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This study addresses three important issues in tree bucking optimization in the context of cut-to-length harvesting. (1) Would the fit between the log demand and log output distributions be better if the price and/or demand matrices controlling the bucking decisions on modern cut-to-length harvesters were adjusted to the unique conditions of each individual stand? (2) In what ways can we generate stand and product specific price and demand matrices? (3) What alternatives do we have to measure the fit between the log demand and log output distributions, and what would be an ideal goodness-of-fit measure? Three iterative search systems were developed for seeking stand-specific price and demand matrix sets: (1) A fuzzy logic control system for calibrating the price matrix of one log product for one stand at a time (the stand-level one-product approach); (2) a genetic algorithm system for adjusting the price matrices of one log product in parallel for several stands (the forest-level one-product approach); and (3) a genetic algorithm system for dividing the overall demand matrix of each of the several log products into stand-specific sub-demands simultaneously for several stands and products (the forest-level multi-product approach). The stem material used for testing the performance of the stand-specific price and demand matrices against that of the reference matrices was comprised of 9 155 Norway spruce (Picea abies (L.) Karst.) sawlog stems gathered by harvesters from 15 mature spruce-dominated stands in southern Finland. The reference price and demand matrices were either direct copies or slightly modified versions of those used by two Finnish sawmilling companies. Two types of stand-specific bucking matrices were compiled for each log product. One was from the harvester-collected stem profiles and the other was from the pre-harvest inventory data. Four goodness-of-fit measures were analyzed for their appropriateness in determining the similarity between the log demand and log output distributions: (1) the apportionment degree (index), (2) the chi-square statistic, (3) Laspeyres quantity index, and (4) the price-weighted apportionment degree. The study confirmed that any improvement in the fit between the log demand and log output distributions can only be realized at the expense of log volumes produced. Stand-level pre-control of price matrices was found to be advantageous, provided the control is done with perfect stem data. Forest-level pre-control of price matrices resulted in no improvement in the cumulative apportionment degree. Cutting stands under the control of stand-specific demand matrices yielded a better total fit between the demand and output matrices at the forest level than was obtained by cutting each stand with non-stand-specific reference matrices. The theoretical and experimental analyses suggest that none of the three alternative goodness-of-fit measures clearly outperforms the traditional apportionment degree measure. Keywords: harvesting, tree bucking optimization, simulation, fuzzy control, genetic algorithms, goodness-of-fit

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African indigenous foods have received limited research. Most of these indigenous foods are fermented and they form part of the rich nutritional culture of many groups in African countries. The industrialization and commercialisation of these indigenous African fermented foods should be preceded by a thorough scientific knowledge of their processing which can be vital in the elimination of hunger and poverty. This study highlighted emerging developments and the microbiology of cereal-based and cassava-based food products that constitute a major part of the human diet in most African countries. In addition, investigations were also carried out on the coagulant of the Calotropis procera plant used in traditional production of Nigerian Wara cheese and on the effects of adding a nisin producing Lactococcus lactis strain originating from human milk to Nigerian Wara cheese. Fermented cereal-based food such as ogi utilize popular African and readily available grains maize, millet or sorghum as substrates and is popular as a weaning diet in infants. In this study, the bulkiness caused by starch gelatinization was solved by amylase treatments in the investigation on cooked and fermented oat bran porridge. A similar treatment could reduce the viscosity of any cereal porridge. The properties of the Sodom apple leaves (Calotropis procera) extract in cheesemaking were studied. C. procera was affected by monovalent (K+ and Na+) and divalent (Mg2+ and Ca2+) cations during coagulation. The rennet strength of this coagulant was found to be 7 % compared to animal rennet at 35 °C. Increasing the incubation temperature to 70 °C increased the rennet strength 28-fold. The molecular weight of the partially purified protease was determined by SDS-PAGE and was confirmed by Zymography to be approximately 60 kilodaltons. The high proteolytic activity at 70 °C supported the suitability of the protease enzyme as a coagulant in future commercial production of Nigerian Wara cheese. It was also possible to extend the shelf life of Wara cheese by a nisin producing lactic acid bacteria Lactococcus lactis LAC309. The levels of nisin in both whey and curd fractions of Wara were investigated, results showed a 3 log reduction of toxicogenic Bacillus licheniformis spiked on Wara after 3 days. These studies are the first in Finland to promote the advancement of scientific knowledge in African foods. Recognizing these indigenous food products and an efficient transfer of technology from the developed countries to industrialize them are necessary towards a successful realization of the United Nations Millenium Development Program.

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Improved information on the product quality of the plantation resource is needed to allow businesses to consider investing in the development of value-adding processing facilities. These facilities are likely to require customised design that optimises the utilisation of future small diameter plantation hardwood logs. This log resource will become available as wood supply in Queensland transitions from native forests to 100% from sustainable plantations. This resource will be controlled by plantations established prior to 2000. A survey of the three main growers (former Forest Enterprises Australia Pty Ltd, former Forestry Corporation of New South Wales, Hancock Queensland Plantation Pty Ltd) revealed that C. citriodora subsp.variegata – CCV (28.0%), Eucalyptus dunnii (27.5%), E. pilularis (23.0%), E. grandis (11.3%) and E. cloeziana –GMS (7.1%) were the most widely planted species in the southern Queensland and northern New South Wales subtropical hardwood estate and would potentially dominate the supply of plantation hardwoods to sawmill processing facilities.

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Telecommunications network management is based on huge amounts of data that are continuously collected from elements and devices from all around the network. The data is monitored and analysed to provide information for decision making in all operation functions. Knowledge discovery and data mining methods can support fast-pace decision making in network operations. In this thesis, I analyse decision making on different levels of network operations. I identify the requirements decision-making sets for knowledge discovery and data mining tools and methods, and I study resources that are available to them. I then propose two methods for augmenting and applying frequent sets to support everyday decision making. The proposed methods are Comprehensive Log Compression for log data summarisation and Queryable Log Compression for semantic compression of log data. Finally I suggest a model for a continuous knowledge discovery process and outline how it can be implemented and integrated to the existing network operations infrastructure.

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Limitations in quality bedding material have resulted in the growing need to re-use litter during broiler farming in some countries, which can be of concern from a food-safety perspective. The aim of this study was to compare the Campylobacter levels in ceca and litter across three litter treatments under commercial farming conditions. The litter treatments were (a) the use of new litter after each farming cycle; (b) an Australian partial litter re-use practice; and (c) a full litter re-use practice. The study was carried out on two farms over two years (Farm 1, from 2009–2010 and Farm 2, from 2010–2011), across three sheds (35,000 to 40,000 chickens/shed) on each farm, adopting three different litter treatments across six commercial cycles. A random sampling design was adopted to test litter and ceca for Campylobacter and Escherichia coli, prior to commercial first thin-out and final pick-up. Campylobacter levels varied little across litter practices and farming cycles on each farm and were in the range of log 8.0–9.0 CFU/g in ceca and log 4.0–6.0 MPN/g for litter. Similarly the E. coli in ceca were ∼log 7.0 CFU/g. At first thin-out and final pick-up, the statistical analysis for both litter and ceca showed that the three-way interaction (treatments by farms by times) was highly significant (P < 0.01), indicating that the patterns of Campylobacter emergence/presence across time vary between the farms, cycles and pickups. The emergence and levels of both organisms were not influenced by litter treatments across the six farming cycles on both farms. Either C. jejuni or C. coli could be the dominant species across litter and ceca, and this phenomenon could not be attributed to specific litter treatments. Irrespective of the litter treatments in place, cycle 2 on Farm 2 remained campylobacter-free. These outcomes suggest that litter treatments did not directly influence the time of emergence and levels of Campylobacter and E. coli during commercial farming.

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In recent years, spatial variability modeling of soil parameters using random field theory has gained distinct importance in geotechnical analysis. In the present Study, commercially available finite difference numerical code FLAC 5.0 is used for modeling the permeability parameter as spatially correlated log-normally distributed random variable and its influence on the steady state seepage flow and on the slope stability analysis are studied. Considering the case of a 5.0 m high cohesive-frictional soil slope of 30 degrees, a range of coefficients of variation (CoV%) from 60 to 90% in the permeability Values, and taking different values of correlation distance in the range of 0.5-15 m, parametric studies, using Monte Carlo simulations, are performed to study the following three aspects, i.e., (i) effect ostochastic soil permeability on the statistics of seepage flow in comparison to the analytic (Dupuit's) solution available for the uniformly constant permeability property; (ii) strain and deformation pattern, and (iii) stability of the given slope assessed in terms of factor of safety (FS). The results obtained in this study are useful to understand the role of permeability variations in slope stability analysis under different slope conditions and material properties. (C) 2009 Elsevier B.V. All rights reserved.

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Juvenile idiopathic arthritis (JIA) is a heterogeneous group of childhood chronic arthritides, associated with chronic uveitis in 20% of cases. For JIA patients responding inadequately to conventional disease-modifying anti-rheumatic drugs (DMARDs), biologic therapies, anti-tumor necrosis factor (anti-TNF) agents are available. In this retrospective multicenter study, 258 JIA-patients refractory to DMARDs and receiving biologic agents during 1999-2007 were included. Prior to initiation of anti-TNFs, growth velocity of 71 patients was delayed in 75% and normal in 25%. Those with delayed growth demonstrated a significant increase in growth velocity after initiation of anti-TNFs. Increase in growth rate was unrelated to pubertal growth spurt. No change was observed in skeletal maturation before and after anti-TNFs. The strongest predictor of change in growth velocity was growth rate prior to anti-TNFs. Change in inflammatory activity remained a significant predictor even after decrease in glucocorticoids was taken into account. In JIA-associated uveitis, impact of two first-line biologic agents, etanercept and infliximab, and second-line or third-line anti-TNF agent, adalimumab, was evaluated. In 108 refractory JIA patients receiving etanercept or infliximab, uveitis occurred in 45 (42%). Uveitis improved in 14 (31%), no change was observed in 14 (31%), and in 17 (38%) uveitis worsened. Uveitis improved more frequently (p=0.047) and frequency of annual uveitis flares was lower (p=0.015) in those on infliximab than in those on etanercept. In 20 patients taking adalimumab, 19 (95%) had previously failed etanercept and/or infliximab. In 7 patients (35%) uveitis improved, in one (5%) worsened, and in 12 (60%) no change occurred. Those with improved uveitis were younger and had shorter disease duration. Serious adverse events (AEs) or side-effects were not observed. Adalimumab was effective also in arthritis. Long-term drug survival (i.e. continuation rate on drug) with etanercept (n=105) vs. infliximab (n=104) was at 24 months 68% vs. 68%, and at 48 months 61% vs. 48% (p=0.194 in log-rank analysis). First-line anti-TNF agent was discontinued either due to inefficacy (etanercept 28% vs. infliximab 20%, p=0.445), AEs (7% vs. 22%, p=0.002), or inactive disease (10% vs. 16%, p=0.068). Females, patients with systemic JIA (sJIA), and those taking infliximab as the first therapy were at higher risk for treatment discontinuation. One-third switched to the second anti-TNF agent, which was discontinued less often than the first. In conclusion, in refractory JIA anti-TNFs induced enhanced growth velocity. Four-year treatment survival was comparable between etanercept and infliximab, and switching from first-line to second-line agent a reasonable therapeutic option. During anti-TNF treatment, one-third with JIA-associated anterior uveitis improved.

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The keyword based search technique suffers from the problem of synonymic and polysemic queries. Current approaches address only theproblem of synonymic queries in which different queries might have the same information requirement. But the problem of polysemic queries,i.e., same query having different intentions, still remains unaddressed. In this paper, we propose the notion of intent clusters, the members of which will have the same intention. We develop a clustering algorithm that uses the user session information in query logs in addition to query URL entries to identify cluster of queries having the same intention. The proposed approach has been studied through case examples from the actual log data from AOL, and the clustering algorithm is shown to be successful in discerning the user intentions.

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A linear time approximate maximum likelihood decoding algorithm on tail-biting trellises is presented, that requires exactly two rounds on the trellis. This is an adaptation of an algorithm proposed earlier with the advantage that it reduces the time complexity from O(m log m) to O(m) where m is the number of nodes in the tail-biting trellis. A necessary condition for the output of the algorithm to differ from the output of the ideal ML decoder is deduced and simulation results on an AWGN channel using tail-biting trellises for two rate 1/2 convolutional codes with memory 4 and 6 respectively, are reported.

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In a paper published in 1993, Erdos proved that if n! = a! b!, where 1 < a a parts per thousand currency sign b, then the difference between n and b does not exceed 5 log log n for large enough n. In the present paper, we improve this upper bound to ((1 + epsilon)/ log 2) log log n and generalize it to the equation a (1)!a (2)! ... a (k) ! = n!. In a recent paper, F. Luca proved that n - b = 1 for large enough n provided that the ABC-hypothesis holds.

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We propose an efficient and parameter-free scoring criterion, the factorized conditional log-likelihood (ˆfCLL), for learning Bayesian network classifiers. The proposed score is an approximation of the conditional log-likelihood criterion. The approximation is devised in order to guarantee decomposability over the network structure, as well as efficient estimation of the optimal parameters, achieving the same time and space complexity as the traditional log-likelihood scoring criterion. The resulting criterion has an information-theoretic interpretation based on interaction information, which exhibits its discriminative nature. To evaluate the performance of the proposed criterion, we present an empirical comparison with state-of-the-art classifiers. Results on a large suite of benchmark data sets from the UCI repository show that ˆfCLL-trained classifiers achieve at least as good accuracy as the best compared classifiers, using significantly less computational resources.

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The behaviour of saturated soils undergoing consolidation is very complex, It may not follow Terzaghi's theory over the entire consolidation process, Different soils may behave in such a way as to fit into Terzaghi's theory over some specific stages of the consolidation process (percentage of consolidation), This may be one of the reasons for the difficulties faced by the existing curve-fitting procedures in obtaining the coefficient of consolidation, c(v). It has been shown that the slope of the initial linear portion of the theoretical log U-log T curve is constant over a wider range of degree of consolidation, U, when compared with the other methods in use, This initial well-defined straight line in the log U-log T plot intersects the U = 100% line at T = pi/4, which corresponds to U = 88.3%, The proposed log delta-log t method is based on this observation, which gives the value of c(v) through simple graphical construction, In the proposed method, which is more versatile, identification of the characteristic straight lines is very clear; the intersection of these lines is more precise and the method does not depend upon the initial compression for the determination of c(v).

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Molecular complexes of melamine with hydroxy and dihydroxybenzoic acids have been analyzed to assess the collective role of the hydroxyl (OH) and carboxyl (COOH) functionalities in the recognition process. In most cases, solvents of crystallization do play a major role in self-assembly and structure stabilization. Hydrated compounds generate linear chains of melamine molecules with acid molecules pendant resulting in a zipper architecture. However, anhydrous and solvated compounds generate tetrameric units consisting of melamine dimers together with acid molecules. These tetramers in turn interweave to form a Lincoln log arrangement in the crystal. The salt/co-crystal formation in these complexes cannot be predicted apriori on the basis of Delta pK(a) values as there exists a salt-to-co-crystal continuum.

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We consider a dense ad hoc wireless network comprising n nodes confined to a given two dimensional region of fixed area. For the Gupta-Kumar random traffic model and a realistic interference and path loss model (i.e., the channel power gains are bounded above, and are bounded below by a strictly positive number), we study the scaling of the aggregate end-to-end throughput with respect to the network average power constraint, P macr, and the number of nodes, n. The network power constraint P macr is related to the per node power constraint, P macr, as P macr = np. For large P, we show that the throughput saturates as Theta(log(P macr)), irrespective of the number of nodes in the network. For moderate P, which can accommodate spatial reuse to improve end-to-end throughput, we observe that the amount of spatial reuse feasible in the network is limited by the diameter of the network. In fact, we observe that the end-to-end path loss in the network and the amount of spatial reuse feasible in the network are inversely proportional. This puts a restriction on the gains achievable using the cooperative communication techniques studied in and, as these rely on direct long distance communication over the network.

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We present a method to guess the realization of an arbitrarily varying source. Let TU be the type of the unknown state sequence. Our method results in a guessing moment that is within Kn (TU) + O(log n=n) of the minimum attainable guessing moment with full knowledge of source statistics, i.e., with knowledge of the sequence of states sn. The quantity Kn (TU) + O(log n=n) can be interpreted as the penalty one pays for not knowing the sequence of states sn of the source. Kn (TU) by itself is the penalty one pays for guessing with the additional knowledge that the state sequence belongs to type TU. Conversely, given any guessing strategy, for every type TU, there is a state sequence belonging to this type whose corresponding source forces a guessing moment penalty of at least Kn (TU) ¡ O(log n=n).