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排序方式: 共有418条查询结果,搜索用时 15 毫秒
1.
Meraj Talha Rauf Hafiz Tayyab Zahoor Saliha Hassan Arslan Lali M. IkramUllah Ali Liaqat Bukhari Syed Ahmad Chan Shoaib Umar 《Neural computing & applications》2021,33(17):10737-10750
Neural Computing and Applications - Lung cancer is a deadly disease if not diagnosed in its early stages. However, early detection of lung cancer is a challenging task due to the shape and size of... 相似文献
2.
Sea urchin-like nanostructures of ZnO consisting of ZnO nanowires with blunt faceted ends were grown on Si (100) substrates by oxidation of metallic Zn at 600 °C. ZnO nanowires having a diameter of 30–60 nm and length of 2–4 Μm were in similar shape with uniform diameter along its entire length with well faceted blunt ends. X-ray diffraction and transmission electron microscope analysis showed that the as-grown nanostructures were highly crystalline with wurtzite hexagonal structure having lattice constants of a=b=3.25 å and c=5.21 å. Room temperature photoluminescence (PL) measurements showed a weak near band-edge emission at 380 nm, but a strong green emission at 500–530 nm. A model for vapor-solid (VS) growth mechanism of ZnO nanowires was presented, in which nucleation of ZnO is crucial for the growth of the nanostructures. 相似文献
3.
Abdullahi Nuhu Jorge Soares Monica Gonzalez-Herrera Andrew Watts Ghulam Hussein Michael Bowker 《Topics in Catalysis》2007,44(1-2):293-297
We have investigated the adsorption and reaction of methanol with Au/TiO2 catalysts using a pulsed flow reactor, DRIFTS and TPD. The TiO2 (P25) surface adsorbed a full monolayer of methanol, much of it in a dissociative manner, forming methoxy groups associated
with the cationic sites, and hydroxyl groups at the anions. The methoxy is relatively stable until 250 °C, at which point
decomposition occurs, producing mainly dimethyl ether by a bimolecular surface reaction. As the concentration of methoxy on
the surface diminishes, so the mechanism reverts to a de-oxygenation pathway, producing mainly methane and water (at ~330 °C
in TPD), but also with some coincident CO and hydrogen. Au catalysts were prepared by the deposition-precipitation method
to give Au loadings between 0.5–3 wt %. The effect of low levels of Au on the reactivity is marked. The pathway which gives
methane, which is characteristic of titania, remains, but a new feature of the reaction is the evolution of CO2 and H2 at lower temperature (a peak is seen in TPD at 220 °C), and the elimination of the DME-producing state. Clearly this is associated
with the presence of Au and appears to be due to the production of a formate species on the surface of the Au component. This
formate species is mainly involved in the reaction of methanol with the Au/TiO2 catalysts which results in a combustion pathway being followed, with complete conversion occurring by ~130 °C. 相似文献
4.
Wireless Personal Communications - Software-defined networking (SDN) is widely perceived to simplify network management and monitoring. The introduction of the SDN model into wireless sensor... 相似文献
5.
Faisal Bahadur Arif Iqbal Umar Insaf Ullah Fahad Algarni Muhammad Asghar Khan 《计算机系统科学与工程》2022,42(2):589-604
Scalability is one of the most important quality attribute of software-intensive systems, because it maintains an effective performance parallel to the large fluctuating and sometimes unpredictable workload. In order to achieve scalability, thread pool system (TPS) (which is also known as executor service) has been used extensively as a middleware service in software-intensive systems. TPS optimization is a challenging problem that determines the optimal size of thread pool dynamically on runtime. In case of distributed-TPS (DTPS), another issue is the load balancing b/w available set of TPSs running at backend servers. Existing DTPSs are overloaded either due to an inappropriate TPS optimization strategy at backend servers or improper load balancing scheme that cannot quickly recover an overload. Consequently, the performance of software-intensive system is suffered. Thus, in this paper, we propose a new DTPS that follows the collaborative round robin load balancing that has the effect of a double-edge sword. On the one hand, it effectively performs the load balancing (in case of overload situation) among available TPSs by a fast overload recovery procedure that decelerates the load on the overloaded TPSs up to their capacities and shifts the remaining load towards other gracefully running TPSs. And on the other hand, its robust load deceleration technique which is applied to an overloaded TPS sets an appropriate upper bound of thread pool size, because the pool size in each TPS is kept equal to the request rate on it, hence dynamically optimizes TPS. We evaluated the results of the proposed system against state of the art DTPSs by a client-server based simulator and found that our system outperformed by sustaining smaller response times. 相似文献
6.
Zhang Jian Yang Xiaokun Deng Hui Qiao Keke Farooq Umar Ishaq Muhammad Yi Fei Liu Huan Tang Jiang Song Haisheng 《纳微快报(英文)》2017,9(3):1-8
Nano-Micro Letters - A NiFe2O4/expanded graphite (NiFe2O4/EG) nanocomposite was prepared via a simple and inexpensive synthesis method. Its lithium storage properties were studied with the goal of... 相似文献
7.
Muhammad Irfan Ahmad Shaf Tariq Ali Umar Farooq Saifur Rahman Salim Nasar Faraj Mursal Mohammed Jalalah Samar M. Alqhtani Omar AlShorman 《计算机、材料和连续体(英文)》2023,76(1):711-729
A brain tumor is a mass or growth of abnormal cells in the brain. In children and adults, brain tumor is considered one of the leading causes of death. There are several types of brain tumors, including benign (non-cancerous) and malignant (cancerous) tumors. Diagnosing brain tumors as early as possible is essential, as this can improve the chances of successful treatment and survival. Considering this problem, we bring forth a hybrid intelligent deep learning technique that uses several pre-trained models (Resnet50, Vgg16, Vgg19, U-Net) and their integration for computer-aided detection and localization systems in brain tumors. These pre-trained and integrated deep learning models have been used on the publicly available dataset from The Cancer Genome Atlas. The dataset consists of 120 patients. The pre-trained models have been used to classify tumor or no tumor images, while integrated models are applied to segment the tumor region correctly. We have evaluated their performance in terms of loss, accuracy, intersection over union, Jaccard distance, dice coefficient, and dice coefficient loss. From pre-trained models, the U-Net model achieves higher performance than other models by obtaining 95% accuracy. In contrast, U-Net with ResNet-50 outperforms all other models from integrated pre-trained models and correctly classified and segmented the tumor region. 相似文献
8.
Robots have played an important role in the automation of computer aided manufacturing. The classical robot control implementation involves an expensive key step of model-based programming. An intuitive way to reduce this expensive exercise is to replace programming with machine learning of robot actions from demonstration where a (learner) robot learns an action by observing a demonstrator robot performing the same. To achieve this learning from demonstration (LFD) different machine learning techniques such as Artificial Neural Networks (ANN), Genetic Algorithms, Hidden Markov Models, Support Vector Machines, etc. can be used. This piece of work focuses exclusively on ANNs. Since ANNs have many standard architectural variations divided into two basic computational categories namely the recurrent networks and feed-forward networks, representative networks from each have been selected for study, i.e. Feed Forward Multilayer Perceptron (FF) network for feed-forward networks category and Elman (EL), and Nonlinear Autoregressive Exogenous Model (NARX) networks for the recurrent networks category. The main objective of this work is to identify the most suitable neural architecture for application of LFD in learning different robot actions. The sensor and actuator streams of demonstrated action are used as training data for ANN learning. Consequently, the learning capability is measured by comparing the error between demonstrator and corresponding learner streams. To achieve fairness in comparison three steps have been taken. First, Dynamic Time Warping is used to measure the error between demonstrator and learner streams, which gives resilience against translation in time. Second, comparison statistics are drawn between the best, instead of weight-equal, configurations of competing architectures so that learning capability of any architecture is not forced handicap. Third, each configuration's error is calculated as the average of ten trials of all possible learning sequences with random weight initialization so that the error value is independent of a particular sequence of learning or a particular set of initial weights. Six experiments are conducted to get a performance pattern of each architecture. In each experiment, a total of nine different robot actions were tested. Error statistics thus obtained have shown that NARX architecture is most suitable for this learning problem whereas Elman architecture has shown the worst suitability. Interestingly the computationally lesser MLP gives much lower and slightly higher error statistics compared to the computationally superior Elman and NARX neural architectures, respectively. 相似文献
9.
Albalawi Umar Mohanty Saraju P. Kougianos Elias 《Multimedia Tools and Applications》2017,76(20):21303-21337
Multimedia Tools and Applications - The multimedia revolution has made a strong impact on our society. The explosive growth of Internet access to this digital information has generated new... 相似文献
10.
Structured decomposition of adaptive applications 总被引:1,自引:0,他引:1