Human-Machine Function Allocation In Information Systems: A Comprehensive Approach

In the past, information systems development methodologies primarily focus on whether the needs of an organization could be met. In recent years, several human-centered systems development methodologies are developed to emphasize both organizational and human needs. In addition to an information system being useful, its usability become a central concern, and user analysis and task analysis are important parts in these methodologies. Human-machine function allocation is an important aspect of task analysis. Yet, current research and practice in this area show a gap for systematic and consistent guidelines and approaches. To address this gap, this paper proposes three guidelines and a comprehensive approach for human-machine function allocation when designing organizational information systems. Built on Price’s decision matrix, Levels of Automation, and the Analytic Hierarchy Process (AHP), our approach consists of four steps in determining human-machine function allocation. To illustrate this approach, an application example is provided

A Typology Of Online Window Shopping Consumers

Consumer online shopping behaviors are well attended in the IS and marketing literature. Yet, there is another group of individuals who spend a lot of time online but do not purchase anything. This online window shopping phenomenon is intriguing to both scholars and marketers yet it is less studied and little understood. Questions such as what the online window shopping consumers do during their visits, how to differentiate their activities and how to design marketing strategies to stimulate them to buy are all essential and beg for investigation. To address this gap, we propose a typology of online window shopping consumers based on the Consumer Information Processing Model, then empirically validate and refine the typology using a set of clickstream data. The final typology contains four main types of online window shopper consumers: 1) promotion finders, 2) social & hedonic experience seekers, 3) information gatherers, and 4) learners & novices. This study extends consumer online behavior research in both e-commerce and social commerce by focusing on the specific group of consumers who only do online window shopping. Besides theoretical contributions, the findings also provide marketers and businesses with valuable references for designing targeted marketing strategies or promotional activities for online window shopping consumers

Foam materials with controllable pore structure prepared from nanofibrillated cellulose with addition of alcohols

Low-density foams based on nanofibrillated cellulose (NFC) made from Pinus massonianesoftwood pulp were prepared from NFC aqueous suspensions containing one of four C2–C4alcohols followed by freeze-drying, with the goal of controlling their pore structure and reducing the shrink rate. The foams prepared from NFC suspensions containing ethanol, isopropanol and n-butanol exhibited highly porous structures with a honeycomb-like cellular texture featuring well-defined “cell walls” between the layers. By contrast, the tert-butanol/NFC foam featured a higher number of smaller size pores with irregular shape. The foams prepared by freezing at −196 °C with ethanol also revealed small size pores, with no layered pore structure. The results obtained suggested that freeze-drying could be used to control the key foam parameters by adding different alcohols into an NFC suspension and adjusting the freezing temperature. Combining the obtained information, a possible formation mechanism was proposed. The microstructure, density, porosity, shrinkage, mechanical properties and thermal properties of NFC foams were determined. The obtained NFC foams feature low shrinkage upon formation and thermal conductivity. Smaller Young’s modulus and energy absorption yet similar yield stress values compared to the blank indicate that the freeze-drying in the presence of alcohols tends to generate “soft” foams

Analysis on the Filament Structure Evolution in Reset Transition of Cu/HfO2/Pt RRAM Device

The resistive switching (RS) process of resistive random access memory (RRAM) is dynamically correlated with the evolution process of conductive path or conductive filament (CF) during its breakdown (rupture) and recovery (reformation). In this study, a statistical evaluation method is developed to analyze the filament structure evolution process in the reset operation of Cu/HfO₂/Pt RRAM device. This method is based on a specific functional relationship between the Weibull slopes of reset parameters' distributions and the CF resistance (R on). The CF of the Cu/HfO₂/Pt device is demonstrated to be ruptured abruptly, and the CF structure of the device has completely degraded in the reset point. Since no intermediate states are generated in the abrupt reset process, it is quite favorable for the reliable and stable one-bit operation in RRAM device. Finally, on the basis of the cell-based analytical thermal dissolution model, a Monte Carlo (MC) simulation is implemented to further verify the experimental results. This work provides inspiration for RRAM reliability and performance design to put RRAM into practical application

Quad-Net: Quad-domain Network for CT Metal Artifact Reduction

Metal implants and other high-density objects in patients introduce severe streaking artifacts in CT images, compromising image quality and diagnostic performance. Although various methods were developed for CT metal artifact reduction over the past decades, including the latest dual-domain deep networks, remaining metal artifacts are still clinically challenging in many cases. Here we extend the state-of-the-art dual-domain deep network approach into a quad-domain counterpart so that all the features in the sinogram, image, and their corresponding Fourier domains are synergized to eliminate metal artifacts optimally without compromising structural subtleties. Our proposed quad-domain network for MAR, referred to as Quad-Net, takes little additional computational cost since the Fourier transform is highly efficient, and works across the four receptive fields to learn both global and local features as well as their relations. Specifically, we first design a Sinogram-Fourier Restoration Network (SFR-Net) in the sinogram domain and its Fourier space to faithfully inpaint metal-corrupted traces. Then, we couple SFR-Net with an Image-Fourier Refinement Network (IFR-Net) which takes both an image and its Fourier spectrum to improve a CT image reconstructed from the SFR-Net output using cross-domain contextual information. Quad-Net is trained on clinical datasets to minimize a composite loss function. Quad-Net does not require precise metal masks, which is of great importance in clinical practice. Our experimental results demonstrate the superiority of Quad-Net over the state-of-the-art MAR methods quantitatively, visually, and statistically. The Quad-Net code is publicly available at https://github.com/longzilicart/Quad-Net

Theoretical Analysis of Double Logistic Distributed Activation Energy Model for Thermal Decomposition Kinetics of Solid Fuels

The distributed activation energy model (DAEM) has been widely used to analyze the thermal decomposition of solid fuels such as lignocellulosic biomass and its components, coal, microalgae, oil shale, waste plastics, and polymer etc. The DAEM with a single distribution of activation energies cannot describe those reactions well since the thermal decomposition normally involves multiple sub-processes of various components. The double DAEM employs a double distribution to represent the activation energies. The Gaussian distribution is usually used to represent the activation energies. However, it is not sufficiently accurate for addressing the activation energies in the initial and final stages of the thermal decomposition reactions of solid fuels. Compared to the Gaussian distribution, the logistic distribution is slightly thicker at the curve tail and suits better to describe the activation energy distribution. In this work, a theoretical analysis of the double logistic DAEM for the thermal decomposition kinetics of solid fuels has been systematically investigated. After the derivation of the double logistic DAEM, its numerical calculation method and the physical meanings of the model parameters have been presented. Three typical types of simulated double logistic DAEM processes have been obtained according to the overlapped situation of two derivative conversion peaks, namely separated, overlapped and partially overlapped processes. It is found that, for the partially overlapped process, the form of the minor peak (overlapped peak or peak shoulder) depends on the values of the frequency factor and heating rate. Considering the simulated processes and related examples from literature, the double logistic DAEM has been remarked as a more reliable tool with abundant flexibility to explain the thermal decomposition of various solid fuels. More accurate results are expected if the double logistic DAEM is coupled with the computational fluid dynamics (CFD) simulation for those reactions mentioned above

Raw rehmannia radix polysaccharide can effectively release peroxidative injury induced by duck hepatitis A virus

Background: Duck viral hepatitis (DVH), caused by duck hepatitis A virus (DHAV), is a fatal contagious infectious disease which spreads rapidly with high morbidity and high mortality, and there is no effective clinical drug against DVH.Materials and Methods: Raw Rehmannia Radix Polysaccharide (RRRP), Lycii Fructus polysaccharides and Astragalus Radix polysaccharides were experimented in vitro and in vivo. Mortality rate, livers change, liver lesion scoring, peroxidative injury evaluation indexes in vitro and in vivo, and hepatic injury evaluation indexes of optimal one were detected and observed in this experiment.Results: RRRP could reduce mortality with the protection rate about 20.0% compared with that of the viral control (VC) group, finding that RRRP was the most effective against DHAV. The average liver scoring of the VC, blank control (BC), RRRP groups were 3.5, 0, 2.1. Significant difference (P<0.05) appeared between any two groups, demonstrating that it can alleviate liver pathological change. RRRP could make the hepatic injury evaluation indexes similar to BC group while the levels of the VC group were higher than other two groups in general. The levels of SOD, GSH-Px, CAT of RRRP group showed significant higher than that of VC group while the levels of NOS and MDA showed the opposite tendency, thus, RRRP could release peroxidative injury.Conclusion: RRRP was the most effective against duck hepatitis A virus (DHAV). RRRP could reduce mortality, alleviate liver pathological change, down-regulate liver lesion score, release peroxidative injury and hepatic injury. The antiviral and peroxidative injury releasing activity of RRRP for DHAV provided a platform to test novel drug strategies for hepatitis A virus in human beings.Keywords: Raw Rehmannia Radix Polysaccharide; duck hepatitis A virus; peroxidative injury; hepatic injur

Identification of a HIV Gp41-Specific Human Monoclonal Antibody With Potent Antibody-Dependent Cellular Cytotoxicity

Antibody-Dependent Cellular Cytotoxicity (ADCC) is a major mechanism of protection against viral infections in vivo. Identification of HIV-1-specific monoclonal antibodies (mAbs) with potent ADCC activity may help develop an effective HIV-1 vaccine. In present study, we isolated such human mAb, designated E10, from an HIV-1-infected patient sample by single B cell sorting and single cell PCR. E10 bound to gp140 trimer and linear peptides derived from gp41 membrane proximal external region (MPER). E10 epitope (QEKNEQELLEL) overlapped with mAb 2F5 epitope. However, E10 differentiated from 2F5 in neutralization breadth and potency, as well as ADCC activity. E10 showed low neutralization activity and narrow spectrum of neutralization compared to 2F5, but it mediated higher ADCC activity than 2F5 at low antibody concentration. Fine mapping of E10 epitope may potentiate MPER-based subunit vaccine development