Summary The cloud infrastructures provide a suitable environment for the execution of large‐scale scientific workflow application. However, it raises new challenges to efficiently allocate resources application and also meet user's quality service requirements. In this paper, we propose an adaptive penalty function strict constraints compared with other genetic algorithms. Moreover, coevolution approach is used adjust crossover mutation probability, which able accelerate convergence prevent...

Domain adaptation aims to train a model on labeled data from source domain while minimizing test error target domain. Most of existing methods only focus reducing shift single-modal data. In this paper, we consider new problem multimodal and propose unified framework solve it. The proposed neural networks(MDANN) consist three important modules. (1) A covariant attention is designed learn common feature representation for multiple modalities. (2) fusion module adaptively fuses attended...

In the context of circular economy, high quantity agroforestry waste should be transformed into sustainable and high-value materials to abate pollution, CO2 emissions, expensive disposal. Herein, apple leaves was initially used as a precursor extract value-added nanomaterial carbon quantum dots (CQDs) by way an easy hydrothermal strategy without complicated purification processes, extracted CQDs doped with N P possess typical graphite-like structure, fine particle size 2.0 nm,...

Cloudlet provides services with low latency and high bandwidth. Some research addresses the resource allocation problem in cloudlet-based mobile cloud computing environment. However, there are few works considering how to optimize while satisfying users' requirements multicloudlet situations. To solve this problem, a two-stage optimization strategy is proposed. First, cloudlet selection model based on mixed integer linear programming (MILP) proposed obtain for users by optimizing mean...

Introduction Multimodal anticancer therapies greatly damage the fertility of breast cancer patients, which raises urgent demand for preservation. The standard options preservation are oocyte and embryo cryopreservation; both require controlled ovarian hyperstimulation (COH). However, there safety concerns regarding relapse due to elevated serum estradiol levels during COH. Serum can be effectively decreased with highly specific aromatase inhibitor letrozole. Letrozole is still uncommonly...

By leveraging the technology of mobile cloud computing, resource capacity, and computing capability devices could be extended. However, it is difficult to schedule tasks submitted by users when number service providers increases optimize multiple objectives while satisfying users' requirements. In this paper, task scheduling modeled as a multi-objective optimization problem we consider both unconstrained time deadline constrained cases. To address problem, heterogeneous earliest finish...

The liquid-phase method is the most commonly utilized strategy for synthesizing fluorescent carbon quantum dots (CQDs). However, synthesis of CQDs faces challenges such as low yield, complex purification, and use toxic solvents, which limit large-scale production practical applications. In this study, with a high product yield 78% were synthesized using glucose source through green facile one-step solid-phase approach, without solvents or post-treatment. A systematic study structure...

With the rapid development of 5G mobile networks services, massive data explodes in network edge. Cloud computing services suffer from long latency and huge bandwidth requirement. Edge has become key technology reducing service delay traffic load networks. However, how to intelligently schedule tasks edge environment is still a critical challenge. In this paper, we define optimization problem minimizing for task scheduling cloud-edge architecture. The proved NP-hard modeled following Markov...

This paper addresses video highlight detection which aims to select a small subset of frames according user's major or special interest. The performances conventional methods highly depend on large-scale manually labeled training data are time-consuming and labor-intensive collect. To deal with this problem, we trace back the original problem definition find that whether user is interested in specific segment heavily depends human's subjective emotions. Leveraging insight, introduce an...

We propose an adaptive search algorithm for solving simulation optimization problems with Lipschitz continuous objective functions. The method combines the strength of several popular strategies in optimization. It employs shrinking ball to estimate performance sampled solutions and uses estimates fit a surrogate model that iteratively approximates response surface function. improved at each iteration is then based on sampling from promising region (a subset decision space) adaptively...

The model-based methods have recently found widespread applications in solving hard nondifferentiable optimization problems. These algorithms are population-based and typically require hundreds of candidate solutions to be sampled at each iteration. In addition, recent convergence analysis these also stipulates a sample size that increases polynomially with the number iterations. this article, we aim improve efficiency by reducing generated per This is carried out through embedding...

Recently, the exploitation of cloud resources for augmenting mobile devices leads to emergence a new research area called Mobile Cloud Computing (MCC). In this work, we present survey and taxonomy MCC architecture, characteristics, open issues aim explore deep in area. We based on key while highlighting specific concerns MCC, discuss related approaches taken tackle these issues. Furthermore, direction future work is discussed.

Abstract The utilization of anti‐CD3/CD28 magnetic beads for T cell expansion in vitro has been investigated adoptive transfer therapy. However, the impact CD3/CD28 antibody ratio on differentiation and function remains incompletely elucidated. This study seeks to address this knowledge gap. To begin with, CD3 antibodies with a relatively low avidity Jurkat cells (Kd = 13.55 nM) CD28 high 5.79 were prepared. Afterwards, different mass ratios attached examine impacts capture, proliferation....

In this work, we adopt Apriori Algorithm to explore the relationship between treatment preferences and survival of breast cancer patient based on other medical attributes. The SEER Public-Use Data 2005 is used in research. After preprocessing dataset, apply algorithm Association Rules. As a result, obtain great deal association rules related. We pick up some easy understandable comparable discuss show that data mining technique efficient method survivability. Medical experts could continue...

Partner selection with due date constraint has been proved to be NP-complete problem, and it is difficult solve by the traditional optimization methods. In paper, a novel gravitational chaotic search algorithm (GCSA) proposed, firstly used partner problem. By combining local search, hybrid can not only avoid disadvantage of easily getting optional solution in later evolution period, but also keep rapid convergence performance. The simulation results show that efficient.

Service selection based on users preference and service deployment are challenge due to the diversity of user demands preferences in multi-cloud environment. Few works have clearly reviewed existing for preference-oriented In this paper, we propose motivate taxonomies deployment. We present a detailed survey state art terms description analysis preference, optimization objectives constraints. Finally, analyze discuss future work area multi-Cloud preference.

We propose a random search algorithm for solving simulation optimization problems with continuous decision variables. The combines ideas from promising area search, shrinking ball methods, and surrogate model optimization. discuss the local convergence property of provide numerical examples to illustrate its performance.

Mobile cloud computing (MCC) can offload heavy computation from mobile devices onto nearby cloudlets or remote to improve the performance as well save energy for these devices.Therefore, it is essential consider how achieve efficient offloading with constraints multiple users.However, there are few works that aim at multi-objective problem users.Most existing concentrate on only single objective optimization obtain a tradeoff solution objectives by simply setting weight values.In this paper,...

Mobile cloud computing (MCC) is the integration of mobile and computing. It provides an opportunity for users to obtain resources over internet. Resource allocation a complex problem owing presence heterogeneous application workloads in MCC. In recent years, few studies have clearly analysed research surveyed resource MCC environment. Hence, it very important provide comprehensive review complement existing literature this paper, survey made MCC, state-of-the-art strategies presented. The...

We propose a random search algorithm for solving simulation optimization problems with continuous decision variables. The combines ideas from promising area search, shrinking ball methods, and surrogate model optimization. discuss the local convergence property of provide numerical examples to illustrate its performance.