Practical Application Of Data Research Articles

Exploring data-in-use: the value of data for Local Government

The power of data to support digital transformation within the context of e-Government is frequently underestimated. In this exploratory research, we develop a conceptual framework where the value of data stems from how it is used. We claim that the impact of digital transformation in the public sector presupposes an organisational culture that recognises and values data-in-use, by which is meant the practical application of data for a specific purpose, particularly by staff who deliver services. Through the lens of two ‘worldviews’ of data sharing, we present case studies of data use in two local authorities in Scotland. We claim that developing a culture where data is leveraged to derive insights for organisational activity requires combining working practices and technical infrastructure that centre on co-creating value with data. The presence of data intermediaries can support effective data-in-use to establish a healthy internal data ecosystem. Our research illustrates that local authorities within Scotland are still at an early stage of developing this culture.

Investigation of Weigh-in-Motion Measurement Accuracy on the Basis of Steering Axle Load Spectra.

Weigh-in-motion systems are installed in pavements or on bridges to identify and reduce the number of overloaded vehicles and minimise their adverse effect on road infrastructure. Moreover, the collected traffic data are used to obtain axle load characteristics, which are very useful in road infrastructure design. Practical application of data from weigh-in-motion has become more common recently, which calls for adequate attention to data quality. This issue is addressed in the presented paper. The aim of the article is to investigate the accuracy of 77 operative weigh-in-motion stations by analysing steering axle load spectra. The proposed methodology and analysis enabled the identification of scale and source of errors that occur in measurements delivered from weigh-in-motion systems. For this purpose, selected factors were investigated, including the type of axle load sensor, air temperature and vehicle speed. The results of the analysis indicated the obvious effect of the axle load sensor type on the measurement results. It was noted that systematic error increases during winter, causing underestimation of axle loads by 5% to 10% for quartz piezoelectric and bending beam load sensors, respectively. A deterioration of system accuracy is also visible when vehicle speed decreases to 30 km/h. For 25% to 35% of cases, depending on the type of sensor, random error increases for lower speeds, while it remains at a constant level at higher speeds. The analysis also delivered a standard steering axle load distribution, which can have practical meaning in the improvement of weigh-in-motion accuracy and traffic data quality.

A Practical Application of Data Mining Methods to Build Predictive Models for Autism Spectrum Disorder Based on Biosensor Data From Janssen Autism Knowledge Engine (JAKE®)

The Janssen Autism Knowledge Engine (JAKE®) collects a large number of features from five biosensors across a range of tasks. The application of data mining methods to these data may be a useful approach to enable objective discrimination between autism spectrum disorder (ASD) and typically developing (TD) participants. Following a prospective observational study using JAKE, ASD participants classified as “moderate” or “severe” based on total scores on the Social Responsiveness Scale, and TD participants were used to build models, using repeated cross-validation, to identify biosensor features contributing to diagnosis. Four different models (partial least squares, random forest, elastic net, and C5.0) were chosen to build diagnostic classifiers using the training set, and the fitted models were evaluated on the test set. Model performance on the training set, based on receiver operating characteristics (ROC), was moderate (area under ROC curve = 0.61–0.72), and model performance on the test set based on kappa statistic was between 0.40 and 0.46 across the four models. Data mining methods applied to biosensor data can lead to models that discriminate ASD from TD. This method may prove useful in creating new diagnostic tests for ASD.

Study on a New Method for Calculating Water Saturation

In order to improve the identification and evaluation accuracy of low resistivity oil layer and complex pore structure oil layer, and to avoid the interpretation error caused by the traditional evaluation mode of “high resistivity is oil layer and low resistivity is water layer”, the method of calculating water saturation by radial resistivity ratio was studied. The results show that the radial resistivity ratio can be used to calculate the reservoir water saturation for completely invaded formation, which can be deduced according to archie formula. The new formula does not evaluate oil and water layers based on high or low of resistivity, but can be used to evaluate low resistivity oil and high resistivity water layers. After testing core experimental data, The new formula can effectively calculate the water saturation and meet the requirement of using. After practical application of data, The average absolute error of the calculated water saturation is 3.55%, which conforms to the industry standard. This method is helpful to improve the coincidence rate of logging interpretation, and is worth popularizing.

A new disclosure index for Non-Governmental Organizations

Website of Non-governmental organization (NGO) is a focal medium of sharing information in response to transparency demands and addressing trust deficits between stakeholders. Many researchers have proposed accountability approaches to measure information sharing trends through websites. This article discusses a new index to measure online disclosure trends along with the theoretical properties of the index and a practical application of data from NGOs working in Pakistan. The websites have been coded in 2016. Results show that NGOs with branch offices have better disclosure scores than single-office NGOs, and international NGOs score better than local NGOs. NGOs that are more often the subject of newspaper reports have better disclosure trends.

Quasi-continuous videodensitometric recording of chromatograms in circular TLC

A new method of quasi-continuous videodensitometric recording of circular thin-layer chromatography (TLC) is proposed. It is based on separation by planar chromatography and simultaneous quasicontinuous videodensitometric recording of the chromatograms on the plate as the chromatograms are developing in real time. This new approach to recording of separation results enables one to expand and simplify substantially the practical application of data on the separation of samples being studied during the entire chromatographic process. It is important to note that the chromatograms are recorded on a plate wetted with the liquid phase (i.e., on a ‘wet’ TLC plate) in the separation process. Use of this new version of TLC enables considerable reduction of the duration of analysis. It should be noted that in this paper we consider not only the traditional circular TLC, but new methods of circular TLC — corner and lateral TLC. Quasi-continuous recording of the separation results can also be used for the detection ...

Machine learning and data mining

The basic model and classification of machine-learning are introduced,and then an analysis is made of the systematic structure and practical application of data mining.Finally,the combination and development of them are examplified.

Teaching data abstraction to the practicing programmer

We have been experimenting at The George Washington University with our undergraduate and graduate courses in Data Structures. In particular, we are using a very modern text [HORO78] and a strong emphasis in lectures and projects on the practical application of data abstraction, and its relationship to both structured programming and machine efficiency. Student projects are subroutine packages written, in “real-world” programming languages, as faithful and modular implementations of the abstractions studied. Throughout the courses, attention is paid to the relationship between structured programming and data structures, and between these two and time/space efficiency considerations. After a preliminary discussion of data abstraction concepts, we present a case study, namely a sparse-matrix system, and some observations.

Effects of Age and Position on Mineral Composition of Mango Leaves1

Abstract As mango leaves increased in age, lower P and K contents were found, while Ca content was higher. The basal leaf was lower in N and Ca but higher in P and K contents when compared with the terminal leaf of the same shoots. Only small differences were observed when leaves were compared from fruiting and nonfruiting shoots. The practical application of data in sampling mango leaves is discussed.