Gotowa bibliografia na temat „Black-box equivalance checking- Building”

The Department of Industry and Trade of Ende Regency is a local government agency that is directly related to the process of data collection and assistance for small and medium industrial enterprises (SME) in Ende Regency which is still done manually, causing problems in data collection. the process is considered to be very slow so there is still a lot of SMI data that is not recorded clearly and completely. This website-based IKM data collection application aims to assist the Trade and Industry Office of the Ende Regency in the computerized IKM data collection process and checking of business assistance funds so that it can run effectively and efficiently. The software design methodology used in this study is the system development life cycle (SDLC) starting from the analysis, design, implementation, testing, and maintenance stages. In this study, researchers used 2 system testing methods, namely system usability scale testing (SUS), and black box testing. The results of the research on 4 respondents obtained an average SUS score of 86.2 with an acceptable interpretation of the B value category. While the results of black box testing are obtained from the tests that have been carried out, it can be concluded that all functional features can run well.

Building design review is the procedure of checking a design against codes and standard provisions to satisfy the accuracy of the design and identify non-compliances before construction begins. The current approaches for conducting the design review process in an automatic or semi-automatic manner are either based on proprietary, domain-specific or hard-coded rule-based mechanisms. These methods may be effective in their specific applications, but they have the downsides of being costly to maintain, inflexible to modify, and lack a generalized framework of rules and regulations modeling that can adapt to various engineering design realms, and thus don’t support a neutral data standard. They are often referred to as 'Black Box' or ‘Gray Box’ approaches. This research offers a new comprehensive framework that reduces the limitations of the cited methods. Building regulations, for instance, are legal documents transcribed and approved by professionals to be interpreted and applied by people. They are hardly as precise as formal logic. Engineers, architects, and contractors can read those technical documents and transform them into scientific notations and software applications. They can extract any data they need, reason about it, and apply it at various phases of the project. How these extraction and use are carried out is a critical component of automating the design review process. The chief goal is to address this issue by developing a Generalized Adaptive Framework (GAF) for a neutral data standard (Industry Foundation Classes (IFC)) that enables automating the code compliance checking processes to achieve design efficiency and cost-effectiveness. The objectives of this study comprise i) to develop a theoretical background to an adaptive framework that supports a neutral data standard for transforming the written code regulations and rules into a computable model, and ii) to define the various modules required for computerizing of the code compliance verification process.

The XYZ cooperation is a business entity dealing with savings and loans, building rental, convection, rice procurement and shops that are very concerned about the welfare of its members. The appraisal process for loan approval decision in the XYZ cooperative was still lack of assessment. It was based on the value of the members’ report cards which covers collateral, wealth, and behavior so that the funds were not often on the target. Moreover, the cooperative members were often careless in repayment process. The method in this research was Exponential Comparison Method. This method determined the priority order of alternative decisions with criteria. Those criteria in this research were: Report cards, BI Checking, Application Purpose, source of income, monthly income, installment period, completeness of files, guarantees, status, and the amount requested. As a result of applying this system and adding some new criteria, cooperation considers loan approval assessments in determining the eligible members. The results of functional testing by black-box method showed that the system ran as expected and the functions of the application ran properly.

Checking the equality of two arrays is a crucial building block of the Fujisaki-Okamoto transformation, and as such it is used in several post-quantum key encapsulation mechanisms including Kyber and Saber. While this comparison operation is easy to perform in a black box setting, it is hard to efficiently protect against side-channel attacks. For instance, the hash-based method by Oder et al. is limited to first-order masking, a higher-order method by Bache et al. was shown to be flawed, and a very recent higher-order technique by Bos et al. suffers in runtime. In this paper, we first demonstrate that the hash-based approach, and likely many similar first-order techniques, succumb to a relatively simple side-channel collision attack. We can successfully recover a Kyber512 key using just 6000 traces. While this does not break the security claims, it does show the need for efficient higher-order methods. We then present a new higher-order masked comparison algorithm based on the (insecure) higher-order method of Bache et al. Our new method is 4.2x, resp. 7.5x, faster than the method of Bos et al. for a 2nd, resp. 3rd, -order masking on the ARM Cortex-M4, and unlike the method of Bache et al., the new technique takes ciphertext compression into account. We prove correctness, security, and masking security in detail and provide performance numbers for 2nd and 3rd-order implementations. Finally, we verify our the side-channel security of our implementation using the test vector leakage assessment (TVLA) methodology.

Sensors in the primary circuit of a pressurized water reactor (PWR) are normally designed with redundant structures to improve system safety and reliability. However, reliability of the actual system is often lower than that obtained by theoretical calculation due to the inevitable occurrence of common mode fault (CMF), which is a dependent failure event that can cause multiple failures in redundant channels. CMF may increase the reliability deviation of the system by orders of magnitude and, hence, seriously affects the reliability of the system. To mitigate the CMF of redundant sensors in nuclear power plants, an artificial neural network (ANN) can serve as a data-driven analytic model to monitor sensor parameters, to identify any possible abnormal status of the sensors, and provide an early warning. In this study, by using the high-fidelity dataset obtained in a full-scope PWR simulator as training, validation, and test data, a relevant parameter-based ANN black-box model (RPANN) was established by employing the back-propagation (BP) learning algorithm, which was then defined as an analytic redundancy. Time series-based ANN checking models (TSANNs) were also established for each of the input and output parameters of the RPANN in order to identify its abnormal state based on historical data in the past. When combined with the existing hardware redundancy, the ANN-based analytic redundancy can serve as an online monitoring tool of the hardware status and an online diagnosis strategy for sensor faults. Furthermore, ANN-based analytic redundancy can replace faulty hardware sensors to analytically reconstruct the reading of the monitored sensor parameter without having to reduce the reactor output power or even shut down the reactor for emergency maintenance so that the on-site calibration frequency of hardware sensors in redundant channels can be effectively reduced. This is not only of vital importance in reducing operation and maintenance costs of existing PWR power plants but also plays an important role in building reactor operation schemes with rapid and frequent changes in power output in the future. Simultaneously, the diverse redundancy combining analytic software redundancy and physical hardware redundancy can effectively reduce the threat of CMF of hardware sensors on the operation safety of reactor systems.