Genetic algorithm hybridized with multilayer perceptron to have an economical slope stability design

The present work aimed to evaluate and optimize the design of an artificial neural network (ANN) combined with an optimization algorithm of genetic algorithm (GA) for the calculation of slope stability safety factors (SF) in a pure cohesive slope. To make datasets of training and testing for the developed predictive models, 630 finite element limit equilibrium (FELE) analyses were performed. Similar to many artificial intelligence-based solutions, the database was involved in 189 testing datasets (e.g., 30% of the entire database) and 441 training datasets; for example, a range of 70% of the total database. Moreover, variables of multilayer perceptron (MLP) algorithm (for example, number of nodes in any hidden layer) and the algorithm of GA like population size was optimized by utilizing a series of trial and error process. The parameters in input, which were used in the analysis, consist of slope angle (β), setback distance ratio (b/B), applied stresses on the slope (F_y) and undrained shear strength of the cohesive soil (C_u) where the output was taken SF. The obtained network outputs for both datasets from MLP and GA-MLP models are evaluated according to many statistical indices. A total of 72 MLP trial and error (e.g., parameter study) the optimal architecture of 4 × 8 × 1 were determined for the MLP structure. Both proposed techniques result in a proper performance; however, according to the statistical indices, the GA–MLP model can somewhat accomplish the least mean square error (MSE) when compared to MLP. In an optimized GA–MLP network, coefficient of determination (R²) and root mean square error (RMSE) values of (0.975, and 0.097) and (0.969, and 0.107) were found, respectively, to both of the normalized training and testing datasets.

     

Nonlinear evolutionary swarm intelligence of grasshopper optimization algorithm and gray wolf optimization for weight adjustment of neural network

Engineering with Computers - The advent of new data-mining techniques and, more recently, swarm-based optimization algorithms have antiquated traditional models in the field of energy performance...     

Potential uses of kairomones for behavioral manipulation ofCotesia marginiventris (Cresson)

The effects of kairomone pattern and preconditioning on parasitization rates of fall armyworm larvae,Spodoptera frugiperda (J.E. Smith) byCotesia (=Apanteles)marginiventris (Cresson) were investigated in the laboratory and greenhouse using a hexane extract of frass and actual fall armyworm frass. Parasitization rates increased 55 and 26% in Petri dishes and on corn seedlings, respectively, when the entire experimental area was sprayed with the frass extract. Applying the extract in spots resulted in a 20–30% reduction in parasitization compared to treating the entire area. However, spot application produced significantly better parasitization rates compared to the control treatment. Exposing the parasitoids to actual fall armyworm frass resulted in ca. 50% greater retention in the release area and an increase of ca. 60–75% in the number of parasitoids searching.C. marginiventris parasitized factitious hosts topically treated with an extract of fall armyworm frass.Mention of a commercial or proprietary product does not constitute an endorsement by the USDA.Submitted in partial fulfillment of the requirements for the degree Doctor of Philosophy, Department of Entomology and Nematology, University of Florida, Gainesville     

Acrylic-based fire-retardant coatings for steel protection: Employing the concept of in situ ceramization

Traditional intumescent coatings are widely used as passive fire-protective coatings for steel structures as they are capable of expanding in the range of 20–50 times the original thickness thereby providing excellent insulation. However, the fragile nature of such residue and susceptibility to thermo-oxidation given their carbonaceous nature are key problematic issues. The concept of in situ ceramization is explored in this work as a means to form inorganic cohesive char with improved rigidity and thermo-oxidative stability. Coating samples were prepared by incorporating ammonium polyphosphate, talc, Mg(OH)₂, and polydimethylsiloxane as additives into acrylic resin at different weight fractions. Thermal analysis and x-ray diffraction have confirmed the reactions between the additives to form various crystalline magnesium phosphate phases, and to a small extent, silicon phosphate, thereby ensuring the thermo-oxidative stability of the residue. This is reiterated by the fire performance tests (by exposing the coatings to a temperature profile in a furnace similar to ISO 834 fire curve). Despite the advantages of rigid char and its thermo-oxidative stability as a result of formation of inorganic phosphates, the lack of swelling has resulted in relatively poor insulation capabilities of the char, and subsequently, compromised the fire protection times (that are in the range of 45–55 min). However, pyrolysis flow combustion calorimeter results of the coatings are promising and have shown a significant drop of up to 70% in the peak of heat release rate values as compared to neat resin.     

Building Taskable Spaces over Ubiquitous Services

Task-based abstraction can express user tasks via underlying services with minimal effort. However, developers must first address several issues including task execution transparency, exception handling, ontologies, and abstract architecture design.     

Energy and Trust Management Framework for MANET using Clustering Algorithm

In General, Mobile Ad-Hoc Network (MANET) has limited energy resources, and it cannot recharge itself. This research goal focuses on building a power management scheme that saves energy in the MANET. Due to power instability, there is a chance that cluster heads fail and function incorrectly in cluster-based routing. As a result, instability occurs with the cluster heads while collecting data and communicating with others effectively. This work focuses on detecting the unstable cluster heads, which are replaced by other nodes implementing the envisaged self-configurable cluster mechanism. A self-configurable cluster mechanism with a k-means protocol approach is proposed to designate cluster heads effectively. The proposed k-means procedure is based on periodic irregular cluster head rotations or altering the number of clusters. We also propose a trust management mechanism in this research to detect and avoid MANET vulnerabilities. Because of the continuously changing topology and limited resources (power, bandwidth, computing), the trust management algorithm should only use local data. Consequently, compared to traditional protocols, the proposed approach with the k-means procedure and its experimental results show lower power usage and provide an optimal system for trust management.

     

Scheduling on Unrelated Machines under Tree-Like Precedence Constraints

We present polylogarithmic approximations for the R|prec|C _max and R|prec|∑ _j w _j C _j problems, when the precedence constraints are “treelike”—i.e., when the undirected graph underlying the precedences is a forest. These are the first non-trivial generalizations of the job shop scheduling problem to scheduling with precedence constraints that are not just chains. These are also the first non-trivial results for the weighted completion time objective on unrelated machines with precedence constraints of any kind. We obtain improved bounds for the weighted completion time and flow time for the case of chains with restricted assignment—this generalizes the job shop problem to these objective functions. We use the same lower bound of “congestion + dilation”, as in other job shop scheduling approaches (e.g. Shmoys, Stein and Wein, SIAM J. Comput. 23, 617–632, 1994). The first step in our algorithm for the R|prec|C _max problem with treelike precedences involves using the algorithm of Lenstra, Shmoys and Tardos to obtain a processor assignment with the congestion + dilation value within a constant factor of the optimal. We then show how to generalize the random-delays technique of Leighton, Maggs and Rao to the case of trees. For the special case of chains, we show a dependent rounding technique which leads to a bicriteria approximation algorithm for minimizing the flow time, a notoriously hard objective function. A preliminary version of this paper appeared in the Proc. International Workshop on Approximation Algorithms for Combinatorial Optimization Problems (APPROX), pages 146–157, 2005. V.S. Anil Kumar supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. M.V. Marathe supported in part by NSF Award CNS-0626964. Part of this work was done while at the Los Alamos National Laboratory, and supported in part by the Department of Energy under Contract W-7405-ENG-36. Part of this work by S. Parthasarathy was done while at the Department of Computer Science, University of Maryland, College Park, MD 20742, and in part while visiting the Los Alamos National Laboratory. Research supported in part by NSF Award CCR-0208005 and NSF ITR Award CNS-0426683. Research of A. Srinivasan supported in part by NSF Award CCR-0208005, NSF ITR Award CNS-0426683, and NSF Award CNS-0626636.     

A queue based mutual exclusion algorithm

A new elegant and simple algorithm for mutual exclusion of N processes is proposed. It only requires shared variables in a memory model where shared variables need not be accessed atomically. We prove mutual exclusion by reformulating the algorithm as a transition system (automaton), and applying simulation of automata. The proof has been verified with the higher-order interactive theorem prover PVS. Under an additional atomicity assumption, the algorithm is starvation free, and we conjecture that no competing process is passed by any other process more than once. This conjecture was verified by model checking for systems with at most five processes.     

Nonatomic dual bakery algorithm with bounded tokens

A simple mutual exclusion algorithm is presented that only uses nonatomic shared variables of bounded size, and that satisfies bounded overtaking. When the shared variables behave atomically, it has the first-come-first-served property (FCFS). Nonatomic access makes information vulnerable. The effects of this can be mitigated by minimizing the information and by spreading it over more variables. The design approach adopted here begins with such mitigating efforts. These resulted in an algorithm with a proof of correctness, first for atomic variables. This proof is then used as a blueprint for the simultaneous development of the algorithm for nonatomic variables and its proof. Mutual exclusion is proved by means of invariants. Bounded overtaking and liveness under weak fairness are proved with invariants and variant functions. Liveness under weak fairness is formalized and proved in a set-theoretic version of temporal logic. All these assertions are verified with the proof assistant PVS. We heavily rely on the possibility offered by a proof assistant like PVS to reuse proofs developed for one context in a different context.