundreds of heterogeneous news websites to provide top hot news services for group customers (e.g., government staffs). In this paper, we propose a hot news recommendation model based on Bayesian model, which is from hundreds of different news websites. In the model, we determine whether the news is hot news by calculating the joint probability of the news. We evaluate and compare our proposed recommendation model with the results of human experts on the real data sets. Experimental results demonstrate the reliability and effectiveness of our method. We also implement this model in hot news recommendation system of Hangzhou city government in year 2013, which achieves very good results.

Hot News Recommendation System from Heterogeneous Websites Based on Bayesian Model

PubMed Central

Xia, Zhengyou; Xu, Shengwu; Liu, Ningzhong; Zhao, Zhengkang

2014-01-01

The most current news recommendations are suitable for news which comes from a single news website, not for news from different heterogeneous news websites. Previous researches about news recommender systems based on different strategies have been proposed to provide news personalization services for online news readers. However, little research work has been reported on utilizing hundreds of heterogeneous news websites to provide top hot news services for group customers (e.g., government staffs). In this paper, we propose a hot news recommendation model based on Bayesian model, which is from hundreds of different news websites. In the model, we determine whether the news is hot news by calculating the joint probability of the news. We evaluate and compare our proposed recommendation model with the results of human experts on the real data sets. Experimental results demonstrate the reliability and effectiveness of our method. We also implement this model in hot news recommendation system of Hangzhou city government in year 2013, which achieves very good results. PMID:25093207

Recruitment recommendation system based on fuzzy measure and indeterminate integral

NASA Astrophysics Data System (ADS)

Yin, Xin; Song, Jinjie

2017-08-01

In this study, we propose a comprehensive evaluation approach based on indeterminate integral. By introducing the related concepts of indeterminate integral and their formulas into the recruitment recommendation system, we can calculate the suitability of each job for different applicants with the defined importance for each criterion listed in the job advertisements, the association between different criteria and subjective assessment as the prerequisite. Thus we can make recommendations to the applicants based on the score of the suitability of each job from high to low. In the end, we will exemplify the usefulness and practicality of this system with samples.

Improved Personalized Recommendation Based on Causal Association Rule and Collaborative Filtering

ERIC Educational Resources Information Center

Lei, Wu; Qing, Fang; Zhou, Jin

2016-01-01

There are usually limited user evaluation of resources on a recommender system, which caused an extremely sparse user rating matrix, and this greatly reduce the accuracy of personalized recommendation, especially for new users or new items. This paper presents a recommendation method based on rating prediction using causal association rules.…

Career Goal-Based E-Learning Recommendation Using Enhanced Collaborative Filtering and PrefixSpan

ERIC Educational Resources Information Center

Ma, Xueying; Ye, Lu

2018-01-01

This article describes how e-learning recommender systems nowadays have applied different kinds of techniques to recommend personalized learning content for users based on their preference, goals, interests and background information. However, the cold-start problem which exists in traditional recommendation algorithms are still left over in…

Constructing compact and effective graphs for recommender systems via node and edge aggregations

DOE PAGES

Lee, Sangkeun; Kahng, Minsuk; Lee, Sang-goo

2014-12-10

Exploiting graphs for recommender systems has great potential to flexibly incorporate heterogeneous information for producing better recommendation results. As our baseline approach, we first introduce a naive graph-based recommendation method, which operates with a heterogeneous log-metadata graph constructed from user log and content metadata databases. Although the na ve graph-based recommendation method is simple, it allows us to take advantages of heterogeneous information and shows promising flexibility and recommendation accuracy. However, it often leads to extensive processing time due to the sheer size of the graphs constructed from entire user log and content metadata databases. In this paper, we proposemore » node and edge aggregation approaches to constructing compact and e ective graphs called Factor-Item bipartite graphs by aggregating nodes and edges of a log-metadata graph. Furthermore, experimental results using real world datasets indicate that our approach can significantly reduce the size of graphs exploited for recommender systems without sacrificing the recommendation quality.« less

The SAPO Campus Recommender System: A Study about Students' and Teachers' Opinions

ERIC Educational Resources Information Center

Pedro, Luís; Santos, Carlos; Almeida, Sara Filipa; Ramos, Fernando; Moreira, António; Almeida, Margarida; Antunes, Maria João

2014-01-01

This paper aims to assess the relevance and usefulness of the SAPO Campus recommender system, through the analysis of students' and teachers' opinions. Recommender systems, assuming a "technology-driven" approach, have been designed with the primary goal of predicting user interests based on the implicit analysis of their actions and…

Shilling attack detection for recommender systems based on credibility of group users and rating time series.

PubMed

Zhou, Wei; Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user's credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method.

Shilling attack detection for recommender systems based on credibility of group users and rating time series

PubMed Central

Wen, Junhao; Qu, Qiang; Zeng, Jun; Cheng, Tian

2018-01-01

Recommender systems are vulnerable to shilling attacks. Forged user-generated content data, such as user ratings and reviews, are used by attackers to manipulate recommendation rankings. Shilling attack detection in recommender systems is of great significance to maintain the fairness and sustainability of recommender systems. The current studies have problems in terms of the poor universality of algorithms, difficulty in selection of user profile attributes, and lack of an optimization mechanism. In this paper, a shilling behaviour detection structure based on abnormal group user findings and rating time series analysis is proposed. This paper adds to the current understanding in the field by studying the credibility evaluation model in-depth based on the rating prediction model to derive proximity-based predictions. A method for detecting suspicious ratings based on suspicious time windows and target item analysis is proposed. Suspicious rating time segments are determined by constructing a time series, and data streams of the rating items are examined and suspicious rating segments are checked. To analyse features of shilling attacks by a group user’s credibility, an abnormal group user discovery method based on time series and time window is proposed. Standard testing datasets are used to verify the effect of the proposed method. PMID:29742134

Salivary dysfunction associated with systemic diseases: systematic review and clinical management recommendations.

PubMed

von Bültzingslöwen, Inger; Sollecito, Thomas P; Fox, Philip C; Daniels, Troy; Jonsson, Roland; Lockhart, Peter B; Wray, David; Brennan, Michael T; Carrozzo, Marco; Gandera, Beatrice; Fujibayashi, Takashi; Navazesh, Mahvash; Rhodus, Nelson L; Schiødt, Morten

2007-03-01

The objective of this study was to identify systemic diseases associated with hyposalivation and xerostomia and develop evidence-based management recommendations for hyposalivation/xerostomia. Literature searches covered the English language medical literature from 1966 to 2005. An evidence-based review process was applied to management studies published from 2002 to 2005. Several systemic diseases were identified. From studies published 2002 to 2005, 15 were identified as high-quality studies and were used to support management recommendations: pilocarpine and cevimeline are recommended for treating hyposalivation and xerostomia in primary and secondary Sjögren's syndrome (SS). IFN-alpha lozenges may enhance saliva flow in primary SS patients. Anti-TNF-alpha agents, such as infliximab or etanercept, are not recommended to treat hyposalivation in SS. Dehydroepiandrosterone is not recommended to relieve hyposalivation or xerostomia in primary SS. There was not enough evidence to support any recommendations for the use of local stimulants, lubricants, and protectants for hyposalivation/xerostomia. However, professional judgment and patient preferences may support the use of a specific product for an individual patient. These evidence-based management recommendations should guide the clinician's management decisions for patients with salivary dysfunction related to systemic disease. Future treatment strategies may include new formulations of existing drugs, e.g., local application of pilocarpine. Recent discoveries on gene expression and a better understanding of the etiopathogenesis of SS may open new treatment options in the future.

a Context-Aware Tourism Recommender System Based on a Spreading Activation Method

NASA Astrophysics Data System (ADS)

Bahramian, Z.; Abbaspour, R. Ali; Claramunt, C.

2017-09-01

Users planning a trip to a given destination often search for the most appropriate points of interest location, this being a non-straightforward task as the range of information available is very large and not very well structured. The research presented by this paper introduces a context-aware tourism recommender system that overcomes the information overload problem by providing personalized recommendations based on the user's preferences. It also incorporates contextual information to improve the recommendation process. As previous context-aware tourism recommender systems suffer from a lack of formal definition to represent contextual information and user's preferences, the proposed system is enhanced using an ontology approach. We also apply a spreading activation technique to contextualize user preferences and learn the user profile dynamically according to the user's feedback. The proposed method assigns more effect in the spreading process for nodes which their preference values are assigned directly by the user. The results show the overall performance of the proposed context-aware tourism recommender systems by an experimental application to the city of Tehran.

Research on personalized recommendation algorithm based on spark

NASA Astrophysics Data System (ADS)

Li, Zeng; Liu, Yu

2018-04-01

With the increasing amount of data in the past years, the traditional recommendation algorithm has been unable to meet people's needs. Therefore, how to better recommend their products to users of interest, become the opportunities and challenges of the era of big data development. At present, each platform enterprise has its own recommendation algorithm, but how to make efficient and accurate push information is still an urgent problem for personalized recommendation system. In this paper, a hybrid algorithm based on user collaborative filtering and content-based recommendation algorithm is proposed on Spark to improve the efficiency and accuracy of recommendation by weighted processing. The experiment shows that the recommendation under this scheme is more efficient and accurate.

Finding Your Literature Match - A Physics Literature Recommender System

NASA Astrophysics Data System (ADS)

Henneken, Edwin; Kurtz, Michael

2010-03-01

A recommender system is a filtering algorithm that helps you find the right match by offering suggestions based on your choices and information you have provided. A latent factor model is a successful approach. Here an item is characterized by a vector describing to what extent a product is described by each of N categories, and a person is characterized by an ``interest'' vector, based on explicit or implicit feedback by this user. The recommender system assigns ratings to new items and suggests items this user might be interested in. Here we present results of a recommender system designed to find recent literature of interest to people working in the field of solid state physics. Since we do not have explicit feedback, our user vector consists of (implicit) ``usage.'' Using a system of N keywords we construct normalized keyword vectors for articles based on the keywords of that article and its bibliography. The normalized ``interest'' vector is created by calculating the normalized frequency of keyword occurrence in the papers cited by the papers read.

Human factors in the Naval Air Systems Command: Computer based training

DOE Office of Scientific and Technical Information (OSTI.GOV)

Seamster, T.L.; Snyder, C.E.; Terranova, M.

1988-01-01

Military standards applied to the private sector contracts have a substantial effect on the quality of Computer Based Training (CBT) systems procured for the Naval Air Systems Command. This study evaluated standards regulating the following areas in CBT development and procurement: interactive training systems, cognitive task analysis, and CBT hardware. The objective was to develop some high-level recommendations for evolving standards that will govern the next generation of CBT systems. One of the key recommendations is that there be an integration of the instructional systems development, the human factors engineering, and the software development standards. Recommendations were also made formore » task analysis and CBT hardware standards. (9 refs., 3 figs.)« less

A Personalized Recommendation-Based Mobile Learning Approach to Improving the Reading Performance of EFL Students

ERIC Educational Resources Information Center

Hsu, Ching-Kun; Hwang, Gwo-Jen; Chang, Chih-Kai

2013-01-01

In this paper, a personalized recommendation-based mobile language learning approach is proposed. A mobile learning system has been developed based on the approach by providing a reading material recommendation mechanism for guiding EFL (English as Foreign Language) students to read articles that match their preferences and knowledge levels, and a…

Personalized recommendation via unbalance full-connectivity inference

NASA Astrophysics Data System (ADS)

Ma, Wenping; Ren, Chen; Wu, Yue; Wang, Shanfeng; Feng, Xiang

2017-10-01

Recommender systems play an important role to help us to find useful information. They are widely used by most e-commerce web sites to push the potential items to individual user according to purchase history. Network-based recommendation algorithms are popular and effective in recommendation, which use two types of elements to represent users and items respectively. In this paper, based on consistence-based inference (CBI) algorithm, we propose a novel network-based algorithm, in which users and items are recognized with no difference. The proposed algorithm also uses information diffusion to find the relationship between users and items. Different from traditional network-based recommendation algorithms, information diffusion initializes from users and items, respectively. Experiments show that the proposed algorithm is effective compared with traditional network-based recommendation algorithms.

A Recommender System for an IPTV Service Provider: a Real Large-Scale Production Environment

NASA Astrophysics Data System (ADS)

Bambini, Riccardo; Cremonesi, Paolo; Turrin, Roberto

In this chapter we describe the integration of a recommender system into the production environment of Fastweb, one of the largest European IP Television (IPTV) providers. The recommender system implements both collaborative and content-based techniques, suitable tailored to the specific requirements of an IPTV architecture, such as the limited screen definition, the reduced navigation capabilities, and the strict time constraints. The algorithms are extensively analyzed by means of off-line and on-line tests, showing the effectiveness of the recommender systems: up to 30% of the recommendations are followed by a purchase, with an estimated lift factor (increase in sales) of 15%.

Answering medical questions at the point of care: a cross-sectional study comparing rapid decisions based on PubMed and Epistemonikos searches with evidence-based recommendations developed with the GRADE approach.

PubMed

Izcovich, Ariel; Criniti, Juan Martín; Popoff, Federico; Ragusa, Martín Alberto; Gigler, Cristel; Gonzalez Malla, Carlos; Clavijo, Manuela; Manzotti, Matias; Diaz, Martín; Catalano, Hugo Norberto; Neumann, Ignacio; Guyatt, Gordon

2017-08-07

Using the best current evidence to inform clinical decisions remains a challenge for clinicians. Given the scarcity of trustworthy clinical practice guidelines providing recommendations to answer clinicians' daily questions, clinical decision support systems (ie, assistance in question identification and answering) emerge as an attractive alternative. The trustworthiness of the recommendations achieved by such systems is unknown. To evaluate the trustworthiness of a question identification and answering system that delivers timely recommendations. Cross-sectional study. We compared the responses to 100 clinical questions related to inpatient management provided by two rapid response methods with 'Gold Standard' recommendations. One of the rapid methods was based on PubMed and the other on Epistemonikos database. We defined our 'Gold Standard' as trustworthy published evidence-based recommendations or, when unavailable, recommendations developed locally by a panel of six clinicians following the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach. Recommendations provided by the rapid strategies were classified as potentially misleading or reasonable. We also determined if the potentially misleading recommendations could have been avoided with the appropriate implementation of searching and evidence summary tools. We were able to answer all of the 100 questions with both rapid methods. Of the 200 recommendations obtained, 6.5% (95% CI 3% to 9.9%) were classified as potentially misleading and 93.5% (95% CI 90% to 96.9%) as reasonable. 6 of the 13 potentially misleading recommendations could have been avoided by the appropriate usage of the Epistemonikos matrix tool or by constructing summary of findings tables. No significant differences were observed between the evaluated rapid response methods. A question answering service based on the GRADE approach proved feasible to implement and provided appropriate guidance for most identified questions. Our approach could help stakeholders in charge of managing resources and defining policies for patient care to improve evidence-based decision-making in an efficient and feasible manner. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2017. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Design of a real-time and continua-based framework for care guideline recommendations.

PubMed

Lin, Yu-Feng; Shie, Hsin-Han; Yang, Yi-Ching; Tseng, Vincent S

2014-04-16

Telehealth is an important issue in the medical and healthcare domains. Although a number of systems have been developed to meet the demands of emerging telehealth services, the following problems still remain to be addressed: (1) most systems do not monitor/predict the vital signs states so that they are able to send alarms to caregivers in real-time; (2) most systems do not focus on reducing the amount of work that caregivers need to do, and provide patients with remote care; and (3) most systems do not recommend guidelines for caregivers. This study thus proposes a framework for a real-time and Continua-based Care Guideline Recommendation System (Cagurs) which utilizes mobile device platforms to provide caregivers of chronic patients with real-time care guideline recommendations, and that enables vital signs data to be transmitted between different devices automatically, using the Continua standard. Moreover, the proposed system adopts the episode mining approach to monitor/predict anomalous conditions of patients, and then offers related recommended care guidelines to caregivers so that they can offer preventive care in a timely manner.

Design of a Real-Time and Continua-Based Framework for Care Guideline Recommendations

PubMed Central

Lin, Yu-Feng; Shie, Hsin-Han; Yang, Yi-Ching; Tseng, Vincent S.

2014-01-01

Telehealth is an important issue in the medical and healthcare domains. Although a number of systems have been developed to meet the demands of emerging telehealth services, the following problems still remain to be addressed: (1) most systems do not monitor/predict the vital signs states so that they are able to send alarms to caregivers in real-time; (2) most systems do not focus on reducing the amount of work that caregivers need to do, and provide patients with remote care; and (3) most systems do not recommend guidelines for caregivers. This study thus proposes a framework for a real-time and Continua-based Care Guideline Recommendation System (Cagurs) which utilizes mobile device platforms to provide caregivers of chronic patients with real-time care guideline recommendations, and that enables vital signs data to be transmitted between different devices automatically, using the Continua standard. Moreover, the proposed system adopts the episode mining approach to monitor/predict anomalous conditions of patients, and then offers related recommended care guidelines to caregivers so that they can offer preventive care in a timely manner. PMID:24743843

A Group Recommender System for Tourist Activities

NASA Astrophysics Data System (ADS)

Garcia, Inma; Sebastia, Laura; Onaindia, Eva; Guzman, Cesar

This paper introduces a method for giving recommendations of tourist activities to a group of users. This method makes recommendations based on the group tastes, their demographic classification and the places visited by the users in former trips. The group recommendation is computed from individual personal recommendations through the use of techniques such as aggregation, intersection or incremental intersection. This method is implemented as an extension of the e-Tourism tool, which is a user-adapted tourism and leisure application, whose main component is the Generalist Recommender System Kernel (GRSK), a domain-independent taxonomy-driven search engine that manages the group recommendation.

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation.

PubMed

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-06-01

This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care.

HealthRecSys: A semantic content-based recommender system to complement health videos.

PubMed

Sanchez Bocanegra, Carlos Luis; Sevillano Ramos, Jose Luis; Rizo, Carlos; Civit, Anton; Fernandez-Luque, Luis

2017-05-15

The Internet, and its popularity, continues to grow at an unprecedented pace. Watching videos online is very popular; it is estimated that 500 h of video are uploaded onto YouTube, a video-sharing service, every minute and that, by 2019, video formats will comprise more than 80% of Internet traffic. Health-related videos are very popular on YouTube, but their quality is always a matter of concern. One approach to enhancing the quality of online videos is to provide additional educational health content, such as websites, to support health consumers. This study investigates the feasibility of building a content-based recommender system that links health consumers to reputable health educational websites from MedlinePlus for a given health video from YouTube. The dataset for this study includes a collection of health-related videos and their available metadata. Semantic technologies (such as SNOMED-CT and Bio-ontology) were used to recommend health websites from MedlinePlus. A total of 26 healths professionals participated in evaluating 253 recommended links for a total of 53 videos about general health, hypertension, or diabetes. The relevance of the recommended health websites from MedlinePlus to the videos was measured using information retrieval metrics such as the normalized discounted cumulative gain and precision at K. The majority of websites recommended by our system for health videos were relevant, based on ratings by health professionals. The normalized discounted cumulative gain was between 46% and 90% for the different topics. Our study demonstrates the feasibility of using a semantic content-based recommender system to enrich YouTube health videos. Evaluation with end-users, in addition to healthcare professionals, will be required to identify the acceptance of these recommendations in a nonsimulated information-seeking context.

Practice-Based Evidence for Children and Adolescents: Advancing the Research Agenda in Schools

ERIC Educational Resources Information Center

Kratochwill, Thomas R.; Hoagwood, Kimberly Eaton; Kazak, Anne E.; Weisz, John R.; Hood, Korey; Vargas, Luis A.; Banez, Gerard A.

2012-01-01

The American Psychological Association Task Force on Evidence- Based Practice for Children and Adolescents (2008) recommended a systems approach to enhancing care in order to improve outcomes for children and adolescents with mental health needs and redress persistent systemic problems with the structure of services. Recommendations for enhancing…

The Effect of Recommendation Systems on Internet-Based Learning for Different Learners: A Data Mining Analysis

ERIC Educational Resources Information Center

Liu, Chen-Chung; Chang, Chia-Jung; Tseng, Jui-Min

2013-01-01

A general challenge facing Internet-based learners is how to identify information objects which are helpful in expanding their understanding of important information in a domain. Recommendation systems may assist learners in identifying potentially helpful information objects. However, the recent literature mainly focuses on the technical…

E-book recommender system design and implementation based on data mining

NASA Astrophysics Data System (ADS)

Wang, Zongjiang

2011-12-01

In the knowledge explosion, rapid development of information age, how quickly the user or users interested in useful information for feedback to the user problem to be solved in this article. This paper based on data mining, association rules to the model and classification model a combination of electronic books on the recommendation of the user's neighboring users interested in e-books to target users. Introduced the e-book recommendation and the key technologies, system implementation algorithms, and implementation process, was proved through experiments that this system can help users quickly find the required e-books.

Friend suggestion in social network based on user log

NASA Astrophysics Data System (ADS)

Kaviya, R.; Vanitha, M.; Sumaiya Thaseen, I.; Mangaiyarkarasi, R.

2017-11-01

Simple friend recommendation algorithms such as similarity, popularity and social aspects is the basic requirement to be explored to methodically form high-performance social friend recommendation. Suggestion of friends is followed. No tags of character were followed. In the proposed system, we use an algorithm for network correlation-based social friend recommendation (NC-based SFR).It includes user activities like where one lives and works. A new friend recommendation method, based on network correlation, by considering the effect of different social roles. To model the correlation between different networks, we develop a method that aligns these networks through important feature selection. We consider by preserving the network structure for a more better recommendations so that it significantly improves the accuracy for better friend-recommendation.

Development of the Parkland-UT Southwestern Colonoscopy Reporting System (CoRS) for evidence-based colon cancer surveillance recommendations

PubMed Central

Gupta, Samir; Halm, Ethan A; Wright, Shaun; McCallister, Katharine; Bishop, Wendy; Santini, Noel; Mayorga, Christian; Agrawal, Deepak; Moran, Brett; Sanders, Joanne M; Singal, Amit G

2016-01-01

Objective Through colonoscopy, polyps can be identified and removed to reduce colorectal cancer incidence and mortality. Appropriate use of surveillance colonoscopy, post polypectomy, is a focus of healthcare reform. Materials and Methods The authors developed and implemented the first electronic medical record–based colonoscopy reporting system (CoRS) that matches endoscopic findings with guideline-consistent surveillance recommendations and generates tailored results and recommendation letters for patients and providers. Results In its first year, CoRS was used in 98.6% of indicated cases. Via a survey, colonoscopists agreed/strongly agreed it is easy to use (83%), provides guideline-based recommendations (89%), improves quality of Spanish letters (94%), they would recommend it for other institutions (78%), and it made their work easier (61%), and led to improved practice (56%). Discussion CoRS’ widespread adoption and acceptance likely resulted from stakeholder engagement throughout the development and implementation process. Conclusion CoRS is well-accepted by clinicians and provides guideline-based recommendations and results communications to patients and providers. PMID:26254481

Enhancing collaborative filtering by user interest expansion via personalized ranking.

PubMed

Liu, Qi; Chen, Enhong; Xiong, Hui; Ding, Chris H Q; Chen, Jian

2012-02-01

Recommender systems suggest a few items from many possible choices to the users by understanding their past behaviors. In these systems, the user behaviors are influenced by the hidden interests of the users. Learning to leverage the information about user interests is often critical for making better recommendations. However, existing collaborative-filtering-based recommender systems are usually focused on exploiting the information about the user's interaction with the systems; the information about latent user interests is largely underexplored. To that end, inspired by the topic models, in this paper, we propose a novel collaborative-filtering-based recommender system by user interest expansion via personalized ranking, named iExpand. The goal is to build an item-oriented model-based collaborative-filtering framework. The iExpand method introduces a three-layer, user-interests-item, representation scheme, which leads to more accurate ranking recommendation results with less computation cost and helps the understanding of the interactions among users, items, and user interests. Moreover, iExpand strategically deals with many issues that exist in traditional collaborative-filtering approaches, such as the overspecialization problem and the cold-start problem. Finally, we evaluate iExpand on three benchmark data sets, and experimental results show that iExpand can lead to better ranking performance than state-of-the-art methods with a significant margin.

Integration of Evidence into a Detailed Clinical Model-based Electronic Nursing Record System

PubMed Central

Park, Hyeoun-Ae; Jeon, Eunjoo; Chung, Eunja

2012-01-01

Objectives The purpose of this study was to test the feasibility of an electronic nursing record system for perinatal care that is based on detailed clinical models and clinical practice guidelines in perinatal care. Methods This study was carried out in five phases: 1) generating nursing statements using detailed clinical models; 2) identifying the relevant evidence; 3) linking nursing statements with the evidence; 4) developing a prototype electronic nursing record system based on detailed clinical models and clinical practice guidelines; and 5) evaluating the prototype system. Results We first generated 799 nursing statements describing nursing assessments, diagnoses, interventions, and outcomes using entities, attributes, and value sets of detailed clinical models for perinatal care which we developed in a previous study. We then extracted 506 recommendations from nine clinical practice guidelines and created sets of nursing statements to be used for nursing documentation by grouping nursing statements according to these recommendations. Finally, we developed and evaluated a prototype electronic nursing record system that can provide nurses with recommendations for nursing practice and sets of nursing statements based on the recommendations for guiding nursing documentation. Conclusions The prototype system was found to be sufficiently complete, relevant, useful, and applicable in terms of content, and easy to use and useful in terms of system user interface. This study has revealed the feasibility of developing such an ENR system. PMID:22844649

Mobile Clinical Decision Support System for Acid-base Balance Diagnosis and Treatment Recommendation

PubMed Central

Mandzuka, Mensur; Begic, Edin; Boskovic, Dusanka; Begic, Zijo; Masic, Izet

2017-01-01

Introduction: This paper presents mobile application implementing a decision support system for acid-base disorder diagnosis and treatment recommendation. Material and methods: The application was developed using the official integrated development environment for the Android platform (to maximize availability and minimize investments in specialized hardware) called Android Studio. Results: The application identifies disorder, based on the blood gas analysis, evaluates whether the disorder has been compensated, and based on additional input related to electrolyte imbalance, provides recommendations for treatment. Conclusion: The application is a tool in the hands of the user, which provides assistance during acid-base disorders treatment. The application will assist the physician in clinical practice and is focused on the treatment in intensive care. PMID:28883678

I should not recommend it to you even if you will like it: the ethics of recommender systems

NASA Astrophysics Data System (ADS)

Tang, Tiffany Ya; Winoto, Pinata

2016-01-01

In this paper, we extend the current research in the recommendation system community by showing that users did attach ethical consideration to items. In an experiment (N = 111) that manipulated several moral factors regarding the potentially harmful content in movies, books, and games, users were asked to evaluate the appropriateness of recommending these items to teenagers and adult couples. Results agreed with previous studies in that gender plays a key role in making moral judgment, especially regarding the ethical appropriateness of an item. The pilot study further identifies degrees of aversion regarding the appeal of these elements in media for ethical recommendations. Based on the study, we propose a user-initiated ethical recommender system to help users pick up morally appropriate items during the post-recommendation process. We believe that the ethical appropriateness of items perceived by end users could predict the trust and credibility of the system.

Automated recommendation for cervical cancer screening and surveillance.

PubMed

Wagholikar, Kavishwar B; MacLaughlin, Kathy L; Casey, Petra M; Kastner, Thomas M; Henry, Michael R; Hankey, Ronald A; Peters, Steve G; Greenes, Robert A; Chute, Christopher G; Liu, Hongfang; Chaudhry, Rajeev

2014-01-01

Because of the complexity of cervical cancer prevention guidelines, clinicians often fail to follow best-practice recommendations. Moreover, existing clinical decision support (CDS) systems generally recommend a cervical cytology every three years for all female patients, which is inappropriate for patients with abnormal findings that require surveillance at shorter intervals. To address this problem, we developed a decision tree-based CDS system that integrates national guidelines to provide comprehensive guidance to clinicians. Validation was performed in several iterations by comparing recommendations generated by the system with those of clinicians for 333 patients. The CDS system extracted relevant patient information from the electronic health record and applied the guideline model with an overall accuracy of 87%. Providers without CDS assistance needed an average of 1 minute 39 seconds to decide on recommendations for management of abnormal findings. Overall, our work demonstrates the feasibility and potential utility of automated recommendation system for cervical cancer screening and surveillance.

Data base management study

NASA Technical Reports Server (NTRS)

1976-01-01

Data base management techniques and applicable equipment are described. Recommendations which will assist potential NASA data users in selecting and using appropriate data base management tools and techniques are presented. Classes of currently available data processing equipment ranging from basic terminals to large minicomputer systems were surveyed as they apply to the needs of potential SEASAT data users. Cost and capabilities projections for this equipment through 1985 were presented. A test of a typical data base management system was described, as well as the results of this test and recommendations to assist potential users in determining when such a system is appropriate for their needs. The representative system tested was UNIVAC's DMS 1100.

A novel video recommendation system based on efficient retrieval of human actions

NASA Astrophysics Data System (ADS)

Ramezani, Mohsen; Yaghmaee, Farzin

2016-09-01

In recent years, fast growth of online video sharing eventuated new issues such as helping users to find their requirements in an efficient way. Hence, Recommender Systems (RSs) are used to find the users' most favorite items. Finding these items relies on items or users similarities. Though, many factors like sparsity and cold start user impress the recommendation quality. In some systems, attached tags are used for searching items (e.g. videos) as personalized recommendation. Different views, incomplete and inaccurate tags etc. can weaken the performance of these systems. Considering the advancement of computer vision techniques can help improving RSs. To this end, content based search can be used for finding items (here, videos are considered). In such systems, a video is taken from the user to find and recommend a list of most similar videos to the query one. Due to relating most videos to humans, we present a novel low complex scalable method to recommend videos based on the model of included action. This method has recourse to human action retrieval approaches. For modeling human actions, some interest points are extracted from each action and their motion information are used to compute the action representation. Moreover, a fuzzy dissimilarity measure is presented to compare videos for ranking them. The experimental results on HMDB, UCFYT, UCF sport and KTH datasets illustrated that, in most cases, the proposed method can reach better results than most used methods.

A system management methodology for building successful resource management systems

NASA Technical Reports Server (NTRS)

Hornstein, Rhoda Shaller; Willoughby, John K.

1989-01-01

This paper presents a system management methodology for building successful resource management systems that possess lifecycle effectiveness. This methodology is based on an analysis of the traditional practice of Systems Engineering Management as it applies to the development of resource management systems. The analysis produced fifteen significant findings presented as recommended adaptations to the traditional practice of Systems Engineering Management to accommodate system development when the requirements are incomplete, unquantifiable, ambiguous and dynamic. Ten recommended adaptations to achieve operational effectiveness when requirements are incomplete, unquantifiable or ambiguous are presented and discussed. Five recommended adaptations to achieve system extensibility when requirements are dynamic are also presented and discussed. The authors conclude that the recommended adaptations to the traditional practice of Systems Engineering Management should be implemented for future resource management systems and that the technology exists to build these systems extensibly.

A comparative study: classification vs. user-based collaborative filtering for clinical prediction.

PubMed

Hao, Fang; Blair, Rachael Hageman

2016-12-08

Recommender systems have shown tremendous value for the prediction of personalized item recommendations for individuals in a variety of settings (e.g., marketing, e-commerce, etc.). User-based collaborative filtering is a popular recommender system, which leverages an individuals' prior satisfaction with items, as well as the satisfaction of individuals that are "similar". Recently, there have been applications of collaborative filtering based recommender systems for clinical risk prediction. In these applications, individuals represent patients, and items represent clinical data, which includes an outcome. Application of recommender systems to a problem of this type requires the recasting a supervised learning problem as unsupervised. The rationale is that patients with similar clinical features carry a similar disease risk. As the "Big Data" era progresses, it is likely that approaches of this type will be reached for as biomedical data continues to grow in both size and complexity (e.g., electronic health records). In the present study, we set out to understand and assess the performance of recommender systems in a controlled yet realistic setting. User-based collaborative filtering recommender systems are compared to logistic regression and random forests with different types of imputation and varying amounts of missingness on four different publicly available medical data sets: National Health and Nutrition Examination Survey (NHANES, 2011-2012 on Obesity), Study to Understand Prognoses Preferences Outcomes and Risks of Treatment (SUPPORT), chronic kidney disease, and dermatology data. We also examined performance using simulated data with observations that are Missing At Random (MAR) or Missing Completely At Random (MCAR) under various degrees of missingness and levels of class imbalance in the response variable. Our results demonstrate that user-based collaborative filtering is consistently inferior to logistic regression and random forests with different imputations on real and simulated data. The results warrant caution for the collaborative filtering for the purpose of clinical risk prediction when traditional classification is feasible and practical. CF may not be desirable in datasets where classification is an acceptable alternative. We describe some natural applications related to "Big Data" where CF would be preferred and conclude with some insights as to why caution may be warranted in this context.

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choo, Jaegul; Kim, Hannah; Clarkson, Edward

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

VisIRR: A Visual Analytics System for Information Retrieval and Recommendation for Large-Scale Document Data

DOE PAGES

Choo, Jaegul; Kim, Hannah; Clarkson, Edward; ...

2018-01-31

In this paper, we present an interactive visual information retrieval and recommendation system, called VisIRR, for large-scale document discovery. VisIRR effectively combines the paradigms of (1) a passive pull through query processes for retrieval and (2) an active push that recommends items of potential interest to users based on their preferences. Equipped with an efficient dynamic query interface against a large-scale corpus, VisIRR organizes the retrieved documents into high-level topics and visualizes them in a 2D space, representing the relationships among the topics along with their keyword summary. In addition, based on interactive personalized preference feedback with regard to documents,more » VisIRR provides document recommendations from the entire corpus, which are beyond the retrieved sets. Such recommended documents are visualized in the same space as the retrieved documents, so that users can seamlessly analyze both existing and newly recommended ones. This article presents novel computational methods, which make these integrated representations and fast interactions possible for a large-scale document corpus. We illustrate how the system works by providing detailed usage scenarios. Finally, we present preliminary user study results for evaluating the effectiveness of the system.« less

N-Screen Aware Multicriteria Hybrid Recommender System Using Weight Based Subspace Clustering

PubMed Central

Ullah, Farman; Lee, Sungchang

2014-01-01

This paper presents a recommender system for N-screen services in which users have multiple devices with different capabilities. In N-screen services, a user can use various devices in different locations and time and can change a device while the service is running. N-screen aware recommendation seeks to improve the user experience with recommended content by considering the user N-screen device attributes such as screen resolution, media codec, remaining battery time, and access network and the user temporal usage pattern information that are not considered in existing recommender systems. For N-screen aware recommendation support, this work introduces a user device profile collaboration agent, manager, and N-screen control server to acquire and manage the user N-screen devices profile. Furthermore, a multicriteria hybrid framework is suggested that incorporates the N-screen devices information with user preferences and demographics. In addition, we propose an individual feature and subspace weight based clustering (IFSWC) to assign different weights to each subspace and each feature within a subspace in the hybrid framework. The proposed system improves the accuracy, precision, scalability, sparsity, and cold start issues. The simulation results demonstrate the effectiveness and prove the aforementioned statements. PMID:25152921

Rural applications of advanced traveler information systems : recommended actions

DOT National Transportation Integrated Search

1997-07-01

The Recommended Action Plan is one in a series of interim documents for the Rural Applications of Advanced Traveler Information Systems (ATIS) project. Based on the investigation of user needs, a technology review, and concept development and assessm...

A hybrid fuzzy-ontology based intelligent system to determine level of severity and treatment recommendation for Benign Prostatic Hyperplasia.

PubMed

Torshizi, Abolfazl Doostparast; Zarandi, Mohammad Hossein Fazel; Torshizi, Ghazaleh Doostparast; Eghbali, Kamyar

2014-01-01

This paper deals with application of fuzzy intelligent systems in diagnosing severity level and recommending appropriate therapies for patients having Benign Prostatic Hyperplasia. Such an intelligent system can have remarkable impacts on correct diagnosis of the disease and reducing risk of mortality. This system captures various factors from the patients using two modules. The first module determines severity level of the Benign Prostatic Hyperplasia and the second module, which is a decision making unit, obtains output of the first module accompanied by some external knowledge and makes an appropriate treatment decision based on its ontology model and a fuzzy type-1 system. In order to validate efficiency and accuracy of the developed system, a case study is conducted by 44 participants. Then the results are compared with the recommendations of a panel of experts on the experimental data. Then precision and accuracy of the results were investigated based on a statistical analysis. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Improved personalized recommendation based on a similarity network

NASA Astrophysics Data System (ADS)

Wang, Ximeng; Liu, Yun; Xiong, Fei

2016-08-01

A recommender system helps individual users find the preferred items rapidly and has attracted extensive attention in recent years. Many successful recommendation algorithms are designed on bipartite networks, such as network-based inference or heat conduction. However, most of these algorithms define the resource-allocation methods for an average allocation. That is not reasonable because average allocation cannot indicate the user choice preference and the influence between users which leads to a series of non-personalized recommendation results. We propose a personalized recommendation approach that combines the similarity function and bipartite network to generate a similarity network that improves the resource-allocation process. Our model introduces user influence into the recommender system and states that the user influence can make the resource-allocation process more reasonable. We use four different metrics to evaluate our algorithms for three benchmark data sets. Experimental results show that the improved recommendation on a similarity network can obtain better accuracy and diversity than some competing approaches.

Diffusion-based recommendation with trust relations on tripartite graphs

NASA Astrophysics Data System (ADS)

Wang, Ximeng; Liu, Yun; Zhang, Guangquan; Xiong, Fei; Lu, Jie

2017-08-01

The diffusion-based recommendation approach is a vital branch in recommender systems, which successfully applies physical dynamics to make recommendations for users on bipartite or tripartite graphs. Trust links indicate users’ social relations and can provide the benefit of reducing data sparsity. However, traditional diffusion-based algorithms only consider rating links when making recommendations. In this paper, the complementarity of users’ implicit and explicit trust is exploited, and a novel resource-allocation strategy is proposed, which integrates these two kinds of trust relations on tripartite graphs. Through empirical studies on three benchmark datasets, our proposed method obtains better performance than most of the benchmark algorithms in terms of accuracy, diversity and novelty. According to the experimental results, our method is an effective and reasonable way to integrate additional features into the diffusion-based recommendation approach.

An Effective News Recommendation Method for Microblog User

PubMed Central

Gu, Wanrong; Dong, Shoubin; Zeng, Zhizhao; He, Jinchao

2014-01-01

Recommending news stories to users, based on their preferences, has long been a favourite domain for recommender systems research. Traditional systems strive to satisfy their user by tracing users' reading history and choosing the proper candidate news articles to recommend. However, most of news websites hardly require any user to register before reading news. Besides, the latent relations between news and microblog, the popularity of particular news, and the news organization are not addressed or solved efficiently in previous approaches. In order to solve these issues, we propose an effective personalized news recommendation method based on microblog user profile building and sub class popularity prediction, in which we propose a news organization method using hybrid classification and clustering, implement a sub class popularity prediction method, and construct user profile according to our actual situation. We had designed several experiments compared to the state-of-the-art approaches on a real world dataset, and the experimental results demonstrate that our system significantly improves the accuracy and diversity in mass text data. PMID:24983011

SemCiR: A Citation Recommendation System Based on a Novel Semantic Distance Measure

ERIC Educational Resources Information Center

Zarrinkalam, Fattane; Kahani, Mohsen

2013-01-01

Purpose: The purpose of this paper is to propose a novel citation recommendation system that inputs a text and recommends publications that should be cited by it. Its goal is to help researchers in finding related works. Further, this paper seeks to explore the effect of using relational features in addition to textual features on the quality of…

Expert Recommender: Designing for a Network Organization

NASA Astrophysics Data System (ADS)

Reichling, Tim; Veith, Michael; Wulf, Volker

Recent knowledge management initiatives focus on expertise sharing within formal organizational units and informal communities of practice. Expert recommender systems seem to be a promising tool in support of these initiatives. This paper presents experiences in designing an expert recommender system for a knowledge- intensive organization, namely the National Industry Association (NIA). Field study results provide a set of specific design requirements. Based on these requirements, we have designed an expert recommender system which is integrated into the specific software infrastructure of the organizational setting. The organizational setting is, as we will show, specific for historical, political, and economic reasons. These particularities influence the employees’ organizational and (inter-)personal needs within this setting. The paper connects empirical findings of a long-term case study with design experiences of an expertise recommender system.

Research on the Application of Persona in Book Recommendation System

NASA Astrophysics Data System (ADS)

Gao, Baozhong; Du, Shouyan; Li, Xinzhi; Liu, Fangai

2017-10-01

Currently, there still exists a host of problems in the book recommendation system, such as low accuracy, weak correlation and poor pertinence. Aiming to unravel these problems, this paper based on the theory of big data and data mining technology, through analyzing internet user behavior and the “5C” model of personal credit evaluation, combined with joint impact weight calculation method, which involves user grade, borrowing credit, book friend recommendation degree, book friend recommended adoption degree, borrowing frequency, borrowing number, and borrowing time interval. User activity and credit are also taken into account in the process of establishing user tagging system so as to build classified book recommendation service. This method is of universal meaning to the book recommendation service of smart campus with user as the core under big data environment.

A Decision Fusion Framework for Treatment Recommendation Systems.

PubMed

Mei, Jing; Liu, Haifeng; Li, Xiang; Xie, Guotong; Yu, Yiqin

2015-01-01

Treatment recommendation is a nontrivial task--it requires not only domain knowledge from evidence-based medicine, but also data insights from descriptive, predictive and prescriptive analysis. A single treatment recommendation system is usually trained or modeled with a limited (size or quality) source. This paper proposes a decision fusion framework, combining both knowledge-driven and data-driven decision engines for treatment recommendation. End users (e.g. using the clinician workstation or mobile apps) could have a comprehensive view of various engines' opinions, as well as the final decision after fusion. For implementation, we leverage several well-known fusion algorithms, such as decision templates and meta classifiers (of logistic and SVM, etc.). Using an outcome-driven evaluation metric, we compare the fusion engine with base engines, and our experimental results show that decision fusion is a promising way towards a more valuable treatment recommendation.

A proposed configurable approach for recommendation systems via data mining techniques

NASA Astrophysics Data System (ADS)

Khedr, Ayman E.; Idrees, Amira M.; Hegazy, Abd El-Fatah; El-Shewy, Samir

2018-02-01

This study presents a configurable approach for recommendations which determines the suitable recommendation method for each field based on the characteristics of its data, the method includes determining the suitable technique for selecting a representative sample of the provided data. Then selecting the suitable feature weighting measure to provide a correct weight for each feature based on its effect on the recommendations. Finally, selecting the suitable algorithm to provide the required recommendations. The proposed configurable approach could be applied on different domains. The experiments have revealed that the approach is able to provide recommendations with only 0.89 error rate percentage.

Appendix C: Rapid development approaches for system engineering and design

NASA Technical Reports Server (NTRS)

1993-01-01

Conventional system architectures, development processes, and tool environments often produce systems which exceed cost expectations and are obsolete before they are fielded. This paper explores some of the reasons for this and provides recommendations for how we can do better. These recommendations are based on DoD and NASA system developments and on our exploration and development of system/software engineering tools.

Information filtering via biased random walk on coupled social network.

PubMed

Nie, Da-Cheng; Zhang, Zi-Ke; Dong, Qiang; Sun, Chongjing; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods.

Information Filtering via Biased Random Walk on Coupled Social Network

PubMed Central

Dong, Qiang; Fu, Yan

2014-01-01

The recommender systems have advanced a great deal in the past two decades. However, most researchers focus their attentions on mining the similarities among users or objects in recommender systems and overlook the social influence which plays an important role in users' purchase process. In this paper, we design a biased random walk algorithm on coupled social networks which gives recommendation results based on both social interests and users' preference. Numerical analyses on two real data sets, Epinions and Friendfeed, demonstrate the improvement of recommendation performance by taking social interests into account, and experimental results show that our algorithm can alleviate the user cold-start problem more effectively compared with the mass diffusion and user-based collaborative filtering methods. PMID:25147867

THE SCIENCE BEHIND THE ICRP 2005 RECOMMENDATIONS

EPA Science Inventory

The ICRP 2005 Recommendations are stated to be "based on a simple, but widely applicable, general system of protection that will clarify its objectives and will provide a basis for the more formal systems needed by operating managements and regulators". The Recommendati...

Improving the recommender algorithms with the detected communities in bipartite networks

NASA Astrophysics Data System (ADS)

Zhang, Peng; Wang, Duo; Xiao, Jinghua

2017-04-01

Recommender system offers a powerful tool to make information overload problem well solved and thus gains wide concerns of scholars and engineers. A key challenge is how to make recommendations more accurate and personalized. We notice that community structures widely exist in many real networks, which could significantly affect the recommendation results. By incorporating the information of detected communities in the recommendation algorithms, an improved recommendation approach for the networks with communities is proposed. The approach is examined in both artificial and real networks, the results show that the improvement on accuracy and diversity can be 20% and 7%, respectively. This reveals that it is beneficial to classify the nodes based on the inherent properties in recommender systems.

Data You May Like: A Recommender System for Research Data Discovery

NASA Astrophysics Data System (ADS)

Devaraju, A.; Davy, R.; Hogan, D.

2016-12-01

Various data portals been developed to facilitate access to research datasets from different sources. For example, the Data Publisher for Earth & Environmental Science (PANGAEA), the Registry of Research Data Repositories (re3data.org), and the National Geoscience Data Centre (NGDC). Due to data quantity and heterogeneity, finding relevant datasets on these portals may be difficult and tedious. Keyword searches based on specific metadata elements or multi-key indexes may return irrelevant results. Faceted searches may be unsatisfactory and time consuming, especially when facet values are exhaustive. We need a much more intelligent way to complement existing searching mechanisms in order to enhance user experiences of the data portals. We developed a recommender system that helps users to find the most relevant research datasets on the CSIRO's Data Access Portal (DAP). The system is based on content-based filtering. We computed the similarity of datasets based on data attributes (e.g., descriptions, fields of research, location, contributors, and provenance) and inference from transaction logs (e.g., the relations among datasets and between queries and datasets). We improved the recommendation quality by assigning weights to data similarities. The weight values are drawn from a survey involving data users. The recommender results for a given dataset are accessible programmatically via a web service. Taking both data attributes and user actions into account, the recommender system will make it easier for researchers to find and reuse data offered through the data portal.

Developing an evidence base of best practices for integrating computerized systems into the exam room: a systematic review.

PubMed

Patel, Minal R; Vichich, Jennifer; Lang, Ian; Lin, Jessica; Zheng, Kai

2017-04-01

The introduction of health information technology systems, electronic health records in particular, is changing the nature of how clinicians interact with patients. Lack of knowledge remains on how best to integrate such systems in the exam room. The purpose of this systematic review was to (1) distill "best" behavioral and communication practices recommended in the literature for clinicians when interacting with patients in the presence of computerized systems during a clinical encounter, (2) weigh the evidence of each recommendation, and (3) rank evidence-based recommendations for electronic health record communication training initiatives for clinicians. We conducted a literature search of 6 databases, resulting in 52 articles included in the analysis. We extracted information such as study setting, research design, sample, findings, and implications. Recommendations were distilled based on consistent support for behavioral and communication practices across studies. Eight behavioral and communication practices received strong support of evidence in the literature and included specific aspects of using computerized systems to facilitate conversation and transparency in the exam room, such as spatial (re)organization of the exam room, maintaining nonverbal communication, and specific techniques that integrate the computerized system into the visit and engage the patient. Four practices, although patient-centered, have received insufficient evidence to date. We developed an evidence base of best practices for clinicians to maintain patient-centered communications in the presence of computerized systems in the exam room. Further work includes development and empirical evaluation of evidence-based guidelines to better integrate computerized systems into clinical care. © The Author 2016. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com

[GRADE system: classification of quality of evidence and strength of recommendation].

PubMed

Aguayo-Albasini, José Luis; Flores-Pastor, Benito; Soria-Aledo, Víctor

2014-02-01

The acquisition and classification of scientific evidence, and subsequent formulation of recommendations constitute the basis for the development of clinical practice guidelines. There are several systems for the classification of evidence and strength of recommendations; the most commonly used nowadays is the Grading of Recommendations, Assessment, Development and Evaluation system (GRADE). The GRADE system initially classifies the evidence into high or low, coming from experimental or observational studies; subsequently and following a series of considerations, the evidence is classified into high, moderate, low or very low. The strength of recommendations is based not only on the quality of the evidence, but also on a series of factors such as the risk/benefit balance, values and preferences of the patients and professionals, and the use of resources or costs. Copyright © 2013 AEC. Published by Elsevier Espana. All rights reserved.

Improved collaborative filtering recommendation algorithm of similarity measure

NASA Astrophysics Data System (ADS)

Zhang, Baofu; Yuan, Baoping

2017-05-01

The Collaborative filtering recommendation algorithm is one of the most widely used recommendation algorithm in personalized recommender systems. The key is to find the nearest neighbor set of the active user by using similarity measure. However, the methods of traditional similarity measure mainly focus on the similarity of user common rating items, but ignore the relationship between the user common rating items and all items the user rates. And because rating matrix is very sparse, traditional collaborative filtering recommendation algorithm is not high efficiency. In order to obtain better accuracy, based on the consideration of common preference between users, the difference of rating scale and score of common items, this paper presents an improved similarity measure method, and based on this method, a collaborative filtering recommendation algorithm based on similarity improvement is proposed. Experimental results show that the algorithm can effectively improve the quality of recommendation, thus alleviate the impact of data sparseness.

Hierarchically Structured Recommender System for Improving NPS

ERIC Educational Resources Information Center

Kuang, Jieyan

2016-01-01

Net Promoter System (NPS) is well known as an evaluation measure of the growth engine of big companies in the business area. The ultimate goal of my research is to build an action rules and meta-actions based recommender system for improving NPS scores of 34 companies (clients) dealing with similar businesses in the US and Canada. With the given…

Using a Recommender System and Hyperwave Attributes To Augment an Electronic Resource Library.

ERIC Educational Resources Information Center

Fenn, B.; Lennon, J.

There has been increasing interest over the past few years in systems that help users exchange recommendations about World Wide Web documents. Programs have ranged from those that rely totally on user pre-selection, to others that are based on artificial intelligence. This paper proposes a system that falls between these two extremes, providing…

Towards A Self Adaptive System for Social Wellness.

PubMed

Khattak, Asad Masood; Khan, Wajahat Ali; Pervez, Zeeshan; Iqbal, Farkhund; Lee, Sungyoung

2016-04-13

Advancements in science and technology have highlighted the importance of robust healthcare services, lifestyle services and personalized recommendations. For this purpose patient daily life activity recognition, profile information, and patient personal experience are required. In this research work we focus on the improvement in general health and life status of the elderly through the use of an innovative services to align dietary intake with daily life and health activity information. Dynamic provisioning of personalized healthcare and life-care services are based on the patient daily life activities recognized using smart phone. To achieve this, an ontology-based approach is proposed, where all the daily life activities and patient profile information are modeled in ontology. Then the semantic context is exploited with an inference mechanism that enables fine-grained situation analysis for personalized service recommendations. A generic system architecture is proposed that facilitates context information storage and exchange, profile information, and the newly recognized activities. The system exploits the patient's situation using semantic inference and provides recommendations for appropriate nutrition and activity related services. The proposed system is extensively evaluated for the claims and for its dynamic nature. The experimental results are very encouraging and have shown better accuracy than the existing system. The proposed system has also performed better in terms of the system support for a dynamic knowledge-base and the personalized recommendations.

78 FR 63208 - UPDATE-Meeting of the Community Preventive Services Task Force (Task Force)

Federal Register 2010, 2011, 2012, 2013, 2014

2013-10-23

..., and issues recommendations. These recommendations provide evidence-based options from which decision makers in communities, companies, health departments, health plans and healthcare systems, non..., available resources, and constraints of their constituents. The Task Force's recommendations, along with the...

Performance evaluation of recommendation algorithms on Internet of Things services

NASA Astrophysics Data System (ADS)

Mashal, Ibrahim; Alsaryrah, Osama; Chung, Tein-Yaw

2016-06-01

Internet of Things (IoT) is the next wave of industry revolution that will initiate many services, such as personal health care and green energy monitoring, which people may subscribe for their convenience. Recommending IoT services to the users based on objects they own will become very crucial for the success of IoT. In this work, we introduce the concept of service recommender systems in IoT by a formal model. As a first attempt in this direction, we have proposed a hyper-graph model for IoT recommender system in which each hyper-edge connects users, objects, and services. Next, we studied the usefulness of traditional recommendation schemes and their hybrid approaches on IoT service recommendation (IoTSRS) based on existing well known metrics. The preliminary results show that existing approaches perform reasonably well but further extension is required for IoTSRS. Several challenges were discussed to point out the direction of future development in IoTSR.

Knowledge-Acquisition Tool For Expert System

NASA Technical Reports Server (NTRS)

Disbrow, James D.; Duke, Eugene L.; Regenie, Victoria A.

1988-01-01

Digital flight-control systems monitored by computer program that evaluates and recommends. Flight-systems engineers for advanced, high-performance aircraft use knowlege-acquisition tool for expert-system flight-status monitor suppling interpretative data. Interpretative function especially important in time-critical, high-stress situations because it facilitates problem identification and corrective strategy. Conditions evaluated and recommendations made by ground-based engineers having essential knowledge for analysis and monitoring of performances of advanced aircraft systems.

EULAR recommendations for conducting clinical studies and/or clinical trials in systemic vasculitis: focus on anti‐neutrophil cytoplasm antibody‐associated vasculitis

PubMed Central

Hellmich, Bernhard; Flossmann, Oliver; Gross, Wolfgang L; Bacon, Paul; Cohen‐Tervaert, Jan Willem; Guillevin, Loic; Jayne, David; Mahr, Alfred; Merkel, Peter A; Raspe, Heiner; Scott, David G I; Witter, James; Yazici, Hasan; Luqmani, Raashid A

2007-01-01

Objectives To develop the European League Against Rheumatism (EULAR) recommendations for conducting clinical studies and/or clinical trials in systemic vasculitis. Methods An expert consensus group was formed consisting of rheumatologists, nephrologists and specialists in internal medicine representing five European countries and the USA, a clinical epidemiologist and representatives from regulatory agencies. Using an evidence‐based and expert opinion‐based approach in accordance with the standardised EULAR operating procedures, the group identified nine topics for a systematic literature search through a modified Delphi technique. On the basis of research questions posed by the group, recommendations were derived for conducting clinical studies and/or clinical trials in systemic vasculitis. Results Based on the results of the literature research, the expert committee concluded that sufficient evidence to formulate guidelines on conducting clinical trials was available only for anti‐neutrophil cytoplasm antibody‐associated vasculitides (AAV). It was therefore decided to focus the recommendations on these diseases. Recommendations for conducting clinical trials in AAV were elaborated and are presented in this summary document. It was decided to consider vasculitis‐specific issues rather than general issues of trial methodology. The recommendations deal with the following areas related to clinical studies of vasculitis: definitions of disease, activity states, outcome measures, eligibility criteria, trial design including relevant end points, and biomarkers. A number of aspects of trial methodology were deemed important for future research. Conclusions On the basis of expert opinion, recommendations for conducting clinical trials in AAV were formulated. Furthermore, the expert committee identified a strong need for well‐designed research in non‐AAV systemic vasculitides. PMID:17170053

Human resource recommendation algorithm based on ensemble learning and Spark

NASA Astrophysics Data System (ADS)

Cong, Zihan; Zhang, Xingming; Wang, Haoxiang; Xu, Hongjie

2017-08-01

Aiming at the problem of “information overload” in the human resources industry, this paper proposes a human resource recommendation algorithm based on Ensemble Learning. The algorithm considers the characteristics and behaviours of both job seeker and job features in the real business circumstance. Firstly, the algorithm uses two ensemble learning methods-Bagging and Boosting. The outputs from both learning methods are then merged to form user interest model. Based on user interest model, job recommendation can be extracted for users. The algorithm is implemented as a parallelized recommendation system on Spark. A set of experiments have been done and analysed. The proposed algorithm achieves significant improvement in accuracy, recall rate and coverage, compared with recommendation algorithms such as UserCF and ItemCF.

Evidence-based recommendations to improve reproductive healthcare for incarcerated women.

PubMed

Knittel, Andrea; Ti, Angeline; Schear, Sarah; Comfort, Megan

2017-09-11

Purpose The purpose of this paper is to describe standards for evidence-based reproductive healthcare for incarcerated women. Design/methodology/approach The literature on reproductive healthcare in the US criminal justice system and recommendations from professional organizations were reviewed and critical areas of concern were identified. Within these areas, studies and expert opinion were synthesized and policy recommendations were formulated through an iterative process of group discussion and document revision. This brief specifically addresses women's incarceration in the USA, but the recommendations are grounded in a human rights framework with global relevance. Findings Women who are incarcerated have health needs that are distinct from those of men, and there is a clear need for gender-responsive reproductive healthcare within the criminal justice system. This brief identifies five core domains of reproductive healthcare: routine screening, menstruation-related concerns, prenatal and postpartum care, contraception and abortion, and sexually transmitted infections. The recommendations emphasize the continuity between the criminal justice system and the community, as well as the dignity and self-determination of incarcerated women. Originality/value This brief provides a unique synthesis of the available evidence with concrete recommendations for improving the reproductive healthcare for incarcerated women.

Personalised news filtering and recommendation system using Chi-square statistics-based K-nearest neighbour (χ2SB-KNN) model

NASA Astrophysics Data System (ADS)

Adeniyi, D. A.; Wei, Z.; Yang, Y.

2017-10-01

Recommendation problem has been extensively studied by researchers in the field of data mining, database and information retrieval. This study presents the design and realisation of an automated, personalised news recommendations system based on Chi-square statistics-based K-nearest neighbour (χ2SB-KNN) model. The proposed χ2SB-KNN model has the potential to overcome computational complexity and information overloading problems, reduces runtime and speeds up execution process through the use of critical value of χ2 distribution. The proposed recommendation engine can alleviate scalability challenges through combined online pattern discovery and pattern matching for real-time recommendations. This work also showcases the development of a novel method of feature selection referred to as Data Discretisation-Based feature selection method. This is used for selecting the best features for the proposed χ2SB-KNN algorithm at the preprocessing stage of the classification procedures. The implementation of the proposed χ2SB-KNN model is achieved through the use of a developed in-house Java program on an experimental website called OUC newsreaders' website. Finally, we compared the performance of our system with two baseline methods which are traditional Euclidean distance K-nearest neighbour and Naive Bayesian techniques. The result shows a significant improvement of our method over the baseline methods studied.

Shilling Attacks Detection in Recommender Systems Based on Target Item Analysis

PubMed Central

Zhou, Wei; Wen, Junhao; Koh, Yun Sing; Xiong, Qingyu; Gao, Min; Dobbie, Gillian; Alam, Shafiq

2015-01-01

Recommender systems are highly vulnerable to shilling attacks, both by individuals and groups. Attackers who introduce biased ratings in order to affect recommendations, have been shown to negatively affect collaborative filtering (CF) algorithms. Previous research focuses only on the differences between genuine profiles and attack profiles, ignoring the group characteristics in attack profiles. In this paper, we study the use of statistical metrics to detect rating patterns of attackers and group characteristics in attack profiles. Another question is that most existing detecting methods are model specific. Two metrics, Rating Deviation from Mean Agreement (RDMA) and Degree of Similarity with Top Neighbors (DegSim), are used for analyzing rating patterns between malicious profiles and genuine profiles in attack models. Building upon this, we also propose and evaluate a detection structure called RD-TIA for detecting shilling attacks in recommender systems using a statistical approach. In order to detect more complicated attack models, we propose a novel metric called DegSim’ based on DegSim. The experimental results show that our detection model based on target item analysis is an effective approach for detecting shilling attacks. PMID:26222882

On the Recommender System for University Library

ERIC Educational Resources Information Center

Fu, Shunkai; Zhang, Yao; Seinminn

2013-01-01

Libraries are important to universities, and they have two primary features: readers as well as collections are highly professional. In this study, based on the experimental study with five millions of users' borrowing records, our discussion covers: (1) the necessity of recommender system for university libraries; (2) collaborative filtering (CF)…

User Controllability in a Hybrid Recommender System

ERIC Educational Resources Information Center

Parra Santander, Denis Alejandro

2013-01-01

Since the introduction of Tapestry in 1990, research on recommender systems has traditionally focused on the development of algorithms whose goal is to increase the accuracy of predicting users' taste based on historical data. In the last decade, this research has diversified, with "human factors" being one area that has received…

A Competitiveness Strategy for America. Reports of the Subcouncils. Second Report to the President & Congress.

ERIC Educational Resources Information Center

Competitiveness Policy Council, Washington, DC.

This publication contains detailed reports from the eight subcouncils established by the Competitiveness Policy Council to develop specific policy recommendations in eight areas. "Building a Standards-Based School System" (Education Subcouncil) recommends redirecting the education system toward achieving the National Education Goals,…

78 FR 79696 - Proposed Data Collections Submitted for Public Comment and Recommendations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-31

...-14FA] Proposed Data Collections Submitted for Public Comment and Recommendations In compliance with the... public health-based surveillance system to coordinate the collection, collation, analysis, and... system to describe the public health impacts on the population of the United States. The ATSDR is seeking...

78 FR 78361 - Proposed Data Collections Submitted for Public Comment and Recommendations

Federal Register 2010, 2011, 2012, 2013, 2014

2013-12-26

... 14-14FA] Proposed Data Collections Submitted for Public Comment and Recommendations In compliance... component. The NTSIP is the only federal public health-based surveillance system to coordinate the... necessary to establish this surveillance system to describe the public health impacts on the population of...

Towards adaptation in e-learning 2.0

NASA Astrophysics Data System (ADS)

Cristea, Alexandra I.; Ghali, Fawaz

2011-04-01

This paper presents several essential steps from an overall study on shaping new ways of learning and teaching, by using the synergetic merger of three different fields: Web 2.0, e-learning and adaptation (in particular, personalisation to the learner). These novel teaching and learning ways-the latter focus of this paper-are reflected in and finally adding to various versions of the My Online Teacher 2.0 adaptive system. In particular, this paper focuses on a study of how to more effectively use and combine the recommendation of peers and content adaptation to enhance the learning outcome in e-learning systems based on Web 2.0. In order to better isolate and examine the effects of peer recommendation and adaptive content presentation, we designed experiments inspecting collaboration between individuals based on recommendation of peers who have greater knowledge, and compare this to adaptive content recommendation, as well as to "simple" learning in a system with a minimum of Web 2.0 support. Overall, the results of adding peer recommendation and adaptive content presentation were encouraging, and are further discussed in detail in this paper.

United European Gastroenterology evidence-based guidelines for the diagnosis and therapy of chronic pancreatitis (HaPanEU).

PubMed

Löhr, J Matthias; Dominguez-Munoz, Enrique; Rosendahl, Jonas; Besselink, Marc; Mayerle, Julia; Lerch, Markus M; Haas, Stephan; Akisik, Fatih; Kartalis, Nikolaos; Iglesias-Garcia, Julio; Keller, Jutta; Boermeester, Marja; Werner, Jens; Dumonceau, Jean-Marc; Fockens, Paul; Drewes, Asbjorn; Ceyhan, Gürlap; Lindkvist, Björn; Drenth, Joost; Ewald, Nils; Hardt, Philip; de Madaria, Enrique; Witt, Heiko; Schneider, Alexander; Manfredi, Riccardo; Brøndum, Frøkjer J; Rudolf, Sasa; Bollen, Thomas; Bruno, Marco

2017-03-01

There have been substantial improvements in the management of chronic pancreatitis, leading to the publication of several national guidelines during recent years. In collaboration with United European Gastroenterology, the working group on 'Harmonizing diagnosis and treatment of chronic pancreatitis across Europe' (HaPanEU) developed these European guidelines using an evidence-based approach. Twelve multidisciplinary review groups performed systematic literature reviews to answer 101 predefined clinical questions. Recommendations were graded using the Grading of Recommendations Assessment, Development and Evaluation system and the answers were assessed by the entire group in a Delphi process online. The review groups presented their recommendations during the 2015 annual meeting of United European Gastroenterology. At this one-day, interactive conference, relevant remarks were voiced and overall agreement on each recommendation was quantified using plenary voting (Test and Evaluation Directorate). After a final round of adjustments based on these comments, a draft version was sent out to external reviewers. The 101 recommendations covered 12 topics related to the clinical management of chronic pancreatitis: aetiology (working party (WP)1), diagnosis of chronic pancreatitis with imaging (WP2 and WP3), diagnosis of pancreatic exocrine insufficiency (WP4), surgery in chronic pancreatitis (WP5), medical therapy (WP6), endoscopic therapy (WP7), treatment of pancreatic pseudocysts (WP8), pancreatic pain (WP9), nutrition and malnutrition (WP10), diabetes mellitus (WP11) and the natural course of the disease and quality of life (WP12). Using the Grading of Recommendations Assessment, Development and Evaluation system, 70 of the 101 (70%) recommendations were rated as 'strong' and plenary voting revealed 'strong agreement' for 99 (98%) recommendations. The 2016 HaPanEU/United European Gastroenterology guidelines provide evidence-based recommendations concerning key aspects of the medical and surgical management of chronic pancreatitis based on current available evidence. These recommendations should serve as a reference standard for existing management of the disease and as a guide for future clinical research.

Enabling Open Research Data Discovery through a Recommender System

NASA Astrophysics Data System (ADS)

Devaraju, Anusuriya; Jayasinghe, Gaya; Klump, Jens; Hogan, Dominic

2017-04-01

Government agencies, universities, research and nonprofit organizations are increasingly publishing their datasets to promote transparency, induce new research and generate economic value through the development of new products or services. The datasets may be downloaded from various data portals (data repositories) which are general or domain-specific. The Registry of Research Data Repository (re3data.org) lists more than 2500 such data repositories from around the globe. Data portals allow keyword search and faceted navigation to facilitate discovery of research datasets. However, the volume and variety of datasets have made finding relevant datasets more difficult. Common dataset search mechanisms may be time consuming, may produce irrelevant results and are primarily suitable for users who are familiar with the general structure and contents of the respective database. Therefore, we need new approaches to support research data discovery. Recommender systems offer new possibilities for users to find datasets that are relevant to their research interests. This study presents a recommender system developed for the CSIRO Data Access Portal (DAP, http://data.csiro.au). The datasets hosted on the portal are diverse, published by researchers from 13 business units in the organisation. The goal of the study is not to replace the current search mechanisms on the data portal, but rather to extend the data discovery through an exploratory search, in this case by building a recommender system. We adopted a hybrid recommendation approach, comprising content-based filtering and item-item collaborative filtering. The content-based filtering computes similarities between datasets based on metadata such as title, keywords, descriptions, fields of research, location, contributors, etc. The collaborative filtering utilizes user search behaviour and download patterns derived from the server logs to determine similar datasets. Similarities above are then combined with different degrees of importance (weights) to determine the overall data similarity. We determined the similarity weights based on a survey involving 150 users of the portal. The recommender results for a given dataset are accessible programmatically via a RESTful web service. An offline evaluation involving data users demonstrates the ability of the recommender system to discover relevant and 'novel' datasets.

[Prevention of infections in adults and adolescents with systemic lupus erythematosus: Guidelines for the clinical practice based on the literature and expert opinion].

PubMed

Mathian, A; Arnaud, L; Adoue, D; Agard, C; Bader-Meunier, B; Baudouin, V; Belizna, C; Bonnotte, B; Boumedine, F; Chaib, A; Chauchard, M; Chiche, L; Daugas, E; Ghali, A; Gobert, P; Gondran, G; Guettrot-Imbert, G; Hachulla, E; Hamidou, M; Haroche, J; Hervier, B; Hummel, A; Jourde-Chiche, N; Korganow, A-S; Kwon, T; Le Guern, V; Le Quellec, A; Limal, N; Magy-Bertrand, N; Marianetti-Guingel, P; Martin, T; Martin Silva, N; Meyer, O; Miyara, M; Morell-Dubois, S; Ninet, J; Pennaforte, J-L; Polomat, K; Pourrat, J; Queyrel, V; Raymond, I; Remy, P; Sacre, K; Sibilia, J; Viallard, J-F; Viau Brabant, A; Hanslik, T; Amoura, Z

2016-05-01

To develop French recommendations about the management of vaccinations, the screening of cervical cancer and the prevention of pneumocystis pneumonia in systemic lupus erythematosus (SLE). Thirty-seven experts qualified in internal medicine, rheumatology, dermatology, nephrology and pediatrics have selected recommendations from a list of proposition based on available data from the literature. For each recommendation, the level of evidence and the level of agreement among the experts were specified. Inactivated vaccines do not cause significant harm in SLE patients. Experts recommend that lupus patient should receive vaccinations accordingly to the recommendations and the schedules for the general public. Pneumococcal vaccination is recommended for all SLE patients. Influenza vaccination is recommended for immunosuppressed SLE patients. Live attenuated vaccines should be avoided in immunosuppressed patients. Yet, recent works suggest that they can be considered in mildly immunosuppressed patients. Experts have recommended a cervical cytology every year for immunosuppressed patients. No consensus was obtained for the prevention of pneumocystis pneumonia. These recommendations can be expected to improve clinical practice uniformity and, in the longer term, to optimize the management of SLE patients. Copyright © 2016 Société nationale française de médecine interne (SNFMI). Published by Elsevier SAS. All rights reserved.

Recommendations for the classification of HIV associated neuromanifestations in the German DRG system.

PubMed

Evers, Stefan; Fiori, W; Brockmeyer, N; Arendt, G; Husstedt, I-W

2005-09-12

HIV associated neuromanifestations are of growing importance in the in-patient treatment of HIV infected patients. In Germany, all in-patients have to be coded according to the ICD-10 classification and the German DRG-system. We present recommendations how to code the different primary and secondary neuromanifestations of HIV infection. These recommendations are based on the commentary of the German DRG procedures and are aimed to establish uniform coding of neuromanifestations.

A Recommender System in the Cyber Defense Domain

DTIC Science & Technology

2014-03-27

monitoring software is a java based program sending updates to the database on the sensor machine. The host monitoring program gathers information about...3.2.2 Database. A MySQL database located on the sensor machine acts as the storage for the sensors on the network. Snort, Nmap, vulnerability scores, and...machine with the IDS and the recommender is labeled “sensor”. The recommender system code is written in java and compiled using java version 1.6.024

Automatic stress-relieving music recommendation system based on photoplethysmography-derived heart rate variability analysis.

PubMed

Shin, Il-Hyung; Cha, Jaepyeong; Cheon, Gyeong Woo; Lee, Choonghee; Lee, Seung Yup; Yoon, Hyung-Jin; Kim, Hee Chan

2014-01-01

This paper presents an automatic stress-relieving music recommendation system (ASMRS) for individual music listeners. The ASMRS uses a portable, wireless photoplethysmography module with a finger-type sensor, and a program that translates heartbeat signals from the sensor to the stress index. The sympathovagal balance index (SVI) was calculated from heart rate variability to assess the user's stress levels while listening to music. Twenty-two healthy volunteers participated in the experiment. The results have shown that the participants' SVI values are highly correlated with their prespecified music preferences. The sensitivity and specificity of the favorable music classification also improved as the number of music repetitions increased to 20 times. Based on the SVI values, the system automatically recommends favorable music lists to relieve stress for individuals.

Context-Awareness Based Personalized Recommendation of Anti-Hypertension Drugs.

PubMed

Chen, Dexin; Jin, Dawei; Goh, Tiong-Thye; Li, Na; Wei, Leiru

2016-09-01

The World Health Organization estimates that almost one-third of the world's adult population are suffering from hypertension which has gradually become a "silent killer". Due to the varieties of anti-hypertensive drugs, patients are interested in how these drugs can be selected to match their respective conditions. This study provides a personalized recommendation service system of anti-hypertensive drugs based on context-awareness and designs a context ontology framework of the service. In addition, this paper introduces a Semantic Web Rule Language (SWRL)-based rule to provide high-level context reasoning and information recommendation and to overcome the limitation of ontology reasoning. To make the information recommendation of the drugs more personalized, this study also devises three categories of information recommendation rules that match different priority levels and uses a ranking algorithm to optimize the recommendation. The experiment conducted shows that combining the anti-hypertensive drugs personalized recommendation service context ontology (HyRCO) with the optimized rule reasoning can achieve a higher-quality personalized drug recommendation service. Accordingly this exploratory study of the personalized recommendation service for hypertensive drugs and its method can be easily adopted for other diseases.

A scalable and practical one-pass clustering algorithm for recommender system

NASA Astrophysics Data System (ADS)

Khalid, Asra; Ghazanfar, Mustansar Ali; Azam, Awais; Alahmari, Saad Ali

2015-12-01

KMeans clustering-based recommendation algorithms have been proposed claiming to increase the scalability of recommender systems. One potential drawback of these algorithms is that they perform training offline and hence cannot accommodate the incremental updates with the arrival of new data, making them unsuitable for the dynamic environments. From this line of research, a new clustering algorithm called One-Pass is proposed, which is a simple, fast, and accurate. We show empirically that the proposed algorithm outperforms K-Means in terms of recommendation and training time while maintaining a good level of accuracy.

E-Learning Personalization Based on Hybrid Recommendation Strategy and Learning Style Identification

ERIC Educational Resources Information Center

Klasnja-Milicevic, Aleksandra; Vesin, Boban; Ivanovic, Mirjana; Budimac, Zoran

2011-01-01

Personalized learning occurs when e-learning systems make deliberate efforts to design educational experiences that fit the needs, goals, talents, and interests of their learners. Researchers had recently begun to investigate various techniques to help teachers improve e-learning systems. In this paper, we describe a recommendation module of a…

ICT Competence-Based Learning Object Recommendations for Teachers

ERIC Educational Resources Information Center

Sergis, Stylianos; Zervas, Panagiotis; Sampson, Demetrios G.

2014-01-01

Recommender Systems (RS) have been applied in the Technology enhanced Learning (TeL) field for facilitating, among others, Learning Object (LO) selection and retrieval. Most of the existing approaches, however, aim at accommodating the needs of learners and teacher-oriented RS are still an under-investigated field. Moreover, the systems that focus…

Hybrid recommendation methods in complex networks.

PubMed

Fiasconaro, A; Tumminello, M; Nicosia, V; Latora, V; Mantegna, R N

2015-07-01

We propose two recommendation methods, based on the appropriate normalization of already existing similarity measures, and on the convex combination of the recommendation scores derived from similarity between users and between objects. We validate the proposed measures on three data sets, and we compare the performance of our methods to other recommendation systems recently proposed in the literature. We show that the proposed similarity measures allow us to attain an improvement of performances of up to 20% with respect to existing nonparametric methods, and that the accuracy of a recommendation can vary widely from one specific bipartite network to another, which suggests that a careful choice of the most suitable method is highly relevant for an effective recommendation on a given system. Finally, we study how an increasing presence of random links in the network affects the recommendation scores, finding that one of the two recommendation algorithms introduced here can systematically outperform the others in noisy data sets.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments.

PubMed

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-10-15

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates.

An Efficient Recommendation Filter Model on Smart Home Big Data Analytics for Enhanced Living Environments

PubMed Central

Chen, Hao; Xie, Xiaoyun; Shu, Wanneng; Xiong, Naixue

2016-01-01

With the rapid growth of wireless sensor applications, the user interfaces and configurations of smart homes have become so complicated and inflexible that users usually have to spend a great amount of time studying them and adapting to their expected operation. In order to improve user experience, a weighted hybrid recommender system based on a Kalman Filter model is proposed to predict what users might want to do next, especially when users are located in a smart home with an enhanced living environment. Specifically, a weight hybridization method was introduced, which combines contextual collaborative filter and the contextual content-based recommendations. This method inherits the advantages of the optimum regression and the stability features of the proposed adaptive Kalman Filter model, and it can predict and revise the weight of each system component dynamically. Experimental results show that the hybrid recommender system can optimize the distribution of weights of each component, and achieve more reasonable recall and precision rates. PMID:27754456

Information filtering via preferential diffusion.

PubMed

Lü, Linyuan; Liu, Weiping

2011-06-01

Recommender systems have shown great potential in addressing the information overload problem, namely helping users in finding interesting and relevant objects within a huge information space. Some physical dynamics, including the heat conduction process and mass or energy diffusion on networks, have recently found applications in personalized recommendation. Most of the previous studies focus overwhelmingly on recommendation accuracy as the only important factor, while overlooking the significance of diversity and novelty that indeed provide the vitality of the system. In this paper, we propose a recommendation algorithm based on the preferential diffusion process on a user-object bipartite network. Numerical analyses on two benchmark data sets, MovieLens and Netflix, indicate that our method outperforms the state-of-the-art methods. Specifically, it can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.

Information filtering via preferential diffusion

NASA Astrophysics Data System (ADS)

Lü, Linyuan; Liu, Weiping

2011-06-01

Recommender systems have shown great potential in addressing the information overload problem, namely helping users in finding interesting and relevant objects within a huge information space. Some physical dynamics, including the heat conduction process and mass or energy diffusion on networks, have recently found applications in personalized recommendation. Most of the previous studies focus overwhelmingly on recommendation accuracy as the only important factor, while overlooking the significance of diversity and novelty that indeed provide the vitality of the system. In this paper, we propose a recommendation algorithm based on the preferential diffusion process on a user-object bipartite network. Numerical analyses on two benchmark data sets, MovieLens and Netflix, indicate that our method outperforms the state-of-the-art methods. Specifically, it can not only provide more accurate recommendations, but also generate more diverse and novel recommendations by accurately recommending unpopular objects.

Recommendation in Higher Education Using Data Mining Techniques

ERIC Educational Resources Information Center

Vialardi, Cesar; Bravo, Javier; Shafti, Leila; Ortigosa, Alvaro

2009-01-01

One of the main problems faced by university students is to take the right decision in relation to their academic itinerary based on available information (for example courses, schedules, sections, classrooms and professors). In this context, this work proposes the use of a recommendation system based on data mining techniques to help students to…

The Threshold and Inclusive Approaches to Determining "Best Available Evidence": An Empirical Analysis

ERIC Educational Resources Information Center

Stockard, Jean; Wood, Timothy W.

2017-01-01

Most evaluators have embraced the goal of evidence-based practice (EBP). Yet, many have criticized EBP review systems that prioritize randomized control trials and use various criteria to limit the studies examined. They suggest this could produce policy recommendations based on small, unrepresentative segments of the literature and recommend a…

Usability Guidelines for Product Recommenders Based on Example Critiquing Research

NASA Astrophysics Data System (ADS)

Pu, Pearl; Faltings, Boi; Chen, Li; Zhang, Jiyong; Viappiani, Paolo

Over the past decade, our group has developed a suite of decision tools based on example critiquing to help users find their preferred products in e-commerce environments. In this chapter, we survey important usability research work relative to example critiquing and summarize the major results by deriving a set of usability guidelines. Our survey is focused on three key interaction activities between the user and the system: the initial preference elicitation process, the preference revision process, and the presentation of the systems recommendation results. To provide a basis for the derivation of the guidelines, we developed a multi-objective framework of three interacting criteria: accuracy, confidence, and effort (ACE). We use this framework to analyze our past work and provide a specific context for each guideline: when the system should maximize its ability to increase users' decision accuracy, when to increase user confidence, and when to minimize the interaction effort for the users. Due to the general nature of this multi-criteria model, the set of guidelines that we propose can be used to ease the usability engineering process of other recommender systems, especially those used in e-commerce environments. The ACE framework presented here is also the first in the field to evaluate the performance of preference-based recommenders from a user-centric point of view.

Exploring Learner Attitudes toward Web-Based Recommendation Learning Service System for Interdisciplinary Applications

ERIC Educational Resources Information Center

Chen, Hong-Ren; Huang, Jhen-Gang

2012-01-01

The booming digital-content industry has resulted in an increasing number of e-learning Internet websites that provide online learning services. Recommendations for learning sites are used by diverse learners to identify the most appropriate learning resources. However, research into recommendations about learning has concentrated primarily on…

Guidelines for diagnosis, prevention and treatment of hand eczema--short version.

PubMed

Diepgen, Thomas L; Andersen, Klaus E; Chosidow, Oliver; Coenraads, Peter Jan; Elsner, Peter; English, John; Fartasch, Manigé; Gimenez-Arnau, Ana; Nixon, Rosemary; Sasseville, Denis; Agner, Tove

2015-01-01

The guidelines aim to provide advice on the management of hand eczema (HE), using an evidence- and consensus-based approach. The guidelines consider a systematic Cochrane review on interventions for HE, which is based on a systematic search of the published literature (including hand-searching). In addition to the evidence- and consensus-based recommendation on the treatment of HE, the guidelines cover mainly consensus-based diagnostic aspects and preventive measures (primary and secondary prevention). Treatment recommendations include non-pharmacological interventions, topical, physical and systemic treatments. Topical corticosteroids are recommended as first line treatment in the management of HE, however continuous long-term treatment beyond six weeks only when necessary and under careful medical supervision. Alitretinoin is recommended as a second line treatment (relative to topical corticosteroids) for patients with severe chronic HE. Randomized control trials (RCT) are missing for other used systemic treatments and comparison of systemic drugs in "head-to-head" RCTs are needed. The guidelines development group is a working group of the European Society of Contact Dermatitis (ESCD) and has carefully tried to reconcile opposite views, define current optimal practice and provide specific recommendations, and meetings have been chaired by a professional moderator of the AWMF (Arbeitsgemeinschaft der Wissenschaftlichen Medizinischen Fachgesellschaften; Association of the Scientific Medical Societies in Germany). No financial support was given by any medical company. The guidelines are expected to be valid until December 2017 at the latest. © 2014 Deutsche Dermatologische Gesellschaft (DDG). Published by John Wiley & Sons Ltd.

A Geospatial Data Recommender System based on Metadata and User Behaviour

NASA Astrophysics Data System (ADS)

Li, Y.; Jiang, Y.; Yang, C. P.; Armstrong, E. M.; Huang, T.; Moroni, D. F.; Finch, C. J.; McGibbney, L. J.

2017-12-01

Earth observations are produced in a fast velocity through real time sensors, reaching tera- to peta- bytes of geospatial data daily. Discovering and accessing the right data from the massive geospatial data is like finding needle in the haystack. To help researchers find the right data for study and decision support, quite a lot of research focusing on improving search performance have been proposed including recommendation algorithm. However, few papers have discussed the way to implement a recommendation algorithm in geospatial data retrieval system. In order to address this problem, we propose a recommendation engine to improve discovering relevant geospatial data by mining and utilizing metadata and user behavior data: 1) metadata based recommendation considers the correlation of each attribute (i.e., spatiotemporal, categorical, and ordinal) to data to be found. In particular, phrase extraction method is used to improve the accuracy of the description similarity; 2) user behavior data are utilized to predict the interest of a user through collaborative filtering; 3) an integration method is designed to combine the results of the above two methods to achieve better recommendation Experiments show that in the hybrid recommendation list, the all the precisions are larger than 0.8 from position 1 to 10.

Association Rule Analysis for Tour Route Recommendation and Application to Wctsnop

NASA Astrophysics Data System (ADS)

Fang, H.; Chen, C.; Lin, J.; Liu, X.; Fang, D.

2017-09-01

The increasing E-tourism systems provide intelligent tour recommendation for tourists. In this sense, recommender system can make personalized suggestions and provide satisfied information associated with their tour cycle. Data mining is a proper tool that extracting potential information from large database for making strategic decisions. In the study, association rule analysis based on FP-growth algorithm is applied to find the association relationship among scenic spots in different cities as tour route recommendation. In order to figure out valuable rules, Kulczynski interestingness measure is adopted and imbalance ratio is computed. The proposed scheme was evaluated on Wangluzhe cultural tourism service network operation platform (WCTSNOP), where it could verify that it is able to quick recommend tour route and to rapidly enhance the recommendation quality.

IAP/APA evidence-based guidelines for the management of acute pancreatitis.

PubMed

2013-01-01

There have been substantial improvements in the management of acute pancreatitis since the publication of the International Association of Pancreatology (IAP) treatment guidelines in 2002. A collaboration of the IAP and the American Pancreatic Association (APA) was undertaken to revise these guidelines using an evidence-based approach. Twelve multidisciplinary review groups performed systematic literature reviews to answer 38 predefined clinical questions. Recommendations were graded using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system. The review groups presented their recommendations during the 2012 joint IAP/APA meeting. At this one-day, interactive conference, relevant remarks were voiced and overall agreement on each recommendation was quantified using plenary voting. The 38 recommendations covered 12 topics related to the clinical management of acute pancreatitis: A) diagnosis of acute pancreatitis and etiology, B) prognostication/predicting severity, C) imaging, D) fluid therapy, E) intensive care management, F) preventing infectious complications, G) nutritional support, H) biliary tract management, I) indications for intervention in necrotizing pancreatitis, J) timing of intervention in necrotizing pancreatitis, K) intervention strategies in necrotizing pancreatitis, and L) timing of cholecystectomy. Using the GRADE system, 21 of the 38 (55%) recommendations, were rated as 'strong' and plenary voting revealed 'strong agreement' for 34 (89%) recommendations. The 2012 IAP/APA guidelines provide recommendations concerning key aspects of medical and surgical management of acute pancreatitis based on the currently available evidence. These recommendations should serve as a reference standard for current management and guide future clinical research on acute pancreatitis. Copyright © 2013 IAP and EPC. Published by Elsevier B.V. All rights reserved.

Which patients with myelofibrosis should receive ruxolitinib therapy? ELN-SIE evidence-based recommendations.

PubMed

Marchetti, M; Barosi, G; Cervantes, F; Birgegård, G; Griesshammer, M; Harrison, C; Hehlmann, R; Kiladjian, J-J; Kröger, N; McMullin, M F; Passamonti, F; Vannucchi, A; Barbui, T

2017-04-01

Ruxolitinib is an oral Janus-activated kinase 1 (JAK1)/JAK2 inhibitor approved for the treatment of patients with myelofibrosis based on the results of two randomized clinical trials. However, discordant indications were provided by regulatory agencies and scientific societies for selecting the most appropriate candidates to this drug. The European LeukemiaNet and the Italian Society of Hematology shared the aim of building evidence-based recommendations for the use of ruxolitinib according to the GRADE methodology. Eighteen patient-intervention-comparator-outcome profiles were listed, each of them comparing ruxolitinib to other therapies with the aim of improving one of the three clinical outcomes: (a) splenomegaly, (b) disease-related symptoms, and (c) survival. Ruxolitinib was strongly recommended for improving symptomatic or severe (>15 cm below the costal margin) splenomegaly in patients with an International Prognostic Scoring System (IPSS)/dynamic IPSS risk intermediate 2 or high. Ruxolitinib was also strongly recommended for improving systemic symptoms in patients with an MPN10 score >44, refractory severe itching, unintended weight loss not attributable to other causes or unexplained fever. Because of weak evidence, the panel does not recommend ruxolitinib therapy for improving survival. Also, the recommendations given above do not necessarily apply to patients who are candidates for allogeneic stem cell transplant.

Social network supported process recommender system.

PubMed

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced.

Learning material recommendation based on case-based reasoning similarity scores

NASA Astrophysics Data System (ADS)

Masood, Mona; Mokmin, Nur Azlina Mohamed

2017-10-01

A personalized learning material recommendation is important in any Intelligent Tutoring System (ITS). Case-based Reasoning (CBR) is an Artificial Intelligent Algorithm that has been widely used in the development of ITS applications. This study has developed an ITS application that applied the CBR algorithm in the development process. The application has the ability to recommend the most suitable learning material to the specific student based on information in the student profile. In order to test the ability of the application in recommending learning material, two versions of the application were created. The first version displayed the most suitable learning material and the second version displayed the least preferable learning material. The results show the application has successfully assigned the students to the most suitable learning material.

Compendium of Unimplemented Recommendations: Apr 1, 2013 - Sept 30, 2013

EPA Pesticide Factsheets

Compendium #14-N-0016, Nov 15, 2013. The OIG identified the unimplemented recommendations listed in this Compendium based on their significance, material impact, and status in the EPA’s Management Audit Tracking System.

A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization

PubMed Central

Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

2016-01-01

With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies’ ratings. The proposed PRS not only considers the movie’s content information but also integrates the users’ demographic and behavioral information to better capture the users’ interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set. PMID:27898691

A Personalized Electronic Movie Recommendation System Based on Support Vector Machine and Improved Particle Swarm Optimization.

PubMed

Wang, Xibin; Luo, Fengji; Qian, Ying; Ranzi, Gianluca

2016-01-01

With the rapid development of ICT and Web technologies, a large an amount of information is becoming available and this is producing, in some instances, a condition of information overload. Under these conditions, it is difficult for a person to locate and access useful information for making decisions. To address this problem, there are information filtering systems, such as the personalized recommendation system (PRS) considered in this paper, that assist a person in identifying possible products or services of interest based on his/her preferences. Among available approaches, collaborative Filtering (CF) is one of the most widely used recommendation techniques. However, CF has some limitations, e.g., the relatively simple similarity calculation, cold start problem, etc. In this context, this paper presents a new regression model based on the support vector machine (SVM) classification and an improved PSO (IPSO) for the development of an electronic movie PRS. In its implementation, a SVM classification model is first established to obtain a preliminary movie recommendation list based on which a SVM regression model is applied to predict movies' ratings. The proposed PRS not only considers the movie's content information but also integrates the users' demographic and behavioral information to better capture the users' interests and preferences. The efficiency of the proposed method is verified by a series of experiments based on the MovieLens benchmark data set.

User-Adapted Recommendation of Content on Mobile Devices Using Bayesian Networks

NASA Astrophysics Data System (ADS)

Iwasaki, Hirotoshi; Mizuno, Nobuhiro; Hara, Kousuke; Motomura, Yoichi

Mobile devices, such as cellular phones and car navigation systems, are essential to daily life. People acquire necessary information and preferred content over communication networks anywhere, anytime. However, usability issues arise from the simplicity of user interfaces themselves. Thus, a recommendation of content that is adapted to a user's preference and situation will help the user select content. In this paper, we describe a method to realize such a system using Bayesian networks. This user-adapted mobile system is based on a user model that provides recommendation of content (i.e., restaurants, shops, and music that are suitable to the user and situation) and that learns incrementally based on accumulated usage history data. However, sufficient samples are not always guaranteed, since a user model would require combined dependency among users, situations, and contents. Therefore, we propose the LK method for modeling, which complements incomplete and insufficient samples using knowledge data, and CPT incremental learning for adaptation based on a small number of samples. In order to evaluate the methods proposed, we applied them to restaurant recommendations made on car navigation systems. The evaluation results confirmed that our model based on the LK method can be expected to provide better generalization performance than that of the conventional method. Furthermore, our system would require much less operation than current car navigation systems from the beginning of use. Our evaluation results also indicate that learning a user's individual preference through CPT incremental learning would be beneficial to many users, even with only a few samples. As a result, we have developed the technology of a system that becomes more adapted to a user the more it is used.

Identifying problems and generating recommendations for enhancing complex systems: applying the abstraction hierarchy framework as an analytical tool.

PubMed

Xu, Wei

2007-12-01

This study adopts J. Rasmussen's (1985) abstraction hierarchy (AH) framework as an analytical tool to identify problems and pinpoint opportunities to enhance complex systems. The process of identifying problems and generating recommendations for complex systems using conventional methods is usually conducted based on incompletely defined work requirements. As the complexity of systems rises, the sheer mass of data generated from these methods becomes unwieldy to manage in a coherent, systematic form for analysis. There is little known work on adopting a broader perspective to fill these gaps. AH was used to analyze an aircraft-automation system in order to further identify breakdowns in pilot-automation interactions. Four steps follow: developing an AH model for the system, mapping the data generated by various methods onto the AH, identifying problems based on the mapped data, and presenting recommendations. The breakdowns lay primarily with automation operations that were more goal directed. Identified root causes include incomplete knowledge content and ineffective knowledge structure in pilots' mental models, lack of effective higher-order functional domain information displayed in the interface, and lack of sufficient automation procedures for pilots to effectively cope with unfamiliar situations. The AH is a valuable analytical tool to systematically identify problems and suggest opportunities for enhancing complex systems. It helps further examine the automation awareness problems and identify improvement areas from a work domain perspective. Applications include the identification of problems and generation of recommendations for complex systems as well as specific recommendations regarding pilot training, flight deck interfaces, and automation procedures.

Is traditional Chinese medicine recommended in Western medicine clinical practice guidelines in China? A systematic analysis

PubMed Central

Ren, Jun; Li, Xun; Sun, Jin; Han, Mei; Yang, Guo-Yan; Li, Wen-Yuan; Robinson, Nicola; Lewith, George; Liu, Jian-Ping

2015-01-01

Background Evidence-based medicine promotes and relies on the use of evidence in developing clinical practice guidelines (CPGs). The Chinese healthcare system includes both traditional Chinese medicine (TCM) and Western medicine, which are expected to be equally reflected in Chinese CPGs. Objective To evaluate the inclusion of TCM-related information in Western medicine CPGs developed in China and the adoption of high level evidence. Methods All CPGs were identified from the China Guideline Clearinghouse (CGC), which is the main Chinese organisation maintaining the guidelines issued by the Ministry of Health of China, the Chinese Medical Association and the Chinese Medical Doctors’ Association. TCM-related contents were extracted from all the CPGs identified. Extracted information comprised the institution issuing the guideline, date of issue, disease, recommendations relating to TCM, evidence level of the recommended content and references supporting the recommendations. Results A total of 604 CPGs were identified, only a small number of which (74/604; 12%) recommended TCM therapy and only five guidelines (7%) had applied evidence grading. The 74 CPGs involved 13 disease systems according to the International Classification of Diseases 10th edition. TCM was mainly recommended in the treatment part of the guidelines (73/74, 99%), and more than half of the recommendations (43/74, 58%) were related to Chinese herbal medicine (single herbs or herbal treatment based on syndrome differentiation). Conclusions Few Chinese Western medicine CPGs recommend TCM therapies and very few provide evidence grading for the TCM recommendation. We suggest that future guideline development should be based on systematic searches for evidence to support CPG recommendations and involve a multidisciplinary approach including TCM expertise. PMID:26041487

Is traditional Chinese medicine recommended in Western medicine clinical practice guidelines in China? A systematic analysis.

PubMed

Ren, Jun; Li, Xun; Sun, Jin; Han, Mei; Yang, Guo-Yan; Li, Wen-Yuan; Robinson, Nicola; Lewith, George; Liu, Jian-Ping

2015-06-03

Evidence-based medicine promotes and relies on the use of evidence in developing clinical practice guidelines (CPGs). The Chinese healthcare system includes both traditional Chinese medicine (TCM) and Western medicine, which are expected to be equally reflected in Chinese CPGs. To evaluate the inclusion of TCM-related information in Western medicine CPGs developed in China and the adoption of high level evidence. All CPGs were identified from the China Guideline Clearinghouse (CGC), which is the main Chinese organisation maintaining the guidelines issued by the Ministry of Health of China, the Chinese Medical Association and the Chinese Medical Doctors' Association.TCM-related contents were extracted from all the CPGs identified. Extracted information comprised the institution issuing the guideline, date of issue, disease, recommendations relating to TCM, evidence level of the recommended content and references supporting the recommendations. A total of 604 CPGs were identified, only a small number of which (74/604; 12%) recommended TCM therapy and only five guidelines (7%) had applied evidence grading. The 74 CPGs involved 13 disease systems according to the International Classification of Diseases 10th edition. TCM was mainly recommended in the treatment part of the guidelines (73/74, 99%), and more than half of the recommendations (43/74, 58%) were related to Chinese herbal medicine (single herbs or herbal treatment based on syndrome differentiation). Few Chinese Western medicine CPGs recommend TCM therapies and very few provide evidence grading for the TCM recommendation. We suggest that future guideline development should be based on systematic searches for evidence to support CPG recommendations and involve a multidisciplinary approach including TCM expertise. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.

PERSON-Personalized Expert Recommendation System for Optimized Nutrition.

PubMed

Chen, Chih-Han; Karvela, Maria; Sohbati, Mohammadreza; Shinawatra, Thaksin; Toumazou, Christofer

2018-02-01

The rise of personalized diets is due to the emergence of nutrigenetics and genetic tests services. However, the recommendation system is far from mature to provide personalized food suggestion to consumers for daily usage. The main barrier of connecting genetic information to personalized diets is the complexity of data and the scalability of the applied systems. Aiming to cross such barriers and provide direct applications, a personalized expert recommendation system for optimized nutrition is introduced in this paper, which performs direct to consumer personalized grocery product filtering and recommendation. Deep learning neural network model is applied to achieve automatic product categorization. The ability of scaling with unknown new data is achieved through the generalized representation of word embedding. Furthermore, the categorized products are filtered with a model based on individual genetic data with associated phenotypic information and a case study with databases from three different sources is carried out to confirm the system.

Using a Recommendation System to Support Problem Solving and Case-Based Reasoning Retrieval

ERIC Educational Resources Information Center

Tawfik, Andrew A.; Alhoori, Hamed; Keene, Charles Wayne; Bailey, Christian; Hogan, Maureen

2018-01-01

In case library learning environments, learners are presented with an array of narratives that can be used to guide their problem solving. However, according to theorists, learners struggle to identify and retrieve the optimal case to solve a new problem. Given the challenges novice face during case retrieval, recommender systems can be embedded…

Effective Trust-Aware E-learning Recommender System Based on Learning Styles and Knowledge Levels

ERIC Educational Resources Information Center

Dwivedi, Pragya; Bharadwaj, Kamal K.

2013-01-01

In the age of information explosion, e-learning recommender systems (ELRSs) have emerged as the most essential tool to deliver personalized learning resources to learners. Due to enormous amount of information on the web, learner faces problem in searching right information. ELRSs deal with the problem of information overload effectively and…

Hierarchy of evidence: a simple system for orthopaedic research?

PubMed

Pemberton, Julia; Kraeva, Juliana; Bhandari, Mohit

2007-01-01

To be able to make a sound recommendation for a treatment based on the best available evidence, it is necessary to follow specific steps in acquiring literature, appraising the study design and quality, and assessing the results. Evidence-based medicine is founded on the concepts of using best evidence, levels of evidence, and grades of recommendation, and aims to provide clinicians with standardized rules to help them appraise the validity of published research. A number of systems have been developed to categorize research studies into consistent levels of evidence. These systems are based primarily on consensus expert opinion, and have not been validated to any extent. The use of different systems does not allow for effective communication between users; there is a lack of accord even between users of the same system. The GRADE working group has devised a new rating system that attempts to address deficiencies seen within other systems.

The Use of a UNIX-Based Workstation in the Information Systems Laboratory

DTIC Science & Technology

1989-03-01

system. The conclusions of the research and the resulting recommendations are presented in Chapter III. These recommendations include how to manage...required to run the program on a new system, these should not be significant changes. 2. Processing Environment The UNIX processing environment is...interactive with multi-tasking and multi-user capabilities. Multi-tasking refers to the fact that many programs can be run concurrently. This capability

Action Recommendation for Cyber Resilience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Choudhury, Sutanay; Rodriguez, Luke R.; Curtis, Darren S.

2015-09-01

This paper presents an unifying graph-based model for representing the infrastructure, behavior and missions of an enterprise. We describe how the model can be used to achieve resiliency against a wide class of failures and attacks. We introduce an algorithm for recommending resilience establishing actions based on dynamic updates to the models. Without loss of generality, we show the effectiveness of the algorithm for preserving latency based quality of service (QoS). Our models and the recommendation algorithms are implemented in a software framework that we seek to release as an open source framework for simulating resilient cyber systems.

Construction of a Clinical Decision Support System for Undergoing Surgery Based on Domain Ontology and Rules Reasoning

PubMed Central

Bau, Cho-Tsan; Huang, Chung-Yi

2014-01-01

Abstract Objective: To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. Materials and Methods: The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé–Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. Results: The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. Conclusions: The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia. PMID:24730353

Construction of a clinical decision support system for undergoing surgery based on domain ontology and rules reasoning.

PubMed

Bau, Cho-Tsan; Chen, Rung-Ching; Huang, Chung-Yi

2014-05-01

To construct a clinical decision support system (CDSS) for undergoing surgery based on domain ontology and rules reasoning in the setting of hospitalized diabetic patients. The ontology was created with a modified ontology development method, including specification and conceptualization, formalization, implementation, and evaluation and maintenance. The Protégé-Web Ontology Language editor was used to implement the ontology. Embedded clinical knowledge was elicited to complement the domain ontology with formal concept analysis. The decision rules were translated into JENA format, which JENA can use to infer recommendations based on patient clinical situations. The ontology includes 31 classes and 13 properties, plus 38 JENA rules that were built to generate recommendations. The evaluation studies confirmed the correctness of the ontology, acceptance of recommendations, satisfaction with the system, and usefulness of the ontology for glycemic management of diabetic patients undergoing surgery, especially for domain experts. The contribution of this research is to set up an evidence-based hybrid ontology and an evaluation method for CDSS. The system can help clinicians to achieve inpatient glycemic control in diabetic patients undergoing surgery while avoiding hypoglycemia.

A framework for diversifying recommendation lists by user interest expansion.

PubMed

Zhang, Zhu; Zheng, Xiaolong; Zeng, Daniel Dajun

2016-08-01

Recommender systems have been widely used to discover users' preferences and recommend interesting items to users during this age of information load. Researchers in the field of recommender systems have realized that the quality of a top-N recommendation list involves not only relevance but also diversity. Most traditional recommendation algorithms are difficult to generate a diverse item list that can cover most of his/her interests for each user, since they mainly focus on predicting accurate items similar to the dominant interests of users. Additionally, they seldom exploit semantic information such as item tags and users' interest labels to improve recommendation diversity. In this paper, we propose a novel recommendation framework which mainly adopts an expansion strategy of user interests based on social tagging information. The framework enhances the diversity of users' preferences by expanding the sizes and categories of the original user-item interaction records, and then adopts traditional recommendation models to generate recommendation lists. Empirical evaluations on three real-world data sets show that our method can effectively improve the accuracy and diversity of item recommendation.

A framework for diversifying recommendation lists by user interest expansion

PubMed Central

Zhang, Zhu; Zeng, Daniel Dajun

2017-01-01

Recommender systems have been widely used to discover users’ preferences and recommend interesting items to users during this age of information load. Researchers in the field of recommender systems have realized that the quality of a top-N recommendation list involves not only relevance but also diversity. Most traditional recommendation algorithms are difficult to generate a diverse item list that can cover most of his/her interests for each user, since they mainly focus on predicting accurate items similar to the dominant interests of users. Additionally, they seldom exploit semantic information such as item tags and users’ interest labels to improve recommendation diversity. In this paper, we propose a novel recommendation framework which mainly adopts an expansion strategy of user interests based on social tagging information. The framework enhances the diversity of users’ preferences by expanding the sizes and categories of the original user-item interaction records, and then adopts traditional recommendation models to generate recommendation lists. Empirical evaluations on three real-world data sets show that our method can effectively improve the accuracy and diversity of item recommendation. PMID:28959089

The Endocrine Society guidelines: when the confidence cart goes before the evidence horse.

PubMed

Brito, Juan P; Domecq, Juan P; Murad, Mohammed H; Guyatt, Gordon H; Montori, Victor M

2013-08-01

In 2005, the Endocrine Society (TES) adopted the GRADE system of developing clinical practice guidelines. Grading of Recommendations, Assessment, Development, and Evaluation working group guidance suggests that strong recommendations based on low or very low (L/VL) confidence may often be inappropriate, and has offered a taxonomy of paradigmatic situations in which strong recommendations based on L/VL confidence estimates may be appropriate. We sought to characterize strong recommendations of TES based on L/VL confidence evidence. We identified all strong recommendations based on L/VL confidence evidence published in TES guidelines between 2005 and 2011. We identified those consistent with one of the paradigmatic situations in the taxonomy. Two hundred six of 357 (58%) of the recommendations of TES were strong; of these, 121 (59%) were based on L/VL confidence evidence. Of these 121, 35 (29%) were consistent with one of the paradigmatic situations. The most common situation (13, 11%) was of a strong recommendation against the intervention because of low confidence evidence for benefit and high confidence evidence for harm. The remaining 86 (71%) comprised 43 (36%) "best practice" statements for which sensible alternatives do not exist; 5 (4%) in which recommendations were for "additional research"; 5 (4%) in which greater confidence in the estimates was warranted; and 33 (27%) for which we could not find a compelling explanation for the incongruence. Guideline panels should beware of formulating strong recommendations when confidence in estimates is low. Our taxonomy when such recommendations are appropriate may be helpful.

Protection of Location Privacy Based on Distributed Collaborative Recommendations

PubMed Central

Wang, Peng; Yang, Jing; Zhang, Jian-Pei

2016-01-01

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users’ location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users’ location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users’ location information profiles and used generalization and encryption to ensure the safety of the user’s location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user’s location privacy. PMID:27649308

Protection of Location Privacy Based on Distributed Collaborative Recommendations.

PubMed

Wang, Peng; Yang, Jing; Zhang, Jian-Pei

2016-01-01

In the existing centralized location services system structure, the server is easily attracted and be the communication bottleneck. It caused the disclosure of users' location. For this, we presented a new distributed collaborative recommendation strategy that is based on the distributed system. In this strategy, each node establishes profiles of their own location information. When requests for location services appear, the user can obtain the corresponding location services according to the recommendation of the neighboring users' location information profiles. If no suitable recommended location service results are obtained, then the user can send a service request to the server according to the construction of a k-anonymous data set with a centroid position of the neighbors. In this strategy, we designed a new model of distributed collaborative recommendation location service based on the users' location information profiles and used generalization and encryption to ensure the safety of the user's location information privacy. Finally, we used the real location data set to make theoretical and experimental analysis. And the results show that the strategy proposed in this paper is capable of reducing the frequency of access to the location server, providing better location services and protecting better the user's location privacy.

IA-Regional-Radio - Social Network for Radio Recommendation

NASA Astrophysics Data System (ADS)

Dziczkowski, Grzegorz; Bougueroua, Lamine; Wegrzyn-Wolska, Katarzyna

This chapter describes the functions of a system proposed for the music hit recommendation from social network data base. This system carries out the automatic collection, evaluation and rating of music reviewers and the possibility for listeners to rate musical hits and recommendations deduced from auditor's profiles in the form of regional Internet radio. First, the system searches and retrieves probable music reviews from the Internet. Subsequently, the system carries out an evaluation and rating of those reviews. From this list of music hits, the system directly allows notation from our application. Finally, the system automatically creates the record list diffused each day depending on the region, the year season, the day hours and the age of listeners. Our system uses linguistics and statistic methods for classifying music opinions and data mining techniques for recommendation part needed for recorded list creation. The principal task is the creation of popular intelligent radio adaptive on auditor's age and region - IA-Regional-Radio.

Compendium of Unimplemented Recommendations: Oct 1, 2012 - Mar 31, 2013

EPA Pesticide Factsheets

Compendium #13-N-0227, Apr 30, 2013. The OIG identified the unimplemented recommendations based on their significance, material impact, and status in the EPA’s Management Audit Tracking System, as well as through OIG review.

Compendium of Unimplemented Recommendations: Apr 1, 2014 - Sept 30, 2014

EPA Pesticide Factsheets

Compendium #15-N-0008, Oct 31, 2014. The OIG identified the unimplemented recommendations based on their significance, material impact, and status in the EPA’s Management Audit Tracking System, as well as through OIG review.

Recommender engine for continuous-time quantum Monte Carlo methods

NASA Astrophysics Data System (ADS)

Huang, Li; Yang, Yi-feng; Wang, Lei

2017-03-01

Recommender systems play an essential role in the modern business world. They recommend favorable items such as books, movies, and search queries to users based on their past preferences. Applying similar ideas and techniques to Monte Carlo simulations of physical systems boosts their efficiency without sacrificing accuracy. Exploiting the quantum to classical mapping inherent in the continuous-time quantum Monte Carlo methods, we construct a classical molecular gas model to reproduce the quantum distributions. We then utilize powerful molecular simulation techniques to propose efficient quantum Monte Carlo updates. The recommender engine approach provides a general way to speed up the quantum impurity solvers.

Recommendations for UAS Crew Ratings. Pilot Ratings and Authorization Requirements for UAS

NASA Technical Reports Server (NTRS)

2005-01-01

This position paper is intended to recommend the minimum certificate and rating requirements for a pilot to operate an Unmanned Aircraft System (UAS) in the National Airspace System. The paper will recommend the minimum requirements based on the Knowledge, Skills, and Abilities (KSA) required of a UAS pilot and show how those compare to the KSAs required by regulation for manned-aircraft pilots. The paper will provide substantiation based on studies conducted using analyses, simulation and flight experience. The paper is not yet complete; only initial working material is included. The material provided describes the body of work completed thus far and the plan for remaining tasks to complete the recommendation. The HSI Pilot KSA document provides an analysis of the knowledge, skills, and abilities required for UAS operation in the NAS. It is the source document used for the position paper.

A vertex similarity index for better personalized recommendation

NASA Astrophysics Data System (ADS)

Chen, Ling-Jiao; Zhang, Zi-Ke; Liu, Jin-Hu; Gao, Jian; Zhou, Tao

2017-01-01

Recommender systems benefit us in tackling the problem of information overload by predicting our potential choices among diverse niche objects. So far, a variety of personalized recommendation algorithms have been proposed and most of them are based on similarities, such as collaborative filtering and mass diffusion. Here, we propose a novel vertex similarity index named CosRA, which combines advantages of both the cosine index and the resource-allocation (RA) index. By applying the CosRA index to real recommender systems including MovieLens, Netflix and RYM, we show that the CosRA-based method has better performance in accuracy, diversity and novelty than some benchmark methods. Moreover, the CosRA index is free of parameters, which is a significant advantage in real applications. Further experiments show that the introduction of two turnable parameters cannot remarkably improve the overall performance of the CosRA index.

Evaluating Recommendation Systems

NASA Astrophysics Data System (ADS)

Shani, Guy; Gunawardana, Asela

Recommender systems are now popular both commercially and in the research community, where many approaches have been suggested for providing recommendations. In many cases a system designer that wishes to employ a recommendation system must choose between a set of candidate approaches. A first step towards selecting an appropriate algorithm is to decide which properties of the application to focus upon when making this choice. Indeed, recommendation systems have a variety of properties that may affect user experience, such as accuracy, robustness, scalability, and so forth. In this paper we discuss how to compare recommenders based on a set of properties that are relevant for the application. We focus on comparative studies, where a few algorithms are compared using some evaluation metric, rather than absolute benchmarking of algorithms. We describe experimental settings appropriate for making choices between algorithms. We review three types of experiments, starting with an offline setting, where recommendation approaches are compared without user interaction, then reviewing user studies, where a small group of subjects experiment with the system and report on the experience, and finally describe large scale online experiments, where real user populations interact with the system. In each of these cases we describe types of questions that can be answered, and suggest protocols for experimentation. We also discuss how to draw trustworthy conclusions from the conducted experiments. We then review a large set of properties, and explain how to evaluate systems given relevant properties. We also survey a large set of evaluation metrics in the context of the properties that they evaluate.

Treatment of severe psoriasis in children: recommendations of an Italian expert group.

PubMed

Fortina, Anna Belloni; Bardazzi, Federico; Berti, Samantha; Carnevale, Claudia; Di Lernia, Vito; El Hachem, Maya; Neri, Iria; Gelmetti, Carlo Mario; Lora, Viviana; Mazzatenta, Carlo; Milioto, Mirella; Moretta, Gaia; Patrizi, Annalisa; Peris, Ketty; Villani, Alberto

2017-10-01

This article provides comprehensive recommendations for the systemic treatment of severe pediatric psoriasis based on evidence obtained from a systematic review of the literature and the consensus opinion of expert dermatologists and pediatricians. For each systemic treatment, the grade of recommendation (A, B, C) based on the treatment's approval by the European Medicines Agency for childhood psoriasis and the experts' opinions is discussed. The grade of recommendation for narrow-band-ultraviolet B phototherapy, cyclosporine, and retinoids is C, while that for methotrexate is C/B. The use of adalimumab, etanercept, and ustekinumab has a grade A recommendation. No conventional systemic treatments are approved for pediatric psoriasis. Adalimumab is approved by the European Medicines Agency as a first-line treatment for severe chronic plaque psoriasis in children (≥ 4 years old) and adolescents. Etanercept and ustekinumab are approved as second-line therapy in children ≥ 6 and ≥ 12 years, respectively. A treatment algorithm as well as practical tools (i.e., tabular summaries of differential diagnoses, treatment mechanism of actions, dosing regimens, control parameters) are provided to assist in therapeutic reasoning and decision-making for individual patients. These treatment recommendations are endorsed by major Italian Pediatric and Dermatology Societies. What is Known: • Guidelines for the treatment of severe pediatric psoriasis are lacking and most traditional systemic treatments are not approved for use in young patients. Although there has been decades of experience with some of the traditional agents such as phototherapy, acitretin, and cyclosporine in children, there are no RCTs on their pediatric use while RCTs investigating new biologic agents have been performed. What is New: • In this manuscript, an Italian multidisciplinary team of experts focused on treatment recommendations for severe forms of psoriasis in children based on an up-to-date review of the literature and experts' opinions.

Systems biology of personalized nutrition

PubMed Central

van Ommen, Ben; van den Broek, Tim; de Hoogh, Iris; van Erk, Marjan; van Someren, Eugene; Rouhani-Rankouhi, Tanja; Anthony, Joshua C; Hogenelst, Koen; Pasman, Wilrike; Boorsma, André; Wopereis, Suzan

2017-01-01

Abstract Personalized nutrition is fast becoming a reality due to a number of technological, scientific, and societal developments that complement and extend current public health nutrition recommendations. Personalized nutrition tailors dietary recommendations to specific biological requirements on the basis of a person’s health status and goals. The biology underpinning these recommendations is complex, and thus any recommendations must account for multiple biological processes and subprocesses occurring in various tissues and must be formed with an appreciation for how these processes interact with dietary nutrients and environmental factors. Therefore, a systems biology–based approach that considers the most relevant interacting biological mechanisms is necessary to formulate the best recommendations to help people meet their wellness goals. Here, the concept of “systems flexibility” is introduced to personalized nutrition biology. Systems flexibility allows the real-time evaluation of metabolism and other processes that maintain homeostasis following an environmental challenge, thereby enabling the formulation of personalized recommendations. Examples in the area of macro- and micronutrients are reviewed. Genetic variations and performance goals are integrated into this systems approach to provide a strategy for a balanced evaluation and an introduction to personalized nutrition. Finally, modeling approaches that combine personalized diagnosis and nutritional intervention into practice are reviewed. PMID:28969366

Acceptance and barriers pertaining to a general practice decision support system for multiple clinical conditions: A mixed methods evaluation.

PubMed

Arts, Derk L; Medlock, Stephanie K; van Weert, Henk C P M; Wyatt, Jeremy C; Abu-Hanna, Ameen

2018-01-01

Many studies have investigated the use of clinical decision support systems as a means to improve care, but have thus far failed to show significant effects on patient-related outcomes. We developed a clinical decision support system that attempted to address issues that were identified in these studies. The system was implemented in Dutch general practice and was designed to be both unobtrusive and to respond in real time. Despite our efforts, usage of the system was low. In the current study we perform a mixed methods evaluation to identify remediable barriers which led to disappointing usage rates for our system. A mixed methods evaluation employing an online questionnaire and focus group. The focus group was organized to clarify free text comments and receive more detailed feedback from general practitioners. Topics consisted of items based on results from the survey and additional open questions. The response rate for the questionnaire was 94%. Results from the questionnaire and focus group can be summarized as follows: The system was perceived as interruptive, despite its design. Participants felt that there were too many recommendations and that the relevance of the recommendations varied. Demographic based recommendations (e.g. age) were often irrelevant, while specific risk-based recommendations (e.g. diagnosis) were more relevant. The other main barrier to use was lack of time during the patient visit. These results are likely to be useful to other researchers who are attempting to address the problems of interruption and alert fatigue in decision support.

Key Findings and Recommendations for Technology Transfer at the ITS JPO

DOT National Transportation Integrated Search

2011-03-18

This report provides key findings and recommendations for technology transfer at the Intelligent Transportation Systems Joint Program Office (ITS JPO) based upon an assessment of best practices in technology transfer in other industries, such as nati...

Product Recommendation System Based on Personal Preference Model Using CAM

NASA Astrophysics Data System (ADS)

Murakami, Tomoko; Yoshioka, Nobukazu; Orihara, Ryohei; Furukawa, Koichi

Product recommendation system is realized by applying business rules acquired by data maining techniques. Business rules such as demographical patterns of purchase, are able to cover the groups of users that have a tendency to purchase products, but it is difficult to recommend products adaptive to various personal preferences only by utilizing them. In addition to that, it is very costly to gather the large volume of high quality survey data, which is necessary for good recommendation based on personal preference model. A method collecting kansei information automatically without questionnaire survey is required. The constructing personal preference model from less favor data is also necessary, since it is costly for the user to input favor data. In this paper, we propose product recommendation system based on kansei information extracted by text mining and user's preference model constructed by Category-guided Adaptive Modeling, CAM for short. CAM is a feature construction method that can generate new features constructing the space where same labeled examples are close and different labeled examples are far away from some labeled examples. It is possible to construct personal preference model by CAM despite less information of likes and dislikes categories. In the system, retrieval agent gathers the products' specification and user agent manages preference model, user's likes and dislikes. Kansei information of the products is gained by applying text mining technique to the reputation documents about the products on the web site. We carry out some experimental studies to make sure that prefrence model obtained by our method performs effectively.

Awarding Dollars Based on Student Need: A Recommendation to Implement Weighted Student Funding in Georgia

ERIC Educational Resources Information Center

Education Resource Strategies, 2014

2014-01-01

As the state of Georgia considers revising its K-12 funding formula, Education Resource Strategies (ERS) recommends the state implement a weighted student-funding formula (WSF) system in order to create resource use flexibility for districts and to remove the marginal inequity found in its current funding system. Additionally, such a change would…

An Inter-Personal Information Sharing Model Based on Personalized Recommendations

NASA Astrophysics Data System (ADS)

Kamei, Koji; Funakoshi, Kaname; Akahani, Jun-Ichi; Satoh, Tetsuji

In this paper, we propose an inter-personal information sharing model among individuals based on personalized recommendations. In the proposed model, we define an information resource as shared between people when both of them consider it important --- not merely when they both possess it. In other words, the model defines the importance of information resources based on personalized recommendations from identifiable acquaintances. The proposed method is based on a collaborative filtering system that focuses on evaluations from identifiable acquaintances. It utilizes both user evaluations for documents and their contents. In other words, each user profile is represented as a matrix of credibility to the other users' evaluations on each domain of interests. We extended the content-based collaborative filtering method to distinguish other users to whom the documents should be recommended. We also applied a concept-based vector space model to represent the domain of interests instead of the previous method which represented them by a term-based vector space model. We introduce a personalized concept-base compiled from each user's information repository to improve the information retrieval in the user's environment. Furthermore, the concept-spaces change from user to user since they reflect the personalities of the users. Because of different concept-spaces, the similarity between a document and a user's interest varies for each user. As a result, a user receives recommendations from other users who have different view points, achieving inter-personal information sharing based on personalized recommendations. This paper also describes an experimental simulation of our information sharing model. In our laboratory, five participants accumulated a personal repository of e-mails and web pages from which they built their own concept-base. Then we estimated the user profiles according to personalized concept-bases and sets of documents which others evaluated. We simulated inter-personal recommendation based on the user profiles and evaluated the performance of the recommendation method by comparing the recommended documents to the result of the content-based collaborative filtering.

Feasibility of Integrated Menu Recommendation and Self-Order System for Small-Scale Restaurants

NASA Astrophysics Data System (ADS)

Kashima, Tomoko; Matsumoto, Shimpei; Ishii, Hiroaki

2010-10-01

In recent years, point of sales (POS) systems with order function have been developed for restaurants. Since expensive apparatus and system are required for installing POS systems, usually only large-scale restaurant chains can afford to introduce them. In this research, we consider the POS management in a restaurant, which cooperates with an automatic order function by using a personal digital device aiming at the safety of the food, pursuit of service, and further operational efficiency improvements, such as foods management, accounting treatment, and ordering work. In traditional POS systems, information recommendation technology is not taken into consideration. We realize the recommendation of a menu according to the user's preference using rough sets and menu planning based on stock status by applying information recommendation technology. Therefore, we believe that this system can be used in comfort with regard to freshness of foods, allergy, diabetes, etc. Furthermore, due to the reduction of the personnel expenses by an operational efficiency improvement such technology becomes even feasible for small-scale stores.

Social Network Supported Process Recommender System

PubMed Central

Ye, Yanming; Yin, Jianwei; Xu, Yueshen

2014-01-01

Process recommendation technologies have gained more and more attention in the field of intelligent business process modeling to assist the process modeling. However, most of the existing technologies only use the process structure analysis and do not take the social features of processes into account, while the process modeling is complex and comprehensive in most situations. This paper studies the feasibility of social network research technologies on process recommendation and builds a social network system of processes based on the features similarities. Then, three process matching degree measurements are presented and the system implementation is discussed subsequently. Finally, experimental evaluations and future works are introduced. PMID:24672309

Managing Trust in Online Social Networks

NASA Astrophysics Data System (ADS)

Bhuiyan, Touhid; Josang, Audun; Xu, Yue

In recent years, there is a dramatic growth in number and popularity of online social networks. There are many networks available with more than 100 million registered users such as Facebook, MySpace, QZone, Windows Live Spaces etc. People may connect, discover and share by using these online social networks. The exponential growth of online communities in the area of social networks attracts the attention of the researchers about the importance of managing trust in online environment. Users of the online social networks may share their experiences and opinions within the networks about an item which may be a product or service. The user faces the problem of evaluating trust in a service or service provider before making a choice. Recommendations may be received through a chain of friends network, so the problem for the user is to be able to evaluate various types of trust opinions and recommendations. This opinion or recommendation has a great influence to choose to use or enjoy the item by the other user of the community. Collaborative filtering system is the most popular method in recommender system. The task in collaborative filtering is to predict the utility of items to a particular user based on a database of user rates from a sample or population of other users. Because of the different taste of different people, they rate differently according to their subjective taste. If two people rate a set of items similarly, they share similar tastes. In the recommender system, this information is used to recommend items that one participant likes, to other persons in the same cluster. But the collaborative filtering system performs poor when there is insufficient previous common rating available between users; commonly known as cost start problem. To overcome the cold start problem and with the dramatic growth of online social networks, trust based approach to recommendation has emerged. This approach assumes a trust network among users and makes recommendations based on the ratings of the users that are directly or indirectly trusted by the target user.

A hybrid personalized data recommendation approach for geoscience data sharing

NASA Astrophysics Data System (ADS)

WANG, M.; Wang, J.

2016-12-01

Recommender systems are effective tools helping Internet users overcome information overloading. The two most widely used recommendation algorithms are collaborating filtering (CF) and content-based filtering (CBF). A number of recommender systems based on those two algorithms were developed for multimedia, online sells, and other domains. Each of the two algorithms has its advantages and shortcomings. Hybrid approaches that combine these two algorithms are better choices in many cases. In geoscience data sharing domain, where the items (datasets) are more informative (in space and time) and domain-specific, no recommender system is specialized for data users. This paper reports a dynamic weighted hybrid recommendation algorithm that combines CF and CBF for geoscience data sharing portal. We first derive users' ratings on items with their historical visiting time by Jenks Natural Break. In the CBF part, we incorporate the space, time, and subject information of geoscience datasets to compute item similarity. Predicted ratings were computed with k-NN method separately using CBF and CF, and then combined with weights. With training dataset we attempted to find the best model describing ideal weights and users' co-rating numbers. A logarithmic function was confirmed to be the best model. The model was then used to tune the weights of CF and CBF on user-item basis with test dataset. Evaluation results show that the dynamic weighted approach outperforms either solo CF or CBF approach in terms of Precision and Recall.

Applying the WHO recommendations on health-sector response to violence against women to assess the Spanish health system. A mixed methods approach.

PubMed

Goicolea, Isabel; Vives-Cases, Carmen; Minvielle, Fauhn; Briones-Vozmediano, Erica; Ohman, Ann

2014-01-01

This methodological note describes the development and application of a mixed-methods protocol to assess the responsiveness of Spanish health systems to violence against women in Spain, based on the World Health Organization (WHO) recommendations. Five areas for exploration were identified based on the WHO recommendations: policy environment, protocols, training, accountability/monitoring, and prevention/promotion. Two data collection instruments were developed to assess the situation of 17 Spanish regional health systems (RHS) with respect to these areas: 1) a set of indicators to guide a systematic review of secondary sources, and 2) an interview guide to be used with 26 key informants at the regional and national levels. We found differences between RHSs in the five areas assessed. The progress of RHSs on the WHO recommendations was notable at the level of policies, moderate in terms of health service delivery, and very limited in terms of preventive actions. Using a mixed-methods approach was useful for triangulation and complementarity during instrument design, data collection and interpretation. Copyright © 2013 SESPAS. Published by Elsevier Espana. All rights reserved.

From fuel taxes to mileage-based user fees : rationale, technology, and transitional issues.

DOT National Transportation Integrated Search

2011-08-01

Two national commissions established by the U.S. Congress recommend replacing the current system of funding : transportation based on fuel taxes with a new distance-based system of user fees. The State of Oregon has done a : pilot project demonstrati...

Compositional descriptor-based recommender system for the materials discovery

NASA Astrophysics Data System (ADS)

Seko, Atsuto; Hayashi, Hiroyuki; Tanaka, Isao

2018-06-01

Structures and properties of many inorganic compounds have been collected historically. However, it only covers a very small portion of possible inorganic crystals, which implies the presence of numerous currently unknown compounds. A powerful machine-learning strategy is mandatory to discover new inorganic compounds from all chemical combinations. Herein we propose a descriptor-based recommender-system approach to estimate the relevance of chemical compositions where crystals can be formed [i.e., chemically relevant compositions (CRCs)]. In addition to data-driven compositional similarity used in the literature, the use of compositional descriptors as a prior knowledge is helpful for the discovery of new compounds. We validate our recommender systems in two ways. First, one database is used to construct a model, while another is used for the validation. Second, we estimate the phase stability for compounds at expected CRCs using density functional theory calculations.

The Impact of Youth and Family Risk Factors on Service Recommendations and Delivery in a School-Based System of Care

PubMed Central

Whitson, Melissa L.; Connell, Christian M.; Bernard, Stanley; Kaufman, Joy S.

2010-01-01

The present study examines the impact of child and family risk factors on service access for youth and families in a school-based system of care. Regression analyses examined the relationships between risk factors and services recommended, services received, and dosage of services received. Logistic regression analyses examined the relationship between risk factors and whether or not youth received specific types of services within the system of care. Results revealed that youth with a personal or family history of substance use had more services recommended than youth without these risk factors, while youth with a family history of substance use received more services. Youth with a history of substance use received a significantly higher dosage of services overall. Finally, history of family mental illness was associated with receiving mental health and operational services (e.g., family advocacy, emergency funds). Implications and limitations are discussed. PMID:20165927

The Skills, Competences, and Attitude toward Information and Communications Technology Recommender System: an online support program for teachers with personalized recommendations

NASA Astrophysics Data System (ADS)

Revilla Muñoz, Olga; Alpiste Penalba, Francisco; Fernández Sánchez, Joaquín

2016-01-01

Teachers deal with Information and Communications Technology (ICT) every day and they often have to solve problems by themselves. To help them in coping with this issue, an online support program has been created, where teachers can pose their problems on ICT and they can receive solutions from other teachers. A Recommender System has been defined and implemented into the support program to suggest to each teacher the most suitable solution based on her Skills, Competences, and Attitude toward ICT (SCAT-ICT). The support program has initially been populated with 70 problems from 86 teachers. 30 teachers grouped these problems into six categories with the card-sorting technique. Real solutions to these problems have been proposed by 25 trained teachers. Finally, 17 teachers evaluated the usability of the support program and the Recommender System, where results showed a high score on the standardized System Usability Scale.

Learning Materials Recommendation Using Good Learners' Ratings and Content-Based Filtering

ERIC Educational Resources Information Center

Ghauth, Khairil Imran; Abdullah, Nor Aniza

2010-01-01

The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim to address this need by proposing a novel e-learning recommender system framework that is based…

Establishing Recommendations for Stroke Systems in the Thrombectomy Era: The Upstate New York Stakeholder Proceedings.

PubMed

Magdon-Ismail, Zainab; Benesch, Curtis; Cushman, Jeremy T; Brissette, Ian; Southerland, Andrew M; Brandler, Ethan S; Sozener, Cemal B; Flor, Sue; Hemmitt, Roseanne; Wales, Kathleen; Parrigan, Krystal; Levine, Steven R

2017-07-01

The American Heart Association/American Stroke Association and Department of Health Stroke Coverdell Program convened a stakeholder meeting in upstate NY to develop recommendations to enhance stroke systems for acute large vessel occlusion. Prehospital, hospital, and Department of Health leadership were invited (n=157). Participants provided goals/concerns and developed recommendations for prehospital triage and interfacility transport, rating each using a 3-level impact (A [high], B, and C [low]) and implementation feasibility (1 [high], 2, and 3 [low]) scale. Six weeks later, participants finalized recommendations. Seventy-one stakeholders (45% of invitees) attended. Six themes around goals/concerns emerged: (1) emergency medical services capacity, (2) validated prehospital screening tools, (3) facility capability, (4) triage/transport guidelines, (5) data capture/feedback tools, and (6) facility competition. In response, high-impact (level A) prehospital recommendations, stratified by implementation feasibility, were (1) use of online medical control for triage (6%); (2) regional transportation strategy (31%), standardized emergency medical services checklists (18%), quality metrics (14%), standardized prehospital screening tools (13%), and feedback for performance improvement (7%); and (3) smartphone application algorithm for screening/decision-making (6%) and ambulance-based telemedicine (6%). Level A interfacility transfer recommendations were (1) standardized transfer process (32%)/timing goals (16%)/regionalized systems (11%), performance metrics (11%), image sharing capabilities (7%); (2) provider education (9%) and stroke toolbox (5%); and (3) interfacility telemedicine (7%) and feedback (2%). The methods used and recommendations generated provide models for stroke system enhancement. Implementation may vary based on geographic need/capacity and be contingent on establishing standard care practices. Further research is needed to establish optimal implementation strategies. © 2017 American Heart Association, Inc.

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems

PubMed Central

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes. PMID:26267477

Item Anomaly Detection Based on Dynamic Partition for Time Series in Recommender Systems.

PubMed

Gao, Min; Tian, Renli; Wen, Junhao; Xiong, Qingyu; Ling, Bin; Yang, Linda

2015-01-01

In recent years, recommender systems have become an effective method to process information overload. However, recommendation technology still suffers from many problems. One of the problems is shilling attacks-attackers inject spam user profiles to disturb the list of recommendation items. There are two characteristics of all types of shilling attacks: 1) Item abnormality: The rating of target items is always maximum or minimum; and 2) Attack promptness: It takes only a very short period time to inject attack profiles. Some papers have proposed item anomaly detection methods based on these two characteristics, but their detection rate, false alarm rate, and universality need to be further improved. To solve these problems, this paper proposes an item anomaly detection method based on dynamic partitioning for time series. This method first dynamically partitions item-rating time series based on important points. Then, we use chi square distribution (χ2) to detect abnormal intervals. The experimental results on MovieLens 100K and 1M indicate that this approach has a high detection rate and a low false alarm rate and is stable toward different attack models and filler sizes.

Alleviating bias leads to accurate and personalized recommendation

NASA Astrophysics Data System (ADS)

Qiu, Tian; Wang, Tian-Tian; Zhang, Zi-Ke; Zhong, Li-Xin; Chen, Guang

2013-11-01

Recommendation bias towards objects has been found to have an impact on personalized recommendation, since objects present heterogeneous characteristics in some network-based recommender systems. In this article, based on a biased heat conduction recommendation algorithm (BHC) which considers the heterogeneity of the target objects, we propose a heterogeneous heat conduction algorithm (HHC), by further taking the heterogeneity of the source objects into account. Tested on three real datasets, the Netflix, RYM and MovieLens, the HHC algorithm is found to present better recommendation in both the accuracy and diversity than two benchmark algorithms, i.e., the original BHC and a hybrid algorithm of heat conduction and mass diffusion (HHM), while not requiring any other accessorial information or parameter. Moreover, the HHC algorithm also elevates the recommendation accuracy on cold objects, referring to the so-called cold-start problem. Eigenvalue analyses show that, the HHC algorithm effectively alleviates the recommendation bias towards objects with different level of popularity, which is beneficial to solving the accuracy-diversity dilemma.

The dynamical modeling and simulation analysis of the recommendation on the user-movie network

NASA Astrophysics Data System (ADS)

Zhang, Shujuan; Jin, Zhen; Zhang, Juan

2016-12-01

At present, most research about the recommender system is based on graph theory and algebraic methods, but these methods cannot predict the evolution of the system with time under the recommendation method, and cannot dynamically analyze the long-term utility of the recommendation method. However, these two aspects can be studied by the dynamical method, which essentially investigates the intrinsic evolution mechanism of things, and is widely used to study a variety of actual problems. So, in this paper, network dynamics is used to study the recommendation on the user-movie network, which consists of users and movies, and the movies are watched either by the personal search or through the recommendation. Firstly, dynamical models are established to characterize the personal search and the system recommendation mechanism: the personal search model, the random recommendation model, the preference recommendation model, the degree recommendation model and the hybrid recommendation model. The rationality of the models established is verified by comparing the stochastic simulation with the numerical simulation. Moreover, the validity of the recommendation methods is evaluated by studying the movie degree, which is defined as the number of the movie that has been watched. Finally, we combine the personal search and the recommendation to establish a more general model. The change of the average degree of all the movies is given with the strength of the recommendation. Results show that for each recommendation method, the change of the movie degree is different, and is related to the initial degree of movies, the adjacency matrix A representing the relation between users and movies, the time t. Additionally, we find that in a long time, the degree recommendation is not as good as that in a short time, which fully demonstrates the advantage of the dynamical method. For the whole user-movie system, the preference recommendation is the best.

Systemic Therapy for Stage IV Non-Small-Cell Lung Cancer: American Society of Clinical Oncology Clinical Practice Guideline Update.

PubMed

Hanna, Nasser; Johnson, David; Temin, Sarah; Baker, Sherman; Brahmer, Julie; Ellis, Peter M; Giaccone, Giuseppe; Hesketh, Paul J; Jaiyesimi, Ishmael; Leighl, Natasha B; Riely, Gregory J; Schiller, Joan H; Schneider, Bryan J; Smith, Thomas J; Tashbar, Joan; Biermann, William A; Masters, Gregory

2017-10-20

Purpose Provide evidence-based recommendations updating the 2015 ASCO guideline on systemic therapy for patients with stage IV non-small-cell lung cancer (NSCLC). Methods The ASCO NSCLC Expert Panel made recommendations based on a systematic review of randomized controlled trials from February 2014 to December 2016 plus the Cancer Care Ontario Program in Evidence-Based Care's update of a previous ASCO search. Results This guideline update reflects changes in evidence since the previous guideline update. Fourteen randomized controlled trials provide the evidence base; earlier phase trials also informed recommendation development. Recommendations New or revised recommendations include the following. Regarding first-line treatment for patients with non-squamous cell carcinoma or squamous cell carcinoma (without positive markers, eg, EGFR/ALK /ROS1), if the patient has high programmed death ligand 1 (PD-L1) expression, pembrolizumab should be used alone; if the patient has low PD-L1 expression, clinicians should offer standard chemotherapy. All other clinical scenarios follow 2015 recommendations. Regarding second-line treatment in patients who received first-line chemotherapy, without prior immune checkpoint therapy, if NSCLC tumor is positive for PD-L1 expression, clinicians should use single-agent nivolumab, pembrolizumab, or atezolizumab; if tumor has negative or unknown PD-L1 expression, clinicians should use nivolumab or atezolizumab. All immune checkpoint therapy is recommended alone plus in the absence of contraindications. For patients who received a prior first-line immune checkpoint inhibitor, clinicians should offer standard chemotherapy. For patients who cannot receive immune checkpoint inhibitor after chemotherapy, docetaxel is recommended; in patients with nonsquamous NSCLC, pemetrexed is recommended. In patients with a sensitizing EGFR mutation, disease progression after first-line epidermal growth factor receptor tyrosine kinase inhibitor therapy, and T790M mutation, osimertinib is recommended; if NSCLC lacks the T790M mutation, then chemotherapy is recommended. Patients with ROS1 gene rearrangement without prior crizotinib may be offered crizotinib, or if they previously received crizotinib, they may be offered chemotherapy.

Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications.

PubMed

Achakulvisut, Titipat; Acuna, Daniel E; Ruangrong, Tulakan; Kording, Konrad

2016-01-01

Finding relevant publications is important for scientists who have to cope with exponentially increasing numbers of scholarly material. Algorithms can help with this task as they help for music, movie, and product recommendations. However, we know little about the performance of these algorithms with scholarly material. Here, we develop an algorithm, and an accompanying Python library, that implements a recommendation system based on the content of articles. Design principles are to adapt to new content, provide near-real time suggestions, and be open source. We tested the library on 15K posters from the Society of Neuroscience Conference 2015. Human curated topics are used to cross validate parameters in the algorithm and produce a similarity metric that maximally correlates with human judgments. We show that our algorithm significantly outperformed suggestions based on keywords. The work presented here promises to make the exploration of scholarly material faster and more accurate.

Science Concierge: A Fast Content-Based Recommendation System for Scientific Publications

PubMed Central

Achakulvisut, Titipat; Acuna, Daniel E.; Ruangrong, Tulakan; Kording, Konrad

2016-01-01

Finding relevant publications is important for scientists who have to cope with exponentially increasing numbers of scholarly material. Algorithms can help with this task as they help for music, movie, and product recommendations. However, we know little about the performance of these algorithms with scholarly material. Here, we develop an algorithm, and an accompanying Python library, that implements a recommendation system based on the content of articles. Design principles are to adapt to new content, provide near-real time suggestions, and be open source. We tested the library on 15K posters from the Society of Neuroscience Conference 2015. Human curated topics are used to cross validate parameters in the algorithm and produce a similarity metric that maximally correlates with human judgments. We show that our algorithm significantly outperformed suggestions based on keywords. The work presented here promises to make the exploration of scholarly material faster and more accurate. PMID:27383424

Content-based Music Search and Recommendation System

NASA Astrophysics Data System (ADS)

Takegawa, Kazuki; Hijikata, Yoshinori; Nishida, Shogo

Recently, the turn volume of music data on the Internet has increased rapidly. This has increased the user's cost to find music data suiting their preference from such a large data set. We propose a content-based music search and recommendation system. This system has an interface for searching and finding music data and an interface for editing a user profile which is necessary for music recommendation. By exploiting the visualization of the feature space of music and the visualization of the user profile, the user can search music data and edit the user profile. Furthermore, by exploiting the infomation which can be acquired from each visualized object in a mutually complementary manner, we make it easier for the user to search music data and edit the user profile. Concretely, the system gives to the user an information obtained from the user profile when searching music data and an information obtained from the feature space of music when editing the user profile.

Stakeholder Analysis for the CF Counter-IED Training Courses

DTIC Science & Technology

2010-05-01

for more than purely research purposes when the experimenter is present. 3.1.3 Learning Style- based Adaptation The Index of Learning Styles (Felder...student. It is recommended that the Adaption Module uses the same ontology based reasoning approach as the Evaluation Module. RacerPro is the recommended...reasoner. RacerPro is used as a system for managing semantic web ontologies based on Web Ontology Language (OWL). The design phase will confirm

How to Get the Recommender Out of the Lab?

NASA Astrophysics Data System (ADS)

Picault, Jérome; Ribière, Myriam; Bonnefoy, David; Mercer, Kevin

A personalised system is a complex system made of many interacting parts, from data ingestion to presenting the results to the users. A plethora of methods, tools, algorithms and approaches exist for each piece of such a system: many data and metadata processing methods, many user models, many filtering techniques, many accuracy metrics, many personalisation levels. In addition, a realworld recommender is a piece of an even larger and more complex environment on which there is little control: often the recommender is part of a larger application introducing constraints for the design of the recommender, e.g. the data may not be in a suitable format, or the environment may impose some architectural or privacy constraints. This can make the task of building such a recommender system daunting, and it is easy to make errors. Based on the experience of the authors and the study of other works, this chapter intends to be a guide on the design, implementation and evaluation of personalised systems. It presents the different aspects that must be studied before the design is even started, and how to avoid pitfalls, in a hands-on approach. The chapter presents the main factors to take into account to design a recommender system, and illustrates them through case studies of existing systems to help navigate in the many and complex choices that have to be faced.

Review of Spatial-Database System Usability: Recommendations for the ADDNS Project

DTIC Science & Technology

2007-12-01

basic GIS background information , with a closer look at spatial databases. A GIS is also a computer- based system designed to capture, manage...foundation for deploying enterprise-wide spatial information systems . According to Oracle® [18], it enables accurate delivery of location- based services...Toronto TR 2007-141 Lanter, D.P. (1991). Design of a lineage- based meta-data base for GIS. Cartography and Geographic Information Systems , 18

Music recommendation system for biofied building considering multiple residents

NASA Astrophysics Data System (ADS)

Ito, Takahiro; Mita, Akira

2012-04-01

This research presents a music recommendation system based on multiple users' communication excitement and productivity. Evaluation is conducted on following two points. 1, Does songA recommended by the system improve the situation of dropped down communication excitement? 2, Does songB recommended by the system improve the situation of dropped down and productivity of collaborative work? The objective of this system is to recommend songs which shall improve the situation of dropped down communication excitement and productivity. Songs are characterized according to three aspects; familiarity, relaxing and BPM(Beat Per Minutes). Communication excitement is calculated from speech data obtained by an audio sensor. Productivity of collaborative brainstorming is manually calculated by the number of time-series key words during mind mapping. First experiment was music impression experiment to 118 students. Based on 1, average points of familiarity, relaxing and BPM 2, cronbach alpha factor, songA(high familiarity, high relaxing and high BPM song) and songB(high familiarity, high relaxing and low BPM) are selected. Exploratory experiment defined dropped down communication excitement and dropped down and productivity of collaborative work. Final experiment was conducted to 32 first meeting students divided into 8 groups. First 4 groups had mind mapping 1 while listening to songA, then had mind mapping 2 while listening songB. Following 4 groups had mind mapping 1 while listening to songB, then had mind mapping 2 while listening songA. Fianl experiment shows two results. Firstly, ratio of communication excitement between music listening section and whole brain storming is 1.27. Secondly, this system increases 69% of average productivity.

Comparing Acquisition of Exchange-Based and Signed Mands with Children with Autism

ERIC Educational Resources Information Center

Barlow, Kathryn E.; Tiger, Jeffrey H.; Slocum, Sarah K.; Miller, Sarah J.

2013-01-01

Therapists and educators frequently teach alternative-communication systems, such as picture exchanges or manual signs, to individuals with developmental disabilities who present with expressive language deficits. Michael (1985) recommended a taxonomy for alternative communication systems that differentiated between selection-based systems in…

Reducing Delay in Diagnosis: Multistage Recommendation Tracking.

PubMed

Wandtke, Ben; Gallagher, Sarah

2017-11-01

The purpose of this study was to determine whether a multistage tracking system could improve communication between health care providers, reducing the risk of delay in diagnosis related to inconsistent communication and tracking of radiology follow-up recommendations. Unconditional recommendations for imaging follow-up of all diagnostic imaging modalities excluding mammography (n = 589) were entered into a database and tracked through a multistage tracking system for 13 months. Tracking interventions were performed for patients for whom completion of recommended follow-up imaging could not be identified 1 month after the recommendation due date. Postintervention compliance with the follow-up recommendation required examination completion or clinical closure (i.e., biopsy, limited life expectancy or death, or subspecialist referral). Baseline radiology information system checks performed 1 month after the recommendation due date revealed timely completion of 43.1% of recommended imaging studies at our institution before intervention. Three separate tracking interventions were studied, showing effectiveness between 29.0% and 57.8%. The multistage tracking system increased the examination completion rate to 70.5% (a 52% increase) and reduced the rate of unknown follow-up compliance and the associated risk of delay in diagnosis to 13.9% (a 74% decrease). Examinations completed after tracking intervention generated revenue of 4.1 times greater than the labor cost. Performing sequential radiology recommendation tracking interventions can substantially reduce the rate of unknown follow-up compliance and add value to the health system. Unknown follow-up compliance is a risk factor for delay in diagnosis, a form of preventable medical error commonly identified in malpractice claims involving radiologists and office-based practitioners.

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs.

PubMed

Tsopra, R; Venot, A; Duclos, C

2014-01-01

Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. We investigated two methods ("exclusion" versus "scoring") for reproducing this reasoning based on antibiotic properties. The "exclusion" method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs.

Effect of recent popularity on heat-conduction based recommendation models

NASA Astrophysics Data System (ADS)

Li, Wen-Jun; Dong, Qiang; Shi, Yang-Bo; Fu, Yan; He, Jia-Lin

2017-05-01

Accuracy and diversity are two important measures in evaluating the performance of recommender systems. It has been demonstrated that the recommendation model inspired by the heat conduction process has high diversity yet low accuracy. Many variants have been introduced to improve the accuracy while keeping high diversity, most of which regard the current node-degree of an item as its popularity. However in this way, a few outdated items of large degree may be recommended to an enormous number of users. In this paper, we take the recent popularity (recently increased item degrees) into account in the heat-conduction based methods, and propose accordingly the improved recommendation models. Experimental results on two benchmark data sets show that the accuracy can be largely improved while keeping the high diversity compared with the original models.

Improving the Care of Individuals with Schizophrenia and Substance Use Disorders: Consensus Recommendations

PubMed Central

ZIEDONIS, DOUGLAS M.; SMELSON, DAVID; ROSENTHAL, RICHARD N.; BATKI, STEVEN L.; GREEN, ALAN I.; HENRY, RENATA J.; MONTOYA, IVAN; PARKS, JOE; D. WEISS, ROGER

2008-01-01

National attention continues to focus on the need to improve care for individuals with co-occurring mental illnesses and substance use disorders, as emphasized in the 2003 President's New Freedom Commission Report on Mental Health and recent publications from the Substance Abuse and Mental Health Services Administration (SAMHSA). These reports document the need for best practice recommendations that can be translated into routine clinical care. Although efforts are underway to synthesize literature in this area, few focused recommendations are available that include expert opinion and evidence-based findings on the management of specific co-occurring disorders, such as schizophrenia and addiction. In response to the need for user-friendly recommendations on the treatment of schizophrenia and addiction, a consensus conference of experts from academic institutions and state mental health systems was organized to 1) frame the problem from clinical and systems-level perspectives; 2) identify effective and problematic psychosocial, pharmacological, and systems practices; and 3) develop a summary publication with recommendations for improving current practice. The results of the consensus meeting served as the foundation for this publication, which presents a broad set of recommendations for clinicians who treat individuals with schizophrenia. “Integrated treatment” is the new standard for evidence-based treatment for this population and recommendations are given to help clinicians implement such integrated treatment. Specific recommendations are provided concerning screening for substance use disorders in patients with schizophrenia, assessing motivation for change, managing medical conditions that commonly occur in patients with dual diagnoses (e.g., cardiovascular disease, liver complications, lung cancer, HIV, and hepatitis B or C infections) and selecting the most appropriate medications for such patients to maximize safety and minimize drug interactions, use of evidence-based psychosocial interventions for patients with dual diagnoses (e.g., Dual Recovery Therapy, modified cognitive-behavioral therapy, modified motivational enhancement therapy, and the Substance Abuse Management Module), and key pharmacotherapy principles for treating schizophrenia, substance use disorders, and comorbid anxiety, depression, and sleep problems in this population. Finally the article reviews programmatic and systemic changes needed to overcome treatment barriers and promote the best outcomes for this patient population. An algorithm summarizing the consensus recommendations is provided in an appendix to the article. PMID:16184072

Autonomous power expert system advanced development

NASA Technical Reports Server (NTRS)

Quinn, Todd M.; Walters, Jerry L.

1991-01-01

The autonomous power expert (APEX) system is being developed at Lewis Research Center to function as a fault diagnosis advisor for a space power distribution test bed. APEX is a rule-based system capable of detecting faults and isolating the probable causes. APEX also has a justification facility to provide natural language explanations about conclusions reached during fault isolation. To help maintain the health of the power distribution system, additional capabilities were added to APEX. These capabilities allow detection and isolation of incipient faults and enable the expert system to recommend actions/procedure to correct the suspected fault conditions. New capabilities for incipient fault detection consist of storage and analysis of historical data and new user interface displays. After the cause of a fault is determined, appropriate recommended actions are selected by rule-based inferencing which provides corrective/extended test procedures. Color graphics displays and improved mouse-selectable menus were also added to provide a friendlier user interface. A discussion of APEX in general and a more detailed description of the incipient detection, recommended actions, and user interface developments during the last year are presented.

On Deep Learning for Trust-Aware Recommendations in Social Networks.

PubMed

Deng, Shuiguang; Huang, Longtao; Xu, Guandong; Wu, Xindong; Wu, Zhaohui

2017-05-01

With the emergence of online social networks, the social network-based recommendation approach is popularly used. The major benefit of this approach is the ability of dealing with the problems with cold-start users. In addition to social networks, user trust information also plays an important role to obtain reliable recommendations. Although matrix factorization (MF) becomes dominant in recommender systems, the recommendation largely relies on the initialization of the user and item latent feature vectors. Aiming at addressing these challenges, we develop a novel trust-based approach for recommendation in social networks. In particular, we attempt to leverage deep learning to determinate the initialization in MF for trust-aware social recommendations and to differentiate the community effect in user's trusted friendships. A two-phase recommendation process is proposed to utilize deep learning in initialization and to synthesize the users' interests and their trusted friends' interests together with the impact of community effect for recommendations. We perform extensive experiments on real-world social network data to demonstrate the accuracy and effectiveness of our proposed approach in comparison with other state-of-the-art methods.

Systemic Therapy for Stage IV Non–Small-Cell Lung Cancer: American Society of Clinical Oncology Clinical Practice Guideline Update

PubMed Central

Masters, Gregory A.; Temin, Sarah; Azzoli, Christopher G.; Giaccone, Giuseppe; Baker, Sherman; Brahmer, Julie R.; Ellis, Peter M.; Gajra, Ajeet; Rackear, Nancy; Schiller, Joan H.; Smith, Thomas J.; Strawn, John R.; Trent, David; Johnson, David H.

2015-01-01

Purpose To provide evidence-based recommendations to update the American Society of Clinical Oncology guideline on systemic therapy for stage IV non–small-cell lung cancer (NSCLC). Methods An Update Committee of the American Society of Clinical Oncology NSCLC Expert Panel based recommendations on a systematic review of randomized controlled trials from January 2007 to February 2014. Results This guideline update reflects changes in evidence since the previous guideline. Recommendations There is no cure for patients with stage IV NSCLC. For patients with performance status (PS) 0 to 1 (and appropriate patient cases with PS 2) and without an EGFR-sensitizing mutation or ALK gene rearrangement, combination cytotoxic chemotherapy is recommended, guided by histology, with early concurrent palliative care. Recommendations for patients in the first-line setting include platinum-doublet therapy for those with PS 0 to 1 (bevacizumab may be added to carboplatin plus paclitaxel if no contraindications); combination or single-agent chemotherapy or palliative care alone for those with PS 2; afatinib, erlotinib, or gefitinib for those with sensitizing EGFR mutations; crizotinib for those with ALK or ROS1 gene rearrangement; and following first-line recommendations or using platinum plus etoposide for those with large-cell neuroendocrine carcinoma. Maintenance therapy includes pemetrexed continuation for patients with stable disease or response to first-line pemetrexed-containing regimens, alternative chemotherapy, or a chemotherapy break. In the second-line setting, recommendations include docetaxel, erlotinib, gefitinib, or pemetrexed for patients with nonsquamous cell carcinoma; docetaxel, erlotinib, or gefitinib for those with squamous cell carcinoma; and chemotherapy or ceritinib for those with ALK rearrangement who experience progression after crizotinib. In the third-line setting, for patients who have not received erlotinib or gefitinib, treatment with erlotinib is recommended. There are insufficient data to recommend routine third-line cytotoxic therapy. Decisions regarding systemic therapy should not be made based on age alone. Additional information can be found at http://www.asco.org/guidelines/nsclc and http://www.asco.org/guidelineswiki. PMID:26324367

Data base design for a worldwide multicrop information system

NASA Technical Reports Server (NTRS)

Driggers, W. G.; Downs, J. M.; Hickman, J. R.; Packard, R. L. (Principal Investigator)

1979-01-01

A description of the USDA Application Test System data base design approach and resources is presented. The data is described in detail by category, with emphasis on those characteristics which influenced the design most. It was concluded that the use of a generalized data base in support of crop assessment is a sound concept. The IDMS11 minicomputer base system is recommended for this purpose.

Does Artificial Tutoring Foster Inquiry Based Learning?

ERIC Educational Resources Information Center

Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro

2014-01-01

This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…

Growing Wikipedia Across Languages via Recommendation.

PubMed

Wulczyn, Ellery; West, Robert; Zia, Leila; Leskovec, Jure

2016-04-01

The different Wikipedia language editions vary dramatically in how comprehensive they are. As a result, most language editions contain only a small fraction of the sum of information that exists across all Wikipedias. In this paper, we present an approach to filling gaps in article coverage across different Wikipedia editions. Our main contribution is an end-to-end system for recommending articles for creation that exist in one language but are missing in another. The system involves identifying missing articles, ranking the missing articles according to their importance, and recommending important missing articles to editors based on their interests. We empirically validate our models in a controlled experiment involving 12,000 French Wikipedia editors. We find that personalizing recommendations increases editor engagement by a factor of two. Moreover, recommending articles increases their chance of being created by a factor of 3.2. Finally, articles created as a result of our recommendations are of comparable quality to organically created articles. Overall, our system leads to more engaged editors and faster growth of Wikipedia with no effect on its quality.

Growing Wikipedia Across Languages via Recommendation

PubMed Central

Wulczyn, Ellery; West, Robert; Zia, Leila; Leskovec, Jure

2016-01-01

The different Wikipedia language editions vary dramatically in how comprehensive they are. As a result, most language editions contain only a small fraction of the sum of information that exists across all Wikipedias. In this paper, we present an approach to filling gaps in article coverage across different Wikipedia editions. Our main contribution is an end-to-end system for recommending articles for creation that exist in one language but are missing in another. The system involves identifying missing articles, ranking the missing articles according to their importance, and recommending important missing articles to editors based on their interests. We empirically validate our models in a controlled experiment involving 12,000 French Wikipedia editors. We find that personalizing recommendations increases editor engagement by a factor of two. Moreover, recommending articles increases their chance of being created by a factor of 3.2. Finally, articles created as a result of our recommendations are of comparable quality to organically created articles. Overall, our system leads to more engaged editors and faster growth of Wikipedia with no effect on its quality. PMID:27819073

Integrated vehicle-based safety systems (IVBSS) : heavy truck extended pilot test summary report.

DOT National Transportation Integrated Search

2009-05-01

This report describes the findings and recommendations from the heavy-truck (HT) extended pilot test (EPT) conducted by University of Michigan Transportation Research Institute (UMTRI) and its partners under the Integrated Vehicle-Based Safety System...

Digital case-based learning system in school.

PubMed

Gu, Peipei; Guo, Jiayang

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Digital case-based learning system in school

PubMed Central

Gu, Peipei

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework. PMID:29107965

Space-Based Solar Power Conversion and Delivery Systems Study. Volume 1: Executive Summary

NASA Technical Reports Server (NTRS)

1977-01-01

The research concerning space-based solar power conversion and delivery systems is summarized. The potential concepts for a photovoltaic satellite solar power system was studied with emphasis on ground output power levels of 5,000 MW and 10,000 MW. A power relay satellite, and certain aspects of the economics of these systems were also studied. A second study phase examined in greater depth the technical and economic aspects of satellite solar power systems. Throughout this study, the focus was on the economics of satellite solar power. The results indicate technical feasibility of the concept, and provide a preliminary economic justification for the first phase of a substantial development program. A development program containing test satellites is recommended. Also, development of alternative solar cell materials (other than silicon) is recommended.

Barriers of and facilitators to physician recommendation of colorectal cancer screening.

PubMed

Guerra, Carmen E; Schwartz, J Sanford; Armstrong, Katrina; Brown, Jamin S; Halbert, Chanita Hughes; Shea, Judy A

2007-12-01

Colorectal cancer screening (CRCS) has been demonstrated to be effective and is consistently recommended by clinical practice guidelines. However, only slightly over half of all Americans have ever been screened. Patients cite physician recommendation as the most important motivator of screening. This study explored the barriers of and facilitators to physician recommendation of CRCS. A 3-component qualitative study to explore the barriers of and facilitators to physician recommendation of CRCS: in-depth, semistructured interviews with 29 purposively sampled, community- and academic-based primary care physicians; chart-stimulated recall, a technique that utilizes patient charts to probe physician recall and provide context about the barriers of and facilitators to physician recommendation of CRCS during actual clinic encounters; and focus groups with 18 academic primary care physicians. Grounded theory techniques of analysis were used. All the participating physicians were aware of and recommended CRCS. The overwhelmingly preferred test was colonoscopy. Barriers of physician recommendation of CRCS included patient comorbidities, prior patient refusal of screening, physician forgetfulness, acute care visits, lack of time, and lack of reminder systems and test tracking systems. Facilitators to physician recommendation of CRCS included patient request, patient age 50-59, physician positive attitudes about CRCS, physician prioritization of screening, visits devoted to preventive health, reminders, and incentives. There are multiple physician, patient, and system barriers to recommending CRCS. Thus, interventions may need to target barriers at multiple levels to successfully increase physician recommendation of CRCS.

Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE): protocol and preliminary results.

PubMed

Treweek, Shaun; Oxman, Andrew D; Alderson, Philip; Bossuyt, Patrick M; Brandt, Linn; Brożek, Jan; Davoli, Marina; Flottorp, Signe; Harbour, Robin; Hill, Suzanne; Liberati, Alessandro; Liira, Helena; Schünemann, Holger J; Rosenbaum, Sarah; Thornton, Judith; Vandvik, Per Olav; Alonso-Coello, Pablo

2013-01-09

Healthcare decision makers face challenges when using guidelines, including understanding the quality of the evidence or the values and preferences upon which recommendations are made, which are often not clear. GRADE is a systematic approach towards assessing the quality of evidence and the strength of recommendations in healthcare. GRADE also gives advice on how to go from evidence to decisions. It has been developed to address the weaknesses of other grading systems and is now widely used internationally. The Developing and Evaluating Communication Strategies to Support Informed Decisions and Practice Based on Evidence (DECIDE) consortium (http://www.decide-collaboration.eu/), which includes members of the GRADE Working Group and other partners, will explore methods to ensure effective communication of evidence-based recommendations targeted at key stakeholders: healthcare professionals, policymakers, and managers, as well as patients and the general public. Surveys and interviews with guideline producers and other stakeholders will explore how presentation of the evidence could be improved to better meet their information needs. We will collect further stakeholder input from advisory groups, via consultations and user testing; this will be done across a wide range of healthcare systems in Europe, North America, and other countries. Targeted communication strategies will be developed, evaluated in randomized trials, refined, and assessed during the development of real guidelines. Results of the DECIDE project will improve the communication of evidence-based healthcare recommendations. Building on the work of the GRADE Working Group, DECIDE will develop and evaluate methods that address communication needs of guideline users. The project will produce strategies for communicating recommendations that have been rigorously evaluated in diverse settings, and it will support the transfer of research into practice in healthcare systems globally.

Technologies for space station autonomy

NASA Technical Reports Server (NTRS)

Staehle, R. L.

1984-01-01

This report presents an informal survey of experts in the field of spacecraft automation, with recommendations for which technologies should be given the greatest development attention for implementation on the initial 1990's NASA Space Station. The recommendations implemented an autonomy philosophy that was developed by the Concept Development Group's Autonomy Working Group during 1983. They were based on assessments of the technologies' likely maturity by 1987, and of their impact on recurring costs, non-recurring costs, and productivity. The three technology areas recommended for programmatic emphasis were: (1) artificial intelligence expert (knowledge based) systems and processors; (2) fault tolerant computing; and (3) high order (procedure oriented) computer languages. This report also describes other elements required for Station autonomy, including technologies for later implementation, system evolvability, and management attitudes and goals. The cost impact of various technologies is treated qualitatively, and some cases in which both the recurring and nonrecurring costs might be reduced while the crew productivity is increased, are also considered. Strong programmatic emphasis on life cycle cost and productivity is recommended.

Recommendation based on trust diffusion model.

PubMed

Yuan, Jinfeng; Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure.

Recommendation Based on Trust Diffusion Model

PubMed Central

Li, Li

2014-01-01

Recommender system is emerging as a powerful and popular tool for online information relevant to a given user. The traditional recommendation system suffers from the cold start problem and the data sparsity problem. Many methods have been proposed to solve these problems, but few can achieve satisfactory efficiency. In this paper, we present a method which combines the trust diffusion (DiffTrust) algorithm and the probabilistic matrix factorization (PMF). DiffTrust is first used to study the possible diffusions of trust between various users. It is able to make use of the implicit relationship of the trust network, thus alleviating the data sparsity problem. The probabilistic matrix factorization (PMF) is then employed to combine the users' tastes with their trusted friends' interests. We evaluate the algorithm on Flixster, Moviedata, and Epinions datasets, respectively. The experimental results show that the recommendation based on our proposed DiffTrust + PMF model achieves high performance in terms of the root mean square error (RMSE), Recall, and F Measure. PMID:25009827

A Novel Approach for Enhancing Lifelong Learning Systems by Using Hybrid Recommender System

ERIC Educational Resources Information Center

Kardan, Ahmad A.; Speily, Omid R. B.; Modaberi, Somayyeh

2011-01-01

The majority of current web-based learning systems are closed learning environments where courses and learning materials are fixed, and the only dynamic aspect is the organization of the material that can be adapted to allow a relatively individualized learning environment. In this paper, we propose an evolving web-based learning system which can…

Applying Web Usage Mining for Personalizing Hyperlinks in Web-Based Adaptive Educational Systems

ERIC Educational Resources Information Center

Romero, Cristobal; Ventura, Sebastian; Zafra, Amelia; de Bra, Paul

2009-01-01

Nowadays, the application of Web mining techniques in e-learning and Web-based adaptive educational systems is increasing exponentially. In this paper, we propose an advanced architecture for a personalization system to facilitate Web mining. A specific Web mining tool is developed and a recommender engine is integrated into the AHA! system in…

IMPLEMENTATION OF DEFENSE NUCLEAR FACILITY SAFETY BOARD RECOMMENDATION 2000-2 AT WIPP

DOE Office of Scientific and Technical Information (OSTI.GOV)

Jackson, K.; Wu, C.

2002-02-26

The Defense Nuclear Safeties Board (DNFSB) issued Recommendation 2000-2 on March 8, 2000, concerning the degrading conditions of vital safety systems, or systems important to nuclear safety, at DOE sites across the nation. The Board recommended that the DOE take action to assess the condition of its nuclear systems to ensure continued operational readiness of vital safety systems that are important for safely accomplishing the DOE's mission. To verify the readiness of vital safety systems, a two-phased approach was established. Phase I consisted of a qualitative assessment to approved criteria of the defined vital safety systems by operating contractor personnel,more » overseen by Federal field office personnel. Based on Phase I Assessment results, vital safety systems with significant deficiencies would be further assessed in Phase II, a more extensive quantitative assessment, by a contractor and Federal team, using a second set of criteria. In addition, Defense Nuclear Facility Safety Board Recommendation 2000-2 concluded that the degradation of confinement ventilation systems was of major concern, and issued a separate set of criteria to perform a Phase II Assessment on confinement ventilation systems.« less

A Machine Learning Recommender System to Tailor Preference Assessments to Enhance Person-Centered Care Among Nursing Home Residents.

PubMed

Gannod, Gerald C; Abbott, Katherine M; Van Haitsma, Kimberly; Martindale, Nathan; Heppner, Alexandra

2018-05-21

Nursing homes (NHs) using the Preferences for Everyday Living Inventory (PELI-NH) to assess important preferences and provide person-centered care find the number of items (72) to be a barrier to using the assessment. Using a sample of n = 255 NH resident responses to the PELI-NH, we used the 16 preference items from the MDS 3.0 Section F to develop a machine learning recommender system to identify additional PELI-NH items that may be important to specific residents. Much like the Netflix recommender system, our system is based on the concept of collaborative filtering whereby insights and predictions (e.g., filters) are created using the interests and preferences of many users. The algorithm identifies multiple sets of "you might also like" patterns called association rules, based upon responses to the 16 MDS preferences that recommends an additional set of preferences with a high likelihood of being important to a specific resident. In the evaluation of the combined apriori and logistic regression approach, we obtained a high recall performance (i.e., the ratio of correctly predicted preferences compared with all predicted preferences and nonpreferences) and high precision (i.e., the ratio of correctly predicted rules with respect to the rules predicted to be true) of 80.2% and 79.2%, respectively. The recommender system successfully provides guidance on how to best tailor the preference items asked of residents and can support preference capture in busy clinical environments, contributing to the feasibility of delivering person-centered care.

Development of Design Guidance for K-12 Schools: From 30% to 50% Energy Savings

DOE Office of Scientific and Technical Information (OSTI.GOV)

Pless, S.; Torcellini, P.; Long, N.

2008-01-01

This paper describes the development of energy efficiency recommendations for achieving 30% whole-building energy savings in K-12 Schools over levels achieved by following the ANSI/ASHRAE/IESNA Standard 90.1, Energy Standard for Buildings Except Low-Rise Residential Buildings (1999 and 2004 versions). Exhaustive simulations were run to create packages of energy design solutions available over a wide range of K-12 schools and climates. These design recommendations look at building envelope, fenestration, lighting systems (including electrical lights and daylighting), HVAC systems, building automation and controls, outside air treatment, and service water heating. We document and discuss the energy modeling performed to demonstrate that themore » recommendations will result in at least 30% energy savings over ASHRAE 90.1-1999 and ASHRAE 90.1-2004. Recommendations are evaluated based on the availability of daylighting for the school and by the type of HVAC system. Compared to the ASHRAE 90.1-1999 baseline, the recommendations result in more than 30% savings in all climate zones for both daylit and nondaylit elementary, middle, and high schools with a range of HVAC system types. These recommendations have been included in the Advanced Energy Design Guide for K-12 School Buildings. Compared to the more stringent ASHRAE 90.1-2004 baseline, the recommendations result in more than 30% savings in all climate zones, for only the daylit elementary, middle, and high schools, with a range of HVAC system types. To inform the future development of recommendations for higher level of energy savings, we analyzed a subset of recommendations to understand which energy efficiency technologies would be needed to achieve 50% energy savings.« less

An Algorithm Using Twelve Properties of Antibiotics to Find the Recommended Antibiotics, as in CPGs

PubMed Central

Tsopra, R.; Venot, A.; Duclos, C.

2014-01-01

Background Clinical Decision Support Systems (CDSS) incorporating justifications, updating and adjustable recommendations can considerably improve the quality of healthcare. We propose a new approach to the design of CDSS for empiric antibiotic prescription, based on implementation of the deeper medical reasoning used by experts in the development of clinical practice guidelines (CPGs), to deduce the recommended antibiotics. Methods We investigated two methods (“exclusion” versus “scoring”) for reproducing this reasoning based on antibiotic properties. Results The “exclusion” method reproduced expert reasoning the more accurately, retrieving the full list of recommended antibiotics for almost all clinical situations. Discussion This approach has several advantages: (i) it provides convincing explanations for physicians; (ii) updating could easily be incorporated into the CDSS; (iii) it can provide recommendations for clinical situations missing from CPGs. PMID:25954422

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems

PubMed Central

Wu, Jun; Su, Zhou; Li, Jianhua

2017-01-01

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on “friend” relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems. PMID:28758943

Crowd Sensing-Enabling Security Service Recommendation for Social Fog Computing Systems.

PubMed

Wu, Jun; Su, Zhou; Wang, Shen; Li, Jianhua

2017-07-30

Fog computing, shifting intelligence and resources from the remote cloud to edge networks, has the potential of providing low-latency for the communication from sensing data sources to users. For the objects from the Internet of Things (IoT) to the cloud, it is a new trend that the objects establish social-like relationships with each other, which efficiently brings the benefits of developed sociality to a complex environment. As fog service become more sophisticated, it will become more convenient for fog users to share their own services, resources, and data via social networks. Meanwhile, the efficient social organization can enable more flexible, secure, and collaborative networking. Aforementioned advantages make the social network a potential architecture for fog computing systems. In this paper, we design an architecture for social fog computing, in which the services of fog are provisioned based on "friend" relationships. To the best of our knowledge, this is the first attempt at an organized fog computing system-based social model. Meanwhile, social networking enhances the complexity and security risks of fog computing services, creating difficulties of security service recommendations in social fog computing. To address this, we propose a novel crowd sensing-enabling security service provisioning method to recommend security services accurately in social fog computing systems. Simulation results show the feasibilities and efficiency of the crowd sensing-enabling security service recommendation method for social fog computing systems.

Systems for grading the quality of evidence and the strength of recommendations I: Critical appraisal of existing approaches The GRADE Working Group

PubMed Central

Atkins, David; Eccles, Martin; Flottorp, Signe; Guyatt, Gordon H; Henry, David; Hill, Suzanne; Liberati, Alessandro; O'Connell, Dianne; Oxman, Andrew D; Phillips, Bob; Schünemann, Holger; Edejer, Tessa Tan-Torres; Vist, Gunn E; Williams, John W

2004-01-01

Background A number of approaches have been used to grade levels of evidence and the strength of recommendations. The use of many different approaches detracts from one of the main reasons for having explicit approaches: to concisely characterise and communicate this information so that it can easily be understood and thereby help people make well-informed decisions. Our objective was to critically appraise six prominent systems for grading levels of evidence and the strength of recommendations as a basis for agreeing on characteristics of a common, sensible approach to grading levels of evidence and the strength of recommendations. Methods Six prominent systems for grading levels of evidence and strength of recommendations were selected and someone familiar with each system prepared a description of each of these. Twelve assessors independently evaluated each system based on twelve criteria to assess the sensibility of the different approaches. Systems used by 51 organisations were compared with these six approaches. Results There was poor agreement about the sensibility of the six systems. Only one of the systems was suitable for all four types of questions we considered (effectiveness, harm, diagnosis and prognosis). None of the systems was considered usable for all of the target groups we considered (professionals, patients and policy makers). The raters found low reproducibility of judgements made using all six systems. Systems used by 51 organisations that sponsor clinical practice guidelines included a number of minor variations of the six systems that we critically appraised. Conclusions All of the currently used approaches to grading levels of evidence and the strength of recommendations have important shortcomings. PMID:15615589

UAS in the NAS - Analysis Results and Recommendations for Integration of CNPC and ATC Communications Simulation Report

NASA Technical Reports Server (NTRS)

Kubat, Gregory

2016-01-01

This report addresses a deliverable to the UAS-in-the-NAS project for recommendations for integration of CNPC and ATC communications based on analysis results from modeled radio system and NAS-wide UA communication architecture simulations. For each recommendation, a brief explanation of the rationale for its consideration is provided with any supporting results obtained or observed in our simulation activity.

Use of the adult attachment projective picture system in psychodynamic psychotherapy with a severely traumatized patient

PubMed Central

George, Carol; Buchheim, Anna

2014-01-01

The following case study is presented to facilitate an understanding of how the attachment information evident from Adult Attachment Projective Picture System (AAP) assessment can be integrated into a psychodynamic perspective in making therapeutic recommendations that integrate an attachment perspective. The Adult Attachment Projective Picture System (AAP) is a valid representational measure of internal representations of attachment based on the analysis of a set of free response picture stimuli designed to systematically activate the attachment system (George and West, 2012). The AAP provides a fruitful diagnostic tool for psychodynamic-oriented clinicians to identify attachment-based deficits and resources for an individual patient in therapy. This paper considers the use of the AAP with a traumatized patient in an inpatient setting and uses a case study to illustrate the components of the AAP that are particularly relevant to a psychodynamic conceptualization. The paper discusses also attachment-based recommendations for intervention. PMID:25140164

Evaluation on the first 2 years of the positive list system in South Korea.

PubMed

Park, Sung Eun; Lim, Sang Hee; Choi, Hyun Woong; Lee, Seung Min; Kim, Dong Won; Yim, Eun Young; Kim, Kook Hee; Yi, So Young

2012-01-01

The South Korean positive list system in pharmaceutical reimbursement was introduced by the Health Care System Reform Act implemented in December 2006. This study introduces this positive list system (PLS), and reports on an evaluation of two years of operation. In addition, decision-making factors are evaluated and current issues and solutions discussed. We analyzed 91 submissions with reimbursement decisions completed by December 31, 2008. Submission characteristics and relevant factors related to decision criteria were identified by the decision outcomes (recommended/rejected). Under the new system, Health Insurance Review and Assessment service (HIRA) recommended 64 submissions for reimbursement and rejected 27 submissions. For recommended submissions, 59 met all criteria and 5 were recommended based on the rule of rescue. The primary reason for rejection was unacceptable cost-effectiveness. The likelihood of recommendation was found to be significantly elevated if a drug was superior to its comparator, if treatment cost was not greater than that of its comparator, or if the number of recommended decisions made by other committees increased. The South Korean PLS has stabilized during the 2 years after its introduction. The recommended submissions were qualified in all decision-making criteria used. Among the various decision criteria, clinical benefit and cost-effectiveness were the main drivers of reimbursement decisions. In addition, there is a certain degree of consistency between the reimbursement decisions of HIRA and other countries. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Translating Guidelines Into Practice: Interpreting the 2016 ACC Expert Consensus Decision Pathway on the Role of Non-Statin Therapies for LDL-Cholesterol Lowering in the Management of Atherosclerotic Cardiovascular Disease Risk.

PubMed

Waite, Laura H; Phan, Yvonne L; Spinler, Sarah A

2017-10-01

In 2016, the American College of Cardiology released a decision pathway, based on expert consensus, to guide use of non-statin agents in the management of atherosclerotic cardiovascular disease risk. The purpose of this article is to assist practitioners, health systems and managed care entities with interpreting this consensus statement in order to simplify implementation of the recommendations into patient care. Major themes from the consensus statement are briefly summarized and explained. Drug therapy recommendations are condensed into a single algorithm, while tables correlate each recommended regimen with the appropriate patient population from both a patient-level and systems-level perspective. Finally, a patient case with evidence-based decision support is explored. These tools allow practitioners to make appropriate patient-specific decisions about the use of non-statin pharmacotherapy and enable health systems and managed care entities to more readily identify guideline-appropriate use of these agents upon review of patient profiles or prescribing patterns. This article provides resources for healthcare providers that facilitate uptake of these recommendations into clinical practice.

[How to assess and reduce social inequalities in cancer screening programmes].

PubMed

Binefa, Gemma; García, Montse; Peiró, Rosana; Molina-Barceló, Ana; Ibáñez, Raquel

2016-01-01

This field note presents the conclusions and recommendations made at the meeting 'How to reduce social inequalities in cancer screening programmes?' held at the XXVI School of Public Health of Mahon (Menorca, Spain). Participants developed recommendations based on experiences of population-based screening programmes (breast and colorectal) and opportunistic screening (cervical). The conclusions and recommendations focused on four main areas (information systems, evaluation and quality, research, and interventions): the inclusion of social variables at an individual level in health information systems; the establishment of minimum standards for gathering information regarding inequalities in access to preventive services; the performance of actions in vulnerable populations; and the promotion of the exchange of experiences and best practices through the Cancer Screening Programmes Network and working groups of the scientific societies. Copyright © 2016 SESPAS. Published by Elsevier Espana. All rights reserved.

TogoDoc server/client system: smart recommendation and efficient management of life science literature.

PubMed

Iwasaki, Wataru; Yamamoto, Yasunori; Takagi, Toshihisa

2010-12-13

In this paper, we describe a server/client literature management system specialized for the life science domain, the TogoDoc system (Togo, pronounced Toe-Go, is a romanization of a Japanese word for integration). The server and the client program cooperate closely over the Internet to provide life scientists with an effective literature recommendation service and efficient literature management. The content-based and personalized literature recommendation helps researchers to isolate interesting papers from the "tsunami" of literature, in which, on average, more than one biomedical paper is added to MEDLINE every minute. Because researchers these days need to cover updates of much wider topics to generate hypotheses using massive datasets obtained from public databases or omics experiments, the importance of having an effective literature recommendation service is rising. The automatic recommendation is based on the content of personal literature libraries of electronic PDF papers. The client program automatically analyzes these files, which are sometimes deeply buried in storage disks of researchers' personal computers. Just saving PDF papers to the designated folders makes the client program automatically analyze and retrieve metadata, rename file names, synchronize the data to the server, and receive the recommendation lists of newly published papers, thus accomplishing effortless literature management. In addition, the tag suggestion and associative search functions are provided for easy classification of and access to past papers (researchers who read many papers sometimes only vaguely remember or completely forget what they read in the past). The TogoDoc system is available for both Windows and Mac OS X and is free. The TogoDoc Client software is available at http://tdc.cb.k.u-tokyo.ac.jp/, and the TogoDoc server is available at https://docman.dbcls.jp/pubmed_recom.

TogoDoc Server/Client System: Smart Recommendation and Efficient Management of Life Science Literature

PubMed Central

Takagi, Toshihisa

2010-01-01

In this paper, we describe a server/client literature management system specialized for the life science domain, the TogoDoc system (Togo, pronounced Toe-Go, is a romanization of a Japanese word for integration). The server and the client program cooperate closely over the Internet to provide life scientists with an effective literature recommendation service and efficient literature management. The content-based and personalized literature recommendation helps researchers to isolate interesting papers from the “tsunami” of literature, in which, on average, more than one biomedical paper is added to MEDLINE every minute. Because researchers these days need to cover updates of much wider topics to generate hypotheses using massive datasets obtained from public databases or omics experiments, the importance of having an effective literature recommendation service is rising. The automatic recommendation is based on the content of personal literature libraries of electronic PDF papers. The client program automatically analyzes these files, which are sometimes deeply buried in storage disks of researchers' personal computers. Just saving PDF papers to the designated folders makes the client program automatically analyze and retrieve metadata, rename file names, synchronize the data to the server, and receive the recommendation lists of newly published papers, thus accomplishing effortless literature management. In addition, the tag suggestion and associative search functions are provided for easy classification of and access to past papers (researchers who read many papers sometimes only vaguely remember or completely forget what they read in the past). The TogoDoc system is available for both Windows and Mac OS X and is free. The TogoDoc Client software is available at http://tdc.cb.k.u-tokyo.ac.jp/, and the TogoDoc server is available at https://docman.dbcls.jp/pubmed_recom. PMID:21179453

An experimental maintenance management system.

DOT National Transportation Integrated Search

1979-01-01

The purpose of this study was to evaluate Virginia's maintenance management system and to recommend modifications directed at improving it. The study revealed that (1) the current system of allocating maintenance monies is based upon centerline milea...

Knowledge of influenza vaccination recommendation and early vaccination uptake during the 2015-16 season among adults aged ≥18years - United States.

PubMed

Lu, Peng-Jun; Srivastav, Anup; Santibanez, Tammy A; Christopher Stringer, M; Bostwick, Michael; Dever, Jill A; Stanley Kurtz, Marshica; Williams, Walter W

2017-08-03

Since 2010, the Advisory Committee on Immunization Practices (ACIP) has recommended that all persons aged ≥6months receive annual influenza vaccination. We analyzed data from the 2015 National Internet Flu Survey (NIFS), to assess knowledge and awareness of the influenza vaccination recommendation and early influenza vaccination coverage during the 2015-16 season among adults. Predictive marginals from a multivariable logistic regression model were used to identify factors independently associated with adults' knowledge and awareness of the vaccination recommendation and early vaccine uptake during the 2015-16 influenza season. Among the 3301 respondents aged ≥18years, 19.6% indicated knowing that influenza vaccination is recommended for all persons aged ≥6months. Of respondents, 62.3% indicated awareness that there was a recommendation for influenza vaccination, but did not indicate correct knowledge of the recommended age group. Overall, 39.9% of adults aged ≥18years reported having an influenza vaccination. Age 65years and older, being female, having a college or higher education, not being in work force, having annual household income ≥$75,000, reporting having received an influenza vaccination early in the 2015-16 season, having children aged ≤17years in the household, and having high-risk conditions were independently associated with a higher correct knowledge of the influenza vaccination recommendation. Approximately 1 in 5 had correct knowledge of the recommendation that all persons aged ≥6months should receive an influenza vaccination annually, with some socio-economic groups being even less aware. Clinic based education in combination with strategies known to increase uptake of recommended vaccines, such as patient reminder/recall systems and other healthcare system-based interventions are needed to improve vaccination, which could also improve awareness. Published by Elsevier Ltd.

Web-based counseling for problem gambling: exploring motivations and recommendations.

PubMed

Rodda, Simone; Lubman, Dan I; Dowling, Nicki A; Bough, Anna; Jackson, Alun C

2013-05-24

For highly stigmatized disorders, such as problem gambling, Web-based counseling has the potential to address common barriers to treatment, including issues of shame and stigma. Despite the exponential growth in the uptake of immediate synchronous Web-based counseling (ie, provided without appointment), little is known about why people choose this service over other modes of treatment. The aim of the current study was to determine motivations for choosing and recommending Web-based counseling over telephone or face-to-face services. The study involved 233 Australian participants who had completed an online counseling session for problem gambling on the Gambling Help Online website between November 2010 and February 2012. Participants were all classified as problem gamblers, with a greater proportion of males (57.4%) and 60.4% younger than 40 years of age. Participants completed open-ended questions about their reasons for choosing online counseling over other modes (ie, face-to-face and telephone), as well as reasons for recommending the service to others. A content analysis revealed 4 themes related to confidentiality/anonymity (reported by 27.0%), convenience/accessibility (50.9%), service system access (34.2%), and a preference for the therapeutic medium (26.6%). Few participants reported helpful professional support as a reason for accessing counseling online, but 43.2% of participants stated that this was a reason for recommending the service. Those older than 40 years were more likely than younger people in the sample to use Web-based counseling as an entry point into the service system (P=.045), whereas those engaged in nonstrategic gambling (eg, machine gambling) were more likely to access online counseling as an entry into the service system than those engaged in strategic gambling (ie, cards, sports; P=.01). Participants older than 40 years were more likely to recommend the service because of its potential for confidentiality and anonymity (P=.04), whereas those younger than 40 years were more likely to recommend the service due to it being helpful (P=.02). This study provides important information about why online counseling for gambling is attractive to people with problem gambling, thereby informing the development of targeted online programs, campaigns, and promotional material.

May I Suggest? Comparing Three PLE Recommender Strategies

ERIC Educational Resources Information Center

Modritscher, Felix; Krumay, Barbara; El Helou, Sandy; Gillet, Denis; Nussbaumer, Alexander; Albert, Dietrich; Dahn, Ingo; Ullrich, Carsten

2011-01-01

Personal learning environment (PLE) solutions aim at empowering learners to design (ICT and web-based) environments for their learning activities, mashing-up content and people and apps for different learning contexts. Widely used in other application areas, recommender systems can be very useful for supporting learners in their PLE-based…

Investigation of Learners' Perceptions for Video Summarization and Recommendation

ERIC Educational Resources Information Center

Yang, Jie Chi; Chen, Sherry Y.

2012-01-01

Recently, multimedia-based learning is widespread in educational settings. A number of studies investigate how to develop effective techniques to manage a huge volume of video sources, such as summarization and recommendation. However, few studies examine how these techniques affect learners' perceptions in multimedia learning systems. This…

System Data Bases In European Satellites Programs: Lessons Learned and Recommendations

NASA Astrophysics Data System (ADS)

Passot, X.; Denuault, D.; Guiral, Ph.; Kerjean, L.; Lebreton, D.; Lecrvain, C.; Valera, S.

2007-08-01

This paper is intended for European space eningeers who must design or interact with all or part of a system database, hereafter referred to as 'SDB'. The document presents the objectives of a system database (SDB), describes the development of an SDB project from the specification stage until operations, and preovides recommendations so that an effective system can be obtained. As part of return on experience, the document gives an overview of exisiting systems in the European space industry. To prepare the new systems, it presents the services to be provided, the tools available and the emerging standars towards which SDBs must converge.

Personalized recommendation based on preferential bidirectional mass diffusion

NASA Astrophysics Data System (ADS)

Chen, Guilin; Gao, Tianrun; Zhu, Xuzhen; Tian, Hui; Yang, Zhao

2017-03-01

Recommendation system provides a promising way to alleviate the dilemma of information overload. In physical dynamics, mass diffusion has been used to design effective recommendation algorithms on bipartite network. However, most of the previous studies focus overwhelmingly on unidirectional mass diffusion from collected objects to uncollected objects, while overlooking the opposite direction, leading to the risk of similarity estimation deviation and performance degradation. In addition, they are biased towards recommending popular objects which will not necessarily promote the accuracy but make the recommendation lack diversity and novelty that indeed contribute to the vitality of the system. To overcome the aforementioned disadvantages, we propose a preferential bidirectional mass diffusion (PBMD) algorithm by penalizing the weight of popular objects in bidirectional diffusion. Experiments are evaluated on three benchmark datasets (Movielens, Netflix and Amazon) by 10-fold cross validation, and results indicate that PBMD remarkably outperforms the mainstream methods in accuracy, diversity and novelty.

Adherence of preventive oral care products in the Syrian market to evidence-based international recommendations.

PubMed

Habes, D; Mahzia, R; Nakhleh, K; Joury, E

2016-09-25

No study has investigated the availability and adherence of preventive oral care products on the Syrian market to evidence-based international recommendations. Data were collected in 2012, and updated in 2016, in terms of availability, characteristics and adherence to evidence-based international recommendations. Few preventive products adhered to the recommendations. Despite the large decrease in the number of oral care products on the Syrian market, due to the Syrian crisis, nonadherence of some of the available products is still present. A multisectorial approach at a policy level is needed to address such important limitations. The Syrian Ministry of Health should reform regulations for fluoride products to become subject to drug monitoring systems; the Syrian Arab Committee for Measurements and Standards needs to update its standards; and the Syrian General Dental Association should distribute a preventive booklet to dental practitioners.

Do Nutrient-Based Front-of-Pack Labelling Schemes Support or Undermine Food-Based Dietary Guideline Recommendations? Lessons from the Australian Health Star Rating System.

PubMed

Lawrence, Mark A; Dickie, Sarah; Woods, Julie L

2018-01-05

Food-based Dietary Guidelines (FBDGs) promote healthy dietary patterns. Nutrient-based Front-of-Pack Labelling (NBFOPL) schemes rate the 'healthiness' of individual foods. This study aimed to investigate whether the Australian Health Star Rating (HSR) system aligns with the Australian Dietary Guidelines (ADGs). The Mintel Global New Products Database was searched for every new food product displaying a HSR entering the Australian marketplace from 27 June 2014 (HSR system endorsement) until 30 June 2017. Foods were categorised as either a five food group (FFG) food or 'discretionary' food in accordance with ADG recommendations. Ten percent (1269/12,108) of new food products displayed a HSR, of which 57% were FFG foods. The median number of 'health' stars displayed on discretionary foods (2.5; range: 0.5-5) was significantly lower ( p < 0.05) than FFG foods (4.0; range: 0.5-5), although a high frequency of anomalies and overlap in the number of stars across the two food categories was observed, with 56.7% of discretionary foods displaying ≥2.5 stars. The HSR system is undermining the ADG recommendations through facilitating the marketing of discretionary foods. Adjusting the HSR's algorithm might correct certain technical flaws. However, supporting the ADGs requires reform of the HSR's design to demarcate the food source (FFG versus discretionary food) of a nutrient.

Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments.

PubMed

Bakker, David; Kazantzis, Nikolaos; Rickwood, Debra; Rickard, Nikki

2016-03-01

The number of mental health apps (MHapps) developed and now available to smartphone users has increased in recent years. MHapps and other technology-based solutions have the potential to play an important part in the future of mental health care; however, there is no single guide for the development of evidence-based MHapps. Many currently available MHapps lack features that would greatly improve their functionality, or include features that are not optimized. Furthermore, MHapp developers rarely conduct or publish trial-based experimental validation of their apps. Indeed, a previous systematic review revealed a complete lack of trial-based evidence for many of the hundreds of MHapps available. To guide future MHapp development, a set of clear, practical, evidence-based recommendations is presented for MHapp developers to create better, more rigorous apps. A literature review was conducted, scrutinizing research across diverse fields, including mental health interventions, preventative health, mobile health, and mobile app design. Sixteen recommendations were formulated. Evidence for each recommendation is discussed, and guidance on how these recommendations might be integrated into the overall design of an MHapp is offered. Each recommendation is rated on the basis of the strength of associated evidence. It is important to design an MHapp using a behavioral plan and interactive framework that encourages the user to engage with the app; thus, it may not be possible to incorporate all 16 recommendations into a single MHapp. Randomized controlled trials are required to validate future MHapps and the principles upon which they are designed, and to further investigate the recommendations presented in this review. Effective MHapps are required to help prevent mental health problems and to ease the burden on health systems.

Mental Health Smartphone Apps: Review and Evidence-Based Recommendations for Future Developments

PubMed Central

Kazantzis, Nikolaos; Rickwood, Debra; Rickard, Nikki

2016-01-01

Background The number of mental health apps (MHapps) developed and now available to smartphone users has increased in recent years. MHapps and other technology-based solutions have the potential to play an important part in the future of mental health care; however, there is no single guide for the development of evidence-based MHapps. Many currently available MHapps lack features that would greatly improve their functionality, or include features that are not optimized. Furthermore, MHapp developers rarely conduct or publish trial-based experimental validation of their apps. Indeed, a previous systematic review revealed a complete lack of trial-based evidence for many of the hundreds of MHapps available. Objective To guide future MHapp development, a set of clear, practical, evidence-based recommendations is presented for MHapp developers to create better, more rigorous apps. Methods A literature review was conducted, scrutinizing research across diverse fields, including mental health interventions, preventative health, mobile health, and mobile app design. Results Sixteen recommendations were formulated. Evidence for each recommendation is discussed, and guidance on how these recommendations might be integrated into the overall design of an MHapp is offered. Each recommendation is rated on the basis of the strength of associated evidence. It is important to design an MHapp using a behavioral plan and interactive framework that encourages the user to engage with the app; thus, it may not be possible to incorporate all 16 recommendations into a single MHapp. Conclusions Randomized controlled trials are required to validate future MHapps and the principles upon which they are designed, and to further investigate the recommendations presented in this review. Effective MHapps are required to help prevent mental health problems and to ease the burden on health systems. PMID:26932350

Multipath/RFI/modulation study for DRSS-RFI problem: Voice coding and intelligibility testing for a satellite-based air traffic control system

NASA Technical Reports Server (NTRS)

Birch, J. N.; Getzin, N.

1971-01-01

Analog and digital voice coding techniques for application to an L-band satellite-basedair traffic control (ATC) system for over ocean deployment are examined. In addition to performance, the techniques are compared on the basis of cost, size, weight, power consumption, availability, reliability, and multiplexing features. Candidate systems are chosen on the bases of minimum required RF bandwidth and received carrier-to-noise density ratios. A detailed survey of automated and nonautomated intelligibility testing methods and devices is presented and comparisons given. Subjective evaluation of speech system by preference tests is considered. Conclusion and recommendations are developed regarding the selection of the voice system. Likewise, conclusions and recommendations are developed for the appropriate use of intelligibility tests, speech quality measurements, and preference tests with the framework of the proposed ATC system.

Final Research Report: Administrative and Legal Issues Associated with a Multi-State VMT-Based Charge System

DOT National Transportation Integrated Search

2010-11-01

In May 2009, the I-95 Coalition convened a workshop of experts to discuss how the Coalition could best contribute to the national dialogue regarding VMT-based charge systems. Following the recommendations of the National Surface Transportation Policy...

International and multidisciplinary expert recommendations for the use of biologics in systemic lupus erythematosus.

PubMed

Kleinmann, Jean-François; Tubach, Florence; Le Guern, Véronique; Mathian, Alexis; Richez, Christophe; Saadoun, David; Sacre, Karim; Sellam, Jérémie; Seror, Raphaèle; Amoura, Zahir; Andres, Emmanuel; Audia, Sylvain; Bader-Meunier, Brigitte; Blaison, Gilles; Bonnotte, Bernard; Cacoub, Patrice; Caillard, Sophie; Chiche, Laurent; Chosidow, Olivier; Costedoat-Chalumeau, Nathalie; Daien, Claire; Daugas, Eric; Derdèche, Nairouz; Doria, Andrea; Fain, Olivier; Fakhouri, Fadi; Farge, Dominique; Gabay, Cem; Guillo, Sylvie; Hachulla, Eric; Hajjaj-Hassouni, Najia; Hamidou, Mohamed; Houssiau, Frédéric A; Jourde-Chiche, Noémie; Koné-Paut, Isabelle; Ladjouz-Rezig, Aïcha; Lambotte, Olivier; Lipsker, Dan; Mariette, Xavier; Martin-Silva, Nicolas; Martin, Thierry; Maurier, François; Meckenstock, Roderich; Mékinian, Arsène; Meyer, Olivier; Mohamed, Shirine; Morel, Jacques; Moulin, Bruno; Mulleman, Denis; Papo, Thomas; Poindron, Vincent; Puéchal, Xavier; Punzi, Leonardo; Quartier, Pierre; Sailler, Laurent; Smail, Amar; Soubrier, Martin; Sparsa, Agnès; Tazi-Mezalek, Zoubida; Zakraoui, Leith; Zuily, Stéphane; Sibilia, Jean; Gottenberg, Jacques-Eric

2017-06-01

Despite conventional immunosuppressants, active and steroid-dependent systemic lupus erythematosus (SLE) represents a therapeutic challenge. Only one biologic, belimumab, has been approved, but other biologics are sometimes used off-label. Given the lack of evidence-based data in some clinical situations encountered in real life, we developed expert recommendations for the use of biologics for SLE. The recommendations were developed by a formal consensus method. This method aims to formalize the degree of agreement among experts by identifying, through iterative ratings with feedback, the points on which experts agree, disagree or are undecided. Hence, the recommendations are based on the agreed-upon points. We gathered the opinion of 59 French-speaking SLE experts from 3 clinical networks dedicated to systemic autoimmune diseases (FLEUR, IMIDIATE, FAI2R) from Algeria, Belgium, France, Italy, Morocco, Switzerland and Tunisia. Represented medical specialities were internal medicine (49%), rheumatology (34%), nephrology (7%), dermatology (5%), pediatrics (3%) and cardiology (2%). Two methodologists and 3 strictly independent SLE expert groups contributed to developing these recommendations: a steering group (SG) (n=9), an evaluation group (EG) (n=28) and a reading group (RG) (n=22). Preliminary recommendations were drafted by the SG, then proposed to the EG. Each EG member rated the degree of agreement from 1 to 9 (1: lowest; 9: strongest) for each recommendation. After 2 rating rounds, the SG submitted a new version of the recommendations to the RG. With comments from the RG, the SG finalised the recommendations. A total of 17 final recommendations were formulated by the SG, considering all agreement scores and comments by the EG and RG members and the two methodologists. These recommendations define the subset of patients who require a biologic; the type of biologics to use (belimumab, rituximab, etc.) depending on the organ involvement and associated co-treatments; what information should be given to patients; and how to evaluate treatment efficacy and when to consider discontinuation. Overall, 17 recommendations for the good use of biologics in SLE were formulated by a large panel of SLE experts to provide guidance for clinicians in daily practice. These recommendations will be regularly updated according to the results of new randomized trials and increasing real life experience. Copyright © 2017 Elsevier B.V. All rights reserved.

Developing a policy guidance for financing dental care in Iran using the RAND Appropriateness Method.

PubMed

Jadidfard, M P; Yazdani, S; Khoshnevisan, M H

2013-12-01

This study aimed to provide recommendations on health care financing with special emphasis on dental care. The RAND Appropriateness Method was employed to obtain the collective opinion of a multidisciplinary panel of experts on a set of recommendation statements regarding Iranian dental care financing. An initial set of recommendations were identified from a literature review. Panel members, selected purposively and by peer nomination, each rated the appropriateness and necessity of the recommendations in a structured process of two rounds. Each recommendation was classified as inappropriate, uncertain, appropriate but not necessary, or appropriate and necessary according to the median rating score and the level of disagreement among the panellists. Of 28 initial recommendations, 25 were agreed on as appropriate, of which 22 were considered as necessary. Altogether, these recommendations provide a holistic picture of an oral health system's financing in three domains: revenue collection, pooling of revenues and purchasing of dental services. The policy guidance recommendations are intended to provide the Iranian oral health authorities with an evidence-base for financing dental care. The recommendations may be transferrable, at least in part, particularly to developing countries with similar hybrid health system structures. Finally, the method used to develop the recommendations can serve as a model for use elsewhere.

Opinion-enhanced collaborative filtering for recommender systems through sentiment analysis

NASA Astrophysics Data System (ADS)

Wang, Wei; Wang, Hongwei

2015-10-01

The motivation of collaborative filtering (CF) comes from the idea that people often get the best recommendations from someone with similar tastes. With the growing popularity of opinion-rich resources such as online reviews, new opportunities arise as we can identify the preferences from user opinions. The main idea of our approach is to elicit user opinions from online reviews, and map such opinions into preferences that can be understood by CF-based recommender systems. We divide recommender systems into two types depending on the number of product category recommended: the multiple-category recommendation and the single-category recommendation. For the former, sentiment polarity in coarse-grained manner is identified while for the latter fine-grained sentiment analysis is conducted for each product aspect. If the evaluation frequency for an aspect by a user is greater than the average frequency by all users, it indicates that the user is more concerned with that aspect. If a user's rating for an aspect is lower than the average rating by all users, he or she is much pickier than others on that aspect. Through sentiment analysis, we then build an opinion-enhanced user preference model, where the higher the similarity between user opinions the more consistent preferences between users are. Experiment results show that the proposed CF algorithm outperforms baseline methods for product recommendation in terms of accuracy and recall.

Social Collaborative Filtering by Trust.

PubMed

Yang, Bo; Lei, Yu; Liu, Jiming; Li, Wenjie

2017-08-01

Recommender systems are used to accurately and actively provide users with potentially interesting information or services. Collaborative filtering is a widely adopted approach to recommendation, but sparse data and cold-start users are often barriers to providing high quality recommendations. To address such issues, we propose a novel method that works to improve the performance of collaborative filtering recommendations by integrating sparse rating data given by users and sparse social trust network among these same users. This is a model-based method that adopts matrix factorization technique that maps users into low-dimensional latent feature spaces in terms of their trust relationship, and aims to more accurately reflect the users reciprocal influence on the formation of their own opinions and to learn better preferential patterns of users for high-quality recommendations. We use four large-scale datasets to show that the proposed method performs much better, especially for cold start users, than state-of-the-art recommendation algorithms for social collaborative filtering based on trust.

Semen analysis with regard to sperm number, sperm morphology and functional aspects

PubMed Central

Eliasson, Rune

2010-01-01

The new World Health Organization (WHO) Manual for Semen Analysis contains several improvements. One is that the 20 million spermatozoa per mL paradigm has been ousted in favour of proper calculations of lower reference limits for semen from men, whose partners had a time-to-pregnancy of 12 months or less. The recommendation to grade the progressive motility as described in the third and fourth editions of the WHO manual was not evidence-based, and WHO was therefore motivated to abandon it. However, the new recommendation is not evidence-based either, and it is difficult to understand the rational for the new assessment. It may have been a compromise to avoid returning to the rather robust system recommended in the first edition (1980). The unconditional recommendation of the 'Tygerberg strict criteria' is not evidence-based, and seems to be the result of an unfortunate bias in the composition of the Committee in favour of individuals known to support the 'strict criteria' method. This recommendation will have negative effects on the development of andrology as a scientific field. Given the importance of the WHO manual, it is unfortunate that the recommendations for such important variables, as motility and morphology, lack evidence-based support. PMID:20111078

Variable Coded Modulation software simulation

NASA Astrophysics Data System (ADS)

Sielicki, Thomas A.; Hamkins, Jon; Thorsen, Denise

This paper reports on the design and performance of a new Variable Coded Modulation (VCM) system. This VCM system comprises eight of NASA's recommended codes from the Consultative Committee for Space Data Systems (CCSDS) standards, including four turbo and four AR4JA/C2 low-density parity-check codes, together with six modulations types (BPSK, QPSK, 8-PSK, 16-APSK, 32-APSK, 64-APSK). The signaling protocol for the transmission mode is based on a CCSDS recommendation. The coded modulation may be dynamically chosen, block to block, to optimize throughput.

Health issues for adolescents in the justice system.

PubMed

Soler, Mark

2002-12-01

Three major health issues for adolescents in the justice system are discussed: the lack of mental health resources and services for youth in the system, increased prosecution of juveniles as adults (and consequent incarceration of youth in adult jails and prisons), and the epidemic of gun violence in this country. For each issue, the paper describes the scope of the problem, analyzes the components of the problem, and makes recommendations for future research and reform efforts. The analysis and recommendations are based on criminal justice, legal, service integration, and public health research.

Implementation of Recommendations from the One System Comparative Evaluation of the Hanford Tank Farms and Waste Treatment Plant Safety Bases

DOE Office of Scientific and Technical Information (OSTI.GOV)

Garrett, Richard L.; Niemi, Belinda J.; Paik, Ingle K.

2013-11-07

A Comparative Evaluation was conducted for One System Integrated Project Team to compare the safety bases for the Hanford Waste Treatment and Immobilization Plant Project (WTP) and Tank Operations Contract (TOC) (i.e., Tank Farms) by an Expert Review Team. The evaluation had an overarching purpose to facilitate effective integration between WTP and TOC safety bases. It was to provide One System management with an objective evaluation of identified differences in safety basis process requirements, guidance, direction, procedures, and products (including safety controls, key safety basis inputs and assumptions, and consequence calculation methodologies) between WTP and TOC. The evaluation identified 25more » recommendations (Opportunities for Integration). The resolution of these recommendations resulted in 16 implementation plans. The completion of these implementation plans will help ensure consistent safety bases for WTP and TOC along with consistent safety basis processes. procedures, and analyses. and should increase the likelihood of a successful startup of the WTP. This early integration will result in long-term cost savings and significant operational improvements. In addition, the implementation plans lead to the development of eight new safety analysis methodologies that can be used at other U.S. Department of Energy (US DOE) complex sites where URS Corporation is involved.« less

TrustRank: a Cold-Start tolerant recommender system

NASA Astrophysics Data System (ADS)

Zou, Haitao; Gong, Zhiguo; Zhang, Nan; Zhao, Wei; Guo, Jingzhi

2015-02-01

The explosive growth of the World Wide Web leads to the fast advancing development of e-commerce techniques. Recommender systems, which use personalised information filtering techniques to generate a set of items suitable to a given user, have received considerable attention. User- and item-based algorithms are two popular techniques for the design of recommender systems. These two algorithms are known to have Cold-Start problems, i.e., they are unable to effectively handle Cold-Start users who have an extremely limited number of purchase records. In this paper, we develop TrustRank, a novel recommender system which handles the Cold-Start problem by leveraging the user-trust networks which are commonly available for e-commerce applications. A user-trust network is formed by friendships or trust relationships that users specify among them. While it is straightforward to conjecture that a user-trust network is helpful for improving the accuracy of recommendations, a key challenge for using user-trust network to facilitate Cold-Start users is that these users also tend to have a very limited number of trust relationships. To address this challenge, we propose a pre-processing propagation of the Cold-Start users' trust network. In particular, by applying the personalised PageRank algorithm, we expand the friends of a given user to include others with similar purchase records to his/her original friends. To make this propagation algorithm scalable to a large amount of users, as required by real-world recommender systems, we devise an iterative computation algorithm of the original personalised TrustRank which can incrementally compute trust vectors for Cold-Start users. We conduct extensive experiments to demonstrate the consistently improvement provided by our proposed algorithm over the existing recommender algorithms on the accuracy of recommendations for Cold-Start users.

World Health Organization strong recommendations based on low-quality evidence (study quality) are frequent and often inconsistent with GRADE guidance.

PubMed

Alexander, Paul E; Brito, Juan P; Neumann, Ignacio; Gionfriddo, Michael R; Bero, Lisa; Djulbegovic, Benjamin; Stoltzfus, Rebecca; Montori, Victor M; Norris, Susan L; Schünemann, Holger J; Guyatt, Gordon H

2016-04-01

In 2007 the World Health Organization (WHO) adopted the GRADE system for development of public health guidelines. Previously we found that many strong recommendations issued by WHO are based on evidence for which there is only low or very low confidence in the estimates of effect (discordant recommendations). GRADE guidance indicates that such discordant recommendations are rarely appropriate but suggests five paradigmatic situations in which discordant recommendations may be warranted. We sought to provide insight into the many discordant recommendations in WHO guidelines. We examined all guidelines that used the GRADE method and were approved by the WHO Guideline Review Committee between 2007 and 2012. Teams of reviewers independently abstracted data from eligible guidelines and classified recommendations either into one of the five paradigms for appropriately-formulated discordant recommendations or into three additional categories in which discordant recommendations were inconsistent with GRADE guidance: 1) the evidence warranted moderate or high confidence (a misclassification of evidence) rather than low or very low confidence; 2) good practice statements; or 3) uncertainty in the estimates of effect would best lead to a conditional (weak) recommendation. The 33 eligible guidelines included 160 discordant recommendations, of which 98 (61.3%) addressed drug interventions and 132 (82.5%) provided some rationale (though not entirely explicit at times) for the strong recommendation. Of 160 discordant recommendations, 25 (15.6%) were judged consistent with one of the five paradigms for appropriate recommendations; 33 (21%) were based on evidence warranting moderate or high confidence in the estimates of effect; 29 (18%) were good practice statements; and 73 (46%) warranted a conditional, rather than a strong recommendation. WHO discordant recommendations are often inconsistent with GRADE guidance, possibly threatening the integrity of the process. Further training in GRADE methods for WHO guideline development group members may be necessary, along with further research on what motivates the formulation of such recommendations. Copyright © 2016 Elsevier Inc. All rights reserved.

Probiotics for gastrointestinal disorders: Proposed recommendations for children of the Asia-Pacific region.

PubMed

Cameron, Donald; Hock, Quak Seng; Kadim, Musal; Mohan, Neelam; Ryoo, Eell; Sandhu, Bhupinder; Yamashiro, Yuichiro; Jie, Chen; Hoekstra, Hans; Guarino, Alfredo

2017-12-07

Recommendations for probiotics are available in several regions. This paper proposes recommendations for probiotics in pediatric gastrointestinal diseases in the Asia-Pacific region. Epidemiology and clinical patterns of intestinal diseases in Asia-Pacific countries were discussed. Evidence-based recommendations and randomized controlled trials in the region were revised. Cultural aspects, health management issues and economic factors were also considered. Final recommendations were approved by applying the Likert scale and rated using the GRADE system. Saccharomyces boulardii CNCM I-745 (Sb) and Lactobacillus rhamnosus GG ( LGG ) were strongly recommended as adjunct treatment to oral rehydration therapy for gastroenteritis. Lactobacillus reuteri could also be considered. Probiotics may be considered for prevention of (with the indicated strains): antibiotic-associated diarrhea (LGG or Sb); Clostridium difficile -induced diarrhea (Sb); nosocomial diarrhea (LGG); infantile colic ( L reuteri ) and as adjunct treatment of Helicobacter pylori (Sb and others). Specific probiotics with a history of safe use in preterm and term infants may be considered in infants for prevention of necrotizing enterocolitis. There is insufficient evidence for recommendations in other conditions. Despite a diversity of epidemiological, socioeconomical and health system conditions, similar recommendations apply well to Asia pacific countries. These need to be validated with local randomized-controlled trials.

Beyond Earth's boundaries: Human exploration of the Solar System in the 21st Century

NASA Technical Reports Server (NTRS)

1991-01-01

This is an annual report describing work accomplished in developing the knowledge base that will permit informed recommendations and decisions concerning national space policy and the goal of human expansion into the solar system. The following topics are presented: (1) pathways to human exploration; (2) human exploration case studies; (3) case study results and assessment; (4) exploration program implementation strategy; (5) approach to international cooperation; (6) recommendations; and (7) future horizons.

Pre-Pregnancy Body Mass Index, Gestational Weight Gain, and Birth Weight: A Cohort Study in China.

PubMed

Yang, Shaoping; Peng, Anna; Wei, Sheng; Wu, Jing; Zhao, Jinzhu; Zhang, Yiming; Wang, Jing; Lu, Yuan; Yu, Yuzhen; Zhang, Bin

2015-01-01

To assess whether pre-pregnancy body mass index (BMI) modify the relationship between gestational weight gain (GWG) and child birth weight (specifically, presence or absence of low birth weight (LBW) or presence of absence of macrosomia), and estimates of the relative risk of macrosomia and LBW based on pre-pregnancy BMI were controlled in Wuhan, China. From June 30, 2011 to June 30, 2013. All data was collected and available from the perinatal health care system. Logistic regression models were used to estimate the independent association among pregnancy weight gain, LBW, normal birth weight, and macrosomia within different pre-pregnancy BMI groups. We built different logistic models for the 2009 Institute of Medicine (IOM) Guidelines and Chinese-recommended GWG which was made from this sample. The Chinese-recommended GWG was derived from the quartile values (25th-75th percentiles) of weight gain at the time of delivery in the subjects which comprised our sample. For LBW children, using the recommended weight gain of the IOM and Chinese women as a reference, the OR for a pregnancy weight gain below recommendations resulted in a positive relationship for lean and normal weight women, but not for overweight and obese women. For macrosomia, considering the IOM's recommended weight gain as a reference, the OR magnitude for pregnancy weight gain above recommendations resulted in a positive correlation for all women. The OR for a pregnancy weight gain below recommendations resulted in a negative relationship for normal BMI and lean women, but not for overweight and obese women based on the IOM recommendations, significant based on the recommended pregnancy weight gain for Chinese women. Of normal weight children, 56.6% were above the GWG based on IOM recommendations, but 26.97% of normal weight children were above the GWG based on Chinese recommendations. A GWG above IOM recommendations might not be helpful for Chinese women. We need unified criteria to classify adult BMI and to expand the sample size to improve representation and to elucidate the relationship between GWG and related outcomes for developing a Chinese GWG recommendation.

Pre-Pregnancy Body Mass Index, Gestational Weight Gain, and Birth Weight: A Cohort Study in China

PubMed Central

Wei, Sheng; Wu, Jing; Zhao, Jinzhu; Zhang, Yiming; Wang, Jing; Lu, Yuan; Yu, Yuzhen; Zhang, Bin

2015-01-01

Objective To assess whether pre-pregnancy body mass index (BMI) modify the relationship between gestational weight gain (GWG) and child birth weight (specifically, presence or absence of low birth weight (LBW) or presence of absence of macrosomia), and estimates of the relative risk of macrosomia and LBW based on pre-pregnancy BMI were controlled in Wuhan, China. Methods From June 30, 2011 to June 30, 2013. All data was collected and available from the perinatal health care system. Logistic regression models were used to estimate the independent association among pregnancy weight gain, LBW, normal birth weight, and macrosomia within different pre-pregnancy BMI groups. We built different logistic models for the 2009 Institute of Medicine (IOM) Guidelines and Chinese-recommended GWG which was made from this sample. The Chinese-recommended GWG was derived from the quartile values (25th-75th percentiles) of weight gain at the time of delivery in the subjects which comprised our sample. Results For LBW children, using the recommended weight gain of the IOM and Chinese women as a reference, the OR for a pregnancy weight gain below recommendations resulted in a positive relationship for lean and normal weight women, but not for overweight and obese women. For macrosomia, considering the IOM’s recommended weight gain as a reference, the OR magnitude for pregnancy weight gain above recommendations resulted in a positive correlation for all women. The OR for a pregnancy weight gain below recommendations resulted in a negative relationship for normal BMI and lean women, but not for overweight and obese women based on the IOM recommendations, significant based on the recommended pregnancy weight gain for Chinese women. Of normal weight children, 56.6% were above the GWG based on IOM recommendations, but 26.97% of normal weight children were above the GWG based on Chinese recommendations. Conclusions A GWG above IOM recommendations might not be helpful for Chinese women. We need unified criteria to classify adult BMI and to expand the sample size to improve representation and to elucidate the relationship between GWG and related outcomes for developing a Chinese GWG recommendation. PMID:26115015

DEMO: Action Recommendation for Cyber Resilience

DOE Office of Scientific and Technical Information (OSTI.GOV)

Rodriguez, Luke R.; Curtis, Darren S.; Choudhury, Sutanay

In this demonstration we show the usefulness of our unifying graph-based model for the representation of infrastructure, behavior, and missions of cyber enterprise in both a software simulation and on an Amazon Web Services (AWS) instance. We show the effectiveness of our recommendation algorithm for preserving various system health metrics in both cases.

Report of the AD HOC Committee on Patent Documentation.

ERIC Educational Resources Information Center

Urbach, Peter; And Others

The Committee was established in September 1967 to study and make recommendations on Recommendation XXIX and XXX of the Report of the President's Commission on the Patent System. Based on interviews with Patent Office officials, patent examiners and classifiers and a review of Patent Office studies and documents, the Committee concluded that the…

78 FR 31560 - Medicare Program; Public Meeting in Calendar Year 2013 for New Clinical Laboratory Test Payment...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-05-24

... announces a public meeting to receive comments and recommendations (including accompanying data on which recommendations are based) from the public on the appropriate basis for establishing payment amounts for new or substantially revised Healthcare Common Procedure Coding System (HCPCS) codes being considered for Medicare...

Information Flow Analysis of Level 4 Payload Processing Operations

NASA Technical Reports Server (NTRS)

Danz, Mary E.

1991-01-01

The Level 4 Mission Sequence Test (MST) was studied to develop strategies and recommendations to facilitate information flow. Recommendations developed as a result of this study include revised format of the Test and Assembly Procedure (TAP) document and a conceptualized software based system to assist in the management of information flow during the MST.

SER consensus statement on the use of biologic therapy for systemic lupus erythematosus.

PubMed

Calvo-Alén, Jaime; Silva-Fernández, Lucía; Úcar-Angulo, Eduardo; Pego-Reigosa, José María; Olivé, Alejandro; Martínez-Fernández, Carmen; Martínez-Taboada, Víctor; Luis Marenco, José; Loza, Estíbaliz; López-Longo, Javier; Gómez-Reino, Juan Jesús; Galindo-Izquierdo, María; Fernández-Nebro, Antonio; Cuadrado, María José; Aguirre-Zamorano, María Ángeles; Zea-Mendoza, Antonio; Rúa-Figueroa, Iñigo

2013-01-01

To provide a reference to rheumatologists and other physicians involved in the treatment of systemic lupus erythematosus (SLE) who are using, or about to use biologic therapies. Recommendations were developed following a nominal group methodology and based on systematic reviews. The level of evidence and degree of recommendation were classified according to a model proposed by the Center for Evidence Based Medicine at Oxford. The level of agreement was established through a Delphi technique. We have produced recommendations on the use of belimumab, the only biological agent with approved indications for SLE, and other biological agents without an indication for SLE. The objective of treatment is to achieve a complete clinical response, taken as the absence of perceived or evident disease activity. Nuances regarding the use of biologic therapies in SLE were reviewed as well, such as the evaluation that should be performed prior to administration and the follow up of patients undergoing these therapies. We present the SER recommendations for the use of biological therapies in patients with SLE. Copyright © 2013 Elsevier España, S.L. All rights reserved.

How updating textual clinical practice guidelines impacts clinical decision support systems: a case study with bladder cancer management.

PubMed

Bouaud, Jacques; Séroussi, Brigitte; Brizon, Ambre; Culty, Thibault; Mentré, France; Ravery, Vincent

2007-01-01

Guideline-based clinical decision support systems (CDSSs) can be effective in increasing physician compliance with recommendations. However, the ever growing pace at which medical knowledge is produced requires that clinical practice guidelines (CPGs) be updated regularly. It is therefore mandatory that CDSSs be revised accordingly. The French Association for Urology publishes CPGs on bladder cancer management every 2 years. We studied the impact of the 2004 revision of these guidelines, with respect to the 2002 version with a CDSS, UroDoc. We proposed a typology of knowledge base modifications resulting from the update of CPGs making the difference between practice, clinical conditions and recommendations refinement as opposed to new practice and new recommendations. The number of formalized recommendations increased from 577 in 2002 to 1,081 in 2004. We evaluated the two versions of UroDoc on a randomized sample of patient records. A single new practice that modifies a decision taken in 49% of all recorded decisions leads to a fall from 67% to 46% of the compliance rate of decisions.

Mining drug-disease relationships as a complement to medical genetics-based drug repositioning: Where a recommendation system meets genome-wide association studies.

PubMed

Wang, H; Gu, Q; Wei, J; Cao, Z; Liu, Q

2015-05-01

A novel recommendation-based drug repositioning strategy is presented to simultaneously determine novel drug indications and side effects in one integrated framework. This strategy provides a complementary method to medical genetics-based drug repositioning, which reduces the occurrence of false positives in medical genetics-based drug repositioning, resulting in a ranked list of new candidate indications and/or side effects with different confidence levels. Several new drug indications and side effects are reported with high prediction confidences. © 2015 American Society for Clinical Pharmacology and Therapeutics.

Recommendations Service for Chronic Disease Patient in Multimodel Sensors Home Environment

PubMed Central

Hussain, Maqbool; Ali, Taqdir; Khan, Wajahat Ali; Afzal, Muhammad; Latif, Khalid

2015-01-01

Abstract With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC3). SC3 services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC3 platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms. PMID:25559934

Recommendations service for chronic disease patient in multimodel sensors home environment.

PubMed

Hussain, Maqbool; Ali, Taqdir; Khan, Wajahat Ali; Afzal, Muhammad; Lee, Sungyoung; Latif, Khalid

2015-03-01

With advanced technologies in hand, there exist potential applications and services built around monitoring activities of daily living (ADL) of elderly people at nursing homes. Most of the elderly people in these facilities are suffering from different chronic diseases such as dementia. Existing technologies are mainly focusing on non-medication interventions and monitoring of ADL for addressing loss of autonomy or well-being. Monitoring and managing ADL related to cognitive behaviors for non-medication intervention are very effective in improving dementia patients' conditions. However, cognitive functions of patients can be improved if appropriate recommendations of medications are delivered at a particular time. Previously we developed the Secured Wireless Sensor Network Integrated Cloud Computing for Ubiquitous-Life Care (SC(3)). SC(3) services were limited to monitoring ADL of elderly people with Alzheimer's disease and providing non-medication recommendations to the patient. In this article, we propose a system called the Smart Clinical Decision Support System (CDSS) as an integral part of the SC(3) platform. Using the Smart CDSS, patients are provided with access to medication recommendations of expert physicians. Physicians are provided with an interface to create clinical knowledge for medication recommendations and to observe the patient's condition. The clinical knowledge created by physicians as the knowledge base of the Smart CDSS produces recommendations to the caregiver for medications based on each patient's symptoms.

Acceptability and effectiveness of a web-based psychosocial intervention among criminal justice involved adults.

PubMed

Lee, J D; Tofighi, B; McDonald, R; Campbell, A; Hu, M C; Nunes, E

2017-12-01

The acceptability, feasibility and effectiveness of web-based interventions among criminal justice involved populations are understudied. This study is a secondary analysis of baseline characteristics associated with criminal justice system (CJS) status as treatment outcome moderators among participants enrolling in a large randomized trial of a web-based psychosocial intervention (Therapeutic Education System [TES]) as part of outpatient addiction treatment. We compared demographic and clinical characteristics, TES participation rates, and the trial's two co-primary outcomes, end of treatment abstinence and treatment retention, by self-reported CJS status at baseline: 1) CJS-mandated to community treatment (CJS-mandated), 2) CJS-recommended to treatment (CJS-recommended), 3) no CJS treatment mandate (CJS-none). CJS-mandated (n = 107) and CJS-recommended (n = 69) participants differed from CJS-none (n = 331) at baseline: CJS-mandated were significantly more likely to be male, uninsured, report cannabis as the primary drug problem, report fewer days of drug use at baseline, screen negative for depression, and score lower for psychological distress and higher on physical health status; CJS-recommended were younger, more likely single, less likely to report no regular Internet use, and to report cannabis as the primary drug problem. Both CJS-involved (CJS -recommended and -mandated) groups were more likely to have been recently incarcerated. Among participants randomized to the TES arm, module completion was similar across the CJS subgroups. A three-way interaction of treatment, baseline abstinence and CJS status showed no associations with the study's primary abstinence outcome. Overall, CJS-involved participants in this study tended to be young, male, and in treatment for a primary cannabis problem. The feasibility and effectiveness of the web-based psychosocial intervention, TES, did not vary by CJS-mandated or CJS-recommended participants compared to CJS-none. Web-based counseling interventions may be effective interventions as US public safety policies begin to emphasize supervised community drug treatment over incarceration.

Factors Influencing the Effectiveness of Systems Engineering Training and Education in the Department of Defense

DTIC Science & Technology

2011-04-30

learning. Recommendations are also presented for additional research into a more effective systems engineering andragogy . 15. SUBJECT TERMS 16...into a more effective systems engineering andragogy . Purpose Competency-based training for defense acquisition workers in the systems engineering

Neonatal physical therapy. Part II: Practice frameworks and evidence-based practice guidelines.

PubMed

Sweeney, Jane K; Heriza, Carolyn B; Blanchard, Yvette; Dusing, Stacey C

2010-01-01

(1) To outline frameworks for neonatal physical therapy based on 3 theoretical models, (2) to describe emerging literature supporting neonatal physical therapy practice, and (3) to identify evidence-based practice recommendations. Three models are presented as a framework for neonatal practice: (1) dynamic systems theory including synactive theory and the theory of neuronal group selection, (2) the International Classification of Functioning, Disability and Health, and (3) family-centered care. Literature is summarized to support neonatal physical therapists in the areas of examination, developmental care, intervention, and parent education. Practice recommendations are offered with levels of evidence identified. Neonatal physical therapy practice has a theoretical and evidence-based structure, and evidence is emerging for selected clinical procedures. Continued research to expand the science of neonatal physical therapy is critical to elevate the evidence and support practice recommendations.

Improving Access and Systems of Care for Evidence-Based Childhood Obesity Treatment: Conference Key Findings and Next Steps

PubMed Central

Wilfley, Denise E.; Staiano, Amanda E.; Altman, Myra; Lindros, Jeanne; Lima, Angela; Hassink, Sandra G.; Dietz, William H.; Cook, Stephen

2017-01-01

Objectives To improve systems of care to advance implementation of the U.S. Preventive Services Task Force recommendations for childhood obesity treatment (i.e. clinicians offer/refer children with obesity to intensive, multicomponent behavioral interventions of >25 hours over 6–12 months to improve weight status) and to expand payment for these services. Methods In July 2015, forty-three cross-sector stakeholders attended a conference supported by the Agency for Healthcare Research and Quality, American Academy of Pediatrics Institute for Healthy Childhood Weight, and The Obesity Society. Plenary sessions presenting scientific evidence and clinical and payment practices were interspersed with breakout sessions to identify consensus recommendations. Results Consensus recommendations for childhood obesity treatment included: family-based multicomponent behavioral therapy; integrated care model; and multi-disciplinary care team. The use of evidence-based protocols, a well-trained healthcare team, medical oversight, and treatment at or above the minimum dose (e.g. >25 hours) are critical components to ensure effective delivery of high-quality care and to achieve clinically meaningful weight loss. Approaches to secure reimbursement for evidence-based obesity treatment within payment models were recommended. Conclusion Continued cross-sector collaboration is crucial to ensure a unified approach to increase payment and access for childhood obesity treatment and to scale-up training to ensure quality of care. PMID:27925451

Improving access and systems of care for evidence-based childhood obesity treatment: Conference key findings and next steps.

PubMed

Wilfley, Denise E; Staiano, Amanda E; Altman, Myra; Lindros, Jeanne; Lima, Angela; Hassink, Sandra G; Dietz, William H; Cook, Stephen

2017-01-01

To improve systems of care to advance implementation of the U.S. Preventive Services Task Force recommendations for childhood obesity treatment (i.e., clinicians offer/refer children with obesity to intensive, multicomponent behavioral interventions of >25 h over 6 to 12 months to improve weight status) and to expand payment for these services. In July 2015, 43 cross-sector stakeholders attended a conference supported by the Agency for Healthcare Research and Quality, American Academy of Pediatrics Institute for Healthy Childhood Weight, and The Obesity Society. Plenary sessions presenting scientific evidence and clinical and payment practices were interspersed with breakout sessions to identify consensus recommendations. Consensus recommendations for childhood obesity treatment included: family-based multicomponent behavioral therapy; integrated care model; and multidisciplinary care team. The use of evidence-based protocols, a well-trained healthcare team, medical oversight, and treatment at or above the minimum dose (e.g., >25 h) are critical components to ensure effective delivery of high-quality care and to achieve clinically meaningful weight loss. Approaches to secure reimbursement for evidence-based obesity treatment within payment models were recommended. Continued cross-sector collaboration is crucial to ensure a unified approach to increase payment and access for childhood obesity treatment and to scale up training to ensure quality of care. © 2016 The Obesity Society.

Design implications for task-specific search utilities for retrieval and re-engineering of code

NASA Astrophysics Data System (ADS)

Iqbal, Rahat; Grzywaczewski, Adam; Halloran, John; Doctor, Faiyaz; Iqbal, Kashif

2017-05-01

The importance of information retrieval systems is unquestionable in the modern society and both individuals as well as enterprises recognise the benefits of being able to find information effectively. Current code-focused information retrieval systems such as Google Code Search, Codeplex or Koders produce results based on specific keywords. However, these systems do not take into account developers' context such as development language, technology framework, goal of the project, project complexity and developer's domain expertise. They also impose additional cognitive burden on users in switching between different interfaces and clicking through to find the relevant code. Hence, they are not used by software developers. In this paper, we discuss how software engineers interact with information and general-purpose information retrieval systems (e.g. Google, Yahoo!) and investigate to what extent domain-specific search and recommendation utilities can be developed in order to support their work-related activities. In order to investigate this, we conducted a user study and found that software engineers followed many identifiable and repeatable work tasks and behaviours. These behaviours can be used to develop implicit relevance feedback-based systems based on the observed retention actions. Moreover, we discuss the implications for the development of task-specific search and collaborative recommendation utilities embedded with the Google standard search engine and Microsoft IntelliSense for retrieval and re-engineering of code. Based on implicit relevance feedback, we have implemented a prototype of the proposed collaborative recommendation system, which was evaluated in a controlled environment simulating the real-world situation of professional software engineers. The evaluation has achieved promising initial results on the precision and recall performance of the system.

Intelligent system for topic survey in MEDLINE by keyword recommendation and learning text characteristics.

PubMed

Tanaka, M; Nakazono, S; Matsuno, H; Tsujimoto, H; Kitamura, Y; Miyano, S

2000-01-01

We have implemented a system for assisting experts in selecting MEDLINE records for database construction purposes. This system has two specific features: The first is a learning mechanism which extracts characteristics in the abstracts of MEDLINE records of interest as patterns. These patterns reflect selection decisions by experts and are used for screening the records. The second is a keyword recommendation system which assists and supplements experts' knowledge in unexpected cases. Combined with a conventional keyword-based information retrieval system, this system may provide an efficient and comfortable environment for MEDLINE record selection by experts. Some computational experiments are provided to prove that this idea is useful.

Moving research tools into practice: the successes and challenges in promoting uptake of classification tools.

PubMed

Cunningham, Barbara Jane; Hidecker, Mary Jo Cooley; Thomas-Stonell, Nancy; Rosenbaum, Peter

2018-05-01

In this paper, we present our experiences - both successes and challenges - in implementing evidence-based classification tools into clinical practice. We also make recommendations for others wanting to promote the uptake and application of new research-based assessment tools. We first describe classification systems and the benefits of using them in both research and practice. We then present a theoretical framework from Implementation Science to report strategies we have used to implement two research-based classification tools into practice. We also illustrate some of the challenges we have encountered by reporting results from an online survey investigating 58 Speech-language Pathologists' knowledge and use of the Communication Function Classification System (CFCS), a new tool to classify children's functional communication skills. We offer recommendations for researchers wanting to promote the uptake of new tools in clinical practice. Specifically, we identify structural, organizational, innovation, practitioner, and patient-related factors that we recommend researchers address in the design of implementation interventions. Roles and responsibilities of both researchers and clinicians in making implementations science a success are presented. Implications for rehabilitation Promoting uptake of new and evidence-based tools into clinical practice is challenging. Implementation science can help researchers to close the knowledge-to-practice gap. Using concrete examples, we discuss our experiences in implementing evidence-based classification tools into practice within a theoretical framework. Recommendations are provided for researchers wanting to implement new tools in clinical practice. Implications for researchers and clinicians are presented.

A personalized health-monitoring system for elderly by combining rules and case-based reasoning.

PubMed

Ahmed, Mobyen Uddin

2015-01-01

Health-monitoring system for elderly in home environment is a promising solution to provide efficient medical services that increasingly interest by the researchers within this area. It is often more challenging when the system is self-served and functioning as personalized provision. This paper proposed a personalized self-served health-monitoring system for elderly in home environment by combining general rules with a case-based reasoning approach. Here, the system generates feedback, recommendation and alarm in a personalized manner based on elderly's medical information and health parameters such as blood pressure, blood glucose, weight, activity, pulse, etc. A set of general rules has used to classify individual health parameters. The case-based reasoning approach is used to combine all different health parameters, which generates an overall classification of health condition. According to the evaluation result considering 323 cases and k=2 i.e., top 2 most similar retrieved cases, the sensitivity, specificity and overall accuracy are achieved as 90%, 97% and 96% respectively. The preliminary result of the system is acceptable since the feedback; recommendation and alarm messages are personalized and differ from the general messages. Thus, this approach could be possibly adapted for other situations in personalized elderly monitoring.

Which Doctor to Trust: A Recommender System for Identifying the Right Doctors.

PubMed

Guo, Li; Jin, Bo; Yao, Cuili; Yang, Haoyu; Huang, Degen; Wang, Fei

2016-07-07

Key opinion leaders (KOLs) are people who can influence public opinion on a certain subject matter. In the field of medical and health informatics, it is critical to identify KOLs on various disease conditions. However, there have been very few studies on this topic. We aimed to develop a recommender system for identifying KOLs for any specific disease with health care data mining. We exploited an unsupervised aggregation approach for integrating various ranking features to identify doctors who have the potential to be KOLs on a range of diseases. We introduce the design, implementation, and deployment details of the recommender system. This system collects the professional footprints of doctors, such as papers in scientific journals, presentation activities, patient advocacy, and media exposure, and uses them as ranking features to identify KOLs. We collected the information of 2,381,750 doctors in China from 3,657,797 medical journal papers they published, together with their profiles, academic publications, and funding. The empirical results demonstrated that our system outperformed several benchmark systems by a significant margin. Moreover, we conducted a case study in a real-world system to verify the applicability of our proposed method. Our results show that doctors' profiles and their academic publications are key data sources for identifying KOLs in the field of medical and health informatics. Moreover, we deployed the recommender system and applied the data service to a recommender system of the China-based Internet technology company NetEase. Patients can obtain authority ranking lists of doctors with this system on any given disease.

Which Doctor to Trust: A Recommender System for Identifying the Right Doctors

PubMed Central

Yao, Cuili; Yang, Haoyu; Huang, Degen; Wang, Fei

2016-01-01

Background Key opinion leaders (KOLs) are people who can influence public opinion on a certain subject matter. In the field of medical and health informatics, it is critical to identify KOLs on various disease conditions. However, there have been very few studies on this topic. Objective We aimed to develop a recommender system for identifying KOLs for any specific disease with health care data mining. Methods We exploited an unsupervised aggregation approach for integrating various ranking features to identify doctors who have the potential to be KOLs on a range of diseases. We introduce the design, implementation, and deployment details of the recommender system. This system collects the professional footprints of doctors, such as papers in scientific journals, presentation activities, patient advocacy, and media exposure, and uses them as ranking features to identify KOLs. Results We collected the information of 2,381,750 doctors in China from 3,657,797 medical journal papers they published, together with their profiles, academic publications, and funding. The empirical results demonstrated that our system outperformed several benchmark systems by a significant margin. Moreover, we conducted a case study in a real-world system to verify the applicability of our proposed method. Conclusions Our results show that doctors’ profiles and their academic publications are key data sources for identifying KOLs in the field of medical and health informatics. Moreover, we deployed the recommender system and applied the data service to a recommender system of the China-based Internet technology company NetEase. Patients can obtain authority ranking lists of doctors with this system on any given disease. PMID:27390219

Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems.

PubMed

Yin, Yuyu; Yu, Fangzheng; Xu, Yueshen; Yu, Lifeng; Mu, Jinglong

2017-09-08

Cyber-physical systems (CPS) have received much attention from both academia and industry. An increasing number of functions in CPS are provided in the way of services, which gives rise to an urgent task, that is, how to recommend the suitable services in a huge number of available services in CPS. In traditional service recommendation, collaborative filtering (CF) has been studied in academia, and used in industry. However, there exist several defects that limit the application of CF-based methods in CPS. One is that under the case of high data sparsity, CF-based methods are likely to generate inaccurate prediction results. In this paper, we discover that mining the potential similarity relations among users or services in CPS is really helpful to improve the prediction accuracy. Besides, most of traditional CF-based methods are only capable of using the service invocation records, but ignore the context information, such as network location, which is a typical context in CPS. In this paper, we propose a novel service recommendation method for CPS, which utilizes network location as context information and contains three prediction models using random walking. We conduct sufficient experiments on two real-world datasets, and the results demonstrate the effectiveness of our proposed methods and verify that the network location is indeed useful in QoS prediction.

Implementation of recommended trauma system criteria in south-eastern Norway: a cross-sectional hospital survey.

PubMed

Kristiansen, Thomas; Ringdal, Kjetil G; Skotheimsvik, Tarjei; Salthammer, Halvor K; Gaarder, Christine; Naess, Pål A; Lossius, Hans M

2012-01-26

Formalized trauma systems have shown beneficial effects on patient survival and have harvested great recognition among health care professionals. In spite of this, the implementation of trauma systems is challenging and often met with resistance.Recommendations for a national trauma system in Norway were published in 2007. We wanted to assess the level of implementation of these recommendations. A survey of all acute care hospitals that receive severely injured patients in the south-eastern health region of Norway was conducted. A structured questionnaire based on the 2007 national recommendations was used in a telephone interview of hospital trauma personnel between January 17 and 21, 2011. Seventeen trauma system criteria were identified from the recommendations. Nineteen hospitals were included in the study and these received more than 2000 trauma patients annually via their trauma teams. Out of the 17 criteria that had been identified, the hospitals fulfilled a median of 12 criteria. Neither the size of the hospitals nor the distance between the hospitals and the regional trauma centre affected the level of trauma resources available. The hospitals scored lowest on the criteria for transfer of patients to higher level of care and on the training requirements for members of the trauma teams. Our study identifies a major shortcoming in the efforts of regionalizing trauma in our region. The findings indicate that training of personnel and protocols for inter-hospital transfer are the major deficiencies from the national trauma system recommendations. Resources for training of personnel partaking in trauma teams and development of inter-hospital transfer agreements should receive immediate attention.

Space shuttle Ku-band integrated rendezvous radar/communications system study

NASA Technical Reports Server (NTRS)

1976-01-01

The results are presented of work performed on the Space Shuttle Ku-Band Integrated Rendezvous Radar/Communications System Study. The recommendations and conclusions are included as well as the details explaining the results. The requirements upon which the study was based are presented along with the predicted performance of the recommended system configuration. In addition, shuttle orbiter vehicle constraints (e.g., size, weight, power, stowage space) are discussed. The tradeoffs considered and the operation of the recommended configuration are described for an optimized, integrated Ku-band radar/communications system. Basic system tradeoffs, communication design, radar design, antenna tradeoffs, antenna gimbal and drive design, antenna servo design, and deployed assembly packaging design are discussed. The communications and radar performance analyses necessary to support the system design effort are presented. Detailed derivations of the communications thermal noise error, the radar range, range rate, and angle tracking errors, and the communications transmitter distortion parameter effect on crosstalk between the unbalanced quadriphase signals are included.

Development of sensors for ceramic components in advanced propulsion systems: Survey and evaluation of measurement techniques for temperature, strain and heat flux for ceramic components in advanced propulsion systems

NASA Technical Reports Server (NTRS)

Atkinson, W. H.; Cyr, M. A.; Strange, R. R.

1988-01-01

The report presents the final results of Tasks 1 and 2, Development of Sensors for Ceramic Components in Advanced Propulsion Systems (NASA program NAS3-25141). During Task 1, an extensive survey was conducted of sensor concepts which have the potential for measuring surface temperature, strain and heat flux on ceramic components for advanced propulsion systems. Each sensor concept was analyzed and evaluated under Task 2; sensor concepts were then recommended for further development. For temperature measurement, both pyrometry and thermographic phosphors are recommended for measurements up to and beyond the melting point of ceramic materials. For lower temperature test programs, the thin-film techniques offer advantages in the installation of temperature sensors. Optical strain measurement techniques are recommended because they offer the possibility of being useful at very high temperature levels. Techniques for the measurement of heat flux are recommended for development based on both a surface mounted sensor and the measurement of the temperature differential across a portion of a ceramic component or metallic substrate.

Uncovering the essential links in online commercial networks

NASA Astrophysics Data System (ADS)

Zeng, Wei; Fang, Meiling; Shao, Junming; Shang, Mingsheng

2016-09-01

Recommender systems are designed to effectively support individuals' decision-making process on various web sites. It can be naturally represented by a user-object bipartite network, where a link indicates that a user has collected an object. Recently, research on the information backbone has attracted researchers' interests, which is a sub-network with fewer nodes and links but carrying most of the relevant information. With the backbone, a system can generate satisfactory recommenda- tions while saving much computing resource. In this paper, we propose an enhanced topology-aware method to extract the information backbone in the bipartite network mainly based on the information of neighboring users and objects. Our backbone extraction method enables the recommender systems achieve more than 90% of the accuracy of the top-L recommendation, however, consuming only 20% links. The experimental results show that our method outperforms the alternative backbone extraction methods. Moreover, the structure of the information backbone is studied in detail. Finally, we highlight that the information backbone is one of the most important properties of the bipartite network, with which one can significantly improve the efficiency of the recommender system.

Improving Vision-Based Motor Rehabilitation Interactive Systems for Users with Disabilities Using Mirror Feedback

PubMed Central

Martínez-Bueso, Pau; Moyà-Alcover, Biel

2014-01-01

Observation is recommended in motor rehabilitation. For this reason, the aim of this study was to experimentally test the feasibility and benefit of including mirror feedback in vision-based rehabilitation systems: we projected the user on the screen. We conducted a user study by using a previously evaluated system that improved the balance and postural control of adults with cerebral palsy. We used a within-subjects design with the two defined feedback conditions (mirror and no-mirror) with two different groups of users (8 with disabilities and 32 without disabilities) using usability measures (time-to-start (T s) and time-to-complete (T c)). A two-tailed paired samples t-test confirmed that in case of disabilities the mirror feedback facilitated the interaction in vision-based systems for rehabilitation. The measured times were significantly worse in the absence of the user's own visual feedback (T s = 7.09 (P < 0.001) and T c = 4.48 (P < 0.005)). In vision-based interaction systems, the input device is the user's own body; therefore, it makes sense that feedback should be related to the body of the user. In case of disabilities the mirror feedback mechanisms facilitated the interaction in vision-based systems for rehabilitation. Results recommends developers and researchers use this improvement in vision-based motor rehabilitation interactive systems. PMID:25295310

A System-Level Approach to Overweight and Obesity in the Veterans Health Administration.

PubMed

Raffa, Susan D; Maciejewski, Matthew L; Zimmerman, Lindsey E; Damschroder, Laura J; Estabrooks, Paul A; Ackermann, Ronald T; Tsai, Adam G; Histon, Trina; Goldstein, Michael G

2017-04-01

Healthcare systems are challenged by steady increases in the number of patients who are overweight and obese. Large-scale, evidence-based behavioral approaches for addressing overweight and obesity have been successfully implemented in systems such as the Veterans Health Administration (VHA). These population-based interventions target reduction in risk for obesity-associated conditions through lifestyle change and weight loss, and are associated with modest weight loss. Despite the fact that VHA has increased the overall reach of these behavioral interventions, the number of high-risk overweight and obese patients continues to rise. Recommendations for weight loss medications and bariatric surgery are included in clinical practice guidelines for the management of overweight and obesity, but these interventions are underutilized. During a recent state of the art conference on weight management held by VHA, subject matter experts identified challenges and gaps, as well as potential solutions and overarching policy recommendations, for implementing an integrated system-wide approach for improving population-based weight management.

Autism Spectrum Disorder: consensus guidelines on assessment, treatment and research from the British Association for Psychopharmacology

PubMed Central

Howes, Oliver D; Charman, Tony; King, Bryan H.; Loth, Eva; McAlonan, Gráinne M.; McCracken, James T.; Parr, Jeremy R; Santosh, Paramala; Wallace, Simon; Murphy, Declan G.

2018-01-01

An expert review of the aetiology, assessment, and treatment of autism spectrum disorder (ASD), and recommendations for diagnosis, management and service provision was coordinated by the British Association for Psychopharmacology, and evidence graded. The aetiology of ASD involves genetic and environmental contributions, and implicates a number of brain systems, in particular the gamma-aminobutyric acid (GABA), serotonergic and glutamatergic systems. The presentation of ASD varies widely and co-occurring health problems (in particular epilepsy, sleep disorders, anxiety, depression, attention deficit/hyperactivity disorder (ADHD), and irritability) are common. We did not recommend the routine use of any pharmacological treatment for the core symptoms of ASD. In children, melatonin may be useful to treat sleep problems, dopamine blockers for irritability, and methylphenidate, atomoxetine and guanfacine for ADHD. The evidence for use of medication in adults is limited and recommendations are largely based on extrapolations from studies in children and patients without ASD. We discuss the conditions for considering and evaluating a trial of medication treatment, when non-pharmacological interventions should be considered, and make recommendations on service delivery. Finally, we identify key gaps and limitations in the current evidence base and make recommendations for future research and the design of clinical trials. PMID:29237331

Autism spectrum disorder: Consensus guidelines on assessment, treatment and research from the British Association for Psychopharmacology.

PubMed

Howes, Oliver D; Rogdaki, Maria; Findon, James L; Wichers, Robert H; Charman, Tony; King, Bryan H; Loth, Eva; McAlonan, Gráinne M; McCracken, James T; Parr, Jeremy R; Povey, Carol; Santosh, Paramala; Wallace, Simon; Simonoff, Emily; Murphy, Declan G

2018-01-01

An expert review of the aetiology, assessment, and treatment of autism spectrum disorder, and recommendations for diagnosis, management and service provision was coordinated by the British Association for Psychopharmacology, and evidence graded. The aetiology of autism spectrum disorder involves genetic and environmental contributions, and implicates a number of brain systems, in particular the gamma-aminobutyric acid, serotonergic and glutamatergic systems. The presentation of autism spectrum disorder varies widely and co-occurring health problems (in particular epilepsy, sleep disorders, anxiety, depression, attention deficit/hyperactivity disorder and irritability) are common. We did not recommend the routine use of any pharmacological treatment for the core symptoms of autism spectrum disorder. In children, melatonin may be useful to treat sleep problems, dopamine blockers for irritability, and methylphenidate, atomoxetine and guanfacine for attention deficit/hyperactivity disorder. The evidence for use of medication in adults is limited and recommendations are largely based on extrapolations from studies in children and patients without autism spectrum disorder. We discuss the conditions for considering and evaluating a trial of medication treatment, when non-pharmacological interventions should be considered, and make recommendations on service delivery. Finally, we identify key gaps and limitations in the current evidence base and make recommendations for future research and the design of clinical trials.

Tailoring implementation strategies for evidence-based recommendations using computerised clinical decision support systems: protocol for the development of the GUIDES tools.

PubMed

Van de Velde, Stijn; Roshanov, Pavel; Kortteisto, Tiina; Kunnamo, Ilkka; Aertgeerts, Bert; Vandvik, Per Olav; Flottorp, Signe

2016-03-05

A computerised clinical decision support system (CCDSS) is a technology that uses patient-specific data to provide relevant medical knowledge at the point of care. It is considered to be an important quality improvement intervention, and the implementation of CCDSS is growing substantially. However, the significant investments do not consistently result in value for money due to content, context, system and implementation issues. The Guideline Implementation with Decision Support (GUIDES) project aims to improve the impact of CCDSS through optimised implementation based on high-quality evidence-based recommendations. To achieve this, we will develop tools that address the factors that determine successful CCDSS implementation. We will develop the GUIDES tools in four steps, using the methods and results of the Tailored Implementation for Chronic Diseases (TICD) project as a starting point: (1) a review of research evidence and frameworks on the determinants of implementing recommendations using CCDSS; (2) a synthesis of a comprehensive framework for the identified determinants; (3) the development of tools for use of the framework and (4) pilot testing the utility of the tools through the development of a tailored CCDSS intervention in Norway, Belgium and Finland. We selected the conservative management of knee osteoarthritis as a prototype condition for the pilot. During the process, the authors will collaborate with an international expert group to provide input and feedback on the tools. This project will provide guidance and tools on methods of identifying implementation determinants and selecting strategies to implement evidence-based recommendations through CCDSS. We will make the GUIDES tools available to CCDSS developers, implementers, researchers, funders, clinicians, managers, educators, and policymakers internationally. The tools and recommendations will be generic, which makes them scalable to a large spectrum of conditions. Ultimately, the better implementation of CCDSS may lead to better-informed decisions and improved care and patient outcomes for a wide range of conditions. PROSPERO, CRD42016033738.

Municipal water-based heat pump heating and/or cooling systems: Findings and recommendations. Final report

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bloomquist, R.G.; Wegman, S.

1998-04-01

The purpose of the present work was to determine if existing heat pump systems based on municipal water systems meet existing water quality standards, to analyze water that has passed through a heat pump or heat exchanger to determine if corrosion products can be detected, to determine residual chlorine levels in municipal waters on the inlet as well as the outlet side of such installations, to analyses for bacterial contaminants and/or regrowth due to the presence of a heat pump or heat exchanger, to develop and suggest criteria for system design and construction, to provide recommendations and specifications for materialmore » and fluid selection, and to develop model rules and regulations for the installation, operation, and monitoring of new and existing systems. In addition, the Washington State University (WSU) has evaluated availability of computer models that would allow for water system mapping, water quality modeling and system operation.« less

Controlled Ecological Life Support System: Research and Development Guidelines

NASA Technical Reports Server (NTRS)

Mason, R. M. (Editor); Carden, J. L. (Editor)

1982-01-01

Results of a workshop designed to provide a base for initiating a program of research and development of controlled ecological life support systems (CELSS) are summarized. Included are an evaluation of a ground based manned demonstration as a milestone in CELSS development, and a discussion of development requirements for a successful ground based CELSS demonstration. Research recommendations are presented concerning the following topics: nutrition and food processing, food production, waste processing, systems engineering and modelling, and ecology-systems safety.

Development of sensor-based nitrogen recommendation algorithms for cereal crops

NASA Astrophysics Data System (ADS)

Asebedo, Antonio Ray

Nitrogen (N) management is one of the most recognizable components of farming both within and outside the world of agriculture. Interest over the past decade has greatly increased in improving N management systems in corn (Zea mays) and winter wheat (Triticum aestivum ) to have high NUE, high yield, and be environmentally sustainable. Nine winter wheat experiments were conducted across seven locations from 2011 through 2013. The objectives of this study were to evaluate the impacts of fall-winter, Feekes 4, Feekes 7, and Feekes 9 N applications on winter wheat grain yield, grain protein, and total grain N uptake. Nitrogen treatments were applied as single or split applications in the fall-winter, and top-dressed in the spring at Feekes 4, Feekes 7, and Feekes 9 with applied N rates ranging from 0 to 134 kg ha-1. Results indicate that Feekes 7 and 9 N applications provide more optimal combinations of grain yield, grain protein levels, and fertilizer N recovered in the grain when compared to comparable rates of N applied in the fall-winter or at Feekes 4. Winter wheat N management studies from 2006 through 2013 were utilized to develop sensor-based N recommendation algorithms for winter wheat in Kansas. Algorithm RosieKat v.2.6 was designed for multiple N application strategies and utilized N reference strips for establishing N response potential. Algorithm NRS v1.5 addressed single top-dress N applications and does not require a N reference strip. In 2013, field validations of both algorithms were conducted at eight locations across Kansas. Results show algorithm RK v2.6 consistently provided highly efficient N recommendations for improving NUE, while achieving high grain yield and grain protein. Without the use of the N reference strip, NRS v1.5 performed statistically equal to the KSU soil test N recommendation in regards to grain yield but with lower applied N rates. Six corn N fertigation experiments were conducted at KSU irrigated experiment fields from 2012 through 2014 to evaluate the previously developed KSU sensor-based N recommendation algorithm in corn N fertigation systems. Results indicate that the current KSU corn algorithm was effective at achieving high yields, but has the tendency to overestimate N requirements. To optimize sensor-based N recommendations for N fertigation systems, algorithms must be specifically designed for these systems to take advantage of their full capabilities, thus allowing implementation of high NUE N management systems.

Quality in the Basic Grant Delivery System: Volume 2, Corrective Actions.

ERIC Educational Resources Information Center

Advanced Technology, Inc., McLean, VA.

Alternative management procedures are recommended that may lower the rate and magnitude of errors in the award of the Basic Educational Opportunity Grants (BEOGs), or Pell Grants. The recommendations are part of the BEOG quality control project and are based on a review of current (1980-1981) levels, distribution, and significance of error in the…

STS-61 mission director's post-mission report

NASA Technical Reports Server (NTRS)

Newman, Ronald L.

1995-01-01

To ensure the success of the complex Hubble Space Telescope servicing mission, STS-61, NASA established a number of independent review groups to assess management, design, planning, and preparation for the mission. One of the resulting recommendations for mission success was that an overall Mission Director be appointed to coordinate management activities of the Space Shuttle and Hubble programs and to consolidate results of the team reviews and expedite responses to recommendations. This report presents pre-mission events important to the experience base of mission management, with related Mission Director's recommendations following the event(s) to which they apply. All Mission Director's recommendations are presented collectively in an appendix. Other appendixes contain recommendations from the various review groups, including Payload Officers, the JSC Extravehicular Activity (EVA) Section, JSC EVA Management Office, JSC Crew and Thermal Systems Division, and the STS-61 crew itself. This report also lists mission events in chronological order and includes as an appendix a post-mission summary by the lead Payload Deployment and Retrieval System Officer. Recommendations range from those pertaining to specific component use or operating techniques to those for improved management, review, planning, and safety procedures.

Advanced endoscopic imaging: European Society of Gastrointestinal Endoscopy (ESGE) Technology Review.

PubMed

East, James E; Vleugels, Jasper L; Roelandt, Philip; Bhandari, Pradeep; Bisschops, Raf; Dekker, Evelien; Hassan, Cesare; Horgan, Gareth; Kiesslich, Ralf; Longcroft-Wheaton, Gaius; Wilson, Ana; Dumonceau, Jean-Marc

2016-11-01

Background and aim: This technical review is an official statement of the European Society of Gastrointestinal Endoscopy (ESGE). It addresses the utilization of advanced endoscopic imaging in gastrointestinal (GI) endoscopy. Methods: This technical review is based on a systematic literature search to evaluate the evidence supporting the use of advanced endoscopic imaging throughout the GI tract. Technologies considered include narrowed-spectrum endoscopy (narrow band imaging [NBI]; flexible spectral imaging color enhancement [FICE]; i-Scan digital contrast [I-SCAN]), autofluorescence imaging (AFI), and confocal laser endomicroscopy (CLE). The Grading of Recommendations Assessment, Development and Evaluation (GRADE) system was adopted to define the strength of recommendation and the quality of evidence. Main recommendations: 1. We suggest advanced endoscopic imaging technologies improve mucosal visualization and enhance fine structural and microvascular detail. Expert endoscopic diagnosis may be improved by advanced imaging, but as yet in community-based practice no technology has been shown consistently to be diagnostically superior to current practice with high definition white light. (Low quality evidence.) 2. We recommend the use of validated classification systems to support the use of optical diagnosis with advanced endoscopic imaging in the upper and lower GI tracts (strong recommendation, moderate quality evidence). 3. We suggest that training improves performance in the use of advanced endoscopic imaging techniques and that it is a prerequisite for use in clinical practice. A learning curve exists and training alone does not guarantee sustained high performances in clinical practice. (Weak recommendation, low quality evidence.) Conclusion: Advanced endoscopic imaging can improve mucosal visualization and endoscopic diagnosis; however it requires training and the use of validated classification systems. © Georg Thieme Verlag KG Stuttgart · New York.

Applicability of the BCLC staging system to patients with hepatocellular carcinoma in Korea: analysis at a single center with a liver transplant center.

PubMed

Kim, Sung Eun; Lee, Han Chu; Kim, Kang Mo; Lim, Young-Suk; Chung, Young-Hwa; Lee, Yung Sang; Suh, Dong Jin

2011-06-01

The Barcelona Clinic Liver Cancer (BCLC) staging system is logical for the staging and treatment of hepatocellular carcinoma (HCC) because it was based on survival data. This study evaluated the applicability of the BCLC staging system and reasons for divergence from BCLC-recommended treatments in Korean HCC patients. One hundred and sixty consecutive HCC patients were prospectively enrolled. Treatments were generally recommended according to the guideline of the American Association for the Study of Liver Diseases, but patients were also informed about alternative treatments. The final decision was made with patient agreement, and was based on the doctor's preferences when a patient was unable to reach a decision. There were 2 (1%), 101 (64%), 20 (12.5%), 34 (21.5%), and 3 (1%) patients with very early-, early-, intermediate-, advanced-, and terminal-stage disease, respectively. Only 64 patients (40%) were treated according to BCLC recommendations. The treatment deviated from BCLC recommendations in 68% (69/101) and 79% (27/34) of patients with early and advanced stage, respectively. The main causes of deviation were refusal to undergo surgery, the presence of an indeterminate malignancy nodule, the absence of a suitable donor, or financial problems. Donor shortage, financial problems, the relatively limited efficacy of molecular targeting agents, and the presence of an indeterminate nodule were the main causes of deviation from BCLC recommendations. Even after excluding cases in which decisions were made by patient preference, only 66% of the HCC patients were treated according to BCLC recommendations. Treatment guidelines that reflect the Korean situation are mandatory for HCC patients.

Recommendation Techniques for Drug-Target Interaction Prediction and Drug Repositioning.

PubMed

Alaimo, Salvatore; Giugno, Rosalba; Pulvirenti, Alfredo

2016-01-01

The usage of computational methods in drug discovery is a common practice. More recently, by exploiting the wealth of biological knowledge bases, a novel approach called drug repositioning has raised. Several computational methods are available, and these try to make a high-level integration of all the knowledge in order to discover unknown mechanisms. In this chapter, we review drug-target interaction prediction methods based on a recommendation system. We also give some extensions which go beyond the bipartite network case.

Personalized professional content recommendation

DOEpatents

Xu, Songhua

2015-10-27

A personalized content recommendation system includes a client interface configured to automatically monitor a user's information data stream transmitted on the Internet. A hybrid contextual behavioral and collaborative personal interest inference engine resident to a non-transient media generates automatic predictions about the interests of individual users of the system. A database server retains the user's personal interest profile based on a plurality of monitored information. The system also includes a server programmed to filter items in an incoming information stream with the personal interest profile and is further programmed to identify only those items of the incoming information stream that substantially match the personal interest profile.

Evidence and consensus based guideline for the management of delirium, analgesia, and sedation in intensive care medicine. Revision 2015 (DAS-Guideline 2015) - short version.

PubMed

Baron, Ralf; Binder, Andreas; Biniek, Rolf; Braune, Stephan; Buerkle, Hartmut; Dall, Peter; Demirakca, Sueha; Eckardt, Rahel; Eggers, Verena; Eichler, Ingolf; Fietze, Ingo; Freys, Stephan; Fründ, Andreas; Garten, Lars; Gohrbandt, Bernhard; Harth, Irene; Hartl, Wolfgang; Heppner, Hans-Jürgen; Horter, Johannes; Huth, Ralf; Janssens, Uwe; Jungk, Christine; Kaeuper, Kristin Maria; Kessler, Paul; Kleinschmidt, Stefan; Kochanek, Matthias; Kumpf, Matthias; Meiser, Andreas; Mueller, Anika; Orth, Maritta; Putensen, Christian; Roth, Bernd; Schaefer, Michael; Schaefers, Rainhild; Schellongowski, Peter; Schindler, Monika; Schmitt, Reinhard; Scholz, Jens; Schroeder, Stefan; Schwarzmann, Gerhard; Spies, Claudia; Stingele, Robert; Tonner, Peter; Trieschmann, Uwe; Tryba, Michael; Wappler, Frank; Waydhas, Christian; Weiss, Bjoern; Weisshaar, Guido

2015-01-01

In 2010, under the guidance of the DGAI (German Society of Anaesthesiology and Intensive Care Medicine) and DIVI (German Interdisciplinary Association for Intensive Care and Emergency Medicine), twelve German medical societies published the "Evidence- and Consensus-based Guidelines on the Management of Analgesia, Sedation and Delirium in Intensive Care". Since then, several new studies and publications have considerably increased the body of evidence, including the new recommendations from the American College of Critical Care Medicine (ACCM) in conjunction with Society of Critical Care Medicine (SCCM) and American Society of Health-System Pharmacists (ASHP) from 2013. For this update, a major restructuring and extension of the guidelines were needed in order to cover new aspects of treatment, such as sleep and anxiety management. The literature was systematically searched and evaluated using the criteria of the Oxford Center of Evidence Based Medicine. The body of evidence used to formulate these recommendations was reviewed and approved by representatives of 17 national societies. Three grades of recommendation were used as follows: Grade "A" (strong recommendation), Grade "B" (recommendation) and Grade "0" (open recommendation). The result is a comprehensive, interdisciplinary, evidence and consensus-based set of level 3 guidelines. This publication was designed for all ICU professionals, and takes into account all critically ill patient populations. It represents a guide to symptom-oriented prevention, diagnosis, and treatment of delirium, anxiety, stress, and protocol-based analgesia, sedation, and sleep-management in intensive care medicine.

Preparing for an epidemic: cancer care in an aging population.

PubMed

Shih, Ya-Chen Tina; Hurria, Arti

2014-01-01

The Institute of Medicine's (IOM) Committee on Improving the Quality of Cancer Care: Addressing the Challenges of an Aging Population was charged with evaluating and proposing recommendations on how to improve the quality of cancer care, with a specific focus on the aging population. Based on their findings, the IOM committee recently released a report highlighting their 10 recommendations for improving the quality of cancer care. Based on those recommendations, this article highlights ways to improve evidence-based care and addresses rising costs in health care for older adults with cancer. The IOM highlighted three recommendations to address the current research gaps in providing evidence-based care in older adults with cancer, which included (1) studying populations which match the age and health-risk profile of the population with the disease, (2) legislative incentives for companies to include patients that are older or with multiple morbidities in new cancer drug trials, and (3) expansion of research that contributes to the depth and breadth of data available for assessing interventions. The recommendations also highlighted the need to maintain affordable and accessible care for older adults with cancer, with an emphasis on finding creative solutions within both the care delivery system and payment models in order to balance costs while preserving quality of care. The implementation of the IOM's recommendations will be a key step in moving closer to the goal of providing accessible, affordable, evidence-based, high-quality care to all patients with cancer.

Web-Based Counseling for Problem Gambling: Exploring Motivations and Recommendations

PubMed Central

Lubman, Dan I; Dowling, Nicki A; Bough, Anna; Jackson, Alun C

2013-01-01

Background For highly stigmatized disorders, such as problem gambling, Web-based counseling has the potential to address common barriers to treatment, including issues of shame and stigma. Despite the exponential growth in the uptake of immediate synchronous Web-based counseling (ie, provided without appointment), little is known about why people choose this service over other modes of treatment. Objective The aim of the current study was to determine motivations for choosing and recommending Web-based counseling over telephone or face-to-face services. Methods The study involved 233 Australian participants who had completed an online counseling session for problem gambling on the Gambling Help Online website between November 2010 and February 2012. Participants were all classified as problem gamblers, with a greater proportion of males (57.4%) and 60.4% younger than 40 years of age. Participants completed open-ended questions about their reasons for choosing online counseling over other modes (ie, face-to-face and telephone), as well as reasons for recommending the service to others. Results A content analysis revealed 4 themes related to confidentiality/anonymity (reported by 27.0%), convenience/accessibility (50.9%), service system access (34.2%), and a preference for the therapeutic medium (26.6%). Few participants reported helpful professional support as a reason for accessing counseling online, but 43.2% of participants stated that this was a reason for recommending the service. Those older than 40 years were more likely than younger people in the sample to use Web-based counseling as an entry point into the service system (P=.045), whereas those engaged in nonstrategic gambling (eg, machine gambling) were more likely to access online counseling as an entry into the service system than those engaged in strategic gambling (ie, cards, sports; P=.01). Participants older than 40 years were more likely to recommend the service because of its potential for confidentiality and anonymity (P=.04), whereas those younger than 40 years were more likely to recommend the service due to it being helpful (P=.02). Conclusions This study provides important information about why online counseling for gambling is attractive to people with problem gambling, thereby informing the development of targeted online programs, campaigns, and promotional material. PMID:23709155

Practice Guideline Recommendations on Perioperative Fasting: A Systematic Review.

PubMed

Lambert, Eva; Carey, Sharon

2016-11-01

Traditionally, perioperative fasting consisted of being nil by mouth (NBM) from midnight before surgery and fasting postoperatively until recovery of bowel function. These outdated practices persist despite emerging evidence revealing that excessive fasting results in negative outcomes and delayed recovery. Various evidence-based, multimodal, enhanced recovery protocols incorporating minimized perioperative fasting have arisen to improve patient outcomes and streamline recovery, but implementation remains limited. This article aims to review current fasting guidelines, assess their quality, summarize relevant recommendations, and identify gaps in evidence. A systematic literature search of Medline and CINAHL and a manual search of relevant websites identified guidelines containing suitable grading systems and fasting recommendations. Guideline quality was assessed using the Appraisal of Guidelines Research and Evaluation (AGREE) tool. Grading systems were standardized to the American Society for Parenteral and Enteral Nutrition format and recommendations summarized based on grading and guideline quality. Nineteen guidelines were included. Rigor of development scores ranged from 29%-95%, with only 8 guidelines explicitly declaring the use of systematic methodology. Applicability scores were lowest, averaging 32%. Ten recommendation types were extracted and summarized. Strong and consistent evidence exists for the minimization of perioperative fasting, for a 2-hour preoperative fast after clear fluids, and for early recommencement of oral food and fluid intake postoperatively. This article presents several high-level recommendations ready for immediate implementation, while poorly graded and inconsistent recommendations reveal key areas for future research. Meanwhile, guideline quality requires improvement, especially regarding rigor of development and applicability, through systematic methodology, reporting transparency, and implementation strategies. © 2015 American Society for Parenteral and Enteral Nutrition.

Accident/Mishap Investigation System

NASA Technical Reports Server (NTRS)

Keller, Richard; Wolfe, Shawn; Gawdiak, Yuri; Carvalho, Robert; Panontin, Tina; Williams, James; Sturken, Ian

2007-01-01

InvestigationOrganizer (IO) is a Web-based collaborative information system that integrates the generic functionality of a database, a document repository, a semantic hypermedia browser, and a rule-based inference system with specialized modeling and visualization functionality to support accident/mishap investigation teams. This accessible, online structure is designed to support investigators by allowing them to make explicit, shared, and meaningful links among evidence, causal models, findings, and recommendations.

Walking on a user similarity network towards personalized recommendations.

PubMed

Gan, Mingxin

2014-01-01

Personalized recommender systems have been receiving more and more attention in addressing the serious problem of information overload accompanying the rapid evolution of the world-wide-web. Although traditional collaborative filtering approaches based on similarities between users have achieved remarkable success, it has been shown that the existence of popular objects may adversely influence the correct scoring of candidate objects, which lead to unreasonable recommendation results. Meanwhile, recent advances have demonstrated that approaches based on diffusion and random walk processes exhibit superior performance over collaborative filtering methods in both the recommendation accuracy and diversity. Building on these results, we adopt three strategies (power-law adjustment, nearest neighbor, and threshold filtration) to adjust a user similarity network from user similarity scores calculated on historical data, and then propose a random walk with restart model on the constructed network to achieve personalized recommendations. We perform cross-validation experiments on two real data sets (MovieLens and Netflix) and compare the performance of our method against the existing state-of-the-art methods. Results show that our method outperforms existing methods in not only recommendation accuracy and diversity, but also retrieval performance.

International recommendations for national patient safety incident reporting systems: an expert Delphi consensus-building process.

PubMed

Howell, Ann-Marie; Burns, Elaine M; Hull, Louise; Mayer, Erik; Sevdalis, Nick; Darzi, Ara

2017-02-01

Patient safety incident reporting systems (PSRS) have been established for over a decade, but uncertainty remains regarding the role that they can and ought to play in quantifying healthcare-related harm and improving care. To establish international, expert consensus on the purpose of PSRS regarding monitoring and learning from incidents and developing recommendations for their future role. After a scoping review of the literature, semi-structured interviews with experts in PSRS were conducted. Based on these findings, a survey-based questionnaire was developed and subsequently completed by a larger expert panel. Using a Delphi approach, consensus was reached regarding the ideal role of PSRSs. Recommendations for best practice were devised. Forty recommendations emerged from the Delphi procedure on the role and use of PSRS. Experts agreed reporting system should not be used as an epidemiological tool to monitor the rate of harm over time or to appraise the relative safety of hospitals. They agreed reporting is a valuable mechanism for identifying organisational safety needs. The benefit of a national system was clear with respect to medication error, device failures, hospital-acquired infections and never events as these problems often require solutions at a national level. Experts recommended training for senior healthcare professionals in incident investigation. Consensus recommendation was for hospitals to take responsibility for creating safety solutions locally that could be shared nationally. We obtained reasonable consensus among experts on aims and specifications of PSRS. This information can be used to reflect on existing and future PSRS, and their role within the wider patient safety landscape. The role of PSRS as instruments for learning needs to be elaborated and developed further internationally. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Towards an agent based traffic regulation and recommendation system for the on-road air quality control.

PubMed

Sadiq, Abderrahmane; El Fazziki, Abdelaziz; Ouarzazi, Jamal; Sadgal, Mohamed

2016-01-01

This paper presents an integrated and adaptive problem-solving approach to control the on-road air quality by modeling the road infrastructure, managing traffic based on pollution level and generating recommendations for road users. The aim is to reduce vehicle emissions in the most polluted road segments and optimizing the pollution levels. For this we propose the use of historical and real time pollution records and contextual data to calculate the air quality index on road networks and generate recommendations for reassigning traffic flow in order to improve the on-road air quality. The resulting air quality indexes are used in the system's traffic network generation, which the cartography is represented by a weighted graph. The weights evolve according to the pollution indexes and path properties and the graph is therefore dynamic. Furthermore, the systems use the available pollution data and meteorological records in order to predict the on-road pollutant levels by using an artificial neural network based prediction model. The proposed approach combines the benefits of multi-agent systems, Big data technology, machine learning tools and the available data sources. For the shortest path searching in the road network, we use the Dijkstra algorithm over Hadoop MapReduce framework. The use Hadoop framework in the data retrieve and analysis process has significantly improved the performance of the proposed system. Also, the agent technology allowed proposing a suitable solution in terms of robustness and agility.

Cellular Automata-Based Application for Driver Assistance in Indoor Parking Areas.

PubMed

Caballero-Gil, Cándido; Caballero-Gil, Pino; Molina-Gil, Jezabel

2016-11-15

This work proposes an adaptive recommendation mechanism for smart parking that takes advantage of the popularity of smartphones and the rise of the Internet of Things. The proposal includes a centralized system to forecast available indoor parking spaces, and a low-cost mobile application to obtain data of actual and predicted parking occupancy. The described scheme uses data from both sources bidirectionally so that the centralized forecast system is fed with data obtained with the distributed system based on smartphones, and vice versa. The mobile application uses different wireless technologies to provide the forecast system with actual parking data and receive from the system useful recommendations about where to park. Thus, the proposal can be used by any driver to easily find available parking spaces in indoor facilities. The client software developed for smartphones is a lightweight Android application that supplies precise indoor positioning systems based on Quick Response codes or Near Field Communication tags, and semi-precise indoor positioning systems based on Bluetooth Low Energy beacons. The performance of the proposed approach has been evaluated by conducting computer simulations and real experimentation with a preliminary implementation. The results have shown the strengths of the proposal in the reduction of the time and energy costs to find available parking spaces.

Cellular Automata-Based Application for Driver Assistance in Indoor Parking Areas †

PubMed Central

Caballero-Gil, Cándido; Caballero-Gil, Pino; Molina-Gil, Jezabel

2016-01-01

This work proposes an adaptive recommendation mechanism for smart parking that takes advantage of the popularity of smartphones and the rise of the Internet of Things. The proposal includes a centralized system to forecast available indoor parking spaces, and a low-cost mobile application to obtain data of actual and predicted parking occupancy. The described scheme uses data from both sources bidirectionally so that the centralized forecast system is fed with data obtained with the distributed system based on smartphones, and vice versa. The mobile application uses different wireless technologies to provide the forecast system with actual parking data and receive from the system useful recommendations about where to park. Thus, the proposal can be used by any driver to easily find available parking spaces in indoor facilities. The client software developed for smartphones is a lightweight Android application that supplies precise indoor positioning systems based on Quick Response codes or Near Field Communication tags, and semi-precise indoor positioning systems based on Bluetooth Low Energy beacons. The performance of the proposed approach has been evaluated by conducting computer simulations and real experimentation with a preliminary implementation. The results have shown the strengths of the proposal in the reduction of the time and energy costs to find available parking spaces. PMID:27854282

Guidelines on eosinophilic esophagitis: evidence-based statements and recommendations for diagnosis and management in children and adults.

PubMed

Lucendo, Alfredo J; Molina-Infante, Javier; Arias, Ángel; von Arnim, Ulrike; Bredenoord, Albert J; Bussmann, Christian; Amil Dias, Jorge; Bove, Mogens; González-Cervera, Jesús; Larsson, Helen; Miehlke, Stephan; Papadopoulou, Alexandra; Rodríguez-Sánchez, Joaquín; Ravelli, Alberto; Ronkainen, Jukka; Santander, Cecilio; Schoepfer, Alain M; Storr, Martin A; Terreehorst, Ingrid; Straumann, Alex; Attwood, Stephen E

2017-04-01

Eosinophilic esophagitis (EoE) is one of the most prevalent esophageal diseases and the leading cause of dysphagia and food impaction in children and young adults. This underlines the importance of optimizing diagnosys and treatment of the condition, especially after the increasing amount of knowledge on EoE recently published. Therefore, the UEG, EAACI ESPGHAN, and EUREOS deemed it necessary to update the current guidelines regarding conceptual and epidemiological aspects, diagnosis, and treatment of EoE. General methodology according to the Appraisal of Guidelines for Research and Evaluation (AGREE) II and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used in order to comply with current standards of evidence assessment in formulation of recommendations. An extensive literature search was conducted up to August 2015 and periodically updated. The working group consisted of gastroenterologists, allergists, pediatricians, otolaryngologists, pathologists, and epidemiologists. Systematic evidence-based reviews were performed based upon relevant clinical questions with respect to patient-important outcomes. The guidelines include updated concept of EoE, evaluated information on disease epidemiology, risk factors, associated conditions, and natural history of EoE in children and adults. Diagnostic conditions and criteria, the yield of diagnostic and disease monitoring procedures, and evidence-based statements and recommendation on the utility of the several treatment options for patients EoE are provided. Recommendations on how to choose and implement treatment and long-term management are provided based on expert opinion and best clinical practice. Evidence-based recommendations for EoE diagnosis, treatment modalities, and patients' follow up are proposed in the guideline.

Probiotics for gastrointestinal disorders: Proposed recommendations for children of the Asia-Pacific region

PubMed Central

Cameron, Donald; Hock, Quak Seng; Kadim, Musal; Mohan, Neelam; Ryoo, Eell; Sandhu, Bhupinder; Yamashiro, Yuichiro; Jie, Chen; Hoekstra, Hans; Guarino, Alfredo

2017-01-01

Recommendations for probiotics are available in several regions. This paper proposes recommendations for probiotics in pediatric gastrointestinal diseases in the Asia-Pacific region. Epidemiology and clinical patterns of intestinal diseases in Asia-Pacific countries were discussed. Evidence-based recommendations and randomized controlled trials in the region were revised. Cultural aspects, health management issues and economic factors were also considered. Final recommendations were approved by applying the Likert scale and rated using the GRADE system. Saccharomyces boulardii CNCM I-745 (Sb) and Lactobacillus rhamnosus GG (LGG) were strongly recommended as adjunct treatment to oral rehydration therapy for gastroenteritis. Lactobacillus reuteri could also be considered. Probiotics may be considered for prevention of (with the indicated strains): antibiotic-associated diarrhea (LGG or Sb); Clostridium difficile-induced diarrhea (Sb); nosocomial diarrhea (LGG); infantile colic (L reuteri) and as adjunct treatment of Helicobacter pylori (Sb and others). Specific probiotics with a history of safe use in preterm and term infants may be considered in infants for prevention of necrotizing enterocolitis. There is insufficient evidence for recommendations in other conditions. Despite a diversity of epidemiological, socioeconomical and health system conditions, similar recommendations apply well to Asia pacific countries. These need to be validated with local randomized-controlled trials. PMID:29259371

Synthesis of an optoelectronic system for tracking (OEST) the information track of the optical record carrier based on the acceleration control principle

NASA Astrophysics Data System (ADS)

Zalogin, Stanislav M.; Zalogin, M. S.

1997-02-01

The problem for construction of control algorithm in OEST the information track of the optical record carrier the realization of which is based on the use of accelerations is considered. Such control algorithms render the designed system the properties of adaptability, feeble sensitivity to the system parameter change and the action of disturbing forces what gives known advantages to information carriers with such system under operation in hard climate conditions as well as at maladjustment, workpieces wear and change of friction in the system. In the paper are investigated dynamic characteristics of a closed OEST, it is shown, that the designed stable system with given quality indices is a high-precision one. The validated recommendations as to design of control algorithms parameters are confirmed by results of mathematical simulation of controlled processes. The proposed methods for OEST synthesis on the basis of the control acceleration principle can be recommended for the use at industrial production of optical information record carriers.

Systems Analysis Of Advanced Coal-Based Power Plants

NASA Technical Reports Server (NTRS)

Ferrall, Joseph F.; Jennings, Charles N.; Pappano, Alfred W.

1988-01-01

Report presents appraisal of integrated coal-gasification/fuel-cell power plants. Based on study comparing fuel-cell technologies with each other and with coal-based alternatives and recommends most promising ones for research and development. Evaluates capital cost, cost of electricity, fuel consumption, and conformance with environmental standards. Analyzes sensitivity of cost of electricity to changes in fuel cost, to economic assumptions, and to level of technology. Recommends further evaluation of integrated coal-gasification/fuel-cell integrated coal-gasification/combined-cycle, and pulverized-coal-fired plants. Concludes with appendixes detailing plant-performance models, subsystem-performance parameters, performance goals, cost bases, plant-cost data sheets, and plant sensitivity to fuel-cell performance.

Canadian Network for Mood and Anxiety Treatments (CANMAT) 2016 Clinical Guidelines for the Management of Adults with Major Depressive Disorder

PubMed Central

Quilty, Lena C.; Ravitz, Paula; Rosenbluth, Michael; Pavlova, Barbara; Grigoriadis, Sophie; Velyvis, Vytas; Kennedy, Sidney H.; Lam, Raymond W.; MacQueen, Glenda M.; Milev, Roumen V.; Ravindran, Arun V.; Uher, Rudolf

2016-01-01

Background: The Canadian Network for Mood and Anxiety Treatments (CANMAT) has revised its 2009 guidelines for the management of major depressive disorder (MDD) in adults by updating the evidence and recommendations. The target audiences for these 2016 guidelines are psychiatrists and other mental health professionals. Methods: Using the question-answer format, we conducted a systematic literature search focusing on systematic reviews and meta-analyses. Evidence was graded using CANMAT-defined criteria for level of evidence. Recommendations for lines of treatment were based on the quality of evidence and clinical expert consensus. “Psychological Treatments” is the second of six sections of the 2016 guidelines. Results: Evidence-informed responses were developed for 25 questions under 5 broad categories: 1) patient characteristics relevant to using psychological interventions; 2) therapist and health system characteristics associated with optimizing outcomes; 3) descriptions of major psychotherapies and their efficacy; 4) additional psychological interventions, such as peer interventions and computer- and technology-delivered interventions; and 5) combining and/or sequencing psychological and pharmacological interventions. Conclusions: First-line psychological treatment recommendations for acute MDD include cognitive-behavioural therapy (CBT), interpersonal therapy (IPT), and behavioural activation (BA). Second-line recommendations include computer-based and telephone-delivered psychotherapy. Where feasible, combining psychological treatment (CBT or IPT) with antidepressant treatment is recommended because combined treatment is superior to either treatment alone. First-line psychological treatments for maintenance include CBT and mindfulness-based cognitive therapy (MBCT). Patient preference, in combination with evidence-based treatments and clinician/system capacity, will yield the optimal treatment strategies for improving individual outcomes in MDD. PMID:27486150

Rocket Based Combined Cycle (RBCC) Propulsion Technology Workshop. Volume 1: Executive summary

NASA Technical Reports Server (NTRS)

Chojnacki, Kent T.

1992-01-01

The goal of the Rocket-Based Combined Cycle (RBCC) Propulsion Technology Workshop was to assess the RBCC propulsion system's viability for Earth-to-Orbit (ETO) transportation systems. This was accomplished by creating a forum (workshop) in which past work in the field of RBCC propulsion systems was reviewed, current technology status was evaluated, and future technology programs in the field of RBCC propulsion systems were postulated, discussed, and recommended.

Security Considerations and Recommendations in Computer-Based Testing

PubMed Central

Al-Saleem, Saleh M.

2014-01-01

Many organizations and institutions around the globe are moving or planning to move their paper-and-pencil based testing to computer-based testing (CBT). However, this conversion will not be the best option for all kinds of exams and it will require significant resources. These resources may include the preparation of item banks, methods for test delivery, procedures for test administration, and last but not least test security. Security aspects may include but are not limited to the identification and authentication of examinee, the risks that are associated with cheating on the exam, and the procedures related to test delivery to the examinee. This paper will mainly investigate the security considerations associated with CBT and will provide some recommendations for the security of these kinds of tests. We will also propose a palm-based biometric authentication system incorporated with basic authentication system (username/password) in order to check the identity and authenticity of the examinee. PMID:25254250

Security considerations and recommendations in computer-based testing.

PubMed

Al-Saleem, Saleh M; Ullah, Hanif

2014-01-01

Many organizations and institutions around the globe are moving or planning to move their paper-and-pencil based testing to computer-based testing (CBT). However, this conversion will not be the best option for all kinds of exams and it will require significant resources. These resources may include the preparation of item banks, methods for test delivery, procedures for test administration, and last but not least test security. Security aspects may include but are not limited to the identification and authentication of examinee, the risks that are associated with cheating on the exam, and the procedures related to test delivery to the examinee. This paper will mainly investigate the security considerations associated with CBT and will provide some recommendations for the security of these kinds of tests. We will also propose a palm-based biometric authentication system incorporated with basic authentication system (username/password) in order to check the identity and authenticity of the examinee.

Development of a Recommender System based on Personal History

NASA Astrophysics Data System (ADS)

Tanaka, Katsuaki; Hori, Koichi; Yamamoto, Masato

The flood of information on the Internet makes a person who surf it without some strong intention strayed into it. One of the ways to control the balance between a person and the flood is a recommender system by computer, and many web sites use it. These systems work on a web site for the same kind of items. However the field of personal activity is not limited to handle the same kind of thing and a web site, but also offline area in the real world. To handle personal offline activities, LifeLog is proposed as method to record it, but the main purpose of LifeLog is recording a personal history. How to use a history has still been studied stage. The authors have developed a recommender system that captures personal context from history of personal online and offline activities, treats information on web sites as a large set of context, and finds out and extends overlap of them, then recommends information located there. The aim of the system is that a person can enjoy waves of information again. The system worked as a part of My-life Assist Service. It was a service for mobile phones provided by NTT DoCoMo, Inc. as a field experiment from Dec. 2007 to Feb. 2008.

INCOG recommendations for management of cognition following traumatic brain injury, part II: attention and information processing speed.

PubMed

Ponsford, Jennie; Bayley, Mark; Wiseman-Hakes, Catherine; Togher, Leanne; Velikonja, Diana; McIntyre, Amanda; Janzen, Shannon; Tate, Robyn

2014-01-01

Traumatic brain injury, due to its diffuse nature and high frequency of injury to frontotemporal and midbrain reticular activating systems, may cause disruption in many aspects of attention: arousal, selective attention, speed of information processing, and strategic control of attention, including sustained attention, shifting and dividing of attention, and working memory. An international team of researchers and clinicians (known as INCOG) convened to develop recommendations for the management of attentional problems. The experts selected recommendations from published guidelines and then reviewed literature to ensure that recommendations were current. Decision algorithms incorporating the recommendations based on inclusion and exclusion criteria of published trials were developed. The team then prioritized recommendations for implementation and developed audit criteria to evaluate adherence to these best practices. The recommendations and discussion highlight that metacognitive strategy training focused on functional everyday activities is appropriate. Appropriate use of dual task training, environmental modifications, and cognitive behavioral therapy is also discussed. There is insufficient evidence to support mindfulness meditation and practice on de-contextualized computer-based tasks for attention. Administration of the medication methylphenidate should be considered to improve information-processing speed. The INCOG recommendations for rehabilitation of attention provide up-to-date guidance for clinicians treating people with traumatic brain injury.

Recommendation system to determine suitable and viable hiking routes: a prototype application in Sierra de las Nieves Nature Reserve (southern Spain)

NASA Astrophysics Data System (ADS)

Vías, Jesús; Rolland, José; Gómez, María Luisa; Ocaña, Carmen; Luque, Ana

2018-05-01

This paper describes a system for recommending hiking routes to help manage hiking activities in a protected area. The system proposes various routes, based on five criteria that maximize some aspects of hikers' requirements (by analyzing the viability and difficulty of the trails) and also those of protected areas managers (by proposals to relieve congestion in areas already used for hiking and to promote awareness of new ones, as a contribution to environmental education). The recommendation system uses network analysis, multi-criteria decision analysis and geographic information system by free software tools: PgRouting, PostgreSQL and PostGIS. This system has been tested in Sierra de las Nieves Nature Reserve (Andalusia, Spain). Of the 182 routes obtained by the system, 62 (34%) are considered viable for hikers in Sierra de las Nieves, taking into account the type of user most likely to visit this protected area. Most routes have a high difficulty level, which is coherent with the mountainous character of the protected area.

American College of Rheumatology/Spondylitis Association of America/Spondyloarthritis Research and Treatment Network 2015 Recommendations for the Treatment of Ankylosing Spondylitis and Nonradiographic Axial Spondyloarthritis

PubMed Central

Ward, Michael M.; Deodhar, Atul; Akl, Elie A.; Lui, Andrew; Ermann, Joerg; Gensler, Lianne S.; Smith, Judith A.; Borenstein, David; Hiratzka, Jayme; Weiss, Pamela F.; Inman, Robert D.; Majithia, Vikas; Haroon, Nigil; Maksymowych, Walter P.; Joyce, Janet; Clark, Bruce M.; Colbert, Robert A.; Figgie, Mark P.; Hallegua, David S.; Prete, Pamela E.; Rosenbaum, James T.; Stebulis, Judith A.; van den Bosch, Filip; Yu, David T. Y.; Miller, Amy S.; Reveille, John D.; Caplan, Liron

2016-01-01

Objective To provide evidence-based recommendations for the treatment of patients with ankylosing spondylitis (AS) and nonradiographic axial spondyloarthritis (SpA). Methods A core group led the development of the recommendations, starting with the treatment questions. A literature review group conducted systematic literature reviews of studies that addressed 57 specific treatment questions, based on searches conducted in OVID Medline (1946–2014), PubMed (1966–2014), and the Cochrane Library. We assessed the quality of evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method. A separate voting group reviewed the evidence and voted on recommendations for each question using the GRADE framework. Results In patients with active AS, the strong recommendations included use of nonsteroidal antiinflammatory drugs (NSAIDs), use of tumor necrosis factor inhibitors (TNFi) when activity persists despite NSAID treatment, not to use systemic glucocorticoids, use of physical therapy, and use of hip arthroplasty for patients with advanced hip arthritis. Among the conditional recommendations was that no particular TNFi was preferred except in patients with concomitant inflammatory bowel disease or recurrent iritis, in whom TNFi monoclonal antibodies should be used. In patients with active nonradiographic axial SpA despite treatment with NSAIDs, we conditionally recommend treatment with TNFi. Other recommendations for patients with nonradiographic axial SpA were based on indirect evidence and were the same as for patients with AS. Conclusion These recommendations provide guidance for the management of common clinical questions in AS and nonradiographic axial SpA. Additional research on optimal medication management over time, disease monitoring, and preventive care is needed to help establish best practices in these areas. PMID:26401991

American College of Rheumatology/Spondylitis Association of America/Spondyloarthritis Research and Treatment Network 2015 Recommendations for the Treatment of Ankylosing Spondylitis and Nonradiographic Axial Spondyloarthritis

PubMed Central

WARD, MICHAEL M.; DEODHAR, ATUL; AKL, ELIE A.; LUI, ANDREW; ERMANN, JOERG; GENSLER, LIANNE S.; SMITH, JUDITH A.; BORENSTEIN, DAVID; HIRATZKA, JAYME; WEISS, PAMELA F.; INMAN, ROBERT D.; MAJITHIA, VIKAS; HAROON, NIGIL; MAKSYMOWYCH, WALTER P.; JOYCE, JANET; CLARK, BRUCE M.; COLBERT, ROBERT A.; FIGGIE, MARK P.; HALLEGUA, DAVID S.; PRETE, PAMELA E.; ROSENBAUM, JAMES T.; STEBULIS, JUDITH A.; VAN DEN BOSCH, FILIP; YU, DAVID T. Y.; MILLER, AMY S.; REVEILLE, JOHN D.; CAPLAN, LIRON

2016-01-01

Objective To provide evidence-based recommendations for the treatment of patients with ankylosing spondylitis (AS) and nonradiographic axial spondyloarthritis (SpA). Methods A core group led the development of the recommendations, starting with the treatment questions. A literature review group conducted systematic literature reviews of studies that addressed 57 specific treatment questions, based on searches conducted in OVID Medline (1946–2014), PubMed (1966–2014), and the Cochrane Library. We assessed the quality of evidence using the Grading of Recommendations, Assessment, Development and Evaluation (GRADE) method. A separate voting group reviewed the evidence and voted on recommendations for each question using the GRADE framework. Results In patients with active AS, the strong recommendations included use of nonsteroidal antiinflammatory drugs (NSAIDs), use of tumor necrosis factor inhibitors (TNFi) when activity persists despite NSAID treatment, not to use systemic glucocorticoids, use of physical therapy, and use of hip arthroplasty for patients with advanced hip arthritis. Among the conditional recommendations was that no particular TNFi was preferred except in patients with concomitant inflammatory bowel disease or recurrent iritis, in whom TNFi monoclonal antibodies should be used. In patients with active nonradiographic axial SpA despite treatment with NSAIDs, we conditionally recommend treatment with TNFi. Other recommendations for patients with nonradiographic axial SpA were based on indirect evidence and were the same as for patients with AS. Conclusion These recommendations provide guidance for the management of common clinical questions in AS and nonradiographic axial SpA. Additional research on optimal medication management over time, disease monitoring, and preventive care is needed to help establish best practices in these areas. PMID:26401907

Report on Legislative and Funding Recommendations, DoDDS Comprehensive Study [of Dependents Schools].

ERIC Educational Resources Information Center

Bartell, Ted; LeBlanc, Linda

The final volume of a comprehensive study of the Department of Defense Dependents Schools (DoDDS), this report consists of a brief background description of the DoDDS system, followed by 10 legislative and funding recommendations based on the findings of the study: (1) increase funding in fiscal year 1984 and beyond to accommodate anticipated…

How Prepared Are America's Colleges and Universities for Major Crises? Assessing the State of Crisis Management

ERIC Educational Resources Information Center

Mitroff, Ian I.; Diamond, Michael A.; Alpaslan, Murat C.

2006-01-01

This article outlines a set of recommendations to college and university leaders and governing bodies on how to develop crisis-management systems to ensure that their institutions are as well prepared as possible for a wide range of crises. These recommendations are based, in part, on crisis-management programs developed for various business…

Implementation of recommended trauma system criteria in south-eastern Norway: a cross-sectional hospital survey

PubMed Central

2012-01-01

Background Formalized trauma systems have shown beneficial effects on patient survival and have harvested great recognition among health care professionals. In spite of this, the implementation of trauma systems is challenging and often met with resistance. Recommendations for a national trauma system in Norway were published in 2007. We wanted to assess the level of implementation of these recommendations. Methods A survey of all acute care hospitals that receive severely injured patients in the south-eastern health region of Norway was conducted. A structured questionnaire based on the 2007 national recommendations was used in a telephone interview of hospital trauma personnel between January 17 and 21, 2011. Seventeen trauma system criteria were identified from the recommendations. Results Nineteen hospitals were included in the study and these received more than 2000 trauma patients annually via their trauma teams. Out of the 17 criteria that had been identified, the hospitals fulfilled a median of 12 criteria. Neither the size of the hospitals nor the distance between the hospitals and the regional trauma centre affected the level of trauma resources available. The hospitals scored lowest on the criteria for transfer of patients to higher level of care and on the training requirements for members of the trauma teams. Conclusion Our study identifies a major shortcoming in the efforts of regionalizing trauma in our region. The findings indicate that training of personnel and protocols for inter-hospital transfer are the major deficiencies from the national trauma system recommendations. Resources for training of personnel partaking in trauma teams and development of inter-hospital transfer agreements should receive immediate attention. PMID:22281020

Using a claims data-based sentinel system to improve compliance with clinical guidelines: results of a randomized prospective study.

PubMed

Javitt, Jonathan C; Steinberg, Gregory; Locke, Todd; Couch, James B; Jacques, Jeffrey; Juster, Iver; Reisman, Lonny

2005-02-01

To demonstrate the potential effect of deploying a sentinel system that scans administrative claims information and clinical data to detect and mitigate errors in care and deviations from best medical practices. Members (n = 39 462; age range, 12-64 years) of a midwestern managed care plan were randomly assigned to an intervention or a control group. The sentinel system was programmed with more than 1000 decision rules that were capable of generating clinical recommendations. Clinical recommendations triggered for subjects in the intervention group were relayed to treating physicians, and those for the control group were deferred to study end. Nine hundred eight clinical recommendations were issued to the intervention group. Among those in both groups who triggered recommendations, there were 19% fewer hospital admissions in the intervention group compared with the control group (P < .001). Charges among those whose recommendations were communicated were dollar 77.91 per member per month (pmpm) lower and paid claims were dollar 68.08 pmpm lower than among controls compared with the baseline values (P = .003 for both). Paid claims for the entire intervention group (with or without recommendations) were dollar 8.07 pmpm lower than those for the entire control group. In contrast, the intervention cost dollar 1.00 pmpm, suggesting an 8-fold return on investment. Ongoing use of a sentinel system to prompt clinically actionable, patient-specific alerts generated from administratively derived clinical data was associated with a reduction in hospitalization, medical costs, and morbidity.

Guidelines for Improving Entry Into and Retention in Care and Antiretroviral Adherence for Persons With HIV: Evidence-Based Recommendations From an International Association of Physicians in AIDS Care Panel

PubMed Central

Thompson, Melanie A.; Mugavero, Michael J.; Amico, K. Rivet; Cargill, Victoria A.; Chang, Larry W.; Gross, Robert; Orrell, Catherine; Altice, Frederick L.; Bangsberg, David R.; Bartlett, John G.; Beckwith, Curt G.; Dowshen, Nadia; Gordon, Christopher M.; Horn, Tim; Kumar, Princy; Scott, James D.; Stirratt, Michael J.; Remien, Robert H.; Simoni, Jane M.; Nachega, Jean B.

2014-01-01

Description After HIV diagnosis, timely entry into HIV medical care and retention in that care are essential to the provision of effective antiretroviral therapy (ART). ART adherence is among the key determinants of successful HIV treatment outcome and is essential to minimize the emergence of drug resistance. The International Association of Physicians in AIDS Care convened a panel to develop evidence-based recommendations to optimize entry into and retention in care and ART adherence for people with HIV. Methods A systematic literature search was conducted to produce an evidence base restricted to randomized, controlled trials and observational studies with comparators that had at least 1 measured biological or behavioral end point. A total of 325 studies met the criteria. Two reviewers independently extracted and coded data from each study using a standardized data extraction form. Panel members drafted recommendations based on the body of evidence for each method or intervention and then graded the overall quality of the body of evidence and the strength for each recommendation. Recommendations Recommendations are provided for monitoring of entry into and retention in care, interventions to improve entry and retention, and monitoring of and interventions to improve ART adherence. Recommendations cover ART strategies, adherence tools, education and counseling, and health system and service delivery interventions. In addition, they cover specific issues pertaining to pregnant women, incarcerated individuals, homeless and marginally housed individuals, and children and adolescents, as well as substance use and mental health disorders. Recommendations for future research in all areas are also provided. PMID:22393036

Teaching topography-based and selection-based verbal behavior to developmentally disabled individuals: Some considerations

PubMed Central

Shafer, Esther

1993-01-01

Augmentative and alternative communication systems are widely recommended for nonvocal developmentally disabled individuals, with selection-based systems becoming increasingly popular. However, theoretical and experimental evidence suggests that topography-based communication systems are easier to learn. This paper discusses research relevant to the ease of acquisition of topography-based and selection-based systems. Additionally, current practices for choosing and designing communication systems are reviewed in order to investigate the extent to which links have been made with available theoretical and experimental knowledge. A stimulus equivalence model is proposed as a clearer direction for practitioners to follow when planning a communication training program. Suggestions for future research are also offered. PMID:22477085

Position statement: hypoglycemia management in patients with diabetes mellitus. Diabetes Mellitus Working Group of the Spanish Society of Endocrinology and Nutrition.

PubMed

Mezquita-Raya, Pedro; Reyes-García, Rebeca; Moreno-Pérez, Óscar; Muñoz-Torres, Manuel; Merino-Torres, Juan Francisco; Gorgojo-Martínez, Juan José; Jódar-Gimeno, Esteban; Escalada San Martín, Javier; Gargallo-Fernández, Manuel; Soto-Gonzalez, Alfonso; González Pérez de Villar, Noemí; Becerra Fernández, Antonio; Bellido Guerrero, Diego; Botella-Serrano, Marta; Gómez-Peralta, Fernando; López de la Torre Casares, Martín

2013-11-01

To provide practical recommendations for evaluation and management of hypoglycemia in patients with diabetes mellitus. Members of the Diabetes Mellitus Working Group of the Spanish Society of Endocrinology and Nutrition. Recommendations were formulated according to the Grading of Recommendations, Assessment, Development, and Evaluation system to describe both the strength of recommendations and the quality of evidence. A systematic search was made in MEDLINE (PubMed). Papers in English and Spanish with publication date before 15 February 2013 were included. For recommendations about drugs only those approved by the European Medicines Agency were included. After formulation of recommendations, they were discussed by the Working Group. The document provides evidence-based practical recommendations for evaluation and management of hypoglycemia in patients with diabetes mellitus. Copyright © 2013 SEEN. Published by Elsevier Espana. All rights reserved.

Recommender system based on scarce information mining.

PubMed

Lu, Wei; Chung, Fu-Lai; Lai, Kunfeng; Zhang, Liang

2017-09-01

Guessing what user may like is now a typical interface for video recommendation. Nowadays, the highly popular user generated content sites provide various sources of information such as tags for recommendation tasks. Motivated by a real world online video recommendation problem, this work targets at the long tail phenomena of user behavior and the sparsity of item features. A personalized compound recommendation framework for online video recommendation called Dirichlet mixture probit model for information scarcity (DPIS) is hence proposed. Assuming that each clicking sample is generated from a representation of user preferences, DPIS models the sample level topic proportions as a multinomial item vector, and utilizes topical clustering on the user part for recommendation through a probit classifier. As demonstrated by the real-world application, the proposed DPIS achieves better performance in accuracy, perplexity as well as diversity in coverage than traditional methods. Copyright © 2017 Elsevier Ltd. All rights reserved.

Systems analysis on laser beamed power

NASA Technical Reports Server (NTRS)

Zeiders, Glenn W., Jr.

1993-01-01

The NASA SELENE power beaming program is intended to supply cost-effective power to space assets via Earth-based lasers and active optics systems. Key elements of the program are analyzed, the overall effort is reviewed, and recommendations are presented.

Improving the Effectiveness of Electronic Health Record-Based Referral Processes

PubMed Central

2012-01-01

Electronic health records are increasingly being used to facilitate referral communication in the outpatient setting. However, despite support by technology, referral communication between primary care providers and specialists is often unsatisfactory and is unable to eliminate care delays. This may be in part due to lack of attention to how information and communication technology fits within the social environment of health care. Making electronic referral communication effective requires a multifaceted “socio-technical” approach. Using an 8-dimensional socio-technical model for health information technology as a framework, we describe ten recommendations that represent good clinical practices to design, develop, implement, improve, and monitor electronic referral communication in the outpatient setting. These recommendations were developed on the basis of our previous work, current literature, sound clinical practice, and a systems-based approach to understanding and implementing health information technology solutions. Recommendations are relevant to system designers, practicing clinicians, and other stakeholders considering use of electronic health records to support referral communication. PMID:22973874

Venous thromboembolism and cancer: guidelines of the Italian Association of Medical Oncology (AIOM).

PubMed

Mandalà, M; Falanga, A; Piccioli, A; Prandoni, P; Pogliani, E M; Labianca, R; Barni, S

2006-09-01

Thromboembolic complications represent one of the most important cause of morbidity and mortality in cancer patients. Although several data have been published demonstrating the strong association between cancer and venous thromboembolism (VTE), there is poor perception, among oncologists, of the level of risk of thrombosis and of relevance of managing VTE in these patients. The Associazione Italiana di Oncologia Medica (AIOM) has provided some recommendations to direct clinical practice according to evidence-based data concerning cancer and VTE. In fact, we conducted an extensive literature review (1996-2005) to produce evidence-based recommendations to improve perceptions of the magnitude of this risk among Italian medical and surgical oncologists and alert on the new approaches to prophylaxis and treatment of VTE in cancer patients. Levels of evidence are given according to a five-point rating system, and similarly for each key recommendation a five-point rating system suggests if the evidence is strong and indicate that the benefits do, or do not, outweigh risks and burden.

Development and validation of an exercise performance support system for people with lower extremity impairment.

PubMed

Minor, M A; Reid, J C; Griffin, J Z; Pittman, C B; Patrick, T B; Cutts, J H

1998-02-01

To identify innovative strategies to support appropriate, self-directed exercise that increase physical activity levels of people with arthritis. This article reports on one interactive, multimedia exercise performance support system (PSS) for people with lower extremity impairments in strength or flexibility. An interdisciplinary team developed the PSS using self-report of lower extremity musculoskeletal impairments (flexibility and strength) to produce an individualized exercise program with video and print educational materials. Initial evaluation has investigated the validity and reliability of program assessments and recommendations. PSS self-report and professional assessments were similar, with more impairments indicated by self-report. PSS exercise recommendations were similar to those made by 3 expert physical therapists using the same exercise data base. Results of PSS impairment assessments were stable over a 1-week period. PSS exercise recommendations appear to be reliable and a valid reflection of current exercise knowledge in rheumatology. Furthermore, users were able to complete the computer-based program with minimal assistance and reported it to be enjoyable and informative.

Similarity from multi-dimensional scaling: solving the accuracy and diversity dilemma in information filtering.

PubMed

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term.

EULAR evidence‐based recommendations on the management of systemic glucocorticoid therapy in rheumatic diseases

PubMed Central

Hoes, J N; Jacobs, J W G; Boers, M; Boumpas, D; Buttgereit, F; Caeyers, N; Choy, E H; Cutolo, M; Da Silva, J A P; Esselens, G; Guillevin, L; Hafstrom, I; Kirwan, J R; Rovensky, J; Russell, A; Saag, K G; Svensson, B; Westhovens, R; Zeidler, H; Bijlsma, J W J

2007-01-01

Objective To develop evidence‐based recommendations for the management of systemic glucocorticoid (GC) therapy in rheumatic diseases. Methods The multidisciplinary guideline development group from 11 European countries, Canada and the USA consisted of 15 rheumatologists, 1 internist, 1 rheumatologist–epidemiologist, 1 health professional, 1 patient and 1 research fellow. The Delphi method was used to agree on 10 key propositions related to the safe use of GCs. A systematic literature search of PUBMED, EMBASE, CINAHL, and Cochrane Library was then used to identify the best available research evidence to support each of the 10 propositions. The strength of recommendation was given according to research evidence, clinical expertise and perceived patient preference. Results The 10 propositions were generated through three Delphi rounds and included patient education, risk factors, adverse effects, concomitant therapy (ie, non‐steroidal anti‐inflammatory drugs, gastroprotection and cyclo‐oxygenase‐2 selective inhibitors, calcium and vitamin D, bisphosphonates) and special safety advice (ie, adrenal insufficiency, pregnancy, growth impairment). Conclusion Ten key recommendations for the management of systemic GC‐therapy were formulated using a combination of systematically retrieved research evidence and expert consensus. There are areas of importance that have little evidence (ie, dosing and tapering strategies, timing, risk factors and monitoring for adverse effects, perioperative GC‐replacement) and need further research; therefore also a research agenda was composed. PMID:17660219

A review of CDC's Web-based Injury Statistics Query and Reporting System (WISQARS™): Planning for the future of injury surveillance✩

PubMed Central

Ballesteros, Michael F.; Webb, Kevin; McClure, Roderick J.

2017-01-01

Introduction The Centers for Disease Control and Prevention (CDC) developed the Web-based Injury Statistics Query and Reporting System (WISQARSTM) to meet the data needs of injury practitioners. In 2015, CDC completed a Portfolio Review of this system to inform its future development. Methods Evaluation questions addressed utilization, technology and innovation, data sources, and tools and training. Data were collected through environmental scans, a review of peer-reviewed and grey literature, a web search, and stakeholder interviews. Results Review findings led to specific recommendations for each evaluation question. Response CDC reviewed each recommendation and initiated several enhancements that will improve the ability of injury prevention practitioners to leverage these data, better make sense of query results, and incorporate findings and key messages into prevention practices. PMID:28454867

PANLAR Consensus Recommendations for the Management in Osteoarthritis of Hand, Hip, and Knee.

PubMed

Rillo, Oscar; Riera, Humberto; Acosta, Carlota; Liendo, Verónica; Bolaños, Joyce; Monterola, Ligia; Nieto, Edgar; Arape, Rodolfo; Franco, Luisa M; Vera, Mariflor; Papasidero, Silvia; Espinosa, Rolando; Esquivel, Jorge A; Souto, Renee; Rossi, Cesar; Molina, José F; Salas, José; Ballesteros, Francisco; Radrigan, Francisco; Guibert, Marlene; Reyes, Gil; Chico, Araceli; Camacho, Walter; Urioste, Lorena; Garcia, Abraham; Iraheta, Isa; Gutierrez, Carmen E; Aragón, Raúl; Duarte, Margarita; Gonzalez, Margarita; Castañeda, Oswaldo; Angulo, Juan; Coimbra, Ibsen; Munoz-Louis, Roberto; Saenz, Ricardo; Vallejo, Carlos; Briceño, Julio; Acuña, Ramón P; De León, Anibal; Reginato, Anthony M; Möller, Ingrid; Caballero, Carlo V; Quintero, Maritza

2016-10-01

The objective of this consensus is to update the recommendations for the treatment of hand, hip, and knee osteoarthritis (OA) by agreeing on key propositions relating to the management of hand, hip, and knee OA, by identifying and critically appraising research evidence for the effectiveness of the treatments and by generating recommendations based on a combination of the available evidence and expert opinion of 18 countries of America. Recommendations were developed by a group of 48 specialists of rheumatologists, members of other medical disciplines (orthopedics and physiatrists), and three patients, one for each location of OA. A systematic review of existing articles, meta-analyses, and guidelines for the management of hand, hip, and knee OA published between 2008 and January 2014 was undertaken. The scores for Level of Evidence and Grade of Recommendation were proposed and fully consented within the committee based on The American Heart Association Evidence-Based Scoring System. The level of agreement was established through a variation of Delphi technique. Both "strong" and "conditional" recommendations are given for management of hand, hip, and knee OA and nonpharmacological, pharmacological, and surgical modalities of treatment are presented according to the different levels of agreement. These recommendations are based on the consensus of clinical experts from a wide range of disciplines taking available evidence into account while balancing the benefits and risks of nonpharmacological, pharmacological, and surgical treatment modalities, and incorporating their preferences and values. Different backgrounds in terms of patient education or drug availability in different countries were not evaluated but will be important.

Problems related to the integration of fault tolerant aircraft electronic systems

NASA Technical Reports Server (NTRS)

Bannister, J. A.; Adlakha, V.; Triyedi, K.; Alspaugh, T. A., Jr.

1982-01-01

Problems related to the design of the hardware for an integrated aircraft electronic system are considered. Taxonomies of concurrent systems are reviewed and a new taxonomy is proposed. An informal methodology intended to identify feasible regions of the taxonomic design space is described. Specific tools are recommended for use in the methodology. Based on the methodology, a preliminary strawman integrated fault tolerant aircraft electronic system is proposed. Next, problems related to the programming and control of inegrated aircraft electronic systems are discussed. Issues of system resource management, including the scheduling and allocation of real time periodic tasks in a multiprocessor environment, are treated in detail. The role of software design in integrated fault tolerant aircraft electronic systems is discussed. Conclusions and recommendations for further work are included.

Micropollutants in source separated wastewater streams and recovered resources of source separated sanitation.

PubMed

Butkovskyi, A; Leal, L Hernandez; Zeeman, G; Rijnaarts, H H M

2017-07-01

The quality of anaerobic sludge and struvite from black water treatment system, aerobic sludge from grey water treatment system and effluents of both systems was assessed for organic micropollutant content in order to ensure safety when reusing these products. Use of anaerobic black water sludge and struvite as soil amendments is recommended based on the low micropollutant content. Aerobic grey water sludge is recommended for disposal, because of the relatively high micropollutant concentrations, exceeding those in sewage sludge. Effluents of black and grey water treatment systems require post-treatment prior to reuse, because the measured micropollutant concentrations in the effluents are above ecotoxicological thresholds. Copyright © 2017 Elsevier Inc. All rights reserved.

Recommendations on disease management for patients with advanced human epidermal growth factor receptor 2-positive breast cancer and brain metastases: American Society of Clinical Oncology clinical practice guideline.

PubMed

Ramakrishna, Naren; Temin, Sarah; Chandarlapaty, Sarat; Crews, Jennie R; Davidson, Nancy E; Esteva, Francisco J; Giordano, Sharon H; Gonzalez-Angulo, Ana M; Kirshner, Jeffrey J; Krop, Ian; Levinson, Jennifer; Modi, Shanu; Patt, Debra A; Perez, Edith A; Perlmutter, Jane; Winer, Eric P; Lin, Nancy U

2014-07-01

To provide formal expert consensus-based recommendations to practicing oncologists and others on the management of brain metastases for patients with human epidermal growth factor receptor 2 (HER2) -positive advanced breast cancer. The American Society of Clinical Oncology (ASCO) convened a panel of medical oncology, radiation oncology, guideline implementation, and advocacy experts and conducted a systematic review of the literature. When that failed to yield sufficiently strong quality evidence, the Expert Panel undertook a formal expert consensus-based process to produce these recommendations. ASCO used a modified Delphi process. The panel members drafted recommendations, and a group of other experts joined them for two rounds of formal ratings of the recommendations. No studies or existing guidelines met the systematic review criteria; therefore, ASCO conducted a formal expert consensus-based process. Patients with brain metastases should receive appropriate local therapy and systemic therapy, if indicated. Local therapies include surgery, whole-brain radiotherapy, and stereotactic radiosurgery. Treatments depend on factors such as patient prognosis, presence of symptoms, resectability, number and size of metastases, prior therapy, and whether metastases are diffuse. Other options include systemic therapy, best supportive care, enrollment onto a clinical trial, and/or palliative care. Clinicians should not perform routine magnetic resonance imaging (MRI) to screen for brain metastases, but rather should have a low threshold for MRI of the brain because of the high incidence of brain metastases among patients with HER2-positive advanced breast cancer. © 2014 by American Society of Clinical Oncology.

Expert system for skin problem consultation in Thai traditional medicine.

PubMed

Nopparatkiat, Pornchai; na Nagara, Byaporn; Chansa-ngavej, Chuvej

2014-01-01

This paper aimed to demonstrate the research and development of a rule-based expert system for skin problem consulting in the areas of acne, melasma, freckle, wrinkle, and uneven skin tone, with recommended treatments from Thai traditional medicine knowledge. The tool selected for developing the expert system is a software program written in the PHP language. MySQL database is used to work together with PHP for building database of the expert system. The system is web-based and can be reached from anywhere with Internet access. The developed expert system gave recommendations on the skin problem treatment with Thai herbal recipes and Thai herbal cosmetics based on 416 rules derived from primary and secondary sources. The system had been tested by 50 users consisting of dermatologists, Thai traditional medicine doctors, and general users. The developed system was considered good for learning and consultation. The present work showed how such a scattered body of traditional knowledge as Thai traditional medicine and herbal recipes could be collected, organised and made accessible to users and interested parties. The expert system developed herein should contribute in a meaningful way towards preserving the knowledge and helping promote the use of Thai traditional medicine as a practical alternative medicine for the treatment of illnesses.

Rail Base Corrosion and Cracking Prevention: Phase 2

DOT National Transportation Integrated Search

2018-04-09

EWI was engaged by the Federal Railroad Administration to research rail treatments to prevent rail base corrosion in corrosive environments. A coating system was selected in Phase 1 and recommended for field trials. In Phase 2, four railroads sponsor...

Network Location-Aware Service Recommendation with Random Walk in Cyber-Physical Systems

PubMed Central

Yin, Yuyu; Yu, Fangzheng; Xu, Yueshen; Yu, Lifeng; Mu, Jinglong

2017-01-01

Cyber-physical systems (CPS) have received much attention from both academia and industry. An increasing number of functions in CPS are provided in the way of services, which gives rise to an urgent task, that is, how to recommend the suitable services in a huge number of available services in CPS. In traditional service recommendation, collaborative filtering (CF) has been studied in academia, and used in industry. However, there exist several defects that limit the application of CF-based methods in CPS. One is that under the case of high data sparsity, CF-based methods are likely to generate inaccurate prediction results. In this paper, we discover that mining the potential similarity relations among users or services in CPS is really helpful to improve the prediction accuracy. Besides, most of traditional CF-based methods are only capable of using the service invocation records, but ignore the context information, such as network location, which is a typical context in CPS. In this paper, we propose a novel service recommendation method for CPS, which utilizes network location as context information and contains three prediction models using random walking. We conduct sufficient experiments on two real-world datasets, and the results demonstrate the effectiveness of our proposed methods and verify that the network location is indeed useful in QoS prediction. PMID:28885602

Evidence-Based Recommendations for Optimizing Light in Day-to-Day Spaceflight Operations

NASA Technical Reports Server (NTRS)

Whitmire, Alexandra; Leveton, Lauren; Barger, Laura; Clark, Toni; Bollweg, Laura; Ohnesorge, Kristine; Brainard, George

2015-01-01

NASA Behavioral Health and Performance Element (BHP) personnel have previously reported on efforts to transition evidence-based recommendations for a flexible lighting system on the International Space Station (ISS). Based on these recommendations, beginning in 2016 the ISS will replace the current fluorescent-based lights with an LED-based system to optimize visual performance, facilitate circadian alignment, promote sleep, and hasten schedule shifting. Additional efforts related to lighting countermeasures in spaceflight operations have also been underway. As an example, a recent BHP research study led by investigators at Harvard Medical School and Brigham and Women's Hospital, evaluated the acceptability, feasibility, and effectiveness of blue-enriched light exposure during exercise breaks for flight controllers working the overnight shift in the Mission Control Center (MCC) at NASA Johnson Space Center. This effort, along with published laboratory studies that have demonstrated the effectiveness of appropriately timed light for promoting alertness, served as an impetus for new light options, and educational protocols for flight controllers. In addition, a separate set of guidelines related to the light emitted from electronic devices, were provided to the Astronaut Office this past year. These guidelines were based on an assessment led by NASA's Lighting Environment Test Facility that included measuring the spectral power distribution, irradiance, and radiance of light emitted from ISS-grade laptops and I-Pads, as well as Android devices. Evaluations were conducted with and without the use of off-the-shelf screen filters as well as a software application that touts minimizing the short-wave length of the visible light spectrum. This presentation will focus on the transition for operations process related to lighting countermeasures in the MCC, as well as the evidence to support recommendations for optimal use of laptops, I-Pads, and Android devices during all phases of spaceflight operations.

Automated Platform Management System Scheduling

NASA Technical Reports Server (NTRS)

Hull, Larry G.

1990-01-01

The Platform Management System was established to coordinate the operation of platform systems and instruments. The management functions are split between ground and space components. Since platforms are to be out of contact with the ground more than the manned base, the on-board functions are required to be more autonomous than those of the manned base. Under this concept, automated replanning and rescheduling, including on-board real-time schedule maintenance and schedule repair, are required to effectively and efficiently meet Space Station Freedom mission goals. In a FY88 study, we developed several promising alternatives for automated platform planning and scheduling. We recommended both a specific alternative and a phased approach to automated platform resource scheduling. Our recommended alternative was based upon use of exactly the same scheduling engine in both ground and space components of the platform management system. Our phased approach recommendation was based upon evolutionary development of the platform. In the past year, we developed platform scheduler requirements and implemented a rapid prototype of a baseline platform scheduler. Presently we are rehosting this platform scheduler rapid prototype and integrating the scheduler prototype into two Goddard Space Flight Center testbeds, as the ground scheduler in the Scheduling Concepts, Architectures, and Networks Testbed and as the on-board scheduler in the Platform Management System Testbed. Using these testbeds, we will investigate rescheduling issues, evaluate operational performance and enhance the platform scheduler prototype to demonstrate our evolutionary approach to automated platform scheduling. The work described in this paper was performed prior to Space Station Freedom rephasing, transfer of platform responsibility to Code E, and other recently discussed changes. We neither speculate on these changes nor attempt to predict the impact of the final decisions. As a consequence some of our work and results may be outdated when this paper is published.

Recommended vitamin D levels in the general population.

PubMed

Varsavsky, Mariela; Rozas Moreno, Pedro; Becerra Fernández, Antonio; Luque Fernández, Inés; Quesada Gómez, José Manuel; Ávila Rubio, Verónica; García Martín, Antonia; Cortés Berdonces, María; Naf Cortés, Silvia; Romero Muñoz, Manuel; Reyes García, Rebeca; Jódar Gimeno, Esteban; Muñoz Torres, Manuel

2017-03-01

To provide recommendations based on evidence on the management of vitaminD deficiency in the general population. Members of the Bone Metabolism Working Group of the Spanish Society of Endocrinology. Recommendations were formulated using the GRADE system (Grading of Recommendations, Assessment, Development, and Evaluation) to describe both the strength of recommendations and the quality of evidence. A systematic search was made in MEDLINE (Pubmed) using the term VitaminD and the name of each issue. Papers in English and Spanish with publication date before 17 March 2016 were included. Recommendations were jointly discussed by the Working Group. This document summarizes the data about vitaminD deficiency in terms of prevalence, etiology, screening indications, adequate levels and effects of supplementation on bone and non-skeletal health outcomes. Copyright © 2017 SEEN. Publicado por Elsevier España, S.L.U. All rights reserved.

Top down, bottom up structured programming and program structuring

NASA Technical Reports Server (NTRS)

Hamilton, M.; Zeldin, S.

1972-01-01

New design and programming techniques for shuttle software. Based on previous Apollo experience, recommendations are made to apply top-down structured programming techniques to shuttle software. New software verification techniques for large software systems are recommended. HAL, the higher order language selected for the shuttle flight code, is discussed and found to be adequate for implementing these techniques. Recommendations are made to apply the workable combination of top-down, bottom-up methods in the management of shuttle software. Program structuring is discussed relevant to both programming and management techniques.

NCCN Guidelines® Insights Bladder Cancer, Version 2.2016 Featured Updates to the NCCN Guidelines

PubMed Central

Clark, Peter E.; Spiess, Philippe E.; Agarwal, Neeraj; Bangs, Rick; Boorjian, Stephen A.; Buyyounouski, Mark K.; Efstathiou, Jason A.; Flaig, Thomas W.; Friedlander, Terence; Greenberg, Richard E.; Guru, Khurshid A.; Hahn, Noah; Herr, Harry W.; Hoimes, Christopher; Inman, Brant A.; Kader, A. Karim; Kibel, Adam S.; Kuzel, Timothy M.; Lele, Subodh M.; Meeks, Joshua J.; Michalski, Jeff; Montgomery, Jeffrey S.; Pagliaro, Lance C.; Pal, Sumanta K.; Patterson, Anthony; Petrylak, Daniel; Plimack, Elizabeth R.; Pohar, Kamal S.; Porter, Michael P.; Sexton, Wade J.; Siefker-Radtke, Arlene O.; Sonpavde, Guru; Tward, Jonathan; Wile, Geoffrey; Dwyer, Mary A.; Smith, Courtney

2017-01-01

These NCCN Guidelines Insights discuss the major recent updates to the NCCN Guidelines for Bladder Cancer based on the review of the evidence in conjunction with the expert opinion of the panel. Recent updates include (1) refining the recommendation of intravesical bacillus Calmette-Guérin, (2) strengthening the recommendations for perioperative systemic chemotherapy, and (3) incorporating immunotherapy into second-line therapy for locally advanced or metastatic disease. These NCCN Guidelines Insights further discuss factors that affect integration of these recommendations into clinical practice. PMID:27697976

NCCN Guidelines Insights: Bladder Cancer, Version 2.2016.

PubMed

Clark, Peter E; Spiess, Philippe E; Agarwal, Neeraj; Bangs, Rick; Boorjian, Stephen A; Buyyounouski, Mark K; Efstathiou, Jason A; Flaig, Thomas W; Friedlander, Terence; Greenberg, Richard E; Guru, Khurshid A; Hahn, Noah; Herr, Harry W; Hoimes, Christopher; Inman, Brant A; Kader, A Karim; Kibel, Adam S; Kuzel, Timothy M; Lele, Subodh M; Meeks, Joshua J; Michalski, Jeff; Montgomery, Jeffrey S; Pagliaro, Lance C; Pal, Sumanta K; Patterson, Anthony; Petrylak, Daniel; Plimack, Elizabeth R; Pohar, Kamal S; Porter, Michael P; Sexton, Wade J; Siefker-Radtke, Arlene O; Sonpavde, Guru; Tward, Jonathan; Wile, Geoffrey; Dwyer, Mary A; Smith, Courtney

2016-10-01

These NCCN Guidelines Insights discuss the major recent updates to the NCCN Guidelines for Bladder Cancer based on the review of the evidence in conjunction with the expert opinion of the panel. Recent updates include (1) refining the recommendation of intravesical bacillus Calmette-Guérin, (2) strengthening the recommendations for perioperative systemic chemotherapy, and (3) incorporating immunotherapy into second-line therapy for locally advanced or metastatic disease. These NCCN Guidelines Insights further discuss factors that affect integration of these recommendations into clinical practice. Copyright © 2016 by the National Comprehensive Cancer Network.

Systems identification and application systems development for monitoring the physiological and health status of crewmen in space

NASA Technical Reports Server (NTRS)

Leonard, J. I.; Furukawa, S.; Vannordstrand, P. C.

1975-01-01

The use of automated, analytical techniques to aid medical support teams is suggested. Recommendations are presented for characterizing crew health in terms of: (1) wholebody function including physiological, psychological and performance factors; (2) a combination of critical performance indexes which consist of multiple factors of measurable parameters; (3) specific responses to low noise level stress tests; and (4) probabilities of future performance based on present and periodic examination of past performance. A concept is proposed for a computerized real time biomedical monitoring and health care system that would have the capability to integrate monitored data, detect off-nominal conditions based on current knowledge of spaceflight responses, predict future health status, and assist in diagnosis and alternative therapies. Mathematical models could play an important role in this approach, especially when operating in a real time mode. Recommendations are presented to update the present health monitoring systems in terms of recent advances in computer technology and biomedical monitoring systems.

Systems Perspective of Amazon Mechanical Turk for Organizational Research: Review and Recommendations

PubMed Central

Keith, Melissa G.; Tay, Louis; Harms, Peter D.

2017-01-01

Amazon Mechanical Turk (MTurk) is becoming a prevalent source of quick and cost effective data for organizational research, but there are questions about the appropriateness of the platform for organizational research. To answer these questions, we conducted an integrative review based on 75 papers evaluating the MTurk platform and 250 MTurk samples used in organizational research. This integrative review provides four contributions: (1) we analyze the trends associated with the use of MTurk samples in organizational research; (2) we develop a systems perspective (recruitment system, selection system, and work management system) to synthesize and organize the key factors influencing data collected on MTurk that may affect generalizability and data quality; (3) within each factor, we also use available MTurk samples from the organizational literature to analyze key issues (e.g., sample characteristics, use of attention checks, payment); and (4) based on our review, we provide specific recommendations and a checklist for data reporting in order to improve data transparency and enable further research on this issue. PMID:28848474

DoD Can Save Millions by Using Energy Efficient Centralized Aircraft Support Systems.

DTIC Science & Technology

1982-05-07

recommends that the Secretary of the Air Force: -- Reevaluate the decision not to install centralized systems at tactical bases. If the systems can be...discontinue using the aircraft’s onboard auxillary power units. These units consume tremendous amounts of jet fuel in providing cabin air-conditioning...requirements. Each command has been asked to analyze its bases to determine if centralized systems should be installed. Although a final decision has not

Dynamic Grover search: applications in recommendation systems and optimization problems

NASA Astrophysics Data System (ADS)

Chakrabarty, Indranil; Khan, Shahzor; Singh, Vanshdeep

2017-06-01

In the recent years, we have seen that Grover search algorithm (Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212-219, 1996) by using quantum parallelism has revolutionized the field of solving huge class of NP problems in comparisons to classical systems. In this work, we explore the idea of extending Grover search algorithm to approximate algorithms. Here we try to analyze the applicability of Grover search to process an unstructured database with a dynamic selection function in contrast to the static selection function used in the original work (Grover in Proceedings, 28th annual ACM symposium on the theory of computing, pp. 212-219, 1996). We show that this alteration facilitates us to extend the application of Grover search to the field of randomized search algorithms. Further, we use the dynamic Grover search algorithm to define the goals for a recommendation system based on which we propose a recommendation algorithm which uses binomial similarity distribution space giving us a quadratic speedup over traditional classical unstructured recommendation systems. Finally, we see how dynamic Grover search can be used to tackle a wide range of optimization problems where we improve complexity over existing optimization algorithms.

40 CFR 1065.1105 - Sampling system design.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 40 Protection of Environment 33 2014-07-01 2014-07-01 false Sampling system design. 1065.1105... Compounds § 1065.1105 Sampling system design. (a) General. We recommend that you design your SVOC batch... practical, adjust sampling times based on the emission rate of target analytes from the engine to obtain...

Modeling a Longitudinal Relational Research Data Systems

ERIC Educational Resources Information Center

Olsen, Michelle D. Hunt

2010-01-01

A study was conducted to propose a research-based model for a longitudinal data research system that addressed recommendations from a synthesis of literature related to: (1) needs reported by the U.S. Department of Education, (2) the twelve mandatory elements that define federally approved state longitudinal data systems (SLDS), (3) the…

Teaching Science through a Systems Approach

ERIC Educational Resources Information Center

Llewellyn, Douglas; Johnson, Scott

2008-01-01

Based on the recommendation of the AAAS and the NRC, middle level science is the rightful introduction for a systems approach, including the study of its parts, subsystems, interconnections, and interrelationships. Dr. Seuss's "The Lorax" provides an excellent opportunity to combine ecological consequences within a systems approach (Sweeney 2001).…

Rain rate measurement capabilities using a Seasat type radar altimeter

NASA Technical Reports Server (NTRS)

Goldhirsh, J.; Walsh, E. J.

1981-01-01

The combined use of a space-based radar and a radiometer for measurement of precipitation is discussed. Phenomena to exploit or overcome is surveyed. Basic measurement problems are discussed. Several active systems are proposed, including three ocean systems and two land-sea systems. Recommendations for future research are given.

[Temporary recommendation for use on off-label baclofen: viewpoint of Prescribers of the CAMTEA system].

PubMed

Rolland, Benjamin; Deheul, Sylvie; Danel, Thierry; Bence, Camille; Blanquart, Marie-Christine; Bonord, Alexandre; Semal, Robin; Briand, Thierry; Sochala, Michel; Dubocage, Christelle; Dupriez, François; Duquesne, Damien; Gibour, Bernard; Loosfeld, Xavier; Henebelle, Dorothée; Henon, Michael; Vernalde, Elodie; Matton, Christian; Bacquet, Jean-Eudes; Molmy, Lucie; Sarasy, François; Simioni, Nicolas; Richez, Cécile; Gentil-Spinosi, Laure; Vosgien, Véronique; Yguel, Jacques; Ledent, Thierry; Auffret, Marine; Wilquin, Maroussia; Ziolkowski, Danièle; Sochala, Michel; Gautier, Sophie; Bordet, Régis; Cottencin, Olivier

2015-01-01

The use of high dose baclofen for alcohol-dependence emerged in France from 2008 based on empirical findings, and is still off-label. However, due to the rapid increase in this prescribing practice, the French health authorities have decided to frame it using an extraordinary regulatory measure named "temporary recommendation for use" (TRU). Baclofen prescribers from CAMTEA, a regional team-based off-label system for supervising baclofen prescribing, which was developed much prior to the TRU, discuss herein the pros and cons of this measure and the applicability of its different aspects in the daily clinical practice. © 2014 Société Française de Pharmacologie et de Thérapeutique.

Integrating complex business processes for knowledge-driven clinical decision support systems.

PubMed

Kamaleswaran, Rishikesan; McGregor, Carolyn

2012-01-01

This paper presents in detail the component of the Complex Business Process for Stream Processing framework that is responsible for integrating complex business processes to enable knowledge-driven Clinical Decision Support System (CDSS) recommendations. CDSSs aid the clinician in supporting the care of patients by providing accurate data analysis and evidence-based recommendations. However, the incorporation of a dynamic knowledge-management system that supports the definition and enactment of complex business processes and real-time data streams has not been researched. In this paper we discuss the process web service as an innovative method of providing contextual information to a real-time data stream processing CDSS.

Impact of inertia, friction, and backlash upon force control in telemanipulation

NASA Technical Reports Server (NTRS)

Duffie, Neil A.; Zik, John J.; Wiker, Steven F.; Gale, Karen L.

1991-01-01

The mechanical behavior of master controllers of telemanipulators has been a concern of both designers and implementors of telerobotic systems. In general, the literature recommends that telemanipulator systems be constructed that minimize inertia, friction, and backlash in an effort to improve telemanipulative performance. For the most part, these recommendations are founded upon theoretical analysis or simply intuition. Although these recommendations are not challenged on their merit, the material results are measured of building and fielding telemanipulators that possess less than ideal mechanical behaviors. Experiments are described in which forces in a mechanical system with human input are evaluated as a function of mechanical characteristics such as inertia, friction, and backlash. Results indicate that the ability of the human to maintain gripping forces was relatively unaffected by dynamic characteristics in the range studied, suggesting that telemanipulator design in this range should be based on task level force control requirements rather than human factors.

International clinical guideline for the management of classical galactosemia: diagnosis, treatment, and follow-up.

PubMed

Welling, Lindsey; Bernstein, Laurie E; Berry, Gerard T; Burlina, Alberto B; Eyskens, François; Gautschi, Matthias; Grünewald, Stephanie; Gubbels, Cynthia S; Knerr, Ina; Labrune, Philippe; van der Lee, Johanna H; MacDonald, Anita; Murphy, Elaine; Portnoi, Pat A; Õunap, Katrin; Potter, Nancy L; Rubio-Gozalbo, M Estela; Spencer, Jessica B; Timmers, Inge; Treacy, Eileen P; Van Calcar, Sandra C; Waisbren, Susan E; Bosch, Annet M

2017-03-01

Classical galactosemia (CG) is an inborn error of galactose metabolism. Evidence-based guidelines for the treatment and follow-up of CG are currently lacking, and treatment and follow-up have been demonstrated to vary worldwide. To provide patients around the world the same state-of-the-art in care, members of The Galactosemia Network (GalNet) developed an evidence-based and internationally applicable guideline for the diagnosis, treatment, and follow-up of CG. The guideline was developed using the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system. A systematic review of the literature was performed, after key questions were formulated during an initial GalNet meeting. The first author and one of the working group experts conducted data-extraction. All experts were involved in data-extraction. Quality of the body of evidence was evaluated and recommendations were formulated. Whenever possible recommendations were evidence-based, if not they were based on expert opinion. Consensus was reached by multiple conference calls, consensus rounds via e-mail and a final consensus meeting. Recommendations addressing diagnosis, dietary treatment, biochemical monitoring, and follow-up of clinical complications were formulated. For all recommendations but one, full consensus was reached. A 93 % consensus was reached on the recommendation addressing age at start of bone density screening. During the development of this guideline, gaps of knowledge were identified in most fields of interest, foremost in the fields of treatment and follow-up.

Achieving Optimal Privacy in Trust-Aware Social Recommender Systems

NASA Astrophysics Data System (ADS)

Dokoohaki, Nima; Kaleli, Cihan; Polat, Huseyin; Matskin, Mihhail

Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers proposed for utilization of interpersonal trust between users, to alleviate many of these crucial shortcomings. Till now, attention has been mainly paid to strong points about trust-aware recommenders such as alleviating profile sparsity or calculation cost efficiency, while least attention has been paid on investigating the notion of privacy surrounding the disclosure of individual ratings and most importantly protection of trust computation across social networks forming the backbone of these systems. To contribute to addressing problem of privacy in trust-aware recommenders, within this paper, first we introduce a framework for enabling privacy-preserving trust-aware recommendation generation. While trust mechanism aims at elevating recommender's accuracy, to preserve privacy, accuracy of the system needs to be decreased. Since within this context, privacy and accuracy are conflicting goals we show that a Pareto set can be found as an optimal setting for both privacy-preserving and trust-enabling mechanisms. We show that this Pareto set, when used as the configuration for measuring the accuracy of base collaborative filtering engine, yields an optimized tradeoff between conflicting goals of privacy and accuracy. We prove this concept along with applicability of our framework by experimenting with accuracy and privacy factors, and we show through experiment how such optimal set can be inferred.

Use of a remote clinical decision support service for a multicenter trial to implement prediction rules for children with minor blunt head trauma.

PubMed

Goldberg, Howard S; Paterno, Marilyn D; Grundmeier, Robert W; Rocha, Beatriz H; Hoffman, Jeffrey M; Tham, Eric; Swietlik, Marguerite; Schaeffer, Molly H; Pabbathi, Deepika; Deakyne, Sara J; Kuppermann, Nathan; Dayan, Peter S

2016-03-01

To evaluate the architecture, integration requirements, and execution characteristics of a remote clinical decision support (CDS) service used in a multicenter clinical trial. The trial tested the efficacy of implementing brain injury prediction rules for children with minor blunt head trauma. We integrated the Epic(®) electronic health record (EHR) with the Enterprise Clinical Rules Service (ECRS), a web-based CDS service, at two emergency departments. Patterns of CDS review included either a delayed, near-real-time review, where the physician viewed CDS recommendations generated by the nursing assessment, or a real-time review, where the physician viewed recommendations generated by their own documentation. A backstopping, vendor-based CDS triggered with zero delay when no recommendation was available in the EHR from the web-service. We assessed the execution characteristics of the integrated system and the source of the generated recommendations viewed by physicians. The ECRS mean execution time was 0.74 ±0.72 s. Overall execution time was substantially different at the two sites, with mean total transaction times of 19.67 and 3.99 s. Of 1930 analyzed transactions from the two sites, 60% (310/521) of all physician documentation-initiated recommendations and 99% (1390/1409) of all nurse documentation-initiated recommendations originated from the remote web service. The remote CDS system was the source of recommendations in more than half of the real-time cases and virtually all the near-real-time cases. Comparisons are limited by allowable variation in user workflow and resolution of the EHR clock. With maturation and adoption of standards for CDS services, remote CDS shows promise to decrease time-to-trial for multicenter evaluations of candidate decision support interventions. Copyright © 2015 Elsevier Ireland Ltd. All rights reserved.

Evidence-based management of systemic sclerosis: Navigating recommendations and guidelines.

PubMed

Pellar, Russell Edward; Pope, Janet Elizabeth

2017-06-01

Systemic sclerosis (SSc) is a rare heterogeneous connective tissue disease. Recommendations addressing the major issues in the management of SSc including screening and treatment of organ complications are needed. The updated European League Against Rheumatism/European Scleroderma Trial and Research (EULAR/EUSTAR) and the British Society of Rheumatology (BSR) and British Health Professionals in Rheumatology (BHPR) guidelines were compared and contrasted. The updated EULAR/EUSTAR guidelines focus specifically on the management of SSc features and include data on newer therapeutic modalities and mention a research agenda. These recommendations are pharmacologic, with few guidelines regarding investigations and non-pharmacologic management. Recommendations from BSR/BHPR are similar to the organ manifestations mentioned in the EULAR/EUSTAR recommendations, and expand on several domains of treatment, including general measures, non-pharmacologic treatment, cardiac involvement, calcinosis, and musculoskeletal features. The guidelines usually agree with one another. Limitations include the lack of guidance for combination or second-line therapy, algorithmic suggestions, the absence of evidence-based recommendations regarding the treatment of specific complications (i.e., gastric antral ectasia and erectile dysfunction). Consensus for when to treat interstitial lung disease in SSc is lacking. There are differences between Europe and North American experts due to access and indications for certain therapies. Care gaps in SSc have been demonstrated so the EULAR/EUSTAR and BSR/BHP guidelines can promote best practices. Certain complications warrant active investigation to further improve outcomes in SSc and future updates of these recommendations. Care gaps in SSc have been demonstrated so the EULAR/EUSTAR and BSR/BHP guidelines can promote best practices. Certain complications warrant active investigation to further improve outcomes in SSc. Copyright © 2017 Elsevier Inc. All rights reserved.

Operating Policies and Procedures of Computer Data-Base Systems.

ERIC Educational Resources Information Center

Anderson, David O.

Speaking on the operating policies and procedures of computer data bases containing information on students, the author divides his remarks into three parts: content decisions, data base security, and user access. He offers nine recommended practices that should increase the data base's usefulness to the user community: (1) the cost of developing…

A fast combination method in DSmT and its application to recommender system

PubMed Central

Liu, Yihai

2018-01-01

In many applications involving epistemic uncertainties usually modeled by belief functions, it is often necessary to approximate general (non-Bayesian) basic belief assignments (BBAs) to subjective probabilities (called Bayesian BBAs). This necessity occurs if one needs to embed the fusion result in a system based on the probabilistic framework and Bayesian inference (e.g. tracking systems), or if one needs to make a decision in the decision making problems. In this paper, we present a new fast combination method, called modified rigid coarsening (MRC), to obtain the final Bayesian BBAs based on hierarchical decomposition (coarsening) of the frame of discernment. Regarding this method, focal elements with probabilities are coarsened efficiently to reduce computational complexity in the process of combination by using disagreement vector and a simple dichotomous approach. In order to prove the practicality of our approach, this new approach is applied to combine users’ soft preferences in recommender systems (RSs). Additionally, in order to make a comprehensive performance comparison, the proportional conflict redistribution rule #6 (PCR6) is regarded as a baseline in a range of experiments. According to the results of experiments, MRC is more effective in accuracy of recommendations compared to original Rigid Coarsening (RC) method and comparable in computational time. PMID:29351297

Feasibility of using algorithm-based clinical decision support for symptom assessment and management in lung cancer.

PubMed

Cooley, Mary E; Blonquist, Traci M; Catalano, Paul J; Lobach, David F; Halpenny, Barbara; McCorkle, Ruth; Johns, Ellis B; Braun, Ilana M; Rabin, Michael S; Mataoui, Fatma Zohra; Finn, Kathleen; Berry, Donna L; Abrahm, Janet L

2015-01-01

Distressing symptoms interfere with the quality of life in patients with lung cancer. Algorithm-based clinical decision support (CDS) to improve evidence-based management of isolated symptoms seems promising, but no reports yet address multiple symptoms. This study examined the feasibility of CDS for a Symptom Assessment and Management Intervention targeting common symptoms in patients with lung cancer (SAMI-L) in ambulatory oncology. The study objectives were to evaluate completion and delivery rates of the SAMI-L report and clinician adherence to the algorithm-based recommendations. Patients completed a web-based symptom assessment and SAMI-L created tailored recommendations for symptom management. Completion of assessments and delivery of reports were recorded. Medical record review assessed clinician adherence to recommendations. Feasibility was defined as 75% or higher report completion and delivery rates and 80% or higher clinician adherence to recommendations. Descriptive statistics and generalized estimating equations were used for data analyses. Symptom assessment completion was 84% (95% CI=81-87%). Delivery of completed reports was 90% (95% CI=86-93%). Depression (36%), pain (30%), and fatigue (18%) occurred most frequently, followed by anxiety (11%) and dyspnea (6%). On average, overall recommendation adherence was 57% (95% CI=52-62%) and was not dependent on the number of recommendations (P=0.45). Adherence was higher for anxiety (66%; 95% CI=55-77%), depression (64%; 95% CI=56-71%), pain (62%; 95% CI=52-72%), and dyspnea (51%; 95% CI=38-64%) than for fatigue (38%; 95% CI=28-47%). The CDS systems, such as SAMI-L, have the potential to fill a gap in promoting evidence-based care. Copyright © 2015 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

Guidelines on eosinophilic esophagitis: evidence-based statements and recommendations for diagnosis and management in children and adults

PubMed Central

Molina-Infante, Javier; Arias, Ángel; von Arnim, Ulrike; Bredenoord, Albert J; Bussmann, Christian; Amil Dias, Jorge; Bove, Mogens; González-Cervera, Jesús; Larsson, Helen; Miehlke, Stephan; Papadopoulou, Alexandra; Rodríguez-Sánchez, Joaquín; Ravelli, Alberto; Ronkainen, Jukka; Santander, Cecilio; Schoepfer, Alain M; Storr, Martin A; Terreehorst, Ingrid; Straumann, Alex; Attwood, Stephen E

2017-01-01

Introduction Eosinophilic esophagitis (EoE) is one of the most prevalent esophageal diseases and the leading cause of dysphagia and food impaction in children and young adults. This underlines the importance of optimizing diagnosys and treatment of the condition, especially after the increasing amount of knowledge on EoE recently published. Therefore, the UEG, EAACI ESPGHAN, and EUREOS deemed it necessary to update the current guidelines regarding conceptual and epidemiological aspects, diagnosis, and treatment of EoE. Methods General methodology according to the Appraisal of Guidelines for Research and Evaluation (AGREE) II and the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) system was used in order to comply with current standards of evidence assessment in formulation of recommendations. An extensive literature search was conducted up to August 2015 and periodically updated. The working group consisted of gastroenterologists, allergists, pediatricians, otolaryngologists, pathologists, and epidemiologists. Systematic evidence-based reviews were performed based upon relevant clinical questions with respect to patient-important outcomes. Results The guidelines include updated concept of EoE, evaluated information on disease epidemiology, risk factors, associated conditions, and natural history of EoE in children and adults. Diagnostic conditions and criteria, the yield of diagnostic and disease monitoring procedures, and evidence-based statements and recommendation on the utility of the several treatment options for patients EoE are provided. Recommendations on how to choose and implement treatment and long-term management are provided based on expert opinion and best clinical practice. Conclusion Evidence-based recommendations for EoE diagnosis, treatment modalities, and patients’ follow up are proposed in the guideline. PMID:28507746

Information filtering in evolving online networks

NASA Astrophysics Data System (ADS)

Chen, Bo-Lun; Li, Fen-Fen; Zhang, Yong-Jun; Ma, Jia-Lin

2018-02-01

Recommender systems use the records of users' activities and profiles of both users and products to predict users' preferences in the future. Considerable works towards recommendation algorithms have been published to solve the problems such as accuracy, diversity, congestion, cold-start, novelty, coverage and so on. However, most of these research did not consider the temporal effects of the information included in the users' historical data. For example, the segmentation of the training set and test set was completely random, which was entirely different from the real scenario in recommender systems. More seriously, all the objects are treated as the same, regardless of the new, the popular or obsoleted products, so do the users. These data processing methods always lose useful information and mislead the understanding of the system's state. In this paper, we detailed analyzed the difference of the network structure between the traditional random division method and the temporal division method on two benchmark data sets, Netflix and MovieLens. Then three classical recommendation algorithms, Global Ranking method, Collaborative Filtering and Mass Diffusion method, were employed. The results show that all these algorithms became worse in all four key indicators, ranking score, precision, popularity and diversity, in the temporal scenario. Finally, we design a new recommendation algorithm based on both users' and objects' first appearance time in the system. Experimental results showed that the new algorithm can greatly improve the accuracy and other metrics.

Leveraging tagging and rating for recommendation: RMF meets weighted diffusion on tripartite graphs

NASA Astrophysics Data System (ADS)

Li, Jianguo; Tang, Yong; Chen, Jiemin

2017-10-01

Recommender systems (RSs) have been a widely exploited approach to solving the information overload problem. However, the performance is still limited due to the extreme sparsity of the rating data. With the popularity of Web 2.0, the social tagging system provides more external information to improve recommendation accuracy. Although some existing approaches combine the matrix factorization models with the tag co-occurrence and context of tags, they neglect the issue of tag sparsity that would also result in inaccurate recommendations. Consequently, in this paper, we propose a novel hybrid collaborative filtering model named WUDiff_RMF, which improves regularized matrix factorization (RMF) model by integrating Weighted User-Diffusion-based CF algorithm(WUDiff) that obtains the information of similar users from the weighted tripartite user-item-tag graph. This model aims to capture the degree correlation of the user-item-tag tripartite network to enhance the performance of recommendation. Experiments conducted on four real-world datasets demonstrate that our approach significantly performs better than already widely used methods in the accuracy of recommendation. Moreover, results show that WUDiff_RMF can alleviate the data sparsity, especially in the circumstance that users have made few ratings and few tags.

Comparing a Mobile Decision Support System Versus the Use of Printed Materials for the Implementation of an Evidence-Based Recommendation: Protocol for a Qualitative Evaluation.

PubMed

Camacho, Jhon; Medina Ch, Ana María; Landis-Lewis, Zach; Douglas, Gerald; Boyce, Richard

2018-04-13

The distribution of printed materials is the most frequently used strategy to disseminate and implement clinical practice guidelines, although several studies have shown that the effectiveness of this approach is modest at best. Nevertheless, there is insufficient evidence to support the use of other strategies. Recent research has shown that the use of computerized decision support presents a promising approach to address some aspects of this problem. The aim of this study is to provide qualitative evidence on the potential effect of mobile decision support systems to facilitate the implementation of evidence-based recommendations included in clinical practice guidelines. We will conduct a qualitative study with two arms to compare the experience of primary care physicians while they try to implement an evidence-based recommendation in their clinical practice. In the first arm, we will provide participants with a printout of the guideline article containing the recommendation, while in the second arm, we will provide participants with a mobile app developed after formalizing the recommendation text into a clinical algorithm. Data will be collected using semistructured and open interviews to explore aspects of behavioral change and technology acceptance involved in the implementation process. The analysis will be comprised of two phases. During the first phase, we will conduct a template analysis to identify barriers and facilitators in each scenario. Then, during the second phase, we will contrast the findings from each arm to propose hypotheses about the potential impact of the system. We have formalized the narrative in the recommendation into a clinical algorithm and have developed a mobile app. Data collection is expected to occur during 2018, with the first phase of analysis running in parallel. The second phase is scheduled to conclude in July 2019. Our study will further the understanding of the role of mobile decision support systems in the implementation of clinical practice guidelines. Furthermore, we will provide qualitative evidence to aid decisions made by low- and middle-income countries' ministries of health about investments in these technologies. ©Jhon Camacho, Ana María Medina Ch, Zach Landis-Lewis, Gerald Douglas, Richard Boyce. Originally published in JMIR Research Protocols (http://www.researchprotocols.org), 13.04.2018.

EULAR/PReS standards and recommendations for the transitional care of young people with juvenile-onset rheumatic diseases.

PubMed

Foster, Helen E; Minden, Kirsten; Clemente, Daniel; Leon, Leticia; McDonagh, Janet E; Kamphuis, Sylvia; Berggren, Karin; van Pelt, Philomine; Wouters, Carine; Waite-Jones, Jennifer; Tattersall, Rachel; Wyllie, Ruth; Stones, Simon R; Martini, Alberto; Constantin, Tamas; Schalm, Susanne; Fidanci, Berna; Erer, Burak; Demirkaya, Erkan; Ozen, Seza; Carmona, Loreto

2017-04-01

To develop standards and recommendations for transitional care for young people (YP) with juvenile-onset rheumatic and musculoskeletal diseases (jRMD). The consensus process involved the following: (1) establishing an international expert panel to include patients and representatives from multidisciplinary teams in adult and paediatric rheumatology; (2) a systematic review of published models of transitional care in jRMDs, potential standards and recommendations, strategies for implementation and tools to evaluate services and outcomes; (3) setting the framework, developing the process map and generating a first draft of standards and recommendations; (4) further iteration of recommendations; (5) establishing consensus recommendations with Delphi methodology and (6) establishing standards and quality indicators. The final consensus derived 12 specific recommendations for YP with jRMD focused on transitional care. These included: high-quality, multidisciplinary care starting in early adolescence; the integral role of a transition co-ordinator; transition policies and protocols; efficient communications; transfer documentation; an open electronic-based platform to access resources; appropriate training for paediatric and adult healthcare teams; secure funding to continue treatments and services into adult rheumatology and the need for increased evidence to inform best practice. These consensus-based recommendations inform strategies to reach optimal outcomes in transitional care for YP with jRMD based on available evidence and expert opinion. They need to be implemented in the context of individual countries, healthcare systems and regulatory frameworks. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Reducing Tobacco Use among Youth: Community-Based Approaches. A Guideline for Prevention Practitioners. Prevention Enhancement Protocols System (PEPS) Series.

ERIC Educational Resources Information Center

Birch & Davis Associates, Inc., Silver Spring, MD.

A substantial knowledge base exists on reduction of tobacco use by youth. Effective prevention in this area can have major health and economic benefits. Information from research and prevention practice, organized by means of the Prevention Enhancement Protocols System (PEPS), is provided in the form of guidelines and recommendations for planning…

Prophylaxis and treatment of seasickness

NASA Technical Reports Server (NTRS)

Yefremenko, M.

1980-01-01

Depending upon the dominant type of symptoms, seasickness is divided into three forms: nervous, gastro-intestinal, and cardiovascular. Various medications are recommended appropriate to these forms. The first goal is normalization of impaired system functions as well as metabolism and the electrolyte and acid-base condition of the organism. Dietary recommendations are made and specific suggestions on the use of physical exercise, including prophylatic vestibular training exercises.

Multiple Interests of Users in Collaborative Tagging Systems

NASA Astrophysics Data System (ADS)

Au Yeung, Ching-Man; Gibbins, Nicholas; Shadbolt, Nigel

Performance of recommender systems depends on whether the user profiles contain accurate information about the interests of the users, and this in turn relies on whether enough information about their interests can be collected. Collaborative tagging systems allow users to use their own words to describe their favourite resources, resulting in some user-generated categorisation schemes commonly known as folksonomies. Folksonomies thus contain rich information about the interests of the users, which can be used to support various recommender systems. Our analysis of the folksonomy in Delicious reveals that the interests of a single user can be very diverse. Traditional methods for representing interests of users are usually not able to reflect such diversity. We propose a method to construct user profiles of multiple interests from folksonomies based on a network clustering technique. Our evaluation shows that the proposed method is able to generate user profiles which reflect the diversity of user interests and can be used as a basis of providing more focused recommendation to the users.

Alignment of practice guidelines with targeted-therapy drug funding policies in Ontario.

PubMed

Ramjeesingh, R; Meyer, R M; Brouwers, M; Chen, B E; Booth, C M

2013-02-01

We evaluated clinical practice guideline (cpg) recommendations from Cancer Care Ontario's Program in Evidence-Based Care (pebc) for molecularly targeted systemic treatments (tts) and subsequent funding decisions from the Ontario Ministry of Health and Long-Term Care. We identified pebc cpgs on tt published before June 1, 2010, and extracted information regarding the key evidence cited in support of cpg recommendations and the effect size associated with each tt. Those variables were compared with mohltc funding decisions as of June 2011. From 23 guidelines related to 17 tts, we identified 43 recommendations, among which 38 (88%) endorsed tt use. Among all the recommendations, 38 (88%) were based on published key evidence, with 82% (31 of 38) being supported by meta-analyses or phase iii trials. For the 38 recommendations endorsing tts, funding was approved in 28 (74%; odds ratio related to cpg recommendation: 29.9; p = 0.003). We were unable to demonstrate that recommendations associated with statistically significant improvements in overall survival [os: 14 of 16 (88%) vs. 8 of 14 (57%); p = 0.10] or disease- (dfs) or progression-free survival [pfs: 16 of 21 (76%) vs. 3 of 5 (60%); p = 0.59] were more likely to be funded than those with no significant difference. Moreover, we did not observe significant associations between funding approvals and absolute improvements of 3 months or more in os [6 of 6 (100%) vs. 3 of 6 (50%), p = 0.18] or pfs [6 of 8 (75%) vs. 10 of 12 (83%), p = 1.00]. For use of tts, most recommendations in pebc cpgs are based on meta-analyses or phase iii data, and funding decisions were strongly associated with those recommendations. Our data suggest a trend toward increased rates of funding for therapies with statistically significant improvements in os.

RB-ARD: A proof of concept rule-based abort

NASA Technical Reports Server (NTRS)

Smith, Richard; Marinuzzi, John

1987-01-01

The Abort Region Determinator (ARD) is a console program in the space shuttle mission control center. During shuttle ascent, the Flight Dynamics Officer (FDO) uses the ARD to determine the possible abort modes and make abort calls for the crew. The goal of the Rule-based Abort region Determinator (RB/ARD) project was to test the concept of providing an onboard ARD for the shuttle or an automated ARD for the mission control center (MCC). A proof of concept rule-based system was developed on a LMI Lambda computer using PICON, a knowdedge-based system shell. Knowdedge derived from documented flight rules and ARD operation procedures was coded in PICON rules. These rules, in conjunction with modules of conventional code, enable the RB-ARD to carry out key parts of the ARD task. Current capabilities of the RB-ARD include: continuous updating of the available abort mode, recognition of a limited number of main engine faults and recommendation of safing actions. Safing actions recommended by the RB-ARD concern the Space Shuttle Main Engine (SSME) limit shutdown system and powerdown of the SSME Ac buses.

Management of a suspicious adnexal mass: a clinical practice guideline

PubMed Central

Dodge, J.E.; Covens, A.L.; Lacchetti, C.; Elit, L.M.; Le, T.; Devries–Aboud, M.; Fung-Kee-Fung, M.

2012-01-01

Questions What is the optimal strategy for preoperative identification of the adnexal mass suspicious for ovarian cancer? What is the most appropriate surgical procedure for a woman who presents with an adnexal mass suspicious for malignancy? Perspectives In Canada in 2010, 2600 new cases of ovarian cancer were estimated to have been diagnosed, and of those patients, 1750 were estimated to have died, making ovarian cancer the 7th most prevalent form of cancer and the 5th leading cause of cancer death in Canadian women. Women with ovarian cancer typically have subtle, nonspecific symptoms such as abdominal pain, bloating, changes in bowel frequency, and urinary or pelvic symptoms, making early detection difficult. Thus, most ovarian cancer cases are diagnosed at an advanced stage, when the cancer has spread outside the pelvis. Because of late diagnosis, the 5-year relative survival ratio for ovarian cancer in Canada is only 40%. Unfortunately, because of the low positive predictive value of potential screening tests (cancer antigen 125 and ultrasonography), there is currently no screening strategy for ovarian cancer. The purpose of this document is to identify evidence that would inform optimal recommended protocols for the identification and surgical management of adnexal masses suspicious for malignancy. Outcomes Outcomes of interest for the identification question included sensitivity and specificity. Outcomes of interest for the surgical question included optimal surgery, overall survival, progression-free or disease-free survival, reduction in the number of surgeries, morbidity, adverse events, and quality of life. Methodology After a systematic review, a practice guideline containing clinical recommendations relevant to patients in Ontario was drafted. The practice guideline was reviewed and approved by the Gynecology Disease Site Group and the Report Approval Panel of the Program in Evidence-based Care. External review by Ontario practitioners was obtained through a survey, the results of which were incorporated into the practice guideline. Practice Guideline These recommendations apply to adult women presenting with a suspicious adnexal mass, either symptomatic or asymptomatic. Identification of an Adnexal Mass Suspicious for Ovarian Cancer Sonography (particularly 3-dimensional sonography), magnetic resonance imaging (mri), and computed tomography (ct) imaging are each recommended for differentiating malignant from benign ovarian masses. However, the working group offers the following further recommendations, based on their expert consensus opinion and a consideration of availability, access, and harm: Where technically feasible, transvaginal sonography should be the modality of first choice in patients with a suspicious isolated ovarian mass.To help clarify malignant potential in patients in whom ultrasonography may be unreliable, mri is the most appropriate test.In cases in which extra-ovarian disease is suspected or needs to be ruled out, ct is the most useful technique.Evaluation of an adnexal mass by Doppler technology alone is not recommended. Doppler technology should be combined with a morphology assessment.Ultrasonography-based morphology scoring systems can be used to differentiate benign from malignant adnexal masses. These scoring systems are based on specific ultrasound parameters, each with several scores base on determined features. All evaluated scoring systems were found to have an acceptable level of sensitivity and specificity; the choice of scoring system may therefore be made based on clinician preference.As a standalone modality, serum cancer antigen 125 is not recommended for distinguishing between benign and malignant adnexal masses.Frozen sections for the intraoperative diagnosis of a suspicious adnexal mass is recommended in settings in which availability and patient preference allow. Surgical Procedures for an Adnexal Mass Suspicious for Malignancy To improve survival, comprehensive surgical staging with lymphadenectomy is recommended for the surgical management of patients with early-stage ovarian cancer. Laparoscopy is a reasonable alternative to laparotomy, provided that appropriate surgery and staging can be done. The choice between laparoscopy and laparotomy should be based on patient and clinician preference. Discussion with a gynecologic oncologist is recommended. Fertility-preserving surgery is an acceptable alternative to more extensive surgery in patients with low-malignant-potential tumours and those with well-differentiated surgical stage i ovarian cancer. Discussion with a gynecologic oncologist is recommended. PMID:22876153

Report of the IAU Working Group on Cartographic Coordinates and Rotational Elements: 2015

NASA Astrophysics Data System (ADS)

Archinal, B. A.; Acton, C. H.; A'Hearn, M. F.; Conrad, A.; Consolmagno, G. J.; Duxbury, T.; Hestroffer, D.; Hilton, J. L.; Kirk, R. L.; Klioner, S. A.; McCarthy, D.; Meech, K.; Oberst, J.; Ping, J.; Seidelmann, P. K.; Tholen, D. J.; Thomas, P. C.; Williams, I. P.

2018-03-01

This report continues the practice where the IAU Working Group on Cartographic Coordinates and Rotational Elements revises recommendations regarding those topics for the planets, satellites, minor planets, and comets approximately every 3 years. The Working Group has now become a "functional working group" of the IAU, and its membership is open to anyone interested in participating. We describe the procedure for submitting questions about the recommendations given here or the application of these recommendations for creating a new or updated coordinate system for a given body. Regarding body orientation, the following bodies have been updated: Mercury, based on MESSENGER results; Mars, along with a refined longitude definition; Phobos; Deimos; (1) Ceres; (52) Europa; (243) Ida; (2867) Šteins; Neptune; (134340) Pluto and its satellite Charon; comets 9P/Tempel 1, 19P/Borrelly, 67P/Churyumov-Gerasimenko, and 103P/Hartley 2, noting that such information is valid only between specific epochs. The special challenges related to mapping 67P/Churyumov-Gerasimenko are also discussed. Approximate expressions for the Earth have been removed in order to avoid confusion, and the low precision series expression for the Moon's orientation has been removed. The previously online only recommended orientation model for (4) Vesta is repeated with an explanation of how it was updated. Regarding body shape, text has been included to explain the expected uses of such information, and the relevance of the cited uncertainty information. The size of the Sun has been updated, and notation added that the size and the ellipsoidal axes for the Earth and Jupiter have been recommended by an IAU Resolution. The distinction of a reference radius for a body (here, the Moon and Titan) is made between cartographic uses, and for orthoprojection and geophysical uses. The recommended radius for Mercury has been updated based on MESSENGER results. The recommended radius for Titan is returned to its previous value. Size information has been updated for 13 other Saturnian satellites and added for Aegaeon. The sizes of Pluto and Charon have been updated. Size information has been updated for (1) Ceres and given for (16) Psyche and (52) Europa. The size of (25143) Itokawa has been corrected. In addition, the discussion of terminology for the poles (hemispheres) of small bodies has been modified and a discussion on cardinal directions added. Although they continue to be used for planets and their satellites, it is assumed that the planetographic and planetocentric coordinate system definitions do not apply to small bodies. However, planetocentric and planetodetic latitudes and longitudes may be used on such bodies, following the right-hand rule. We repeat our previous recommendations that planning and efforts be made to make controlled cartographic products; newly recommend that common formulations should be used for orientation and size; continue to recommend that a community consensus be developed for the orientation models of Jupiter and Saturn; newly recommend that historical summaries of the coordinate systems for given bodies should be developed, and point out that for planets and satellites planetographic systems have generally been historically preferred over planetocentric systems, and that in cases when planetographic coordinates have been widely used in the past, there is no obvious advantage to switching to the use of planetocentric coordinates. The Working Group also requests community input on the question submitting process, posting of updates to the Working Group website, and on whether recommendations should be made regarding exoplanet coordinate systems.

Teleconsultation in children with abdominal pain: a comparison of physician triage recommendations and an established paediatric telephone triage protocol.

PubMed

Staub, Gabrielle Marmier; von Overbeck, Jan; Blozik, Eva

2013-09-30

Quality assessment and continuous quality feedback to the staff is crucial for safety and efficiency of teleconsultation and triage. This study evaluates whether it is feasible to use an already existing telephone triage protocol to assess the appropriateness of point-of-care and time-to-treat recommendations after teleconsultations. Based on electronic patient records, we retrospectively compared the point-of-care and time-to-treat recommendations of the paediatric telephone triage protocol with the actual recommendations of trained physicians for children with abdominal pain, following a teleconsultation. In 59 of 96 cases (61%) these recommendations were congruent with the paediatric telephone protocol. Discrepancies were either of organizational nature, due to factors such as local referral policies or gatekeeping insurance models, or of medical origin, such as milder than usual symptoms or clear diagnosis of a minor ailment. A paediatric telephone triage protocol may be applicable in healthcare systems other than the one in which it has been developed, if triage rules are adapted to match the organisational aspects of the local healthcare system.

Walking on a User Similarity Network towards Personalized Recommendations

PubMed Central

Gan, Mingxin

2014-01-01

Personalized recommender systems have been receiving more and more attention in addressing the serious problem of information overload accompanying the rapid evolution of the world-wide-web. Although traditional collaborative filtering approaches based on similarities between users have achieved remarkable success, it has been shown that the existence of popular objects may adversely influence the correct scoring of candidate objects, which lead to unreasonable recommendation results. Meanwhile, recent advances have demonstrated that approaches based on diffusion and random walk processes exhibit superior performance over collaborative filtering methods in both the recommendation accuracy and diversity. Building on these results, we adopt three strategies (power-law adjustment, nearest neighbor, and threshold filtration) to adjust a user similarity network from user similarity scores calculated on historical data, and then propose a random walk with restart model on the constructed network to achieve personalized recommendations. We perform cross-validation experiments on two real data sets (MovieLens and Netflix) and compare the performance of our method against the existing state-of-the-art methods. Results show that our method outperforms existing methods in not only recommendation accuracy and diversity, but also retrieval performance. PMID:25489942

Detection of abnormal item based on time intervals for recommender systems.

PubMed

Gao, Min; Yuan, Quan; Ling, Bin; Xiong, Qingyu

2014-01-01

With the rapid development of e-business, personalized recommendation has become core competence for enterprises to gain profits and improve customer satisfaction. Although collaborative filtering is the most successful approach for building a recommender system, it suffers from "shilling" attacks. In recent years, the research on shilling attacks has been greatly improved. However, the approaches suffer from serious problem in attack model dependency and high computational cost. To solve the problem, an approach for the detection of abnormal item is proposed in this paper. In the paper, two common features of all attack models are analyzed at first. A revised bottom-up discretized approach is then proposed based on time intervals and the features for the detection. The distributions of ratings in different time intervals are compared to detect anomaly based on the calculation of chi square distribution (χ(2)). We evaluated our approach on four types of items which are defined according to the life cycles of these items. The experimental results show that the proposed approach achieves a high detection rate with low computational cost when the number of attack profiles is more than 15. It improves the efficiency in shilling attacks detection by narrowing down the suspicious users.

Conducting Creativity Brainstorming Sessions in Small and Medium-Sized Enterprises Using Computer-Mediated Communication Tools

NASA Astrophysics Data System (ADS)

Murthy, Uday S.

A variety of Web-based low cost computer-mediated communication (CMC) tools are now available for use by small and medium-sized enterprises (SME). These tools invariably incorporate chat systems that facilitate simultaneous input in synchronous electronic meeting environments, allowing what is referred to as “electronic brainstorming.” Although prior research in information systems (IS) has established that electronic brainstorming can be superior to face-to-face brainstorming, there is a lack of detailed guidance regarding how CMC tools should be optimally configured to foster creativity in SMEs. This paper discusses factors to be considered in using CMC tools for creativity brainstorming and proposes recommendations for optimally configuring CMC tools to enhance creativity in SMEs. The recommendations are based on lessons learned from several recent experimental studies on the use of CMC tools for rich brainstorming tasks that require participants to invoke domain-specific knowledge. Based on a consideration of the advantages and disadvantages of the various configuration options, the recommendations provided can form the basis for selecting a CMC tool for creativity brainstorming or for creating an in-house CMC tool for the purpose.

QoS prediction for web services based on user-trust propagation model

NASA Astrophysics Data System (ADS)

Thinh, Le-Van; Tu, Truong-Dinh

2017-10-01

There is an important online role for Web service providers and users; however, the rapidly growing number of service providers and users, it can create some similar functions among web services. This is an exciting area for research, and researchers seek to to propose solutions for the best service to users. Collaborative filtering (CF) algorithms are widely used in recommendation systems, although these are less effective for cold-start users. Recently, some recommender systems have been developed based on social network models, and the results show that social network models have better performance in terms of CF, especially for cold-start users. However, most social network-based recommendations do not consider the user's mood. This is a hidden source of information, and is very useful in improving prediction efficiency. In this paper, we introduce a new model called User-Trust Propagation (UTP). The model uses a combination of trust and the mood of users to predict the QoS value and matrix factorisation (MF), which is used to train the model. The experimental results show that the proposed model gives better accuracy than other models, especially for the cold-start problem.

ASSESSMENT AND RECOMMENDATIONS FOR IMPROVING THE PERFORMANCE OF WASTE CONTAINMENT SYSTEMS

EPA Science Inventory

This broad-based study addressed three categories of issues related to the design,
construction, and performance of waste containment systems used at landfills, surface
impoundments, and waste piles, and in the remediation of contaminated sites. Geosynthetic materials have...

Composition and analysis of a model waste for a CELSS (Controlled Ecological Life Support System)

NASA Technical Reports Server (NTRS)

Wydeven, T. J.

1983-01-01

A model waste based on a modest vegetarian diet is given, including composition and elemental analysis. Its use is recommended for evaluation of candidate waste treatment processes for a Controlled Ecological Life Support System (CELSS).

The Status of the Rural Status Offender.

ERIC Educational Resources Information Center

Gross, Carol J.

1990-01-01

Describes studies of two rural programs for diverting status offenders from court system to alternative community programs. Examines communities and programs, suggests rural offender characteristics are similar to urban ones. Recommends development of community-based alternatives to child welfare and juvenile justice systems. (TES)

Discriminating nutritional quality of foods using the 5-Color nutrition label in the French food market: consistency with nutritional recommendations.

PubMed

Julia, Chantal; Ducrot, Pauline; Péneau, Sandrine; Deschamps, Valérie; Méjean, Caroline; Fézeu, Léopold; Touvier, Mathilde; Hercberg, Serge; Kesse-Guyot, Emmanuelle

2015-09-28

Our objectives were to assess the performance of the 5-Colour nutrition label (5-CNL) front-of-pack nutrition label based on the Food Standards Agency nutrient profiling system to discriminate nutritional quality of foods currently on the market in France and its consistency with French nutritional recommendations. Nutritional composition of 7777 foods available on the French market collected from the web-based collaborative project Open Food Facts were retrieved. Distribution of products across the 5-CNL categories according to food groups, as arranged in supermarket shelves was assessed. Distribution of similar products from different brands in the 5-CNL categories was also assessed. Discriminating performance was considered as the number of color categories present in each food group. In the case of discrepancies between the category allocation and French nutritional recommendations, adaptations of the original score were proposed. Overall, the distribution of foodstuffs in the 5-CNL categories was consistent with French recommendations: 95.4% of 'Fruits and vegetables', 72.5% of 'Cereals and potatoes' were classified as 'Green' or 'Yellow' whereas 86.0% of 'Sugary snacks' were classified as 'Pink' or 'Red'. Adaptations to the original FSA score computation model were necessary for beverages, added fats and cheese in order to be consistent with French official nutritional recommendations. The 5-CNL label displays a high performance in discriminating nutritional quality of foods across food groups, within a food group and for similar products from different brands. Adaptations from the original model were necessary to maintain consistency with French recommendations and high performance of the system.

The recommender system for virtual items in MMORPGs based on a novel collaborative filtering approach

NASA Astrophysics Data System (ADS)

Li, S. G.; Shi, L.

2014-10-01

The recommendation system for virtual items in massive multiplayer online role-playing games (MMORPGs) has aroused the interest of researchers. Of the many approaches to construct a recommender system, collaborative filtering (CF) has been the most successful one. However, the traditional CFs just lure customers into the purchasing action and overlook customers' satisfaction, moreover, these techniques always suffer from low accuracy under cold-start conditions. Therefore, a novel collaborative filtering (NCF) method is proposed to identify like-minded customers according to the preference similarity coefficient (PSC), which implies correlation between the similarity of customers' characteristics and the similarity of customers' satisfaction level for the product. Furthermore, the analytic hierarchy process (AHP) is used to determine the relative importance of each characteristic of the customer and the improved ant colony optimisation (IACO) is adopted to generate the expression of the PSC. The IACO creates solutions using the Markov random walk model, which can accelerate the convergence of algorithm and prevent prematurity. For a target customer whose neighbours can be found, the NCF can predict his satisfaction level towards the suggested products and recommend the acceptable ones. Under cold-start conditions, the NCF will generate the recommendation list by excluding items that other customers prefer.

A novel framework to alleviate the sparsity problem in context-aware recommender systems

NASA Astrophysics Data System (ADS)

Yu, Penghua; Lin, Lanfen; Wang, Jing

2017-04-01

Recommender systems have become indispensable for services in the era of big data. To improve accuracy and satisfaction, context-aware recommender systems (CARSs) attempt to incorporate contextual information into recommendations. Typically, valid and influential contexts are determined in advance by domain experts or feature selection approaches. Most studies have focused on utilizing the unitary context due to the differences between various contexts. Meanwhile, multi-dimensional contexts will aggravate the sparsity problem, which means that the user preference matrix would become extremely sparse. Consequently, there are not enough or even no preferences in most multi-dimensional conditions. In this paper, we propose a novel framework to alleviate the sparsity issue for CARSs, especially when multi-dimensional contextual variables are adopted. Motivated by the intuition that the overall preferences tend to show similarities among specific groups of users and conditions, we first explore to construct one contextual profile for each contextual condition. In order to further identify those user and context subgroups automatically and simultaneously, we apply a co-clustering algorithm. Furthermore, we expand user preferences in a given contextual condition with the identified user and context clusters. Finally, we perform recommendations based on expanded preferences. Extensive experiments demonstrate the effectiveness of the proposed framework.

Fluid therapy in neurointensive care patients: ESICM consensus and clinical practice recommendations.

PubMed

Oddo, Mauro; Poole, Daniele; Helbok, Raimund; Meyfroidt, Geert; Stocchetti, Nino; Bouzat, Pierre; Cecconi, Maurizio; Geeraerts, Thomas; Martin-Loeches, Ignacio; Quintard, Hervé; Taccone, Fabio Silvio; Geocadin, Romergryko G; Hemphill, Claude; Ichai, Carole; Menon, David; Payen, Jean-François; Perner, Anders; Smith, Martin; Suarez, José; Videtta, Walter; Zanier, Elisa R; Citerio, Giuseppe

2018-04-01

To report the ESICM consensus and clinical practice recommendations on fluid therapy in neurointensive care patients. A consensus committee comprising 22 international experts met in October 2016 during ESICM LIVES2016. Teleconferences and electronic-based discussions between the members of the committee subsequently served to discuss and develop the consensus process. Population, intervention, comparison, and outcomes (PICO) questions were reviewed and updated as needed, and evidence profiles generated. The consensus focused on three main topics: (1) general fluid resuscitation and maintenance in neurointensive care patients, (2) hyperosmolar fluids for intracranial pressure control, (3) fluid management in delayed cerebral ischemia after subarachnoid haemorrhage. After an extensive literature search, the principles of the Grading of Recommendations Assessment, Development and Evaluation (GRADE) system were applied to assess the quality of evidence (from high to very low), to formulate treatment recommendations as strong or weak, and to issue best practice statements when applicable. A modified Delphi process based on the integration of evidence provided by the literature and expert opinions-using a sequential approach to avoid biases and misinterpretations-was used to generate the final consensus statement. The final consensus comprises a total of 32 statements, including 13 strong recommendations and 17 weak recommendations. No recommendations were provided for two statements. We present a consensus statement and clinical practice recommendations on fluid therapy for neurointensive care patients.

Web-Based Learning Information System for Web 3.0

NASA Astrophysics Data System (ADS)

Rego, Hugo; Moreira, Tiago; García-Peñalvo, Francisco Jose

With the emergence of Web/eLearning 3.0 we have been developing/adjusting AHKME in order to face this great challenge. One of our goals is to allow the instructional designer and teacher to access standardized resources and evaluate the possibility of integration and reuse in eLearning systems, not only content but also the learning strategy. We have also integrated some collaborative tools for the adaptation of resources, as well as the collection of feedback from users to provide feedback to the system. We also provide tools for the instructional designer to create/customize specifications/ontologies to give structure and meaning to resources, manual and automatic search with recommendation of resources and instructional design based on the context, as well as recommendation of adaptations in learning resources. We also consider the concept of mobility and mobile technology applied to eLearning, allowing access by teachers and students to learning resources, regardless of time and space.

Using a trauma-informed policy approach to create a resilient urban food system.

PubMed

Hecht, Amelie A; Biehl, Erin; Buzogany, Sarah; Neff, Roni A

2018-07-01

Food insecurity is associated with toxic stress and adverse long-term physical and mental health outcomes. It can be experienced chronically and also triggered or exacerbated by natural and human-made hazards that destabilize the food system. The Baltimore Food System Resilience Advisory Report was created to strengthen the resilience of the city's food system and improve short- and long-term food security. Recognizing food insecurity as a form of trauma, the report was developed using the principles of trauma-informed social policy. In the present paper, we examine how the report applied trauma-informed principles to policy development, discuss the challenges and benefits of using a trauma-informed approach, and provide recommendations for others seeking to create trauma-informed food policy. Report recommendations were developed based on: semi-structured interviews with food system stakeholders; input from community members at outreach events; a literature review; Geographic Information System mapping; and other analyses. The present paper explores findings from the stakeholder interviews. Baltimore, Maryland, USA. Baltimore food system stakeholders stratified by two informant categories: organizations focused on promoting food access (n 13) and community leaders (n 12). Stakeholder interviews informed the recommendations included in the report and supported the idea that chronic and acute food insecurity are experienced as trauma in the Baltimore community. Applying a trauma-informed approach to the development of the Baltimore Food System Resilience Advisory Report contributed to policy recommendations that were community-informed and designed to lessen the traumatic impact of food insecurity.

Web survey data collection and retrieval to plan teleradiology implementation

NASA Astrophysics Data System (ADS)

Alaoui, Adil; Collmann, Jeff R.; Johnson, Jeffrey A.; Lindisch, David; Nguyen, Dan; Mun, Seong K.

2003-05-01

This case study details the experience of system engineers of the Imaging Science and Information Systems Center, Georgetown University Medical Center (ISIS) and radiologists from the department of Radiology in the implementation of a new Teleradiology system. The Teleradiology system enables radiologists to view medical images from remote sites under those circumstances where a resident radiologist needs assistance in evaluating the images after hours and during weekends; it also enables clinicians access to patients" medical images from different workstations within the hospital. The Implementation of the Teleradiology project was preceded by an evaluation phase to perform testing, gather users feedback using a web site and collect information that helped eliminate system bugs, complete recommendations regarding minimum hardware configuration and bandwidth and enhance system"s functions, this phase included a survey-based system assessment of computer configurations, Internet connections, problem identification, and recommendations for improvement, and a testing period with 2 radiologists and ISIS engineers; The second phase was designed to launch the system and make it available to all attending radiologists in the department. To accomplish the first phase of the project a web site was designed and ASP pages were created to enable users to securely logon and enter feedback and recommendations into an SQL database. This efficient, accurate data flow alleviated networking, software and hardware problems. Corrective recommendations were immediately forwarded to the software vendor. The vendor responded with software updates that better met the needs of the radiologists. The ISIS Center completed recommendations for minimum hardware and bandwidth requirements. This experience illustrates that the approach used in collecting the data and facilitating the teamwork between the system engineers and radiologists was instrumental in the project"s success. Major problems with the Teleradiology system were discovered and remedied early by linking the actual practice experience of the physicians to the system improvements.

Creating More Credible and Persuasive Recommender Systems: The Influence of Source Characteristics on Recommender System Evaluations

NASA Astrophysics Data System (ADS)

Yoo, Kyung-Hyan; Gretzel, Ulrike

Whether users are likely to accept the recommendations provided by a recommender system is of utmost importance to system designers and the marketers who implement them. By conceptualizing the advice seeking and giving relationship as a fundamentally social process, important avenues for understanding the persuasiveness of recommender systems open up. Specifically, research regarding the influence of source characteristics, which is abundant in the context of humanhuman relationships, can provide an important framework for identifying potential influence factors. This chapter reviews the existing literature on source characteristics in the context of human-human, human-computer, and human-recommender system interactions. It concludes that many social cues that have been identified as influential in other contexts have yet to be implemented and tested with respect to recommender systems. Implications for recommender system research and design are discussed.

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks

PubMed Central

Zhang, Fu-Guo; Zeng, An

2015-01-01

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case. PMID:26125631

Information Filtering via Heterogeneous Diffusion in Online Bipartite Networks.

PubMed

Zhang, Fu-Guo; Zeng, An

2015-01-01

The rapid expansion of Internet brings us overwhelming online information, which is impossible for an individual to go through all of it. Therefore, recommender systems were created to help people dig through this abundance of information. In networks composed by users and objects, recommender algorithms based on diffusion have been proven to be one of the best performing methods. Previous works considered the diffusion process from user to object, and from object to user to be equivalent. We show in this work that it is not the case and we improve the quality of the recommendation by taking into account the asymmetrical nature of this process. We apply this idea to modify the state-of-the-art recommendation methods. The simulation results show that the new methods can outperform these existing methods in both recommendation accuracy and diversity. Finally, this modification is checked to be able to improve the recommendation in a realistic case.

From the Children’s Oncology Group: Evidence-based recommendations for PEG-asparaginase nurse monitoring, hypersensitivity reaction management, and patient/family education

PubMed Central

Woods, Deborah; Winchester, Kari; Towerman, Alison; Gettinger, Katie; Carey, Christina; Timmermann, Karen; Langley, Rachel; Browne, Emily

2017-01-01

PEG-aspariginase is a backbone chemotherapy agent in pediatric acute lymphoblastic leukemia and in some non-Hodgkin lymphoma therapies. Nurses lack standardized guidelines for monitoring patients receiving PEG-asparaginase and for educating patients/families about hypersensitivity reaction risks. An electronic search of six databases using publication years 2000–2015 and multiple professional organizations and clinical resources was conducted. Evidence sources were reviewed for topic applicability. Each of the final 23 sources was appraised by two team members. The GRADE system was used to assign a quality and strength rating for each recommendation. Multiple recommendations were developed: four relating to nurse monitoring of patients during and after drug administration, eight guiding hypersensitivity reaction management, and four concerning patient/family educational content. These strong recommendations were based on moderate, low, or very-low quality evidence. Several recommendations relied upon generalized drug hypersensitivity guidelines. Additional research is needed to safely guide PEG-asparaginase monitoring, hypersensitivity reaction management and patient/family education. Nurses administering PEG-asparaginase play a critical role in the early identification and management of hypersensitivity reactions. PMID:28602129

Development and empirical user-centered evaluation of semantically-based query recommendation for an electronic health record search engine.

PubMed

Hanauer, David A; Wu, Danny T Y; Yang, Lei; Mei, Qiaozhu; Murkowski-Steffy, Katherine B; Vydiswaran, V G Vinod; Zheng, Kai

2017-03-01

The utility of biomedical information retrieval environments can be severely limited when users lack expertise in constructing effective search queries. To address this issue, we developed a computer-based query recommendation algorithm that suggests semantically interchangeable terms based on an initial user-entered query. In this study, we assessed the value of this approach, which has broad applicability in biomedical information retrieval, by demonstrating its application as part of a search engine that facilitates retrieval of information from electronic health records (EHRs). The query recommendation algorithm utilizes MetaMap to identify medical concepts from search queries and indexed EHR documents. Synonym variants from UMLS are used to expand the concepts along with a synonym set curated from historical EHR search logs. The empirical study involved 33 clinicians and staff who evaluated the system through a set of simulated EHR search tasks. User acceptance was assessed using the widely used technology acceptance model. The search engine's performance was rated consistently higher with the query recommendation feature turned on vs. off. The relevance of computer-recommended search terms was also rated high, and in most cases the participants had not thought of these terms on their own. The questions on perceived usefulness and perceived ease of use received overwhelmingly positive responses. A vast majority of the participants wanted the query recommendation feature to be available to assist in their day-to-day EHR search tasks. Challenges persist for users to construct effective search queries when retrieving information from biomedical documents including those from EHRs. This study demonstrates that semantically-based query recommendation is a viable solution to addressing this challenge. Published by Elsevier Inc.

Brief Strategic Family Therapy: Implementing evidence-based models in community settings

PubMed Central

Szapocznik, José; Muir, Joan A.; Duff, Johnathan H.; Schwartz, Seth J.; Brown, C. Hendricks

2014-01-01

Reflecting a nearly 40-year collaborative partnership between clinical researchers and clinicians, the present article reviews the authors’ experience in developing, investigating, and implementing the Brief Strategic Family Therapy (BSFT) model. The first section of the article focuses on the theory, practice, and studies related to this evidence-based family therapy intervention targeting adolescent drug abuse and delinquency. The second section focuses on the implementation model created for the BSFT intervention– a model that parallels many of the recommendations furthered within the implementation science literature. Specific challenges encountered during the BSFT implementation process are reviewed, along with ways of conceptualizing and addressing these challenges from a systemic perspective. The implementation approach that we employ uses the same systemic principles and intervention techniques as those that underlie the BSFT model itself. Recommendations for advancing the field of implementation science, based on our on-the-ground experiences, are proposed. PMID:24274187

Uncovering the information core in recommender systems

NASA Astrophysics Data System (ADS)

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhou, Tao

2014-08-01

With the rapid growth of the Internet and overwhelming amount of information that people are confronted with, recommender systems have been developed to effectively support users' decision-making process in online systems. So far, much attention has been paid to designing new recommendation algorithms and improving existent ones. However, few works considered the different contributions from different users to the performance of a recommender system. Such studies can help us improve the recommendation efficiency by excluding irrelevant users. In this paper, we argue that in each online system there exists a group of core users who carry most of the information for recommendation. With them, the recommender systems can already generate satisfactory recommendation. Our core user extraction method enables the recommender systems to achieve 90% of the accuracy of the top-L recommendation by taking only 20% of the users into account. A detailed investigation reveals that these core users are not necessarily the large-degree users. Moreover, they tend to select high quality objects and their selections are well diversified.

Benchmarking the quality of schizophrenia pharmacotherapy: a comparison of the Department of Veterans Affairs and the private sector.

PubMed

Leslie, Douglas L; Rosenheck, Robert A

2003-09-01

Comparing quality of care between large health care systems is important for health systems management. This study used measures of the quality of pharmacotherapy for patients with schizophrenia and compared these measures across a sample of patients from the Department of Veterans Affairs (VA) and the private sector. A random sample of all patients diagnosed with schizophrenia in the VA during fiscal year (FY) 2000 was identified using administrative data. In the private sector, a sample of patients diagnosed with schizophrenia in 2000 was identified using MEDSTAT's MarketScan database. For both groups, use of antipsychotic medications was studied and measures of the quality of pharmacotherapy were constructed, including whether patients were prescribed any antipsychotic medication, one of the newer atypical antipsychotics, and whether dosing adhered to established treatment recommendations. These measures were compared across the two groups using logistic regression models, controlling for age, gender, and comorbid diagnoses. Most patients with a diagnosis of schizophrenia (82% in the VA and 73% in the private sector) received an antipsychotic medication, usually one of the newer atypical drugs. Patients in the VA were more likely to be dosed above treatment recommendations, and less likely to be dosed below treatment recommendations. Overall, differences in proportion schizophrenia patients dosed according to recommendations were not statistically different across the two systems (60% in the VA, 58% in the private sector). Differences between the two systems were mixed, with the VA outperforming the private sector with respect to some measures and doing worse on others. Although the VA and the private sector were comparable with respect to the quality measures used in this study, there is room for improvement in both systems. Treatment recommendations are based on the best available clinical evidence of effectiveness and safety. Quality of care might be improved with better adherence to these recommendations. Relatively low rates of adherence to treatment recommendations may be due to lack of awareness of these recommendations among prescribing physicians, or a belief that the recommendations are inadequate. To the extent that low rates of adherence to treatment recommendations are caused by a lack of awareness among physicians, policies should be developed to disseminate this information and encourage the appropriate use of these medications. Further research is needed to understand physician prescribing decisions for these medications. To the extent that physicians feel treatment recommendations for these drugs are inadequate, further research is needed to refine the recommendations.

Personalized Recommender System for e-Learning Environment

ERIC Educational Resources Information Center

Benhamdi, Soulef; Babouri, Abdesselam; Chiky, Raja

2017-01-01

Traditional e-Learning environments are based on static contents considering that all learners are similar, so they are not able to respond to each learner's needs. These systems are less adaptive and once a system that supports a particular strategy has been designed and implemented, it is less likely to change according to student's interactions…

The Global Positioning System and Its Integration into College Geography Curricula.

ERIC Educational Resources Information Center

Wikle, Thomas A.; Lambert, Dean P.

1996-01-01

Introduces global positioning system (GPS) technology to nonspecialist geographers and recommends a framework for implementing GPS instructional modules in college geography courses. GPS was developed as a worldwide satellite-based system by the U.S. Department of Defense to simplify and improve military and civilian navigation and positioning.…

Component-based control of oil-gas-water mixture composition in pipelines

NASA Astrophysics Data System (ADS)

Voytyuk, I. N.

2018-03-01

The article theoretically proves the method for measuring the changes in content of oil, gas and water in pipelines; also the measurement system design for implementation thereof is discussed. An assessment is presented in connection with random and systemic errors for the future system, and recommendations for optimization thereof are presented.

Supportive and palliative care for metastatic breast cancer: resource allocations in low- and middle-income countries. A Breast Health Global Initiative 2013 consensus statement.

PubMed

Cleary, James; Ddungu, Henry; Distelhorst, Sandra R; Ripamonti, Carla; Rodin, Gary M; Bushnaq, Mohammad A; Clegg-Lamptey, Joe N; Connor, Stephen R; Diwani, Msemo B; Eniu, Alexandru; Harford, Joe B; Kumar, Suresh; Rajagopal, M R; Thompson, Beti; Gralow, Julie R; Anderson, Benjamin O

2013-10-01

Many women diagnosed with breast cancer in low- and middle-income countries (LMICs) present with advanced-stage disease. While cure is not a realistic outcome, site-specific interventions, supportive care, and palliative care can achieve meaningful outcomes and improve quality of life. As part of the 5th Breast Health Global Initiative (BHGI) Global Summit, an expert international panel identified thirteen key resource recommendations for supportive and palliative care for metastatic breast cancer. The recommendations are presented in three resource-stratified tables: health system resource allocations, resource allocations for organ-based metastatic breast cancer, and resource allocations for palliative care. These tables illustrate how health systems can provide supportive and palliative care services for patients at a basic level of available resources, and incrementally add services as more resources become available. The health systems table includes health professional education, patient and family education, palliative care models, and diagnostic testing. The metastatic disease management table provides recommendations for supportive care for bone, brain, liver, lung, and skin metastases as well as bowel obstruction. The third table includes the palliative care recommendations: pain management, and psychosocial and spiritual aspects of care. The panel considered pain management a priority at a basic level of resource allocation and emphasized the need for morphine to be easily available in LMICs. Regular pain assessments and the proper use of pharmacologic and non-pharmacologic interventions are recommended. Basic-level resources for psychosocial and spiritual aspects of care include health professional and patient and family education, as well as patient support, including community-based peer support. Copyright © 2013 The Authors. Published by Elsevier Ltd.. All rights reserved.

Recommendation for axillary lymph node dissection in women with early breast cancer and sentinel node metastasis: A systematic review and meta-analysis of randomized controlled trials using the GRADE system.

PubMed

Huang, Tsai-Wei; Kuo, Ken N; Chen, Kee-Hsin; Chen, Chiehfeng; Hou, Wen-Hsuan; Lee, Wei-Hwa; Chao, Tsu-Yi; Tsai, Jo-Ting; Su, Chih-Ming; Huang, Ming-Te; Tam, Ka-Wai

2016-10-01

In 2014, the American Society of Clinical Oncology published an updated clinical practice guideline on axillary lymph node dissection (ALND) for early-stage breast cancer patients. However, these recommendations have been challenged because they were based on data from only one randomized controlled trial (RCT). We evaluated the rationale of these recommendations by systematically reviewing RCTs using the Grading of Recommendations, Assessment, Development, and Evaluations (GRADE) system. We searched articles in the PubMed, EMBASE, CINAHL, Scopus, and Cochrane databases. The primary endpoints were overall survival (OS) and disease-free survival (DFS). The secondary endpoints were recurrence rate and surgical complications of axillary dissection. The quality of evidence was assessed using the GRADE profiler. Five eligible studies were retrieved and analyzed. We divided sentinel lymph node (SLN) metastasis into two categories: SLN micrometastasis and SLN macrometastasis. In patients with 1 or 2 SLN micrometastasis, no significant difference was observed in OS, DFS, or recurrence rate between the ALND and non-ALND groups. For patients with 1 or 2 SLN marcometastasis, only one trial with a moderate risk of bias was included, and non-ALND was the preferred management overall. However, ALND might be appropriate for patients who placed a greater emphasis on longer-term survival at any cost. We recommend non-ALND management for early breast cancer patients with 1 or 2 SLN micrometastasis or macrometastasis on the basis of a systematic review of the current evidence conducted using the GRADE system. However, the optimal practice of evidence-based medicine should incorporate patient preferences, particularly when evidence is limited. Copyright © 2016 IJS Publishing Group Ltd. Published by Elsevier Ltd. All rights reserved.

Recommending blood glucose monitors, a pharmacy perspective.

PubMed

Carter, Alan

2007-03-01

Selection of what blood glucose monitoring system to utilize has become an issue for physicians, diabetes educators, pharmacists, and patients. The field of competing makes and models of blood glucose monitoring systems has become crowded, with manufacturers touting improvements in accuracy, ease of use/alternate site options, stored results capacity, software evaluation tools, and/or price point. Personal interviews of 12 pharmacists from community and academic practice settings about monitor preference, as well as results from a national survey of pharmacist recommendations, were compared to actual wholesale sales data to estimate the impact of such recommendations on final monitor selection by the patient. Accu-Chek monitors were recommended 34.65% of the time and represented 28.58% of sales, with a success rate of 82.48% of being the monitor selected. OneTouch monitors had 27.72% of recommendations but represented 31.43% of sales, indicating possible patient brand loyalty or formulary preference for that product. FreeStyle(R) monitors came in third for pharmacist recommendations and were selected by the patient 61.68% of the time when recommended. The category of "other monitor" choices was selected 60.89% of the time by patients given those suggestions. Included in the "other monitor" category was the new disposable monitor marketed as the Sidekick. Based on sales data provided, the Sidekick made up 2.87% of "other monitor" category sales, representing 68% of the "other monitor" segment. While patients frequently follow pharmacist monitoring system suggestions, the ultimate deciding factor is most often the final out-of-pocket cost to the patient. As a result, cost of supplies often becomes the most important determining factor in final monitor selection at the patient level. If the patient cannot afford to perform the recommended daily testing intervals, all other determining factors and suggestions become moot.

A method for evaluating discoverability and navigability of recommendation algorithms.

PubMed

Lamprecht, Daniel; Strohmaier, Markus; Helic, Denis

2017-01-01

Recommendations are increasingly used to support and enable discovery, browsing, and exploration of items. This is especially true for entertainment platforms such as Netflix or YouTube, where frequently, no clear categorization of items exists. Yet, the suitability of a recommendation algorithm to support these use cases cannot be comprehensively evaluated by any recommendation evaluation measures proposed so far. In this paper, we propose a method to expand the repertoire of existing recommendation evaluation techniques with a method to evaluate the discoverability and navigability of recommendation algorithms. The proposed method tackles this by means of first evaluating the discoverability of recommendation algorithms by investigating structural properties of the resulting recommender systems in terms of bow tie structure, and path lengths. Second, the method evaluates navigability by simulating three different models of information seeking scenarios and measuring the success rates. We show the feasibility of our method by applying it to four non-personalized recommendation algorithms on three data sets and also illustrate its applicability to personalized algorithms. Our work expands the arsenal of evaluation techniques for recommendation algorithms, extends from a one-click-based evaluation towards multi-click analysis, and presents a general, comprehensive method to evaluating navigability of arbitrary recommendation algorithms.

Monitoring guidance for patients with hypophosphatasia treated with asfotase alfa.

PubMed

Kishnani, Priya S; Rush, Eric T; Arundel, Paul; Bishop, Nick; Dahir, Kathryn; Fraser, William; Harmatz, Paul; Linglart, Agnès; Munns, Craig F; Nunes, Mark E; Saal, Howard M; Seefried, Lothar; Ozono, Keiichi

2017-09-01

Hypophosphatasia (HPP) is a rare, inherited, systemic, metabolic disorder caused by autosomal recessive mutations or a single dominant-negative mutation in the gene encoding tissue-nonspecific alkaline phosphatase (TNSALP). The disease is associated with a broad range of signs, symptoms, and complications, including impaired skeletal mineralization, altered calcium and phosphate metabolism, recurrent fractures, pain, respiratory problems, impaired growth and mobility, premature tooth loss, developmental delay, and seizures. Asfotase alfa is a human, recombinant enzyme replacement therapy that is approved in many countries for the treatment of patients with HPP. To address the unmet need for guidance in the monitoring of patients receiving asfotase alfa, an international panel of physicians with experience in diagnosing and managing HPP convened in May 2016 to discuss treatment monitoring parameters. The panel discussions focused on recommendations for assessing and monitoring patients after the decision to treat with asfotase alfa had been made and did not include recommendations for whom to treat. Based on the consensus of panel members, this review provides guidance on the monitoring of patients with HPP during treatment with asfotase alfa, including recommendations for laboratory, efficacy, and safety assessments and the frequency with which these should be performed during the course of treatment. Recommended assessments are based on patient age and include regular monitoring of biochemistry, skeletal radiographs, respiratory function, growth, pain, mobility and motor function, and quality of life. Because of the systemic presentation of HPP, a coordinated, multidisciplinary, team-based, patient-focused approach is recommended in the management of patients receiving asfotase alfa. Monitoring of efficacy and safety outcomes must be tailored to the individual patient, depending on medical history, clinical manifestations, availability of resources in the clinical setting, and the clinician's professional judgment. Copyright © 2017 The Authors. Published by Elsevier Inc. All rights reserved.

Design Recommendations for Query Languages

DTIC Science & Technology

1980-09-01

DESIGN RECOMMENDATIONS FOR QUERY LANGUAGES S.L. Ehrenreich Submitted by: Stanley M. Halpin, Acting Chief HUMAN FACTORS TECHNICAL AREA Approved by: Edgar ...respond to que- ries that it recognizes as faulty. Codd (1974) states that in designing a nat- ural query language, attention must be given to dealing...impaired. Codd (1974) also regarded the user’s perception of the data base to be of critical importance in properly designing a query language system

Conceptual design study. Science and Applications Space Platform (SASP). Final briefing

NASA Technical Reports Server (NTRS)

1980-01-01

The modularity, shape, and size of the recommended platform concept offers a low investment, early option to demonstrate the system; flexibility to conservative growth; adaptability to great variety of multi or dedicated payload groups; and good dispersion and viewing freedom for payloads. Platform configuration effectively supports 80 to 85% of the NASA/OSS and OSTA payloads. The subsystem approaches recommended are based on cost effective distribution of functions.

Panacea, a semantic-enabled drug recommendations discovery framework.

PubMed

Doulaverakis, Charalampos; Nikolaidis, George; Kleontas, Athanasios; Kompatsiaris, Ioannis

2014-03-06

Personalized drug prescription can be benefited from the use of intelligent information management and sharing. International standard classifications and terminologies have been developed in order to provide unique and unambiguous information representation. Such standards can be used as the basis of automated decision support systems for providing drug-drug and drug-disease interaction discovery. Additionally, Semantic Web technologies have been proposed in earlier works, in order to support such systems. The paper presents Panacea, a semantic framework capable of offering drug-drug and drug-diseases interaction discovery. For enabling this kind of service, medical information and terminology had to be translated to ontological terms and be appropriately coupled with medical knowledge of the field. International standard classifications and terminologies, provide the backbone of the common representation of medical data while the medical knowledge of drug interactions is represented by a rule base which makes use of the aforementioned standards. Representation is based on a lightweight ontology. A layered reasoning approach is implemented where at the first layer ontological inference is used in order to discover underlying knowledge, while at the second layer a two-step rule selection strategy is followed resulting in a computationally efficient reasoning approach. Details of the system architecture are presented while also giving an outline of the difficulties that had to be overcome. Panacea is evaluated both in terms of quality of recommendations against real clinical data and performance. The quality recommendation gave useful insights regarding requirements for real world deployment and revealed several parameters that affected the recommendation results. Performance-wise, Panacea is compared to a previous published work by the authors, a service for drug recommendations named GalenOWL, and presents their differences in modeling and approach to the problem, while also pinpointing the advantages of Panacea. Overall, the paper presents a framework for providing an efficient drug recommendations service where Semantic Web technologies are coupled with traditional business rule engines.

Using Data From Ontario's Episode-Based Funding Model to Assess Quality of Chemotherapy.

PubMed

Kaizer, Leonard; Simanovski, Vicky; Lalonde, Carlin; Tariq, Huma; Blais, Irene; Evans, William K

2016-10-01

A new episode-based funding model for ambulatory systemic therapy was implemented in Ontario, Canada on April 1, 2014, after a comprehensive knowledge transfer and exchange strategy with providers and administrators. An analysis of the data from the first year of the new funding model provided an opportunity to assess the quality of chemotherapy, which was not possible under the old funding model. Options for chemotherapy regimens given with adjuvant/curative intent or palliative intent were informed by input from disease site groups. Bundles were developed and priced to enable evidence-informed best practice. Analysis of systemic therapy utilization after model implementation was performed to assess the concordance rate of the treatments chosen with recommended practice. The actual number of cycles of treatment delivered was also compared with expert recommendations. Significant improvement compared with baseline was seen in the proportion of adjuvant/curative regimens that aligned with disease site group-recommended options (98% v 90%). Similar improvement was seen for palliative regimens (94% v 89%). However, overall, the number of cycles of adjuvant/curative therapy delivered was lower than recommended best practice in 57.5% of patients. There was significant variation by disease site and between facilities. Linking funding to quality, supported by knowledge transfer and exchange, resulted in a rapid improvement in the quality of systemic treatment in Ontario. This analysis has also identified further opportunities for improvement and the need for model refinement.

An assessment of ground-based techniques for detecting other planetary systems. Volume 1: An overview. [workshop conclusions

NASA Technical Reports Server (NTRS)

Black, D. C. (Editor); Brunk, W. E. (Editor)

1980-01-01

The feasibility and limitations of ground-based techniques for detecting other planetary systems are discussed as well as the level of accuracy at which these limitations would occur and the extent to which they can be overcome by new technology and instrumenation. Workshop conclusions and recommendations are summarized and a proposed high priority program is considered.

Functional Analysis and Preliminary Specifications for a Single Integrated Central Computer System for Secondary Schools and Junior Colleges. Interim Report.

ERIC Educational Resources Information Center

1968

The present report proposes a central computing facility and presents the preliminary specifications for such a system. It is based, in part, on the results of earlier studies by two previous contractors on behalf of the U.S. Office of Education. The recommendations are based upon the present contractors considered evaluation of the earlier…

Solar water heating system for a lunar base

NASA Technical Reports Server (NTRS)

Somers, Richard E.; Haynes, R. Daniel

1992-01-01

An investigation of the feasibility of using a solar water heater for a lunar base is described. During the investigation, computer codes were developed to model the lunar base configuration, lunar orbit, and heating systems. Numerous collector geometries, orientation variations, and system options were identified and analyzed. The results indicate that the recommended solar water heater could provide 88 percent of the design load and would not require changes in the overall lunar base design. The system would give a 'safe-haven' water heating capability and use only 7 percent to 10 percent as much electricity as an electric heating system. As a result, a fixed position photovoltaic array can be reduced by 21 sq m.

Response assessment in neuro-oncology.

PubMed

Quant, Eudocia C; Wen, Patrick Y

2011-02-01

Accuracy and reproducibility in determining response to therapy and tumor progression can be difficult to achieve for nervous system tumors. Current response criteria vary depending on the pathology and have several limitations. Until recently, the most widely used criteria for gliomas were "Macdonald criteria," based on two-dimensional tumor measurements on neuroimaging studies. However, the Response Assessment in Neuro-Oncology (RANO) Working Group has published new recommendations in high-grade gliomas and is working on recommendations for other nervous system tumors. This article reviews current response criteria for high-grade glioma, low-grade glioma, brain metastasis, meningioma, and schwannoma.

Emotion Chat: A Web Chatroom with Emotion Regulation for E-Learners

NASA Astrophysics Data System (ADS)

Zheng, Deli; Tian, Feng; Liu, Jun; Zheng, Qinghua; Qin, Jiwei

In order to compensate for lack of emotion communication between teachers and students in e-learning systems, we have designed and implemented the EmotionChat -- a web chatroom with emotion regulation. EmotionChat perceives e-learners' emotional states based on interactive text. And it recommends resources such as music, cartoons, and mottos to an e-learner when it detects negative emotional states. Meanwhile, it recommends emotion regulation cases to the e-learner's listeners and teachers. The result of our initial experiment shows that EmotionChat can recommend valuable emotion regulation policies for e-learners.

[Public health research in obstetrics coordinated by the Italian National Health Institute.

PubMed

Donati, Serena

2017-10-01

The Italian National Institute of Health (ISS) has set up a population-based surveillance system for maternal mortality and severe morbidity that covers 75% of total births and promotes the prevention of avoidable outcomes through knowledge-based action. The surveillance system promotes the continuous training of health professionals by distance learning, provides recommendations for clinical practice under the auspices of the ISS - National Guidelines System and strengthens a "no blame" culture among health professionals.

Emotional Mining: Tagging Emoticons to Online News

NASA Astrophysics Data System (ADS)

Kasinathan, Vinothini; Mustapha, Aida; Zhi Yong, Lee; Aida Zamnah, Z. A.

2017-08-01

This paper presents an emotion mining system, which assigns emoticons to newspaper articles into a pre-defined emotion category based on the underlying emotion in the news. Next, the system makes recommendation to the reader by tagging the news headline with the respective emoticons. Users are then able to decide whether to read the news based on the emoticons provided. The system also provides a filter for the users to choose the category of news to read following the emoticons.

Electronic prescribing in pediatrics: toward safer and more effective medication management.

PubMed

Johnson, Kevin B; Lehmann, Christoph U

2013-04-01

This technical report discusses recent advances in electronic prescribing (e-prescribing) systems, including the evidence base supporting their limitations and potential benefits. Specifically, this report acknowledges that there are limited but positive pediatric data supporting the role of e-prescribing in mitigating medication errors, improving communication with dispensing pharmacists, and improving medication adherence. On the basis of these data and on the basis of federal statutes that provide incentives for the use of e-prescribing systems, the American Academy of Pediatrics recommends the adoption of e-prescribing systems with pediatric functionality. This report supports the accompanying policy statement from the American Academy of Pediatrics recommending the adoption of e-prescribing by pediatric health care providers.

An Analysis of Performance-Based Funding Policies and Recommendations for the Florida College System

ERIC Educational Resources Information Center

Balog, Scott E.

2016-01-01

Nearly 30 states have adopted or are transitioning to performance-based funding programs for community colleges that allocate funding based on institutional performance according to defined metrics. While embraced by state lawmakers and promoted by outside advocacy groups as a method to improve student outcomes, enhance accountability and ensure…

77 FR 29033 - Medicare and Medicaid Programs; Reform of Hospital and Critical Access Hospital Conditions of...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-05-16

... organizational structure, whereby multi- hospital systems have integrated their governing body functions to... based on nationally recognized and evidence-based guidelines and recommendations. Verbal Orders: We have..., Outpatient services ($300 million). Our estimates were based on input from stakeholders as well as on our own...

Empirical comparison of local structural similarity indices for collaborative-filtering-based recommender systems

NASA Astrophysics Data System (ADS)

Zhang, Qian-Ming; Shang, Ming-Sheng; Zeng, Wei; Chen, Yong; Lü, Linyuan

2010-08-01

Collaborative filtering is one of the most successful recommendation techniques, which can effectively predict the possible future likes of users based on their past preferences. The key problem of this method is how to define the similarity between users. A standard approach is using the correlation between the ratings that two users give to a set of objects, such as Cosine index and Pearson correlation coefficient. However, the costs of computing this kind of indices are relatively high, and thus it is impossible to be applied in the huge-size systems. To solve this problem, in this paper, we introduce six local-structure-based similarity indices and compare their performances with the above two benchmark indices. Experimental results on two data sets demonstrate that the structure-based similarity indices overall outperform the Pearson correlation coefficient. When the data is dense, the structure-based indices can perform competitively good as Cosine index, while with lower computational complexity. Furthermore, when the data is sparse, the structure-based indices give even better results than Cosine index.

Have Your Computer Call My Computer.

ERIC Educational Resources Information Center

Carabi, Peter

1992-01-01

As more school systems adopt site-based management, local decision makers need greater access to all kinds of information. Microcomputer-based networks can help with classroom management, scheduling, student program design, counselor recommendations, and financial reporting operations. Administrators are provided with planning tips and a sample…

Designing and Developing a Novel Hybrid Adaptive Learning Path Recommendation System (ALPRS) for Gamification Mathematics Geometry Course

ERIC Educational Resources Information Center

Su, Chung-Ho

2017-01-01

Since recommendation systems possess the advantage of adaptive recommendation, they have gradually been applied to e-learning systems to recommend subsequent learning content for learners. However, problems exist in current learning recommender systems available to students in that they are often general learning content and unable to offer…

Treating juvenile idiopathic arthritis to target: recommendations of an international task force.

PubMed

Ravelli, Angelo; Consolaro, Alessandro; Horneff, Gerd; Laxer, Ronald M; Lovell, Daniel J; Wulffraat, Nico M; Akikusa, Jonathan D; Al-Mayouf, Sulaiman M; Antón, Jordi; Avcin, Tadej; Berard, Roberta A; Beresford, Michael W; Burgos-Vargas, Ruben; Cimaz, Rolando; De Benedetti, Fabrizio; Demirkaya, Erkan; Foell, Dirk; Itoh, Yasuhiko; Lahdenne, Pekka; Morgan, Esi M; Quartier, Pierre; Ruperto, Nicolino; Russo, Ricardo; Saad-Magalhães, Claudia; Sawhney, Sujata; Scott, Christiaan; Shenoi, Susan; Swart, Joost F; Uziel, Yosef; Vastert, Sebastiaan J; Smolen, Josef S

2018-06-01

Recent therapeutic advances in juvenile idiopathic arthritis (JIA) have made remission an achievable goal for most patients. Reaching this target leads to improved outcomes. The objective was to develop recommendations for treating JIA to target. A Steering Committee formulated a set of recommendations based on evidence derived from a systematic literature review. These were subsequently discussed, amended and voted on by an international Task Force of 30 paediatric rheumatologists in a consensus-based, Delphi-like procedure. Although the literature review did not reveal trials that compared a treat-to-target approach with another or no strategy, it provided indirect evidence regarding an optimised approach to therapy that facilitated development of recommendations. The group agreed on six overarching principles and eight recommendations. The main treatment target, which should be based on a shared decision with parents/patients, was defined as remission, with the alternative target of low disease activity. The frequency and timeline of follow-up evaluations to ensure achievement and maintenance of the target depend on JIA category and level of disease activity. Additional recommendations emphasise the importance of ensuring adequate growth and development and avoiding long-term systemic glucocorticoid administration to maintain the target. All items were agreed on by more than 80% of the members of the Task Force. A research agenda was formulated. The Task Force developed recommendations for treating JIA to target, being aware that the evidence is not strong and needs to be expanded by future research. These recommendations can inform various stakeholders about strategies to reach optimal outcomes for JIA. © Article author(s) (or their employer(s) unless otherwise stated in the text of the article) 2018. All rights reserved. No commercial use is permitted unless otherwise expressly granted.

Energy Integrated Design of Lighting, Heating, and Cooling Systems, and Its Effect on Building Energy Requirements.

ERIC Educational Resources Information Center

Meckler, Gershon

Comments on the need for integrated design of lighting, heating, and cooling systems. In order to eliminate the penalty of refrigerating the lighting heat, minimize the building non-usable space, and optimize the total energy input, a "systems approach" is recommended. This system would employ heat-recovery techniques based on the ability of the…

The proposal of recommendations for the operation of vacuum sewerage

NASA Astrophysics Data System (ADS)

Mazák, J.; Dvorský, T.; Václavík, V.; Zajac, R.; Hluštík, P.

2017-10-01

This article deals with a comparison of vacuum sewerage system and gravity based sewerage system. It also includes the results of the comparison of both of these systems from various cities, and there are measures suggested on the basis of the findings focused on increasing the efficiency and reducing the operational costs of the selected vacuum sewerage system.

Publishing web-based guidelines using interactive decision models.

PubMed

Sanders, G D; Nease, R F; Owens, D K

2001-05-01

Commonly used methods for guideline development and dissemination do not enable developers to tailor guidelines systematically to specific patient populations and update guidelines easily. We developed a web-based system, ALCHEMIST, that uses decision models and automatically creates evidence-based guidelines that can be disseminated, tailored and updated over the web. Our objective was to demonstrate the use of this system with clinical scenarios that provide challenges for guideline development. We used the ALCHEMIST system to develop guidelines for three clinical scenarios: (1) Chlamydia screening for adolescent women, (2) antiarrhythmic therapy for the prevention of sudden cardiac death; and (3) genetic testing for the BRCA breast-cancer mutation. ALCHEMIST uses information extracted directly from the decision model, combined with the additional information from the author of the decision model, to generate global guidelines. ALCHEMIST generated electronic web-based guidelines for each of the three scenarios. Using ALCHEMIST, we demonstrate that tailoring a guideline for a population at high-risk for Chlamydia changes the recommended policy for control of Chlamydia from contact tracing of reported cases to a population-based screening programme. We used ALCHEMIST to incorporate new evidence about the effectiveness of implantable cardioverter defibrillators (ICD) and demonstrate that the cost-effectiveness of use of ICDs improves from $74 400 per quality-adjusted life year (QALY) gained to $34 500 per QALY gained. Finally, we demonstrate how a clinician could use ALCHEMIST to incorporate a woman's utilities for relevant health states and thereby develop patient-specific recommendations for BRCA testing; the patient-specific recommendation improved quality-adjusted life expectancy by 37 days. The ALCHEMIST system enables guideline developers to publish both a guideline and an interactive decision model on the web. This web-based tool enables guideline developers to tailor guidelines systematically, to update guidelines easily, and to make the underlying evidence and analysis transparent for users.

An item-oriented recommendation algorithm on cold-start problem

NASA Astrophysics Data System (ADS)

Qiu, Tian; Chen, Guang; Zhang, Zi-Ke; Zhou, Tao

2011-09-01

Based on a hybrid algorithm incorporating the heat conduction and probability spreading processes (Proc. Natl. Acad. Sci. U.S.A., 107 (2010) 4511), in this letter, we propose an improved method by introducing an item-oriented function, focusing on solving the dilemma of the recommendation accuracy between the cold and popular items. Differently from previous works, the present algorithm does not require any additional information (e.g., tags). Further experimental results obtained in three real datasets, RYM, Netflix and MovieLens, show that, compared with the original hybrid method, the proposed algorithm significantly enhances the recommendation accuracy of the cold items, while it keeps the recommendation accuracy of the overall and the popular items. This work might shed some light on both understanding and designing effective methods for long-tailed online applications of recommender systems.

Organizing Books and Authors by Multilayer SOM.

PubMed

Zhang, Haijun; Chow, Tommy W S; Wu, Q M Jonathan

2016-12-01

This paper introduces a new framework for the organization of electronic books (e-books) and their corresponding authors using a multilayer self-organizing map (MLSOM). An author is modeled by a rich tree-structured representation, and an MLSOM-based system is used as an efficient solution to the organizational problem of structured data. The tree-structured representation formulates author features in a hierarchy of author biography, books, pages, and paragraphs. To efficiently tackle the tree-structured representation, we used an MLSOM algorithm that serves as a clustering technique to handle e-books and their corresponding authors. A book and author recommender system is then implemented using the proposed framework. The effectiveness of our approach was examined in a large-scale data set containing 3868 authors along with the 10500 e-books that they wrote. We also provided visualization results of MLSOM for revealing the relevance patterns hidden from presented author clusters. The experimental results corroborate that the proposed method outperforms other content-based models (e.g., rate adapting poisson, latent Dirichlet allocation, probabilistic latent semantic indexing, and so on) and offers a promising solution to book recommendation, author recommendation, and visualization.

Similarity from Multi-Dimensional Scaling: Solving the Accuracy and Diversity Dilemma in Information Filtering

PubMed Central

Zeng, Wei; Zeng, An; Liu, Hao; Shang, Ming-Sheng; Zhang, Yi-Cheng

2014-01-01

Recommender systems are designed to assist individual users to navigate through the rapidly growing amount of information. One of the most successful recommendation techniques is the collaborative filtering, which has been extensively investigated and has already found wide applications in e-commerce. One of challenges in this algorithm is how to accurately quantify the similarities of user pairs and item pairs. In this paper, we employ the multidimensional scaling (MDS) method to measure the similarities between nodes in user-item bipartite networks. The MDS method can extract the essential similarity information from the networks by smoothing out noise, which provides a graphical display of the structure of the networks. With the similarity measured from MDS, we find that the item-based collaborative filtering algorithm can outperform the diffusion-based recommendation algorithms. Moreover, we show that this method tends to recommend unpopular items and increase the global diversification of the networks in long term. PMID:25343243

48 CFR 1852.235-73 - Final Scientific and Technical Reports.

Code of Federal Regulations, 2010 CFR

2010-10-01

... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Final Scientific and Technical Reports. 1852.235-73 Section 1852.235-73 Federal Acquisition Regulations System NATIONAL..., including recommendations and conclusions based on the experience and results obtained. The final report...

Industrial energy systems and assessment opportunities

NASA Astrophysics Data System (ADS)

Barringer, Frank Leonard, III

Industrial energy assessments are performed primarily to increase energy system efficiency and reduce energy costs in industrial facilities. The most common energy systems are lighting, compressed air, steam, process heating, HVAC, pumping, and fan systems, and these systems are described in this document. ASME has produced energy assessment standards for four energy systems, and these systems include compressed air, steam, process heating, and pumping systems. ASHRAE has produced an energy assessment standard for HVAC systems. Software tools for energy systems were developed for the DOE, and there are software tools for almost all of the most common energy systems. The software tools are AIRMaster+ and LogTool for compressed air systems, SSAT and 3E Plus for steam systems, PHAST and 3E Plus for process heating systems, eQUEST for HVAC systems, PSAT for pumping systems, and FSAT for fan systems. The recommended assessment procedures described in this thesis are used to set up an energy assessment for an industrial facility, collect energy system data, and analyze the energy system data. The assessment recommendations (ARs) are opportunities to increase efficiency and reduce energy consumption for energy systems. A set of recommended assessment procedures and recommended assessment opportunities are presented for each of the most common energy systems. There are many assessment opportunities for industrial facilities, and this thesis describes forty-three ARs for the seven different energy systems. There are seven ARs for lighting systems, ten ARs for compressed air systems, eight ARs for boiler and steam systems, four ARs for process heating systems, six ARs for HVAC systems, and four ARs for both pumping and fan systems. Based on a history of past assessments, average potential energy savings and typical implementation costs are shared in this thesis for most ARs. Implementing these ARs will increase efficiency and reduce energy consumption for energy systems in industrial facilities. This thesis does not explain all energy saving ARs that are available, but does describe the most common ARs.

Data Recommender: An Alternative Way to Discover Open Scientific Datasets

NASA Astrophysics Data System (ADS)

Klump, J. F.; Devaraju, A.; Williams, G.; Hogan, D.; Davy, R.; Page, J.; Singh, D.; Peterson, N.

2017-12-01

Over the past few years, institutions and government agencies have adopted policies to openly release their data, which has resulted in huge amounts of open data becoming available on the web. When trying to discover the data, users face two challenges: an overload of choice and the limitations of the existing data search tools. On the one hand, there are too many datasets to choose from, and therefore, users need to spend considerable effort to find the datasets most relevant to their research. On the other hand, data portals commonly offer keyword and faceted search, which depend fully on the user queries to search and rank relevant datasets. Consequently, keyword and faceted search may return loosely related or irrelevant results, although the results may contain the same query. They may also return highly specific results that depend more on how well metadata was authored. They do not account well for variance in metadata due to variance in author styles and preferences. The top-ranked results may also come from the same data collection, and users are unlikely to discover new and interesting datasets. These search modes mainly suits users who can express their information needs in terms of the structure and terminology of the data portals, but may pose a challenge otherwise. The above challenges reflect that we need a solution that delivers the most relevant (i.e., similar and serendipitous) datasets to users, beyond the existing search functionalities on the portals. A recommender system is an information filtering system that presents users with relevant and interesting contents based on users' context and preferences. Delivering data recommendations to users can make data discovery easier, and as a result may enhance user engagement with the portal. We developed a hybrid data recommendation approach for the CSIRO Data Access Portal. The approach leverages existing recommendation techniques (e.g., content-based filtering and item co-occurrence) to produce similar and serendipitous data recommendations. It measures the relevance between datasets based on their properties, and search and download patterns. We evaluated the recommendation approach in a user study, and the obtained user judgments revealed the ability of the approach to accurately quantify the relevance of the datasets.

Emergence of Scale-Free Leadership Structure in Social Recommender Systems

PubMed Central

Zhou, Tao; Medo, Matúš; Cimini, Giulio; Zhang, Zi-Ke; Zhang, Yi-Cheng

2011-01-01

The study of the organization of social networks is important for the understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a “good get richer” mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems. PMID:21857891

2013 Up-date of the consensus statement of the Spanish Menopause Society on postmenopausal osteoporosis.

PubMed

Mendoza, Nicolás; Sánchez-Borrego, Rafael; Villero, José; Baró, Francesc; Calaf, Joaquim; Cancelo, Ma Jesús; Coronado, Pluvio; Estévez, Antonio; Fernández-Moya, Jose M; González, Silvia; Llaneza, Plácido; Neyro, Jose Luis; del Pino, Javier; Rodríguez, Esteban; Ruiz, Elena; Cano, Antonio

2013-09-01

Postmenopausal osteoporosis is a major female health problem that increases morbidity, mortality and healthcare system costs. Considering that gynecologists are the primary health practitioners involved in the treatment of women with osteoporosis in our country, a panel of experts from the Spanish Menopause Society met to establish a set of criteria and procedures for the diagnosis and treatment of this disease based on the best available evidence and according to the model proposed by the GRADE (Grading of Recommendations Assessment, Development and Evaluation) system to elaborate clinical practice guidelines and to classify the quality of the evidence and the strength of the recommendations. These recommendations should be a reference to gynecologist and other health professionals involved in the treatment of postmenopausal women. Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.

Functional Specifications for Computer Aided Training Systems Development and Management (CATSDM) Support Functions. Final Report.

ERIC Educational Resources Information Center

Hughes, John; And Others

This report provides a description of a Computer Aided Training System Development and Management (CATSDM) environment based on state-of-the-art hardware and software technology, and including recommendations for off the shelf systems to be utilized as a starting point in addressing the particular systematic training and instruction design and…

Crossing the health IT chasm: considerations and policy recommendations to overcome current challenges and enable value-based care.

PubMed

Adler-Milstein, Julia; Embi, Peter J; Middleton, Blackford; Sarkar, Indra Neil; Smith, Jeff

2017-09-01

While great progress has been made in digitizing the US health care system, today's health information technology (IT) infrastructure remains largely a collection of systems that are not designed to support a transition to value-based care. In addition, the pursuit of value-based care, in which we deliver better care with better outcomes at lower cost, places new demands on the health care system that our IT infrastructure needs to be able to support. Provider organizations pursuing new models of health care delivery and payment are finding that their electronic systems lack the capabilities needed to succeed. The result is a chasm between the current health IT ecosystem and the health IT ecosystem that is desperately needed.In this paper, we identify a set of focal goals and associated near-term achievable actions that are critical to pursue in order to enable the health IT ecosystem to meet the acute needs of modern health care delivery. These ideas emerged from discussions that occurred during the 2015 American Medical Informatics Association Policy Invitational Meeting. To illustrate the chasm and motivate our recommendations, we created a vignette from the multistakeholder perspectives of a patient, his provider, and researchers/innovators. It describes an idealized scenario in which each stakeholder's needs are supported by an integrated health IT environment. We identify the gaps preventing such a reality today and present associated policy recommendations that serve as a blueprint for critical actions that would enable us to cross the current health IT chasm by leveraging systems and information to routinely deliver high-value care. © The Author 2017. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

Secondary Prevention of Cervical Cancer: ASCO Resource-Stratified Clinical Practice Guideline

PubMed Central

Jeronimo, Jose; Castle, Philip E.; Temin, Sarah; Denny, Lynette; Gupta, Vandana; Kim, Jane J.; Luciani, Silvana; Murokora, Daniel; Ngoma, Twalib; Qiao, Youlin; Quinn, Michael; Sankaranarayanan, Rengaswamy; Sasieni, Peter; Schmeler, Kathleen M.; Shastri, Surendra S.

2017-01-01

Purpose To provide resource-stratified, evidence-based recommendations on the secondary prevention of cervical cancer globally. Methods ASCO convened a multidisciplinary, multinational panel of oncology, primary care, epidemiology, health economic, cancer control, public health, and patient advocacy experts to produce recommendations reflecting four resource-tiered settings. A review of existing guidelines, a formal consensus-based process, and a modified ADAPTE process to adapt existing guidelines were conducted. Other experts participated in formal consensus. Results Seven existing guidelines were identified and reviewed, and adapted recommendations form the evidence base. Four systematic reviews plus cost-effectiveness analyses provided indirect evidence to inform consensus, which resulted in ≥ 75% agreement. Recommendations Human papillomavirus (HPV) DNA testing is recommended in all resource settings; visual inspection with acetic acid may be used in basic settings. Recommended age ranges and frequencies by setting are as follows: maximal: ages 25 to 65, every 5 years; enhanced: ages 30 to 65, if two consecutive negative tests at 5-year intervals, then every 10 years; limited: ages 30 to 49, every 10 years; and basic: ages 30 to 49, one to three times per lifetime. For basic settings, visual assessment is recommended as triage; in other settings, genotyping and/or cytology are recommended. For basic settings, treatment is recommended if abnormal triage results are present; in other settings, colposcopy is recommended for abnormal triage results. For basic settings, treatment options are cryotherapy or loop electrosurgical excision procedure; for other settings, loop electrosurgical excision procedure (or ablation) is recommended. Twelve-month post-treatment follow-up is recommended in all settings. Women who are HIV positive should be screened with HPV testing after diagnosis and screened twice as many times per lifetime as the general population. Screening is recommended at 6 weeks postpartum in basic settings; in other settings, screening is recommended at 6 months. In basic settings without mass screening, infrastructure for HPV testing, diagnosis, and treatment should be developed. Additional information can be found at www.asco.org/rs-cervical-cancer-secondary-prev-guideline and www.asco.org/guidelineswiki. It is the view of of ASCO that health care providers and health care system decision makers should be guided by the recommendations for the highest stratum of resources available. The guideline is intended to complement, but not replace, local guidelines. PMID:29094101

The Power of Ground User in Recommender Systems

PubMed Central

Zhou, Yanbo; Lü, Linyuan; Liu, Weiping; Zhang, Jianlin

2013-01-01

Accuracy and diversity are two important aspects to evaluate the performance of recommender systems. Two diffusion-based methods were proposed respectively inspired by the mass diffusion (MD) and heat conduction (HC) processes on networks. It has been pointed out that MD has high recommendation accuracy yet low diversity, while HC succeeds in seeking out novel or niche items but with relatively low accuracy. The accuracy-diversity dilemma is a long-term challenge in recommender systems. To solve this problem, we introduced a background temperature by adding a ground user who connects to all the items in the user-item bipartite network. Performing the HC algorithm on the network with ground user (GHC), it showed that the accuracy can be largely improved while keeping the diversity. Furthermore, we proposed a weighted form of the ground user (WGHC) by assigning some weights to the newly added links between the ground user and the items. By turning the weight as a free parameter, an optimal value subject to the highest accuracy is obtained. Experimental results on three benchmark data sets showed that the WGHC outperforms the state-of-the-art method MD for both accuracy and diversity. PMID:23936380

Guide for inservice inspection of ground-based pressure vessels and systems

NASA Technical Reports Server (NTRS)

1976-01-01

This guide includes recommendations for inservice inspection and recertification of ground based, unfired pressure vessels and all pressurized systems including those served by fired pressure vessels hereinafter referred to as pressure vessels, systems and components of systems. It covers the vast array of pound based industrial and special purpose pressurized components and systems used at NASA field installations for research and development and those utility systems and components that require more than routine maintenance to insure continued structural integrity for their useful life. Through surveillance and correction of inservice deterioration, NASA will maintain a safe working environment for their own and contractor personnel, safety for the public sector and protection against loss of capital investment.

Wildlife and Wildlife Habitat Mitigation Plan for Hungry Horse Hydroelectric Project, Final Report.

DOE Office of Scientific and Technical Information (OSTI.GOV)

Bissell, Gael

1985-01-01

This report describes the proposed mitigation plan for wildlife losses attributable to the construction of the Hungry Horse hydroelectric project. In this report, mitigation objectives and alternatives, the recommended mitigation projects, and the crediting system for each project are described by each target species. Mitigation objectives for each species (group) were established based on the loss estimates but tailored to the recommended projects. 13 refs., 3 figs., 19 tabs.

Clustering recommendations to compute agent reputation

NASA Astrophysics Data System (ADS)

Bedi, Punam; Kaur, Harmeet

2005-03-01

Traditional centralized approaches to security are difficult to apply to multi-agent systems which are used nowadays in e-commerce applications. Developing a notion of trust that is based on the reputation of an agent can provide a softer notion of security that is sufficient for many multi-agent applications. Our paper proposes a mechanism for computing reputation of the trustee agent for use by the trustier agent. The trustier agent computes the reputation based on its own experience as well as the experience the peer agents have with the trustee agents. The trustier agents intentionally interact with the peer agents to get their experience information in the form of recommendations. We have also considered the case of unintentional encounters between the referee agents and the trustee agent, which can be directly between them or indirectly through a set of interacting agents. The clustering is done to filter off the noise in the recommendations in the form of outliers. The trustier agent clusters the recommendations received from referee agents on the basis of the distances between recommendations using the hierarchical agglomerative method. The dendogram hence obtained is cut at the required similarity level which restricts the maximum distance between any two recommendations within a cluster. The cluster with maximum number of elements denotes the views of the majority of recommenders. The center of this cluster represents the reputation of the trustee agent which can be computed using c-means algorithm.

A Data Management System Integrating Web-based Training and Randomized Trials: Requirements, Experiences and Recommendations.

PubMed

Muroff, Jordana; Amodeo, Maryann; Larson, Mary Jo; Carey, Margaret; Loftin, Ralph D

2011-01-01

This article describes a data management system (DMS) developed to support a large-scale randomized study of an innovative web-course that was designed to improve substance abuse counselors' knowledge and skills in applying a substance abuse treatment method (i.e., cognitive behavioral therapy; CBT). The randomized trial compared the performance of web-course-trained participants (intervention group) and printed-manual-trained participants (comparison group) to determine the effectiveness of the web-course in teaching CBT skills. A single DMS was needed to support all aspects of the study: web-course delivery and management, as well as randomized trial management. The authors briefly reviewed several other systems that were described as built either to handle randomized trials or to deliver and evaluate web-based training. However it was clear that these systems fell short of meeting our needs for simultaneous, coordinated management of the web-course and the randomized trial. New England Research Institute's (NERI) proprietary Advanced Data Entry and Protocol Tracking (ADEPT) system was coupled with the web-programmed course and customized for our purposes. This article highlights the requirements for a DMS that operates at the intersection of web-based course management systems and randomized clinical trial systems, and the extent to which the coupled, customized ADEPT satisfied those requirements. Recommendations are included for institutions and individuals considering conducting randomized trials and web-based training programs, and seeking a DMS that can meet similar requirements.

Integration of health technology assessment recommendations into organizational and clinical practice: A case study in Catalonia.

PubMed

Gagnon, Marie-Pierre; Sánchez, Emília; Pons, Joan M V

2006-01-01

Evaluating the impact of recommendations based upon health technology assessment (HTA) represents a challenge for both HTA agencies and healthcare policy makers. This research sought to understand factors affecting the uptake of HTA recommendations to support decision making with respect to the introduction of three health technologies. Using a multidimensional framework, based upon a combination of theoretical models, a case study was conducted. A total of twenty-eight semistructured interviews were done with physicians from fifteen hospitals and other stakeholders in Catalonia. Interview content was analyzed iteratively and classified according to theoretical dimensions and contextual factors. At the sociopolitical level, factors related to the organization and financing of the health system were found to affect the utilization of HTA recommendations. At the healthcare organization level, existing collaborations between the hospital and the HTA agency favored the integration of recommendations into practices. Formalism in the organization also influenced the utilization of HTA recommendations. At the professional level, the high degree of autonomy of specialists, the importance of peers and collegial control, and the definition of professional roles and responsibilities influenced physicians' willingness to integrate HTA recommendations into their practice. This study offers a comprehensive framework to understand the complex dynamics that affect adoption of health technologies in organizational and professional practices. The findings suggest some avenues to promote the integration of HTA recommendations into practices and, thus, increase the utilization of scientific evidence to support decision making in health care.

Orbit determination software development for microprocessor based systems: Evaluation and recommendations

NASA Technical Reports Server (NTRS)

Shenitz, C. M.; Mcgarry, F. E.; Tasaki, K. K.

1980-01-01

A guide is presented for National Aeronautics and Space Administration management personnel who stand to benefit from the lessons learned in developing microprocessor-based flight dynamics software systems. The essential functional characteristics of microprocessors are presented. The relevant areas of system support software are examined, as are the distinguishing characteristics of flight dynamics software. Design examples are provided to illustrate the major points presented, and actual development experience obtained in this area is provided as evidence to support the conclusions reached.

Recommendations for acupuncture in clinical practice guidelines of the national guideline clearinghouse.

PubMed

Guo, Yao; Zhao, Hong; Wang, Fang; Li, Si-Nuo; Sun, Yu-Xiu; Han, Ming-Juan; Liu, Bao-Yan

2017-11-01

To organize the clinical practice guidelines (CPGs) related to acupuncture included in the National Guideline Clearinghouse (NGC) to systematically summarize the diseases and disorders most commonly treated with acupuncture, the strength of recommendations for acupuncture and the quality of evidence. The NGC database was systematically searched for guidelines that included acupuncture as an intervention. Two independent reviewers studied the summaries and the full texts of the guidelines and included guidelines based on the inclusion and exclusion criteria. Thirty-nine guidelines were collected with 80 recommendations. The Appraisal of Guidelines for Research and Evaluation (AGREE) II instrument was used to assess the quality of these guidelines. Of the 80 recommendations on acupuncture, 49 recommendations were clearly for acupuncture, 25 recommendations were against acupuncture and 6 recommendations did not indicate any clear recommendations, 37 recommendations were for painful diseases/disorders, and 12 recommendations were for non-painful diseases/disorders. Locomotor system disorders were the most common in the painful diseases/disorders category. Out of all the recommendations for acupuncture, most recommendations (87.76%) were weak in strength, and most of the evidence (40.84%) was of low quality. In the National Guideline Clearinghouse, the recommendations for acupuncture focus on painful diseases/disorders. The recommendations in the guidelines are not high in strength, and most of the evidence is moderate or low in quality.

Which Refrigeration System is Best for Your School?

ERIC Educational Resources Information Center

Little, Philip F.

1963-01-01

Several types of refrigeration systems available to the consulting engineer are discussed. The engineer should analyze all energy sources and base his recommendations on comparative costs and availability of sources, keeping in mind that operating costs are of primary importance to schools. The analysis begins with a careful appraisal of the…

Closing the gap in systems engineering education for the space industry

NASA Technical Reports Server (NTRS)

Carlisle, R.

1986-01-01

The education of system engineers with emphasis on designing systems for space applications is discussed. System engineers determine the functional requirements, performance needs, and implementation procedures for proposed systems and their education is based on aeronautics and mathematics. Recommendations from industry for improving the curriculum of system engineers at the undergraduate and graduate levels are provided. The assistance provided by companies to the education of system engineers is examined.

Space station/base food system study. Volume 1: Systems design handbook

NASA Technical Reports Server (NTRS)

1970-01-01

A description is given of the approach used in a study to identify and define engineering data for a spectrum of possible items and equipment comprising potential food systems. In addition, the material presented includes: (1) the study results containing the candidate concepts considered and technical data, performance characteristics, and sketches for each of the concepts by functional area; (2) human factors considerations for crew tasks; (3) shuttle supply interface requirements; (4) special food system study areas; and (5) recommendations and conclusions based on the study results.

A development of logistics management models for the Space Transportation System

NASA Technical Reports Server (NTRS)

Carrillo, M. J.; Jacobsen, S. E.; Abell, J. B.; Lippiatt, T. F.

1983-01-01

A new analytic queueing approach was described which relates stockage levels, repair level decisions, and the project network schedule of prelaunch operations directly to the probability distribution of the space transportation system launch delay. Finite source population and limited repair capability were additional factors included in this logistics management model developed specifically for STS maintenance requirements. Data presently available to support logistics decisions were based on a comparability study of heavy aircraft components. A two-phase program is recommended by which NASA would implement an integrated data collection system, assemble logistics data from previous STS flights, revise extant logistics planning and resource requirement parameters using Bayes-Lin techniques, and adjust for uncertainty surrounding logistics systems performance parameters. The implementation of these recommendations can be expected to deliver more cost-effective logistics support.

Reframing the Dissemination Challenge: A Marketing and Distribution Perspective

PubMed Central

Bernhardt, Jay M.

2009-01-01

A fundamental obstacle to successful dissemination and implementation of evidence-based public health programs is the near-total absence of systems and infrastructure for marketing and distribution. We describe the functions of a marketing and distribution system, and we explain how it would help move effective public health programs from research to practice. Then we critically evaluate the 4 dominant strategies now used to promote dissemination and implementation, and we explain how each would be enhanced by marketing and distribution systems. Finally, we make 6 recommendations for building the needed system infrastructure and discuss the responsibility within the public health community for implementation of these recommendations. Without serious investment in such infrastructure, application of proven solutions in public health practice will continue to occur slowly and rarely. PMID:19833993

Reframing the dissemination challenge: a marketing and distribution perspective.

PubMed

Kreuter, Matthew W; Bernhardt, Jay M

2009-12-01

A fundamental obstacle to successful dissemination and implementation of evidence-based public health programs is the near-total absence of systems and infrastructure for marketing and distribution. We describe the functions of a marketing and distribution system, and we explain how it would help move effective public health programs from research to practice. Then we critically evaluate the 4 dominant strategies now used to promote dissemination and implementation, and we explain how each would be enhanced by marketing and distribution systems. Finally, we make 6 recommendations for building the needed system infrastructure and discuss the responsibility within the public health community for implementation of these recommendations. Without serious investment in such infrastructure, application of proven solutions in public health practice will continue to occur slowly and rarely.

Recommended system of application and development

NASA Astrophysics Data System (ADS)

Wang, Wei

2018-04-01

A recommender system is a project that helps users identify their wishes and needs. The recommender system has been successfully applied to many e-commerce environments, such as news, film, music, books and other areas of recommendation. This paper mainly discusses the application of recommendation technology in software engineering, data and knowledge engineering, configurable projects and persuasion technology, and summarizes the development trend of recommendation technology in the future.

Out-of-Hospital Cardiac Arrest Resuscitation Systems of Care: A Scientific Statement From the American Heart Association.

PubMed

McCarthy, James J; Carr, Brendan; Sasson, Comilla; Bobrow, Bentley J; Callaway, Clifton W; Neumar, Robert W; Ferrer, Jose Maria E; Garvey, J Lee; Ornato, Joseph P; Gonzales, Louis; Granger, Christopher B; Kleinman, Monica E; Bjerke, Chris; Nichol, Graham

2018-05-22

The American Heart Association previously recommended implementation of cardiac resuscitation systems of care that consist of interconnected community, emergency medical services, and hospital efforts to measure and improve the process of care and outcome for patients with cardiac arrest. In addition, the American Heart Association proposed a national process to develop and implement evidence-based guidelines for cardiac resuscitation systems of care. Significant experience has been gained with implementing these systems, and new evidence has accumulated. This update describes recent advances in the science of cardiac resuscitation systems and evidence of their effectiveness, as well as recent progress in dissemination and implementation throughout the United States. Emphasis is placed on evidence published since the original recommendations (ie, including and since 2010). © 2018 American Heart Association, Inc.

Review: Feeding conserved forage to horses: recent advances and recommendations.

PubMed

Harris, P A; Ellis, A D; Fradinho, M J; Jansson, A; Julliand, V; Luthersson, N; Santos, A S; Vervuert, I

2017-06-01

The horse is a non-ruminant herbivore adapted to eating plant-fibre or forage-based diets. Some horses are stabled for most or the majority of the day with limited or no access to fresh pasture and are fed preserved forage typically as hay or haylage and sometimes silage. This raises questions with respect to the quality and suitability of these preserved forages (considering production, nutritional content, digestibility as well as hygiene) and required quantities. Especially for performance horses, forage is often replaced with energy dense feedstuffs which can result in a reduction in the proportion of the diet that is forage based. This may adversely affect the health, welfare, behaviour and even performance of the horse. In the past 20 years a large body of research work has contributed to a better and deeper understanding of equine forage needs and the physiological and behavioural consequences if these are not met. Recent nutrient requirement systems have incorporated some, but not all, of this new knowledge into their recommendations. This review paper amalgamates recommendations based on the latest understanding in forage feeding for horses, defining forage types and preservation methods, hygienic quality, feed intake behaviour, typical nutrient composition, digestion and digestibility as well as health and performance implications. Based on this, consensual applied recommendations for feeding preserved forages are provided.

Assisting Consumer Health Information Retrieval with Query Recommendations

PubMed Central

Zeng, Qing T.; Crowell, Jonathan; Plovnick, Robert M.; Kim, Eunjung; Ngo, Long; Dibble, Emily

2006-01-01

Objective: Health information retrieval (HIR) on the Internet has become an important practice for millions of people, many of whom have problems forming effective queries. We have developed and evaluated a tool to assist people in health-related query formation. Design: We developed the Health Information Query Assistant (HIQuA) system. The system suggests alternative/additional query terms related to the user's initial query that can be used as building blocks to construct a better, more specific query. The recommended terms are selected according to their semantic distance from the original query, which is calculated on the basis of concept co-occurrences in medical literature and log data as well as semantic relations in medical vocabularies. Measurements: An evaluation of the HIQuA system was conducted and a total of 213 subjects participated in the study. The subjects were randomized into 2 groups. One group was given query recommendations and the other was not. Each subject performed HIR for both a predefined and a self-defined task. Results: The study showed that providing HIQuA recommendations resulted in statistically significantly higher rates of successful queries (odds ratio = 1.66, 95% confidence interval = 1.16–2.38), although no statistically significant impact on user satisfaction or the users' ability to accomplish the predefined retrieval task was found. Conclusion: Providing semantic-distance-based query recommendations can help consumers with query formation during HIR. PMID:16221944

Psychological treatments for adults and children with epilepsy: Evidence-based recommendations by the International League Against Epilepsy Psychology Task Force.

PubMed

Michaelis, Rosa; Tang, Venus; Goldstein, Laura H; Reuber, Markus; LaFrance, William Curt; Lundgren, Tobias; Modi, Avani C; Wagner, Janelle L

2018-06-19

Given the significant impact that psychosocial factors and epilepsy treatments can have on the health-related quality of life (HRQOL) of individuals with epilepsy and their families, there is great clinical interest in the role of psychological evaluation and treatments to improve HRQOL and comorbidities. Therefore, the International League Against Epilepsy (ILAE) charged the Psychology Task Force with the development of recommendations for clinical care based on evaluation of the evidence from their recent Cochrane review of psychological treatments in individuals with epilepsy. The literature search for a recent Cochrane review of randomized controlled trials investigating psychological treatments for individuals with epilepsy constitutes the key source of evidence for this article. To provide practical guidance to service providers, we provide ratings on study research designs based on (1) the American Academy of Neurology's Level of Evidence system and (2) the Grading of Recommendations, Assessment, Development, and Evaluation system. This paper is the culmination of an international collaboration process involving pediatric and adult psychologists, neurologists, psychiatrists, and neuropsychiatrists. The process and conclusions were reviewed and approved by the ILAE Executive Committee. The strongest evidence for psychological interventions was identified for the most common mental health problems, including depression, neurocognitive disturbances, and medication adherence. Psychological interventions targeting the enhancement of HRQOL and adherence and a decrease in comorbidity symptoms (anxiety, depression) should be incorporated into comprehensive epilepsy care. There is a range of psychological strategies (ie, cognitive behavioral therapy and mindfulness-based therapies) that show promise for improving the lives of persons with epilepsy, and clinical recommendations are provided to assist epilepsy health care providers in treating the comorbidities and challenges associated with epilepsy and its treatments. Wiley Periodicals, Inc. © 2018 International League Against Epilepsy.

Study of Thermal Control Systems for orbiting power systems

NASA Technical Reports Server (NTRS)

Howell, H. R.

1981-01-01

Thermal control system designs were evaluated for the 25 kW power system. Factors considered include long operating life, high reliability, and meteoroid hazards to the space radiator. Based on a cost advantage, the bumpered pumped fluid radiator is recommended for the initial 25 kW power system and intermediate versions up to 50 kW. For advanced power systems with heat rejection rates above 50 kW the lower weight of the advanced heat pipe radiator offsets the higher cost and this design is recommended. The power system payloads heat rejection allocations studies show that a centralized heat rejection system is the most weight and cost effective approach. The thermal interface between the power system and the payloads was addressed and a concept for a contact heat exchanger that eliminates fluid transfer between the power system and the payloads was developed. Finally, a preliminary design of the thermal control system, with emphasis on the radiator and radiator deployment mechanism, is presented.

Formation of integrated structural units using the systematic and integrated method when implementing high-rise construction projects

NASA Astrophysics Data System (ADS)

Abramov, Ivan

2018-03-01

Development of design documentation for a future construction project gives rise to a number of issues with the main one being selection of manpower for structural units of the project's overall implementation system. Well planned and competently staffed integrated structural construction units will help achieve a high level of reliability and labor productivity and avoid negative (extraordinary) situations during the construction period eventually ensuring improved project performance. Research priorities include the development of theoretical recommendations for enhancing reliability of a structural unit staffed as an integrated construction crew. The author focuses on identification of destabilizing factors affecting formation of an integrated construction crew; assessment of these destabilizing factors; based on the developed mathematical model, highlighting the impact of these factors on the integration criterion with subsequent identification of an efficiency and reliability criterion for the structural unit in general. The purpose of this article is to develop theoretical recommendations and scientific and methodological provisions of an organizational and technological nature in order to identify a reliability criterion for a structural unit based on manpower integration and productivity criteria. With this purpose in mind, complex scientific tasks have been defined requiring special research, development of corresponding provisions and recommendations based on the system analysis findings presented herein.

Evaluating Recommender Systems for Technology Enhanced Learning: A Quantitative Survey

ERIC Educational Resources Information Center

Erdt, Mojisola; Fernandez, Alejandro; Rensing, Christoph

2015-01-01

The increasing number of publications on recommender systems for Technology Enhanced Learning (TEL) evidence a growing interest in their development and deployment. In order to support learning, recommender systems for TEL need to consider specific requirements, which differ from the requirements for recommender systems in other domains like…

Space shuttle food system study. Volume 1: System design report

NASA Technical Reports Server (NTRS)

1974-01-01

Data were assembled which define the optimum food system to support the space shuttle program, and which provide sufficient engineering data to support necessary requests for proposals towards final development and installment of the system. The study approach used is outlined, along with technical data and sketches for each functional area. Logistic support analysis, system assurance, and recommendations and conclusions based on the study results are also presented.

MSFC Skylab thermal and environmental control system mission evaluation

NASA Technical Reports Server (NTRS)

Hopson, G. D.; Littles, J. W.; Patterson, W. C.

1974-01-01

An evaluation of the performance of the Skylab thermal and environmental control system is presented. Actual performance is compared to design and functional requirements and anomalies and discrepancies and their resolution are discussed. The thermal and environmental control systems performed their intended role. Based on the experience gained in design, development and flight, recommendations are provided which may be beneficial to future system designs.

Washington's Community and Technical Colleges' Student Achievement Initiative: Lessons Learned since the 2012 Revision and Considerations for New Allocation Model. Research Report 16-1

ERIC Educational Resources Information Center

Washington State Board for Community and Technical Colleges, 2016

2016-01-01

In January 2012, a system-wide task force came together for a nearly year-long process of revising the community and technical college system's performance-based funding (PBF) system, the Student Achievement Initiative. This review was consistent with national experts' recommendations for continuous evaluation of PBF systems to ensure overall…

Cost/Benefit Analysis of Competing Patient Education Systems.

DTIC Science & Technology

1977-10-28

The purpose of this study was to determine the best of three methods of administering patient education based on both cost and benefits. The two...objectives were to perform a cost/benefit analysis (CBA) on the various approaches to administering patient education , and to make a recommendation based

Core components for effective infection prevention and control programmes: new WHO evidence-based recommendations.

PubMed

Storr, Julie; Twyman, Anthony; Zingg, Walter; Damani, Nizam; Kilpatrick, Claire; Reilly, Jacqui; Price, Lesley; Egger, Matthias; Grayson, M Lindsay; Kelley, Edward; Allegranzi, Benedetta

2017-01-01

Health care-associated infections (HAI) are a major public health problem with a significant impact on morbidity, mortality and quality of life. They represent also an important economic burden to health systems worldwide. However, a large proportion of HAI are preventable through effective infection prevention and control (IPC) measures. Improvements in IPC at the national and facility level are critical for the successful containment of antimicrobial resistance and the prevention of HAI, including outbreaks of highly transmissible diseases through high quality care within the context of universal health coverage. Given the limited availability of IPC evidence-based guidance and standards, the World Health Organization (WHO) decided to prioritize the development of global recommendations on the core components of effective IPC programmes both at the national and acute health care facility level, based on systematic literature reviews and expert consensus. The aim of the guideline development process was to identify the evidence and evaluate its quality, consider patient values and preferences, resource implications, and the feasibility and acceptability of the recommendations. As a result, 11 recommendations and three good practice statements are presented here, including a summary of the supporting evidence, and form the substance of a new WHO IPC guideline.

Secondary Prevention of Cervical Cancer: ASCO Resource-Stratified Clinical Practice Guideline.

PubMed

Jeronimo, Jose; Castle, Philip E; Temin, Sarah; Denny, Lynette; Gupta, Vandana; Kim, Jane J; Luciani, Silvana; Murokora, Daniel; Ngoma, Twalib; Qiao, Youlin; Quinn, Michael; Sankaranarayanan, Rengaswamy; Sasieni, Peter; Schmeler, Kathleen M; Shastri, Surendra S

2017-10-01

To provide resource-stratified, evidence-based recommendations on the secondary prevention of cervical cancer globally. ASCO convened a multidisciplinary, multinational panel of oncology, primary care, epidemiology, health economic, cancer control, public health, and patient advocacy experts to produce recommendations reflecting four resource-tiered settings. A review of existing guidelines, a formal consensus-based process, and a modified ADAPTE process to adapt existing guidelines were conducted. Other experts participated in formal consensus. Seven existing guidelines were identified and reviewed, and adapted recommendations form the evidence base. Four systematic reviews plus cost-effectiveness analyses provided indirect evidence to inform consensus, which resulted in ≥ 75% agreement. Human papillomavirus (HPV) DNA testing is recommended in all resource settings; visual inspection with acetic acid may be used in basic settings. Recommended age ranges and frequencies by setting are as follows: maximal: ages 25 to 65, every 5 years; enhanced: ages 30 to 65, if two consecutive negative tests at 5-year intervals, then every 10 years; limited: ages 30 to 49, every 10 years; and basic: ages 30 to 49, one to three times per lifetime. For basic settings, visual assessment is recommended as triage; in other settings, genotyping and/or cytology are recommended. For basic settings, treatment is recommended if abnormal triage results are present; in other settings, colposcopy is recommended for abnormal triage results. For basic settings, treatment options are cryotherapy or loop electrosurgical excision procedure; for other settings, loop electrosurgical excision procedure (or ablation) is recommended. Twelve-month post-treatment follow-up is recommended in all settings. Women who are HIV positive should be screened with HPV testing after diagnosis and screened twice as many times per lifetime as the general population. Screening is recommended at 6 weeks postpartum in basic settings; in other settings, screening is recommended at 6 months. In basic settings without mass screening, infrastructure for HPV testing, diagnosis, and treatment should be developed.Additional information can be found at www.asco.org/rs-cervical-cancer-secondary-prev-guideline and www.asco.org/guidelineswiki.It is the view of of ASCO that health care providers and health care system decision makers should be guided by the recommendations for the highest stratum of resources available. The guideline is intended to complement, but not replace, local guidelines.

Life cycle cost based program decisions

NASA Technical Reports Server (NTRS)

Dick, James S.

1991-01-01

The following subject areas are covered: background (space propulsion facility assessment team final report); changes (Advanced Launch System, National Aerospace Plane, and space exploration initiative); life cycle cost analysis rationale; and recommendation to panel.

National Recommended Water Quality Criteria - Organoleptic Effects

EPA Pesticide Factsheets

These criteria are based on organoleptic (taste and odor) effects. Because of variations in chemical nomenclature systems, this listing of pollutants does not duplicate the listing in Appendix A of 40 CFR Part 423.

Strategy for exploration of the outer planets: 1986-1996

NASA Technical Reports Server (NTRS)

1986-01-01

Over the past decade COMPLEX has published three strategy reports which, taken together, encompass the entire planetary system and recommend a coherent program of planetary exploration. The highest priority for outer planet exploration during the next decade is intensive study of Saturn (the planet, satellites, rings, and magnetosphere) as a system. The Committee additionally recommends that NASA engage in the following supporting activities: increased support of laboratory and theoretical studies; pursuit of earth-based and earth-orbital observations; commitment to continued operation of productive spacecraft; implementation of the instrument development plan as appropriate for the outer solar system; studies of deep atmospheric probes; development of penetrators or other hard landers; development of radiation-hardened spacecraft; and development of low-thrust propulsion systems. Longer-term objectives include exploration and intensive study of: the Uranus and Neptune systems; planetology of the Galilean satellites and Titan; and the inner Jovian system.

SYNAISTHISI: an IoT-powered smart visitor management and cognitive recommendations system

NASA Astrophysics Data System (ADS)

Thanos, Giorgos Konstandinos; Karafylli, Christina; Karafylli, Maria; Zacharakis, Dimitris; Papadimitriou, Apostolis; Dimitros, Kostantinos; Kanellopoulou, Konstantina; Kyriazanos, Dimitris M.; Thomopoulos, Stelios C. A.

2016-05-01

Location-based and navigation services are really needed to help visitors and audience of big events, complex buildings, shopping malls, airports and large companies. However, the lack of GPS and proper mapping indoors usually renders location-based applications and services useless or simply not applicable in such environments. SYNAISTHISI introduces a mobile application for smartphones which offers navigation capabilities outside and inside buildings and through multiple floor levels. The application comes together with a suite of helpful services, including personalized recommendations, visit/event management and a helpful search functionality in order to navigate to a specific location, event or person. As the user finds his way towards his destination, NFC-enabled checkpoints and bluetooth beacons assist him, while offering re-routing, check-in/out capabilities and useful information about ongoing meetings and nearby events. The application is supported by a back-end GIS system which can provide a broad and clear view to event organizers, campus managers and field personnel for purposes of event logistics, safety and security. SYNAISTHISI system comes with plenty competitive advantages including (a) Seamless Navigation as users move between outdoor and indoor areas and different floor levels by using innovative routing algorithms, (b) connection to and powered by IoT platform, for localization and real-time information feedback, (c) dynamic personalized recommendations based on user profile, location and real-time information provided by the IoT platform and (d) Indoor localization without the need for expensive infrastructure and installations.

An exposure indicator for digital radiography: AAPM Task Group 116 (executive summary).

PubMed

Shepard, S Jeff; Wang, Jihong; Flynn, Michael; Gingold, Eric; Goldman, Lee; Krugh, Kerry; Leong, David L; Mah, Eugene; Ogden, Kent; Peck, Donald; Samei, Ehsan; Wang, Jihong; Willis, Charles E

2009-07-01

Digital radiographic imaging systems, such as those using photostimulable storage phosphor, amorphous selenium, amorphous silicon, CCD, and MOSFET technology, can produce adequate image quality over a much broader range of exposure levels than that of screen/film imaging systems. In screen/film imaging, the final image brightness and contrast are indicative of over- and underexposure. In digital imaging, brightness and contrast are often determined entirely by digital postprocessing of the acquired image data. Overexposure and underexposures are not readily recognizable. As a result, patient dose has a tendency to gradually increase over time after a department converts from screen/film-based imaging to digital radiographic imaging. The purpose of this report is to recommend a standard indicator which reflects the radiation exposure that is incident on a detector after every exposure event and that reflects the noise levels present in the image data. The intent is to facilitate the production of consistent, high quality digital radiographic images at acceptable patient doses. This should be based not on image optical density or brightness but on feedback regarding the detector exposure provided and actively monitored by the imaging system. A standard beam calibration condition is recommended that is based on RQA5 but uses filtration materials that are commonly available and simple to use. Recommendations on clinical implementation of the indices to control image quality and patient dose are derived from historical tolerance limits and presented as guidelines.

An exposure indicator for digital radiography: AAPM Task Group 116 (Executive Summary)

PubMed Central

Shepard, S. Jeff; Wang, Jihong; Flynn, Michael; Gingold, Eric; Goldman, Lee; Krugh, Kerry; Leong, David L.; Mah, Eugene; Ogden, Kent; Peck, Donald; Samei, Ehsan; Wang, Jihong; Willis, Charles E.

2009-01-01

Digital radiographic imaging systems, such as those using photostimulable storage phosphor, amorphous selenium, amorphous silicon, CCD, and MOSFET technology, can produce adequate image quality over a much broader range of exposure levels than that of screen/film imaging systems. In screen/film imaging, the final image brightness and contrast are indicative of over- and underexposure. In digital imaging, brightness and contrast are often determined entirely by digital postprocessing of the acquired image data. Overexposure and underexposures are not readily recognizable. As a result, patient dose has a tendency to gradually increase over time after a department converts from screen/film-based imaging to digital radiographic imaging. The purpose of this report is to recommend a standard indicator which reflects the radiation exposure that is incident on a detector after every exposure event and that reflects the noise levels present in the image data. The intent is to facilitate the production of consistent, high quality digital radiographic images at acceptable patient doses. This should be based not on image optical density or brightness but on feedback regarding the detector exposure provided and actively monitored by the imaging system. A standard beam calibration condition is recommended that is based on RQA5 but uses filtration materials that are commonly available and simple to use. Recommendations on clinical implementation of the indices to control image quality and patient dose are derived from historical tolerance limits and presented as guidelines. PMID:19673189

The load shedding advisor: An example of a crisis-response expert system

NASA Technical Reports Server (NTRS)

Bollinger, Terry B.; Lightner, Eric; Laverty, John; Ambrose, Edward

1987-01-01

A Prolog-based prototype expert system is described that was implemented by the Network Operations Branch of the NASA Goddard Space Flight Center. The purpose of the prototype was to test whether a small, inexpensive computer system could be used to host a load shedding advisor, a system which would monitor major physical environment parameters in a computer facility, then recommend appropriate operator reponses whenever a serious condition was detected. The resulting prototype performed significantly to efficiency gains achieved by replacing a purely rule-based design methodology with a hybrid approach that combined procedural, entity-relationship, and rule-based methods.

An Evidence-based Guideline for the air medical transportation of prehospital trauma patients.

PubMed

Thomas, Stephen H; Brown, Kathleen M; Oliver, Zoë J; Spaite, Daniel W; Lawner, Benjamin J; Sahni, Ritu; Weik, Tasmeen S; Falck-Ytter, Yngve; Wright, Joseph L; Lang, Eddy S

2014-01-01

Decisions about the transportation of trauma patients by helicopter are often not well informed by research assessing the risks, benefits, and costs of such transport. The objective of this evidence-based guideline (EBG) is to recommend a strategy for the selection of prehospital trauma patients who would benefit most from aeromedical transportation. A multidisciplinary panel was recruited consisting of experts in trauma, EBG development, and emergency medical services (EMS) outcomes research. Representatives of the Federal Interagency Committee on Emergency Medical Services (FICEMS), the National Highway Traffic Safety Administration (NHTSA) (funding agency), and the Children's National Medical Center (investigative team) also contributed to the process. The panel used the Grading of Recommendations Assessment, Development and Evaluation (GRADE) methodology to guide question formulation, evidence retrieval, appraisal/synthesis, and formulate recommendations. The process followed the National Evidence-Based Guideline Model Process, which has been approved by the Federal Interagency Committee on EMS and the National EMS Advisory Council. Two strong and three weak recommendations emerged from the process, all supported only by low or very low quality evidence. The panel strongly recommended that the 2011 CDC Guideline for the Field Triage of Injured Patients be used as the initial step in the triage process, and that ground emergency medical services (GEMS) be used for patients not meeting CDC anatomic, physiologic, and situational high-acuity criteria. The panel issued a weak recommendation to use helicopter emergency medical services (HEMS) for higher-acuity patients if there is a time-savings versus GEMS, or if an appropriate hospital is not accessible by GEMS due to systemic/logistical factors. The panel strongly recommended that online medical direction should not be required for activating HEMS. Special consideration was given to the potential need for local adaptation. Systematic and transparent methodology was used to develop an evidence-based guideline for the transportation of prehospital trauma patients. The recommendations provide specific guidance regarding the activation of GEMS and HEMS for patients of varying acuity. Future research is required to strengthen the data and recommendations, define optimal approaches for guideline implementation, and determine the impact of implementation on safety and outcomes including cost.

Collaborative Filtering Recommendation on Users' Interest Sequences.

PubMed

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users' dynamic preferences in many papers. However, the sequence of users' behaviour is rarely studied in recommender systems. Due to the users' unique behavior evolution patterns and personalized interest transitions among items, users' similarity in sequential dimension should be introduced to further distinguish users' preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users' interest sequences (IS) that rank users' ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users' longest common sub-IS (LCSIS) and the count of users' total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users' IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users' preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction.

Collaborative Filtering Recommendation on Users’ Interest Sequences

PubMed Central

Cheng, Weijie; Yin, Guisheng; Dong, Yuxin; Dong, Hongbin; Zhang, Wansong

2016-01-01

As an important factor for improving recommendations, time information has been introduced to model users’ dynamic preferences in many papers. However, the sequence of users’ behaviour is rarely studied in recommender systems. Due to the users’ unique behavior evolution patterns and personalized interest transitions among items, users’ similarity in sequential dimension should be introduced to further distinguish users’ preferences and interests. In this paper, we propose a new collaborative filtering recommendation method based on users’ interest sequences (IS) that rank users’ ratings or other online behaviors according to the timestamps when they occurred. This method extracts the semantics hidden in the interest sequences by the length of users’ longest common sub-IS (LCSIS) and the count of users’ total common sub-IS (ACSIS). Then, these semantics are utilized to obtain users’ IS-based similarities and, further, to refine the similarities acquired from traditional collaborative filtering approaches. With these updated similarities, transition characteristics and dynamic evolution patterns of users’ preferences are considered. Our new proposed method was compared with state-of-the-art time-aware collaborative filtering algorithms on datasets MovieLens, Flixster and Ciao. The experimental results validate that the proposed recommendation method is effective and outperforms several existing algorithms in the accuracy of rating prediction. PMID:27195787

Diagnosis of Acute Gout: A Clinical Practice Guideline From the American College of Physicians.

PubMed

Qaseem, Amir; McLean, Robert M; Starkey, Melissa; Forciea, Mary Ann

2017-01-03

The American College of Physicians (ACP) developed this guideline to present the evidence and provide clinical recommendations on the diagnosis of gout. This guideline is based on a systematic review of published studies on gout diagnosis, identified using several databases, from database inception to February 2016. Evaluated outcomes included the accuracy of the test results; intermediate outcomes (results of laboratory and radiographic tests, such as serum urate and synovial fluid crystal analysis and radiographic or ultrasonography changes); clinical decision making (additional testing and pharmacologic or dietary management); short-term clinical (patient-centered) outcomes, such as pain and joint swelling and tenderness; and adverse effects of the tests. This guideline grades the evidence and recommendations by using the ACP grading system, which is based on the GRADE (Grading of Recommendations Assessment, Development and Evaluation) method. The target audience for this guideline includes all clinicians, and the target patient population includes adults with joint inflammation suspected to be gout. ACP recommends that clinicians use synovial fluid analysis when clinical judgment indicates that diagnostic testing is necessary in patients with possible acute gout. (Grade: weak recommendation, low-quality evidence).

Nursing considerations to complement the Surviving Sepsis Campaign guidelines.

PubMed

Aitken, Leanne M; Williams, Ged; Harvey, Maurene; Blot, Stijn; Kleinpell, Ruth; Labeau, Sonia; Marshall, Andrea; Ray-Barruel, Gillian; Moloney-Harmon, Patricia A; Robson, Wayne; Johnson, Alexander P; Lan, Pang Nguk; Ahrens, Tom

2011-07-01

To provide a series of recommendations based on the best available evidence to guide clinicians providing nursing care to patients with severe sepsis. Modified Delphi method involving international experts and key individuals in subgroup work and electronic-based discussion among the entire group to achieve consensus. We used the Surviving Sepsis Campaign guidelines as a framework to inform the structure and content of these guidelines. We used the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system to rate the quality of evidence from high (A) to very low (D) and to determine the strength of recommendations, with grade 1 indicating clear benefit in the septic population and grade 2 indicating less confidence in the benefits in the septic population. In areas without complete agreement between all authors, a process of electronic discussion of all evidence was undertaken until consensus was reached. This process was conducted independently of any funding. Sixty-three recommendations relating to the nursing care of severe sepsis patients are made. Prevention recommendations relate to education, accountability, surveillance of nosocomial infections, hand hygiene, and prevention of respiratory, central line-related, surgical site, and urinary tract infections, whereas infection management recommendations related to both control of the infection source and transmission-based precautions. Recommendations related to initial resuscitation include improved recognition of the deteriorating patient, diagnosis of severe sepsis, seeking further assistance, and initiating early resuscitation measures. Important elements of hemodynamic support relate to improving both tissue oxygenation and macrocirculation. Recommendations related to supportive nursing care incorporate aspects of nutrition, mouth and eye care, and pressure ulcer prevention and management. Pediatric recommendations relate to the use of antibiotics, steroids, vasopressors and inotropes, fluid resuscitation, sedation and analgesia, and the role of therapeutic end points. Consensus was reached regarding many aspects of nursing care of the severe sepsis patient. Despite this, there is an urgent need for further evidence to better inform this area of critical care.

On the Effect of Group Structures on Ranking Strategies in Folksonomies

NASA Astrophysics Data System (ADS)

Abel, Fabian; Henze, Nicola; Krause, Daniel; Kriesell, Matthias

Folksonomies have shown interesting potential for improving information discovery and exploration. Recent folksonomy systems explore the use of tag assignments, which combine Web resources with annotations (tags), and the users that have created the annotations. This article investigates on the effect of grouping resources in folksonomies, i.e. creating sets of resources, and using this additional structure for the tasks of search & ranking, and for tag recommendations. We propose several group-sensitive extensions of graph-based search and recommendation algorithms, and compare them with non group-sensitive versions. Our experiments show that the quality of search result ranking can be significantly improved by introducing and exploiting the grouping of resources (one-tailed t-Test, level of significance α=0.05). Furthermore, tag recommendations profit from the group context, and it is possible to make very good recommendations even for untagged resources- which currently known tag recommendation algorithms cannot fulfill.

A Policy Language for Modelling Recommendations

NASA Astrophysics Data System (ADS)

Abou El Kalam, Anas; Balbiani, Philippe

While current and emergent applications become more and more complex, most of existing security policies and models only consider a yes/no response to the access requests. Consequently, modelling, formalizing and implementing permissions, obligations and prohibitions do not cover the richness of all the possible scenarios. In fact, several applications have access rules with the recommendation access modality. In this paper we focus on the problem of formalizing security policies with recommendation needs. The aim is to provide a generic domain-independent formal system for modelling not only permissions, prohibitions and obligations, but also recommendations. In this respect, we present our logic-based language, the semantics, the truth conditions, our axiomatic as well as inference rules. We also give a representative use case with our specification of recommendation requirements. Finally, we explain how our logical framework could be used to query the security policy and to check its consistency.

Simple Additive Weighting to Diagnose Rabbit Disease

NASA Astrophysics Data System (ADS)

Ramadiani; Marissa, Dyna; Jundillah, Muhammad Labib; Azainil; Hatta, Heliza Rahmania

2018-02-01

Rabbit is one of the many pets maintained by the general public in Indonesia. Like other pet, rabbits are also susceptible to various diseases. Society in general does not understand correctly the type of rabbit disease and the way of treatment. To help care for sick rabbits it is necessary a decision support system recommendation diagnosis of rabbit disease. The purpose of this research is to make the application of rabbit disease diagnosis system so that can help user in taking care of rabbit. This application diagnoses the disease by tracing the symptoms and calculating the recommendation of the disease using Simple Additive Weighting method. This research produces a web-based decision support system that is used to help rabbit breeders and the general public.

Manned space flight nuclear system safety. Volume 6: Space base nuclear system safety plan

NASA Technical Reports Server (NTRS)

1972-01-01

A qualitative identification of the steps required to assure the incorporation of radiological system safety principles and objectives into all phases of a manned space base program are presented. Specific areas of emphasis include: (1) radiological program management, (2) nuclear system safety plan implementation, (3) impact on program, and (4) summary of the key operation and design guidelines and requirements. The plan clearly indicates the necessity of considering and implementing radiological system safety recommendations as early as possible in the development cycle to assure maximum safety and minimize the impact on design and mission plans.

New similarity of triangular fuzzy number and its application.

PubMed

Zhang, Xixiang; Ma, Weimin; Chen, Liping

2014-01-01

The similarity of triangular fuzzy numbers is an important metric for application of it. There exist several approaches to measure similarity of triangular fuzzy numbers. However, some of them are opt to be large. To make the similarity well distributed, a new method SIAM (Shape's Indifferent Area and Midpoint) to measure triangular fuzzy number is put forward, which takes the shape's indifferent area and midpoint of two triangular fuzzy numbers into consideration. Comparison with other similarity measurements shows the effectiveness of the proposed method. Then, it is applied to collaborative filtering recommendation to measure users' similarity. A collaborative filtering case is used to illustrate users' similarity based on cloud model and triangular fuzzy number; the result indicates that users' similarity based on triangular fuzzy number can obtain better discrimination. Finally, a simulated collaborative filtering recommendation system is developed which uses cloud model and triangular fuzzy number to express users' comprehensive evaluation on items, and result shows that the accuracy of collaborative filtering recommendation based on triangular fuzzy number is higher.

Using Google Blogs and Discussions to Recommend Biomedical Resources: A Case Study

PubMed Central

Reed, Robyn B.; Chattopadhyay, Ansuman; Iwema, Carrie L.

2013-01-01

This case study investigated whether data gathered from discussions within the social media provide a reliable basis for a biomedical resources recommendation system. Using a search query to mine text from Google Blogs and Discussions, a ranking of biomedical resources was determined based on those most frequently mentioned. To establish quality, these results were compared to rankings by subject experts. An overall agreement between the frequency of social media discussions and subject expert recommendations was observed when identifying key bioinformatics and consumer health resources. Testing the method in more than one biomedical area implies this procedure could be employed across different subjects. PMID:24180648

Do recommender systems benefit users? a modeling approach

NASA Astrophysics Data System (ADS)

Yeung, Chi Ho

2016-04-01

Recommender systems are present in many web applications to guide purchase choices. They increase sales and benefit sellers, but whether they benefit customers by providing relevant products remains less explored. While in many cases the recommended products are relevant to users, in other cases customers may be tempted to purchase the products only because they are recommended. Here we introduce a model to examine the benefit of recommender systems for users, and find that recommendations from the system can be equivalent to random draws if one always follows the recommendations and seldom purchases according to his or her own preference. Nevertheless, with sufficient information about user preferences, recommendations become accurate and an abrupt transition to this accurate regime is observed for some of the studied algorithms. On the other hand, we find that high estimated accuracy indicated by common accuracy metrics is not necessarily equivalent to high real accuracy in matching users with products. This disagreement between estimated and real accuracy serves as an alarm for operators and researchers who evaluate recommender systems merely with accuracy metrics. We tested our model with a real dataset and observed similar behaviors. Finally, a recommendation approach with improved accuracy is suggested. These results imply that recommender systems can benefit users, but the more frequently a user purchases the recommended products, the less relevant the recommended products are in matching user taste.

Innovations in adult influenza vaccination in China, 2014-2015: Leveraging a chronic disease management system in a community-based intervention.

PubMed

Yi, Bo; Zhou, Suizan; Song, Ying; Chen, Enfu; Lao, Xuyin; Cai, Jian; Greene, Carolyn M; Feng, Luzhao; Zheng, Jiandong; Yu, Hongjie; Dong, Hongjun

2018-04-03

To evaluate a community-based intervention that leveraged the non-communicable disease management system to increase seasonal influenza vaccination coverage among older adults in Ningbo, China. From October 2014 - March 2015, we piloted the following on one street in Ningbo, China: educating community healthcare workers (C-HCWs) about influenza and vaccination; requiring C-HCWs to recommend influenza vaccination to older adults during routine chronic disease follow-up; and opening 14 additional temporary vaccination clinics. We selected a non-intervention street for comparison pre- and post-intervention vaccine coverage. In April 2016, we interviewed a random sample of unvaccinated older adults on the intervention street to ask why they remained unvaccinated. Pre-intervention influenza vaccine coverage among adults aged 60 years and older on both streets was 0.3%. Post-intervention, coverage among adults 60 years and older was 19% (1338/7013) on the intervention street and 0.4% (20/5500) on the non-intervention street (p<0.01). Among vaccinated older adults, 98% reported their main reason for vaccination was receiving a C-HCW's recommendation, 90% were vaccinated at temporary vaccination clinics, and 53% paid for vaccine (10 USD) out-of-pocket. Reasons for not getting vaccinated among 150 unvaccinated adults (response rate = 75%) included: good health (39%); not trusting C-HCWs' recommendations (24%); not knowing where to get vaccinated (17%); and not wanting to pay (9%). Recommending influenza vaccination within a non-communicable disease management system, combined with adding vaccination sites, increased vaccine coverage among older adults in Ningbo, China.

Clinical factors associated with rape victims' ability to testify in court: a records-based study of final psychiatric recommendation to court.

PubMed

Phaswana, T D; Van der Westhuizen, D; Krüger, C

2013-09-01

A rape victim may encounter professionals in both the health and the legal systems. Unanswered questions remain about clinical factors associated with a rape victim's ability to testify in court, and the quality of care offered to rape victims. The objectives of this study were thus to determine the clinical factors that are associated with a rape victim's ability to testify in court, as well as to undertake a preliminary exploration of the referral system between the court and the mental health services. A retrospective study was conducted of rape victims referred by the court (n=70) to be assessed psycho-legally by psychiatrists. Rape victims who were recommended as able and those recommended as unable to testify in court were compared with regard to their clinical characteristics. Thirty-seven (53.6%) victims were recommended as able to testify and 32 (46.4%) victims as unable to testify in court. Victims from rural areas and victims with severe mental retardation were statistically significantly more often found to be unable to testify in court. Almost half (49.2%) of the victims were referred by court for first assessment within six months of being raped. Most (63.5%) victims were assessed for the first time within one month of being referred. The decision about a victim's ability to testify should not be based solely on the two statistically significant variables but, rather, individualised. Optimal mental health and legal services should be offered to rape victims. Further studies are required in assessing the collaboration between the health and legal systems.

[Inflammatory and infectious breast mastitis outside of pregnancy and lactation: Guidelines].

PubMed

Laas, E; Touboul, C; Kerdraon, O; Catteau-Jonard, S

2015-12-01

This work's objective was to define the various non-cancerous inflammatory and infectious mastitis, which may occur outside of pregnancy and lactation, and to identify recommendations for their care based on an exhaustive literature review. A literature review was conducted by consulting Medline, Cochrane Library, Google scholar and international recommendations in French and English until 31st August 2014. Infectious mastitis (periareolar abscess) is the most common form of non-puerperal abscesses and it is recommended that a suction/drainage needle for abscesses under 5 cm, involving antibiotic therapy (grade C). For abscesses over 5 cm, there is no evidence to recommend a first surgery or suction/drainage. Inflammatory mastitis can be primary or secondary to a systemic disease (diabetes, collagen…; LE4). In case of idiopathic granulomatous mastitis, a steroid therapy or surgery may be indicated, without one or the other of these methods can be recommended. In case of plasma cell mastitis or ductal ectasia, no treatment is recommended. Copyright © 2015 Elsevier Masson SAS. All rights reserved.

Consensus document on osteoporosis in males.

PubMed

Varsavsky, Mariela; Romero Muñoz, Manuel; Ávila Rubio, Verónica; Becerra, Antonio; García Martín, Antonia; Martínez Díaz-Guerra, Guillermo; Rozas Moreno, Pedro; Jódar Gimeno, Esteban; Muñoz Torres, Manuel

2018-03-01

To provide practical recommendations to assess and treat osteoporosis in males. Members of the Bone Metabolism Working Group of the Spanish Society of Endocrinology. Recommendations were formulated using the GRADE system (Grading of Recommendations, Assessment, Development, and Evaluation) to describe both the strength of recommendations and the quality of evidence. A systematic search was made in Medline (PubMed) using the following associated terms: «osteoporosis», «men», «fractures», «bone mineral density», «treatment», «hypogonadism», and «prostate cancer». Papers in English and Spanish with publication date before 30 August 2017 were included. Current evidence for each disease was reviewed by 2group members. Finally, recommendations were discussed in a meeting of the working group. The document provides evidence-based practical recommendations for diagnosis, assessment, and management of osteoporosis in men and special situations such as hypogonadism and prostate cancer. Copyright © 2018 SEEN y SED. Publicado por Elsevier España, S.L.U. All rights reserved.