Hasil untuk "Information technology"

Dimitrios Buhalis

K. Stiroh

Mary C. Lacity, L. Willcocks

P. Horn

B. Reich, I. Benbasat

V. Sambamurthy, R. Zmud

D. Feeny, L. Willcocks

Z. Baida, F. Koldijk, Yao-Hua Tan et al.

Hüseyin Tanriverdi

Lawrence Loh, N. Venkatraman

Abstract:This paper develops and tests a model of the determinants of information technology (IT) outsourcing by integrating both business and IT perspectives. Specifically, we attempt to explain the degree of IT outsourcing using business and IT competences as represented by their cost structures and economic performances. In addition, we posit that outsourcing is dependent on business governance, particularly financial leverage. Based on factor analyses and multiple regressions using data from fIfty-five major U.S. corporations, we observed that the degree of IT outsourcing is positively related to both business and IT cost structures. We also established that the degree ofIT outsourcing is negatively related to IT performance. Finally, we conclude with implications and future research directions.

E. Swanson, Neil C. Ramiller

Sunil Mithas, Ali Tafti, I. Bardhan et al.

Landon Kleis, Paul Chwelos, R. Ramirez et al.

Santu Mondal, Sneha Ray, Aritra Acharyya et al.

This work investigates the application of artificial neural network (ANN)-based regression models to predict the static and dynamic characteristics of GaN impact avalanche transit time (IMPATT) sources in the terahertz (THz) frequency regime. A comprehensive dataset, derived from self-consistent quantum drift-diffusion (SCQDD) simulations of GaN IMPATT structures designed for a wide frequency range from the microwave frequency bands, up to 5 THz, is used to train the ANN models. The models effectively capture the impact of variations in structural, doping, and biasing parameters on device performance. The proposed ANN approach significantly reduces computational time for predicting breakdown characteristics, power output, and conversion efficiency properties of IMPATT sources, achieving similar accuracy to traditional SCQDD simulations while requiring only 7.8&#x2013;20.1% of the computational time. Mean square errors are observed to be on the order of <inline-formula> <tex-math notation="LaTeX">$10^{-4}$ </tex-math></inline-formula>&#x2013;<inline-formula> <tex-math notation="LaTeX">$10^{-6}$ </tex-math></inline-formula>, demonstrating the models&#x2019; high accuracy. Experimental validation shows strong agreement in terms of breakdown voltage, power output, and efficiency, supporting the potential of machine learning to streamline the design and optimization of high-frequency semiconductor devices.

Xiangmeng Lin, Junyi Zhang, Kai Yuan et al.

Previous studies have shown that terahertz (THz) signals could penetrate hypersonic plasma sheaths. Thus, it is considered to be a potential solution to the “blackout” problem. Nevertheless, although previous studies have systematically revealed the signal transmission characteristics in hypersonic plasma sheaths and the influence of vehicle parameters on the communication performance, the coupling mechanism between the dynamical time-varying plasma sheath flow field and Doppler shift of THz communication signals has rarely been investigated. In this study, a layered medium model was developed to investigate the characteristics and the mechanisms for the Doppler shift in dynamical hypersonic plasma environments. The results revealed that the total Doppler shifts could be up to several megahertz (MHz), in which the Doppler shift yielded by the inhomogeneous flow field of the hypersonic plasma sheath could also reach the magnitude of several MHz. It indicates that the inhomogeneous flow field is an important mechanism for the communication capacity of Doppler shift. The dynamical evolution of the flow field yields the fluctuation of the total Doppler shift. The dynamical Doppler frequency shifts could have serious impacts on the signal demodulation, channel estimation, synchronization, and the communication capacity of the onboard system.

Saeedeh Lotfi, Martin Janda, Jan Reboun et al.

Abstract Printed electronics (PE) present a promising alternative to conventional photolithography by enabling rapid prototyping with reduced costs, material waste, and enhanced design flexibility and advantages, particularly relevant for high-frequency microwave applications. This study presents the design, fabrication, and evaluation of two microstrip low-pass filters (LPFs) with cutoff frequencies of 2.60 GHz and 3.55 GHz serving as representative components for microwave circuits, using three additive manufacturing techniques: Direct-Write (DW), Screen Printing (SP), and Aerosol Jet Printing (AJP). Over 60 filter samples were fabricated and measured to systematically assess performance across different printing methods. The LPFs were designed and analyzed through electromagnetic simulations, complemented by an LC equivalent circuit model based on actual device dimensions to better understand their behavior. Measured frequency responses showed strong agreement with simulations, validating the effectiveness of all three printing methods. Each technique demonstrated unique trade-offs between resolution, fabrication complexity, and electrical performance, emphasizing the need to tailor method selection to specific application requirements. This paper offers valuable insights into the design, analysis, and fabrication of RF and microwave circuits using printed electronics, highlighting the strengths and limitations of each technique. It serves as a practical guide for researchers in selecting suitable methods for high-frequency applications.

Cheng-Hong Yang, Chih-Hsien Wu, Kuei-Hau Luo et al.

Air pollution has become a major global threat to human health. Urbanization and industrialization over the past few decades have increased the air pollution. Plausible connections have been made between air pollutants and dementia. This study used machine learning algorithms (k-nearest neighbors, random forest, gradient-boosted decision trees, eXtreme gradient boosting, and CatBoost) to investigate the association between cognitive impairment and air pollution. Data from the Taiwan Biobank and 75 air-pollution-monitoring stations in Taiwan were analyzed to determine individual levels of exposure to air pollutants. The pollutants examined were particulate matter with a diameter of ≤ 2.5 μm (PM2.5), nitrogen dioxide, nitric oxide, carbon monoxide, and ozone. The results revealed that the most strongly correlated with cognitive impairment were ozone, PM2.5, and carbon monoxide levels with adjustment of educational level, age, and household income. The model based on these factors achieved accuracy as high as 0.97 for detecting cognitive impairment, indicating a positive association between air pollutions and cognitive impairment.

Nurezayana Zainal, Mohanavali Sithambranathan, Umar Farooq Khattak et al.

Because of its versatility and ability to work with difficult materials, Electrical Discharge Machining (EDM) has become an essential tool in many different industries. It can produce precise shapes and intricate details. EDM has transformed fabrication processes in a variety of industries, including aerospace and electronics, medical implants and surgical instruments, and the shaping of small components. Its capacity to machine undercuts and deep cavities with little material removal makes it ideal for producing complex geometries that would be challenging or impossible to accomplish with conventional machining techniques. Several attempts have been carried out to solve the optimization problem involved in the EDM process. This paper emphasizes optimizing the EDM process using three metaheuristic algorithms: Glowworm Swarm Optimization (GSO), Grey Wolf Optimizer (GWO), and Whale Optimization Algorithm (WOA). The study's outcome showed that the GWO algorithm outperformed the GSO and WOA algorithms in solving the EDM optimization problem and achieved the minimum surface roughness value of 1.7593µm.

Keenan J. A. Down, Pedro A. M. Mediano

The Shannon entropy of a random variable $X$ has much behaviour analogous to a signed measure. Previous work has concretized this connection by defining a signed measure $μ$ on an abstract information space $\tilde{X}$, which is taken to represent the information that $X$ contains. This construction is sufficient to derive many measure-theoretical counterparts to information quantities such as the mutual information $I(X; Y) = μ(\tilde{X} \cap \tilde{Y})$, the joint entropy $H(X,Y) = μ(\tilde{X} \cup \tilde{Y})$, and the conditional entropy $H(X|Y) = μ(\tilde{X}\, \setminus \, \tilde{Y})$. We demonstrate that there exists a much finer decomposition with intuitive properties which we call the logarithmic decomposition (LD). We show that this signed measure space has the useful property that its logarithmic atoms are easily characterised with negative or positive entropy, while also being coherent with Yeung's $I$-measure. We present the usability of our approach by re-examining the Gács-Körner common information from this new geometric perspective and characterising it in terms of our logarithmic atoms. We then highlight that our geometric refinement can account for an entire class of information quantities, which we call logarithmically decomposable quantities.

Laura Vilela Rodrigues Rezende, Elizabete Cristina de Souza de Aguiar Monteiro, Ketlen Stueber et al.

Aims: This article presents a study of a conceptual model for a machine-actionable Data Management Plan (maDMP - Machine Actionable Data Management Plan) for the Brazilian setting conducted by the Brazilian Institute of Information and Technology (IBICT). The objectives were to analyse the existing tools; to consider the feasibility of developing a new solution from the very beginning, or adapting and remodeling an existing one; and to design the conceptual model considering the agents involved in the Brazilian research ecosystem. Methods: This article reports an exploratory study on the development of a conceptual model of a Data Management Plan for use in the Brazilian scenario. The Design Science Research method was used, a systematic process that allows researchers to study and describe a phenomenon and also design or prescribe solutions for a specific problem (Dresch et al., 2014). Results: A detailed comparative study of the existing development tools for DMPs is presented, in addition to a description of the design of the conceptual model of the Brazilian solution. The ideal scenario for this case is the improvement of the existing DMPTool tool, optimizing resources and development time. This robust instrument has accompanied the development of resources that will establish it a tool for creating DMPs that can be activated by machines. The study identifies the connections and exchanges of information necessary for the Brazilian Science ecosystem, in which the IBICT's DMP tool can play a centralizing and aggregating role.