The teaching of qualitative research methods in information systems: an explorative study utilizing learning theory

Empirical evidence suggests that the Information Systems field continues to be dominated by the positivist paradigm and the use of quantitative methods. This is so despite the diversity of research methods available, the emergence of an interpretivist tradition, and some isolated examples of methodological pluralism. While there have been significant contributions in guiding qualitative research methods teaching, little research has been undertaken that considers the training actually provided, and the possible impacts this may have on the quality and quantity of qualitative research articles in our journals. This explorative study aims to provide some insight into what training is provided, the issues confronted, and possible impediments to publishing qualitative research. Data were collected from interviews with a panel of international colleagues who have a range of experience in teaching and applying qualitative methods. Grounded Theory is used to identify emergent and interconnected themes. Experiential and social learning lenses are used to reflect on the results, providing some initial understanding of the complexities of teaching and undertaking qualitative research. Theoretical as well as practical contributions are made regarding the means by which qualitative research may be introduced, developed and extended within the IS academy, and further theorisation of social and experiential learning.     

Efficient Interval Linear Equality Solving in Constraint Logic Programming

Existing interval constraint logic programming languages, such as BNR Prolog, work under the framework of interval narrowing and are deficient in solving systems of linear constraints over real numbers, which constitute an important class of problems in engineering and other applications. In this paper, we suggest to separate linear equality constraint solving from inequality and non-linear constraint solving. The implementation of an efficient interval linear constraint solver, which is based on the preconditioned interval Gauss-Seidel method, is proposed. We show how the solver can be adapted to incremental execution and incorporated into a constraint logic programming language already equipped with a non-linear solver based on interval narrowing. The two solvers share common interval variables, interact and cooperate in a round-robin fashion during computation, resulting in an efficient interval constraint arithmetic language CIAL. The CIAL prototypes, based on CLP(R), are constructed and compared favorably against several major interval constraint logic programming languages.     

Denoising Medical Images Using Deep Learning in IoT Environment

Medical Resonance Imaging (MRI) is a noninvasive, nonradioactive, and meticulous diagnostic modality capability in the field of medical imaging. However, the efficiency of MR image reconstruction is affected by its bulky image sets and slow process implementation. Therefore, to obtain a high-quality reconstructed image we presented a sparse aware noise removal technique that uses convolution neural network (SANR_CNN) for eliminating noise and improving the MR image reconstruction quality. The proposed noise removal or denoising technique adopts a fast CNN architecture that aids in training larger datasets with improved quality, and SARN algorithm is used for building a dictionary learning technique for denoising large image datasets. The proposed SANR_CNN model also preserves the details and edges in the image during reconstruction. An experiment was conducted to analyze the performance of SANR_CNN in a few existing models in regard with peak signal-to-noise ratio (PSNR), structural similarity index (SSIM), and mean squared error (MSE). The proposed SANR_CNN model achieved higher PSNR, SSIM, and MSE efficiency than the other noise removal techniques. The proposed architecture also provides transmission of these denoised medical images through secured IoT architecture.     

On embedding cycles into faulty twisted cubes

The twisted cube TQ_n is an alternative to the popular hypercube network. Recently, some interesting properties of TQ_n were investigated. In this paper, we study the pancycle problem on faulty twisted cubes. Let f_e and f_v be the numbers of faulty edges and faulty vertices in TQ_n, respectively. We show that, with f_e + f_v ? n − 2, a faulty TQ_n still contains a cycle of length l for every 4 ? l ? ∣V(TQ_n)∣ − f_v and odd integer n ? 3.     

Modeling of gas absorption cross sections by use of principal-component-analysis model parameters

Monitoring the amount of gaseous species in the atmosphere and exhaust gases by remote infrared spectroscopic methods calls for the use of a compilation of spectral data, which can be used to match spectra measured in a practical application. Model spectra are based on time-consuming line-by-line calculations of absorption cross sections in databases by use of temperature as input combined with path length and partial and total pressure. It is demonstrated that principal component analysis (PCA) can be used to compress the spectrum of absorption cross sections, which depend strongly on temperature, into a reduced representation of score values and loading vectors. The temperature range from 300 to 1000 K is studied. This range is divided into two subranges (300-650 K and 650-1000K), and separate PCA models are constructed for each. The relationship between the scores and the temperature values is highly nonlinear. It is shown, however, that because the score-temperature relationships are smooth and continuous, they can be modeled by polynomials of varying degrees. The accuracy of the data compression method is validated with line-by-line-calculated absorption data of carbon monoxide and water vapor. Relative deviations between the absorption cross sections reconstructed from the PCA model parameters and the line-by-line-calculated values are found to be smaller than 0.15% for cross sections exceeding 1.27 x 10(-21) cm(-1) atm(-1) (CO) and 0.20% for cross sections exceeding 4.03 x 10(-21) cm(-1) atm(-1) (H2O). The computing time is reduced by a factor of 10(4).     

Investigation of NiO<Subscript>x</Subscript>-hole transport layers in triple cation perovskite solar cells

Perovskite solar cells with a planar p-i-n device structure offer easy processability at low temperatures, suitable for roll-to-roll fabrication on flexible substrates. Herein we investigate different hole transport layers (solution processed NiO_x, sputtered NiO_x, PEDOT:PSS) in planar p-i-n perovskite solar cells using the triple cation lead halide perovskite Cs_0.08(MA_0.17FA_0.83)_0.92Pb(I_0.83Br_0.17)₃ as absorber layer. Overall, reproducible solar cell performances with power conversion efficiencies up to 12.8% were obtained using solution processed NiO_x as hole transport layer in the devices. Compared to that, devices with PEDOT:PSS as hole transport layer yield efficiencies of approx. 8.4%. Further improvement of the fill factor was achieved by the use of an additional zinc oxide nanoparticle layer between the PC₆₀BM film and the Ag electrode.     

Ambient Protection of Few‐Layer Black Phosphorus via Sequestration of Reactive Oxygen Species

Few‐layer black phosphorous (BP) has emerged as a promising candidate for next‐generation nanophotonic and nanoelectronic devices. However, rapid ambient degradation of mechanically exfoliated BP poses challenges in its practical deployment in scalable devices. To date, the strategies employed to protect BP have relied upon preventing its exposure to atmospheric conditions. Here, an approach that allows this sensitive material to remain stable without requiring its isolation from the ambient environment is reported. The method draws inspiration from the unique ability of biological systems to avoid photo‐oxidative damage caused by reactive oxygen species. Since BP undergoes similar photo‐oxidative degradation, imidazolium‐based ionic liquids are employed as quenchers of these damaging species on the BP surface. This chemical sequestration strategy allows BP to remain stable for over 13 weeks, while retaining its key electronic characteristics. This study opens opportunities to practically implement BP and other environmentally sensitive 2D materials for electronic applications.     

Factors contributing to officers' fatigue in high-speed maritime craft operations

The purpose of this study was to investigate the difference in the level of fatigue induced by high-speed maritime craft operation between the day- and night-shift officers. The demographic and work-related factors that contribute to fatigue were also explored. A total of 93 high-speed maritime craft officers participated in the survey, of whom 35 worked a day shift (Mean age=48.3 years) and 58 worked a night shift (Mean age=45.8 years). Fatigue experience was measured with the Chinese version of the Swedish Occupational Fatigue Inventory (SOFI-C) at the beginning, in the middle and at the end of the work shift. Information on age, work experience, perceived voyage difficulty and duty schedule was obtained. The study found that the night-shift officers seemed to manifest an overall higher level of perceived fatigue than the day-shift officers, while the day-shift officers demonstrated a fatigue carry-over effect across the two workdays. Besides the shift pattern, age, experience in operating high-speed maritime craft and perceived voyage difficulty were the significant factors contributing to the officers' fatigue experience. The finding that the fatigue experience associated with high-speed maritime craft operation has a rapid and accumulative nature suggests that different occupational safety and health guidelines should be devised for these two groups of officers.     

Dynamics of Polymer Interdiffusion: The Ripple Experiment

We explore the interdiffusion of oppositely labeled triblock polystyrene chains, HDH/DHD, during welding in the melt using dynamic secondary ion mass spectroscopy (DSIMS) and specular neutron reflectivity (SNR). The HDH chains have the central portion of the chain deuterated (D) approximately 50% while the two ends (H) each have approximately 25% protonation; the DHD is oppositely labeled, but each set of chains contains about 50% deuteration. During welding, the deuterium depth profile exhibits "ripples" whose characteristic features, such as the time and molecular weight dependent shape, amplitude, and position, are very sensitive to the microscopic details of the polymer dynamics. The ripple experiment is especially sensitive to the presence, or absence, of topological constraints and anisotropic motion of chains. The current work significantly extends the molecular weight range up to 400 000. This allows greater separation of the six key ripple features used in deciphering the correct polymer dynamics model at the polymer-polymer interface. The DSIMS and SNR experimental results are compared to theoretical predictions and ripple simulations for Rouse, polymer mode-coupling, reptation (with and without tube broadening), and other phenomenological dynamics models. The six ripple characteristics were found to be perfectly correlated and convincingly consistent with the predictions of the reptation dynamics model. The ripple results are in significant disagreement with the polymer mode-coupling model proposed by Schweizer and other tubeless models. We conclude that the reptation model, proposed by DeGennes in 1971 with parallel developments by Edwards, is the correct model to describe the dynamics of polymer interdiffusion.