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排序方式: 共有523条查询结果,搜索用时 156 毫秒
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Hussain Sheikha Anil K. Mehrotra Mehran Pooladi-Darvish 《Journal of Petroleum Science and Engineering》2006,53(3-4):189-202
An inverse solution methodology is developed for the estimation of diffusion coefficient of gases in highly viscous, oil-sands bitumens from isothermal, pressure-decay measurements. The approach involves modeling the rate of change in pressure using the diffusion equation for the liquid phase coupled with a mass balance equation for the gas phase. The inverse solution framework is utilized to arrive at two graphical techniques for estimating the diffusion coefficient. Both techniques involve the determination of the slope of a straight line resulting from plotting the experimental data in accordance with the developed model. An advantage of the proposed techniques is that the diffusion coefficient is estimated directly, i.e. without making it an adjustable parameter. The novelty of the proposed method is in its simplicity as well as its ability to isolate portions of the pressure-decay data affected by experimental fluctuations. The effect of the initial pressure on the predicted diffusion coefficient and pressure-decay profile was also investigated. The diffusion coefficients of CO2, CH4, C2H6 and N2 in Athabasca bitumen at 50–90 °C and about 8 MPa were estimated and compared with literature values. 相似文献
3.
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
4.
Nowadays malware is one of the serious problems in the modern societies. Although the signature based malicious code detection is the standard technique in all commercial antivirus softwares, it can only achieve detection once the virus has already caused damage and it is registered. Therefore, it fails to detect new malwares (unknown malwares). Since most of malwares have similar behavior, a behavior based method can detect unknown malwares. The behavior of a program can be represented by a set of called API's (application programming interface). Therefore, a classifier can be employed to construct a learning model with a set of programs' API calls. Finally, an intelligent malware detection system is developed to detect unknown malwares automatically. On the other hand, we have an appealing representation model to visualize the executable files structure which is control flow graph (CFG). This model represents another semantic aspect of programs. This paper presents a robust semantic based method to detect unknown malwares based on combination of a visualize model (CFG) and called API's. The main contribution of this paper is extracting CFG from programs and combining it with extracted API calls to have more information about executable files. This new representation model is called API-CFG. In addition, to have fast learning and classification process, the control flow graphs are converted to a set of feature vectors by a nice trick. Our approach is capable of classifying unseen benign and malicious code with high accuracy. The results show a statistically significant improvement over n-grams based detection method. 相似文献
5.
Multibody System Dynamics - Heretofore, the Serret–Frenet frame has been the ubiquitous choice for analyzing the elastic deformations of beam elements. It is well-known that this frame is... 相似文献
6.
A novel voltammetric sensor based on chemically modified bentonite–porphyrin carbon paste electrode (MBPCE) has been introduced for the determination of trace amount of Mn(II) in wheat flour, wheat rice and vegetables. In this method Mn(II) gives well-defined voltammetric peak at the pH range of 3.5–7.5. For the preliminary screening purpose, the catalyst was prepared by modification of bentonite with porphyrin and characterized by thermogravimetric method (TG) and UV–vis spectroscopy. The detection limit (three times signal-to-noise) with 4 min accumulation is 1.07 × 10−7 mol L−1 Mn(II). The peak currents increases linearly with Mn(II) concentration over the range of 6.0 × 10−7 to 5.0 × 10−4 mol L−1 (r2 = 0.9959). Statistical treatment of the results gave a relative standard deviation lower than 2.30%. The chemical and instrumental parameters have been optimized and the results showed that 1000-fold excess of the additive ions had not interferences on the determination of Mn(II). 相似文献
7.
Huda Al Amri Author Vitae Mehran Abolhasan Author Vitae 《Computers & Electrical Engineering》2010,36(4):752-765
In Mobile Ad hoc Network (MANET), mobility, traffic and node density are main network conditions that significantly affect performance of routing protocols. Much of the previous research in MANET routing have focused on developing strategies, which suit one specific networking scenario. Therefore, there is no existing protocol that can work well in all different networking scenarios. This paper reviews characteristics of several different classes of routing protocols. Moreover, most of current routing protocols assume homogeneous networking conditions where all nodes have the same capabilities and resources. This paper presents extensive studies simulations for DSR, AODV, LAR1, FSR and WRP in homogenous and heterogeneous networks that consist of different nodes with different resources. The results showed that while all protocols perform reasonably well in homogenous networking conditions, their performance suffer significantly over heterogonous networks. 相似文献
8.
Skin detection is a difficult and primary task in many image processing applications. Because of the diversity of various
image processing tasks, there exists no optimum method that can perform properly for all applications. In this paper, we have
proposed a novel skin detection algorithm that combines color and texture information of skin with cellular learning automata
to detect skin-like regions in color images. Skin color regions are first detected, by using a committee structure, from among
several explicit boundary skin models. Detected skin-color regions are then fed to a texture analyzer which extracts texture
features via their color statistical properties and maps them to a skin probability map. This map is then used by cellular
learning automata to adaptively make a decision on skin regions. Conducted experiments show that the proposed algorithm achieves
the true positive rate of about 86.3% and the false positive rate of about 9.2% on Compaq skin database which shows its efficiency. 相似文献
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10.
Asif Hussain Khoja Arslan Mazhar Faisal Saleem Muhammad Taqi Mehran Salman Raza Naqvi Mustafa Anwar Sehar Shakir Nor Aishah Saidina Amin Muhammad Bilal Sajid 《International Journal of Hydrogen Energy》2021,46(29):15367-15388
The catalyst has a significant role in gas processing applications such as reforming technologies for H2 and syngas production. The stable catalyst is requisite for any industrial catalysis application to make it commercially viable. Several methods are employed to synthesize the catalysts. However, there is still a challenge to achieve a controlled morphology and pure catalyst which majorly influences the catalytic activity in reforming applications. The conventional methods are expansive, and the removal of the impurities are major challenges. Nevertheless, it is not straightforward to achieve the desired structure and stability. Therefore, significant interest has been developed on the advanced techniques to take control of the physicochemical properties of the catalyst through non-thermal plasma (NTP) techniques. In this review, the systematic evolution of the catalyst synthesis using NTP technique is elucidated. The emerging DBD plasma to synthesized and effective surface treatment is reviewed. DBD plasma synthesized catalyst performance in reforming application for H2 and syngas production is summarised. Furthermore, the status of DBD plasma for catalyst synthesis and proposed future avenues to design environmentally suitable and cost-effective synthesis techniques are discussed. 相似文献