Hasil untuk "Information technology"

D. Bandyopadhyay, Jaydip Sen

D. McKnight, Michelle Carter, J. Thatcher et al.

Rupak Rauniar, Greg Rawski, Jei Yang et al.

M. Paris

Several quantities of interest in quantum information, including entanglement and purity, are nonlinear functions of the density matrix and cannot, even in principle, correspond to proper quantum o...

O. Bandiera, Imran Rasul

T. Ravichandran, Chalermsak Lertwongsatien, Chalermsak Lertwongsatien

Lei-da Chen, M. Gillenson, D. Sherrell

P. Geroski

A. Gunasekaran, E. Ngai

D. Avison, M. D. Myers

E. Brodman

The original edition of this book summarized more than a decade of work on communications flow in science and engineering organizations, showing how human and organizational systems could be restructured to bring about improved productivity and better person-to-person contact. While many studies have been done since then, few of them invalidate the general conclusions and recommendations Allen offers. In a new preface he points out new developments, noting areas that need some modification, elaboration, or extension, and directing readers to the appropriate journal articles where the findings, are reported. The first three chapters provide an overview of the communication system in technology, present the author's research methods, and describe differences in the career paths and goals of engineers and scientists that cause special problems for organizations. The book then discusses how technological information is acquired by the R & D organization, shows how critical technical communication within the laboratory is for R & D performance, and originates the idea of the "gatekeeper," the person who links his or her organization to the world at large. Concluding chapters take up the influence of formal and informal organization and of architecture and office layouts on communication. Many of these ideas have been successfully incorporated by architects and managers in the design of new R & D facilities and complexes. Suggested Citation Handle: RePEc:mtp:titles:0262510278 Download reference as HTML Thomas J. Allen, 1984. "Managing the Flow of Technology: Technology Transfer and the Dissemination of Technological Information Within the R&D Organization," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262510278, November. More services and features MyIDEAS Follow serials, authors, keywords & more New papers by email Subscribe to new additions to RePEc Author registration Public profiles for Economics researchers MPRA Upload your paper to be listed on RePEc and IDEAS EconAcademics Blog aggregator for economics research Plagiarism Cases of plagiarism in Economics Rankings Various rankings of research in Economics & related fields RePEc Genealogy Who was a student of whom, using RePEc RePEc Biblio Curated articles & papers on various economics topics Job market papers RePEc working paper series dedicated to the job market Fantasy league Pretend you are at the helm of an economics department Services from the StL Fed Data, research, apps & more from the St. Louis Fed IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.

Xin Li, Traci J. Hess, J. Valacich

H. Ernst

Bruce Bimber

Gil Gonzales

At present, biometric systems of human identification are widely used. Classical identification systems require knowledge of the password, the presence of a key, identification card, or other identifying item, it can forget or lose. In contrast, biometric systems are based on unique biological characteristics of a person that are difficult to forge and which uniquely identify a particular person. Such characteristics include, for example, fingerprints, palm shape, face geometry, iris pattern and retina image [1]. According to the report «Faith in Technology», prepared in May 2017 by HSBC, the countries of Asia and the Middle East are ahead of the West in the introduction of biometric technologies. India tops the list of countries with the greatest distribution of biometric identification tools, whose residents three times (9 %) used «iris recognition» for identification, than residents of any other country (3 %) who participated in the study. The Chinese prefer using fingerprint scanners (40 %). They are followed by Indians (31 %) and residents of the UAE (25 %). At the same time, only 9 % of French and Germans, and 14 % of Canadians used fingerprint scanning technology for identification [2]. At the same time, the regular use of traditional technologies, such as password-based identification, is most common in the West. When it comes to managing money assets, people in India (50 %) and China (48 %) are much more likely to trust computer advice than people, while for Canada and the UK this figure was 18 % and 21 %, respectively [2]. The task of identifying a person’s face in a natural or artificial environment and further identification has always been among the top priorities for researchers working in the field of computer vision systems and artificial intelligence. Nevertheless, many studies conducted in leading scientific centers around the world for several decades have not led to the creation of real computer vision systems capable of detecting and recognizing a person in any conditions. Despite the proximity of the tasks and methods used in the development of alternative systems for biometric identification of a person, such as fingerprint identification or iris image, the face image recognition systems are significantly inferior to these systems. Therefore, the issue of research, improvement and development of modern methods and technologies for human face recognition is an urgent task.

Yunfei Li, Jun Wei, Shaohua Cheng et al.

Spectral detection technology offers non-destructive, in situ, and high-speed capabilities, making it widely applicable for detecting biological and chemical samples and quantifying their concentrations. Water resources, essential to life on Earth, are widely distributed across the planet. The application of spectral technology to underwater environments is useful for wide-area water resource monitoring. Although spectral detection technology is well-established, its underwater application presents challenges, including waterproof housing design, power supply, and data transmission, which limit widespread application of underwater spectral detection. Furthermore, underwater spectral detection necessitates the development of compatible computational methods for sample classification or regression analysis. Focusing on underwater spectral detection, this work involved the construction of a suitable hardware system. A compact spectrometer and LEDs (400 nm–800 nm) were employed as the detection and light source modules, respectively, resulting in a compact system architecture. Extensive tests confirmed that the miniaturized design-maintained system performance. Further, this study addressed the estimation of total phosphorus (TP) concentration in water using spectral data. Samples with varying TP concentrations were prepared and calibrated against standard detection instruments. Subsequently, classification algorithms applied to the acquired spectral data enabled the in situ underwater determination of TP concentration in these samples. This work demonstrates the feasibility of underwater spectral detection for future in situ, high-speed monitoring of aquatic biochemical indicators. In the future, after adding UV LED light source, more water quality parameter information can be obtained.

Shuangyu Chen, Wenqian Chen, Tinghui Xu et al.

Gastric cancer (GC) remains one of the leading causes of cancer-related mortality worldwide, with limited responses to immune checkpoint blockade (ICB) therapies in most patients. Increasing evidence indicates that the tumor immune microenvironment (TIME) plays a crucial role in immunotherapy outcomes. Among various metabolic abnormalities in the TIME, dysregulated lipid metabolism has emerged as a critical determinant of immune cell fate, differentiation, and function. In this review, we comprehensively summarize the current understanding of the immune landscape in GC, focusing on how altered lipid metabolism reshapes immune cell populations—including tumor-associated macrophages (TAMs), dendritic cells (DCs), regulatory T cells (Tregs), myeloid-derived suppressor cells (MDSCs), and cytotoxic CD8+ T cells. We highlight key metabolic pathways such as fatty acid oxidation(FAO), cholesterol homeostasis, and lipid uptake that impact immune cell activity, contributing to immune evasion and therapeutic resistance. Importantly, we explore emerging therapeutic strategies targeting lipid metabolism, including inhibitors of cluster of differentiation 36 (CD36), fatty acid synthase (FASN), and sterol regulatory element-binding protein 1 (SREBP1) and discuss their synergistic potential when combined with ICB therapies. In conclusion, lipid metabolic reprogramming represents a promising yet underexplored axis in modulating antitumor immunity in GC. Integrating metabolic intervention with immunotherapy holds potential to overcome current treatment limitations and improve clinical outcomes. Future studies incorporating spatial omics and single-cell profiling will be essential to elucidate cell-type specific metabolic dependencies and foster translational breakthroughs.

ZHANG Wanxiang, ZHANG Xianyong, YANG Jilin et al.

Attribute reduction relies on knowledge granulation and uncertainty measurement， thus facilitating intelligent recognition. For incomplete continuous data， neighborhood decision rough sets induce attribute reduction. However， the related neighborhood relation deserves optimal improvements， while the existing decision cost deserves integrated reinforcements. In this paper， a new neighborhood relation is proposed， and three decision-cost fusion measures are constructed， so new incomplete neighborhood decision rough sets are established and the attribute reduction is systematically researched. At first， an improved distance is introduced to produce an incomplete neighborhood relation， so improved rough sets on incomplete neighborhood are proposed. Then， the dependence degree and neighborhood entropy are introduced based on decision costs， so three fusion measures on decision costs are obtained by multiplication fusion， thus acquiring granulation non-monotonicity. Furthermore， eight heuristic reduction algorithms based on attribute importances are designed from two neighborhood relations and four relevant measures of decision costs. As finally verified by data experiments， the five algorithms out of the seven new algorithms have good performance of classification learning， thus improving the basic reduction algorithm.

Gebrail Bekdaş, Yaren Aydın, Umit Işıkdağ et al.

Shear wave velocity (V_s) is an important soil parameter to be known for earthquake-resistant structural design and an important parameter for determining the dynamic properties of soils such as modulus of elasticity and shear modulus. Different V_s measurement methods are available. However, these methods, which are costly and labor intensive, have led to the search for new methods for determining the V_s. This study aims to predict shear wave velocity (V_s (m/s)) using depth (m), cone resistance (q_c) (MPa), sleeve friction (f_s) (kPa), pore water pressure (u₂) (kPa), N, and unit weight (kN/m³). Since shear wave velocity varies with depth, regression studies were performed at depths up to 30 m in this study. The dataset used in this study is an open-source dataset, and the soil data are from the Taipei Basin. This dataset was extracted, and a 494-line dataset was created. In this study, using HyperNetExplorer 2024V1, V_s prediction based on depth (m), cone resistance (q_c) (MPa), shell friction (f_s), pore water pressure (u₂) (kPa), N, and unit weight (kN/m³) values could be performed with satisfactory results (R² = 0.78, MSE = 596.43). Satisfactory results were obtained in this study, in which Explainable Artificial Intelligence (XAI) models were also used.

N. Roztocki, Piotr Soja, H. Weistroffer

ABSTRACT In this introduction to the special issue on the role of information and communication technologies (ICT) in socioeconomic development, we provide a conceptual framework that considers four dimensions that impact socioeconomic development: policy, business, technology, and society. This framework, which is systematically constructed from reviewing several earlier frameworks but more general in focus, is intended to provide context for the eight papers in this special issue, and also guidance for future-related research.