全文获取类型
收费全文 | 34763篇 |
免费 | 5482篇 |
国内免费 | 2346篇 |
专业分类
电工技术 | 11191篇 |
技术理论 | 2篇 |
综合类 | 3037篇 |
化学工业 | 1142篇 |
金属工艺 | 937篇 |
机械仪表 | 4670篇 |
建筑科学 | 994篇 |
矿业工程 | 2085篇 |
能源动力 | 1278篇 |
轻工业 | 257篇 |
水利工程 | 794篇 |
石油天然气 | 2493篇 |
武器工业 | 583篇 |
无线电 | 2322篇 |
一般工业技术 | 1863篇 |
冶金工业 | 921篇 |
原子能技术 | 271篇 |
自动化技术 | 7751篇 |
出版年
2024年 | 136篇 |
2023年 | 640篇 |
2022年 | 1167篇 |
2021年 | 1385篇 |
2020年 | 1482篇 |
2019年 | 1055篇 |
2018年 | 966篇 |
2017年 | 1186篇 |
2016年 | 1360篇 |
2015年 | 1552篇 |
2014年 | 2409篇 |
2013年 | 1956篇 |
2012年 | 2677篇 |
2011年 | 2776篇 |
2010年 | 2035篇 |
2009年 | 2181篇 |
2008年 | 2094篇 |
2007年 | 2586篇 |
2006年 | 2280篇 |
2005年 | 1885篇 |
2004年 | 1616篇 |
2003年 | 1460篇 |
2002年 | 1096篇 |
2001年 | 1005篇 |
2000年 | 790篇 |
1999年 | 687篇 |
1998年 | 434篇 |
1997年 | 342篇 |
1996年 | 313篇 |
1995年 | 278篇 |
1994年 | 182篇 |
1993年 | 140篇 |
1992年 | 106篇 |
1991年 | 86篇 |
1990年 | 67篇 |
1989年 | 42篇 |
1988年 | 33篇 |
1987年 | 15篇 |
1986年 | 11篇 |
1985年 | 9篇 |
1984年 | 6篇 |
1982年 | 6篇 |
1981年 | 6篇 |
1980年 | 9篇 |
1979年 | 4篇 |
1977年 | 4篇 |
1975年 | 4篇 |
1966年 | 3篇 |
1961年 | 3篇 |
1951年 | 4篇 |
排序方式: 共有10000条查询结果,搜索用时 15 毫秒
11.
Junyu Chen Yuze Li Yuming Jiang Liucheng Mao Mi Lai Lixia Jiang Huihui Liu Zongxiu Nie 《Advanced functional materials》2021,31(52):2106743
Cancer remains an intractable medical problem. Rapid diagnosis and identification of cancer are critical to differentiate it from nonmalignant diseases. High-throughput biofluid metabolic analysis has potential for cancer diagnosis. Nevertheless, the present metabolite analysis method does not meet the demand for high-throughput screening of diseases. Herein, a high-throughput, cost-effective, and noninvasive urine metabolic profiling method based on TiO2/MXene-assisted laser desorption/ionization mass spectrometry (LDI-MS) is presented for the efficient screening of bladder cancer (BC) and nonmalignant urinary disease. Combined with machine learning, TiO2/MXene-assisted LDI-MS enables high diagnostic accuracy (96.8%) for the classification of patient groups (including 47 BC and 46 ureteral calculus (UC) patients) from healthy controls (113 cases). In addition, BC patients can also be identified from noncancerous UC individuals with an accuracy of 88.3% in the independent test cohort. Furthermore, metabolite variations between BC and UC individuals are investigated based on relative quantification, and related pathways are also discussed. These results suggest that this method, based on urine metabolic patterns, provides a potential tool for rapidly distinguishing urinary diseases and it may pave the way for precision medicine. 相似文献
12.
Myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) is a persistent and unexplained pathological state characterized by exertional and severely debilitating fatigue, with/without infectious or neuropsychiatric symptoms, and with a minimum duration of 6 consecutive months. Its pathogenesis is not fully understood. There are no firmly established diagnostic biomarkers or treatment, due to incomplete understanding of the etiology of ME/CFS and diagnostic uncertainty. Establishing a biomarker for the objective diagnosis is urgently needed to treat a lot of patients. Recently, research on ME/CFS using metabolome analysis methods has been increasing. Here, we overview recent findings concerning the metabolic features in patients with ME/CFS and the animal models which contribute to the development of diagnostic biomarkers for ME/CFS and its treatment. In addition, we discuss future perspectives of studies on ME/CFS. 相似文献
13.
Leo H. Chiang Birgit Braun Zhenyu Wang Ivan Castillo 《American Institute of Chemical Engineers》2022,68(6):e17644
In the Industry 4.0 era, the chemical industry is embracing broad adoption of artificial intelligence (AI) and machine learning (ML) methods. This article provides a holistic view of how the industry is transforming digitally towards AI at scale. First, a historical perspective on how the industry used AI to aid humans in better decision-making is shown. Then state-of-the-art AI research addressing industrial needs on reliability and safety, process optimization, supply chain, material discovery, and reaction engineering is highlighted. Finally, a vision of the plant of the future is illustrated with critical components of AI-ready culture, model life cycle management, and renewed role of humans in chemical manufacturing. 相似文献
14.
Process analytics is one of the popular research domains that advanced in the recent years. Process analytics encompasses identification, monitoring, and improvement of the processes through knowledge extraction from historical data. The evolution of Artificial Intelligence (AI)-enabled Electronic Health Records (EHRs) revolutionized the medical practice. Type 2 Diabetes Mellitus (T2DM) is a syndrome characterized by the lack of insulin secretion. If not diagnosed and managed at early stages, it may produce severe outcomes and at times, death too. Chronic Kidney Disease (CKD) and Coronary Heart Disease (CHD) are the most common, long-term and life-threatening diseases caused by T2DM. Therefore, it becomes inevitable to predict the risks of CKD and CHD in T2DM patients. The current research article presents automated Deep Learning (DL)-based Deep Neural Network (DNN) with Adagrad Optimization Algorithm i.e., DNN-AGOA model to predict CKD and CHD risks in T2DM patients. The paper proposes a risk prediction model for T2DM patients who may develop CKD or CHD. This model helps in alarming both T2DM patients and clinicians in advance. At first, the proposed DNN-AGOA model performs data preprocessing to improve the quality of data and make it compatible for further processing. Besides, a Deep Neural Network (DNN) is employed for feature extraction, after which sigmoid function is used for classification. Further, Adagrad optimizer is applied to improve the performance of DNN model. For experimental validation, benchmark medical datasets were used and the results were validated under several dimensions. The proposed model achieved a maximum precision of 93.99%, recall of 94.63%, specificity of 73.34%, accuracy of 92.58%, and F-score of 94.22%. The results attained through experimentation established that the proposed DNN-AGOA model has good prediction capability over other methods. 相似文献
15.
16.
17.
The present study proposes an algorithm for fault detection in terms of condition‐based maintenance with data mining techniques. The proposed algorithm is applied on an aircraft turbofan engine using flight data and consists of two main sections. In the first section, the relationship between engine exhaust gas temperature (EGT) as the main engine health monitoring criterion and other operational and environmental parameters of the engine was modelled using the data‐driven models. In the second section, a data set including EGT residuals, that is, the difference between the actual EGT of the system and the EGT estimated by the developed model in the health conditions of the engine, was created. Finally, faults occurring in each flight were detected based on the identification of abnormal events by a one‐class support vector machine trained by the health condition EGT residual data set. The results indicated that the proposed algorithm was an effective approach for inspecting aircraft engine conditions and detecting faults, with no need for technical knowledge on the interior characteristics of the aircraft engine. 相似文献
18.
Yong Zhang Zi-Ran Liu Ding-Wang Yuan Qin Shao Jiang-Hua Chen Cui-Lan Wu Zao-Li Zhang 《金属学报(英文版)》2019,32(9):1099-1110
Owing to the excellent elastic properties and chemical stability, binary metal or light element borides, carbides and nitrides have been extensively applied as hard and low-compressible materials. Researchers are searching for harder materials all the time. Recently, the successful fabrication of nano-twinned cubic BN(Tian et al. Nature 493:385–388, 2013) and diamond(Huang et al. Nature 510:250–253, 2014) exhibiting superior properties than their twin-free counterparts allows an efficient way to be harder. From this point of view, the borides, carbides and nitrides may be stronger by introducing twins, whose formation tendency can be measured using stacking fault energies(SFEs). The lower the SFEs, the easier the formation of twins. In the present study, by means of first-principles calculations, we first calculated the fundamental elastic constants of forty-two borides, seventeen carbides and thirty-one nitrides, and their moduli, elastic anisotropy factors and bonding characters were accordingly derived. Then, the SFEs of the {111} 112 glide system of twenty-seven compounds with the space group F43 m or Fm3m were calculated. Based on the obtained elastic properties and SFEs, we find that(1) light element compounds usually exhibit superior elastic properties over the metal borides, carbides or nitrides;(2) the 5 d transitionmetal compounds(ReB_2, WB, OsC, RuC, WC, OsN_2, TaN and WN) possess comparable bulk modulus( B) with that of cBN( B = 363 GPa);(3) twins may form in ZrB, HfN, PtN, VN and ZrN, since their SFEs are lower or slightly higher than that of diamond(SFE = 277 mJ/m~2). Our work can be used as a valuable database to compare these compounds. 相似文献
19.
Ghulam Gilanie Usama Ijaz Bajwa Mustansar Mahmood Waraich Zulfiqar Habib 《International journal of imaging systems and technology》2019,29(3):260-271
The drive of this study is to develop a robust system. A method to classify brain magnetic resonance imaging (MRI) image into brain-related disease groups and tumor types has been proposed. The proposed method employed Gabor texture, statistical features, and support vector machine. Brain MRI images have been classified into normal, cerebrovascular, degenerative, inflammatory, and neoplastic. The proposed system has been trained on a complete dataset of Brain Atlas-Harvard Medical School. Further, to achieve robustness, a dataset developed locally has been used. Extraordinary results on different orientations, sequences of both of these datasets as per accuracy (up to 99.6%), sensitivity (up to 100%), specificity (up to 100%), precision (up to 100%), and AUC value (up to 1.0) have been achieved. The tumorous slices are further classified into primary or secondary tumor as well as their further types as glioma, sarcoma, meningioma, bronchogenic carcinoma, and adenocarcinoma, which could not be possible to determine without biopsy, otherwise. 相似文献
20.
Frequency band selection (FBS) in rotating machinery fault diagnosis aims to recognize frequency band location including a fault transient out of a full band spectrum, and thus fault diagnosis can suppress noise influence from other frequency components. Impulsiveness and cyclostationarity have been recently recognized as two distinctive signatures of a transient. Thus, many studies have focused on developing quantification metrics of the two signatures and using them as indicators to guide FBS. However, most previous studies almost ignore another aspect of FBS, i.e. health reference, which significantly affect FBS performance. To address this issue, this paper investigates importance of a health reference and recognize it as the third critical aspect in FBS. With help of the health reference, the frequency band where the fault transient exists could be located. A novel approach based on classification is proposed to integrate all three aspects (impulsiveness, cyclostationarity, and health reference) for FBS. Classification accuracy is developed as a novel indicator to select the most sensitive frequency band for rotating machinery fault diagnosis. The proposed method (coined by accugram) has been validated on benchmark and experiment datasets. Comparison results show its effectiveness and robustness over conventional envelope analysis, the kurtogram, and the infogram. 相似文献