973 resultados para process dynamics
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The present study on the dynamics of land use in recently settled forest areas. In the course of events, tribals lost their land; the demographic structure of Attappady changed; the cropping pattern got diversified; traditional techniques of production were ruined; new crops and new techniques of cultivation came to stay; and the entire cost and return structure of production underwent radical change. Migration to Attappady is essentially a continuation of the Malabar migration process from Travancore, through, some people from Tamil Nadu also had migrated to this region earlier. The demographic structure, along with land structure, has changed in favour of the settlers within a short span of time. Lack of security of ownership has acted as a strong reason for wanton exploitation of land resources. The major influencing factors on crop choices among settlers were labour endowment, date of settlement and education. Attappady is an unique ecosystem in Kerala characterized by many interdependables. The latest hand of environmental degradation is a grave danger especially on sloppy terrains,which are under cultivation of tapioca and dry annual crops like groundnuts, cotton, grams etc. Soil erosion as a result of the unplanned cultivation of these crops has resulted in dramatic decline in soil fertility and hence low crop productivity. This calls for a watershed management approach for the sustainable development of the region. A progressive agrarian transformation is warranted to maintain the homegarden as a sustainable production system in ecological and socio-economic terms.
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Machine tool chatter is an unfavorable phenomenon during metal cutting, which results in heavy vibration of cutting tool. With increase in depth of cut, the cutting regime changes from chatter-free cutting to one with chatter. In this paper, we propose the use of permutation entropy (PE), a conceptually simple and computationally fast measurement to detect the onset of chatter from the time series using sound signal recorded with a unidirectional microphone. PE can efficiently distinguish the regular and complex nature of any signal and extract information about the dynamics of the process by indicating sudden change in its value. Under situations where the data sets are huge and there is no time for preprocessing and fine-tuning, PE can effectively detect dynamical changes of the system. This makes PE an ideal choice for online detection of chatter, which is not possible with other conventional nonlinear methods. In the present study, the variation of PE under two cutting conditions is analyzed. Abrupt variation in the value of PE with increase in depth of cut indicates the onset of chatter vibrations. The results are verified using frequency spectra of the signals and the nonlinear measure, normalized coarse-grained information rate (NCIR).
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Medical fields requires fast, simple and noninvasive methods of diagnostic techniques. Several methods are available and possible because of the growth of technology that provides the necessary means of collecting and processing signals. The present thesis details the work done in the field of voice signals. New methods of analysis have been developed to understand the complexity of voice signals, such as nonlinear dynamics aiming at the exploration of voice signals dynamic nature. The purpose of this thesis is to characterize complexities of pathological voice from healthy signals and to differentiate stuttering signals from healthy signals. Efficiency of various acoustic as well as non linear time series methods are analysed. Three groups of samples are used, one from healthy individuals, subjects with vocal pathologies and stuttering subjects. Individual vowels/ and a continuous speech data for the utterance of the sentence "iruvarum changatimaranu" the meaning in English is "Both are good friends" from Malayalam language are recorded using a microphone . The recorded audio are converted to digital signals and are subjected to analysis.Acoustic perturbation methods like fundamental frequency (FO), jitter, shimmer, Zero Crossing Rate(ZCR) were carried out and non linear measures like maximum lyapunov exponent(Lamda max), correlation dimension (D2), Kolmogorov exponent(K2), and a new measure of entropy viz., Permutation entropy (PE) are evaluated for all three groups of the subjects. Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. The results shows that nonlinear dynamical methods seem to be a suitable technique for voice signal analysis, due to the chaotic component of the human voice. Permutation entropy is well suited due to its sensitivity to uncertainties, since the pathologies are characterized by an increase in the signal complexity and unpredictability. Pathological groups have higher entropy values compared to the normal group. The stuttering signals have lower entropy values compared to the normal signals.PE is effective in charaterising the level of improvement after two weeks of speech therapy in the case of stuttering subjects. PE is also effective in characterizing the dynamical difference between healthy and pathological subjects. This suggests that PE can improve and complement the recent voice analysis methods available for clinicians. The work establishes the application of the simple, inexpensive and fast algorithm of PE for diagnosis in vocal disorders and stuttering subjects.
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Timely detection of sudden change in dynamics that adversely affect the performance of systems and quality of products has great scientific relevance. This work focuses on effective detection of dynamical changes of real time signals from mechanical as well as biological systems using a fast and robust technique of permutation entropy (PE). The results are used in detecting chatter onset in machine turning and identifying vocal disorders from speech signal.Permutation Entropy is a nonlinear complexity measure which can efficiently distinguish regular and complex nature of any signal and extract information about the change in dynamics of the process by indicating sudden change in its value. Here we propose the use of permutation entropy (PE), to detect the dynamical changes in two non linear processes, turning under mechanical system and speech under biological system.Effectiveness of PE in detecting the change in dynamics in turning process from the time series generated with samples of audio and current signals is studied. Experiments are carried out on a lathe machine for sudden increase in depth of cut and continuous increase in depth of cut on mild steel work pieces keeping the speed and feed rate constant. The results are applied to detect chatter onset in machining. These results are verified using frequency spectra of the signals and the non linear measure, normalized coarse-grained information rate (NCIR).PE analysis is carried out to investigate the variation in surface texture caused by chatter on the machined work piece. Statistical parameter from the optical grey level intensity histogram of laser speckle pattern recorded using a charge coupled device (CCD) camera is used to generate the time series required for PE analysis. Standard optical roughness parameter is used to confirm the results.Application of PE in identifying the vocal disorders is studied from speech signal recorded using microphone. Here analysis is carried out using speech signals of subjects with different pathological conditions and normal subjects, and the results are used for identifying vocal disorders. Standard linear technique of FFT is used to substantiate thc results.The results of PE analysis in all three cases clearly indicate that this complexity measure is sensitive to change in regularity of a signal and hence can suitably be used for detection of dynamical changes in real world systems. This work establishes the application of the simple, inexpensive and fast algorithm of PE for the benefit of advanced manufacturing process as well as clinical diagnosis in vocal disorders.
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Natural systems are inherently non linear. Recurrent behaviours are typical of natural systems. Recurrence is a fundamental property of non linear dynamical systems which can be exploited to characterize the system behaviour effectively. Cross recurrence based analysis of sensor signals from non linear dynamical system is presented in this thesis. The mutual dependency among relatively independent components of a system is referred as coupling. The analysis is done for a mechanically coupled system specifically designed for conducting experiment. Further, cross recurrence method is extended to the actual machining process in a lathe to characterize the chatter during turning. The result is verified by permutation entropy method. Conventional linear methods or models are incapable of capturing the critical and strange behaviours associated with the dynamical process. Hence any effective feature extraction methodologies should invariably gather information thorough nonlinear time series analysis. The sensor signals from the dynamical system normally contain noise and non stationarity. In an effort to get over these two issues to the maximum possible extent, this work adopts the cross recurrence quantification analysis (CRQA) methodology since it is found to be robust against noise and stationarity in the signals. The study reveals that the CRQA is capable of characterizing even weak coupling among system signals. It also divulges the dependence of certain CRQA variables like percent determinism, percent recurrence and entropy to chatter unambiguously. The surrogate data test shows that the results obtained by CRQA are the true properties of the temporal evolution of the dynamics and contain a degree of deterministic structure. The results are verified using permutation entropy (PE) to detect the onset of chatter from the time series. The present study ascertains that this CRP based methodology is capable of recognizing the transition from regular cutting to the chatter cutting irrespective of the machining parameters or work piece material. The results establish this methodology to be feasible for detection of chatter in metal cutting operation in a lathe.
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This paper describes the current information dynamics and its effect in higher education and research in science and technology. Open access movement ,Institutional repositories ,Digital libraries,Knowledge gateways,Blogs,Wikis,and social bookmark tools have rapidly emerged on the web creating a new scenerio that radically changes the knowledge production process such as the creation of information,formats and sources of information,coding and processing ,accessing managing sharing and dissemination of information.The management of knowledge created by academia of Cochin University Of Science And Technology is examined in this challenging context of information dynamics.
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Distribution and chemistry of major inorganic forms of nutrients along with physico-chemical parameters were investigated. Surface sediments and overlying waters of the Ashtamudi and Vembanad Lakes were taken for the study, which is situated in the southwest coast of India. High concentrations of dissolved nitrogen and phosphorus compounds carried by the river leads to oxygen depletion in the water column. A concurrent increase in the bottom waters along with decrease in dissolved oxygen was noticed. This support to nitrification process operating in the sediment-water interface of the Ashtamudi and Vembanad Lake. Estuarine sediments are clayey sand to silty sand both in Ashtamudi and Vembanad in January and May. Present study indicates that the sediment texture is the major controlling factor in the distribution of these nutrient forms. For water samples nitrite, inorganic phosphate was high in Vembanad in January and May compared to Ashtamudi. For sediments, enhanced level of inorganic phosphate and nitrite was found in Vembanad during January and May. It had been observed that the level of N and P is more in sediments. A comparative assessment of the Ashtamudi and Vembanad Lake reveals that the Vembanad wetland is more deteriorated compared to the Ashtamudi wetland system
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A better understanding of effects after digestate application on plant community, soil microbial community as well as nutrient and carbon dynamics is crucial for a sustainable grassland management and the prevention of species and functional diversity loss. The specific research objectives of the thesis were: (i) to investigate effects after digestate application on grass species and soil microbial community, especially focussing on nitrogen dynamic in the plant-soil system and to examine the suitability of the digestate from the “integrated generation of solid fuel and biogas from biomass” (IFBB) system as fertilizer (Chapter 3). (ii) to investigate the relationship between plant community and functionality of soil microbial community of extensively managed meadows, taking into account temporal variations during the vegetation period and abiotic soil conditions (Chapter 4). (iii) to investigate the suitability of IFBB-concept implementation as grassland conservation measure for meadows and possible associated effects of IFBB digestate application on plant and soil microbial community as well as soil microbial substrate utilization and catabolic evenness (Chapter 5). Taken together the results indicate that the digestate generated during the IFBB process stands out from digestates of conventional whole crop digestion on the basis of higher nitrogen use efficiency and that it is useful for increasing harvestable biomass and the nitrogen content of the biomass, especially of L. perenne, which is a common species of intensively used grasslands. Further, a medium application rate of IFBB digestate (50% of nitrogen removed with harvested biomass, corresponding to 30 50 kg N ha-1 a-1) may be a possibility for conservation management of different meadows without changing the functional above- and belowground characteristic of the grasslands, thereby offering an ecologically worthwhile alternative to mulching. Overall, the soil microbial biomass and catabolic performance under planted soil was marginally affected by digestate application but rather by soil properties and partly by grassland species and legume occurrence. The investigated extensively managed meadows revealed a high soil catabolic evenness, which was resilient to medium IFBB application rate after a three-year period of application.
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In the past decades since Schumpeter’s influential writings economists have pursued research to examine the role of innovation in certain industries on firm as well as on industry level. Researchers describe innovations as the main trigger of industry dynamics, while policy makers argue that research and education are directly linked to economic growth and welfare. Thus, research and education are an important objective of public policy. Firms and public research are regarded as the main actors which are relevant for the creation of new knowledge. This knowledge is finally brought to the market through innovations. What is more, policy makers support innovations. Both actors, i.e. policy makers and researchers, agree that innovation plays a central role but researchers still neglect the role that public policy plays in the field of industrial dynamics. Therefore, the main objective of this work is to learn more about the interdependencies of innovation, policy and public research in industrial dynamics. The overarching research question of this dissertation asks whether it is possible to analyze patterns of industry evolution – from evolution to co-evolution – based on empirical studies of the role of innovation, policy and public research in industrial dynamics. This work starts with a hypothesis-based investigation of traditional approaches of industrial dynamics. Namely, the testing of a basic assumption of the core models of industrial dynamics and the analysis of the evolutionary patterns – though with an industry which is driven by public policy as example. Subsequently it moves to a more explorative approach, investigating co-evolutionary processes. The underlying questions of the research include the following: Do large firms have an advantage because of their size which is attributable to cost spreading? Do firms that plan to grow have more innovations? What role does public policy play for the evolutionary patterns of an industry? Are the same evolutionary patterns observable as those described in the ILC theories? And is it possible to observe regional co-evolutionary processes of science, innovation and industry evolution? Based on two different empirical contexts – namely the laser and the photovoltaic industry – this dissertation tries to answer these questions and combines an evolutionary approach with a co-evolutionary approach. The first chapter starts with an introduction of the topic and the fields this dissertation is based on. The second chapter provides a new test of the Cohen and Klepper (1996) model of cost spreading, which explains the relationship between innovation, firm size and R&D, at the example of the photovoltaic industry in Germany. First, it is analyzed whether the cost spreading mechanism serves as an explanation for size advantages in this industry. This is related to the assumption that the incentives to invest in R&D increase with the ex-ante output. Furthermore, it is investigated whether firms that plan to grow will have more innovative activities. The results indicate that cost spreading serves as an explanation for size advantages in this industry and, furthermore, growth plans lead to higher amount of innovative activities. What is more, the role public policy plays for industry evolution is not finally analyzed in the field of industrial dynamics. In the case of Germany, the introduction of demand inducing policy instruments stimulated market and industry growth. While this policy immediately accelerated market volume, the effect on industry evolution is more ambiguous. Thus, chapter three analyzes this relationship by considering a model of industry evolution, where demand-inducing policies will be discussed as a possible trigger of development. The findings suggest that these instruments can take the same effect as a technical advance to foster the growth of an industry and its shakeout. The fourth chapter explores the regional co-evolution of firm population size, private-sector patenting and public research in the empirical context of German laser research and manufacturing over more than 40 years from the emergence of the industry to the mid-2000s. The qualitative as well as quantitative evidence is suggestive of a co-evolutionary process of mutual interdependence rather than a unidirectional effect of public research on private-sector activities. Chapter five concludes with a summary, the contribution of this work as well as the implications and an outlook of further possible research.
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The Networks and Complexity in Social Systems course commences with an overview of the nascent field of complex networks, dividing it into three related but distinct strands: Statistical description of large scale networks, viewed as static objects; the dynamic evolution of networks, where now the structure of the network is understood in terms of a growth process; and dynamical processes that take place on fixed networks; that is, "networked dynamical systems". (A fourth area of potential research ties all the previous three strands together under the rubric of co-evolution of networks and dynamics, but very little research has been done in this vein and so it is omitted.) The remainder of the course treats each of the three strands in greater detail, introducing technical knowledge as required, summarizing the research papers that have introduced the principal ideas, and pointing out directions for future development. With regard to networked dynamical systems, the course treats in detail the more specific topic of information propagation in networks, in part because this topic is of great relevance to social science, and in part because it has received the most attention in the literature to date.
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The themes of this paper are equality, reasonableness and gender rights in the dynamics of two sequential and convergent processes: the constitutionalization of judicial law, and the internationalization of constitutional law. The thesis of this paper is that in the face of non-compliance of the obligation to regulate, guarantee and protect gender rights, the best option has been to strengthen judicial law, which has enabled the development of rules for protection, the adoption of contemporary methods of interpretation and adjudication of the law, as well as the resolution of shortfalls in protection based on said processes of the constitutionalization and internationalization of local law.
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The present article analyze the urban transformations happened in the sector of Saint Victorino and Saint Ines in the city of Bogota D.C. between 1948 and 2010, making use of the "Genealogical Methodology" during the process of inquiry that allow to contrast the visions that are usually accepted of "progress" and "urban renovation" in the urban market context by the existence of a informal economic and a population in conditions of marginality that configures a good part of the "popular urban culture" of the Bogota in the 20th and 21st century. This vision permit to observe from various perspectives the changes that happened in this sector of the city, the impacts of the history facts occurred en this time period and, in special, the real effects of a rearrangement urban process that began in 1998 and has been prolonged to date, which has left a significant mark about the urban and social physiognomy of the place.
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This paper describes the relationship between the executive and legislative branches during the first government of Alvaro Uribe Vélez. We will focus on reviewing the legislative output of each branch of power, along with the effectiveness and efficiency they showed as promoters of this production. We will review the impact they had on the legislative agenda setting and on the control of the legislative process itself, making a diachronic analysis in which each legislature is used as a unit. Thus, we will try to identify the presence (or not) of some kind of pattern interactions, and we will evaluate, at one hand, the existence of hierarchical and transactional trends, and, on the other, the different types of balances produced between them.
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Despite the many models developed for phosphorus concentration prediction at differing spatial and temporal scales, there has been little effort to quantify uncertainty in their predictions. Model prediction uncertainty quantification is desirable, for informed decision-making in river-systems management. An uncertainty analysis of the process-based model, integrated catchment model of phosphorus (INCA-P), within the generalised likelihood uncertainty estimation (GLUE) framework is presented. The framework is applied to the Lugg catchment (1,077 km2), a River Wye tributary, on the England–Wales border. Daily discharge and monthly phosphorus (total reactive and total), for a limited number of reaches, are used to initially assess uncertainty and sensitivity of 44 model parameters, identified as being most important for discharge and phosphorus predictions. This study demonstrates that parameter homogeneity assumptions (spatial heterogeneity is treated as land use type fractional areas) can achieve higher model fits, than a previous expertly calibrated parameter set. The model is capable of reproducing the hydrology, but a threshold Nash-Sutcliffe co-efficient of determination (E or R 2) of 0.3 is not achieved when simulating observed total phosphorus (TP) data in the upland reaches or total reactive phosphorus (TRP) in any reach. Despite this, the model reproduces the general dynamics of TP and TRP, in point source dominated lower reaches. This paper discusses why this application of INCA-P fails to find any parameter sets, which simultaneously describe all observed data acceptably. The discussion focuses on uncertainty of readily available input data, and whether such process-based models should be used when there isn’t sufficient data to support the many parameters.
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Whereas the predominance of El Niño Southern Oscillation (ENSO) mode in the tropical Pacific sea surface temperature (SST) variability is well established, no such consensus seems to have been reached by climate scientists regarding the Indian Ocean. While a number of researchers think that the Indian Ocean SST variability is dominated by an active dipolar-type mode of variability, similar to ENSO, others suggest that the variability is mostly passive and behaves like an autocorrelated noise. For example, it is suggested recently that the Indian Ocean SST variability is consistent with the null hypothesis of a homogeneous diffusion process. However, the existence of the basin-wide warming trend represents a deviation from a homogeneous diffusion process, which needs to be considered. An efficient way of detrending, based on differencing, is introduced and applied to the Hadley Centre ice and SST. The filtered SST anomalies over the basin (23.5N-29.5S, 30.5E-119.5E) are then analysed and found to be inconsistent with the null hypothesis on intraseasonal and interannual timescales. The same differencing method is then applied to the smaller tropical Indian Ocean domain. This smaller domain is also inconsistent with the null hypothesis on intraseasonal and interannual timescales. In particular, it is found that the leading mode of variability yields the Indian Ocean dipole, and departs significantly from the null hypothesis only in the autumn season.