Communication and Quality in Distributed Agile Development: An Empirical Case Study

Through inward perceptions, we intuitively expect distributed software development to increase the risks associated with achieving cost, schedule, and quality goals. To compound this problem, agile software development (ASD) insists one of the main ingredients of its success is cohesive communication attributed to collocation of the development team. The following study identified the degree of communication richness needed to achieve comparable software quality (reduce pre-release defects) between distributed and collocated teams. This paper explores the relevancy of communication richness in various development phases and its impact on quality. Through examination of a large distributed agile development project, this investigation seeks to understand the levels of communication required within each ASD phase to produce comparable quality results achieved by collocated teams. Obviously, a multitude of factors affects the outcome of software projects. However, within distributed agile software development teams, the mode of communication is one of the critical components required to achieve team cohesiveness and effectiveness. As such, this study constructs a distributed agile communication model (DAC-M) for potential application to similar distributed agile development efforts using the measurement of the suitable level of communication. The results of the study show that less rich communication methods, in the appropriate phase, might be satisfactory to achieve equivalent quality in distributed ASD efforts.

Analysis of Combustion, Performance and Emission Characteristics of Turbocharged LHR Extended Expansion DI Diesel Engine

The fundamental aim of extended expansion concept is to achieve higher work done which in turn leads to higher thermal efficiency. This concept is compatible with the application of turbocharger and LHR engine. The Low Heat Rejection engine was developed by coating the piston crown, cylinder head inside with valves and cylinder liner with partially stabilized zirconia coating of 0.5 mm thickness. Extended expansion in diesel engines is termed as Miller cycle in which the expansion ratio is increased by reducing the compression ratio by modifying the inlet cam for late inlet valve closing. The specific fuel consumption reduces to an appreciable level and the thermal efficiency of the extended expansion turbocharged LHR engine is improved. In this work, a thermodynamic model was formulated and developed to simulate the LHR based extended expansion turbocharged direct injection diesel engine. It includes a gas flow model, a heat transfer model, and a two zone combustion model. Gas exchange model is modified by incorporating the Miller cycle, by delaying inlet valve closing timing which had resulted in considerable improvement in thermal efficiency of turbocharged LHR engines. The heat transfer model, calculates the convective and radiative heat transfer between the gas and wall by taking into account of the combustion chamber surface temperature swings. Using the two-zone combustion model, the combustion parameters and the chemical equilibrium compositions were determined. The chemical equilibrium compositions were used to calculate the Nitric oxide formation rate by assuming a modified Zeldovich mechanism. The accuracy of this model is scrutinized against actual test results from the engine. The factors which affect thermal efficiency and exhaust emissions were deduced and their influences were discussed. In the final analysis it is seen that there is an excellent agreement in all of these evaluations.

Roll of Membership functions in Fuzzy Logic for Prediction of Shoot Length of Mustard Plant Based on Residual Analysis

The selection for plantation of a particular type of mustard plant depending on its productivity (pod yield) at the stage of maturity. The growth of mustard plant dependent on some parameters of that plant, these are shoot length, number of leaves, number of roots and roots length etc. As the plant is growing, some leaves may be fall down and some new leaves may come, so it can not gives the idea to develop the relationship with the seeds weight at mature stage of that plant. It is not possible to find the number of roots and root length of mustard plant at growing stage that will be harmful of this plant as roots goes deeper to deeper inside the land. Only the value of shoot length which increases in course of time can be measured at different time instances. Weather parameters are maximum and minimum humidity, rain fall, maximum and minimum temperature may effect the growth of the plant. The parameters of pollution, water, soil, distance and crop management may be dominant factors of growth of plant and its productivity. Considering all parameters, the growth of the plant is very uncertain, fuzzy environment can be considered for the prediction of shoot length at maturity of the plant. Fuzzification plays a greater role for fuzzification of data, which is based on certain membership functions. Here an effort has been made to fuzzify the original data based on gaussian function, triangular function, s-function, Trapezoidal and L –function. After that all fuzzified data are defuzzified to get normal form. Finally the error analysis (calculation of forecasting error and average error) indicates the membership function appropriate for fuzzification of data and use to predict the shoot length at maturity. The result is also verified using residual (Absolute Residual, Maximum of Absolute Residual, Mean Absolute Residual, Mean of Mean Absolute Residual, Median of Absolute Residual and Standard Deviation) analysis.

Hybrid Markov Game Controller Design Algorithms for Nonlinear Systems

Markov games can be effectively used to design controllers for nonlinear systems. The paper presents two novel controller design algorithms by incorporating ideas from gametheory literature that address safety and consistency issues of the 'learned' control strategy. A more widely used approach for controller design is the H∞ optimal control, which suffers from high computational demand and at times, may be infeasible. We generate an optimal control policy for the agent (controller) via a simple Linear Program enabling the controller to learn about the unknown environment. The controller is facing an unknown environment and in our formulation this environment corresponds to the behavior rules of the noise modeled as the opponent. Proposed approaches aim to achieve 'safe-consistent' and 'safe-universally consistent' controller behavior by hybridizing 'min-max', 'fictitious play' and 'cautious fictitious play' approaches drawn from game theory. We empirically evaluate the approaches on a simulated Inverted Pendulum swing-up task and compare its performance against standard Q learning.

Morphology of Machined Surfaces from Electro Discharge Sawing and Sinking Electro Discharge Machining

Electro Discharge Sawing is a hybrid process combining the features of SEDM and ECM. Its major characteristic is extremely fast erosion rate compare to either of the above processes. This paper brings out its relative feature of SEDM and EDS about their erosion rates, surface roughness, and morphology of machined surfaces.

Iterative Way to Acquire Information Technology for Defense and Aerospace

Defense and Aerospace environment is continuously striving to keep up with increasingly sophisticated Information Technology (IT) in order to remain effective in today-s dynamic and unpredictable threat environment. This makes IT one of the largest and fastest growing expenses of Defense. Hundreds of millions of dollars spent a year on IT projects. But, too many of those millions are wasted on costly mistakes. Systems that do not work properly, new components that are not compatible with old ones, trendy new applications that do not really satisfy defense needs or lost through poorly managed contracts. This paper investigates and compiles the effective strategies that aim to end exasperation with low returns and high cost of Information Technology acquisition for defense; it tries to show how to maximize value while reducing time and expenditure.

Rethinking the Analysis of Means-End Chain Data in Marketing Research

This paper proposes a new procedure for analyzing means-end chain data in marketing research. Most commonly the collected data is summarized in the Hierarchical Value Map (HVM) illustrating the main attribute-consequence-value linkages. This paper argues that traditionally constructed HVM may give an erroneous impression of the results of a means-end study. To justify the arguments, an alternative procedure to (1) determine the dominant attribute-consequence-value linkages and (2) construct HVM in a precise manner is presented. The current approach makes a contribution to means-end analysis, allowing marketers to address a set of marketing problems, such as advertising strategy.

Study The Effects of Conventional and Low Input Production System on Energy Efficiency of Silybum marianum L.

Medicinal plants are most suitable crops for ecological production systems because of their role in human health and the aim of sustainable agriculture to improve ecosystem efficiency and its products quality. Calculations include energy output (contents of energy in seed) and energy inputs (consumption of fertilizers, pesticides, labor, machines, fuel and electricity). The ratio of output of the production to inputs is called the energy outputs / inputs ratio or energy efficiency. One way to quantify essential parts of agricultural development is the energy flow method. The output / input energy ratio is proposed as the most comprehensive single factor in pursuing the objective of sustainability. Sylibum marianum L. is one of the most important medicinal plants in Iran and has effective role on health of growing population in Iran. The objective of this investigation was to find out energy efficiency in conventional and low input production system of Milk thistle. This investigation was carried out in the spring of 2005 – 2007 in the Research Station of Rangelands in Hamand - Damavand region of IRAN. This experiment was done in split-split plot based on randomized complete block design with 3 replications. Treatments were 2 production systems (Conventional and Low input system) in the main plots, 3 planting time (25 of March, 4 and 14 of April) in the sub plots and 2 seed types (Improved and Native of Khoozestan) in the sub-sub plots. Results showed that in conventional production system energy efficiency, because of higher inputs and less seed yield, was less than low input production system. Seed yield was 1199.5 and 1888 kg/ha in conventional and low input systems, respectively. Total energy inputs and out puts for conventional system was 10068544.5 and 7060515.9 kcal. These amounts for low input system were 9533885.6 and 11113191.8 kcal. Results showed that energy efficiency for seed production in conventional and low input system was 0.7 and 1.16, respectively. So, milk thistle seed production in low input system has 39.6 percent higher energy efficiency than conventional production system. Also, higher energy efficiency were found in sooner planting time (25 of March) and native seed of Khoozestan.

Image Enhancement of Medical Images using Gabor Filter Bank on Hexagonal Sampled Grids

For about two decades scientists have been developing techniques for enhancing the quality of medical images using Fourier transform, DWT (Discrete wavelet transform),PDE model etc., Gabor wavelet on hexagonal sampled grid of the images is proposed in this work. This method has optimal approximation theoretic performances, for a good quality image. The computational cost is considerably low when compared to similar processing in the rectangular domain. As X-ray images contain light scattered pixels, instead of unique sigma, the parameter sigma of 0.5 to 3 is found to satisfy most of the image interpolation requirements in terms of high Peak Signal-to-Noise Ratio (PSNR) , lower Mean Squared Error (MSE) and better image quality by adopting windowing technique.

A Self Supervised Bi-directional Neural Network (BDSONN) Architecture for Object Extraction Guided by Beta Activation Function and Adaptive Fuzzy Context Sensitive Thresholding

A multilayer self organizing neural neural network (MLSONN) architecture for binary object extraction, guided by a beta activation function and characterized by backpropagation of errors estimated from the linear indices of fuzziness of the network output states, is discussed. Since the MLSONN architecture is designed to operate in a single point fixed/uniform thresholding scenario, it does not take into cognizance the heterogeneity of image information in the extraction process. The performance of the MLSONN architecture with representative values of the threshold parameters of the beta activation function employed is also studied. A three layer bidirectional self organizing neural network (BDSONN) architecture comprising fully connected neurons, for the extraction of objects from a noisy background and capable of incorporating the underlying image context heterogeneity through variable and adaptive thresholding, is proposed in this article. The input layer of the network architecture represents the fuzzy membership information of the image scene to be extracted. The second layer (the intermediate layer) and the final layer (the output layer) of the network architecture deal with the self supervised object extraction task by bi-directional propagation of the network states. Each layer except the output layer is connected to the next layer following a neighborhood based topology. The output layer neurons are in turn, connected to the intermediate layer following similar topology, thus forming a counter-propagating architecture with the intermediate layer. The novelty of the proposed architecture is that the assignment/updating of the inter-layer connection weights are done using the relative fuzzy membership values at the constituent neurons in the different network layers. Another interesting feature of the network lies in the fact that the processing capabilities of the intermediate and the output layer neurons are guided by a beta activation function, which uses image context sensitive adaptive thresholding arising out of the fuzzy cardinality estimates of the different network neighborhood fuzzy subsets, rather than resorting to fixed and single point thresholding. An application of the proposed architecture for object extraction is demonstrated using a synthetic and a real life image. The extraction efficiency of the proposed network architecture is evaluated by a proposed system transfer index characteristic of the network.

A Novel Plausible Deniability Scheme in Secure Steganography

The goal of steganography is to avoid drawing suspicion to the transmission of a hidden message. If suspicion is raised, steganography may fail. The success of steganography depends on the secrecy of the action. If steganography is detected, the system will fail but data security depends on the robustness of the applied algorithm. In this paper, we propose a novel plausible deniability scheme in steganography by using a diversionary message and encrypt it with a DES-based algorithm. Then, we compress the secret message and encrypt it by the receiver-s public key along with the stego key and embed both messages in a carrier using an embedding algorithm. It will be demonstrated how this method can support plausible deniability and is robust against steganalysis.

Development of Synthetic Jet Air Blower for Air-breathing PEM Fuel Cell

This paper presents a synthetic jet air blower actuated by PZT for air blowing for air-breathing micro PEM fuel cell. The several factors to affect the performance of air-breathing PEM fuel cell such as air flow rate, opening ratio and cathode open type in the cathode side were studied. Especially, an air flow rate is critical condition to improve its performance. In this paper, we developed a synthetic jet air blower to supply a high stoichiometric air flow. The synthetic jet mechanism is a zero mass flux device that converts electrical energy into the momentum. The synthetic jet actuation is usually generated by a traditional PZT actuator, which consists of a small cylindrical cavity, in/outlet channel and PZT diaphragms. The flow rate of the fabricated synthetic jet air blower was 400cc/min at 550Hz and its power consumption was very low under 0.3W. The proposed air-breathing PEM fuel cell which installed synthetic jet air blower was higher performance and stability during continuous operation than the air-breathing fuel cell without auxiliary device to supply the air. The results showed that the maximum power density was 188mW/cm2 at 400mA/cm2. This maximum power density and durability were improved more than 40% and 20%, respectively.

Design of a Hybrid Fuel Cell with Battery Energy Storage for Stand-Alone Distributed Generation Applications

This paper presents the modeling and simulation of a hybrid proton exchange membrane fuel cell (PEMFC) with an energy storage system for use in a stand-alone distributed generation (DG) system. The simulation model consists of fuel cell DG, lead-acid battery, maximum power point tracking and power conditioning unit which is modeled in the MATLAB/Simulink platform. Poor loadfollowing characteristics and slow response to rapid load changes are some of the weaknesses of PEMFC because of the gas processing reaction and the fuel cell dynamics. To address the load-tracking issues in PEMFC, a hybrid PEMFC and battery storage system is considered and modelled. The model utilizes PEMFC as the main energy source whereas the battery functions as energy storage to compensate for the limitations of PEMFC.Simulation results are given to show the overall system performance under light and heavyloading conditions.

Application of Neural Network and Finite Element for Prediction the Limiting Drawing Ratio in Deep Drawing Process

In this paper back-propagation artificial neural network (BPANN) is employed to predict the limiting drawing ratio (LDR) of the deep drawing process. To prepare a training set for BPANN, some finite element simulations were carried out. die and punch radius, die arc radius, friction coefficient, thickness, yield strength of sheet and strain hardening exponent were used as the input data and the LDR as the specified output used in the training of neural network. As a result of the specified parameters, the program will be able to estimate the LDR for any new given condition. Comparing FEM and BPANN results, an acceptable correlation was found.

Implementation of RSA Blind Signature on CryptO-0N2 Protocol

Blind Signature were introduced by Chaum. In this scheme, a signer can “sign” a document without knowing the document contain. This is particularly important in electronic voting. CryptO-0N2 is an electronic voting protocol which is development of CryptO-0N. During its development this protocol has not been furnished with the requirement of blind signature, so the choice of voters can be determined by counting center. In this paper will be presented of implementation of blind signature using RSA algorithm.

Flow Properties of Commercial Infant Formula Powders

The objective of this work was to investigate flow properties of powdered infant formula samples. Samples were purchased at a local pharmacy and differed in composition. Lactose free infant formula, gluten free infant formula and infant formulas containing dietary fibers and probiotics were tested and compared with a regular infant formula sample which did not contain any of these supplements. Particle size and bulk density were determined and their influence on flow properties was discussed. There were no significant differences in bulk densities of the samples, therefore the connection between flow properties and bulk density could not be determined. Lactose free infant formula showed flow properties different to standard supplement-free sample. Gluten free infant formula with addition of probiotic microorganisms and dietary fiber had the narrowest particle size distribution range and exhibited the best flow properties. All the other samples exhibited the same tendency of decreasing compaction coefficient with increasing flow speed, which means they all become freer flowing with higher flow speeds.

3 State Current Mode of a Grid Connected PV Converter

Nowadays in applications of renewable energy sources it is important to develop powerful and energy-saving photovoltaic converters and to keep the prescriptions of the standards. In grid connected PV converters the obvious solution to increase the efficiency is to reduce the switching losses. Our new developed control method reduces the switching losses and keeps the limitations of the harmonic distortion standards. The base idea of the method is the utilization of 3-state control causing discontinuous current mode at low input power. In the following sections the control theory, the realizations and the simulation results are presented.

International Financial Crises and the Political Economy of Financial Reforms in Turkey: 1994-2009

This study1 holds for the formation of international financial crisis and political factors for economic crisis in Turkey, are evaluated in chronological order. The international arena and relevant studies conducted in Turkey work in the literature are assessed. The main purpose of the study is to hold the linkage between the crises and political stability in Turkey in details, and to examine the position of Turkey in this regard. The introduction part follows the literature survey on the models explaining causes and results of the crises, the second part of the study. In the third part, the formations of the world financial crises are studied. The fourth part, financial crisis in Turkey in 1994, 2000, 2001 and 2008 are reviewed and their political reasons are analyzed. In the last part of the study the results and recommendations are held. Political administrations have laid the grounds for an economic crisis in Turkey. In this study, the emergence of an economic crisis in Turkey and the developments after the crisis are chronologically examined and an explanation is offered as to the cause and effect relationship between the political administration and economic equilibrium in the country. Economic crises can be characterized as follows: high prices of consumables, high interest rates, current account deficits, budget deficits, structural defects in government finance, rising inflation and fixed currency applications, rising government debt, declining savings rates and increased dependency on foreign capital stock. Entering into the conditions of crisis during a time when the exchange value of the country-s national currency was rising, speculative finance movements and shrinking of foreign currency reserves happened due to expectations for devaluation and because of foreign investors- resistance to financing national debt, and a financial risk occurs. During the February 2001 crisis and immediately following, devaluation and reduction of value occurred in Turkey-s stock market. While changing over to the system of floating exchange rates in the midst of this crisis, the effects of the crisis on the real economy are discussed in this study. Administered politics include financial reforms, such as the rearrangement of banking systems. These reforms followed with the provision of foreign financial support. There have been winners and losers in the imbalance of income distribution, which has recently become more evident in Turkey-s fragile economy.

Person Identification by Using AR Model for EEG Signals

A direct connection between ElectroEncephaloGram (EEG) and the genetic information of individuals has been investigated by neurophysiologists and psychiatrists since 1960-s; and it opens a new research area in the science. This paper focuses on the person identification based on feature extracted from the EEG which can show a direct connection between EEG and the genetic information of subjects. In this work the full EO EEG signal of healthy individuals are estimated by an autoregressive (AR) model and the AR parameters are extracted as features. Here for feature vector constitution, two methods have been proposed; in the first method the extracted parameters of each channel are used as a feature vector in the classification step which employs a competitive neural network and in the second method a combination of different channel parameters are used as a feature vector. Correct classification scores at the range of 80% to 100% reveal the potential of our approach for person classification/identification and are in agreement to the previous researches showing evidence that the EEG signal carries genetic information. The novelty of this work is in the combination of AR parameters and the network type (competitive network) that we have used. A comparison between the first and the second approach imply preference of the second one.

Lemon Effect on Some Elements in Turkish Teas

Tea has several types of essential elements. Potassium, magnesium and phosphorus are some examples of these elements. Tea is widely used drink in Turkey, also some people puts a lemon wedge to tea for different taste. In this study potassium, magnesium and phosphorus contents after the hot water brewing of black and green tea were determined by Optical Emission Spectroscopy (ICPOES). Furthermore, how the lemon addition to teas affects the concentrations of the potassium, magnesium and phosphorus amount are investigated. From the results, potassium, magnesium and phosphorus concentrations are found as 3003.3, 597.1, 1167.2 ppm in black tea and 3718.0, 3830.5, 376.4 ppm in green tea, respectively. After lemon addition potassium, magnesium and phosphorus concentrations are changed to 14930, 830.4, 1113.5 ppm in black tea and 15460.0, 909.5, 1152.5 ppm in green tea, respectively. It is seen that lemon addition affects some essential elements in black and green Turkish teas.