Quality Assessment of Software Reliability Growth Models

The two main important properties of software components are reliability and robustness. Reliability can be defined as the probability of failure free operation and on the other hand the robustness can be defined as how far the software can be able to with stand for intrusion attacks. In both the cases there should be some metric to evaluate the performance of these properties. In this paper metrics are been described which can be used to assess the quality of performance for these properties within a software reliability growth model. Keywords: Software growth model, reliability, robustness, Quality metrics

Performance Analysis of Improved Component based Software Reliability Model

Software reliability engineering techniques focus on development and maintenance of software systems. This paper presents a improved component model. The model is used to estimate the reliability of software systems and the usage ration of each component. A component impact analysis which helps in focusing of testing is presented .The proposed method exhibits considerable improvement when compared against conventional methods

Tietokierto ilmakehäfysiikassa : mitatusta millivoltista ilmakehän ymmärtämiseen

In this thesis the concept of data cycle is introduced. The concept itself is general and only gets the real content when the field of application is defined. If applied in the field of atmospheric physics the data cycle includes measurements, data acquisition, processing, analysis and interpretation. The atmosphere is a complex system in which everything is in a constantly moving equilibrium. The scientific community agrees unanimously that it is human activity, which is accelerating the climate change. Nevertheless a complete understanding of the process is still lacking. The biggest uncertainty in our understanding is connected to the role of nano- to micro-scale atmospheric aerosol particles, which are emitted to the atmosphere directly or formed from precursor gases. The latter process has only been discovered recently in the long history of science and links nature s own processes to human activities. The incomplete understanding of atmospheric aerosol formation and the intricacy of the process has motivated scientists to develop novel ways to acquire data, new methods to explore already acquired data, and unprecedented ways to extract information from the examined complex systems - in other words to compete a full data cycle. Until recently it has been impossible to directly measure the chemical composition of precursor gases and clusters that participate in atmospheric particle formation. However, with the arrival of the so-called atmospheric pressure interface time-of-flight mass spectrometer we are now able to detect atmospheric ions that are taking part in particle formation. The amount of data generated from on-line analysis of atmospheric particle formation with this instrument is vast and requires efficient processing. For this purpose dedicated software was developed and tested in this thesis. When combining processed data from multiple instruments, the information content is increasing which requires special tools to extract useful information. Source apportionment and data mining techniques were explored as well as utilized to investigate the origin of atmospheric aerosol in urban environments (two case studies: Krakow and Helsinki) and to uncover indirect variables influencing the atmospheric formation of new particles.Tässä työssä esitellään konsepti - tietokierto ilmakehätieteissä. Tietokierto on sinänsä yleinen käsite ja ei liity mihinkään tiettyyn tieteenalaan. Tietokierto huomioi jokaisen vaiheen raa asta mittausarvosta datan soveltamiseen, ymmärtämiseen ja tulkintaan. Ilmakehäfysiikassa tietokierto sisältää vaiheet signaalin havainnoinnista, datan keräämiseen, esikäsittelyyn, ja työstämiseen sekä sitä kautta tulkintaan. Ilmakehä on monimutkainen kokonaisuus, jossa kaikki on jatkuvasti muuttuvassa tasapainossa keskenään. Tiedeyhteisö on yksimielisesti sitä mieltä, että kiihtyvä ilmastonmuutos on ihmisen toiminnan seurausta. Tarkalleen sitä prosessia ei kuitenkaan tunneta. Suurin epävarmuus ymmärryksessä on pienhiukkasten aiheuttama vaikutus ilmastomuutokseen. Pienhiukkasia päätyy ilmakehään joko suoraan päästölähteistä tai ne muodostuvat nukleaation eli kaasu-hiukkasmuuntuman kautta. Viimeksi mainittu ilmiö on havaittu vasta hiljattain ja sen yksityiskohtainen ymmärrys vielä puuttuu. Ilmiön monimutkaisuus on kiehtonut ja motivoinut tutkijoita kehittämään uusia mittalaitteistoja, mittausmenetelmiä, datan analysointimenetelmiä ja uusia tapoja suodattaa tietoa jo kerätystä datasta - toisin sanoen täydentää ja parantaa tietokiertoa. Aikaisemmin on ollut mahdotonta mitata suoraan kaasu-hiukkasmuuntumisessa osallistuvien kaasujen kemiallista koostumusta. Tässä työssä käytetty laitteisto (ilmakehäpaineliitännäinen lentoaikamassaspektrometri, APiTOF) pystyy havaitsemaan kyseisiä kaasuja suoraan ilman esikäsittelyä. Koska laitteisto on uusi ja sen tuottama data määrä on iso, kehitettiin tässä työssä tehokas raakadatan esikäsittelymenetelmä ja työkalu. Kun yhdistetään prosessoitu data useista laitteista, informaation sisältö kasvaa, mutta sen esille saaminen hankaloituu. Tässä työssä kehitettiin ja käytettiin menetelmiä ilmamassojen päästölähdekartoitukseen, tarkoituksena selvittää kaupunginympäristön pahimmat saastuttajat ja päästölähteet. Datan louhintaa hyödynnettiin löytämään kaasu-hiukkasmuuntumaan vaikuttavia tekijöitä

Proceedings of Abstracts 12th International Conference on Air Quality Science and Application

© 2020 The Author(s). This an open access work distributed under the terms of the Creative Commons Attribution Licence (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited.Final Published versio

a review of airq models and their applications for forecasting the air pollution health outcomes

Even though clean air is considered as a basic requirement for the maintenance of human health, air pollution continues to pose a significant health threat in developed and developing countries alike. Monitoring and modeling of classic and emerging pollutants is vital to our knowledge of health outcomes in exposed subjects and to our ability to predict them. The ability to anticipate and manage changes in atmospheric pollutant concentrations relies on an accurate representation of the chemical state of the atmosphere. The task of providing the best possible analysis of air pollution thus requires efficient computational tools enabling efficient integration of observational data into models. A number of air quality models have been developed and play an important role in air quality management. Even though a large number of air quality models have been discussed or applied, their heterogeneity makes it difficult to select one approach above the others. This paper provides a brief review on air quality models with respect to several aspects such as prediction of health effects

NETWORKED MICROGRID OPTIMIZATION AND ENERGY MANAGEMENT

Military vehicles possess attributes consistent with a microgrid, containing electrical energy generation, storage, government furnished equipment (GFE), and the ability to share these capabilities via interconnection. Many military vehicles have significant energy storage capacity to satisfy silent watch requirements, making them particularly well-suited to share their energy storage capabilities with stationary microgrids for more efficient energy management. Further, the energy generation capacity and the fuel consumption rate of the vehicles are comparable to standard diesel generators, for certain scenarios, the use of the vehicles could result in more efficient operation. Energy management of a microgrid is an open area of research especially in generation constrained scenarios where shedding of low-priority loads may be required. Typical metrics used to assess the effectiveness of an energy management strategy or policy include fuel consumption, electrical storage energy requirements, or the net exergy destruction. When considering a military outpost consisting of a stationary microgrid and a set of vehicles, the metrics used for managing the network become more complex. For example, the metrics used to manage a vehicle’s onboard equipment while on patrol may include fuel consumption, the acoustic signature, and the heat signature. Now consider that the vehicles are parked at an outpost and participating in vehicle-to-grid power-sharing and control. The metrics used to manage the grid assets may now include fuel consumption, the electrical storage’s state of charge, frequency regulation, load prioritization, and load dispatching. The focus of this work is to develop energy management and control strategies that allow a set of diverse assets to be controlled, yielding optimal operation. The provided policies result in both short-term and long-term optimal control of the electrical generation assets. The contributions of this work were: (1) development of a methodology to generate a time-varying electrical load based on (1) a U.S. Army-relevant event schedule and (2) a set of meteorological conditions, resulting in a scenario rich environment suitable for modeling and control of hybrid AC/DC tactical military microgrids, (2) the development of a multi-tiered hierarchical control architecture, suitable for development of both short and long term optimal energy management strategies for hybrid electric microgrids, and (3) the development of blending strategies capable of blending a diverse set of heterogeneous assets with multiple competing objective functions. This work could be extended to include a more diverse set of energy generation assets, found within future energy networks

Multivariable optimization of pyramidal compound substrates for cooling of power-electronics in modern hybrid and electric propulsion systems

We present a method for the optimization of the thermal cooling of heat sources mounted on top of layered composites and pyramidal substrates, that are widely used in the power electronics of hybrid-electric propulsion systems. The analytical solution of the Laplace's heat equation is approximated via Fourier expansion series and it is coupled to the Influence Coefficient Method (ICM) to provide a functional of the overall thermal stress to minimize. A multivariable optimization method is derived by coupling the equations for the heat transfer with the Sequential Least-Square Quadratic Programming (SLSQP), or the Bounded Limited-Memory BFGS (L-BFGS-B) algorithm. Code validation is performed against three-dimensional simulations and experimental data available from the literature. It is shown that an optimal component relocation and apportionment of the overall thickness of the multilayer substrate promotes a sensible reduction of the thermal stress

Advanced Rotorcraft Transmission (ART) program

Work performed by the McDonnell Douglas Helicopter Company and Lucas Western, Inc. within the U.S. Army/NASA Advanced Rotorcraft Transmission (ART) Program is summarized. The design of a 5000 horsepower transmission for a next generation advanced attack helicopter is described. Government goals for the program were to define technology and detail design the ART to meet, as a minimum, a weight reduction of 25 percent, an internal noise reduction of 10 dB plus a mean-time-between-removal (MTBR) of 5000 hours compared to a state-of-the-art baseline transmission. The split-torque transmission developed using face gears achieved a 40 percent weight reduction, a 9.6 dB noise reduction and a 5270 hour MTBR in meeting or exceeding the above goals. Aircraft mission performance and cost improvements resulting from installation of the ART would include a 17 to 22 percent improvement in loss-exchange ratio during combat, a 22 percent improvement in mean-time-between-failure, a transmission acquisition cost savings of 23 percent of $165K, per unit, and an average transmission direct operating cost savings of 33 percent, or$24K per flight hour. Face gear tests performed successfully at NASA Lewis are summarized. Also, program results of advanced material tooth scoring tests, single tooth bending tests, Charpy impact energy tests, compact tension fracture toughness tests and tensile strength tests are summarized