Optimizing data collection for public health decisions: a data mining approach

PubMed Central

2014-01-01

Background Collecting data can be cumbersome and expensive. Lack of relevant, accurate and timely data for research to inform policy may negatively impact public health. The aim of this study was to test if the careful removal of items from two community nutrition surveys guided by a data mining technique called feature selection, can (a) identify a reduced dataset, while (b) not damaging the signal inside that data. Methods The Nutrition Environment Measures Surveys for stores (NEMS-S) and restaurants (NEMS-R) were completed on 885 retail food outlets in two counties in West Virginia between May and November of 2011. A reduced dataset was identified for each outlet type using feature selection. Coefficients from linear regression modeling were used to weight items in the reduced datasets. Weighted item values were summed with the error term to compute reduced item survey scores. Scores produced by the full survey were compared to the reduced item scores using a Wilcoxon rank-sum test. Results Feature selection identified 9 store and 16 restaurant survey items as significant predictors of the score produced from the full survey. The linear regression models built from the reduced feature sets had R2 values of 92% and 94% for restaurant and grocery store data, respectively. Conclusions While there are many potentially important variables in any domain, the most useful set may only be a small subset. The use of feature selection in the initial phase of data collection to identify the most influential variables may be a useful tool to greatly reduce the amount of data needed thereby reducing cost. PMID:24919484

Optimizing data collection for public health decisions: a data mining approach.

PubMed

Partington, Susan N; Papakroni, Vasil; Menzies, Tim

2014-06-12

Collecting data can be cumbersome and expensive. Lack of relevant, accurate and timely data for research to inform policy may negatively impact public health. The aim of this study was to test if the careful removal of items from two community nutrition surveys guided by a data mining technique called feature selection, can (a) identify a reduced dataset, while (b) not damaging the signal inside that data. The Nutrition Environment Measures Surveys for stores (NEMS-S) and restaurants (NEMS-R) were completed on 885 retail food outlets in two counties in West Virginia between May and November of 2011. A reduced dataset was identified for each outlet type using feature selection. Coefficients from linear regression modeling were used to weight items in the reduced datasets. Weighted item values were summed with the error term to compute reduced item survey scores. Scores produced by the full survey were compared to the reduced item scores using a Wilcoxon rank-sum test. Feature selection identified 9 store and 16 restaurant survey items as significant predictors of the score produced from the full survey. The linear regression models built from the reduced feature sets had R2 values of 92% and 94% for restaurant and grocery store data, respectively. While there are many potentially important variables in any domain, the most useful set may only be a small subset. The use of feature selection in the initial phase of data collection to identify the most influential variables may be a useful tool to greatly reduce the amount of data needed thereby reducing cost.

Statistical evaluation of synchronous spike patterns extracted by frequent item set mining

PubMed Central

Torre, Emiliano; Picado-Muiño, David; Denker, Michael; Borgelt, Christian; Grün, Sonja

2013-01-01

We recently proposed frequent itemset mining (FIM) as a method to perform an optimized search for patterns of synchronous spikes (item sets) in massively parallel spike trains. This search outputs the occurrence count (support) of individual patterns that are not trivially explained by the counts of any superset (closed frequent item sets). The number of patterns found by FIM makes direct statistical tests infeasible due to severe multiple testing. To overcome this issue, we proposed to test the significance not of individual patterns, but instead of their signatures, defined as the pairs of pattern size z and support c. Here, we derive in detail a statistical test for the significance of the signatures under the null hypothesis of full independence (pattern spectrum filtering, PSF) by means of surrogate data. As a result, injected spike patterns that mimic assembly activity are well detected, yielding a low false negative rate. However, this approach is prone to additionally classify patterns resulting from chance overlap of real assembly activity and background spiking as significant. These patterns represent false positives with respect to the null hypothesis of having one assembly of given signature embedded in otherwise independent spiking activity. We propose the additional method of pattern set reduction (PSR) to remove these false positives by conditional filtering. By employing stochastic simulations of parallel spike trains with correlated activity in form of injected spike synchrony in subsets of the neurons, we demonstrate for a range of parameter settings that the analysis scheme composed of FIM, PSF and PSR allows to reliably detect active assemblies in massively parallel spike trains. PMID:24167487

Improving the Scalability of an Exact Approach for Frequent Item Set Hiding

ERIC Educational Resources Information Center

LaMacchia, Carolyn

2013-01-01

Technological advances have led to the generation of large databases of organizational data recognized as an information-rich, strategic asset for internal analysis and sharing with trading partners. Data mining techniques can discover patterns in large databases including relationships considered strategically relevant to the owner of the data.…

Method of data mining including determining multidimensional coordinates of each item using a predetermined scalar similarity value for each item pair

DOEpatents

Meyers, Charles E.; Davidson, George S.; Johnson, David K.; Hendrickson, Bruce A.; Wylie, Brian N.

1999-01-01

A method of data mining represents related items in a multidimensional space. Distance between items in the multidimensional space corresponds to the extent of relationship between the items. The user can select portions of the space to perceive. The user also can interact with and control the communication of the space, focusing attention on aspects of the space of most interest. The multidimensional spatial representation allows more ready comprehension of the structure of the relationships among the items.

Mining for preparatory processes of transfer learning in a blended course

NASA Astrophysics Data System (ADS)

Ng, K.; Hartman, K.; Goodkin, N.; Wai Hoong Andy, K.

2017-12-01

585 undergraduate science students enrolled in a multidisciplinary environmental sustainability course. Each week, students were given the opportunity to read online materials, answer multiple choice and short answer questions, and attend a three-hour lecture. The online materials and questions were released one week prior to the lecture. After each week, we mined the student data logs exported from the course learning management system and used a model-based clustering algorithm to divide the class into six groups according to resource access patterns. The patterns were mostly based on the frequency with which a student accessed the items in the growing set of online resources and whether those resources were relevant to the upcoming exam. Each exam was self-contained—meaning the second exam did not reference content taught during the first half of the course. The exam items themselves were intentionally designed to provide a mix of recall, application, and transfer items. Recall items referenced facts and examples provided during the lectures and course materials. Application items asked students to solve problems using the methods shown during lecture. Transfer items asked students to use what they had learned to analyze new data sets and unfamiliar problems. We then used a log-likelihood analysis to determine if there were differences in item accuracy on the exams by resource pattern clusters. We found students who deviated from the majority of student access patterns by accessing prior material during the recess break before new material had been assigned and introduced performed significantly more accurately on the transfer items than the other cluster groups. This finding fits with the concept of Preparation for Future Learning (Bransford & Schwartz, 1999) which suggests learners can be strategic about their learning to prepare themselves to complete new tasks in the future. Our findings also suggest that using learning analytics to call attention activity during expected lulls in a course might be a productive method of predicting future performance. Bransford, J. D., & Schwartz, D. L. (1999). Rethinking transfer: A simple proposal with multiple implications. In A. Iran-Nejad & P. D. Pearson (Eds.), Review of research in education, 24 (pp. 61-101). Washington, DC: American Educational Research Association

Assessing the evolution of sustainability reporting in the mining sector.

PubMed

Perez, Fabiana; Sanchez, Luis E

2009-06-01

Since the 1990s several large companies have been publishing nonfinancial performance reports. Focusing initially on the physical environment, these reports evolved to consider social relations, as well as data on the firm's economic performance. A few mining companies pioneered this trend, and in the last years some of them incorporated the three dimensions of sustainable development, publishing so-called sustainability reports. This article reviews 31 reports published between 2001 and 2006 by four major mining companies. A set of 62 assessment items organized in six categories (namely context and commitment, management, environmental, social and economic performance, and accessibility and assurance) were selected to guide the review. The items were derived from international literature and recommended best practices, including the Global Reporting Initiative G3 framework. A content analysis was performed using the report as a sampling unit, and using phrases, graphics, or tables containing certain information as data collection units. A basic rating scale (0 or 1) was used for noting the presence or absence of information and a final percentage score was obtained for each report. Results show that there is a clear evolution in report's comprehensiveness and depth. Categories "accessibility and assurance" and "economic performance" featured the lowest scores and do not present a clear evolution trend in the period, whereas categories "context and commitment" and "social performance" presented the best results and regular improvement; the category "environmental performance," despite it not reaching the biggest scores, also featured constant evolution. Description of data measurement techniques, besides more comprehensive third-party verification are the items most in need of improvement.

RANWAR: rank-based weighted association rule mining from gene expression and methylation data.

PubMed

Mallik, Saurav; Mukhopadhyay, Anirban; Maulik, Ujjwal

2015-01-01

Ranking of association rules is currently an interesting topic in data mining and bioinformatics. The huge number of evolved rules of items (or, genes) by association rule mining (ARM) algorithms makes confusion to the decision maker. In this article, we propose a weighted rule-mining technique (say, RANWAR or rank-based weighted association rule-mining) to rank the rules using two novel rule-interestingness measures, viz., rank-based weighted condensed support (wcs) and weighted condensed confidence (wcc) measures to bypass the problem. These measures are basically depended on the rank of items (genes). Using the rank, we assign weight to each item. RANWAR generates much less number of frequent itemsets than the state-of-the-art association rule mining algorithms. Thus, it saves time of execution of the algorithm. We run RANWAR on gene expression and methylation datasets. The genes of the top rules are biologically validated by Gene Ontologies (GOs) and KEGG pathway analyses. Many top ranked rules extracted from RANWAR that hold poor ranks in traditional Apriori, are highly biologically significant to the related diseases. Finally, the top rules evolved from RANWAR, that are not in Apriori, are reported.

Using Data Mining to Predict K-12 Students' Performance on Large-Scale Assessment Items Related to Energy

ERIC Educational Resources Information Center

Liu, Xiufeng; Ruiz, Miguel E.

2008-01-01

This article reports a study on using data mining to predict K-12 students' competence levels on test items related to energy. Data sources are the 1995 Third International Mathematics and Science Study (TIMSS), 1999 TIMSS-Repeat, 2003 Trend in International Mathematics and Science Study (TIMSS), and the National Assessment of Educational…

A novel approach for incremental uncertainty rule generation from databases with missing values handling: application to dynamic medical databases.

PubMed

Konias, Sokratis; Chouvarda, Ioanna; Vlahavas, Ioannis; Maglaveras, Nicos

2005-09-01

Current approaches for mining association rules usually assume that the mining is performed in a static database, where the problem of missing attribute values does not practically exist. However, these assumptions are not preserved in some medical databases, like in a home care system. In this paper, a novel uncertainty rule algorithm is illustrated, namely URG-2 (Uncertainty Rule Generator), which addresses the problem of mining dynamic databases containing missing values. This algorithm requires only one pass from the initial dataset in order to generate the item set, while new metrics corresponding to the notion of Support and Confidence are used. URG-2 was evaluated over two medical databases, introducing randomly multiple missing values for each record's attribute (rate: 5-20% by 5% increments) in the initial dataset. Compared with the classical approach (records with missing values are ignored), the proposed algorithm was more robust in mining rules from datasets containing missing values. In all cases, the difference in preserving the initial rules ranged between 30% and 60% in favour of URG-2. Moreover, due to its incremental nature, URG-2 saved over 90% of the time required for thorough re-mining. Thus, the proposed algorithm can offer a preferable solution for mining in dynamic relational databases.

SPMBR: a scalable algorithm for mining sequential patterns based on bitmaps

NASA Astrophysics Data System (ADS)

Xu, Xiwei; Zhang, Changhai

2013-12-01

Now some sequential patterns mining algorithms generate too many candidate sequences, and increase the processing cost of support counting. Therefore, we present an effective and scalable algorithm called SPMBR (Sequential Patterns Mining based on Bitmap Representation) to solve the problem of mining the sequential patterns for large databases. Our method differs from previous related works of mining sequential patterns. The main difference is that the database of sequential patterns is represented by bitmaps, and a simplified bitmap structure is presented firstly. In this paper, First the algorithm generate candidate sequences by SE(Sequence Extension) and IE(Item Extension), and then obtain all frequent sequences by comparing the original bitmap and the extended item bitmap .This method could simplify the problem of mining the sequential patterns and avoid the high processing cost of support counting. Both theories and experiments indicate that the performance of SPMBR is predominant for large transaction databases, the required memory size for storing temporal data is much less during mining process, and all sequential patterns can be mined with feasibility.

An Incremental High-Utility Mining Algorithm with Transaction Insertion

PubMed Central

Gan, Wensheng; Zhang, Binbin

2015-01-01

Association-rule mining is commonly used to discover useful and meaningful patterns from a very large database. It only considers the occurrence frequencies of items to reveal the relationships among itemsets. Traditional association-rule mining is, however, not suitable in real-world applications since the purchased items from a customer may have various factors, such as profit or quantity. High-utility mining was designed to solve the limitations of association-rule mining by considering both the quantity and profit measures. Most algorithms of high-utility mining are designed to handle the static database. Fewer researches handle the dynamic high-utility mining with transaction insertion, thus requiring the computations of database rescan and combination explosion of pattern-growth mechanism. In this paper, an efficient incremental algorithm with transaction insertion is designed to reduce computations without candidate generation based on the utility-list structures. The enumeration tree and the relationships between 2-itemsets are also adopted in the proposed algorithm to speed up the computations. Several experiments are conducted to show the performance of the proposed algorithm in terms of runtime, memory consumption, and number of generated patterns. PMID:25811038

An Integrated Suite of Text and Data Mining Tools - Phase II

DTIC Science & Technology

2005-08-30

Riverside, CA, USA Mazda Motor Corp, Jpn Univ of Darmstadt, Darmstadt, Ger Navy Center for Applied Research in Artificial Intelligence Univ of...with Georgia Tech Research Corporation developed a desktop text-mining software tool named TechOASIS (known commercially as VantagePoint). By the...of this dataset and groups the Corporate Source items that co-occur with the found items. He decides he is only interested in the institutions

Sensor Technology Assessment for Ordnance and Explosive Waste Detection and Location. Revision B.

DTIC Science & Technology

1995-03-01

5 Figure 1.5 Examples Of Anti-Tank Mines .................... .................... 5 Figure 1.6. Sample Drawing of a Bomb...6 Figure 1.7. Examples of Scatterable Anti-Personnel Mines (top) and Scatterable Anti-Tank Mines (bottom...individuals, and therefore the OEW items must be detected and located. OEW examples are bombs, warheads, guided missiles, mortars, small arms, mines

Research on parallel algorithm for sequential pattern mining

NASA Astrophysics Data System (ADS)

Zhou, Lijuan; Qin, Bai; Wang, Yu; Hao, Zhongxiao

2008-03-01

Sequential pattern mining is the mining of frequent sequences related to time or other orders from the sequence database. Its initial motivation is to discover the laws of customer purchasing in a time section by finding the frequent sequences. In recent years, sequential pattern mining has become an important direction of data mining, and its application field has not been confined to the business database and has extended to new data sources such as Web and advanced science fields such as DNA analysis. The data of sequential pattern mining has characteristics as follows: mass data amount and distributed storage. Most existing sequential pattern mining algorithms haven't considered the above-mentioned characteristics synthetically. According to the traits mentioned above and combining the parallel theory, this paper puts forward a new distributed parallel algorithm SPP(Sequential Pattern Parallel). The algorithm abides by the principal of pattern reduction and utilizes the divide-and-conquer strategy for parallelization. The first parallel task is to construct frequent item sets applying frequent concept and search space partition theory and the second task is to structure frequent sequences using the depth-first search method at each processor. The algorithm only needs to access the database twice and doesn't generate the candidated sequences, which abates the access time and improves the mining efficiency. Based on the random data generation procedure and different information structure designed, this paper simulated the SPP algorithm in a concrete parallel environment and implemented the AprioriAll algorithm. The experiments demonstrate that compared with AprioriAll, the SPP algorithm had excellent speedup factor and efficiency.

Data mining learning bootstrap through semantic thumbnail analysis

NASA Astrophysics Data System (ADS)

Battiato, Sebastiano; Farinella, Giovanni Maria; Giuffrida, Giovanni; Tribulato, Giuseppe

2007-01-01

The rapid increase of technological innovations in the mobile phone industry induces the research community to develop new and advanced systems to optimize services offered by mobile phones operators (telcos) to maximize their effectiveness and improve their business. Data mining algorithms can run over data produced by mobile phones usage (e.g. image, video, text and logs files) to discover user's preferences and predict the most likely (to be purchased) offer for each individual customer. One of the main challenges is the reduction of the learning time and cost of these automatic tasks. In this paper we discuss an experiment where a commercial offer is composed by a small picture augmented with a short text describing the offer itself. Each customer's purchase is properly logged with all relevant information. Upon arrival of new items we need to learn who the best customers (prospects) for each item are, that is, the ones most likely to be interested in purchasing that specific item. Such learning activity is time consuming and, in our specific case, is not applicable given the large number of new items arriving every day. Basically, given the current customer base we are not able to learn on all new items. Thus, we need somehow to select among those new items to identify the best candidates. We do so by using a joint analysis between visual features and text to estimate how good each new item could be, that is, whether or not is worth to learn on it. Preliminary results show the effectiveness of the proposed approach to improve classical data mining techniques.

77 FR 67362 - Application for Final Commitment for a Long-Term Loan or Financial Guarantee in Excess of $100...

Federal Register 2010, 2011, 2012, 2013, 2014

2012-11-09

... transaction: To support the export of mining trucks and bulldozers to Ukraine. Brief non-proprietary description of the anticipated use of the items being exported: To mine iron ore in Ukraine To the extent that... industry. Parties: Principal Supplier: Caterpillar Inc. Obligors: OJSC Ferrexpo Poltava Mining, Ukraine...

Data mining: comparing the empiric CFS to the Canadian ME/CFS case definition.

PubMed

Jason, Leonard A; Skendrovic, Beth; Furst, Jacob; Brown, Abigail; Weng, Angela; Bronikowski, Christine

2012-01-01

This article contrasts two case definitions for myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS). We compared the empiric CFS case definition (Reeves et al., 2005) and the Canadian ME/CFS clinical case definition (Carruthers et al., 2003) with a sample of individuals with CFS versus those without. Data mining with decision trees was used to identify the best items to identify patients with CFS. Data mining is a statistical technique that was used to help determine which of the survey questions were most effective for accurately classifying cases. The empiric criteria identified about 79% of patients with CFS and the Canadian criteria identified 87% of patients. Items identified by the Canadian criteria had more construct validity. The implications of these findings are discussed. © 2011 Wiley Periodicals, Inc.

A Case-Based Toxicology Module on Agricultural- and Mining-Related Occupational Exposures

PubMed Central

2012-01-01

Objective. To develop and assess a toxicology module to teach pharmacy students about farming- and mining-related occupational exposures in the context of an existing toxicology elective course. Design. A teaching unit that included lectures and case studies was developed to address the unique occupational exposures of patients working in agricultural and mining environments. Upon completion of this 4-hour (2 class periods) module, students were expected to recognize the clinical signs and symptoms associated with these occupational exposures and propose acceptable therapeutic plans. Assessment. After completing the module, students scored significantly higher on a patient case involving suicide resulting from pesticide consumption. Seventy-three percent of the students scored higher than 90% on a 33-item multiple-choice examination. Eighty-two percent of students were able to correctly read a product label to determine the type of pesticide involved in an occupational exposure. Conclusion. Pharmacy students who completed a module on occupation exposure demonstrated competence in distinguishing occupational exposures from each other and from exposure to prescription and nonprescription drugs. This module can be used to educate future pharmacists about occupational health issues, some of which may be more prevalent in a rural setting. PMID:23049108

Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care

PubMed Central

Ismail, Walaa N.; Hassan, Mohammad Mehedi

2017-01-01

The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants’ health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth) to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones. PMID:28445441

Mining Productive-Associated Periodic-Frequent Patterns in Body Sensor Data for Smart Home Care.

PubMed

Ismail, Walaa N; Hassan, Mohammad Mehedi

2017-04-26

The understanding of various health-oriented vital sign data generated from body sensor networks (BSNs) and discovery of the associations between the generated parameters is an important task that may assist and promote important decision making in healthcare. For example, in a smart home scenario where occupants' health status is continuously monitored remotely, it is essential to provide the required assistance when an unusual or critical situation is detected in their vital sign data. In this paper, we present an efficient approach for mining the periodic patterns obtained from BSN data. In addition, we employ a correlation test on the generated patterns and introduce productive-associated periodic-frequent patterns as the set of correlated periodic-frequent items. The combination of these measures has the advantage of empowering healthcare providers and patients to raise the quality of diagnosis as well as improve treatment and smart care, especially for elderly people in smart homes. We develop an efficient algorithm named PPFP-growth (Productive Periodic-Frequent Pattern-growth) to discover all productive-associated periodic frequent patterns using these measures. PPFP-growth is efficient and the productiveness measure removes uncorrelated periodic items. An experimental evaluation on synthetic and real datasets shows the efficiency of the proposed PPFP-growth algorithm, which can filter a huge number of periodic patterns to reveal only the correlated ones.

Types of Online Hierarchical Repository Structures

ERIC Educational Resources Information Center

Hershkovitz, Arnon; Azran, Ronit; Hardof-Jaffe, Sharon; Nachmias, Rafi

2011-01-01

This study presents an empirical investigation of online hierarchical repositories of items presented to university students in Web-supported course websites, using Web mining methods. To this end, data from 1747 courses were collected, and the use of online repositories of content items in these courses was examined. At a later stage, courses…

ORD'S ORGANIZATION AND HOW IT IS FUNDED. OVERVIEW OF SCIENTIST-TO-SCIENTIST MINING (TOPICS, OUTCOMES, MAJOR OUTCOMES). FOLLOW-UP ACTION ITEMS.

EPA Science Inventory

This discussion was geered to mining experts and discussed mixed ownership sites, ecological risk ssessments, Good Sam Legislation, and lessons learned on Superfund Sites. An overview of ORD was also presented as well as a dicussion on funding, and the purpose of scientist-to-sc...

Method using a density field for locating related items for data mining

DOEpatents

Wylie, Brian N.

2002-01-01

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method makes use of numeric values as a measure of similarity between each pairing of items. The items are given initial coordinates in the space. An energy is then determined for each item from the item's distance and similarity to other items, and from the density of items assigned coordinates near the item. The distance and similarity component can act to draw items with high similarities close together, while the density component can act to force all items apart. If a terminal condition is not yet reached, then new coordinates can be determined for one or more items, and the energy determination repeated. The iteration can terminate, for example, when the total energy reaches a threshold, when each item's energy is below a threshold, after a certain amount of time or iterations.

Efficient Algorithms for Segmentation of Item-Set Time Series

NASA Astrophysics Data System (ADS)

Chundi, Parvathi; Rosenkrantz, Daniel J.

We propose a special type of time series, which we call an item-set time series, to facilitate the temporal analysis of software version histories, email logs, stock market data, etc. In an item-set time series, each observed data value is a set of discrete items. We formalize the concept of an item-set time series and present efficient algorithms for segmenting a given item-set time series. Segmentation of a time series partitions the time series into a sequence of segments where each segment is constructed by combining consecutive time points of the time series. Each segment is associated with an item set that is computed from the item sets of the time points in that segment, using a function which we call a measure function. We then define a concept called the segment difference, which measures the difference between the item set of a segment and the item sets of the time points in that segment. The segment difference values are required to construct an optimal segmentation of the time series. We describe novel and efficient algorithms to compute segment difference values for each of the measure functions described in the paper. We outline a dynamic programming based scheme to construct an optimal segmentation of the given item-set time series. We use the item-set time series segmentation techniques to analyze the temporal content of three different data sets—Enron email, stock market data, and a synthetic data set. The experimental results show that an optimal segmentation of item-set time series data captures much more temporal content than a segmentation constructed based on the number of time points in each segment, without examining the item set data at the time points, and can be used to analyze different types of temporal data.

Data Mining of Extremely Large Ad Hoc Data Sets to Produce Inverted Indices

DTIC Science & Technology

2016-06-01

NAVAL POSTGRADUATE SCHOOL MONTEREY, CALIFORNIA THESIS Approved for public release; distribution is unlimited DATA MINING OF...COVERED Master’s Thesis 4. TITLE AND SUBTITLE DATA MINING OF EXTREMELY LARGE AD HOC DATA SETS TO PRODUCE INVERTED INDICES 5. FUNDING NUMBERS 6...INTENTIONALLY LEFT BLANK iii Approved for public release; distribution is unlimited DATA MINING OF EXTREMELY LARGE AD HOC DATA SETS TO PRODUCE

Impact of grouping complications on mortality in traumatic brain injury: A nationwide population-based study.

PubMed

Ho, Chung-Han; Liang, Fu-Wen; Wang, Jhi-Joung; Chio, Chung-Ching; Kuo, Jinn-Rung

2018-01-01

Traumatic brain injury (TBI) is an important health issue with high mortality. Various complications of physiological and cognitive impairment may result in disability or death after TBI. Grouping of these complications could be treated as integrated post-TBI syndromes. To improve risk estimation, grouping TBI complications should be investigated, to better predict TBI mortality. This study aimed to estimate mortality risk based on grouping of complications among TBI patients. Taiwan's National Health Insurance Research Database was used in this study. TBI was defined according to the International Classification of Diseases, Ninth Revision, Clinical Modification codes: 801-804 and 850-854. The association rule data mining method was used to analyze coexisting complications after TBI. The mortality risk of post-TBI complication sets with the potential risk factors was estimated using Cox regression. A total 139,254 TBI patients were enrolled in this study. Intracerebral hemorrhage was the most common complication among TBI patients. After frequent item set mining, the most common post-TBI grouping of complications comprised pneumonia caused by acute respiratory failure (ARF) and urinary tract infection, with mortality risk 1.55 (95% C.I.: 1.51-1.60), compared with those without the selected combinations. TBI patients with the combined combinations have high mortality risk, especially those aged <20 years with septicemia, pneumonia, and ARF (HR: 4.95, 95% C.I.: 3.55-6.88). We used post-TBI complication sets to estimate mortality risk among TBI patients. According to the combinations determined by mining, especially the combination of septicemia with pneumonia and ARF, TBI patients have a 1.73-fold increased mortality risk, after controlling for potential demographic and clinical confounders. TBI patients aged<20 years with each combination of complications also have increased mortality risk. These results could provide physicians and caregivers with important information to increase their awareness about sequences of clinical syndromes among TBI patients, to prevent possible deaths among these patients.

Text mining a self-report back-translation.

PubMed

Blanch, Angel; Aluja, Anton

2016-06-01

There are several recommendations about the routine to undertake when back translating self-report instruments in cross-cultural research. However, text mining methods have been generally ignored within this field. This work describes a text mining innovative application useful to adapt a personality questionnaire to 12 different languages. The method is divided in 3 different stages, a descriptive analysis of the available back-translated instrument versions, a dissimilarity assessment between the source language instrument and the 12 back-translations, and an item assessment of item meaning equivalence. The suggested method contributes to improve the back-translation process of self-report instruments for cross-cultural research in 2 significant intertwined ways. First, it defines a systematic approach to the back translation issue, allowing for a more orderly and informed evaluation concerning the equivalence of different versions of the same instrument in different languages. Second, it provides more accurate instrument back-translations, which has direct implications for the reliability and validity of the instrument's test scores when used in different cultures/languages. In addition, this procedure can be extended to the back-translation of self-reports measuring psychological constructs in clinical assessment. Future research works could refine the suggested methodology and use additional available text mining tools. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Real-time intelligent decision making with data mining

NASA Astrophysics Data System (ADS)

Gupta, Deepak P.; Gopalakrishnan, Bhaskaran

2004-03-01

Database mining, widely known as knowledge discovery and data mining (KDD), has attracted lot of attention in recent years. With the rapid growth of databases in commercial, industrial, administrative and other applications, it is necessary and interesting to extract knowledge automatically from huge amount of data. Almost all the organizations are generating data and information at an unprecedented rate and they need to get some useful information from this data. Data mining is the extraction of non-trivial, previously unknown and potentially useful patterns, trends, dependence and correlation known as association rules among data values in large databases. In last ten to fifteen years, data mining spread out from one company to the other to help them understand more about customers' aspect of quality and response and also distinguish the customers they want from those they do not. A credit-card company found that customers who complete their applications in pencil rather than pen are more likely to default. There is a program that identifies callers by purchase history. The bigger the spender, the quicker the call will be answered. If you feel your call is being answered in the order in which it was received, think again. Many algorithms assume that data is static in nature and mine the rules and relations in that data. But for a dynamic database e.g. in most of the manufacturing industries, the rules and relations thus developed among the variables/items no longer hold true. A simple approach may be to mine the associations among the variables after every fixed period of time. But again, how much the length of this period should be, is a question to be answered. The next problem with the static data mining is that some of the relationships that might be of interest from one period to the other may be lost after a new set of data is used. To reflect the effect of new data set and current status of the association rules where some of the strong rules might become weak and vice versa, there is a need to develop an efficient algorithm to adapt to the current patterns and associations. Some work has been done in developing the association rules for incremental database but to the best of the author"s knowledge no work has been done to do the same for periodic cause and effect analysis for online association rules in manufacturing industries. The present research attempts to answer these questions and develop an algorithm that can display the association rules online, find the periodic patterns in the data and detect the root cause of the problem.

Double Mine Building, general view in setting; view northeast ...

Library of Congress Historic Buildings Survey, Historic Engineering Record, Historic Landscapes Survey

Double Mine Building, general view in setting; view northeast - Fort McKinley, Double Mine Building, East side of East Side Drive, approximately 125 feet south of Weymouth Way, Great Diamond Island, Portland, Cumberland County, ME

Data Mining Techniques Applied to Hydrogen Lactose Breath Test.

PubMed

Rubio-Escudero, Cristina; Valverde-Fernández, Justo; Nepomuceno-Chamorro, Isabel; Pontes-Balanza, Beatriz; Hernández-Mendoza, Yoedusvany; Rodríguez-Herrera, Alfonso

2017-01-01

Analyze a set of data of hydrogen breath tests by use of data mining tools. Identify new patterns of H2 production. Hydrogen breath tests data sets as well as k-means clustering as the data mining technique to a dataset of 2571 patients. Six different patterns have been extracted upon analysis of the hydrogen breath test data. We have also shown the relevance of each of the samples taken throughout the test. Analysis of the hydrogen breath test data sets using data mining techniques has identified new patterns of hydrogen generation upon lactose absorption. We can see the potential of application of data mining techniques to clinical data sets. These results offer promising data for future research on the relations between gut microbiota produced hydrogen and its link to clinical symptoms.

Boosting association rule mining in large datasets via Gibbs sampling.

PubMed

Qian, Guoqi; Rao, Calyampudi Radhakrishna; Sun, Xiaoying; Wu, Yuehua

2016-05-03

Current algorithms for association rule mining from transaction data are mostly deterministic and enumerative. They can be computationally intractable even for mining a dataset containing just a few hundred transaction items, if no action is taken to constrain the search space. In this paper, we develop a Gibbs-sampling-induced stochastic search procedure to randomly sample association rules from the itemset space, and perform rule mining from the reduced transaction dataset generated by the sample. Also a general rule importance measure is proposed to direct the stochastic search so that, as a result of the randomly generated association rules constituting an ergodic Markov chain, the overall most important rules in the itemset space can be uncovered from the reduced dataset with probability 1 in the limit. In the simulation study and a real genomic data example, we show how to boost association rule mining by an integrated use of the stochastic search and the Apriori algorithm.

Defining value through quantity and quality-Chimpanzees (Pan troglodytes) undervalue food quantities when items are broken.

PubMed

Parrish, Audrey E; Evans, Theodore A; Beran, Michael J

2015-02-01

Decision-making largely is influenced by the relative value of choice options, and the value of such options can be determined by a combination of different factors (e.g., the quantity, size, or quality of a stimulus). In this study, we examined the competing influences of quantity (i.e., the number of food items in a set) and quality (i.e., the original state of a food item) of choice items on chimpanzees' food preferences in a two-option natural choice paradigm. In Experiment 1, chimpanzees chose between sets of food items that were either entirely whole or included items that were broken into pieces before being shown to the chimpanzees. Chimpanzees exhibited a bias for whole food items even when such choice options consisted of a smaller overall quantity of food than the sets containing broken items. In Experiment 2, chimpanzees chose between sets of entirely whole food items and sets of initially whole items that were subsequently broken in view of the chimpanzees just before choice time. Chimpanzees continued to exhibit a bias for sets of whole items. In Experiment 3, chimpanzees chose between sets of new food items that were initially discrete but were subsequently transformed into a larger cohesive unit. Here, chimpanzees were biased to choose the discrete sets that retained their original qualitative state rather than toward the cohesive or clumped sets. These results demonstrate that beyond a food set's quantity (i.e., the value dimension that accounts for maximization in terms of caloric intake), other seemingly non-relevant features (i.e., quality in terms of a set's original state) affect how chimpanzees assign value to their choice options. Copyright © 2014 Elsevier B.V. All rights reserved.

Historical archaeology at the Clarkson Mine, an eastern Ohio mining complex

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

Keener, C.S.

2003-07-01

This study examines the Clarkson Mine (33BL333), an eastern Ohio coal mine complex dating to the 1910s to 1920s, situated along Wheeling Creek. The results of preliminary surveys and the subsequent mitigation of four structures at the site are presented. The historical archaeology conducted at the site demonstrates the significant research possibilities inherent at many of these early industrial mine complexes. Of particular interest is the findings of depositional patterning around residential structures that revealed the influence of architecture on where and how items were deposited on the land surface. The ceramic and faunal assemblage were analyzed and provide significantmore » details on socioeconomic attributes associated with the workers or staff. Artifacts recovered at the site provide an excellent diagnostic framework from which other similarly aged sites can be compared and dated. The findings at the Clarkson Mine are also placed into a more regional perspective and compared with other contemporary studies.« less

FlyMine: an integrated database for Drosophila and Anopheles genomics

PubMed Central

Lyne, Rachel; Smith, Richard; Rutherford, Kim; Wakeling, Matthew; Varley, Andrew; Guillier, Francois; Janssens, Hilde; Ji, Wenyan; Mclaren, Peter; North, Philip; Rana, Debashis; Riley, Tom; Sullivan, Julie; Watkins, Xavier; Woodbridge, Mark; Lilley, Kathryn; Russell, Steve; Ashburner, Michael; Mizuguchi, Kenji; Micklem, Gos

2007-01-01

FlyMine is a data warehouse that addresses one of the important challenges of modern biology: how to integrate and make use of the diversity and volume of current biological data. Its main focus is genomic and proteomics data for Drosophila and other insects. It provides web access to integrated data at a number of different levels, from simple browsing to construction of complex queries, which can be executed on either single items or lists. PMID:17615057

Set-fit effects in choice.

PubMed

Evers, Ellen R K; Inbar, Yoel; Zeelenberg, Marcel

2014-04-01

In 4 experiments, we investigate how the "fit" of an item with a set of similar items affects choice. We find that people have a notion of a set that "fits" together--one where all items are the same, or all items differ, on salient attributes. One consequence of this notion is that in addition to preferences over the set's individual items, choice reflects set-fit. This leads to predictable shifts in preferences, sometimes even resulting in people choosing normatively inferior options over superior ones.

78 FR 35974 - Proposed Information Collection; Comment Request; Coal Mine Rescue Teams; Arrangements for...

Federal Register 2010, 2011, 2012, 2013, 2014

2013-06-14

... Request; Coal Mine Rescue Teams; Arrangements for Emergency Medical Assistance and Transportation for... Part 49, Mine Rescue Teams, Subpart B--Mine Rescue Teams for Underground Coal Mines, sets standards related to the availability of mine rescue teams; alternate mine rescue capability for small and remote...

Method of locating related items in a geometric space for data mining

DOEpatents

Hendrickson, B.A.

1999-07-27

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity. 12 figs.

Method of locating related items in a geometric space for data mining

DOEpatents

Hendrickson, Bruce A.

1999-01-01

A method for locating related items in a geometric space transforms relationships among items to geometric locations. The method locates items in the geometric space so that the distance between items corresponds to the degree of relatedness. The method facilitates communication of the structure of the relationships among the items. The method is especially beneficial for communicating databases with many items, and with non-regular relationship patterns. Examples of such databases include databases containing items such as scientific papers or patents, related by citations or keywords. A computer system adapted for practice of the present invention can include a processor, a storage subsystem, a display device, and computer software to direct the location and display of the entities. The method comprises assigning numeric values as a measure of similarity between each pairing of items. A matrix is constructed, based on the numeric values. The eigenvectors and eigenvalues of the matrix are determined. Each item is located in the geometric space at coordinates determined from the eigenvectors and eigenvalues. Proper construction of the matrix and proper determination of coordinates from eigenvectors can ensure that distance between items in the geometric space is representative of the numeric value measure of the items' similarity.

What Kind of Memory Supports Visual Marking?

ERIC Educational Resources Information Center

Jiang, Yuhong; Wang, Stephanie W.

2004-01-01

In visual search tasks, if a set of items is presented for 1 s before another set of new items (containing the target) is added, search can be restricted to the new set. The process that eliminates old items from search is visual marking. This study investigates the kind of memory that distinguishes the old items from the new items during search.…

[Mokken scaling of the Cognitive Screening Test].

PubMed

Diesfeldt, H F A

2009-10-01

The Cognitive Screening Test (CST) is a twenty-item orientation questionnaire in Dutch, that is commonly used to evaluate cognitive impairment. This study applied Mokken Scale Analysis, a non-parametric set of techniques derived from item response theory (IRT), to CST-data of 466 consecutive participants in psychogeriatric day care. The full item set and the standard short version of fourteen items both met the assumptions of the monotone homogeneity model, with scalability coefficient H = 0.39, which is considered weak. In order to select items that would fulfil the assumption of invariant item ordering or the double monotonicity model, the subjects were randomly partitioned into a training set (50% of the sample) and a test set (the remaining half). By means of an automated item selection eleven items were found to measure one latent trait, with H = 0.67 and item H coefficients larger than 0.51. Cross-validation of the item analysis in the remaining half of the subjects gave comparable values (H = 0.66; item H coefficients larger than 0.56). The selected items involve year, place of residence, birth date, the monarch's and prime minister's names, and their predecessors. Applying optimal discriminant analysis (ODA) it was found that the full set of twenty CST items performed best in distinguishing two predefined groups of patients of lower or higher cognitive ability, as established by an independent criterion derived from the Amsterdam Dementia Screening Test. The chance corrected predictive value or prognostic utility was 47.5% for the full item set, 45.2% for the fourteen items of the standard short version of the CST, and 46.1% for the homogeneous, unidimensional set of selected eleven items. The results of the item analysis support the application of the CST in cognitive assessment, and revealed a more reliable 'short' version of the CST than the standard short version (CST14).

Healthcare information systems: data mining methods in the creation of a clinical recommender system

NASA Astrophysics Data System (ADS)

Duan, L.; Street, W. N.; Xu, E.

2011-05-01

Recommender systems have been extensively studied to present items, such as movies, music and books that are likely of interest to the user. Researchers have indicated that integrated medical information systems are becoming an essential part of the modern healthcare systems. Such systems have evolved to an integrated enterprise-wide system. In particular, such systems are considered as a type of enterprise information systems or ERP system addressing healthcare industry sector needs. As part of efforts, nursing care plan recommender systems can provide clinical decision support, nursing education, clinical quality control, and serve as a complement to existing practice guidelines. We propose to use correlations among nursing diagnoses, outcomes and interventions to create a recommender system for constructing nursing care plans. In the current study, we used nursing diagnosis data to develop the methodology. Our system utilises a prefix-tree structure common in itemset mining to construct a ranked list of suggested care plan items based on previously-entered items. Unlike common commercial systems, our system makes sequential recommendations based on user interaction, modifying a ranked list of suggested items at each step in care plan construction. We rank items based on traditional association-rule measures such as support and confidence, as well as a novel measure that anticipates which selections might improve the quality of future rankings. Since the multi-step nature of our recommendations presents problems for traditional evaluation measures, we also present a new evaluation method based on average ranking position and use it to test the effectiveness of different recommendation strategies.

Collaborative Data Mining

NASA Astrophysics Data System (ADS)

Moyle, Steve

Collaborative Data Mining is a setting where the Data Mining effort is distributed to multiple collaborating agents - human or software. The objective of the collaborative Data Mining effort is to produce solutions to the tackled Data Mining problem which are considered better by some metric, with respect to those solutions that would have been achieved by individual, non-collaborating agents. The solutions require evaluation, comparison, and approaches for combination. Collaboration requires communication, and implies some form of community. The human form of collaboration is a social task. Organizing communities in an effective manner is non-trivial and often requires well defined roles and processes. Data Mining, too, benefits from a standard process. This chapter explores the standard Data Mining process CRISP-DM utilized in a collaborative setting.

30 CFR 7.311 - Approval checklist.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINING PRODUCTS TESTING BY APPLICANT OR THIRD PARTY Electric Motor Assemblies § 7.311 Approval checklist. Each motor assembly bearing an MSHA approval marking shall be accompanied by a list of items necessary for maintenance of the motor assembly as approved. ...

Depression symptoms across cultures: an IRT analysis of standard depression symptoms using data from eight countries.

PubMed

Haroz, E E; Bolton, P; Gross, A; Chan, K S; Michalopoulos, L; Bass, J

2016-07-01

Prevalence estimates of depression vary between countries, possibly due to differential functioning of items between settings. This study compared the performance of the widely used Hopkins symptom checklist 15-item depression scale (HSCL-15) across multiple settings using item response theory analyses. Data came from adult populations in the low and middle income countries (LMIC) of Colombia, Indonesia, Kurdistan Iraq, Rwanda, Iraq, Thailand (Burmese refugees), and Uganda (N = 4732). Item parameters based on a graded response model were compared across LMIC settings. Differential item functioning (DIF) by setting was evaluated using multiple indicators multiple causes (MIMIC) models. Most items performed well across settings except items related to suicidal ideation and "loss of sexual interest or pleasure," which had low discrimination parameters (suicide: a = 0.31 in Thailand to a = 2.49 in Indonesia; sexual interest: a = 0.74 in Rwanda to a = 1.26 in one region of Kurdistan). Most items showed some degree of DIF, but DIF only impacted aggregate scale-level scores in Indonesia. Thirteen of the 15 HSCL depression items performed well across diverse settings, with most items showing a strong relationship to the underlying trait of depression. The results support the cross-cultural applicability of most of these depression symptoms across LMIC settings. DIF impacted aggregate depression scores in one setting illustrating a possible source of measurement invariance in prevalence estimates.

A Comparison of Three Types of Test Development Procedures Using Classical and Latent Trait Methods.

ERIC Educational Resources Information Center

Benson, Jeri; Wilson, Michael

Three methods of item selection were used to select sets of 38 items from a 50-item verbal analogies test and the resulting item sets were compared for internal consistency, standard errors of measurement, item difficulty, biserial item-test correlations, and relative efficiency. Three groups of 1,500 cases each were used for item selection. First…

Setting Priorities: A Handbook of Alternative Techniques.

ERIC Educational Resources Information Center

Price, Nelson C.

Six models for setting priorities are presented in a workbook format with exercises for evaluating or practicing five techniques. In the San Mateo model one sets priorities, clarifies priority purpose, lists items, determines criteria, lists items and criteria on a rating sheet, studies all information on items, rates each item, tallies results,…

Potential minability and economic viability of the Antaramut-Kurtan-Dzoragukh coal field, north-central Armenia; a prefeasibility study

USGS Publications Warehouse

Huber, Douglas W.; Pierce, Brenda S.

2000-01-01

The U. S. Geological Survey (USGS) conducted a coal resource assessment of several areas in Armenia from 1997 to 1999. This report, which presents a prefeasibility study of the economic and mining potential of one coal deposit found and studied by the USGS team, was prepared using all data available at the time of the study and the results of the USGS exploratory work, including core drilling, trenching, coal quality analyses, and other ongoing field work. On the basis of information currently available, it is the authors? opinion that a small surface coal mine having about a 20-year life span could be developed in the Antaramut-Kurtan-Dzoragukh coal field, specifically at the Dzoragukh site. The mining organization selected or created to establish the mine will need to conduct necessary development drilling and other work to establish the final feasibility study for the mine. The company will need to be entrepreneurial, profit oriented, and sensitive to the coal consumer; have an analytical management staff; and focus on employee training, safety, and protection of the environment. It is anticipated that any interested parties will be required to submit detailed mining plans to the appropriate Armenian Government agencies. Further development work will be required to reach a final decision regarding the economic feasibility of the mine. However, available information indicates that a small, economic surface mine can be developed at this locality. The small mine suggested is a typical surface-outcropstripping, contour mining operation. In addition, auger mining is strongly suggested, because the recovery of these low-cost mining reserves will help to ensure that the operation will be a viable, economic enterprise. (Auger mining is a system in which large-diameter boreholes are placed horizontally into the coal seam at the final highwall set as the economic limit for the surface mining operation). A special horizontal boring machine, which can be imported from Russia, is required for auger mining. Although auger-mining coal reserves do exist, the necessary development work will further verify the extent of these reserves and all of the other indicated reserves. The following items are based on the detailed study reported in this publication. Initial investment.?Following an investment of US $85,000 over a 12-month period in mine development drilling and other activities, a decision must be taken regarding further investment in an ongoing mining operation. If the new data support the opening of the surface mine, __________________________ 1Consultant, 6024 Morning Dew Drive, Austin, TX 78749. 2 U.S. Geological Survey, 956 National Center, Reston, VA 20192 1 2 MINABILITY AND ECONOMIC VIABILITY, ANTARAMUT-KURTAN-DZORAGUKH COAL FIELD the $85,000 development cost is amortized over the first 10 years of mine production. If the new data do not support the opening of the mine, the $85,000 is considered a business development expense that may be written off against profits from other operations for income or other tax purposes or simply as a business loss. Total capital required.?The equipment costs will reach a total of $900,500 which will be amortized over a 7-year period to establish estimated coal mining costs. Estimated working capital costs are $300,000, which will be borrowed. Surface mining reserves.?Approximately 840,200 metric tonnes of surface minable coal reserves at 9.3 m3 of overburden per metric tonne of minable coal is indicated. Recovery of the minable coal at 85 percent will yield 714,000 recoverable metric tonnes of marketable as-mined coal. Auger mining reserves.?Auger-mining reserves of 576,000 metric tonnes are indicated. Recoverable auger-mining reserves of 202,000 metric tonnes (at 35-percent recovery) can be expected. Auger-mining production will vary according to the hole size being used, but, in either case, augering is a very profitable addition to the mining oper

Combined mining: discovering informative knowledge in complex data.

PubMed

Cao, Longbing; Zhang, Huaifeng; Zhao, Yanchang; Luo, Dan; Zhang, Chengqi

2011-06-01

Enterprise data mining applications often involve complex data such as multiple large heterogeneous data sources, user preferences, and business impact. In such situations, a single method or one-step mining is often limited in discovering informative knowledge. It would also be very time and space consuming, if not impossible, to join relevant large data sources for mining patterns consisting of multiple aspects of information. It is crucial to develop effective approaches for mining patterns combining necessary information from multiple relevant business lines, catering for real business settings and decision-making actions rather than just providing a single line of patterns. The recent years have seen increasing efforts on mining more informative patterns, e.g., integrating frequent pattern mining with classifications to generate frequent pattern-based classifiers. Rather than presenting a specific algorithm, this paper builds on our existing works and proposes combined mining as a general approach to mining for informative patterns combining components from either multiple data sets or multiple features or by multiple methods on demand. We summarize general frameworks, paradigms, and basic processes for multifeature combined mining, multisource combined mining, and multimethod combined mining. Novel types of combined patterns, such as incremental cluster patterns, can result from such frameworks, which cannot be directly produced by the existing methods. A set of real-world case studies has been conducted to test the frameworks, with some of them briefed in this paper. They identify combined patterns for informing government debt prevention and improving government service objectives, which show the flexibility and instantiation capability of combined mining in discovering informative knowledge in complex data.

Final Report: Sampling-Based Algorithms for Estimating Structure in Big Data.

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

Matulef, Kevin Michael

The purpose of this project was to develop sampling-based algorithms to discover hidden struc- ture in massive data sets. Inferring structure in large data sets is an increasingly common task in many critical national security applications. These data sets come from myriad sources, such as network traffic, sensor data, and data generated by large-scale simulations. They are often so large that traditional data mining techniques are time consuming or even infeasible. To address this problem, we focus on a class of algorithms that do not compute an exact answer, but instead use sampling to compute an approximate answer using fewermore » resources. The particular class of algorithms that we focus on are streaming algorithms , so called because they are designed to handle high-throughput streams of data. Streaming algorithms have only a small amount of working storage - much less than the size of the full data stream - so they must necessarily use sampling to approximate the correct answer. We present two results: * A streaming algorithm called HyperHeadTail , that estimates the degree distribution of a graph (i.e., the distribution of the number of connections for each node in a network). The degree distribution is a fundamental graph property, but prior work on estimating the degree distribution in a streaming setting was impractical for many real-world application. We improve upon prior work by developing an algorithm that can handle streams with repeated edges, and graph structures that evolve over time. * An algorithm for the task of maintaining a weighted subsample of items in a stream, when the items must be sampled according to their weight, and the weights are dynamically changing. To our knowledge, this is the first such algorithm designed for dynamically evolving weights. We expect it may be useful as a building block for other streaming algorithms on dynamic data sets.« less

Customizing FP-growth algorithm to parallel mining with Charm++ library

NASA Astrophysics Data System (ADS)

Puścian, Marek

2017-08-01

This paper presents a frequent item mining algorithm that was customized to handle growing data repositories. The proposed solution applies Master Slave scheme to frequent pattern growth technique. Efficient utilization of available computation units is achieved by dynamic reallocation of tasks. Conditional frequent trees are assigned to parallel workers basing on their workload. Proposed enhancements have been successfully implemented using Charm++ library. This paper discusses results of the performance of parallelized FP-growth algorithm against different datasets. The approach has been illustrated with many experiments and measurements performed using multiprocessor and multithreaded computer.

Quantity judgments of sequentially presented food items by capuchin monkeys (Cebus apella).

PubMed

Evans, Theodore A; Beran, Michael J; Harris, Emily H; Rice, Daniel F

2009-01-01

Recent assessments have shown that capuchin monkeys, like chimpanzees and other Old World primate species, are sensitive to quantitative differences between sets of visible stimuli. In the present study, we examined capuchins' performance in a more sophisticated quantity judgment task that required the ability to form representations of food quantities while viewing the quantities only one piece at a time. In three experiments, we presented monkeys with the choice between two sets of discrete homogeneous food items and allowed the monkeys to consume the set of their choice. In Experiments 1 and 2, monkeys compared an entirely visible food set to a second set, presented item-by-item into an opaque container. All monkeys exhibited high accuracy in choosing the larger set, even when the entirely visible set was presented last, preventing the use of one-to-one item correspondence to compare quantities. In Experiment 3, monkeys compared two sets that were each presented item-by-item into opaque containers, but at different rates to control for temporal cues. Some monkeys performed well in this experiment, though others exhibited near-chance performance, suggesting that this species' ability to form representations of food quantities may be limited compared to previously tested species such as chimpanzees. Overall, these findings support the analog magnitude model of quantity representation as an explanation for capuchin monkeys' quantification of sequentially presented food items.

Open-source tools for data mining.

PubMed

Zupan, Blaz; Demsar, Janez

2008-03-01

With a growing volume of biomedical databases and repositories, the need to develop a set of tools to address their analysis and support knowledge discovery is becoming acute. The data mining community has developed a substantial set of techniques for computational treatment of these data. In this article, we discuss the evolution of open-source toolboxes that data mining researchers and enthusiasts have developed over the span of a few decades and review several currently available open-source data mining suites. The approaches we review are diverse in data mining methods and user interfaces and also demonstrate that the field and its tools are ready to be fully exploited in biomedical research.

Towards Cooperative Predictive Data Mining in Competitive Environments

NASA Astrophysics Data System (ADS)

Lisý, Viliam; Jakob, Michal; Benda, Petr; Urban, Štěpán; Pěchouček, Michal

We study the problem of predictive data mining in a competitive multi-agent setting, in which each agent is assumed to have some partial knowledge required for correctly classifying a set of unlabelled examples. The agents are self-interested and therefore need to reason about the trade-offs between increasing their classification accuracy by collaborating with other agents and disclosing their private classification knowledge to other agents through such collaboration. We analyze the problem and propose a set of components which can enable cooperation in this otherwise competitive task. These components include measures for quantifying private knowledge disclosure, data-mining models suitable for multi-agent predictive data mining, and a set of strategies by which agents can improve their classification accuracy through collaboration. The overall framework and its individual components are validated on a synthetic experimental domain.

Mines, prospects, and occurrences of metallic (excluding gold), pegmatite, and rare-earth mineral commodities in the Greenville 1 degree by 2 degrees Quadrangle, South Carolina, Georgia, and North Carolina

USGS Publications Warehouse

D'Agostino, John P.; Zupan, Alan Jon; Maybin, Arthur H.; Abrams, Charlotte E.; German, Jerry M.

1994-01-01

All of the known mines, prospects, and occurrences of metallic (excluding gold, pegmatite, and rare-earth mineral commodities for the Greenville 1° x 2° quadrangle are tabulated in this report. The table lists, in consecutive order for each county (fig. 1), the map number of each item, which correlates and locates the item on the accompanying Greenville 1° x 2° quadrangle map. The known name of the feature; the 7.5' topographic map on the which the commodity site is located; the Universal Transverse Mercator (UTM) northing and easting grid coordinates from the appropriate 7.5' topographic map; the commodity; remarks; and references are also listed. Some locations are known, but many sites are not verified and their locations are only approximate. References are listed in References Cited and referred to by number to save space.

Influence of occupational safety management on the incidence rate of occupational accidents in the Spanish industrial and ornamental stone mining.

PubMed

Sanmiquel, Lluís; Rossell, Josep M; Vintró, Carla; Freijo, Modesto

2014-01-01

Mines are hazardous and workers can suffer many types of accidents caused by fire, flood, explosion or collapse. Injury incidence rates in mining are considerably higher than those registered by other economic sectors. One of the main reasons for this high-level incidence rate is the existence of a large number of dangerous workplaces. This work analyzes the influence that occupational safety management had on the accidents that took place in Spanish mining of industrial and ornamental stone during the period 2007-2008. Primary data sources are: (a) Results from a statistical study of the occupational health and safety management practices of 71 quarries defined by a questionnaire of 41 items; and (b) Occupational accidents registered in the Spanish industrial and ornamental stone mining throughout the period 2007-2008. The obtained results indicate that workplaces with a low average score in the analysis of occupational safety management have a higher incidence rate of accidents. Studies on mining workplaces are very important to help detect occupational safety concerns. Results from this study help raise awareness and will encourage the adoption of appropriate measures to improve safety.

Prediction of adverse outcomes of acute coronary syndrome using intelligent fusion of triage information with HUMINT

NASA Astrophysics Data System (ADS)

McCullough, Claire L.; Novobilski, Andrew J.; Fesmire, Francis M.

2006-04-01

Faculty from the University of Tennessee at Chattanooga and the University of Tennessee College of Medicine, Chattanooga Unit, have used data mining techniques and neural networks to examine a set of fourteen features, data items, and HUMINT assessments for 2,148 emergency room patients with symptoms possibly indicative of Acute Coronary Syndrome. Specifically, the authors have generated Bayesian networks describing linkages and causality in the data, and have compared them with neural networks. The data includes objective information routinely collected during triage and the physician's initial case assessment, a HUMINT appraisal. Both the neural network and the Bayesian network were used to fuse the disparate types of information with the goal of forecasting thirty-day adverse patient outcome. This paper presents details of the methods of data fusion including both the data mining techniques and the neural network. Results are compared using Receiver Operating Characteristic curves describing the outcomes of both methods, both using only objective features and including the subjective physician's assessment. While preliminary, the results of this continuing study are significant both from the perspective of potential use of the intelligent fusion of biomedical informatics to aid the physician in prescribing treatment necessary to prevent serious adverse outcome from ACS and as a model of fusion of objective data with subjective HUMINT assessment. Possible future work includes extension of successfully demonstrated intelligent fusion methods to other medical applications, and use of decision level fusion to combine results from data mining and neural net approaches for even more accurate outcome prediction.

Installation Restoration Program. Phase II. Confirmation/Quantification. Stage 1 for Carswell AFB, Texas. Volume 3. Appendices B-L.

DTIC Science & Technology

1986-10-01

investigate the environ- mental feasibility of disposing of flue gas desulfurization (FGD) wastes, ash ’’p and sludge, from a mine mouth power plant by...Department of Defense o EMP - Electromagnetic Profiling o EPA - Environmental Protection Agency o GC - Gas Chromatography o GC-MS - Gas Chromatography-Mass...IN ITEM NO.) ADDITION 01 DELETION CODES: 0 -INTERMEDIATE CIRR: CONTROLLED ITEM RPT ROMT AFSC oRM 705 PREVOIJ EOTO’ , RE U C-4 4rsc-Aad.r IF ,,d 0,P E

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine

PubMed Central

Elsik, Christine G.; Tayal, Aditi; Diesh, Colin M.; Unni, Deepak R.; Emery, Marianne L.; Nguyen, Hung N.; Hagen, Darren E.

2016-01-01

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. PMID:26578564

Physics Mining of Multi-Source Data Sets

NASA Technical Reports Server (NTRS)

Helly, John; Karimabadi, Homa; Sipes, Tamara

2012-01-01

Powerful new parallel data mining algorithms can produce diagnostic and prognostic numerical models and analyses from observational data. These techniques yield higher-resolution measures than ever before of environmental parameters by fusing synoptic imagery and time-series measurements. These techniques are general and relevant to observational data, including raster, vector, and scalar, and can be applied in all Earth- and environmental science domains. Because they can be highly automated and are parallel, they scale to large spatial domains and are well suited to change and gap detection. This makes it possible to analyze spatial and temporal gaps in information, and facilitates within-mission replanning to optimize the allocation of observational resources. The basis of the innovation is the extension of a recently developed set of algorithms packaged into MineTool to multi-variate time-series data. MineTool is unique in that it automates the various steps of the data mining process, thus making it amenable to autonomous analysis of large data sets. Unlike techniques such as Artificial Neural Nets, which yield a blackbox solution, MineTool's outcome is always an analytical model in parametric form that expresses the output in terms of the input variables. This has the advantage that the derived equation can then be used to gain insight into the physical relevance and relative importance of the parameters and coefficients in the model. This is referred to as physics-mining of data. The capabilities of MineTool are extended to include both supervised and unsupervised algorithms, handle multi-type data sets, and parallelize it.

Numerical judgments by chimpanzees (Pan troglodytes) in a token economy.

PubMed

Beran, Michael J; Evans, Theodore A; Hoyle, Daniel

2011-04-01

We presented four chimpanzees with a series of tasks that involved comparing two token sets or comparing a token set to a quantity of food. Selected tokens could be exchanged for food items on a one-to-one basis. Chimpanzees successfully selected the larger numerical set for comparisons of 1 to 5 items when both sets were visible and when sets were presented through one-by-one addition of tokens into two opaque containers. Two of four chimpanzees used the number of tokens and food items to guide responding in all conditions, rather than relying on token color, size, total amount, or duration of set presentation. These results demonstrate that judgments of simultaneous and sequential sets of stimuli are made by some chimpanzees on the basis of the numerousness of sets rather than other non-numerical dimensions. The tokens were treated as equivalent to food items on the basis of their numerousness, and the chimpanzees maximized reward by choosing the larger number of items in all situations.

30 CFR 57.14100 - Safety defects; examination, correction and records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... NONMETAL MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 57.14100 Safety defects; examination, correction and records. (a) Self-propelled mobile equipment to be used during a... persons, the defective items including self-propelled mobile equipment shall be taken out of service and...

27 CFR 447.21 - The U.S. Munitions Import List.

Code of Federal Regulations, 2010 CFR

2010-04-01

...—launch vehicles, guided missiles, ballistic missiles, rockets, torpedoes, bombs and mines (a) Rockets (including but not limited to meteorological and other sounding rockets), bombs, grenades, torpedoes, depth..., the following: Fuses and components for the items in this category, bomb racks and shackles, bomb...

Which Statistic Should Be Used to Detect Item Preknowledge When the Set of Compromised Items Is Known?

PubMed

Sinharay, Sandip

2017-09-01

Benefiting from item preknowledge is a major type of fraudulent behavior during educational assessments. Belov suggested the posterior shift statistic for detection of item preknowledge and showed its performance to be better on average than that of seven other statistics for detection of item preknowledge for a known set of compromised items. Sinharay suggested a statistic based on the likelihood ratio test for detection of item preknowledge; the advantage of the statistic is that its null distribution is known. Results from simulated and real data and adaptive and nonadaptive tests are used to demonstrate that the Type I error rate and power of the statistic based on the likelihood ratio test are very similar to those of the posterior shift statistic. Thus, the statistic based on the likelihood ratio test appears promising in detecting item preknowledge when the set of compromised items is known.

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2010 CFR

2010-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2013 CFR

2013-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2012 CFR

2012-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2011 CFR

2011-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

30 CFR 75.1 - Scope.

Code of Federal Regulations, 2014 CFR

2014-07-01

... SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES General § 75.1 Scope. This part 75 sets forth safety standards compliance with which is mandatory in each underground coal mine subject to the Federal Mine Safety and Health Act...

Bear's bullish in tight market. [Colorado

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

Jackson, D.

Bear Coal Co. have re-opened an old mine near Somerset, Colorado, which will produce 300,000 tpy of coal. This is mined from the super section, consisting of two complete sets of production equipment. The mine alternates development and room-and-pillar mining. Coal is crushed and sized at the Terror Creek plant, along with coal from three other mines in the area.

Finite Optimal Stopping Problems: The Seller's Perspective

ERIC Educational Resources Information Center

Hemmati, Mehdi; Smith, J. Cole

2011-01-01

We consider a version of an optimal stopping problem, in which a customer is presented with a finite set of items, one by one. The customer is aware of the number of items in the finite set and the minimum and maximum possible value of each item, and must purchase exactly one item. When an item is presented to the customer, she or he observes its…

Omnidirectional Learning - A New Paradigm for Learning to Predict Any Set of Variables from Any Other Set

DTIC Science & Technology

2016-05-06

ABSTRACT Awards: Best Paper Honorable Mention Award at the SIAM (Society for Industrial and Applied Mathematics Conference on Data Mining (SDM...magnitude in computation time over the state of the art. 15. SUBJECT TERMS Data Mining 16. SECURITY CLASSIFICATION OF: 17...International Conference on Data Mining and received Best Paper Honorable mention. To ensure broad use and uptake of the outcomes of this research

Proceedings of the Seventh International Conference on Educational Data Mining (EDM) (7th, London, United Kingdom, July 4-7, 2014)

ERIC Educational Resources Information Center

Stamper, John, Ed.; Pardos, Zachary, Ed.; Mavrikis, Manolis, Ed.; McLaren, Bruce M., Ed.

2014-01-01

The 7th International Conference on Education Data Mining held on July 4th-7th, 2014, at the Institute of Education, London, UK is the leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning process. These data sets may come from the traces…

30 CFR 56.14100 - Safety defects; examination, correction and records.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINES Machinery and Equipment Safety Devices and Maintenance Requirements § 56.14100 Safety defects; examination, correction and records. (a) Self-propelled mobile equipment to be used during a shift shall be... defective items including self-propelled mobile equipment shall be taken out of service and placed in a...

Combining the Best of Two Standard Setting Methods: The Ordered Item Booklet Angoff

ERIC Educational Resources Information Center

Smith, Russell W.; Davis-Becker, Susan L.; O'Leary, Lisa S.

2014-01-01

This article describes a hybrid standard setting method that combines characteristics of the Angoff (1971) and Bookmark (Mitzel, Lewis, Patz & Green, 2001) methods. The proposed approach utilizes strengths of each method while addressing weaknesses. An ordered item booklet, with items sorted based on item difficulty, is used in combination…

Comparison of mine waste assessment methods at the Rattler mine site, Virginia Canyon, Colorado

USGS Publications Warehouse

Hageman, Phil L.; Smith, Kathleen S.; Wildeman, Thomas R.; Ranville, James F.

2005-01-01

In a joint project, the mine waste-piles at the Rattler Mine near Idaho Springs, Colorado, were sampled and analyzed by scientists from the U.S. Geological Survey (USGS) and the Colorado School of Mines (CSM). Separate sample collection, sample leaching, and leachate analyses were performed by both groups and the results were compared. For the study, both groups used the USGS sampling procedure and the USGS Field Leach Test (FLT). The leachates generated from these tests were analyzed for a suite of elements using ICP-AES (CSM) and ICP-MS (USGS). Leachate geochemical fingerprints produced by the two groups for composites collected from the same mine waste showed good agreement. In another set of tests, CSM collected another set of Rattler mine waste composite samples using the USGS sampling procedure. This set of composite samples was leached using the Colorado Division of Minerals and Geology (CDMG) leach test, and a modified Toxicity Characteristic Leaching Procedure (TCLP) leach test. Leachate geochemical fingerprints produced using these tests showed a variation of more than a factor of two from the geochemical fingerprints produced using the USGS FLT leach test. We have concluded that the variation in the results is due to the different parameters of the leaching tests and not due to the sampling or analytical methods.

Application of the MERIT survey in the multi-criteria quality assessment of occupational health and safety management.

PubMed

Korban, Zygmunt

2015-01-01

Occupational health and safety management systems apply audit examinations as an integral element of these systems. The examinations are used to verify whether the undertaken actions are in compliance with the accepted regulations, whether they are implemented in a suitable way and whether they are effective. One of the earliest solutions of that type applied in the mining industry in Poland involved the application of audit research based on the MERIT survey (Management Evaluation Regarding Itemized Tendencies). A mathematical model applied in the survey facilitates the determination of assessment indexes WOPi for each of the assessed problem areas, which, among other things, can be used to set up problem area rankings and to determine an aggregate (synthetic) assessment. In the paper presented here, the assessment indexes WOPi were used to calculate a development measure, and the calculation process itself was supplemented with sensitivity analysis.

A Comparison of the One-and Three-Parameter Logistic Models on Measures of Test Efficiency.

ERIC Educational Resources Information Center

Benson, Jeri

Two methods of item selection were used to select sets of 40 items from a 50-item verbal analogies test, and the resulting item sets were compared for relative efficiency. The BICAL program was used to select the 40 items having the best mean square fit to the one parameter logistic (Rasch) model. The LOGIST program was used to select the 40 items…

Three nested randomized controlled trials of peer-only or multiple stakeholder group feedback within Delphi surveys during core outcome and information set development.

PubMed

Brookes, Sara T; Macefield, Rhiannon C; Williamson, Paula R; McNair, Angus G; Potter, Shelley; Blencowe, Natalie S; Strong, Sean; Blazeby, Jane M

2016-08-17

Methods for developing a core outcome or information set require involvement of key stakeholders to prioritise many items and achieve agreement as to the core set. The Delphi technique requires participants to rate the importance of items in sequential questionnaires (or rounds) with feedback provided in each subsequent round such that participants are able to consider the views of others. This study examines the impact of receiving feedback from different stakeholder groups, on the subsequent rating of items and the level of agreement between stakeholders. Randomized controlled trials were nested within the development of three core sets each including a Delphi process with two rounds of questionnaires, completed by patients and health professionals. Participants rated items from 1 (not essential) to 9 (absolutely essential). For round 2, participants were randomized to receive feedback from their peer stakeholder group only (peer) or both stakeholder groups separately (multiple). Decisions as to which items to retain following each round were determined by pre-specified criteria. Whilst type of feedback did not impact on the percentage of items for which a participant subsequently changed their rating, or the magnitude of change, it did impact on items retained at the end of round 2. Each core set contained discordant items retained by one feedback group but not the other (3-22 % discordant items). Consensus between patients and professionals in items to retain was greater amongst those receiving multiple group feedback in each core set (65-82 % agreement for peer-only feedback versus 74-94 % for multiple feedback). In addition, differences in round 2 scores were smaller between stakeholder groups receiving multiple feedback than between those receiving peer group feedback only. Variability in item scores across stakeholders was reduced following any feedback but this reduction was consistently greater amongst the multiple feedback group. In the development of a core outcome or information set, providing feedback within Delphi questionnaires from all stakeholder groups separately may influence the final core set and improve consensus between the groups. Further work is needed to better understand how participants rate and re-rate items within a Delphi process. The three randomized controlled trials reported here were each nested within the development of a core information or outcome set to investigate processes in core outcome and information set development. Outcomes were not health-related and therefore trial registration was not applicable.

Converging evidence for control of color-word Stroop interference at the item level.

PubMed

Bugg, Julie M; Hutchison, Keith A

2013-04-01

Prior studies have shown that cognitive control is implemented at the list and context levels in the color-word Stroop task. At first blush, the finding that Stroop interference is reduced for mostly incongruent items as compared with mostly congruent items (i.e., the item-specific proportion congruence [ISPC] effect) appears to provide evidence for yet a third level of control, which modulates word reading at the item level. However, evidence to date favors the view that ISPC effects reflect the rapid prediction of high-contingency responses and not item-specific control. In Experiment 1, we first show that an ISPC effect is obtained when the relevant dimension (i.e., color) signals proportion congruency, a problematic pattern for theories based on differential response contingencies. In Experiment 2, we replicate and extend this pattern by showing that item-specific control settings transfer to new stimuli, ruling out alternative frequency-based accounts. In Experiment 3, we revert to the traditional design in which the irrelevant dimension (i.e., word) signals proportion congruency. Evidence for item-specific control, including transfer of the ISPC effect to new stimuli, is apparent when 4-item sets are employed but not when 2-item sets are employed. We attribute this pattern to the absence of high-contingency responses on incongruent trials in the 4-item set. These novel findings provide converging evidence for reactive control of color-word Stroop interference at the item level, reveal theoretically important factors that modulate reliance on item-specific control versus contingency learning, and suggest an update to the item-specific control account (Bugg, Jacoby, & Chanani, 2011).

The role of object categories in hybrid visual and memory search

PubMed Central

Cunningham, Corbin A.; Wolfe, Jeremy M.

2014-01-01

In hybrid search, observers (Os) search for any of several possible targets in a visual display containing distracting items and, perhaps, a target. Wolfe (2012) found that responses times (RT) in such tasks increased linearly with increases in the number of items in the display. However, RT increased linearly with the log of the number of items in the memory set. In earlier work, all items in the memory set were unique instances (e.g. this apple in this pose). Typical real world tasks involve more broadly defined sets of stimuli (e.g. any “apple” or, perhaps, “fruit”). The present experiments show how sets or categories of targets are handled in joint visual and memory search. In Experiment 1, searching for a digit among letters was not like searching for targets from a 10-item memory set, though searching for targets from an N-item memory set of arbitrary alphanumeric characters was like searching for targets from an N-item memory set of arbitrary objects. In Experiment 2, Os searched for any instance of N sets or categories held in memory. This hybrid search was harder than search for specific objects. However, memory search remained logarithmic. Experiment 3 illustrates the interaction of visual guidance and memory search when a subset of visual stimuli are drawn from a target category. Furthermore, we outline a conceptual model, supported by our results, defining the core components that would be necessary to support such categorical hybrid searches. PMID:24661054

Mining subspace clusters from DNA microarray data using large itemset techniques.

PubMed

Chang, Ye-In; Chen, Jiun-Rung; Tsai, Yueh-Chi

2009-05-01

Mining subspace clusters from the DNA microarrays could help researchers identify those genes which commonly contribute to a disease, where a subspace cluster indicates a subset of genes whose expression levels are similar under a subset of conditions. Since in a DNA microarray, the number of genes is far larger than the number of conditions, those previous proposed algorithms which compute the maximum dimension sets (MDSs) for any two genes will take a long time to mine subspace clusters. In this article, we propose the Large Itemset-Based Clustering (LISC) algorithm for mining subspace clusters. Instead of constructing MDSs for any two genes, we construct only MDSs for any two conditions. Then, we transform the task of finding the maximal possible gene sets into the problem of mining large itemsets from the condition-pair MDSs. Since we are only interested in those subspace clusters with gene sets as large as possible, it is desirable to pay attention to those gene sets which have reasonable large support values in the condition-pair MDSs. From our simulation results, we show that the proposed algorithm needs shorter processing time than those previous proposed algorithms which need to construct gene-pair MDSs.

Variation in passing standards for graduation-level knowledge items at UK medical schools.

PubMed

Taylor, Celia A; Gurnell, Mark; Melville, Colin R; Kluth, David C; Johnson, Neil; Wass, Val

2017-06-01

Given the absence of a common passing standard for students at UK medical schools, this paper compares independently set standards for common 'one from five' single-best-answer (multiple-choice) items used in graduation-level applied knowledge examinations and explores potential reasons for any differences. A repeated cross-sectional study was conducted. Participating schools were sent a common set of graduation-level items (55 in 2013-2014; 60 in 2014-2015). Items were selected against a blueprint and subjected to a quality review process. Each school employed its own standard-setting process for the common items. The primary outcome was the passing standard for the common items by each medical school set using the Angoff or Ebel methods. Of 31 invited medical schools, 22 participated in 2013-2014 (71%) and 30 (97%) in 2014-2015. Schools used a mean of 49 and 53 common items in 2013-2014 and 2014-2015, respectively, representing around one-third of the items in the examinations in which they were embedded. Data from 19 (61%) and 26 (84%) schools, respectively, met the inclusion criteria for comparison of standards. There were statistically significant differences in the passing standards set by schools in both years (effect sizes (f 2 ): 0.041 in 2013-2014 and 0.218 in 2014-2015; both p < 0.001). The interquartile range of standards was 5.7 percentage points in 2013-2014 and 6.5 percentage points in 2014-2015. There was a positive correlation between the relative standards set by schools in the 2 years (Pearson's r = 0.57, n = 18, p = 0.014). Time allowed per item, method of standard setting and timing of examination in the curriculum did not have a statistically significant impact on standards. Independently set standards for common single-best-answer items used in graduation-level examinations vary across UK medical schools. Further work to examine standard-setting processes in more detail is needed to help explain this variability and develop methods to reduce it. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Ultrawideband radar echoes of land mine targets measured at oblique incidence using a 250-kW impulse radar system

NASA Astrophysics Data System (ADS)

Chant, Ian J.; Staines, Geoff

1997-07-01

United Nations Peacekeeping forces around the world need to transport food, personnel and medical supplies through disputed regions were land mines are in active use as road blocks and terror weapons. A method of fast, effective land mine detection is needed to combat this threat to road transport. The technique must operate from a vehicle travelling at a reasonable velocity and give warning far enough ahead for the vehicle to stop in time to avoid the land mine. There is particular interest in detecting low- metallic content land mines. One possible solutionis the use of ultra-wide-band (UWB) radar. The Australian Defence Department is investigating the feasibility of using UWB radar for land mine detection from a vehicle. A 3 GHz UWB system has been used to collect target response from a series of inert land mines and mine-like objects placed on the ground and buried in the ground. The targets measured were a subset of those in the target set described in Wong et al. with the addition of inert land mines corresponding to some of the surrogate targets in this set. The results are encouraging for the detection of metallic land mines and the larger non-metallic land mines. Smaller low-metallic- content anti-personnel land mines are less likely to be detected.

Black Thunder reaches new highs

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

Fiscor, S.

After successfully merging North Rochelle mine with Black Thunder mine, Arch Coal set its sights on reopening Coal Creek. Coal Creek mine was idled in 2000. An annual production of 15 million tons is targeted. The article describes operations at Black Thunder opencast mine and talks about the integration of North Rochelle. 2 figs., 2 photos.

30 CFR 57.22213 - Air flow (III mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Air flow (III mines). 57.22213 Section 57.22213... Methane in Metal and Nonmetal Mines Ventilation § 57.22213 Air flow (III mines). The quantity of air coursed through the last open crosscut in pairs or sets of entries, or through other ventilation openings...

A Model-Based Analysis of Semi-Automated Data Discovery and Entry Using Automated Content Extraction

DTIC Science & Technology

2011-02-01

Accomplish Goal) to (a) visually search the contents of a file folder until the icon corresponding to the desired file is located (Choose...Item_from_set), and (b) move the mouse to that icon and double click to open it (Double_select Object). Note that Choose Item_from_set and Double_select...argument, which Open File fills with <found_item>, a working memory pointer to the file icon that Choose_item_from Set finds. Look_at, Point_to

Item Response Data Analysis Using Stata Item Response Theory Package

ERIC Educational Resources Information Center

Yang, Ji Seung; Zheng, Xiaying

2018-01-01

The purpose of this article is to introduce and review the capability and performance of the Stata item response theory (IRT) package that is available from Stata v.14, 2015. Using a simulated data set and a publicly available item response data set extracted from Programme of International Student Assessment, we review the IRT package from…

A Proposed Data Fusion Architecture for Micro-Zone Analysis and Data Mining

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

Kevin McCarthy; Milos Manic

Data Fusion requires the ability to combine or “fuse” date from multiple data sources. Time Series Analysis is a data mining technique used to predict future values from a data set based upon past values. Unlike other data mining techniques, however, Time Series places special emphasis on periodicity and how seasonal and other time-based factors tend to affect trends over time. One of the difficulties encountered in developing generic time series techniques is the wide variability of the data sets available for analysis. This presents challenges all the way from the data gathering stage to results presentation. This paper presentsmore » an architecture designed and used to facilitate the collection of disparate data sets well suited to Time Series analysis as well as other predictive data mining techniques. Results show this architecture provides a flexible, dynamic framework for the capture and storage of a myriad of dissimilar data sets and can serve as a foundation from which to build a complete data fusion architecture.« less

Hymenoptera Genome Database: integrating genome annotations in HymenopteraMine.

PubMed

Elsik, Christine G; Tayal, Aditi; Diesh, Colin M; Unni, Deepak R; Emery, Marianne L; Nguyen, Hung N; Hagen, Darren E

2016-01-04

We report an update of the Hymenoptera Genome Database (HGD) (http://HymenopteraGenome.org), a model organism database for insect species of the order Hymenoptera (ants, bees and wasps). HGD maintains genomic data for 9 bee species, 10 ant species and 1 wasp, including the versions of genome and annotation data sets published by the genome sequencing consortiums and those provided by NCBI. A new data-mining warehouse, HymenopteraMine, based on the InterMine data warehousing system, integrates the genome data with data from external sources and facilitates cross-species analyses based on orthology. New genome browsers and annotation tools based on JBrowse/WebApollo provide easy genome navigation, and viewing of high throughput sequence data sets and can be used for collaborative genome annotation. All of the genomes and annotation data sets are combined into a single BLAST server that allows users to select and combine sequence data sets to search. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

Introduction to the mining of clinical data.

PubMed

Harrison, James H

2008-03-01

The increasing volume of medical data online, including laboratory data, represents a substantial resource that can provide a foundation for improved understanding of disease presentation, response to therapy, and health care delivery processes. Data mining supports these goals by providing a set of techniques designed to discover similarities and relationships between data elements in large data sets. Currently, medical data have several characteristics that increase the difficulty of applying these techniques, although there have been notable medical data mining successes. Future developments in integrated medical data repositories, standardized data representation, and guidelines for the appropriate research use of medical data will decrease the barriers to mining projects.

Charcoal from a prehistoric copper mine in the Austrian Alps: dendrochronological and dendrological data, demand for wood and forest utilisation.

PubMed

Pichler, Thomas; Nicolussi, Kurt; Goldenberg, Gert; Hanke, Klaus; Kovács, Kristóf; Thurner, Andrea

2013-02-01

During prehistory fire-setting was the most appropriate technique for exploiting ore deposits. Charcoal fragments found in the course of archaeological excavations in a small mine called Mauk E in the area of Schwaz/Brixlegg (Tyrol, Austria) are argued to be evidence for the use of this technology. Dendrochronological analyses of the charcoal samples yielded calendar dates for the mining activities showing that the exploitation of the Mauk E mine lasted approximately one decade in the late 8th century BC. Dendrological studies show that the miners utilised stem wood of spruce and fir from forests with high stand density for fire-setting and that the exploitation of the Mauk E mine had only a limited impact on the local forests.

The Evaluation of Land Ecological Safety of Chengchao Iron Mine Based on PSR and MEM

NASA Astrophysics Data System (ADS)

Jin, Xiangdong; Chen, Yong

2018-01-01

Land ecological security is of vital importance to local security and sustainable development of mining activities. The study has analyzed the potential causal chains between the land ecological security of Iron Mine mining environment, mine resource and the social-economic background. On the base of Pressure-State-Response model, the paper set up a matter element evaluation model of land ecological security, and applies it in Chengchao iron mine. The evaluation result proves to be effective in land ecological evaluation.

30 CFR 57.22004 - Category placement or change in placement.

Code of Federal Regulations, 2010 CFR

2010-07-01

... MINES Safety Standards for Methane in Metal and Nonmetal Mines Mine Categorization § 57.22004 Category... conditions set forth in § 57.22003(b) indicate that the hazards of methane exist under circumstances more... events occur: (1) An outburst that results in 0.25 percent or more methane in the mine atmosphere; (2) A...

30 CFR 57.22211 - Air flow (I-A mines).

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Air flow (I-A mines). 57.22211 Section 57.22211... Methane in Metal and Nonmetal Mines Ventilation § 57.22211 Air flow (I-A mines). The average air velocity in the last open crosscut in pairs or sets of developing entries, or through other ventilation...

30 CFR 57.22004 - Category placement or change in placement.

Code of Federal Regulations, 2011 CFR

2011-07-01

... MINES Safety Standards for Methane in Metal and Nonmetal Mines Mine Categorization § 57.22004 Category... conditions set forth in § 57.22003(b) indicate that the hazards of methane exist under circumstances more... events occur: (1) An outburst that results in 0.25 percent or more methane in the mine atmosphere; (2) A...

A Comparison of Methods of Vertical Equating.

ERIC Educational Resources Information Center

Loyd, Brenda H.; Hoover, H. D.

Rasch model vertical equating procedures were applied to three mathematics computation tests for grades six, seven, and eight. Each level of the test was composed of 45 items in three sets of 15 items, arranged in such a way that tests for adjacent grades had two sets (30 items) in common, and the sixth and eighth grades had 15 items in common. In…

30 CFR 50.20-7 - Criteria-MSHA Form 7000-1, Section D.

Code of Federal Regulations, 2010 CFR

2010-07-01

... Section 50.20-7 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR ACCIDENTS... regular job as a direct result of the occupational injury or occupational illness. (b) Item 29. Show the date that the injured person returned to his regular job at full capacity (not to restricted work...

76 FR 60048 - Federal Acquisition Regulation; Submission for OMB Review; Trade Agreements Certificate

Federal Register 2010, 2011, 2012, 2013, 2014

2011-09-28

... submitting to the Office of Management and Budget (OMB) a request to review and approve an extension of a... posted without change to http://www.regulations.gov , including any personal and/or business confidential... products. Items having components of unknown origin are considered to have been mined, produced, or...

29 CFR 570.118 - Sixteen-year minimum.

Code of Federal Regulations, 2010 CFR

2010-07-01

... for employment in manufacturing or mining occupations. Furthermore, this age minimum is applicable to... convenience of the user, the revised text is set forth as follows: § 570.118 Sixteen-year minimum. The Act sets a 16-year-age minimum for employment in manufacturing or mining occupations, although under FLSA...

Capuchin monkeys (Cebus apella) treat small and large numbers of items similarly during a relative quantity judgment task.

PubMed

Beran, Michael J; Parrish, Audrey E

2016-08-01

A key issue in understanding the evolutionary and developmental emergence of numerical cognition is to learn what mechanism(s) support perception and representation of quantitative information. Two such systems have been proposed, one for dealing with approximate representation of sets of items across an extended numerical range and another for highly precise representation of only small numbers of items. Evidence for the first system is abundant across species and in many tests with human adults and children, whereas the second system is primarily evident in research with children and in some tests with non-human animals. A recent paper (Choo & Franconeri, Psychonomic Bulletin & Review, 21, 93-99, 2014) with adult humans also reported "superprecise" representation of small sets of items in comparison to large sets of items, which would provide more support for the presence of a second system in human adults. We first presented capuchin monkeys with a test similar to that of Choo and Franconeri in which small or large sets with the same ratios had to be discriminated. We then presented the same monkeys with an expanded range of comparisons in the small number range (all comparisons of 1-9 items) and the large number range (all comparisons of 10-90 items in 10-item increments). Capuchin monkeys showed no increased precision for small over large sets in making these discriminations in either experiment. These data indicate a difference in the performance of monkeys to that of adult humans, and specifically that monkeys do not show improved discrimination performance for small sets relative to large sets when the relative numerical differences are held constant.

Market Basket Analysis: a new tool in ecology to describe chemical relations in the environment--a case study of the fern Athyrium distentifolium in the Tatra National Park in Poland.

PubMed

Samecka-Cymerman, Aleksandra; Stankiewicz, Andrzej; Kolon, Krzysztof; Kempers, Alexander J; Leuven, Rob S E W

2010-09-01

In this study, the novel data mining technique Market Basket Analysis (MBA) was applied for the first time in biogeochemical and ecological investigations. The method was tested on the fern Athyrium distentifolium, in which we measured concentrations of the elements Ca, Cd, Cr, Cu, Fe, K, Mg, Mn, Na, Ni, Pb, and Zn. Plants were sampled from sites with different types of bedrock in the Tatra National Park in Poland. MBA was used to investigate whether specimens of Athyrium distentifolium that contain elevated levels of certain elements occur more frequently on a specific type of bedrock and to identify relationships between the type of bedrock and the concentrations of the elements in this fern. The results were compared with those of the commonly used principal component and classification analysis (PCCA) technique. MBA and PCCA ordination both yielded distinct groups of ferns growing on different types of bedrock. Although the results of MBA and PCCA were similar, MBA has the advantage of being independent of the size of the data set. In addition, MBA revealed not only dominant elements but, in the case of limestone bedrock, also showed very low concentrations of Cd, Fe, Mn, and Pb in ferns growing on this type of parent material. MBA, thus, appeared to be a promising data mining method to reveal chemical relations in the environment as well as the accumulation of chemical elements in bioindicators. This technique can be used to reveal associations and correlations among items in large data sets collected on a national or even larger scale.

Bi-dimensional acculturation and cultural response set in CES-D among Korean immigrants

PubMed Central

Kim, Eunjung; Seo, Kumin; Cain, Kevin C.

2017-01-01

This study examined a cultural response set to positive affect items and depressive symptom items in CES-D among 172 Korean immigrants. Bi-dimensional acculturation approach, which considers maintenance of Korean Orientation and adoption of American Orientation, was utilized. As Korean immigrants increased American Orientation, they tended to score higher on positive affect items, while no changes occurred in depressive symptom items. Korean Orientation was not related to either positive affect items or depressive symptom items. Korean immigrants have response bias toward positive affect items in CES-D, which decreases as they adopt more American Orientation. CES-D lacks cultural equivalence for Korean immigrants. PMID:20701420

Map showing locations of mines, prospects, and patented mining claims, and classification of mineral deposits in the Silver City 7 1/2-minute Quadrangle, Black Hills, South Dakota

USGS Publications Warehouse

DeWitt, Ed; Buscher, David; Wilson, A.B.; Johnson, Thomas

1988-01-01

This map is one in a set of 26 maps (see index map) at 1:24,000 scale of the Black Hills region of South Dakota and Wyoming om which are shown a geologic classification of mines, a bibliography of mineral deposits, and locations of active and inactive mines, prospects, and patented mining claims. Some of these maps are published as U. S. Geological Survey Miscellaneous Field Studies Maps (MF series) and some as U.S. Geological Survey Open-File Reports (QF series); see index map. An earlier unpublished version of this set of maps was the data base from which plate 4 (scale 1:250,000) of DeWitt and others (1986) was compiled. Subsequent to that publication, the set has been revised and updated, and prospects and patented claims have been added. These revised and more detailed 1:24,000-scale maps should be used for the equivalent areas of plate 4 of DeWitt and others (1986).

Mining large heterogeneous data sets in drug discovery.

PubMed

Wild, David J

2009-10-01

Increasingly, effective drug discovery involves the searching and data mining of large volumes of information from many sources covering the domains of chemistry, biology and pharmacology amongst others. This has led to a proliferation of databases and data sources relevant to drug discovery. This paper provides a review of the publicly-available large-scale databases relevant to drug discovery, describes the kinds of data mining approaches that can be applied to them and discusses recent work in integrative data mining that looks for associations that pan multiple sources, including the use of Semantic Web techniques. The future of mining large data sets for drug discovery requires intelligent, semantic aggregation of information from all of the data sources described in this review, along with the application of advanced methods such as intelligent agents and inference engines in client applications.

The Impact of Test Dimensionality, Common-Item Set Format, and Scale Linking Methods on Mixed-Format Test Equating

ERIC Educational Resources Information Center

Öztürk-Gübes, Nese; Kelecioglu, Hülya

2016-01-01

The purpose of this study was to examine the impact of dimensionality, common-item set format, and different scale linking methods on preserving equity property with mixed-format test equating. Item response theory (IRT) true-score equating (TSE) and IRT observed-score equating (OSE) methods were used under common-item nonequivalent groups design.…

Approximation Algorithms for the Highway Problem under the Coupon Model

NASA Astrophysics Data System (ADS)

Hamane, Ryoso; Itoh, Toshiya; Tomita, Kouhei

When a store sells items to customers, the store wishes to decide the prices of items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy the items, and also assume that each item i ∈ V has the production cost di and each customer ej ∈ E has the valuation vj on the bundle ej ⊆ V of items. When the store sells an item i ∈ V at the price ri, the profit for the item i is pi = ri - di. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that pi ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of “loss-leader, ” and showed that the seller can get more total profit in the case that pi < 0 is allowed than in the case that pi < 0 is not allowed. In this paper, we consider the line highway problem (in which each customer is interested in an interval on the line of the items) and the cycle highway problem (in which each customer is interested in an interval on the cycle of the items), and show approximation algorithms for the line highway problem and the cycle highway problem in which the smallest valuation is s and the largest valuation is l (this is called an [s, l]-valuation setting) or all valuations are identical (this is called a single valuation setting).

Development and validation of a socioculturally competent trust in physician scale for a developing country setting.

PubMed

Gopichandran, Vijayaprasad; Wouters, Edwin; Chetlapalli, Satish Kumar

2015-05-03

Trust in physicians is the unwritten covenant between the patient and the physician that the physician will do what is in the best interest of the patient. This forms the undercurrent of all healthcare relationships. Several scales exist for assessment of trust in physicians in developed healthcare settings, but to our knowledge none of these have been developed in a developing country context. To develop and validate a new trust in physician scale for a developing country setting. Dimensions of trust in physicians, which were identified in a previous qualitative study in the same setting, were used to develop a scale. This scale was administered among 616 adults selected from urban and rural areas of Tamil Nadu, south India, using a multistage sampling cross sectional survey method. The individual items were analysed using a classical test approach as well as item response theory. Cronbach's α was calculated and the item to total correlation of each item was assessed. After testing for unidimensionality and absence of local dependence, a 2 parameter logistic Semajima's graded response model was fit and item characteristics assessed. Competence, assurance of treatment, respect for the physician and loyalty to the physician were important dimensions of trust. A total of 31 items were developed using these dimensions. Of these, 22 were selected for final analysis. The Cronbach's α was 0.928. The item to total correlations were acceptable for all the 22 items. The item response analysis revealed good item characteristic curves and item information for all the items. Based on the item parameters and item information, a final 12 item scale was developed. The scale performs optimally in the low to moderate trust range. The final 12 item trust in physician scale has a good construct validity and internal consistency. 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.

Development and validation of a socioculturally competent trust in physician scale for a developing country setting

PubMed Central

Gopichandran, Vijayaprasad; Wouters, Edwin; Chetlapalli, Satish Kumar

2015-01-01

Trust in physicians is the unwritten covenant between the patient and the physician that the physician will do what is in the best interest of the patient. This forms the undercurrent of all healthcare relationships. Several scales exist for assessment of trust in physicians in developed healthcare settings, but to our knowledge none of these have been developed in a developing country context. Objectives To develop and validate a new trust in physician scale for a developing country setting. Methods Dimensions of trust in physicians, which were identified in a previous qualitative study in the same setting, were used to develop a scale. This scale was administered among 616 adults selected from urban and rural areas of Tamil Nadu, south India, using a multistage sampling cross sectional survey method. The individual items were analysed using a classical test approach as well as item response theory. Cronbach's α was calculated and the item to total correlation of each item was assessed. After testing for unidimensionality and absence of local dependence, a 2 parameter logistic Semajima's graded response model was fit and item characteristics assessed. Results Competence, assurance of treatment, respect for the physician and loyalty to the physician were important dimensions of trust. A total of 31 items were developed using these dimensions. Of these, 22 were selected for final analysis. The Cronbach's α was 0.928. The item to total correlations were acceptable for all the 22 items. The item response analysis revealed good item characteristic curves and item information for all the items. Based on the item parameters and item information, a final 12 item scale was developed. The scale performs optimally in the low to moderate trust range. Conclusions The final 12 item trust in physician scale has a good construct validity and internal consistency. PMID:25941182

New approach for reduction of diesel consumption by comparing different mining haulage configurations.

PubMed

Rodovalho, Edmo da Cunha; Lima, Hernani Mota; de Tomi, Giorgio

2016-05-01

The mining operations of loading and haulage have an energy source that is highly dependent on fossil fuels. In mining companies that select trucks for haulage, this input is the main component of mining costs. How can the impact of the operational aspects on the diesel consumption of haulage operations in surface mines be assessed? There are many studies relating the consumption of fuel trucks to several variables, but a methodology that prioritizes higher-impact variables under each specific condition is not available. Generic models may not apply to all operational settings presented in the mining industry. This study aims to create a method of analysis, identification, and prioritization of variables related to fuel consumption of haul trucks in open pit mines. For this purpose, statistical analysis techniques and mathematical modelling tools using multiple linear regressions will be applied. The model is shown to be suitable because the results generate a good description of the fuel consumption behaviour. In the practical application of the method, the reduction of diesel consumption reached 10%. The implementation requires no large-scale investments or very long deadlines and can be applied to mining haulage operations in other settings. Copyright © 2016 Elsevier Ltd. All rights reserved.

DMT-TAFM: a data mining tool for technical analysis of futures market

NASA Astrophysics Data System (ADS)

Stepanov, Vladimir; Sathaye, Archana

2002-03-01

Technical analysis of financial markets describes many patterns of market behavior. For practical use, all these descriptions need to be adjusted for each particular trading session. In this paper, we develop a data mining tool for technical analysis of the futures markets (DMT-TAFM), which dynamically generates rules based on the notion of the price pattern similarity. The tool consists of three main components. The first component provides visualization of data series on a chart with different ranges, scales, and chart sizes and types. The second component constructs pattern descriptions using sets of polynomials. The third component specifies the training set for mining, defines the similarity notion, and searches for a set of similar patterns. DMT-TAFM is useful to prepare the data, and then reveal and systemize statistical information about similar patterns found in any type of historical price series. We performed experiments with our tool on three decades of trading data fro hundred types of futures. Our results for this data set shows that, we can prove or disprove many well-known patterns based on real data, as well as reveal new ones, and use the set of relatively consistent patterns found during data mining for developing better futures trading strategies.

13 CFR 121.406 - How does a small business concern qualify to provide manufactured products or other supply items...

Code of Federal Regulations, 2013 CFR

2013-01-01

...-disabled veteran-owned small business set-aside, WOSB or EDWOSB set-aside, or 8(a) contract? 121.406... items under a small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or... small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or EDWOSB set...

13 CFR 121.406 - How does a small business concern qualify to provide manufactured products or other supply items...

Code of Federal Regulations, 2014 CFR

2014-01-01

...-disabled veteran-owned small business set-aside, WOSB or EDWOSB set-aside, or 8(a) contract? 121.406... items under a small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or... small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or EDWOSB set...

13 CFR 121.406 - How does a small business concern qualify to provide manufactured products or other supply items...

Code of Federal Regulations, 2012 CFR

2012-01-01

...-disabled veteran-owned small business set-aside, WOSB or EDWOSB set-aside, or 8(a) contract? 121.406... items under a small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or... small business set-aside, service-disabled veteran-owned small business set-aside, WOSB or EDWOSB set...

Efficient discovery of risk patterns in medical data.

PubMed

Li, Jiuyong; Fu, Ada Wai-chee; Fahey, Paul

2009-01-01

This paper studies a problem of efficiently discovering risk patterns in medical data. Risk patterns are defined by a statistical metric, relative risk, which has been widely used in epidemiological research. To avoid fruitless search in the complete exploration of risk patterns, we define optimal risk pattern set to exclude superfluous patterns, i.e. complicated patterns with lower relative risk than their corresponding simpler form patterns. We prove that mining optimal risk pattern sets conforms an anti-monotone property that supports an efficient mining algorithm. We propose an efficient algorithm for mining optimal risk pattern sets based on this property. We also propose a hierarchical structure to present discovered patterns for the easy perusal by domain experts. The proposed approach is compared with two well-known rule discovery methods, decision tree and association rule mining approaches on benchmark data sets and applied to a real world application. The proposed method discovers more and better quality risk patterns than a decision tree approach. The decision tree method is not designed for such applications and is inadequate for pattern exploring. The proposed method does not discover a large number of uninteresting superfluous patterns as an association mining approach does. The proposed method is more efficient than an association rule mining method. A real world case study shows that the method reveals some interesting risk patterns to medical practitioners. The proposed method is an efficient approach to explore risk patterns. It quickly identifies cohorts of patients that are vulnerable to a risk outcome from a large data set. The proposed method is useful for exploratory study on large medical data to generate and refine hypotheses. The method is also useful for designing medical surveillance systems.

Natural Language Processing Technologies in Radiology Research and Clinical Applications.

PubMed

Cai, Tianrun; Giannopoulos, Andreas A; Yu, Sheng; Kelil, Tatiana; Ripley, Beth; Kumamaru, Kanako K; Rybicki, Frank J; Mitsouras, Dimitrios

2016-01-01

The migration of imaging reports to electronic medical record systems holds great potential in terms of advancing radiology research and practice by leveraging the large volume of data continuously being updated, integrated, and shared. However, there are significant challenges as well, largely due to the heterogeneity of how these data are formatted. Indeed, although there is movement toward structured reporting in radiology (ie, hierarchically itemized reporting with use of standardized terminology), the majority of radiology reports remain unstructured and use free-form language. To effectively "mine" these large datasets for hypothesis testing, a robust strategy for extracting the necessary information is needed. Manual extraction of information is a time-consuming and often unmanageable task. "Intelligent" search engines that instead rely on natural language processing (NLP), a computer-based approach to analyzing free-form text or speech, can be used to automate this data mining task. The overall goal of NLP is to translate natural human language into a structured format (ie, a fixed collection of elements), each with a standardized set of choices for its value, that is easily manipulated by computer programs to (among other things) order into subcategories or query for the presence or absence of a finding. The authors review the fundamentals of NLP and describe various techniques that constitute NLP in radiology, along with some key applications. ©RSNA, 2016.

A large-scale, long-term study of scale drift: The micro view and the macro view

NASA Astrophysics Data System (ADS)

He, W.; Li, S.; Kingsbury, G. G.

2016-11-01

The development of measurement scales for use across years and grades in educational settings provides unique challenges, as instructional approaches, instructional materials, and content standards all change periodically. This study examined the measurement stability of a set of Rasch measurement scales that have been in place for almost 40 years. In order to investigate the stability of these scales, item responses were collected from a large set of students who took operational adaptive tests using items calibrated to the measurement scales. For the four scales that were examined, item samples ranged from 2183 to 7923 items. Each item was administered to at least 500 students in each grade level, resulting in approximately 3000 responses per item. Stability was examined at the micro level analysing change in item parameter estimates that have occurred since the items were first calibrated. It was also examined at the macro level, involving groups of items and overall test scores for students. Results indicated that individual items had changes in their parameter estimates, which require further analysis and possible recalibration. At the same time, the results at the total score level indicate substantial stability in the measurement scales over the span of their use.

ESTIMATE OF GLOBAL METHANE EMISSIONS FROM COAL MINES

EPA Science Inventory

Country-specific emissions of methane (CH4) from underground coal mines, surface coal mines, and coal crushing and transport operations are estimated for 1989. Emissions for individual countries are estimated by using two sets of regression equations (R2 values range from 0.56 to...

A Recommendation Algorithm for Automating Corollary Order Generation

PubMed Central

Klann, Jeffrey; Schadow, Gunther; McCoy, JM

2009-01-01

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards. PMID:20351875

A recommendation algorithm for automating corollary order generation.

PubMed

Klann, Jeffrey; Schadow, Gunther; McCoy, J M

2009-11-14

Manual development and maintenance of decision support content is time-consuming and expensive. We explore recommendation algorithms, e-commerce data-mining tools that use collective order history to suggest purchases, to assist with this. In particular, previous work shows corollary order suggestions are amenable to automated data-mining techniques. Here, an item-based collaborative filtering algorithm augmented with association rule interestingness measures mined suggestions from 866,445 orders made in an inpatient hospital in 2007, generating 584 potential corollary orders. Our expert physician panel evaluated the top 92 and agreed 75.3% were clinically meaningful. Also, at least one felt 47.9% would be directly relevant in guideline development. This automated generation of a rough-cut of corollary orders confirms prior indications about automated tools in building decision support content. It is an important step toward computerized augmentation to decision support development, which could increase development efficiency and content quality while automatically capturing local standards.

Efficient frequent pattern mining algorithm based on node sets in cloud computing environment

NASA Astrophysics Data System (ADS)

Billa, V. N. Vinay Kumar; Lakshmanna, K.; Rajesh, K.; Reddy, M. Praveen Kumar; Nagaraja, G.; Sudheer, K.

2017-11-01

The ultimate goal of Data Mining is to determine the hidden information which is useful in making decisions using the large databases collected by an organization. This Data Mining involves many tasks that are to be performed during the process. Mining frequent itemsets is the one of the most important tasks in case of transactional databases. These transactional databases contain the data in very large scale where the mining of these databases involves the consumption of physical memory and time in proportion to the size of the database. A frequent pattern mining algorithm is said to be efficient only if it consumes less memory and time to mine the frequent itemsets from the given large database. Having these points in mind in this thesis we proposed a system which mines frequent itemsets in an optimized way in terms of memory and time by using cloud computing as an important factor to make the process parallel and the application is provided as a service. A complete framework which uses a proven efficient algorithm called FIN algorithm. FIN algorithm works on Nodesets and POC (pre-order coding) tree. In order to evaluate the performance of the system we conduct the experiments to compare the efficiency of the same algorithm applied in a standalone manner and in cloud computing environment on a real time data set which is traffic accidents data set. The results show that the memory consumption and execution time taken for the process in the proposed system is much lesser than those of standalone system.

Bayesian Modal Estimation of the Four-Parameter Item Response Model in Real, Realistic, and Idealized Data Sets.

PubMed

Waller, Niels G; Feuerstahler, Leah

2017-01-01

In this study, we explored item and person parameter recovery of the four-parameter model (4PM) in over 24,000 real, realistic, and idealized data sets. In the first analyses, we fit the 4PM and three alternative models to data from three Minnesota Multiphasic Personality Inventory-Adolescent form factor scales using Bayesian modal estimation (BME). Our results indicated that the 4PM fits these scales better than simpler item Response Theory (IRT) models. Next, using the parameter estimates from these real data analyses, we estimated 4PM item parameters in 6,000 realistic data sets to establish minimum sample size requirements for accurate item and person parameter recovery. Using a factorial design that crossed discrete levels of item parameters, sample size, and test length, we also fit the 4PM to an additional 18,000 idealized data sets to extend our parameter recovery findings. Our combined results demonstrated that 4PM item parameters and parameter functions (e.g., item response functions) can be accurately estimated using BME in moderate to large samples (N ⩾ 5, 000) and person parameters can be accurately estimated in smaller samples (N ⩾ 1, 000). In the supplemental files, we report annotated [Formula: see text] code that shows how to estimate 4PM item and person parameters in [Formula: see text] (Chalmers, 2012 ).

Development and evaluation of CAHPS survey items assessing how well healthcare providers address health literacy.

PubMed

Weidmer, Beverly A; Brach, Cindy; Hays, Ron D

2012-09-01

The complexity of health information often exceeds patients' skills to understand and use it. To develop survey items assessing how well healthcare providers communicate health information. Domains and items for the Consumer Assessment of Healthcare Providers and Systems (CAHPS) Item Set for Addressing Health Literacy were identified through an environmental scan and input from stakeholders. The draft item set was translated into Spanish and pretested in both English and Spanish. The revised item set was field tested with a randomly selected sample of adult patients from 2 sites using mail and telephonic data collection. Item-scale correlations, confirmatory factor analysis, and internal consistency reliability estimates were estimated to assess how well the survey items performed and identify composite measures. Finally, we regressed the CAHPS global rating of the provider item on the CAHPS core communication composite and the new health literacy composites. A total of 601 completed surveys were obtained (52% response rate). Two composite measures were identified: (1) Communication to Improve Health Literacy (16 items); and (2) How Well Providers Communicate About Medicines (6 items). These 2 composites were significantly uniquely associated with the global rating of the provider (communication to improve health literacy: P<0.001, b=0.28; and communication about medicines composite: P=0.02, b=0.04). The 2 composites and the CAHPS core communication composite accounted for 51% of the variance in the global rating of the provider. A 5-item subset of the Communication to Improve Health Literacy composite accounted for 90% of the variance of the original 16-item composite. This study provides support for reliability and validity of the CAHPS Item Set for Addressing Health Literacy. These items can serve to assess whether healthcare providers have communicated effectively with their patients and as a tool for quality improvement.

30 CFR 876.12 - Eligibility.

Code of Federal Regulations, 2012 CFR

2012-07-01

... LAND RECLAMATION ACID MINE DRAINAGE TREATMENT AND ABATEMENT PROGRAM § 876.12 Eligibility. (a) Beginning... distributed to it for an acid mine drainage fund. All amounts set aside under this section must be deposited into an acid mine drainage abatement and treatment fund established under State or Indian tribal law...

30 CFR 876.12 - Eligibility.

Code of Federal Regulations, 2013 CFR

2013-07-01

... LAND RECLAMATION ACID MINE DRAINAGE TREATMENT AND ABATEMENT PROGRAM § 876.12 Eligibility. (a) Beginning... distributed to it for an acid mine drainage fund. All amounts set aside under this section must be deposited into an acid mine drainage abatement and treatment fund established under State or Indian tribal law...

30 CFR 876.12 - Eligibility.

Code of Federal Regulations, 2011 CFR

2011-07-01

... LAND RECLAMATION ACID MINE DRAINAGE TREATMENT AND ABATEMENT PROGRAM § 876.12 Eligibility. (a) Beginning... distributed to it for an acid mine drainage fund. All amounts set aside under this section must be deposited into an acid mine drainage abatement and treatment fund established under State or Indian tribal law...

30 CFR 876.12 - Eligibility.

Code of Federal Regulations, 2010 CFR

2010-07-01

... LAND RECLAMATION ACID MINE DRAINAGE TREATMENT AND ABATEMENT PROGRAM § 876.12 Eligibility. (a) Beginning... distributed to it for an acid mine drainage fund. All amounts set aside under this section must be deposited into an acid mine drainage abatement and treatment fund established under State or Indian tribal law...

30 CFR 876.12 - Eligibility.

Code of Federal Regulations, 2014 CFR

2014-07-01

... LAND RECLAMATION ACID MINE DRAINAGE TREATMENT AND ABATEMENT PROGRAM § 876.12 Eligibility. (a) Beginning... distributed to it for an acid mine drainage fund. All amounts set aside under this section must be deposited into an acid mine drainage abatement and treatment fund established under State or Indian tribal law...

Proceedings of the International Conference on Educational Data Mining (EDM) (5th, Chania, Greece, June 19-21, 2012)

ERIC Educational Resources Information Center

International Educational Data Mining Society, 2012

2012-01-01

The 5th International Conference on Educational Data Mining (EDM 2012) is held in picturesque Chania on the beautiful Crete island in Greece, under the auspices of the International Educational Data Mining Society (IEDMS). The EDM 2012 conference is a leading international forum for high quality research that mines large data sets of educational…

Improved Approximation Algorithms for Item Pricing with Bounded Degree and Valuation

NASA Astrophysics Data System (ADS)

Hamane, Ryoso; Itoh, Toshiya

When a store sells items to customers, the store wishes to decide the prices of the items to maximize its profit. If the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. It would be hard for the store to decide the prices of items. Assume that a store has a set V of n items and there is a set C of m customers who wish to buy those items. The goal of the store is to decide the price of each item to maximize its profit. We refer to this maximization problem as an item pricing problem. We classify the item pricing problems according to how many items the store can sell or how the customers valuate the items. If the store can sell every item i with unlimited (resp. limited) amount, we refer to this as unlimited supply (resp. limited supply). We say that the item pricing problem is single-minded if each customer j∈C wishes to buy a set ej⊆V of items and assigns valuation w(ej)≥0. For the single-minded item pricing problems (in unlimited supply), Balcan and Blum regarded them as weighted k-hypergraphs and gave several approximation algorithms. In this paper, we focus on the (pseudo) degree of k-hypergraphs and the valuation ratio, i. e., the ratio between the smallest and the largest valuations. Then for the single-minded item pricing problems (in unlimited supply), we show improved approximation algorithms (for k-hypergraphs, general graphs, bipartite graphs, etc.) with respect to the maximum (pseudo) degree and the valuation ratio.

Reconnaissance study of water quality in the mining-affected Aries River Basin, Romania

USGS Publications Warehouse

Friedel, Michael J.; Tindall, James A.; Sardan, Daniel; Fey, David L.; Poputa, G.L.

2008-01-01

The Aries River basin of western Romania has been subject to mining activities as far back as Roman times. Present mining activities are associated with the extraction and processing of various metals including Au, Cu, Pb, and Zn. To understand the effects of these mining activities on the environment, this study focused on three objectives: (1) establish a baseline set of physical parameters, and water- and sediment-associated concentrations of metals in river-valley floors and floodplains; (2) establish a baseline set of physical and chemical measurements of pore water and sediment in tailings; and (3) provide training in sediment and water sampling to personnel in the National Agency for Mineral Resources and the Rosia Poieni Mine. This report summarizes basin findings of physical parameters and chemistry (sediment and water), and ancillary data collected during the low-flow synoptic sampling of May 2006.

Market basket analysis visualization on a spherical surface

NASA Astrophysics Data System (ADS)

Hao, Ming C.; Hsu, Meichun; Dayal, Umeshwar; Wei, Shu F.; Sprenger, Thomas; Holenstein, Thomas

2001-05-01

This paper discusses the visualization of the relationships in e-commerce transactions. To date, many practical research projects have shown the usefulness of a physics-based mass- spring technique to layout data items with close relationships on a graph. We describe a market basket analysis visualization system using this technique. This system is described as the following: (1) integrates a physics-based engine into a visual data mining platform; (2) use a 3D spherical surface to visualize the cluster of related data items; and (3) for large volumes of transactions, uses hidden structures to unclutter the display. Several examples of market basket analysis are also provided.

Approximate classification of mining tremors harmfulness based on free-field and building foundation vibrations

NASA Astrophysics Data System (ADS)

Kuzniar, Krystyna; Stec, Krystyna; Tatara, Tadeusz

2018-04-01

The paper compares the results of an approximate evaluation of mining tremors harmfulness performed on the basis of free-field and simultaneously measured building foundation vibrations. The focus is on the office building located in the Upper Silesian Basin (USB). The empirical Mining Intensity Scale GSI-GZWKW-2012 has been applied to classify the harmfulness of the rockbursts. This scale is based on the measurements of free-field vibrations but, for research purposes, it was also used in the cases of building foundation vibrations. The analysis was carried out using the set of 156 pairs ground - foundation of velocity vibration records as well as the set of 156 pairs of acceleration records induced by the same mining tremors.

Clusters of cultures: diversity in meaning of family value and gender role items across Europe.

PubMed

van Vlimmeren, Eva; Moors, Guy B D; Gelissen, John P T M

2017-01-01

Survey data are often used to map cultural diversity by aggregating scores of attitude and value items across countries. However, this procedure only makes sense if the same concept is measured in all countries. In this study we argue that when (co)variances among sets of items are similar across countries, these countries share a common way of assigning meaning to the items. Clusters of cultures can then be observed by doing a cluster analysis on the (co)variance matrices of sets of related items. This study focuses on family values and gender role attitudes. We find four clusters of cultures that assign a distinct meaning to these items, especially in the case of gender roles. Some of these differences reflect response style behavior in the form of acquiescence. Adjusting for this style effect impacts on country comparisons hence demonstrating the usefulness of investigating the patterns of meaning given to sets of items prior to aggregating scores into cultural characteristics.

A Study of the Homogeneity of Items Produced From Item Forms Across Different Taxonomic Levels.

ERIC Educational Resources Information Center

Weber, Margaret B.; Argo, Jana K.

This study determined whether item forms ( rules for constructing items related to a domain or set of tasks) would enable naive item writers to generate multiple-choice items at three taxonomic levels--knowledge, comprehension, and application. Students wrote 120 multiple-choice items from 20 item forms, corresponding to educational objectives…

Remediation of Acid Mine Drainage with Sulfate Reducing Bacteria

ERIC Educational Resources Information Center

Hauri, James F.; Schaider, Laurel A.

2009-01-01

Sulfate reducing bacteria have been shown to be effective at treating acid mine drainage through sulfide production and subsequent precipitation of metal sulfides. In this laboratory experiment for undergraduate environmental chemistry courses, students design and implement a set of bioreactors to remediate acid mine drainage and explain observed…

An Evaluation of Text Mining Tools as Applied to Selected Scientific and Engineering Literature.

ERIC Educational Resources Information Center

Trybula, Walter J.; Wyllys, Ronald E.

2000-01-01

Addresses an approach to the discovery of scientific knowledge through an examination of data mining and text mining techniques. Presents the results of experiments that investigated knowledge acquisition from a selected set of technical documents by domain experts. (Contains 15 references.) (Author/LRW)

Analyzing Student Inquiry Data Using Process Discovery and Sequence Classification

ERIC Educational Resources Information Center

Emond, Bruno; Buffett, Scott

2015-01-01

This paper reports on results of applying process discovery mining and sequence classification mining techniques to a data set of semi-structured learning activities. The main research objective is to advance educational data mining to model and support self-regulated learning in heterogeneous environments of learning content, activities, and…

TEDS-M 2008 User Guide for the International Database. Supplement 4: TEDS-M Released Mathematics and Mathematics Pedagogy Knowledge Assessment Items

ERIC Educational Resources Information Center

Brese, Falk, Ed.

2012-01-01

The goal for selecting the released set of test items was to have approximately 25% of each of the full item sets for mathematics content knowledge (MCK) and mathematics pedagogical content knowledge (MPCK) that would represent the full range of difficulty, content, and item format used in the TEDS-M study. The initial step in the selection was to…

Mining and Integration of Environmental Data

NASA Astrophysics Data System (ADS)

Tran, V.; Hluchy, L.; Habala, O.; Ciglan, M.

2009-04-01

The project ADMIRE (Advanced Data Mining and Integration Research for Europe) is a 7th FP EU ICT project aims to deliver a consistent and easy-to-use technology for extracting information and knowledge. The project is motivated by the difficulty of extracting meaningful information by data mining combinations of data from multiple heterogeneous and distributed resources. It will also provide an abstract view of data mining and integration, which will give users and developers the power to cope with complexity and heterogeneity of services, data and processes. The data sets describing phenomena from domains like business, society, and environment often contain spatial and temporal dimensions. Integration of spatio-temporal data from different sources is a challenging task due to those dimensions. Different spatio-temporal data sets contain data at different resolutions (e.g. size of the spatial grid) and frequencies. This heterogeneity is the principal challenge of geo-spatial and temporal data sets integration - the integrated data set should hold homogeneous data of the same resolution and frequency. Thus, to integrate heterogeneous spatio-temporal data from distinct source, transformation of one or more data sets is necessary. Following transformation operation are required: • transformation to common spatial and temporal representation - (e.g. transformation to common coordinate system), • spatial and/or temporal aggregation - data from detailed data source are aggregated to match the resolution of other resources involved in the integration process, • spatial and/or temporal record decomposition - records from source with lower resolution data are decomposed to match the granularity of the other data source. This operation decreases data quality (e.g. transformation of data from 50km grid to 10 km grid) - data from lower resolution data set in the integrated schema are imprecise, but it allows us to preserve higher resolution data. We can decompose the spatio-temporal data integration to following phases: • pre-integration data processing - different data set can be physically stored in different formats (e.g. relational databases, text files); it might be necessary to pre-process the data sets to be integrated, • identification of transformation operations necessary to integrate data in spatio-temporal dimensions, • identification of transformation operations to be performed on non-spatio-temporal attributes and • output data schema and set generation - given prepared data and the set of transformation, operations, the final integrated schema is produces. Spatio-temporal dimension brings its specifics also to the problem of mining spatio-temporal data sets. Spatio-temporal relationships exist among records in (s-t) data sets and those relationships should be considered in mining operation. This means that when analyzing a record in spatio-temporal data set, the records in its spatial and/or temporal proximity should be taken into account. In addition, the relationships discovered in spatio-temporal data can be different when mining the same data on different scales (e.g. mining the same data sets on 50 km grid with daily data vs. 10 km grid with hourly data). To be able to do effective data mining, we first needed to gather a sufficient amount of environmental data covering similar area and time span. For this purpose we have engaged in cooperation with several organizations working in the environmental domain in Slovakia, some of which are also our partners from previous research efforts. The organizations which volunteered some of their data are the Slovak Hydro-meteorological Institute (SHMU), the Slovak Water Enterprise (SVP), the Soil Science and Conservation Institute (VUPOP), and the Institute of Hydrology of the Slovak Academy of Sciences (UHSAV). We have prepared scenarios from general meteorology, as well as specialized in hydrology and soil protection.

What I Wish I Knew about Assessment.

ERIC Educational Resources Information Center

Guion, Robert M.

Reflecting on a career spent in assessment in personnel selection and managment, the author lists 12 things (items) that he wishes he knew about assessment. The first four items are underdeveloped ideas set aside because of the field's preoccupation with equal employment opportunity. A second set (items five through eight) comes from intellectual…

Microcomputer keeps watch at Emerald Mine

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

Not Available

1987-04-01

This paper reviews the computerized mine monitoring system set up at the Emerald Mine, SW Pennsylvania, USA. This coal mine has pioneered the automation of many production and safety features and this article covers their work in fire detection and conveyor belt monitoring. A central computer control room can safely watch over the whole underground mining operation using one 25 inch colour monitor. These new data-acquisition systems will lead the way, in the future, to safer move efficient coal mining. Multi-point monitoring of carbon monoxide, heat anomalies, toxic gases and the procedures in conveyor belt operation from start-up to closedown.

Can health care providers recognise a fibromyalgia personality?

PubMed

Da Silva, José A P; Jacobs, Johannes W G; Branco, Jaime C; Canaipa, Rita; Gaspar, M Filomena; Griep, Ed N; van Helmond, Toon; Oliveira, Paula J; Zijlstra, Theo J; Geenen, Rinie

2017-01-01

To determine if experienced health care providers (HCPs) can recognise patients with fibromyalgia (FM) based on a limited set of personality items, exploring the existence of a FM personality. From the 240-item NEO-PI-R personality questionnaire, 8 HCPs from two different countries each selected 20 items they considered most discriminative of FM personality. Then, evaluating the scores on these items of 129 female patients with FM and 127 female controls, each HCP rated the probability of FM for each individual on a 0-10 scale. Personality characteristics (domains and facets) of selected items were determined. Scores of patients with FM and controls on the eight 20-item sets, and HCPs' estimates of each individual's probability of FM were analysed for their discriminative value. The eight 20-item sets discriminated for FM, with areas under the receiver operating characteristic curve ranging from 0.71-0.81. The estimated probabilities for FM showed, in general, percentages of correct classifications above 50%, with rising correct percentages for higher estimated probabilities. The most often chosen and discriminatory items were predominantly of the domain neuroticism (all with higher scores in FM), followed by some items of the facet trust (lower scores in FM). HCPs can, based on a limited set of items from a personality questionnaire, distinguish patients with FM from controls with a statistically significant probability. The HCPs' expectation that personality in FM patients is associated with higher levels for aspects of neuroticism (proneness to psychological distress) and lower scores for aspects of trust, proved to be correct.

Hazards identified and the need for health risk assessment in the South African mining industry.

PubMed

Utembe, W; Faustman, E M; Matatiele, P; Gulumian, M

2015-12-01

Although mining plays a prominent role in the economy of South Africa, it is associated with many chemical hazards. Exposure to dust from mining can lead to many pathological effects depending on mineralogical composition, size, shape and levels and duration of exposure. Mining and processing of minerals also result in occupational exposure to toxic substances such as platinum, chromium, vanadium, manganese, mercury, cyanide and diesel particulate. South Africa has set occupational exposure limits (OELs) for some hazards, but mine workers are still at a risk. Since the hazard posed by a mineral depends on its physiochemical properties, it is recommended that South Africa should not simply adopt OELs from other countries but rather set her own standards based on local toxicity studies. The limits should take into account the issue of mixtures to which workers could be exposed as well as the health status of the workers. The mining industry is also a source of contamination of the environment, due inter alia to the large areas of tailings dams and dumps left behind. Therefore, there is need to develop guidelines for safe land-uses of contaminated lands after mine closure. © The Author(s) 2015.

Evidence for a Global Sampling Process in Extraction of Summary Statistics of Item Sizes in a Set.

PubMed

Tokita, Midori; Ueda, Sachiyo; Ishiguchi, Akira

2016-01-01

Several studies have shown that our visual system may construct a "summary statistical representation" over groups of visual objects. Although there is a general understanding that human observers can accurately represent sets of a variety of features, many questions on how summary statistics, such as an average, are computed remain unanswered. This study investigated sampling properties of visual information used by human observers to extract two types of summary statistics of item sets, average and variance. We presented three models of ideal observers to extract the summary statistics: a global sampling model without sampling noise, global sampling model with sampling noise, and limited sampling model. We compared the performance of an ideal observer of each model with that of human observers using statistical efficiency analysis. Results suggest that summary statistics of items in a set may be computed without representing individual items, which makes it possible to discard the limited sampling account. Moreover, the extraction of summary statistics may not necessarily require the representation of individual objects with focused attention when the sets of items are larger than 4.

Testing whether the DSM-5 personality disorder trait model can be measured with a reduced set of items: An item response theory investigation of the Personality Inventory for DSM-5.

PubMed

Maples, Jessica L; Carter, Nathan T; Few, Lauren R; Crego, Cristina; Gore, Whitney L; Samuel, Douglas B; Williamson, Rachel L; Lynam, Donald R; Widiger, Thomas A; Markon, Kristian E; Krueger, Robert F; Miller, Joshua D

2015-12-01

The fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5) includes an alternative model of personality disorders (PDs) in Section III, consisting in part of a pathological personality trait model. To date, the 220-item Personality Inventory for DSM-5 (PID-5; Krueger, Derringer, Markon, Watson, & Skodol, 2012) is the only extant self-report instrument explicitly developed to measure this pathological trait model. The present study used item response theory-based analyses in a large sample (n = 1,417) to investigate whether a reduced set of 100 items could be identified from the PID-5 that could measure the 25 traits and 5 domains. This reduced set of PID-5 items was then tested in a community sample of adults currently receiving psychological treatment (n = 109). Across a wide range of criterion variables including NEO PI-R domains and facets, DSM-5 Section II PD scores, and externalizing and internalizing outcomes, the correlational profiles of the original and reduced versions of the PID-5 were nearly identical (rICC = .995). These results provide strong support for the hypothesis that an abbreviated set of PID-5 items can be used to reliably, validly, and efficiently assess these personality disorder traits. The ability to assess the DSM-5 Section III traits using only 100 items has important implications in that it suggests these traits could still be measured in settings in which assessment-related resources (e.g., time, compensation) are limited. (c) 2015 APA, all rights reserved).

Rehearsal development as development of iterative recall processes.

PubMed

Lehmann, Martin

2015-01-01

Although much is known about the critical importance of active verbal rehearsal for successful recall, knowledge about the mechanisms of rehearsal and their respective development in children is very limited. To be able to rehearse several items together, these items have to be available, or, if presented and rehearsed previously, retrieved from memory. Therefore, joint rehearsal of several items may itself be considered recall. Accordingly, by analyzing free recall, one cannot only gain insight into how recall and rehearsal unfold, but also into how principles that govern children's recall govern children's rehearsal. Over a period of three and a half years (beginning at grade 3) 54 children were longitudinally assessed seven times on several overt rehearsal free recall trials. A first set of analyses on recall revealed significant age-related increases in the primacy effect and an age-invariant recency effect. In the middle portion of the list, wave-shaped recall characteristics emerged and increased with age, indicating grouping of the list into subsequences. In a second set of analyses, overt rehearsal behavior was decomposed into distinct rehearsal sets. Analyses of these sets revealed that the distribution of rehearsals within each set resembled the serial position curves with one- or two-item primacy and recency effects and wave-shaped rehearsal patterns in between. In addition, rehearsal behavior throughout the list was characterized by a decreasing tendency to begin rehearsal sets with the first list item. This result parallels the phenomenon of beginning recall with the first item on short lists and with the last item on longer lists.

Rehearsal development as development of iterative recall processes

PubMed Central

Lehmann, Martin

2015-01-01

Although much is known about the critical importance of active verbal rehearsal for successful recall, knowledge about the mechanisms of rehearsal and their respective development in children is very limited. To be able to rehearse several items together, these items have to be available, or, if presented and rehearsed previously, retrieved from memory. Therefore, joint rehearsal of several items may itself be considered recall. Accordingly, by analyzing free recall, one cannot only gain insight into how recall and rehearsal unfold, but also into how principles that govern children’s recall govern children’s rehearsal. Over a period of three and a half years (beginning at grade 3) 54 children were longitudinally assessed seven times on several overt rehearsal free recall trials. A first set of analyses on recall revealed significant age-related increases in the primacy effect and an age-invariant recency effect. In the middle portion of the list, wave-shaped recall characteristics emerged and increased with age, indicating grouping of the list into subsequences. In a second set of analyses, overt rehearsal behavior was decomposed into distinct rehearsal sets. Analyses of these sets revealed that the distribution of rehearsals within each set resembled the serial position curves with one- or two-item primacy and recency effects and wave-shaped rehearsal patterns in between. In addition, rehearsal behavior throughout the list was characterized by a decreasing tendency to begin rehearsal sets with the first list item. This result parallels the phenomenon of beginning recall with the first item on short lists and with the last item on longer lists. PMID:25870569

Item Purification Does Not Always Improve DIF Detection: A Counterexample with Angoff's Delta Plot

ERIC Educational Resources Information Center

Magis, David; Facon, Bruno

2013-01-01

Item purification is an iterative process that is often advocated as improving the identification of items affected by differential item functioning (DIF). With test-score-based DIF detection methods, item purification iteratively removes the items currently flagged as DIF from the test scores to get purified sets of items, unaffected by DIF. The…

Redundancy and Novelty Mining in the Business Blogosphere

ERIC Educational Resources Information Center

Tsai, Flora S.; Chan, Kap Luk

2010-01-01

Purpose: The paper aims to explore the performance of redundancy and novelty mining in the business blogosphere, which has not been studied before. Design/methodology/approach: Novelty mining techniques are implemented to single out novel information out of a massive set of text documents. This paper adopted the mixed metric approach which…

Exploring the Integration of Data Mining and Data Visualization

ERIC Educational Resources Information Center

Zhang, Yi

2011-01-01

Due to the rapid advances in computing and sensing technologies, enormous amounts of data are being generated everyday in various applications. The integration of data mining and data visualization has been widely used to analyze these massive and complex data sets to discover hidden patterns. For both data mining and visualization to be…

A Data Preparation Methodology in Data Mining Applied to Mortality Population Databases.

PubMed

Pérez, Joaquín; Iturbide, Emmanuel; Olivares, Víctor; Hidalgo, Miguel; Martínez, Alicia; Almanza, Nelva

2015-11-01

It is known that the data preparation phase is the most time consuming in the data mining process, using up to 50% or up to 70% of the total project time. Currently, data mining methodologies are of general purpose and one of their limitations is that they do not provide a guide about what particular task to develop in a specific domain. This paper shows a new data preparation methodology oriented to the epidemiological domain in which we have identified two sets of tasks: General Data Preparation and Specific Data Preparation. For both sets, the Cross-Industry Standard Process for Data Mining (CRISP-DM) is adopted as a guideline. The main contribution of our methodology is fourteen specialized tasks concerning such domain. To validate the proposed methodology, we developed a data mining system and the entire process was applied to real mortality databases. The results were encouraging because it was observed that the use of the methodology reduced some of the time consuming tasks and the data mining system showed findings of unknown and potentially useful patterns for the public health services in Mexico.

Examining the Effectiveness of Test Accommodation Using DIF and a Mixture IRT Model

ERIC Educational Resources Information Center

Cho, Hyun-Jeong; Lee, Jaehoon; Kingston, Neal

2012-01-01

This study examined the validity of test accommodation in third-eighth graders using differential item functioning (DIF) and mixture IRT models. Two data sets were used for these analyses. With the first data set (N = 51,591) we examined whether item type (i.e., story, explanation, straightforward) or item features were associated with item…

Law on Geological Exploration in Poland.

DTIC Science & Technology

1961-02-23

control of mining bureaus, as set forth in the mining law and the decree of 21 October 1954 concerning mining enterprises (Dziennik Ustaw, No 47, Poz...meters, unless such work is carried out on mining lane or in a protected mountain mineral sorites area. _Supp.xvis.ion and control over activities...the grounds and the methods of performing tne work defined in paragraph 2, as well as the administration of supervision and control over this work

75 FR 26828 - Self-Regulatory Organizations; Chicago Board Options Exchange, Incorporated; Notice of Filing and...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-05-12

... amend [sic] its rules relating to the Penny Pilot Program. The text of the rule proposal is available on... proposed rule change. The text of those statements may be examined at the places specified in Item IV below... Technology Select Sector XME SPDR S&P Metals & Mining SPDR Fund. ETF. AKS AK Steel Holding Corp... KGC...

A Preliminary Investigation of the Direct Standard Setting Method.

ERIC Educational Resources Information Center

Jones, J. Patrick; And Others

Three studies assessed the psychometric characteristics of the Direct Standard Setting Method (DSSM). The Angoff technique was also used in each study. The DSSM requires judges to consider an examination 10 items at a time and determine the minimum items in that set a candidate should answer correctly to receive the credential. Nine judges set a…

One portion size of foods frequently consumed by Korean adults

PubMed Central

Choi, Mi-Kyeong; Hyun, Wha-Jin; Lee, Sim-Yeol; Park, Hong-Ju; Kim, Se-Na

2010-01-01

This study aimed to define a one portion size of food items frequently consumed for convenient use by Koreans in food selection, diet planning, and nutritional evaluation. We analyzed using the original data on 5,436 persons (60.87%) aged 20 ~ 64 years among 8,930 persons to whom NHANES 2005 and selected food items consumed by the intake frequency of 30 or higher among the 500 most frequently consumed food items. A total of 374 varieties of food items of regular use were selected. And the portion size of food items was set on the basis of the median (50th percentile) of the portion size for a single intake by a single person was analyzed. In cereals, the portion size of well polished rice was 80 g. In meats, the portion size of Korean beef cattle was 25 g. Among vegetable items, the portion size of Baechukimchi was 40 g. The portion size of the food items of regular use set in this study will be conveniently and effectively used by general consumers in selecting food items for a nutritionally balanced diet. In addition, these will be used as the basic data in setting the serving size in meal planning. PMID:20198213

Item Difficulty in the Evaluation of Computer-Based Instruction: An Example from Neuroanatomy

PubMed Central

Chariker, Julia H.; Naaz, Farah; Pani, John R.

2012-01-01

This article reports large item effects in a study of computer-based learning of neuroanatomy. Outcome measures of the efficiency of learning, transfer of learning, and generalization of knowledge diverged by a wide margin across test items, with certain sets of items emerging as particularly difficult to master. In addition, the outcomes of comparisons between instructional methods changed with the difficulty of the items to be learned. More challenging items better differentiated between instructional methods. This set of results is important for two reasons. First, it suggests that instruction may be more efficient if sets of consistently difficult items are the targets of instructional methods particularly suited to them. Second, there is wide variation in the published literature regarding the outcomes of empirical evaluations of computer-based instruction. As a consequence, many questions arise as to the factors that may affect such evaluations. The present paper demonstrates that the level of challenge in the material that is presented to learners is an important factor to consider in the evaluation of a computer-based instructional system. PMID:22231801

Item difficulty in the evaluation of computer-based instruction: an example from neuroanatomy.

PubMed

Chariker, Julia H; Naaz, Farah; Pani, John R

2012-01-01

This article reports large item effects in a study of computer-based learning of neuroanatomy. Outcome measures of the efficiency of learning, transfer of learning, and generalization of knowledge diverged by a wide margin across test items, with certain sets of items emerging as particularly difficult to master. In addition, the outcomes of comparisons between instructional methods changed with the difficulty of the items to be learned. More challenging items better differentiated between instructional methods. This set of results is important for two reasons. First, it suggests that instruction may be more efficient if sets of consistently difficult items are the targets of instructional methods particularly suited to them. Second, there is wide variation in the published literature regarding the outcomes of empirical evaluations of computer-based instruction. As a consequence, many questions arise as to the factors that may affect such evaluations. The present article demonstrates that the level of challenge in the material that is presented to learners is an important factor to consider in the evaluation of a computer-based instructional system. Copyright © 2011 American Association of Anatomists.

Pattern Mining for Extraction of mentions of Adverse Drug Reactions from User Comments

PubMed Central

Nikfarjam, Azadeh; Gonzalez, Graciela H.

2011-01-01

Rapid growth of online health social networks has enabled patients to communicate more easily with each other. This way of exchange of opinions and experiences has provided a rich source of information about drugs and their effectiveness and more importantly, their possible adverse reactions. We developed a system to automatically extract mentions of Adverse Drug Reactions (ADRs) from user reviews about drugs in social network websites by mining a set of language patterns. The system applied association rule mining on a set of annotated comments to extract the underlying patterns of colloquial expressions about adverse effects. The patterns were tested on a set of unseen comments to evaluate their performance. We reached to precision of 70.01% and recall of 66.32% and F-measure of 67.96%. PMID:22195162

Parameter Estimation in Rasch Models for Examinee-Selected Items

ERIC Educational Resources Information Center

Liu, Chen-Wei; Wang, Wen-Chung

2017-01-01

The examinee-selected-item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set of items (e.g., choose one item to respond from a pair of items), always yields incomplete data (i.e., only the selected items are answered and the others have missing data) that are likely nonignorable. Therefore, using…

Ensemble representations: effects of set size and item heterogeneity on average size perception.

PubMed

Marchant, Alexander P; Simons, Daniel J; de Fockert, Jan W

2013-02-01

Observers can accurately perceive and evaluate the statistical properties of a set of objects, forming what is now known as an ensemble representation. The accuracy and speed with which people can judge the mean size of a set of objects have led to the proposal that ensemble representations of average size can be computed in parallel when attention is distributed across the display. Consistent with this idea, judgments of mean size show little or no decrement in accuracy when the number of objects in the set increases. However, the lack of a set size effect might result from the regularity of the item sizes used in previous studies. Here, we replicate these previous findings, but show that judgments of mean set size become less accurate when set size increases and the heterogeneity of the item sizes increases. This pattern can be explained by assuming that average size judgments are computed using a limited capacity sampling strategy, and it does not necessitate an ensemble representation computed in parallel across all items in a display. Copyright © 2012 Elsevier B.V. All rights reserved.

Characterizing Ground-Water Flow Paths in High-Altitude Fractured Rock Settings Impacted by Mining Activities

NASA Astrophysics Data System (ADS)

Wireman, M.; Williams, D.

2003-12-01

The Rocky Mountains of the western USA have tens of thousands of abandoned, inactive and active precious-metal(gold,silver,copper)mine sites. Most of these sites occur in fractured rock hydrogeologic settings. Mining activities often resulted in mobilization and transport of associated heavy metals (zinc,cadmium,lead) which pose a significant threat to aquatic communities in mountain streams.Transport of heavy metals from mine related sources (waste rock piles,tailings impoudments,underground workings, mine pits)can occur along numerous hydrological pathways including complex fracture controlled ground-water pathways. Since 1991, the United States Environmental Protection Agency, the Colorado Division of Minerals and Geology and the University of Colorado (INSTAAR)have been conducting applied hydrologic research at the Mary Murphy underground mine. The mine is in the Chalk Creek mining district which is located on the southwestern flanks of the Mount Princeton Batholith, a Tertiary age intrusive comprised primarily of quartz monzonite.The Mount Princeton batholith comprises a large portion of the southern part of the Collegiate Range west of Buena Vista in Chaffee County, CO. Chalk Creek and its 14 tributaries drain about 24,900 hectares of the eastern slopes of the Range including the mining district. Within the mining district, ground-water flow is controlled by the distribution, orientation and permeability of discontinuities within the bedrock. Important discontinuities include faults, joints and weathered zones. Local and intermediate flow systems are perturbed by extensive underground excavations associated with mining (adits, shafts, stopes, drifts,, etc.). During the past 12 years numerous hydrological investigations have been completed. The investigations have been focused on developing tools for characterizing ground-water flow and contaminant transport in the vicinity of hard-rock mines in fractured-rock settings. In addition, the results from these investigations have been used to develop a sound conceptual model of ground-water flow and transport of heavy metals from the mine workings to Chalk Creek. Ground-water tracing techniques (using organic, fluorescent dyes) have been successfully used to delineate ground-water flow paths. Surface-water tracing techniques have been used to acquire very accurate stream flow measuements and to identify ground-water inflow zones to streams. Stable (O18/D)and radioactive (tritium,sulphur 35) isotope anlysis of waters flowing into and out of underground workings have proved useful for conducting end member mixing analysis to determine which inflows and outflows are most significant with respect to metals loading. Hydrogeologic mapping, inverse geochemical modeling (using MINTEQAK code)and helium 3 analysis of ground water have also proven to useful tools. These tools, used in combination have provided multiple lines of evidence regarding the nature, timing and magnitude of ground-water inflow into underground mine workings and the distribution and types of hydrologic pathways that transport metals from the underground workings to Chalk Creek. This paper presents the results of some of the more important hydrologic investigations completed at the site and a conceptual model of ground-water flow in fractured rock settings that have been impacted by underground mining activites.

Diagnostic support for selected neuromuscular diseases using answer-pattern recognition and data mining techniques: a proof of concept multicenter prospective trial.

PubMed

Grigull, Lorenz; Lechner, Werner; Petri, Susanne; Kollewe, Katja; Dengler, Reinhard; Mehmecke, Sandra; Schumacher, Ulrike; Lücke, Thomas; Schneider-Gold, Christiane; Köhler, Cornelia; Güttsches, Anne-Katrin; Kortum, Xiaowei; Klawonn, Frank

2016-03-08

Diagnosis of neuromuscular diseases in primary care is often challenging. Rare diseases such as Pompe disease are easily overlooked by the general practitioner. We therefore aimed to develop a diagnostic support tool using patient-oriented questions and combined data mining algorithms recognizing answer patterns in individuals with selected neuromuscular diseases. A multicenter prospective study for the proof of concept was conducted thereafter. First, 16 interviews with patients were conducted focusing on their pre-diagnostic observations and experiences. From these interviews, we developed a questionnaire with 46 items. Then, patients with diagnosed neuromuscular diseases as well as patients without such a disease answered the questionnaire to establish a database for data mining. For proof of concept, initially only six diagnoses were chosen (myotonic dystrophy and myotonia (MdMy), Pompe disease (MP), amyotrophic lateral sclerosis (ALS), polyneuropathy (PNP), spinal muscular atrophy (SMA), other neuromuscular diseases, and no neuromuscular disease (NND). A prospective study was performed to validate the automated malleable system, which included six different classification methods combined in a fusion algorithm proposing a final diagnosis. Finally, new diagnoses were incorporated into the system. In total, questionnaires from 210 individuals were used to train the system. 89.5 % correct diagnoses were achieved during cross-validation. The sensitivity of the system was 93-97 % for individuals with MP, with MdMy and without neuromuscular diseases, but only 69 % in SMA and 81 % in ALS patients. In the prospective trial, 57/64 (89 %) diagnoses were predicted correctly by the computerized system. All questions, or rather all answers, increased the diagnostic accuracy of the system, with the best results reached by the fusion of different classifier methods. Receiver operating curve (ROC) and p-value analyses confirmed the results. A questionnaire-based diagnostic support tool using data mining methods exhibited good results in predicting selected neuromuscular diseases. Due to the variety of neuromuscular diseases, additional studies are required to measure beneficial effects in the clinical setting.

Manual of good practices for sanitation in coal mining operations

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

Not Available

The purpose of the manual was to act as a guideline, setting reasonable recommendations relative to mine sanitation which will enable mines to install adequate facilities and make appropriate alterations conserving and improving the health and welfare of the mine worker. A systematic evaluation was undertaken of the sanitation facilities and maintenance at coal mines. Consideration was given to central facilities including building, floors, walls, partitions, ceilings, lockers, baskets and benches, showers, toilets, lavatories, lighting, ventilation and temperature control, and maintenance. Also discussed were food vending machines, water source, water quality, water treatment, water delivery systems for underground and surfacemore » mines, sanitary waste disposal, workplace toilets in underground and surface mines, refuse control and handling for underground and surface mines, and pest control.« less

The enviornmental assessment of a contemporary coal mining system

NASA Technical Reports Server (NTRS)

Dutzi, E. J.; Sullivan, P. J.; Hutchinson, C. F.; Stevens, C. M.

1980-01-01

A contemporary underground coal mine in eastern Kentucky was assessed in order to determine potential off-site and on-site environmental impacts associated with the mining system in the given environmental setting. A 4 section, continuous room and pillor mine plan was developed for an appropriate site in eastern Kentucky. Potential environmental impacts were identified, and mitigation costs determined. The major potential environmental impacts were determined to be: acid water drainage from the mine and refuse site, uneven subsidence of the surface as a result of mining activity, and alteration of ground water aquifers in the subsidence zone. In the specific case examined, the costs of environmental impact mitigation to levels prescribed by regulations would not exceed $1/ton of coal mined, and post mining land values would not be affected.

Searching while loaded: Visual working memory does not interfere with hybrid search efficiency but hybrid search uses working memory capacity.

PubMed

Drew, Trafton; Boettcher, Sage E P; Wolfe, Jeremy M

2016-02-01

In "hybrid search" tasks, such as finding items on a grocery list, one must search the scene for targets while also searching the list in memory. How is the representation of a visual item compared with the representations of items in the memory set? Predominant theories would propose a role for visual working memory (VWM) either as the site of the comparison or as a conduit between visual and memory systems. In seven experiments, we loaded VWM in different ways and found little or no effect on hybrid search performance. However, the presence of a hybrid search task did reduce the measured capacity of VWM by a constant amount regardless of the size of the memory or visual sets. These data are broadly consistent with an account in which VWM must dedicate a fixed amount of its capacity to passing visual representations to long-term memory for comparison to the items in the memory set. The data cast doubt on models in which the search template resides in VWM or where memory set item representations are moved from LTM through VWM to earlier areas for comparison to visual items.

Definition of redox and pH influence in the AMD mine system using a fuzzy qualitative tool (Iberian Pyrite Belt, SW Spain).

PubMed

de la Torre, M L; Grande, J A; Valente, T; Perez-Ostalé, E; Santisteban, M; Aroba, J; Ramos, I

2016-03-01

Poderosa Mine is an abandoned pyrite mine, located in the Iberian Pyrite Belt which pours its acid mine drainage (AMD) waters into the Odiel river (South-West Spain). This work focuses on establishing possible reasons for interdependence between the potential redox and pH, with the load of metals and sulfates, as well as a set of variables that define the physical chemistry of the water-conductivity, temperature, TDS, and dissolved oxygen-transported by a channel from Poderosa mine affected by acid mine drainage, through the use of techniques of artificial intelligence: fuzzy logic and data mining. The sampling campaign was carried out in May of 2012. There were a total of 16 sites, the first inside the tunnel and the last at the mouth of the river Odiel, with a distance of approximately 10 m between each pair of measuring stations. While the tools of classical statistics, which are widely used in this context, prove useful for defining proximity ratios between variables based on Pearson's correlations, in addition to making it easier to handle large volumes of data and producing easier-to-understand graphs, the use of fuzzy logic tools and data mining results in better definition of the variations produced by external stimuli on the set of variables. This tool is adaptable and can be extrapolated to any system polluted by acid mine drainage using simple, intuitive reasoning.

A Quantitative Analysis of Organizational Factors That Relate to Data Mining Success

ERIC Educational Resources Information Center

Huebner, Richard A.

2017-01-01

The ubiquity of data in various forms has fueled the need for advanced data-mining techniques within organizations. The advent of data mining methods used to uncover hidden nuggets of information buried within large data sets has also fueled the need for determining how these unique projects can be successful. There are many challenges associated…

The Consumer Assessment of Healthcare Providers and Systems (CAHPS) cultural competence (CC) item set.

PubMed

Weech-Maldonado, Robert; Carle, Adam; Weidmer, Beverly; Hurtado, Margarita; Ngo-Metzger, Quyen; Hays, Ron D

2012-09-01

There is a need for reliable and valid measures of cultural competence (CC) from the patient's perspective. This paper evaluates the reliability and validity of the Consumer Assessments of Healthcare Providers and Systems (CAHPS) CC item set. Using 2008 survey data, we assessed the internal consistency of the CAHPS CC scales using the Cronbach α's and examined the validity of the measures using exploratory and confirmatory factor analysis, multitrait scaling analysis, and regression analysis. A random stratified sample (based on race/ethnicity and language) of 991 enrollees, younger than 65 years, from 2 Medicaid managed care plans in California and New York. CAHPS CC item set after excluding screener items and ratings. Confirmatory factor analysis (Comparative Fit Index=0.98, Tucker Lewis Index=0.98, and Root Mean Square Error or Approximation=0.06) provided support for a 7-factor structure: Doctor Communication--Positive Behaviors, Doctor Communication--Negative Behaviors, Doctor Communication--Health Promotion, Doctor Communication--Alternative Medicine, Shared Decision-Making, Equitable Treatment, and Trust. Item-total correlations (corrected for item overlap) for the 7 scales exceeded 0.40. Exploratory factor analysis showed support for 1 additional factor: Access to Interpreter Services. Internal consistency reliability estimates ranged from 0.58 (Alternative Medicine) to 0.92 (Positive Behaviors) and was 0.70 or higher for 4 of the 8 composites. All composites were positively and significantly associated with the overall doctor rating. The CAHPS CC 26-item set demonstrates adequate measurement properties and can be used as a supplemental item set to the CAHPS Clinician and Group Surveys in assessing culturally competent care from the patient's perspective.

A Survey on Distributed Mobile Database and Data Mining

NASA Astrophysics Data System (ADS)

Goel, Ajay Mohan; Mangla, Neeraj; Patel, R. B.

2010-11-01

The anticipated increase in popular use of the Internet has created more opportunity in information dissemination, Ecommerce, and multimedia communication. It has also created more challenges in organizing information and facilitating its efficient retrieval. In response to this, new techniques have evolved which facilitate the creation of such applications. Certainly the most promising among the new paradigms is the use of mobile agents. In this paper, mobile agent and distributed database technologies are applied in the banking system. Many approaches have been proposed to schedule data items for broadcasting in a mobile environment. In this paper, an efficient strategy for accessing multiple data items in mobile environments and the bottleneck of current banking will be proposed.

Visual search for arbitrary objects in real scenes

PubMed Central

Alvarez, George A.; Rosenholtz, Ruth; Kuzmova, Yoana I.; Sherman, Ashley M.

2011-01-01

How efficient is visual search in real scenes? In searches for targets among arrays of randomly placed distractors, efficiency is often indexed by the slope of the reaction time (RT) × Set Size function. However, it may be impossible to define set size for real scenes. As an approximation, we hand-labeled 100 indoor scenes and used the number of labeled regions as a surrogate for set size. In Experiment 1, observers searched for named objects (a chair, bowl, etc.). With set size defined as the number of labeled regions, search was very efficient (~5 ms/item). When we controlled for a possible guessing strategy in Experiment 2, slopes increased somewhat (~15 ms/item), but they were much shallower than search for a random object among other distinctive objects outside of a scene setting (Exp. 3: ~40 ms/item). In Experiments 4–6, observers searched repeatedly through the same scene for different objects. Increased familiarity with scenes had modest effects on RTs, while repetition of target items had large effects (>500 ms). We propose that visual search in scenes is efficient because scene-specific forms of attentional guidance can eliminate most regions from the “functional set size” of items that could possibly be the target. PMID:21671156

Visual search for arbitrary objects in real scenes.

PubMed

Wolfe, Jeremy M; Alvarez, George A; Rosenholtz, Ruth; Kuzmova, Yoana I; Sherman, Ashley M

2011-08-01

How efficient is visual search in real scenes? In searches for targets among arrays of randomly placed distractors, efficiency is often indexed by the slope of the reaction time (RT) × Set Size function. However, it may be impossible to define set size for real scenes. As an approximation, we hand-labeled 100 indoor scenes and used the number of labeled regions as a surrogate for set size. In Experiment 1, observers searched for named objects (a chair, bowl, etc.). With set size defined as the number of labeled regions, search was very efficient (~5 ms/item). When we controlled for a possible guessing strategy in Experiment 2, slopes increased somewhat (~15 ms/item), but they were much shallower than search for a random object among other distinctive objects outside of a scene setting (Exp. 3: ~40 ms/item). In Experiments 4-6, observers searched repeatedly through the same scene for different objects. Increased familiarity with scenes had modest effects on RTs, while repetition of target items had large effects (>500 ms). We propose that visual search in scenes is efficient because scene-specific forms of attentional guidance can eliminate most regions from the "functional set size" of items that could possibly be the target.

Item Response Models for Examinee-Selected Items

ERIC Educational Resources Information Center

Wang, Wen-Chung; Jin, Kuan-Yu; Qiu, Xue-Lan; Wang, Lei

2012-01-01

In some tests, examinees are required to choose a fixed number of items from a set of given items to answer. This practice creates a challenge to standard item response models, because more capable examinees may have an advantage by making wiser choices. In this study, we developed a new class of item response models to account for the choice…

Item Estimates under Low-Stakes Conditions: How Should Omits Be Treated?

ERIC Educational Resources Information Center

DeMars, Christine

Using data from a pilot test of science and math from students in 30 high schools, item difficulties were estimated with a one-parameter model (partial-credit model for the multi-point items). Some items were multiple-choice items, and others were constructed-response items (open-ended). Four sets of estimates were obtained: estimates for males…

Development of the PROMIS coping expectancies of smoking item banks.

PubMed

Shadel, William G; Edelen, Maria Orlando; Tucker, Joan S; Stucky, Brian D; Hansen, Mark; Cai, Li

2014-09-01

Smoking is a coping strategy for many smokers who then have difficulty finding new ways to cope with negative affect when they quit. This paper describes analyses conducted to develop and evaluate item banks for assessing the coping expectancies of smoking for daily and nondaily smokers. Using data from a large sample of daily (N = 4,201) and nondaily (N = 1,183) smokers, we conducted a series of item factor analyses, item response theory analyses, and differential item functioning (DIF) analyses (according to gender, age, and ethnicity) to arrive at a unidimensional set of items for daily and nondaily smokers. We also evaluated performance of short forms (SFs) and computer adaptive tests (CATs) for assessing coping expectancies of smoking. For both daily and nondaily smokers, the unidimensional Coping Expectancies item banks (21 items) are relatively DIF free and are highly reliable (0.96 and 0.97, respectively). A common 4-item SF for daily and nondaily smokers also showed good reliability (0.85). Adaptive tests required an average of 4.3 and 3.7 items for simulated daily and nondaily respondents, respectively, and achieved reliabilities of 0.91 for both when the maximum test length was 10 items. This research provides a new set of items that can be used to reliably assess coping expectancies of smoking, through a SF, CAT, or a tailored set selected for a specific research purpose. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Item-Writing Guidelines for Physics

ERIC Educational Resources Information Center

Regan, Tom

2015-01-01

A teacher learning how to write test questions (test items) will almost certainly encounter item-writing guidelines--lists of item-writing do's and don'ts. Item-writing guidelines usually are presented as applicable across all assessment settings. Table I shows some guidelines that I believe to be generally applicable and two will be briefly…

Graph Mining Meets the Semantic Web

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

Lee, Sangkeun; Sukumar, Sreenivas R; Lim, Seung-Hwan

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today, data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. We address that need through implementation of three popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, and PageRank). We implement these algorithms as SPARQL queries, wrapped within Python scripts. We evaluatemore » the performance of our implementation on 6 real world data sets and show graph mining algorithms (that have a linear-algebra formulation) can indeed be unleashed on data represented as RDF graphs using the SPARQL query interface.« less

Have infant gross motor abilities changed in 20 years? A re-evaluation of the Alberta Infant Motor Scale normative values

PubMed Central

Darrah, Johanna; Bartlett, Doreen; Maguire, Thomas O; Avison, William R; Lacaze-Masmonteil, Thierry

2014-01-01

Aim To compare the original normative data of the Alberta Infant Motor Scale (AIMS) (n=2202) collected 20 years ago with a contemporary sample of Canadian infants. Method This was a cross-sectional cohort study of 650 Canadian infants (338 males, 312 females; mean age 30.9wks [SD 15.5], range 2wks–18mo) assessed once on the AIMS. Assessments were stratified by age, and infants proportionally represented the ethnic diversity of Canada. Logistic regression was used to place AIMS items on an age scale representing the age at which 50% of the infants passed an item on the contemporary data set and the original data set. Forty-three items met the criterion for stable regression results in both data sets. Results The correlation coefficient between the age locations of items on the original and contemporary data sets was 0.99. The mean age difference between item locations was 0.7 weeks. Age values from the original data set when converted to the contemporary scale differed by less than 1 week. Interpretation The sequence and age at emergence of AIMS items has remained similar over 20 years and current normative values remain valid. Concern that the ‘back to sleep’ campaign has influenced the age at emergence of gross motor abilities is not supported. PMID:24684556

Examining the Impact of Drifted Polytomous Anchor Items on Test Characteristic Curve (TCC) Linking and IRT True Score Equating. Research Report. ETS RR-12-09

ERIC Educational Resources Information Center

Li, Yanmei

2012-01-01

In a common-item (anchor) equating design, the common items should be evaluated for item parameter drift. Drifted items are often removed. For a test that contains mostly dichotomous items and only a small number of polytomous items, removing some drifted polytomous anchor items may result in anchor sets that no longer resemble mini-versions of…

Reduced-Item Food Audits Based on the Nutrition Environment Measures Surveys.

PubMed

Partington, Susan N; Menzies, Tim J; Colburn, Trina A; Saelens, Brian E; Glanz, Karen

2015-10-01

The community food environment may contribute to obesity by influencing food choice. Store and restaurant audits are increasingly common methods for assessing food environments, but are time consuming and costly. A valid, reliable brief measurement tool is needed. The purpose of this study was to develop and validate reduced-item food environment audit tools for stores and restaurants. Nutrition Environment Measures Surveys for stores (NEMS-S) and restaurants (NEMS-R) were completed in 820 stores and 1,795 restaurants in West Virginia, San Diego, and Seattle. Data mining techniques (correlation-based feature selection and linear regression) were used to identify survey items highly correlated to total survey scores and produce reduced-item audit tools that were subsequently validated against full NEMS surveys. Regression coefficients were used as weights that were applied to reduced-item tool items to generate comparable scores to full NEMS surveys. Data were collected and analyzed in 2008-2013. The reduced-item tools included eight items for grocery, ten for convenience, seven for variety, and five for other stores; and 16 items for sit-down, 14 for fast casual, 19 for fast food, and 13 for specialty restaurants-10% of the full NEMS-S and 25% of the full NEMS-R. There were no significant differences in median scores for varying types of retail food outlets when compared to the full survey scores. Median in-store audit time was reduced 25%-50%. Reduced-item audit tools can reduce the burden and complexity of large-scale or repeated assessments of the retail food environment without compromising measurement quality. Copyright © 2015 American Journal of Preventive Medicine. Published by Elsevier Inc. All rights reserved.

Aiming for a holistic integrated service for men diagnosed with prostate cancer - Definitions of standards and skill sets for nurses and allied healthcare professionals.

PubMed

Lamb, Alastair D; Thompson, Sue; Kinsella, Netty; Gerbitz, Ingmar; Chapman, Elaine; Putt, Lisa; Bennett, Sophie; Thankappannair, Vineetha; Geoghegan, Lisa; Wright, Naomi; Stirton-Croft, Alison; Nixon, Penny; Styling, Andrew; Whitney, Diane; Hodgson, Lindsay; Punt, Lisa; Longmore, Jenny; Carter, Mike; Petch, Bill; Rimmer, Yvonne; Russell, Simon; Hughes-Davies, Luke; Mazhar, Danish; Shah, Nimish C; Gnanapragasam, Vincent J; Doble, Andrew; Bratt, Ola; Kastner, Christof

2017-08-01

To establish a comprehensive set of recommendations for the service structure and skill set of nurses and allied healthcare professionals in prostate cancer care. Using components of formal consensus methodology, a 30-member multidisciplinary panel produced 53 items for discussion relating to the provision of care for prostate cancer patients by specialist nurses and allied healthcare professionals. Items were developed by two rounds of email correspondence in which, first, items were generated and, second, items refined to form the basis of a consensus meeting which constituted the third round of review. The fourth and final round was an email review of the consensus output. The panel agreed on 33 items that were appropriate for recommendations to be made. These items were grouped under categories of "Environment" and "Patient Pathway" and included comments on training, leadership, communication and quality assessment as well as specific items related to prostate diagnosis clinics, radical treatment clinics and follow-up survivor groups. Specialist nurses and allied healthcare professionals play a vital role alongside urologists and oncologists to provide care to men with prostate cancer and their families. We present a set of standards and consensus recommendations for the roles and skill-set required for these practitioners to provide gold-standard prostate cancer care. These recommendations could form the basis for development of comprehensive integrated prostate cancer pathways in prostate cancer centres as well as providing guidance for any units treating men with prostate cancer. Copyright © 2017. Published by Elsevier Ltd.

Web mining in soft computing framework: relevance, state of the art and future directions.

PubMed

Pal, S K; Talwar, V; Mitra, P

2002-01-01

The paper summarizes the different characteristics of Web data, the basic components of Web mining and its different types, and the current state of the art. The reason for considering Web mining, a separate field from data mining, is explained. The limitations of some of the existing Web mining methods and tools are enunciated, and the significance of soft computing (comprising fuzzy logic (FL), artificial neural networks (ANNs), genetic algorithms (GAs), and rough sets (RSs) are highlighted. A survey of the existing literature on "soft Web mining" is provided along with the commercially available systems. The prospective areas of Web mining where the application of soft computing needs immediate attention are outlined with justification. Scope for future research in developing "soft Web mining" systems is explained. An extensive bibliography is also provided.

Mine or Yours? Development of Sharing in Toddlers in Relation to Ownership Understanding

ERIC Educational Resources Information Center

Brownell, Celia A.; Iesue, Stephanie S.; Nichols, Sara R.; Svetlova, Margarita

2013-01-01

To examine early developments in other-oriented resource sharing, fifty-one 18- and 24-month-old children were administered 6 tasks with toys or food that could be shared with an adult playmate who had none. On each task the playmate communicated her desire for the items in a series of progressively more explicit cues. Twenty-four-month-olds…

Learning User Preferences for Sets of Objects

NASA Technical Reports Server (NTRS)

desJardins, Marie; Eaton, Eric; Wagstaff, Kiri L.

2006-01-01

Most work on preference learning has focused on pairwise preferences or rankings over individual items. In this paper, we present a method for learning preferences over sets of items. Our learning method takes as input a collection of positive examples--that is, one or more sets that have been identified by a user as desirable. Kernel density estimation is used to estimate the value function for individual items, and the desired set diversity is estimated from the average set diversity observed in the collection. Since this is a new learning problem, we introduce a new evaluation methodology and evaluate the learning method on two data collections: synthetic blocks-world data and a new real-world music data collection that we have gathered.

Evaluating data mining algorithms using molecular dynamics trajectories.

PubMed

Tatsis, Vasileios A; Tjortjis, Christos; Tzirakis, Panagiotis

2013-01-01

Molecular dynamics simulations provide a sample of a molecule's conformational space. Experiments on the mus time scale, resulting in large amounts of data, are nowadays routine. Data mining techniques such as classification provide a way to analyse such data. In this work, we evaluate and compare several classification algorithms using three data sets which resulted from computer simulations, of a potential enzyme mimetic biomolecule. We evaluated 65 classifiers available in the well-known data mining toolkit Weka, using 'classification' errors to assess algorithmic performance. Results suggest that: (i) 'meta' classifiers perform better than the other groups, when applied to molecular dynamics data sets; (ii) Random Forest and Rotation Forest are the best classifiers for all three data sets; and (iii) classification via clustering yields the highest classification error. Our findings are consistent with bibliographic evidence, suggesting a 'roadmap' for dealing with such data.

The Effects of Judgment-Based Stratum Classifications on the Efficiency of Stratum Scored CATs.

ERIC Educational Resources Information Center

Finney, Sara J.; Smith, Russell W.; Wise, Steven L.

Two operational item pools were used to investigate the performance of stratum computerized adaptive tests (CATs) when items were assigned to strata based on empirical estimates of item difficulty or human judgments of item difficulty. Items from the first data set consisted of 54 5-option multiple choice items from a form of the ACT mathematics…

Recognition memory reveals just how CONTRASTIVE contrastive accenting really is

PubMed Central

Fraundorf, Scott H.; Watson, Duane G.; Benjamin, Aaron S.

2010-01-01

The effects of pitch accenting on memory were investigated in three experiments. Participants listened to short recorded discourses that contained contrast sets with two items (e.g. British scientists and French scientists); a continuation specified one item from the set. Pitch accenting on the critical word in the continuation was manipulated between non-contrastive (H* in the ToBI system) and contrastive (L+H*). On subsequent recognition memory tests, the L+H* accent increased hits to correct statements and correct rejections of the contrast item (Experiments 1–3), but did not impair memory for other parts of the discourse (Experiment 2). L+H* also did not facilitate correct rejections of lures not in the contrast set (Experiment 3), indicating that contrastive accents do not simply strengthen the representation of the target item. These results suggest comprehenders use pitch accenting to encode and update information about multiple elements in a contrast set. PMID:20835405

Guidelines for the revision of practice data sets.

PubMed

Culpepper, L

1980-09-01

As residencies and practices mature, a frequent undertaking is the revision of initial data sets and information systems. This report presents an expanded data set which has been developed in the Family Medicine Residency Program at the University of Rochester and suggests guidelines for the selection of data items and revision of existing information systems. In the selection of data items it is important to carefully identify planned use and definition of terms, as well as to carefully consider the complexity of the items and the realistic ability of personnel to maintain and update both individual items and the entire set of data. The implementation of a revised data system requires careful planning and frequent involvement of staff to insure accurate collection of information and proper managment of workload. The implementation phase should not be considered complete until an ongoing system for reviewing and maintaining data is established.

Exploring Item Characteristics That Are Related to the Difficulty of TOEFL Dialogue Items. Research Reports. RR-79. RR-04-11

ERIC Educational Resources Information Center

Kostin, Irene

2004-01-01

The purpose of this study is to explore the relationship between a set of item characteristics and the difficulty of TOEFL[R] dialogue items. Identifying characteristics that are related to item difficulty has the potential to improve the efficiency of the item-writing process The study employed 365 TOEFL dialogue items, which were coded on 49…

Building an Evaluation Scale using Item Response Theory.

PubMed

Lalor, John P; Wu, Hao; Yu, Hong

2016-11-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.

Building an Evaluation Scale using Item Response Theory

PubMed Central

Lalor, John P.; Wu, Hao; Yu, Hong

2016-01-01

Evaluation of NLP methods requires testing against a previously vetted gold-standard test set and reporting standard metrics (accuracy/precision/recall/F1). The current assumption is that all items in a given test set are equal with regards to difficulty and discriminating power. We propose Item Response Theory (IRT) from psychometrics as an alternative means for gold-standard test-set generation and NLP system evaluation. IRT is able to describe characteristics of individual items - their difficulty and discriminating power - and can account for these characteristics in its estimation of human intelligence or ability for an NLP task. In this paper, we demonstrate IRT by generating a gold-standard test set for Recognizing Textual Entailment. By collecting a large number of human responses and fitting our IRT model, we show that our IRT model compares NLP systems with the performance in a human population and is able to provide more insight into system performance than standard evaluation metrics. We show that a high accuracy score does not always imply a high IRT score, which depends on the item characteristics and the response pattern.1 PMID:28004039

Using Set Covering with Item Sampling to Analyze the Infeasibility of Linear Programming Test Assembly Models

ERIC Educational Resources Information Center

Huitzing, Hiddo A.

2004-01-01

This article shows how set covering with item sampling (SCIS) methods can be used in the analysis and preanalysis of linear programming models for test assembly (LPTA). LPTA models can construct tests, fulfilling a set of constraints set by the test assembler. Sometimes, no solution to the LPTA model exists. The model is then said to be…

Measuring impairments of functioning and health in patients with axial spondyloarthritis by using the ASAS Health Index and the Environmental Item Set: translation and cross-cultural adaptation into 15 languages.

PubMed

Kiltz, U; van der Heijde, D; Boonen, A; Bautista-Molano, W; Burgos-Vargas, R; Chiowchanwisawakit, P; Duruoz, T; El-Zorkany, B; Essers, I; Gaydukova, I; Géher, P; Gossec, L; Grazio, S; Gu, J; Khan, M A; Kim, T J; Maksymowych, W P; Marzo-Ortega, H; Navarro-Compán, V; Olivieri, I; Patrikos, D; Pimentel-Santos, F M; Schirmer, M; van den Bosch, F; Weber, U; Zochling, J; Braun, J

2016-01-01

The Assessments of SpondyloArthritis international society Health Index (ASAS HI) measures functioning and health in patients with spondyloarthritis (SpA) across 17 aspects of health and 9 environmental factors (EF). The objective was to translate and adapt the original English version of the ASAS HI, including the EF Item Set, cross-culturally into 15 languages. Translation and cross-cultural adaptation has been carried out following the forward-backward procedure. In the cognitive debriefing, 10 patients/country across a broad spectrum of sociodemographic background, were included. The ASAS HI and the EF Item Set were translated into Arabic, Chinese, Croatian, Dutch, French, German, Greek, Hungarian, Italian, Korean, Portuguese, Russian, Spanish, Thai and Turkish. Some difficulties were experienced with translation of the contextual factors indicating that these concepts may be more culturally-dependent. A total of 215 patients with axial SpA across 23 countries (62.3% men, mean (SD) age 42.4 (13.9) years) participated in the field test. Cognitive debriefing showed that items of the ASAS HI and EF Item Set are clear, relevant and comprehensive. All versions were accepted with minor modifications with respect to item wording and response option. The wording of three items had to be adapted to improve clarity. As a result of cognitive debriefing, a new response option 'not applicable' was added to two items of the ASAS HI to improve appropriateness. This study showed that the items of the ASAS HI including the EFs were readily adaptable throughout all countries, indicating that the concepts covered were comprehensive, clear and meaningful in different cultures.

Measuring impairments of functioning and health in patients with axial spondyloarthritis by using the ASAS Health Index and the Environmental Item Set: translation and cross-cultural adaptation into 15 languages

PubMed Central

Kiltz, U; van der Heijde, D; Boonen, A; Bautista-Molano, W; Burgos-Vargas, R; Chiowchanwisawakit, P; Duruoz, T; El-Zorkany, B; Essers, I; Gaydukova, I; Géher, P; Gossec, L; Grazio, S; Gu, J; Khan, M A; Kim, T J; Maksymowych, W P; Marzo-Ortega, H; Navarro-Compán, V; Olivieri, I; Patrikos, D; Pimentel-Santos, F M; Schirmer, M; van den Bosch, F; Weber, U; Zochling, J; Braun, J

2016-01-01

Introduction The Assessments of SpondyloArthritis international society Health Index (ASAS HI) measures functioning and health in patients with spondyloarthritis (SpA) across 17 aspects of health and 9 environmental factors (EF). The objective was to translate and adapt the original English version of the ASAS HI, including the EF Item Set, cross-culturally into 15 languages. Methods Translation and cross-cultural adaptation has been carried out following the forward–backward procedure. In the cognitive debriefing, 10 patients/country across a broad spectrum of sociodemographic background, were included. Results The ASAS HI and the EF Item Set were translated into Arabic, Chinese, Croatian, Dutch, French, German, Greek, Hungarian, Italian, Korean, Portuguese, Russian, Spanish, Thai and Turkish. Some difficulties were experienced with translation of the contextual factors indicating that these concepts may be more culturally-dependent. A total of 215 patients with axial SpA across 23 countries (62.3% men, mean (SD) age 42.4 (13.9) years) participated in the field test. Cognitive debriefing showed that items of the ASAS HI and EF Item Set are clear, relevant and comprehensive. All versions were accepted with minor modifications with respect to item wording and response option. The wording of three items had to be adapted to improve clarity. As a result of cognitive debriefing, a new response option ‘not applicable’ was added to two items of the ASAS HI to improve appropriateness. Discussion This study showed that the items of the ASAS HI including the EFs were readily adaptable throughout all countries, indicating that the concepts covered were comprehensive, clear and meaningful in different cultures. PMID:27752358

Statistical Approaches to the Study of Item Difficulty.

ERIC Educational Resources Information Center

Olson, John F.; And Others

Traditionally, item difficulty has been defined in terms of the performance of examinees. For test development purposes, a more useful concept would be some kind of intrinsic item difficulty, defined in terms of the item's content, context, or characteristics and the task demands set by the item. In this investigation, the measurement literature…

Knowledge mining from clinical datasets using rough sets and backpropagation neural network.

PubMed

Nahato, Kindie Biredagn; Harichandran, Khanna Nehemiah; Arputharaj, Kannan

2015-01-01

The availability of clinical datasets and knowledge mining methodologies encourages the researchers to pursue research in extracting knowledge from clinical datasets. Different data mining techniques have been used for mining rules, and mathematical models have been developed to assist the clinician in decision making. The objective of this research is to build a classifier that will predict the presence or absence of a disease by learning from the minimal set of attributes that has been extracted from the clinical dataset. In this work rough set indiscernibility relation method with backpropagation neural network (RS-BPNN) is used. This work has two stages. The first stage is handling of missing values to obtain a smooth data set and selection of appropriate attributes from the clinical dataset by indiscernibility relation method. The second stage is classification using backpropagation neural network on the selected reducts of the dataset. The classifier has been tested with hepatitis, Wisconsin breast cancer, and Statlog heart disease datasets obtained from the University of California at Irvine (UCI) machine learning repository. The accuracy obtained from the proposed method is 97.3%, 98.6%, and 90.4% for hepatitis, breast cancer, and heart disease, respectively. The proposed system provides an effective classification model for clinical datasets.

Indicators of Family Care for Development for Use in Multicountry Surveys

PubMed Central

Kariger, Patricia; Engle, Patrice; Britto, Pia M. Rebello; Sywulka, Sara M.; Menon, Purnima

2012-01-01

Indicators of family care for development are essential for ascertaining whether families are providing their children with an environment that leads to positive developmental outcomes. This project aimed to develop indicators from a set of items, measuring family care practices and resources important for caregiving, for use in epidemiologic surveys in developing countries. A mixed method (quantitative and qualitative) design was used for item selection and evaluation. Qualitative and quantitative analyses were conducted to examine the validity of candidate items in several country samples. Qualitative methods included the use of global expert panels to identify and evaluate the performance of each candidate item as well as in-country focus groups to test the content validity of the items. The quantitative methods included analyses of item-response distributions, using bivariate techniques. The selected items measured two family care practices (support for learning/stimulating environment and limit-setting techniques) and caregiving resources (adequacy of the alternate caregiver when the mother worked). Six play-activity items, indicative of support for learning/stimulating environment, were included in the core module of UNICEF's Multiple Cluster Indictor Survey 3. The other items were included in optional modules. This project provided, for the first time, a globally-relevant set of items for assessing family care practices and resources in epidemiological surveys. These items have multiple uses, including national monitoring and cross-country comparisons of the status of family care for development used globally. The obtained information will reinforce attention to efforts to improve the support for development of children. PMID:23304914

Software tool for data mining and its applications

NASA Astrophysics Data System (ADS)

Yang, Jie; Ye, Chenzhou; Chen, Nianyi

2002-03-01

A software tool for data mining is introduced, which integrates pattern recognition (PCA, Fisher, clustering, hyperenvelop, regression), artificial intelligence (knowledge representation, decision trees), statistical learning (rough set, support vector machine), computational intelligence (neural network, genetic algorithm, fuzzy systems). It consists of nine function models: pattern recognition, decision trees, association rule, fuzzy rule, neural network, genetic algorithm, Hyper Envelop, support vector machine, visualization. The principle and knowledge representation of some function models of data mining are described. The software tool of data mining is realized by Visual C++ under Windows 2000. Nonmonotony in data mining is dealt with by concept hierarchy and layered mining. The software tool of data mining has satisfactorily applied in the prediction of regularities of the formation of ternary intermetallic compounds in alloy systems, and diagnosis of brain glioma.

Long-Term Changes In The Shallow Water Table In A Mining Area: The Lubin-Glogow Copper Region, Southwestern Poland

NASA Astrophysics Data System (ADS)

Bochenska, T.; Limisiewicz, P.; Loprawski, L.

1995-03-01

In regions of intense mining, shortages of water are common. Increased water demand is normally associated with industry in mining areas, and mine unwatering has negative effects on the natural groundwater balance. The study area occupies 3,300 square kilometers within the copper mining region of Lubin-Glogow, southwestern Poland. Pumping of groundwater to drain mines has created a cone of depression that underlies 2,500 square kilometers. The lowering of potentiometric surfaces has occurred in deep aquifers, which are isolated from the surface by thick confining units (loams and clays). Changes of hydraulic head in the shallow aquifer have not previously been observed. In this study, the authors analyzed the water-table changes in the shallow aquifer. The statistical analysis of the water table was based on two sets of water-level measurements in about 1,200 farm wells during dry seasons. The first set was done in the fall of 1986, the second in the fall of 1991. In addition to these measurements, multi-seasonal observations were made by the mining survey in several tens of wells. During five years, the head declined an average of 0.4 meter. Locally, the lowering was as great as five meters. The regional decline of head resulted in a loss of water resources about 2×108 cubic meters. Regionally, this loss is not directly related to the dewatering of copper mines. Locally, however, mining activity strongly influences the water table. The general trend of the decline is probably an effect of decreasing precipitation.

Sustainable gold mining management waste policy in Romania

NASA Astrophysics Data System (ADS)

Tudor, Elena; Filipciuc, Constantina

2016-04-01

Sustainable mining practices and consistent implementation of the mining for the closure planning approach, within an improved legislative framework, create conditions for the development of creative, profitable, environmentally-sound and socially-responsible management and reuse of mine lands. According to the World Commission on Environment and Development definition, sustainable development is the type of development that meets the needs of the present without compromising the ability of future generations to meet their own needs. Romania has the largest gold reserves in Europe (760 million tons of gold-silver ores, of which 40 million tons in 68 gold deposits in the Apuseni Mountains. New mining projects draw particular attention regarding the environmental risks they cause. Rehabilitation is an ongoing consideration throughout the mine's lifecycle, both from a technical and a financial standpoint. The costs of land rehabilitation are classified as the mine's operating costs. According to Directive 2004/35/EC on environmental liability, the prevention and remedying of environmental damage should be implemented by applying the "polluter pays" principle, in line with the principle of sustainable development. Directive on the management of waste from extractive industries and amending Directive obliges operators to provide (and periodically adjust in size) a financial guarantee for waste facility maintenance and post-closure site restoration, including land rehabilitation. According to the Romanian Mining Law, the license holder has the following obligations related to land use and protection: to provide environmental agreements as one of the prerequisites for a building permit; to regularly update the mine closure plan; to set up and maintain the financial guarantee for environmental rehabilitation; and to execute and finalize the environmental rehabilitation of affected land in the mining site, according to the mine closure plan, including the post-closure monitoring program implementation and financing. Apart from the Mining Law, the Government Decision, which transposes EU Directive on the management of waste from extractive industries, as well as Government Emergency Ordinance, which implements the requirements of EU Directive 2004/35/CE on environmental liability, requests financial guarantees for waste facilities maintenance and for environment restoration in the case of pollution, respectively. In practice, there are problems in the calculation of the financial guarantee and the development of financial security instruments and markets as required by Directive, due to the lack of expertise in financial, economic and liability matters. Mining companies are usually not required to set up a special guarantee for the waste facilities, but only to set up and maintain the financial guarantee regulated under the Mining Law. Romania - because of the structure of its mining sector - has serious environmental legacies, a lack of funds for their restoration and the need to strengthen the administrative capacity in this area, as well as the important tasks on harmonization and/or implementation of the EU mining waste legislation. This work is presented within the framework of SUSMIN project. Key words : sustainable development, waste management, policy

Children's reasoning about gender-atypical preferences in different settings.

PubMed

Conry-Murray, Clare

2013-05-01

Two age groups of children, 5- and 6-year-olds (n=30) and 8- and 9-year-olds (n=26), made judgments about which of two items a character should choose: a gender-typical item or a gender-atypical item that was preferred by the character. Judgments were made about situations where the character was (a) in a familiar public setting and (b) in a country where the reversed preference was typical for that culture. At both ages and in both settings, a majority of responses endorsed the character's atypical preference. However, at both ages, endorsements of the atypical preferences were significantly less frequent in the familiar public setting that in the norm-reversed setting, and justifications indicated that there would be social consequences for defying gender norms in the familiar setting. Copyright © 2012 Elsevier Inc. All rights reserved.

Data mining in soft computing framework: a survey.

PubMed

Mitra, S; Pal, S K; Mitra, P

2002-01-01

The present article provides a survey of the available literature on data mining using soft computing. A categorization has been provided based on the different soft computing tools and their hybridizations used, the data mining function implemented, and the preference criterion selected by the model. The utility of the different soft computing methodologies is highlighted. Generally fuzzy sets are suitable for handling the issues related to understandability of patterns, incomplete/noisy data, mixed media information and human interaction, and can provide approximate solutions faster. Neural networks are nonparametric, robust, and exhibit good learning and generalization capabilities in data-rich environments. Genetic algorithms provide efficient search algorithms to select a model, from mixed media data, based on some preference criterion/objective function. Rough sets are suitable for handling different types of uncertainty in data. Some challenges to data mining and the application of soft computing methodologies are indicated. An extensive bibliography is also included.

Study on Mine Emergency Mechanism based on TARP and ICS

NASA Astrophysics Data System (ADS)

Xi, Jian; Wu, Zongzhi

2018-01-01

By analyzing the experiences and practices of mine emergency in China and abroad, especially the United States and Australia, normative principle, risk management principle and adaptability principle of constructing mine emergency mechanism based on Trigger Action Response Plans (TARP) and Incident Command System (ICS) are summarized. Classification method, framework, flow and subject of TARP and ICS which are suitable for the actual situation of domestic mine emergency are proposed. The system dynamics model of TARP and ICS is established. The parameters such as evacuation ratio, response rate, per capita emergency capability and entry rate of rescuers are set up. By simulating the operation process of TARP and ICS, the impact of these parameters on the emergency process are analyzed, which could provide a reference and basis for building emergency capacity, formulating emergency plans and setting up action plans in the emergency process.

Audio Adapted Assessment Data: Does the Addition of Audio to Written Items Modify the Item Calibration?

ERIC Educational Resources Information Center

Snyder, James

2010-01-01

This dissertation research examined the changes in item RIT calibration that occurred when adding audio to a set of currently calibrated RIT items and then placing these new items as field test items in the modified assessments on the NWEA MAP test platform. The researcher used test results from over 600 students in the Poway School District in…

Combining item response theory with multiple imputation to equate health assessment questionnaires.

PubMed

Gu, Chenyang; Gutman, Roee

2017-09-01

The assessment of patients' functional status across the continuum of care requires a common patient assessment tool. However, assessment tools that are used in various health care settings differ and cannot be easily contrasted. For example, the Functional Independence Measure (FIM) is used to evaluate the functional status of patients who stay in inpatient rehabilitation facilities, the Minimum Data Set (MDS) is collected for all patients who stay in skilled nursing facilities, and the Outcome and Assessment Information Set (OASIS) is collected if they choose home health care provided by home health agencies. All three instruments or questionnaires include functional status items, but the specific items, rating scales, and instructions for scoring different activities vary between the different settings. We consider equating different health assessment questionnaires as a missing data problem, and propose a variant of predictive mean matching method that relies on Item Response Theory (IRT) models to impute unmeasured item responses. Using real data sets, we simulated missing measurements and compared our proposed approach to existing methods for missing data imputation. We show that, for all of the estimands considered, and in most of the experimental conditions that were examined, the proposed approach provides valid inferences, and generally has better coverages, relatively smaller biases, and shorter interval estimates. The proposed method is further illustrated using a real data set. © 2016, The International Biometric Society.

Consistency of Angoff-Based Standard-Setting Judgments: Are Item Judgments and Passing Scores Replicable across Different Panels of Experts?

ERIC Educational Resources Information Center

Tannenbaum, Richard J.; Kannan, Priya

2015-01-01

Angoff-based standard setting is widely used, especially for high-stakes licensure assessments. Nonetheless, some critics have claimed that the judgment task is too cognitively complex for panelists, whereas others have explicitly challenged the consistency in (replicability of) standard-setting outcomes. Evidence of consistency in item judgments…

Reliability of the Client-Centeredness of Goal Setting (C-COGS) Scale in Acquired Brain Injury Rehabilitation.

PubMed

Doig, Emmah; Prescott, Sarah; Fleming, Jennifer; Cornwell, Petrea; Kuipers, Pim

2016-01-01

To examine the internal reliability and test-retest reliability of the Client-Centeredness of Goal Setting (C-COGS) scale. The C-COGS scale was administered to 42 participants with acquired brain injury after completion of multidisciplinary goal planning. Internal reliability of scale items was examined using item-partial total correlations and Cronbach's α coefficient. The scale was readministered within a 1-mo period to a subsample of 12 participants to examine test-retest reliability by calculating exact and close percentage agreement for each item. After examination of item-partial total correlations, test items were revised. The revised items demonstrated stronger internal consistency than the original items. Preliminary evaluation of test-retest reliability was fair, with an average exact percent agreement across all test items of 67%. Findings support the preliminary reliability of the C-COGS scale as a tool to evaluate and promote client-centered goal planning in brain injury rehabilitation. Copyright © 2016 by the American Occupational Therapy Association, Inc.

Have infant gross motor abilities changed in 20 years? A re-evaluation of the Alberta Infant Motor Scale normative values.

PubMed

Darrah, Johanna; Bartlett, Doreen; Maguire, Thomas O; Avison, William R; Lacaze-Masmonteil, Thierry

2014-09-01

To compare the original normative data of the Alberta Infant Motor Scale (AIMS) (n=2202) collected 20 years ago with a contemporary sample of Canadian infants. This was a cross-sectional cohort study of 650 Canadian infants (338 males, 312 females; mean age 30.9 wks [SD 15.5], range 2 wks-18 mo) assessed once on the AIMS. Assessments were stratified by age, and infants proportionally represented the ethnic diversity of Canada. Logistic regression was used to place AIMS items on an age scale representing the age at which 50% of the infants passed an item on the contemporary data set and the original data set. Forty-three items met the criterion for stable regression results in both data sets. The correlation coefficient between the age locations of items on the original and contemporary data sets was 0.99. The mean age difference between item locations was 0.7 weeks. Age values from the original data set when converted to the contemporary scale differed by less than 1 week. The sequence and age at emergence of AIMS items has remained similar over 20 years and current normative values remain valid. Concern that the 'back to sleep' campaign has influenced the age at emergence of gross motor abilities is not supported. © 2014 The Authors. Developmental Medicine & Child Neurology published by John Wiley & Sons Ltd on behalf of Mac Keith Press.

Assembling a Computerized Adaptive Testing Item Pool as a Set of Linear Tests

ERIC Educational Resources Information Center

van der Linden, Wim J.; Ariel, Adelaide; Veldkamp, Bernard P.

2006-01-01

Test-item writing efforts typically results in item pools with an undesirable correlational structure between the content attributes of the items and their statistical information. If such pools are used in computerized adaptive testing (CAT), the algorithm may be forced to select items with less than optimal information, that violate the content…

The Licensing of Negative Sensitive Items in Jordanian Arabic

ERIC Educational Resources Information Center

Alsarayreh, Atef

2012-01-01

This study investigates the licensing conditions on Negative Sensitive Items (NSIs) in Jordanian Arabic (JA). JA exhibits both types of NSIs that are discussed in the literature: Negative Polarity Items (NPIs) and Negative Concord Items (NCIs). Although these two sets of items seem to form a natural class in the sense that they show certain…

Utilizing Response Time Distributions for Item Selection in CAT

ERIC Educational Resources Information Center

Fan, Zhewen; Wang, Chun; Chang, Hua-Hua; Douglas, Jeffrey

2012-01-01

Traditional methods for item selection in computerized adaptive testing only focus on item information without taking into consideration the time required to answer an item. As a result, some examinees may receive a set of items that take a very long time to finish, and information is not accrued as efficiently as possible. The authors propose two…

Pretest and refinement of items for alcohol highway safety surveys

DOT National Transportation Integrated Search

1984-05-30

This study summarizes the procedures employed in pre-testing a set of alcohol-highway safety questionnaire items. The procedures included conducting a set of focus groups and a series of telephone interviews on several forms of the questionnaires. Th...

The Utrecht questionnaire (U-CEP) measuring knowledge on clinical epidemiology proved to be valid.

PubMed

Kortekaas, Marlous F; Bartelink, Marie-Louise E L; de Groot, Esther; Korving, Helen; de Wit, Niek J; Grobbee, Diederick E; Hoes, Arno W

2017-02-01

Knowledge on clinical epidemiology is crucial to practice evidence-based medicine. We describe the development and validation of the Utrecht questionnaire on knowledge on Clinical epidemiology for Evidence-based Practice (U-CEP); an assessment tool to be used in the training of clinicians. The U-CEP was developed in two formats: two sets of 25 questions and a combined set of 50. The validation was performed among postgraduate general practice (GP) trainees, hospital trainees, GP supervisors, and experts. Internal consistency, internal reliability (item-total correlation), item discrimination index, item difficulty, content validity, construct validity, responsiveness, test-retest reliability, and feasibility were assessed. The questionnaire was externally validated. Internal consistency was good with a Cronbach alpha of 0.8. The median item-total correlation and mean item discrimination index were satisfactory. Both sets were perceived as relevant to clinical practice. Construct validity was good. Both sets were responsive but failed on test-retest reliability. One set took 24 minutes and the other 33 minutes to complete, on average. External GP trainees had comparable results. The U-CEP is a valid questionnaire to assess knowledge on clinical epidemiology, which is a prerequisite for practicing evidence-based medicine in daily clinical practice. Copyright © 2016 Elsevier Inc. All rights reserved.

Environmental and genetic factors that contribute to Escherichia coli K-12 biofilm formation

PubMed Central

Prüß, Birgit M.; Verma, Karan; Samanta, Priyankar; Sule, Preeti; Kumar, Sunil; Wu, Jianfei; Christianson, David; Horne, Shelley M.; Stafslien, Shane J.; Wolfe, Alan J.; Denton, Anne

2010-01-01

Biofilms are communities of bacteria whose formation on surfaces requires a large portion of the bacteria’s transcriptional network. To identify environmental conditions and transcriptional regulators that contribute to sensing these conditions, we used a high-throughput approach to monitor biofilm biomass produced by an isogenic set of Escherichia coli K-12 strains grown under combinations of environmental conditions. Of the environmental combinationsd, growth in tryptic soy broth at 37°C supported the most biofilm production. To analyze the complex relationships between the diverse cell surface organelles, transcriptional regulators, and metabolic enzymes represented by the tested mutant set, we used a novel vector-item pattern-mining algorithm. The algorithm related biofilm amounts to the functional annotations of each mutated protein. The pattern with the best statistical significance was the gene ontology ‘pyruvate catabolic process,’ which is associated with enzymes of acetate metabolism. Phenotype microarray experiments illustrated that carbon sources that are metabolized to acetyl-coenzyme A, acetyl phosphate, and acetate are particularly supportive of biofilm formation. Scanning electron microscopy revealed structural differences between mutants that lack acetate metabolism enzymes and their parent and confirmed the quantitative differences. We conclude that acetate metabolism functions as a metabolic sensor, transmitting changes in environmental conditions to biofilm biomass and structure. PMID:20559621

A prototype system based on visual interactive SDM called VGC

NASA Astrophysics Data System (ADS)

Jia, Zelu; Liu, Yaolin; Liu, Yanfang

2009-10-01

In many application domains, data is collected and referenced by its geo-spatial location. Spatial data mining, or the discovery of interesting patterns in such databases, is an important capability in the development of database systems. Spatial data mining recently emerges from a number of real applications, such as real-estate marketing, urban planning, weather forecasting, medical image analysis, road traffic accident analysis, etc. It demands for efficient solutions for many new, expensive, and complicated problems. For spatial data mining of large data sets to be effective, it is also important to include humans in the data exploration process and combine their flexibility, creativity, and general knowledge with the enormous storage capacity and computational power of today's computers. Visual spatial data mining applies human visual perception to the exploration of large data sets. Presenting data in an interactive, graphical form often fosters new insights, encouraging the information and validation of new hypotheses to the end of better problem-solving and gaining deeper domain knowledge. In this paper a visual interactive spatial data mining prototype system (visual geo-classify) based on VC++6.0 and MapObject2.0 are designed and developed, the basic algorithms of the spatial data mining is used decision tree and Bayesian networks, and data classify are used training and learning and the integration of the two to realize. The result indicates it's a practical and extensible visual interactive spatial data mining tool.

Issues of Exploitation of Induction Motors in the Course of Underground Mining Operations

NASA Astrophysics Data System (ADS)

Gumula, Stanisław; Hudy, Wiktor; Piaskowska-Silarska, Malgorzata; Pytel, Krzysztof

2017-09-01

Mining industry is one of the most important customers of electric motors. The most commonly used in the contemporary mining industry is alternating current machines used for processing electrical energy into mechanical energy. The operating problems and the influence of qualitative interference acting on the inputs of individual regulators to field-oriented system in the course of underground mining operations has been presented in the publication. The object of controlling the speed is a slip-ring induction motor. Settings of regulators were calculated using an evolutionary algorithm. Examination of system dynamics was performed by a computer with the use of the MATLAB / Simulink software. According to analyzes, large distortion of input signals of regulators adversely affects the rotational speed that pursued by the control system, which may cause a large vibration of the whole system and, consequently, its much faster destruction. Designed system is characterized by a significantly better resistance to interference. The system is stable with the properly selected settings of regulators, which is particularly important during the operation of machinery used in underground mining.

A data mining based approach to predict spatiotemporal changes in satellite images

NASA Astrophysics Data System (ADS)

Boulila, W.; Farah, I. R.; Ettabaa, K. Saheb; Solaiman, B.; Ghézala, H. Ben

2011-06-01

The interpretation of remotely sensed images in a spatiotemporal context is becoming a valuable research topic. However, the constant growth of data volume in remote sensing imaging makes reaching conclusions based on collected data a challenging task. Recently, data mining appears to be a promising research field leading to several interesting discoveries in various areas such as marketing, surveillance, fraud detection and scientific discovery. By integrating data mining and image interpretation techniques, accurate and relevant information (i.e. functional relation between observed parcels and a set of informational contents) can be automatically elicited. This study presents a new approach to predict spatiotemporal changes in satellite image databases. The proposed method exploits fuzzy sets and data mining concepts to build predictions and decisions for several remote sensing fields. It takes into account imperfections related to the spatiotemporal mining process in order to provide more accurate and reliable information about land cover changes in satellite images. The proposed approach is validated using SPOT images representing the Saint-Denis region, capital of Reunion Island. Results show good performances of the proposed framework in predicting change for the urban zone.

The association rules search of Indonesian university graduate’s data using FP-growth algorithm

NASA Astrophysics Data System (ADS)

Faza, S.; Rahmat, R. F.; Nababan, E. B.; Arisandi, D.; Effendi, S.

2018-02-01

The attribute varieties in university graduates data have caused frustrations to the institution in finding the combinations of attributes that often emerge and have high integration between attributes. Association rules mining is a data mining technique to determine the integration of the data or the way of a data set affects another set of data. By way of explanation, there are possibilities in finding the integration of data on a large scale. Frequent Pattern-Growth (FP-Growth) algorithm is one of the association rules mining technique to determine a frequent itemset in an FP-Tree data set. From the research on the search of university graduate’s association rules, it can be concluded that the most common attributes that have high integration between them are in the combination of State-owned High School outside Medan, regular university entrance exam, GPA of 3.00 to 3.49 and over 4-year-long study duration.

Text Mining for Neuroscience

NASA Astrophysics Data System (ADS)

Tirupattur, Naveen; Lapish, Christopher C.; Mukhopadhyay, Snehasis

2011-06-01

Text mining, sometimes alternately referred to as text analytics, refers to the process of extracting high-quality knowledge from the analysis of textual data. Text mining has wide variety of applications in areas such as biomedical science, news analysis, and homeland security. In this paper, we describe an approach and some relatively small-scale experiments which apply text mining to neuroscience research literature to find novel associations among a diverse set of entities. Neuroscience is a discipline which encompasses an exceptionally wide range of experimental approaches and rapidly growing interest. This combination results in an overwhelmingly large and often diffuse literature which makes a comprehensive synthesis difficult. Understanding the relations or associations among the entities appearing in the literature not only improves the researchers current understanding of recent advances in their field, but also provides an important computational tool to formulate novel hypotheses and thereby assist in scientific discoveries. We describe a methodology to automatically mine the literature and form novel associations through direct analysis of published texts. The method first retrieves a set of documents from databases such as PubMed using a set of relevant domain terms. In the current study these terms yielded a set of documents ranging from 160,909 to 367,214 documents. Each document is then represented in a numerical vector form from which an Association Graph is computed which represents relationships between all pairs of domain terms, based on co-occurrence. Association graphs can then be subjected to various graph theoretic algorithms such as transitive closure and cycle (circuit) detection to derive additional information, and can also be visually presented to a human researcher for understanding. In this paper, we present three relatively small-scale problem-specific case studies to demonstrate that such an approach is very successful in replicating a neuroscience expert's mental model of object-object associations entirely by means of text mining. These preliminary results provide the confidence that this type of text mining based research approach provides an extremely powerful tool to better understand the literature and drive novel discovery for the neuroscience community.

Mixed-Format Test Score Equating: Effect of Item-Type Multidimensionality, Length and Composition of Common-Item Set, and Group Ability Difference

ERIC Educational Resources Information Center

Wang, Wei

2013-01-01

Mixed-format tests containing both multiple-choice (MC) items and constructed-response (CR) items are now widely used in many testing programs. Mixed-format tests often are considered to be superior to tests containing only MC items although the use of multiple item formats leads to measurement challenges in the context of equating conducted under…

Natural Language Processing Of Online Propaganda As A Means Of Passively Monitoring An Adversarial Ideology

DTIC Science & Technology

2017-03-01

Warfare. 14. SUBJECT TERMS data mining, natural language processing, machine learning, algorithm design , information warfare, propaganda 15. NUMBER OF...Speech Tags. Adapted from [12]. CC Coordinating conjunction PRP$ Possessive pronoun CD Cardinal number RB Adverb DT Determiner RBR Adverb, comparative ... comparative UH Interjection JJS Adjective, superlative VB Verb, base form LS List item marker VBD Verb, past tense MD Modal VBG Verb, gerund or

Have a little faith: measuring the impact of illness on positive and negative aspects of faith.

PubMed

Salsman, John M; Garcia, Sofia F; Lai, Jin-Shei; Cella, David

2012-12-01

The importance of faith and its associations with health are well documented. As part of the Patient Reported Outcomes Measurement Information System, items tapping positive and negative impact of illness (PII and NII) were developed across four content domains: Coping/Stress Response, Self-Concept, Social Connection/Isolation, and Meaning and Spirituality. Faith items were included within the concept of meaning and spirituality. This measurement model was tested on a heterogeneous group of 509 cancer survivors. To evaluate dimensionality, we applied two bi-factor models, specifying a general factor (PII or NII) and four local factors: Coping/Stress Response, Self-Concept, Social Connection/Isolation, and Meaning and Spirituality. Bi-factor analysis supported sufficient unidimensionality within PII and NII item sets. The unidimensionality of both PII and NII item sets was enhanced by extraction of the faith items from the rest of the questions. Of the 10 faith items, nine demonstrated higher local than general factor loadings (range for local factor loadings = 0.402 to 0.876), suggesting utility as a separate but related 'faith' factor. The same was true for only two of the remaining 63 items across the PII and NII item sets. Although conceptually and to a degree empirically related to Meaning and Spirituality, Faith appears to be a distinct subdomain of PII and NII, better handled by distinct assessment. A 10-item measure of the impact of illness upon faith (II-Faith) was therefore assembled. Copyright © 2011 John Wiley & Sons, Ltd.

Monitoring strip mining and reclamation with LANDSAT data in Belmont County, Ohio

NASA Technical Reports Server (NTRS)

Witt, R. G.; Schaal, G. M.; Bly, B. G.

1983-01-01

The utility of LANDSAT digital data for mapping and monitoring surface mines in Belmont County, Ohio was investigated. Two data sets from 1976 and 1979 were processed to classify level 1 land covers and three strip mine categories in order to examine change over time and assess reclamation efforts. The two classifications were compared with aerial photographs. Results of the accuracy assessment show that both classifications are approximately 86 per cent correct, and that surface mine change detection (date-to-date comparison) is facilitated by the digital format of LANDSAT data.

Application and Exploration of Big Data Mining in Clinical Medicine.

PubMed

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-03-20

To review theories and technologies of big data mining and their application in clinical medicine. Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster-Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Big data mining has the potential to play an important role in clinical medicine.

Lunar surface mine feasibility study

NASA Astrophysics Data System (ADS)

Blair, Brad R.

This paper describes a lunar surface mine, and demonstrates the economic feasibility of mining oxygen from the moon. The mine will be at the Apollo 16 landing site. Mine design issues include pit size and shape, excavation equipment, muck transport, and processing requirements. The final mine design will be driven by production requirements, and constrained by the lunar environment. This mining scenario assumes the presence of an operating lunar base. Lunar base personnel will set-up a and run the mine. The goal of producing lunar oxygen is to reduce dependence on fuel shipped from Earth. Thus, the lunar base is the customer for the finished product. The perspective of this paper is that of a mining contractor who must produce a specific product at a remote location, pay local labor, and sell the product to an onsite captive market. To make a profit, it must be less costly to build and ship specialized equipment to the site, and pay high labor and operating costs, than to export the product directly to the site.

Risky Business: Factor Analysis of Survey Data – Assessing the Probability of Incorrect Dimensionalisation

PubMed Central

van der Eijk, Cees; Rose, Jonathan

2015-01-01

This paper undertakes a systematic assessment of the extent to which factor analysis the correct number of latent dimensions (factors) when applied to ordered-categorical survey items (so-called Likert items). We simulate 2400 data sets of uni-dimensional Likert items that vary systematically over a range of conditions such as the underlying population distribution, the number of items, the level of random error, and characteristics of items and item-sets. Each of these datasets is factor analysed in a variety of ways that are frequently used in the extant literature, or that are recommended in current methodological texts. These include exploratory factor retention heuristics such as Kaiser’s criterion, Parallel Analysis and a non-graphical scree test, and (for exploratory and confirmatory analyses) evaluations of model fit. These analyses are conducted on the basis of Pearson and polychoric correlations. We find that, irrespective of the particular mode of analysis, factor analysis applied to ordered-categorical survey data very often leads to over-dimensionalisation. The magnitude of this risk depends on the specific way in which factor analysis is conducted, the number of items, the properties of the set of items, and the underlying population distribution. The paper concludes with a discussion of the consequences of over-dimensionalisation, and a brief mention of alternative modes of analysis that are much less prone to such problems. PMID:25789992

Dual representation of item positions in verbal short-term memory: Evidence for two access modes.

PubMed

Lange, Elke B; Verhaeghen, Paul; Cerella, John

Memory sets of N = 1~5 digits were exposed sequentially from left-to-right across the screen, followed by N recognition probes. Probes had to be compared to memory list items on identity only (Sternberg task) or conditional on list position. Positions were probed randomly or in left-to-right order. Search functions related probe response times to set size. Random probing led to ramped, "Sternbergian" functions whose intercepts were elevated by the location requirement. Sequential probing led to flat search functions-fast responses unaffected by set size. These results suggested that items in STM could be accessed either by a slow search-on-identity followed by recovery of an associated location tag, or in a single step by following item-to-item links in study order. It is argued that this dual coding of location information occurs spontaneously at study, and that either code can be utilised at retrieval depending on test demands.

Revising the Lubben Social Network Scale for use in residential long-term care settings.

PubMed

Munn, Jean; Radey, Melissa; Brown, Kristin; Kim, Hyejin

2018-04-19

We revised the Lubben Social Network Scale (LSNS) to develop a measure of social support specific to residential long-term care (LTC) settings, the LSNS-LTC with five domains (i.e., family, friends, residents, volunteers, and staff). The authors modified the LSNS-18 to capture sources of social support specific to LTC, specifically relationships with residents, volunteers, and staff. We piloted the resultant 28-item measure with 64 LTC residents. Fifty-four respondents provided adequate information for analyses that included descriptive statistics and reliability coefficients. Twenty of the items performed well (had correlations >0.3, overall α = 0.85) and were retained. Three items required modification. The five items related to volunteers were eliminated due to extensive (>15%) missing data resulting in a proposed 23-item measure. We identified, and to some degree quantified, supportive relationships within the LTC environment, while developing a self-report tool to measure social support in these settings.

Confidence Bounds and Power for the Reliability of Observational Measures on the Quality of a Social Setting

ERIC Educational Resources Information Center

Shin, Yongyun; Raudenbush, Stephen W.

2012-01-01

Social scientists are frequently interested in assessing the qualities of social settings such as classrooms, schools, neighborhoods, or day care centers. The most common procedure requires observers to rate social interactions within these settings on multiple items and then to combine the item responses to obtain a summary measure of setting…

Evaluating Common Item Block Options When Faced with Practical Constraints

ERIC Educational Resources Information Center

Wolkowitz, Amanda; Davis-Becker, Susan

2015-01-01

This study evaluates the impact of common item characteristics on the outcome of equating in credentialing examinations when traditionally recommended representation is not possible. This research used real data sets from several credentialing exams to test the impact of content representation, item statistics, and number of common items on…

Automatic Item Generation of Probability Word Problems

ERIC Educational Resources Information Center

Holling, Heinz; Bertling, Jonas P.; Zeuch, Nina

2009-01-01

Mathematical word problems represent a common item format for assessing student competencies. Automatic item generation (AIG) is an effective way of constructing many items with predictable difficulties, based on a set of predefined task parameters. The current study presents a framework for the automatic generation of probability word problems…

Computerized Numerical Control Test Item Bank.

ERIC Educational Resources Information Center

Reneau, Fred; And Others

This guide contains 285 test items for use in teaching a course in computerized numerical control. All test items were reviewed, revised, and validated by incumbent workers and subject matter instructors. Items are provided for assessing student achievement in such aspects of programming and planning, setting up, and operating machines with…

The Effects of Test Length and Sample Size on Item Parameters in Item Response Theory

ERIC Educational Resources Information Center

Sahin, Alper; Anil, Duygu

2017-01-01

This study investigates the effects of sample size and test length on item-parameter estimation in test development utilizing three unidimensional dichotomous models of item response theory (IRT). For this purpose, a real language test comprised of 50 items was administered to 6,288 students. Data from this test was used to obtain data sets of…

Investigating Separate and Concurrent Approaches for Item Parameter Drift in 3PL Item Response Theory Equating

ERIC Educational Resources Information Center

Arce-Ferrer, Alvaro J.; Bulut, Okan

2017-01-01

This study examines separate and concurrent approaches to combine the detection of item parameter drift (IPD) and the estimation of scale transformation coefficients in the context of the common item nonequivalent groups design with the three-parameter item response theory equating. The study uses real and synthetic data sets to compare the two…

Knowledge Discovery and Data Mining: An Overview

NASA Technical Reports Server (NTRS)

Fayyad, U.

1995-01-01

The process of knowledge discovery and data mining is the process of information extraction from very large databases. Its importance is described along with several techniques and considerations for selecting the most appropriate technique for extracting information from a particular data set.

Report of investigation on underground limestone mines in the Ohio region. [Jonathan Mine, Alpha Portland Cement Mine, and Lewisburg Mine

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

Byerly, D.W.

1976-06-01

The following is a report of investigation on the geologic setting of several underground limestone mines in Ohio other than the PPG mine at Barberton, Ohio. Due to the element of available time, the writer is only able to deliver a brief synopsis of the geology of three sites visited. These three sites and the Barberton, Ohio site are the only underground limestone mines in Ohio to the best of the writer's knowledge. The sites visited include: (1) the Jonathan Mine located near Zanesville, Ohio, and currently operated by the Columbia Cement Corporation; (2) the abandoned Alpha Portland Cement Minemore » located near Ironton, Ohio; and (3) the Lewisburg Mine located at Lewisburg, Ohio, and currently being utilized as an underground storage facility. Other remaining possibilities where limestone is being mined underground are located in middle Ordovician strata near Carntown and Maysville, Kentucky. These are drift mines into a thick sequence of carbonates. The writer predicts, however, that these mines would have some problems with water due to the preponderance of carbonate rocks and the proximity of the mines to the Ohio River. None of the sites visited nor the sites in Kentucky have conditions comparable to the deep mine at Barberton, Ohio.« less

System and method for generating a relationship network

DOEpatents

Franks, Kasian; Myers, Cornelia A; Podowski, Raf M

2015-05-05

A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

System and method for generating a relationship network

DOEpatents

Franks, Kasian [Kensington, CA; Myers, Cornelia A [St. Louis, MO; Podowski, Raf M [Pleasant Hill, CA

2011-07-26

A computer-implemented system and process for generating a relationship network is disclosed. The system provides a set of data items to be related and generates variable length data vectors to represent the relationships between the terms within each data item. The system can be used to generate a relationship network for documents, images, or any other type of file. This relationship network can then be queried to discover the relationships between terms within the set of data items.

Data Mining of Extremely Large Ad-Hoc Data Sets to Produce Reverse Web-Link Graphs

DTIC Science & Technology

2017-03-01

in most of the MR cases. From these studies , we also learned that computing -optimized instances should be chosen for serialized/compressed input data...maximum 200 words) Data mining can be a valuable tool, particularly in the acquisition of military intelligence. As the second study within a larger Naval...open web crawler data set Common Crawl. Similar to previous studies , this research employs MapReduce (MR) for sorting and categorizing output value

Development and initial evaluation of the SCI-FI/AT

PubMed Central

Jette, Alan M.; Slavin, Mary D.; Ni, Pengsheng; Kisala, Pamela A.; Tulsky, David S.; Heinemann, Allen W.; Charlifue, Susie; Tate, Denise G.; Fyffe, Denise; Morse, Leslie; Marino, Ralph; Smith, Ian; Williams, Steve

2015-01-01

Objectives To describe the domain structure and calibration of the Spinal Cord Injury Functional Index for samples using Assistive Technology (SCI-FI/AT) and report the initial psychometric properties of each domain. Design Cross sectional survey followed by computerized adaptive test (CAT) simulations. Setting Inpatient and community settings. Participants A sample of 460 adults with traumatic spinal cord injury (SCI) stratified by level of injury, completeness of injury, and time since injury. Interventions None Main outcome measure SCI-FI/AT Results Confirmatory factor analysis (CFA) and Item response theory (IRT) analyses identified 4 unidimensional SCI-FI/AT domains: Basic Mobility (41 items) Self-care (71 items), Fine Motor Function (35 items), and Ambulation (29 items). High correlations of full item banks with 10-item simulated CATs indicated high accuracy of each CAT in estimating a person's function, and there was high measurement reliability for the simulated CAT scales compared with the full item bank. SCI-FI/AT item difficulties in the domains of Self-care, Fine Motor Function, and Ambulation were less difficult than the same items in the original SCI-FI item banks. Conclusion With the development of the SCI-FI/AT, clinicians and investigators have available multidimensional assessment scales that evaluate function for users of AT to complement the scales available in the original SCI-FI. PMID:26010975

Comparative Characterization of Crofelemer Samples Using Data Mining and Machine Learning Approaches With Analytical Stability Data Sets.

PubMed

Nariya, Maulik K; Kim, Jae Hyun; Xiong, Jian; Kleindl, Peter A; Hewarathna, Asha; Fisher, Adam C; Joshi, Sangeeta B; Schöneich, Christian; Forrest, M Laird; Middaugh, C Russell; Volkin, David B; Deeds, Eric J

2017-11-01

There is growing interest in generating physicochemical and biological analytical data sets to compare complex mixture drugs, for example, products from different manufacturers. In this work, we compare various crofelemer samples prepared from a single lot by filtration with varying molecular weight cutoffs combined with incubation for different times at different temperatures. The 2 preceding articles describe experimental data sets generated from analytical characterization of fractionated and degraded crofelemer samples. In this work, we use data mining techniques such as principal component analysis and mutual information scores to help visualize the data and determine discriminatory regions within these large data sets. The mutual information score identifies chemical signatures that differentiate crofelemer samples. These signatures, in many cases, would likely be missed by traditional data analysis tools. We also found that supervised learning classifiers robustly discriminate samples with around 99% classification accuracy, indicating that mathematical models of these physicochemical data sets are capable of identifying even subtle differences in crofelemer samples. Data mining and machine learning techniques can thus identify fingerprint-type attributes of complex mixture drugs that may be used for comparative characterization of products. Copyright © 2017 American Pharmacists Association®. All rights reserved.

Subpart B: National Emission Standards for Radon Emissions From Underground Uranium Mines

EPA Pesticide Factsheets

Subpart B sets a limit on the emission of radon-222 that ensures that no member of the public in any year receives an effective dose equivalent of more than 10 mrem/year from an underground uranium mine.

An Efficiency Balanced Information Criterion for Item Selection in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Han, Kyung T.

2012-01-01

Successful administration of computerized adaptive testing (CAT) programs in educational settings requires that test security and item exposure control issues be taken seriously. Developing an item selection algorithm that strikes the right balance between test precision and level of item pool utilization is the key to successful implementation…

Screening Test Items for Differential Item Functioning

ERIC Educational Resources Information Center

Longford, Nicholas T.

2014-01-01

A method for medical screening is adapted to differential item functioning (DIF). Its essential elements are explicit declarations of the level of DIF that is acceptable and of the loss function that quantifies the consequences of the two kinds of inappropriate classification of an item. Instead of a single level and a single function, sets of…

The Asymptotic Distribution of Ability Estimates: Beyond Dichotomous Items and Unidimensional IRT Models

ERIC Educational Resources Information Center

Sinharay, Sandip

2015-01-01

The maximum likelihood estimate (MLE) of the ability parameter of an item response theory model with known item parameters was proved to be asymptotically normally distributed under a set of regularity conditions for tests involving dichotomous items and a unidimensional ability parameter (Klauer, 1990; Lord, 1983). This article first considers…

Design risk assessment for burst-prone mines: Application in a Canadian mine

NASA Astrophysics Data System (ADS)

Cheung, David J.

A proactive stance towards improving the effectiveness and consistency of risk assessments has been adopted recently by mining companies and industry. The next 10-20 years forecasts that ore deposits accessible using shallow mining techniques will diminish. The industry continues to strive for success in "deeper" mining projects in order to keep up with the continuing demand for raw materials. Although the returns are quite profitable, many projects have been sidelined due to high uncertainty and technical risk in the mining of the mineral deposit. Several hardrock mines have faced rockbursting and seismicity problems. Within those reported, mines in countries like South Africa, Australia and Canada have documented cases of severe rockburst conditions attributed to the mining depth. Severe rockburst conditions known as "burst-prone" can be effectively managed with design. Adopting a more robust design can ameliorate the exposure of workers and equipment to adverse conditions and minimize the economic consequences, which can hinder the bottom line of an operation. This thesis presents a methodology created for assessing the design risk in burst-prone mines. The methodology includes an evaluation of relative risk ratings for scenarios with options of risk reduction through several design principles. With rockbursts being a hazard of seismic events, the methodology is based on research in the area of mining seismicity factoring in rockmass failure mechanisms, which results from a combination of mining induced stress, geological structures, rockmass properties and mining influences. The methodology was applied to case studies at Craig Mine of Xstrata Nickel in Sudbury, Ontario, which is known to contain seismically active fault zones. A customized risk assessment was created and applied to rockburst case studies, evaluating the seismic vulnerability and consequence for each case. Application of the methodology to Craig Mine demonstrates that changes in the design can reduce both exposure risk (personnel and equipment), and economical risk (revenue and costs). Fatal and catastrophic consequences can be averted through robust planning and design. Two customized approaches were developed to conduct risk assessment of case studies at Craig Mine. Firstly, the Brownfield Approach utilizes the seismic database to determine the seismic hazard from a rating system that evaluates frequency-magnitude, event size, and event-blast relation. Secondly, the Greenfield Approach utilizes the seismic database, focusing on larger magnitude events, rocktype, and geological structure. The customized Greenfield Approach can also be applied in the evaluation of design risk in deep mines with the same setting and condition as Craig Mine. Other mines with different settings and conditions can apply the principles in the methodology to evaluate design alternatives and risk reduction strategies for burst-prone mines.

Approximation Preserving Reductions among Item Pricing Problems

NASA Astrophysics Data System (ADS)

Hamane, Ryoso; Itoh, Toshiya; Tomita, Kouhei

When a store sells items to customers, the store wishes to determine the prices of the items to maximize its profit. Intuitively, if the store sells the items with low (resp. high) prices, the customers buy more (resp. less) items, which provides less profit to the store. So it would be hard for the store to decide the prices of items. Assume that the store has a set V of n items and there is a set E of m customers who wish to buy those items, and also assume that each item i ∈ V has the production cost di and each customer ej ∈ E has the valuation vj on the bundle ej ⊆ V of items. When the store sells an item i ∈ V at the price ri, the profit for the item i is pi = ri - di. The goal of the store is to decide the price of each item to maximize its total profit. We refer to this maximization problem as the item pricing problem. In most of the previous works, the item pricing problem was considered under the assumption that pi ≥ 0 for each i ∈ V, however, Balcan, et al. [In Proc. of WINE, LNCS 4858, 2007] introduced the notion of “loss-leader, ” and showed that the seller can get more total profit in the case that pi < 0 is allowed than in the case that pi < 0 is not allowed. In this paper, we derive approximation preserving reductions among several item pricing problems and show that all of them have algorithms with good approximation ratio.

Exploring virtual mental practice in maintenance task training.

PubMed

Bauerle, Tim; Brnich, Michael J; Navoyski, Jason

- This paper aims to contribute to a general understanding of mental practice by investigating the utility of and participant reaction to a virtual reality maintenance training among underground coal mine first responders. - Researchers at the National Institute for Occupational Safety and Health's Office of Mine Safety and Health Research (OMSHR) developed software to provide opportunities for mine rescue team members to learn to inspect, assemble and test their closed-circuit breathing apparatus and to practice those skills. In total, 31 mine rescue team members utilized OMSHR's BG 4 Benching Trainer software and provided feedback to the development team. After training, participants completed a brief post-training questionnaire, which included demographics, perceived training climate and general training evaluation items. - The results overall indicate a generally positive reaction to and high perceived utility of the BG 4 benching software. In addition, the perceived training climate appears to have an effect on the perceived utility of the mental practice virtual reality game, with benchmen from mines with more positive training climates reporting greater perceived efficacy in the training's ability to prepare trainees for real emergencies. - This paper helps to broaden current applications of mental practice and is one of the few empirical investigations into a non-rehabilitation virtual reality extension of mental practice. This paper also contributes to the growing literature advocating for greater usage of accurate and well-informed mental practice techniques, tools and methodologies, especially for occupational populations with limitations on exposure to hands-on training.

Use of IT platform in determination of efficiency of mining machines

NASA Astrophysics Data System (ADS)

Brodny, Jarosław; Tutak, Magdalena

2018-01-01

Determination of effective use of mining devices has very significant meaning for mining enterprises. High costs of their purchase and tenancy cause that these enterprises tend to the best use of possessed technical potential. However, specifics of mining production causes that this process not always proceeds without interferences. Practical experiences show that determination of objective measure of utilization of machine in mining enterprise is not simple. In the paper a proposition for solution of this problem is presented. For this purpose an IT platform and overall efficiency model OEE were used. This model enables to evaluate the machine in a range of its availability performance and quality of product, and constitutes a quantitative tool of TPM strategy. Adapted to the specificity of mining branch the OEE model together with acquired data from industrial automatic system enabled to determine the partial indicators and overall efficiency of tested machines. Studies were performed for a set of machines directly use in coal exploitation process. They were: longwall-shearer and armoured face conveyor, and beam stage loader. Obtained results clearly indicate that degree of use of machines by mining enterprises are unsatisfactory. Use of IT platforms will significantly facilitate the process of registration, archiving and analytical processing of the acquired data. In the paper there is presented methodology of determination of partial indices and total OEE together with a practical example of its application for investigated machines set. Also IT platform was characterized for its construction, function and application.

Educational Data Mining Application for Estimating Students Performance in Weka Environment

NASA Astrophysics Data System (ADS)

Gowri, G. Shiyamala; Thulasiram, Ramasamy; Amit Baburao, Mahindra

2017-11-01

Educational data mining (EDM) is a multi-disciplinary research area that examines artificial intelligence, statistical modeling and data mining with the data generated from an educational institution. EDM utilizes computational ways to deal with explicate educational information keeping in mind the end goal to examine educational inquiries. To make a country stand unique among the other nations of the world, the education system has to undergo a major transition by redesigning its framework. The concealed patterns and data from various information repositories can be extracted by adopting the techniques of data mining. In order to summarize the performance of students with their credentials, we scrutinize the exploitation of data mining in the field of academics. Apriori algorithmic procedure is extensively applied to the database of students for a wider classification based on various categorizes. K-means procedure is applied to the same set of databases in order to accumulate them into a specific category. Apriori algorithm deals with mining the rules in order to extract patterns that are similar along with their associations in relation to various set of records. The records can be extracted from academic information repositories. The parameters used in this study gives more importance to psychological traits than academic features. The undesirable student conduct can be clearly witnessed if we make use of information mining frameworks. Thus, the algorithms efficiently prove to profile the students in any educational environment. The ultimate objective of the study is to suspect if a student is prone to violence or not.

Automated Analysis of Renewable Energy Datasets ('EE/RE Data Mining')

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

Bush, Brian; Elmore, Ryan; Getman, Dan

This poster illustrates methods to substantially improve the understanding of renewable energy data sets and the depth and efficiency of their analysis through the application of statistical learning methods ('data mining') in the intelligent processing of these often large and messy information sources. The six examples apply methods for anomaly detection, data cleansing, and pattern mining to time-series data (measurements from metering points in buildings) and spatiotemporal data (renewable energy resource datasets).

30 CFR 75.601-1 - Short circuit protection; ratings and settings of circuit breakers.

Code of Federal Regulations, 2011 CFR

2011-07-01

... (amperes) 14 50 12 75 10 150 8 200 6 300 4 500 3 600 2 800 1 1,000 1/0 1,250 2/0 1,500 3/0 2,000 4/0 2,500... of circuit breakers. 75.601-1 Section 75.601-1 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR COAL MINE SAFETY AND HEALTH MANDATORY SAFETY STANDARDS-UNDERGROUND COAL MINES...

Optimizing the use of video-tapes of clinical sessions: the data-mining approach for scale construction and theory building for bereaved persons in Hong Kong.

PubMed

Chow, Amy Yin Man

2010-01-01

Video-taping clinical sessions is a common practice among social workers so that the tapes may be used for clinical supervision and reviewed with the individuals or families involved. They are usually underused for research purposes. This article reports on an innovative research method using such tapes as a basis for clinical data mining to explore the bereavement experience of Chinese people in Hong Kong. Using this data, a rich item pool, containing both negative and positive reactions, was generated to allow the development of a culturally relevant measurement tool of grief reactions. The data also facilitated theory building in the area of grief and bereavement. This study extended the use of video-tapes in clinical sessions for research purposes and helped to collect reliable and timely data in a non-intrusive way. It has also advanced the use of quantitative data in the clinical data-mining approach. The study encouraged collaboration between clinicians and researchers to develop knowledge and skills about their special target group of clients.

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level

PubMed Central

Savalei, Victoria; Rhemtulla, Mijke

2017-01-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data—that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study. PMID:29276371

Normal Theory Two-Stage ML Estimator When Data Are Missing at the Item Level.

PubMed

Savalei, Victoria; Rhemtulla, Mijke

2017-08-01

In many modeling contexts, the variables in the model are linear composites of the raw items measured for each participant; for instance, regression and path analysis models rely on scale scores, and structural equation models often use parcels as indicators of latent constructs. Currently, no analytic estimation method exists to appropriately handle missing data at the item level. Item-level multiple imputation (MI), however, can handle such missing data straightforwardly. In this article, we develop an analytic approach for dealing with item-level missing data-that is, one that obtains a unique set of parameter estimates directly from the incomplete data set and does not require imputations. The proposed approach is a variant of the two-stage maximum likelihood (TSML) methodology, and it is the analytic equivalent of item-level MI. We compare the new TSML approach to three existing alternatives for handling item-level missing data: scale-level full information maximum likelihood, available-case maximum likelihood, and item-level MI. We find that the TSML approach is the best analytic approach, and its performance is similar to item-level MI. We recommend its implementation in popular software and its further study.

DEMONSTRATION REPORT: Demonstration of Advanced Geophysics and Classification Technologies on Munitions Response Sites Former Fort Ord, Monterey County, CA

DTIC Science & Technology

2017-06-01

DGM Digital Geophysical Mapping DTSC California Department of Toxic Substances Control EM Electromagnetic EPA U.S. Environmental...land mines, pyrotechnics, bombs , and demolition materials. Surface sweeps identified MEC items throughout Units 11 and 12, including 37mm, 40mm, 57mm...electromagnetic ( EM ) data are being collected. If no GPS readings are collected during that period, the most recent GPS position and the platform

Autonomous Planning and Replanning for Mine-Sweeping Unmanned Underwater Vehicles

NASA Technical Reports Server (NTRS)

Gaines, Daniel M.

2010-01-01

This software generates high-quality plans for carrying out mine-sweeping activities under resource constraints. The autonomous planning and replanning system for unmanned underwater vehicles (UUVs) takes as input a set of prioritized mine-sweep regions, and a specification of available UUV resources including available battery energy, data storage, and time available for accomplishing the mission. Mine-sweep areas vary in location, size of area to be swept, and importance of the region. The planner also works with a model of the UUV, as well as a model of the power consumption of the vehicle when idle and when moving.

Intrajudge Consistency Using the Angoff Standard-Setting Method.

ERIC Educational Resources Information Center

Plake, Barbara S.; Impara, James C.

This study investigated the intrajudge consistency of Angoff-based item performance estimates. The examination used was a certification examination in an emergency medicine specialty. Ten expert panelists rated the same 24 items twice during an operational standard setting study. Results indicate that the panelists were highly consistent, in terms…

Development and psychometric evaluation of the Impact of Health Information Technology (I-HIT) scale.

PubMed

Dykes, Patricia C; Hurley, Ann; Cashen, Margaret; Bakken, Suzanne; Duffy, Mary E

2007-01-01

The use of health information technology (HIT) for the support of communication processes and data and information access in acute care settings is a relatively new phenomenon. A means of evaluating the impact of HIT in hospital settings is needed. The purpose of this research was to design and psychometrically evaluate the Impact of Health Information Technology scale (I-HIT). I-HIT was designed to measure the perception of nurses regarding the ways in which HIT influences interdisciplinary communication and workflow patterns and nurses' satisfaction with HIT applications and tools. Content for a 43-item tool was derived from the literature, and supported theoretically by the Coiera model and by nurse informaticists. Internal consistency reliability analysis using Cronbach's alpha was conducted on the 43-item scale to initiate the item reduction process. Items with an item total correlation of less than 0.35 were removed, leaving a total of 29 items. Item analysis, exploratory principal component analysis and internal consistency reliability using Cronbach's alpha were used to confirm the 29-item scale. Principal components analysis with Varimax rotation produced a four-factor solution that explained 58.5% of total variance (general advantages, information tools to support information needs, information tools to support communication needs, and workflow implications). Internal consistency of the total scale was 0.95 and ranged from 0.80-0.89 for four subscales. I-HIT demonstrated psychometric adequacy and is recommended to measure the impact of HIT on nursing practice in acute care settings.

Progress in the Visualization and Mining of Chemical and Target Spaces.

PubMed

Medina-Franco, José L; Aguayo-Ortiz, Rodrigo

2013-12-01

Chemogenomics is a growing field that aims to integrate the chemical and target spaces. As part of a multi-disciplinary effort to achieve this goal, computational methods initially developed to visualize the chemical space of compound collections and mine single-target structure-activity relationships, are being adapted to visualize and mine complex relationships in chemogenomics data sets. Similarly, the growing evidence that clinical effects are many times due to the interaction of single or multiple drugs with multiple targets, is encouraging the development of novel methodologies that are integrated in multi-target drug discovery endeavors. Herein we review advances in the development and application of approaches to generate visual representations of chemical space with particular emphasis on methods that aim to explore and uncover relationships between chemical and target spaces. Also, progress in the data mining of the structure-activity relationships of sets of compounds screened across multiple targets are discussed in light of the concept of activity landscape modeling. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Secure Secondary Use of Clinical Data with Cloud-based NLP Services. Towards a Highly Scalable Research Infrastructure.

PubMed

Christoph, J; Griebel, L; Leb, I; Engel, I; Köpcke, F; Toddenroth, D; Prokosch, H-U; Laufer, J; Marquardt, K; Sedlmayr, M

2015-01-01

The secondary use of clinical data provides large opportunities for clinical and translational research as well as quality assurance projects. For such purposes, it is necessary to provide a flexible and scalable infrastructure that is compliant with privacy requirements. The major goals of the cloud4health project are to define such an architecture, to implement a technical prototype that fulfills these requirements and to evaluate it with three use cases. The architecture provides components for multiple data provider sites such as hospitals to extract free text as well as structured data from local sources and de-identify such data for further anonymous or pseudonymous processing. Free text documentation is analyzed and transformed into structured information by text-mining services, which are provided within a cloud-computing environment. Thus, newly gained annotations can be integrated along with the already available structured data items and the resulting data sets can be uploaded to a central study portal for further analysis. Based on the architecture design, a prototype has been implemented and is under evaluation in three clinical use cases. Data from several hundred patients provided by a University Hospital and a private hospital chain have already been processed. Cloud4health has shown how existing components for secondary use of structured data can be complemented with text-mining in a privacy compliant manner. The cloud-computing paradigm allows a flexible and dynamically adaptable service provision that facilitates the adoption of services by data providers without own investments in respective hardware resources and software tools.

Data Streams: An Overview and Scientific Applications

NASA Astrophysics Data System (ADS)

Aggarwal, Charu C.

In recent years, advances in hardware technology have facilitated the ability to collect data continuously. Simple transactions of everyday life such as using a credit card, a phone, or browsing the web lead to automated data storage. Similarly, advances in information technology have lead to large flows of data across IP networks. In many cases, these large volumes of data can be mined for interesting and relevant information in a wide variety of applications. When the volume of the underlying data is very large, it leads to a number of computational and mining challenges: With increasing volume of the data, it is no longer possible to process the data efficiently by using multiple passes. Rather, one can process a data item at most once. This leads to constraints on the implementation of the underlying algorithms. Therefore, stream mining algorithms typically need to be designed so that the algorithms work with one pass of the data. In most cases, there is an inherent temporal component to the stream mining process. This is because the data may evolve over time. This behavior of data streams is referred to as temporal locality. Therefore, a straightforward adaptation of one-pass mining algorithms may not be an effective solution to the task. Stream mining algorithms need to be carefully designed with a clear focus on the evolution of the underlying data. Another important characteristic of data streams is that they are often mined in a distributed fashion. Furthermore, the individual processors may have limited processing and memory. Examples of such cases include sensor networks, in which it may be desirable to perform in-network processing of data stream with limited processing and memory [1, 2]. This chapter will provide an overview of the key challenges in stream mining algorithms which arise from the unique setup in which these problems are encountered. This chapter is organized as follows. In the next section, we will discuss the generic challenges that stream mining poses to a variety of data management and data mining problems. The next section also deals with several issues which arise in the context of data stream management. In Sect. 3, we discuss several mining algorithms on the data stream model. Section 4 discusses various scientific applications of data streams. Section 5 discusses the research directions and conclusions.

Tertiary coals in South Texas: Anomalous cannel-like coals of Webb County (Claiborne Group, Eocene) and lignites of Atascosa County (Jackson Group, Eocene) - Geologic setting, character, source-rock and coal-bed methane potential

USGS Publications Warehouse

Warwick, Peter D.; Aubourg, Claire E.; Willett, Jason C.

1999-01-01

The coal-bearing Gulf of Mexico Coastal Plain of North America contains a variety of depositional settings and coal types. The coal-bearing region extends westward from Alabama and Mississippi, across Louisiana to the northern part of the Mississippi Embayment, and then southward to eastern Arkansas, Texas and northern Mexico (fig. 1). Most of the coal currently mined in Texas is lignite from the upper part of the Wilcox Group (Paleocene-Eocene) and, in Louisiana, lignite is mined from the lower part of the Wilcox (fig. 2). Gulf Coast coal is used primarily as fuel for mine-mouth electric plants. On this field trip we will visit the only two non-Wilcox coal mining intervals in the Texas-Louisiana Coastal Plain; these include the San Pedro - Santo Tomas bituminous cannel-like coal zone of the Eocene Claiborne Group, and the San Miguel lignite coal zone of the Eocene Jackson Group (fig. 2). Other coal-mining areas in northern Mexico are currently producing bituminous coal from the Cretaceous Olmos Formation of the Navaro Group (fig. 2).

Item Parameter Drift as an Indication of Differential Opportunity to Learn: An Exploration of Item Flagging Methods & Accurate Classification of Examinees

ERIC Educational Resources Information Center

Sukin, Tia M.

2010-01-01

The presence of outlying anchor items is an issue faced by many testing agencies. The decision to retain or remove an item is a difficult one, especially when the content representation of the anchor set becomes questionable by item removal decisions. Additionally, the reason for the aberrancy is not always clear, and if the performance of the…

Measuring ability to assess claims about treatment effects: a latent trait analysis of items from the ‘Claim Evaluation Tools’ database using Rasch modelling

PubMed Central

Austvoll-Dahlgren, Astrid; Guttersrud, Øystein; Nsangi, Allen; Semakula, Daniel; Oxman, Andrew D

2017-01-01

Background The Claim Evaluation Tools database contains multiple-choice items for measuring people’s ability to apply the key concepts they need to know to be able to assess treatment claims. We assessed items from the database using Rasch analysis to develop an outcome measure to be used in two randomised trials in Uganda. Rasch analysis is a form of psychometric testing relying on Item Response Theory. It is a dynamic way of developing outcome measures that are valid and reliable. Objectives To assess the validity, reliability and responsiveness of 88 items addressing 22 key concepts using Rasch analysis. Participants We administrated four sets of multiple-choice items in English to 1114 people in Uganda and Norway, of which 685 were children and 429 were adults (including 171 health professionals). We scored all items dichotomously. We explored summary and individual fit statistics using the RUMM2030 analysis package. We used SPSS to perform distractor analysis. Results Most items conformed well to the Rasch model, but some items needed revision. Overall, the four item sets had satisfactory reliability. We did not identify significant response dependence between any pairs of items and, overall, the magnitude of multidimensionality in the data was acceptable. The items had a high level of difficulty. Conclusion Most of the items conformed well to the Rasch model’s expectations. Following revision of some items, we concluded that most of the items were suitable for use in an outcome measure for evaluating the ability of children or adults to assess treatment claims. PMID:28550019

Improving Measurement Efficiency of the Inner EAR Scale with Item Response Theory.

PubMed

Jessen, Annika; Ho, Andrew D; Corrales, C Eduardo; Yueh, Bevan; Shin, Jennifer J

2018-02-01

Objectives (1) To assess the 11-item Inner Effectiveness of Auditory Rehabilitation (Inner EAR) instrument with item response theory (IRT). (2) To determine whether the underlying latent ability could also be accurately represented by a subset of the items for use in high-volume clinical scenarios. (3) To determine whether the Inner EAR instrument correlates with pure tone thresholds and word recognition scores. Design IRT evaluation of prospective cohort data. Setting Tertiary care academic ambulatory otolaryngology clinic. Subjects and Methods Modern psychometric methods, including factor analysis and IRT, were used to assess unidimensionality and item properties. Regression methods were used to assess prediction of word recognition and pure tone audiometry scores. Results The Inner EAR scale is unidimensional, and items varied in their location and information. Information parameter estimates ranged from 1.63 to 4.52, with higher values indicating more useful items. The IRT model provided a basis for identifying 2 sets of items with relatively lower information parameters. Item information functions demonstrated which items added insubstantial value over and above other items and were removed in stages, creating a 8- and 3-item Inner EAR scale for more efficient assessment. The 8-item version accurately reflected the underlying construct. All versions correlated moderately with word recognition scores and pure tone averages. Conclusion The 11-, 8-, and 3-item versions of the Inner EAR scale have strong psychometric properties, and there is correlational validity evidence for the observed scores. Modern psychometric methods can help streamline care delivery by maximizing relevant information per item administered.

Evaluation of item candidates for a diabetic retinopathy quality of life item bank.

PubMed

Fenwick, Eva K; Pesudovs, Konrad; Khadka, Jyoti; Rees, Gwyn; Wong, Tien Y; Lamoureux, Ecosse L

2013-09-01

We are developing an item bank assessing the impact of diabetic retinopathy (DR) on quality of life (QoL) using a rigorous multi-staged process combining qualitative and quantitative methods. We describe here the first two qualitative phases: content development and item evaluation. After a comprehensive literature review, items were generated from four sources: (1) 34 previously validated patient-reported outcome measures; (2) five published qualitative articles; (3) eight focus groups and 18 semi-structured interviews with 57 DR patients; and (4) seven semi-structured interviews with diabetes or ophthalmic experts. Items were then evaluated during 3 stages, namely binning (grouping) and winnowing (reduction) based on key criteria and panel consensus; development of item stems and response options; and pre-testing of items via cognitive interviews with patients. The content development phase yielded 1,165 unique items across 7 QoL domains. After 3 sessions of binning and winnowing, items were reduced to a minimally representative set (n = 312) across 9 domains of QoL: visual symptoms; ocular surface symptoms; activity limitation; mobility; emotional; health concerns; social; convenience; and economic. After 8 cognitive interviews, 42 items were amended resulting in a final set of 314 items. We have employed a systematic approach to develop items for a DR-specific QoL item bank. The psychometric properties of the nine QoL subscales will be assessed using Rasch analysis. The resulting validated item bank will allow clinicians and researchers to better understand the QoL impact of DR and DR therapies from the patient's perspective.

Scoring best-worst data in unbalanced many-item designs, with applications to crowdsourcing semantic judgments.

PubMed

Hollis, Geoff

2018-04-01

Best-worst scaling is a judgment format in which participants are presented with a set of items and have to choose the superior and inferior items in the set. Best-worst scaling generates a large quantity of information per judgment because each judgment allows for inferences about the rank value of all unjudged items. This property of best-worst scaling makes it a promising judgment format for research in psychology and natural language processing concerned with estimating the semantic properties of tens of thousands of words. A variety of different scoring algorithms have been devised in the previous literature on best-worst scaling. However, due to problems of computational efficiency, these scoring algorithms cannot be applied efficiently to cases in which thousands of items need to be scored. New algorithms are presented here for converting responses from best-worst scaling into item scores for thousands of items (many-item scoring problems). These scoring algorithms are validated through simulation and empirical experiments, and considerations related to noise, the underlying distribution of true values, and trial design are identified that can affect the relative quality of the derived item scores. The newly introduced scoring algorithms consistently outperformed scoring algorithms used in the previous literature on scoring many-item best-worst data.

FIM-Minimum Data Set Motor Item Bank: Short Forms Development and Precision Comparison in Veterans.

PubMed

Li, Chih-Ying; Romero, Sergio; Simpson, Annie N; Bonilha, Heather S; Simpson, Kit N; Hong, Ickpyo; Velozo, Craig A

2018-03-01

To improve the practical use of the short forms (SFs) developed from the item bank, we compared the measurement precision of the 4- and 8-item SFs generated from a motor item bank composed of the FIM and the Minimum Data Set (MDS). The FIM-MDS motor item bank allowed scores generated from different instruments to be co-calibrated. The 4- and 8-item SFs were developed based on Rasch analysis procedures. This article compared person strata, ceiling/floor effects, and test SE plots for each administration form and examined 95% confidence interval error bands of anchored person measures with the corresponding SFs. We used 0.3 SE as a criterion to reflect a reliability level of .90. Veterans' inpatient rehabilitation facilities and community living centers. Veterans (N=2500) who had both FIM and the MDS data within 6 days during 2008 through 2010. Not applicable. Four- and 8-item SFs of FIM, MDS, and FIM-MDS motor item bank. Six SFs were generated with 4 and 8 items across a range of difficulty levels from the FIM-MDS motor item bank. The three 8-item SFs all had higher correlations with the item bank (r=.82-.95), higher person strata, and less test error than the corresponding 4-item SFs (r=.80-.90). The three 4-item SFs did not meet the criteria of SE <0.3 for any theta values. Eight-item SFs could improve clinical use of the item bank composed of existing instruments across the continuum of care in veterans. We also found that the number of items, not test specificity, determines the precision of the instrument. Copyright © 2017 American Congress of Rehabilitation Medicine. All rights reserved.

Application and Exploration of Big Data Mining in Clinical Medicine

PubMed Central

Zhang, Yue; Guo, Shu-Li; Han, Li-Na; Li, Tie-Ling

2016-01-01

Objective: To review theories and technologies of big data mining and their application in clinical medicine. Data Sources: Literatures published in English or Chinese regarding theories and technologies of big data mining and the concrete applications of data mining technology in clinical medicine were obtained from PubMed and Chinese Hospital Knowledge Database from 1975 to 2015. Study Selection: Original articles regarding big data mining theory/technology and big data mining's application in the medical field were selected. Results: This review characterized the basic theories and technologies of big data mining including fuzzy theory, rough set theory, cloud theory, Dempster–Shafer theory, artificial neural network, genetic algorithm, inductive learning theory, Bayesian network, decision tree, pattern recognition, high-performance computing, and statistical analysis. The application of big data mining in clinical medicine was analyzed in the fields of disease risk assessment, clinical decision support, prediction of disease development, guidance of rational use of drugs, medical management, and evidence-based medicine. Conclusion: Big data mining has the potential to play an important role in clinical medicine. PMID:26960378

Data-Mining Technologies for Diabetes: A Systematic Review

PubMed Central

Marinov, Miroslav; Mosa, Abu Saleh Mohammad; Yoo, Illhoi; Boren, Suzanne Austin

2011-01-01

Background The objective of this study is to conduct a systematic review of applications of data-mining techniques in the field of diabetes research. Method We searched the MEDLINE database through PubMed. We initially identified 31 articles by the search, and selected 17 articles representing various data-mining methods used for diabetes research. Our main interest was to identify research goals, diabetes types, data sets, data-mining methods, data-mining software and technologies, and outcomes. Results The applications of data-mining techniques in the selected articles were useful for extracting valuable knowledge and generating new hypothesis for further scientific research/experimentation and improving health care for diabetes patients. The results could be used for both scientific research and real-life practice to improve the quality of health care diabetes patients. Conclusions Data mining has played an important role in diabetes research. Data mining would be a valuable asset for diabetes researchers because it can unearth hidden knowledge from a huge amount of diabetes-related data. We believe that data mining can significantly help diabetes research and ultimately improve the quality of health care for diabetes patients. PMID:22226277

The Therapeutic Environment Screening Survey for Nursing Homes (TESS-NH): an observational instrument for assessing the physical environment of institutional settings for persons with dementia.

PubMed

Sloane, Philip D; Mitchell, C Madeline; Weisman, Gerald; Zimmerman, Sheryl; Foley, Kristie M Long; Lynn, Mary; Calkins, Margaret; Lawton, M Powell; Teresi, Jeanne; Grant, Leslie; Lindeman, David; Montgomery, Rhonda

2002-03-01

To develop an observational instrument that describes the ability of physical environments of institutional settings to address therapeutic goals for persons with dementia. A National Institute on Aging workgroup identified and subsequently revised items that evaluated exit control, maintenance, cleanliness, safety, orientation/cueing, privacy, unit autonomy, outdoor access, lighting, noise, visual/tactile stimulation, space/seating, and familiarity/homelikeness. The final instrument contains 84 discrete items and one global rating. A summary scale, the Special Care Unit Environmental Quality Scale (SCUEQS), consists of 18 items. Lighting items were validated using portable light meters. Concurrent criterion validation compared SCUEQS scores with the Professional Environmental Assessment Protocol (PEAP). Interrater kappa statistics for 74% of items were above.60. For another 10% of items, kappas could not be calculated due to empty cells, but interrater agreement was above 80%. The SCUEQS demonstrated an interrater reliability of.93, a test--retest reliability of.88, and an internal consistency of.81--.83. Light meter ratings correlated significantly with the Therapeutic Environment Screening Survey for Nursing Homes (TESS-NH) lighting items (r =.29--.38, p =.01--.04), and the SCUEQS correlated significantly with global PEAP ratings (r =.52, p <.01). The TESS-NH efficiently assesses discrete elements of the physical environment and has strong reliability and validity. The SCUEQS provides a quantitative measure of environmental quality in institutional settings.

Analysis on online word-of-mouth of customer satisfaction in cultural and creative industries of Taiwan: using crafts as an example

NASA Astrophysics Data System (ADS)

Tsai, Li-Fen; Shaw, Jing-Chi; Wang, Pei-Wen; Shih, Meng-Long; Yang, Min-Chieh

2011-10-01

This study aims to analyze customers' online word-of-mouth for crafts in Cultural and Creative Industries of Taiwan, and extracts articles from Yahoo and Wretch Blogs by the online writing mining technique. The research scope is from Jan. 1, 2008 to Dec. 31, 2010. The subjects include 2457 valid articles on customers' online word-of-mouth regarding the craft industry of Taiwan. Findings demonstrate that, regarding online word-of-mouth, the most important word-of-mouth items of ceramics, stone craft, wood craft manufacturing, and metal craft is decoration and display of surroundings; while brand is valued in glass craft; and the most important item for consumers of paper craft is cultural characteristics of handicrafts.

Effects of underground mining and mine collapse on the hydrology of selected basins in West Virginia

USGS Publications Warehouse

Hobba, William A.

1993-01-01

The effects of underground mining and mine collapse on areal hydrology were determined at one site where the mined bed of coal lies above major streams and at two sites where the bed of coal lies below major streams. Subsidence cracks observed at land surface generally run parallel to predominant joint sets in the rocks. The mining and subsidence cracks increase hydraulic conductivity and interconnection of water-bearing rock units, which in turn cause increased infiltration of precipitation and surface water, decreased evapotranspiration, and higher base flows in some small streams. Water levels in observation wells in mined areas fluctuate as much as 100 ft annually. Both gaining and losing streams are found in mined areas. Mine pumpage and drainage can cause diversion of water underground from one basin to another. Areal and single-well aquifer tests indicated that near-surface rocks have higher transmissivity in a mine-subsided basin than in unmined basins. Increased infiltration and circulation through shallow subsurface rocks increase dissolved mineral loads in streams, as do treated and untreated contributions from mine pumpage and drainage. Abandoned and flooded underground mines make good reservoirs because of their increased transmissivity and storage. Subsidence cracks were not detectable by thermal imagery, but springs and seeps were detectable.

The Effects of Testlets on Reliability and Differential Item Functioning

ERIC Educational Resources Information Center

Teker, Gulsen Tasdelen; Dogan, Nuri

2015-01-01

Reliability and differential item functioning (DIF) analyses were conducted on testlets displaying local item dependence in this study. The data set employed in the research was obtained from the answers given by 1,500 students to the 20 items included in six testlets given in English Proficiency Exam by the School of Foreign Languages of a state…

Integrating Test-Form Formatting into Automated Test Assembly

ERIC Educational Resources Information Center

Diao, Qi; van der Linden, Wim J.

2013-01-01

Automated test assembly uses the methodology of mixed integer programming to select an optimal set of items from an item bank. Automated test-form generation uses the same methodology to optimally order the items and format the test form. From an optimization point of view, production of fully formatted test forms directly from the item pool using…

Item Difficulty in the Evaluation of Computer-Based Instruction: An Example from Neuroanatomy

ERIC Educational Resources Information Center

Chariker, Julia H.; Naaz, Farah; Pani, John R.

2012-01-01

This article reports large item effects in a study of computer-based learning of neuroanatomy. Outcome measures of the efficiency of learning, transfer of learning, and generalization of knowledge diverged by a wide margin across test items, with certain sets of items emerging as particularly difficult to master. In addition, the outcomes of…

Estimation of Item Response Theory Parameters in the Presence of Missing Data

ERIC Educational Resources Information Center

Finch, Holmes

2008-01-01

Missing data are a common problem in a variety of measurement settings, including responses to items on both cognitive and affective assessments. Researchers have shown that such missing data may create problems in the estimation of item difficulty parameters in the Item Response Theory (IRT) context, particularly if they are ignored. At the same…

An Alternative Approach for the Analyses and Interpretation of Attachment Sort Items

ERIC Educational Resources Information Center

Kirkland, John; Bimler, David; Drawneek, Andrew; McKim, Margaret; Scholmerich, Axel

2004-01-01

Attachment Q-Sort (AQS) is a tool for quantifying observations about toddler/caregiver relationships. Previous studies have applied factor analysis to the full 90 AQS item set to explore the structure underlying them. Here we explore that structure by applying multidimensional scaling (MDS) to judgements of inter-item similarity. AQS items are…

A Comparison of Two Area Measures for Detecting Differential Item Functioning.

ERIC Educational Resources Information Center

Kim, Seock-Ho; Cohen, Allan S.

1991-01-01

The exact and closed-interval area measures for detecting differential item functioning are compared for actual data from 1,000 African-American and 1,000 white college students taking a vocabulary test with items intentionally constructed to favor 1 set of examinees. No real differences in detection of biased items were found. (SLD)

Mining problems caused by tectonic stress in Illinois basin

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

Nelson, W.J.

1991-08-01

The Illinois basin coalfield is subject to a contemporary tectonic stress field in which the principal compressive stress axis ({sigma}1) is horizontal and strikes N60{degree}E to east-west. This stress is responsible for widespread development of kind zones and directional roof failures in mine headings driven perpendicular to {sigma}1. Also, small thrust faults perpendicular to {sigma}1 and joints parallel to {sigma}1 weaken the mine roof and occasionally admit water and gas to workings, depending upon geologic setting. The direction of magnitude of stress have been identified by a variety of techniques that can be applied both prior to mining and duringmore » development. Mining experience shows that the best method of minimizing stress-related problems is to drive mine headings at about 45 to {sigma}1.« less

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques

PubMed Central

Mande, Sharmila S.

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm. PMID:27124399

Inferring Intra-Community Microbial Interaction Patterns from Metagenomic Datasets Using Associative Rule Mining Techniques.

PubMed

Tandon, Disha; Haque, Mohammed Monzoorul; Mande, Sharmila S

2016-01-01

The nature of inter-microbial metabolic interactions defines the stability of microbial communities residing in any ecological niche. Deciphering these interaction patterns is crucial for understanding the mode/mechanism(s) through which an individual microbial community transitions from one state to another (e.g. from a healthy to a diseased state). Statistical correlation techniques have been traditionally employed for mining microbial interaction patterns from taxonomic abundance data corresponding to a given microbial community. In spite of their efficiency, these correlation techniques can capture only 'pair-wise interactions'. Moreover, their emphasis on statistical significance can potentially result in missing out on several interactions that are relevant from a biological standpoint. This study explores the applicability of one of the earliest association rule mining algorithm i.e. the 'Apriori algorithm' for deriving 'microbial association rules' from the taxonomic profile of given microbial community. The classical Apriori approach derives association rules by analysing patterns of co-occurrence/co-exclusion between various '(subsets of) features/items' across various samples. Using real-world microbiome data, the efficiency/utility of this rule mining approach in deciphering multiple (biologically meaningful) association patterns between 'subsets/subgroups' of microbes (constituting microbiome samples) is demonstrated. As an example, association rules derived from publicly available gut microbiome datasets indicate an association between a group of microbes (Faecalibacterium, Dorea, and Blautia) that are known to have mutualistic metabolic associations among themselves. Application of the rule mining approach on gut microbiomes (sourced from the Human Microbiome Project) further indicated similar microbial association patterns in gut microbiomes irrespective of the gender of the subjects. A Linux implementation of the Association Rule Mining (ARM) software (customised for deriving 'microbial association rules' from microbiome data) is freely available for download from the following link: http://metagenomics.atc.tcs.com/arm.

Development of ACLEEM questionnaire, an instrument measuring residents' educational environment in postgraduate ambulatory setting.

PubMed

Riquelme, Arnoldo; Padilla, Oslando; Herrera, Cristian; Olivos, Trinidad; Román, José Antonio; Sarfatis, Alberto; Solís, Nancy; Pizarro, Margarita; Torres, Patricio; Roff, Sue

2013-01-01

Students' perceptions of their educational environment (EE) have been studied in undergraduate and postgraduate curricula. Postgraduate EE has been measured in hospital settings. However, there are no instruments available to measure the EE in postgraduate ambulatory settings. The aim of this study was to develop the "ambulatory care learning education environment measure" (ACLEEM). A mixed methodology was used including three stages: (1) Grounded theory (focus groups); (2) Delphi technique to identify consensus; and (3) Pilot study. Three quota samples of approximately 60 stakeholders were formed, one as focus groups and two as Delphi panels. Eight focus groups were carried out including 58 residents (Latin-American Spanish speakers). The results were analysed and 173 items were offered to a National Delphi panel (61 residents and teachers). They reduced in two rounds the number of important items to 54. The 54-item questionnaire was then piloted with 63 residents and refined to the final version of the ACLEEM with 50 items and three domains. The 50-item inventory is a valid instrument to measure the EE in postgraduate ambulatory setting in Chile. Large-scale administration of the ACLEEM questionnaire to evaluate its construct validity and reliability are the next steps to test the psychometric properties of the instrument.

The impact of affect on willingness-to-pay and desired-set-size.

PubMed

Hafenbrädl, Sebastian; Hoffrage, Ulrich; White, Chris M

2013-01-01

What role does affect play in economic decision making? Previous research showed that the number of items had a linear effect on the willingness-to-pay for those items when participants were computationally primed, whereas participants' willingness-to-pay was insensitive to the amount when they were affectively primed. We extend this research by also studying the impact of affect on nonmonetary costs of waiting for items to be displayed and of screening them in a computer task. We assessed these costs by asking participants how many items they desired to see before making their selection. In our experiment, the effect of priming on desired-set-size was even larger than on willingness-to-pay, which can be explained by the fact that the nonmonetary costs, waiting time, were real, whereas willingness-to-pay was hypothetical. Participants also reported their satisfaction with the choosing process and the chosen items; no linear or nonlinear relationship was found between the self-determined desired-set-size and satisfaction. Copyright © 2013 Elsevier B.V. All rights reserved.

Lazy collaborative filtering for data sets with missing values.

PubMed

Ren, Yongli; Li, Gang; Zhang, Jun; Zhou, Wanlei

2013-12-01

As one of the biggest challenges in research on recommender systems, the data sparsity issue is mainly caused by the fact that users tend to rate a small proportion of items from the huge number of available items. This issue becomes even more problematic for the neighborhood-based collaborative filtering (CF) methods, as there are even lower numbers of ratings available in the neighborhood of the query item. In this paper, we aim to address the data sparsity issue in the context of neighborhood-based CF. For a given query (user, item), a set of key ratings is first identified by taking the historical information of both the user and the item into account. Then, an auto-adaptive imputation (AutAI) method is proposed to impute the missing values in the set of key ratings. We present a theoretical analysis to show that the proposed imputation method effectively improves the performance of the conventional neighborhood-based CF methods. The experimental results show that our new method of CF with AutAI outperforms six existing recommendation methods in terms of accuracy.

Equal Area Logistic Estimation for Item Response Theory

NASA Astrophysics Data System (ADS)

Lo, Shih-Ching; Wang, Kuo-Chang; Chang, Hsin-Li

2009-08-01

Item response theory (IRT) models use logistic functions exclusively as item response functions (IRFs). Applications of IRT models require obtaining the set of values for logistic function parameters that best fit an empirical data set. However, success in obtaining such set of values does not guarantee that the constructs they represent actually exist, for the adequacy of a model is not sustained by the possibility of estimating parameters. In this study, an equal area based two-parameter logistic model estimation algorithm is proposed. Two theorems are given to prove that the results of the algorithm are equivalent to the results of fitting data by logistic model. Numerical results are presented to show the stability and accuracy of the algorithm.

30 CFR 18.90 - Purpose.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Purpose. 18.90 Section 18.90 Mineral Resources... PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.90 Purpose. The regulations of this subpart E set forth the procedures and...

30 CFR 18.90 - Purpose.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Purpose. 18.90 Section 18.90 Mineral Resources... PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.90 Purpose. The regulations of this subpart E set forth the procedures and...

30 CFR 18.90 - Purpose.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Purpose. 18.90 Section 18.90 Mineral Resources... PRODUCTS ELECTRIC MOTOR-DRIVEN MINE EQUIPMENT AND ACCESSORIES Field Approval of Electrically Operated Mining Equipment § 18.90 Purpose. The regulations of this subpart E set forth the procedures and...

Translations on North Korea, Number 573.

DTIC Science & Technology

1978-02-02

Production 61 Ore Production 61 Changsong Mine 61 - c - KIM IL-SONG PHOTOS APPEARING IN ’NODONG SINMUN,’ DECEMBER 1977 [Editorial Report] The...Pyongyang Domestic Service in Korean 0800 GMT 12 Jan 78 SK] CHANGSONG MINE—The Changsong mine has overfulfilled the tagets set for tunneling by 270

Discrimination between stages of Alzheimer's disease with subsets of Mini-Mental State Examination items. An analysis of Consortium to Establish a Registry for Alzheimer's Disease data.

PubMed

Fillenbaum, G G; Wilkinson, W E; Welsh, K A; Mohs, R C

1994-09-01

To identify minimal sets of Mini-Mental State Examination (MMSE) items that can distinguish normal control subjects from patients with mild Alzheimer's disease (AD), patients with mild from those with moderate AD, and those with moderate from those with severe AD. Two randomly selected equivalent half samples. Results of logistic regression analysis from data from the first half of the sample were confirmed by receiver operating characteristic curves on the second half. Memory disorders clinics at major medical centers in the United States affiliated with the Consortium to establish a Registry for Alzheimer's Disease (CERAD). White, normal control subjects (n = 412) and patients with AD (n = 621) who met CERAD criteria; nonwhite subjects (n = 165) and persons with missing data (n = 27) were excluded. Three four-item sets of MMSE items that discriminate, respectively, (1) normal controls from patients with mild AD, (2) patients with mild from those with moderate AD, and (3) patients with moderate from those with severe AD. The MMSE items discriminating normal controls from patients with mild AD were day, date, recall of apple, and recall of penny; those discriminating patients with mild from those with moderate AD were month, city, spelling world backward, and county, and those discriminating patients with moderate from those with severe AD were floor of building, repeating the word table, naming watch, and folding paper in half. Performance on the first two four-item sets was comparable with that of the full MMSE; the third set distinguished patients with moderate from those with severe AD better than chance. A minimum set of MMSE items can effectively discriminate normal controls from patients with mild AD and between successive levels of severity of AD. Data apply only to white patients with AD. Performance in minorities, more heterogeneous groups, or normal subjects with questionable cognitive status has not been assessed.

TREatment of ATopic eczema (TREAT) Registry Taskforce: An international Delphi exercise to identify a core set of domains and domain items for national atopic eczema photo- and systemic therapy registries.

PubMed

Gerbens, L A A; Apfelbacher, C J; Irvine, A D; Barbarot, S; de Booij, R J; Boyce, A E; Deleuran, M; Eichenfield, L F; Hof, M H; Middelkamp-Hup, M A; Roberts, A; Schmitt, J; Vestergaard, C; Wall, D; Weidinger, S; Williamson, P R; Flohr, C; Spuls, P I

2018-05-15

Evidence of immunomodulatory therapies to guide clinical management for atopic eczema (AE) is scarce, despite frequent and often off-label use. Patient registries provide valuable evidence for the effects of treatments under real world conditions which can inform treatment guidelines, give the opportunity for health economic evaluation and the evaluation of quality of care, as well as pharmacogenetic and -dynamic research which cannot be adequately addressed in clinical trials. The TREatment of ATopic eczema (TREAT) Registry Taskforce aims to seek international consensus on a core set of domains and items ('what to measure') for AE research registries, using a Delphi approach. Participants from six stakeholder groups were included: doctors, nurses, non-clinical researchers, patients, industry and regulatory body representatives. The eDelphi comprised 3 sequential online rounds, requesting participants to rate the importance of each proposed domain item. Participants could add domain items to the proposed list in round 1. A final consensus meeting was held to ratify the core set. 479 participants from 36 countries accessed the eDelphi platform, of whom 86%, 79% and 74% completed rounds 1, 2, and 3 respectively. At the face-to-face consensus meeting attended by 42 participants the final core set was established containing 19 domains with 69 domain items (49 baseline and 20 follow-up items). This core set of domains and items to be captured by national AE systemic therapy registries will standardise data collection and thereby allow direct comparability across registries and facilitate data pooling between countries. Ultimately, it will provide greater insight into the effectiveness, safety and cost-effectiveness of photo- and systemic immunomodulatory therapies. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Developing an item bank to measure economic quality of life for individuals with disabilities.

PubMed

Tulsky, David S; Kisala, Pamela A; Lai, Jin-Shei; Carlozzi, Noelle; Hammel, Joy; Heinemann, Allen W

2015-04-01

To develop and evaluate the psychometric properties of an item set measuring economic quality of life (QOL) for use by individuals with disabilities. Survey. Community settings. Individuals with disabilities completed individual interviews (n=64), participated in focus groups (n=172), and completed cognitive interviews (n=15). Inclusion criteria included the following: traumatic brain injury, spinal cord injury, or stroke; age ≥18 years; and ability to read and speak English. We calibrated the items with 305 former rehabilitation inpatients. None. Economic QOL. Confirmatory factor analysis showed acceptable fit indices (comparative fit index=.939, root mean square error of approximation=.089) for the 37 items. However, 3 items demonstrated local item dependence. Dropping 9 items improved fit and obviated local dependence. Rasch analysis of the remaining 28 items yielded a person reliability of .92, suggesting that these items discriminate about 4 economic QOL levels. We developed a 28-item bank that measures economic aspects of QOL. Preliminary confirmatory factor analysis and Rasch analysis results support the psychometric properties of this new measure. It fills a gap in health-related QOL measurement by describing the economic barriers and facilitators of community participation. Future development will make the item bank available as a computer adaptive test. Copyright © 2015 American Congress of Rehabilitation Medicine. Published by Elsevier Inc. All rights reserved.

Saving Lives With Rocket Power

NASA Technical Reports Server (NTRS)

2000-01-01

Thiokol Propulsion uses NASA's surplus rocket fuel to produce a flare that can safely destroy land mines. Through a Memorandum of Agreement between Thiokol and Marshall Space Flight Center, Thiokol uses the scrap Reusable Solid Rocket Motor (RSRM) propellant. The resulting Demining Device was developed by Thiokol with the help of DE Technologies. The Demining Device neutralizes land mines in the field without setting them off. The Demining Device flare is placed next to an uncovered land mine. Using a battery-triggered electric match, the flare is then ignited. Using the excess and now solidified rocket fuel, the flare burns a hole in the mine's case and ignites the explosive contents. Once the explosive material is burned away, the mine is disarmed and no longer dangerous.

toxoMine: an integrated omics data warehouse for Toxoplasma gondii systems biology research

PubMed Central

Rhee, David B.; Croken, Matthew McKnight; Shieh, Kevin R.; Sullivan, Julie; Micklem, Gos; Kim, Kami; Golden, Aaron

2015-01-01

Toxoplasma gondii (T. gondii) is an obligate intracellular parasite that must monitor for changes in the host environment and respond accordingly; however, it is still not fully known which genetic or epigenetic factors are involved in regulating virulence traits of T. gondii. There are on-going efforts to elucidate the mechanisms regulating the stage transition process via the application of high-throughput epigenomics, genomics and proteomics techniques. Given the range of experimental conditions and the typical yield from such high-throughput techniques, a new challenge arises: how to effectively collect, organize and disseminate the generated data for subsequent data analysis. Here, we describe toxoMine, which provides a powerful interface to support sophisticated integrative exploration of high-throughput experimental data and metadata, providing researchers with a more tractable means toward understanding how genetic and/or epigenetic factors play a coordinated role in determining pathogenicity of T. gondii. As a data warehouse, toxoMine allows integration of high-throughput data sets with public T. gondii data. toxoMine is also able to execute complex queries involving multiple data sets with straightforward user interaction. Furthermore, toxoMine allows users to define their own parameters during the search process that gives users near-limitless search and query capabilities. The interoperability feature also allows users to query and examine data available in other InterMine systems, which would effectively augment the search scope beyond what is available to toxoMine. toxoMine complements the major community database ToxoDB by providing a data warehouse that enables more extensive integrative studies for T. gondii. Given all these factors, we believe it will become an indispensable resource to the greater infectious disease research community. Database URL: http://toxomine.org PMID:26130662

Development of the PROMIS positive emotional and sensory expectancies of smoking item banks.

PubMed

Tucker, Joan S; Shadel, William G; Edelen, Maria Orlando; Stucky, Brian D; Li, Zhen; Hansen, Mark; Cai, Li

2014-09-01

The positive emotional and sensory expectancies of cigarette smoking include improved cognitive abilities, positive affective states, and pleasurable sensorimotor sensations. This paper describes development of Positive Emotional and Sensory Expectancies of Smoking item banks that will serve to standardize the assessment of this construct among daily and nondaily cigarette smokers. Data came from daily (N = 4,201) and nondaily (N =1,183) smokers who completed an online survey. To identify a unidimensional set of items, we conducted item factor analyses, item response theory analyses, and differential item functioning analyses. Additionally, we evaluated the performance of fixed-item short forms (SFs) and computer adaptive tests (CATs) to efficiently assess the construct. Eighteen items were included in the item banks (15 common across daily and nondaily smokers, 1 unique to daily, 2 unique to nondaily). The item banks are strongly unidimensional, highly reliable (reliability = 0.95 for both), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.86). Results from simulated CATs indicated that, on average, less than 8 items are needed to assess the construct with adequate precision using the item banks. These analyses identified a new set of items that can assess the positive emotional and sensory expectancies of smoking in a reliable and standardized manner. Considerable efficiency in assessing this construct can be achieved by using the item bank SF, employing computer adaptive tests, or selecting subsets of items tailored to specific research or clinical purposes. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Core Items for a Standardized Resource Use Measure: Expert Delphi Consensus Survey.

PubMed

Thorn, Joanna C; Brookes, Sara T; Ridyard, Colin; Riley, Ruth; Hughes, Dyfrig A; Wordsworth, Sarah; Noble, Sian M; Thornton, Gail; Hollingworth, William

2018-06-01

Resource use measurement by patient recall is characterized by inconsistent methods and a lack of validation. A validated standardized resource use measure could increase data quality, improve comparability between studies, and reduce research burden. To identify a minimum set of core resource use items that should be included in a standardized adult instrument for UK health economic evaluation from a provider perspective. Health economists with experience of UK-based economic evaluations were recruited to participate in an electronic Delphi survey. Respondents were asked to rate 60 resource use items (e.g., medication names) on a scale of 1 to 9 according to the importance of the item in a generic context. Items considered less important according to predefined consensus criteria were dropped and a second survey was developed. In the second round, respondents received the median score and their own score from round 1 for each item alongside summarized comments and were asked to rerate items. A final project team meeting was held to determine the recommended core set. Forty-five participants completed round 1. Twenty-six items were considered less important and were dropped, 34 items were retained for the second round, and no new items were added. Forty-two respondents (93.3%) completed round 2, and greater consensus was observed. After the final meeting, 10 core items were selected, with further items identified as suitable for "bolt-on" questionnaire modules. The consensus on 10 items considered important in a generic context suggests that a standardized instrument for core resource use items is feasible. Copyright © 2018. Published by Elsevier Inc.

Radon exposure in uranium mining industry vs. exposure in tourist caves.

PubMed

Quindós Poncela, L; Fernández Navarro, P; Sainz Fernández, C; Gómez Arozamena, J; Bordonoba Perez, M

2004-01-01

There is a fairly general consensus among health physicists and radiation professionals that exposure to radon progeny is the largest and most variable contribution to the population's exposure to natural sources of radiation. However, this exposure is the subject of continuing debate concerning the validity of risk assessment and recommendations on how to act in radon-prone areas. The purpose of this contribution is to situate the radon issue in Spain in two very different settings. The first is a uranium mining industry located in Saelices el Chico (Salamanca), which is under strict control of the Spanish Nuclear Safety Council (CSN). We have measured radon concentrations in different workplaces in this mine over a five-year period. The second setting comprises four tourist caves, three of which are located in the province of Cantabria and the fourth on the Canary Island of Lanzarote. These caves are not subject to any administrative control of radiation exposure. Measured air 222Rn concentrations were used to estimate annual effective doses due to radon inhalation in the two settings, and dose values were found to be from 2 to 10 times lower in the uranium mine than in the tourist caves. These results were analysed in the context of the new European Basic Safety Standards Directive (EU-BSS, 1996).

Data mining and computationally intensive methods: summary of Group 7 contributions to Genetic Analysis Workshop 13.

PubMed

Costello, Tracy J; Falk, Catherine T; Ye, Kenny Q

2003-01-01

The Framingham Heart Study data, as well as a related simulated data set, were generously provided to the participants of the Genetic Analysis Workshop 13 in order that newly developed and emerging statistical methodologies could be tested on that well-characterized data set. The impetus driving the development of novel methods is to elucidate the contributions of genes, environment, and interactions between and among them, as well as to allow comparison between and validation of methods. The seven papers that comprise this group used data-mining methodologies (tree-based methods, neural networks, discriminant analysis, and Bayesian variable selection) in an attempt to identify the underlying genetics of cardiovascular disease and related traits in the presence of environmental and genetic covariates. Data-mining strategies are gaining popularity because they are extremely flexible and may have greater efficiency and potential in identifying the factors involved in complex disorders. While the methods grouped together here constitute a diverse collection, some papers asked similar questions with very different methods, while others used the same underlying methodology to ask very different questions. This paper briefly describes the data-mining methodologies applied to the Genetic Analysis Workshop 13 data sets and the results of those investigations. Copyright 2003 Wiley-Liss, Inc.

Developing and testing new smoking measures for the Health Plan Employer Data and Information Set.

PubMed

Pbert, Lori; Vuckovic, Nancy; Ockene, Judith K; Hollis, Jack F; Riedlinger, Karen

2003-04-01

To develop and test items for the Health Plan Employee Data and Information Set (HEDIS) that assess delivery of the full range of provider-delivered tobacco interventions. The authors identified potential items via literature review; items were reviewed by national experts. Face validity of candidate items was tested in focus groups. The final survey was sent to a random sample of 1711 adult primary care patients; the re-test survey was sent to self-identified smokers. The process identified reliable items to capture provider assessment of motivation and provision of assistance and follow-up. One can reliably assess patient self-report of provider delivery of the full range of brief tobacco interventions. Such assessment and feedback to health plans and providers may increase use of evidence-based brief interventions.

7 CFR 2902.50 - Multipurpose cleaners.

Code of Federal Regulations, 2010 CFR

2010-01-01

..., DEPARTMENT OF AGRICULTURE GUIDELINES FOR DESIGNATING BIOBASED PRODUCTS FOR FEDERAL PROCUREMENT Designated Items § 2902.50 Multipurpose cleaners. (a) Definition. Products used to clean dirt, grease, and grime from a variety of items in both industrial and domestic settings. This designated item does not include...

Judgmental Standard Setting Using a Cognitive Components Model.

ERIC Educational Resources Information Center

McGinty, Dixie; Neel, John H.

A new standard setting approach is introduced, called the cognitive components approach. Like the Angoff method, the cognitive components method generates minimum pass levels (MPLs) for each item. In both approaches, the item MPLs are summed for each judge, then averaged across judges to yield the standard. In the cognitive components approach,…

Determining the Capacity of Time-Based Selection

ERIC Educational Resources Information Center

Watson, Derrick G.; Kunar, Melina A.

2012-01-01

In visual search, a set of distractor items can be suppressed from future selection if they are presented (previewed) before a second set of search items arrive. This "visual marking" mechanism provides a top-down way of prioritizing the selection of new stimuli, at the expense of old stimuli already in the field (Watson & Humphreys,…

Combination of automated high throughput platforms, flow cytometry, and hierarchical clustering to detect cell state.

PubMed

Kitsos, Christine M; Bhamidipati, Phani; Melnikova, Irena; Cash, Ethan P; McNulty, Chris; Furman, Julia; Cima, Michael J; Levinson, Douglas

2007-01-01

This study examined whether hierarchical clustering could be used to detect cell states induced by treatment combinations that were generated through automation and high-throughput (HT) technology. Data-mining techniques were used to analyze the large experimental data sets to determine whether nonlinear, non-obvious responses could be extracted from the data. Unary, binary, and ternary combinations of pharmacological factors (examples of stimuli) were used to induce differentiation of HL-60 cells using a HT automated approach. Cell profiles were analyzed by incorporating hierarchical clustering methods on data collected by flow cytometry. Data-mining techniques were used to explore the combinatorial space for nonlinear, unexpected events. Additional small-scale, follow-up experiments were performed on cellular profiles of interest. Multiple, distinct cellular profiles were detected using hierarchical clustering of expressed cell-surface antigens. Data-mining of this large, complex data set retrieved cases of both factor dominance and cooperativity, as well as atypical cellular profiles. Follow-up experiments found that treatment combinations producing "atypical cell types" made those cells more susceptible to apoptosis. CONCLUSIONS Hierarchical clustering and other data-mining techniques were applied to analyze large data sets from HT flow cytometry. From each sample, the data set was filtered and used to define discrete, usable states that were then related back to their original formulations. Analysis of resultant cell populations induced by a multitude of treatments identified unexpected phenotypes and nonlinear response profiles.

Implementation of the EM Algorithm in the Estimation of Item Parameters: The BILOG Computer Program.

ERIC Educational Resources Information Center

Mislevy, Robert J.; Bock, R. Darrell

This paper reviews the basic elements of the EM approach to estimating item parameters and illustrates its use with one simulated and one real data set. In order to illustrate the use of the BILOG computer program, runs for 1-, 2-, and 3-parameter models are presented for the two sets of data. First is a set of responses from 1,000 persons to five…

29 CFR 570.33 - Prohibited occupations for minors 14 and 15 years of age.

Code of Federal Regulations, 2010 CFR

2010-07-01

... shall apply to all occupations other than the following: (a) Manufacturing, mining, or processing... revised text is set forth as follows: § 570.33 Occupations that are prohibited to minors 14 and 15 years... age: (a) Manufacturing, mining, or processing occupations, including occupations requiring the...

29 CFR 570.122 - General.

Code of Federal Regulations, 2010 CFR

2010-07-01

... other than the following: (1) Manufacturing, (2) Mining, (3) An occupation found by the Secretary to be..., the revised text is set forth as follows: § 570.122 General. (a) Specific exemptions from the child... sixteen years in any occupation other than manufacturing, mining, or an occupation found by the Secretary...

29 CFR 570.119 - Fourteen-year minimum.

Code of Federal Regulations, 2010 CFR

2010-07-01

... occupations other than manufacturing and mining, the Secretary is authorized to issue regulations or orders... Subpart C of this part. 29-30 [Reserved] (a) Manufacturing, mining, or processing occupations; (b... of the user, the revised text is set forth as follows: § 570.119 Fourteen-year minimum. With respect...

Restoring tropical forests on bauxite mined lands: lessons from the Brazilian Amazon

Treesearch

John A. Parrotta; Oliver H. Knowles

2001-01-01

Restoring self-sustaining tropical forest ecosystems on surface mined sites is a formidable challenge that requires the integration of proven reclamation techniques and reforestation strategies appropriate to specific site conditions, including landscape biodiversity patterns. Restorationists working in most tropical settings are usually hampered by lack of basic...

30 CFR 77.1707 - First aid equipment; location; minimum requirements.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false First aid equipment; location; minimum... OF UNDERGROUND COAL MINES Miscellaneous § 77.1707 First aid equipment; location; minimum requirements. (a) Each operator of a surface coal mine shall maintain a supply of the first aid equipment set forth...

Discovery of novel phosphonate natural products and their biosynthetic pathways by large-scale genome mining

USDA-ARS?s Scientific Manuscript database

Genome mining has revolutionized the field of natural products, providing hope that new antibiotics can be discovered in time before all remainders are rendered useless against multidrug resistant pathogens. While this approach has been successful in academic settings focused on small collections or...

Item Selection and Pre-equating with Empirical Item Characteristic Curves.

ERIC Educational Resources Information Center

Livingston, Samuel A.

An empirical item characteristic curve shows the probability of a correct response as a function of the student's total test score. These curves can be estimated from large-scale pretest data. They enable test developers to select items that discriminate well in the score region where decisions are made. A similar set of curves can be used to…

Identification of Differential Item Functioning in Multiple-Group Settings: A Multivariate Outlier Detection Approach

ERIC Educational Resources Information Center

Magis, David; De Boeck, Paul

2011-01-01

We focus on the identification of differential item functioning (DIF) when more than two groups of examinees are considered. We propose to consider items as elements of a multivariate space, where DIF items are outlying elements. Following this approach, the situation of multiple groups is a quite natural case. A robust statistics technique is…

National Longitudinal Study of the High School Class of 1972: Critical Data Base. 22U-884.

ERIC Educational Resources Information Center

Talbert, Robin

The National Longitudinal Study of the High School Class of 1972 (NLS) critical data base contains 151 items (plus background information) from the base year and followup questionnaires; about thirty-seven percent of all items. This set of critical items consists of: (1) basic demographic variables; (2) items necessary for defining activity states…

Existing reporting guidelines for clinical trials are not completely relevant for implantable medical devices: a systematic review.

PubMed

Motte, Anne-France; Diallo, Stéphanie; van den Brink, Hélène; Châteauvieux, Constance; Serrano, Carole; Naud, Carole; Steelandt, Julie; Alsac, Jean-Marc; Aubry, Pierre; Cour, Florence; Pellerin, Olivier; Pineau, Judith; Prognon, Patrice; Borget, Isabelle; Bonan, Brigitte; Martelli, Nicolas

2017-11-01

The aim of this study was to determine relevant items for reporting clinical trials on implantable medical devices (IMDs) and to identify reporting guidelines which include these items. A panel of experts identified the most relevant items for evaluating IMDs from an initial list based on reference papers. We then conducted a systematic review of articles indexed in MEDLINE. We retrieved reporting guidelines from the EQUATOR network's library for health research reporting. Finally, we screened these reporting guidelines to find those using our set of reporting items. Seven relevant reporting items were selected that related to four topics: randomization, learning curve, surgical setting, and device information. A total of 348 reporting guidelines were identified, among which 26 met our inclusion criteria. However, none of the 26 reporting guidelines presented all seven items together. The most frequently reported item was timing of randomization (65%). On the contrary, device information and learning curve effects were poorly specified. To our knowledge, this study is the first to identify specific items related to IMDs in reporting guidelines for clinical trials. We have shown that no existing reporting guideline is totally suitable for these devices. Copyright © 2017 Elsevier Inc. All rights reserved.

Differential item functioning analysis of the Vanderbilt Expertise Test for cars.

PubMed

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge.

Automated Data Base Implementation Requirements for the Avionics Planning Baseline - Army

DTIC Science & Technology

1983-07-01

PJRQT PJRSG .... PRJR owns PJRQTR Item EFT A32 A26 In record EFR Item ESFT A36 A40 In record ESFR Item EQPOC ALCPOC A20 In record EQR Iten EPHONE LPHONE...USING EF DUPLICATES ARE NOT ALLOWED WITHIN EQSEG. EF TYPE CHARACTER 4. EFT TYPE CHARACTER 32. EG TYPE CHARACTER 4. RECORD NAME IS ESFR LOCATION MODE... ESFR MANDATORY AUTOMATIC LINKED TO OWNER ASCENDING KEY IS ESF DUPLICATES NOT SET SELECTION THRU LOCATION MODE OF OWNER. SET NAME IS ESEQ MODE CHAIN

The factor structure of the Values in Action Inventory of Strengths (VIA-IS): An item-level exploratory structural equation modeling (ESEM) bifactor analysis.

PubMed

Ng, Vincent; Cao, Mengyang; Marsh, Herbert W; Tay, Louis; Seligman, Martin E P

2017-08-01

The factor structure of the Values in Action Inventory of Strengths (VIA-IS; Peterson & Seligman, 2004) has not been well established as a result of methodological challenges primarily attributable to a global positivity factor, item cross-loading across character strengths, and questions concerning the unidimensionality of the scales assessing character strengths. We sought to overcome these methodological challenges by applying exploratory structural equation modeling (ESEM) at the item level using a bifactor analytic approach to a large sample of 447,573 participants who completed the VIA-IS with all 240 character strengths items and a reduced set of 107 unidimensional character strength items. It was found that a 6-factor bifactor structure generally held for the reduced set of unidimensional character strength items; these dimensions were justice, temperance, courage, wisdom, transcendence, humanity, and an overarching general factor that is best described as dispositional positivity. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Measuring ability to assess claims about treatment effects: a latent trait analysis of items from the 'Claim Evaluation Tools' database using Rasch modelling.

PubMed

Austvoll-Dahlgren, Astrid; Guttersrud, Øystein; Nsangi, Allen; Semakula, Daniel; Oxman, Andrew D

2017-05-25

The Claim Evaluation Tools database contains multiple-choice items for measuring people's ability to apply the key concepts they need to know to be able to assess treatment claims. We assessed items from the database using Rasch analysis to develop an outcome measure to be used in two randomised trials in Uganda. Rasch analysis is a form of psychometric testing relying on Item Response Theory. It is a dynamic way of developing outcome measures that are valid and reliable. To assess the validity, reliability and responsiveness of 88 items addressing 22 key concepts using Rasch analysis. We administrated four sets of multiple-choice items in English to 1114 people in Uganda and Norway, of which 685 were children and 429 were adults (including 171 health professionals). We scored all items dichotomously. We explored summary and individual fit statistics using the RUMM2030 analysis package. We used SPSS to perform distractor analysis. Most items conformed well to the Rasch model, but some items needed revision. Overall, the four item sets had satisfactory reliability. We did not identify significant response dependence between any pairs of items and, overall, the magnitude of multidimensionality in the data was acceptable. The items had a high level of difficulty. Most of the items conformed well to the Rasch model's expectations. Following revision of some items, we concluded that most of the items were suitable for use in an outcome measure for evaluating the ability of children or adults to assess treatment claims. © 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.

Development of the PROMIS health expectancies of smoking item banks.

PubMed

Edelen, Maria Orlando; Tucker, Joan S; Shadel, William G; Stucky, Brian D; Cerully, Jennifer; Li, Zhen; Hansen, Mark; Cai, Li

2014-09-01

Smokers' health-related outcome expectancies are associated with a number of important constructs in smoking research, yet there are no measures currently available that focus exclusively on this domain. This paper describes the development and evaluation of item banks for assessing the health expectancies of smoking. Using data from a sample of daily (N = 4,201) and nondaily (N = 1,183) smokers, we conducted a series of item factor analyses, item response theory analyses, and differential item functioning analyses (according to gender, age, and race/ethnicity) to arrive at a unidimensional set of health expectancies items for daily and nondaily smokers. We also evaluated the performance of short forms (SFs) and computer adaptive tests (CATs) to efficiently assess health expectancies. A total of 24 items were included in the Health Expectancies item banks; 13 items are common across daily and nondaily smokers, 6 are unique to daily, and 5 are unique to nondaily. For both daily and nondaily smokers, the Health Expectancies item banks are unidimensional, reliable (reliability = 0.95 and 0.96, respectively), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.87). Results from simulated CATs showed that health expectancies can be assessed with good precision with an average of 5-6 items adaptively selected from the item banks. Health expectancies of smoking can be assessed on the basis of these item banks via SFs, CATs, or through a tailored set of items selected for a specific research purpose. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of the PROMIS nicotine dependence item banks.

PubMed

Shadel, William G; Edelen, Maria Orlando; Tucker, Joan S; Stucky, Brian D; Hansen, Mark; Cai, Li

2014-09-01

Nicotine dependence is a core construct important for understanding cigarette smoking and smoking cessation behavior. This article describes analyses conducted to develop and evaluate item banks for assessing nicotine dependence among daily and nondaily smokers. Using data from a sample of daily (N = 4,201) and nondaily (N =1,183) smokers, we conducted a series of item factor analyses, item response theory analyses, and differential item functioning analyses (according to gender, age, and race/ethnicity) to arrive at a unidimensional set of nicotine dependence items for daily and nondaily smokers. We also evaluated performance of short forms (SFs) and computer adaptive tests (CATs) to efficiently assess dependence. A total of 32 items were included in the Nicotine Dependence item banks; 22 items are common across daily and nondaily smokers, 5 are unique to daily smokers, and 5 are unique to nondaily smokers. For both daily and nondaily smokers, the Nicotine Dependence item banks are strongly unidimensional, highly reliable (reliability = 0.97 and 0.97, respectively), and perform similarly across gender, age, and race/ethnicity groups. SFs common to daily and nondaily smokers consist of 8 and 4 items (reliability = 0.91 and 0.81, respectively). Results from simulated CATs showed that dependence can be assessed with very good precision for most respondents using fewer than 6 items adaptively selected from the item banks. Nicotine dependence on cigarettes can be assessed on the basis of these item banks via one of the SFs, by using CATs, or through a tailored set of items selected for a specific research purpose. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Development of the PROMIS negative psychosocial expectancies of smoking item banks.

PubMed

Stucky, Brian D; Edelen, Maria Orlando; Tucker, Joan S; Shadel, William G; Cerully, Jennifer; Kuhfeld, Megan; Hansen, Mark; Cai, Li

2014-09-01

Negative psychosocial expectancies of smoking include aspects of social disapproval and disappointment in oneself. This paper describes analyses conducted to develop and evaluate item banks for assessing psychosocial expectancies among daily and nondaily smokers. Using data from a sample of daily (N = 4,201) and nondaily (N =1,183) smokers, we conducted a series of item factor analyses, item response theory analyses, and differential item functioning analyses (according to gender, age, and race/ethnicity) to arrive at a unidimensional set of psychosocial expectancies items for daily and nondaily smokers. We also evaluated performance of short forms (SFs) and computer adaptive tests (CATs) to efficiently assess psychosocial expectancies. A total of 21 items were included in the Psychosocial Expectancies item banks: 14 items are common across daily and nondaily smokers, 6 are unique to daily, and 1 is unique to nondaily. For both daily and nondaily smokers, the Psychosocial Expectancies item banks are strongly unidimensional, highly reliable (reliability = 0.95 and 0.93, respectively), and perform similarly across gender, age, and race/ethnicity groups. A SF common to daily and nondaily smokers consists of 6 items (reliability = 0.85). Results from simulated CATs showed that, on average, fewer than 8 items are needed to assess psychosocial expectancies with adequate precision when using the item banks. Psychosocial expectancies of smoking can be assessed on the basis of these item banks via the SF, by using CAT, or through a tailored set of items selected for a specific research purpose. © The Author 2014. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.

Measuring sexual orientation in adolescent health surveys: evaluation of eight school-based surveys.

PubMed

Saewyc, Elizabeth M; Bauer, Greta R; Skay, Carol L; Bearinger, Linda H; Resnick, Michael D; Reis, Elizabeth; Murphy, Aileen

2004-10-01

To examine the performance of various items measuring sexual orientation within 8 school-based adolescent health surveys in the United States and Canada from 1986 through 1999. Analyses examined nonresponse and unsure responses to sexual orientation items compared with other survey items, demographic differences in responses, tests for response set bias, and congruence of responses to multiple orientation items; analytical methods included frequencies, contingency tables with Chi-square, and ANOVA with least significant differences (LSD)post hoc tests; all analyses were conducted separately by gender. In all surveys, nonresponse rates for orientation questions were similar to other sexual questions, but not higher; younger students, immigrants, and students with learning disabilities were more likely to skip items or select "unsure." Sexual behavior items had the lowest nonresponse, but fewer than half of all students reported sexual behavior, limiting its usefulness for indicating orientation. Item placement in the survey, wording, and response set bias all appeared to influence nonresponse and unsure rates. Specific recommendations include standardizing wording across future surveys, and pilot testing items with diverse ages and ethnic groups of teens before use. All three dimensions of orientation should be assessed where possible; when limited to single items, sexual attraction may be the best choice. Specific wording suggestions are offered for future surveys.

Application of text mining for customer evaluations in commercial banking

NASA Astrophysics Data System (ADS)

Tan, Jing; Du, Xiaojiang; Hao, Pengpeng; Wang, Yanbo J.

2015-07-01

Nowadays customer attrition is increasingly serious in commercial banks. To combat this problem roundly, mining customer evaluation texts is as important as mining customer structured data. In order to extract hidden information from customer evaluations, Textual Feature Selection, Classification and Association Rule Mining are necessary techniques. This paper presents all three techniques by using Chinese Word Segmentation, C5.0 and Apriori, and a set of experiments were run based on a collection of real textual data that includes 823 customer evaluations taken from a Chinese commercial bank. Results, consequent solutions, some advice for the commercial bank are given in this paper.

Text Mining in Organizational Research

PubMed Central

Kobayashi, Vladimer B.; Berkers, Hannah A.; Kismihók, Gábor; Den Hartog, Deanne N.

2017-01-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies. PMID:29881248

Text Mining in Organizational Research.

PubMed

Kobayashi, Vladimer B; Mol, Stefan T; Berkers, Hannah A; Kismihók, Gábor; Den Hartog, Deanne N

2018-07-01

Despite the ubiquity of textual data, so far few researchers have applied text mining to answer organizational research questions. Text mining, which essentially entails a quantitative approach to the analysis of (usually) voluminous textual data, helps accelerate knowledge discovery by radically increasing the amount data that can be analyzed. This article aims to acquaint organizational researchers with the fundamental logic underpinning text mining, the analytical stages involved, and contemporary techniques that may be used to achieve different types of objectives. The specific analytical techniques reviewed are (a) dimensionality reduction, (b) distance and similarity computing, (c) clustering, (d) topic modeling, and (e) classification. We describe how text mining may extend contemporary organizational research by allowing the testing of existing or new research questions with data that are likely to be rich, contextualized, and ecologically valid. After an exploration of how evidence for the validity of text mining output may be generated, we conclude the article by illustrating the text mining process in a job analysis setting using a dataset composed of job vacancies.

Examining psychosocial and physical hazards in the Ghanaian mining industry and their implications for employees' safety experience.

PubMed

Amponsah-Tawiah, Kwesi; Jain, Aditya; Leka, Stavroula; Hollis, David; Cox, Tom

2013-06-01

In addition to hazardous conditions that are prevalent in mines, there are various physical and psychosocial risk factors that can affect mine workers' safety and health. Without due diligence to mine safety, these risk factors can affect workers' safety experience, in terms of near misses, disabling injuries and accidents experienced or witnessed by workers. This study sets out to examine the effects of physical and psychosocial risk factors on workers' safety experience in a sample of Ghanaian miners. 307 participants from five mining companies responded to a cross sectional survey examining physical and psychosocial hazards and their implications for employees' safety experience. Zero-inflated Poisson regression models indicated that mining conditions, equipment, ambient conditions, support and security, and work demands and control are significant predictors of near misses, disabling injuries, and accidents experienced or witnessed by workers. The type of mine had important implications for workers' safety experience. Copyright © 2013 Elsevier Ltd and National Safety Council. All rights reserved.

Fuzzy linear model for production optimization of mining systems with multiple entities

NASA Astrophysics Data System (ADS)

Vujic, Slobodan; Benovic, Tomo; Miljanovic, Igor; Hudej, Marjan; Milutinovic, Aleksandar; Pavlovic, Petar

2011-12-01

Planning and production optimization within multiple mines or several work sites (entities) mining systems by using fuzzy linear programming (LP) was studied. LP is the most commonly used operations research methods in mining engineering. After the introductory review of properties and limitations of applying LP, short reviews of the general settings of deterministic and fuzzy LP models are presented. With the purpose of comparative analysis, the application of both LP models is presented using the example of the Bauxite Basin Niksic with five mines. After the assessment, LP is an efficient mathematical modeling tool in production planning and solving many other single-criteria optimization problems of mining engineering. After the comparison of advantages and deficiencies of both deterministic and fuzzy LP models, the conclusion presents benefits of the fuzzy LP model but is also stating that seeking the optimal plan of production means to accomplish the overall analysis that will encompass the LP model approaches.

Evaluation of the environmental contamination at an abandoned mining site using multivariate statistical techniques--the Rodalquilar (Southern Spain) mining district.

PubMed

Bagur, M G; Morales, S; López-Chicano, M

2009-11-15

Unsupervised and supervised pattern recognition techniques such as hierarchical cluster analysis, principal component analysis, factor analysis and linear discriminant analysis have been applied to water samples recollected in Rodalquilar mining district (Southern Spain) in order to identify different sources of environmental pollution caused by the abandoned mining industry. The effect of the mining activity on waters was monitored determining the concentration of eleven elements (Mn, Ba, Co, Cu, Zn, As, Cd, Sb, Hg, Au and Pb) by inductively coupled plasma mass spectrometry (ICP-MS). The Box-Cox transformation has been used to transform the data set in normal form in order to minimize the non-normal distribution of the geochemical data. The environmental impact is affected mainly by the mining activity developed in the zone, the acid drainage and finally by the chemical treatment used for the benefit of gold.

Data Mining for Understanding and Impriving Decision-Making Affecting Ground Delay Programs

NASA Technical Reports Server (NTRS)

Kulkarni, Deepak; Wang, Yao Xun; Sridhar, Banavar

2013-01-01

The continuous growth in the demand for air transportation results in an imbalance between airspace capacity and traffic demand. The airspace capacity of a region depends on the ability of the system to maintain safe separation between aircraft in the region. In addition to growing demand, the airspace capacity is severely limited by convective weather. During such conditions, traffic managers at the FAA's Air Traffic Control System Command Center (ATCSCC) and dispatchers at various Airlines' Operations Center (AOC) collaborate to mitigate the demand-capacity imbalance caused by weather. The end result is the implementation of a set of Traffic Flow Management (TFM) initiatives such as ground delay programs, reroute advisories, flow metering, and ground stops. Data Mining is the automated process of analyzing large sets of data and then extracting patterns in the data. Data mining tools are capable of predicting behaviors and future trends, allowing an organization to benefit from past experience in making knowledge-driven decisions. The work reported in this paper is focused on ground delay programs. Data mining algorithms have the potential to develop associations between weather patterns and the corresponding ground delay program responses. If successful, they can be used to improve and standardize TFM decision resulting in better predictability of traffic flows on days with reliable weather forecasts. The approach here seeks to develop a set of data mining and machine learning models and apply them to historical archives of weather observations and forecasts and TFM initiatives to determine the extent to which the theory can predict and explain the observed traffic flow behaviors.

Linking Existing Instruments to Develop an Activity of Daily Living Item Bank.

PubMed

Li, Chih-Ying; Romero, Sergio; Bonilha, Heather S; Simpson, Kit N; Simpson, Annie N; Hong, Ickpyo; Velozo, Craig A

2018-03-01

This study examined dimensionality and item-level psychometric properties of an item bank measuring activities of daily living (ADL) across inpatient rehabilitation facilities and community living centers. Common person equating method was used in the retrospective veterans data set. This study examined dimensionality, model fit, local independence, and monotonicity using factor analyses and fit statistics, principal component analysis (PCA), and differential item functioning (DIF) using Rasch analysis. Following the elimination of invalid data, 371 veterans who completed both the Functional Independence Measure (FIM) and minimum data set (MDS) within 6 days were retained. The FIM-MDS item bank demonstrated good internal consistency (Cronbach's α = .98) and met three rating scale diagnostic criteria and three of the four model fit statistics (comparative fit index/Tucker-Lewis index = 0.98, root mean square error of approximation = 0.14, and standardized root mean residual = 0.07). PCA of Rasch residuals showed the item bank explained 94.2% variance. The item bank covered the range of θ from -1.50 to 1.26 (item), -3.57 to 4.21 (person) with person strata of 6.3. The findings indicated the ADL physical function item bank constructed from FIM and MDS measured a single latent trait with overall acceptable item-level psychometric properties, suggesting that it is an appropriate source for developing efficient test forms such as short forms and computerized adaptive tests.

The influence of regional geological settings on the seismic hazard level in copper mines in the Legnica-Głogów Copper Belt Area (Poland)

NASA Astrophysics Data System (ADS)

Burtan, Zbigniew

2017-11-01

The current level of rockburst hazard in copper mines of the (LGOM) Legnica- Głogów Copper Belt Area is mostly the consequence of mining-induced seismicity, whilst the majority of rockbursting events registered to date were caused by high-energy tremors. The analysis of seismic readings in recent years reveals that the highest seismic activity among the copper mines in the LGOM is registered in the mine Rudna. This study investigates the seismic activity in the rock strata in the Rudna mine fields over the years 2006-2015. Of particular interest are the key seismicity parameters: the number of registered seismic events, the total energy emissions, the energy index. It appears that varied seismic activity in the area may be the function of several variables: effective mining thickness, the thickness of burst-prone strata and tectonic intensity. The results support and corroborate the view that principal factors influencing the actual seismic hazard level are regional geological conditions in the copper mines within the Legnica-Głogów Copper Belt Area.

Parameter Estimation for Thurstone Choice Models

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

Vojnovic, Milan; Yun, Seyoung

We consider the estimation accuracy of individual strength parameters of a Thurstone choice model when each input observation consists of a choice of one item from a set of two or more items (so called top-1 lists). This model accommodates the well-known choice models such as the Luce choice model for comparison sets of two or more items and the Bradley-Terry model for pair comparisons. We provide a tight characterization of the mean squared error of the maximum likelihood parameter estimator. We also provide similar characterizations for parameter estimators defined by a rank-breaking method, which amounts to deducing one ormore » more pair comparisons from a comparison of two or more items, assuming independence of these pair comparisons, and maximizing a likelihood function derived under these assumptions. We also consider a related binary classification problem where each individual parameter takes value from a set of two possible values and the goal is to correctly classify all items within a prescribed classification error. The results of this paper shed light on how the parameter estimation accuracy depends on given Thurstone choice model and the structure of comparison sets. In particular, we found that for unbiased input comparison sets of a given cardinality, when in expectation each comparison set of given cardinality occurs the same number of times, for a broad class of Thurstone choice models, the mean squared error decreases with the cardinality of comparison sets, but only marginally according to a diminishing returns relation. On the other hand, we found that there exist Thurstone choice models for which the mean squared error of the maximum likelihood parameter estimator can decrease much faster with the cardinality of comparison sets. We report empirical evaluation of some claims and key parameters revealed by theory using both synthetic and real-world input data from some popular sport competitions and online labor platforms.« less

Attitudes towards Internationalism through the Lens of Cognitive Effort, Global Mindset, and Cultural Intelligence

ERIC Educational Resources Information Center

Romano, Joan; Platania, Judith

2014-01-01

In the current study we examine attitudes towards internationalism through the lens of a specific set of constructs necessary in defining an effective global leader. One hundred fifty-nine undergraduates responded to items measuring need for cognition, cultural intelligence, and a set of items measuring the correlates of global mindset. In…

Item Response Theory Evaluation of the Light and Spectroscopy Concept Inventory National Data Set

ERIC Educational Resources Information Center

Wallace, Colin S.; Chambers, Timothy G.; Prather, Edward E.

2018-01-01

[This paper is part of the Focused Collection on Astronomy Education Research.] This paper presents the first item response theory (IRT) analysis of the national data set on introductory, general education, college-level astronomy teaching using the Light and Spectroscopy Concept Inventory (LSCI). We used the difference between students' pre- and…

Using Empirical Data to Set Cutoff Scores.

ERIC Educational Resources Information Center

Hills, John R.

Six experimental approaches to the problems of setting cutoff scores and choosing proper test length are briefly mentioned. Most of these methods share the premise that a test is a random sample of items, from a domain associated with a carefully specified objective. Each item is independent and is scored zero or one, with no provision for…

Subitizing Reflects Visuo-Spatial Object Individuation Capacity

ERIC Educational Resources Information Center

Piazza, Manuela; Fumarola, Antonia; Chinello, Alessandro; Melcher, David

2011-01-01

Subitizing is the immediate apprehension of the exact number of items in small sets. Despite more than a 100 years of research around this phenomenon, its nature and origin are still unknown. One view posits that it reflects a number estimation process common for small and large sets, which precision decreases as the number of items increases,…

Optimizing Balanced Incomplete Block Designs for Educational Assessments

ERIC Educational Resources Information Center

van der Linden, Wim J.; Veldkamp, Bernard P.; Carlson, James E.

2004-01-01

A popular design in large-scale educational assessments as well as any other type of survey is the balanced incomplete block design. The design is based on an item pool split into a set of blocks of items that are assigned to sets of "assessment booklets." This article shows how the problem of calculating an optimal balanced incomplete block…

Item Selection, Evaluation, and Simple Structure in Personality Data

PubMed Central

Pettersson, Erik; Turkheimer, Eric

2010-01-01

We report an investigation of the genesis and interpretation of simple structure in personality data using two very different self-reported data sets. The first consists of a set of relatively unselected lexical descriptors, whereas the second is based on responses to a carefully constructed instrument. In both data sets, we explore the degree of simple structure by comparing factor solutions to solutions from simulated data constructed to have either strong or weak simple structure. The analysis demonstrates that there is little evidence of simple structure in the unselected items, and a moderate degree among the selected items. In both instruments, however, much of the simple structure that could be observed originated in a strong dimension of positive vs. negative evaluation. PMID:20694168

Risky business or not? FIFOs, sexual risk taking and the Australian mining industry.

PubMed

O'Mullan, Cathy; Debattista, Joseph; Browne, Matthew

2016-04-01

Issue addressed The fly-in, fly-out (FIFO) and drive-in, drive-out (DIDO) models of mining in Australia have led to concerns about adverse health and psychosocial impacts. Despite speculation that increased levels of sexually transmitted infections (STIs) in Australia, including HIV, are associated with FIFO/DIDO work, we know little about sexual risk-taking behaviours in mining populations. This study explores differences in sexual risk taking and perceptions of risk between FIFO/DIDO miners and residential miners. Methods A cross-sectional survey was administered to a sample (n=444) of male miners working in Queensland, Australia. The self-completed survey contained 49 questions relating to knowledge, attitudes and behaviour and included demographic information and specific items related to sex and relationships. Results FIFO/DIDO status was not associated with any differential sexual risk-taking behaviours, except for an increased probability of reporting 'ever being diagnosed with an STI'; 10.8% of FIFO/DIDO respondents versus 3.6% of others (x(2) (1)=4.43, P=0.35). Conclusions Our results appear to counter anecdotal evidence that FIFO/DIDO miners engage in higher sexual risk behaviours when compared with residential miners. So what? Anecdotal evidence linking the rise of sexually transmitted infections with the FIFO/DIDO mining workforce could drive costly and unnecessary approaches to prevention. Further research, surveillance and monitoring are required to inform health promotion interventions.

Study on the Rule of Super Strata Movement and Subsidence

NASA Astrophysics Data System (ADS)

Yao, Shunli; Yuan, Hongyong; Jiang, Fuxing; Chen, Tao; Wu, Peng

2018-01-01

The movement of key strata is related to the safety of the whole earth’s surface for coal mining under super strata. Based on the key strata theory, the paper comprehensively analyzes the characteristics of the subsidence before and after the instability of the super strata by studing through FLAC3D and microseismic dynamic monitoring of the surface rock movement observation. The stability of the super strata movement is analyzed according to the characteristic value of the subsidence. The subsidence law and quantitative indexes under the control of the super rock strata that provides basis for the prevention and control of surface risk, optimize mining area and face layout and reasonably set mining boundary around mining area. It provides basis for the even growth of mine safety production and regional public safety.

Robotic Mining Competition - Setup

NASA Image and Video Library

2018-05-14

On the first day of NASA's 9th Robotic Mining Competition, set-up day on May 14, team members from the South Dakota School of Mines & Technology work on their robot miner in the RobotPits in the Educator Resource Center at Kennedy Space Center Visitor Complex in Florida. More than 40 student teams from colleges and universities around the U.S. will use their mining robots to dig in a supersized sandbox filled with BP-1, or simulated Martian soil, gravel and rocks, and participate in other competition requirements. The Robotic Mining Competition is a NASA Human Exploration and Operations Mission Directorate project designed to encourage students in science, technology, engineering and math, or STEM fields. The project provides a competitive environment to foster innovative ideas and solutions that could be used on NASA's deep space missions.

Exploring virtual mental practice in maintenance task training

PubMed Central

Bauerle, Tim; Brnich, Michael J.; Navoyski, Jason

2016-01-01

Purpose – This paper aims to contribute to a general understanding of mental practice by investigating the utility of and participant reaction to a virtual reality maintenance training among underground coal mine first responders. Design/methodology/approach – Researchers at the National Institute for Occupational Safety and Health's Office of Mine Safety and Health Research (OMSHR) developed software to provide opportunities for mine rescue team members to learn to inspect, assemble and test their closed-circuit breathing apparatus and to practice those skills. In total, 31 mine rescue team members utilized OMSHR's BG 4 Benching Trainer software and provided feedback to the development team. After training, participants completed a brief post-training questionnaire, which included demographics, perceived training climate and general training evaluation items. Findings – The results overall indicate a generally positive reaction to and high perceived utility of the BG 4 benching software. In addition, the perceived training climate appears to have an effect on the perceived utility of the mental practice virtual reality game, with benchmen from mines with more positive training climates reporting greater perceived efficacy in the training's ability to prepare trainees for real emergencies. Originality/value – This paper helps to broaden current applications of mental practice and is one of the few empirical investigations into a non-rehabilitation virtual reality extension of mental practice. This paper also contributes to the growing literature advocating for greater usage of accurate and well-informed mental practice techniques, tools and methodologies, especially for occupational populations with limitations on exposure to hands-on training. PMID:27594801

Surface Mining and Reclamation Effects on Flood Response of Watersheds in the Central Appalachian Plateau Region

NASA Technical Reports Server (NTRS)

Ferrari, J. R.; Lookingbill, T. R.; McCormick, B.; Townsend, P. A.; Eshleman, K. N.

2009-01-01

Surface mining of coal and subsequent reclamation represent the dominant land use change in the central Appalachian Plateau (CAP) region of the United States. Hydrologic impacts of surface mining have been studied at the plot scale, but effects at broader scales have not been explored adequately. Broad-scale classification of reclaimed sites is difficult because standing vegetation makes them nearly indistinguishable from alternate land uses. We used a land cover data set that accurately maps surface mines for a 187-km2 watershed within the CAP. These land cover data, as well as plot-level data from within the watershed, are used with HSPF (Hydrologic Simulation Program-Fortran) to estimate changes in flood response as a function of increased mining. Results show that the rate at which flood magnitude increases due to increased mining is linear, with greater rates observed for less frequent return intervals. These findings indicate that mine reclamation leaves the landscape in a condition more similar to urban areas rather than does simple deforestation, and call into question the effectiveness of reclamation in terms of returning mined areas to the hydrological state that existed before mining.

Physical environment and hydrologic characteristics of coal-mining areas in Missouri

USGS Publications Warehouse

Vaill, J.E.; Barks, James H.

1980-01-01

Hydrologic information for the north-central and western coal-mining regions of Missouri is needed to define the hydrologic system in these areas of major historic and planned coal development. This report describes the physical setting, climate, coal-mining practices, general hydrologic system, and the current (1980) hydrologie data base in these two coal-mining regions. Streamflow in both mining regions is poorly sustained. Stream water quality generally varies with location and the magnitude of coal-mining activity in a watershed. Streams in non coal-mining areas generally have dissolved-solids concentrations less than 400 milligrams per liter. Acid-mine drainage has seriously affected some streams by reducing the pH to less than 4.0 and increasing the dissolved-solids concentrations to greater than 1,000 milligrams per liter. This has resulted in fish kills in some instances. Ground-water movement is impeded both laterally and vertically in both mining regions, especially in western Missouri, because of the low hydraulic conductivity of the rocks of Pennsylvanian age. The quality of ground water varies widely depending on location and depth. Ground water commonly contains high concentrations of iron and sulfate, and dissolved-solids concentrations generally are greater than 1,000 milligrams per liter.

A Graphical Approach to Item Analysis. Research Report. ETS RR-04-10

ERIC Educational Resources Information Center

Livingston, Samuel A.; Dorans, Neil J.

2004-01-01

This paper describes an approach to item analysis that is based on the estimation of a set of response curves for each item. The response curves show, at a glance, the difficulty and the discriminating power of the item and the popularity of each distractor, at any level of the criterion variable (e.g., total score). The curves are estimated by…

The Disgust Scale: Item Analysis, Factor Structure, and Suggestions for Refinement

ERIC Educational Resources Information Center

Olatunji, Bunmi O.; Williams, Nathan L.; Tolin, David F.; Abramowitz, Jonathan S.; Sawchuk, Craig N.; Lohr, Jeffrey M.; Elwood, Lisa S.

2007-01-01

In the 4 studies presented (N = 1,939), a converging set of analyses was conducted to evaluate the item adequacy, factor structure, reliability, and validity of the Disgust Scale (DS; J. Haidt, C. McCauley, & P. Rozin, 1994). The results suggest that 7 items (i.e., Items 2, 7, 8, 21, 23, 24, and 25) should be considered for removal from the DS.…

Department of Defense Logistics Roadmap 2008. Volume 1

DTIC Science & Technology

2008-07-01

machine readable identification mark on the Department’s tangible qualifying assets, and establishes the data management protocols needed to...uniquely identify items with a Unique Item Identifier (UII) via machine - readable information (MRI) marking represented by a two-dimensional data...property items with a machine -readable Unique Item Identifier (UII), which is a set of globally unique data elements. The UII is used in functional

Diverse Food Items Are Similarly Categorized by 8- to 13-Year-Old Children

ERIC Educational Resources Information Center

Beltran, Alicia; Knight Sepulveda, Karina; Watson, Kathy; Baranowski, Tom; Baranowski, Janice; Islam, Noemi; Missaghian, Mariam

2008-01-01

Objective: Assess how 8- to 13-year-old children categorized and labeled food items for possible use as part of a food search strategy in a computerized 24-hour dietary recall. Design: A set of 62 cards with pictures and names of food items from 18 professionally defined food groups was sorted by each child into piles of similar food items.…

Automatic generation of Web mining environments

NASA Astrophysics Data System (ADS)

Cibelli, Maurizio; Costagliola, Gennaro

1999-02-01

The main problem related to the retrieval of information from the world wide web is the enormous number of unstructured documents and resources, i.e., the difficulty of locating and tracking appropriate sources. This paper presents a web mining environment (WME), which is capable of finding, extracting and structuring information related to a particular domain from web documents, using general purpose indices. The WME architecture includes a web engine filter (WEF), to sort and reduce the answer set returned by a web engine, a data source pre-processor (DSP), which processes html layout cues in order to collect and qualify page segments, and a heuristic-based information extraction system (HIES), to finally retrieve the required data. Furthermore, we present a web mining environment generator, WMEG, that allows naive users to generate a WME specific to a given domain by providing a set of specifications.

Development of a Survey to Explore Factors Influencing the Adoption of Best Practices for Diabetic Foot Ulcer Offloading.

PubMed

Bleau Lavigne, Maude; Reeves, Isabelle; Sasseville, Marie-Josée; Loignon, Christine

The primary purpose of this study was to develop 2 survey tools to explore factors influencing adoption of best practices for diabetic foot ulcer offloading treatment in primary health care settings. One survey was intended for the patients receiving care for a diabetic foot ulcer in primary health care settings and the other was intended for the health professionals providing treatment. The second purpose of this study was to evaluate the psychometric properties of the 2 surveys. Development and validation of survey instruments. Two surveys were developed using a published guide. Following review of pertinent literature and identification of variables to be measured, a bank of items was developed and pretested to determine clarity of the item and responses. Psychometric testing comprised measurement of content validity index (CVI) and intraclass correlation coefficient (ICC). Only items obtaining satisfactory CVI and ICC scores were included in the final version of the surveys. The final version of the patient survey contained 41 items and the final version of the survey for health care professionals contained 21 items. The patient-intended survey's items demonstrate high content validity scores and satisfactory test-retest reliability scores. The overall CVI score was 0.98. Forty of the 49 items eligible for testing obtain satisfactory ICC scores. One item's test-retest reliability could not be tested but it was retained based on its high CVI. The health professional-intended survey, an overall CVI score of 0.91 but items had lower ICC scores (63%, 31 of the 49 items), did not achieve a satisfactory ICC score for inclusion in the final instrument. This project led to development of 2 instruments designed to identify and explore factors influencing adoption of best practices for diabetic foot ulcer offloading treatment in the primary health care setting. Future research and testing is required to translate these French surveys into English and additional languages, in order to reach a broader population.

When less is more: validating a brief scale to rate interprofessional team competencies.

PubMed

Lie, Désirée A; Richter-Lagha, Regina; Forest, Christopher P; Walsh, Anne; Lohenry, Kevin

2017-01-01

There is a need for validated and easy-to-apply behavior-based tools for assessing interprofessional team competencies in clinical settings. The seven-item observer-based Modified McMaster-Ottawa scale was developed for the Team Objective Structured Clinical Encounter (TOSCE) to assess individual and team performance in interprofessional patient encounters. We aimed to improve scale usability for clinical settings by reducing item numbers while maintaining generalizability; and to explore the minimum number of observed cases required to achieve modest generalizability for giving feedback. We administered a two-station TOSCE in April 2016 to 63 students split into 16 newly-formed teams, each consisting of four professions. The stations were of similar difficulty. We trained sixteen faculty to rate two teams each. We examined individual and team performance scores using generalizability (G) theory and principal component analysis (PCA). The seven-item scale shows modest generalizability (.75) with individual scores. PCA revealed multicollinearity and singularity among scale items and we identified three potential items for removal. Reducing items for individual scores from seven to four (measuring Collaboration, Roles, Patient/Family-centeredness, and Conflict Management) changed scale generalizability from .75 to .73. Performance assessment with two cases is associated with reasonable generalizability (.73). Students in newly-formed interprofessional teams show a learning curve after one patient encounter. Team scores from a two-station TOSCE demonstrate low generalizability whether the scale consisted of four (.53) or seven items (.55). The four-item Modified McMaster-Ottawa scale for assessing individual performance in interprofessional teams retains the generalizability and validity of the seven-item scale. Observation of students in teams interacting with two different patients provides reasonably reliable ratings for giving feedback. The four-item scale has potential for assessing individual student skills and the impact of IPE curricula in clinical practice settings. IPE: Interprofessional education; SP: Standardized patient; TOSCE: Team objective structured clinical encounter.

Accuracy Assessment of Geometrical Elements for Setting-Out in Horizontal Plane of Conveying Chambers at the Bauxite Mine "KOSTURI" Srebrenica

NASA Astrophysics Data System (ADS)

Milutinović, Aleksandar; Ganić, Aleksandar; Tokalić, Rade

2014-03-01

Setting-out of objects on the exploitation field of the mine, both in surface mining and in the underground mines, is determined by the specified setting-out accuracy of reference points, which are best to define spatial position of the object projected. For the purpose of achieving of the specified accuracy, it is necessary to perform a priori accuracy assessment of parameters, which are to be used when performing setting-out. Based on the a priori accuracy assessment, verification of the quality of geometrical setting- -out elements specified in the layout; definition of the accuracy for setting-out of geometrical elements; selection of setting-out method; selection at the type and class of instruments and tools that need to be applied in order to achieve predefined accuracy. The paper displays the accuracy assessment of geometrical elements for setting-out of the main haul gallery, haul downcast and helical conveying downcasts in shape of an inclined helix in horizontal plane, using the example of the underground bauxite mine »Kosturi«, Srebrenica. Wytyczanie obiektów na polu wydobywczym w kopalniach, zarówno podziemnych jak i odkrywkowych, zależy w dużej mierze od określonej dokładności wytyczania punktów referencyjnych, przy pomocy których określane jest następnie położenie przestrzenne pozostałych obiektów. W celu uzyskania założonej dokładności, należy przeprowadzić wstępną analizę dokładności oszacowania parametrów które następnie wykorzystane będą w procesie wytyczania. W oparciu o wyniki wstępnej analizy dokładności dokonuje się weryfikacji jakości geometrycznego wytyczenia elementów zaznaczonych na szkicu, uwzględniając te wyniki dobrać należy odpowiednią metodę wytyczania i rodzaj oraz klasę wykorzystywanych narzędzi i instrumentów, tak by osiągnąć założony poziom dokładności. W pracy przedstawiono oszacowanie dokładności wytyczania elementów geometrycznych dla głównego chodnika transportowego, chodnika upadowego oraz szybów wlotowych, naniesionych na płaszczyznę poziomą, dla podziemnej kopalni boksytu "Kosturi' w Srebrenicy.

Pesticide applicators questionnaire content validation: A fuzzy delphi method.

PubMed

Manakandan, S K; Rosnah, I; Mohd Ridhuan, J; Priya, R

2017-08-01

The most crucial step in forming a set of survey questionnaire is deciding the appropriate items in a construct. Retaining irrelevant items and removing important items will certainly mislead the direction of a particular study. This article demonstrates Fuzzy Delphi method as one of the scientific analysis technique to consolidate consensus agreement within a panel of experts pertaining to each item's appropriateness. This method reduces the ambiguity, diversity, and discrepancy of the opinions among the experts hence enhances the quality of the selected items. The main purpose of this study was to obtain experts' consensus on the suitability of the preselected items on the questionnaire. The panel consists of sixteen experts from the Occupational and Environmental Health Unit of Ministry of Health, Vector-borne Disease Control Unit of Ministry of Health and Occupational and Safety Health Unit of both public and private universities. A set of questionnaires related to noise and chemical exposure were compiled based on the literature search. There was a total of six constructs with 60 items in which three constructs for knowledge, attitude, and practice of noise exposure and three constructs for knowledge, attitude, and practice of chemical exposure. The validation process replicated recent Fuzzy Delphi method that using a concept of Triangular Fuzzy Numbers and Defuzzification process. A 100% response rate was obtained from all the sixteen experts with an average Likert scoring of four to five. Post FDM analysis, the first prerequisite was fulfilled with a threshold value (d) ≤ 0.2, hence all the six constructs were accepted. For the second prerequisite, three items (21%) from noise-attitude construct and four items (40%) from chemical-practice construct had expert consensus lesser than 75%, which giving rise to about 12% from the total items in the questionnaire. The third prerequisite was used to rank the items within the constructs by calculating the average fuzzy numbers. The seven items which did not fulfill the second prerequisite similarly had lower ranks during the analysis, therefore those items were discarded from the final draft. Post FDM analysis, the experts' consensus on the suitability of the pre-selected items on the questionnaire set were obtained, hence it is now ready for further construct validation process.

Predicting the decision to pursue mediation in civil disputes: a hierarchical classes analysis.

PubMed

Reich, Warren A; Kressel, Kenneth; Scanlon, Kathleen M; Weiner, Gary A

2007-11-01

Clients (N = 185) involved in civil court cases completed the CPR Institute's Mediation Screen, which is designed to assist in making a decision about pursuing mediation. The authors modeled data using hierarchical classes analysis (HICLAS), a clustering algorithm that places clients into 1 set of classes and CPRMS items into another set of classes. HICLAS then links the sets of classes so that any class of clients can be identified in terms of the classes of items they endorsed. HICLAS-derived item classes reflected 2 underlying themes: (a) suitability of the dispute for a problem-solving process and (b) potential benefits of mediation. All clients who perceived that mediation would be beneficial also believed that the context of their conflict was favorable to mediation; however, not all clients who saw a favorable context believed they would benefit from mediation. The majority of clients who agreed to pursue mediation endorsed items reflecting both contextual suitability and perceived benefits of mediation.

30 CFR 730.11 - Inconsistent and more stringent State laws and regulations.

Code of Federal Regulations, 2010 CFR

2010-07-01

... regulations. 730.11 Section 730.11 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... Register setting forth the text or a summary of any State law or regulation initially determined by him to... stringent land use and environmental controls and regulations of coal exploration and surface coal mining...

30 CFR 33.34 - Drilling test.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Drilling test. 33.34 Section 33.34 Mineral... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES Test Requirements § 33.34 Drilling test. (a) A drilling test shall consist of drilling a set of 10 test holes, without...

30 CFR 33.34 - Drilling test.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Drilling test. 33.34 Section 33.34 Mineral... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES Test Requirements § 33.34 Drilling test. (a) A drilling test shall consist of drilling a set of 10 test holes, without...

30 CFR 33.34 - Drilling test.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Drilling test. 33.34 Section 33.34 Mineral... MINING PRODUCTS DUST COLLECTORS FOR USE IN CONNECTION WITH ROCK DRILLING IN COAL MINES Test Requirements § 33.34 Drilling test. (a) A drilling test shall consist of drilling a set of 10 test holes, without...

A Novel Method for Discovering Fuzzy Sequential Patterns Using the Simple Fuzzy Partition Method.

ERIC Educational Resources Information Center

Chen, Ruey-Shun; Hu, Yi-Chung

2003-01-01

Discusses sequential patterns, data mining, knowledge acquisition, and fuzzy sequential patterns described by natural language. Proposes a fuzzy data mining technique to discover fuzzy sequential patterns by using the simple partition method which allows the linguistic interpretation of each fuzzy set to be easily obtained. (Author/LRW)

Development of a statewide transportation data warehousing and mining system under the Louisiana Transportation Information System (LATIS) Program.

DOT National Transportation Integrated Search

2009-04-01

The objectives of this study are to assess whether introducing a data warehousing/data mining system in Louisiana would be feasible and beneficial. The study sets out to identify the features of the most suitable system for the state as well as to ou...

75 FR 39934 - The Effects of Mountaintop Mines and Valley Fills on Aquatic Ecosystems of the Central...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-07-13

... additional time to evaluate the data used to derive a benchmark for conductivity. The original Federal... below, reviewers may download the initial data and EPA's derivative data sets that were used to... and other surface coal mining projects, in coordination with federal and state regulatory agencies...

Development and Preliminary Validation of Refugee Trauma History Checklist (RTHC)—A Brief Checklist for Survey Studies

PubMed Central

Gottvall, Maria; Vaez, Marjan

2017-01-01

A high proportion of refugees have been subjected to potentially traumatic experiences (PTEs), including torture. PTEs, and torture in particular, are powerful predictors of mental ill health. This paper reports the development and preliminary validation of a brief refugee trauma checklist applicable for survey studies. Methods: A pool of 232 items was generated based on pre-existing instruments. Conceptualization, item selection and item refinement was conducted based on existing literature and in collaboration with experts. Ten cognitive interviews using a Think Aloud Protocol (TAP) were performed in a clinical setting, and field testing of the proposed checklist was performed in a total sample of n = 137 asylum seekers from Syria. Results: The proposed refugee trauma history checklist (RTHC) consists of 2 × 8 items, concerning PTEs that occurred before and during the respondents’ flight, respectively. Results show low item non-response and adequate psychometric properties Conclusions: RTHC is a usable tool for providing self-report data on refugee trauma history surveys of community samples. The core set of included events can be augmented and slight modifications can be applied to RTHC for use also in other refugee populations and settings. PMID:28976937

PPInterFinder--a mining tool for extracting causal relations on human proteins from literature.

PubMed

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein-protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder--a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. DATABASE URL: http://www.biomining-bu.in/ppinterfinder/

Efficient Mining and Detection of Sequential Intrusion Patterns for Network Intrusion Detection Systems

NASA Astrophysics Data System (ADS)

Shyu, Mei-Ling; Huang, Zifang; Luo, Hongli

In recent years, pervasive computing infrastructures have greatly improved the interaction between human and system. As we put more reliance on these computing infrastructures, we also face threats of network intrusion and/or any new forms of undesirable IT-based activities. Hence, network security has become an extremely important issue, which is closely connected with homeland security, business transactions, and people's daily life. Accurate and efficient intrusion detection technologies are required to safeguard the network systems and the critical information transmitted in the network systems. In this chapter, a novel network intrusion detection framework for mining and detecting sequential intrusion patterns is proposed. The proposed framework consists of a Collateral Representative Subspace Projection Modeling (C-RSPM) component for supervised classification, and an inter-transactional association rule mining method based on Layer Divided Modeling (LDM) for temporal pattern analysis. Experiments on the KDD99 data set and the traffic data set generated by a private LAN testbed show promising results with high detection rates, low processing time, and low false alarm rates in mining and detecting sequential intrusion detections.

PPInterFinder—a mining tool for extracting causal relations on human proteins from literature

PubMed Central

Raja, Kalpana; Subramani, Suresh; Natarajan, Jeyakumar

2013-01-01

One of the most common and challenging problem in biomedical text mining is to mine protein–protein interactions (PPIs) from MEDLINE abstracts and full-text research articles because PPIs play a major role in understanding the various biological processes and the impact of proteins in diseases. We implemented, PPInterFinder—a web-based text mining tool to extract human PPIs from biomedical literature. PPInterFinder uses relation keyword co-occurrences with protein names to extract information on PPIs from MEDLINE abstracts and consists of three phases. First, it identifies the relation keyword using a parser with Tregex and a relation keyword dictionary. Next, it automatically identifies the candidate PPI pairs with a set of rules related to PPI recognition. Finally, it extracts the relations by matching the sentence with a set of 11 specific patterns based on the syntactic nature of PPI pair. We find that PPInterFinder is capable of predicting PPIs with the accuracy of 66.05% on AIMED corpus and outperforms most of the existing systems. Database URL: http://www.biomining-bu.in/ppinterfinder/ PMID:23325628

Detecting Local Item Dependence in Polytomous Adaptive Data

ERIC Educational Resources Information Center

Mislevy, Jessica L.; Rupp, Andre A.; Harring, Jeffrey R.

2012-01-01

A rapidly expanding arena for item response theory (IRT) is in attitudinal and health-outcomes survey applications, often with polytomous items. In particular, there is interest in computer adaptive testing (CAT). Meeting model assumptions is necessary to realize the benefits of IRT in this setting, however. Although initial investigations of…

Personality assessment in aviation : an analysis of the item ambiguity characteristics of the 16PF and MMPI.

DOT National Transportation Integrated Search

1971-07-01

Devices such as the 16PF and MMPI have been widely employed in the evaluation of personnel in aviation settings. The present study investigated the problem of item ambiguity (the degree to which an item elicits multiple interpretation) which may limi...

The MIMIC Model as a Tool for Differential Bundle Functioning Detection

ERIC Educational Resources Information Center

Finch, W. Holmes

2012-01-01

Increasingly, researchers interested in identifying potentially biased test items are encouraged to use a confirmatory, rather than exploratory, approach. One such method for confirmatory testing is rooted in differential bundle functioning (DBF), where hypotheses regarding potential differential item functioning (DIF) for sets of items (bundles)…

Tree versus Geometric Representation of Tests and Items.

ERIC Educational Resources Information Center

Beller, Michael

1990-01-01

Geometric approaches to representing interrelations among tests and items are compared with an additive tree model (ATM), using 2,644 examinees and 2 other data sets. The ATM's close fit to the data and its coherence of presentation indicate that it is the best means of representing tests and items. (TJH)

Information mining in weighted complex networks with nonlinear rating projection

NASA Astrophysics Data System (ADS)

Liao, Hao; Zeng, An; Zhou, Mingyang; Mao, Rui; Wang, Bing-Hong

2017-10-01

Weighted rating networks are commonly used by e-commerce providers nowadays. In order to generate an objective ranking of online items' quality according to users' ratings, many sophisticated algorithms have been proposed in the complex networks domain. In this paper, instead of proposing new algorithms we focus on a more fundamental problem: the nonlinear rating projection. The basic idea is that even though the rating values given by users are linearly separated, the real preference of users to items between the different given values is nonlinear. We thus design an approach to project the original ratings of users to more representative values. This approach can be regarded as a data pretreatment method. Simulation in both artificial and real networks shows that the performance of the ranking algorithms can be improved when the projected ratings are used.

Dynamic association rules for gene expression data analysis.

PubMed

Chen, Shu-Chuan; Tsai, Tsung-Hsien; Chung, Cheng-Han; Li, Wen-Hsiung

2015-10-14

The purpose of gene expression analysis is to look for the association between regulation of gene expression levels and phenotypic variations. This association based on gene expression profile has been used to determine whether the induction/repression of genes correspond to phenotypic variations including cell regulations, clinical diagnoses and drug development. Statistical analyses on microarray data have been developed to resolve gene selection issue. However, these methods do not inform us of causality between genes and phenotypes. In this paper, we propose the dynamic association rule algorithm (DAR algorithm) which helps ones to efficiently select a subset of significant genes for subsequent analysis. The DAR algorithm is based on association rules from market basket analysis in marketing. We first propose a statistical way, based on constructing a one-sided confidence interval and hypothesis testing, to determine if an association rule is meaningful. Based on the proposed statistical method, we then developed the DAR algorithm for gene expression data analysis. The method was applied to analyze four microarray datasets and one Next Generation Sequencing (NGS) dataset: the Mice Apo A1 dataset, the whole genome expression dataset of mouse embryonic stem cells, expression profiling of the bone marrow of Leukemia patients, Microarray Quality Control (MAQC) data set and the RNA-seq dataset of a mouse genomic imprinting study. A comparison of the proposed method with the t-test on the expression profiling of the bone marrow of Leukemia patients was conducted. We developed a statistical way, based on the concept of confidence interval, to determine the minimum support and minimum confidence for mining association relationships among items. With the minimum support and minimum confidence, one can find significant rules in one single step. The DAR algorithm was then developed for gene expression data analysis. Four gene expression datasets showed that the proposed DAR algorithm not only was able to identify a set of differentially expressed genes that largely agreed with that of other methods, but also provided an efficient and accurate way to find influential genes of a disease. In the paper, the well-established association rule mining technique from marketing has been successfully modified to determine the minimum support and minimum confidence based on the concept of confidence interval and hypothesis testing. It can be applied to gene expression data to mine significant association rules between gene regulation and phenotype. The proposed DAR algorithm provides an efficient way to find influential genes that underlie the phenotypic variance.

Graph mining for next generation sequencing: leveraging the assembly graph for biological insights.

PubMed

Warnke-Sommer, Julia; Ali, Hesham

2016-05-06

The assembly of Next Generation Sequencing (NGS) reads remains a challenging task. This is especially true for the assembly of metagenomics data that originate from environmental samples potentially containing hundreds to thousands of unique species. The principle objective of current assembly tools is to assemble NGS reads into contiguous stretches of sequence called contigs while maximizing for both accuracy and contig length. The end goal of this process is to produce longer contigs with the major focus being on assembly only. Sequence read assembly is an aggregative process, during which read overlap relationship information is lost as reads are merged into longer sequences or contigs. The assembly graph is information rich and capable of capturing the genomic architecture of an input read data set. We have developed a novel hybrid graph in which nodes represent sequence regions at different levels of granularity. This model, utilized in the assembly and analysis pipeline Focus, presents a concise yet feature rich view of a given input data set, allowing for the extraction of biologically relevant graph structures for graph mining purposes. Focus was used to create hybrid graphs to model metagenomics data sets obtained from the gut microbiomes of five individuals with Crohn's disease and eight healthy individuals. Repetitive and mobile genetic elements are found to be associated with hybrid graph structure. Using graph mining techniques, a comparative study of the Crohn's disease and healthy data sets was conducted with focus on antibiotics resistance genes associated with transposase genes. Results demonstrated significant differences in the phylogenetic distribution of categories of antibiotics resistance genes in the healthy and diseased patients. Focus was also evaluated as a pure assembly tool and produced excellent results when compared against the Meta-velvet, Omega, and UD-IDBA assemblers. Mining the hybrid graph can reveal biological phenomena captured by its structure. We demonstrate the advantages of considering assembly graphs as data-mining support in addition to their role as frameworks for assembly.

Information mining over heterogeneous and high-dimensional time-series data in clinical trials databases.

PubMed

Altiparmak, Fatih; Ferhatosmanoglu, Hakan; Erdal, Selnur; Trost, Donald C

2006-04-01

An effective analysis of clinical trials data involves analyzing different types of data such as heterogeneous and high dimensional time series data. The current time series analysis methods generally assume that the series at hand have sufficient length to apply statistical techniques to them. Other ideal case assumptions are that data are collected in equal length intervals, and while comparing time series, the lengths are usually expected to be equal to each other. However, these assumptions are not valid for many real data sets, especially for the clinical trials data sets. An addition, the data sources are different from each other, the data are heterogeneous, and the sensitivity of the experiments varies by the source. Approaches for mining time series data need to be revisited, keeping the wide range of requirements in mind. In this paper, we propose a novel approach for information mining that involves two major steps: applying a data mining algorithm over homogeneous subsets of data, and identifying common or distinct patterns over the information gathered in the first step. Our approach is implemented specifically for heterogeneous and high dimensional time series clinical trials data. Using this framework, we propose a new way of utilizing frequent itemset mining, as well as clustering and declustering techniques with novel distance metrics for measuring similarity between time series data. By clustering the data, we find groups of analytes (substances in blood) that are most strongly correlated. Most of these relationships already known are verified by the clinical panels, and, in addition, we identify novel groups that need further biomedical analysis. A slight modification to our algorithm results an effective declustering of high dimensional time series data, which is then used for "feature selection." Using industry-sponsored clinical trials data sets, we are able to identify a small set of analytes that effectively models the state of normal health.

PTBA Coal Briquette Development Project: A status report, March 1995

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

Purba, A.C.; Supriyanto, H.; Djamal, T.S.

1995-12-31

Indonesia has a vast coal reserved amounted around 36 Billion Tons (As May 1993), of which more than 98% located in two big islands: Sumatera & Kalimantan. Indonesian Energy Policy, set up in 1976 were shifting the National Energy Mix to encourage the use of other alternative energy for fulfilling the domestic energy demand. Coal, as it was available in enormous reserve become the most suitable alternative fuel. Indonesian coal mining industry was then gaining a big momentum for its resurrection since it was for long had been overlooked. As the result of reconstruction of old mines, expanding the currentmore » mines and the opening of new mines by foreign investor (Contractors) in Kalimantan, since 1986, ten years after the set up of New National Energy Policy or 45 years after peak production level in the past, 2 million tons of coal production was regained. Afterward the coal production of Indonesian coal mine industry are increasing in an exponential rate of growth. With more than 29 million tons of coal produced in 1994, Indonesia will continue to play greater role in the world coal export market in the future. It is projected that by the year of 1998, Indonesia will rank the 3rd as the world coal exporter next to Australia and South African with around 14% of world market share. In this paper, author would only like to report the current status of Indonesian Coal Briquette Industry of which PT Tambang Batubara Bukit Asam (Persero), PTBA, the state owned coal mining company was being appointed to pioneer the establishment of the first coal briquette industry in Indonesia. Process Technology that being compared here in this paper were based on the technical compliance to specification set by government and the techno-economic evaluation. Due to limitations and constrains, all aspects concerning the project will only be discussed in an overview.« less

Space assets for demining assistance

NASA Astrophysics Data System (ADS)

Kruijff, Michiel; Eriksson, Daniel; Bouvet, Thomas; Griffiths, Alexander; Craig, Matthew; Sahli, Hichem; González-Rosón, Fernando Valcarce; Willekens, Philippe; Ginati, Amnon

2013-02-01

Populations emerging from armed conflicts often remain threatened by landmines and explosive remnants of war. The international mine action community is concerned with the relief of this threat. The Space Assets for Demining Assistance (SADA) undertaking is a set of activities that aim at developing new services to improve the socio-economic impact of mine action activities, primarily focused on the release of land thought to be contaminated, a process described as land release. SADA was originally initiated by the International Astronautical Federation (IAF). It has been implemented under the Integrated Applications Promotion (IAP) program of the European Space Agency (ESA). Land release in mine action is the process whereby the demining community identifies, surveys and prioritizes suspected hazardous areas for more detailed investigation, which eventually results in the clearance of landmines and other explosives, thereby releasing land to the local population. SADA has a broad scope, covering activities, such as planning (risk and impact analysis, prioritization, and resource management), field operations and reporting. SADA services are developed in two phases: feasibility studies followed by demonstration projects. Three parallel feasibility studies have been performed. They aimed at defining an integrated set of space enabled services to support the land release process in mine action, and at analyzing their added value, viability and sustainability. The needs of the mine action sector have been assessed and the potential contribution of space assets has been identified. Support services have been formulated. To test their fieldability, proofs of concept involving mine action end users in various operational field settings have been performed by each of the study teams. The economic viability has also been assessed. Whenever relevant and cost-effective, SADA aims at integrating Earth observation data, GNSS navigation and SatCom technologies with existing mine action tools and procedures, as well as with novel aerial survey technologies. Such conformity with existing user processes, as well as available budgets and appropriateness of technology based solutions given the field level operational setting are important conditions for success. The studies have demonstrated that Earth observation data, satellite navigation solutions and in some cases, satellite communication, indeed can provide added value to mine action activities if properly tailored based on close user interaction and provided through a suitable channel. Such added value for example includes easy and sustained access to Earth observation data for general purpose mapping, land use assessment for post-release progress reporting, and multi-source data fusion algorithms to help quantify risks and socio-economic impact for prioritization and planning purposes. The environment and boundaries of a hazardous area can also be better specified to support the land release process including detailed survey and clearance operations. Satellite communication can help to provide relevant data to remote locations, but is not regarded as strongly user driven. Finally, satellite navigation can support more precise non-technical surveys, as well as aerial observation with small planes or hand-launched UAV's. To ensure the activity is genuinely user driven, the Geneva International Center for Humanitarian Demining (GICHD) plays an important role as ESA's external advisor. ESA is furthermore supported by a representative field operator, the Swiss Foundation of Mine Action (FSD), providing ESA with a direct connection to the field level end users. Specifically FSD has provided a shared user needs baseline to the three study teams. To ensure solutions meet with end user requirements, the study teams themselves include mine action representatives and have interacted closely with their pre-existing and newly established contacts within the mine action community.

Lost in the supermarket: Quantifying the cost of partitioning memory sets in hybrid search.

PubMed

Boettcher, Sage E P; Drew, Trafton; Wolfe, Jeremy M

2018-01-01

The items on a memorized grocery list are not relevant in every aisle; for example, it is useless to search for the cabbage in the cereal aisle. It might be beneficial if one could mentally partition the list so only the relevant subset was active, so that vegetables would be activated in the produce section. In four experiments, we explored observers' abilities to partition memory searches. For example, if observers held 16 items in memory, but only eight of the items were relevant, would response times resemble a search through eight or 16 items? In Experiments 1a and 1b, observers were not faster for the partition set; however, they suffered relatively small deficits when "lures" (items from the irrelevant subset) were presented, indicating that they were aware of the partition. In Experiment 2 the partitions were based on semantic distinctions, and again, observers were unable to restrict search to the relevant items. In Experiments 3a and 3b, observers attempted to remove items from the list one trial at a time but did not speed up over the course of a block, indicating that they also could not limit their memory searches. Finally, Experiments 4a, 4b, 4c, and 4d showed that observers were able to limit their memory searches when a subset was relevant for a run of trials. Overall, observers appear to be unable or unwilling to partition memory sets from trial to trial, yet they are capable of restricting search to a memory subset that remains relevant for several trials. This pattern is consistent with a cost to switching between currently relevant memory items.

Conversion of Propellant Grade Picrite to Spherical Nitroguanidine, an Insensitive Filler for Melt-Cast TNT Formulations

DTIC Science & Technology

1991-09-01

problem with the solvent/non-solvent process reported by ICT is the inability to recycle the mother liquors. Apparently "strawberries" or " sea urchins ...inevitable for the foreseeable future. Exceptions could include lower production rate items such as sea mines or missile warheads, or speLfic nunitions where...Leitz Orthomat 35 mm automatic camera on polaroid film type 667, Magnification ranged up to X42. 14K 1* Scanning Electron Microscopy ( SEM ) SEM was

Data Collection using the MetalMapper in Dynamic Data Acquisition and Cued Modes

DTIC Science & Technology

2017-07-01

land mines, pyrotechnics, bombs , and demolition materials. Surface sweeps identified MEC items throughout Units 11 and 12, including 37mm, 40mm...munitions testing and as impact areas for 4.2-in mortars, large caliber projectiles (75mm–155mm), and numerous types of bombs . With the exception of some...RSA-073 includes AN-M76 bombs , PT1 (incendiary mixture similar to “goop”)-filled; M47-type bombs , Isobutyl Methacrylate Incendiary Mix (IM-AE)- and

Examining Construct Congruence for Psychometric Tests: A Note on an Extension to Binary Items and Nesting Effects

ERIC Educational Resources Information Center

Raykov, Tenko; Marcoulides, George A.; Dimitrov, Dimiter M.; Li, Tatyana

2018-01-01

This article extends the procedure outlined in the article by Raykov, Marcoulides, and Tong for testing congruence of latent constructs to the setting of binary items and clustering effects. In this widely used setting in contemporary educational and psychological research, the method can be used to examine if two or more homogeneous…

Detecting Intrajudge Inconsistency in Standard Setting Using Test Items with a Selected-Response Format. Research Report.

ERIC Educational Resources Information Center

van der Linden, Wim J.; Vos, Hans J.; Chang, Lei

In judgmental standard setting experiments, it may be difficult to specify subjective probabilities that adequately take the properties of the items into account. As a result, these probabilities are not consistent with each other in the sense that they do not refer to the same borderline level of performance. Methods to check standard setting…

Direct-Comparison Judgments: When and Why above- and below-Average Effects Reverse

ERIC Educational Resources Information Center

Windschitl, Paul D.; Conybeare, Daniel; Krizan, Zlatan

2008-01-01

Above-average and below-average effects appear to be common and consistent across a variety of judgment domains. For example, several studies show that individual items from a high- (low-) quality set tend to be rated as better (worse) than the other items in the set (e.g., E. E. Giladi & Y. Klar, 2002). Experiments in this article demonstrate…

How I Feel About Some Other Kids.

ERIC Educational Resources Information Center

Purdue Univ., Lafayette, IN. Educational Research Center.

This rating scale was developed to yield a measure of peer acceptance and socialization for students in grades 1-6. Each child is asked to consider his classmates in terms of three sets of questions, each set having 20 items. The child responds to the question by circling yes or no or sometimes on the answer sheet. Items are organized around three…

Relative quantity judgments in South American sea lions (Otaria flavescens).

PubMed

Abramson, José Z; Hernández-Lloreda, Victoria; Call, Josep; Colmenares, Fernando

2011-09-01

There is accumulating evidence that a variety of species possess quantitative abilities although their cognitive substrate is still unclear. This study is the first to investigate whether sea lions (Otaria flavescens), in the absence of training, are able to assess and select the larger of two sets of quantities. In Experiment 1, the two sets of quantities were presented simultaneously as whole sets, that is, the subjects could compare them directly. In Experiment 2, the two sets of quantities were presented item-by-item, and the totality of items was never visually available at the time of choice. For each type of presentation, we analysed the effect of the ratio between quantities, the difference between quantities and the total number of items presented. The results showed that (1) sea lions can make relative quantity judgments successfully and (2) there is a predominant influence of the ratio between quantities on the subjects' performance. The latter supports the idea that an analogue representational mechanism is responsible for sea lions' relative quantities judgments. These findings are consistent with previous reports of relative quantities judgments in other species such as monkeys and apes and suggest that sea lions might share a similar mechanism to compare and represent quantities.

The word-length effect and disyllabic words.

PubMed

Lovatt, P; Avons, S E; Masterson, J

2000-02-01

Three experiments compared immediate serial recall of disyllabic words that differed on spoken duration. Two sets of long- and short-duration words were selected, in each case maximizing duration differences but matching for frequency, familiarity, phonological similarity, and number of phonemes, and controlling for semantic associations. Serial recall measures were obtained using auditory and visual presentation and spoken and picture-pointing recall. In Experiments 1a and 1b, using the first set of items, long words were better recalled than short words. In Experiments 2a and 2b, using the second set of items, no difference was found between long and short disyllabic words. Experiment 3 confirmed the large advantage for short-duration words in the word set originally selected by Baddeley, Thomson, and Buchanan (1975). These findings suggest that there is no reliable advantage for short-duration disyllables in span tasks, and that previous accounts of a word-length effect in disyllables are based on accidental differences between list items. The failure to find an effect of word duration casts doubt on theories that propose that the capacity of memory span is determined by the duration of list items or the decay rate of phonological information in short-term memory.

Applications of Geomatics in Surface Mining

NASA Astrophysics Data System (ADS)

Blachowski, Jan; Górniak-Zimroz, Justyna; Milczarek, Wojciech; Pactwa, Katarzyna

2017-12-01

In terms of method of extracting mineral from deposit, mining can be classified into: surface, underground, and borehole mining. Surface mining is a form of mining, in which the soil and the rock covering the mineral deposits are removed. Types of surface mining include mainly strip and open-cast methods, as well as quarrying. Tasks associated with surface mining of minerals include: resource estimation and deposit documentation, mine planning and deposit access, mine plant development, extraction of minerals from deposits, mineral and waste processing, reclamation and reclamation of former mining grounds. At each stage of mining, geodata describing changes occurring in space during the entire life cycle of surface mining project should be taken into consideration, i.e. collected, analysed, processed, examined, distributed. These data result from direct (e.g. geodetic) and indirect (i.e. remote or relative) measurements and observations including airborne and satellite methods, geotechnical, geological and hydrogeological data, and data from other types of sensors, e.g. located on mining equipment and infrastructure, mine plans and maps. Management of such vast sources and sets of geodata, as well as information resulting from processing, integrated analysis and examining such data can be facilitated with geomatic solutions. Geomatics is a discipline of gathering, processing, interpreting, storing and delivering spatially referenced information. Thus, geomatics integrates methods and technologies used for collecting, management, processing, visualizing and distributing spatial data. In other words, its meaning covers practically every method and tool from spatial data acquisition to distribution. In this work examples of application of geomatic solutions in surface mining on representative case studies in various stages of mine operation have been presented. These applications include: prospecting and documenting mineral deposits, assessment of land accessibility for a potential large-scale surface mining project, modelling mineral deposit (granite) management, concept of a system for management of conveyor belt network technical condition, project of a geoinformation system of former mining terrains and objects, and monitoring and control of impact of surface mining on mine surroundings with satellite radar interferometry.

Kernel-Smoothing Estimation of Item Characteristic Functions for Continuous Personality Items: An Empirical Comparison with the Linear and the Continuous-Response Models

ERIC Educational Resources Information Center

Ferrando, Pere J.

2004-01-01

This study used kernel-smoothing procedures to estimate the item characteristic functions (ICFs) of a set of continuous personality items. The nonparametric ICFs were compared with the ICFs estimated (a) by the linear model and (b) by Samejima's continuous-response model. The study was based on a conditioned approach and used an error-in-variables…

Heat acclimation: Gold mines and genes

PubMed Central

Schneider, Suzanne M.

2016-01-01

ABSTRACT The underground gold mines of South Africa offer a unique historical setting to study heat acclimation. The early heat stress research was conducted and described by a young medical officer, Dr. Aldo Dreosti. He developed practical and specific protocols to first assess the heat tolerance of thousands of new mining recruits, and then used the screening results as the basis for assigning a heat acclimation protocol. The mines provide an interesting paradigm where the prevention of heat stroke evolved from genetic selection, where only Black natives were recruited due to a false assumption of their intrinsic tolerance to heat, to our current appreciation of the epigenetic and other molecular adaptations that occur with exposure to heat. PMID:28090556

Chemical composition of samples collected from waste rock dumps and other mining-related features at selected phosphate mines in southeastern Idaho, western Wyoming, and northern Utah

USGS Publications Warehouse

Moyle, Phillip R.; Causey, J. Douglas

2001-01-01

This report provides chemical analyses for 31 samples collected from various phosphate mine sites in southeastern Idaho (25), northern Utah (2), and western Wyoming (4). The sampling effort was undertaken as a reconnaissance and does not constitute a characterization of mine wastes. Twenty-five samples were collected from waste rock dumps, 2 from stockpiles, and 1 each from slag, tailings, mill shale, and an outcrop. All samples were analyzed for a suite of major, minor, and trace elements. Although the analytical data set for the 31 samples is too small for detailed statistical analysis, a summary of general observations is made.

Psychometric evaluation of the Questionnaire about the Process of Recovery (QPR).

PubMed

Williams, Julie; Leamy, Mary; Pesola, Francesca; Bird, Victoria; Le Boutillier, Clair; Slade, Mike

2015-12-01

Supporting recovery is the aim of national mental health policy in many countries. However, only one measure of recovery has been developed in England: the Questionnaire about the Process of Recovery (QPR), which measures recovery from the perspective of adult mental health service users with a psychosis diagnosis. To independently evaluate the psychometric properties of the 15- and 22-item versions of the QPR. Two samples were used: data-set 1 (n = 88) involved assessment of the QPR at baseline, 2 weeks and 3 months. Data-set 2 (n = 399; trial registration: ISRCTN02507940) involved assessment of the QPR at baseline and 1 year. For the 15-item version, internal consistency was 0.89, convergent validity was 0.73, test-retest reliability was 0.74 and sensitivity to change was 0.40. Confirmatory factor analysis showed the 15-item version offered a good fit. For the 22-item version, the interpersonal subscale was found to underperform and the intrapersonal subscale overlaps substantially with the 15-item version. Both the 15-item and the intrapersonal subscale of the 22-item versions of the QPR demonstrated satisfactory psychometric properties. The 15-item version is slightly more robust and also less burdensome, so it can be recommended for use in research and clinical practice. © The Royal College of Psychiatrists 2015.

Evaluating the Psychometric Properties of the Maslach Burnout Inventory-Human Services Survey (MBI-HSS) among Italian Nurses: How Many Factors Must a Researcher Consider?

PubMed Central

Loera, Barbara; Converso, Daniela; Viotti, Sara

2014-01-01

Background The Maslach Burnout Inventory (MBI) is the mainstream measure for burnout. However, its psychometric properties have been questioned, and alternative measurement models of the inventory have been suggested. Aims Different models for the number of items and factors of the MBI-HSS, the version of the Inventory for the Human Service sector, were tested in order to identify the most appropriate model for measuring burnout in Italy. Methods The study dataset consisted of a sample of 925 nurses. Ten alternative models of burnout were compared using confirmatory factor analysis. The psychometric properties of items and reliability of the MBI-HSS subscales were evaluated. Results Item malfunctioning may confound the MBI-HSS factor structure. The analysis confirmed the factorial structure of the MBI-HSS with a three-dimensional, 20-item assessment. Conclusions The factorial structure underlying the MBI-HSS follows Maslach’s definition when items are reduced from the original 22 to a 20-item set. Alternative models, either with fewer items or with an increased number of latent dimensions in the burnout structure, do not yield better results to justify redefining the item set or theoretically revising the syndrome construct. PMID:25501716

Differential item functioning analysis of the Vanderbilt Expertise Test for cars

PubMed Central

Lee, Woo-Yeol; Cho, Sun-Joo; McGugin, Rankin W.; Van Gulick, Ana Beth; Gauthier, Isabel

2015-01-01

The Vanderbilt Expertise Test for cars (VETcar) is a test of visual learning for contemporary car models. We used item response theory to assess the VETcar and in particular used differential item functioning (DIF) analysis to ask if the test functions the same way in laboratory versus online settings and for different groups based on age and gender. An exploratory factor analysis found evidence of multidimensionality in the VETcar, although a single dimension was deemed sufficient to capture the recognition ability measured by the test. We selected a unidimensional three-parameter logistic item response model to examine item characteristics and subject abilities. The VETcar had satisfactory internal consistency. A substantial number of items showed DIF at a medium effect size for test setting and for age group, whereas gender DIF was negligible. Because online subjects were on average older than those tested in the lab, we focused on the age groups to conduct a multigroup item response theory analysis. This revealed that most items on the test favored the younger group. DIF could be more the rule than the exception when measuring performance with familiar object categories, therefore posing a challenge for the measurement of either domain-general visual abilities or category-specific knowledge. PMID:26418499

Mines, prospects, and occurrences of nonmetallic mineral commodities in the Greenville 1 degree by 2 degrees Quadrangle, South Carolina, Georgia, and North Carolina

USGS Publications Warehouse

D'Agostino, John P.; O'Connor, Bruce J.; Zupan, Alan J.W.; Maybin, Arthur H.

1994-01-01

Mines, prospects, and occurrences of nonmetal mineral commodities in the Greenville 1° x 2° quadrangle are tabulated in this report. There are 488 symbols representing 579 mines, prospects, and occurrences located in the quadrangle. There are 379 symbols used for 466 features in Georgia, 106 symbols for 110 features in South Carolina, and 3 symbols for 3 features in North Carolina. The table lists, in consecutive orders for each county (fig. 1), the map number of each feature, which correlates and locates the item on the accompanying Greenville 1° x 2° quadrangle map. Also listed are the known name of the feature; the 7.5 topographic map on which the commodity site is located; the Transverse Mercator (UTM) northing and easting grid coordinates from the appropriate 7.5’ topographic map; the commodity; remarks; and references. Some locations are known, but many sites are not verified and their locations are only approximate. Reference are listed in References Cited and referred to by number to save space. The generalized tectonic framework for the quadrangle is shown in figure 2.

GExplore: a web server for integrated queries of protein domains, gene expression and mutant phenotypes

PubMed Central

2009-01-01

Background The majority of the genes even in well-studied multi-cellular model organisms have not been functionally characterized yet. Mining the numerous genome wide data sets related to protein function to retrieve potential candidate genes for a particular biological process remains a challenge. Description GExplore has been developed to provide a user-friendly database interface for data mining at the gene expression/protein function level to help in hypothesis development and experiment design. It supports combinatorial searches for proteins with certain domains, tissue- or developmental stage-specific expression patterns, and mutant phenotypes. GExplore operates on a stand-alone database and has fast response times, which is essential for exploratory searches. The interface is not only user-friendly, but also modular so that it accommodates additional data sets in the future. Conclusion GExplore is an online database for quick mining of data related to gene and protein function, providing a multi-gene display of data sets related to the domain composition of proteins as well as expression and phenotype data. GExplore is publicly available at: http://genome.sfu.ca/gexplore/ PMID:19917126

Intergenerational equity and conservation

NASA Technical Reports Server (NTRS)

Otoole, R. P.; Walton, A. L.

1980-01-01

The issue of integenerational equity in the use of natural resources is discussed in the context of coal mining conversion. An attempt to determine if there is a clear-cut benefit to future generations in setting minimum coal extraction efficiency standards in mining is made. It is demonstrated that preserving fossil fuels beyond the economically efficient level is not necessarily beneficial to future generations even in terms of their own preferences. Setting fossil fuel conservation targets for intermediate products (i.e. energy) may increase the quantities of fossil fuels available to future generations and hence lower the costs, but there may be serious disadvantages to future generations as well. The use of relatively inexpensive fossil fuels in this generation may result in more infrastructure development and more knowledge production available to future generations. The value of fossil fuels versus these other endowments in the future depends on many factors which cannot possibly be evaluated at present. Since there is no idea of whether future generations are being helped or harmed, it is recommended that integenerational equity not be used as a factor in setting coal mine extraction efficiency standards, or in establishing requirements.

Comprehensive clinical assessment in community setting: applicability of the MDS-HC.

PubMed

Morris, J N; Fries, B E; Steel, K; Ikegami, N; Bernabei, R; Carpenter, G I; Gilgen, R; Hirdes, J P; Topinková, E

1997-08-01

To describe the results of an international trial of the home care version of the MDS assessment and problem identification system (the MDS-HC), including reliability estimates, a comparison of MDS-HC reliabilities with reliabilities of the same items in the MDS 2.0 nursing home assessment instrument, and an examination of the types of problems found in home care clients using the MDS-HC. Independent, dual assessment of clients of home-care agencies by trained clinicians using a draft of the MDS-HC, with additional descriptive data regarding problem profiles for home care clients. Reliability data from dual assessments of 241 randomly selected clients of home care agencies in five countries, all of whom volunteered to test the MDS-HC. Also included are an expanded sample of 780 home care assessments from these countries and 187 dually assessed residents from 21 nursing homes in the United States. The array of MDS-HC assessment items included measures in the following areas: personal items, cognitive patterns, communication/hearing, vision, mood and behavior, social functioning, informal support services, physical functioning, continence, disease diagnoses health conditions and preventive health measures, nutrition/hydration, dental status, skin condition, environmental assessment, service utilization, and medications. Forty-seven percent of the functional, health status, social environment, and service items in the MDS-HC were taken from the MDS 2.0 for nursing homes. For this item set, it is estimated that the average weighted Kappa is .74 for the MDS-HC and .75 for the MDS 2.0. Similarly, high reliability values were found for items newly introduced in the MDS-HC (weighted Kappa = .70). Descriptive findings also characterize the problems of home care clients, with subanalyses within cognitive performance levels. Findings indicate that the core set of items in the MDS 2.0 work equally well in community and nursing home settings. New items are highly reliable. In tandem, these instruments can be used within the international community, assisting and planning care for older adults within a broad spectrum of service settings, including nursing homes and home care programs. With this community-based, second-generation problem and care plan-driven assessment instrument, disability assessment can be performed consistently across the world.

Causes and Consequences of Water Flux on the Example of Transverse Heading Mina in the Salt Mine "Wieliczka" / Przyczyny i Skutki Dopływu Wody na Przykładzie Poprzeczni Mina w Kopalni Soli "Wieliczka"

NASA Astrophysics Data System (ADS)

Gonet, Andrzej; Stryczek, Stanisław; Brudnik, Krzysztof

2012-11-01

The causes of disastrous water flux in the historical Salt Mine "Wieliczka" have been presented on the example of transverse heading Mina at the IV level at a depth of 175 m bsl. The complex geological setting of direct environment of the transverse heading Mina has been described paying attention to unfavorable hydrogeological conditions in the northern part of the salt deposit. The main activities oriented to limiting the water hazard in the Salt Mine "Wieliczka" and the reconstruction of inner safety pillar, which had been seriously damaged by mining activities, have been analyzed. A selection of objects inside the mine, saved from flooding thanks to protection works has been visualized in photos.

A Two-Decision Model for Responses to Likert-Type Items

ERIC Educational Resources Information Center

Thissen-Roe, Anne; Thissen, David

2013-01-01

Extreme response set, the tendency to prefer the lowest or highest response option when confronted with a Likert-type response scale, can lead to misfit of item response models such as the generalized partial credit model. Recently, a series of intrinsically multidimensional item response models have been hypothesized, wherein tendency toward…

Use of Automated Scoring Features to Generate Hypotheses Regarding Language-Based DIF

ERIC Educational Resources Information Center

Shermis, Mark D.; Mao, Liyang; Mulholland, Matthew; Kieftenbeld, Vincent

2017-01-01

This study uses the feature sets employed by two automated scoring engines to determine if a "linguistic profile" could be formulated that would help identify items that are likely to exhibit differential item functioning (DIF) based on linguistic features. Sixteen items were administered to 1200 students where demographic information…

Development and Validation of a Unidimensional Maltreatment Scale in the Add Health Data Set

ERIC Educational Resources Information Center

Marszalek, Jacob M.; Hamilton, Jessica L.

2012-01-01

Four maltreatment items were examined from Wave III (N = 13,516) of the National Longitudinal Study of Adolescent Health. Item analysis, confirmatory factor analysis, cross-validation, reliability estimates, and convergent validity coefficients strongly supported the validity of using the four items as a unidimensional composite. Implications for…

Minimum Sample Size Requirements for Mokken Scale Analysis

ERIC Educational Resources Information Center

Straat, J. Hendrik; van der Ark, L. Andries; Sijtsma, Klaas

2014-01-01

An automated item selection procedure in Mokken scale analysis partitions a set of items into one or more Mokken scales, if the data allow. Two algorithms are available that pursue the same goal of selecting Mokken scales of maximum length: Mokken's original automated item selection procedure (AISP) and a genetic algorithm (GA). Minimum…

Automated Test-Form Generation

ERIC Educational Resources Information Center

van der Linden, Wim J.; Diao, Qi

2011-01-01

In automated test assembly (ATA), the methodology of mixed-integer programming is used to select test items from an item bank to meet the specifications for a desired test form and optimize its measurement accuracy. The same methodology can be used to automate the formatting of the set of selected items into the actual test form. Three different…

A Comparison of Item-Level and Scale-Level Multiple Imputation for Questionnaire Batteries

ERIC Educational Resources Information Center

Gottschall, Amanda C.; West, Stephen G.; Enders, Craig K.

2012-01-01

Behavioral science researchers routinely use scale scores that sum or average a set of questionnaire items to address their substantive questions. A researcher applying multiple imputation to incomplete questionnaire data can either impute the incomplete items prior to computing scale scores or impute the scale scores directly from other scale…

Development process of an assessment tool for disruptive behavior problems in cross-cultural settings: the Disruptive Behavior International Scale – Nepal version (DBIS-N)

PubMed Central

Burkey, Matthew D.; Ghimire, Lajina; Adhikari, Ramesh P.; Kohrt, Brandon A.; Jordans, Mark J. D.; Haroz, Emily; Wissow, Lawrence

2017-01-01

Systematic processes are needed to develop valid measurement instruments for disruptive behavior disorders (DBDs) in cross-cultural settings. We employed a four-step process in Nepal to identify and select items for a culturally valid assessment instrument: 1) We extracted items from validated scales and local free-list interviews. 2) Parents, teachers, and peers (n=30) rated the perceived relevance and importance of behavior problems. 3) Highly rated items were piloted with children (n=60) in Nepal. 4) We evaluated internal consistency of the final scale. We identified 49 symptoms from 11 scales, and 39 behavior problems from free-list interviews (n=72). After dropping items for low ratings of relevance and severity and for poor item-test correlation, low frequency, and/or poor acceptability in pilot testing, 16 items remained for the Disruptive Behavior International Scale—Nepali version (DBIS-N). The final scale had good internal consistency (α=0.86). A 4-step systematic approach to scale development including local participation yielded an internally consistent scale that included culturally relevant behavior problems. PMID:28093575

The application of knowledge discovery in databases to post-marketing drug safety: example of the WHO database.

PubMed

Bate, A; Lindquist, M; Edwards, I R

2008-04-01

After market launch, new information on adverse effects of medicinal products is almost exclusively first highlighted by spontaneous reporting. As data sets of spontaneous reports have become larger, and computational capability has increased, quantitative methods have been increasingly applied to such data sets. The screening of such data sets is an application of knowledge discovery in databases (KDD). Effective KDD is an iterative and interactive process made up of the following steps: developing an understanding of an application domain, creating a target data set, data cleaning and pre-processing, data reduction and projection, choosing the data mining task, choosing the data mining algorithm, data mining, interpretation of results and consolidating and using acquired knowledge. The process of KDD as it applies to the analysis of spontaneous reports can be exemplified by its routine use on the 3.5 million suspected adverse drug reaction (ADR) reports in the WHO ADR database. Examples of new adverse effects first highlighted by the KDD process on WHO data include topiramate glaucoma, infliximab vasculitis and the association of selective serotonin reuptake inhibitors (SSRIs) and neonatal convulsions. The KDD process has already improved our ability to highlight previously unsuspected ADRs for clinical review in spontaneous reporting, and we anticipate that such techniques will be increasingly used in the successful screening of other healthcare data sets such as patient records in the future.

Fracture, fluid flow and paleostress at Sunrise Dam Gold Mine, W. Australia

NASA Astrophysics Data System (ADS)

Blenkinsop, Thomas; Sanderson, David; Nugus, Michael

2017-04-01

Some of the clearest examples of Interactions between fracture, fluid flow, pore fluid pressure and differential stress can be inferred from underground observations in mines. This study examines the inferred stress conditions and resulting fracture network that constitutes a stockwork type ore body at Sunrise Dam gold mine, Western Australia. Stockworks in mine workings are particularly instructive for such analyses, because the abundance of veins allows cross-cutting relationships to be observed, which are commonly hard to see in situations of lower fracture intensity or incomplete outcrop. Sunrise Dam has produced in excess of 8.5Moz of gold since 1989, with current Mineral Resources and Ore Reserves at 58.96Mt@2.41g/t Au (4.55Moz) and 21.45Mt@1.87g/t Au (1.29Moz), respectively. The stockwork examined is in the Astro ore body, and consists of three sets of extensional veins and one set of low-angle strike-slip shear veins. Cross-cutting relationships suggest broadly contemporaneous formation of all fracture sets, which are also related by a common quartz-carbonate mineralogy. The extensional veins intersect the shear veins along the direction of shear, a geometry that can be predicted for certain stress ratios. Combined with observations and paleostress inferences from other parts of the mine, the veining and gold mineralisation can be associated with a D4 strike-slip shearing event, which had a maximum compressive stress plunging gently NE. Fracture intensity varies by 50% on a scale of 10s of metres. The stockwork formed by repeated extensional and shear failure events, showing fluctuations in pore fluid pressure and stress conditions, which would have required fracture healing/sealing in order for the deformation to spread throughout the stockwork volume.

Application of Elements of TPM Strategy for Operation Analysis of Mining Machine

NASA Astrophysics Data System (ADS)

Brodny, Jaroslaw; Tutak, Magdalena

2017-12-01

Total Productive Maintenance (TPM) strategy includes group of activities and actions in order to maintenance machines in failure-free state and without breakdowns thanks to tending limitation of failures, non-planned shutdowns, lacks and non-planned service of machines. These actions are ordered to increase effectiveness of utilization of possessed devices and machines in company. Very significant element of this strategy is connection of technical actions with changes in their perception by employees. Whereas fundamental aim of introduction this strategy is improvement of economic efficiency of enterprise. Increasing competition and necessity of reduction of production costs causes that also mining enterprises are forced to introduce this strategy. In the paper examples of use of OEE model for quantitative evaluation of selected mining devices were presented. OEE model is quantitative tool of TPM strategy and can be the base for further works connected with its introduction. OEE indicator is the product of three components which include availability and performance of the studied machine and the quality of the obtained product. The paper presents the results of the effectiveness analysis of the use of a set of mining machines included in the longwall system, which is the first and most important link in the technological line of coal production. The set of analyzed machines included the longwall shearer, armored face conveyor and cruscher. From a reliability point of view, the analyzed set of machines is a system that is characterized by the serial structure. The analysis was based on data recorded by the industrial automation system used in the mines. This method of data acquisition ensured their high credibility and a full time synchronization. Conclusions from the research and analyses should be used to reduce breakdowns, failures and unplanned downtime, increase performance and improve production quality.

30 CFR 75.161 - Plans for training programs.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Plans for training programs. 75.161 Section 75... Provision] § 75.161 Plans for training programs. Each operator must submit to the district manager, of the Coal Mine Safety and Health District in which the mine is located, a program or plan setting forth what...

Data Mining Tools Make Flights Safer, More Efficient

NASA Technical Reports Server (NTRS)

2014-01-01

A small data mining team at Ames Research Center developed a set of algorithms ideal for combing through flight data to find anomalies. Dallas-based Southwest Airlines Co. signed a Space Act Agreement with Ames in 2011 to access the tools, helping the company refine its safety practices, improve its safety reviews, and increase flight efficiencies.

43 CFR 3472.2-5 - Special qualifications, public bodies.

Code of Federal Regulations, 2013 CFR

2013-10-01

... authorized by its governing body. (b) To obtain a license to mine, a municipality shall submit with its... license to mine; and (3) Evidence that the action proposed has been duly authorized by its governing body. (c) To qualify to bid for a lease on a tract of acquired land set apart for military or naval...

43 CFR 3472.2-5 - Special qualifications, public bodies.

Code of Federal Regulations, 2011 CFR

2011-10-01

... authorized by its governing body. (b) To obtain a license to mine, a municipality shall submit with its... license to mine; and (3) Evidence that the action proposed has been duly authorized by its governing body. (c) To qualify to bid for a lease on a tract of acquired land set apart for military or naval...

43 CFR 3472.2-5 - Special qualifications, public bodies.

Code of Federal Regulations, 2014 CFR

2014-10-01

... authorized by its governing body. (b) To obtain a license to mine, a municipality shall submit with its... license to mine; and (3) Evidence that the action proposed has been duly authorized by its governing body. (c) To qualify to bid for a lease on a tract of acquired land set apart for military or naval...

43 CFR 3472.2-5 - Special qualifications, public bodies.

Code of Federal Regulations, 2012 CFR

2012-10-01

... authorized by its governing body. (b) To obtain a license to mine, a municipality shall submit with its... license to mine; and (3) Evidence that the action proposed has been duly authorized by its governing body. (c) To qualify to bid for a lease on a tract of acquired land set apart for military or naval...

Proceedings of the International Conference on Educational Data Mining (EDM) (2nd, Cordoba, Spain, July 1-3, 2009)

ERIC Educational Resources Information Center

Barnes, Tiffany, Ed.; Desmarais, Michel, Ed.; Romero, Cristobal, Ed.; Ventura, Sebastian, Ed.

2009-01-01

The Second International Conference on Educational Data Mining (EDM2009) was held at the University of Cordoba, Spain, on July 1-3, 2009. EDM brings together researchers from computer science, education, psychology, psychometrics, and statistics to analyze large data sets to answer educational research questions. The increase in instrumented…

75 FR 30393 - The Effects of Mountaintop Mines and Valley Fills on Aquatic Ecosystems of the Central...

Federal Register 2010, 2011, 2012, 2013, 2014

2010-06-01

... opportunity to evaluate the data used to derive a benchmark for conductivity. By following the link below, reviewers may download the initial data and EPA's derivative data sets that were used to calculate the... surface coal mining projects, in coordination with Federal and State regulatory agencies ( http://www.epa...

EAGLE: 'EAGLE'Is an' Algorithmic Graph Library for Exploration

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

2015-01-16

The Resource Description Framework (RDF) and SPARQL Protocol and RDF Query Language (SPARQL) were introduced about a decade ago to enable flexible schema-free data interchange on the Semantic Web. Today data scientists use the framework as a scalable graph representation for integrating, querying, exploring and analyzing data sets hosted at different sources. With increasing adoption, the need for graph mining capabilities for the Semantic Web has emerged. Today there is no tools to conduct "graph mining" on RDF standard data sets. We address that need through implementation of popular iterative Graph Mining algorithms (Triangle count, Connected component analysis, degree distribution,more » diversity degree, PageRank, etc.). We implement these algorithms as SPARQL queries, wrapped within Python scripts and call our software tool as EAGLE. In RDF style, EAGLE stands for "EAGLE 'Is an' algorithmic graph library for exploration. EAGLE is like 'MATLAB' for 'Linked Data.'« less

Underwater target classification using wavelet packets and neural networks.

PubMed

Azimi-Sadjadi, M R; Yao, D; Huang, Q; Dobeck, G J

2000-01-01

In this paper, a new subband-based classification scheme is developed for classifying underwater mines and mine-like targets from the acoustic backscattered signals. The system consists of a feature extractor using wavelet packets in conjunction with linear predictive coding (LPC), a feature selection scheme, and a backpropagation neural-network classifier. The data set used for this study consists of the backscattered signals from six different objects: two mine-like targets and four nontargets for several aspect angles. Simulation results on ten different noisy realizations and for signal-to-noise ratio (SNR) of 12 dB are presented. The receiver operating characteristic (ROC) curve of the classifier generated based on these results demonstrated excellent classification performance of the system. The generalization ability of the trained network was demonstrated by computing the error and classification rate statistics on a large data set. A multiaspect fusion scheme was also adopted in order to further improve the classification performance.

A Temporal Pattern Mining Approach for Classifying Electronic Health Record Data

PubMed Central

Batal, Iyad; Valizadegan, Hamed; Cooper, Gregory F.; Hauskrecht, Milos

2013-01-01

We study the problem of learning classification models from complex multivariate temporal data encountered in electronic health record systems. The challenge is to define a good set of features that are able to represent well the temporal aspect of the data. Our method relies on temporal abstractions and temporal pattern mining to extract the classification features. Temporal pattern mining usually returns a large number of temporal patterns, most of which may be irrelevant to the classification task. To address this problem, we present the Minimal Predictive Temporal Patterns framework to generate a small set of predictive and non-spurious patterns. We apply our approach to the real-world clinical task of predicting patients who are at risk of developing heparin induced thrombocytopenia. The results demonstrate the benefit of our approach in efficiently learning accurate classifiers, which is a key step for developing intelligent clinical monitoring systems. PMID:25309815

A Comparison of different learning models used in Data Mining for Medical Data

NASA Astrophysics Data System (ADS)

Srimani, P. K.; Koti, Manjula Sanjay

2011-12-01

The present study aims at investigating the different Data mining learning models for different medical data sets and to give practical guidelines to select the most appropriate algorithm for a specific medical data set. In practical situations, it is absolutely necessary to take decisions with regard to the appropriate models and parameters for diagnosis and prediction problems. Learning models and algorithms are widely implemented for rule extraction and the prediction of system behavior. In this paper, some of the well-known Machine Learning(ML) systems are investigated for different methods and are tested on five medical data sets. The practical criteria for evaluating different learning models are presented and the potential benefits of the proposed methodology for diagnosis and learning are suggested.

Open pit mining profit maximization considering selling stage and waste rehabilitation cost

NASA Astrophysics Data System (ADS)

Muttaqin, B. I. A.; Rosyidi, C. N.

2017-11-01

In open pit mining activities, determination of the cut-off grade becomes crucial for the company since the cut-off grade affects how much profit will be earned for the mining company. In this study, we developed a cut-off grade determination mode for the open pit mining industry considering the cost of mining, waste removal (rehabilitation) cost, processing cost, fixed cost, and selling stage cost. The main goal of this study is to develop a model of cut-off grade determination to get the maximum total profit. Secondly, this study is also developed to observe the model of sensitivity based on changes in the cost components. The optimization results show that the models can help mining company managers to determine the optimal cut-off grade and also estimate how much profit that can be earned by the mining company. To illustrate the application of the models, a numerical example and a set of sensitivity analysis are presented. From the results of sensitivity analysis, we conclude that the changes in the sales price greatly affects the optimal cut-off value and the total profit.

ABC for AIDS prevention in Guinea: migrant gold mining communities address their risks.

PubMed

Kis, Adam Daniel

2010-04-01

Contrary to expectation when compared with other migrant mining zones of sub-Saharan Africa, the nation of Guinea has a comparatively low and stable HIV rate. In addition, the regions with the largest gold, diamond, and bauxite mining operations report the lowest HIV rates within the country. This research set out to explain practices and beliefs within gold mining communities near Siguiri, Guinea--the highest-producing gold mining zone in the country--that may contribute to this phenomenon, particularly as they relate to the Abstinence, Be faithful, use a Condom approach to AIDS prevention. Structured interviews on a randomly selected sample of 460 adults and regular visitation to 16 pharmacies and health clinics within the mining zone yielded data showing that abstinence and condom use are minimally practiced for AIDS prevention. Instead, faithfulness to partners was overwhelmingly reported as the method of choice for AIDS avoidance. In addition, this research explored ways in which local conceptions of fidelity differed from those generally understood in other contexts, including engagement in short-term marriages at the gold mining sites.

Development of the International Spinal Cord Injury Activities and Participation Basic Data Set.

PubMed

Post, M W; Charlifue, S; Biering-Sørensen, F; Catz, A; Dijkers, M P; Horsewell, J; Noonan, V K; Noreau, L; Tate, D G; Sinnott, K A

2016-07-01

Consensus decision-making process. The objective of this study was to develop an International Spinal Cord Injury (SCI) Activities and Participation (A&P) Basic Data Set. International working group. A committee of experts was established to select and define A&P data elements to be included in this data set. A draft data set was developed and posted on the International Spinal Cord Society (ISCoS) and American Spinal Injury Association websites and was also disseminated among appropriate organizations for review. Suggested revisions were considered, and a final version of the A&P Data Set was completed. Consensus was reached to define A&P and to incorporate both performance and satisfaction ratings. Items that were considered core to each A&P domain were selected from two existing questionnaires. Four items measuring activities were selected from the Spinal Cord Independence Measure III to provide basic data on task execution in activities of daily living. Eight items were selected from the Craig Handicap Assessment and Reporting Technique to provide basic data on the frequency of participation. An additional rating of satisfaction on a three-point scale for each item completes the total of 24 A&P variables. Collection of the International SCI A&P Basic Data Set variables in all future research on SCI outcomes is advised to facilitate comparison of results across published studies from around the world. Additional standardised instruments to assess activities of daily living or participation can be administered, depending on the purpose of a particular study.

Diagnostic Efficiency among Psychiatric Outpatients of a Self-Report Version of a Subset of Screen Items of the Structured Clinical Interview for DSM-IV-TR Personality Disorders (SCID-II)

ERIC Educational Resources Information Center

Germans, Sara; Van Heck, Guus L.; Masthoff, Erik D.; Trompenaars, Fons J. W. M.; Hodiamont, Paul P. G.

2010-01-01

This article describes the identification of a 10-item set of the Structured Clinical Interview for DSM-IV Personality Disorders (SCID-II) items, which proved to be effective as a self-report assessment instrument in screening personality disorders. The item selection was based on the retrospective analyses of 495 SCID-II interviews. The…

Reliability and validity of a short form household food security scale in a Caribbean community.

PubMed

Gulliford, Martin C; Mahabir, Deepak; Rocke, Brian

2004-06-16

We evaluated the reliability and validity of the short form household food security scale in a different setting from the one in which it was developed. The scale was interview administered to 531 subjects from 286 households in north central Trinidad in Trinidad and Tobago, West Indies. We evaluated the six items by fitting item response theory models to estimate item thresholds, estimating agreement among respondents in the same households and estimating the slope index of income-related inequality (SII) after adjusting for age, sex and ethnicity. Item-score correlations ranged from 0.52 to 0.79 and Cronbach's alpha was 0.87. Item responses gave within-household correlation coefficients ranging from 0.70 to 0.78. Estimated item thresholds (standard errors) from the Rasch model ranged from -2.027 (0.063) for the 'balanced meal' item to 2.251 (0.116) for the 'hungry' item. The 'balanced meal' item had the lowest threshold in each ethnic group even though there was evidence of differential functioning for this item by ethnicity. Relative thresholds of other items were generally consistent with US data. Estimation of the SII, comparing those at the bottom with those at the top of the income scale, gave relative odds for an affirmative response of 3.77 (95% confidence interval 1.40 to 10.2) for the lowest severity item, and 20.8 (2.67 to 162.5) for highest severity item. Food insecurity was associated with reduced consumption of green vegetables after additionally adjusting for income and education (0.52, 0.28 to 0.96). The household food security scale gives reliable and valid responses in this setting. Differing relative item thresholds compared with US data do not require alteration to the cut-points for classification of 'food insecurity without hunger' or 'food insecurity with hunger'. The data provide further evidence that re-evaluation of the 'balanced meal' item is required.

Automated UMLS-Based Comparison of Medical Forms

PubMed Central

Dugas, Martin; Fritz, Fleur; Krumm, Rainer; Breil, Bernhard

2013-01-01

Medical forms are very heterogeneous: on a European scale there are thousands of data items in several hundred different systems. To enable data exchange for clinical care and research purposes there is a need to develop interoperable documentation systems with harmonized forms for data capture. A prerequisite in this harmonization process is comparison of forms. So far – to our knowledge – an automated method for comparison of medical forms is not available. A form contains a list of data items with corresponding medical concepts. An automatic comparison needs data types, item names and especially item with these unique concept codes from medical terminologies. The scope of the proposed method is a comparison of these items by comparing their concept codes (coded in UMLS). Each data item is represented by item name, concept code and value domain. Two items are called identical, if item name, concept code and value domain are the same. Two items are called matching, if only concept code and value domain are the same. Two items are called similar, if their concept codes are the same, but the value domains are different. Based on these definitions an open-source implementation for automated comparison of medical forms in ODM format with UMLS-based semantic annotations was developed. It is available as package compareODM from http://cran.r-project.org. To evaluate this method, it was applied to a set of 7 real medical forms with 285 data items from a large public ODM repository with forms for different medical purposes (research, quality management, routine care). Comparison results were visualized with grid images and dendrograms. Automated comparison of semantically annotated medical forms is feasible. Dendrograms allow a view on clustered similar forms. The approach is scalable for a large set of real medical forms. PMID:23861827

Set of Criteria for Efficiency of the Process Forming the Answers to Multiple-Choice Test Items

ERIC Educational Resources Information Center

Rybanov, Alexander Aleksandrovich

2013-01-01

Is offered the set of criteria for assessing efficiency of the process forming the answers to multiple-choice test items. To increase accuracy of computer-assisted testing results, it is suggested to assess dynamics of the process of forming the final answer using the following factors: loss of time factor and correct choice factor. The model…

Progress Monitoring the Effects of Daily Report Cards across Elementary and Secondary Settings Using Direct Behavior Rating: Single Item Scales

ERIC Educational Resources Information Center

Miller, Faith G.; Crovello, Nicholas J.; Chafouleas, Sandra M.

2017-01-01

Direct Behavior Rating-Single Item Scales (DBR-SIS) have been advanced as a promising, systematic, behavioral, progress-monitoring method that is flexible, efficient, and defensible. This study aimed to extend existing literature on the use of DBR-SIS in elementary and secondary settings, and to examine methods of monitoring student progress in…

Effectiveness of Using Computer-Based Video Instruction (CBVI) in Teaching the Location of Grocery Items to Students with Intellectual Disabilities

ERIC Educational Resources Information Center

Goo, Minkowan

2013-01-01

The purpose of this study is to examine whether or not CBVI is an effective method in teaching students with intellectual disabilities the skills of locating grocery items in classroom settings and whether or not the acquired skills in classroom settings generalize to actual grocery stores. Four high school students with intellectual disabilities…

Energy budgets of mining-induced earthquakes and their interactions with nearby stopes

USGS Publications Warehouse

McGarr, A.

2000-01-01

In the early 1960's, N.G.W. Cook, using an underground network of geophones, demonstrated that most Witwatersrand tremors are closely associated with deep level gold mining operations. He also showed that the energy released by the closure of the tabular stopes at depths of the order of 2 km was more than sufficient to account for the mining-induced earthquakes. I report here updated versions of these two results based on more modern underground data acquired in the Witwatersrand gold fields. Firstly, an extensive suite of in situ stress data indicate that the ambient state of crustal stress here is close to the failure state in the absence of mining even though the tectonic setting is thoroughly stable. Mining initially stabilizes the rock mass by reducing the pore fluid pressure from its initial hydrostatic state to nearly zero. The extensive mine excavations, as Cook showed, concentrate the deviatoric stresses, in localized regions of the abutments, back into a failure state resulting in seismicity. Secondly, there appears to be two distinct types of mining-induced earthquakes: the first is strongly coupled to the mining and involves shear failure plus a coseismic volume reduction; the second type is not evidently coupled to any particular mine face, shows purely deviatoric failure, and is presumably caused by more regional changes in the state of stress due to mining. Thirdly, energy budgets for mining induced earthquakes of both types indicate that, of the available released energy, only a few per cent is radiated by the seismic waves with the majority being consumed in overcoming fault friction. Published by Elsevier Science Ltd.In the early 1960's, N.G.W. Cook, using an underground network of geophones, demonstrated that most Witwatersrand tremors are closely associated with deep level gold mining operations. He also showed that the energy released by the closure of the tabular stopes at depths of the order of 2 km was more than sufficient to account for the mining-induced earthquakes. I report here updated versions of these two results based on more modern underground data acquired in the Witwatersrand gold fields. Firstly, an extensive suite of in situ stress data indicate that the ambient state of crustal stress here is close to the failure state in the absence of mining even though the tectonic setting is thoroughly stable. Mining initially stabilizes the rock mass by reducing the pore fluid pressure from its initial hydrostatic state to nearly zero. The extensive mine excavations, as Cook showed, concentrate the deviatoric stresses, in localized regions of the abutments, back into a failure state resulting in seismicity. Secondly, there appears to be two distinct types of mining-induced earthquakes: the first is strongly coupled to the mining and involves shear failure plus a coseismic volume reduction; the second type is not evidently coupled to any particular mine face, shows purely deviatoric failure, and is presumably caused by more regional changes in the state of stress due to mining. Thirdly, energy budgets for mining induced earthquakes of both types indicate that, of the available released energy, only a few per cent is radiated by the seismic waves with the majority being consumed in overcoming fault friction.

Health measurement using the ICF: Test-retest reliability study of ICF codes and qualifiers in geriatric care

PubMed Central

Okochi, Jiro; Utsunomiya, Sakiko; Takahashi, Tai

2005-01-01

Background The International Classification of Functioning, Disability and Health (ICF) was published by the World Health Organization (WHO) to standardize descriptions of health and disability. Little is known about the reliability and clinical relevance of measurements using the ICF and its qualifiers. This study examines the test-retest reliability of ICF codes, and the rate of immeasurability in long-term care settings of the elderly to evaluate the clinical applicability of the ICF and its qualifiers, and the ICF checklist. Methods Reliability of 85 body function (BF) items and 152 activity and participation (AP) items of the ICF was studied using a test-retest procedure with a sample of 742 elderly persons from 59 institutional and at home care service centers. Test-retest reliability was estimated using the weighted kappa statistic. The clinical relevance of the ICF was estimated by calculating immeasurability rate. The effect of the measurement settings and evaluators' experience was analyzed by stratification of these variables. The properties of each item were evaluated using both the kappa statistic and immeasurability rate to assess the clinical applicability of WHO's ICF checklist in the elderly care setting. Results The median of the weighted kappa statistics of 85 BF and 152 AP items were 0.46 and 0.55 respectively. The reproducibility statistics improved when the measurements were performed by experienced evaluators. Some chapters such as genitourinary and reproductive functions in the BF domain and major life area in the AP domain contained more items with lower test-retest reliability measures and rated as immeasurable than in the other chapters. Some items in the ICF checklist were rated as unreliable and immeasurable. Conclusion The reliability of the ICF codes when measured with the current ICF qualifiers is relatively low. The result in increase in reliability according to evaluators' experience suggests proper education will have positive effects to raise the reliability. The ICF checklist contains some items that are difficult to be applied in the geriatric care settings. The improvements should be achieved by selecting the most relevant items for each measurement and by developing appropriate qualifiers for each code according to the interest of the users. PMID:16050960

A Framework for Web Usage Mining in Electronic Government

NASA Astrophysics Data System (ADS)

Zhou, Ping; Le, Zhongjian

Web usage mining has been a major component of management strategy to enhance organizational analysis and decision. The literature on Web usage mining that deals with strategies and technologies for effectively employing Web usage mining is quite vast. In recent years, E-government has received much attention from researchers and practitioners. Huge amounts of user access data are produced in Electronic government Web site everyday. The role of these data in the success of government management cannot be overstated because they affect government analysis, prediction, strategies, tactical, operational planning and control. Web usage miming in E-government has an important role to play in setting government objectives, discovering citizen behavior, and determining future courses of actions. Web usage mining in E-government has not received adequate attention from researchers or practitioners. We developed a framework to promote a better understanding of the importance of Web usage mining in E-government. Using the current literature, we developed the framework presented herein, in hopes that it would stimulate more interest in this important area.

Predicting fatty acid profiles in blood based on food intake and the FADS1 rs174546 SNP.

PubMed

Hallmann, Jacqueline; Kolossa, Silvia; Gedrich, Kurt; Celis-Morales, Carlos; Forster, Hannah; O'Donovan, Clare B; Woolhead, Clara; Macready, Anna L; Fallaize, Rosalind; Marsaux, Cyril F M; Lambrinou, Christina-Paulina; Mavrogianni, Christina; Moschonis, George; Navas-Carretero, Santiago; San-Cristobal, Rodrigo; Godlewska, Magdalena; Surwiłło, Agnieszka; Mathers, John C; Gibney, Eileen R; Brennan, Lorraine; Walsh, Marianne C; Lovegrove, Julie A; Saris, Wim H M; Manios, Yannis; Martinez, Jose Alfredo; Traczyk, Iwona; Gibney, Michael J; Daniel, Hannelore

2015-12-01

A high intake of n-3 PUFA provides health benefits via changes in the n-6/n-3 ratio in blood. In addition to such dietary PUFAs, variants in the fatty acid desaturase 1 (FADS1) gene are also associated with altered PUFA profiles. We used mathematical modeling to predict levels of PUFA in whole blood, based on multiple hypothesis testing and bootstrapped LASSO selected food items, anthropometric and lifestyle factors, and the rs174546 genotypes in FADS1 from 1607 participants (Food4Me Study). The models were developed using data from the first reported time point (training set) and their predictive power was evaluated using data from the last reported time point (test set). Among other food items, fish, pizza, chicken, and cereals were identified as being associated with the PUFA profiles. Using these food items and the rs174546 genotypes as predictors, models explained 26-43% of the variability in PUFA concentrations in the training set and 22-33% in the test set. Selecting food items using multiple hypothesis testing is a valuable contribution to determine predictors, as our models' predictive power is higher compared to analogue studies. As unique feature, we additionally confirmed our models' power based on a test set. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Data mining in pharma sector: benefits.

PubMed

Ranjan, Jayanthi

2009-01-01

The amount of data getting generated in any sector at present is enormous. The information flow in the pharma industry is huge. Pharma firms are progressing into increased technology-enabled products and services. Data mining, which is knowledge discovery from large sets of data, helps pharma firms to discover patterns in improving the quality of drug discovery and delivery methods. The paper aims to present how data mining is useful in the pharma industry, how its techniques can yield good results in pharma sector, and to show how data mining can really enhance in making decisions using pharmaceutical data. This conceptual paper is written based on secondary study, research and observations from magazines, reports and notes. The author has listed the types of patterns that can be discovered using data mining in pharma data. The paper shows how data mining is useful in the pharma industry and how its techniques can yield good results in pharma sector. Although much work can be produced for discovering knowledge in pharma data using data mining, the paper is limited to conceptualizing the ideas and view points at this stage; future work may include applying data mining techniques to pharma data based on primary research using the available, famous significant data mining tools. Research papers and conceptual papers related to data mining in Pharma industry are rare; this is the motivation for the paper.

Multiple-Instance Regression with Structured Data

NASA Technical Reports Server (NTRS)

Wagstaff, Kiri L.; Lane, Terran; Roper, Alex

2008-01-01

We present a multiple-instance regression algorithm that models internal bag structure to identify the items most relevant to the bag labels. Multiple-instance regression (MIR) operates on a set of bags with real-valued labels, each containing a set of unlabeled items, in which the relevance of each item to its bag label is unknown. The goal is to predict the labels of new bags from their contents. Unlike previous MIR methods, MI-ClusterRegress can operate on bags that are structured in that they contain items drawn from a number of distinct (but unknown) distributions. MI-ClusterRegress simultaneously learns a model of the bag's internal structure, the relevance of each item, and a regression model that accurately predicts labels for new bags. We evaluated this approach on the challenging MIR problem of crop yield prediction from remote sensing data. MI-ClusterRegress provided predictions that were more accurate than those obtained with non-multiple-instance approaches or MIR methods that do not model the bag structure.

Arsenic associated with historical gold mining in the Sierra Nevada foothills: Case study and field trip guide for Empire Mine State Historic Park, California

USGS Publications Warehouse

Alpers, Charles N.; Myers, Perry A; Millsap, Daniel; Regnier, Tamsen B; Bowell, Robert J.; Alpers, Charles N.; Jamieson, Heather E.; Nordstrom, D. Kirk; Majzlan, Juraj

2014-01-01

The Empire Mine, together with other mines in the Grass Valley mining district, produced at least 21.3 million troy ounces (663 tonnes) of gold (Au) during the 1850s through the 1950s, making it the most productive hardrock Au mining district in California history (Clark 1970). The Empire Mine State Historic Park (Empire Mine SHP or EMSHP), established in 1975, provides the public with an opportunity to see many well-preserved features of the historic mining and mineral processing operations (CDPR 2014a).A legacy of Au mining at Empire Mine and elsewhere is contamination of mine wastes and associated soils, surface waters, and groundwaters with arsenic (As), mercury (Hg), lead (Pb), and other metals. At EMSHP, As has been the principal contaminant of concern and the focus of extensive remediation efforts over the past several years by the State of California, Department of Parks and Recreation (DPR) and Newmont USA, Ltd. In addition, the site is the main focus of a multidisciplinary research project on As bioavailability and bioaccessibility led by the California Department of Toxic Substances Control (DTSC) and funded by the U.S. Environmental Protection Agency’s (USEPA’s) Brownfields Program.This chapter was prepared as a guide for a field trip to EMSHP held on June 14, 2014, in conjunction with a short course on “Environmental Geochemistry, Mineralogy, and Microbiology of Arsenic” held in Nevada City, California on June 15–16, 2014. This guide contains background information on geological setting, mining history, and environmental history at EMSHP and other historical Au mining districts in the Sierra Nevada, followed by descriptions of the field trip stops.

Development of industrial minerals in Colorado

USGS Publications Warehouse

Arbogast, Belinda F.; Knepper, Daniel H.; Langer, William H.; Cappa, James A.; Keller, John W.; Widmann, Beth L.; Ellefsen, Karl J.; Klein, Terry L.; Lucius, Jeffrey E.; Dersch, John S.

2011-01-01

Technology and engineering have helped make mining safer and cleaner for both humans and the environment. Inevitably, mineral development entails costs as well as benefits. Developing a mine is an environmental, engineering, and planning challenge that must conform to many Federal, State, and local regulations. Community collaboration, creative design, and best management practices of sustainability and biodiversity can be positive indicators for the mining industry. A better understanding of aesthetics, culture, economics, geology, climate, vegetation and wildlife, topography, historical significance, and regional land planning is important in resolving land-use issues and managing mineral resources wisely. Ultimately, the consuming public makes choices about product use (including water, food, highways, housing, and thousands of other items) that influence operations of the mineral industry. Land planners, resource managers, earth scientists, designers, and public groups have a responsibility to consider sound scientific information, society's needs, and community appeals in making smart decisions concerning resource use and how complex landscapes should change. An effort to provide comprehensive geosciences data for land management agencies in central Colorado was undertaken in 2003 by scientists of the U.S. Geological Survey and the Colorado Geological Survey. This effort, the Central Colorado Assessment Project, addressed a variety of land-use issues: an understanding of the availability of industrial and metallic rocks and minerals, the geochemical and environmental effects of historic mining activity on surface water and groundwater, and the geologic controls on the availability and quality of groundwater. The USDA Forest Service and other land management agencies have the opportunity to contribute to the sustainable management of natural aggregate and other mineral resources through the identification and selective development of mineral resources and the reclamation of mines on lands that they administer. The information in this Circular will help them carry out that task.

Computational Psychometrics for the Measurement of Collaborative Problem Solving Skills

PubMed Central

Polyak, Stephen T.; von Davier, Alina A.; Peterschmidt, Kurt

2017-01-01

This paper describes a psychometrically-based approach to the measurement of collaborative problem solving skills, by mining and classifying behavioral data both in real-time and in post-game analyses. The data were collected from a sample of middle school children who interacted with a game-like, online simulation of collaborative problem solving tasks. In this simulation, a user is required to collaborate with a virtual agent to solve a series of tasks within a first-person maze environment. The tasks were developed following the psychometric principles of Evidence Centered Design (ECD) and are aligned with the Holistic Framework developed by ACT. The analyses presented in this paper are an application of an emerging discipline called computational psychometrics which is growing out of traditional psychometrics and incorporates techniques from educational data mining, machine learning and other computer/cognitive science fields. In the real-time analysis, our aim was to start with limited knowledge of skill mastery, and then demonstrate a form of continuous Bayesian evidence tracing that updates sub-skill level probabilities as new conversation flow event evidence is presented. This is performed using Bayes' rule and conversation item conditional probability tables. The items are polytomous and each response option has been tagged with a skill at a performance level. In our post-game analysis, our goal was to discover unique gameplay profiles by performing a cluster analysis of user's sub-skill performance scores based on their patterns of selected dialog responses. PMID:29238314

Computational Psychometrics for the Measurement of Collaborative Problem Solving Skills.

PubMed

Polyak, Stephen T; von Davier, Alina A; Peterschmidt, Kurt

2017-01-01

This paper describes a psychometrically-based approach to the measurement of collaborative problem solving skills, by mining and classifying behavioral data both in real-time and in post-game analyses. The data were collected from a sample of middle school children who interacted with a game-like, online simulation of collaborative problem solving tasks. In this simulation, a user is required to collaborate with a virtual agent to solve a series of tasks within a first-person maze environment. The tasks were developed following the psychometric principles of Evidence Centered Design (ECD) and are aligned with the Holistic Framework developed by ACT. The analyses presented in this paper are an application of an emerging discipline called computational psychometrics which is growing out of traditional psychometrics and incorporates techniques from educational data mining, machine learning and other computer/cognitive science fields. In the real-time analysis, our aim was to start with limited knowledge of skill mastery, and then demonstrate a form of continuous Bayesian evidence tracing that updates sub-skill level probabilities as new conversation flow event evidence is presented. This is performed using Bayes' rule and conversation item conditional probability tables. The items are polytomous and each response option has been tagged with a skill at a performance level. In our post-game analysis, our goal was to discover unique gameplay profiles by performing a cluster analysis of user's sub-skill performance scores based on their patterns of selected dialog responses.

Generalizability and Dependability of a Multi-Item Direct Behavior Rating Scale in a Kindergarten Classroom Setting

ERIC Educational Resources Information Center

Wickerd, Garry; Hulac, David

2017-01-01

Accurate and rapid identification of students displaying behavioral problems requires instrumentation that is user friendly and reliable. The purpose of the study was to evaluate a multi-item direct behavior rating scale called the Direct Behavior Rating-Multiple Item Scale (DBR-MIS) for disruptive behavior to determine the number of…

An Analysis of the Individual Effects of Sex Bias.

ERIC Educational Resources Information Center

Smith, Richard M.

Most attempts to correct for the presence of biased test items in a measurement instrument have been either to remove the items or to adjust the scores to correct for the bias. Using the Rasch Dichotomous Response Model and the independent ability estimates derived from three sets of items, those which favor females, those which favor males, and…

Improving the Quality of Innovative Item Types: Four Tasks for Design and Development

ERIC Educational Resources Information Center

Parshall, Cynthia G.; Harmes, J. Christine

2009-01-01

Many exam programs have begun to include innovative item types in their operational assessments. While innovative item types appear to have great promise for expanding measurement, there can also be genuine challenges to their successful implementation. In this paper we present a set of four activities that can be beneficially incorporated into…

Estimating the Reliability of a Test Battery Composite or a Test Score Based on Weighted Item Scoring

ERIC Educational Resources Information Center

Feldt, Leonard S.

2004-01-01

In some settings, the validity of a battery composite or a test score is enhanced by weighting some parts or items more heavily than others in the total score. This article describes methods of estimating the total score reliability coefficient when differential weights are used with items or parts.

A Comparison of Four Item-Selection Methods for Severely Constrained CATs

ERIC Educational Resources Information Center

He, Wei; Diao, Qi; Hauser, Carl

2014-01-01

This study compared four item-selection procedures developed for use with severely constrained computerized adaptive tests (CATs). Severely constrained CATs refer to those adaptive tests that seek to meet a complex set of constraints that are often not conclusive to each other (i.e., an item may contribute to the satisfaction of several…

An Explanatory Item Response Theory Approach for a Computer-Based Case Simulation Test

ERIC Educational Resources Information Center

Kahraman, Nilüfer

2014-01-01

Problem: Practitioners working with multiple-choice tests have long utilized Item Response Theory (IRT) models to evaluate the performance of test items for quality assurance. The use of similar applications for performance tests, however, is often encumbered due to the challenges encountered in working with complicated data sets in which local…

Short Form of the Developmental Behaviour Checklist

ERIC Educational Resources Information Center

Taffe, John R.; Gray, Kylie M.; Einfeld, Stewart L.; Dekker, Marielle C.; Koot, Hans M.; Emerson, Eric; Koskentausta, Terhi; Tonge, Bruce J.

2007-01-01

A 24-item short form of the 96-item Developmental Behaviour Checklist was developed to provide a brief measure of Total Behaviour Problem Score for research purposes. The short form Developmental Behaviour Checklist (DBC-P24) was chosen for low bias and high precision from among 100 randomly selected item sets. The DBC-P24 was developed from…

Comparison of Distributed Acoustic Sensing (DAS) from Fiber-Optic Cable to Three Component Geophones in an Underground Mine

NASA Astrophysics Data System (ADS)

Speece, M. A.; Nesladek, N. J.; Kammerer, C.; Maclaughlin, M.; Wang, H. F.; Lord, N. E.

2017-12-01

We conducted experiments in the Underground Education Mining Center on the Montana Tech campus, Butte, Montana, to make a direct comparison between Digital Acoustic Sensing (DAS) and three-component geophones in a mining setting. The sources used for this project where a vertical sledgehammer, oriented shear sledgehammer, and blasting caps set off in both unstemmed and stemmed drillholes. Three-component Geospace 20DM geophones were compared with three different types of fiber-optic cable: (1) Brugg strain, (2) Brugg temperature, and (3) Optical Cable Corporation strain. We attached geophones to the underground mine walls and on the ground surface above the mine. We attached fiber-optic cables to the mine walls and placed fiber-optic cable in boreholes drilled through an underground pillar. In addition, we placed fiber-optic cables in a shallow trench at the surface of the mine. We converted the DAS recordings from strain rate to strain prior to comparison with the geophone data. The setup of the DAS system for this project led to a previously unknown triggering problem that compromised the early samples of the DAS traces often including the first-break times on the DAS records. Geophones clearly recorded the explosives; however, the large amount of energy and its close distance from the fiber-optic cables seemed to compromise the entire fiber loop. The underground hammer sources produced a rough match between the DAS records and the geophone records. However, the sources on the surface of the mine, specifically the sources oriented inline with the fiber-optic cables, produced a close match between the fiber-optic traces and the geophone traces. All three types of fiber-optic cable that were in the mine produced similar results, and one type did not clearly outperform the others. Instead, the coupling of the cable to rock appears to be the most important factor determining DAS data quality. Moreover, we observed the importance of coupling in the boreholes, where fiber-optic cables that were pressed against the rock face with a spacer outperformed fiber-optic cables that were fully embedded within the grout filling the inside of the borehole.

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules

PubMed Central

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

2015-01-01

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods. PMID:25938136

A Bayesian Scoring Technique for Mining Predictive and Non-Spurious Rules.

PubMed

Batal, Iyad; Cooper, Gregory; Hauskrecht, Milos

Rule mining is an important class of data mining methods for discovering interesting patterns in data. The success of a rule mining method heavily depends on the evaluation function that is used to assess the quality of the rules. In this work, we propose a new rule evaluation score - the Predictive and Non-Spurious Rules (PNSR) score. This score relies on Bayesian inference to evaluate the quality of the rules and considers the structure of the rules to filter out spurious rules. We present an efficient algorithm for finding rules with high PNSR scores. The experiments demonstrate that our method is able to cover and explain the data with a much smaller rule set than existing methods.

Robotic Mining Competition - Setup

NASA Image and Video Library

2018-05-14

On the first day of NASA's 9th Robotic Mining Competition, set-up day on May 14, college team members work on their robot miner in the RobotPits in the Educator Resource Center at Kennedy Space Center Visitor Complex in Florida. More than 40 student teams from colleges and universities around the U.S. will use their mining robots to dig in a supersized sandbox filled with BP-1, or simulated Martian soil, gravel and rocks, and participate in other competition requirements. The Robotic Mining Competition is a NASA Human Exploration and Operations Mission Directorate project designed to encourage students in science, technology, engineering and math, or STEM fields. The project provides a competitive environment to foster innovative ideas and solutions that could be used on NASA's deep space missions.

Biomedical data mining in clinical routine: expanding the impact of hospital information systems.

PubMed

Müller, Marcel; Markó, Kornel; Daumke, Philipp; Paetzold, Jan; Roesner, Arnold; Klar, Rüdiger

2007-01-01

In this paper we want to describe how the promising technology of biomedical data mining can improve the use of hospital information systems: a large set of unstructured, narrative clinical data from a dermatological university hospital like discharge letters or other dermatological reports were processed through a morpho-semantic text retrieval engine ("MorphoSaurus") and integrated with other clinical data using a web-based interface and brought into daily clinical routine. The user evaluation showed a very high user acceptance - this system seems to meet the clinicians' requirements for a vertical data mining in the electronic patient records. What emerges is the need for integration of biomedical data mining into hospital information systems for clinical, scientific, educational and economic reasons.

A Note on Interfacing Object Warehouses and Mass Storage Systems for Data Mining Applications

NASA Technical Reports Server (NTRS)

Grossman, Robert L.; Northcutt, Dave

1996-01-01

Data mining is the automatic discovery of patterns, associations, and anomalies in data sets. Data mining requires numerically and statistically intensive queries. Our assumption is that data mining requires a specialized data management infrastructure to support the aforementioned intensive queries, but because of the sizes of data involved, this infrastructure is layered over a hierarchical storage system. In this paper, we discuss the architecture of a system which is layered for modularity, but exploits specialized lightweight services to maintain efficiency. Rather than use a full functioned database for example, we use light weight object services specialized for data mining. We propose using information repositories between layers so that components on either side of the layer can access information in the repositories to assist in making decisions about data layout, the caching and migration of data, the scheduling of queries, and related matters.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts.

PubMed

Westergaard, David; Stærfeldt, Hans-Henrik; Tønsberg, Christian; Jensen, Lars Juhl; Brunak, Søren

2018-02-01

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823-2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein-protein, disease-gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only.

A comprehensive and quantitative comparison of text-mining in 15 million full-text articles versus their corresponding abstracts

PubMed Central

Westergaard, David; Stærfeldt, Hans-Henrik

2018-01-01

Across academia and industry, text mining has become a popular strategy for keeping up with the rapid growth of the scientific literature. Text mining of the scientific literature has mostly been carried out on collections of abstracts, due to their availability. Here we present an analysis of 15 million English scientific full-text articles published during the period 1823–2016. We describe the development in article length and publication sub-topics during these nearly 250 years. We showcase the potential of text mining by extracting published protein–protein, disease–gene, and protein subcellular associations using a named entity recognition system, and quantitatively report on their accuracy using gold standard benchmark data sets. We subsequently compare the findings to corresponding results obtained on 16.5 million abstracts included in MEDLINE and show that text mining of full-text articles consistently outperforms using abstracts only. PMID:29447159

A case-based reasoning tool for breast cancer knowledge management with data mining concepts and techniques

NASA Astrophysics Data System (ADS)

Demigha, Souâd.

2016-03-01

The paper presents a Case-Based Reasoning Tool for Breast Cancer Knowledge Management to improve breast cancer screening. To develop this tool, we combine both concepts and techniques of Case-Based Reasoning (CBR) and Data Mining (DM). Physicians and radiologists ground their diagnosis on their expertise (past experience) based on clinical cases. Case-Based Reasoning is the process of solving new problems based on the solutions of similar past problems and structured as cases. CBR is suitable for medical use. On the other hand, existing traditional hospital information systems (HIS), Radiological Information Systems (RIS) and Picture Archiving Information Systems (PACS) don't allow managing efficiently medical information because of its complexity and heterogeneity. Data Mining is the process of mining information from a data set and transform it into an understandable structure for further use. Combining CBR to Data Mining techniques will facilitate diagnosis and decision-making of medical experts.

Activity recognition from minimal distinguishing subsequence mining

NASA Astrophysics Data System (ADS)

Iqbal, Mohammad; Pao, Hsing-Kuo

2017-08-01

Human activity recognition is one of the most important research topics in the era of Internet of Things. To separate different activities given sensory data, we utilize a Minimal Distinguishing Subsequence (MDS) mining approach to efficiently find distinguishing patterns among different activities. We first transform the sensory data into a series of sensor triggering events and operate the MDS mining procedure afterwards. The gap constraints are also considered in the MDS mining. Given the multi-class nature of most activity recognition tasks, we modify the MDS mining approach from a binary case to a multi-class one to fit the need for multiple activity recognition. We also study how to select the best parameter set including the minimal and the maximal support thresholds in finding the MDSs for effective activity recognition. Overall, the prediction accuracy is 86.59% on the van Kasteren dataset which consists of four different activities for recognition.

Exploring patterns of epigenetic information with data mining techniques.

PubMed

Aguiar-Pulido, Vanessa; Seoane, José A; Gestal, Marcos; Dorado, Julián

2013-01-01

Data mining, a part of the Knowledge Discovery in Databases process (KDD), is the process of extracting patterns from large data sets by combining methods from statistics and artificial intelligence with database management. Analyses of epigenetic data have evolved towards genome-wide and high-throughput approaches, thus generating great amounts of data for which data mining is essential. Part of these data may contain patterns of epigenetic information which are mitotically and/or meiotically heritable determining gene expression and cellular differentiation, as well as cellular fate. Epigenetic lesions and genetic mutations are acquired by individuals during their life and accumulate with ageing. Both defects, either together or individually, can result in losing control over cell growth and, thus, causing cancer development. Data mining techniques could be then used to extract the previous patterns. This work reviews some of the most important applications of data mining to epigenetics.

Using tracers to evaluate streamflow gain-loss characteristics of Terror Creek, in the vicinity of a mine-permit area, Delta County, Colorado, water year 2003

USGS Publications Warehouse

Williams, Cory A.; Leib, Kenneth J.

2005-01-01

In 2003, the U.S. Geological Survey, in cooperation with Delta County, initiated a study to characterize streamflow gainloss in a reach of Terror Creek, in the vicinity of a mine-permit area planned for future coal mining. This report describes the methods of the study and includes results from a comparison of two sets of streamflow measurements using tracer techniques following the constant-rate injection method. Two measurement sets were used to characterize the streamflow gain-loss associated with reservoir-supplemented streamflow conditions and with natural base-flow conditions. A comparison of the measurement sets indicates that the streamflow gain-loss characteristics of the Terror Creek study reach are consistent between the two hydrologic conditions evaluated. A substantial streamflow gain occurs between measurement locations 4 and 5 in both measurement sets, and streamflow is lost between measurement locations 5 and 7 (measurement set 1, measurement location 6 not visited) and 5 and 6 (measurement set 2). A comparison of the measurement sets above and below the mine-permit area (measurement locations 3 and 7) shows a consistent loss of 0.37 and 0.31 cubic foot per second (representing 5- and 12-percent streamflow losses normalized to measurement location 3) for measurement sets 1 and 2, respectively. This indicates that similar streamflow losses occur both during reservoir-supplemented and natural base-flow conditions, with a mean streamflow loss of 0.34 cubic foot per second for measurement sets 1 and 2. Findings from a previous investigation support the observed streamflow loss between measurement locations 3 and 7 in this study. The findings from the previous investigation indicate a streamflow loss of 0.59 cubic foot per second occurs between these measurement locations. Statistical testing of the differences in streamflow between measurement locations 3 and 7 indicates that there is a discernible streamflow loss. The p-value of 0.0236 for the parametric paired t-test indicates that there is a 2.36-percent probability of observing a sample mean difference of 0.34 cubic foot per second if the population mean is zero. The p-value of 0.125 for the nonparametric exact Wilcoxon signed rank test indicates that there is a 12.5-percent probability of observing a sample mean difference this large if the population mean is zero. The similarity in streamflow gain-loss between measurement sets indicates that the process controlling streamflow may be the same between the two hydrologic conditions evaluated. Gains between measurement locations 4 and 5 may be related to hyporheic flow from tributaries that were dry during the study. No other obvious sources of surface water were identified during the investigation. The cause for the observed streamflow loss between measurement locations 5 and 6 is unknown but may be related to mapped local faulting, 100 years of coal mining in the area, and aquifer recharge.

Recommending personally interested contents by text mining, filtering, and interfaces

DOEpatents

Xu, Songhua

2015-10-27

A personalized content recommendation system includes a client interface device configured to monitor a user's information data stream. A collaborative filter remote from the client interface device generates automated predictions about the interests of the user. A database server stores personal behavioral profiles and user's preferences based on a plurality of monitored past behaviors and an output of the collaborative user personal interest inference engine. A programmed personal content recommendation server filters items in an incoming information stream with the personal behavioral profile and identifies only those items of the incoming information stream that substantially matches the personal behavioral profile. The identified personally relevant content is then recommended to the user following some priority that may consider the similarity between the personal interest matches, the context of the user information consumption behaviors that may be shown by the user's content consumption mode.

Use HypE to Hide Association Rules by Adding Items

PubMed Central

Cheng, Peng; Lin, Chun-Wei; Pan, Jeng-Shyang

2015-01-01

During business collaboration, partners may benefit through sharing data. People may use data mining tools to discover useful relationships from shared data. However, some relationships are sensitive to the data owners and they hope to conceal them before sharing. In this paper, we address this problem in forms of association rule hiding. A hiding method based on evolutionary multi-objective optimization (EMO) is proposed, which performs the hiding task by selectively inserting items into the database to decrease the confidence of sensitive rules below specified thresholds. The side effects generated during the hiding process are taken as optimization goals to be minimized. HypE, a recently proposed EMO algorithm, is utilized to identify promising transactions for modification to minimize side effects. Results on real datasets demonstrate that the proposed method can effectively perform sanitization with fewer damages to the non-sensitive knowledge in most cases. PMID:26070130

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.

Development and validation of brief scales to measure emotional and behavioural problems among Chinese adolescents

PubMed Central

Shen, Minxue; Hu, Ming; Sun, Zhenqiu

2017-01-01

Objectives To develop and validate brief scales to measure common emotional and behavioural problems among adolescents in the examination-oriented education system and collectivistic culture of China. Setting Middle schools in Hunan province. Participants 5442 middle school students aged 11–19 years were sampled. 4727 valid questionnaires were collected and used for validation of the scales. The final sample included 2408 boys and 2319 girls. Primary and secondary outcome measures The tools were assessed by the item response theory, classical test theory (reliability and construct validity) and differential item functioning. Results Four scales to measure anxiety, depression, study problem and sociality problem were established. Exploratory factor analysis showed that each scale had two solutions. Confirmatory factor analysis showed acceptable to good model fit for each scale. Internal consistency and test–retest reliability of all scales were above 0.7. Item response theory showed that all items had acceptable discrimination parameters and most items had appropriate difficulty parameters. 10 items demonstrated differential item functioning with respect to gender. Conclusions Four brief scales were developed and validated among adolescents in middle schools of China. The scales have good psychometric properties with minor differential item functioning. They can be used in middle school settings, and will help school officials to assess the students’ emotional/behavioural problems. PMID:28062469

Consensus on Quality Indicators of Postgraduate Medical E-Learning: Delphi Study

PubMed Central

Walsh, Kieran; Westerman, Michiel; Scheele, Fedde

2018-01-01

Background The progressive use of e-learning in postgraduate medical education calls for useful quality indicators. Many evaluation tools exist. However, these are diversely used and their empirical foundation is often lacking. Objective We aimed to identify an empirically founded set of quality indicators to set the bar for “good enough” e-learning. Methods We performed a Delphi procedure with a group of 13 international education experts and 10 experienced users of e-learning. The questionnaire started with 57 items. These items were the result of a previous literature review and focus group study performed with experts and users. Consensus was met when a rate of agreement of more than two-thirds was achieved. Results In the first round, the participants accepted 37 items of the 57 as important, reached no consensus on 20, and added 15 new items. In the second round, we added the comments from the first round to the items on which there was no consensus and added the 15 new items. After this round, a total of 72 items were addressed and, of these, 37 items were accepted and 34 were rejected due to lack of consensus. Conclusions This study produced a list of 37 items that can form the basis of an evaluation tool to evaluate postgraduate medical e-learning. This is, to our knowledge, the first time that quality indicators for postgraduate medical e-learning have been defined and validated. The next step is to create and validate an e-learning evaluation tool from these items. PMID:29699970

Optimization of injection molding process parameters for a plastic cell phone housing component

NASA Astrophysics Data System (ADS)

Rajalingam, Sokkalingam; Vasant, Pandian; Khe, Cheng Seong; Merican, Zulkifli; Oo, Zeya

2016-11-01

To produce thin-walled plastic items, injection molding process is one of the most widely used application tools. However, to set optimal process parameters is difficult as it may cause to produce faulty items on injected mold like shrinkage. This study aims at to determine such an optimum injection molding process parameters which can reduce the fault of shrinkage on a plastic cell phone cover items. Currently used setting of machines process produced shrinkage and mis-specified length and with dimensions below the limit. Thus, for identification of optimum process parameters, maintaining closer targeted length and width setting magnitudes with minimal variations, more experiments are needed. The mold temperature, injection pressure and screw rotation speed are used as process parameters in this research. For optimal molding process parameters the Response Surface Methods (RSM) is applied. The major contributing factors influencing the responses were identified from analysis of variance (ANOVA) technique. Through verification runs it was found that the shrinkage defect can be minimized with the optimal setting found by RSM.

The Effect of Mental Rotation on Surgical Pathological Diagnosis.

PubMed

Park, Heejung; Kim, Hyun Soo; Cha, Yoon Jin; Choi, Junjeong; Minn, Yangki; Kim, Kyung Sik; Kim, Se Hoon

2018-05-01

Pathological diagnosis involves very delicate and complex consequent processing that is conducted by a pathologist. The recognition of false patterns might be an important cause of misdiagnosis in the field of surgical pathology. In this study, we evaluated the influence of visual and cognitive bias in surgical pathologic diagnosis, focusing on the influence of "mental rotation." We designed three sets of the same images of uterine cervix biopsied specimens (original, left to right mirror images, and 180-degree rotated images), and recruited 32 pathologists to diagnose the 3 set items individually. First, the items found to be adequate for analysis by classical test theory, Generalizability theory, and item response theory. The results showed statistically no differences in difficulty, discrimination indices, and response duration time between the image sets. Mental rotation did not influence the pathologists' diagnosis in practice. Interestingly, outliers were more frequent in rotated image sets, suggesting that the mental rotation process may influence the pathological diagnoses of a few individual pathologists. © Copyright: Yonsei University College of Medicine 2018.

[The principal components analysis--method to classify the statistical variables with applications in medicine].

PubMed

Dascălu, Cristina Gena; Antohe, Magda Ecaterina

2009-01-01

Based on the eigenvalues and the eigenvectors analysis, the principal component analysis has the purpose to identify the subspace of the main components from a set of parameters, which are enough to characterize the whole set of parameters. Interpreting the data for analysis as a cloud of points, we find through geometrical transformations the directions where the cloud's dispersion is maximal--the lines that pass through the cloud's center of weight and have a maximal density of points around them (by defining an appropriate criteria function and its minimization. This method can be successfully used in order to simplify the statistical analysis on questionnaires--because it helps us to select from a set of items only the most relevant ones, which cover the variations of the whole set of data. For instance, in the presented sample we started from a questionnaire with 28 items and, applying the principal component analysis we identified 7 principal components--or main items--fact that simplifies significantly the further data statistical analysis.

"Sticking Together!" Policy Activism from within a UK Coal-Mining Community

ERIC Educational Resources Information Center

Bright, N. Geoffrey

2012-01-01

This article reflects on some aspects of a doctoral ethnographic study of young people disaffected from schooling in a post-industrial space of ruin in a former coal-mining community in England. It considers how their experiences of resistance and refusal of schooling can, in the relational ethos of non-school support settings, come to speak back…

Cluster Analysis-Based Approaches for Geospatiotemporal Data Mining of Massive Data Sets for Identification of Forest Threats

Treesearch

Richard Trans Mills; Forrest M Hoffman; Jitendra Kumar; William W. Hargrove

2011-01-01

We investigate methods for geospatiotemporal data mining of multi-year land surface phenology data (250 m2 Normalized Difference Vegetation Index (NDVI) values derived from the Moderate Resolution Imaging Spectrometer (MODIS) in this study) for the conterminous United States (CONUS) as part of an early warning system for detecting threats to forest ecosystems. The...

Compass: a hybrid method for clinical and biobank data mining.

PubMed

Krysiak-Baltyn, K; Nordahl Petersen, T; Audouze, K; Jørgensen, Niels; Angquist, L; Brunak, S

2014-02-01

We describe a new method for identification of confident associations within large clinical data sets. The method is a hybrid of two existing methods; Self-Organizing Maps and Association Mining. We utilize Self-Organizing Maps as the initial step to reduce the search space, and then apply Association Mining in order to find association rules. We demonstrate that this procedure has a number of advantages compared to traditional Association Mining; it allows for handling numerical variables without a priori binning and is able to generate variable groups which act as "hotspots" for statistically significant associations. We showcase the method on infertility-related data from Danish military conscripts. The clinical data we analyzed contained both categorical type questionnaire data and continuous variables generated from biological measurements, including missing values. From this data set, we successfully generated a number of interesting association rules, which relate an observation with a specific consequence and the p-value for that finding. Additionally, we demonstrate that the method can be used on non-clinical data containing chemical-disease associations in order to find associations between different phenotypes, such as prostate cancer and breast cancer. Copyright © 2013 Elsevier Inc. All rights reserved.

Detection of bulk explosives using the GPR only portion of the HSTAMIDS system

NASA Astrophysics Data System (ADS)

Tabony, Joshua; Carlson, Douglas O.; Duvoisin, Herbert A., III; Torres-Rosario, Juan

2010-04-01

The legacy AN/PSS-14 (Army-Navy Portable Special Search-14) Handheld Mine Detecting Set (also called HSTAMIDS for Handheld Standoff Mine Detection System) has proven itself over the last 7 years as the state-of-the-art in land mine detection, both for the US Army and for Humanitarian Demining groups. Its dual GPR (Ground Penetrating Radar) and MD (Metal Detection) sensor has provided receiver operating characteristic curves (probability of detection or Pd versus false alarm rate or FAR) that routinely set the mark for such devices. Since its inception and type-classification in 2003 as the US (United States) Army standard, the desire for use of the AN/PSS-14 against alternate threats - such as bulk explosives - has recently become paramount. To this end, L-3 CyTerra has developed and tested bulk explosive detection and discrimination algorithms using only the Stepped Frequency Continuous Wave (SFCW) Ground Penetrating Radar (GPR) portion of the system, versus the fused version that is used to optimally detect land mines. Performance of the new bulk explosive algorithm against representative zero-metal bulk explosive target and clutter emplacements is depicted, with the utility to the operator also described.

30 CFR 917.13 - State statutory and regulatory provisions set aside.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false State statutory and regulatory provisions set aside. 917.13 Section 917.13 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... § 917.13 State statutory and regulatory provisions set aside. (a) The following provision of Kentucky...

An intelligent knowledge mining model for kidney cancer using rough set theory.

PubMed

Durai, M A Saleem; Acharjya, D P; Kannan, A; Iyengar, N Ch Sriman Narayana

2012-01-01

Medical diagnosis processes vary in the degree to which they attempt to deal with different complicating aspects of diagnosis such as relative importance of symptoms, varied symptom pattern and the relation between diseases themselves. Rough set approach has two major advantages over the other methods. First, it can handle different types of data such as categorical, numerical etc. Secondly, it does not make any assumption like probability distribution function in stochastic modeling or membership grade function in fuzzy set theory. It involves pattern recognition through logical computational rules rather than approximating them through smooth mathematical functional forms. In this paper we use rough set theory as a data mining tool to derive useful patterns and rules for kidney cancer faulty diagnosis. In particular, the historical data of twenty five research hospitals and medical college is used for validation and the results show the practical viability of the proposed approach.

The representation of order information in auditory-verbal short-term memory.

PubMed

Kalm, Kristjan; Norris, Dennis

2014-05-14

Here we investigate how order information is represented in auditory-verbal short-term memory (STM). We used fMRI and a serial recall task to dissociate neural activity patterns representing the phonological properties of the items stored in STM from the patterns representing their order. For this purpose, we analyzed fMRI activity patterns elicited by different item sets and different orderings of those items. These fMRI activity patterns were compared with the predictions made by positional and chaining models of serial order. The positional models encode associations between items and their positions in a sequence, whereas the chaining models encode associations between successive items and retain no position information. We show that a set of brain areas in the postero-dorsal stream of auditory processing store associations between items and order as predicted by a positional model. The chaining model of order representation generates a different pattern similarity prediction, which was shown to be inconsistent with the fMRI data. Our results thus favor a neural model of order representation that stores item codes, position codes, and the mapping between them. This study provides the first fMRI evidence for a specific model of order representation in the human brain. Copyright © 2014 the authors 0270-6474/14/346879-08$15.00/0.

Refining and validating the Social Interaction Anxiety Scale and the Social Phobia Scale.

PubMed

Carleton, R Nicholas; Collimore, Kelsey C; Asmundson, Gordon J G; McCabe, Randi E; Rowa, Karen; Antony, Martin M

2009-01-01

The Social Interaction Anxiety Scale and Social Phobia Scale are companion measures for assessing symptoms of social anxiety and social phobia. The scales have good reliability and validity across several samples, however, exploratory and confirmatory factor analyses have yielded solutions comprising substantially different item content and factor structures. These discrepancies are likely the result of analyzing items from each scale separately or simultaneously. The current investigation sets out to assess items from those scales, both simultaneously and separately, using exploratory and confirmatory factor analyses in an effort to resolve the factor structure. Participants consisted of a clinical sample (n 5353; 54% women) and an undergraduate sample (n 5317; 75% women) who completed the Social Interaction Anxiety Scale and Social Phobia Scale, along with additional fear-related measures to assess convergent and discriminant validity. A three-factor solution with a reduced set of items was found to be most stable, irrespective of whether the items from each scale are assessed together or separately. Items from the Social Interaction Anxiety Scale represented one factor, whereas items from the Social Phobia Scale represented two other factors. Initial support for scale and factor validity, along with implications and recommendations for future research, is provided. (c) 2009 Wiley-Liss, Inc.

The special role of item-context associations in the direct-access region of working memory.

PubMed

Campoy, Guillermo

2017-09-01

The three-embedded-component model of working memory (WM) distinguishes three representational states corresponding to three WM regions: activated long-term memory, direct-access region (DAR), and focus of attention. Recent neuroimaging research has revealed that access to the DAR is associated with enhanced hippocampal activity. Because the hippocampus mediates the encoding and retrieval of item-context associations, it has been suggested that this hippocampal activation is a consequence of the fact that item-context associations are particularly strong and accessible in the DAR. This study provides behavioral evidence for this view using an item-recognition task to assess the effect of non-intentional encoding and maintenance of item-location associations across WM regions. Five pictures of human faces were sequentially presented in different screen locations followed by a recognition probe. Visual cues immediately preceding the probe indicated the location thereof. When probe stimuli appeared in the same location that they had been presented within the memory set, the presentation of the cue was expected to elicit the activation of the corresponding WM representation through the just-established item-location association, resulting in faster recognition. Results showed this same-location effect, but only for items that, according to their serial position within the memory set, were held in the DAR.

Recommended core items to assess e-cigarette use in population-based surveys.

PubMed

Pearson, Jennifer L; Hitchman, Sara C; Brose, Leonie S; Bauld, Linda; Glasser, Allison M; Villanti, Andrea C; McNeill, Ann; Abrams, David B; Cohen, Joanna E

2018-05-01

A consistent approach using standardised items to assess e-cigarette use in both youth and adult populations will aid cross-survey and cross-national comparisons of the effect of e-cigarette (and tobacco) policies and improve our understanding of the population health impact of e-cigarette use. Focusing on adult behaviour, we propose a set of e-cigarette use items, discuss their utility and potential adaptation, and highlight e-cigarette constructs that researchers should avoid without further item development. Reliable and valid items will strengthen the emerging science and inform knowledge synthesis for policy-making. Building on informal discussions at a series of international meetings of 65 experts from 15 countries, the authors provide recommendations for assessing e-cigarette use behaviour, relative perceived harm, device type, presence of nicotine, flavours and reasons for use. We recommend items assessing eight core constructs: e-cigarette ever use, frequency of use and former daily use; relative perceived harm; device type; primary flavour preference; presence of nicotine; and primary reason for use. These items should be standardised or minimally adapted for the policy context and target population. Researchers should be prepared to update items as e-cigarette device characteristics change. A minimum set of e-cigarette items is proposed to encourage consensus around items to allow for cross-survey and cross-jurisdictional comparisons of e-cigarette use behaviour. These proposed items are a starting point. We recognise room for continued improvement, and welcome input from e-cigarette users and scientific colleagues. © 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.

A Core Outcome Set for the Benefits and Adverse Events of Bariatric and Metabolic Surgery: The BARIACT Project.

PubMed

Coulman, Karen D; Hopkins, James; Brookes, Sara T; Chalmers, Katy; Main, Barry; Owen-Smith, Amanda; Andrews, Robert C; Byrne, James; Donovan, Jenny L; Mazza, Graziella; Reeves, Barnaby C; Rogers, Chris A; Thompson, Janice L; Welbourn, Richard; Wordsworth, Sarah; Blazeby, Jane M

2016-11-01

Bariatric and metabolic surgery is used as a treatment for patients with severe and complex obesity. However, there is a need to improve outcome selection and reporting in bariatric surgery trials. A Core Outcome Set (COS), an agreed minimum set of outcomes reported in all studies of a specific condition, may achieve this. Here, we present the development of a COS for BARIAtric and metabolic surgery Clinical Trials-the BARIACT Study. Outcomes identified from systematic reviews and patient interviews informed a questionnaire survey. Patients and health professionals were surveyed three times and asked to rate the importance of each item on a 1-9 scale. Delphi methods provided anonymised feedback to participants. Items not meeting predefined criteria were discarded between rounds. Remaining items were discussed at consensus meetings, held separately with patients and professionals, where the COS was agreed. Data sources identified 2,990 outcomes, which were used to develop a 130-item questionnaire. Round 1 response rates were moderate but subsequently improved to above 75% for other rounds. After rounds 2 and 3, 81 and 14 items were discarded, respectively, leaving 35 items for discussion at consensus meetings. The final COS included nine items: "weight," "diabetes status," "cardiovascular risk," "overall quality of life (QOL)," "mortality," "technical complications of the specific operation," "any re-operation/re-intervention," "dysphagia/regurgitation," and "micronutrient status." The main limitation of this study was that it was based in the United Kingdom only. The COS is recommended to be used as a minimum in all trials of bariatric and metabolic surgery. Adoption of the COS will improve data synthesis and the value of research data. Future work will establish methods for the measurement of the outcomes in the COS.

Mixed methods evaluation of a quality improvement and audit tool for nurse-to-nurse bedside clinical handover in ward settings.

PubMed

Redley, Bernice; Waugh, Rachael

2018-04-01

Nurse bedside handover quality is influenced by complex interactions related to the content, processes used and the work environment. Audit tools are seldom tested in 'real' settings. Examine the reliability, validity and usability of a quality improvement tool for audit of nurse bedside handover. Naturalistic, descriptive, mixed-methods. Six inpatient wards at a single large not-for-profit private health service in Victoria, Australia. Five nurse experts and 104 nurses involved in 199 change-of-shift bedside handovers. A focus group with experts and pilot test were used to examine content and face validity, and usability of the handover audit tool. The tool was examined for inter-rater reliability and usability using observation audits of handovers across six wards. Data were collected in 2013-2014. Two independent observers for 72 audits demonstrated acceptable inter-observer agreement for 27 (77%) items. Reliability was weak for items examining the handover environment. Seventeen items were not observed reflecting gaps in practices. Across 199 observation audits, gaps in nurse bedside handover practice most often related to process and environment, rather than content items. Usability was impacted by high observer burden, familiarity and non-specific illustrative behaviours. The reliability and validity of most items to audit handover content was acceptable. Gaps in practices for process and environment items were identified. Context specific exemplars and reducing the items used at each handover audit can enhance usability. Further research is needed to develop context specific exemplars and undertake additional reliability testing using a wide range of handover settings. CONTRIBUTION OF THE PAPER. Copyright © 2017 Elsevier Inc. All rights reserved.

Earth Observation taken during the Expedition 37 mission

NASA Image and Video Library

2013-10-30

ISS037-E-022990 (30 Oct. 2013) --- This detailed image, photographed by an Expedition 37 crew member on the International Space Station, features the former US Borax mine located to the northwest of Boron, California. The mine, currently owned by the Rio Tinto Group, is the largest open-pit mine in California (covering approximately 54 square kilometers) and is among the largest borate mines in the world. Borates, chemical compounds that include the element boron (B), are important both as providers of an essential plant micronutrient, for metallurgical applications, and as components of specialized types of glass, anticorrosive coatings, fire retardants, and detergents (among other uses). Borate minerals such as borax, kernite, and ulexite are found in deposits at the Rio Tinto borax mine. The geologic setting is a structural, nonmarine basin ? a permanent shallow lake ? fed by thermal springs rich in sodium and boron that existed approximately 16 million years ago, according to scientists. The first mining claim in the area was filed in 1913, following discovery of boron-bearing nodules during well drilling. Much of the mine workings were underground until 1957, when US Borax changed to open-pit mining. The open pit is clearly visible at center; concentric benches along the pit wall are accentuated by shadows and mark successive levels of material extraction. Mine tailings are visible as stacked terraces along the northern boundary of the mine. Ore processing facilities occupy a relatively small percentage of the mine area, and are located directly to the west of the open pit. The Rio Tinto mine is one of the Earth?s richest borate deposits; together with mines in Argentina, they produce almost 40 percent of the world?s supply of industrial borate minerals.