Description:
Desiccation cracking is a common, undesirable phenomenon in many geotechnical engineering applications, particularly in compacted clay liners as it causes significant changes to the hydraulic and mechanical properties of soils. This is one of the major concerns in design and construction of landfill clay liners in arid regions. This paper reports the findings of laboratory tests conducted to investigate the effects of adding nylon fibre, guar gum and organic enzyme to the soil to control desiccation cracks. Merri-Creek clay, a highly expansive soil from Victoria, Australia, was used in the tests. The additives were mixed with soil in different combinations and in varying proportions. Desiccation tests were conducted in thin, long moulds as in the free shrinkage tests. It was observed that very small quantities of these additives were sufficient to alter the properties of overall mixture. The results indicated that fibre – enzyme is the most effective combination to reduce desiccation cracks. This additive combination contained 0.3% percent of fibres by dry weight of soil and 0.35 g of enzyme per kg of dry soil. There was a modest improvement in dry density in the fibre -enzyme mixture compared to pure Merri-Creek clay. Fibre-enzyme combination also showed the ability to reduce the hydraulic conductivity. It was discovered that guar gum is not desirable to mix with clays in terms of reducing desiccation cracking or decreasing hydraulic conductivity.
Description:
Multi-instance multi-label learning (MIML) is a learning paradigm where an object is represented by a bag of instances and each bag is associated with multiple labels. Ordinary MIML setting assumes a fixed target label set. In real applications, multiple novel labels may exist outside this set, but hidden in the training data and unknown to the MIML learner. Existing MIML approaches are unable to discover the hidden novel labels, let alone predicting these labels in the previously unseen test data. In this paper, we propose the first approach to discover multiple novel labels in MIML problem using an efficient augmented lagrangian optimization, which has a bag-dependent loss term and a bag-independent clustering regularization term, enabling the known labels and multiple novel labels to be modeled simultaneously. The effectiveness of the proposed approach is validated in experiments.
Description:
The protocol diversities of mobile ad hoc have already got hold of the field to a peak of a matured and developed area. Still, the restraint of delay and bandwidth of mobile ad hoc network have kept a little room to draft a routing protocol for the pursuit of providing quality of service. In the paper, we proposed protocol namely Efficient Route Selection in Ad Hoc On-Demand Distance Vector Routing. We select the best path among multiple paths from source to destination using covariance and delay. We consider the delay, link stability and energy to devise a covariance-based metric to discover the most balanced path. We also propose a metric for the selection of a node that acts as a local backup node for the most vulnerable nodes on the selected path. We accomplish our implementation in NS3and it shows the more reliable path and less end to end delay than other counterpart protocols.
Description:
The protocol diversities of mobile ad hoc have already got hold of the field to a peak of a matured and developed area. Still, the restraint of delay and bandwidth of mobile ad hoc network have kept a little room to draft a routing protocol for the pursuit of providing quality of service. In the paper, we proposed protocol namely Efficient Route Selection in Ad Hoc On-Demand Distance Vector Routing. We select the best path among multiple paths from source to destination using covariance and delay. We consider the delay, link stability and energy to devise a covariance-based metric to discover the most balanced path. We also propose a metric for the selection of a node that acts as a local backup node for the most vulnerable nodes on the selected path. We accomplish our implementation in NS3and it shows the more reliable path and less end to end delay than other counterpart protocols.
Description:
Hydraulic performance and its evolution over time is a key design parameter for stormwater filter systems. The major impact affecting stormwater filters is the reduction in infiltration rate, or otherwise known as clogging. This paper focuses on the effect of biological clogging of non-vegetated high flow stormwater filters in Australian conditions. An experimental column study was undertaken. Five semi-synthetic stormwater dosing configurations were tested: (i) Typical stormwater (base), (ii) Stormwater with high nutrient load, (iii) Typical stormwater with chlorine tablets, (iv) sterilized stormwater, and (v) potable water. Each configuration had 6 replicate columns, 3 were placed inside under controlled laboratory conditions and 3 were placed outside under normal Australian spring weather conditions, except for the potable water case (v) where it only had 2 replicate columns and both were placed outside. The results found were inconclusive due to the insignificant reduction of the infiltration rate over time and the columns did not clog, which is due to the size of sediment used in this study. It is suggested that further work should be undertaken on investigating the effect of stormwater composition in stormwater filters in real world conditions.
Description:
Management of maritime military platform life is a real challenge for operators and maintainers. One of the major problems is how to capture cost effective information about the hull defect and predict the remaining life? This paper will focus on the automation process for calculation of the failure rate and prediction from collated hull defects information. This data is assessed for accuracy, sensitivity and correctness of defect location and failure modes. An outline of the automation techniques investigated to determine the hull failures rates is discussed. Five major failure modes are analysed and a high level approach for integrating failure data collation is presented. The paper then discusses some of the issues and challenges with obtaining reliable maintenance data and opportunities for further research in finding a better solution.
Description:
This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
Description:
This paper investigates the impact of time delay in the control of a grid-connected microgrid with renewable energy resources. The considered microgrid has a critical load that needs to be powered and protected in the event of grid voltage disturbance while the microgrid maintains connection to the grid. Three case studies are performed considering three different time delays to indicate the advantages of fast communication system in the performance of renewable microgrids. Detailed simulation results illustrate that the proposed communication system using IEC 61850 substation automation standard provides better voltage and current quality to the critical local load with larger phase and gain margins while keeping the microgid connected to main grid.
Description:
External confining devices are often used to enhance the strength and ductility of reinforced concrete columns. Among the available external confining devices, steel tube is one of the most widely used in construction. However, steel tube has some drawbacks such as local buckling which needs to be considered when estimating the axial load carrying capacity of the concrete-filled-steel-tube (CFST) column. To tackle this problem in design, Eurocode 4 provided guidelines to estimate the effective yield strength of the steel tube material. To study the behavior of CFST column, in this paper, a non-linear analysis using a fiber-based approach was conducted. The use of the fiber-based approach allows the engineers to predict not only the axial load carrying capacity but also the complete load-deformation curve of the CFST columns for a known confining pressure. In the proposed fiber-based approach, an inverse analysis is used to estimate the constant confining pressure similar to design-oriented models. This paper also presents comparisons between the fiber-based approach model with the experimental results and the 3D non-linear finite element analysis.
Description:
External confining devices are often used to enhance the strength and ductility of reinforced concrete columns. Among the available external confining devices, steel tube is one of the most widely used in construction. However, steel tube has some drawbacks such as local buckling which needs to be considered when estimating the axial load carrying capacity of the concrete-filled-steel-tube (CFST) column. To tackle this problem in design, Eurocode 4 provided guidelines to estimate the effective yield strength of the steel tube material. To study the behavior of CFST column, in this paper, a non-linear analysis using a fiber-based approach was conducted. The use of the fiber-based approach allows the engineers to predict not only the axial load carrying capacity but also the complete load-deformation curve of the CFST columns for a known confining pressure. In the proposed fiber-based approach, an inverse analysis is used to estimate the constant confining pressure similar to design-oriented models. This paper also presents comparisons between the fiber-based approach model with the experimental results and the 3D non-linear finite element analysis.
Description:
Large remote area networks normally have self-suffi-cient electricity systems. These systems also rely on non-dispatchable DGs (N-DGs) for overall reduction in cost of electricity production. It is a fact that uncertainties included in the nature of N-DGs as well as load demand can cause cost burden on islanded microgrids (MGs). This paper proposes development of power exchange strategy for an interconnected MGs (IMG) system as part of large remote area network with optimized controls of dispatchable (D-DGs) which are members of master control unit (MCU). MCU analysis includes equal cost increment principle to give idea about the amount of power exchange which could take place with neighbor MGs in case of overloading situation. Sudden changes in N-DGs and load are defined as interruptions and are part of analysis too. Optimization problem is formulated on the basis of MCU adjustment for overloading or under loading situation and suitability of support MG (S-MG) in IMG system for power exchange along with key features of low cost and minimum technical impacts. Mixed integer linear programming (MILP) technique is applied to solve the formulated problem. The impact of proposed strategy is assessed by numerical analysis in MATLAB programming under stochastic environment.
Description:
Large remote area networks normally have self-suffi-cient electricity systems. These systems also rely on non-dispatchable DGs (N-DGs) for overall reduction in cost of electricity production. It is a fact that uncertainties included in the nature of N-DGs as well as load demand can cause cost burden on islanded microgrids (MGs). This paper proposes development of power exchange strategy for an interconnected MGs (IMG) system as part of large remote area network with optimized controls of dispatchable (D-DGs) which are members of master control unit (MCU). MCU analysis includes equal cost increment principle to give idea about the amount of power exchange which could take place with neighbor MGs in case of overloading situation. Sudden changes in N-DGs and load are defined as interruptions and are part of analysis too. Optimization problem is formulated on the basis of MCU adjustment for overloading or under loading situation and suitability of support MG (S-MG) in IMG system for power exchange along with key features of low cost and minimum technical impacts. Mixed integer linear programming (MILP) technique is applied to solve the formulated problem. The impact of proposed strategy is assessed by numerical analysis in MATLAB programming under stochastic environment.
Description:
Malware analysts, besides being tasked to create signatures, are also called upon to generate indicators of compromise, to disrupt botnets, to attribute an attack to an actor, and to understand the adversary's intent. This requires extracting from malware a variety of secrets, aka threat intelligence. After studying a few samples from a malware family and locating where its secrets are embedded, analysts create rules that may be used to automatically extract threat intelligence from malware variants in the future. Rules to extract secrets from malware are today written as regular expressions over bytecodes, such as using Yara. These rules are easily invalidated by polymorphic variants or evolutionary versions. Keeping the rules updated is a maintenance challenge for malware analysts. Instead of using bytecode, we present the use of code semantics to create rules to extract malware secrets. The semantics of code captures the effect of instructions on the registers and memory. Rules written using the structure of the symbolic content of registers and memory, instead of bytecode, are more resilient to code transformation and evolutionary changes, and are thus less brittle and easier to maintain.
Description:
One pass learning updates a model with only a single scan of the dataset, without storing historical data. Previous studies focus on classification tasks with a fixed class set, and will perform poorly in an open dynamic environment when new classes emerge in a data stream. The performance degrades because the classifier needs to receive a sufficient number of instances from new classes to establish a good model. This can take a long period of time. In order to reduce this period to deal with any-time prediction task, we introduce a framework to handle emerging new classes called One-Pass Class Incremental Learning (OPCIL). The central issue in OPCIL is: how to effectively adapt a classifier of existing classes to incorporate emerging new classes. We call it the new class adaptation issue, and propose a new approach to address it, which requires only one new class instance. The key is to generate pseudo instances which are optimized to satisfy properties that produce a good discriminative classifier. We provide the necessary propertiesand optimization procedures required to address this issue. Experiments validate the effectiveness of this approach.