An improved fast scanning algorithm based on distance measure and threshold function in region image segmentation

Segmentation is an essential and important process that separates an image into regions that have similar characteristics or features. This will transform the image for a better image analysis and evaluation. An important benefit of segmentation is the identification of region of interest in a particular image. Various algorithms have been proposed for image segmentation and this includes the Fast Scanning algorithm which has been employed on food, sport and medical image segmentation. The clustering process in Fast Scanning algorithm is performed by merging pixels with similar neighbor based on an identified threshold and the use of Euclidean Distance as distance measure. Such an approach leads to a weak reliability and shape matching of the produced segments. Hence, this study proposes an Improved Fast Scanning algorithm that is based on Sorensen distance measure and adaptive threshold function. The proposed adaptive threshold function is based on the grey value in an image’s pixels and variance. The proposed Improved Fast Scanning algorithm is realized on two datasets which contains images of cars and nature. Evaluation is made by calculating the Peak Signal to Noise Ratio (PSNR) for the Improved Fast Scanning and standard Fast Scanning algorithm. Experimental results showed that proposed algorithm produced higher PSNR compared to the standard Fast Scanning. Such a result indicate that the proposed Improved Fast Scanning algorithm is useful in image segmentation and later contribute in identifying region of interesting in pattern recognition

A Historical Account of Types of Fuzzy Sets and Their Relationships

In this paper, we review the definition and basic properties of the different types of fuzzy sets that have appeared up to now in the literature. We also analyze the relationships between them and enumerate some of the applications in which they have been used

Hybrid-fuzzy techniques with flexibility and attitudinal parameters for supporting early product design and reliability management

The main aim of the research work presented in this thesis is to define and develop novel Hybrid Fuzzy-based techniques for supporting aspects of product development engineering, specifically product reliability at the early phase of product design under the design for reliability philosophy and concept designs assessment problems when the required information is rough and incomplete. Thus, to achieve the above-stated aim, which has been formulated in the effort to filling the identified gaps in the literature which comprise of the need for a holistic, flexible and adjustable method to facilitate and support product design concept assessment and product reliability at the early product design phase. The need for the incorporation of the attitudinal character of the DMs into the product reliability and design concept assessment and finally, the need to account for the several interrelated complex attributes in the product reliability and design concept assessment process. A combination of research methods has been employed which includes an extensive literature review, multiple case study approach, and personal interview of experts, through which data were, collected that provided information for the real-life case study. With the new Hybrid Fuzzy-based techniques (i.e. the intuitionistic fuzzy TOPSIS model which is based on an exponential-related function (IF-TOPSISEF) and the Multi-attribute group decision-making (MAGDM) method which is based on a generalized triangular intuitionistic fuzzy geometric averaging (GTIFGA) operator), a more robust method for the product reliability and design concepts assessment respectively have been achieved as displayed in the comparative analysis in the thesis. The new methods have provided a more complete and a holistic view of the assessment process, by looking at the product reliability and design concept assessment from different scenario depending on the interest of the DMs. Using the above methods, the thesis has been able to evaluated some complex mechanical systems in literature and in real-life including Crawler Crane Machine and Forklift Truck for design change with the purpose of gaining appropriate reliability knowledge and information needed at the early product design phase, and that can subsequently aid and improve the product design concepts after all such useful information have been added into the new design. With the application of the new methods, and their proven feasibility and rationality as displayed in the assessment results of the complex mechanical systems in literature and that of the real-life case studies, this thesis, therefore, can conclude that the Hybrid Fuzzy-based techniques proposed, has provided a better and a novel alternative to existing product reliability and design concepts assessment methods

A Micro-Genetic Algorithm Approach for Soft Constraint Satisfaction Problem in University Course Scheduling

A university course timetabling problem is a combination of optimization problems. The problems are more challenging when a set of events need to be scheduled in the time slot, to be located to the suitable rooms, which is subjected to several sets of hard and soft constraints. All these constraints that exist as regulations within each resource for the event need to be fulfilled in order to achieve the optimum tasks. In addition, the design of course timetables for universities is a very difficult task because it is a non-deterministic polynomial, (NP) hard problem. This problem can be minimized by using a Micro Genetic Algorithm approach. This approach, encodes a chromosome representation as one of the key elements to ensure the infeasible individual chromosome produced is minimized. Thus, this study proposes an encoding chromosome representation using one-dimensional arrays to improve the Micro Genetic algorithm approach to soft constraint problems in the university course schedule. The research contribution of this study is in developing effective and feasible timetabling software using Micro Genetic Algorithm approach in order to minimize the production of an infeasible individual chromosome compared to the existing optimization algorithm for university course timetabling where UNITAR International University have been used as a data sample. The Micro Genetic Algorithm proposed has been tested in a test comparison with the Standard Genetic algorithm and the Guided Search Genetic algorithm as a benchmark. The results showed that the proposed algorithm is able to generate a minimum number of an infeasible individual chromosome. The result from the experiment also demonstrated that the Micro Genetic Algorithm is capable to produce the best course schedule to the UNITAR International University

Literature Review of the Recent Trends and Applications in various Fuzzy Rule based systems

Fuzzy rule based systems (FRBSs) is a rule-based system which uses linguistic fuzzy variables as antecedents and consequent to represent human understandable knowledge. They have been applied to various applications and areas throughout the soft computing literature. However, FRBSs suffers from many drawbacks such as uncertainty representation, high number of rules, interpretability loss, high computational time for learning etc. To overcome these issues with FRBSs, there exists many extensions of FRBSs. This paper presents an overview and literature review of recent trends on various types and prominent areas of fuzzy systems (FRBSs) namely genetic fuzzy system (GFS), hierarchical fuzzy system (HFS), neuro fuzzy system (NFS), evolving fuzzy system (eFS), FRBSs for big data, FRBSs for imbalanced data, interpretability in FRBSs and FRBSs which use cluster centroids as fuzzy rules. The review is for years 2010-2021. This paper also highlights important contributions, publication statistics and current trends in the field. The paper also addresses several open research areas which need further attention from the FRBSs research community.Comment: 49 pages, Accepted for publication in ijf

A process model for quality in use evaluation on clinical decision support systems

Developing or purchasing software is an expensive investment and needs to be justified. Furthermore, the software must be useful in its purpose, reliable, efficient and, among other characteristics, meet the expectations of users [1, 2]. It would be no different in the case of a clinical Decision Support System - CDSS. CDSS are systems developed to support clinicians and other health professionals in a medical decision making [3]. They are developed within a clinical context, following medical guidelines, with varied purposes such as diagnoses [4, 5, 6] patient monitoring [7, 8, 9], prevention [10] and disease treatment [11, 12]. Conversely, even with all the benefits offered by a CDSS, its acceptance in the medical field is still a matter of debate [13, 14]. The CDSS acceptance is linked to the perception of the end user, such as 1) the system’s ease of use and utility, 2) the quality of its results and its reliability [14], 3) the contextual accessibility of the system, sometimes not included in the health professional’s routine and workflow, and 4) the fact that numerous CDSSs are not integrated with existing systems [15]. One manner to extend the use and disseminate positive contributions of CDSSs to the medical world is to develop them in a reliable and useful way. For this, one must follow the best practices of software engineering (SE, acronym in English) [16] and be concerned with its quality, both in the design and development process and in its effective use. Evaluating the quality of the software is to measure its characteristics and sub-characteristics of quality. In order to better structure the assessment, a series of international standards, with models and frameworks, were developed for assisting software developers in assessing the quality of software products. The latest series is the ISO/IEC 25000 - System and Software Quality Requirements and Evaluation (SQuaRE) [17]. Two of the SQuaRE divisions are addressed in this thesis: 1) Division of quality models standard (ISO/IEC 25010) [18], and 2) Quality measurement division standard (ISO/IEC 25022) [19]. The ISO/IEC 25010 are divided in product quality model and the quality model in use. Quality in use (QiU), a model of ISO/IEC 25010, is the focus of this study, through its evaluation in the context of a CDSS. The quality in use model refers to the quality of the software when executed, mentioning the result of the interaction between users and the software system/product in a specific context. This model consists of five quality characteristics: • Effectiveness - means the level of precision and completeness with which users achieve their specific goals when using the system; • Efficiency - refers to the resources spent to achieve the goals and its measure is related to the level of effectiveness achieved with the consumed resources; • Satisfaction - refers to whether user requirements are satisfied in a particular context of system use; • Freedom from risk - refers to the degree to which the quality of a system reduces or avoids potential risks to human life, the economic situation, and health of the environment; • Context coverage - deals with the use of the system in all specific contexts and/or in contexts that extend beyond the initially identified contexts. Context completeness and flexibility are the sub-characteristics that represent context coverage. Thus, when measuring the quality of a CDSS, we must consider both the context of use and the choice of the characteristic and sub-characteristic that best suits the purpose of the measurement [20]. The QiU model provides a powerful contribution to the practice of evaluating a system and determining its quality. According to Harrison et al. [21], Effectiveness, Efficiency and Satisfaction are considered the key criteria to reflect the quality of use. Therefore, these QiU characteristics meet the needs and expectations of the users of the systems, in our case of CDSSs, as they consider the user experience. As a contribution, we proposed a process model to evaluate two QiU characteristics in a CDSS: satisfaction and efficiency. We believe these characteristics are important in the evaluation of a CDSS because, due to its links with the user experience and the usability of the system, when measured, can corroborate the quality of the CDSS and mitigate the non-use and non-acceptance of this type of software. Other contributions from our work are 1) in the academic context, a significant study in the area of software quality, focusing on its characteristics, especially on the quality in use. A guideline for collecting and measuring these characteristics was built into our process model; 2) in the area of software development, professionals can make use of a simple and adaptable process, applicable to other types of systems, to measure the quality-in-use characteristics of their products.Desenvolver ou adquirir software é um investimento caro e precisa ser justificado. Além de útil, o sistema deve ser confiável, eficiente e, entre outras características, atender às expectativas dos usuários [1, 2]. Não seria diferente no caso de um sistema de apoio à decisão clínica (CDSS, acrônimo em inglês), sistemas desenvolvidos para apoiar médicos e outros profissionais de saúde na tomada de uma decisão médica [3]. CDSSs são elaborados dentro de um contexto clínico, seguindo guidelines com propósitos variados, sejam para diagnósticos [4, 5, 6], acompanhamento do paciente [7, 8, 9], na prevenção [10] e tratamento de doenças [11, 12]. No entanto, apesar de todo os benefícios oferecidos por um CDSS, sua aceitação na área médica ainda é motivo de debate [13, 14]. Essa aceitação está ligada à percepção do usuário final, como 1) a facilidade de uso e utilidade do sistema; 2) a qualidade dos resultados produzidos e sua confiabilidade [14]; 3) a acessibilidade contextual do sistema, muitas vezes não incluída na rotina e no fluxo de trabalho do profissional de saúde, e 4) o fato de muitos CDSSs não estarem integrados aos sistemas existentes [15]. Uma forma de estender o uso de CDSSs e disseminar suas contribuições positivas entre os profissionais de saúde é garantir a confiabilidade de seus resultados e a satisfação do usuáriofinal. Para tal deve-se seguir as melhores práticas da engenharia de software (SE, acrônimo em inglês) em sua concepção [16]. Isso implica em preocupar-se com a qualidade do sistema tanto no processo do projeto e desenvolvimento quanto em sua efetiva utilização. Uma forma de certificar se um software obedece a essa premissa é realizando avaliações de qualidade. Avaliar a qualidade do software é medir suas características e subcaracterísticas de qualidade. Para uma melhor estruturação desta medição foram desenvolvidos séries de padrões internacionais como guidelines de avaliação de qualidade de produtos de software. A série mais recente trata-se da ISO/IEC 25000 System and Software Quality Requirements and Evaluation (SQUARE) [17]. Dois padrões desta série foram abordadas nesta tese, sendo 1) o modelos de qualidade de software e sistemas (ISO/IEC 25010) [18], no qual trabalhamos especificamente com o modelo de qualidade em uso, e 2) o padrão de medição da qualidade em uso (ISO/IEC 25022) [19]. Qualidade em uso é o foco desta tese, através de sua avaliação no contexto de utilização de um CDSS. O Modelo de qualidade em uso trata da qualidade do software quando em execução, referindose ao resultado da interação dos usuários e o software em um cenário específico. Este modelo é composto de cinco características de qualidade: • Eficácia (ou efetividade) - esta característica representa o nível de precisão e completude com que os usuários alcançam os objetivos específicos, durante a utilização do sistema ou produto de software; • Eficiência - sua medição representa o nível de eficácia alcançada em relação aos recursos consumidos para o alcance das metas; • Satisfação - trata do quanto as necessidades do usuário são satisfeitas dentro de um determinado contexto de uso do sistema ou produto de software. Esta característica é composta pelas subcaracterísticas Utilidade, Confiança, Prazer e Conforto do usuário em relação ao sistema; • Livre de risco - trata do grau em que a qualidade de um sistema ou produto permite mitigar ou evitar riscos potenciais à vida humana, à situação econômica, à saúde ou ao meio ambiente, sendo estas suas três subcaracterísticas; • Cobertura de contexto - trata do uso do sistema em todos os contextos específicos e/ou em contextos além dos inicialmente identificados, sendo composta pelas subcaracterísticas completude de contexto e flexibilidade do sistema. Assim, para se medir a qualidade de um CDSS deve-se considerar tanto o contexto de utilização quanto a escolha da característica e subcaracterística que melhor condizem ao propósito da avaliação [20]. De acordo com Harrison et al. [21], Eficácia, Eficiência e Satisfação são considerados os principais critérios a serem avaliados para refletir a qualidade de uso. Tais características de qualidades em uso refletem o atendimento das necessidades e expectativas dos usuários dos sistemas, em especial ao usuário primário ou final, uma vez que estão diretamente relacionadas com a experiência do usuário. O modelo de qualidade em uso fornece uma contribuição poderosa para a prática de avaliar um sistema e determinar sua qualidade. Como contribuição, propusemos um modelo de processo para avaliação de qualidade em uso de um CDSS através da medição, a priori, de duas características de qualidade - satisfação e eficiência. Acreditamos que tais características são importantes na avaliação de um CDSS devido estreita relação destas com a experiência do usuário-final e a usabilidade do sistema. Assim, quando mensuradas, tais características podem corroborar com a qualidade do CDSS e mitigar a não utilização e não aceitação desse tipo de software. Nosso modelo proposto é definido por cinco (5) fases, a saber: 1) Identificação de cenário e contexto de uso do sistema, 2) seleção das medidas, métricas e métodos para mensurar as características, 3) a medição da qualidade, 4) a análise dos valores encontrados na medição e 5) a apresentação dos resultados obtidos. O resultado da aplicação do modelo de processo traduz-se em um conjunto de informações que nortearão um melhoramento do software, caso a medição das características fique abaixo de um padrão pré-definido pelos atores envolvidos no processo de medição do sistema. Por outro lado, se a medição for positiva, isso vem ratificar a qualidade do sistema e ações poderão ser tomadas para disseminar esse bom resultado, buscando a adesão de mais utilizadores. Como forma de validação do modelo proposto, após sua utilização para identificação de cenários e contexto-de-uso possíveis de serem mensurados, foi apresentado um CDSS da área oncológica a profissionais de saúde, estudantes de medicina e profissionais da área de qualidade de software que, ao final de sua utilização, responderam a um inquérito com o objetivo de avaliar o sistema. A aplicação se deu de forma online, dado a necessidade de mantermos o distanciamento social e o de cumprirmos as orientações sanitárias. As respostas serviram como fonte de dados para a medição das características de qualidadeem- uso do sistema. Os resultados da aplicação revelou que nosso modelo de processo de avaliação é válido, relevante e de fácil utilização para identificar as características importantes em um sistema, bem como suas medições por meio das funções matemáticas do modelo ISO/IEC 25022. Outras contribuições do nosso trabalho, temos 1) no âmbito acadêmico, um estudo significativo na área de qualidade de software, com foco em suas características, especialmente na qualidade em uso. Uma guideline para a coleta e mensuração dessas características foi construída em nosso modelo de processo; 2) na área de desenvolvimento de software, os profissionais podem contar com um processo simples e adaptável, aplicável a outros tipos de sistema, para mensuração da qualidade em uso de seus produtos.The research has been partially funded by the FCT/MCTES through national funds, and when applicable, co-funded EU funds under the project UIDB/EEA/50008/2020 and Operação Centro 01-0145-FEDER-000019 – C4 – Centro de Competências em Cloud Computing, co-financed by the Programa Operacional Regional do Centro (CENTRO 2020), through the Sistema de Apoio à Investigação Científica e Tecnológica – Programas Integrados de IC&DT. I would also like to acknowledge the contribution of the COST Action IC1303: AAPELE—Archi- tectures, Algorithms and Protocols for Enhanced Living Environments and COST Action CA16226; SHELD-ON—Indoor living space improvement: Smart Habitat for the Elderly, supported by COST (European Cooperation in Science and Technology)

Machine Learning Aided Static Malware Analysis: A Survey and Tutorial

Malware analysis and detection techniques have been evolving during the last decade as a reflection to development of different malware techniques to evade network-based and host-based security protections. The fast growth in variety and number of malware species made it very difficult for forensics investigators to provide an on time response. Therefore, Machine Learning (ML) aided malware analysis became a necessity to automate different aspects of static and dynamic malware investigation. We believe that machine learning aided static analysis can be used as a methodological approach in technical Cyber Threats Intelligence (CTI) rather than resource-consuming dynamic malware analysis that has been thoroughly studied before. In this paper, we address this research gap by conducting an in-depth survey of different machine learning methods for classification of static characteristics of 32-bit malicious Portable Executable (PE32) Windows files and develop taxonomy for better understanding of these techniques. Afterwards, we offer a tutorial on how different machine learning techniques can be utilized in extraction and analysis of a variety of static characteristic of PE binaries and evaluate accuracy and practical generalization of these techniques. Finally, the results of experimental study of all the method using common data was given to demonstrate the accuracy and complexity. This paper may serve as a stepping stone for future researchers in cross-disciplinary field of machine learning aided malware forensics.Comment: 37 Page

Investigating Potential Interventions on disruptive impacts of Industry 4.0 technologies in Circular Supply chains: Evidence from SMEs of an Emerging Economy

As a transversal theme, the intertwining of digitalization and sustainability has crossed all Supply Chains (SCs) levels dealing with widespread environmental and societal concerns. This paper investigates the potential interventions and disruptive impacts that Industry 4.0 technologies may have on pharmaceutical Circular SCs (CSCs). To accomplish this, a novel method involving a literature review and Pythagorean fuzzy-Delphi has initially been employed to identify and screen categorized lists of Industry 4.0 Disruptive Technologies (IDTs) and their impacts on pharmaceutical CSC. Subsequently, the weight of finalized impacts and the performance score of finalized IDTs have simultaneously been measured via a novel version of Pythagorean fuzzy SECA (Simultaneously Evaluation of Criteria and Alternatives). Then, the priority of each intervention for disruptive impacts of Industry 4.0 has been determined via the Hanlon method. This is one of the first papers to provide in-depth insights into advancing the study of the disruptive action of Industry 4.0 technologies cross-fertilizing CE throughout pharmaceutical SCs in the emerging economy of Iran. The results indicate that digital technologies such as Big Data Analytics, Global Positioning Systems, Enterprise Resource Planning, and Digital Platforms are quite available in the Irans' pharmaceutical industry. These technologies, along with four available interventions, e.g., environmental regulations, subsidy, fine, and reward, would facilitate moving towards a lean, agile, resilient, and sustainable supply chain through the efficient utilization of resources, optimized waste management, and substituting the human workforce by machines

MITIGATE THE REAL POWER LOSSES IN RADIAL DISTRIBUTED NETWORK USING DG BY ABC ALGORITHM

Recently, integration of Distributed generation (DG) in distribution system has increased to high penetration levels. The impact of DG on various aspects of distribution system operation, such as reliability and energy loss depend highly on DG location in distribution feeder .Optimal DG placement plays an important role . This project presents a new methodology using Artificial Bee Colony  algorithm (ABC) to find the optimal size and optimum location for the placement of DG in the radial distribution networks for active power compensation by reduction in real power losses .The proposed technique is tested on standard IEEE-33 bus test system