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1.
2.
Vicious codes, especially viruses, as a kind of impressive malware have caused many disasters and continue to exploit more vulnerabilities. These codes are injected inside benign programs in order to abuse their hosts and ease their propagation. The offsets of injected virus codes are unknown and their targets usually are latent until they are executed and activated, what in turn makes viruses very hard to detect. In this paper enriched control flow graph miner, ECFGM in short, is presented to detect infected files corrupted by unknown viruses. ECFGM uses enriched control flow graph model to represent the benign and vicious codes. This model has more information than traditional control flow graph (CFG) by utilizing statistical information of dependent assembly instructions and API calls. To the best of our knowledge, the presented approach in this paper, for the first time, can recognize the offset of infected code of unknown viruses in the victim files. The main contributions of this paper are two folds: first, the presented model is able to detect unknown vicious code using ECFG model with reasonable complexity and desirable accuracy. Second, our approach is resistant against metamorphic viruses which utilize dead code insertion, variable renaming and instruction reordering methods. 相似文献
3.
Hossein Derakhshankhah Rana Jahanban-Esfahlan Somayeh Vandghanooni Sattar Akbari-Nakhjavani Bakhshali Massoumi Babak Haghshenas Aram Rezaei Amir Farnudiyan-Habibi Hadi Samadian Mehdi Jaymand 《应用聚合物科学杂志》2021,138(24):50578
Gelatin (Gel)-based pH- and thermal-responsive magnetic hydrogels (MH-1 and MH-2) were designed and developed as novel drug delivery systems (DDSs) for cancer chemo/hyperthermia therapy. For this goal, Gel was functionalized with methacrylic anhydride (GelMA), and then copolymerized with (2-dimethylaminoethyl) methacrylate (DMAEMA) monomer in the presence of methacrylate-end capped magnetic nanoparticles (MNPs) as well as triethylene glycol dimethacrylate (TEGDMA; as crosslinker). Afterward, a thiol-end capped poly(N-isopropylacrylamide) (PNIPAAm-SH) was synthesized through an atom transfer radical polymerization technique, and then attached onto the hydrogel through “thiol-ene” click grafting. The preliminary performances of developed MHs for chemo/hyperthermia therapy of human breast cancer was investigated through the loading of doxorubicin hydrochloride (Dox) as an anticancer agent followed by cytotoxicity measurement of drug-loaded DDSs using MTT assay by both chemo- and chemo/hyperthermia-therapies. Owing to porous morphologies of the fabricated magnetic hydrogels according to scanning electron microscopy images and strong physicochemical interactions (e.g., hydrogen bonding) the drug loading capacities of the MH-1 and MH-2 were obtained as 72 ± 1.4 and 77 ± 1.8, respectively. The DDSs exhibited acceptable pH- and thermal-triggered drug release behaviors. The MTT assay results revealed that the combination of hyperthermia therapy and chemotherapy has synergic effect on the anticancer activities of the developed DDSs. 相似文献
4.
Flexible decision tree for data stream classification in the presence of concept change, noise and missing values 总被引:1,自引:0,他引:1
In recent years, classification learning for data streams has become an important and active research topic. A major challenge
posed by data streams is that their underlying concepts can change over time, which requires current classifiers to be revised
accordingly and timely. To detect concept change, a common methodology is to observe the online classification accuracy. If
accuracy drops below some threshold value, a concept change is deemed to have taken place. An implicit assumption behind this
methodology is that any drop in classification accuracy can be interpreted as a symptom of concept change. Unfortunately however,
this assumption is often violated in the real world where data streams carry noise that can also introduce a significant reduction
in classification accuracy. To compound this problem, traditional noise cleansing methods are incompetent for data streams.
Those methods normally need to scan data multiple times whereas learning for data streams can only afford one-pass scan because
of data’s high speed and huge volume. Another open problem in data stream classification is how to deal with missing values.
When new instances containing missing values arrive, how a learning model classifies them and how the learning model updates
itself according to them is an issue whose solution is far from being explored. To solve these problems, this paper proposes
a novel classification algorithm, flexible decision tree (FlexDT), which extends fuzzy logic to data stream classification.
The advantages are three-fold. First, FlexDT offers a flexible structure to effectively and efficiently handle concept change. Second, FlexDT is robust to noise. Hence it can prevent noise
from interfering with classification accuracy, and accuracy drop can be safely attributed to concept change. Third, it deals
with missing values in an elegant way. Extensive evaluations are conducted to compare FlexDT with representative existing
data stream classification algorithms using a large suite of data streams and various statistical tests. Experimental results
suggest that FlexDT offers a significant benefit to data stream classification in real-world scenarios where concept change,
noise and missing values coexist. 相似文献
5.
Md. Abdus Sattar 《国际能源研究杂志》1993,17(1):1-7
An analytical study is made of the free and forced convection boundary layer flow past a porous medium bounded by a semi-infinite vertical porous plate. Locally similar solutions are then obtained by a perturbation method for large suction. Solutions for the velocity and temperature distributions are shown graphically for various suction velocities and values of the driving parameter Gr/R, where Gr is the Grashof number and Re is the Reynolds number. The corresponding values of the skin friction coefficient and the Nusselt number are finally shown in tabular form. 相似文献
6.
Abdus Sattar J. M. Deman J. C. Alexander 《Journal of the American Oil Chemists' Society》1976,53(7):473-477
Butter, butterfat, and corn, coconut, rapeseed, and soybean oils were exposed to 500 ft-c of fluorescent light at varying
time-temperature conditions. Oxidation rates were measured by the peroxide values. Vitamin A and β-carotene content of butterfat
were estimated. The effect of wavelength on the relative rates of oxidation was determined. The light transmitting properties
of the samples at 15 and 30 C over a spectral range of 380–750 nm were measured. It was observed that there was no increase
in oxidation rate when the light was switched off. The stability of the oils as shown by the oxidation rates did not correlate
well with the ratios of C18:2 to C18:1 or C18:3 to C18:2 nor with the degree of unsaturation. Increase in temperature alone
had minimal effect; however, in the presence of light the rate of oxidation increased considerably with a corresponding decrease
in the content of Vitamin A and β-carotene. β-Carotene provided strong protective properties. After the photobleaching of
β-carotene in butterfat, there was a rapid increase in peroxide values. With coconut oil, the oxidation rate was greater at
15 C than at 30 C due to greater light absorption at 15 C over the entire spectrum. The rate of oxidation decreased at higher
wavelengths, and this effect was more pronounced in the vegetable oils than in butterfat, where the β-carotene was considered
to serve as a filter for light of low wavelength.
Presented at the AOCS meeting, Dallas, April 1975. 相似文献
7.
Sona Taheri John Yearwood Musa Mammadov Sattar Seifollahi 《Neural computing & applications》2014,24(5):995-1002
The Naive Bayes classifier is a popular classification technique for data mining and machine learning. It has been shown to be very effective on a variety of data classification problems. However, the strong assumption that all attributes are conditionally independent given the class is often violated in real-world applications. Numerous methods have been proposed in order to improve the performance of the Naive Bayes classifier by alleviating the attribute independence assumption. However, violation of the independence assumption can increase the expected error. Another alternative is assigning the weights for attributes. In this paper, we propose a novel attribute weighted Naive Bayes classifier by considering weights to the conditional probabilities. An objective function is modeled and taken into account, which is based on the structure of the Naive Bayes classifier and the attribute weights. The optimal weights are determined by a local optimization method using the quasisecant method. In the proposed approach, the Naive Bayes classifier is taken as a starting point. We report the results of numerical experiments on several real-world data sets in binary classification, which show the efficiency of the proposed method. 相似文献
8.
Sunhye Yang Kamrun Nahar Fatema Ick-Jun Kim Jihyeon Ryu Sang Eun Shim Won-Chun Oh 《Advanced Powder Technology》2021,32(4):1116-1126
This paper reports the synthesis of various molar concentrations of manganese (Mn)-doped Ultra-High Surface area Activated Carbon (USAC) additives and their efficient use as cathode materials for supercapacitors. We synthesized the nanoparticles via a novel and facile dip-coating process and characterized them in detail by various analytical techniques. The SEM, EDAX, and XPS results showed that the Mn ions were successfully substituted on the USAC additives’ layered structure without any structural changes. The long cyclic stability of the as-prepared Mn-doped USAC additives was tested as a cathode material for supercapacitors at different current densities. The detailed experimental results showed that the Mn dopant content crucially determines the electrochemical performances of the USAC additives. Electrochemical measurements showed that the MnCEP-S600HTT with 0.10 mol% molar concentration of Mn dopant gives the best cycling performances. It delivers a discharge capacity of 262.9 mAh g?1 after 100 cycles. Further increasing the current density to 1000 mA g?1 allowed it to still maintain 253.6 mAh g?1 after 200 cycles. We confirmed that the structure of Mn-doped USAC additives is an important pole to improve the structural stability and electrochemical properties. 相似文献
9.
针对非实时通信对安全性要求高且信道中存在噪声的问题,提出了基于超混沌掩盖调制的自适应异步抗噪声保密通信方案。通信原理是由超混沌Lorenz系统生成四个状态变量的伪随机向量,并通过信号增益将它们调整到同一区间;再由分段线性混沌映射(PWLCM)生成两个向量,用于在四个状态变量之间随机切换选取和确定动态时滞步长,以生成载体信号;然后将预编码后的二进制信息成对掩盖到载体信号中,添加高斯噪声后发送出去。实验结果分析发现最小信号增益和噪声系数的比值稳定在一个小区间[0.08,0.11]内,如果把该比值设置成某个大于该区间上限的值,则比特误码率可达到零,因此接收端可在噪声信道中接收并完美恢复出被掩盖信号。该方案利用超混沌系统的非线性动力学特性,能够在噪声信道中自适应实现异步保密通信,数值仿真验证了其有效性。 相似文献
10.