Performance Evaluation of Software using Formal Methods

Formal Methods (FMs) can be used in varied areas of applications and to solve critical and fundamental problems of Performance Evaluation (PE). Modelling and analysis techniques can be used for both system and software performance evaluation. The functional features and performance properties of modern software used for performance evaluation has become so intertwined. Traditional models and methods for performance evaluation has been studied widely which culminated into the modern models and methods for system and software engineering evaluation such as formal methods. Techniques have transcended from functionality to performance modeling and analysis. Formal models help in identifying faulty reasoning far earlier than in traditional design; and formal specification has proved useful even on already existing software and systems. Formal approach eliminates ambiguity. The basic and final goal of the performance evaluation technique is to come to a conclusion, whether the software and system are working in a good condition or satisfactorily

Application of Artificial Intelligence in User Interfaces Design for Cyber Security Threat Modeling

In recent years, Cyber Security threat modeling has been discovered to have the capacity of combatting and mitigating against online threats. In order to minimize the associated risk, these threats need to be modelled with appropriate Intelligent User Interface (IUI) design and consequently the development and evaluation of threat metrics. Artificial Intelligence (AI) has revolutionized every facet of our daily lives and building a responsive Cyber Security Threat Model requires an IUI. The current threat models lack IUI, hence they cannot deliver convenience and efficiency. However, as the User Interface (UI) functionalities and User Experience (UX) continue to increase and deliver more astonishing possibilities, the present threat models lack the predictability capacity thus Machine Learning paradigms must be incorporated. Meanwhile, this deficiency can only be handled through AI-enabled UI that utilizes baseline principles in the design of interfaces for effective Human-Machine Interaction (HMI) with lasting UX. IUI helps developers or designers enhance flexibility, usability, and the relevance of the interaction to improving communication between computer and human. Baseline principles must be applied for developing threat models that will ensure fascinating UI-UX. Application of AI in UI design for Cyber Security Threat Modeling brings about reduction in critical design time and ensures the development of better threat modeling applications and solutions

pGReMLIN: previsão de ligantes usando subestruturas conservadas na interação proteína-proteína

One of the sources of data for the protein dataset being explored in bioinformatics is the Protein Data Bank (PDB). Searching for similar conserved structures in biological problems was an early attempt and is still a popular method widely used by researchers. In this work, a graph-based approach named pGReMLIN is proposed, which predicts similar structures in protein-protein or protein-peptide complexes using the established conserved structural arrangements of Serine protease and BCL-2. The protein-protein or protein-peptide complexes are downloaded from the PDB, and the interface between proteins at the atomic level is modeled as a graph, with atoms as nodes and the non-covalent interactions between atoms as edges. The computation of a similar pattern of structural arrangement in the data graph was achieved using a set of candidate pairs of data graph D(G) and query graph Q(G) based on state space representation and feasibility rules that embed equality of structure and attributes. pGReMLIN was able to compute, in the data graph, a conserved structural arrangement that represents highly conserved interactions at the specificity binding interface of trypsin and trypsin-like proteins. Also, our method was able to identify similar patterns with large pattern size in the data graph common to Serine protease and BCL-2 and as well as unique to Serine protease and BCL-2. Furthermore, pGReMLIN was able to present various large patterns of similar conserved patterns that can be further explored to determine their potency. Hence, the presence of similar patterns in our protein-protein dataset indicates the possibility that patterns found in our dataset have similar functions to the conserved structures. Keywords: Protein-protein interaction. Graph-subgraph isomorphism. Ligands prediction.Uma das fontes de dados para o conjunto de dados de proteínas que está sendo explorado em bioinformática é o Protein Data Bank (PDB). A busca por estruturas conservadas semelhantes em problemas biológicos foi uma tentativa inicial e ainda é um método popular amplamente utilizado por pesquisadores. Neste trabalho, uma abordagem baseada em gráficos chamada pGReMLIN é proposta, que prediz estruturas similares em complexos proteína-proteína ou proteína-peptídeo usando os arranjos estruturais conservados estabelecidos de Serina protease e BCL-2. Os complexos proteína-proteína ou proteína-peptídeo são baixados do PDB, e a interface entre as proteínas no nível atômico é modelada como um gráfico, com os átomos como nós e as interações não covalentes entre os átomos como arestas. O cálculo de um padrão semelhante de arranjo estrutural no gráfico de dados foi obtido usando um conjunto de pares candidatos de gráfico de dados D(G) e gráfico de consulta Q(G) com base na representação do espaço de estado e regras de viabilidade que incorporam a igualdade de estrutura e atributos . pGReMLIN foi capaz de calcular, no gráfico de dados, um arranjo estrutural conservado que representa interações altamente conservadas na interface de ligação de especificidade de tripsina e proteínas semelhantes a tripsina. Além disso, nosso método foi capaz de identificar padrões semelhantes com tamanho de padrão grande no gráfico de dados comum à serina protease e BCL-2 e também exclusivo para serina protease e BCL-2. Além disso, pGReMLIN foi capaz de apresentar vários grandes padrões de padrões conservados semelhantes que podem ser mais explorados para determinar sua potência. Portanto, a presença de padrões semelhantes em nosso conjunto de dados proteína-proteína indica a possibilidade de que os padrões encontrados em nosso conjunto de dados tenham funções semelhantes às estruturas conservadas. Palavras-chave: Interação proteína-proteína. Isomorfismo grafo-subgrafo. previsão de ligantes.FAR