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The gene regulatory network
2008
Proceedings of the 10th annual conference on Genetic and evolutionary computation - GECCO '08
This paper proposes a new approach for biologically inspired computing on the basis of Gene Regulatory Networks. These networks are models of genes and dynamic interactions that take place between them. The differential equation representations of such networks resemble neural networks as well as idiotypic networks in immune system. Although several potential applications have been outlined, an example, the problem of placing sensors optimally in a distributed environment is considered in
doi:10.1145/1389095.1389381
dblp:conf/gecco/DasKCWS08
fatcat:cayrflidkfc2jlngypnril37uu
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... . A comparison with NSGA-II suggest that the new method is able to accomplish near-optimal coverage of sensors in a network.
A multi-objective approach for the prediction of loan defaults
2011
Expert systems with applications
Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines and models are incapable of handling the problems. This study applies Fuzzy dominance based Simplex Genetic Algorithm (a multi-objective evolutionary optimization algorithm) in generating decision rules for predicting loan default in a typical credit institution.
doi:10.1016/j.eswa.2011.01.096
fatcat:jj3ulbjwszaqblsgap2oje6z24
Multi-objective hybrid PSO using µ-fuzzy dominance
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
This paper describes a PSO-Nelder Mead Simplex hybrid multiobjective optimization algorithm based on a numerical metric called ε -fuzzy dominance. Within each iteration of this approach, in addition to the position and velocity update of each particle using PSO, the k-means algorithm is applied to divide the population into smaller sized clusters. The Nelder-Mead simplex algorithm is used separately within each cluster for added local search. The proposed algorithm is shown to perform better
doi:10.1145/1276958.1277125
dblp:conf/gecco/KoduruDW07
fatcat:qh65c52lv5fkzicqdssk4fj44i
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... n MOPSO on several test problems as well as for the optimization of a genetic model for flowering time control in Arabidopsis. Adding the local search achieves faster convergence, an important feature in computationally intensive optimization of gene networks.
Fuzzy Dominance Based Multi-objective GA-Simplex Hybrid Algorithms Applied to Gene Network Models
[chapter]
2004
Lecture Notes in Computer Science
Hybrid algorithms that combine genetic algorithms with the Nelder-Mead simplex algorithm have been effective in solving certain optimization problems. In this article, we apply a similar technique to estimate the parameters of a gene regulatory network for flowering time control in rice. The algorithm minimizes the difference between the model behavior and real world data. Because of the nature of the data, a multiobjective approach is necessary. The concept of fuzzy dominance is introduced,
doi:10.1007/978-3-540-24854-5_37
fatcat:4acdrerdyjfwvnjrjtioo6u7ou
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... a multi-objective simplex algorithm based on this concept is proposed as a part of the hybrid approach. Results suggest that the proposed method performs well in estimating the model parameters.
A particle swarm optimization approach for estimating parameter confidence regions
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
Point estimates of the parameters in real world models convey valuable information about the actual system. However, parameter comparisons and/or statistical inference requires determination of parameter space confidence regions in addition to point estimates. In most practical applications, the relation of the parameters to model fitness is highly nonlinear and noisy data leads to further deviations. Thus the confidence regions obtained by using locally linearized models are often misleading.
doi:10.1145/1276958.1276969
dblp:conf/gecco/KoduruWD07
fatcat:ydfy75xktvhm7cq75fotjsejca
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... niform covering by probabilistic rejection (UCPR) is a robust technique that has been developed to solve this problem, and has been proven to be more efficient than other approximate random search techniques. In this paper, we propose a contour particle swarm optimization (C-PSO) technique and compare its performance against UCPR in predicting the confidence regions. Results indicate that for problems with low number of parameters, both the algorithms are quite comparable. However, real world models such as genetic networks have a large number of parameters and the UCPR fails in finding good convergence due to its limited search capabilities. In such problems, the C-PSO technique was able to find the confidence regions with better resolution and efficiency.
Discovering structures in gene regulatory networks using genetic programming and particle swarms
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
In this paper, we describe a genetic programming and particle swarm hybrid algorithm for gene network discovery.
doi:10.1145/1276958.1277300
dblp:conf/gecco/CaiWKD07
fatcat:lf5qpukzsrc2fpbrkn54t5w3cy
Urine Analysis as a Screening Tool in Early Detection of Renal Abnormalities in Asymptomatic School Children
2018
World Journal of Nephrology and Urology
Early identification of kidney diseases in children and adolescents is an important initial step in prevention of chronic kidney diseases (CKD). The current study was undertaken to screen asymptomatic school children in Nellore, Andhra Pradesh, and to detect the prevalence of renal disorders using urine dipstick method and associated risk factors. Method: Out of total 1,626 children, 883 (54.31%) were male children and remaining 743 (45.69%) were female students. During the first screening by
doi:10.14740/wjnu325w
fatcat:skgatz3srnhnbcvfi2gxap52cu
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... ine dipstick method, 45 (2.77%) children were found to having urinary abnormalities which were further investigated by confirmatory complete urine analysis. Results: Finally 37 were diagnosed having urinary abnormalities. The prevalence rate of isolated hematuria (IH) was 0.62%; isolated proteinuria (IP) was 0.18%; combined hematuria and proteinuria (CHP) was 0.18% and urinary tract infection (UTI) was 1.23%. Renal stone was the cause in 20% cases while post-infectious golmerulonephritis (PIGN) and IgA nephropathy (IgAN) were the causes of hematuria in 10% cases each. Out of three cases of CHP, two (66.67%) cases were due to PIGN and one was due to membranoproliferative glomerulonephritis (MPGN). Totally 26 cases were confirmed having UTI. Out of these 26 cases, gram-negative bacilli were detected in 11 (42.31%) cases and gram-positive were detected in five (19.23%) cases. The prevalence rate of renal abnormalities among 6 -7 years, 8 -9 years, 10 -11 years and 12 -13 years students was 2.07%, 2.43%, 2.19 and 2.41% respectively. Out of 889 urban students, 19 were having confirmed renal abnormalities which indicated that the prevalence of renal problem in asymptomatic urban student was 2.14%. Out of 737 rural students, 18 were having confirmed renal abnormalities which indicated that the prevalence of renal problem in asymptomatic rural student was 2.44%. Prevalence of hematuria in male was 0.23 and in female 1.08 and the difference was statistically significant (P < 0.05) which indicated hematuria more in female asymptomatic students compared to male asymptomatic students. Age wise prevalence of IP ranged from 0% in 6 -7 years age group and 12 -13 years age group to 0.44% in 10 -11 years age group. Prevalence of UTIs in male was 0.57 and in female 2.02, and the difference was statistically significant (P < 0.05) indicating that the prevalence of UTIs was significantly more in female asymptomatic students compared to male asymptomatic students. Conclusions: In conclusion, asymptomatic urinary abnormalities might be detected by urine screening program at school age. Further work-up should be offered to define the exact etiology of any abnormal finding.
A multi-objective approach for the prediction of loan defaults
2007
Proceedings of the 9th annual conference on Genetic and evolutionary computation - GECCO '07
Credit institutions are seldom faced with problems dealing with single objectives. Often, decisions involving optimizing two or more competing goals simultaneously need to be made, and conventional optimization routines and models are incapable of handling the problems. This study applies Fuzzy dominance based Simplex Genetic Algorithm (a multi-objective evolutionary optimization algorithm) in generating decision rules for predicting loan default in a typical credit institution.
doi:10.1145/1276958.1277370
dblp:conf/gecco/OdehKDFW07
fatcat:ah2c4l4erbcazn7n7vdiuouziu
Study comparing the efficacy of platelet rich plasma versus steroid versus placebo in lateral epicondylitis
2017
International Journal of Research in Orthopaedics
<p><strong>Background: </strong>Lateral epicondylitis is seen more commonly in non-athletes than athletes. Non-operative methods are the mainstay of treatment being effective in more than 95% of cases. Platelet rich plasma (PRP) has shown promising results in many studies as compared to steroid injection & other modes of conservative management. Hence, this study was done to evaluate PRP efficacy in our clinical setup and in the people of age group most commonly being
doi:10.18203/issn.2455-4510.intjresorthop20170532
fatcat:srn4qgbaz5f27c27q45rrewt7u
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... ng></p><p><strong>Methods: </strong>This randomized study was conducted at Narayana Medical College Hospital, Nellore, for a period of two years from December 2014 to June 2016 on 150 consenting patients diagnosed as suffering from lateral epicondylitis. Using lottery method for randomization the patients were divided into three groups, based on which the treatment was received. Group –N with 50 patients received 3 ml of normal saline as placebo. Group –P with 50 patients received 3 ml of extracted PRP injection. Group –S with 50 patients received depot preparation of 40 mg of methyl prednisiolone injected into the affected area. The data collected and recorded in the appropriate proforma. Post therapy assessment was done using with Oxford elbow score.</p><p><strong>Results: </strong>The overall mean ages of the patients in the three groups (Group P, Group S and Group N) are 38.62±7.53, 37.82±7.79 and 36.3±6.93 respectively. Female preponderance was observed in all the groups. Most common presenting complaint was elbow pain seen in 100% of cases. Most common side involved was the dominant side, right side involvement was seen in 136 cases and left side in 14 cases. The Oxford elbow score pre-treatment in all the groups was not statistically significant and the Oxford elbow score at the end of 12 weeks and 24 weeks treatment showed that PRP and steroid was better than normal saline in control of pain.<strong></strong></p><p><strong>Conclusion: </strong>Lateral epicondylitis or tennis elbow is a painful debilitating condition of elbow, which creates disturbance in functional activities. A single injection of PRP at the site of the elbow pain resulted in relief of pain in patients with longer duration as compared to local steroids to other conservative treatments.</p>
A co-evolutionary hybrid algorithm for multi-objective optimization of gene regulatory network models
2005
Proceedings of the 2005 conference on Genetic and evolutionary computation - GECCO '05
In this paper, the parameters of a genetic network for rice flowering time control have been estimated using a multiobjective genetic algorithm approach. We have modified the recently introduced concept of fuzzy dominance to hybridize the well-known Nelder Mead Simplex algorithm for better exploitation with a multi-objective genetic algorithm. A coevolutionary approach is proposed to adapt the fuzzy dominance parameters. Additional changes to the previous approach have also been incorporated
doi:10.1145/1068009.1068073
dblp:conf/gecco/KoduruDWRL05
fatcat:2bmpopex4bhapgwc2lbbs2ux4a
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... e for faster convergence, including elitism. Our results suggest that this hybrid algorithm performs significantly better than NSGA-II, a standard algorithm for multiobjective optimization.
Table of Contents
2020
2020 Fourth International Conference on I-SMAC (IoT in Social, Mobile, Analytics and Cloud) (I-SMAC)
Ajitha
627
112
Integrated Cloud Internet of Things for Realtime Applications
Koduru Suresh, G Vinoth Kumar
631
113
Microcontroller based Automatic Sun Tracking Solar Panel
Ghassan Khazal Ali, ...
AroulCanessane
166
31
IoT enabled Aquaponics with wireless Sensor Smart Monitoring
Praveen C Menon
171
32
Lossless Compression Techniques for Low Bandwidth IoTs
Sudhir K. ...
doi:10.1109/i-smac49090.2020.9243441
fatcat:tmn4i477wfddzion6tzlw57wj4
INTERNATIONAL JOURNAL OF PHARMACY AND PHARMACEUTICAL ANALYSIS VALIDATED SPECTROPHOTOMETRIC ESTIMATION OF ALOGLIPTIN IN PURE AND TABLET DOSAGE FORM
2018
unpublished
Praveen kumar, G. Aruna, K. ):58-68. 10. Koduru Swathi, Kalepu swathi, Mitta chaitanya. Method development for the Simultaneous Estimation of Metformin and Alogliptin by using RP-HPLC. ...
fatcat:lzyznvfmhrav5og5byp2olfuoa
A non-dominated sorting hybrid algorithm for multi-objective optimization of engineering problems
2011
Engineering optimization (Print)
Koduru et al. (2005) used the concept of fuzzy dominance to assign a single measure of fitness to each individual. ...
Maneeratana et al. (2005) and Praveen Kumar et al. (2007) proposed a co-evolution of multiple species by splitting the population into a number of sub-populations or species that share a gene similarity ...
doi:10.1080/03052151003739598
fatcat:qv6k6rqozredpjh2iz4jxjwqxi
A putative merR family transcription factor Slr0701 regulates mercury inducible expression of MerA in the cyanobacterium Synechocystis sp. PCC6803
2019
MicrobiologyOpen
Praveen Kumar for the technical support in SPR experiments. ...
doi:10.1002/mbo3.838
pmid:31094100
pmcid:PMC6741143
fatcat:tgaqeo2covfmbckuirwbq6upxy
Abstract Listings
2010
Journal of the American College of Cardiology
Weinsaft, Jin-Ho Choi, Nina Koduru, James K. ...
Sturgeon, Sheara
Williamson, Praveen Veerabhadrappa, Deborah Crabbe, Michael D. ...
doi:10.1016/s0735-1097(10)62068-2
fatcat:5vgqcts6vzhg7f7or2i7rsl67y