SamACO: variable sampling ant colony optimization algorithm for continuous optimization

An ant colony optimization (ACO) algorithm offers algorithmic techniques for optimization by simulating the foraging behavior of a group of ants to perform incremental solution constructions and to realize a pheromone laying-and-following mechanism. Although ACO is first designed for solving discrete (combinatorial) optimization problems, the ACO procedure is also applicable to continuous optimization. This paper presents a new way of extending ACO to solving continuous optimization problems by focusing on continuous variable sampling as a key to transforming ACO from discrete optimization to continuous optimization. The proposed SamACO algorithm consists of three major steps, i.e., the generation of candidate variable values for selection, the ants’ solution construction, and the pheromone update process. The distinct characteristics of SamACO are the cooperation of a novel sampling method for discretizing the continuous search space and an efficient incremental solution construction method based on the sampled values. The performance of SamACO is tested using continuous numerical functions with unimodal and multimodal features. Compared with some state-of-the-art algorithms, including traditional ant-based algorithms and representative computational intelligence algorithms for continuous optimization, the performance of SamACO is seen competitive and promising

An ant colony optimization approach for maximizing the lifetime of heterogeneous wireless sensor networks

Maximizing the lifetime of wireless sensor networks (WSNs) is a challenging problem. Although some methods exist to address the problem in homogeneous WSNs, research on this problem in heterogeneous WSNs have progressed at a slow pace. Inspired by the promising performance of ant colony optimization (ACO) to solve combinatorial problems, this paper proposes an ACO-based approach that can maximize the lifetime of heterogeneous WSNs. The methodology is based on finding the maximum number of disjoint connected covers that satisfy both sensing coverage and network connectivity. A construction graph is designed with each vertex denoting the assignment of a device in a subset. Based on pheromone and heuristic information, the ants seek an optimal path on the construction graph to maximize the number of connected covers. The pheromone serves as a metaphor for the search experiences in building connected covers. The heuristic information is used to reflect the desirability of device assignments. A local search procedure is designed to further improve the search efficiency. The proposed approach has been applied to a variety of heterogeneous WSNs. The results show that the approach is effective and efficient in finding high-quality solutions for maximizing the lifetime of heterogeneous WSNs

Sequential optimization for efficient high-quality object proposal generation

We are motivated by the need for a generic object proposal generation algorithm which achieves good balance between object detection recall, proposal localization quality and computational efficiency. We propose a novel object proposal algorithm, BING ++, which inherits the virtue of good computational efficiency of BING [1] but significantly improves its proposal localization quality. At high level we formulate the problem of object proposal generation from a novel probabilistic perspective, based on which our BING++ manages to improve the localization quality by employing edges and segments to estimate object boundaries and update the proposals sequentially. We propose learning the parameters efficiently by searching for approximate solutions in a quantized parameter space for complexity reduction. We demonstrate the generalization of BING++ with the same fixed parameters across different object classes and datasets. Empirically our BING++ can run at half speed of BING on CPU, but significantly improve the localization quality by 18.5 and 16.7 percent on both VOC2007 and Microhsoft COCO datasets, respectively. Compared with other state-of-the-art approaches, BING++ can achieve comparable performance, but run significantly faster

New mechanism to cross the phantom divide

Recently, type Ia supernovae data appear to support a dark energy whose equation of state $w$ crosses -1, which is a much more amazing problem than the acceleration of the universe. We show that it is possible for the equation of state to cross the phantom divide by a scalar field in the gravity with an additional inverse power-law term of Ricci scalar in the Lagrangian. The necessary and sufficient condition for a universe in which the dark energy can cross the phantom divide is obtained. Some analytical solutions with $w<-1$ or $w>-1$ are obtained. A minimal coupled scalar with different potentials, including quadratic, cubic, quantic, exponential and logarithmic potentials are investigated via numerical methods, respectively. All these potentials lead to the crossing behavior. We show that it is a robust result which is hardly dependent on the concrete form of the potential of the scalar.Comment: 11 pages, 5 figs, v3: several references added, to match the published versio

Sequential drain amylase to guide drain removal following pancreatectomy

BACKGROUND: Although used as criterion for early drain removal, postoperative day (POD) 1 drain fluid amylase (DFA) ≤ 5000 U/L has low negative predictive value for clinically relevant postoperative pancreatic fistula (CR-POPF). It was hypothesized that POD3 DFA ≤ 350 could provide further information to guide early drain removal. METHODS: Data from a pancreas surgery consortium database for pancreatoduodenectomy and distal pancreatectomy patients were analyzed retrospectively. Those patients without drains or POD 1 and 3 DFA data were excluded. Patients with POD1 DFA ≤ 5000 were divided into groups based on POD3 DFA: Group A (≤350) and Group B (>350). Operative characteristics and 60-day outcomes were compared using chi-square test. RESULTS: Among 687 patients in the database, all data were available for 380. Fifty-five (14.5%) had a POD1 DFA > 5000. Among 325 with POD1 DFA ≤ 5000, 254 (78.2%) were in Group A and 71 (21.8%) in Group B. Complications (35 (49.3%) vs 87 (34.4%); p = 0.021) and CR-POPF (13 (18.3%) vs 10 (3.9%); p < 0.001) were more frequent in Group B. CONCLUSIONS: In patients with POD1 DFA ≤ 5000, POD3 DFA ≤ 350 may be a practical test to guide safe early drain removal. Further prospective testing may be useful

Phenotyping canola flowering using UAV-based phenomics

Non-Peer Reviewe

Growth, immunity and ammonia excretion of albino and normal Apostichopus japonicus (Selenka) feeding with various experimental diets

An experiment was conducted to evaluate the effects of six experimental diets on growth performance, ammonia excretion and immunity of albino and normal Apostichopus japonicus. A factorial design was used, the factors being type of diets (six levels) and colour of A. japonicus (two levels). A total of 30 randomly selected albino A. japonicus were housed in each (60 × 50 × 30 cm3) of 18 blue plastic aquaria to form six groups in triplicate, and the same set-up was used for the normal A. japonicus. Each group of animals was fed with one of the six experimental diets. Apparent dry matter digestibility (ADMD) and apparent crude protein digestibility (ACPD) were analysed using acid-insoluble ash (AIA) content method. At the end of the experiment, all A. japonicus were harvested and weighed to calculate growth parameters. After weighing, six individuals from each aquarium were randomly sampled for immune indices. Results indicated that all growth parameters of A. japonicus increased with decreasing nutrient content in their diets (p < .01), whereas an opposite result was observed in case of the ammonia-nitrogen production by A. japonicus. Normal A. japonicus grew better (p < .01) and produced lower (p < .01) quantity of ammonia nitrogen compared to the albino A. japonicus. Immunity particularly superoxide dismutase and lysozyme activities was higher (p < .05) in normal compared to albino A. japonicus. Considering all measured variables, D1 (diet containing crude protein, crude lipid, carbohydrate and crude ash 51.8, 8.7, 231.3, 708.2 g/kg, respectively) was the best diet among all experimental diets. More research is still needed to optimize nutrients in the diet of A. japonicus, as this study does not provide information about critical threshold level of nutrients in diets. Until then, diet D1 can be recommended for A. japonicus aquaculture

Exact Master Equation and Non-Markovian Decoherence for Quantum Dot Quantum Computing

In this article, we report the recent progress on decoherence dynamics of electrons in quantum dot quantum computing systems using the exact master equation we derived recently based on the Feynman-Vernon influence functional approach. The exact master equation is valid for general nanostructure systems coupled to multi-reservoirs with arbitrary spectral densities, temperatures and biases. We take the double quantum dot charge qubit system as a specific example, and discuss in details the decoherence dynamics of the charge qubit under coherence controls. The decoherence dynamics risen from the entanglement between the system and the environment is mainly non-Markovian. We further discuss the decoherence of the double-dot charge qubit induced by quantum point contact (QPC) measurement where the master equation is re-derived using the Keldysh non-equilibrium Green function technique due to the non-linear coupling between the charge qubit and the QPC. The non-Markovian decoherence dynamics in the measurement processes is extensively discussed as well.Comment: 15 pages, Invited article for the special issue "Quantum Decoherence and Entanglement" in Quantum Inf. Proces