Improper Data Research Articles

Data Validation System For A Relational Database

One of the most neglected areas in systems implementation is data validation. Most application systems fail to achieve its set goals because there is no adequate and efficient data validation system to filter out input data that is not correct. Improper input data is responsible for a large number of system failures; and such failures could have been avoided or reduced if proper input data had been fed into the system. In this paper we focused on enhancing and elaborating on existing data validation methods like limits checks, character checks, range checks, presence checks, consistency checks, format or picture checks and data type checks, to improve the performance of our application systems. We also develop a sample program that integrates these validation techniques. A report was finally generated based on validated customer records created for Fractal Construction Nigeria Limited. The system was developed using PHP, MYSQL and XAMPP web server. Keywords: Data validation, database, data base management system, database specification, relational model, normalization

Hardness Variation of Ball Bond Wire Bonding

In semiconductor packaging, conventional test procedures for evaluating mechanical properties of ball bonded gold wire bonding are well established. However these tests do not provide clear understanding related to the strength mechanism leading to improper reliability data. The nanoindentation approach, uses equipment called nanoindenter, gives advances mechanical (sub-micromechanical) characterization, particularly the combination effect of elastic and plastic deformation. Wire bonding process was prepared using thermosonic-wire bonding technology with 25m diameter gold wire and copper as substrate. To obtain mechanical properties, ball-bonded was cross-sectioned diagonally before indented at various locations. Results show that mechanical properties vary according the locations throughout the surface; at the centre, at the edge and at the area near intermetallics layer. This indicates test location plays important role in determining ‘meaningful’ mechanical properties.

Group aggregating normalization method for the preprocessing of NMR-based metabolomic data

Data normalization plays a crucial role in metabolomics to take into account the inevitable variation in sample concentration and the efficiency of sample preparation procedure. The conventional methods such as constant sum normalization (CSN) and probabilistic quotient normalization (PQN) are widely used, but both methods have their own shortcomings. In the current study, a new data normalization method called group aggregating normalization (GAN) is proposed, by which the samples were normalized so that they aggregate close to their group centers in a principal component analysis (PCA) subspace. This is in contrast with CSN and PQN which rely on a constant reference for all samples. The evaluation of GAN method using both simulated and experimental metabolomic data demonstrated that GAN produces more robust model in the subsequent multivariate data analysis, more superior than both CSN and PQN methods. The current study also demonstrated that some of the differential metabolites identified using the CSN or PQN method could be false positives due to improper data normalization.

Quantitative Analysis of Complex Tropical Forest Stands: A Review

The importance of data analysis in quantitative assessment of natural resources remains significant in the sustainable management of complex tropical forest resources. Analyses of data from complex tropical forest stands have not been easy or clear due to improper data management. It is pivotal to practical researches and discovery that promote development in forestry and many related disciplines. Many quantitative methods andapproaches are strongly dependent on the source, nature, and quality of the data. However, many issues related to data analysis in the tropical complex forests are inimical and may render quantitative methods impossible if not resolved. Data collection in many complex tropical forests is very difficult and oftentimes results in data violating simple assumptions of statistical models. The use of relevant data transformation proffers significant solution to this perennial challenge within the complex tropical forests. This paper therefore reviews statistical issues related to quantitative data collection and analyses in the complex tropical forests and provides pragmatic approaches for solving data analysis challenges in complex tropical forests’ management and planning.Keywords: data issues, analysis, complex stands, forestry

A reduced data set method for support vector regression

Support vector regression (SVR) has been very successful in pattern recognition, text categorization, and function approximation. The theory of SVR is based on the idea of structural risk minimization. In real application systems, data domain often suffers from noise and outliers. When there is noise and/or outliers exist in sampling data, the SVR may try to fit those improper data, and obtained systems may have the phenomenon of overfitting. In addition, the memory space for storing the kernel matrix of SVR will be increment with O( N 2), where N is the number of training data. Hence, for a large training data set, the kernel matrix cannot be saved in the memory. In this paper, a reduced support vector regression is proposed for nonlinear function approximation problems with noise and outliers. The core idea of this approach is to adopt fuzzy clustering and a robust fuzzy c-means (RFCM) algorithm to reduce the computational time of SVR and greatly mitigates the influence of data noise and outliers.

Development of a model for compensating the influence of temperature gradients within the sample on DSC-results on phase change materials

The use of phase change materials (PCMs) in thermal storage is not a new concept, but engineers are continually finding new ways to utilize them in a wide range of applications. A PCM takes advantage of high latent heat in the phase change process to store large amounts of heat while undergoing only a small change in temperature. This property makes PCMs suitable for thermal storage purposes in a wide range of engineering applications. Due to the nature of these applications, it is vital to have a precise knowledge of the thermal characteristics of any PCM. Unfortunately, due to the low thermal conductivities and high latent heats found in PCMs, current measuring tools such as differential scanning calorimetry, provide inconsistent results. This paper conjectures that these errors come from the effects of low thermal diffusivity samples as well as improper data analysis methods.

Children's Educational Records and Privacy: A Study of Elementary and Secondary School State Reporting Systems

Following the No Child Left Behind mandate to improve school quality, there has been a growing trend among state departments of education to establish statewide longitudinal databases of personally identifiable information for all K-12 children within a state in order to track progress and change over time. This trend is accompanied by a movement to create uniform data collection systems so that each state’s student data systems are interoperable with one another. This study examines the privacy concerns implicated by these trends. The study reports on the results of a survey of all fifty states and finds that state educational databases across the country ignore key privacy protections for the nation's K-12 children. The study finds that large amounts of personally identifiable data and sensitive personal information about children are stored by the state departments of education in electronic warehouses or for the states by third party vendors. These data warehouses typically lack adequate privacy protections, such as clear access and use restrictions and data retention policies, are often not compliant with the Family Educational Rights and Privacy Act, and leave K-12 children unprotected from data misuse, improper data release, and data breaches. The study provides recommendations for best practices and legislative reform to address these privacy problems.

Report from the Working Group of the Molecular Biology Society of Japan for the investigation of fraud in research papers

Report from the Working Group of the Molecular Biology Society of Japan for the investigation of fraud in research papers

The powerful law of the power law and other myths in network biology

For almost 10 years, topological analysis of different large-scale biological networks (metabolic reactions, protein interactions, transcriptional regulation) has been highlighting some recurrent properties: power law distribution of degree, scale-freeness, small world, which have been proposed to confer functional advantages such as robustness to environmental changes and tolerance to random mutations. Stochastic generative models inspired different scenarios to explain the growth of interaction networks during evolution. The power law and the associated properties appeared so ubiquitous in complex networks that they were qualified as "universal laws". However, these properties are no longer observed when the data are subjected to statistical tests: in most cases, the data do not fit the expected theoretical models, and the cases of good fitting merely result from sampling artefacts or improper data representation. The field of network biology seems to be founded on a series of myths, i.e. widely believed but false ideas. The weaknesses of these foundations should however not be considered as a failure for the entire domain. Network analysis provides a powerful frame for understanding the function and evolution of biological processes, provided it is brought to an appropriate level of description, by focussing on smaller functional modules and establishing the link between their topological properties and their dynamical behaviour.

A clustering approach to free form surface reconstruction from multi-view range images

3D modelling finds a wide range of applications in robot vision and reverse engineering. However due to the presence of surface scanning noise, accumulative registration errors, and improper data fusion, the reconstructed surfaces from multiple registered range images are often non-smooth and distorted with thick patches, false connections and blurred features. These shortcomings will limit the wide applications of 3D modelling using the latest laser scanning systems. In this paper, the clustering approach, surface segmentation and classification are employed to fuse registered range images to reduce the adverse effect of large accumulative registration errors and heavy scanning noise, minimize the dissimilarity of the fused surface with respect to the original overlapping surfaces, and produce smooth and detailed 3D object computer models. For initialization of the clustering approach, an automatic method is developed, shifting possible corresponding points from different viewpoints toward each other and thus, making sure that the initialization of the cluster centroids are in between the two data sets so that more efficient and effective integration of data can be obtained. Then the principal component analysis (PCA) is employed to segment these centroids into different areas for the representation of the initially fused surface and then the tensor analysis is applied to classify these areas into featured and non-featured ones. In the integration process, the K means and fuzzy c means clustering approaches from the pattern recognition and machine learning literatures are employed to integrate non-featured areas for a smooth fused surface and featured areas for keeping the geometric details. By controlling a parameter, the final integrated surface can be traded off between smoothness and geometric details. Finally the fused point set is triangulated using an improved Delaunay method, guaranteeing a watertight surface. The new method is theoretically guaranteed to converge and minimize the dissimilarity between the final fused surface and original surfaces. A comparative study based on real images shows that the proposed algorithm desirably retains geometric details, produces smooth surface and minimizes the integration error.

Unbiased Statistical Comparison of Creep and Shrinkage Prediction Models

This paper addresses the problem of selecting the most realistic creep and shrinkage prediction model, important for designing durable and safe concrete structures. Statistical methods of standard and several nonstandard types and a very large experimental database have recently been used to compare and rank the existing prediction models, but conflicting results have been obtained by various investigators. This paper attempts to overcome this confusion. It introduces data weighting required to eliminate the bias due to improper data sampling in the database, and then examines Bazant and Baweja's Model B3, the ACI model, the CEB model, and two of Gardner's models. The statistics of prediction errors are based strictly on the method of least squares, which is the standard and the only statistically correct method, dictated by the maximum likelihood criterion and the central limit theorem of the theory of probability, as well as the requirement of noncorrelation of errors. Several nonstandard statistical methods that have recently been invented to evaluate creep and shrinkage models are also examined and their deficiencies are pointed out. The ranking of the models that ensues from the least-square regression statistics is shown to be quite different from the rankings obtained by the nonstandard statistics.

The Importance of Data Partitioning and the Utility of Bayes Factors in Bayesian Phylogenetics

As larger, more complex data sets are being used to infer phylogenies, accuracy of these phylogenies increasingly requires models of evolution that accommodate heterogeneity in the processes of molecular evolution. We investigated the effect of improper data partitioning on phylogenetic accuracy, as well as the type I error rate and sensitivity of Bayes factors, a commonly used method for choosing among different partitioning strategies in Bayesian analyses. We also used Bayes factors to test empirical data for the need to divide data in a manner that has no expected biological meaning. Posterior probability estimates are misleading when an incorrect partitioning strategy is assumed. The error was greatest when the assumed model was underpartitioned. These results suggest that model partitioning is important for large data sets. Bayes factors performed well, giving a 5% type I error rate, which is remarkably consistent with standard frequentist hypothesis tests. The sensitivity of Bayes factors was found to be quite high when the across-class model heterogeneity reflected that of empirical data. These results suggest that Bayes factors represent a robust method of choosing among partitioning strategies. Lastly, results of tests for the inclusion of unexpected divisions in empirical data mirrored the simulation results, although the outcome of such tests is highly dependent on accounting for rate variation among classes. We conclude by discussing other approaches for partitioning data, as well as other applications of Bayes factors.

Accurate integration of multi-view range images using k-means clustering

3D modelling finds a wide range of applications in industry. However, due to the presence of surface scanning noise, accumulative registration errors, and improper data fusion, reconstructed object surfaces using range images captured from multiple viewpoints are often distorted with thick patches, false connections, blurred features and artefacts. Moreover, the existing integration methods are often expensive in the sense of both computational time and data storage. These shortcomings limit the wide applications of 3D modelling using the latest laser scanning systems. In this paper, the k-means clustering approach (from the pattern recognition and machine learning literatures) is employed to minimize the integration error and to optimize the fused point locations. To initialize the clustering approach, an automatic method is developed, shifting points in the overlapping areas between neighbouring views towards each other, so that the initialized cluster centroids are in between the two overlapping surfaces. This results in more efficient and effective integration of data. While the overlapping areas were initially detected using a single distance threshold, they are then refined using the k-means clustering method. For more accurate integration results, a weighting scheme reflecting the imaging principle is developed to integrate the corresponding points in the overlapping areas. The fused point set is finally triangulated using an improved Delaunay method, guaranteeing a watertight surface. A comparative study based on real images shows that the proposed algorithm is efficient in the sense of either running time or memory usage and reduces significantly the integration error, while desirably retaining geometric details of 3D object surfaces of interest.

Present condition of highway bridges in Vietnam: an analysis of current failure modes and their main causes

This paper reports on research conducted to evaluate the current status of highway bridges in Vietnam. The adopted approach included literature reviews to identify common failure modes and causes, together with site inspections to ascertain their validity. Interviews were also conducted with the various stakeholders to further understand the current condition of the inspected bridges. Results show an overall picture of existing bridges in poor physical condition, thus providing poor service to users. Defects that have previously been identified in the literature include corrosion, settlement, fatigue damage, obsolescence, scouring and aging. New problems identified were human invasions and missing elements. Previous literature identifies traffic overload and jams, collision, adverse environmental conditions and poor maintenance as causes for these problems. Additionally, this paper considers war, improper data retention and other country-specific causes. The authors suggest that maintenance efforts should be prioritized to remedy and eliminate serious failures. Properly trained maintenance crews need to be established and further research carried out to establish adequate bridge maintenance systems.

Applications of quality assurance in an educational chemistry laboratory

It is a well-known fact that, the over all student performance in practical work is a function of a closely interwoven ternary system that includes the teacher, the laboratory technician and the student. The contribution of these people towards the success of a students starts from experimental design and reagent preparation stages. The implementation of a quality assurance system in a Chemistry laboratory reduces shortcomings associated with student failure, which includes unpreparedness, mismanagement of time, lack of practical work techniques, improper data processing and presentation. This can be instituted, in part, by the application of cheap and reliable reference materials made by the teachers. A collaborative proficiency-testing group involving a number of Chemistry teachers and peers can be set to select suitable candidates for reference materials. A quality assurance system installs teacher confidence that the Chemistry laboratory is performing effectively in training students. African Journal of Educational Studies in Mathematics and Sciences Vol. 1, 2001: 13-19

Current status of existing railway bridges in Vietnam: An overview of steel deficiencies

Currently, the deterioration of bridge conditions is causing many problems. Therefore, the work reported in this paper was carried out to survey the present condition of railway bridges in Vietnam, concentrating on steel deficiencies. Literature reviews were initiated to identify common defects with site inspections and personal interviews to ascertain their validity. Finding the defects draws an overall picture of Vietnamese railway bridges that are in poor physical condition, thus providing poor serviceability. Besides structural failure, local defects were already identified, consisting of corrosion, fatigue, functional obsolescence and aging. New problems that have been identified are human invasions and missing elements. It is widely considered that overload, collision impacts, adverse climate conditions and poor maintenance are the main causes. Additionally, this paper includes previous wars, improper data keeping, and elemental burglary as country-specific causes. It suggests that maintenance efforts should be prioritized to eliminate these deficiencies. Trained maintenance crews need to be established and further research should be carried out to create an adequate maintenance management system in Vietnam.

KTDA: emerging patterns based data analysis system

Emerging patterns are kind of relationships discovered in databases containing a decision attribute. They represent contrast characteristics of individual decision classes. This form of knowledge can be useful for experts and has been successfully employed in a field of classification. In this paper we present the KTDA system. It enables discovering emerging patterns and applies them to classification purposes. The system has capabilities of identifying improper data by making use of data credibility analysis, a new approach to assessment data typicality.

Influence of System Calibration on Direct Sensor Orientation

The determination of object coordinates based on direct sensor orientation is an extrapolation from the projection centers to the ground coordinate system. Like any extrapolation, it is sensitive to random and systematic errors, as well as, to improper data handling. Direct sensor orientation is based on the combination of an Inertial Measurement System (IMU) and GPS. The GPS antenna, the IMU, and the imaging sensor are located in different positions, and the latter two have different orientations. Therefore, the calibration of all sensors and the relation between the sensors is of vital importance for precise ground positioning. The system calibration includes the determination of the boresight misalignment, the interior camera orientation, and the GPS antenna offset. A rigorous mathematical model is required. The inner orientation of the camera used has to be determined under flight conditions to achieve sufficient results. In this paper, the influence of the system calibration to the direct sensor orientation and improper data handling will be shown.

Conformational Analysis of Self-Organized Monolayers with Scanning Tunneling Microscopy at Near-Atomic Resolution

We describe the synthesis and a novel approach to the conformational analysis of 2,2'-bipyridines (bpy) bearing aromatic rich Frechet-type dendritic wedges of the first and second generation as substituents. The evaporation of solutions of these new ligands on graphite surfaces under ambient conditions results in the formation of self-organized monolayers. Scanning tunneling microscopy (STM) investigations of the monolayers under ambient conditions (air, 298 K) gave images at submolecular and near-atomic resolution. The analysis of the STM images includes the following processes: (i) identification and reproduction of potential homoconformational domains, (ii) exclusion of improper data using quality criteria for drift and feedback artifacts, (iii) compilation of running averages and checking for averaging artifacts, (iv) analysis of three-dimensional and contour plots, (v) calculation of the HOMO properties of the free molecules, and (vi) final conformational assignment based on all accessible information. Following this procedure, two different conformations could be assigned to domains observed in the monolayers of the first-generation (G1) and second-generation (G2) dendritic compounds. Homoconformational domains are observed side-by-side. The different conformations arise from syn or anti arrangements at the ether substituents. An additional conformational effect is found upon treating the G1 domains with HCl gas, when a partial rearrangement of the bpy from trans to cis occurs, concomitant with protonation.

Language barrier, funding, communication and time management problems found in the Medical Journal of Indonesia, 1995 - 2001

The objective of this study is to assess the problems encountered in the management of Medical Journal of Indonesia and whether any progress has been achieved during the past 7 years. A retrospective descriptive study was done in the MJI. Available data used as parameters were: number of articles submitted and author's home institution, number of articles submitted and rejected, cause/criteria of rejection, qualification of reviewers and editors, duration of manuscript processing, and whether pre-scheduled time is met in the Med J Indones. For this purpose, all manuscripts from January 1995- January 2001 were evaluated. In addition, recent problems encountered were noted. Problems encountered were limited supply of manuscript that might be due to language barrier, decrease in circulation due to limited budget, communication problems due to seniority, and increase in average processing time that might be due to restriction in the time allocated for MJI Number of articles submitted by authors originating from national versus foreign institutions in 1995-1997 was 101 versus 16, and in 1998 - 2000 were 124 versus 84. Articles rejected were ±26.4 % (1999-2001) and the most frequent causes of rejection were insignificancy of substance and improper data analysis. As for the qualification of editors there was an increase in the number of PhDs and professors. Average processing time is approximately 1.5 times the scheduled time. It seems that the 4 main problems encountered were (1) Language barrier, (2) Funding, (3) Communication problems and (4) Time management; and though not impressive, there are definitely positive changes in the number of manuscipts submitted, qualification of editors and peer reviewers. Average processing time is about the same, and the prescheduled time of editing is yet to be met. (Med J Indones 2001; 10: 252-8) Keywords: language barrier, funding, communication problems, time management