A survey of face detection, extraction and recognition

The goal of this paper is to present a critical survey of existing literatures on human face recognition over the last 4-5 years. Interest and research activities in face recognition have increased significantly over the past few years, especially after the American airliner tragedy on September 11 in 2001. While this growth largely is driven by growing application demands, such as static matching of controlled photographs as in mug shots matching, credit card verification to surveillance video images, identification for law enforcement and authentication for banking and security system access, advances in signal analysis techniques, such as wavelets and neural networks, are also important catalysts. As the number of proposed techniques increases, survey and evaluation becomes important

Evaluation on Mengnong Clover No.1--China\u27s First Variety of Caucasian Clover (\u3cem\u3eTrifolium ambiguum Bieb.\u3c/em\u3e)

Many research reports about Caucasian clover (Trifolium ambiguum Bieb.) could be retrieved. A breeding research for Caucasian clover was started since 1996 in Inner Mongolia Agricultural University, China. The goal was to breed new varieties with strong cold resistance and drought, salt tolerance, as well as quick regenerating capacity after use. By December 2012, China\u27s first new variety of Caucasian clover - Mengnong clover No.1 (Mc No.1) was successfully registered by Forage Variety Approval Committee of Inner Mongolia Autonomous Region. Through a comparison test with red clover (T. pratense ) and white clover (T. repens), Mc No.1 showed outstanding prospects for animal forage and garden use

CBS: constraint-based approach for scheduling in bluetooth networks

In Bluetooth networks, devices are organized into small piconets and large scatternets, and each node acts as the role of master, slave or gateway. Due to dynamic topology changes, different bandwidth available and unpredictable interference of media in Bluetooth networks, the congestion of data flow will inevitably emerges on the link, and the gateway has to switch between piconets on a time division basis, so its presence in the different piconet has to be controlled by scheduling mechanism such as inter- and intra -piconet scheduling. However, the time division in gateways will limit the network capacity and introduce bottleneck points in the network, and the switch between piconets will prevent the packet from transmitting smoothly and efficiently. Most of the published work on Bluetooth scheduling has focused on the polling scheme between master and slaves. In this paper, we put our approach on the inner constraints of Bluetooth networks and present a constraint-based scheduler (CBS), to adaptively cater to the changing role of each node throughout Bluetooth ad hoc networks, thereby it will save time and definitely enhance fairness and efficiency on packet scheduling in Bluetooth environment.Facultad de Informátic

The Compensation Method of Vehicle Magnetic Interference for the Magnetic Gradiometer

The magnetic interference of vehicle imposes a strong influence on the magnetic gradiometer. Based on the mechanism of the vehicle magnetic interference, we firstly use the difference algorithm of the magnetic gradient tensor to fuse the magnetic interference of each vector magnetometer and establish a mathematical model of vehicle magnetic interference for the magnetic gradiometer. Next, we propose a compensation method for the vehicle magnetic interference and a recognition method for the estimation of compensation coefficients based on this mathematical model. The simulation results show that the proposed method can compensate as much as 96.2% of the vehicle magnetic interference efficiently

Application of symmetric orthogonal multiwavelets and prefilter technique for image compression

Multiwavelets are new addition to the body of wavelet theory. There are many types of symmetric multiwavelets such as Geronimo-Hardin-Massopust (GHM) and Chui-Lian (CL) multiwavelets. However, the matrix filter generating the GHM system multiwavelets does not satisfy the symmetric property. For this reason, this paper presents a new method to construct the symmetric orthogonal matrix filter, which leads to the symmetric orthogonal multiwavelets (SOM). Moreover, we analyze the prefilter technique, corresponding to the symmetric orthogonal matrix filter, to get a good combining frequency response. To prove the good property of SOM in image compression application, we compared the compression effect with other writers' work, which was in published literature.Facultad de Informátic

Inclusive wealth index measuring sustainable development potentials for Chinese cities

The UN Sustainable Development Goals (SDGs) are the blueprint to achieve a better and more sustainable future. To achieve the goal, tracking progress — not just on a national level, but locally — is crucial to guide future policy development. While sustainability assessment at the national evel is quite advanced in China, similar assessments focusing at the regional or even at the city-level are currently lacking. Here, we advanced the Inclusive Wealth Index (IWI) framework, which is firstly proposed by the United Nations Development Programme, through taking water wealth into account and adjusting the variable based on data availability. Then we investigate the sustainability performance of 210 cities in China in 2016 via the advanced version of the IWI framework. The analysis makes a holistic assessment based on produced, human, and natural capital, as well as considering heterogeneities in economy, social, and environmental conditions across these cities. We find that cities clustered in the eastern parts of China are characterized by high levels of sustainability performance and increasing capacities for sustainability, largely driven by their high quality and quantity of human capital. In comparison, the western cities have a large amount of low-skilled human capital and low levels of produced capital, which determines their low sustainability performance. Cities clustered in the north are heavily dependent on low value-added products and resource-intensive industries. Furthermore, we make projections of the IWI and its three components for different cities from 2020 to 2030, referring to the index systems presented in city planning which describe the development speed of income, education, fixed asset investment, forests etc. In the future, cities in central and western clusters show considerable potential for increasing IWI per capita, whereas cities with a dominant energy sector in the north would face declining capacity for sustainability due to the exhaustion of fossil fuels and raw materials. By fully taking account of and adapting to local circumstances, we tailor-design pathways for different types of cities to grow their sustainability potentials. Those resources-dependent cities in the north could avoid the impending decline by gradually developing their human and produced capital while abandoning their resource dependency. Our study contributes to city-level sustainable development in China through the lens of per capita IWI and the potential future dynamics of changing compositions in their capital

SurrealDriver: Designing Generative Driver Agent Simulation Framework in Urban Contexts based on Large Language Model

Simulation plays a critical role in the research and development of autonomous driving and intelligent transportation systems. However, the current simulation platforms exhibit limitations in the realism and diversity of agent behaviors, which impede the transfer of simulation outcomes to the real world. In this paper, we propose a generative driver agent simulation framework based on large language models (LLMs), capable of perceiving complex traffic scenarios and providing realistic driving maneuvers. Notably, we conducted interviews with 24 drivers and used their detailed descriptions of driving behavior as chain-of-thought prompts to develop a `coach agent' module, which can evaluate and assist driver agents in accumulating driving experience and developing human-like driving styles. Through practical simulation experiments and user experiments, we validate the feasibility of this framework in generating reliable driver agents and analyze the roles of each module. The results show that the framework with full architect decreased the collision rate by 81.04% and increased the human-likeness by 50%. Our research proposes the first urban context driver agent simulation framework based on LLMs and provides valuable insights into the future of agent simulation for complex tasks.Comment: 12 pages, 8 figure