Re-examining the causal structure of information technology impact research

About 20 years ago, Markus and Robey noted that most research on IT impacts had been guided by deterministic perspectives and had neglected to use an emergent perspective, which could account for contradictory findings. They further observed that most research in this area had been carried out using variance theories at the expense of process theories. Finally, they suggested that more emphasis on multilevel theory building would likely improve empirical reliability. In this paper, we reiterate the observations and suggestions made by Markus and Robey on the causal structure of IT impact theories and carry out an analysis of empirical research published in four major IS journals, Management Information Systems Quarterly (MISQ), Information Systems Research (ISR), the European Journal of Information Systems (EJIS), and Information and Organization (I&O), to assess compliance with those recommendations. Our final sample consisted of 161 theory-driven articles, accounting for approximately 21% of all the empirical articles published in these journals. Our results first reveal that 91% of the studies in MISQ, ISR, and EJIS focused on deterministic theories, while 63% of those in I&O adopted an emergent perspective. Furthermore, 91% of the articles in MISQ, ISR, and EJIS adopted a variance model; this compares with 71% from I&O that applied a process model. Lastly, mixed levels of analysis were found in 14% of all the surveyed articles. Implications of these findings for future research are discussed.     

A Randomized Algorithm for Online Unit Clustering

In this paper, we consider the online version of the following problem: partition a set of input points into subsets, each enclosable by a unit ball, so as to minimize the number of subsets used. In the one-dimensional case, we show that surprisingly the naïve upper bound of 2 on the competitive ratio can be beaten: we present a new randomized 15/8-competitive online algorithm. We also provide some lower bounds and an extension to higher dimensions.     

Strategic reasoning about business models: a conceptual modeling approach

Strategic reasoning about business models is an integral part of service design. In fast moving markets, businesses must be able to recognize and respond strategically to disruptive change. They have to answer questions such as: what are the threats and opportunities in emerging technologies and innovations? How should they target customer groups? Who are their real competitors? How will competitive battles take shape? In this paper we define a strategic modeling framework to help understand and analyze the goals, intentions, roles, and the rationale behind the strategic actions in a business environment. This understanding is necessary in order to improve existing or design new services. The key component of the framework is a strategic business model ontology for representing and analyzing business models and strategies, using the i* agent and goal oriented methodology as a basis. The ontology introduces a strategy layer which reasons about alternative strategies that are realized in the operational layer. The framework is evaluated using a retroactive example of disruptive technology in the telecommunication services sector from the literature.     

Weak and strong stabilization of linear systems

We study the problem of stabilizing a distributed linear system on a subregion of its geometrical domain. We are concerned with two methods： the first approach enables us to characterize a stabilizing control via the steady state Riccati equation, and the second one is based on decomposing the state space into two suitable subspaces and studying the projections of the initial system onto such subspaces. The obtained results are performed through various examples.     

Agent-based time delay margin in consensus of multi-agent systems by an event-triggered control method: Concept and computation

This paper deals with defining the concept of agent-based time delay margin and computing its value in multi-agent systems controlled by event-triggered based controllers. The agent-based time delay margin specifying the time delay tolerance of each agent for ensuring consensus in event-triggered controlled multi-agent systems can be considered as complementary for the concept of (network) time delay margin, which has been previously introduced in some literature. In this paper, an event-triggered control method for achieving consensus in multi-agent systems with time delay is considered. It is shown that the Zeno behavior is excluded by applying this method. Then, in a multi-agent system controlled by the considered event-triggered method, the concept of agent-based time delay margin in the presence of a fixed network delay is defined. Moreover, an algorithm for computing the value of the time delay margin for each agent is proposed. Numerical simulation results are also provided to verify the obtained theoretical results.     

Modulation Based Combination of High Level Features Generated from SCCF & Contourlet Transforms for CBIR Applications

The need for suitable and cost-effective technologies rise with the growth of the internet of things (IoT) applications. These aim at handling voluminous data transmission in addition to minimum energy and latency cost constraints. LoRa networks are recommended for applications in confined spaces, long ranges, and less battery consumption requirements. However, the end devices in these networks communicate to all gateways in their ranges, thereby expediting energy unproductively in redundant transmissions. In our article, we explore the possibilities of whether LoRa networks could employ the advantages of clustering and propose two algorithms, path-based and data-centric, for such networks. We suggest that LoRaWAN technology with clustering can be apt for long-range, low power consumption IoT applications in the future. We study the impact of network density, node range, and cluster range on the energy consumption in data transmissions. The algorithms are compared with the inherent star-based communication of LoRa networks based on energy consumed, and our results show that, for dense deployments, clustering becomes advantageous.

     

An Improvement Energy Consumption Policy Using Communication Reduction in Wireless Body Sensor Network

Dedicated short-range communications (DSRC) is an important wireless technology for current and future automotive safety and mitigation of traffic jams. In this work, we have designed a Coplanar waveguide microstrip patch antenna with linear, upper and bottom and side slots for application in DSRC. The patch antenna was designed using glass epoxy substrate (FR4). Various parametric analyses such as the current distribution, reflection coefficient, radiation pattern on E- and H-plane as well as the realized gain (dB) were performed. The results were obtained by simulation using high-frequency structure simulator tool. The proposed antenna covers a frequency band of 5.8–5.9 GHz which is highly dedicated to the DSRC wireless communication technology for enhancement of safety of the automotive transport system. The designed antenna shows a good return loss of ??19 dB at 5.9 GHz.The designed antenna shows a promising gain, return loss and radiation pattern for use in DSRC for automotive transport systems.

     

Electrohydrodynamic‐Induced SERS Immunoassay for Extensive Multiplexed Biomarker Sensing

Cancer diagnosis and patient monitoring require sensitive and simultaneous measurement of multiple cancer biomarkers considering that single biomarker analysis present inadequate information on the underlying biological transformations. Thus, development of sensitive and selective assays for multiple biomarker detection might improve clinical diagnosis and expedite the treatment process. Herein, a microfluidic platform for the rapid, sensitive, and parallel detection of multiple cancer‐specific protein biomarkers from complex biological samples is presented. This approach utilizes alternating current electrohydrodynamic‐induced surface shear forces that provide exquisite control over fluid flow thereby enhancing target–sensor interactions and minimizing non‐specific binding. Further, the use of surface‐enhanced Raman scattering‐based spectral encoding with individual barcodes for different targets enables specific and simultaneous detection of captured protein biomarkers. Using this approach, the specific and sensitive detection of clinically relevant biomarkers including human epidermal growth factor receptor 2 (HER2); Mucin 1, cell surface associated (MUC1); epidermal growth factor receptor; and Mucin 16, cell surface associated (MUC16) at concentrations as low as 10 fg mL^?1 in patient serum is demonstrated. Successful target detection from patient samples further demonstrates the potential of this current approach for the clinical diagnosis, which envisages a clinical translation for a rapid and sensitive appraisal of clinical samples in cancer diagnostics.     

Effect of Ag‐NPs synthesised by Chamaemelum nobile extract on the inflammation and oxidative stress induced by carrageenan in mice paw

An environmentally friendly and rapid procedure was developed to synthesise silver nanoparticles (Ag‐NPs) by Chamaemelum nobile extract and to evaluate its in vivo anti‐inflammatory and antioxidant activities. The ultraviolet–visible absorption spectrum of the synthesised Ag‐NPs showed an absorbance peak at 422. The average size of spherical nanoparticles was 24 nm as revealed by transmission electron microscopy. Fourier transform infra‐red spectroscopy analysis supported the presence of biological active compounds involved in the reduction of Ag ion and X‐ray diffraction confirmed the crystalline structure of the metallic Ag. The anti‐inflammatory and antioxidant activity of the Ag‐NPs was investigated against carrageenan‐induced paw oedema in mice. The levels of malondialdehyde (MDA) and antioxidant enzymes superoxide dismutase, catalase, glutathione peroxidase and inflammatory cytokines tumour necrosis factor (TNF‐α), interferon gamma and interleukin (IL)‐6, IL‐1β were assessed in this respect. The results demonstrated that anti‐inflammatory activity of the Ag‐NPs might be due to the ability of the nanoparticles to reduce IL‐1β, IL‐6 and TNF‐α. Moreover, reduction of antioxidant enzymes along with an increase in MDA level shows that the anti‐inflammatory activity of the synthesised Ag‐NPs by C. nobile is attributed to its ameliorating effect on the oxidative damage.Inspec keywords: silver, nanoparticles, nanofabrication, ultraviolet spectra, visible spectra, particle size, transmission electron microscopy, Fourier transform infrared spectra, X‐ray diffraction, crystal structure, enzymes, molecular biophysics, tumours, biomedical materials, nanomedicineOther keywords: Chamaemelum nobile extract, oxidative stress, mice paw, silver nanoparticles, antiinflammatory activity, antioxidant activity, ultraviolet‐visible absorption spectrum, spherical nanoparticle size, transmission electron microscopy, Fourier transform infrared spectroscopy, biological active compounds, X‐ray diffraction, crystalline structure, carrageenan‐induced paw oedema, malondialdehyde, antioxidant enzymes, superoxide dismutase, catalase, glutathione peroxidase, inflammatory cytokines, tumour necrosis factor, interferon gamma, interleukin, IL‐1β, IL‐6, TNF‐α, MDA level, Ag