How to improve the assessment of BPM maturity in the era of digital transformation

For almost 30 years, the way of building business process management maturity models (BPM MMs), the importance assigned to individual maturity levels, and the criteria and critical success factors chosen for BPM maturity assessment have not changed significantly, despite the fact that during those three decades, the business environment and organizations themselves have changed enormously. The impact of hyperautomation and the increasing pace of change require the integration of maturity assessment with the BPM implementation methodology, including the repetition of maturity assessment for selected groups of processes. This causes an urgent need to adapt both process maturity assessment methods and BPM MMs to changing working conditions and business requirements. This conceptual paper is based on a model approach. The framework presented in the article continues and at the same time clearly deviates from the tradition of building BPM MMs on the basis of the Capability Maturity Model (CMM). It proposes a two-stage comprehensive process of organizational process maturity assessment, fully integrated into the process of BPM implementation and further business process management. The presented framework makes it possible to assess the process maturity of Industry 4.0 organizations in which dynamic knowledge-intensive business processes (kiBPs) play a key role in creating value.

     

Classifier ensemble for an effective cytological image analysis

Breast cancer is the most common type of cancer among women. As early detection is crucial for the patient’s health, much attention has been paid to the development of tools for effective recognition of this disease. This article presents an application of image analysis and classification methods for fine needle biopsy. In our approach, each patient is described by nine microscopic images taken from the biopsy sample. The images are related to regions of the biopsy that seem interesting to the physician who selects them arbitrarily. We propose four different hybrid segmentation algorithms dedicated to processing these images and examine their effectiveness for the nuclei feature extraction task. Classification is carried out with the usage of a classifier ensemble based on the Random Subspaces approach. To boost its effectiveness, we use a linear combination of the support functions returned by the individual classifiers in the ensemble. In the proposed medical support system, the final decision about the patient is delivered after a fusion of nine separate outputs of the classifier – each for a different image. Experimental results carried out on a diverse dataset collected by the authors prove that the proposed solution outperforms state-of-the-art classifiers and shows itself to be a valuable tool for supporting day-to-day cytologist’s routine.     

Classical and Quantum Complexity of the Sturm–Liouville Eigenvalue Problem

We study the approximation of the smallest eigenvalue of a Sturm–Liouville problem in the classical and quantum settings. We consider a univariate Sturm–Liouville eigenvalue problem with a nonnegative function q from the class C² ([0,1]) and study the minimal number n() of function evaluations or queries that are necessary to compute an -approximation of the smallest eigenvalue. We prove that n()=(^–1/2) in the (deterministic) worst case setting, and n()=(^–2/5) in the randomized setting. The quantum setting offers a polynomial speedup with bit queries and an exponential speedup with power queries. Bit queries are similar to the oracle calls used in Grovers algorithm appropriately extended to real valued functions. Power queries are used for a number of problems including phase estimation. They are obtained by considering the propagator of the discretized system at a number of different time moments. They allow us to use powers of the unitary matrix exp((1/2) iM), where M is an n× n matrix obtained from the standard discretization of the Sturm–Liouville differential operator. The quantum implementation of power queries by a number of elementary quantum gates that is polylog in n is an open issue. In particular, we show how to compute an -approximation with probability (3/4) using n()=(^–1/3) bit queries. For power queries, we use the phase estimation algorithm as a basic tool and present the algorithm that solves the problem using n()=(log ^–1) power queries, log ^2–1 quantum operations, and (3/2) log ^–1 quantum bits. We also prove that the minimal number of qubits needed for this problem (regardless of the kind of queries used) is at least roughly (1/2) log ^–1. The lower bound on the number of quantum queries is proven in Bessen (in preparation). We derive a formula that relates the Sturm–Liouville eigenvalue problem to a weighted integration problem. Many computational problems may be recast as this weighted integration problem, which allows us to solve them with a polylog number of power queries. Examples include Grovers search, the approximation of the Boolean mean, NP-complete problems, and many multivariate integration problems. In this paper we only provide the relationship formula. The implications are covered in a forthcoming paper (in preparation).PACS: 03.67.Lx, 02.60.-x.     

An investigation of mass transfer in a countercurrent three-phase fluidized bed

The rate of absorption with chemical reaction has been measured in a bed of solid spheres fluidized by upward flowing gas and irrigated by downward flowing liquid for different reactant concentrations in the liquid phase and different values of the liquid superficial velocity.Values of the effective inerfacial area per unit volume of a static bed, a, and the gas-film mass-transfer coefficient, k_g, are reported as functions of the liquid superficial velocity.     

Automatic apparatus for precise measuring and recording of pzc value of liquid electrodes and its application

The equipment for automatic measurement of liquid electrodes zero charge potential values based on the use of the immersion method, has been presented. The advantages of this method in comparison with the streaming method have been described. The paper presents block diagrams of the three versions of the equipment and the analysis of its functioning, and describes the construction of the measuring cell. The measurements of pzc of mercury in KF solution have been carried out in mixtures of water-isopropanol and the component values of the potential drop at the investigated phase boundary have been determined by extrapolation.     

Bacterial Cellulose Membrane Containing Epilobium angustifolium L. Extract as a Promising Material for the Topical Delivery of Antioxidants to the Skin

Bacterial cellulose membranes (BCs) are becoming useful as a drug delivery system to the skin. However, there are very few reports on their application of plant substances to the skin. Komagataeibacter xylinus was used for the production of bacterial cellulose (BC). The BC containing 5% and 10% ethanolic extract of Epilobium angustifolium (FEE) (BC-5%FEE and BC-10%FEE, respectively) were prepared. Their mechanical, structural, and antioxidant properties, as well as phenolic acid content, were evaluated. The bioavailability of BC-FESs using mouse L929 fibroblasts as model cells was tested. Moreover, In Vitro penetration through the pigskin of the selected phenolic acids contained in FEE and their accumulation in the skin after topical application of BC-FEEs was examined. The BC-FEEs were characterized by antioxidant activity. The BC-5% FEE showed relatively low toxicity to healthy mouse fibroblasts. Gallic acid (GA), chlorogenic acid (ChA), 3,4-dihydroxybenzoic acid (3,4-DHB), 4-hydroxybenzoic acid (4-HB), 3-hydroxybenzoic acid (3-HB), and caffeic acid (CA) found in FEE were also identified in the membranes. After topical application of the membranes to the pigskin penetration of some phenolic acid and other antioxidants through the skin as well as their accumulation in the skin was observed. The bacterial cellulose membrane loaded by plant extract may be an interesting solution for topical antioxidant delivery to the skin.     

The deterministic subspace method for constructing classifier ensembles

Ensemble classification remains one of the most popular techniques in contemporary machine learning, being characterized by both high efficiency and stability. An ideal ensemble comprises mutually complementary individual classifiers which are characterized by the high diversity and accuracy. This may be achieved, e.g., by training individual classification models on feature subspaces. Random Subspace is the most well-known method based on this principle. Its main limitation lies in stochastic nature, as it cannot be considered as a stable and a suitable classifier for real-life applications. In this paper, we propose an alternative approach, Deterministic Subspace method, capable of creating subspaces in guided and repetitive manner. Thus, our method will always converge to the same final ensemble for a given dataset. We describe general algorithm and three dedicated measures used in the feature selection process. Finally, we present the results of the experimental study, which prove the usefulness of the proposed method.     

Context‐aware language‐learning application in the green technology building: Which group can benefit the most?

To assess the effects and learner perceptions of context‐aware ubiquitous language learning (CAULL), a green‐building English‐learning application (GBELA) employing sensing technology was created to develop participants' English listening and reading skills using smartphones and QR codes. This study investigated the effects of 40 participants' perceived ease of use, usability, usefulness, learner attitude, satisfaction with the use of GBELA, and self‐efficacy in smartphone and GBELA usage. Quantitative and qualitative data through pretest/post‐test, questionnaires, and semistructured interviews were collected with a focus on green building–based English (GBbE) reading and listening skills. Results proved the effectiveness of the GBELA for both high‐achievement (HA) and low‐achievement (LA) groups. Furthermore, correlations were found between the HA group and ease of use of the GBELA. The correlations among learner perceptions and self‐efficacy showed that a well‐designed context‐aware learning system can help learners enhance self‐efficacy in CAULL mode. Implications for the design of effective context‐ and knowledge‐specific ubiquitous learning systems are provided in the study.     

On the effect of interface micro-cracks on interactions in stratified media

The aim of this paper is to describe how micro-cracks distributed on the interfaces in a periodic stratified medium effect apparent properties of this medium. The problem is investigated for linear-elastic materials and under assumption of the long-wave approximation. The general results are illustrated by a simple example of two-component stratified medium.     

Extraction of ions from a plasma source and formation of beams

The current of ions extracted from a plasma source has been measured as a function of extraction voltage U _e . Comparison of the obtained characteristics to theoretical predictions has shown that the experimental data agree with the Child-Langmuir theory only within a certain range of U _e . The results of our measurements and computer simulation of the ion-beam profile allowed the assessment of the parameters of the ion-emitting surface and the average ion energy in the plasma of the source under study.