Sharif Digital Repository

In this paper the setup assembly line balancing and scheduling problem (SUALBSP) is considered. Since this problem is NP-hard, a hybrid genetic algorithm (GA) is proposed to solve the problem. This problem involves assigning the tasks to the stations and scheduling them inside each station. A simple permutation is used to determine the sequence of tasks. To determine the assignment of tasks to stations, the algorithm is hybridized using a dynamic programming procedure. Using dynamic programming, at any time a chromosome can be converted to an optimal solution (subject to the chromosome sequence). Since population diversity is very important to prevent from being trapped in local optimum... 

Fuzzy rule-based classifiers are one of the famous forms of the classification systems particularly in the data mining field. Genetic algorithm is a useful technique for discovering this kind of classifiers and it has been used for this purpose in some studies. In this paper, we propose a new symbiotic evolutionary approach to find desired fuzzy rulebased classifiers. For this purpose, a symbiotic combination operator has been designed as an alternative to the recombination operator (crossover) in the genetic algorithms. In the proposed approach, the evolution starts from simple chromosomes and the structure of chromosomes gets complex gradually during the evolutionary process. Experimental... 

Scheduling projects incorporated with materials ordering results in a more realistic problem. This paper deals with the combined problem of project scheduling and material ordering. The purpose of this paper is to minimize the total cost of this problem by determining the optimal values of activity duration, activity finish time and the material ordering schedule subject to constraints. We employ a genetic algorithm approach to solve it. Elements of the algorithm, such as chromosome structure, unfitness function, crossover, mutation and local search operations are explained. The results of the experimentation are quite satisfactory  

In this paper, a genetic algorithm for solving a class of project scheduling problems, called Resource Investment Problems, is presented. Tardiness of the project is permitted with a defined penalty. The decision variables are the level of resources and the start times of the activities. The objective is to minimize the sum of resources and delay penalty costs, subject to the activities' precedence relations and some other constraints. A revised form of the Akpan heuristic method for this problem is used to find better chromosomes. Elements of the algorithm, such as chromosome structure, unfitness function, crossover, mutation, immigration and local search operations, are explained. The... 

Local three-stranded DNA/RNA hybrid regions of genomes (R-loops) have been detected either by binding of a monoclonal antibody (DRIP assay) or by enzymatic recognition by RNaseH. Such a structure has been postulated for mouse and human telomeres, clearly suggested by the identification of the complementary RNA Telomeric repeat-containing RNA “TERRA”. However, the tremendous disparity in the information obtained with antibody-based technology drove us to investigate a new strategy. Based on the observation that DNA/RNA hybrids in a triplex complex genome co-purify with the double-stranded chromosomal DNA fraction, we developed a direct preparative approach from total protein-free cellular... 

LBP coefficients are essential and determine the priority of gray differences. The objectives of this paper are to reveal this and propose a method for finding an optimal priority through the genetic algorithm. On the other hand, the genetic operators such as initialization and cross-over operators, generate invalid coefficients, defective chromosomes. This paper also recommends a rectifying method for correcting defective chromosomes. Results on the FERET and Extended Yale B datasets indicate that the proposed method has markedly higher recognition rates than LBP. © 2017 IEEE  

Ground-state pluripotency is a cell state in which pluripotency is established and maintained through efficient repression of endogenous differentiation pathways. Self-renewal and pluripotency of embryonic stem cells (ESCs) are influenced by ESC-associated microRNAs (miRNAs). Here, we provide a comprehensive assessment of the “miRNome” of ESCs cultured under conditions favoring ground-state pluripotency. We found that ground-state ESCs express a distinct set of miRNAs compared with ESCs grown in serum. Interestingly, most “ground-state miRNAs” are encoded by an imprinted region on chromosome 12 within the Dlk1-Dio3 locus. Functional analysis revealed that ground-state miRNAs embedded in the... 

Analyzing the features of the chromosomes can be very useful for diagnosis of many genetic disorders or prediction of the possible abnormalities that may occur in the future generations. For this purpose, karyotype is often used which to make it, there is necessary to identify each one of the 24 chromosomes from the microscopic images. Definition and extraction of the morphological and band pattern based features for each chromosome is the first step to identify them. An important class of the morphological features is the location of the chromosome's centromere. Thus, centromere localization is an initial step in designing an automatic karyotyping system. In this paper, a novel algorithm... 

Bioinspired materials can mimic the stem cell environment and modulate stem cell differentiation and proliferation. In this study, biomimetic micro/nanoenvironments were fabricated by cell-imprinted substrates based on mature human keratinocyte morphological templates. The data obtained from atomic force microscopy and field emission scanning electron microscopy revealed that the keratinocyte-cell-imprinted poly(dimethylsiloxane) casting procedure could imitate the surface morphology of the plasma membrane, ranging from the nanoscale to the macroscale, which may provide the required topographical cell fingerprints to induce differentiation. Gene expression levels of the genes analyzed... 

Karyotype is a genetic test that is used for detection of chromosomal defects. In a karyotype test, an image is captured from chromosomes during the cell division. The captured images are then analyzed by cytogeneticists in order to detect possible chromosomal defects. In this paper, we have proposed an automated pipeline for analysis of karyotype images. There are three main steps for karyotype image analysis: image enhancement, image segmentation and chromosome classification. In this paper, we have proposed a novel chromosome segmentation algorithm to decompose overlapped chromosomes. We have also proposed a CNN-based classifier which outperforms all the existing classifiers. Our... 

Alzheimer’s disease (AD) is an irreversible neurological disorder that progresses gradually and can cause severe cognitive and behavioral impairments. This disease is currently considered a social and economic incurable issue due to its complicated and multifactorial characteristics. Despite decades of extensive research, we still lack definitive AD diagnostic and effective therapeutic tools. Consequently, one of the most challenging subjects in modern medicine is the need for the development of new strategies for the treatment of AD. A large body of evidence indicates that amyloid-β (Aβ) peptide fibrillation plays a key role in the onset and progression of AD. Recent studies have reported... 

Karyotyping, is the process of classification of human chromosomes within the microscopic images. This is a common task for diagnosing many genetic disorders and abnormalities. Automatic Karyotyping algorithms usually suffer the poor quality of the images due to the non rigid nature of the chromosomes which makes them to have unpredictable shapes and sizes in various images. One of the main problems that usually need operator's interaction is the identification and separation of the overlapping/touching chromosomes. This paper presents an effective algorithm for identification of any cluster of the overlapping/touching chromosomes together with the number of chromosomes in the cluster, which... 

High reliability and low power consumption are among the major requirements in design of wireless sensor networks (WSNs). In this paper, a multi-objective problem is formulated as a Joint Power consumption and data Reliability (JPR) optimization problem. For this purpose, a connected dominating set (CDS)-based topology control approach is proposed. Our objective is to self-organize the network with minimum interference and power consumption. We consider the power changes into a topology with minimum CDS infrastructure subject to connectivity constraints. Since this problem is NP-hard, it cannot be dealt with using polynomial-time exact algorithms. Therefore, we first present a genetic... 

Wireless sensor networks consist of a large number of nodes which are distributed sporadically in a geographic area. The energy of all nodes on the network is limited. For this reason, providing a method of communication between nodes and network administrator to manage energy consumption is crucial. For this purpose, one of the proposed methods with high performance, is clustering methods. The big challenge in clustering methods is dividing network into several clusters that each cluster is managed by a cluster head (CH). In this paper, a centralized genetic-based clustering (CGC) protocol using onion approach is proposed. The CGC protocol selects the appropriate nodes as CHs according to... 

Evolutionary Algorithms are vastly used in development of rule based classifier systems in data mining where the rule base is usually a set of If-Then rules and an evolutionary trait develops and optimizes these rules. Genetic Algorithm is usually a favorite solution for such tasks as it globally searches for good rule-sets without any prior bias or greedy force, but it is usually slow. Also, designing a good genetic algorithm for rule base evolution requires the design of a recombination operator that merges two rule bases without disrupting the functionalities of each of them. To overcome the speed problem and the need to design recombination operator, this paper presents a novel algorithm... 

Recombination in Genetic Algorithms (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations, hopefully producing an offspring that has the good characteristics of both parents, and this requires explicit chromosome and recombination, operator by design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination, and by using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets: combinatorial optimization category, deceptive problems, and fully deceptive... 

Recombination in the Genetic Algorithm (GA) is supposed to extract the component characteristics from two parents and reassemble them in different combinations hopefully producing an offspring that has the good characteristics of both parents and this requires explicit chromosome and recombination operator design. This paper presents a novel evolutionary approach based on symbiogenesis which uses symbiotic combination instead of sexual recombination and using this operator, it requires no domain knowledge for chromosome or combination operator design. The algorithm is benchmarked on three problem sets, combinatorial optimization, deceptive, and fully deceptive, and is compared with standard... 

Background: Long reads provide valuable information regarding the sequence composition of genomes. Long reads are usually very noisy which renders their alignments on the reference genome a daunting task. It may take days to process datasets enough to sequence a human genome on a single node. Hence, it is of primary importance to have an aligner which can operate on distributed clusters of computers with high performance in accuracy and speed. Results: In this paper, we presented IMOS, an aligner for mapping noisy long reads to the reference genome. It can be used on a single node as well as on distributed nodes. In its single-node mode, IMOS is an Improved version of Meta-aligner (IM)... 

Supercoiled DNA, crumpled interphase chromosomes, and topologically constrained ring polymers often adopt treelike, double-folded, randomly branching configurations. Here we study an elastic lattice model for tightly double-folded ring polymers, which allows for the spontaneous creation and deletion of side branches coupled to a diffusive mass transport, which is local both in space and on the connectivity graph of the tree. We use Monte Carlo simulations to study systems falling into three different universality classes: ideal double-folded rings without excluded volume interactions, self-avoiding double-folded rings, and double-folded rings in the melt state. The observed static properties...