Market orientation,restructuring and collaboration: The impact of digital design on organizational competitiveness

Design is commonly understood as a key element of products, contributing to their distinctiveness, usability and aesthetics. The success of a product is increasingly related to the user experience or the aesthetics of the user interface, meaning that design is increasingly important in the digital environment. The shift in competitive focus to the customer induced by digital design encourages companies to innovate and can also lead to changes in internal operations, market orientation and the reconfiguration of external collaboration procedures. This dimension of digital design-induced effects has to date seen very little research. The objective of this study is to investigate how digital design-induced changes in market orientation, internal restructuring and external cooperation affect firms' competitive orientation. The simultaneous equation framework was applied to a survey of 515 user interface and experience designers from France. Our results suggest that market orientation is not the only channel through which digital design influences firm competitiveness. Digital design leads to organizational change and the reconfiguration of external relationships that directly and indirectly help companies build competitive advantages and increase customer satisfaction.     

A systematic review on the use of quantitative imaging to detect cancer therapy adverse effects in normal-appearing brain tissue

Cancer therapy for both central nervous system (CNS) and non-CNS tumors has been previously associated with transient and long-term cognitive deterioration, commonly referred to as ‘chemo fog’. This therapy-related damage to otherwise normal-appearing brain tissue is reported using post-mortem neuropathological analysis. Although the literature on monitoring therapy effects on structural magnetic resonance imaging (MRI) is well established, such macroscopic structural changes appear relatively late and irreversible. Early quantitative MRI biomarkers of therapy-induced damage would potentially permit taking these treatment side effects into account, paving the way towards a more personalized treatment planning.

This systematic review (PROSPERO number 224196) provides an overview of quantitative tomographic imaging methods, potentially identifying the adverse side effects of cancer therapy in normal-appearing brain tissue. Seventy studies were obtained from the MEDLINE and Web of Science databases. Studies reporting changes in normal-appearing brain tissue using MRI, PET, or SPECT quantitative biomarkers, related to radio-, chemo-, immuno-, or hormone therapy for any kind of solid, cystic, or liquid tumor were included. The main findings of the reviewed studies were summarized, providing also the risk of bias of each study assessed using a modified QUADAS-2 tool. For each imaging method, this review provides the methodological background, and the benefits and shortcomings of each method from the imaging perspective. Finally, a set of recommendations is proposed to support future research.

     

Model-based Predictive Control of Hybrid Systems: A Probabilistic Neural-network Approach to Real-time Control

This paper proposes an approach for reducing the computational complexity of a model-predictive-control strategy for discrete-time hybrid systems with discrete inputs only. Existing solutions are based on dynamic programming and multi-parametric programming approaches, while the one proposed in this paper is based on a modified version of performance-driven reachability analyses. The algorithm abstracts the behaviour of the hybrid system by building a ’tree of evolution’. The nodes of the tree represent the reachable states of a process, and the branches correspond to input combinations leading to designated states. A cost-function value is associated with each node and based on this value the exploration of the tree is driven. For any initial state, an input sequence is thus obtained, driving the system optimally over a finite horizon. According to the model predictive strategy, only the first input is actually applied to the system. The number of possible discrete input combinations is finite and the feasible set of the states of the system may be partitioned according to the optimization results. In the proposed approach, the partitioning is performed offline and a probabilistic neural network (PNN) is then trained by the set of points at the borders of the state-space partitions. The trained PNN is used as a system-state-based control-law classifier. Thus, the online computational effort is minimized and the control can be implemented in real time.     

Differential evolution and differential ant-stigmergy on dynamic optimisation problems

Many real-world optimisation problems are of dynamic nature, requiring an optimisation algorithm which is able to continuously track a changing optimum over time. To achieve this, we propose two population-based algorithms for solving dynamic optimisation problems (DOPs) with continuous variables: the self-adaptive differential evolution algorithm (jDE) and the differential ant-stigmergy algorithm (DASA). The performances of the jDE and the DASA are evaluated on the set of well-known benchmark problems provided for the special session on Evolutionary Computation in Dynamic and Uncertain Environments. We analyse the results for five algorithms presented by using the non-parametric statistical test procedure. The two proposed algorithms show a consistently superior performance over other recently proposed methods. The results show that both algorithms are appropriate candidates for DOPs.     

Automated building extraction from IKONOS images in suburban areas

The article addresses automatic building extraction from IKONOS images in suburban areas. In the proposed approach, we used a stereo pair of IKONOS images. Automatic photogrammetric methods of image matching were used to generate a digital surface model (DSM) and a digital elevation model. In further processing, single-image methods were used. The orthophotos of individual bands were created. The initial building mask was generated from the calculated normalized DSM (nDSM). The calculated normalized difference vegetation index and the road data extracted from the existing topographical database were used to remove vegetation and traffic surfaces. The mask was further improved with our own combination of methods based on non-linear diffusion filtering, unsupervised classification, colour segmentation and region growing. The final mask was vectorized using the Hough transform. Compared with a reference building database, 83.2% of the buildings in the test area were detected using the proposed approach with a quality percentage (how likely a building pixel produced by an automatic approach is correct) of 49.46.     

0-homogeneous effect algebras

In the present paper, we introduce a proper superclass of homogeneous effect algebras. We call this superclass as 0-homogeneous effect algebras. We prove that in every 0-homogeneous effect algebra, the set of all sharp elements forms a subalgebra. Every chain-complete 0-homogeneous effect algebra is homogeneous.     

Microhardness characterization of stability of Fe-Ni-base metallic glasses

The stability of Fe-Ni-base metallic glasses on annealing in the range 30 to 1000° C was investigated by microhardness measurements. The results (i.e. two maxima in all recorded curves, for annealing temperatures below and above 400° C) were correlated with other recent experimental evidence for structural relaxation and structural changes in the same metallic glasses.     

Polymerization of carbazolyl-containing epoxides with triphenylcarbenium salts

Summary Polymerization of 9-(2,3-epoxypropyl) carbazole (EPC) and 1,2-epoxy-6-(9-carbazolyl)-4-oxahexane (ECOH) with triphenylcarbenium hexachloroantimonate and triphenylcarbenium tetrafluoroborate have been studied by the microcalorimetric technique. Triphenylcarbenium salts have turn out to be more efficient catalyst for the polymerization of carbazolyl-containing epoxides than Lewis acids, giving high yields at low initial concentration of the catalyst. Using comparatively restricted conditions of reaction ([triphenylcarbenium saltyda]_o0.02 mol/l t50° C) transition from the conventional active chain end mechanism to the activated monomer mechanism has been observed at a sufficiently high degree of conversion of monomer.