Search

This work deals with the analysis of Kabsch and quaternion algorithms, which may be used for 3D superimposition of molecules by rigid roto-translation in computational chemistry and biology. Both algorithms, which are very important for in silico drug design, were studied from the point of view of their non-trivial mathematical structure. Their computational complexity was investigated by a superimposition of various random pseudo-molecules with 2 – 100,000 atoms in Matlab. It was found that both proposed algorithm implementations exhibit the same asymptotic time computational complexity of O(n), with the quaternion algorithm involving a higher number of floating-point operations (FLOPs) and showing lower computational performance in terms of serial CPU time.

Medical image processing is a highly challenging research area, thus medical imaging techniques are used to make diagnosis in human body. Moreover, as tumor in the brain is a critical and medical complaint, segmentation of the images has an important role to make segmentation of the brain tumor and it provides suspicious region diagnosis from the medical images. By the help of MRI scanners, signals generated by the human body tissues could be detected and determined spatially. Thus, we in this paper try to propose basics of MRI image modalities as a guide for understanding the processes and methods. Since original brain image is not appropriate for the examination, segmentation of the images could be very useful method for partition of the digital image into similar regions. This research also presents a guide for understanding the brain MRI sequences in other words modalities.

Parallel processing is an execution of processes that make computation and calculation on many things simultaneously. In addition, parallel processing methods are applied extensively to the examination of MR imaging in treatment. As parallel computer systems become larger and faster at the present time; scientists, researchers and engineers are eventually able to find solutions to the problems in medicine, which had been taken too long to run before. Therefore, various fields including medicine and bioinformatics have already taken the advantages of parallel processing. In this review study, we deal with analyzing key concepts and eminent parallel processing methods that have been used to analyze the brain MRI images. In addition to this, we indicate great number of examples from the current literature in a comprehensive literature matrix. Based on the literature matrix that is created according to the Web of Science analysis, information graphics are presented in a comprehensive manner. As a result, parallel processing methods in brain magnetic resonance imaging offer powerful replacements to computer clusters in order to run large, disseminated solicitations.

Thermal radiation generated by limited resources is emitted from the surfaces and interpreted as temperature. On the other hand, the limited resources necessitate prevention of energy leakages causing noticeable temperature differences on surfaces. Providing sensitive information on temperature contrast, infrared thermography (IRT) is a prominent tool for detecting infrared energy on the surfaces of the objects. IRT is also very promising method for detecting thermal irregularities, air leakages and even moisture abnormalities on building envelopes. Since the concept of nearly zero energy buildings is to be the main target of energy policies in European Union published by European Commission, improving thermal performance of buildings becomes crucial in the last decade. Therefore, implementation of IRT for visualizing and analyzing concealed defects on building envelopes is very promising for improving the energy efficiency of buildings. Given recent regulations and benefits of emerging thermogram technologies mentioned above, a detailed review of the previous studies investigating the abnormalities of building envelopes by IRT is presented in this paper. Furthermore, the applications with measurement methods, analysis schemes and analysis types are classified to highlight the potential of IRT in inspection of building envelopes for providing energy efficient solutions. Finally, recent advances and practical future opportunities are presented for additional contribution of the IRT methods previously employed.

Infrared thermography (IRT) is a non-destructive imaging technique that is used for revealing temperature differences on the surfaces of the human body or objects. Once it is used for biomedical purpose, it measures the emitted radiation on the surfaces of the human body. We, in this research, present Biomedical Infrared Thermography (B-IRT) applications with various measurement methods, analysis types, analysis schemes and study types from the existing literature in a detailed literature matrix. A mini-review of 30 studies from the literature are summarized through focusing on substantial features and backgrounds. Finally, recent advances and future opportunities are also presented to highlight high potential use of IRT in biomedical applications.

As integrated components of the building envelopes, shading devices are the elements designed for stopping excessive amount of direct and indirect sunlight passing through and for avoiding undesirable admission of light into glazed buildings. Shading devices also reduce the operational cost of active systems, mostly heating and cooling, by providing considerable energy saving without completely blocking the daylight. However, the conventional shading device types in real world applications and even the ones presented in the literature stick to non-amorphous shapes providing limited improvement of the energy performance with negligible rates. Considering the lack of amorphous solutions in the literature, we propose novel design alternatives of energy-efficient shading device with panels in amorphous forms generated by parametric modeling and performance evaluation-based optimization in contrast with the conventionally designed structures. Initially, a performance evaluation-based optimization model was developed by employing evolutionary multi-objective optimization algorithms to overcome the complexity of the design process. Moreover, minimization of TEC (Total Energy Consumption) and maximization of the UDI (Useful Daylight Illuminance) are defined as the main objective functions to be optimized by non-dominated sorting genetic algorithm (NSGA II) and self-adaptive continuous genetic algorithm with differential evolution (JcGA-DE) in the shading model. According to the numerical results of the annual energy consumption, we managed to reach considerable energy saving up to 14%, while keeping the daylight availability above 50%. SPEV project "Smart Solutions in Ubiquitous Computing Environments", University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic [UHK-FIM-SPEV-2019] The work and the contribution were supported by the SPEV project "Smart Solutions in Ubiquitous Computing Environments", University of Hradec Kralove, Faculty of Informatics and Management, Czech Republic (under ID: UHK-FIM-SPEV-2019). WOS:000471087200010 Q2

Floating neighborhoods are innovative and promising urban areas for challenges in the development of cities and settlements. However, this design task requires a lot of considerations and technical challenges. Computational tools and methods can be beneficial to tackle the complexity of floating neighborhood design. This paper considers the design of a self-sufficient floating neighborhood by using computational intelligence techniques. In this respect, we consider a design problem for locating each neighborhood function in each cluster with a certain density within a floating neighborhood. In order to develop a self-sufficient floating neighborhood, we propose multi-objective evolutionary algorithms, namely, a self-adaptive real-coded genetic algorithm (CGA) as well as a self-adaptive real-coded genetic algorithm (CGA_DE) employing mutation operator of differential evolution algorithm. The only difference between CGA and CGA_DE is the fact that CGA uses random immigration of certain individuals into the population as a mutation operator whereas in the mutation phase of CGA_DE algorithm, the traditional mutation operator DE/rand/1/bin of DE algorithms. The arrangement of individual functions to develop each neighborhood function is further elaborated and formed by using Voronoi diagram algorithm. An application to design a self-sufficient floating neighborhood in Urla district, which is on the west coast of Turkey, Izmir, is presented.

Many countries around the world are confronted with the challenge of decreasing energy consumption, while the use of electrical appliances is continuously increasing in buildings. The requirement to minimize the energy consumption can be fulfilled by revaluating architectural aspects. One of these aspects is related to overheating problems, caused by facades with large, glazed portions. In such designs, shading elements must carefully be integrated and considered at an early-design stage in the design process. Shading of buildings is crucial especially in climates with hot summer. It is significant to protect the window from solar radiation in summer while allowing maximum solar radiation in winter. For this reason, precise figures of their performance are needed. As such, simulation tools are often used for identifying the most suitable shading element that suits the building. In literature, there are many studies that have been done to designate the energy performance of shading devices in buildings by using simulation tools. This study focuses both on the shading device types used in the building sector and the previous studies done for designating the performance aspects of different shading devices types. Numerous studies for different building types located in different climatic regions have been reviewed in order to underline the importance of simulation modeling for shading devices in buildings.

Architectural design is a process that considers many objectives to satisfy. In general, these objectives are conflicting with each other. On the other hand, many design parameters are associated with these conflicting objectives, too. Therefore, architectural design is described as a complex task. To handle the complexity, computational optimization methods can be employed to investigate architectural design process in detail. This paper focuses on investigating Pareto-front solutions for theatre hall design using multi-objective evolutionary algorithms. To formulate the theatre hall acoustic design problem, we consider three objectives. Two objectives are minimization of both reverberation time, and total initial cost whereas the third objective is the maximization of seating capacity. In addition, several designs and acoustical performance constraints are defined. To tackle this problem, a multi-objective self-adaptive differential evolution algorithm (JDEMO) is proposed and compared with a well-known non-dominated sorting genetic algorithm-II (NSGA-II) from the literature. Computational results show that the proposed JDEMO algorithm achieves competitive results when compared to the NSGA-II.

An implementation of multi-objective optimization for design of an office room is presented through maximizing illuminance value and minimizing cooling energy consumption on a summer extreme day in a Mediterranean hot climate region. Existing literature shows different examples of multi-objective optimization problems in the field of performance-based building design. Principally, performance criteria such as energy and daylight should be integrated in the early stage of the conceptual design phase to provide energy-efficient solutions in buildings. Since most of the architectural design problems are difficult to solve, multi-objective optimization methods provide many design solutions to the decision makers. We used Non-Dominated Sorting Genetic Algorithm II namely NSGA-II to present many design alternatives by satisfying two conflicting objectives at the same time in the presented office room problem.

The aim of the research is to find a feasible set of theatre hall design alternatives for two objectives, which are the total cost and the reverberation time, subject to several constraints. We formulate the problem as a multi-objective realparameter constrained optimization problem. To handle this problem, we investigated two different optimization algorithms, namely, a Non-Dominated Sorting Genetic Algorithm II (NSGA-II) and a multi-objective Harmony Search algorithm (MOHS) in order to gather Pareto front approximation with a set of non-dominated solutions. We demonstrate that the MOHS yields slightly better results than the NSGA-II algorithm.