Ann Laura Stoler

This essay will cover Foucault’s panopticon in relation to Jeremy Bentham’s centralized prison system as an “all seeing eye” over the human prisoner and that of postmodern surveillance as well (McHoul and Grace 1995). Moreover, I will examine the connection between biopower and discipline through the panopticon context in which society has evidently expanded this Benthamite prison system into the territorial boundaries of security and crime control over the human body. While this panopticon prison design has also entered the realm of not just security cultures but transnational capitalism too; while forming a type of “consumer control” over the human mind and acknowledged human body as argued by (Haggerty et al. 2011, p.232).

Furthermore, I will also instrument pop-culture references in relation to biopower and discipline, especially, in the form of science fiction like the movie Blade Runner (1982). In which Harrison Ford’s character Deckard, an assigned Blade Runner e.g., death squad member is sent out by a “capitalist panopticon” power structure. To then enforce the death plenty in violent law enforcement over the replicants and their four-year lifespan; throughout both a biopower and even a panopticon Hobbesian stage of hyper-security measures combined. For example, the replicants in the movie represents the citizen through labour control while they are also subjected to persistent control by the states “all seeing eye” (e.g.,) the panopticon (Sorensen, 2015, p.115.). And so, I will correspondingly link this pop-culture orientation to the technology of power over the human body in managing humans through the disciplining through the subject’s body by altering his/her behaviour into matching that’s state’s regulatory and violent laws. As, the subject under the context of security control will then act according with a large range of disciplines throughout their short lifespan. In which this is also a part of surveillance over both public and private individuals as well (Galič et al. 2016, p.2).

Investigating the terms camp, campus, and colony, this essay offers a reframing of encampment and its conceptual offshoots. To shed light
on recent encampment protests, it explores the interconnected genealogies of these three concepts, focusing on the Palestinian refugee camp and
its colonial counter-insurgent role. Encampment emerges here as a crucial political process of spatial division and allocation, whose unstable and often
insurrectionary dynamism is obscured when it is regarded as a finished product—as a camp or a college campus. By examining the intersecting histories of camp and campus alongside the Gaza case, the essay challenges existing scholarly paradigms of the camp, highlighting instead three understudied camp functions—colonial militarism, depoliticized moralism, and the diverting containment of political energies. Indeed, this study suggests that university leaders used the hyperbolic and hyper-visible violence they inflicted on college campuses to divert attention away from Palestine.

Software effort estimation is an important step in software development. It predicts the amount of effort and development time required to build a software system. It is one of the most important tasks and an accurate estimate is vital to the successful completion of the project. Building software effort estimation requires developing sound computational models. This paper investigates the use of fuzzy-neural systems in estimating software effort. A comparison is made with a radial basis neural network. Results obtained based on the China dataset indicates that a hybrid model that combine fuzzy inferencing with neural networks ability to learn from examples provided more accurate results than using neural networks alone.

I am very grateful for the opportunity, provided by a panel on "American History after Post-Structuralism," to respond to such interesting papers by three historians of a new generation, an interdisciplinary exchange made possible because the AHA and MLA no longer hold their meetings at the same time. I am also happy to be hosted in print by American Studies, but I have chosen to maintain the focus of my remarks on disciplinary issues between literature and history-as complicated, rather than mediated, by "theory"-and not to address myself only to issues specific to Americanists. Apparently, to judge from the three papers, poststructuralism has not yet made much difference to the writing of American History. That is, the papers, amidst quite copious citations, refer to only a few articles and no books that might be examples, whether for better or worse, of the change produced in American historiography by the impact of poststructuralism. There are, it seems, no landmarks yet. This leads me to a question: have there been any other intellectual developments or movements in American historiography, the impact of which has been, in this way, discussed in advance of its occurrence? Even psychohistory, which provoked a lot of fuss and small results, had from the beginning the remarkable interdisciplinary foray of Erik Erikson's Young Man Luther. This apparent absence leads to a further question: Is it possible that the pattern of citation in these papers indicates a change in what will count as the "field" of American history? Such a question ("how do you define the field or discipline. .. ?") is the kind scholars in other fields, such as literary and philosophical studies, have been led to by the work associated with Jacques

In the present paper, applicability and capability of A.I techniques for effort estimation prediction has been investigated. It is seen that neuro fuzzy models are very robust, characterized by fast computation, capable of handling the distorted data. Due to the presence of data non-linearity, it is an efficient quantitative tool to predict effort estimation. The one hidden layer network has been developed named as OHLANFIS using MATLAB simulation environment. Here the initial parameters of the OHLANFIS are identified using the subtractive clustering method. Parameters of the Gaussian membership function are optimally determined using the hybrid learning algorithm. From the analysis it is seen that the Effort Estimation prediction model developed using OHLANFIS technique has been able to perform well over normal ANFIS Model.

The work is about using Simulated Annealing Algorithm for the effort estimation model parameter optimization which can lead to the reduction in the difference in actual and estimated effort used in model development. The model has been tested using OOP's dataset, obtained from NASA for research purpose.The data set based model equation parameters have been found that consists of two independent variables, viz. Lines of Code (LOC) along with one more attribute as a dependent variable related to software development effort (DE). The results have been compared with the earlier work done by the author on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) and it has been observed that the developed SA based model is more capable to provide better estimation of software development effort than ANN and ANFIS.

1 M.E CSE, 2Assitant Professor, UIET, Panjab University , Chandigarh, INDIA __________________________________________________________________________________ ABSTRACT: Software estimation is a process of estimating the effort, size and cost of the software, before the actual development of the software. Realistic estimation helps the software developers and managers in finding the required resources, man-hours, time and cost required in developing software. There are various types of estimation methods such as algorithmic, regression, machine learning, function pts etc, but still there is need of an accurate and precise software estimation method. Some models don’t include all the parameters, some are extremely vulnerable to misclassification or error deviation is high. In this paper neural network training functions are used for software estimation as neural network is good at discovering relations (linear or non linear). Results of neural network are compared with cocomo 2 effort...

Software Effort Estimation is highly important and considered to be a primary activity in software project management. The accurate estimates are conducted in the development of business case in the earlier stages of project management. This accurate prediction helps the investors and customers to identify the total investment and schedule of the project. The project developers define process to estimate the effort more accurately with the available mythologies using the attributes of the project. The algorithmic estimation models are very simple and reliable but not so accurate. The categorical datasets cannot be estimated using the existing techniques. Also the attributes of effort estimation are measured in linguistic values which may leads to confusion. This paper looks in to the accuracy and reliability of a non-algorithmic approach based on adaptive neuro fuzzy logic in the problem of effort estimation. The performance of the proposed method demonstrates that there is a accura...

Software development effort estimation is one of the major activities in software project management. During the project proposal stage there is high probability of estimates being made inaccurate but later on this inaccuracy decreases. In the field of software development there are certain matrices, based on which the effort estimation is being made. Till date various methods has been proposed for software effort estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more suitable in such situations. The present paper is concerned with developing software effort estimation model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS provided better results than ANN and COCOMO model.

Software cost estimation SCE is directly related to quality of software. The paper presents a hybrid approach that is an amalgamation of algorithmic (parametric models) and non-algorithmic (expert estimation) models. Algorithmic model uses COCOMO II while non algorithmic utilizes Neuro-Fuzzy technique that can be further used to estimate accuracy in irregular functions. For generalization of the model, Neuro-fuzzy membership functions have been used and simulated using mathematical tool MATLAB. Also, the proposed model has been validated with traditional COCOMO model (COCOMO 81) by using NASA software project data. The experimental results suggest that the proposed model gives better SCE as compared to its traditional counterpart.

The effort estimation needs to be done at early stages for successful delivery of software. Numerous models have been developed to estimate software effort during the last decades, but effort estimation of a software project is still a challenging task and in the case of web based projects, it is even harder. The selection of programming language and use of different type of objects i.e. hyperlinks, graphics, and scripts etc. make the web effort estimation process really complex. An estimation model "WebMo", proposed to estimate the effort of web based projects inspired by COCOMO. This research presents a non-algorithmic model named "Neuro-Web" based on Artificial Neural Networks (ANN). The proposed model will use the WebMo parameters as input. These parameters include web application size, productivity coefficients, and 9 different cost drivers. This proposed model is calibrated using the dataset of 164 real-life web applications developed by different freelancers and software houses. The "Neuro-Web" model is compared with the existing model "WebMo" and results reveal that Neuro-Web performs better than "WebMo". The MMRE of the proposed method is just 9.92% as compared to 26.27% for WebMo.

Edward Said is regarded as the originator of colonial discourse theory. He deploys Michel Foucault’s notion of discourse to accomplish his project in Orientalism and emphasizes Foucault’s notion of discourse and its relation to power, rendering discourse a carceral system. Although Said explicitly expresses the similarity between Orientalism and Foucault’s discourse theory, it seems he implicitly suggests that the carceral quality of Foucault’s idea affects his formulation of Orientalism. This study examines the validity of Said’s understanding of Foucault and shows that Said’s construction of Orientalism is based on an imperfect image of Foucault. Argument here is to postulate that Foucault’s discourse theory provides space for resistance and his theorization of power helps the idea of struggle in discursive practices. Besides, Foucault himself is trapped in a discourse produced by Said. This study casts light on Foucault’s theory of discourse and modifies this misreading.

Software cost estimation SCE is directly related to quality of software. The paper presents a hybrid approach that is an amalgamation of algorithmic (parametric models) and non-algorithmic (expert estimation) models. Algorithmic model uses COCOMO II while non algorithmic utilizes Neuro-Fuzzy technique that can be further used to estimate accuracy in irregular functions. For generalization of the model, Neuro-fuzzy membership functions have been used and simulated using mathematical tool MATLAB. Also, the proposed model has been validated with traditional COCOMO model (COCOMO 81) by using NASA software project data. The experimental results suggest that the proposed model gives better SCE as compared to its traditional counterpart.

Edward Said is regarded as the originator of colonial discourse theory. He deploys Michel Foucault’s notion of discourse to accomplish his project in Orientalism and emphasizes Foucault’s notion of discourse and its relation to power, rendering discourse a carceral system. Although Said explicitly expresses the similarity between Orientalism and Foucault’s discourse theory, it seems he implicitly suggests that the carceral quality of Foucault’s idea affects his formulation of Orientalism. This study examines the validity of Said’s understanding of Foucault and shows that Said’s construction of Orientalism is based on an imperfect image of Foucault. Argument here is to postulate that Foucault’s discourse theory provides space for resistance and his theorization of power helps the idea of struggle in discursive practices. Besides, Foucault himself is trapped in a discourse produced by Said. This study casts light on Foucault’s theory of discourse and modifies this misreading.

In this, artificial neural network controller is designed for LLC resonant converter for voltage regulation. The performance of the proposed converter with proportional-integral (PI) controller and ANN controller are analysed from the simulation results. A voltage mode control is provided to get regulated load voltage irrespective of the changes in supply. ANN controller is used for the voltage mode control and the efficiency of the proposed ANN controller is estimated and comparison is made with conventional PI controller. The simulation work is done with MATLAB/Simulink software.

A number of theories and terms have been developed through history thanks to the outstanding efforts of different scholars and philosophers. Michel Foucault is one of the most important philosophers of the 20 th century whose thoughts are still essential up to now. He was born on

Artificial intelligence techniques are day by day getting involvement in all the classification and prediction based process like environmental monitoring, stock exchange conditions, biomedical diagnosis, software engineering etc. However still there are yet to be simplify the challenges of selecting training criteria for design of artificial intelligence models used for prediction of results. This work focus on the defect prediction mechanism development using software metric data of KC1.We have taken subtractive clustering approach for generation of fuzzy inference system (FIS).The FIS rules are generated at different radius of influence of input attribute vectors and the developed rules are further modified by ANFIS technique to obtain the prediction of number of defects in software project using fuzzy logic system.

IN A CROOKED LINE, GEOFF ELEY OFFERS a survey of the fundamental transformation that overtook the practice of social history between the 1970s and 1980s with the rise of cultural history in response to challenges to prevailing forms of social history posed by the linguistic turn. Triangulating, as he says, "the political, the historical and the personal," the story he tells is embedded in the context of his own formation as a historian, a formation with a distinctively British (and Marxist) voice, and one surprisingly free of French accents, Michel Foucault excepted. 1 It is a story, as well, of a particular professional generation that came to maturity in the aftermath of the 1960s and was deeply committed to historical change in the present, a problem that its members approached both in their lives and in their work, and through the interpenetrating influences that this conjuncture implied. One of Eley's goals in A Crooked Line is to map "a series of personal encounters between the tasks of historical writing and the surrounding political climate" (6) in order to underline the inevitable imbrication of history and politics in any historian's thought and writing-in short, to advocate a historiographical practice "powered by the politics of commitment and the ethics of conviction" (7). It is worth noting that the chapter headings by which Eley denotes his participation in the changing styles and aims of historiography over the last four decades point to the psychic and emotional investments that accompany the historian's labor: "Optimism," "Disappointment," "Reflectiveness," and "Defiance." 2 I would like to thank my colleague David Nirenberg for his comments on this article, from which, as always, I have benefited greatly.

Edward Said is regarded as the originator of colonial discourse theory. He deploys Michel Foucault’s notion of discourse to accomplish his project in Orientalism and emphasizes Foucault’s notion of discourse and its relation to power, rendering discourse a carceral system. Although Said explicitly expresses the similarity between Orientalism and Foucault’s discourse theory, it seems he implicitly suggests that the carceral quality of Foucault’s idea affects his formulation of Orientalism. This study examines the validity of Said’s understanding of Foucault and shows that Said’s construction of Orientalism is based on an imperfect image of Foucault. Argument here is to postulate that Foucault’s discourse theory provides space for resistance and his theorization of power helps the idea of struggle in discursive practices. Besides, Foucault himself is trapped in a discourse produced by Said. This study casts light on Foucault’s theory of discourse and modifies this misreading.

Edward Said is regarded as the originator of colonial discourse theory. He deploys Michel Foucault’s notion of discourse to accomplish his project in Orientalism and emphasizes Foucault’s notion of discourse and its relation to power, rendering discourse a carceral system. Although Said explicitly expresses the similarity between Orientalism and Foucault’s discourse theory, it seems he implicitly suggests that the carceral quality of Foucault’s idea affects his formulation of Orientalism. This study examines the validity of Said’s understanding of Foucault and shows that Said’s construction of Orientalism is based on an imperfect image of Foucault. Argument here is to postulate that Foucault’s discourse theory provides space for resistance and his theorization of power helps the idea of struggle in discursive practices. Besides, Foucault himself is trapped in a discourse produced by Said. This study casts light on Foucault’s theory of discourse and modifies this misreading.

Finding accurately the amount of effort needed to develop any software is quite essential in software project management because inaccurate estimates affect both the software resources and the deliverables. A number of models have been developed for the estimation of the amount of effort required to develop a software. One of such models is the Constructive Cost Model (COCOMO), which was found to contain uncertain and imprecise inputs. To improve the COCOMO, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was built by training the data acquired from PROMISE repository-NASA COCOMO with ANFIS back propagation and hybrid algorithm using MATLAB R 2017. This was done after Principal Component Analysis (PCA) was employed to reduce the dimensionality of the datasets from 23 to 6. With 6 attributes, the datasets were trained on the back propagation learning rule and the hybrid learning rule. It was revealed that the hybrid learns faster from epoch 70 and above. The performance of the outputs of the ANFIS algorithms was evaluated using Mean Magnitude Relative Error (MMRE) and Root Mean Square Error (RMSE). The results show that the Hybrid model has the least MMRE and RMSE of 31.4829 and 0.00000187 respectively, which is a confirmation that ANFIS hybrid learning performs better than ANFIS Back Propagation methods in terms of training convergence, reduced error and performance.

Finding accurately the amount of effort needed to develop any software is quite essential in software project management because inaccurate estimates affect both the software resources and the deliverables. A number of models have been developed for the estimation of the amount of effort required to develop a software. One of such models is the Constructive Cost Model (COCOMO), which was found to contain uncertain and imprecise inputs. To improve the COCOMO, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was built by training the data acquired from PROMISE repository-NASA COCOMO with ANFIS back propagation and hybrid algorithm using MATLAB R 2017. This was done after Principal Component Analysis (PCA) was employed to reduce the dimensionality of the datasets from 23 to 6. With 6 attributes, the datasets were trained on the back propagation learning rule and the hybrid learning rule. It was revealed that the hybrid learns faster from epoch 70 and above. The performance of the outputs of the ANFIS algorithms was evaluated using Mean Magnitude Relative Error (MMRE) and Root Mean Square Error (RMSE). The results show that the Hybrid model has the least MMRE and RMSE of 31.4829 and 0.00000187 respectively, which is a confirmation that ANFIS hybrid learning performs better than ANFIS Back Propagation methods in terms of training convergence, reduced error and performance.

Finding accurately the amount of effort needed to develop any software is quite essential in software project management because inaccurate estimates affect both the software resources and the deliverables. A number of models have been developed for the estimation of the amount of effort required to develop a software. One of such models is the Constructive Cost Model (COCOMO), which was found to contain uncertain and imprecise inputs. To improve the COCOMO, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was built by training the data acquired from PROMISE repository-NASA COCOMO with ANFIS back propagation and hybrid algorithm using MATLAB R 2017. This was done after Principal Component Analysis (PCA) was employed to reduce the dimensionality of the datasets from 23 to 6. With 6 attributes, the datasets were trained on the back propagation learning rule and the hybrid learning rule. It was revealed that the hybrid learns faster from epoch 70 and above. The performance of the outputs of the ANFIS algorithms was evaluated using Mean Magnitude Relative Error (MMRE) and Root Mean Square Error (RMSE). The results show that the Hybrid model has the least MMRE and RMSE of 31.4829 and 0.00000187 respectively, which is a confirmation that ANFIS hybrid learning performs better than ANFIS Back Propagation methods in terms of training convergence, reduced error and performance.

Finding accurately the amount of effort needed to develop any software is quite essential in software project management because inaccurate estimates affect both the software resources and the deliverables. A number of models have been developed for the estimation of the amount of effort required to develop a software. One of such models is the Constructive Cost Model (COCOMO), which was found to contain uncertain and imprecise inputs. To improve the COCOMO, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was built by training the data acquired from PROMISE repository-NASA COCOMO with ANFIS back propagation and hybrid algorithm using MATLAB R 2017. This was done after Principal Component Analysis (PCA) was employed to reduce the dimensionality of the datasets from 23 to 6. With 6 attributes, the datasets were trained on the back propagation learning rule and the hybrid learning rule. It was revealed that the hybrid learns faster from epoch 70 and above. The performance of the outputs of the ANFIS algorithms was evaluated using Mean Magnitude Relative Error (MMRE) and Root Mean Square Error (RMSE). The results show that the Hybrid model has the least MMRE and RMSE of 31.4829 and 0.00000187 respectively, which is a confirmation that ANFIS hybrid learning performs better than ANFIS Back Propagation methods in terms of training convergence, reduced error and performance.

Finding accurately the amount of effort needed to develop any software is quite essential in software project management because inaccurate estimates affect both the software resources and the deliverables. A number of models have been developed for the estimation of the amount of effort required to develop a software. One of such models is the Constructive Cost Model (COCOMO), which was found to contain uncertain and imprecise inputs. To improve the COCOMO, an Adaptive Neuro-Fuzzy Inference System (ANFIS) was built by training the data acquired from PROMISE repository-NASA COCOMO with ANFIS back propagation and hybrid algorithm using MATLAB R 2017. This was done after Principal Component Analysis (PCA) was employed to reduce the dimensionality of the datasets from 23 to 6. With 6 attributes, the datasets were trained on the back propagation learning rule and the hybrid learning rule. It was revealed that the hybrid learns faster from epoch 70 and above. The performance of the outputs of the ANFIS algorithms was evaluated using Mean Magnitude Relative Error (MMRE) and Root Mean Square Error (RMSE). The results show that the Hybrid model has the least MMRE and RMSE of 31.4829 and 0.00000187 respectively, which is a confirmation that ANFIS hybrid learning performs better than ANFIS Back Propagation methods in terms of training convergence, reduced error and performance.

Egg production is geared towards large scale production of eggs for profit maximization and consumption. But poultry farmers are faced with challenges that affect the quantity and quality of egg production during the production life cycle such as quality of feed intake, management issues, genetic factors of the breed birds, age at egg laying period, presence of diseases, molting flock, housing and others. Several mechanical solutions have been suggested to implement the production cycle but with very high cost implication which calls for the need of soft computing methods to model the egg production process. However, modelling egg production curve is a complex task because a typical egg production curve (from week 20 to week 72) is characterized by nonlinear probabilities and imprecise knowledge in the egg production process. This paper proposes an optimal fuzzy predictive model for poultry egg production. The motivation stems from analyzing the non-linearity and imprecision in egg production which is best handled by fuzzy logic as compared to other soft computing techniques. Data samples were collected on the age of chicks, quantity of feeds, quality of feeds, body weight of chicks and total egg production as input into the proposed system. The first stage of implementation is carried out in the Statistical Package for Social Science (SPSS) software environment to perform correlation analysis while the last two stages are carried out using Fuzzy Toolbox in MATLAB based on its capability to model and simulate complex systems with robust and interpretable predictions. Gaussian membership function was used in the fuzzification process while Mamdami structure was adopted as the fuzzy inference system (FIS). Model performance evaluation showed that the proposed system performed excellently by achieving best prediction accuracy 100% Pred(30) with an approximate mean magnitude relative error (MMRE) of 0.11744 as compared to the results in the reported literature. The method has proven to be a cost-effective and simple approach to modelling through the use of samples and parameters from poultry house. ranking 19th in world hen egg production and the top producer in Africa (USDA 2013). Egg production, often seen as a commercial business, involves fulltime labour and is geared toward producing sufficient scale of eggs. Egg production can be mechanized or traditional. The latter is mostly referred to as backyard poultry or farm flock production. The process of egg production whether through mechanized or traditional means have same generic life cycle of production. Day-old chicks (DOCs) are obtained from local hatcheries licensed by international hybrid breeding companies (Ajayi, 2010). The small chicks are either brooded naturally or artificially, if brooded artificially, DOCs must be housed separately from laying chickens so as to protect the chicks from predators, diseases and catching colds. This brooding stage lasts for about eight weeks. Brooding is the process whereby the mother hen protects and warms the chicks after they have been hatched. This is an essential part for their maturity (Ajayi, 2010). During the first four weeks of life, small chicks are kept in brooding box. After the first month, they are removed

This project involves research about software effort estimation using machine learning algorithms. Software cost and effort estimation are crucial parts of software project development. It determines the budget, time and resources needed to develop a software project. One of the well-established software project estimation models is Constructive Cost Model (COCOMO) which was developed in the 1980s. Even though such a model is being used, COCOMO has some weaknesses and software developers still facing the problem of lack of accuracy of the effort and cost estimation. Inaccuracy in the estimated effort will affect the schedule and cost of the whole project as well. The objective of this research is to use several algorithms of machine learning to estimate the effort of software project development. The best machine learning model is chosen to compare with the COCOMO.

Obiettivo della tesi è indagare il concetto di stato di eccezione, in particolare nella sua declinazione internazionale e in quello che la Scuola di Copenaghen chiama “processo di securitizzazione”. Si è indagata la relazione tra anarchia internazionale ed eccezione e l’idea che l’eccezione vada intesa come “processo correttivo” e non come un “evento”, utilizzando alcune categorie di pensiero ebraico/kabbalistiche ed il “Costruttivismo evolutivo” di Emanuel Adler. Ci si è anche soffermati su come il neoliberismo “tecnologico” potrebbe controllare questo processo. La tesi è divisa in tre capitoli. Nel primo capitolo si cerca di delineare un’attinenza internazionale al concetto di stato di eccezione e si sono approfonditi autori chiave del pensiero sull’eccezione, come Carl Schmitt, Walter Benjamin e Giorgio Agamben. Nel secondo capitolo si è introdotto il concetto affine di “emergenza”, per poi introdurre la Scuola di Copenaghen ed il suo concetto di securitizzazione, concludendo con un’indagine sulle origini schmittiane della stessa Scuola. Infine nel terzo capitolo si è introdotta la tematica dell’anarchia internazionale, spostando poi l’attenzione su un discorso di “anarchia umana”, utile ad introdurre una discussione “ebraico-kabbalistica” dell’eccezione incentrata sulla categoria del “tikkun” (correzione) e del Costruttivismo di Adler, concludendo con un’analisi sul neoliberismo tecnologico.

The present study deals with the optimization of the COCOMO Model parameters using Simulated Annealing algorithm so as to minimize the variance in software development effort. For this data is taken from the NASA projects. The data set that has been used consists of two independent variables, viz. Lines of Code (LOC) and Effort Adjustment Factor (EAF) and dependent variable as Development Effort (DE). The results so obtained have been compared with the earlier work done by the author on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS), along with COCOMO results. The developed SA based model was able to provide better estimation capabilities than COCOMO, ANN and ANFIS.

Software cost prediction is the technique of accurately evaluating the amount while developing the software. Estimation involves the total time required for the completion of the software, effort required that is measured in terms of person per month (PM), and the total cost to complete the activity. Accuracy and duration are the two desirable criteria in the software estimation process. In software estimation process, there are several inputs that are being fed to the system and these inputs are used for the generation or calculation of the set of outputs. The important work of the software project managers in the present scenario is the computation of cost or effort before the absolute advancement of any particular software. There are several methods applied for software cost estimation but we will focus on the fuzzy logic which is a soft-computing method. We feel that model which is based on fuzzy logic for the software cost estimation should be able to give the uncertain values ...

Software cost prediction is the technique of accurately evaluating the amount while developing the software. Estimation involves the total time required for the completion of the software, effort required that is measured in terms of person per month (PM), and the total cost to complete the activity. Accuracy and duration are the two desirable criteria in the software estimation process. In software estimation process, there are several inputs that are being fed to the system and these inputs are used for the generation or calculation of the set of outputs. The important work of the software project managers in the present scenario is the computation of cost or effort before the absolute advancement of any particular software. There are several methods applied for software cost estimation but we will focus on the fuzzy logic which is a soft-computing method. We feel that model which is based on fuzzy logic for the software cost estimation should be able to give the uncertain values ...

The present study deals with the optimization of the COCOMO Model parameters using Simulated Annealing algorithm so as to minimize the variance in software development effort. For this data is taken from the NASA projects. The data set that has been used consists of two independent variables, viz. Lines of Code (LOC) and Effort Adjustment Factor (EAF) and dependent variable as Development Effort (DE). The results so obtained have been compared with the earlier work done by the author on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS), along with COCOMO results. The developed SA based model was able to provide better estimation capabilities than COCOMO, ANN and ANFIS.

Le goût de l'archive qu'entretient Ann Laura Stoler est aussi sûr que celui de sa préfacière en français, Arlette Farge, et tout aussi compréhensif. Si Au coeur de l'archive coloniale pose un certain nombre de questions de méthode, comme l'indique le sous-titre de cet ouvrage paru dix ans avant sa traduction française, c'est que son autrice entrevoit « un nouveau tournant méthodologique envisageant le traitement des archives comme un exercice ethnographique plutôt que comme un simple exercice extractif. » (p. 81) Stoler regarde en effet les archives produites aux Indes néerlandaises pendant un siècle (de 1830 à 1930) non comme un matériau brut où puiser les preuves de l'exploitation coloniale, mais comme une trame, analogue en cela aux documents qu'elle étudie, une trame dont le « filigrane constitue la trace d'une histoire qui ne peut être ni raturée, ni supprimée sans que cela ne détruise le papier » (p. 30), ou comparable à une peau qu'elle n'entend pas soulever pour y découvrir la Chair de l'empire, comme dans son premier ouvrage traduit en français en 2013, mais simplement ausculter afin d'en prendre le « pouls » (p. 66). Le goût de Stoler pour les métaphores pourrait bien exercer sur ses lecteurs certaine séduction interprétative, comme lorsque le titre de son chapitre 3 les invite à connaître « les habitudes d'un coeur colonial », au risque qu'à trop incarner l'archive on néglige le système dans lequel elle prend place. C'est pourtant afin d'en pénétrer la complexité que l'historienne se penche sur sa complexion, si l'on peut dire, et qu'elle peut y mesurer « l'écart entre les règles et les pratiques, entre les mandats de l'État et les stratégies par lesquelles les gens y répondaient, entre les règles normatives et la manière dont ceux-ci vivaient réellement leur vie. » (p. 63) Là se manifestent à ses yeux « des mouvements inquiets dans un champ de forces » ; là surgissent « des espaces dans lesquels les sentiments et l'affectif traversent l'apparente abstraction des rationalités politiques. » (Ibid.) Ces dernières demeurent trop souvent surestimées, juge Stoler, pour qui « le panoptique » est l'exemple-type d'« un concept fragile » lorsqu'on le confronte à des « vues d'ensemble de l'administration [qui] sont moins l'indice d'un savoir exhaustif que de formes stéréotypées de maîtrise supposée. » (p. 51) Plus largement, les études coloniales pâtissent, selon elle, « d'un surinvestissement du vocabulaire de Foucault » (p. 76), au point que des notions telles que celles d'épistémè et de régime de vérité finissent par occulter les processus conflictuels, concurrentiels ou simplement coïncidents au travers desquels savoir et pouvoir s'élaborent mutuellement, sans nécessairement que l'on puisse tracer entre eux un signe d'égalité, ni accepter sans nuance « l'idée que les États coloniaux ont toujours cherché à accroître l'un et l'autre. » (p. 85) Stoler propose en ce sens d'emprunter une voie qu'elle considère plus stimulante, parallèle à celle de « l'approche critique des archives coloniales », caractérisée par « l'idée permanente d'une lecture "à contre-courantˮ [against the grain], une "histoire à reboursˮ de l'histoire impériale » (p. 80). Une voie consistant au contraire à « lire l'archive dans le droit fil [along the grain] », et permettant de ce fait de tirer « notre sensibilité moins vers la texture homogène de l'archive que vers son relief, vers la surface rugueuse qui nuance sa couleur et modèle sa

Accurate Software effort estimation is an ongoing challenge for the modern software engineers in computer science engineering since last 30 years due to the dynamic behavior of the software [1] [2][14]. This is only because of the time and cost estimation during the early stage of the software development is quite difficult and erroneous. So many algorithmic and non algorithmic techniques are used such as SLIM (Software life cycle management), Halstead Model, Bailey-Basil Model, COCOMO model and Function point analysis, etc, but does not estimate all kinds of software accurately. Nowadays these traditional techniques are not acceptable. This research work proposes a new fuzzy model to achieve higher accuracy by multiplying a fuzzy factor with the effort equation predicted empirically. As comparison to both model based and equation based, Model based estimation focused on specific models where as equation based techniques are based on traditional equations. Fuzzy logic is more suitable and flexible to meet the realistic challenges of today's software estimation process.

Software cost estimation has always been a serious challenge lying ahead of software teams that should be seriously considered in the early stages of a project. Lack of sufficient information on final requirements, as well as the existence of inaccurate and vague requirements, are among the main reasons for unreliable estimations in this area. Though several effort estimation models have been proposed over the recent decade, an increase in their accuracy has always been a controversial issue, and researchers' efforts in this area are still ongoing. This study presents a new model based on a hybrid of adaptive network-based fuzzy inference system (ANFIS) and differential evolution (DE) algorithm. This model tries to obtain a more accurate estimation of software development effort that is capable of presenting a better estimate within a wide range of software projects compared to previous works. The proposed method outperformed other optimization algorithms adopted from the geneti...

In this article, two different architectures of Artificial Neural Networks (ANN) are proposed as an efficient tool for predicting and estimating software effort. Artificial Neural Networks, as a branch of machine learning, are used in estimation because they tend towards fast learning and giving better and more accurate results. The search/optimization embraced here is motivated by the Taguchi method based on Orthogonal Arrays (an extraordinary set of Latin Squares), which demonstrated to be an effective apparatus in a robust design. This article aims to minimize the magnitude relative error (MRE) in effort estimation by using Taguchi's Orthogonal Arrays, as well as to find the simplest possible architecture of an artificial Neural Network for optimized learning. A descending gradient (GA) criterion has also been introduced to know when to stop performing iterations. Given the importance of estimating software projects, our work aims to cover as many different values of actual efficiency of a wide range of projects as possible by division into clusters and a certain coding method, in addition to the mentioned tools. In this way, the risk of error estimation can be reduced, to increase the rate of completed software projects. INDEX TERMS Software effort estimation, Taguchi method, artificial neural networks design, orthogonal array-based experiments, clustering, COCOMO81, COCOMO2000, NASA project dataset, Kemerer dataset.

The work is about using Simulated Annealing Algorithm for the effort estimation model parameter optimization which can lead to the reduction in the difference in actual and estimated effort used in model development. The model has been tested using OOP's dataset, obtained from NASA for research purpose.The data set based model equation parameters have been found that consists of two independent variables, viz. Lines of Code (LOC) along with one more attribute as a dependent variable related to software development effort (DE). The results have been compared with the earlier work done by the author on Artificial Neural Network (ANN) and Adaptive Neuro Fuzzy Inference System (ANFIS) and it has been observed that the developed SA based model is more capable to provide better estimation of software development effort than ANN and ANFIS.

Software development effort estimation is one of the major activities in software project management. During the project proposal stage there is high probability of estimates being made inaccurate but later on this inaccuracy decreases. In the field of software development there are certain matrices, based on which the effort estimation is being made. Till date various methods has been proposed for software effort estimation, of which the non algorithmic methods, like artificial intelligence techniques have been very successful. A Hybrid Fuzzy-ANN model, known as Adaptive Neuro Fuzzy Inference System (ANFIS) is more suitable in such situations. The present paper is concerned with developing software effort estimation model based on ANFIS. The present study evaluates the efficiency of the proposed ANFIS model, for which COCOMO81 datasets has been used. The result so obtained has been compared with Artificial Neural Network (ANN) and Intermediate COCOCMO model developed by Boehm. The results were analyzed using Magnitude of Relative Error (MRE) and Root Mean Square Error (RMSE). It is observed that the ANFIS provided better results than ANN and COCOMO model.

Software cost estimation has always been a serious challenge lying ahead of software teams that should be considered in the early phases of a software project. Lack of sufficient information on final requirements, as well as the existence of inaccurate and vague requirements, are among the main reasons for unreliable estimations in this area. Though several effort and cost estimation techniques and models have been proposed over the recent years, an increase in their accuracy has always been a controversial issue, and researchers' efforts in this area are still ongoing. This study presents a new model based on a hybrid of adaptive network-based fuzzy inference system (ANFIS) and differential evolution (DE) algorithm. This model tries to obtain a more accurate estimation of software development effort that is capable of presenting a better estimate within software projects compared to previous works. The proposed method outperformed other optimization algorithms adopted from the genetic algorithm, evolutionary algorithms, meta-heuristic algorithms, and neuro-fuzzy based optimization algorithms, and could improve the accuracy using MMRE and PRED (0.25) criteria up to 7%.

Welding is widely used by manufacturing engineers and production personnel to quickly and effectively set up manufacturing processes for new products. The MIG welding parameters are the most important factors affecting the quality, productivity and cost of welding. This paper presents the influence of welding parameters like welding current, welding voltage, Gas flow rate, wire feed rate, etc. on weld strength, ultimate tensile strength, and hardness of weld joint, weld pool geometry of various metal material during welding. By using DOE method, the parameters can be optimize and having the best parameters combination for target quality. The analysis from DOE method can give the significance of the parameters as it give effect to change of the quality and strength of product.

Asian Genders This course will explore ways that genders are mobilized and produced in parts of Asia. The course seeks to understand gender in its diversity and in attempts to "fix" or locate it in various bodies and places. We will attempt also to see how gender is made knowable in terms of sexuality, medicine, nation, class, ethnicity, religion, and other discourses. Possible themes include: gendered aspects of industrial labour in Asia, gendered qualities of colonialism, and gendered dimensions of autonomy.

В статье рассматривается несколько эпизодов продолжающегося диалога фило-
софии и антропологии с тем, чтобы проследить различные способы взаимовлия-
ния представителей этих дисциплин; отмечается переход от обсуждения эписте-
мологических проблем в 1980-е годы к соединению онтологии и эпистемологии
в текстах некоторых антропологов в 2010-е годы; приводятся рассуждения не-
скольких ученых-антропологов, не относящих себя к философам-профессиона-
лам, но активно использующих философские теории, аргументы и термины.

This article surveys Theory Revolt's compelling case for historians to take theory seriously in their work, including Joan Scott's reflections on why the feminist turn to theory in the 1980s she helped lead apparently failed to influence the discipline as a whole. It also includes Ann Stoler's recent critiques of capital-T Theory: As she has remarked, "I don’t think we need the word theory any more,” she said, claiming what is meant by the word theory itself “isn’t even problematized half the time.” “Theory with a capital T,” Stoler said, has become “a black box.” “We are doing a disfavor to our graduate students by constantly talking about theory and history, theory and practice. It paralyzes them.”