This paper presents a neural network (NN) approach to detect intrusions. Previous works used many KDD records to train NNs for detecting intrusions. That is why; our objective here is to show that in case of the KDD data sets, we can obtain good results by training some NNs with a small data subset. To prove that, this study compares the attacks detection and classification by using two training sets: a set of only 260 records and a set of 65536 records. The testing set is composed of 65536 records randomly chosen from the KDD testing set. Our study focused on two classification types of records: a single class (normal or attack), and a multi class where the category of the attack is detected by the NN. Four different types of NNs were tested: Multi-Layer Perceptron (MLP), Modular, Jordan/Elman and Principal Component Analysis (PCA) NN. Two NN structures were used: the first one contains only one hidden layer and the second contains ten hidden layers. Our simulations show that the small data subset (260 records) can be trained to detect and classify attacks more efficiently than the second data subset.
The purpose of this study is to analyze the performances of some neural networks (NNs) when all the KDD data set is used to train them, in order to classify and detect attacks. Five different types of NNs were tested: Multi-Layer Perceptron (MLP), Self Organization Feature Map (SOFM), Radial Basis Function/Generalized Regression/Probabilistic (RBF/GR/P), Jordan/Elman, and Recurrent NNs. The experiment study is done on the Knowledge Discovery and Data mining (KDD) data sets. We consider two levels of attack granularities depending on whether dealing with four main categories, or only focusing on the normal/attack connection types. Our simulations show that our results are competitive with some other artificial intelligence or data mining intrusion detection systems.
Efficient and systematic survey methods are essential for wildlife researchers and conservationists to collect accurate ecological data that can be used to make informed conservation decisions. For endangered and elusive species, that are not easily detected by conventional methods, reliable, time- and cost-efficient methodologies become increasingly important. Across a growing spectrum of conservation research projects, survey outcomes are benefitting from scent detection dogs that assist with locating elusive species. This paper describes the training methodology used to investigate the ability of a scent detection dog to locate live riverine rabbits (Bunolagus monticularis) in their natural habitat, and to determine how species-specific the dog was towards the target scent in a controlled environment. The dog was trained using operant conditioning and a non-visual methodology, with only limited scent from roadkill specimens available. The dog achieved a 98% specificity rate towards the target scent, indicating that the dog was able to distinguish the scent of riverine rabbits from the scent of other lagomorph species. The dog has already been able to locate ten of these elusive individuals in the wild. The training method proved successful in the detection of this critically endangered species, where scent for training was only available from deceased specimens.
Sparse-elm grassland is the remarkable landscape of Hunshandak Sandland in Inner Mongolia Autonomic Region of China. Maximum quantum efficiency (Fv/Fm) of 99 native plant species (85 grasses, 11 shrubs, and 3 trees) of different plant functional Types (PFTs) distributed in fixed sand dune, lowland, and wetland was investigated. Deep-rooted plant species (tree, shrub, and perennial grass) had higher Fv/Fm values than the shallow-rooted species (annual grasses), suggesting that soil drought is the major environmental stress. Annual C4 grasses had higher Fv/Fm values than annual C3 or CAM ones, indicating that C4 photosynthesis is more ecologically adaptive than CAM and C3 grasses. According to the habitats with annual C3 grass distribution, Fv/Fm values were in the order of fixed dune>lowland>wetland, suggesting that salt and pH value may enhance irradiance or heat stress for those distributed in pickled and watery habitats. Based on such characteristics, Ulmus pumila, Salix gordejevii, Caragana microphylla, Agriophyllum pungens, and Agropyron cristatum are recommended as ideal species for ecological restoration in degraded sand-land ecosystems. and Yong-Geng Li ... [et al.].
In the paper the existing results concerning a special kind of trajectories and the theory of first return continuous functions connected with them are used to examine some algebraic properties of classes of functions. To that end we define a new class of functions (denoted $Conn^*$) contained between the families (widely described in literature) of Darboux Baire 1 functions (${\rm DB}_1$) and connectivity functions ($Conn$). The solutions to our problems are based, among other, on the suitable construction of the ring, which turned out to be in some senses an “optimal construction“. These considerations concern mainly real functions defined on $[0,1]$ but in the last chapter we also extend them to the case of real valued iteratively $H$-connected functions defined on topological spaces.
Stanislav of Znojmo (died 1414), a professor of the Prague Theological Faculty, first a teacher and friend to Jan Hus, but then his decided opponent, wrote a comprehensive treatise, probably around 1403, entitled De vero et falso. The subject of my article is an analysis of the content of this work. In it, Stanislav deals with the question of the truth of a proposition and the problem of its truth-maker. The question of the truth-maker falls into the area of metaphysics, and so the author speaks of metaphysical truth. In so far as metaphysical truth is concerned, Stanislav of Znojmo defends a decidedly realist standpoint, judging that categorematic expressions are not alone in having real counterparts in the world, but syncategorematic expressions (for example, statement conjunctions, words expressing negations and so on) also have such counterparts. Stanislav’s treatise, in its overall orientation, belongs to propositionalism, a trend in logical thought widespread at the end of the Middle Ages. Although the author of the treatise De vero et falso does not cite contemporary authors, he shows a knowledge of some exponents of propositional logic (namely Gregory of Rimini, for example). His main inspiration, however, is undoubtedly the work of John Wyclif.