1,258 research outputs found
Enterprises Public Service Platform of China
Small and medium-sized enterprises public service platform(SMEPSP for short in the following paper) is a comprehensive service platform to provide services such as technology innovation, financing guarantee, business supporting and management consulting to small and medium-sized enterprise(SME for short in the following paper). This article is based on questionnaire surveys and interviews to those service departments who have participated the construction and operation of SMEPSP. After the statistics and analysis, we have firstly summarized the main features of SMEPSP of our country; Then we have analyzed the main existing problems of SMEPSP in construction and operation, such as repeated construction of hardware and software, weak coordination and integration of resources, and so on; At last, we have come up with a countermeasure that by establishing a national level total SMEPSP, adopt unified planning and top-level designing, to perfect the system construction of SMEPSP of our country
USING CLUSTERING ALGORITHM AND FOG COMPUTING FOR EN-ROUTE FILTERING IN LOW POWER AND LOSS NETWORKS
Due to trustless link quality in Wireless Mesh Networks (WMNs), Power Outage Notification (PON) and Power Restoration Notification (PRN) messages are often dropped or delayed en-route, which may fail to satisfy customer requirements in practice. Therefore, proposed herein are techniques that use machine learning and Fog computing to efficiently deduce missing PON/PRN messages
DISASTER MANAGEMENT SYSTEM USING NETWORK SNAPSHOT IN LOW POWER AND LOSSY NETWORKS (LLNS)
Presented herein are techniques to introduce snapshot technology into wireless networks. In particular, the remote side of the network (e.g., edge devices, border routers, cloud, etc.) collect status information from all nodes of a network, such as a personal area network (PAN), while at the same time collecting and storing one or more snapshot(s) of the network. If the wireless network crashes, the remote side is configured to restore the entire network from the existing saved snapshot(s)
Land-leasing behavior, local officials’ promotions, and Chinese cities’ debt risks
This study first analyzes how local governments’ land-leasing behaviors affect Chinese cities’ debt risk then examines the impact of officials’ promotion mechanisms on debt risk in China’s urban land bank system. The land-leasing behavior is reflected through three indicators, namely, land-leasing revenue, land-leasing scale, and land financial dependence level. Two new indicators are constructed to measure the local government’ debt risk from the perspective of debt scale and debt repayment: the debt scale risk and debt burden risk. Empirical analyses are based on the data of 281 prefecture-level cities from 2006–2015. The main findings are twofold. First, the debt scale risk is positively affected by the land-leasing revenue, and officials’ promotion pressure. The debt burden risk is positively affected by the land financial dependence and officials’ promotion pressure. Second, the officials’ promotion pressure significantly enhances the positive effect of land-leasing revenue on the debt scale risk. Local officials, who are under promotion pressure, are inclined to expand the size of urban investment bonds, which increases debt scale risk
Synthesizing mixed-integer linear programming models from natural language descriptions
Numerous real-world decision-making problems can be formulated and solved
using Mixed-Integer Linear Programming (MILP) models. However, the
transformation of these problems into MILP models heavily relies on expertise
in operations research and mathematical optimization, which restricts
non-experts' accessibility to MILP. To address this challenge, we propose a
framework for automatically formulating MILP models from unstructured natural
language descriptions of decision problems, which integrates Large Language
Models (LLMs) and mathematical modeling techniques. This framework consists of
three phases: i) identification of decision variables, ii) classification of
objective and constraints, and iii) finally, generation of MILP models.
In this study, we present a constraint classification scheme and a set of
constraint templates that can guide the LLMs in synthesizing a complete MILP
model. After fine-tuning LLMs, our approach can identify and synthesize logic
constraints in addition to classic demand and resource constraints. The logic
constraints have not been studied in existing work.
To evaluate the performance of the proposed framework, we extend the NL4Opt
dataset with more problem descriptions and constraint types, and with the new
dataset, we compare our framework with one-step model generation methods
offered by LLMs. The experimental results reveal that with respect to the
accuracies of generating the correct model, objective, and constraints, our
method which integrates constraint classification and templates with LLMs
significantly outperforms the others. The prototype system that we developed
has a great potential to capture more constraints for more complex MILPs. It
opens up opportunities for developing training tools for operations research
practitioners and has the potential to be a powerful tool for automatic
decision problem modeling and solving in practice
GENETIC SIMULATED ANNEALING BASED GROUP MANAGEMENT SOLUTION FOR MULTIPLE VENDORS IN LOW-POWER AND LOSSY NETWORKS
Techniques are described herein to transform logical group traffic into a combination of broadcast and unicast messages rather than flood of broadcast messages. These techniques limit redundant traffic to manage logical group traffic over Wireless Mesh Networks (WMNs)
Joint Detection Algorithm for Multiple Cognitive Users in Spectrum Sensing
Spectrum sensing technology is a crucial aspect of modern communication
technology, serving as one of the essential techniques for efficiently
utilizing scarce information resources in tight frequency bands. This paper
first introduces three common logical circuit decision criteria in hard
decisions and analyzes their decision rigor. Building upon hard decisions, the
paper further introduces a method for multi-user spectrum sensing based on soft
decisions. Then the paper simulates the false alarm probability and detection
probability curves corresponding to the three criteria. The simulated results
of multi-user collaborative sensing indicate that the simulation process
significantly reduces false alarm probability and enhances detection
probability. This approach effectively detects spectrum resources unoccupied
during idle periods, leveraging the concept of time-division multiplexing and
rationalizing the redistribution of information resources. The entire
computation process relies on the calculation principles of power spectral
density in communication theory, involving threshold decision detection for
noise power and the sum of noise and signal power. It provides a secondary
decision detection, reflecting the perceptual decision performance of logical
detection methods with relative accuracy.Comment: https://aei.ewapublishing.org/article.html?pk=e24c40d220434209ae2fe2e984bcf2c
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