Employment and unemployment statistics as indexes of economic activity and capacity utilization /

"April 1979"--Cover.

Modelagem matemática para maximização da produção da cana-de-açúcar (Saccharum spp.) e impactos sobre o custo de operações mecanizadas de corte e carregamento

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Research monograph : emergence of smart urban ecosystems : application of ICT for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been the key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Web-based Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these web-based tools for collaborative decision making.

Planning for smart urban ecosystems : information technology applications for capacity building in environmental decision making

Since the industrial revolution, our world has experienced rapid and unplanned industrialization and urbanization. As a result, we have had to cope with serious environmental challenges. In this context, an explanation of how smart urban ecosystems can emerge, gains a crucial importance. Capacity building and community involvement have always been key issues in achieving sustainable development and enhancing urban ecosystems. By considering these, this paper looks at new approaches to increase public awareness of environmental decision making. This paper will discuss the role of Information and Communication Technologies (ICT), particularly Webbased Geographic Information Systems (Web-based GIS) as spatial decision support systems to aid public participatory environmental decision making. The paper also explores the potential and constraints of these webbased tools for collaborative decision making.

Modelling and solving train scheduling problems under capacity constraints

Many large coal mining operations in Australia rely heavily on the rail network to transport coal from mines to coal terminals at ports for shipment. Over the last few years, due to the fast growing demand, the coal rail network is becoming one of the worst industrial bottlenecks in Australia. As a result, this provides great incentives for pursuing better optimisation and control strategies for the operation of the whole rail transportation system under network and terminal capacity constraints. This PhD research aims to achieve a significant efficiency improvement in a coal rail network on the basis of the development of standard modelling approaches and generic solution techniques. Generally, the train scheduling problem can be modelled as a Blocking Parallel- Machine Job-Shop Scheduling (BPMJSS) problem. In a BPMJSS model for train scheduling, trains and sections respectively are synonymous with jobs and machines and an operation is regarded as the movement/traversal of a train across a section. To begin, an improved shifting bottleneck procedure algorithm combined with metaheuristics has been developed to efficiently solve the Parallel-Machine Job- Shop Scheduling (PMJSS) problems without the blocking conditions. Due to the lack of buffer space, the real-life train scheduling should consider blocking or hold-while-wait constraints, which means that a track section cannot release and must hold a train until the next section on the routing becomes available. As a consequence, the problem has been considered as BPMJSS with the blocking conditions. To develop efficient solution techniques for BPMJSS, extensive studies on the nonclassical scheduling problems regarding the various buffer conditions (i.e. blocking, no-wait, limited-buffer, unlimited-buffer and combined-buffer) have been done. In this procedure, an alternative graph as an extension of the classical disjunctive graph is developed and specially designed for the non-classical scheduling problems such as the blocking flow-shop scheduling (BFSS), no-wait flow-shop scheduling (NWFSS), and blocking job-shop scheduling (BJSS) problems. By exploring the blocking characteristics based on the alternative graph, a new algorithm called the topological-sequence algorithm is developed for solving the non-classical scheduling problems. To indicate the preeminence of the proposed algorithm, we compare it with two known algorithms (i.e. Recursive Procedure and Directed Graph) in the literature. Moreover, we define a new type of non-classical scheduling problem, called combined-buffer flow-shop scheduling (CBFSS), which covers four extreme cases: the classical FSS (FSS) with infinite buffer, the blocking FSS (BFSS) with no buffer, the no-wait FSS (NWFSS) and the limited-buffer FSS (LBFSS). After exploring the structural properties of CBFSS, we propose an innovative constructive algorithm named the LK algorithm to construct the feasible CBFSS schedule. Detailed numerical illustrations for the various cases are presented and analysed. By adjusting only the attributes in the data input, the proposed LK algorithm is generic and enables the construction of the feasible schedules for many types of non-classical scheduling problems with different buffer constraints. Inspired by the shifting bottleneck procedure algorithm for PMJSS and characteristic analysis based on the alternative graph for non-classical scheduling problems, a new constructive algorithm called the Feasibility Satisfaction Procedure (FSP) is proposed to obtain the feasible BPMJSS solution. A real-world train scheduling case is used for illustrating and comparing the PMJSS and BPMJSS models. Some real-life applications including considering the train length, upgrading the track sections, accelerating a tardy train and changing the bottleneck sections are discussed. Furthermore, the BPMJSS model is generalised to be a No-Wait Blocking Parallel- Machine Job-Shop Scheduling (NWBPMJSS) problem for scheduling the trains with priorities, in which prioritised trains such as express passenger trains are considered simultaneously with non-prioritised trains such as freight trains. In this case, no-wait conditions, which are more restrictive constraints than blocking constraints, arise when considering the prioritised trains that should traverse continuously without any interruption or any unplanned pauses because of the high cost of waiting during travel. In comparison, non-prioritised trains are allowed to enter the next section immediately if possible or to remain in a section until the next section on the routing becomes available. Based on the FSP algorithm, a more generic algorithm called the SE algorithm is developed to solve a class of train scheduling problems in terms of different conditions in train scheduling environments. To construct the feasible train schedule, the proposed SE algorithm consists of many individual modules including the feasibility-satisfaction procedure, time-determination procedure, tune-up procedure and conflict-resolve procedure algorithms. To find a good train schedule, a two-stage hybrid heuristic algorithm called the SE-BIH algorithm is developed by combining the constructive heuristic (i.e. the SE algorithm) and the local-search heuristic (i.e. the Best-Insertion- Heuristic algorithm). To optimise the train schedule, a three-stage algorithm called the SE-BIH-TS algorithm is developed by combining the tabu search (TS) metaheuristic with the SE-BIH algorithm. Finally, a case study is performed for a complex real-world coal rail network under network and terminal capacity constraints. The computational results validate that the proposed methodology would be very promising because it can be applied as a fundamental tool for modelling and solving many real-world scheduling problems.

Effect of pedestrian movement on MIMO-OFDM channel capacity in an indoor environment

The rapid growth of mobile telephone use, satellite services, and now the wireless Internet and WLANs are generating tremendous changes in telecommunication and networking. As indoor wireless communications become more prevalent, modeling indoor radio wave propagation in populated environments is a topic of significant interest. Wireless MIMO communication exploits phenomena such as multipath propagation to increase data throughput and range, or reduce bit error rates, rather than attempting to eliminate effects of multipath propagation as traditional SISO communication systems seek to do. The MIMO approach can yield significant gains for both link and network capacities, with no additional transmitting power or bandwidth consumption when compared to conventional single-array diversity methods. When MIMO and OFDM systems are combined and deployed in a suitable rich scattering environment such as indoors, a significant capacity gain can be observed due to the assurance of multipath propagation. Channel variations can occur as a result of movement of personnel, industrial machinery, vehicles and other equipment moving within the indoor environment. The time-varying effects on the propagation channel in populated indoor environments depend on the different pedestrian traffic conditions and the particular type of environment considered. A systematic measurement campaign to study pedestrian movement effects in indoor MIMO-OFDM channels has not yet been fully undertaken. Measuring channel variations caused by the relative positioning of pedestrians is essential in the study of indoor MIMO-OFDM broadband wireless networks. Theoretically, due to high multipath scattering, an increase in MIMO-OFDM channel capacity is expected when pedestrians are present. However, measurements indicate that some reductions in channel capacity could be observed as the number of pedestrians approaches 10 due to a reduction in multipath conditions as more human bodies absorb the wireless signals. This dissertation presents a systematic characterization of the effects of pedestrians in indoor MIMO-OFDM channels. Measurement results, using the MIMO-OFDM channel sounder developed at the CSIRO ICT Centre, have been validated by a customized Geometric Optics-based ray tracing simulation. Based on measured and simulated MIMO-OFDM channel capacity and MIMO-OFDM capacity dynamic range, an improved deterministic model for MIMO-OFDM channels in indoor populated environments is presented. The model can be used for the design and analysis of future WLAN to be deployed in indoor environments. The results obtained show that, in both Fixed SNR and Fixed Tx for deterministic condition, the channel capacity dynamic range rose with the number of pedestrians as well as with the number of antenna combinations. In random scenarios with 10 pedestrians, an increment in channel capacity of up to 0.89 bits/sec/Hz in Fixed SNR and up to 1.52 bits/sec/Hz in Fixed Tx has been recorded compared to the one pedestrian scenario. In addition, from the results a maximum increase in average channel capacity of 49% has been measured while 4 antenna elements are used, compared with 2 antenna elements. The highest measured average capacity, 11.75 bits/sec/Hz, corresponds to the 4x4 array with 10 pedestrians moving randomly. Moreover, Additionally, the spread between the highest and lowest value of the the dynamic range is larger for Fixed Tx, predicted 5.5 bits/sec/Hz and measured 1.5 bits/sec/Hz, in comparison with Fixed SNR criteria, predicted 1.5 bits/sec/Hz and measured 0.7 bits/sec/Hz. This has been confirmed by both measurements and simulations ranging from 1 to 5, 7 and 10 pedestrians.

Measurement, modelling and capacity analysis for novel, fixed multi-user single-antenna MIMO-OFDM system, in rural environments

High-speed broadband internet access is widely recognised as a catalyst to social and economic development. However, the provision of broadband Internet services with the existing solutions to rural population, scattered over an extensive geographical area, remains both an economic and technical challenge. As a feasible solution, the Commonwealth Scientific and Industrial Research Organization (CSIRO) proposed a highly spectrally efficient, innovative and cost-effective fixed wireless broadband access technology, which uses analogue TV frequency spectrum and Multi-User MIMO (MUMIMO) technology with Orthogonal-Frequency-Division-Multiplexing (OFDM). MIMO systems have emerged as a promising solution for the increasing demand of higher data rates, better quality of service, and higher network capacity. However, the performance of MIMO systems can be significantly affected by different types of propagation environments e.g., indoor, outdoor urban, or outdoor rural and operating frequencies. For instance, large spectral efficiencies associated with MIMO systems, which assume a rich scattering environment in urban environments, may not be valid for all propagation environments, such as outdoor rural environments, due to the presence of less scatterer densities. Since this is the first time a MU-MIMO-OFDM fixed broadband wireless access solution is deployed in a rural environment, questions from both theoretical and practical standpoints arise; For example, what capacity gains are available for the proposed solution under realistic rural propagation conditions?. Currently, no comprehensive channel measurement and capacity analysis results are available for MU-MIMO-OFDM fixed broadband wireless access systems which employ large scale multiple antennas at the Access Point (AP) and analogue TV frequency spectrum in rural environments. Moreover, according to the literature, no deterministic MU-MIMO channel models exist that define rural wireless channels by accounting for terrain effects. This thesis fills the aforementioned knowledge gaps with channel measurements, channel modeling and comprehensive capacity analysis for MU-MIMO-OFDM fixed wireless broadband access systems in rural environments. For the first time, channel measurements were conducted in a rural farmland near Smithton, Tasmania using CSIRO's broadband wireless access solution. A novel deterministic MU-MIMO-OFDM channel model, which can be used for accurate performance prediction of rural MUMIMO channels with dominant Line-of-Sight (LoS) paths, was developed under this research. Results show that the proposed solution can achieve 43.7 bits/s/Hz at a Signal-to- Noise Ratio (SNR) of 20 dB in rural environments. Based on channel measurement results, this thesis verifies that the deterministic channel model accurately predicts channel capacity in rural environments with a Root Mean Square (RMS) error of 0.18 bits/s/Hz. Moreover, this study presents a comprehensive capacity analysis of rural MU-MIMOOFDM channels using experimental, simulated and theoretical models. Based on the validated deterministic model, further investigations on channel capacity and the eects of capacity variation, with different user distribution angles (θ) around the AP, were analysed. For instance, when SNR = 20dB, the capacity increases from 15.5 bits/s/Hz to 43.7 bits/s/Hz as θ increases from 10° to 360°. Strategies to mitigate these capacity degradation effects are also presented by employing a suitable user grouping method. Outcomes of this thesis have already been used by CSIRO scientists to determine optimum user distribution angles around the AP, and are of great significance for researchers and MU-MUMO-OFDM system developers to understand the advantages and potential capacity gains of MU-MIMO systems in rural environments. Also, results of this study are useful to further improve the performance of MU-MIMO-OFDM systems in rural environments. Ultimately, this knowledge contribution will be useful in delivering efficient, cost-effective high-speed wireless broadband systems that are tailor-made for rural environments, thus, improving the quality of life and economic prosperity of rural populations.

Prediction of Ultimate Capacity of Laterally Loaded Piles in Clay: A Relevance Vector Machine Approach

This study investigates the potential of Relevance Vector Machine (RVM)-based approach to predict the ultimate capacity of laterally loaded pile in clay. RVM is a sparse approximate Bayesian kernel method. It can be seen as a probabilistic version of support vector machine. It provides much sparser regressors without compromising performance, and kernel bases give a small but worthwhile improvement in performance. RVM model outperforms the two other models based on root-mean-square-error (RMSE) and mean-absolute-error (MAE) performance criteria. It also stimates the prediction variance. The results presented in this paper clearly highlight that the RVM is a robust tool for prediction Of ultimate capacity of laterally loaded piles in clay.

Fatigue capacity of cold-formed steel roof battens under cyclic wind uplift loads

Steel roofs made of thin cold-formed steel roof claddings and battens are widely used in low-rise residential and industrial buildings all around the world. However, they suffer from premature localised pull-through failures in the batten to rafter connections during high wind events. A recent study proposed a suitable design equation for the pull-through failures of thin steel roof battens. However, it was limited to static wind uplift loading. In contrast, most cyclone/storm events produce cyclic wind uplift forces on roofs for a significantly long period, thus causing premature fatigue pull-through failures at lower loads. Therefore, a series of constant amplitude cyclic load tests was conducted on small and full scale roof panels made of a commonly used industrial roof batten to develop their S-N curves. A series of multi-level cyclic tests, including the recently introduced low-high-low (LHL) fatigue loading test, was also undertaken to simulate a design cyclone. Using the S-N curves, the static pull-through design capacity equation was modified to include the effects of fatigue. Applicability of Miner’s rule was evaluated in order to predict the fatigue damage caused by multi-level cyclic tests such as the LHL test, and suitable modifications were made. The combined use of the modified Miner’s law and the S-N curve of roof battens will allow a conservative estimation of the fatigue design capacity of roof battens without conducting the LHL tests simulating a design cyclone. This paper presents the details of this study, and the results.

Síntese e avaliação de hidrogéis à base de alginato e nanopartículas magnéticas preparadas in situ para remoção de Mn(II) e Ni(II) de efluente industrial

Esta Dissertação teve como objetivo,a síntese de hidrogéis à base de alginato e nanopartículas magnéticas (maghemita) preparadas in situ. Os hidrogéis foram preparados em diferentes concentrações de alginato de sódio (2 e 3% m/v), FeSO4 (0,3 e 0,5 mol L-1) e CaCl2 (0,1 e 0,3 mol L-1). As propriedades físico-químicas dos hidrogéis foram analisadas e, posteriormente, foram avaliados quanto à capacidade de remoção de íons Ni2+ e Mn2+ de soluções aquosas. Para caracterização das amostras foram utilizadas diversas técnicas de análises, tais como, análise granulométrica, microscopia óptica (OM), microscopia eletrônica de varredura (SEM), microscopia eletrônica de transmissão (TEM), magnetometria de amostra vibrante (VSM), espectroscopia na região do infravermelho por transformada de Fourier (FTIR), difratometria de raios-X (XRD), espectroscopia Mössbauer, e análise termogravimétrica (TGA). Foram preparados hidrogéis com morfologia predominantemente esférica e dimensões micrométricas (500 a 850 m), com átomos de Fe e Ca dispersos uniformemente em sua estrutura. Os hidrogéis apresentaram boa resistência térmica e comportamento superparamagnético. As amostras foram intumescidas em água deionizada durante um intervalo de tempo a fim de avaliar o grau de intumescimento (Q) para determinar a amostra com a melhor resposta para posterior aplicação em solução aquosa contendo íons metálicos (Ni2+ e Mn2+). Os resultados revelaram que a amostra cuja concentração de 3% m/v de alginato de sódio, 0,3 mol L-1 de FeSO4 e 0,3 mol L-1 de CaCl2 obteve maior Q (50%). Em consequência deste resultado, optou-se por utilizar estaamostra, na remoção de metais pesados presentes em soluções aquosas e em efluentes industriais. Vários parâmetros,tais como: tempo de contato,pH, concentração inicial do íon e massa de hidrogel foram estudados.Os resultados, para efluente sintético, revelaram que o tempo de equilíbrio foi de 60 minutos; a capacidade de remoção dos metais melhora com o aumento de pH (3 a 9), sendo máxima em pH 7;quanto menor a concentração inicial da solução iônica (50 a 500 mg L-1), maior a capacidade de remoção, 52% de Ni2+ e 49% de Mn2+ (concentração inicial de 50 mg L-1). No efluente industrial, a remoção foi de 61% de Ni2+ e 57% de Mn2+(300 mg de hidrogel). Os resultados encontrados revelaram que os hidrogéis magnéticos produzidos à base de alginato têm potencial uso no tratamento de efluentes industriais contaminados com metais pesados

Comparison of deterministic, stochastic and fuzzy logic uncertainty modelling for capacity extension projects of DI/WFI pharmaceutical plant utilities with variable/dynamic demand

The last 30 years have seen Fuzzy Logic (FL) emerging as a method either complementing or challenging stochastic methods as the traditional method of modelling uncertainty. But the circumstances under which FL or stochastic methods should be used are shrouded in disagreement, because the areas of application of statistical and FL methods are overlapping with differences in opinion as to when which method should be used. Lacking are practically relevant case studies comparing these two methods. This work compares stochastic and FL methods for the assessment of spare capacity on the example of pharmaceutical high purity water (HPW) utility systems. The goal of this study was to find the most appropriate method modelling uncertainty in industrial scale HPW systems. The results provide evidence which suggests that stochastic methods are superior to the methods of FL in simulating uncertainty in chemical plant utilities including HPW systems in typical cases whereby extreme events, for example peaks in demand, or day-to-day variation rather than average values are of interest. The average production output or other statistical measures may, for instance, be of interest in the assessment of workshops. Furthermore the results indicate that the stochastic model should be used only if found necessary by a deterministic simulation. Consequently, this thesis concludes that either deterministic or stochastic methods should be used to simulate uncertainty in chemical plant utility systems and by extension some process system because extreme events or the modelling of day-to-day variation are important in capacity extension projects. Other reasons supporting the suggestion that stochastic HPW models are preferred to FL HPW models include: 1. The computer code for stochastic models is typically less complex than a FL models, thus reducing code maintenance and validation issues. 2. In many respects FL models are similar to deterministic models. Thus the need for a FL model over a deterministic model is questionable in the case of industrial scale HPW systems as presented here (as well as other similar systems) since the latter requires simpler models. 3. A FL model may be difficult to "sell" to an end-user as its results represent "approximate reasoning" a definition of which is, however, lacking. 4. Stochastic models may be applied with some relatively minor modifications on other systems, whereas FL models may not. For instance, the stochastic HPW system could be used to model municipal drinking water systems, whereas the FL HPW model should or could not be used on such systems. This is because the FL and stochastic model philosophies of a HPW system are fundamentally different. The stochastic model sees schedule and volume uncertainties as random phenomena described by statistical distributions based on either estimated or historical data. The FL model, on the other hand, simulates schedule uncertainties based on estimated operator behaviour e.g. tiredness of the operators and their working schedule. But in a municipal drinking water distribution system the notion of "operator" breaks down. 5. Stochastic methods can account for uncertainties that are difficult to model with FL. The FL HPW system model does not account for dispensed volume uncertainty, as there appears to be no reasonable method to account for it with FL whereas the stochastic model includes volume uncertainty.

Industrial water pollution in Dhaka, Bangladesh: strategies and incentives for pollution control in small and medium enterprises

The extent and gravity of the environmental degradation of the water resources in Dhaka due to untreated industrial waste is not fully recognised in international discourse. Pollution levels affect vast numbers, but the poor and the vulnerable are the worst affected. For example, rice productivity, the mainstay of poor farmers, in the Dhaka watershed has declined by 40% over a period of ten years. The study found significant correlations between water pollution and diseases such as jaundice, diarrhoea and skin problems. It was reported that the cost of treatment of one episode of skin disease could be as high as 29% of the weekly earnings of some of the poorest households. The dominant approach to deal with pollution in the SMEs is technocratic. Given the magnitude of the problem this paper argues that to control industrial pollution by SMEs and to enhance their compliance it is necessary to move from the technocratic approach to one which can also address the wider institutional and attitudinal issues. Underlying this shift is the need to adopt the appropriate methodology. The multi-stakeholder analysis enables an understanding of the actors, their influence, their capacity to participate in, or oppose change, and the existing and embedded incentive structures which allow them to pursue interests which are generally detrimental to environmental good. This enabled core and supporting strategies to be developed around three types of actors in industrial pollution, i.e., (i) principal actors, who directly contribute to industrial pollution; (ii) stakeholders who exacerbate the situation; and (iii) potential actors in mitigation. Within a carrot-and-stick framework, the strategies aim to improve environmental governance and transparency, set up a packet to incentive for industry and increase public awareness.

Production of lightweight aggregate from industrial waste and carbon dioxide

The concomitant recycling of waste and carbon dioxide emissions is the subject of developing technology designed to close the industrial process loop and facilitate the bulk-re-use of waste in, for example, construction. The present work discusses a treatment step that employs accelerated carbonation to convert gaseous carbon dioxide into solid calcium carbonate through a reaction with industrial thermal residues. Treatment by accelerated carbonation enabled a synthetic aggregate to be made from thermal residues and waste quarry fines. The aggregates produced had a bulk density below 1000 kg/m3 and a high water absorption capacity. Aggregate crushing strengths were between 30% and 90% stronger than the proprietary lightweight expanded clay aggregate available in the UK. Cast concrete blocks containing the carbonated aggregate achieve compressive strengths of 24 MPa, making them suitable for use with concrete exposed to non-aggressive service environments. The energy intensive firing and sintering processes traditionally required to produce lightweight aggregates can now be augmented by a cold-bonding, low energy method that contributes to the reduction of green house gases to the atmosphere.

Characterization of carbonated tricalcium silicate and its sorption capacity for heavy metals: A micron-scale composite adsorbent of active silicate gel and calcite

Adsorption-based processes are widely used in the treatment of dilute metal-bearing wastewaters. The development of versatile, low-cost adsorbents is the subject of continuing interest. This paper examines the preparation, characterization and performance of a micro-scale composite adsorbent composed of silica gel (15.9 w/w%), calcium silicate hydrate gel (8.2 w/w%) and calcite (75.9 w/w%), produced by the accelerated carbonation of tricalcium silicate (C(3)S, Ca(3)SiO(5)). The Ca/Si ratio of calcium silicate hydrate gel (C-S-H) was determined at 0.12 (DTA/TG), 0.17 ((29)Si solid-state MAS/NMR) and 0.18 (SEM/EDS). The metals-retention capacity for selected Cu(II), Pb(II), Zn(II) and Cr(III) was determined by batch and column sorption experiments utilizing nitrate solutions. The effects of metal ion concentration, pH and contact time on binding ability was investigated by kinetic and equilibrium adsorption isotherm studies. The adsorption capacity for Pb(II), Cr(III), Zn(II) and Cu(II) was found to be 94.4 mg/g, 83.0 mg/g, 52.1 mg/g and 31.4 mg/g, respectively. It is concluded that the composite adsorbent has considerable potential for the treatment of industrial wastewater containing heavy metals.