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Long description: In this thesis a functorial approach to the category of derived manifolds is developed. We use a similar approach as Demazure and Gabriel did when they described the category of schemes as a full subcategory of the category of sheaves on the big Zariski site. Their work is further developed leading to the definition of C#-schemes and derived manifolds as certain sheaves on appropriate big sites. The new description of C#-schemes and derived manifolds via functors is compared to the previous approaches via locally ringed spaces given by D. Joyce and D. Spivak. Furthermore, it is proven that both approaches lead to equivalent categories.

We formally prove correct a C program that implements a numerical scheme for the resolution of the one-dimensional acoustic wave equation. Such an implementation introduces errors at several levels: the numerical scheme introduces method errors, and floating-point computations lead to round-off errors. We annotate this C program to specify both method error and round-off error. We use Frama-C to generate theorems that guarantee the soundness of the code. We discharge these theorems using SMT solvers, Gappa, and Coq. This involves a large Coq development to prove the adequacy of the C program to the numerical scheme and to bound errors. To our knowledge, this is the first time such a numerical analysis program is fully machine-checked.

Many development environments offer refactorings aimed at improving non-functional properties of software, but we have no guarantees that these transformations indeed preserve the observable behavior of the source code they are applied on. An existing domain-specific language makes it possible to formalize automatically verifiable refactorings via instantiating predefined transformation schemes with conditional term rewrite rules. We present a proposal for adapting this language from the functional to the object-oriented programming paradigm, using Java instead of Erlang as a representative. The behavior-preserving property of discussed refactorings is characterized with a multilayered definition of equivalence for Java programs, including the conformity relation of class hierarchies. Based on the decomposition of a complex refactoring rule, we show how new transformation schemes can be identified, along with modifications and extensions of the description language required to accommodate them. Finally, we formally define the chosen base refactoring as a composition of scheme instances.

In software development, requirements traceability is often mandated. It is important to apply to support various software development activities like result evaluation, regression testing and coverage analysis. Model-Driven Testing is one approach to provide a way to verify and validate requirements. However, it has many challenges in test generation in addition to the creation and maintenance of traceability information across test-related artifacts. This paper presents a model-based methodology for requirements traceability that relies on leveraging model transformation traceability techniques to achieve compliance with DO-178C standard as defined in the software verification process. This paper also demonstrates and evaluates the proposed methodology using avionics case studies focusing on the functional aspects of the requirements specified with the UCM (Use Case Maps) modeling language.

This research was aimed at constructing a thesaurus of the ethnic groups in the Mekong River Basin that is a compilation of controlled vocabularies of both Thai and English language, with a digital platform that enables semantic search and linked open data. The research method involved four steps: (1) organization of knowledge content; (2) construction of the thesaurus; (3) development of a digital thesaurus platform; and (4) evaluation. The concepts and theories used in the research comprised knowledge organization, thesaurus construction, digital platform development, and system evaluation. The tool for developing the digital thesaurus was the Tematres web application. The research results are: (1) there are 4273 principle words related to the ethnic groups that have been compiled and classified by the terms for each of the eight deep levels, 2596 were found to have hierarchical relationships, and 6858 had associative relationships; (2) the digital thesaurus platform was able to manage the controlled vocabularies related to the Mekong ethnic groups by storing both Thai and English vocabularies. When retrieved, the vocabulary, details of the broader term, narrow term, related term, cross reference, and scope note are displayed. Thus, semantic search is viable through applications, linked open data technology, and web services.

PurposeThis paper aims to propose an automated mobile app labeling framework based on a novel app classification scheme that is aligned with users’ primary motivations for using smartphones. The study addresses the gaps in incorporating the needs of users and other context information in app classification as well as recommendation systems.Design/methodology/approachBased on a corpus of mobile app descriptions collected from Google Play store, this study applies extensive text analytics and topic modeling procedures to profile mobile apps within the categories of the classification scheme. Sufficient number of representative and labeled app descriptions are then used to train a classifier using machine learning algorithms, such as rule-based, decision tree and artificial neural network.FindingsExperimental results of the classifiers show high accuracy in automatically labeling new apps based on their descriptions. The accuracy of the classification results suggests a feasible direction in facilitating app searching and retrieval in different Web-based usage environments.Research limitations/implicationsAs a common challenge in textual data projects, the problem of data size and data quality issues exists throughout the multiple phases of experiments. Future research will extend the data collection scope in many aspects to address the issues that constrained the current experiments.Practical implicationsThese empirical experiments demonstrate the feasibility of textual data analysis in profiling apps and user context information. This study also benefits app developers by improving app descriptions through a better understanding of user needs and context information. Finally, the classification framework can also guide practitioners in customizing products and services beyond mobile apps where context information and user needs play an important role.Social implicationsGiven the widespread usage and applications of smartphones today, the proposed app classification framework will have broader implications to different Web-based application environments.Originality/valueWhile there have been other classification approaches in the literature, to the best of the authors’ knowledge, this framework is the first study on building an automated app labeling framework based on primary motivations of smartphone usage.

Bibliographic classification is among the core activities of Library & Information Science that brings order and proper management to the holdings of a library. Compared to printed media, digital collections present numerous challenges regarding their preservation, curation, organization and their resource discovery and access. In this regard true native perspective is needed to be adopted for bibliographic classification in digital environments. In this research article, we have investigated and reported different approaches to bibliographic classification of digital collections. The article also contributes two evaluation frameworks that evaluate different classification schemes and elaborate different approaches that exist in theory, in manual practice and automatically in digital environments. The article presents a bird-eye-view for researchers in reaching a generalized and holistic approach towards bibliographic classification research, where new research avenues have been identified. 

LITERATURE REVIEW: 1)Multiport Railway Power Conditioner and its Clean Energy Access Management Strategy [1] A multi-port railway power conditioner (MP-RPC) with access to renewable energy is proposed to achieve the mutual benefits between railway systems and renewable energy systems (RESs) in order to realize on-site power usage and compensation for negative series. [...]the traction power platform and virtual prototype are installed in the Lab and MP-RPC's topology and control methods are effectively tested. 2)Prediction of device failure based on a Markov Bayesian model of the network [2] Because of the complexity of software products and production processes, software reliability models need to provide several parameter handling capacity. Sqoop fetches table metadata from MySQL database before exporting. [...]we need to create a table with the metadata needed first. 3) Analysis Query Language (Hive) Hive is a Hadoop data warehouse framework that runs SQL like HQL (Hive query language) queries that are transformed internally to map reduces work. Hadoop ecosystem has hive, pig, map reduces resources to process if production takes less time to processand outcome is going to be very fast. [...]in this project, data from the Railway Network, which will traditionally be stored in RDBMS, will be reduced in performance, hence,

A number of similarities between living cells and universal computers are considered. Intracellular life processes are compared to computation processes inside a computer. Proteins coordinating intracellular processes are associated with computer programs during runtime. The possibility of the existence of a genetic programming language that allows effectively building new genes from the existing ones is considered.