纳米黏土与再生聚酯纤维混合处理黏土砂的抗剪强度

近年来,以纳米尺度和纳米颗粒以及定向或随机分布的离散单元(如纤维)来加固土体的材料已被广泛应用于岩土工程中.本研究的主要目的是研究纳米黏土与再生聚酯纤维混合作为一种新的稳定材料对土壤力学行为的影响.对于未强化和三种纤维含量介于0.1％和0.5％的强化土壤标本,以及三种纳米黏土含量介于0.5％和1.5％的土壤进行排干剪切...     

Automatic navigation of mobile robots in unknown environments

Online navigation with known target and unknown obstacles is an interesting problem in mobile robotics. This article presents a technique based on utilization of neural networks and reinforcement learning to enable a mobile robot to learn constructed environments on its own. The robot learns to generate efficient navigation rules automatically without initial settings of rules by experts. This is regarded as the main contribution of this work compared to traditional fuzzy models based on notion of artificial potential fields. The ability for generalization of rules has also been examined. The initial results qualitatively confirmed the efficiency of the model. More experiments showed at least 32 % of improvement in path planning from the first till the third path planning trial in a sample environment. Analysis of the results, limitations, and recommendations is included for future work.     

Genetic-based minimum classification error mapping for accurate identifying Peer-to-Peer applications in the internet traffic

In this paper, we propose a hybrid approach using genetic algorithm and neural networks to classify Peer-to-Peer (P2P) traffic in IP networks. We first compute the minimum classification error (MCE) matrix using genetic algorithm. The MCE matrix is then used during the pre-processing step to map the original dataset into a new space. The mapped data set is then fed to three different classifiers: distance-based, K-Nearest Neighbors, and neural networks classifiers. We measure three different indexes, namely mutual information, Dunn, and SD to evaluate the extent of separation of the data points before and after mapping is performed. The experimental results demonstrate that with the proposed mapping scheme we achieve, on average, 8% higher accuracy in classification of the P2P traffic compare to the previous solutions. Moreover, the genetic-based MCE matrix increases the classification accuracy more than what the basic MCE does.     

Formal process algebraic modeling,verification, and analysis of an abstract Fuzzy Inference Cloud Service

In cloud computing, services play key roles. Services are well defined and autonomous components. Nowadays, the demand of using Fuzzy inference as a service is increasing in the domain of complex and critical systems. In such systems, along with the development of the software, the cost of detecting and fixing software defects increases. Therefore, using formal methods, which provide clear, concise, and mathematical interpretation of the system, is crucial for the design of these Fuzzy systems. To obtain this goal, we introduce the Fuzzy Inference Cloud Service (FICS) and propose a novel discipline for formal modeling of the FICS. The FICS provides the service of Fuzzy inference to the consumers. We also introduce four novel formal verification tests, which allow strict analysis of certain behavioral disciplines in the FICS as follows: (1) Internal consistency, which analyzes the service in a strict and delicate manner; (2) Deadlock freeness; (3) Divergence freeness; and (4) Goal reach ability. The four tests are discussed and the FICS is verified to ensure that it can pass all these tests.     

Phenolic composition and functional properties of wild mint (Mentha longifolia var. calliantha (Stapf) Briq.)

Mints (Mentha species) are widely used as food, medicine, spice, and flavoring agents. At the present work, phenolics profile of infusion and ethanol extract of Mentha longifolia was determined using an RP–HPLC–DAD system. Total bioactive contents, radical scavenging, reducing power, metal chelating, and enzyme inhibitory activities relevant to Alzheimer’s disease, diabetes mellitus, and skin disorders were evaluated. Sixteen phenolic compounds (ten phenolic acids and six flavonoids) were identified in the extracts in which sinapic acid (7132 µg/g extract) and rosmarinic acid (6260 µg/g extract) were the most abundant compounds. Strong antioxidant effects were observed in 1,1-diphenyl-2-picrylhydrazyl radical, 2,2?-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid), cupric ion reducing activity, ferric reducing antioxidant power, phosphomolybdenum, and metal chelating assays. Results indicated selective acetylcholinesterase inhibitory activity and high α-amylase and α-glucosidase inhibitory potential. Findings showed that M. longifolia has promising health benefits due to its high concentration of useful phenolic compounds and has great potential for possible applications in the preparation of functional ingredients.