Selforganizology (ISSN 2410-0080)
http://www.iaees.org/publications/journals/selforganizology/selforganizology.asp
International Academy of Ecology and Environmental SciencesSelforganizology (ISSN 2410-0080); Publisher: International Academy of Ecology and Environmental Sciences; Address: Address: Unit 3, 6/F., Kam Hon Industrial Building, 8 Wang Kwun Road, Kowloon Bay, Hong Kong; Tel: 00852-2138 6086; Fax: 00852-3069 1955; E-mail: office@iaees.orgWhat is RSS
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Selforganizology
http://www.iaees.org/publications/journals/selforganizology/online-version.asp
International Academy of Ecology and Environmental Sciences
Without external forces and instructions, a dissipative system far away from equilibrium may spontaneuously evolve toward one or more steady states through between-component interactions at different hierarchies. This is a self-organization process. Self-organization is considered as a universe mechanism in nature. The fundamental science, selforganizology, has been proposed for finding and creating theories and methods from self-organization phenomena in nature, simulating and reconstructing self-organization phenomena, exploring mechanisms behind numerous self-organization phenomena, and promoting the applications of self-organization theories methods in science and industry. Selforganizology is a science that deals with self-organization. Many properties, principles, theories and methods on self-organization hold in this science. The theory of dissipative structures and stability theory are two of the fundamental theories in selforganizology. Some theories and methods should be futher improved. Evolution-, interaction-, behavior-, organization-, intelligence- and feedback-based theories, such as coevolution theory, coextinction theory, community succession theory, correlation analysis, parrondo paradox, game theory, neural networks, artificial intelligence, behavioral theory, organization theory and automation theory in various scientific disciplines can be reviewed, revised and introduced to selforganizology.
The Selforganizology (ISSN 2410-0080) is an open access, peer/open reviewed online journal that considers scientific articles in all different areas of selforganizology. The goal of this journal is to keep a record of the state-of-the-art research and promote the research work in these fast moving areas. The topics to be covered by Selforganizology include, but are not limited to:
innovative theories and methods on self-organization; Applications of evolution-, interaction-, behavior-, organization-, intelligence- and feedback-based theories, such as coevolution theory, coextinction theory, community succession theory, correlation analysis, parrondo's paradox, game theory, neural networks, artificial intelligence, behavioral theory, organization theory, and automation theory, in self-organization; simulation and modeling of self-organizing systems; algorithms of self-organization, including intelligence computation (swarm intelligence algorithms, genetic algorithms, etc.), cellular automata, self-adaptation and automation, etc., and various self-organization phenomena in nature. We are particullarly interested in short communications that clearly address a specific issue or completely describe a new self-organization phenomena.
The influence of deterministic and stochastic waiting time for triggering mortality and colonization events on the coexistence of cooperators and defectors in an evolutionary game model
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/coexistence-of-cooperators-and-defectors-in-evolutionary-game-model.pdf
YouHua Chen.Selforganizology,2014,1(1):1-7
In the present report, the coexistence of Prisoners' Dilemma game players (cooperators and defectors) were explored in an individual-based framework with the consideration of the impacts of deterministic and stochastic waiting time (WT) for triggering mortality and/or colonization events. For the type of deterministic waiting time, the time step for triggering a mortality and/or colonization event is fixed. For the type of stochastic waiting time, whether a mortality and/or colonization event should be triggered for each time step of a simulation is randomly determined by a given acceptance probability (the event takes place when a variate drawn from a uniform distribution [0,1] is smaller than the acceptance probability). The two strategies of modeling waiting time are considered simultaneously and applied to both quantities (mortality: WTm, colonization: WTc). As such, when WT (WTm and/or WTc) is an integral >=1, it indicated a deterministically triggering strategy. In contrast, when 1>WT>0, it indicated a stochastically triggering strategy and the WT value itself is used as the acceptance probability. The parameter space between the waiting time for mortality (WTm-[0.1,40]) and colonization (WTc-[0.1,40]) was traversed to explore the coexistence and non-coexistence regions. The role of defense award was evaluated. My results showed that, one non-coexistence region is identified consistently, located at the area where 1>=WTm>=0.3 and 40>=WTc>=0.1. As a consequence, it was found that the coexistence of cooperators and defectors in the community is largely dependent on the waiting time of mortality events, regardless of the defense or cooperation rewards. When the mortality events happen in terms of stochastic waiting time (1>=WTm>=0.3), extinction of either cooperators or defectors or both could be very likely, leading to the emergence of non-coexistence scenarios. However, when the mortality events occur in forms of relatively long deterministic waiting time, both defectors and cooperators could coexist, regardless of the types of waiting time for colonization events. Defense (or cooperation) rewards could determine the persistence time of both game players. When the defense reward is low, cooperators could persist better in the simulation. But when the defense reward becomes sufficiently higher, defectors would persist better. Overall, non-coexistence of cooperators and defectors in the present evolutionary game model is dependent on the stochastic mortality events, but not colonization events. In conclusion, my present study quantifies the influence of the temporally fluctuating motility-colonization dynamic on modeling the coexistence of species in the spatial evolutionary game.
Invertebrate diversity classification using self-organizing map neural network: with some special topological functions
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/self-organizing-map-neural-network-with-some-special-topological-
functions.pdf
WenJun Zhang, QuHuan Li.Selforganizology,2014,1(1):8-15
In present study we used self-organizing map (SOM) neural network to conduct the non-supervisory clustering of invertebrate orders in rice field. Four topological functions, i.e., cossintopf, sincostopf, acossintopf, and expsintopf, established on the template in toolbox of Matlab, were used in SOM neural network learning. Results showed that clusters were different when using different topological functions because different topological functions will generate different spatial structure of neurons in neural network. We may chose these functions and results based on comparison with the practical situation.
A framework for agent-based modeling of community assembly and succession
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/a-framework-for-agent-based-modeling.pdf
WenJun Zhang.Selforganizology,2014,1(1):16-22
Ecological communities are self-adaptive systems. Community assembly and succession is a self-organizing process. It is generated from multiple species invasions, selection, adaptation and optimization. A framework for agent-based modeling of community assembly and succession was presented in this paper. Species agents,
space agents, functional agents and their behaviors were defined. Major procedures for agent-based modeling of community assembly and succession were proposed.
A review on biological adaptation: with applications in engineering science
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/a-review-on-biological-adaptation.pdf
LiMin Luo, WenJun Zhang.Selforganizology,2014,1(1):23-30
Biological adaptation refers to that organisms change themselves at morphological, physiological, behavioral and molecular level to better survive in a changing environment. It includes phenotype adaptation and molecular adaptation. Biological adaptation is a driving force of evolution. Biological adaptation was described from Darwinian theory of evolution to the theory of molecular evolution in present paper. Adaptive control and adaptive filtering were briefly described also.
Selforganizology: A more detailed description
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/selforganizology.pdf
WenJun Zhang.Selforganizology,2014,1(1):31-46
Selforganizology is a science on self-organization. It was first proposed by the author in 2013. Theories and methods of selforganizology should be continuously revised and improved. More details on selforganizology were described in present report as compared to the original study.
A review on the book, Self-organization: Theories and Methods
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(1)/bookreview.pdf
Jing Luo.Selforganizology,2014,1(1):47-50
The book, Self-organization: Theories and Methods, edited by WenJun Zhang and published by Nova Science Publishers, USA, was briefly reviewed in present report.
Structure and dynamics of Lithocolletis ringoniella-Parasitoids food web in
apple orchards of Shaanxi, China
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(2)/structure-and-dynamics-of-food-web.pdf
Xin Li, YuYu Liu.Selforganizology,2014,1(2):51-61
The formation and evolution of food web is a self-organizing process. A food web, L. ringoniella-Parasitoids food web, was proposed in present study. With the apple pest Lithocolletis ringoniella as the basic host, four parasitoids, Apanteles theivorae, Sympiesis sericeicornis, Ageniaspis testaceipes, and Sympiesis Foerst are included in the food web. In this food web, A. theivorae and A. testaceipes are primary parasitoids of L. ringoniella. A. theivorae mainly parasitizes apodous larva of L. ringoniella while A. testaceipes only chooses L. ringoniella egg to parasitize (egg-larva endoparasitization). S. Foerst and S. sericeicornis are facultative hyper-parasitoids. They can parasitize not only the larvae and pupae of L. ringoniella, but also A. theivorae. S. sericeicornis can be hyper-parasitized by S. Foerst. The occurrence mechanism and population dynamics of L. ringoniella and parasitoids, and parasitization effect of parasitoids in apple orchards of Shaanxi, China, were described in detail.
Two-dimensional ordered cluster analysis of component groups in
self-organization
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(2)/two-dimensional-ordered-cluster-analysis.pdf
WenJun Zhang, YanHong Qi, ZhiGuo Zhang.Selforganizology,2014,1(2):62-77
An algorithm for two-dimensional cluster analysis of component groups, originally from Zhang et al., (2004), was introduced in this study. The algorithm composes of three procedures, i.e., calculation of distance measures, randomization statistic test, and ordered clustering of components.
Diversity and aggregation patterns of plant species in a grass
community
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(2)/diversity-and-aggregation-patterns-of-plant-species.pdf
Ran Li, DanTing Chen, GongWei Liang, Wei Huang, HanQing Li, AiJuan Li, PengHui Huang, BiNi Chen, Bing Chen, Liang Chen, LinXing Chen, ShaoJing Chen, QinSon Wang, HeCon Wang, Jing Wang, CiHui Wu, YuanHui Xu, WenJun Zhang.Selforganizology,2014,1(2):78-88
Both composition and aggregation patterns of species in a community are the outcome of community self-organizing. In this paper we conducted analysis on species diversity and aggregation patterns of plant species in a grass community, Zhuhai, China. According to the sampling survey, in total of 47 plant species, belonging to 16 families, were found. Compositae had 10 species (21.3%), seconded by Gramineae (9 species, 19.1%), Leguminosae (6 species, 12.8%), Cyperaceae (4 species, 8.5%), and Malvaceae (3 species, 6.4%). The results revealed that the means of aggregation indices I-delta, I and m*/m were 21.71, 15.71 and 19.89 respectively and thus individuals of most of plant species strongly followed aggregative distribution. Iwao analysis indicated that both individuals of all species and clumps of all individuals of all species followed aggregative distribution. Taylor's power law indicated that individuals of all species followed aggregative distribution and aggregation intensity strengthened as the increase of mean density. We held that the strong aggregation intensity of a species has been resulted from the strong adaptation ability to the environment, the strong interspecific competition ability and the earlier establishment of the species. Fitting goodness of the mean, I, I-delta, m*/m with probability distributions demonstrated that the mean (density), I, I-delta, and m*/m over all species followed Weibull distribution rather than normal distribution. Lophatherum gracile, Paederia scandens (Lour.) Merr., Eleusine indica, and Alternanthera philoxeroides (Mart.) Griseb. were mostly aggregative, and Oxalis sp., Eleocharis plantagineiformis, Vernonia cinerea (L.) Less., and Sapium sebiferum (L.) Roxb, were mostly uniform in the spatial distribution. Importance values (IV) showed that Cynodon dactylon was the most important species, seconded by Desmodium triflorum (L.) DC., Cajanus scarabaeoides (L.) Benth., Paspalum scrobiculatum L., and Rhynchelytrum repens. Oxalis sp., Eleocharis plantagineiformis, and Vernonia cinerea (L.) Less. were the least important species in the community. Summed dominance ratio (SDR2) revealed that Cynodon dactylon and Desmodium triflorum (L.) DC. were the most dominant species in the community, followed by Rhynchelytrum repens, Paspalum scrobiculatum L., and Cajanus scarabaeoides (L.) Benth.
Interspecific associations and community structure: A local survey
and analysis in a grass community
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(2)/interspecific-associations-and-community-structure-local-survey.pdf
WenJun Zhang.Selforganizology,2014,1(2):89-129
Interspecific associations in the plant community may help to understand the self-organizing assembly and succession of the community. In present study, Pearson correlation, net correlation, Spearman rank correlation, and point correlation were used to detect the interspecific (inter-family) associations of grass species (families) using the sampling data collected in a grass community of Zhuhai, China. We found that most associations between grass species (families) were positive associations. The competition/interference/niche separation between grass species (families) was not significant. A lot of pairs of grass species and families with statistically significant interspecific (inter-family) associations based on four correlation measures were discovered. Cluster trees for grass species/families were obtained by using cluster analysis. Relationship among positive/negative associations, interspecific relationship and community succession/stability/robustness was discussed. I held that species with significant positive or negative associations are generally keystone species in the community. Although both negative and positive associations occur in the community succession, the adaptation and selection will finally result in the successful coexistence of the species with significant positive associations in the climax community. As the advance of community succession, the significant positive associations increase and maximize in climax community, and the significant negative associations increase to a maximum and then decline into climax community. Dominance of significant positive associations in the climax community means the relative stablility and equilibrium of the community. No significant associations usually account for the majority of possible interspecific associations at each phase of community succession. They guarantee the robustness of community. They are candidates of keystone species. Lose of some existing keystone species might be filled with some species previously with no significant associations. In addition, a Java program, associCoeff, re-writed from my earlier work, was introduced. A large number of data were thus given also.
A review on the book, Ecological Modeling
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(2)/book-review.pdf
GuangHua Liu.Selforganizology,2014,1(2):130-137
The book, Ecological Modeling, edited by WenJun Zhang and published by Nova Science Publishers, USA, was briefly reviewed in present report.
Pattern classification of HLA-DRB1 alleles, human races and populations: Application of self-organizing competitive neural network
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(3-4)/pattern-classification-of-HLA-DRB1-alleles.pdf
WenJun Zhang, YanHong Qi.Selforganizology,2014,1(3-4):138-142
HLA-DRB1 gene is concerned with human immune systems. There are about 300 alleles of HLA-DRB1 gene. The self-organizing competitive neural network was used in present study to make non-supervisory classification on 14 HLA-DRB1 alleles, and 54 human races and populations (Zhang and Qi, 2005). It was found that HLA-DRB1-0901 and 1402 are similar to each other in the distribution in human races and populations. There were higher similarity between HLA-DRB1-0101 and 0302, and between HLA-DRB1-0701 and 0301. The results showed that there were significant differences among the various races and there were similarities among populations in the same race. South America Indians and Siberians are highly similar to each other. There was relatively significant difference between Northern Chinese and Southern Chinese. Han Chinese in Guangdong was similar to ethnic minorities such as the Lahu Chinese and Yao Chinese.
Interspecific associations of weed species around rice fields in Pearl
River Delta, China: A regional survey
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(3-4)/.pdf
WenJun Zhang, Rui Wang, DanLin Zhang, Wu Wei, HaiDong Chen.Selforganizology,2014,1(3-4):143-205
Determination of interspecific associations contributes to understand the assembly and succession of community, a self-organizing process. In present study, point correlation, Spearman rank correlation, and Pearson correlation were used to detect the interspecific (inter-family) associations of weed species (families) using the sampling data (55 samples, each with the size of 2m by 2m) collected around rice fields in Pearl River Delta (Zhuhai, Zhongshan, Dongguan, and Guangzhou), China. The results showed that most of the associations between weed species/families were positive associations. The competition/interference/niche separation between weed species/families was not significant. Combing the conclusion of RPH test, we concluded that the positive associations may largely result from similar requirements to environmental conditions. A lot of pairs of weed species and families with statistically significant interspecific/inter-family associations based on three correlation measures were discovered. Major species and families that determine between-sample variation was detected by using PCA. It is a data type paper. A large number of data were thus given also.
A mini review on theories and measures of interspecific associations
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(3-4)/theories-and-measures-of-interspecific-associations.pdf
Malhaba Maihaiti, WenJun Zhang.Selforganizology,2014,1(3-4):206-210
Ecological community is a self-organizing system. Interspecific association is the conceptual basis of direct or indirect interactions between species. In present paper we made a brief review on theories and methods of interspecific associations. Some measures for interspecific associations were given.
A new game theory algorithm simulates soccer matches: Reducing
complexity to its irreducible essence
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(3-4)/a-new-game-theory-algorithm-simulates-soccer-matches.pdf
Alessandro Ferrarini.Selforganizology,2014,1(3-4):211-218
How much complex is a human event like a soccer match? How much difficult is to predict its result? Can we disentangle the complexity behind such event? In this work, I state that the use of multiagent systems to simulate soccer events is improper: too many possible space-time configurations are possible, and the resulting complexity is unimaginable. A proper way to simulate such complex event is to turn its complexity into its irreducible essence. When such irreducible essence is tamed, stochasticity and iteration can then be added. I describe here in outline a math algorithm, named Soccer-Decoder and implemented through the software Soccer-Lab, that is based on game theory and differential calculus and that exactly does this: 1) it turns the complexity of a soccer match into its irreducible and structural essence, 2) it simulates soccer matches by adding stochasticity and iteration to such structural essence. An illustrative example is given. The philosophy on the underside of Soccer-Decoder is that even very complex real world events, when transformed into their irreducible essence, can be understood and predicted.
A review on the book, Grasslands: Types, Biodiversity and Impacts
http://www.iaees.org/publications/journals/selforganizology/articles/2014-1(3-4)/bookreview.pdf
GuangHua Liu.Selforganizology,2014,1(3-4):219-223
The book, Grasslands: Types, Biodiversity and Impacts, edited by WenJun Zhang and published by Nova Science Publishers, USA, was briefly reviewed in present report.
Connecting game theory and evolutionary network control for the
computational control of soccer matches
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(1)/connecting-game-theory-and-evolutionary-network-control.pdf
Alessandro Ferrarini.Selforganizology,2015,2(1):1-12
Game theory, also known as interactive decision theory, is an umbrella term for the logical side of decision science, including both human and non-human events. In this paper a new game theory model is introduced in order to tame complex human events like soccer matches. Soccer-Decoder is a math algorithm recently introduced in order to simulate soccer matches by merging together 3 scientific methods: game theory, differential calculus and stochastic simulations. The philosophy behind Soccer-Decoder is that even very complex real world events, when turned into their irreducible essence, can be understood and predicted. In this work, Soccer-Decoder is combined with Evolutionary Network Control in order to provide a proficient tool to decide the most proper game strategies for determining winning strategies in soccer events. An illustrative example is given. The ratio behind this work is that even very complex real world events can be simulated and then controlled when using appropriate scientific tools.
A cellular automaton for population diffusion in the homogeneous
rectangular area
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(1)/a-cellular-automaton-for-population-diffusion.pdf
WenJun Zhang, YanHong Qi, ZhiGuo Zhang.Selforganizology,2015,2(1):13-17
In this paper, a cellular automaton for population diffusion was introduced. A group of discrete partial differential equations was used to simulate population diffusion in the homogeneous rectangular area. The population dynamics was described by Malthus model, Logistic model, and oscillation model. The cellular automaton can be used to analyze the effects of initial distribution of organisms on diffusion process and distribution pattern, to estimate the diffusion speed and possible diffusion directions, and to determine the major regions occupied by organisms.
Complete Impact Factor (CIF): A full index to evaluate journal impact
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(1)/dynamic-impact-factor.pdf
WenJun Zhang.Selforganizology,2015,2(1):18-20
In this article, a full index to evaluate journal impact, Complete Impact Factor (CIF), was proposed. In general, CIF= total citations for published articles in the journal since it has been sponsored / total number of published articles of the journal since it has been sponsored. CIF changes dynamically over time.
Effects of parasitism on robustness of food webs
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(2)/effects-of-parasitism-on-robustness-of-food-webs.pdf
LiQin Jiang, WenJun Zhang.Selforganizology,2015,2(2):21-34
Food webs are always self-organizing systems. Parasitism is ubiquitous and important in the food webs. In present study we analyzed the CSM food web with parasites and the predator-prey sub-web without parasites based on some topological indices in order to understand the effects of parasitism on robustness of food webs. The results showed that parasites dominated the food web links. The full CSM food web had more basal species and preys, and the predator-prey sub-web without parasites had more top species and predators. Existence of parasitism did not affect the similarity degree of free-living species, but would reduce the robustness of food web and increase intervality and clustering coefficient of food web.
Coevolution: A synergy in biology and ecology
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(2)/coevolution-a-synergy-in-biology-and-ecology.pdf
WenJun Zhang, GuangHua Liu.Selforganizology,2015,2(2):35-38
Synergy refers to that in an open and complex system consisting of a large number of subsystems, far from equilibrium, its subsystems interact in a nonlinear way to produce synergistic effects and thus make the system generate a self-organization structure in space/time with certain functions. Biologists and ecologists, tend to use coevolution/coadaptation to represent the terminology "synergy". Coevolution and research methodology were briefly discussed in present paper.
Linear correlation analysis in finding interactions: Half of predicted
interactions are undeterministic and one-third of candidate direct
interactions are missed
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(3)/linear-correlation-analysis-in-finding-interactions.pdf
WenJun Zhang, Xin Li.Selforganizology,2015,2(3):39-45
An ecological network can be constructed by calculating the sampling data of taxon by sample type. A statistically significant Pearson linear correlation means an indirect or direct linear interaction between two taxa, and a statistically significant partial correlation based on Pearson linear correlation, due to elimination of indirect effects of other taxa, means a candidate direct interaction between two taxa. People always use Pearson linear correlation to find interactions. However, some undeterministic interactions may be found and some candidate direct interactions may be missed when using this method. The results show that partial linear correlation (y) is approximately half of the Pearson linear correlation (x) (y=-0.0064+0.4785x, r2=0.173, p is less than 0.00001, n=1447), which means that indirect interactions increase mean interaction strength of taxa in the network. In all predicted interactions by partial linear correlation, about 34.35 percent (x, 0-100 percent) (i.e., one-third) of them are not successfully detected by linear correlation. In all predicted interactions by Pearson linear correlation, 50.58 percent (y, 0-100 percent) (i.e., half) of them are undeterministic interactions, i.e., not successfully detected by partial linear correlation, and 49.42 percent (z, 0-100 percent) (i.e., half) of them are candidate direct interactions, i.e., successfully detected by partial linear correlation also. The proportion of missed (x), mis-predicted (y) and precisely predicted candidate direct interactions (z) by Pearson linear correlation analysis decreases (r=-0.49, p=0.07), increases (r=0.48, p=0.08), and decreases (r=-0.48, p=0.08) slightly with the number of taxa (m) respectively. Results show that the precisely predicted (z) candidate direct interactions by Pearson linear correlation analysis are not necessarily those with the highest Pearson linear correlations. We should not try to choose a portion (e.g., 49.42 percent (z)) of predicted interactions with the greatest Pearson linear correlations as candidate direct interactions. We suggest jointly using Pearson linear correlation and partial linear correlation to analyze various interactions. Candidate direct interactions detected by both linear correlation measures should be the most focused interactions, seconded by those interactions detected by partial linear correlation only and by Pearson linear correlation only.
Refactoring of non-dispatchable flaws in the design model based on
coupling
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(3)/refactoring-of-non-dispatchable-flaws-in-the-design-model-based-on-coupling.pdf
Syed Uzair Ahmad, Muhammad Naeem, Fawad Qayum, Faqir Gul, Faisal Bahadur, Hafiz Abdul
Wahab.Selforganizology,2015,2(3):46-54
It is always better to detect and dispatch flaws at design level before the start of development for better and economic results. Refactoring is considered as a better way to address the design flaws. To the best of our knowledge, none of the available techniques targets non-dispatchable flaws of the design model in their approaches. In this paper, we are focused on multiple aspects that have been missed by the existing researchers of refactoring. For example, use of coupling to define flaws in the design model; secondly, use of refactoring to address the non-dispatchable flaws in the design models; thirdly, confirmation that whether addressing of a design flaw caused other flaws or not. Furthermore, we have used real life example of a telephonic call system to elaborate our approach.
A generalized network evolution model and self-organization theory
on community assembly
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(3)/A-network-evolution-model-and-self-organization-theory.pdf
WenJun Zhang.Selforganizology,2015,2(3):55-64
Community assembly is the process that species grow and interact to establish a community. In present study, a generalized, rule-based network evolution model, CommAssembly, for community assembly was proposed. The model is based on difference equations with different number of species in different stages of evolution. It consists of pioneer rule, invasion and growth rule, extinction rule, connection (flow) rule and termination rule, etc. Species invades, grows in, or quits the community following specific rules. In addition, I proposed the self-organization theory on community assembly. In this theory, I think that community assembly is a self-organization process. In terms of the model proposed, the practical community can spontaneously adjust its A(t), and guarantee itself to evolve in a natural way. Temporal dynamics and species composition of community depend on species composition of species pool, between-species interactions, intrinsic growth of species, environmental capacity (resource availability), and the probability, strength and history of invasions, etc. The invasion, establishment, growth, and extinction of species follow a series of rules. Community assembly can be best described and modeled with self-organization approaches. The model provides the basis to build self-organization models of community assembly.
Calculation and statistic test of partial correlation of general
correlation measures
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(4)/statistic-test-of-partial-correlation-of-general-correlation-measures.pdf
WenJun Zhang.Selforganizology,2015,2(4):65-77
It is well known that Pearson linear correlations between more than two attributes (nodes, taxa, variables, etc) can be adjusted to partial linear correlations for eliminating indirect between-attribute interactions of other attributes not being tested. In present study I first proposed three correlation measures, revised Dice coefficient, overlap coefficient, and proportion correlation. In addition, I proposed partial correlation measures for some correlation measures, of which Jaccard correlation, revised Dice coefficient, overlap coefficient, and point correlation are for binary attributes; Spearman rank correlation and proportion correlation are for interval value attributes. The full algorithm and Matlab codes (Pearson linear correlation is included also) are given. Users can add other general correlation measures in the Matlab codes.
Robots arm motion representation in Petri NETS using sequent
calculus
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(4)/robots-arm-motion-representation-in-Petri-NETS.pdf
Syed Uzair Ahmad.Selforganizology,2015,2(4):78-90
There are many sort of motion in robots structure. Such as the robot locomotion robot jumps robots picking and so on but all are presented through Petri NETS. The one motion which is also the important one and most worthy motion of the robots is the robots arm motion. Which till yet not represented through Petri NETS. In this paper we are going to represent the motion of the robot arm in different angles and different aspect, such as up, down, circular, back and front moment of the robot arm, through Petri net we can present the complex form of motions into simplex paths.
Prediction of missing connections in the network: A node-similarity
based algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(4)/prediction-of-missing-connections-in-the-network.pdf
WenJun Zhang.Selforganizology,2015,2(4):91-101
In present study, I proposed a node-similarity based algorithm for prediction of missing connections in the network. In this algorithm, whether a node vk can connect to vi or not, depending on the similarity between vk and vi, the similarities between vi and its adjacent nodes, the similarities between vk and the adjacent nodes of vi, and the degree of node vi, and vice versa. Pearson correlation measure, cosine measure, and (negative) Euclidean distance measure (the three measures are for interval attributes), contingency correlation measure (for nominal attributes), and Jaccard coefficient measure (for binary attributes) were used as the between-node similarity. Two application examples showed a better prediction of the algorithm (approximately 60% of missing connections are successfully predicted). Matlab codes of the algorithm were provided.
Semantics of cardinality-based service feature diagrams based on
linear logic
http://www.iaees.org/publications/journals/selforganizology/articles/2015-2(4)/semantics-of-cardinality-based-service-feature-diagrams.pdf
Ghulam Mustafa Assad, Muhammad Naeem, Hafiz Abdul Wahab, Faisal Bahadur, Sarfraz Ahmed.Selforganizology,2015,2(4):102-114
To provide efficient services to end-user it is essential to manage variability among services. Feature modeling is an important approach to manage variability and commonalities of a system in product line. Feature models are composed of feature diagrams. Service feature diagrams (an extended form of feature diagrams) introduced some new notations to classical feature diagrams. Service feature diagrams provide selection rights for variable features. In our previous work, we introduced cardinalities for the selection of features from a service feature diagram which we call cardinality-based service feature diagrams (CSFD). In this paper, we provide semantics to CSFDs. These semantics are backed by the formal calculus of Linear Logic. We provide rules to interpret CSFDs into linear logical formula. Our results show that the linear formulas of CSFDs give the same results as expected from the CSFDs.
A random network based, node attraction facilitated network
evolution method
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(1)/a-node-attraction-facilitated-network-evolution-method.pdf
WenJun Zhang.Selforganizology,2016,3(1):1-9
In present study, I present a method of network evolution that based on random network, and facilitated by node attraction. In this method, I assume that the initial network is a random network, or a given initial network. When a node is ready to connect, it tends to link to the node already owning the most connections, which coincides with the general rule (Barabasi and Albert, 1999) of node connecting. In addition, a node may randomly disconnect a connection i.e., the addition of connections in the network is accompanied by the pruning of some connections. The dynamics of network evolution is determined of the attraction factor lamda of nodes, the probability of node connection, the probability of node disconnection, and the expected initial connectance. The attraction factor of nodes, the probability of node connection, and the probability of node disconnection are time and node varying. Various dynamics can be achieved by adjusting these parameters. Effects of simplified parameters on network evolution are analyzed. The changes of attraction factor lamda can reflect various effects of the node degree on connection mechanism. Even the changes of lamda only will generate various networks from the random to the complex. Therefore, the present algorithm can be treated as a general model for network evolution. Modeling results show that to generate a power-law type of network, the likelihood of a node attracting connections is dependent upon the power function of the node's degree with a higher-order power. Matlab codes for simplified version of the method are provided.
A review on research of the predator-prey interactions
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(1)/a-review-on-research-of-the-predator-prey-interactions.pdf
H. A. Wahab, Hazrat Ali, Muhammad Naeem, Sarfraz Ahmad, Saira Bhatti, Muhammad Shahzad,
Khalid Usman.Selforganizology,2016,3(1):10-15
In this review article, we aim to study predator-prey interactions and their historical development from time to time. A general overview of the predator-prey model, its evolution, and the physical meanings of this model has been discussed here. A brief discussion on the classification of predators and process of predation it its effect on the environment is presented in this review article. One important characteristic of the predation process is that predators co-operate with each other against preys which becomes more visible when the prey are strong enough to be over-powered easily.
Validity process for refactored coupling based non-dispatchable flaws in the design model
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(1)/validity-process-for-refactored-coupling.pdf
Syed Uzair Ahmad, Muhammad Naeem.Selforganizology,2016,3(1):16-24
As we know that in the start level, it is better to pick out flaw and refactored it, as soon as possible. It is best way to address flaw through refactoring. All of techniques cover the area of refactoring or validation, no approach has been used to refactor the non dispatchable flaw based on coupling and validate that refactored design. In this paper we are going to address the missing point as for founded in previous works. For example, we will use model based on coupling defined model, second will refactored it, third will check bad fixes and at last we will validate the model, the validation needs because to ensure that the model has changed design or in same design.
Non-traditional approach to fitting of time series of larch bud moth
dynamics: Application of Moran - Ricker model with time lags
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(1)/approach-to-fitting-time-series-of-larch-bud-moth-dynamics.pdf
L.V. Nedorezov.Selforganizology,2016,3(1):25-40
In current publication analyses of time series of larch bud moth (Zeiraphera diniana Gn.) dynamics are considered. For fitting of time series Moran - Ricker model with time lags was used. Estimations of model parameters were provided with non-traditional approach: for every considered case feasible sets of points in space of model parameters were determined where selected statistical criterions give required results for deviations between theoretical (model) and empirical datasets. In all considered situations obtained results were compared with other results obtained with least squared method. It was obtained that Moran - Ricker model without time lag and with time lag in one year is not suitable for fitting of time series. Best correspondences on quantitative and qualitative levels between model trajectories and empirical dataset were found for cases with time lag in 3 years.
A review on the book, Selforganizology: The Science of Self-
Organization
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(1)/book-review-selforganizology.pdf
GuangHua Liu.Selforganizology,2016,3(1):41-42
The book, Selforganizology: The Science of Self-Organization, authored by WenJun Zhang and published by World Scientific, was briefly reviewed in present report.
Network informatics: A new science
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(2)/network-informatics.pdf
WenJun Zhang.Selforganizology,2016,3(2):43-50
Based on my previous study, in present article I further outlined and defined the aims, scope, theory and methodology of network informatics.
Order out of chaos: emergent patterns in soccer matches
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(2)/emergent-patterns-in-soccer-matches.pdf
Alessandro Ferrarini.Selforganizology,2016,3(2):51-58
A soccer match is a very complex, apparently chaotic, human event. However, order clearly emerges from such chaos if we have at hand the right tools to extract pattern configurations. In this work, a new algorithm called Soccer-Decompiler is presented, which is able to analyze soccer matches and extract emerging patterns from apparently chaotic sequences of events. Detecting and filtering the frequencies of events is used by Soccer-Decompiler to discover such patterns. The application of Soccer-Decompiler to a real soccer match shows that order out of chaos in complex human events can be effectively extracted by isolating highly frequent events. An applicative example is given.
Automated inconsistency detection in feature models: A generative
programming based approach
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(2)/automated-inconsistency-detection-in-feature-models.pdf
Muhammad Javed, Muhammad Naeem, Aarif Iqbal Umar, Faisal Bahadur.Selforganizology,2016,3(2):59-74
The quality of feature model represents the quality of end products because it is used to develop products. Hence, quality evaluation of feature model is the most important task. The quality detection mechanism should be efficient enough to evaluate the quality of a given feature model within limited time. So, there is a need of automated quality evaluation system. Generative Programming (GP) is the most effective way to automate the quality detection system for feature models. This effort is to present an efficient way to automate the quality detection system by using one of the GP based technique (GenVoca Layered Architecture) for inconsistencies in feature model. We implemented this quality detection technique in C++. We applied this technique on the feature models contain errors.
Screening node attributes that significantly influence node centrality
in the network
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(3)/screening-node-attributes-that-influence-node-centrality.pdf
WenJun Zhang.Selforganizology,2016,3(3):75-86
In present study, I proposed a method to screen node attributes that significantly influencing node centrality in the network. One of four node centralities, degree centrality, closeness centrality, betweenness centrality, and
circuit centrality, can be used as the dependent variable and attribute-by-node data are used as the data of independent variables. Stepwise linear regression method was applied to screen statistically significant node
attributes from candidate attributes. Matlab codes of the algorithm are provided also.
An efficient algorithm for color image segmentation
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(3)/an-efficient-algorithm-for-color-image-segmentation.pdf
Neha Bhardwaj, Arun Solanki.Selforganizology,2016,3(3):87-99
In field of image processing, image segmentation plays an important role that focus on splitting the whole image into segments. Representation of an image so that it can be more easily analysed and involves more information is an important segmentation goal. The process of partitioning an image can be usually realized by Region based, Boundary based or edge based method. In this work a hybrid approach is followed that combines improved bee colony optimization and Tabu search for color image segmentation. The results produced from this hybrid approach are compared with non-sorted particle swarm optimization, non-sorted genetic algorithm and improved bee colony optimization. Results show that the Hybrid algorithm has better or somewhat similar performance as compared to other algorithms that are based on population. The algorithm is successfully implemented on MATLAB.
An algorithm to transform natural language into SQL queries for
relational databases
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(3)/algorithm-to-transform-natural-language-into-SQL-queries.pdf
Garima Singh, Arun Solanki.Selforganizology,2016,3(3):100-116
Intelligent interface, to enhance efficient interactions between user and databases, is the need of the database applications. Databases must be intelligent enough to make the accessibility faster. However, not every user familiar with the Structured Query Language (SQL) queries as they may not aware of structure of the database and they thus require to learn SQL. So, non-expert users need a system to interact with relational databases in their natural language such as English. For this, Database Management System (DBMS) must have an ability to understand Natural Language (NL). In this research, an intelligent interface is developed using semantic matching technique which translates natural language query to SQL using set of production rules and data dictionary. The data dictionary consists of semantics sets for relations and attributes. A series of steps like lower case conversion, tokenization, speech tagging, database element and SQL element extraction is used to convert Natural Language Query (NLQ) to SQL Query. The transformed query is executed and the results are obtained by the user. Intelligent Interface is the need of database applications to enhance efficient interaction between user and DBMS.
Detecting connectedness of network: A Matlab program and
application in tumor pathways and a phylogenic network
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(4)/detecting-connectedness-of-network.pdf
WenJun Zhang.Selforganizology,2016,3(4):117-120
Two nodes in a network are called to be connected if there is a path between the two nodes. In a connected network, each pair of nodes is connected. In this article, I present full Matlab codes of the vertex-fusion algorithm to detect network connectedness. In the program, the number of connected components and all nodes of each connected component will be displayed. It is expected for using in some studies of network pharmacology.
An improved data clustering algorithm for outlier detection
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(4)/an-improved-data-clustering-algorithm-for-outlier-detection.pdf
Anant Agarwal, Arun Solanki.Selforganizology,2016,3(4):121-139
Data mining is the extraction of hidden predictive information from large databases. This is a technology with potential to study and analyze useful information present in data. Data objects which do not usually fit into the general behavior of the data are termed as outliers. Outlier Detection in databases has numerous applications such as fraud detection, customized marketing, and the search for terrorism. By definition, outliers are rare occurrences and hence represent a small portion of the data. However, the use of Outlier Detection for various purposes is not an easy task. This research proposes a modified PAM for detecting outliers. The proposed technique has been implemented in JAVA. The results produced by the proposed technique are found better than existing technique in terms of outliers detected and time complexity.
Cost estimation of feature oriented software development: Statistical
approach
http://www.iaees.org/publications/journals/selforganizology/articles/2016-3(4)/cost-estimation-of-feature-oriented-software-development.pdf
Jawad Khan, Faisal Bhadur, Muhammad Naeem, Muhammad Javed, Naveed Jan.Selforganizology,2016,3(4):140-151
Software cost estimation is the important part of software development and used to predict the effort which is mandatory part for development of software system. Feature Model is a set of products that represents set of feature in feature model. Software cost estimation is about predicting amount of cost in software development cycle. SCE give analysis both to user as well customer regarding to budging planning. In this paper we have represent a statistical approach for finding cost estimation of feature oriented software development. We have used CPM approach from which we will find commonality as well cost of each feature which will be deploy in feature oriented software development.
Graphical matching rules for cardinality based service feature
diagrams
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(1)/graphical-matching-rules-for-service-feature-diagrams.pdf
Faiza Kanwal, Ghulam Mustafa Assad, Arif Iqbal Umer, Muhammad Naeem, Sheraz Ahmad.Selforganizology,2017,4(1):1-9
To provide efficient services to end-users, variability and commonality among the features of the product line is a challenge for industrialist and researchers. Feature modeling provides great services to deal with variability and commonality among the features of product line. Cardinality based service feature diagrams changed the basic framework of service feature diagrams by putting constraints to them, which make service specifications more flexible, but apart from their variation in selection third party services may have to be customizable. Although to control variability, cardinality based service feature diagrams provide high level visual notations. For specifying variability, the use of cardinality based service feature diagrams raises the problem of matching a required feature diagram against the set of provided diagrams.
Estimation of node richness by sampling: Application of
nonparametric methods
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(1)/estimation-of-node-richness-by-sampling.pdf
WenJun Zhang.Selforganizology,2017,4(1):10-13
In the sampling of statistc networks (Zhang, 2011, 2012a, 2012b), the number of new nodes will decline as increase of sample size, and it tends to an upper asymptote as sample size tends to the infinity. However, in most cases our sampling is incomplete. Therefore, the exact number of nodes of a stastic network is unknown. We need to find some methods to estimate node richness in statistic networks. In this study, I use some of the known nonparametric methods to estimate node richness. Computer software and codes were given.
Finding fundamental circuits in the network: A Matlab program and
application in tumor pathway
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(1)/finding-fundamental-circuits-in-the-network.pdf
WenJun Zhang.Selforganizology,2017,4(1):14-17
In present article, I present full Matlab codes of the Paton algorithm for calculating fundamental circuit set and use it in tumor pathways.
Analysis of seven stages supply chain management in electronic component inventory optimization for warehouse with economic load dispatch using genetic algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(2)/genetic-algorithm.pdf
Ajay Singh Yadav, Anupam Swami, Geethanjali Kher, Ankur Garg.Selforganizology,2017,4(2):18-29
The purpose of the proposed study is to give a new dimension on warehouse with Economic Load Dispatch using genetic algorithm processes in Seven Stages - 10 Member Supply Chain in Electronic component inventory optimization to describe the certain and uncertain market demand which is based on supply reliability and to develop more realistic and more flexible models. we hope that the proposed study has a great potential to solve various practical tribulations related to the warehouse using genetic algorithm processes in Seven Stages - 10 Member Supply Chain in Electronic component inventory optimization and also provide a general review for the application of soft computing techniques like genetic algorithms to use for improve the effectiveness and efficiency for various aspect of warehouse with Economic Load Dispatch using genetic algorithm.
Finding minimum cost flow in the network: A Matlab program and
application
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(2)/finding-minimum-cost-flow-in-the-network.pdf
WenJun Zhang.Selforganizology,2017,4(2):30-34
In this study, I present full Matlab codes of minimum cost flow algorithm and demonstrate an example.
Phase recognition in network evolution
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(3)/phase-recognition-in-network-evolution.pdf
WenJun Zhang.Selforganizology,2017,4(3):35-40
In present study I used one dimensional ordered cluster method to recognize different phases in network evolution by clustering time points in a time series. Matlab codes of the algorithm were provided.
Analysis of six stages supply chain management in inventory
optimization for warehouse with artificial bee colony algorithm using
genetic algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(3)/inventory-optimization-with-artificial-bee-colony-algorithm.pdf
Ajay Singh Yadav, Prerna Maheshwari (Sharma), Anupam Swami, Ankur Garg.Selforganizology,2017,4(3):41-51
The purpose of the proposed study is to give a new dimension on warehouse with Artificial bee colony
algorithm using genetic algorithm processes in six stages - 11 member supply chain in inventory optimization
to describe the certain and uncertain market demand which is based on supply reliability and to develop more
realistic and more flexible models. we hope that the proposed study has a great potential to solve various
practical tribulations related to the warehouse using genetic algorithm processes in six stages - 11 member
supply chain in inventory optimization and also provide a general review for the application of soft computing
techniques like genetic algorithms to use for improve the effectiveness and efficiency for various aspect of
warehouse with Artificial bee colony algorithm using genetic algorithm.
Analysis of electronic component inventory optimization in six stages
supply chain management for warehouse with ABC using genetic
algorithm and PSO
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(4)/electronic-component-inventory-optimization.pdf
Ajay Singh Yadav, Anupam Swami, C. B. Gupta, Ankur Garg.Selforganizology,2017,4(4):52-64
The purpose of the proposed study is to give a new dimension on warehouse with artificial bee colony algorithm using genetic algorithm and particle swarm optimization algorithm processes in six stages - 11 member supply chain in electronic component inventory optimization to describe the certain and uncertain market demand which is based on supply reliability and to develop more realistic and more flexible models. We hope that the proposed study has a great potential to solve various practical tribulations related to the warehouse using genetic algorithm processes in six stages - 11 member supply chain in electronic component inventory optimization and also provide a general review for the application of soft computing techniques like genetic algorithms to use for improve the effectiveness and efficiency for various aspect of warehouse with artificial bee colony algorithm using genetic algorithm and particle swarm optimization algorithm.
Maximum matching of the network: A Matlab program and application
http://www.iaees.org/publications/journals/selforganizology/articles/2017-4(4)/maximum-matching-of-the-network.pdf
WenJun Zhang.Selforganizology,2017,4(4):65-68
In this article, I present full Matlab codes of Hungarian Algorithm for maximum matching in the network.
A supply chain management of chemical industry for deteriorating items with warehouse using genetic algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2018-5(1-2)/a-supply-chain-management-of-chemical-industry.pdf
Ajay Singh Yadav, Prerna Sharma, Anupam Swami, Garima Pandey.Selforganizology,2018,5(1-2):1-9
This study discussed the supply chain inventory optimization of chemical industry and genetic algorithm for deteriorating items in a manufacture of chemical industry, warehouse of chemical industry, three distribution centers of chemical industry, and three retailer's of chemical industry environment using genetic algorithm. Demand is assumed to be known and constant. Shortages of chemical industry are not allowed and apply inflation of chemical industry. A warehouse of chemical industry is used to store the excess units over the fixed capacity of the two distribution centers of chemical industry. Further supply chain inventory optimization of chemical industry and genetic algorithm optimization dispatching policies was investigated in different scenarios in the model.
A Green supply chain management of Auto industry for inventory
model with distribution centers using Particle Swarm Optimization
http://www.iaees.org/publications/journals/selforganizology/articles/2018-5(3-4)/inventory-model-with-distribution-centers-using-Particle-Swarm-Optimization.pdf
Ajay Singh Yadav, Anupam Swami, Navin Ahlawat.Selforganizology,2018,5(3-4):10-18
Green supply chain inventory optimization of Auto industry and Particle Swarm Optimization (PSO) for deteriorating items in a manufacture of Auto industry, warehouse of Auto industry, three distribution centers of Auto industry, and three Retailer's of Auto industry environment using Particle Swarm Optimization (PSO). Demand is assumed to be known and constant. Shortages of Auto industry are not allowed and apply inflation of Auto industry. The distribution centers of Auto industry is used to store the excess units over the fixed capacity of the distribution centers of Auto industry. Further Green supply chain inventory optimization of Auto industry and Particle Swarm Optimization (PSO) dispatching policies has been investigated in different scenarios in the model.
The structure of democracy and dictatorship of firms (corporate
governance) in relation to the non-competitive product market and
stock abnormal returns
http://www.iaees.org/publications/journals/selforganizology/articles/2019-6(1-2)/structure-of-democracy-and-dictatorship-of-firms.pdf
Hamideh Afshari.Selforganizology,2019,6(1-2):1-12
In this research, the relationship between the structure of democracy and dictatorship of enterprises, noncompetitive structure of markets and abnormal returns is evaluated. This assessment is conducted through the relationship between the most important criteria for this structure in the literature of research in Iran's money market, the institutional shareholder, and product market competition with abnormal returns. This issue is carried out using the data extracted from information published by TSE-Tehran Stock Exchange and tax records of 78 firms are acquired by TSE-Tehran Stock Exchange using the Carhart model and the combined data regression. The results indicated that there is a meaningful relationship between the democracy structure of firms, percentage of institutional shareholders and abnormal returns on the non-competitive market. In other words, in a non-competitive market, the more desirable the firm's democracy structure or business governance is, returns are also greater.
Blood bank supply chain inventory model for blood collection sites
and hospital using genetic algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2019-6(3-4)/blood-bank-supply-chain-inventory-model-using-genetic-algorithm.pdf
Ajay Singh Yadav, Anupam Swami, Geethanjali Kher.Selforganizology,2019,6(3-4):13-23
Optimal blood management is one of the key tasks in managing a blood bank supply chain. Optimal methods of blood supply management are aimed at reducing costs in the blood bank supply chain through effective blood supply management so that members of monitoring committees are not affected by excess or shortage. In this article, we proposed an efficient approach that uses a genetic algorithm for optimal inventory management. This article presented a method based on a genetic algorithm for optimizing stocks in managing a blood bank supply chain. In particular, we focused on identifying the most likely stocks and levels of interaction needed to optimize blood supply in the blood bank supply chain in order to minimize the total cost of the blood bank supply chain.
A Matlab algorithm for detection of protein complexes from multiple
heterogeneous networks
http://www.iaees.org/publications/journals/selforganizology/articles/2020-7(1-2)/Matlab-detection-of-protein-complexes-from-multiple-heterogeneous-networks.pdf
WenJun Zhang, ShangHong Xin.Selforganizology,2020,7(1-2):1-7
In present article, we presented the Matlab algorithm of Ou-Yang's model (Ou-Yang et al., 2017). It can be used to explore the shared clustering structure in PPI (protein-protein interaction) and DDI (domain-domain interaction) networks. A final matrix H can be achieved using the algorithm. Protein i belongs to complex k if Hik=1, otherwise Hik=0, i=1, 2, ..., N1; k=1, 2, ..., K, where N1 is the number of proteins in PPI network, and K is the number of complexes (clusters).
Matlab algorithm to generate adjacency matrix from connection pairs
that nodes are represented by strings
http://www.iaees.org/publications/journals/selforganizology/articles/2020-7(3-4)/generate-adjacency-matrix-from-connection-pair.pdf
WenJun Zhang, Yanhong Qi.Selforganizology,2020,7(3-4):8-14
It is harder to generate an adjacency matrix from connection (i.e., link) pairs that nodes are represented by strings than by numerical ID numbers. In present article, we developed a Matlab algorithm to generate adjacency matrix from connection pairs in which nodes are represented by strings. Full codes and executable program of the algorithm were given.
A Matlab method to fit an image with polygons using genetic algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2021-8(1-2)/Matlab-method-to-fit-image-with-polygons-using-genetic-algorithm.pdf
WenJun Zhang.Selforganizology,2021,8(1-2):1-6
Genetic algorithms are a kind of algorithms to simulate genetic evolution, which belong to the subject of selforganizology. They have been used in function optimization, automatic control, robotics, and image processing, etc. In this article, a Matlab algorithm of the genetic algorithm to fit the given image with polygons is presented. Full codes are given for further use.
Centralities of galaxies in the weighted network model of the Local
Group
http://www.iaees.org/publications/journals/selforganizology/articles/2021-8(3-4)/centralities-of-galaxies-in-weighted-network-model.pdf
Emir Haliki.Selforganizology,2021,8(3-4):7-20
Little is known about the structures and characteristics of the networks behind galaxy clusters. Considering that the essential interaction between the elements of a cluster is the gravitational attraction, the study has modeled the Local Group, a local galaxy cluster of which the Milky Way is a member, as a weighted network according to gravitational attraction. After the galaxies' unknown masses have been calculated from their apparent and absolute magnitudes, the gravitational attraction matrix, being the adjacency matrix of the network, would be formed from the matrix of their positions relative to each other. Various centrality measurements known as fundamental network metrics were thus performed to determine if the massive galaxies of the cluster have high centrality values. In the proposed weighted network model, direct and indirect correlations have been observed between centrality values and masses of the galaxies.
A study of Covid-19 pandemic on fertilizer supply chain inventory
management using travelling salesman problem for Cuckoo Search
Algorithms
http://www.iaees.org/publications/journals/selforganizology/articles/2021-8(3-4)/supply-chain-travelling-salesman-problem-Cuckoo-Search-Algorithms.pdf
Ajay Singh Yadav, Anupam Swami, Navin Ahlawat, Tarun Kumar Arora, Pavan Kumar Chaubey,
Krishan Kumar Yadav.Selforganizology,2021,8(3-4):21-35
The impact of the Covid-19 epidemic on inventory management in the fertilizer supply chain is an important part of inventory management in the region and has been an important idea for the overall benefit of the industrial situation. It consists of several steps through which the material goes through different stages to reach the end customer. The effects of the Covid-19 epidemic on the management of the three-fertilizer supply chain inventory include fertilizer production sites, fertilizer distribution center, and costly fertilizer representative. A coordinated approach between rates is needed to adjust the chain for lower stocks and lower costs, and thus higher profits. This paper discusses the effect of coordinating the three-step Covid-19 epidemic on inventory management in a single fertilizer distribution chain that provides one type of product to distribution centers for individual fertilizers and then for each fertilizer representative the Covid-19 on the inventory management in the fertilizer distribution chain is solved by using the problem of a traveling salesman to add an ant colony to better values of decision-making variables and targeting functions. A numerical model is provided and the results obtained here are compared with these methods.
Effect of Covid-19 pandemic on semiconductor industry supply chain
inventory management: travelling salesman problem for simulated
annealing and Cuckoo Search Algorithms
http://www.iaees.org/publications/journals/selforganizology/articles/2022-9(1-2)/simulated-annealing-and-Cuckoo-Search-Algorithms.pdf
Ajay Singh Yadav, Anupam Swami, Navin Ahlawat, Tarun Kumar Arora, Pavan Kumar Chaubey,
Pooja Chaudhary.Selforganizology,2022,9(1-2):1-16
The impact of the Covid-19 epidemic on inventory management in the semiconductor industry supply is an important part of inventory management and has been an important idea for the overall benefit of the industrial situation. It consists of several steps through which the material goes through different stages to reach the end customer. The impact of the Covid-19 pandemic on the inventory management of the three-tier semiconductor industry includes the locations of the semiconductor trading unit, the semiconductor industry warehouse, and the cost-effective agent of the semiconductor industry. A coordinated approach between rates is needed to adjust the chain for lower stocks and lower costs, and thus higher profits. In this paper, we discuss the effect of coordinating the three-step Covid-19 epidemic on the supply chain management of the semiconductor industry and one part of the semiconductor industry conference that provides one type of product for distribution centers for each industry of semiconductor and then semiconductor agent sector. The mathematical model is developed for the coordinated effects of the Covid-19 epidemic on inventory management in the supply of the semiconductor industry, solved by the problem of a traveling salesman adding an ant colony to better values for decision-making and targeting functions. A numerical model is provided and the results obtained here are compared with these methods.
Inauguration of Kifilideen theorem of matrix transformation of
negative power of - n of trinomial expression in which three variables
x, y and z are found in parts of the trinomial expression with some
other applications
http://www.iaees.org/publications/journals/selforganizology/articles/2022-9(1-2)/Kifilideen-theorem-of-matrix-transformation.pdf
Kifilideen L. Osanyinpeju.Selforganizology,2022,9(1-2):17-34
Kifilideen trinomial theorem of negative power of - n is theorem which is used to generate the series and terms of a trinomial expression of negative power of - n in an orderly and periodicity manner that is based on standardized and matrix methods. Negative power of Newton binomial theorem had been used to produce series of partial fractions of a compound fraction. The establishment of the negative power of - n of trinomial theorem would extend the number of compound fraction in which series (expansion) can be produced. This study applied Kifilideen expansion of negative power of - n of Kifilideen trinomial theorem for the transformation of compound fraction into series of partial fractions with other developments. A theorem of matrix transformation of negative power of - n of trinomial expression in which three variables x, y and z are found in parts of the trinomial expression was inauguration. The development would ease the process of evaluating such trinomial expression of negative power of - n. This standardized and matrix method used in arranging the terms of the Kifilideen expansion of negative power of - n of trinomial expression yield an interesting results in which it is utilized in transforming compound fraction into series of partial fractions in a unique way.
Particle swarm optimization: A Matlab algorithm
http://www.iaees.org/publications/journals/selforganizology/articles/2022-9(3-4)/particle-swarm-optimization-Matlab-algorithm.pdf
WenJun Zhang.Selforganizology,2022,9(3-4):35-41
In present study, the Matlab algorithm and full codes for particle swarm optimization was given. An example was demonstrated.
Genetic algorithm: A Matlab software
http://www.iaees.org/publications/journals/selforganizology/articles/2023-10(1-2)/genetic-algorithm-Matlab-software.pdf
WenJun Zhang.Selforganizology,2023,10(1-2):1-6
In present study, the Matlab software for a genetic algorithm was given. An example was demonstrated for easy use.
A new chaotic system's qualitative analysis, with a focus on Hopf
bifurcation analysis
http://www.iaees.org/publications/journals/selforganizology/articles/2023-10(3-4)/new-chaotic-systems-qualitative-analysis.pdf
Md. Jasim Uddin, Esrat Nur Nipu.Selforganizology,2023,10(3-4):7-21
In this study, a brand-new chaotic system with a particular set of parameters is presented. In addition, this study offers instructions about how to resolve the new system. Also demonstrated and stated are some of the system's dynamical characteristics. In essence, this work demonstrates the identification of the fixed points for the system, dynamical analysis utilizing the complementary-cluster energy-barrier criteria (CCEBC), eigenvalue discovery for stability, and Lyapunov exponent discovery to examine some of the dynamical behaviors of the system. Additionally, this research uses the first Lyapunov coefficient to determine the Hopf bifurcation of the new three-dimensional system. With the help of MATLAB, many parameters are changed to display images and diagrams for chaotic systems.
netGen 3.0: The executable Java software for network visualization
http://www.iaees.org/publications/journals/selforganizology/articles/2024-11(1-2)/executable-Java-software-for-network-visualization.pdf
WenJun Zhang.Selforganizology,2024,11(1-2):1-27
The executable Java software, netGen 3.0, for network visualization was developed in present study. A network can be generated and interactively visualized from a text file by using netGen. Compared to the previous versions, there are substantial improvements in netGen 3.0. In addition to the visualization of both unweighted and weighted (and both undirected and directed) networks, node size / color, link width / length / color, node name color, canvas size, etc., can be specified by the user. Moreover, network layout can be conducted in artificial or automatic manners. Both netGen 3.0 and demonstration data files were given.
objectVisual3D: A standalone executable software for 3D visualization
of objects
http://www.iaees.org/publications/journals/selforganizology/articles/2024-11(3-4)/objectVisual3D-executable-software-for-3D-visualization.pdf
WenJun Zhang.Selforganizology,2024,11(3-4):28-53
A standalone executable software, objectVisual3D (version 1.0), for 3D visualization of objects, was developed in present study. The software uses the OBJ file of an object to generate its 3D graphics. Various parameters can be specified by users. In the generated 3D graphics window, users can right- or left-click mouse to zoom in or zoom out the 3D graphics, or mouse-drag the graphics to rotate the 3D graphics, or slide scrollbar to vertically or horizontally translate the 3D graphics. The 3D graphics can be saved as an image file (in BMP format). Both objectVisual3D and demonstration data files were given.
An interactive interior point method for mathematical multi-objective
linear optimization problems based on approximate gradients
http://www.iaees.org/publications/journals/selforganizology/articles/2024-11(3-4)/interactive-interior-point-method.pdf
M. Tlas.Selforganizology,2024,11(3-4):54-75
An interactive interior point method for solving multiple-objective linear programming problems has been proposed. The method uses a single-objective linear variant in order to generate, at each iterate, interior search directions. New feasible points are found along these directions which will be later used for deriving bestapproximation to the gradient of the implicitly-known utility function at the current iterate. Using this approximate gradient, a single feasible interior direction for the implicitly-utility function could be generated by projecting this approximate gradient onto the null space of the feasible region. An interior step can be taken from the current iterate to the next one along this feasible direction. During the execution of the algorithm, a sequence of interior points will be generated. It has been proved that this sequence converges to an e - optimal solution, where e is a predetermined error tolerance known a priori. A numerical multi-objective example is illustrated using this algorithm.