Heterogeneous Cooperative Research Articles

Heterogeneous Cooperative Teaching Method in College English Teaching

Heterogeneous Cooperative Teaching Method in College English Teaching

Titanium Tetrachloride‐Based Ionic Liquids Immobilized on Mesoporous Fe‐MCM‐41 for the Heterogeneous Cooperative Synthesis of Dihydroquinazolinones

AbstractIn this study, we report a successful strategy for the generation of a type of multifunctional heterogeneous supported ionic liquids catalysts. The synthesized supported ionic liquids (Fe‐MCM‐41/IL) were used in the catalytic cyclocondensation of 2‐aminobenzamide and various ketones and aldehydes towards the efficient synthesis of the dihydroquinazolinones under green conditions. The influence of the different catalysts and reaction parameters on the catalytic behaviors were sufficiently investigated. The supported catalyst (2)Fe‐MCM‐41/IL(0.6) showed the optimal catalytic efficiency. A hot filtration experiment revealed that the reaction proceeded in a heterogeneous pathway. The catalytic activity of (2)Fe‐MCM‐41/IL(0.6) could be maintained efficiently after recycling up to five consecutive runs under the optimized reaction conditions. Merits of this meticulously designed protocol are the use of novel supported catalyst, easy work‐up process, feasibility and sustainability, indicating its potential industrial application prospect.

GRACO: A Multimodal Dataset for Ground and Aerial Cooperative Localization and Mapping

Compared with using only a single type of robot, the use of drones and ground vehicles to jointly explore unknown areas can bring efficiency improvements. However, due to the difficulty of ground-aerial loop detection and especially the lack of ground-air datasets in large outdoor scenes, there is no good solution for ground-aerial cooperative localization technology right now. Therefore, this letter introduces a dataset to facilitate the development of multimodal Simultaneous Localization And Mapping (SLAM) as well as ground-air heterogeneous Cooperative SLAM (C-SLAM) algorithms. This dataset was collected by a group of ground and aerial robots equipped with Light Detection and Ranging (LiDAR), cameras, and Global Navigation Satellite/Inertial Navigation Systems (GNSS/INS). All sensors were well-calibrated and triggered by a self-made synchronization module, and the synchronization accuracy can reach millisecond level. The high-precision ground truth is obtained by post-processing the navigation information collected by the GNSS/INS system. There are considerable overlaps in the acquisition routes on the ground and in the air, which facilitates C-SLAM algorithms and loop detection. Also, the special installation angles in the air, and scenes such as channel and roof bring new challenges to the SLAM algorithm. We also tested several well-known algorithms on our dataset.

HCE: A Runtime System for Efficiently Supporting Heterogeneous Cooperative Execution

Heterogeneous systems with multiple different compute devices have come into common use recently, and the heterogeneity of the compute device is mainly reflected in three aspects: hardware architecture, instruction set architecture, and processing capability. Heterogeneous CPU-accelerator systems have attracted increasing attention especially. To make full use of multiple CPUs and accelerators to execute data-parallel applications, programmers may need to manually map computation and data to all available compute devices, which is tedious, error-prone, and difficult. Especially for some data-parallel applications, the inter-device communication could easily become the performance bottleneck of multi-device co-execution. Therefore, firstly, a runtime system is designed for supporting heterogeneous cooperative execution (HCE) of data-parallel applications, which can help programmers to automatically and efficiently map computation and data to multiple compute devices. Secondly, an incremental data transfer method is designed to avoid redundant data transfers between devices, and a three-way overlapping communication optimization method based on software pipelining is designed to effectively hide the inter-device communication overhead. Based on our previously proposed feedback-based dynamic and elastic task scheduling (FDETS) scheme and asynchronous-based dynamic and elastic task scheduling (ADETS) scheme, the modified FDETS that supports incremental data transfer and the modified ADETS that supports three-way overlapping communication optimization are proposed, which not only can effectively partition and balance the workload among multiple compute devices but also can significantly reduce data transfer overhead between devices. Thirdly, a prototype of the proposed runtime system is implemented, which provides a set of runtime APIs for task scheduling, device management, memory management, and transfer optimization. Our experimental results show that the communication overhead between devices is greatly reduced using the proposed inter-device communication optimization methods and the multi-device co-execution significantly outperforms the best single-device execution.

Heterogeneous Cooperative Bare-Bones Particle Swarm Optimization with Jump for High-Dimensional Problems

This paper proposes a novel Bare-Bones Particle Swarm Optimization (BBPSO) algorithm for solving high-dimensional problems. BBPSO is a variant of Particle Swarm Optimization (PSO) and is based on a Gaussian distribution. The BBPSO algorithm does not consider the selection of controllable parameters for PSO and is a simple but powerful optimization method. This algorithm, however, is vulnerable to high-dimensional problems, i.e., it easily becomes stuck at local optima and is subject to the “two steps forward, one step backward” phenomenon. This study improves its performance for high-dimensional problems by combining heterogeneous cooperation based on the exchange of information between particles to overcome the “two steps forward, one step backward” phenomenon and a jumping strategy to avoid local optima. The CEC 2010 Special Session on Large-Scale Global Optimization (LSGO) identified 20 benchmark problems that provide convenience and flexibility for comparing various optimization algorithms specifically designed for LSGO. Simulations are performed using these benchmark problems to verify the performance of the proposed optimizer by comparing the results of other variants of the PSO algorithm.

Resilient Output Containment of Heterogeneous Cooperative and Adversarial Multigroup Systems

This note introduces a new concept of cooperative and adversarial multigroup system, which consists of cooperative leaders and followers, as well as adversaries. For example, cooperation of multiple military vehicles operate in complex dynamic networked environments with unknown enemies and hidden malicious attackers. The lack of global situational awareness in distributed settings makes autonomous vehicles prone to cyberattacks and infiltration. Each agent is unaware of the motives of its neighbors and may receive information/data from both the teammates and the adversaries. Secure and resilient control protocols are essential for the networked multigroup systems to prevent the adversaries’ attacks from propagating across the network, which may influence the system performance and even overall stability. To counter sensor faults and attacks from the adversaries, a distributed resilient control architecture is proposed, which guarantees uniform ultimate boundedness of the closed-loop dynamical system. Numerical simulations illustrate the effectiveness of the proposed results.

Supporting Cooperative Dialogue in Heterogeneous Groups in Elementary Education

Literature agrees that learning in heterogeneous groups could benefit from support that structures the cooperative process, but has been inconclusive as to what this support should look like. This study investigated the effects of a worksheet that structured a heterogeneous cooperative process. The worksheet addressed the elements of social interdependence theory. Fourth to sixth graders ( n = 136) worked cooperatively in 34 heterogeneous groups of four, either with or without the worksheet. Results showed that heterogeneous cooperation benefited from the worksheet. Group members with the worksheet participated more equally in the domain-related dialogue, and a larger proportion of the group dialogue was task oriented and spent on exchanging domain-related explanations in comparison with the control group. However, adding the worksheet helped only low-ability children to increase their level of knowledge. Future research should look into possibilities for children’s learning outcomes to benefit more from improved heterogeneous group dialogue.

Applying Heterogeneous Cooperative Relay Network Based Cooperative Relay Node Selection and PSO Algorithm

In this paper a novel scheme of cooperative networks depending on the number and locations of relays in the network. The effect of relay number and locations are investigated by considering energy optimization. First selects the optimal relay from a set of available relays and then uses this “optimal” relay for cooperation between the source and the destination. The simulation-based performance analysis confirms that the cooperative relaying scheme has an advantage of diversity gain thus improving the bit error ratio performance. The simulation results demonstrate that the proposed cooperative relay node selection algorithm can improve performances by achieving the cooperative gain.

Design and Profit Allocation in Two-Echelon Heterogeneous Cooperative Logistics Network Optimization

In modern supply chain, logistics companies usually operate individually and optimization researches often concentrate on solving problems related to separate networks. Consequences like the complexity of urban transportation networks and long distance deliveries or pickups and pollution are leading problems to more expenses and more complaints from environment protection organizations. A solution approach to these issues is proposed in this article and consists in the adoption of two-echelon heterogeneous cooperative logistics networks (THCLN). The optimization methodology includes the formation of cooperative coalitions, the reallocation of customers to appropriate logistics facilities, and the determination of the best profit allocation scheme. First, a mixed integer linear programing model is introduced to minimize the total operating cost of nonempty coalitions. Thus, the Genetic Algorithm (GA) and the Particle Swarm Optimization (PSO) algorithm are hybridized to propose GA-PSO heuristics. GA-PSO is employed to provide good solutions to customer clustering units’ reallocation problem. In addition, a negotiation process is established based on logistics centers as coordinators. The case study of Chongqing city is conducted to verify the feasibility of THCLN in practice. The grand coalition and two heterogeneous subcoalitions are designed, and the collective profit is distributed based on cooperative game theory. The Minimum Cost Remaining Savings (MCRS) model is used to determine good allocation schemes and strictly monotonic path principles are considered to evaluate and decide the most appropriate coalition sequence. Comparisons proved the combination of GA-PSO and MCRS better as results are found closest to the core center. Therefore, the proposed approach can be implemented in real world environment, increase the reliability of urban logistics network, and allow decision makers to improve service efficiency.

An Opportunistic Dissemination Protocol for VANETs

In this article, we propose an Opportunistic information dissemination protocol by mixing both flooding and an enhanced DHVN (Dissemination protocol for heterogeneous Cooperative Vehicular Network) protocol, allowing them to run opportunistically in a Manhattan plan. Special additional logic is added to the existing version of DHVN protocol in order to efficiently disseminate information in two steps: 1) by adding three tags, Initial Diffusion, Standard DHVN and DHVN Near Intersection; the Initial Diffusion tag is used for the first flooding transmission only and 2) by changing the SNF (Store and Forward) period by making it adaptive depending on the region. Detailed simulation results show that our opportunistic protocol outperforms the DHVN protocol by analyzing its performances using an integrated framework VNS.

Heterogeneous Cooperative Co-Evolution Memetic Differential Evolution Algorithm for Big Data Optimization Problems

Evolutionary algorithms (EAs) have recently been suggested as a candidate for solving big data optimization problems that involve a very large number of variables and need to be analyzed in a short period of time. However, EAs face a scalability issue when dealing with big data problems. Moreover, the performance of EAs critically hinges on the utilized parameter values and operator types, thus it is impossible to design a single EA that can outperform all others in every problem instance. To address these challenges, we propose a heterogeneous framework that integrates a cooperative co-evolution method with various types of memetic algorithms. We use the cooperative co-evolution method to split the big problem into subproblems in order to increase the efficiency of the solving process. The subproblems are then solved using various heterogeneous memetic algorithms. The proposed heterogeneous framework adaptively assigns, for each solution, different operators, parameter values and a local search algorithm to efficiently explore and exploit the search space of the given problem instance. The performance of the proposed algorithm is assessed using the Big Data 2015 competition benchmark problems that contain data with and without noise. Experimental results demonstrate that the proposed algorithm, with the cooperative co-evolution method, performs better than without the cooperative co-evolution method. Furthermore, it obtained very competitive results for all tested instances, if not better, when compared to other algorithms using lower computational times.

Heterogeneous Cooperative Localization for Social Networks

Location-aware techniques has become a hot research topic with great value in commercial and military applications. Cooperative localization, which utilizes multiple sensors in portable devices to estimate locations of the mobile users in the social networks, is one of the most promising solution for the indoor geo-location. Traditional cooperative localization methods are based on ranging techniques, they are highly dependent on the distance interpreted from the received signal strength (RSS) or time of arrival from anchors. However, a precise ranging procedure demands high performance hardware which would increase the cost to the current mobile platform. In this paper, we describes four ranging-free probabilistic cooperative localization algorithms: centroid scheme, nearest neighbor scheme, kernel scheme and AP density scheme to improve the accuracy for the indoor geo-location using current mobile devices. Since the GPS sensor embedded in the smart phone is able to provide accurate location information in the outdoor area, those mobile nodes can be used as calibrated anchors. The position of the indoor mobile node can be estimated by exchanging locations and RSSs from shared wireless access points information between the target node and anchor nodes. An empirical evaluation of the system is given to demonstrate the feasibility of these cooperative localization algorithms by reporting the results in a real-world environments, e.g. suburban area and city downtown. Moreover, we compared our results with the WiFi positioning system made by Skyhook Wireless to validate the accuracy of the proposed algorithms. Meanwhile, a Monte Carlo simulation is carried out to evaluate the performance of the cooperative algorithms under different scenarios. Results show that given the same scenario setting, the AP density scheme and kernel scheme outperform than other schemes.

Selection Cooperation in Heterogeneous Cooperative Networks

Selection cooperation is an attractive cooperative strategy for wireless networks due to its simplicity and efficiency. In this paper, we consider a heterogeneous cooperative network consisting of different kinds of nodes with low-cost radios where the activities of one kind of nodes are triggered by the other kinds of nodes. This is a common scenario for many networks, such as wireless sensor networks. By exploiting the transmission relationship between heterogeneous nodes, we propose a selection cooperation protocol where inducing nodes can cooperate with the following nodes after their own transmissions for improving the communication reliability of the latter nodes. Through performance analysis, we show an interesting feature that the diversity-multiplexing tradeoff of the proposed protocol does not rely on the best relay selection method and the protocol always achieves the full diversity gain. We further develop an energy-efficient best relay selection method based on power control where the power consumption is minimized without decreasing the full diversity order. Simulation results demonstrate the good performance of the protocol and the remarkable energy reduction of the proposed best relay selection method.

Unmanned air/ground vehicles heterogeneous cooperative techniques: Current status and prospects

Multiple unmanned air/ground vehicles heterogeneous cooperation is a novel and challenging filed. Heterogeneous cooperative techniques can widen the application fields of unmanned air or ground vehicles, and enhance the effectiveness of implementing detection, search and rescue tasks. This paper mainly focused on the key issues in multiple unmanned air/ground vehicles heterogeneous cooperation, including heterogeneous flocking, formation control, formation stability, network control, and actual applications. The main problems and future directions in this field were also analyzed in detail. These innovative technologies can significantly enhance the effectiveness of implementing complicated tasks, which definitely provide a series of novel breakthroughs for the intelligence, integration and advancement of future robot systems.

A Versatile Co(bisalen) Unit for Homogeneous and Heterogeneous Cooperative Catalysis in the Hydrolytic Kinetic Resolution of Epoxides

Bisalen-very cooperative: A novel styryl-substituted, unsymmetrical bisalen is shown to be a versatile precursor to both soluble and insoluble cooperative catalysts for the hydrolytic kinetic resolution of epoxides. The unique bisalen motif ensures all catalysts derived from it have the necessary molecular-level ligand pairing needed for cooperative bimetallic catalytic reactions (see scheme).

Grounded Symbolic Communication between Heterogeneous Cooperating Robots

In this paper, we describe the implementation of a heterogeneous cooperative multi-robot system that was designed with a goal of engineering a grounded symbolic representation in a bottom-up fashion. The system comprises two autonomous mobile robots that perform cooperative cleaning. Experiments demonstrate successful purposive navigation, map building and the symbolic communication of locations in a behavior-based system. We also examine the perceived shortcomings of the system in detail and attempt to understand them in terms of contemporary knowledge of human representation and symbolic communication. From this understanding, we propose the Adaptive Symbol Grounding Hypothesis as a conception for how symbolic systems can be envisioned.