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…

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.

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.

Quantum algorithm for association rules mining

NASA Astrophysics Data System (ADS)

Yu, Chao-Hua; Gao, Fei; Wang, Qing-Le; Wen, Qiao-Yan

2016-10-01

Association rules mining (ARM) is one of the most important problems in knowledge discovery and data mining. Given a transaction database that has a large number of transactions and items, the task of ARM is to acquire consumption habits of customers by discovering the relationships between itemsets (sets of items). In this paper, we address ARM in the quantum settings and propose a quantum algorithm for the key part of ARM, finding frequent itemsets from the candidate itemsets and acquiring their supports. Specifically, for the case in which there are Mf(k ) frequent k -itemsets in the Mc(k ) candidate k -itemsets (Mf(k )≤Mc(k ) ), our algorithm can efficiently mine these frequent k -itemsets and estimate their supports by using parallel amplitude estimation and amplitude amplification with complexity O (k/√{Mc(k )Mf(k ) } ɛ ) , where ɛ is the error for estimating the supports. Compared with the classical counterpart, i.e., the classical sampling-based algorithm, whose complexity is O (k/Mc(k ) ɛ2) , our quantum algorithm quadratically improves the dependence on both ɛ and Mc(k ) in the best case when Mf(k )≪Mc(k ) and on ɛ alone in the worst case when Mf(k )≈Mc(k ) .

Apriori Versions Based on MapReduce for Mining Frequent Patterns on Big Data.

PubMed

Luna, Jose Maria; Padillo, Francisco; Pechenizkiy, Mykola; Ventura, Sebastian

2017-09-27

Pattern mining is one of the most important tasks to extract meaningful and useful information from raw data. This task aims to extract item-sets that represent any type of homogeneity and regularity in data. Although many efficient algorithms have been developed in this regard, the growing interest in data has caused the performance of existing pattern mining techniques to be dropped. The goal of this paper is to propose new efficient pattern mining algorithms to work in big data. To this aim, a series of algorithms based on the MapReduce framework and the Hadoop open-source implementation have been proposed. The proposed algorithms can be divided into three main groups. First, two algorithms [Apriori MapReduce (AprioriMR) and iterative AprioriMR] with no pruning strategy are proposed, which extract any existing item-set in data. Second, two algorithms (space pruning AprioriMR and top AprioriMR) that prune the search space by means of the well-known anti-monotone property are proposed. Finally, a last algorithm (maximal AprioriMR) is also proposed for mining condensed representations of frequent patterns. To test the performance of the proposed algorithms, a varied collection of big data datasets have been considered, comprising up to 3 · 10#x00B9;⁸ transactions and more than 5 million of distinct single-items. The experimental stage includes comparisons against highly efficient and well-known pattern mining algorithms. Results reveal the interest of applying MapReduce versions when complex problems are considered, and also the unsuitability of this paradigm when dealing with small data.

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 ).

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.

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.

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.

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…

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.…

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.

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

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).

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…

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.

Rare itemsets mining algorithm based on RP-Tree and spark framework

NASA Astrophysics Data System (ADS)

Liu, Sainan; Pan, Haoan

2018-05-01

For the issues of the rare itemsets mining in big data, this paper proposed a rare itemsets mining algorithm based on RP-Tree and Spark framework. Firstly, it arranged the data vertically according to the transaction identifier, in order to solve the defects of scan the entire data set, the vertical datasets are divided into frequent vertical datasets and rare vertical datasets. Then, it adopted the RP-Tree algorithm to construct the frequent pattern tree that contains rare items and generate rare 1-itemsets. After that, it calculated the support of the itemsets by scanning the two vertical data sets, finally, it used the iterative process to generate rare itemsets. The experimental show that the algorithm can effectively excavate rare itemsets and have great superiority in execution time.

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…

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…

Discovering Psychological Principles by Mining Naturally Occurring Data Sets.

PubMed

Goldstone, Robert L; Lupyan, Gary

2016-07-01

The very expertise with which psychologists wield their tools for achieving laboratory control may have had the unwelcome effect of blinding psychologists to the possibilities of discovering principles of behavior without conducting experiments. When creatively interrogated, a diverse range of large, real-world data sets provides powerful diagnostic tools for revealing principles of human judgment, perception, categorization, decision-making, language use, inference, problem solving, and representation. Examples of these data sets include patterns of website links, dictionaries, logs of group interactions, collections of images and image tags, text corpora, history of financial transactions, trends in twitter tag usage and propagation, patents, consumer product sales, performance in high-stakes sporting events, dialect maps, and scientific citations. The goal of this issue is to present some exemplary case studies of mining naturally existing data sets to reveal important principles and phenomena in cognitive science, and to discuss some of the underlying issues involved with conducting traditional experiments, analyses of naturally occurring data, computational modeling, and the synthesis of all three methods. Copyright © 2016 Cognitive Science Society, Inc.

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…

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.

Evaluation of Item Candidates: The PROMIS Qualitative Item Review

PubMed Central

DeWalt, Darren A.; Rothrock, Nan; Yount, Susan; Stone, Arthur A.

2009-01-01

One of the PROMIS (Patient-Reported Outcome Measurement Information System) network's primary goals is the development of a comprehensive item bank for patient-reported outcomes of chronic diseases. For its first set of item banks, PROMIS chose to focus on pain, fatigue, emotional distress, physical function, and social function. An essential step for the development of an item pool is the identification, evaluation, and revision of extant questionnaire items for the core item pool. In this work, we also describe the systematic process wherein items are classified for subsequent statistical processing by the PROMIS investigators. Six phases of item development are documented: identification of extant items, item classification and selection, item review and revision, focus group input on domain coverage, cognitive interviews with individual items, and final revision before field testing. Identification of items refers to the systematic search for existing items in currently available scales. Expert item review and revision was conducted by trained professionals who reviewed the wording of each item and revised as appropriate for conventions adopted by the PROMIS network. Focus groups were used to confirm domain definitions and to identify new areas of item development for future PROMIS item banks. Cognitive interviews were used to examine individual items. Items successfully screened through this process were sent to field testing and will be subjected to innovative scale construction procedures. PMID:17443114

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…

Chemical Topic Modeling: Exploring Molecular Data Sets Using a Common Text-Mining Approach.

PubMed

Schneider, Nadine; Fechner, Nikolas; Landrum, Gregory A; Stiefl, Nikolaus

2017-08-28

Big data is one of the key transformative factors which increasingly influences all aspects of modern life. Although this transformation brings vast opportunities it also generates novel challenges, not the least of which is organizing and searching this data deluge. The field of medicinal chemistry is not different: more and more data are being generated, for instance, by technologies such as DNA encoded libraries, peptide libraries, text mining of large literature corpora, and new in silico enumeration methods. Handling those huge sets of molecules effectively is quite challenging and requires compromises that often come at the expense of the interpretability of the results. In order to find an intuitive and meaningful approach to organizing large molecular data sets, we adopted a probabilistic framework called "topic modeling" from the text-mining field. Here we present the first chemistry-related implementation of this method, which allows large molecule sets to be assigned to "chemical topics" and investigating the relationships between those. In this first study, we thoroughly evaluate this novel method in different experiments and discuss both its disadvantages and advantages. We show very promising results in reproducing human-assigned concepts using the approach to identify and retrieve chemical series from sets of molecules. We have also created an intuitive visualization of the chemical topics output by the algorithm. This is a huge benefit compared to other unsupervised machine-learning methods, like clustering, which are commonly used to group sets of molecules. Finally, we applied the new method to the 1.6 million molecules of the ChEMBL22 data set to test its robustness and efficiency. In about 1 h we built a 100-topic model of this large data set in which we could identify interesting topics like "proteins", "DNA", or "steroids". Along with this publication we provide our data sets and an open-source implementation of the new method (CheTo) which

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.

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.

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…

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.

Integrating Entropy and Closed Frequent Pattern Mining for Social Network Modelling and Analysis

NASA Astrophysics Data System (ADS)

Adnan, Muhaimenul; Alhajj, Reda; Rokne, Jon

The recent increase in the explicitly available social networks has attracted the attention of the research community to investigate how it would be possible to benefit from such a powerful model in producing effective solutions for problems in other domains where the social network is implicit; we argue that social networks do exist around us but the key issue is how to realize and analyze them. This chapter presents a novel approach for constructing a social network model by an integrated framework that first preparing the data to be analyzed and then applies entropy and frequent closed patterns mining for network construction. For a given problem, we first prepare the data by identifying items and transactions, which arc the basic ingredients for frequent closed patterns mining. Items arc main objects in the problem and a transaction is a set of items that could exist together at one time (e.g., items purchased in one visit to the supermarket). Transactions could be analyzed to discover frequent closed patterns using any of the well-known techniques. Frequent closed patterns have the advantage that they successfully grab the inherent information content of the dataset and is applicable to a broader set of domains. Entropies of the frequent closed patterns arc used to keep the dimensionality of the feature vectors to a reasonable size; it is a kind of feature reduction process. Finally, we analyze the dynamic behavior of the constructed social network. Experiments were conducted on a synthetic dataset and on the Enron corpus email dataset. The results presented in the chapter show that social networks extracted from a feature set as frequent closed patterns successfully carry the community structure information. Moreover, for the Enron email dataset, we present an analysis to dynamically indicate the deviations from each user's individual and community profile. These indications of deviations can be very useful to identify unusual events.

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.

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…

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…

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

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…

Mining functionally relevant gene sets for analyzing physiologically novel clinical expression data.

PubMed

Turcan, Sevin; Vetter, Douglas E; Maron, Jill L; Wei, Xintao; Slonim, Donna K

2011-01-01

Gene set analyses have become a standard approach for increasing the sensitivity of transcriptomic studies. However, analytical methods incorporating gene sets require the availability of pre-defined gene sets relevant to the underlying physiology being studied. For novel physiological problems, relevant gene sets may be unavailable or existing gene set databases may bias the results towards only the best-studied of the relevant biological processes. We describe a successful attempt to mine novel functional gene sets for translational projects where the underlying physiology is not necessarily well characterized in existing annotation databases. We choose targeted training data from public expression data repositories and define new criteria for selecting biclusters to serve as candidate gene sets. Many of the discovered gene sets show little or no enrichment for informative Gene Ontology terms or other functional annotation. However, we observe that such gene sets show coherent differential expression in new clinical test data sets, even if derived from different species, tissues, and disease states. We demonstrate the efficacy of this method on a human metabolic data set, where we discover novel, uncharacterized gene sets that are diagnostic of diabetes, and on additional data sets related to neuronal processes and human development. Our results suggest that our approach may be an efficient way to generate a collection of gene sets relevant to the analysis of data for novel clinical applications where existing functional annotation is relatively incomplete.

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.

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

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…

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.

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.

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…

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.

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…

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…

Evaluation of a four-item DSM-5 Limited Prosocial Emotions specifier scale within and across settings with Spanish children.

PubMed

Seijas, Raquel; Servera, Mateu; García-Banda, Gloria; Barry, Christopher T; Burns, G Leonard

2018-04-01

The objective was to evaluate a 4-item measure of the DSM-5 Limited Prosocial Emotions (LPE) specifier (a 4-item measure of prosocial emotions). Mothers, fathers, primary teachers, and ancillary teachers completed measures of prosocial emotions (PE), oppositional defiant disorder (ODD), attention-deficit/hyperactivity disorder (ADHD)-inattention (IN), ADHD-hyperactivity/impulsivity (HI), academic and social impairment on 811 Spanish first-grade children (46% girls). Confirmatory factor and structural regression analyses showed PE symptom scores to have (a) good reliability for the 4 sources (80% to 89% true score variance), (b) invariance of like-symptom loadings and intercepts across the 4 sources, (c) strong convergent and discriminant validity within home and school settings, (d) no convergent validity across settings, and (e) associations with academic and social impairment independent of the ODD dimension (the unique effects of PE also remained significant after controlling for ODD, ADHD-IN, and ADHD-HI for mothers and ancillary teachers). A graded response item response theory analysis indicated that PE scores provided an accurate measure of the PE trait across a wide trait range and especially at low PE trait levels (i.e., scores in the clinical range). Findings also supported the DSM-5 diagnostic criteria of 2 or more LPE symptoms in 2 or more settings (e.g., high levels of the LPE trait were associated with the occurrence of 2 or more symptoms with 4% of the sample showing 2 or more symptoms in both settings). Although additional studies are still required, the PE measure appears useful as a brief measure of the LPE specifier. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

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

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.

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…

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

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…

Can a Simple Dietary Index Derived from a Sub-Set of Questionnaire Items Assess Diet Quality in a Sample of Australian Adults?

PubMed Central

Trapp, Georgina S. A.; Knuiman, Matthew; Hooper, Paula; Ambrosini, Gina L.

2018-01-01

Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004–2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point (n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman’s rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen’s weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality. PMID:29652828

Can a Simple Dietary Index Derived from a Sub-Set of Questionnaire Items Assess Diet Quality in a Sample of Australian Adults?

PubMed

Bivoltsis, Alexia; Trapp, Georgina S A; Knuiman, Matthew; Hooper, Paula; Ambrosini, Gina L

2018-04-13

Large, longitudinal surveys often lack consistent dietary data, limiting the use of existing tools and methods that are available to measure diet quality. This study describes a method that was used to develop a simple index for ranking individuals according to their diet quality in a longitudinal study. The RESIDential Environments (RESIDE) project (2004-2011) collected dietary data in varying detail, across four time points. The most detailed dietary data were collected using a 24-item questionnaire at the final time point ( n = 555; age ≥ 25 years). At preceding time points, sub-sets of the 24 items were collected. A RESIDE dietary guideline index (RDGI) that was based on the 24-items was developed to assess diet quality in relation to the Australian Dietary Guidelines. The RDGI scores were regressed on the longitudinal sub-sets of six and nine questionnaire items at T4, from which two simple index scores (S-RDGI1 and S-RDGI2) were predicted. The S-RDGI1 and S-RDGI2 showed reasonable agreement with the RDGI (Spearman's rho = 0.78 and 0.84; gross misclassification = 1.8%; correct classification = 64.9% and 69.7%; and, Cohen's weighted kappa = 0.58 and 0.64, respectively). For all of the indices, higher diet quality was associated with being female, undertaking moderate to high amounts of physical activity, not smoking, and self-reported health. The S-RDGI1 and S-RDGI2 explained 62% and 73% of the variation in RDGI scores, demonstrating that a large proportion of the variability in diet quality scores can be captured using a relatively small sub-set of questionnaire items. The methods described in this study can be applied elsewhere, in situations where limited dietary data are available, to generate a sample-specific score for ranking individuals according to diet quality.

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…

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

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

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.

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.

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…

Higher-Order Asymptotics and Its Application to Testing the Equality of the Examinee Ability Over Two Sets of Items.

PubMed

Sinharay, Sandip; Jensen, Jens Ledet

2018-06-27

In educational and psychological measurement, researchers and/or practitioners are often interested in examining whether the ability of an examinee is the same over two sets of items. Such problems can arise in measurement of change, detection of cheating on unproctored tests, erasure analysis, detection of item preknowledge, etc. Traditional frequentist approaches that are used in such problems include the Wald test, the likelihood ratio test, and the score test (e.g., Fischer, Appl Psychol Meas 27:3-26, 2003; Finkelman, Weiss, & Kim-Kang, Appl Psychol Meas 34:238-254, 2010; Glas & Dagohoy, Psychometrika 72:159-180, 2007; Guo & Drasgow, Int J Sel Assess 18:351-364, 2010; Klauer & Rettig, Br J Math Stat Psychol 43:193-206, 1990; Sinharay, J Educ Behav Stat 42:46-68, 2017). This paper shows that approaches based on higher-order asymptotics (e.g., Barndorff-Nielsen & Cox, Inference and asymptotics. Springer, London, 1994; Ghosh, Higher order asymptotics. Institute of Mathematical Statistics, Hayward, 1994) can also be used to test for the equality of the examinee ability over two sets of items. The modified signed likelihood ratio test (e.g., Barndorff-Nielsen, Biometrika 73:307-322, 1986) and the Lugannani-Rice approximation (Lugannani & Rice, Adv Appl Prob 12:475-490, 1980), both of which are based on higher-order asymptotics, are shown to provide some improvement over the traditional frequentist approaches in three simulations. Two real data examples are also provided.

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.

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…

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…

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…

A 67-Item Stress Resilience item bank showing high content validity was developed in a psychosomatic sample.

PubMed

Obbarius, Nina; Fischer, Felix; Obbarius, Alexander; Nolte, Sandra; Liegl, Gregor; Rose, Matthias

2018-04-10

To develop the first item bank to measure Stress Resilience (SR) in clinical populations. Qualitative item development resulted in an initial pool of 131 items covering a broad theoretical SR concept. These items were tested in n=521 patients at a psychosomatic outpatient clinic. Exploratory and Confirmatory Factor Analysis (CFA), as well as other state-of-the-art item analyses and IRT were used for item evaluation and calibration of the final item bank. Out of the initial item pool of 131 items, we excluded 64 items (54 factor loading <.5, 4 residual correlations >.3, 2 non-discriminative Item Response Curves, 4 Differential Item Functioning). The final set of 67 items indicated sufficient model fit in CFA and IRT analyses. Additionally, a 10-item short form with high measurement precision (SE≤.32 in a theta range between -1.8 and +1.5) was derived. Both the SR item bank and the SR short form were highly correlated with an existing static legacy tool (Connor-Davidson Resilience Scale). The final SR item bank and 10-item short form showed good psychometric properties. When further validated, they will be ready to be used within a framework of Computer-Adaptive Tests for a comprehensive assessment of the Stress-Construct. Copyright © 2018. Published by Elsevier Inc.

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

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…

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.

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

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.

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.

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.

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

NASA Astrophysics Data System (ADS)

Cheung, David J.

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.

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.

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…

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

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

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…

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.

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.

The Communicative Participation Item Bank (CPIB): Item bank calibration and development of a disorder-generic short form

PubMed Central

Baylor, Carolyn; Yorkston, Kathryn; Eadie, Tanya; Kim, Jiseon; Chung, Hyewon; Amtmann, Dagmar

2015-01-01

Purpose The purpose of this study was to calibrate the items for the Communicative Participation Item Bank (CPIB) using Item Response Theory (IRT). One overriding objective was to examine if the IRT item parameters would be consistent across different diagnostic groups, thereby allowing creation of a disorder-generic instrument. The intended outcomes were the final item bank and a short form ready for clinical and research applications. Methods Self-report data were collected from 701 individuals representing four diagnoses: multiple sclerosis, Parkinson’s disease, amyotrophic lateral sclerosis and head and neck cancer. Participants completed the CPIB and additional self-report questionnaires. CPIB data were analyzed using the IRT Graded Response Model (GRM). Results The initial set of 94 candidate CPIB items were reduced to an item bank of 46 items demonstrating unidimensionality, local independence, good item fit, and good measurement precision. Differential item function (DIF) analyses detected no meaningful differences across diagnostic groups. A 10-item, disorder-generic short form was generated. Conclusions The CPIB provides speech-language pathologists with a unidimensional, self-report outcomes measurement instrument dedicated to the construct of communicative participation. This instrument may be useful to clinicians and researchers wanting to implement measures of communicative participation in their work. PMID:23816661

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.

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…

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.

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

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.

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.

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.…

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.

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.

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

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…

DEVELOPING AND EXPLOITING A UNIQUE SEISMIC DATA SET FROM SOUTH AFRICAN GOLD MINES FOR SOURCE CHARACTERIZATION AND WAVE PROPAGATION

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

Julia, J; Nyblade, A A; Gok, R

2008-07-08

In this project, we are developing and exploiting a unique seismic data set to address the characteristics of small seismic events and the associated seismic signals observed at local (< 200 km) and regional (< 2000 km) distances. The dataset is being developed using mining-induced events from 3 deep gold mines in South Africa recorded on inmine networks (< 1 km) comprised of tens of high-frequency sensors, a network of 4 broadband stations installed as part of this project at the surface around the mines (1-10 km), and a network of existing broadband seismic stations at local/regional distances (50-1000 km)more » from the mines. After 1 year of seismic monitoring of mine activity (2007), over 10,000 events in the range -3.4 < ML < 4.4 have been catalogued and recorded by the in-mine networks. Events with positive magnitudes are generally well recorded by the surface-mine stations, while magnitudes 3.0 and larger are seen at regional distances (up to {approx}600 km) in high-pass filtered recordings. We have analyzed in-mine recordings in detail at one of the South African mines (Savuka) to (i) improve on reported hypocentral locations, (ii) verify sensor orientations, and (iii) determine full moment tensor solutions. Hypocentral relocations on all catalogued events have been obtained from P- and S-wave travel-times reported by the mine network operator through an automated procedure that selects travel-times falling on Wadati lines with slopes in the 0.6-0.7 range; sensor orientations have been verified and, when possible, corrected by correlating P-, SV-, and SH-waveforms obtained from theoretical and empirical (polarization filter) rotation angles; full moment tensor solutions have been obtained by inverting P-, SV-, and SH- spectral amplitudes measured on the theoretically rotated waveforms with visually assigned polarities. The relocation procedure has revealed that origin times often necessitate a negative correction of a few tenths of second and that

Detection performance assessment of hand-held mine detection systems in a procurement process: test set-up for MDs and MD/GPRs

NASA Astrophysics Data System (ADS)

Schoolderman, Arnold J.; Roosenboom, Jacques H. J.

2005-06-01

The Engineers Centre of Expertise of the Royal Netherlands Army (RNLA) has conducted a study on countermine in peace operations. This study, finished in 2002, concluded that the final solution to countermine will depend in the first place on better detection of buried low-metal mines, e.g. by direct detection of the explosive components in mines. Until such detection systems are available, intermediate solutions are necessary in order to assure freedom of movement in peace operations. Because countermine operations consist of a number of different activities (area preparation, detection, clearance, etc) and the suitability of the different types of available equipment depends on the scenario, the toolbox concept for countermine equipment was adopted. In 2003 a procurement process was started in order to fill this toolbox with commercial-off-the-shelf and military-off-the-shelf equipment. The paper gives a concise description of the study on countermine operations and the procurement process, and subsequently focuses on the set-up of the tests that were conducted in the framework of the procurement of hand-held mine detection systems, like metal detectors and dual-sensor mine detectors. Programs of requirements for these systems were drawn up, aiming at systems for general use and special purpose systems. Blind tests to check the compliancy to the detection performance requirements were designed and conducted in the short timeframe that was available in the procurement process. These tests are discussed in this paper, including the set-up of the test lanes, the targets used and their depths, and the role of the operator. The tests of the capability of the detectors to discriminate small targets adjacent to large targets were conducted according the guidelines of the CEN Workshop Agreement on metal detector tests. Although the results of the tests are commercially confidential, conclusions and lessons learned from the execution of these tests are presented.

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).

Item-focussed Trees for the Identification of Items in Differential Item Functioning.

PubMed

Tutz, Gerhard; Berger, Moritz

2016-09-01

A novel method for the identification of differential item functioning (DIF) by means of recursive partitioning techniques is proposed. We assume an extension of the Rasch model that allows for DIF being induced by an arbitrary number of covariates for each item. Recursive partitioning on the item level results in one tree for each item and leads to simultaneous selection of items and variables that induce DIF. For each item, it is possible to detect groups of subjects with different item difficulties, defined by combinations of characteristics that are not pre-specified. The way a DIF item is determined by covariates is visualized in a small tree and therefore easily accessible. An algorithm is proposed that is based on permutation tests. Various simulation studies, including the comparison with traditional approaches to identify items with DIF, show the applicability and the competitive performance of the method. Two applications illustrate the usefulness and the advantages of the new method.

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,…

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.

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…

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

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.

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

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…

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)

Item Writer Judgments of Item Difficulty versus Actual Item Difficulty: A Case Study

ERIC Educational Resources Information Center

Sydorenko, Tetyana

2011-01-01

This study investigates how accurate one item writer can be on item difficulty estimates and whether factors affecting item writer judgments correspond to predictors of actual item difficulty. The items were based on conversational dialogs (presented as videos online) that focus on pragmatic functions. Thirty-five 2nd-, 3rd-, and 4th-year learners…

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.

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.

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.

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.

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

Methods for Linking Item Parameters.

DTIC Science & Technology

1981-08-01

within and across data sets; all proportion-correct distributions were quite platykurtic . Biserial item-total correlations had relatively consistent...would produce a distribution of a parameters which had a larger mean and standard deviation, was more positively skewed, and was somewhat more platykurtic

An Item Gains and Losses Analysis of False Memories Suggests Critical Items Receive More Item-Specific Processing than List Items

ERIC Educational Resources Information Center

Burns, Daniel J.; Martens, Nicholas J.; Bertoni, Alicia A.; Sweeney, Emily J.; Lividini, Michelle D.

2006-01-01

In a repeated testing paradigm, list items receiving item-specific processing are more likely to be recovered across successive tests (item gains), whereas items receiving relational processing are likely to be forgotten progressively less on successive tests. Moreover, analysis of cumulative-recall curves has shown that item-specific processing…

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…

Does remembering emotional items impair recall of same-emotion items?

PubMed

Sison, Jo Ann G; Mather, Mara

2007-04-01

In the part-set cuing effect, cuing a subset of previously studied items impairs recall of the remaining noncued items. This experiment reveals that cuing participants with previously-studied emotional pictures (e.g., fear-evoking pictures of people) can impair recall of pictures involving the same emotion but different content (e.g., fear-evoking pictures of animals). This indicates that new events can be organized in memory using emotion as a grouping function to create associations. However, whether new information is organized in memory along emotional or nonemotional lines appears to be a flexible process that depends on people's current focus. Mentioning in the instructions that the pictures were either amusement- or fear-related led to memory impairment for pictures with the same emotion as cued pictures, whereas mentioning that the pictures depicted either animals or people led to memory impairment for pictures with the same type of actor.

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...

Item Difficulty Modeling of Paragraph Comprehension Items

ERIC Educational Resources Information Center

Gorin, Joanna S.; Embretson, Susan E.

2006-01-01

Recent assessment research joining cognitive psychology and psychometric theory has introduced a new technology, item generation. In algorithmic item generation, items are systematically created based on specific combinations of features that underlie the processing required to correctly solve a problem. Reading comprehension items have been more…

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.

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.

Item validity vs. item discrimination index: a redundancy?

NASA Astrophysics Data System (ADS)

Panjaitan, R. L.; Irawati, R.; Sujana, A.; Hanifah, N.; Djuanda, D.

2018-03-01

In several literatures about evaluation and test analysis, it is common to find that there are calculations of item validity as well as item discrimination index (D) with different formula for each. Meanwhile, other resources said that item discrimination index could be obtained by calculating the correlation between the testee’s score in a particular item and the testee’s score on the overall test, which is actually the same concept as item validity. Some research reports, especially undergraduate theses tend to include both item validity and item discrimination index in the instrument analysis. It seems that these concepts might overlap for both reflect the test quality on measuring the examinees’ ability. In this paper, examples of some results of data processing on item validity and item discrimination index were compared. It would be discussed whether item validity and item discrimination index can be represented by one of them only or it should be better to present both calculations for simple test analysis, especially in undergraduate theses where test analyses were included.

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.

Item response theory - A first approach

NASA Astrophysics Data System (ADS)

Nunes, Sandra; Oliveira, Teresa; Oliveira, Amílcar

2017-07-01

The Item Response Theory (IRT) has become one of the most popular scoring frameworks for measurement data, frequently used in computerized adaptive testing, cognitively diagnostic assessment and test equating. According to Andrade et al. (2000), IRT can be defined as a set of mathematical models (Item Response Models - IRM) constructed to represent the probability of an individual giving the right answer to an item of a particular test. The number of Item Responsible Models available to measurement analysis has increased considerably in the last fifteen years due to increasing computer power and due to a demand for accuracy and more meaningful inferences grounded in complex data. The developments in modeling with Item Response Theory were related with developments in estimation theory, most remarkably Bayesian estimation with Markov chain Monte Carlo algorithms (Patz & Junker, 1999). The popularity of Item Response Theory has also implied numerous overviews in books and journals, and many connections between IRT and other statistical estimation procedures, such as factor analysis and structural equation modeling, have been made repeatedly (Van der Lindem & Hambleton, 1997). As stated before the Item Response Theory covers a variety of measurement models, ranging from basic one-dimensional models for dichotomously and polytomously scored items and their multidimensional analogues to models that incorporate information about cognitive sub-processes which influence the overall item response process. The aim of this work is to introduce the main concepts associated with one-dimensional models of Item Response Theory, to specify the logistic models with one, two and three parameters, to discuss some properties of these models and to present the main estimation procedures.

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.

Item Structural Properties as Predictors of Item Difficulty and Item Association.

ERIC Educational Resources Information Center

Solano-Flores, Guillermo

1993-01-01

Studied the ability of logical test design (LTD) to predict student performance in reading Roman numerals for 211 sixth graders in Mexico City tested on Roman numeral items varying on LTD-related and non-LTD-related variables. The LTD-related variable item iterativity was found to be the best predictor of item difficulty. (SLD)

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…

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.

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)

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.

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.

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…

TREatment of ATopic eczema (TREAT) Registry Taskforce: protocol for an international Delphi exercise to identify a core set of domains and domain items for national atopic eczema registries.

PubMed

Gerbens, Louise A A; Boyce, Aaron E; Wall, Dmitri; Barbarot, Sebastien; de Booij, Richard J; Deleuran, Mette; Middelkamp-Hup, Maritza A; Roberts, Amanda; Vestergaard, Christian; Weidinger, Stephan; Apfelbacher, Christian J; Irvine, Alan D; Schmitt, Jochen; Williamson, Paula R; Spuls, Phyllis I; Flohr, Carsten

2017-02-27

Patients with moderate-to-severe atopic eczema (AE) often require photo- or systemic immunomodulatory therapies to induce disease remission and maintain long-term control. The current evidence to guide clinical management is small, despite the frequent and often off-label use of these treatments. Registries of patients on photo- and systemic immunomodulatory therapies could fill this gap, and the collection of a core set concerning these therapies in AE will allow direct comparisons across registries as well as data sharing and pooling. Using an eDelphi approach, the international TREatment of ATopic eczema (TREAT) Registry Taskforce aims to seek consensus between key stakeholders internationally on a core set of domains and domain items for AE patient registries with a research focus that collect data of children and adults on photo- and systemic immunomodulatory therapies. Participants from six stakeholder groups will be invited: doctors, nurses, non-clinical researchers, patients, as well as industry and regulatory body representatives. The eDelphi will comprise three sequential online rounds, requesting participants to rate the importance of each proposed domain and domain items. Participants will be able to add domains and domain items to the proposed list in round 1. A final consensus meeting will be held with representatives of each stakeholder group. Identifying a uniform core set of domains and domain items to be captured by AE patient registries will increase the utility of individual registries, and provide greater insight into the effectiveness, safety and cost-effectiveness of photo- and systemic immunomodulatory therapies to guide clinical management across dermatology centres and country borders. Not applicable. This eDelphi study was registered in the Core Outcome Measures for Effectiveness Trials (COMET) database.

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.

Extending item response theory to online homework

NASA Astrophysics Data System (ADS)

Kortemeyer, Gerd

2014-06-01

Item response theory (IRT) becomes an increasingly important tool when analyzing "big data" gathered from online educational venues. However, the mechanism was originally developed in traditional exam settings, and several of its assumptions are infringed upon when deployed in the online realm. For a large-enrollment physics course for scientists and engineers, the study compares outcomes from IRT analyses of exam and homework data, and then proceeds to investigate the effects of each confounding factor introduced in the online realm. It is found that IRT yields the correct trends for learner ability and meaningful item parameters, yet overall agreement with exam data is moderate. It is also found that learner ability and item discrimination is robust over a wide range with respect to model assumptions and introduced noise. Item difficulty is also robust, but over a narrower range.

A note on monotonicity of item response functions for ordered polytomous item response theory models.

PubMed

Kang, Hyeon-Ah; Su, Ya-Hui; Chang, Hua-Hua

2018-03-08

A monotone relationship between a true score (τ) and a latent trait level (θ) has been a key assumption for many psychometric applications. The monotonicity property in dichotomous response models is evident as a result of a transformation via a test characteristic curve. Monotonicity in polytomous models, in contrast, is not immediately obvious because item response functions are determined by a set of response category curves, which are conceivably non-monotonic in θ. The purpose of the present note is to demonstrate strict monotonicity in ordered polytomous item response models. Five models that are widely used in operational assessments are considered for proof: the generalized partial credit model (Muraki, 1992, Applied Psychological Measurement, 16, 159), the nominal model (Bock, 1972, Psychometrika, 37, 29), the partial credit model (Masters, 1982, Psychometrika, 47, 147), the rating scale model (Andrich, 1978, Psychometrika, 43, 561), and the graded response model (Samejima, 1972, A general model for free-response data (Psychometric Monograph no. 18). Psychometric Society, Richmond). The study asserts that the item response functions in these models strictly increase in θ and thus there exists strict monotonicity between τ and θ under certain specified conditions. This conclusion validates the practice of customarily using τ in place of θ in applied settings and provides theoretical grounds for one-to-one transformations between the two scales. © 2018 The British Psychological Society.

Generating constrained randomized sequences: item frequency matters.

PubMed

French, Robert M; Perruchet, Pierre

2009-11-01

All experimental psychologists understand the importance of randomizing lists of items. However, randomization is generally constrained, and these constraints-in particular, not allowing immediately repeated items-which are designed to eliminate particular biases, frequently engender others. We describe a simple Monte Carlo randomization technique that solves a number of these problems. However, in many experimental settings, we are concerned not only with the number and distribution of items but also with the number and distribution of transitions between items. The algorithm mentioned above provides no control over this. We therefore introduce a simple technique that uses transition tables for generating correctly randomized sequences. We present an analytic method of producing item-pair frequency tables and item-pair transitional probability tables when immediate repetitions are not allowed. We illustrate these difficulties and how to overcome them, with reference to a classic article on word segmentation in infants. Finally, we provide free access to an Excel file that allows users to generate transition tables with up to 10 different item types, as well as to generate appropriately distributed randomized sequences of any length without immediately repeated elements. This file is freely available from http://leadserv.u-bourgogne.fr/IMG/xls/TransitionMatrix.xls.

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...

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.

Non-ignorable missingness item response theory models for choice effects in examinee-selected items.

PubMed

Liu, Chen-Wei; Wang, Wen-Chung

2017-11-01

Examinee-selected item (ESI) design, in which examinees are required to respond to a fixed number of items in a given set, always yields incomplete data (i.e., when only the selected items are answered, data are missing for the others) that are likely non-ignorable in likelihood inference. Standard item response theory (IRT) models become infeasible when ESI data are missing not at random (MNAR). To solve this problem, the authors propose a two-dimensional IRT model that posits one unidimensional IRT model for observed data and another for nominal selection patterns. The two latent variables are assumed to follow a bivariate normal distribution. In this study, the mirt freeware package was adopted to estimate parameters. The authors conduct an experiment to demonstrate that ESI data are often non-ignorable and to determine how to apply the new model to the data collected. Two follow-up simulation studies are conducted to assess the parameter recovery of the new model and the consequences for parameter estimation of ignoring MNAR data. The results of the two simulation studies indicate good parameter recovery of the new model and poor parameter recovery when non-ignorable missing data were mistakenly treated as ignorable. © 2017 The British Psychological Society.

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…

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...

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

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.

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…

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.

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

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.

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

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.

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...

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…

Three controversies over item disclosure in medical licensure examinations

PubMed Central

Park, Yoon Soo; Yang, Eunbae B.

2015-01-01

In response to views on public's right to know, there is growing attention to item disclosure – release of items, answer keys, and performance data to the public – in medical licensure examinations and their potential impact on the test's ability to measure competence and select qualified candidates. Recent debates on this issue have sparked legislative action internationally, including South Korea, with prior discussions among North American countries dating over three decades. The purpose of this study is to identify and analyze three issues associated with item disclosure in medical licensure examinations – 1) fairness and validity, 2) impact on passing levels, and 3) utility of item disclosure – by synthesizing existing literature in relation to standards in testing. Historically, the controversy over item disclosure has centered on fairness and validity. Proponents of item disclosure stress test takers’ right to know, while opponents argue from a validity perspective. Item disclosure may bias item characteristics, such as difficulty and discrimination, and has consequences on setting passing levels. To date, there has been limited research on the utility of item disclosure for large scale testing. These issues requires ongoing and careful consideration. PMID:26374693

Three controversies over item disclosure in medical licensure examinations.

PubMed

Park, Yoon Soo; Yang, Eunbae B

2015-01-01

In response to views on public's right to know, there is growing attention to item disclosure - release of items, answer keys, and performance data to the public - in medical licensure examinations and their potential impact on the test's ability to measure competence and select qualified candidates. Recent debates on this issue have sparked legislative action internationally, including South Korea, with prior discussions among North American countries dating over three decades. The purpose of this study is to identify and analyze three issues associated with item disclosure in medical licensure examinations - 1) fairness and validity, 2) impact on passing levels, and 3) utility of item disclosure - by synthesizing existing literature in relation to standards in testing. Historically, the controversy over item disclosure has centered on fairness and validity. Proponents of item disclosure stress test takers' right to know, while opponents argue from a validity perspective. Item disclosure may bias item characteristics, such as difficulty and discrimination, and has consequences on setting passing levels. To date, there has been limited research on the utility of item disclosure for large scale testing. These issues requires ongoing and careful consideration.

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.

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 Temple University 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.

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

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.…

The 11-item Medication Adherence Reasons Scale: reliability and factorial validity among patients with hypertension in Malaysian primary healthcare settings.

PubMed

Shima, Razatul; Farizah, Hairi; Majid, Hazreen Abdul

2015-08-01

The aim of this study was to assess the reliability and validity of a modified Malaysian version of the Medication Adherence Reasons Scale (MAR-Scale). In this cross-sectional study, the 15-item MAR-Scale was administered to 665 patients with hypertension who attended one of the four government primary healthcare clinics in the Hulu Langat and Klang districts of Selangor, Malaysia, between early December 2012 and end-March 2013. The construct validity was examined in two phases. Phase I consisted of translation of the MAR-Scale from English to Malay, a content validity check by an expert panel, a face validity check via a small preliminary test among patients with hypertension, and exploratory factor analysis (EFA). Phase II involved internal consistency reliability calculations and confirmatory factor analysis (CFA). EFA verified five existing factors that were previously identified (i.e. issues with medication management, multiple medications, belief in medication, medication availability, and the patient's forgetfulness and convenience), while CFA extracted four factors (medication availability issues were not extracted). The final modified MAR-Scale model, which had 11 items and a four-factor structure, provided good evidence of convergent and discriminant validities. Cronbach's alpha coefficient was > 0.7, indicating good internal consistency of the items in the construct. The results suggest that the modified MAR-Scale has good internal consistencies and construct validity. The validated modified MAR-Scale (Malaysian version) was found to be suitable for use among patients with hypertension receiving treatment in primary healthcare settings. However, the comprehensive measurement of other factors that can also lead to non-adherence requires further exploration.

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

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…

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…

Cueing cognitive flexibility: Item-specific learning of switch readiness.

PubMed

Chiu, Yu-Chin; Egner, Tobias

2017-12-01

The rich behavioral repertoire of the human species derives from our ability to flexibly reconfigure processing strategies (task sets) in response to changing requirements. This updating of task sets is effortful, as reflected by longer response times when switching a task than repeating it (switch costs). However, some recent data suggest that switch costs can be reduced by cueing switch readiness bottom-up, by associating particular stimuli with frequent switch requirements. This type of "stimulus-control (S-C) learning" would be highly adaptive, as it combines the speed of automatic (bottom-up) processing with the flexibility and generalizability of controlled (top-down) processing. However, it is unclear whether S-C learning of switch readiness is truly possible, and what the underlying mechanisms are. Here we address these questions by pairing specific stimuli with a need to update task-sets either frequently or rarely. In all 3 experiments, we observe robust item-specific switch probability (ISSP) effects as revealed by smaller switch costs for frequent switch items than for rare switch items. By including a neutral condition, we also show that the ISSP effect is primarily driven by S-C learning reducing switch costs in frequent switch items. Furthermore, by employing 3 tasks in Experiment 3, we establish that the ISSP effect reflects an enhancement of general switch readiness, rather than of the readiness to switch to a specific alternate task. These results firmly establish that switch readiness is malleable by item-specific S-C learning processes, documenting that a generalizable state of cognitive flexibility can be primed by a bottom-up stimulus. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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.

Examining Differential Item Functions of Different Item Ordered Test Forms According to Item Difficulty Levels

ERIC Educational Resources Information Center

Çokluk, Ömay; Gül, Emrah; Dogan-Gül, Çilem

2016-01-01

The study aims to examine whether differential item function is displayed in three different test forms that have item orders of random and sequential versions (easy-to-hard and hard-to-easy), based on Classical Test Theory (CTT) and Item Response Theory (IRT) methods and bearing item difficulty levels in mind. In the correlational research, the…

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.

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.

The Role of Item Models in Automatic Item Generation

ERIC Educational Resources Information Center

Gierl, Mark J.; Lai, Hollis

2012-01-01

Automatic item generation represents a relatively new but rapidly evolving research area where cognitive and psychometric theories are used to produce tests that include items generated using computer technology. Automatic item generation requires two steps. First, test development specialists create item models, which are comparable to templates…

Radioecological impacts of tin mining.

PubMed

Aliyu, Abubakar Sadiq; Mousseau, Timothy Alexander; Ramli, Ahmad Termizi; Bununu, Yakubu Aliyu

2015-12-01

The tin mining activities in the suburbs of Jos, Plateau State, Nigeria, have resulted in technical enhancement of the natural background radiation as well as higher activity concentrations of primordial radionuclides in the topsoil of mining sites and their environs. Several studies have considered the radiological human health risks of the mining activity; however, to our knowledge no documented study has investigated the radiological impacts on biota. Hence, an attempt is made to assess potential hazards using published data from the literature and the ERICA Tool. This paper considers the effects of mining and milling on terrestrial organisms like shrubs, large mammals, small burrowing mammals, birds (duck), arthropods (earth worm), grasses, and herbs. The dose rates and risk quotients to these organisms are computed using conservative values for activity concentrations of natural radionuclides reported in Bitsichi and Bukuru mining areas. The results suggest that grasses, herbs, lichens, bryophytes and shrubs receive total dose rates that are of potential concern. The effects of dose rates to specific indicator species of interest are highlighted and discussed. We conclude that further investigation and proper regulations should be set in place in order to reduce the risk posed by the tin mining activity on biota. This paper also presents a brief overview of the impact of mineral mining on biota based on documented literature for other countries.

Item response theory detects differential item functioning between healthy and ill children in QoL measures

PubMed Central

Langer, Michelle M.; Hill, Cheryl D.; Thissen, David; Burwinkle, Tasha M.; Varni, James W.; DeWalt, Darren A.

2008-01-01

Objective To demonstrate the value of item response theory (IRT) and differential item functioning (DIF) methods in examining a health-related quality of life (HRQOL) measure in children and adolescents. Study Design and Setting This illustration uses data from 5,429 children using the four subscales of the PedsQL™ 4.0 Generic Core Scales. The IRT model-based likelihood ratio test was used to detect and evaluate DIF between healthy children and children with a chronic condition. Results DIF was detected for a majority of items but cancelled out at the total test score level due to opposing directions of DIF. Post-hoc analysis indicated that this pattern of results may be due to multidimensionality. We discuss issues in detecting and handling DIF. Conclusion This paper describes how to perform DIF analyses in validating a questionnaire to ensure that scores have equivalent meaning across subgroups. It offers insight into ways information gained through the analysis can be used to evaluate an existing scale. PMID:18226750

Assessing item fit for unidimensional item response theory models using residuals from estimated item response functions.

PubMed

Haberman, Shelby J; Sinharay, Sandip; Chon, Kyong Hee

2013-07-01

Residual analysis (e.g. Hambleton & Swaminathan, Item response theory: principles and applications, Kluwer Academic, Boston, 1985; Hambleton, Swaminathan, & Rogers, Fundamentals of item response theory, Sage, Newbury Park, 1991) is a popular method to assess fit of item response theory (IRT) models. We suggest a form of residual analysis that may be applied to assess item fit for unidimensional IRT models. The residual analysis consists of a comparison of the maximum-likelihood estimate of the item characteristic curve with an alternative ratio estimate of the item characteristic curve. The large sample distribution of the residual is proved to be standardized normal when the IRT model fits the data. We compare the performance of our suggested residual to the standardized residual of Hambleton et al. (Fundamentals of item response theory, Sage, Newbury Park, 1991) in a detailed simulation study. We then calculate our suggested residuals using data from an operational test. The residuals appear to be useful in assessing the item fit for unidimensional IRT models.

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.

Item Information and Discrimination Functions for Trinary PCM Items.

ERIC Educational Resources Information Center

Akkermans, Wies; Muraki, Eiji

1997-01-01

For trinary partial credit items, the shape of the item information and item discrimination functions is examined in relation to the item parameters. Conditions under which these functions are unimodal and bimodal are discussed, and the locations and values of maxima are derived. Practical relevance of the results is discussed. (SLD)

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 University of Minnesota-Twin Cities 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.

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 Montana Tech of the University of Montana 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.

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 Illinois Institute of 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.

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 University of North Carolina at Charlotte 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.

Conjunctive and Disjunctive Item Response Functions.

DTIC Science & Technology

1984-10-01

fed set ofvaluesof a, b, AI , B1 A2 2 . 2 A3 , and 13 , the f ’. g ’a. nd h’a in (7) are fied. Equation (7) must still hold for S - e19029e3,..* . Thus...for Item I Is -- b ?(a:1 , b1 ,O) (1 + ’)(I + e4 (22 where a and pi are arbitrary constants. These constants mst be the sam for all Items In a given...NETHERLIS I E3I1 Focility-Acquisitions 4133 Rugby Avnue 1 Lee Cronbach Bethesda, NO 20014 16 Laburnue Road Atherton, CA 94205 1 Dr. Benjamin A. Fairbank

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

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…

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…

Effects of Ignoring Item Interaction on Item Parameter Estimation and Detection of Interacting Items

ERIC Educational Resources Information Center

Chen, Cheng-Te; Wang, Wen-Chung

2007-01-01

This study explores the effects of ignoring item interaction on item parameter estimation and the efficiency of using the local dependence index Q[subscript 3] and the SAS NLMIXED procedure to detect item interaction under the three-parameter logistic model and the generalized partial credit model. Through simulations, it was found that ignoring…

Goal setting, using goal attainment scaling, as a method to identify patient selected items for measuring arm function.

PubMed

Ashford, Stephen; Jackson, Diana; Turner-Stokes, Lynne

2015-03-01

Following stroke or brain injury, goals for rehabilitation of the hemiparetic upper limb include restoring active function if there is return of motor control or, if none is possible, improving passive function, and facilitating care for the limb. To inform development of a new patient reported outcome measure (PROM) of active and passive function in the hemiparetic upper limb, the Arm Activity measure, we examined functional goals for the upper limb, identified during goal setting for spasticity intervention (physical therapy and concomitant botulinum toxin A interventions). Using secondary analysis of a prospective observational cohort study, functional goals determined between patients, their carers and the clinical team were assigned into categories by two raters. Goal category identification, followed by assignment of goals to a category, was undertaken and then confirmed by a second reviewer. Participants comprised nine males and seven females of mean (SD) age 54.5 (15.7) years and their carers. Fifteen had sustained a stroke and one a traumatic brain injury. Goals were used to identify five categories: passive function, active function, symptoms, cosmesis and impairment. Two passive function items not previously identified by a previous systematic review were identified. Analysis of goals important to patients and carers revealed items for inclusion in a new measure of arm function and provide a useful alternative method to involve patients and carers in standardised measure development. Copyright © 2014 Chartered Society of Physiotherapy. Published by Elsevier Ltd. All rights reserved.

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…

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…

The 11-item Medication Adherence Reasons Scale: reliability and factorial validity among patients with hypertension in Malaysian primary healthcare settings

PubMed Central

Shima, Razatul; Farizah, Hairi; Majid, Hazreen Abdul

2015-01-01

INTRODUCTION The aim of this study was to assess the reliability and validity of a modified Malaysian version of the Medication Adherence Reasons Scale (MAR-Scale). METHODS In this cross-sectional study, the 15-item MAR-Scale was administered to 665 patients with hypertension who attended one of the four government primary healthcare clinics in the Hulu Langat and Klang districts of Selangor, Malaysia, between early December 2012 and end-March 2013. The construct validity was examined in two phases. Phase I consisted of translation of the MAR-Scale from English to Malay, a content validity check by an expert panel, a face validity check via a small preliminary test among patients with hypertension, and exploratory factor analysis (EFA). Phase II involved internal consistency reliability calculations and confirmatory factor analysis (CFA). RESULTS EFA verified five existing factors that were previously identified (i.e. issues with medication management, multiple medications, belief in medication, medication availability, and the patient’s forgetfulness and convenience), while CFA extracted four factors (medication availability issues were not extracted). The final modified MAR-Scale model, which had 11 items and a four-factor structure, provided good evidence of convergent and discriminant validities. Cronbach’s alpha coefficient was > 0.7, indicating good internal consistency of the items in the construct. The results suggest that the modified MAR-Scale has good internal consistencies and construct validity. CONCLUSION The validated modified MAR-Scale (Malaysian version) was found to be suitable for use among patients with hypertension receiving treatment in primary healthcare settings. However, the comprehensive measurement of other factors that can also lead to non-adherence requires further exploration. PMID:25902719

Mine Water Treatment in Hongai Coal Mines

NASA Astrophysics Data System (ADS)

Dang, Phuong Thao; Dang, Vu Chi

2018-03-01

Acid mine drainage (AMD) is recognized as one of the most serious environmental problem associated with mining industry. Acid water, also known as acid mine drainage forms when iron sulfide minerals found in the rock of coal seams are exposed to oxidizing conditions in coal mining. Until 2009, mine drainage in Hongai coal mines was not treated, leading to harmful effects on humans, animals and aquatic ecosystem. This report has examined acid mine drainage problem and techniques for acid mine drainage treatment in Hongai coal mines. In addition, selection and criteria for the design of the treatment systems have been presented.

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...

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.

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.

[Perceptions on item disclosure for the Korean medical licensing examination].

PubMed

Yang, Eunbae B

2015-09-01

This study analyzed the perceptions of medical students and faculty regarding disclosure of test items on the Korean medical licensing examination. I conducted a survey of medical students from medical colleges and professional medical schools nationwide. Responses were analyzed from 718 participants as well as 69 faculty members who participated in creating the medical licensing examination item sets. Data were analyzed using descriptive statistics and the chi-square test. It is important to maintain test quality and to keep the test items unavailable to the public. There are also concerns among students that disclosure of test items would prompt increasing difficulty of test items (48.3%). Further, few students found it desirable to disclose test items regardless of any considerations (28.5%). The professors, who had experience in designing the test items, also expressed their opposition to test item disclosure (60.9%). It is desirable not to disclose the test items of the Korean medical licensing examination to the public on the condition that students are provided with a sufficient amount of information regarding the examination. This is so that the exam can appropriately identify candidates with the required qualifications.

Validity and measurement precision of the PROMIS physical function item bank and a content validity-driven 20-item short form in rheumatoid arthritis compared with traditional measures.

PubMed

Oude Voshaar, Martijn A H; Ten Klooster, Peter M; Glas, Cees A W; Vonkeman, Harald E; Taal, Erik; Krishnan, Eswar; Bernelot Moens, Hein J; Boers, Maarten; Terwee, Caroline B; van Riel, Piet L C M; van de Laar, Mart A F J

2015-12-01

To evaluate the content validity and measurement properties of the Patient-Reported Outcome Measurement Information System (PROMIS) physical function item bank and a 20-item short form in patients with RA in comparison with the HAQ disability index (HAQ-DI) and 36-item Short Form Health Survey (SF-36) physical functioning scale (PF-10). The content validity of the instruments was evaluated by linking their items to the International Classification of Functioning, Disability and Health (ICF) core set for RA. The measures were administered to 690 RA patients enrolled in the Dutch Rheumatoid Arthritis Monitoring registry. Measurement precision was evaluated using item response theory methods and construct validity was evaluated by correlating physical function scores with other clinical and patient-reported outcome measures. All 207 health concepts identified in the physical function measures referred to activities that are featured in the ICF. Twenty-three of 26 ICF RA core set domains are featured in the full PROMIS physical function item bank compared with 13 and 8 for the HAQ-DI and PF-10, respectively. As hypothesized, all three physical function instruments were highly intercorrelated (r 0.74-0.84), moderately correlated with disease activity measures (r 0.44-0.63) and weakly correlated with age (rs 0.07-0.14). Item response theory-based analysis revealed that a 20-item PROMIS physical function short form covered a wider range of physical function levels than the HAQ-DI or PF-10. The PROMIS physical function item bank demonstrated excellent measurement properties in RA. A content-driven 20-item short form may be a useful tool for assessing physical function in RA. © The Author 2015. Published by Oxford University Press on behalf of the British Society for Rheumatology. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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.

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.

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data.

PubMed

Hettne, Kristina M; Boorsma, André; van Dartel, Dorien A M; Goeman, Jelle J; de Jong, Esther; Piersma, Aldert H; Stierum, Rob H; Kleinjans, Jos C; Kors, Jan A

2013-01-29

Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals. Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants had a similar toxicity

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.

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

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…

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.

Moment tensor inversion with three-dimensional sensor configuration of mining induced seismicity (Kiruna mine, Sweden)

NASA Astrophysics Data System (ADS)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-06-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). A stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double-couple and full moment tensor with high frequency data, is very challenging. Moreover, the application to underground mining system requires accounting for the 3-D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3-D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in the presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to eight events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double-couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip and rake configurations of the double-couple term were obtained

Moment Tensor Inversion with 3D sensor configuration of Mining Induced Seismicity (Kiruna mine, Sweden)

NASA Astrophysics Data System (ADS)

Ma, Ju; Dineva, Savka; Cesca, Simone; Heimann, Sebastian

2018-03-01

Mining induced seismicity is an undesired consequence of mining operations, which poses significant hazard to miners and infrastructures and requires an accurate analysis of the rupture process. Seismic moment tensors of mining-induced events help to understand the nature of mining-induced seismicity by providing information about the relationship between the mining, stress redistribution and instabilities in the rock mass. In this work, we adapt and test a waveform-based inversion method on high frequency data recorded by a dense underground seismic system in one of the largest underground mines in the world (Kiruna mine, Sweden). Stable algorithm for moment tensor inversion for comparatively small mining induced earthquakes, resolving both the double couple and full moment tensor with high frequency data is very challenging. Moreover, the application to underground mining system requires accounting for the 3D geometry of the monitoring system. We construct a Green's function database using a homogeneous velocity model, but assuming a 3D distribution of potential sources and receivers. We first perform a set of moment tensor inversions using synthetic data to test the effects of different factors on moment tensor inversion stability and source parameters accuracy, including the network spatial coverage, the number of sensors and the signal-to-noise ratio. The influence of the accuracy of the input source parameters on the inversion results is also tested. Those tests show that an accurate selection of the inversion parameters allows resolving the moment tensor also in presence of realistic seismic noise conditions. Finally, the moment tensor inversion methodology is applied to 8 events chosen from mining block #33/34 at Kiruna mine. Source parameters including scalar moment, magnitude, double couple, compensated linear vector dipole and isotropic contributions as well as the strike, dip, rake configurations of the double couple term were obtained. The orientations

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…

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

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.

Urban Mining of E-Waste is Becoming More Cost-Effective Than Virgin Mining.

PubMed

Zeng, Xianlai; Mathews, John A; Li, Jinhui

2018-04-17

Stocks of virgin-mined materials utilized in linear economic flows continue to present enormous challenges. E-waste is one of the fastest growing waste streams, and threatens to grow into a global problem of unmanageable proportions. An effective form of management of resource recycling and environmental improvement is available, in the form of extraction and purification of precious metals taken from waste streams, in a process known as urban mining. In this work, we demonstrate utilizing real cost data from e-waste processors in China that ingots of pure copper and gold could be recovered from e-waste streams at costs that are comparable to those encountered in virgin mining of ores. Our results are confined to the cases of copper and gold extracted and processed from e-waste streams made up of recycled TV sets, but these results indicate a trend and potential if applied across a broader range of e-waste sources and metals extracted. If these results can be extended to other metals and countries, they promise to have positive impact on waste disposal and mining activities globally, as the circular economy comes to displace linear economic pathways.

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.…

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

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.

Hydrogeologic setting and simulation of groundwater flow near the Canterbury and Leadville Mine Drainage Tunnels, Leadville, Colorado

USGS Publications Warehouse

Wellman, Tristan P.; Paschke, Suzanne S.; Minsley, Burke; Dupree, Jean A.

2011-01-01

63 percent of the total water budget, respectively). The largest contributions to the water budget were groundwater entering from the upper reaches of the watershed and the hydrologic interaction of the groundwater with the East Fork Arkansas River. Potentiometric surface maps of the simulated model results were generated for depths of 50, 100, and 250 m. The surfaces revealed a positive trend in hydraulic head with land-surface altitude and evidence of increased control on fluid movement by the fault network structure at progressively greater depths in the aquifer. Results of advective particle-tracking simulations indicate that the sets of simulated flow paths for the Canterbury Tunnel and the Leadville Mine Drainage Tunnel were mutually exclusive of one another, which also suggested that no major hydraulic connection was present between the tunnels. Particle-tracking simulations also revealed that although the fault network generally restricted groundwater movement locally, hydrologic conditions were such that groundwater did cross the fault network at many locations. This cross-fault movement indicates that the fault network controls regional groundwater flow to some degree but is not a complete barrier to flow. The cumulative distributions of adjusted age results for the watershed indicate that approximately 30 percent of the flow pathways transmit groundwater that was younger than 68 years old (post-1941) and that about 70 percent of the flow pathways transmit old groundwater. The particle-tracking results are consistent with the apparent ages and mixing ratios developed from the chlorofluorocarbon and tritium results. The model simulations also indicate that approximately 50 percent of the groundwater flowing through the study area was less than 200 years old and about 50 percent of the groundwater flowing through the study area is old water stored in low-permeability geologic units and fault blocks. As a final examination of model response, the conductance

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…

Extending Item Response Theory to Online Homework

ERIC Educational Resources Information Center

Kortemeyer, Gerd

2014-01-01

Item response theory (IRT) becomes an increasingly important tool when analyzing "big data" gathered from online educational venues. However, the mechanism was originally developed in traditional exam settings, and several of its assumptions are infringed upon when deployed in the online realm. For a large-enrollment physics course for…

IRT Item Parameter Scaling for Developing New Item Pools

ERIC Educational Resources Information Center

Kang, Hyeon-Ah; Lu, Ying; Chang, Hua-Hua

2017-01-01

Increasing use of item pools in large-scale educational assessments calls for an appropriate scaling procedure to achieve a common metric among field-tested items. The present study examines scaling procedures for developing a new item pool under a spiraled block linking design. The three scaling procedures are considered: (a) concurrent…

Large Mine Permitting - Div. of Mining, Land, and Water

Science.gov Websites

Pebble Project Pogo Mine Red Dog Mine Rock Creek Project True North Mine OPMP Canadian Large Projects Pebble Project Pogo Mine Red Dog Mine Rock Creek Project True North Mine Contact: Kyle Moselle Large Mine

A Bifactor Multidimensional Item Response Theory Model for Differential Item Functioning Analysis on Testlet-Based Items

ERIC Educational Resources Information Center

Fukuhara, Hirotaka; Kamata, Akihito

2011-01-01

A differential item functioning (DIF) detection method for testlet-based data was proposed and evaluated in this study. The proposed DIF model is an extension of a bifactor multidimensional item response theory (MIRT) model for testlets. Unlike traditional item response theory (IRT) DIF models, the proposed model takes testlet effects into…

Gender-Based Differential Item Performance in Mathematics Achievement Items.

ERIC Educational Resources Information Center

Doolittle, Allen E.; Cleary, T. Anne

1987-01-01

Eight randomly equivalent samples of high school seniors were each given a unique form of the ACT Assessment Mathematics Usage Test (ACTM). Signed measures of differential item performance (DIP) were obtained for each item in the eight ACTM forms. DIP estimates were analyzed and a significant item category effect was found. (Author/LMO)

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.

Real and Artificial Differential Item Functioning in Polytomous Items

ERIC Educational Resources Information Center

Andrich, David; Hagquist, Curt

2015-01-01

Differential item functioning (DIF) for an item between two groups is present if, for the same person location on a variable, persons from different groups have different expected values for their responses. Applying only to dichotomously scored items in the popular Mantel-Haenszel (MH) method for detecting DIF in which persons are classified by…

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…

Next-generation text-mining mediated generation of chemical response-specific gene sets for interpretation of gene expression data

PubMed Central

2013-01-01

Background Availability of chemical response-specific lists of genes (gene sets) for pharmacological and/or toxic effect prediction for compounds is limited. We hypothesize that more gene sets can be created by next-generation text mining (next-gen TM), and that these can be used with gene set analysis (GSA) methods for chemical treatment identification, for pharmacological mechanism elucidation, and for comparing compound toxicity profiles. Methods We created 30,211 chemical response-specific gene sets for human and mouse by next-gen TM, and derived 1,189 (human) and 588 (mouse) gene sets from the Comparative Toxicogenomics Database (CTD). We tested for significant differential expression (SDE) (false discovery rate -corrected p-values < 0.05) of the next-gen TM-derived gene sets and the CTD-derived gene sets in gene expression (GE) data sets of five chemicals (from experimental models). We tested for SDE of gene sets for six fibrates in a peroxisome proliferator-activated receptor alpha (PPARA) knock-out GE dataset and compared to results from the Connectivity Map. We tested for SDE of 319 next-gen TM-derived gene sets for environmental toxicants in three GE data sets of triazoles, and tested for SDE of 442 gene sets associated with embryonic structures. We compared the gene sets to triazole effects seen in the Whole Embryo Culture (WEC), and used principal component analysis (PCA) to discriminate triazoles from other chemicals. Results Next-gen TM-derived gene sets matching the chemical treatment were significantly altered in three GE data sets, and the corresponding CTD-derived gene sets were significantly altered in five GE data sets. Six next-gen TM-derived and four CTD-derived fibrate gene sets were significantly altered in the PPARA knock-out GE dataset. None of the fibrate signatures in cMap scored significant against the PPARA GE signature. 33 environmental toxicant gene sets were significantly altered in the triazole GE data sets. 21 of these toxicants

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.

Environmental hazard assessment of a marine mine tailings deposit site and potential implications for deep-sea mining.

PubMed

Mestre, Nélia C; Rocha, Thiago L; Canals, Miquel; Cardoso, Cátia; Danovaro, Roberto; Dell'Anno, Antonio; Gambi, Cristina; Regoli, Francesco; Sanchez-Vidal, Anna; Bebianno, Maria João

2017-09-01

Portmán Bay is a heavily contaminated area resulting from decades of metal mine tailings disposal, and is considered a suitable shallow-water analogue to investigate the potential ecotoxicological impact of deep-sea mining. Resuspension plumes were artificially created by removing the top layer of the mine tailings deposit by bottom trawling. Mussels were deployed at three sites: i) off the mine tailings deposit area; ii) on the mine tailings deposit beyond the influence from the resuspension plumes; iii) under the influence of the artificially generated resuspension plumes. Surface sediment samples were collected at the same sites for metal analysis and ecotoxicity assessment. Metal concentrations and a battery of biomarkers (oxidative stress, metal exposure, biotransformation and oxidative damage) were measured in different mussel tissues. The environmental hazard posed by the resuspension plumes was investigated by a quantitative weight of evidence (WOE) model that integrated all the data. The resuspension of sediments loaded with metal mine tails demonstrated that chemical contaminants were released by trawling subsequently inducing ecotoxicological impact in mussels' health. Considering as sediment quality guidelines (SQGs) those indicated in Spanish action level B for the disposal of dredged material at sea, the WOE model indicates that the hazard is slight off the mine tailings deposit, moderate on the mine tailings deposit without the influence from the resuspension plumes, and major under the influence of the resuspension plumes. Portmán Bay mine tailings deposit is a by-product of sulphide mining, and despite differences in environmental setting, it can reflect the potential ecotoxic effects to marine fauna from the impact of resuspension of plumes created by deep-sea mining of polymetallic sulphides. A similar approach as in this study could be applied in other areas affected by sediment resuspension and for testing future deep-sea mining sites in

Component Identification and Item Difficulty of Raven's Matrices Items.

ERIC Educational Resources Information Center

Green, Kathy E.; Kluever, Raymond C.

Item components that might contribute to the difficulty of items on the Raven Colored Progressive Matrices (CPM) and the Standard Progressive Matrices (SPM) were studied. Subjects providing responses to CPM items were 269 children aged 2 years 9 months to 11 years 8 months, most of whom were referred for testing as potentially gifted. A second…

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.

The LANL/LLNL/AFTAC Black Thunder Coal Mine regional mine monitoring experiment

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

Pearson, D.C.; Stump, B.W.; Baker, D.F.

Cast blasting operations associated with near surface coal recovery provide relatively large explosive sources that generate regional seismograms of interest in monitoring a Comprehensive Test Ban Treaty (CTBT). This paper describes preliminary results of a series of experiments currently being conducted at the Black Thunder Coal Mine in northeast Wyoming as part of the DOE CTBT Research and Development Program. These experiments are intended to provide an integrated set of near-source and regional seismic data for the purposes of quantifying the coupling and source characterization of the explosions. The focus of this paper is on the types of data beingmore » recovered with some preliminary implications. The Black Thunder experiments are designed to assess three major questions: (1) how many mining explosions produce seismograms at regional distances that will have to be detected, located and ultimately identified by the National Data Center and what are the waveform characteristics of these particular mining explosions; (2) can discrimination techniques based on empirical studies be placed on a firm physical basis so that they can be applied to other regions where there is little monitoring experience; (3) can large scale chemical explosions (possibly mining explosions) be used to calibrate source and propagation path effects to regional stations, can source depth of burial and decoupling effects be studied in such a controlled environment? With these key questions in mind and given the cooperation of the Black Thunder Mine, a suite of experiments have been and are currently being conducted. This paper will describe the experiments and their relevance to CTBT issues.« less

Data Mining and Analysis

NASA Technical Reports Server (NTRS)

Samms, Kevin O.

2015-01-01

The Data Mining project seeks to bring the capability of data visualization to NASA anomaly and problem reporting systems for the purpose of improving data trending, evaluations, and analyses. Currently NASA systems are tailored to meet the specific needs of its organizations. This tailoring has led to a variety of nomenclatures and levels of annotation for procedures, parts, and anomalies making difficult the realization of the common causes for anomalies. Making significant observations and realizing the connection between these causes without a common way to view large data sets is difficult to impossible. In the first phase of the Data Mining project a portal was created to present a common visualization of normalized sensitive data to customers with the appropriate security access. The tool of the visualization itself was also developed and fine-tuned. In the second phase of the project we took on the difficult task of searching and analyzing the target data set for common causes between anomalies. In the final part of the second phase we have learned more about how much of the analysis work will be the job of the Data Mining team, how to perform that work, and how that work may be used by different customers in different ways. In this paper I detail how our perspective has changed after gaining more insight into how the customers wish to interact with the output and how that has changed the product.

"Ready, Set, FLOW!"

ERIC Educational Resources Information Center

Stroud, Wesley

2018-01-01

All educators want their classrooms to be inviting areas that support investigations. However, a common mistake is to fill learning spaces with items or objects that are set up by the teacher or are simply "for show." This type of setting, although it may create a comfortable space for students, fails to stimulate investigations and…

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.

Identifying high-cost patients using data mining techniques and a small set of non-trivial attributes.

PubMed

Izad Shenas, Seyed Abdolmotalleb; Raahemi, Bijan; Hossein Tekieh, Mohammad; Kuziemsky, Craig

2014-10-01

In this paper, we use data mining techniques, namely neural networks and decision trees, to build predictive models to identify very high-cost patients in the top 5 percentile among the general population. A large empirical dataset from the Medical Expenditure Panel Survey with 98,175 records was used in our study. After pre-processing, partitioning and balancing the data, the refined dataset of 31,704 records was modeled by Decision Trees (including C5.0 and CHAID), and Neural Networks. The performances of the models are analyzed using various measures including accuracy, G-mean, and Area under ROC curve. We concluded that the CHAID classifier returns the best G-mean and AUC measures for top performing predictive models ranging from 76% to 85%, and 0.812 to 0.942 units, respectively. We also identify a small set of 5 non-trivial attributes among a primary set of 66 attributes to identify the top 5% of the high cost population. The attributes are the individual׳s overall health perception, age, history of blood cholesterol check, history of physical/sensory/mental limitations, and history of colonic prevention measures. The small set of attributes are what we call non-trivial and does not include visits to care providers, doctors or hospitals, which are highly correlated with expenditures and does not offer new insight to the data. The results of this study can be used by healthcare data analysts, policy makers, insurer, and healthcare planners to improve the delivery of health services. Copyright © 2014 Elsevier Ltd. All rights reserved.

Evaluation of psychometric properties and differential item functioning of 8-item Child Perceptions Questionnaires using item response theory.

PubMed

Yau, David T W; Wong, May C M; Lam, K F; McGrath, Colman

2015-08-19

Four-factor structure of the two 8-item short forms of Child Perceptions Questionnaire CPQ11-14 (RSF:8 and ISF:8) has been confirmed. However, the sum scores are typically reported in practice as a proxy of Oral health-related Quality of Life (OHRQoL), which implied a unidimensional structure. This study first assessed the unidimensionality of 8-item short forms of CPQ11-14. Item response theory (IRT) was employed to offer an alternative and complementary approach of validation and to overcome the limitations of classical test theory assumptions. A random sample of 649 12-year-old school children in Hong Kong was analyzed. Unidimensionality of the scale was tested by confirmatory factor analysis (CFA), principle component analysis (PCA) and local dependency (LD) statistic. Graded response model was fitted to the data. Contribution of each item to the scale was assessed by item information function (IIF). Reliability of the scale was assessed by test information function (TIF). Differential item functioning (DIF) across gender was identified by Wald test and expected score functions. Both CPQ11-14 RSF:8 and ISF:8 did not deviate much from the unidimensionality assumption. Results from CFA indicated acceptable fit of the one-factor model. PCA indicated that the first principle component explained >30 % of the total variation with high factor loadings for both RSF:8 and ISF:8. Almost all LD statistic <10 indicated the absence of local dependency. Flat and low IIFs were observed in the oral symptoms items suggesting little contribution of information to the scale and item removal caused little practical impact. Comparing the TIFs, RSF:8 showed slightly better information than ISF:8. In addition to oral symptoms items, the item "Concerned with what other people think" demonstrated a uniform DIF (p < 0.001). The expected score functions were not much different between boys and girls. Items related to oral symptoms were not informative to OHRQoL and deletion of these

Underground coal mining section data

NASA Technical Reports Server (NTRS)

Gabrill, C. P.; Urie, J. T.

1981-01-01

A set of tables which display the allocation of time for ten personnel and eight pieces of underground coal mining equipment to ten function categories is provided. Data from 125 full shift time studies contained in the KETRON database was utilized as the primary source data. The KETRON activity and delay codes were mapped onto JPL equipment, personnel and function categories. Computer processing was then performed to aggregate the shift level data and generate the matrices. Additional, documented time study data were analyzed and used to supplement the KETRON databased. The source data including the number of shifts are described. Specific parameters of the mines from which there data were extracted are presented. The result of the data processing including the required JPL matrices is presented. A brief comparison with a time study analysis of continuous mining systems is presented. The procedures used for processing the source data are described.

Separating relational from item load effects in paired recognition: temporoparietal and middle frontal gyral activity with increased associates, but not items during encoding and retention.

PubMed

Phillips, Steven; Niki, Kazuhisa

2002-10-01

Working memory is affected by items stored and the relations between them. However, separating these factors has been difficult, because increased items usually accompany increased associations/relations. Hence, some have argued, relational effects are reducible to item effects. We overcome this problem by manipulating index length: the fewest number of item positions at which there is a unique item, or tuple of items (if length >1), for every instance in the relational (memory) set. Longer indexes imply greater similarity (number of shared items) between instances and higher load on encoding processes. Subjects were given lists of study pairs and asked to make a recognition judgement. The number of unique items and index length in the three list conditions were: (1) AB, CD: four/one; (2) AB, CD, EF: six/one; and (3) AB, AD, CB: four/two, respectively. Japanese letters were used in Experiments 1 (kanji-ideograms) and 2 (hiragana-phonograms); numbers in Experiment 3; and shapes generated from Fourier descriptors in Experiment 4. Across all materials, right dominant temporoparietal and middle frontal gyral activity was found with increased index length, but not items during study. In Experiment 5, a longer delay was used to isolate retention effects in the absence of visual stimuli. Increased left hemispheric activity was observed in the precuneus, middle frontal gyrus, and superior temporal gyrus with increased index length for the delay period. These results show that relational load is not reducible to item load.

Geochemical characterisation of seepage and drainage water quality from two sulphide mine tailings impoundments: Acid mine drainage versus neutral mine drainage

USGS Publications Warehouse

Heikkinen, P.M.; Raisanen, M.L.; Johnson, R.H.

2009-01-01

Seepage water and drainage water geochemistry (pH, EC, O2, redox, alkalinity, dissolved cations and trace metals, major anions, total element concentrations) were studied at two active sulphide mine tailings impoundments in Finland (the Hitura Ni mine and Luikonlahti Cu mine/talc processing plant). The data were used to assess the factors influencing tailings seepage quality and to identify constraints for water treatment. Changes in seepage water quality after equilibration with atmospheric conditions were evaluated based on geochemical modelling. At Luikonlahti, annual and seasonal changes were also studied. Seepage quality was largely influenced by the tailings mineralogy, and the serpentine-rich, low sulphide Hitura tailings produced neutral mine drainage with high Ni. In contrast, drainage from the high sulphide, multi-metal tailings of Luikonlahti represented typical acid mine drainage with elevated contents of Zn, Ni, Cu, and Co. Other factors affecting the seepage quality included weathering of the tailings along the seepage flow path, process water input, local hydrological settings, and structural changes in the tailings impoundment. Geochemical modelling showed that pH increased and some heavy metals were adsorbed to Fe precipitates after net alkaline waters equilibrated with the atmosphere. In the net acidic waters, pH decreased and no adsorption occurred. A combination of aerobic and anaerobic treatments is proposed for Hitura seepages to decrease the sulphate and metal loading. For Luikonlahti, prolonged monitoring of the seepage quality is suggested instead of treatment, since the water quality is still adjusting to recent modifications to the tailings impoundment.

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.

Quantifying Associations between Environmental Stressors and Demographic Factors

EPA Science Inventory

Association rule mining (ARM) [1-3], also known as frequent item set mining [4] or market basket analysis [1], has been widely applied in many different areas, such as business product portfolio planning [5], intrusion detection infrastructure design [6], gene expression analysis...

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

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.

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways

PubMed Central

Koumakis, Lefteris; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Vassou, Despoina; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-01-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

MinePath: Mining for Phenotype Differential Sub-paths in Molecular Pathways.

PubMed

Koumakis, Lefteris; Kanterakis, Alexandros; Kartsaki, Evgenia; Chatzimina, Maria; Zervakis, Michalis; Tsiknakis, Manolis; Vassou, Despoina; Kafetzopoulos, Dimitris; Marias, Kostas; Moustakis, Vassilis; Potamias, George

2016-11-01

Pathway analysis methodologies couple traditional gene expression analysis with knowledge encoded in established molecular pathway networks, offering a promising approach towards the biological interpretation of phenotype differentiating genes. Early pathway analysis methodologies, named as gene set analysis (GSA), view pathways just as plain lists of genes without taking into account either the underlying pathway network topology or the involved gene regulatory relations. These approaches, even if they achieve computational efficiency and simplicity, consider pathways that involve the same genes as equivalent in terms of their gene enrichment characteristics. Most recent pathway analysis approaches take into account the underlying gene regulatory relations by examining their consistency with gene expression profiles and computing a score for each profile. Even with this approach, assessing and scoring single-relations limits the ability to reveal key gene regulation mechanisms hidden in longer pathway sub-paths. We introduce MinePath, a pathway analysis methodology that addresses and overcomes the aforementioned problems. MinePath facilitates the decomposition of pathways into their constituent sub-paths. Decomposition leads to the transformation of single-relations to complex regulation sub-paths. Regulation sub-paths are then matched with gene expression sample profiles in order to evaluate their functional status and to assess phenotype differential power. Assessment of differential power supports the identification of the most discriminant profiles. In addition, MinePath assess the significance of the pathways as a whole, ranking them by their p-values. Comparison results with state-of-the-art pathway analysis systems are indicative for the soundness and reliability of the MinePath approach. In contrast with many pathway analysis tools, MinePath is a web-based system (www.minepath.org) offering dynamic and rich pathway visualization functionality, with the

Poker Flats Mine - Div. of Mining, Land, and Water

Science.gov Websites

Lands Coal Regulatory Program Large Mine Permits Mineral Property and Rights Mining Index Land Fishery Water Resources Factsheets Forms banner image of landscape Poker Flats Mine Home Mining Coal Regulatory Program Poker Flats Mine Mining Coal Regulatory Program Info Chickaloon Chuit Watershed Chuitna

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

MINE: Module Identification in Networks

PubMed Central

2011-01-01

Background Graphical models of network associations are useful for both visualizing and integrating multiple types of association data. Identifying modules, or groups of functionally related gene products, is an important challenge in analyzing biological networks. However, existing tools to identify modules are insufficient when applied to dense networks of experimentally derived interaction data. To address this problem, we have developed an agglomerative clustering method that is able to identify highly modular sets of gene products within highly interconnected molecular interaction networks. Results MINE outperforms MCODE, CFinder, NEMO, SPICi, and MCL in identifying non-exclusive, high modularity clusters when applied to the C. elegans protein-protein interaction network. The algorithm generally achieves superior geometric accuracy and modularity for annotated functional categories. In comparison with the most closely related algorithm, MCODE, the top clusters identified by MINE are consistently of higher density and MINE is less likely to designate overlapping modules as a single unit. MINE offers a high level of granularity with a small number of adjustable parameters, enabling users to fine-tune cluster results for input networks with differing topological properties. Conclusions MINE was created in response to the challenge of discovering high quality modules of gene products within highly interconnected biological networks. The algorithm allows a high degree of flexibility and user-customisation of results with few adjustable parameters. MINE outperforms several popular clustering algorithms in identifying modules with high modularity and obtains good overall recall and precision of functional annotations in protein-protein interaction networks from both S. cerevisiae and C. elegans. PMID:21605434

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.

A Primer on the 2- and 3-Parameter Item Response Theory Models.

ERIC Educational Resources Information Center

Thornton, Artist

Item response theory (IRT) is a useful and effective tool for item response measurement if used in the proper context. This paper discusses the sets of assumptions under which responses can be modeled while exploring the framework of the IRT models relative to response testing. The one parameter model, or one parameter logistic model, is perhaps…

Item Bank Development for a Revised Pediatric Evaluation of Disability Inventory (PEDI)

ERIC Educational Resources Information Center

Dumas, Helene; Fragala-Pinkham, Maria; Haley, Stephen; Coster, Wendy; Kramer, Jessica; Kao, Ying-Chia; Moed, Richard

2010-01-01

The Pediatric Evaluation of Disability Inventory (PEDI) is a useful clinical and research assessment, but it has limitations in content, age range, and efficiency. The purpose of this article is to describe the development of the item bank for a new computer adaptive testing version of the PEDI (PEDI-CAT). An expanded item set and response options…

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

Abandoned mines and their impact on the environment: Case studies from Franklin and Sterling Mines, NJ and Rondout Quarry, NY

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

Kolkas, M.M.; Nehru, C.E.

1995-09-01

Water logged abandoned mines have an impact on the environment. In this project we selected abandoned mines from two sets of different ore bodies to learn about their environmental impact. Franklin and Sterling Pb-Zn mines, NJ and the limestone quarry in Rondout formation, NY were selected as case study examples. In the Pb-Zn mines metalimestone is the country rock and in the Rondout quarry limestone is the country rock. Soil water samples from selected strategic locations were analyzed for toxic and related heavy metal elements such as Pb, Zn, Cd, Cr and U. The levels of concentrations of these elementsmore » varied from one location to another according to the chemistry of the ore body and the ground movement throughout the area. In particular Cd, Cr and U concentration were variable from Franklin to Sterling mine. However, in the Rondout limestone (cement) quarry, higher concentrations of Cr and lower concentrations of Pb and Zn were noted. We conclude that ore body chemistry, mine dumps and tailing contaminated ponds along with the ground water movement throughout the area have an impact on the ground water and nearby river/stream contaminant chemistry in the areas.« less

Item Banking Enables Stand-Alone Measurement of Driving Ability.

PubMed

Khadka, Jyoti; Fenwick, Eva K; Lamoureux, Ecosse L; Pesudovs, Konrad

2016-12-01

To explore whether large item sets, as used in item banking, enable important latent traits, such as driving, to form stand-alone measures. The 88-item activity limitation (AL) domain of the glaucoma module of the Eye-tem Bank was interviewer-administered to patients with glaucoma. Rasch analysis was used to calibrate all items in AL domain on the same interval-level scale and test its psychometric properties. Based on Rasch dimensionality metrics, the AL scale was separated into subscales. These subscales underwent separate Rasch analyses to test whether they could form stand-alone measures. Independence of these measures was tested with Bland and Altman (B&A) Limit of Agreement (LOA). The AL scale was completed by 293 patients (median age, 71 years). It demonstrated excellent precision (3.12). However, Rasch analysis dimensionality metrics indicated that the domain arguably had other dimensions which were driving, luminance, and reading. Once separated, the remaining AL items, driving and luminance subscales, were unidimensional and had excellent precision of 4.25, 2.94, and 2.22, respectively. The reading subscale showed poor precision (1.66), so it was not examined further. The luminance subscale demonstrated excellent agreement (mean bias, 0.2 logit; 95% LOA, -2.2 to 3.3 logit); however, the driving subscale demonstrated poor agreement (mean bias, 1.1 logit; 95% LOA, -4.8 to 7.0 logit) with the AL scale. These findings indicate that driving items in the AL domain of the glaucoma module were perceived and responded to differently from the other AL items, but the reading and luminance items were not. Therefore, item banking enables stand-alone measurement of driving ability in glaucoma.

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.

Text mining for the biocuration workflow

PubMed Central

Hirschman, Lynette; Burns, Gully A. P. C; Krallinger, Martin; Arighi, Cecilia; Cohen, K. Bretonnel; Valencia, Alfonso; Wu, Cathy H.; Chatr-Aryamontri, Andrew; Dowell, Karen G.; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G.

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on ‘Text Mining for the BioCuration Workflow’ at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community. PMID:22513129

Text mining for the biocuration workflow.

PubMed

Hirschman, Lynette; Burns, Gully A P C; Krallinger, Martin; Arighi, Cecilia; Cohen, K Bretonnel; Valencia, Alfonso; Wu, Cathy H; Chatr-Aryamontri, Andrew; Dowell, Karen G; Huala, Eva; Lourenço, Anália; Nash, Robert; Veuthey, Anne-Lise; Wiegers, Thomas; Winter, Andrew G

2012-01-01

Molecular biology has become heavily dependent on biological knowledge encoded in expert curated biological databases. As the volume of biological literature increases, biocurators need help in keeping up with the literature; (semi-) automated aids for biocuration would seem to be an ideal application for natural language processing and text mining. However, to date, there have been few documented successes for improving biocuration throughput using text mining. Our initial investigations took place for the workshop on 'Text Mining for the BioCuration Workflow' at the third International Biocuration Conference (Berlin, 2009). We interviewed biocurators to obtain workflows from eight biological databases. This initial study revealed high-level commonalities, including (i) selection of documents for curation; (ii) indexing of documents with biologically relevant entities (e.g. genes); and (iii) detailed curation of specific relations (e.g. interactions); however, the detailed workflows also showed many variabilities. Following the workshop, we conducted a survey of biocurators. The survey identified biocurator priorities, including the handling of full text indexed with biological entities and support for the identification and prioritization of documents for curation. It also indicated that two-thirds of the biocuration teams had experimented with text mining and almost half were using text mining at that time. Analysis of our interviews and survey provide a set of requirements for the integration of text mining into the biocuration workflow. These can guide the identification of common needs across curated databases and encourage joint experimentation involving biocurators, text mining developers and the larger biomedical research community.

All set, indeed! N2pc components reveal simultaneous attentional control settings for multiple target colors.

PubMed

Grubert, Anna; Eimer, Martin

2016-08-01

To study whether top-down attentional control processes can be set simultaneously for different visual features, we employed a spatial cueing procedure to measure behavioral and electrophysiological markers of task-set contingent attentional capture during search for targets defined by 1 or 2 possible colors (one-color and two-color tasks). Search arrays were preceded by spatially nonpredictive color singleton cues. Behavioral spatial cueing effects indicative of attentional capture were elicited only by target-matching but not by distractor-color cues. However, when search displays contained 1 target-color and 1 distractor-color object among gray nontargets, N2pc components were triggered not only by target-color but also by distractor-color cues both in the one-color and two-color task, demonstrating that task-set nonmatching items attracted attention. When search displays contained 6 items in 6 different colors, so that participants had to adopt a fully feature-specific task set, the N2pc to distractor-color cues was eliminated in both tasks, indicating that nonmatching items were now successfully excluded from attentional processing. These results demonstrate that when observers adopt a feature-specific search mode, attentional task sets can be configured flexibly for multiple features within the same dimension, resulting in the rapid allocation of attention to task-set matching objects only. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

A Monte Carlo Study Investigating the Influence of Item Discrimination, Category Intersection Parameters, and Differential Item Functioning Patterns on the Detection of Differential Item Functioning in Polytomous Items

ERIC Educational Resources Information Center

Thurman, Carol

2009-01-01

The increased use of polytomous item formats has led assessment developers to pay greater attention to the detection of differential item functioning (DIF) in these items. DIF occurs when an item performs differently for two contrasting groups of respondents (e.g., males versus females) after controlling for differences in the abilities of the…

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.

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…

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…

Implementation of Paste Backfill Mining Technology in Chinese Coal Mines

PubMed Central

Chang, Qingliang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application. PMID:25258737

Implementation of paste backfill mining technology in Chinese coal mines.

PubMed

Chang, Qingliang; Chen, Jianhang; Zhou, Huaqiang; Bai, Jianbiao

2014-01-01

Implementation of clean mining technology at coal mines is crucial to protect the environment and maintain balance among energy resources, consumption, and ecology. After reviewing present coal clean mining technology, we introduce the technology principles and technological process of paste backfill mining in coal mines and discuss the components and features of backfill materials, the constitution of the backfill system, and the backfill process. Specific implementation of this technology and its application are analyzed for paste backfill mining in Daizhuang Coal Mine; a practical implementation shows that paste backfill mining can improve the safety and excavation rate of coal mining, which can effectively resolve surface subsidence problems caused by underground mining activities, by utilizing solid waste such as coal gangues as a resource. Therefore, paste backfill mining is an effective clean coal mining technology, which has widespread application.

The impact of item order on ratings of cancer risk perception.

PubMed

Taylor, Kathryn L; Shelby, Rebecca A; Schwartz, Marc D; Ackerman, Josh; LaSalle, V Holland; Gelmann, Edward P; McGuire, Colleen

2002-07-01

Although perceived risk is central to most theories of health behavior, there is little consensus on its measurement with regard to item wording, response set, or the number of items to include. In a methodological assessment of perceived risk, we assessed the impact of changing the order of three commonly used perceived risk items: quantitative personal risk, quantitative population risk, and comparative risk. Participants were 432 men and women enrolled in an ancillary study of the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial. Three groups of consecutively enrolled participants responded to the three items in one of three question orders. Results indicated that item order was related to the perceived risk ratings of both ovarian (P < 0.05) and colorectal (P < 0.05) cancers. Perceptions of risk were significantly lower when the comparative rating was made first. The findings suggest that compelling participants to consider their own risk relative to the risk of others results in lower ratings of perceived risk. Although the use of multiple items may provide more information than when only a single method is used, different conclusions may be reached depending on the context in which an item is assessed.

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.

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…

A New Item Selection Procedure for Mixed Item Type in Computerized Classification Testing.

ERIC Educational Resources Information Center

Lau, C. Allen; Wang, Tianyou

This paper proposes a new Information-Time index as the basis for item selection in computerized classification testing (CCT) and investigates how this new item selection algorithm can help improve test efficiency for item pools with mixed item types. It also investigates how practical constraints such as item exposure rate control, test…

Relationship between Item Responses of Negative Affect Items and the Distribution of the Sum of the Item Scores in the General Population

PubMed Central

Kawasaki, Yohei; Ide, Kazuki; Akutagawa, Maiko; Yamada, Hiroshi; Furukawa, Toshiaki A.; Ono, Yutaka

2016-01-01

Background Several studies have shown that total depressive symptom scores in the general population approximate an exponential pattern, except for the lower end of the distribution. The Center for Epidemiologic Studies Depression Scale (CES-D) consists of 20 items, each of which may take on four scores: “rarely,” “some,” “occasionally,” and “most of the time.” Recently, we reported that the item responses for 16 negative affect items commonly exhibit exponential patterns, except for the level of “rarely,” leading us to hypothesize that the item responses at the level of “rarely” may be related to the non-exponential pattern typical of the lower end of the distribution. To verify this hypothesis, we investigated how the item responses contribute to the distribution of the sum of the item scores. Methods Data collected from 21,040 subjects who had completed the CES-D questionnaire as part of a Japanese national survey were analyzed. To assess the item responses of negative affect items, we used a parameter r, which denotes the ratio of “rarely” to “some” in each item response. The distributions of the sum of negative affect items in various combinations were analyzed using log-normal scales and curve fitting. Results The sum of the item scores approximated an exponential pattern regardless of the combination of items, whereas, at the lower end of the distributions, there was a clear divergence between the actual data and the predicted exponential pattern. At the lower end of the distributions, the sum of the item scores with high values of r exhibited higher scores compared to those predicted from the exponential pattern, whereas the sum of the item scores with low values of r exhibited lower scores compared to those predicted. Conclusions The distributional pattern of the sum of the item scores could be predicted from the item responses of such items. PMID:27806132

Using PROMIS Pain Interference Items to Improve Quality Measurement in Inpatient Rehabilitation Facilities.

PubMed

Schalet, Benjamin D; Kallen, Michael A; Heinemann, Allen W; Deutsch, Anne; Cook, Karon F; Foster, Linda; Cella, David

2018-05-24

To evaluate the Patient-Reported Outcomes Measurement Information System (PROMIS) pain interference items for use in a quality measure and to compare the resulting quality score, along with internal reliability and validity, to a similar item set in the Minimum Data Set Version 3.0 (MDS). Cross-sectional, observational study. One freestanding inpatient rehabilitation facility (IRF) and one large hospital-based IRF. Patients with neurologic disorders. Of 1055 consecutive admissions, 26% were excluded based on clinician-determined cognitive impairment or emotional distress. Of the remainder, 50% consented and completed the survey near the end of their IRF stay (N = 391). Of these, more than half (57%) reported pain over the last day (n = 224). Psychometric statistics and quality scores were computed from a 55-question survey, including the MDS and PROMIS pain interference items. Estimates for internal reliability were higher for the PROMIS 2-item scale compared to the MDS: Cronbach α (0.86 vs 0.48) and interitem correlations (0.75 vs 0.31). The PROMIS-2 items were better able to detect differences in patients with mild and severe pain intensity (Cohen d = 1.57) relative to the corresponding MDS items (Cohen d = 0.81). Two quality scores based on the PROMIS-2 items, reflecting low and high levels of pain interference, showed 46% or 12% of patients meeting these thresholds. This compared to a 30% rate when patients were classified by the MDS as experiencing pain interference. PROMIS pain interference items appear to be more internally consistent than similar MDS items. The graded PROMIS items permit the creation of multiple quality scores, showing predictable overlap with corresponding MDS quality scores. Because PROMIS items provide finer distinctions, they allow greater latitude in reporting quality scores. We recommend further study of pain interference scores across IRFs to improve their reliability and validity. Copyright © 2018 AMDA – The Society for

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.

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.

The Consequences of Ignoring Item Parameter Drift in Longitudinal Item Response Models

ERIC Educational Resources Information Center

Lee, Wooyeol; Cho, Sun-Joo

2017-01-01

Utilizing a longitudinal item response model, this study investigated the effect of item parameter drift (IPD) on item parameters and person scores via a Monte Carlo study. Item parameter recovery was investigated for various IPD patterns in terms of bias and root mean-square error (RMSE), and percentage of time the 95% confidence interval covered…

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…

Evaluating Item Fit for Multidimensional Item Response Models

ERIC Educational Resources Information Center

Zhang, Bo; Stone, Clement A.

2008-01-01

This research examines the utility of the s-x[superscript 2] statistic proposed by Orlando and Thissen (2000) in evaluating item fit for multidimensional item response models. Monte Carlo simulation was conducted to investigate both the Type I error and statistical power of this fit statistic in analyzing two kinds of multidimensional test…

30 CFR 819.21 - Auger mining: Protection of underground mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Auger mining: Protection of underground mining. 819.21 Section 819.21 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT... STANDARDS-AUGER MINING § 819.21 Auger mining: Protection of underground mining. Auger holes shall not extend...

Considering the Use of General and Modified Assessment Items in Computerized Adaptive Testing

ERIC Educational Resources Information Center

Wyse, Adam E.; Albano, Anthony D.

2015-01-01

This article used several data sets from a large-scale state testing program to examine the feasibility of combining general and modified assessment items in computerized adaptive testing (CAT) for different groups of students. Results suggested that several of the assumptions made when employing this type of mixed-item CAT may not be met for…

Diverse Food Items Are Similarly Categorized by 8- to 13-year-old Children

USDA-ARS?s Scientific Manuscript database

The study objective was to 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. A set of 62 cards with pictures and names of food items from 18 professionally defined food groups was sor...

Predicting Item Difficulty in a Reading Comprehension Test with an Artificial Neural Network.

ERIC Educational Resources Information Center

Perkins, Kyle; And Others

This paper reports the results of using a three-layer backpropagation artificial neural network to predict item difficulty in a reading comprehension test. Two network structures were developed, one with and one without a sigmoid function in the output processing unit. The data set, which consisted of a table of coded test items and corresponding…

Automatic Item Generation: A More Efficient Process for Developing Mathematics Achievement Items?

ERIC Educational Resources Information Center

Embretson, Susan E.; Kingston, Neal M.

2018-01-01

The continual supply of new items is crucial to maintaining quality for many tests. Automatic item generation (AIG) has the potential to rapidly increase the number of items that are available. However, the efficiency of AIG will be mitigated if the generated items must be submitted to traditional, time-consuming review processes. In two studies,…

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.

Solving the measurement invariance anchor item problem in item response theory.

PubMed

Meade, Adam W; Wright, Natalie A

2012-09-01

The efficacy of tests of differential item functioning (measurement invariance) has been well established. It is clear that when properly implemented, these tests can successfully identify differentially functioning (DF) items when they exist. However, an assumption of these analyses is that the metric for different groups is linked using anchor items that are invariant. In practice, however, it is impossible to be certain which items are DF and which are invariant. This problem of anchor items, or referent indicators, has long plagued invariance research, and a multitude of suggested approaches have been put forth. Unfortunately, the relative efficacy of these approaches has not been tested. This study compares 11 variations on 5 qualitatively different approaches from recent literature for selecting optimal anchor items. A large-scale simulation study indicates that for nearly all conditions, an easily implemented 2-stage procedure recently put forth by Lopez Rivas, Stark, and Chernyshenko (2009) provided optimal power while maintaining nominal Type I error. With this approach, appropriate anchor items can be easily and quickly located, resulting in more efficacious invariance tests. Recommendations for invariance testing are illustrated using a pedagogical example of employee responses to an organizational culture measure.

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.

The role of attention in item-item binding in visual working memory.

PubMed

Peterson, Dwight J; Naveh-Benjamin, Moshe

2017-09-01

An important yet unresolved question regarding visual working memory (VWM) relates to whether or not binding processes within VWM require additional attentional resources compared with processing solely the individual components comprising these bindings. Previous findings indicate that binding of surface features (e.g., colored shapes) within VWM is not demanding of resources beyond what is required for single features. However, it is possible that other types of binding, such as the binding of complex, distinct items (e.g., faces and scenes), in VWM may require additional resources. In 3 experiments, we examined VWM item-item binding performance under no load, articulatory suppression, and backward counting using a modified change detection task. Binding performance declined to a greater extent than single-item performance under higher compared with lower levels of concurrent load. The findings from each of these experiments indicate that processing item-item bindings within VWM requires a greater amount of attentional resources compared with single items. These findings also highlight an important distinction between the role of attention in item-item binding within VWM and previous studies of long-term memory (LTM) where declines in single-item and binding test performance are similar under divided attention. The current findings provide novel evidence that the specific type of binding is an important determining factor regarding whether or not VWM binding processes require attention. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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

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).

Better assessment of physical function: item improvement is neglected but essential.

PubMed

Bruce, Bonnie; Fries, James F; Ambrosini, Debbie; Lingala, Bharathi; Gandek, Barbara; Rose, Matthias; Ware, John E

2009-01-01

having comparable model fits. Correlations between factors in the test data sets were > 0.90. Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes.

Better assessment of physical function: item improvement is neglected but essential

PubMed Central

2009-01-01

-, three-, and four-factor models having comparable model fits. Correlations between factors in the test data sets were > 0.90. Conclusions Item improvement must underlie attempts to improve outcome assessment. The clear, personally important and relevant, ability-framed items in the PROMIS Physical Function item bank perform well in PRO assessment. They will benefit from further study and application in a wider variety of rheumatic diseases in diverse clinical groups, including those at the extremes of physical functioning, and in different administration modes. PMID:20015354

Item Purification in Differential Item Functioning Using Generalized Linear Mixed Models

ERIC Educational Resources Information Center

Liu, Qian

2011-01-01

For this dissertation, four item purification procedures were implemented onto the generalized linear mixed model for differential item functioning (DIF) analysis, and the performance of these item purification procedures was investigated through a series of simulations. Among the four procedures, forward and generalized linear mixed model (GLMM)…

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.

Mine Waste at The Kherzet Youcef Mine : Environmental Characterization

NASA Astrophysics Data System (ADS)

Issaad, Mouloud; Boutaleb, Abdelhak; Kolli, Omar

2017-04-01

Mining activity in Algeria has existed since antiquity. But it was very important since the 20th century. This activity has virtually ceased since the beginning of the 1990s, leaving many mine sites abandoned (so-called orphan mines). The abandonment of mining today poses many environmental problems (soil pollution, contamination of surface water, mining collapses...). The mining wastes often occupy large volumes that can be hazardous to the environment and human health, often neglected in the past: Faulting geotechnical implementation, acid mine drainage (AMD), alkalinity, presence of pollutants and toxic substances (heavy metals, cyanide...). The study started already six years ago and it covers all mines located in NE Algeria, almost are stopped for more than thirty years. So the most important is to have an overview of all the study area. After the inventory job of the abandoned mines, the rock drainage prediction will help us to classify sites according to their acid generating potential.

Modeling Answer Change Behavior: An Application of a Generalized Item Response Tree Model

ERIC Educational Resources Information Center

Jeon, Minjeong; De Boeck, Paul; van der Linden, Wim

2017-01-01

We present a novel application of a generalized item response tree model to investigate test takers' answer change behavior. The model allows us to simultaneously model the observed patterns of the initial and final responses after an answer change as a function of a set of latent traits and item parameters. The proposed application is illustrated…

Suspect/Counterfeit Items Information Guide for Subcontractors/Suppliers

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

Tessmar, Nancy D.; Salazar, Michael J.

2012-09-18

Counterfeiting of industrial and commercial grade items is an international problem that places worker safety, program objectives, expensive equipment, and security at risk. In order to prevent the introduction of Suspect/Counterfeit Items (S/CI), this information sheet is being made available as a guide to assist in the implementation of S/CI awareness and controls, in conjunction with subcontractor's/supplier's quality assurance programs. When it comes to counterfeit goods, including industrial materials, items, and equipment, no market is immune. Some manufactures have been known to misrepresent their products and intentionally use inferior materials and processes to manufacture substandard items, whose properties can significantlymore » cart from established standards and specifications. These substandard items termed by the Department of Energy (DOE) as S/CI, pose immediate and potential threats to the safety of DOE and contractor workers, the public, and the environment. Failure of certain systems and processes caused by an S/CI could also have national security implications at Los Alamos National Laboratory (LANL). Nuclear Safety Rules (federal Laws), DOE Orders, and other regulations set forth requirements for DOE contractors to implement effective controls to assure that items and services meet specified requirements. This includes techniques to implement and thereby minimizing the potential threat of entry of S/CI to LANL. As a qualified supplier of goods or services to the LANL, your company will be required to establish and maintain effective controls to prevent the introduction of S/CI to LANL. This will require that your company warrant that all items (including their subassemblies, components, and parts) sold to LANL are genuine (i.e. not counterfeit), new, and unused, and conform to the requirements of the LANL purchase orders/contracts unless otherwise approved in writing to the Los Alamos National Security (LANS) contract administrator

Repeated retrieval practice and item difficulty: does criterion learning eliminate item difficulty effects?

PubMed

Vaughn, Kalif E; Rawson, Katherine A; Pyc, Mary A

2013-12-01

A wealth of previous research has established that retrieval practice promotes memory, particularly when retrieval is successful. Although successful retrieval promotes memory, it remains unclear whether successful retrieval promotes memory equally well for items of varying difficulty. Will easy items still outperform difficult items on a final test if all items have been correctly recalled equal numbers of times during practice? In two experiments, normatively difficult and easy Lithuanian-English word pairs were learned via test-restudy practice until each item had been correctly recalled a preassigned number of times (from 1 to 11 correct recalls). Despite equating the numbers of successful recalls during practice, performance on a delayed final cued-recall test was lower for difficult than for easy items. Experiment 2 was designed to diagnose whether the disadvantage for difficult items was due to deficits in cue memory, target memory, and/or associative memory. The results revealed a disadvantage for the difficult versus the easy items only on the associative recognition test, with no differences on cue recognition, and even an advantage on target recognition. Although successful retrieval enhanced memory for both difficult and easy items, equating retrieval success during practice did not eliminate normative item difficulty differences.

Mining Hierarchies and Similarity Clusters from Value Set Repositories.

PubMed

Peterson, Kevin J; Jiang, Guoqian; Brue, Scott M; Shen, Feichen; Liu, Hongfang

2017-01-01

A value set is a collection of permissible values used to describe a specific conceptual domain for a given purpose. By helping to establish a shared semantic understanding across use cases, these artifacts are important enablers of interoperability and data standardization. As the size of repositories cataloging these value sets expand, knowledge management challenges become more pronounced. Specifically, discovering value sets applicable to a given use case may be challenging in a large repository. In this study, we describe methods to extract implicit relationships between value sets, and utilize these relationships to overlay organizational structure onto value set repositories. We successfully extract two different structurings, hierarchy and clustering, and show how tooling can leverage these structures to enable more effective value set discovery.

No Evidence for an Item Limit in Change Detection (Open Access)

DTIC Science & Technology

2013-02-28

memory : a reconsideration of mental storage capacity. Behav Brain Sci 24: 87–114. 17. Eng HY, Chen D, Jiang Y (2005) Visual working memory for simple...working memory can hold no more than a fixed number of items (‘‘item-limit models’’). Recent findings force us to consider the alternative view that working... memory is limited by the precision in stimulus encoding, with mean precision decreasing with increasing set size (‘‘continuous-resource models

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.

POST-MINING DEVELOPMENT USING RESOURCES FROM FLOODED UNDERGROUND MINE WORKINGS

EPA Science Inventory

Post-mining issues of land and surface utilization now serve to accentuate how important it is to incorporate sustainable development aspects into hard rock mining. In an effort to revitalize lands degraded by historic mining, 10 acres of mine tailings near the Belmont Mine have...

Identification of metallic items that caused nickel dermatitis in Danish patients.

PubMed

Thyssen, Jacob P; Menné, Torkil; Johansen, Jeanne D

2010-09-01

Nickel allergy is prevalent as assessed by epidemiological studies. In an attempt to further identify and characterize sources that may result in nickel allergy and dermatitis, we analysed items identified by nickel-allergic dermatitis patients as causative of nickel dermatitis by using the dimethylglyoxime (DMG) test. Dermatitis patients with nickel allergy of current relevance were identified over a 2-year period in a tertiary referral patch test centre. When possible, their work tools and personal items were examined with the DMG test. Among 95 nickel-allergic dermatitis patients, 70 (73.7%) had metallic items investigated for nickel release. A total of 151 items were investigated, and 66 (43.7%) gave positive DMG test reactions. Objects were nearly all purchased or acquired after the introduction of the EU Nickel Directive. Only one object had been inherited, and only two objects had been purchased outside of Denmark. DMG testing is valuable as a screening test for nickel release and should be used to identify relevant exposures in nickel-allergic patients. Mainly consumer items, but also work tools used in an occupational setting, released nickel in dermatitis patients. This study confirmed 'risk items' from previous studies, including mobile phones.

Item response theory analysis of the Pain Self-Efficacy Questionnaire.

PubMed

Costa, Daniel S J; Asghari, Ali; Nicholas, Michael K

2017-01-01

The Pain Self-Efficacy Questionnaire (PSEQ) is a 10-item instrument designed to assess the extent to which a person in pain believes s/he is able to accomplish various activities despite their pain. There is strong evidence for the validity and reliability of both the full-length PSEQ and a 2-item version. The purpose of this study is to further examine the properties of the PSEQ using an item response theory (IRT) approach. We used the two-parameter graded response model to examine the category probability curves, and location and discrimination parameters of the 10 PSEQ items. In item response theory, responses to a set of items are assumed to be probabilistically determined by a latent (unobserved) variable. In the graded-response model specifically, item response threshold (the value of the latent variable for which adjacent response categories are equally likely) and discrimination parameters are estimated for each item. Participants were 1511 mixed, chronic pain patients attending for initial assessment at a tertiary pain management centre. All items except item 7 ('I can cope with my pain without medication') performed well in IRT analysis, and the category probability curves suggested that participants used the 7-point response scale consistently. Items 6 ('I can still do many of the things I enjoy doing, such as hobbies or leisure activity, despite pain'), 8 ('I can still accomplish most of my goals in life, despite the pain') and 9 ('I can live a normal lifestyle, despite the pain') captured higher levels of the latent variable with greater precision. The results from this IRT analysis add to the body of evidence based on classical test theory illustrating the strong psychometric properties of the PSEQ. Despite the relatively poor performance of Item 7, its clinical utility warrants its retention in the questionnaire. The strong psychometric properties of the PSEQ support its use as an effective tool for assessing self-efficacy in people with pain

Interactions Between Item Content And Group Membership on Achievement Test Items.

ERIC Educational Resources Information Center

Linn, Robert L.; Harnisch, Delwyn L.

The purpose of this investigation was to examine the interaction of item content and group membership on achievement test items. Estimates of the parameters of the three parameter logistic model were obtained on the 46 item math test for the sample of eighth grade students (N = 2055) participating in the Illinois Inventory of Educational Progress,…

Item difficulty and item validity for the Children's Group Embedded Figures Test.

PubMed

Rusch, R R; Trigg, C L; Brogan, R; Petriquin, S

1994-02-01

The validity and reliability of the Children's Group Embedded Figures Test was reported for students in Grade 2 by Cromack and Stone in 1980; however, a search of the literature indicates no evidence for internal consistency or item analysis. Hence the purpose of this study was to examine the item difficulty and item validity of the test with children in Grades 1 and 2. Confusion in the literature over development and use of this test was seemingly resolved through analysis of these descriptions and through an interview with the test developer. One early-appearing item was unreasonably difficult. Two or three other items were quite difficult and made little contribution to the total score. Caution is recommended, however, in any reordering or elimination of items based on these findings, given the limited number of subjects (n = 84).

Proceedings: Fourth Workshop on Mining Scientific Datasets

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

Kamath, C

Commercial applications of data mining in areas such as e-commerce, market-basket analysis, text-mining, and web-mining have taken on a central focus in the JCDD community. However, there is a significant amount of innovative data mining work taking place in the context of scientific and engineering applications that is not well represented in the mainstream KDD conferences. For example, scientific data mining techniques are being developed and applied to diverse fields such as remote sensing, physics, chemistry, biology, astronomy, structural mechanics, computational fluid dynamics etc. In these areas, data mining frequently complements and enhances existing analysis methods based on statistics, exploratorymore » data analysis, and domain-specific approaches. On the surface, it may appear that data from one scientific field, say genomics, is very different from another field, such as physics. However, despite their diversity, there is much that is common across the mining of scientific and engineering data. For example, techniques used to identify objects in images are very similar, regardless of whether the images came from a remote sensing application, a physics experiment, an astronomy observation, or a medical study. Further, with data mining being applied to new types of data, such as mesh data from scientific simulations, there is the opportunity to apply and extend data mining to new scientific domains. This one-day workshop brings together data miners analyzing science data and scientists from diverse fields to share their experiences, learn how techniques developed in one field can be applied in another, and better understand some of the newer techniques being developed in the KDD community. This is the fourth workshop on the topic of Mining Scientific Data sets; for information on earlier workshops, see http://www.ahpcrc.org/conferences/. This workshop continues the tradition of addressing challenging problems in a field where the diversity of

30 CFR 77.1712 - Reopening mines; notification; inspection prior to mining.

Code of Federal Regulations, 2010 CFR

2010-07-01

... to mining. 77.1712 Section 77.1712 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... prior to mining. Prior to reopening any surface coal mine after it has been abandoned or declared... an authorized representative of the Secretary before any mining operations in such mine are...

30 CFR 77.1712 - Reopening mines; notification; inspection prior to mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... to mining. 77.1712 Section 77.1712 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION... prior to mining. Prior to reopening any surface coal mine after it has been abandoned or declared... an authorized representative of the Secretary before any mining operations in such mine are...

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.

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.

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.

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.

Differential Item Functioning Analysis Using Rasch Item Information Functions

ERIC Educational Resources Information Center

Wyse, Adam E.; Mapuranga, Raymond

2009-01-01

Differential item functioning (DIF) analysis is a statistical technique used for ensuring the equity and fairness of educational assessments. This study formulates a new DIF analysis method using the information similarity index (ISI). ISI compares item information functions when data fits the Rasch model. Through simulations and an international…

Assessing the Utility of Item Response Theory Models: Differential Item Functioning.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd

The current status of item response theory (IRT) is discussed. Several IRT methods exist for assessing whether an item is biased. Focus is on methods proposed by L. M. Rudner (1975), F. M. Lord (1977), D. Thissen et al. (1988) and R. L. Linn and D. Harnisch (1981). Rudner suggested a measure of the area lying between the two item characteristic…

Identification and Development of Items Comprising Organizational Citizenship Behaviors Among Pharmacy Faculty

PubMed Central

Semsick, Gretchen R.

2016-01-01

Objective. Identify behaviors that can compose a measure of organizational citizenship by pharmacy faculty. Methods. A four-round, modified Delphi procedure using open-ended questions (Round 1) was conducted with 13 panelists from pharmacy academia. The items generated were evaluated and refined for inclusion in subsequent rounds. A consensus was reached after completing four rounds. Results. The panel produced a set of 26 items indicative of extra-role behaviors by faculty colleagues considered to compose a measure of citizenship, which is an expressed manifestation of collegiality. Conclusions. The items generated require testing for validation and reliability in a large sample to create a measure of organizational citizenship. Even prior to doing so, the list of items can serve as a resource for mentorship of junior and senior faculty alike. PMID:28179717

Differential item functioning magnitude and impact measures from item response theory models.

PubMed

Kleinman, Marjorie; Teresi, Jeanne A

2016-01-01

Measures of magnitude and impact of differential item functioning (DIF) at the item and scale level, respectively are presented and reviewed in this paper. Most measures are based on item response theory models. Magnitude refers to item level effect sizes, whereas impact refers to differences between groups at the scale score level. Reviewed are magnitude measures based on group differences in the expected item scores and impact measures based on differences in the expected scale scores. The similarities among these indices are demonstrated. Various software packages are described that provide magnitude and impact measures, and new software presented that computes all of the available statistics conveniently in one program with explanations of their relationships to one another.

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.

Development and community-based validation of eight item banks to assess mental health.

PubMed

Batterham, Philip J; Sunderland, Matthew; Carragher, Natacha; Calear, Alison L

2016-09-30

There is a need for precise but brief screening of mental health problems in a range of settings. The development of item banks to assess depression and anxiety has resulted in new adaptive and static screeners that accurately assess severity of symptoms. However, expansion to a wider array of mental health problems is required. The current study developed item banks for eight mental health problems: social anxiety disorder, panic disorder, post-traumatic stress disorder, obsessive-compulsive disorder, adult attention-deficit hyperactivity disorder, drug use, psychosis and suicidality. The item banks were calibrated in a population-based Australian adult sample (N=3175) by administering large item pools (45-75 items) and excluding items on the basis of local dependence or measurement non-invariance. Item Response Theory parameters were estimated for each item bank using a two-parameter graded response model. Each bank consisted of 19-47 items, demonstrating excellent fit and precision across a range of -1 to 3 standard deviations from the mean. No previous study has developed such a broad range of mental health item banks. The calibrated item banks will form the basis of a new system of static and adaptive measures to screen for a broad array of mental health problems in the community. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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.

Representation of item position in immediate serial recall: Evidence from intrusion errors.

PubMed

Fischer-Baum, Simon; McCloskey, Michael

2015-09-01

In immediate serial recall, participants are asked to recall novel sequences of items in the correct order. Theories of the representations and processes required for this task differ in how order information is maintained; some have argued that order is represented through item-to-item associations, while others have argued that each item is coded for its position in a sequence, with position being defined either by distance from the start of the sequence, or by distance from both the start and the end of the sequence. Previous researchers have used error analyses to adjudicate between these different proposals. However, these previous attempts have not allowed researchers to examine the full set of alternative proposals. In the current study, we analyzed errors produced in 2 immediate serial recall experiments that differ in the modality of input (visual vs. aural presentation of words) and the modality of output (typed vs. spoken responses), using new analysis methods that allow for a greater number of alternative hypotheses to be considered. We find evidence that sequence positions are represented relative to both the start and the end of the sequence, and show a contribution of the end-based representation beyond the final item in the sequence. We also find limited evidence for item-to-item associations, suggesting that both a start-end positional scheme and item-to-item associations play a role in representing item order in immediate serial recall. (c) 2015 APA, all rights reserved).

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.

Item response theory in personality assessment: a demonstration using the MMPI-2 depression scale.

PubMed

Childs, R A; Dahlstrom, W G; Kemp, S M; Panter, A T

2000-03-01

Item response theory (IRT) analyses have, over the past 3 decades, added much to our understanding of the relationships among and characteristics of test items, as revealed in examinees response patterns. Assessment instruments used outside the educational context have only infrequently been analyzed using IRT, however. This study demonstrates the relevance of IRT to personality data through analyses of Scale 2 (the Depression Scale) on the revised Minnesota Multiphasic Personality Inventory (MMPI-2). A rich set of hypotheses regarding the items on this scale, including contrasts among the Harris-Lingoes and Wiener-Harmon subscales and differences in the items measurement characteristics for men and women, are investigated through the IRT analyses.

Empirical Mining of Large Data Sets Already Helps to Solve Practical Ecological Problems; A Panoply of Working Examples (Invited)

NASA Astrophysics Data System (ADS)

Hargrove, W. W.; Hoffman, F. M.; Kumar, J.; Spruce, J.; Norman, S. P.

2013-12-01

Here we present diverse examples where empirical mining and statistical analysis of large data sets have already been shown to be useful for a wide variety of practical decision-making problems within the realm of large-scale ecology. Because a full understanding and appreciation of particular ecological phenomena are possible only after hypothesis-directed research regarding the existence and nature of that process, some ecologists may feel that purely empirical data harvesting may represent a less-than-satisfactory approach. Restricting ourselves exclusively to process-driven approaches, however, may actually slow progress, particularly for more complex or subtle ecological processes. We may not be able to afford the delays caused by such directed approaches. Rather than attempting to formulate and ask every relevant question correctly, empirical methods allow trends, relationships and associations to emerge freely from the data themselves, unencumbered by a priori theories, ideas and prejudices that have been imposed upon them. Although they cannot directly demonstrate causality, empirical methods can be extremely efficient at uncovering strong correlations with intermediate "linking" variables. In practice, these correlative structures and linking variables, once identified, may provide sufficient predictive power to be useful themselves. Such correlation "shadows" of causation can be harnessed by, e.g., Bayesian Belief Nets, which bias ecological management decisions, made with incomplete information, toward favorable outcomes. Empirical data-harvesting also generates a myriad of testable hypotheses regarding processes, some of which may even be correct. Quantitative statistical regionalizations based on quantitative multivariate similarity have lended insights into carbon eddy-flux direction and magnitude, wildfire biophysical conditions, phenological ecoregions useful for vegetation type mapping and monitoring, forest disease risk maps (e.g., sudden oak

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.

The improved Apriori algorithm based on matrix pruning and weight analysis

NASA Astrophysics Data System (ADS)

Lang, Zhenhong

2018-04-01

This paper uses the matrix compression algorithm and weight analysis algorithm for reference and proposes an improved matrix pruning and weight analysis Apriori algorithm. After the transactional database is scanned for only once, the algorithm will construct the boolean transaction matrix. Through the calculation of one figure in the rows and columns of the matrix, the infrequent item set is pruned, and a new candidate item set is formed. Then, the item's weight and the transaction's weight as well as the weight support for items are calculated, thus the frequent item sets are gained. The experimental result shows that the improved Apriori algorithm not only reduces the number of repeated scans of the database, but also improves the efficiency of data correlation mining.

Geophysical Technologies to Image Old Mine Works

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

Kanaan Hanna; Jim Pfeiffer

2007-01-15

ZapataEngineering, Blackhawk Division performed geophysical void detection demonstrations for the US Department of Labor Mine Safety and Health Administration (MSHA). The objective was to advance current state-of-practices of geophysical technologies for detecting underground mine voids. The presence of old mine works above, adjacent, or below an active mine presents major health and safety hazards to miners who have inadvertently cut into locations with such features. In addition, the presence of abandoned mines or voids beneath roadways and highway structures may greatly impact the performance of the transportation infrastructure in terms of cost and public safety. Roads constructed over abandoned minesmore » are subject to potential differential settlement, subsidence, sinkholes, and/or catastrophic collapse. Thus, there is a need to utilize geophysical imaging technologies to accurately locate old mine works. Several surface and borehole geophysical imaging methods and mapping techniques were employed at a known abandoned coal mine in eastern Illinois to investigate which method best map the location and extent of old works. These methods included: 1) high-resolution seismic (HRS) using compressional P-wave (HRPW) and S-wave (HRSW) reflection collected with 3-D techniques; 2) crosshole seismic tomography (XHT); 3) guided waves; 4) reverse vertical seismic profiling (RVSP); and 5) borehole sonar mapping. In addition, several exploration borings were drilled to confirm the presence of the imaged mine voids. The results indicated that the RVSP is the most viable method to accurately detect the subsurface voids with horizontal accuracy of two to five feet. This method was then applied at several other locations in Colorado with various topographic, geologic, and cultural settings for the same purpose. This paper presents the significant results obtained from the geophysical investigations in Illinois.« less

Item Analyses of Memory Differences

PubMed Central

Salthouse, Timothy A.

2017-01-01

Objective Although performance on memory and other cognitive tests is usually assessed with a score aggregated across multiple items, potentially valuable information is also available at the level of individual items. Method The current study illustrates how analyses of variance with item as one of the factors, and memorability analyses in which item accuracy in one group is plotted as a function of item accuracy in another group, can provide a more detailed characterization of the nature of group differences in memory. Data are reported for two memory tasks, word recall and story memory, across age, ability, repetition, delay, and longitudinal contrasts. Results The item-level analyses revealed evidence for largely uniform differences across items in the age, ability, and longitudinal contrasts, but differential patterns across items in the repetition contrast, and unsystematic item relations in the delay contrast. Conclusion Analyses at the level of individual items have the potential to indicate the manner by which group differences in the aggregate test score are achieved. PMID:27618285

Designing P-Optimal Item Pools in Computerized Adaptive Tests with Polytomous Items

ERIC Educational Resources Information Center

Zhou, Xuechun

2012-01-01

Current CAT applications consist of predominantly dichotomous items, and CATs with polytomously scored items are limited. To ascertain the best approach to polytomous CAT, a significant amount of research has been conducted on item selection, ability estimation, and impact of termination rules based on polytomous IRT models. Few studies…

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.

Metropolis-Hastings Robbins-Monro Algorithm for Confirmatory Item Factor Analysis

ERIC Educational Resources Information Center

Cai, Li

2010-01-01

Item factor analysis (IFA), already well established in educational measurement, is increasingly applied to psychological measurement in research settings. However, high-dimensional confirmatory IFA remains a numerical challenge. The current research extends the Metropolis-Hastings Robbins-Monro (MH-RM) algorithm, initially proposed for…

Dimensionality Assessment for Dichotomously Scored Items Using Multidimensional Scaling.

ERIC Educational Resources Information Center

Jones, Patricia B.; And Others

In order to determine the effectiveness of multidimensional scaling (MDS) in recovering the dimensionality of a set of dichotomously-scored items, data were simulated in one, two, and three dimensions for a variety of correlations with the underlying latent trait. Similarity matrices were constructed from these data using three margin-sensitive…

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.

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…

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.

Identifying content for the glaucoma-specific item bank to measure quality-of-life parameters.

PubMed

Khadka, Jyoti; McAlinden, Colm; Craig, Jamie E; Fenwick, Eva K; Lamoureux, Ecosse L; Pesudovs, Konrad

2015-01-01

Patient-reported outcomes (PROs) have become essential clinical trial end points. However, a comprehensive, multidimensional, patient-relevant, and precise glaucoma-specific PRO instrument is not available. Therefore, the purpose of this study was to identify content for a new, glaucoma-specific, quality-of-life (QOL) item bank. Content identification was undertaken in 5 phases: (1) identification of extant items in glaucoma-specific instruments and the qualitative literature; (2) focus groups and interviews with glaucoma patients; (3) item classification and selection; (4) expert review and revision of items; and (5) cognitive interviews with patients. A total of 737 unique items (extant items from PRO instruments, 247; qualitative articles, 14 items; focus groups and semistructured interviews, 476 items) were identified. These items were classified into 10 QOL domains. Four criteria (item redundancy, item inconsistent with domain definition, item content too narrow to have wider applicability, and item clarity) were used to remove and refine the items. After the cognitive interviews, the final minimally representative item set had a total of 342 unique items belonging to 10 domains: activity limitation (88), mobility (20), visual symptoms (19), ocular surface symptoms (22), general symptoms (15), convenience (39), health concerns (45), emotional well-being (49), social issues (23), and economic issues (22). The systematic content identification process identified 10 QOL domains, which were important to patients with glaucoma. The majority of the items were identified from the patient-specific focus groups and semistructured interviews suggesting that the existing PRO instruments do not adequately address QOL issues relevant to individuals with glaucoma.

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)

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.

Evolution of a Test Item

ERIC Educational Resources Information Center

Spaan, Mary

2007-01-01

This article follows the development of test items (see "Language Assessment Quarterly", Volume 3 Issue 1, pp. 71-79 for the article "Test and Item Specifications Development"), beginning with a review of test and item specifications, then proceeding to writing and editing of items, pretesting and analysis, and finally selection of an item for a…

Item Banking. ERIC/AE Digest.

ERIC Educational Resources Information Center

Rudner, Lawrence

This digest discusses the advantages and disadvantages of using item banks, and it provides useful information for those who are considering implementing an item banking project in their school districts. The primary advantage of item banking is in test development. Using an item response theory method, such as the Rasch model, items from multiple…

Effects of spacing of item repetitions in continuous recognition memory: does item retrieval difficulty promote item retention in older adults?

PubMed

Kılıç, Aslı; Hoyer, William J; Howard, Marc W

2013-01-01

BACKGROUND/STUDY CONTEXT: Older adults exhibit an age-related deficit in item memory as a function of the length of the retention interval, but older adults and young adults usually show roughly equivalent benefits due to the spacing of item repetitions in continuous memory tasks. The current experiment investigates the seemingly paradoxical effects of retention interval and spacing in young and older adults using a continuous recognition memory procedure. Fifty young adults and 52 older adults gave memory confidence ratings to words that were presented once (P1), twice (P2), or three times (P3), and the effects of the lag length and retention interval were assessed at P2 and at P3, respectively. Response times at P2 were disproportionately longer for older adults than for younger adults as a function of the number of items occurring between P1 and P2, suggestive of age-related loss in item memory. Ratings of confidence in memory responses revealed that older adults remembered fewer items at P2 with a high degree of certainty. Confidence ratings given at P3 suggested that young and older adults derived equivalent benefits from the spacing between P1 and P2. Findings of this study support theoretical accounts that suggest that recursive reminding and/or item retrieval difficulty promote item retention in older adults.

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.

Development of an item bank and computer adaptive test for role functioning.

PubMed

Anatchkova, Milena D; Rose, Matthias; Ware, John E; Bjorner, Jakob B

2012-11-01

Role functioning (RF) is a key component of health and well-being and an important outcome in health research. The aim of this study was to develop an item bank to measure impact of health on role functioning. A set of different instruments including 75 newly developed items asking about the impact of health on role functioning was completed by 2,500 participants. Established item response theory methods were used to develop an item bank based on the generalized partial credit model. Comparison of group mean bank scores of participants with different self-reported general health status and chronic conditions was used to test the external validity of the bank. After excluding items that did not meet established requirements, the final item bank consisted of a total of 64 items covering three areas of role functioning (family, social, and occupational). Slopes in the bank ranged between .93 and 4.37; the mean threshold range was -1.09 to -2.25. Item bank-based scores were significantly different for participants with and without chronic conditions and with different levels of self-reported general health. An item bank assessing health impact on RF across three content areas has been successfully developed. The bank can be used for development of short forms or computerized adaptive tests to be applied in the assessment of role functioning as one of the common denominators across applications of generic health assessment.

Hydrological and geophysical investigation of streamflow losses and restoration strategies in an abandoned mine lands setting

USGS Publications Warehouse

Cravotta, Charles A.; Sherrod, Laura; Galeone, Daniel G.; Lehman, Wayne G.; Ackman, Terry E.; Kramer, Alexa

2017-01-01

Longitudinal discharge and water-quality campaigns (seepage runs) were combined with surface-geophysical surveys, hyporheic-temperature profiling, and watershed-scale hydrological monitoring to evaluate the locations, magnitude, and impact of streamwater losses from the West Creek subbasin of the West West Branch Schuylkill River into the underground Oak Hill Mine complex that extends beneath the watershed divide. Abandoned mine drainage (AMD), containing iron and other contaminants, from the Oak Hill Boreholes to the West Branch Schuylkill River was sustained during low-flow conditions and correlated to streamflow lost through the West Creek streambed. During high-flow conditions, streamflow was transmitted throughout West Creek; however, during low-flow conditions, all streamflow from the perennial headwaters was lost within the 300-to-600-m "upper reach" where an 1889 mine map indicated steeply dipping coalbeds underlie the channel. During low-flow conditions, the channel within the "intermediate reach" 700-to-1650-m downstream gained groundwater seepage with higher pH and specific conductance than upstream; however, all streamflow 1650-to-2050-m downstream was lost to underlying mines. Electrical resistivity and electromagnetic conductivity surveys indicated conductive zones beneath the upper reach, where flow loss occurred, and through the intermediate reach, where gains and losses occurred. Temperature probes at 0.06-to-0.10-m depth within the hyporheic zone of the intermediate reach indicated potential downward fluxes as high as 2.1x10-5 m/s. Cumulative streamflow lost from West Creek during seepage runs averaged 53.4 L/s, which equates to 19.3 percent of the daily average discharge of AMD from the Oak Hill Boreholes and a downward flux of 1.70x10-5 m/s across the 2.1-km-by-1.5-m West Creek stream-channel area.

Inverse MDS: Inferring Dissimilarity Structure from Multiple Item Arrangements

PubMed Central

Kriegeskorte, Nikolaus; Mur, Marieke

2012-01-01

The pairwise dissimilarities of a set of items can be intuitively visualized by a 2D arrangement of the items, in which the distances reflect the dissimilarities. Such an arrangement can be obtained by multidimensional scaling (MDS). We propose a method for the inverse process: inferring the pairwise dissimilarities from multiple 2D arrangements of items. Perceptual dissimilarities are classically measured using pairwise dissimilarity judgments. However, alternative methods including free sorting and 2D arrangements have previously been proposed. The present proposal is novel (a) in that the dissimilarity matrix is estimated by “inverse MDS” based on multiple arrangements of item subsets, and (b) in that the subsets are designed by an adaptive algorithm that aims to provide optimal evidence for the dissimilarity estimates. The subject arranges the items (represented as icons on a computer screen) by means of mouse drag-and-drop operations. The multi-arrangement method can be construed as a generalization of simpler methods: It reduces to pairwise dissimilarity judgments if each arrangement contains only two items, and to free sorting if the items are categorically arranged into discrete piles. Multi-arrangement combines the advantages of these methods. It is efficient (because the subject communicates many dissimilarity judgments with each mouse drag), psychologically attractive (because dissimilarities are judged in context), and can characterize continuous high-dimensional dissimilarity structures. We present two procedures for estimating the dissimilarity matrix: a simple weighted-aligned-average of the partial dissimilarity matrices and a computationally intensive algorithm, which estimates the dissimilarity matrix by iteratively minimizing the error of MDS-predictions of the subject’s arrangements. The Matlab code for interactive arrangement and dissimilarity estimation is available from the authors upon request. PMID:22848204

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.

Item Response Theory analysis of Fagerström Test for Cigarette Dependence.

PubMed

Svicher, Andrea; Cosci, Fiammetta; Giannini, Marco; Pistelli, Francesco; Fagerström, Karl

2018-02-01

The Fagerström Test for Cigarette Dependence (FTCD) and the Heaviness of Smoking Index (HSI) are the gold standard measures to assess cigarette dependence. However, FTCD reliability and factor structure have been questioned and HSI psychometric properties are in need of further investigations. The present study examined the psychometrics properties of the FTCD and the HSI via the Item Response Theory. The study was a secondary analysis of data collected in 862 Italian daily smokers. Confirmatory factor analysis was run to evaluate the dimensionality of FTCD. A Grade Response Model was applied to FTCD and HSI to verify the fit to the data. Both item and test functioning were analyzed and item statistics, Test Information Function, and scale reliabilities were calculated. Mokken Scale Analysis was applied to estimate homogeneity and Loevinger's coefficients were calculated. The FTCD showed unidimensionality and homogeneity for most of the items and for the total score. It also showed high sensitivity and good reliability from medium to high levels of cigarette dependence, although problems related to some items (i.e., items 3 and 5) were evident. HSI had good homogeneity, adequate item functioning, and high reliability from medium to high levels of cigarette dependence. Significant Differential Item Functioning was found for items 1, 4, 5 of the FTCD and for both items of HSI. HSI seems highly recommended in clinical settings addressed to heavy smokers while FTCD would be better used in smokers with a level of cigarette dependence ranging between low and high. Copyright © 2017 Elsevier Ltd. All rights reserved.

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).

A Procedure to Detect Item Bias Present Simultaneously in Several Items

DTIC Science & Technology

1991-04-25

exhibit a coherent and major biasing influence at the test level. In partic- ular, this can be true even if each individual item displays only a minor...response functions (IRFs) without the use of item parameter estimation algorithms when the sample size is too small for their use. Thissen, Steinberg...convention). A random sample of examinees is drawn from each group, and a test of N items is administered to them. Typically it is suspected that a

Developing an Interpretation of Item Parameters for Personality Items: Content Correlates of Parameter Estimates.

ERIC Educational Resources Information Center

Zickar, Michael J.; Ury, Karen L.

2002-01-01

Attempted to relate content features of personality items to item parameter estimates from the partial credit model of E. Muraki (1990) by administering the Adjective Checklist (L. Goldberg, 1992) to 329 undergraduates. As predicted, the discrimination parameter was related to the item subtlety ratings of personality items but the level of word…

On an Extension of the Rasch Model to the Case of Polychotomously Scored Items.

ERIC Educational Resources Information Center

Vogt, Dorothee K.

The Rasch model for the probability of a person's response to an item is extended to the case where this response depends on a set of scoring or category weights, in addition to person and item parameters. The maximum likelihood approach introduced by Wright for the dichotomous case is applicable here also, and it is shown to yield a unique…

Trust Mines

EPA Pesticide Factsheets

The United States and the Navajo Nation entered into settlement agreements that provide funds to conduct investigations and any needed cleanup at 16 of the 46 priority mines, including six mines in the Northern Abandoned Uranium Mine Region.

Expertise sensitive item selection.

PubMed

Chow, P; Russell, H; Traub, R E

2000-12-01

In this paper we describe and illustrate a procedure for selecting items from a large pool for a certification test. The proposed procedure, which is intended to improve the alignment of the certification test with on-the-job performance, is based on an expertise sensitive index. This index for an item is the difference between the item's p values for experts and novices. An example is provided of the application of the index for selecting items to be used in certifying bakers.

Development of six PROMIS pediatrics proxy-report item banks

PubMed Central

2012-01-01

diagnosed or treated within 6 months prior to the interview. The PROMIS proxy sample scored similar or better on the other proxy instruments compared to normative samples. Conclusions The initial calibration data was provided by a diverse set of caregivers of children with a variety of common chronic illnesses and racial/ethnic backgrounds. The PROMIS pediatric proxy-report item banks include physical function (mobility n = 23; upper extremity n = 29), emotional distress (anxiety n = 15; depressive symptoms n = 14; anger n = 5), social peer relationships (n = 15), fatigue (n = 34), pain interference (n = 13), and asthma impact (n = 17). PMID:22357192

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...

Pricing policy for declining demand using item preservation technology.

PubMed

Khedlekar, Uttam Kumar; Shukla, Diwakar; Namdeo, Anubhav

2016-01-01

We have designed an inventory model for seasonal products in which deterioration can be controlled by item preservation technology investment. Demand for the product is considered price sensitive and decreases linearly. This study has shown that the profit is a concave function of optimal selling price, replenishment time and preservation cost parameter. We simultaneously determined the optimal selling price of the product, the replenishment cycle and the cost of item preservation technology. Additionally, this study has shown that there exists an optimal selling price and optimal preservation investment to maximize the profit for every business set-up. Finally, the model is illustrated by numerical examples and sensitive analysis of the optimal solution with respect to major parameters.

On Bayesian Rules for Selecting 3PL Binary Items for Criterion-Referenced Interpretations and Creating Booklets for Bookmark Standard Setting.

ERIC Educational Resources Information Center

Huynh, Huynh

By noting that a Rasch or two parameter logistic (2PL) item belongs to the exponential family of random variables and that the probability density function (pdf) of the correct response (X=1) and the incorrect response (X=0) are symmetric with respect to the vertical line at the item location, it is shown that the conjugate prior for ability is…

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.

Instructional Topics in Educational Measurement (ITEMS) Module: Using Automated Processes to Generate Test Items

ERIC Educational Resources Information Center

Gierl, Mark J.; Lai, Hollis

2013-01-01

Changes to the design and development of our educational assessments are resulting in the unprecedented demand for a large and continuous supply of content-specific test items. One way to address this growing demand is with automatic item generation (AIG). AIG is the process of using item models to generate test items with the aid of computer…

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…

Optimal ordering quantities for substitutable deteriorating items under joint replenishment with cost of substitution

NASA Astrophysics Data System (ADS)

Mishra, Vinod Kumar

2017-09-01

In this paper we develop an inventory model, to determine the optimal ordering quantities, for a set of two substitutable deteriorating items. In this inventory model the inventory level of both items depleted due to demands and deterioration and when an item is out of stock, its demands are partially fulfilled by the other item and all unsatisfied demand is lost. Each substituted item incurs a cost of substitution and the demands and deterioration is considered to be deterministic and constant. Items are order jointly in each ordering cycle, to take the advantages of joint replenishment. The problem is formulated and a solution procedure is developed to determine the optimal ordering quantities that minimize the total inventory cost. We provide an extensive numerical and sensitivity analysis to illustrate the effect of different parameter on the model. The key observation on the basis of numerical analysis, there is substantial improvement in the optimal total cost of the inventory model with substitution over without substitution.

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.

Biomedical text mining and its applications in cancer research.

PubMed

Zhu, Fei; Patumcharoenpol, Preecha; Zhang, Cheng; Yang, Yang; Chan, Jonathan; Meechai, Asawin; Vongsangnak, Wanwipa; Shen, Bairong

2013-04-01

Cancer is a malignant disease that has caused millions of human deaths. Its study has a long history of well over 100years. There have been an enormous number of publications on cancer research. This integrated but unstructured biomedical text is of great value for cancer diagnostics, treatment, and prevention. The immense body and rapid growth of biomedical text on cancer has led to the appearance of a large number of text mining techniques aimed at extracting novel knowledge from scientific text. Biomedical text mining on cancer research is computationally automatic and high-throughput in nature. However, it is error-prone due to the complexity of natural language processing. In this review, we introduce the basic concepts underlying text mining and examine some frequently used algorithms, tools, and data sets, as well as assessing how much these algorithms have been utilized. We then discuss the current state-of-the-art text mining applications in cancer research and we also provide some resources for cancer text mining. With the development of systems biology, researchers tend to understand complex biomedical systems from a systems biology viewpoint. Thus, the full utilization of text mining to facilitate cancer systems biology research is fast becoming a major concern. To address this issue, we describe the general workflow of text mining in cancer systems biology and each phase of the workflow. We hope that this review can (i) provide a useful overview of the current work of this field; (ii) help researchers to choose text mining tools and datasets; and (iii) highlight how to apply text mining to assist cancer systems biology research. Copyright © 2012 Elsevier Inc. All rights reserved.

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…

Using Likert-type and ipsative/forced choice items in sequence to generate a preference.

PubMed

Ried, L Douglas

2014-01-01

Collaboration and implementation of a minimum, standardized set of core global educational and professional competencies seems appropriate given the expanding international evolution of pharmacy practice. However, winnowing down hundreds of competencies from a plethora of local, national and international competency frameworks to select the most highly preferred to be included in the core set is a daunting task. The objective of this paper is to describe a combination of strategies used to ascertain the most highly preferred items among a large number of disparate items. In this case, the items were >100 educational and professional competencies that might be incorporated as the core components of new and existing competency frameworks. Panelists (n = 30) from the European Union (EU) and United States (USA) were chosen to reflect a variety of practice settings. Each panelist completed two electronic surveys. The first survey presented competencies in a Likert-type format and the second survey presented many of the same competencies in an ipsative/forced choice format. Item mean scores were calculated for each competency, the competencies were ranked, and non-parametric statistical tests were used to ascertain the consistency in the rankings achieved by the two strategies. This exploratory study presented over 100 competencies to the panelists in the beginning. The two methods provided similar results, as indicated by the significant correlation between the rankings (Spearman's rho = 0.30, P < 0.09). A two-step strategy using Likert-type and ipsative/forced choice formats in sequence, appears to be useful in a situation where a clear preference is required from among a large number of choices. The ipsative/forced choice format resulted in some differences in the competency preferences because the panelists could not rate them equally by design. While this strategy was used for the selection of professional educational competencies in this exploratory study, it is

The five item Barthel index

PubMed Central

Hobart, J; Thompson, A

2001-01-01

OBJECTIVES—Routine data collection is now considered mandatory. Therefore, staff rated clinical scales that consist of multiple items should have the minimum number of items necessary for rigorous measurement. This study explores the possibility of developing a short form Barthel index, suitable for use in clinical trials, epidemiological studies, and audit, that satisfies criteria for rigorous measurement and is psychometrically equivalent to the 10 item instrument.
METHODS—Data were analysed from 844 consecutive admissions to a neurological rehabilitation unit in London. Random half samples were generated. Short forms were developed in one sample (n=419), by selecting items with the best measurement properties, and tested in the other (n=418). For each of the 10 items of the BI, item total correlations and effect sizes were computed and rank ordered. The best items were defined as those with the lowest cross product of these rank orderings. The acceptability, reliability, validity, and responsiveness of three short form BIs (five, four, and three item) were determined and compared with the 10 item BI. Agreement between scores generated by short forms and 10 item BI was determined using intraclass correlation coefficients and the method of Bland and Altman.
RESULTS—The five best items in this sample were transfers, bathing, toilet use, stairs, and mobility. Of the three short forms examined, the five item BI had the best measurement properties and was psychometrically equivalent to the 10 item BI. Agreement between scores generated by the two measures for individual patients was excellent (ICC=0.90) but not identical (limits of agreement=1.84±3.84).
CONCLUSIONS—The five item short form BI may be a suitable outcome measure for group comparison studies in comparable samples. Further evaluations are needed. Results demonstrate a fundamental difference between assessment and measurement and the importance of incorporating psychometric methods in the

Computerized Adaptive Test (CAT) Applications and Item Response Theory Models for Polytomous Items

ERIC Educational Resources Information Center

Aybek, Eren Can; Demirtasli, R. Nukhet

2017-01-01

This article aims to provide a theoretical framework for computerized adaptive tests (CAT) and item response theory models for polytomous items. Besides that, it aims to introduce the simulation and live CAT software to the related researchers. Computerized adaptive test algorithm, assumptions of item response theory models, nominal response…

Design Patterns for Digital Item Types in Higher Education

ERIC Educational Resources Information Center

Draaijer, S.; Hartog, R. J. M.

2007-01-01

A set of design patterns for digital item types has been developed in response to challenges identified in various projects by teachers in higher education. The goal of the projects in question was to design and develop formative and summative tests, and to develop interactive learning material in the form of quizzes. The subject domains involved…

Item development process and analysis of 50 case-based items for implementation on the Korean Nursing Licensing Examination.

PubMed

Park, In Sook; Suh, Yeon Ok; Park, Hae Sook; Kang, So Young; Kim, Kwang Sung; Kim, Gyung Hee; Choi, Yeon-Hee; Kim, Hyun-Ju

2017-01-01

The purpose of this study was to improve the quality of items on the Korean Nursing Licensing Examination by developing and evaluating case-based items that reflect integrated nursing knowledge. We conducted a cross-sectional observational study to develop new case-based items. The methods for developing test items included expert workshops, brainstorming, and verification of content validity. After a mock examination of undergraduate nursing students using the newly developed case-based items, we evaluated the appropriateness of the items through classical test theory and item response theory. A total of 50 case-based items were developed for the mock examination, and content validity was evaluated. The question items integrated 34 discrete elements of integrated nursing knowledge. The mock examination was taken by 741 baccalaureate students in their fourth year of study at 13 universities. Their average score on the mock examination was 57.4, and the examination showed a reliability of 0.40. According to classical test theory, the average level of item difficulty of the items was 57.4% (80%-100% for 12 items; 60%-80% for 13 items; and less than 60% for 25 items). The mean discrimination index was 0.19, and was above 0.30 for 11 items and 0.20 to 0.29 for 15 items. According to item response theory, the item discrimination parameter (in the logistic model) was none for 10 items (0.00), very low for 20 items (0.01 to 0.34), low for 12 items (0.35 to 0.64), moderate for 6 items (0.65 to 1.34), high for 1 item (1.35 to 1.69), and very high for 1 item (above 1.70). The item difficulty was very easy for 24 items (below -2.0), easy for 8 items (-2.0 to -0.5), medium for 6 items (-0.5 to 0.5), hard for 3 items (0.5 to 2.0), and very hard for 9 items (2.0 or above). The goodness-of-fit test in terms of the 2-parameter item response model between the range of 2.0 to 0.5 revealed that 12 items had an ideal correct answer rate. We surmised that the low reliability of the

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.

Selecting Items for Criterion-Referenced Tests.

ERIC Educational Resources Information Center

Mellenbergh, Gideon J.; van der Linden, Wim J.

1982-01-01

Three item selection methods for criterion-referenced tests are examined: the classical theory of item difficulty and item-test correlation; the latent trait theory of item characteristic curves; and a decision-theoretic approach for optimal item selection. Item contribution to the standardized expected utility of mastery testing is discussed. (CM)

Geriatric Anxiety Scale: item response theory analysis, differential item functioning, and creation of a ten-item short form (GAS-10).

PubMed

Mueller, Anne E; Segal, Daniel L; Gavett, Brandon; Marty, Meghan A; Yochim, Brian; June, Andrea; Coolidge, Frederick L

2015-07-01

The Geriatric Anxiety Scale (GAS; Segal et al. (Segal, D. L., June, A., Payne, M., Coolidge, F. L. and Yochim, B. (2010). Journal of Anxiety Disorders, 24, 709-714. doi:10.1016/j.janxdis.2010.05.002) is a self-report measure of anxiety that was designed to address unique issues associated with anxiety assessment in older adults. This study is the first to use item response theory (IRT) to examine the psychometric properties of a measure of anxiety in older adults. A large sample of older adults (n = 581; mean age = 72.32 years, SD = 7.64 years, range = 60 to 96 years; 64% women; 88% European American) completed the GAS. IRT properties were examined. The presence of differential item functioning (DIF) or measurement bias by age and sex was assessed, and a ten-item short form of the GAS (called the GAS-10) was created. All GAS items had discrimination parameters of 1.07 or greater. Items from the somatic subscale tended to have lower discrimination parameters than items on the cognitive or affective subscales. Two items were flagged for DIF, but the impact of the DIF was negligible. Women scored significantly higher than men on the GAS and its subscales. Participants in the young-old group (60 to 79 years old) scored significantly higher on the cognitive subscale than participants in the old-old group (80 years old and older). Results from the IRT analyses indicated that the GAS and GAS-10 have strong psychometric properties among older adults. We conclude by discussing implications and future research directions.

Asymptotic Standard Errors for Item Response Theory True Score Equating of Polytomous Items

ERIC Educational Resources Information Center

Cher Wong, Cheow

2015-01-01

Building on previous works by Lord and Ogasawara for dichotomous items, this article proposes an approach to derive the asymptotic standard errors of item response theory true score equating involving polytomous items, for equivalent and nonequivalent groups of examinees. This analytical approach could be used in place of empirical methods like…

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.

Data Mining Web Services for Science Data Repositories

NASA Astrophysics Data System (ADS)

Graves, S.; Ramachandran, R.; Keiser, K.; Maskey, M.; Lynnes, C.; Pham, L.

2006-12-01

The maturation of web services standards and technologies sets the stage for a distributed "Service-Oriented Architecture" (SOA) for NASA's next generation science data processing. This architecture will allow members of the scientific community to create and combine persistent distributed data processing services and make them available to other users over the Internet. NASA has initiated a project to create a suite of specialized data mining web services designed specifically for science data. The project leverages the Algorithm Development and Mining (ADaM) toolkit as its basis. The ADaM toolkit is a robust, mature and freely available science data mining toolkit that is being used by several research organizations and educational institutions worldwide. These mining services will give the scientific community a powerful and versatile data mining capability that can be used to create higher order products such as thematic maps from current and future NASA satellite data records with methods that are not currently available. The package of mining and related services are being developed using Web Services standards so that community-based measurement processing systems can access and interoperate with them. These standards-based services allow users different options for utilizing them, from direct remote invocation by a client application to deployment of a Business Process Execution Language (BPEL) solutions package where a complex data mining workflow is exposed to others as a single service. The ability to deploy and operate these services at a data archive allows the data mining algorithms to be run where the data are stored, a more efficient scenario than moving large amounts of data over the network. This will be demonstrated in a scenario in which a user uses a remote Web-Service-enabled clustering algorithm to create cloud masks from satellite imagery at the Goddard Earth Sciences Data and Information Services Center (GES DISC).

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.

MIMIC Methods for Assessing Differential Item Functioning in Polytomous Items

ERIC Educational Resources Information Center

Wang, Wen-Chung; Shih, Ching-Lin

2010-01-01

Three multiple indicators-multiple causes (MIMIC) methods, namely, the standard MIMIC method (M-ST), the MIMIC method with scale purification (M-SP), and the MIMIC method with a pure anchor (M-PA), were developed to assess differential item functioning (DIF) in polytomous items. In a series of simulations, it appeared that all three methods…

Data Mining.

ERIC Educational Resources Information Center

Benoit, Gerald

2002-01-01

Discusses data mining (DM) and knowledge discovery in databases (KDD), taking the view that KDD is the larger view of the entire process, with DM emphasizing the cleaning, warehousing, mining, and visualization of knowledge discovery in databases. Highlights include algorithms; users; the Internet; text mining; and information extraction.…

Random Item IRT Models

ERIC Educational Resources Information Center

De Boeck, Paul

2008-01-01

It is common practice in IRT to consider items as fixed and persons as random. Both, continuous and categorical person parameters are most often random variables, whereas for items only continuous parameters are used and they are commonly of the fixed type, although exceptions occur. It is shown in the present article that random item parameters…

Ramsay-Curve Item Response Theory for the Three-Parameter Logistic Item Response Model

ERIC Educational Resources Information Center

Woods, Carol M.

2008-01-01

In Ramsay-curve item response theory (RC-IRT), the latent variable distribution is estimated simultaneously with the item parameters of a unidimensional item response model using marginal maximum likelihood estimation. This study evaluates RC-IRT for the three-parameter logistic (3PL) model with comparisons to the normal model and to the empirical…

Evaluation of Northwest University, Kano Post-UTME Test Items Using Item Response Theory

ERIC Educational Resources Information Center

Bichi, Ado Abdu; Hafiz, Hadiza; Bello, Samira Abdullahi

2016-01-01

High-stakes testing is used for the purposes of providing results that have important consequences. Validity is the cornerstone upon which all measurement systems are built. This study applied the Item Response Theory principles to analyse Northwest University Kano Post-UTME Economics test items. The developed fifty (50) economics test items was…

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2014 CFR

2014-07-01

... 30 Mineral Resources 1 2014-07-01 2014-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2012 CFR

2012-07-01

... 30 Mineral Resources 1 2012-07-01 2012-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2013 CFR

2013-07-01

... 30 Mineral Resources 1 2013-07-01 2013-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS Mine Rescue Teams for Underground Metal and...

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…

Is the Factor Observed in Investigations on the Item-Position Effect Actually the Difficulty Factor?

PubMed

Schweizer, Karl; Troche, Stefan

2018-02-01

In confirmatory factor analysis quite similar models of measurement serve the detection of the difficulty factor and the factor due to the item-position effect. The item-position effect refers to the increasing dependency among the responses to successively presented items of a test whereas the difficulty factor is ascribed to the wide range of item difficulties. The similarity of the models of measurement hampers the dissociation of these factors. Since the item-position effect should theoretically be independent of the item difficulties, the statistical ex post manipulation of the difficulties should enable the discrimination of the two types of factors. This method was investigated in two studies. In the first study, Advanced Progressive Matrices (APM) data of 300 participants were investigated. As expected, the factor thought to be due to the item-position effect was observed. In the second study, using data simulated to show the major characteristics of the APM data, the wide range of items with various difficulties was set to zero to reduce the likelihood of detecting the difficulty factor. Despite this reduction, however, the factor now identified as item-position factor, was observed in virtually all simulated datasets.

Using Differential Item Functioning Procedures to Explore Sources of Item Difficulty and Group Performance Characteristics.

ERIC Educational Resources Information Center

Scheuneman, Janice Dowd; Gerritz, Kalle

1990-01-01

Differential item functioning (DIF) methodology for revealing sources of item difficulty and performance characteristics of different groups was explored. A total of 150 Scholastic Aptitude Test items and 132 Graduate Record Examination general test items were analyzed. DIF was evaluated for males and females and Blacks and Whites. (SLD)

Correlates of a Single-Item Indicator Versus a Multi-Item Scale of Outness About Same-Sex Attraction

PubMed Central

Noor, Syed W.; Galos, Dylan L.; Simon Rosser, B. R.

2017-01-01

In this study, we investigated if a single-item indicator measured the degree to which people were open about their same-sex attraction (“out”) as accurately as a multi-item scale. For the multi-item scale, we used the Outness Inventory, which includes three subscales: family, world, and religion. We examined correlations between the single- and multi-item measures; between the single-item indicator and the subscales of the multi-item scale; and between the measures and internalized homonegativity, social attitudes towards homosexuality, and depressive symptoms. In addition, we calculated Tjur’s R2 as a measure of predictive power of the single-item indicator, multi-item scale, and subscales of the multi-item scale in predicting two health-related outcomes: depressive symptoms and condomless anal sex with multiple partners. There was a strong correlation between the single- and multi-item measures (r = 0.73). Furthermore, there were strong correlations between the single-item indicator and each subscale of the multi-item scale: family (r = 0.70), world (r = 0.77), and religion (r = 0.50). In addition, the correlations between the single-item indicator and internalized homonegativity (r = −0.63), social attitudes towards homosexuality (r = −0.38), and depression (r = −0.14) were higher than those between the multi-item scale and internalized homonegativity (r = −0.55), social attitudes towards homosexuality (r = −0.21), and depression (r = −0.13). Contrary to the premise that multi-item measures are superior to single-item measures, our collective findings indicate that the single-item indicator of outness performs better than the multi-item scale of outness. PMID:26292840

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.

Development and assessment of floor and ceiling items for the PROMIS physical function item bank

PubMed Central

2013-01-01

Introduction Disability and Physical Function (PF) outcome assessment has had limited ability to measure functional status at the floor (very poor functional abilities) or the ceiling (very high functional abilities). We sought to identify, develop and evaluate new floor and ceiling items to enable broader and more precise assessment of PF outcomes for the NIH Patient-Reported-Outcomes Measurement Information System (PROMIS). Methods We conducted two cross-sectional studies using NIH PROMIS item improvement protocols with expert review, participant survey and focus group methods. In Study 1, respondents with low PF abilities evaluated new floor items, and those with high PF abilities evaluated new ceiling items for clarity, importance and relevance. In Study 2, we compared difficulty ratings of new floor items by low functioning respondents and ceiling items by high functioning respondents to reference PROMIS PF-10 items. We used frequencies, percentages, means and standard deviations to analyze the data. Results In Study 1, low (n = 84) and high (n = 90) functioning respondents were mostly White, women, 70 years old, with some college, and disability scores of 0.62 and 0.30. More than 90% of the 31 new floor and 31 new ceiling items were rated as clear, important and relevant, leaving 26 ceiling and 30 floor items for Study 2. Low (n = 246) and high (n = 637) functioning Study 2 respondents were mostly White, women, 70 years old, with some college, and Health Assessment Questionnaire (HAQ) scores of 1.62 and 0.003. Compared to difficulty ratings of reference items, ceiling items were rated to be 10% more to greater than 40% more difficult to do, and floor items were rated to be about 12% to nearly 90% less difficult to do. Conclusions These new floor and ceiling items considerably extend the measurable range of physical function at either extreme. They will help improve instrument performance in populations with broad functional ranges and those concentrated at

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2010 CFR

2010-07-01

... 30 Mineral Resources 1 2010-07-01 2010-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS § 49.4 Alternative mine rescue capability for...

30 CFR 49.4 - Alternative mine rescue capability for special mining conditions.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 1 2011-07-01 2011-07-01 false Alternative mine rescue capability for special mining conditions. 49.4 Section 49.4 Mineral Resources MINE SAFETY AND HEALTH ADMINISTRATION, DEPARTMENT OF LABOR EDUCATION AND TRAINING MINE RESCUE TEAMS § 49.4 Alternative mine rescue capability for...

PREVENTION OF ACID MINE DRAINAGE GENERATION FROM OPEN-PIT MINE HIGHWALLS

EPA Science Inventory

Exposed, open pit mine highwalls contribute significantly to the production of acid mine

drainage (AMD) thus causing environmental concerns upon closure of an operating mine. Available information on the generation of AMD from open-pit mine highwalls is very limit...

30 CFR 780.27 - Reclamation plan: Surface mining near underground mining.

Code of Federal Regulations, 2011 CFR

2011-07-01

... 30 Mineral Resources 3 2011-07-01 2011-07-01 false Reclamation plan: Surface mining near underground mining. 780.27 Section 780.27 Mineral Resources OFFICE OF SURFACE MINING RECLAMATION AND ENFORCEMENT, DEPARTMENT OF THE INTERIOR SURFACE COAL MINING AND RECLAMATION OPERATIONS PERMITS AND COAL...

Assessing the Item Response Theory with Covariate (IRT-C) Procedure for Ascertaining Differential Item Functioning

ERIC Educational Resources Information Center

Tay, Louis; Vermunt, Jeroen K.; Wang, Chun

2013-01-01

We evaluate the item response theory with covariates (IRT-C) procedure for assessing differential item functioning (DIF) without preknowledge of anchor items (Tay, Newman, & Vermunt, 2011). This procedure begins with a fully constrained baseline model, and candidate items are tested for uniform and/or nonuniform DIF using the Wald statistic.…

Analysis of Item-Level Bias in the Bayley-III Language Subscales: The Validity and Utility of Standardized Language Assessment in a Multilingual Setting.

PubMed

Goh, Shaun K Y; Tham, Elaine K H; Magiati, Iliana; Sim, Litwee; Sanmugam, Shamini; Qiu, Anqi; Daniel, Mary L; Broekman, Birit F P; Rifkin-Graboi, Anne

2017-09-18

The purpose of this study was to improve standardized language assessments among bilingual toddlers by investigating and removing the effects of bias due to unfamiliarity with cultural norms or a distributed language system. The Expressive and Receptive Bayley-III language scales were adapted for use in a multilingual country (Singapore). Differential item functioning (DIF) was applied to data from 459 two-year-olds without atypical language development. This involved investigating if the probability of success on each item varied according to language exposure while holding latent language ability, gender, and socioeconomic status constant. Associations with language, behavioral, and emotional problems were also examined. Five of 16 items showed DIF, 1 of which may be attributed to cultural bias and another to a distributed language system. The remaining 3 items favored toddlers with higher bilingual exposure. Removal of DIF items reduced associations between language scales and emotional and language problems, but improved the validity of the expressive scale from poor to good. Our findings indicate the importance of considering cultural and distributed language bias in standardized language assessments. We discuss possible mechanisms influencing performance on items favoring bilingual exposure, including the potential role of inhibitory processing.

Item Response Theory: Overview, Applications, and Promise for Institutional Research

ERIC Educational Resources Information Center

Bowman, Nicholas A.; Herzog, Serge; Sharkness, Jessica

2014-01-01

Item Response Theory (IRT) is a measurement theory that is ideal for scale and test development in institutional research, but it is not without its drawbacks. This chapter provides an overview of IRT, describes an example of its use, and highlights the pros and cons of using IRT in applied settings.

Multi-scale 46-year remote sensing change detection of diamond mining and land cover in a conflict and post-conflict setting

USGS Publications Warehouse

Dewitt, Jessica D.; Chirico, Peter G.; Bergstresser, Sarah E.; Warner, Timothy A.

2017-01-01

The town of Tortiya was created in the rural northern region of Côte d′Ivoire in the late 1940s to house workers for a new diamond mine. Nearly three decades later, the closure of the industrial-scale diamond mine in 1975 did not diminish the importance of diamond profits to the region's economy, and resulted in the growth of artisanal and small-scale diamond mining (ASM) within the abandoned industrial-scale mining concession. In the early 2000s, the violent conflict that arose in Côte d′Ivoire highlighted the importance of ASM land use to the local economy, but also brought about international concerns that diamond profits were being used to fund the rebellion. In recent years, cashew plantations have expanded exponentially in the region, diversifying economic activity, but also creating the potential for conflict between diamond mining and agricultural land uses. As the government looks to address the future of Tortiya and this potential conflict, a detailed spatio-temporal understanding of the changes in these two land uses over time may assist in informing policymaking. Remotely sensed imagery presents an objective and detailed spatial record of land use/land cover (LULC), and change detection methods can provide quantitative insight regarding regional land cover trends. However, the vastly different scales of ASM and cashew orchards present a unique challenge to comprehensive understanding of land use change in the region. In this study, moderate-scale categories of LULC, including cashew orchards, uncultivated forest, urban space, mining/ bare, and mixed vegetation, were produced through supervised classification of Landsat multispectral imagery from 1984, 1991, 2000, 2007, and 2014. The fine-scale ASM land use was identified through manual interpretation of annually acquired high resolution satellite imagery. Corona imagery was also integrated into the study to extend the temporal duration of the remote sensing record back to the period of industrial

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,…

Orapa Diamond Mine, Botswana

NASA Image and Video Library

2015-11-16

This image from NASA Terra spacecraft shows the Orapa diamond mine, the world largest diamond mine by area. The mine is located in Botswana. It is the oldest of four mines operated by the same company, having begun operations in 1971. Orapa is an open pit style of mine, located on two kimberlite pipes. Currently, the Orapa mine annually produces approximately 11 million carats (2200 kg) of diamonds. The Letlhakane diamond mine is also an open pit construction. In 2003, the Letlhakane mine produced 1.06 million carats of diamonds. The Damtshaa diamond mine is the newest of four mines, located on top of four distinct kimberlite pipes of varying ore grade. The mine is forecast to produce about 5 million carats of diamond over the projected 31 year life of the mine. The image was acquired October 5, 2014, covers an area of 28 by 45 km, and is located at 21.3 degrees south, 25.4 degrees east. http://photojournal.jpl.nasa.gov/catalog/PIA20104