An Optimal g-Guidance Scheme for Satellite Launch Vehicles

A closed-loop steering logic based on an optimal (2-guidance is developed here. The guidance system drives the satellite launch vehicle along a two- or three- dimensional trajectory for placing the payload into a specified circular orbit. The modified g-guidance algorithm makes use of the optimal required velocity vector, which minimizes the total impulse needed for an equivalent two-impluse transfer from the present state to the final orbit. The required velocity vector is defined as velocity of the vehicle on the hypothetical transfer orbit immediately after the application of the first impulse. For this optimal transfer orbit, a simple and elegant expression for the Q-matrix is derived. A working principle for the guidance algorithm in terms of the major and minor cycles, and also for the generation of the steering command, is outlined.

Fungal Biopesticide for cattle tick and buffalo fly control

Cattle ticks and buffalo flies impose significant economic burdens on the Northern Australian cattle and dairy industries. With the increased temperatures expected under climate change the range of parasites such as these is likely to extend. Current control options for these ectoparasites are limited by problems associated with chemical resistance and residues. Fungal biopesticides offer a sustainable and promising alternative method of control. Laboratory and animal studies have established the potential for the fungus Metarhizium in tick control and provided data that suggests a secondary effect of buffalo fly control is possible. Small field trials are required to obtain a proof of concept for the control of ticks and buffalo flies on animals.

Some aspects of multilevel load-frequency control of a power system

The application of multilevel control strategies for load-frequency control of interconnected power systems is assuming importance. A large multiarea power system may be viewed as an interconnection of several lower-order subsystems, with possible change of interconnection pattern during operation. The solution of the control problem involves the design of a set of local optimal controllers for the individual areas, in a completely decentralised environment, plus a global controller to provide the corrective signal to account for interconnection effects. A global controller, based on the least-square-error principle suggested by Siljak and Sundareshan, has been applied for the LFC problem. A more recent work utilises certain possible beneficial aspects of interconnection to permit more desirable system performances. The paper reports the application of the latter strategy to LFC of a two-area power system. The power-system model studied includes the effects of excitation system and governor controls. A comparison of the two strategies is also made.

Alternative fruit fly control for market access and to enhance IPM in eggplant

Eggplant was identified as another fruit fly host commodity where recent changes to interstate market access requirements are causing problems for industry. The proposed research aims to develop a systems approach to meet interstate market access requirements.

Improved Disease control in Hydroponic Production

Hydroponic production systems offer optimal conditions for rapid growth, protection from adverse weather and greater water use efficiency. The most important limitation for hydroponic production production is water borne disease. Water borne disease can rapidly spread causing up to 100% crop failure.

Introduction, establishment, and potential geographic range of Carmenta sp. nr ithacae (Lepidoptera: Sesiidae), a biological control agent for Parthenium hysterophorus (Asteraceae) in Australia

Parthenium (Parthenium hysterophorus L.), a major weed causing economic, environmental, and human and animal health problems in Australia and several countries in Asia, Africa, and the Pacific, has been a target for biological control in Australia since the mid-1970s. Nine species of insects and two rust fungi have been introduced as biological control agents into Australia. These include Carmenta sp. nr ithacae, a root feeding agent from Mexico. The larvae of C. sp. nr ithacae bore through the stem-base into the root where they feed on the cortical tissue of the taproot. During 1998-2002, 2,816 larval-infested plants and 387 adults were released at 31 sites across Queensland, Australia. Evidence of field establishment was first observed in two of the release sites in central Queensland in 2004. Annual surveys at these sites and nonrelease sites during 2006-2011 showed wide variations in the incidence and abundance of C. sp. nr ithacae between years and sites. Surveys at three of the nine release sites in northern Queensland and 16 of the 22 release sites in central Queensland confirmed the field establishment of C. sp. nr ithacae in four release sites and four nonrelease sites, all in central Queensland. No field establishment was evident in the inland region or in northern Queensland. A CLIMEX model based on the native range distribution of C. sp. nr ithacae predicts that areas east of the dividing range along the coast are more suitable for field establishment than inland areas. Future efforts to redistribute this agent should be restricted to areas identified as climatically favorable by the CLIMEX model.

Active vibration suppression of non-linear beams using optimal dynamic inversion

Euler–Bernoulli beams are distributed parameter systems that are governed by a non-linear partial differential equation (PDE) of motion. This paper presents a vibration control approach for such beams that directly utilizes the non-linear PDE of motion, and hence, it is free from approximation errors (such as model reduction, linearization etc.). Two state feedback controllers are presented based on a newly developed optimal dynamic inversion technique which leads to closed-form solutions for the control variable. In one formulation a continuous controller structure is assumed in the spatial domain, whereas in the other approach it is assumed that the control force is applied through a finite number of discrete actuators located at predefined discrete locations in the spatial domain. An implicit finite difference technique with unconditional stability has been used to solve the PDE with control actions. Numerical simulation studies show that the beam vibration can effectively be decreased using either of the two formulations.

Improved management of key northern region weeds: diverse problems, diverse solutions

The cropping region of northern Australia has a diverse range of cropping systems and weed flora. A fallow phase is commonly required between crops to enable the accumulation of stored soil water in these farming systems dominated by reduced tillage. During the fallow phase, weed control is important and is heavily reliant on herbicides. The most commonly used herbicide has been glyphosate. As a result of over-reliance on glyphosate, there are now seven confirmed glyphosate-resistant weeds and several glyphosate-tolerant species common in the region. As a result, the control of summer fallow weeds is become more complex. This paper outlines project work investigating improved weed control for summer fallows in the northern cropping region. Areas of research include weed ecology, chemical and non-chemical tactics, glyphosate resistance and resistance surveys. The project also has an economic and extension component. As a result of our research we have a better understanding of the ecology of major northern weeds and spread of glyphosate resistance in the region. We have identified and defined alternative herbicide and non-chemical approaches for the effective control of summer fallow weeds and have extended our research effectively to industry.

Australia’s present scientific capacity to progress the biological control of weeds

Australia has a very proud record of achievement in biological control of weeds and the underpinning science. From the earliest campaigns against prickly pear and lantana, weed biocontrol developed with major contributions from CSIRO and state governments to produce outstanding successes against weeds such as salvinia, rubber vine, Noogoora burr, bridal creeper and prickly pear. Maximum research activity occurred in the 1980s when some 30 scientists were working world wide on Australia’s weed problems. Activity declined gradually until the last few years when government divestment in agricultural research greatly diminished capacity. There are now approximately eight full-time scientist equivalents supporting Australia’s weed biocontrol effort. Australia may now need to adopt a team approach to tackle future major weed biological control projects.

Weeds of Direct-Seeded Rice in Asia: Problems and Opportunities

Rice production symbolizes the single largest land use for food production on the Earth. The significance of this cereal as a source of energy and income seems overwhelming for millions of people in Asia, representing 90% of global rice production and consumption. Estimates indicate that the burgeoning population will need 25% more rice by 2025 than today's consumption. As the demand for rice is increasing, its production in Asia is threatened by a dwindling natural resource base, socioeconomic limitations, and uncertainty of climatic optima. Transplanting in puddled soil with continuous flooding is a common method of rice crop establishment in Asia. There is a dire need to look for rice production technologies that not only cope with existing limitations of transplanted rice but also are viable, economical, and secure for future food demand.Direct seeding of rice has evolved as a potential alternative to the current detrimental practice of puddling and nursery transplanting. The associated benefits include higher water productivity, less labor and energy inputs, less methane emissions, elimination of time and edaphic conflicts in the rice-wheat cropping system, and early crop maturity. Realization of the yield potential and sustainability of this resource-conserving rice production technique lies primarily in sustainable weed management, since weeds have been recognized as the single largest biological constraint in direct-seeded rice (DSR). Weed competition can reduce DSR yield by 30-80% and even complete crop failure can occur under specific conditions. Understanding the dynamics and outcomes of weed-crop competition in DSR requires sound knowledge of weed ecology, besides production factors that influence both rice and weeds, as well as their association. Successful adoption of direct seeding at the farmers' level in Asia will largely depend on whether farmers can control weeds and prevent shifts in weed populations from intractable weeds to more difficult-to-control weeds as a consequence of direct seeding. Sustainable weed management in DSR comprises all the factors that give DSR a competitive edge over weeds regarding acquisition and use of growth resources. This warrants the need to integrate various cultural practices with weed control measures in order to broaden the spectrum of activity against weed flora. A weed control program focusing entirely on herbicides is no longer ecologically sound, economically feasible, and effective against diverse weed flora and may result in the evolution of herbicide-resistant weed biotypes. Rotation of herbicides with contrasting modes of action in conjunction with cultural measures such as the use of weed-competitive rice cultivars, sowing time, stale seedbed technique, seeding rate, crop row spacing, fertilizer and water inputs and their application method/timing, and manual and mechanical hoeing can prove more effective and need to be optimized keeping in view the type and intensity of weed infestation. This chapter tries to unravel the dynamics of weed-crop competition in DSR. Technological issues, limitations associated with DSR, and opportunities to combat the weed menace are also discussed as a pragmatic approach for sustainable DSR production. A realistic approach to secure yield targets against weed competition will combine the abovementioned strategies and tactics in a coordinated manner. This chapter further suggests the need of multifaceted and interdisciplinary research into ecologically based weed management, as DSR seems inevitable in the near future.

Weed control in dry direct-seeded rice using tank mixtures of herbicides in South Asia

Dry direct-seeded rice (DSR) faces with complex weed problems particularly when farmers missed pre-emergence herbicide applications. Thus, an effective and strategic weed control in DSR is often required with available options of post-emergence herbicides. In such situations, tank mixtures of herbicides may provide broad spectrum weed control in DSR. Field experiments were conducted in the wet seasons of 2013 and 2014 to study weed control in response to tank mixtures of herbicides currently applied in DSR in South Asia. Results revealed that the tank mixtures of the currently available herbicides (azimsulfuron plus bispyribac or fenoxaprop, bispyribac plus fenoxaprop, and azimsulfuron plus bispyribac plus fenoxaprop; all applied as post-emergence) rarely resulted in antagonistic effects. Highest weed control efficiency (∼98%) was recorded with the tank mixture of azimsulfuron plus bispyribac plus fenoxaprop during both the years. This treatment also produced highest grain yield (7.2 t ha−1 in 2013 and 7.9 t ha−1in 2014), which was similar to the grain yield in the plots treated with the tank mix of azimsulfuron plus fenoxaprop, pendimethalin (applied as pre-emergence) followed by (fb) bispyribac, pendimethalin fb fenoxaprop, as well as pendimethalin fb azimsulfuron. Plots treated with the post-emergence application of single herbicide (i.e., azimsulfuron, bispyribac, or fenoxaprop) had lower grain yield (3.0–5.2 t ha−1 in 2013 to 3.5–6.1 t ha−1in 2014) than all the sequential herbicide treatments and tank mixtures (azimsulfuron plus fenoxaprop and azimsulfuron plus bispyribac), owing to a broad spectrum weed control. The study suggested that if farmers missed the pre-emergence application of herbicides (e.g., pendimethalin) due to erratic rains or due to other reasons, good weed control and high yield can still be obtained with tank mix applications of azimsulfuron plus fenoxaprop or azimsulfuron plus bispyribac plus fenoxaprop in DSR.

Solution of a class of vibration problems by flowgraph methods

A 4-degree-of-freedom single-input system and a 3-degree-of-freedom multi-input system are solved by the Coates', modified Coates' and Chan-Mai flowgraph methods. It is concluded that the Chan-Mai flowgraph method is superior to other flowgraph methods in such cases.

Halosulfuron-methyl: A selective herbicide option for the control of the invasive 'Cyperus aromaticus' (Ridley) Mattf. and Kukenth (Navua sedge)

There are currently limited options for the control of the invasive tropical perennial sedge 'Cyperus aromaticus' (Ridley) Mattf. and Kukenth (Navua sedge). The potential for halosulfuron-methyl as a selective herbicide for Navua sedge control in tropical pastures was investigated by undertaking successive field and shade house experiments in North Queensland, Australia. Halosulfuron-methyl and adjuvant rates, and combinations with other herbicides, were examined to identify a herbicide regime that most effectively reduced Navua sedge. Our research indicated that combining halosulfuron- methyl with other herbicides did not improve efficacy for Navua sedge control. We also identified that low rates of halosulfuron-methyl (25 g ha-1 a.i.) were just as effective as higher rates (73 g ha-1 a.i.) at controlling the sedge, and that this control relied on the addition of the adjuvant Bonza at the recommended concentration (1% of the spray volume). Pot trials in the controlled environment of the shade house achieved total mortality under these regimes. Field trials demonstrated more variable results with reductions in Navua sedge ranging between 40-95% at 8-10 weeks after treatment. After this period (16-24 weeks after treatment), regrowth of sedge, either from newly germinated seed, or of small plants protected from initial treatment, indicated sedge populations can rapidly increase to levels similar to pre-application, depending on the location and climatic conditions. Such variable results highlight the need for concerted monitoring of pastures to identify optimal treatment times. Ideally, initial treatment should be done when the sedge is healthy and actively growing, with follow up-treatments applied when new seed heads are produced from regrowth.

Problems and Algorithms for Sequence Segmentations

The analysis of sequential data is required in many diverse areas such as telecommunications, stock market analysis, and bioinformatics. A basic problem related to the analysis of sequential data is the sequence segmentation problem. A sequence segmentation is a partition of the sequence into a number of non-overlapping segments that cover all data points, such that each segment is as homogeneous as possible. This problem can be solved optimally using a standard dynamic programming algorithm. In the first part of the thesis, we present a new approximation algorithm for the sequence segmentation problem. This algorithm has smaller running time than the optimal dynamic programming algorithm, while it has bounded approximation ratio. The basic idea is to divide the input sequence into subsequences, solve the problem optimally in each subsequence, and then appropriately combine the solutions to the subproblems into one final solution. In the second part of the thesis, we study alternative segmentation models that are devised to better fit the data. More specifically, we focus on clustered segmentations and segmentations with rearrangements. While in the standard segmentation of a multidimensional sequence all dimensions share the same segment boundaries, in a clustered segmentation the multidimensional sequence is segmented in such a way that dimensions are allowed to form clusters. Each cluster of dimensions is then segmented separately. We formally define the problem of clustered segmentations and we experimentally show that segmenting sequences using this segmentation model, leads to solutions with smaller error for the same model cost. Segmentation with rearrangements is a novel variation to the segmentation problem: in addition to partitioning the sequence we also seek to apply a limited amount of reordering, so that the overall representation error is minimized. We formulate the problem of segmentation with rearrangements and we show that it is an NP-hard problem to solve or even to approximate. We devise effective algorithms for the proposed problem, combining ideas from dynamic programming and outlier detection algorithms in sequences. In the final part of the thesis, we discuss the problem of aggregating results of segmentation algorithms on the same set of data points. In this case, we are interested in producing a partitioning of the data that agrees as much as possible with the input partitions. We show that this problem can be solved optimally in polynomial time using dynamic programming. Furthermore, we show that not all data points are candidates for segment boundaries in the optimal solution.

Computationally Efficient Methods for MDL-Optimal Density Estimation and Data Clustering

The Minimum Description Length (MDL) principle is a general, well-founded theoretical formalization of statistical modeling. The most important notion of MDL is the stochastic complexity, which can be interpreted as the shortest description length of a given sample of data relative to a model class. The exact definition of the stochastic complexity has gone through several evolutionary steps. The latest instantation is based on the so-called Normalized Maximum Likelihood (NML) distribution which has been shown to possess several important theoretical properties. However, the applications of this modern version of the MDL have been quite rare because of computational complexity problems, i.e., for discrete data, the definition of NML involves an exponential sum, and in the case of continuous data, a multi-dimensional integral usually infeasible to evaluate or even approximate accurately. In this doctoral dissertation, we present mathematical techniques for computing NML efficiently for some model families involving discrete data. We also show how these techniques can be used to apply MDL in two practical applications: histogram density estimation and clustering of multi-dimensional data.