Ranger, a novel intrusion detection system architecture for mobile ad hoc networks

The proliferation of wireless communication and mobile computing is driving the emergence of Mobile Ad hoc Networks (MANETs) with wide application ranges from civilian environment to military communication. However, securing MANETs is a highly challenging issue due to their inherent characteristics. Intrusion detection is an important security mechanism, but little effort has been directed towards efficient and effective architectures for Intrusion Detection System (IDS) in the context of MANETs. We investigate existing IDS architecture design issues, and propose a novel mobile agent based IDS architecture that has each node implementing basic IDS functions, while ranger agents roam the network executing more advanced IDS functions. This is suited to MANETs because it avoids the single point of failure problem, minimises communication overheads at the same time as providing up to date information for intrusion decisions

A flow based detection mechanism against flooding attacks in mobile ad hoc networks

Mobile ad hoc network (MANET) is particularly vulnerable to flooding attacks. To evade being identified, attackers usually recruit multiple accomplices to dilute attack traffic density of each attack source, and use the address spoofing technique to challenge attack tracing. In this paper, we present a detailed investigation of the flooding attack in MANET. Further, we design two flow based detection features, and apply the cumulative sum algorithm on them to effectively and accurately detect such attack

Vision Transformer: to discover the “Four Secrets” of image patches

Vision Transformer (ViT) is widely used in the field of computer vision, in ViT, there are four main steps, which are “four secrets”, such as patch division, token selection, position encoding addition, attention calculation, the existing research on transformer in computer vision mainly focuses on the above four steps. Therefore, “how to divide patch?”, “how to select token?”, “how to add position encoding?”, and “how to calculate attention?” are crucial to improve ViT performance. But so far, most of the review literatures are summarized from the perspective of application, and there is no corresponding literature to comprehensively summarize these four steps from the technology perspective, which restricts the further development of ViT in some degree. To address the above questions, the 4 major mechanisms and 5 applications of ViT are summarized in this paper, the main innovative works are as follows: Firstly, the basic principle and model structure of ViT are elaborated; Secondly, aiming to “how to divide patch?”, the 5 key techniques of patch division mechanism are summarized: from single-size division to multi-size division, from fixed number division to adaptive number division, from non-overlapping division to overlapping division, from semantic segmentation division to semantic aggregation division, and from original image division to feature map division; Thirdly, aiming to “how to select token?”, the 3 key techniques of token selection mechanism are summarized: token selection based on score, token selection based on merge, token selection based on convolution and pooling; Fourthly, aiming to “how to add position encoding?”, the 5 key techniques of position encoding mechanism are summarized: absolute position encoding, relative position encoding, conditional position encoding, locally-enhanced position encoding, and zero-padding position encoding; Fifthly, aiming to “how to calculate attention?”, 18 attention mechanisms are summarized based on the timeline; Sixthly, these models that Transformer is combined with U-Net, GAN, YOLO, ResNet, and DenseNet are discussed in the medical image processing field; Finally, around these four questions proposed in this paper, we look forward to the future development direction of frontier technologies such as patch division mechanism, token selection mechanism, position encoding mechanism, and attention mechanism et al, which play an important role in the further development of ViT.</p

Maximal transient receptor potential vanilloid 1 (TRPV1) immunoreactivity is seen in the keratinocytes of the suprabasal layer of the epidermis

<p><b>Copyright information:</b></p><p>Taken from "Epidermal transient receptor potential vanilloid 1 in idiopathic small nerve fibre disease, diabetic neuropathy and healthy human subjects"</p><p></p><p>Histopathology 2007;51(5):674-680.</p><p>Published online Jan 2007</p><p>PMCID:PMC2121152.</p><p>© 2007 The Authors. Journal compilation © 2007 Blackwell Publishing Limited.</p> The parentheses indicate the suprabasal region. Note the lack of nuclear TRPV1 staining. (TRPV1 peroxidase stain.

Animal behaviour understanding using wireless sensor networks

This paper presents research that is being conducted by the Commonwealth Scientific and Industrial Research Organisation (CSIRO) with the aim of investigating the use of wireless sensor networks for automated livestock monitoring and control. It is difficult to achieve practical and reliable cattle monitoring with current conventional technologies due to challenges such as large grazing areas of cattle, long time periods of data sampling, and constantly varying physical environments. Wireless sensor networks bring a new level of possibilities into this area with the potential for greatly increased spatial and temporal resolution of measurement data. CSIRO has created a wireless sensor platform for animal behaviour monitoring where we are able to observe and collect information of animals without significantly interfering with them. Based on such monitoring information, we can identify each animal’sbehaviour and activities successfully

Using accelerometer, high sample rate GPS and magnetometer data to develop a cattle movement and behaviour model

The study described in this paper developed a model of animal movement, which explicitly recognised each individual as the central unit of measure. The model was developed by learning from a real dataset that measured and calculated, for individual cows in a herd, their linear and angular positions and directional and angular speeds. Two learning algorithms were implemented: a Hidden Markov model (HMM) and a long-term prediction algorithm. It is shown that a HMM can be used to describe the animal’s movement and state transition behaviour within several “stay” areas where cows remained for long periods. Model parameters were estimated for hidden behaviour states such as relocating, foraging and bedding. For cows’ movement between the “stay” areas a long-term prediction algorithm was implemented. By combining these two algorithms it was possible to develop a successful model, which achieved similar results to the animal behaviour data collected. This modelling methodology could easily be applied to interactions of other animal species

Boundary Detection in Three Dimensions With Application to the SMILE Mission: The Effect of Photon Noise

Imaging magnetospheric satellite missions provide information, which is complementary to in situ observations. Imaging is often able to provide an instantaneous picture of large‐scale structures, whereas in situ measurements, even multipoint in situ measurements, can only provide an average view of large‐scale structure. But imaging also presents some challenges. When three‐dimensional structures need to be extracted from two‐dimensional images, it is necessary to either make suitable assumptions or record a large enough number of images from different viewing geometries to allow a reconstruction (e.g., tomography). Imaging data exist over a wide range of sources including visible light, ultraviolet light, extreme ultraviolet, energetic neutral atoms, and X‐rays, each informing different physical mechanisms. In this paper we consider the extraction of the geometry of the magnetopause and the bow shock from single X‐ray images expected from the Solar wind Magnetosphere Ionosphere Link Explorer (SMILE) mission. We examine the effect of photon‐counting noise in determining the boundary geometries. We also consider the effect of different viewing geometries in the form of orbital vantage point and target look direction. Finally, we consider the effect of background noise. We find that our approach is relatively robust to viewing geometry effects and works at low count rates

A Satellite-based Model for Estimating PM2.5 Concentration - Report to Victoria EPA

An atmospheric aerosol modelling, mapping and spatial analysis of fine mode particulate for the Environment Protection Agency of the Victorian State Government

Transforming agriculture through pervasive wireless sensor networks

A large-scale, outdoor, pervasive computing system based on the Fleck hardware platform applies sensor network technology to farming. Comprising static and animal-borne mobile nodes, the system measures the state of a complex, dynamic system comprising climate, soil, pasture, and animals

The prevalence of onchocerciasis in Africa and Yemen, 2000–2018: a geospatial analysis

Background: Onchocerciasis is a disease caused by infection with Onchocerca volvulus, which is transmitted to humans via the bite of several species of black fly, and is responsible for permanent blindness or vision loss, as well as severe skin disease. Predominantly endemic in parts of Africa and Yemen, preventive chemotherapy with mass drug administration of ivermectin is the primary intervention recommended for the elimination of its transmission. Methods: A dataset of 18,116 geo-referenced prevalence survey datapoints was used to model annual 2000–2018 infection prevalence in Africa and Yemen. Using Bayesian model-based geostatistics, we generated spatially continuous estimates of all-age 2000–2018 onchocerciasis infection prevalence at the 5 × 5-km resolution as well as aggregations to the national level, along with corresponding estimates of the uncertainty in these predictions. Results: As of 2018, the prevalence of onchocerciasis infection continues to be concentrated across central and western Africa, with the highest mean estimates at the national level in Ghana (12.2%, 95% uncertainty interval [UI] 5.0–22.7). Mean estimates exceed 5% infection prevalence at the national level for Cameroon, Central African Republic, Democratic Republic of the Congo (DRC), Guinea-Bissau, Sierra Leone, and South Sudan. Conclusions: Our analysis suggests that onchocerciasis infection has declined over the last two decades throughout western and central Africa. Focal areas of Angola, Cameroon, the Democratic Republic of the Congo, Ethiopia, Ghana, Guinea, Mali, Nigeria, South Sudan, and Uganda continue to have mean microfiladermia prevalence estimates exceeding 25%. At and above this level, the continuation or initiation of mass drug administration with ivermectin is supported. If national programs aim to eliminate onchocerciasis infection, additional surveillance or supervision of areas of predicted high prevalence would be warranted to ensure sufficiently high coverage of program interventions