nils-herrmann/clean_scirepeval huggingface dataset:
The design of wireless air mouse based on LPC54100

With the development of the times, the traditional flat-type mouse can not meet the mobile office and entertainment on the three-dimensional space control requirements. In this context, wireless squirrels do not need any plane. In the air, gently swing the mouse can achieve large-screen control, so it has a good market prospects. In this paper, after knowing the wireless flying mouse needs to achieve the requirements of air control, wireless transmission and low power consumption, we have carried out the design of wireless flying mouse. First, according to the characteristics of low power consumption, the main part of the wireless flying mouse is chosen as below. LPC54100 Series MCU is chosen as the main controller. The motion sensor module called MPU6050 is used to receive the hand control information. Two Bluetooth supporting low-power are used as communication module. The reduced click jitter capacitance touch key module is added. Then the Altium Designer is used to design the hardware circuit and the PCB circuit board divided into two parts of the mouse and the receiving end. The program is wrote to achieve the function of controlling the computer cursor, clicking the left and right key of the mouse, low power sleep mode and Bluetooth communication. Finally the actual use effect is tested and some adjustments is made on the basis of the test.
Fast Bitstream Switching Algorithms for Real-Time Adaptive Video Multicasting

Bitstream switching among multiple bitstreams encoded at different bit rates is an effective way to address the bandwidth variation issue in transmitting multimedia over the Internet or wireless networks. This paper proposes two new fast real-time bitstream switching algorithms that aim to minimize the drifting error, while avoiding the problems of long delay, high complexity and bit-rate overhead for storage and transmission that often occur in prior solutions. The basic idea is to choose a switching point in a neighborhood with the highest encoding quality, within a switching window determined by the switching delay constraint. We show that they can significantly outperform a simple switching algorithm, and achieve performance that is closer to an offline mean-square-error-optimized bitstream switching solution, when compared to our previous work based on the similarity of the reference frames. The proposed schemes are especially useful in the scenario of real-time multicasting over dynamic heterogeneous networks, where multiple bitstreams with different bit rates are generated on the fly and dynamic bitstream switching is required for individual clients
Supporting Video Streaming Services in Infrastructure Wireless Mesh Networks: Architecture and Protocols

In this paper, we present UPAC, a unified peer-to-peer (P2P) and cache framework for high quality video-on-demand services over infrastructure multi-hop wireless mesh networks. Streaming video in multi-hop wireless networks faces many challenges, e.g., the varying available path bandwidth, interference due to shared medium, the impact of multiple relay nodes, etc. To increase the capacity of streaming services and ensure high video quality, in UPAC, the video content is cached at selected wireless mesh access points (MAPs) inside the mesh network. Furthermore peers help each other on video downloading in a best effort manner to reduce the workload imposed on the servers and networks. This unified framework has the advantages of both the content distribution network approach and peer-to-peer network approach. To obtain optimal video quality, a user device can form the P2P relationship with MAP content cache servers and other user devices. Meanwhile, the client-server relationship is established between the device and the MAP content cache servers. In addition, we propose and compare several methods to select the content cache servers for serving a device and to establish the end-to-end routes between the device and the selected servers. Our preliminary simulation results show that the proposed framework increases the number of users that can be concurrently served in the infrastructure wireless mesh network and improves the received video quality.
A format-compliant configurable encryption framework for access control of video

We introduce new methods of performing selective encryption and spatial/frequency shuffling of compressed digital content that maintain syntax compliance after content has been secured. The tools described have been proposed to the MPEG-4 Intellectual Property Management and Protection (IPMP) standardization group and have been adopted into the MPEG-4 IPMP Final Proposed Draft Amendment (FPDAM). We describe the application of the new methods to the protection of MPEG-4 video content in the wireless environment, and illustrate how they are used to leverage established encryption algorithms for the protection of only the information fields in the bitstream that are critical to the reconstructed video quality, while maintaining compliance to the syntax of MPEG-4 video, and thereby reduces the amount of data to be encrypted and guarantees the inheritance of many of the good properties of the unprotected bitstreams that have been carefully studied and built, such as error resiliency and network friendliness. The encrypted content bitstream works with many existing random access, network bandwidth adaptation, and error control techniques that have been developed for standard-compliant compressed video, thus making it especially suitable for wireless multimedia applications. Standard compliance also allows subsequent signal processing techniques to be applied to the encrypted bitstream.
The Attention Automaton: Sensing Collective User Interests in Social Network Communities

The vast quantity of information shared in social networks has brought us to an age of attention scarcity, where getting users to be attentive to a message is not a given. In fact, it has become the limiting factor in the consumption of information by end users. Understanding what captures the collective attention within a community of users in a social network is invaluable to many applications, such as product marketing, targeted advertising and social or political campaign organization. Several scholars have analyzed how information spreads in social networks under the constraint of attention. However, few papers provide a quantitative method to model and predict attention at every instant in the dynamic social web. In this paper, we propose the Attention Automaton, a probabilistic finite automata that can estimate the collective attention of some user community. Communities are based on geographical vicinity of users or having common interests (like followers of a given account) on Twitter. We identify two key factors that drive collective user attention: (1) the attention volatility of the community (frequency of change of trending topics), and (2) the selective categorical affinity of the user group towards certain trends. Our results, which are based on a eight-month dataset of Twitter trending topics across 111 geographic regions and audience trends of approximately 50 brands indicate that the proposed Attention Automaton can predict audience reception of impending trends based on categorical filters and inherent oscillations in user activity.
Greedy tree growing algorithms for designing variable rate vector quantizers

The performance of vector quantization for image compression can be improved by using a variable-rate code which is able to designate more bits to regions of an image that are active or difficult to code, and fewer bits to less active regions. Two schemes are presented for directly designing variable-rate tree-structured vector quantizers by growing the tree one node at a time. One involves selecting the node with the largest average distortion within one node to split. The other involves splitting the node with the largest eigenvalue of the input covariance matrix. A comparison with the scheme of E.A. Riskin and R.M. Gray (1991) shows that the proposed schemes perform better in terms of visual quality with reduced complexity.<<ETX>>
Resolution-progressive compression of encrypted grayscale images

Compression of encrypted data can be achieved by employing Slepian-Wolf coding (SWC). However, how to efficiently exploit the source dependency in an encrypted colored signal such as an image remains a challenging issue. Previous works incorporate 2-D Markov models in the SWC, which is not accurate enough for natural grayscale images; as a result, the compression performance is usually poor. In this paper, we propose to compress the image progressively, such that the decoder can observe a low-resolution version of the image, from which local statistics is learned and used for the decoding of the next resolution level. Good performance is observed both theoretically and experimentally.
Video Based Real-World Remote Target Tracking on Smartphones

Smartphone's increasing computing power and built-in sensors such as digital camera and GPS have created a new and open platform for developing compelling mobile multimedia tools and systems. In this paper, a novel, accurate and computationally efficient video-based remote target positioning and tracking system on Android smart phones is proposed and presented, with the assumption that the physical size of the remote target is known. Smartphone's user-friendly interface is exploited in our system to facilitate accurate and efficient video object tracking. With the help of some initial user input, our algorithm generates tight bounding boxes around the moving targets across video frames with high accuracy and low complexity. Unlike most existing video tracking systems that are limited to tracking on the image plane, we re-project the accurately detected object locations on the image plane to real world positions to estimate the remote target's moving trajectory. In addition, the Extended Kalman Filtering model is applied to provide a smooth remote target trajectory and velocity estimation. Our experimental results show that the proposed mobile multimedia system works accurately and efficiently for tracking remote moving targets.
A statistical watermark detection technique without using original images for resolving rightful ownerships of digital images

Digital watermarking has been proposed as the means for copyright protection of multimedia data. Many of existing watermarking schemes focused on the robust means to mark an image invisibly without really addressing the ends of these schemes. This paper first discusses some scenarios in which many current watermarking schemes fail to resolve the rightful ownership of an image. The key problems are then identified, and some crucial requirements for a valid invisible watermark detection are discussed. In particular, we show that, for the particular application of resolving rightful ownership using invisible watermarks, it might be crucial to require that the original image not be directly involved in the watermark detection process. A general framework for validly detecting the invisible watermarks is then proposed. Some requirements on the claimed signature/watermarks to be used for detection are discussed to prevent the existence of any counterfeit scheme. The optimal detection strategy within the framework is derived. We show the effectiveness of this technique based on some visual-model-based watermark encoding schemes.
Two fast bitstream switching algorithms for real-time adaptive multicasting of video

Bitstream switching is an effective way to deal with the bandwidth variation issue in transmitting multimedia over the Internet or wireless networks. This paper proposes two new fast intelligent bitstream switching algorithms that aim to minimize the drifting error while avoiding the problem of long delay and high complexity that often occurred in prior solutions. The basic ideas are to choose a switching point in the most stationary neighborhood or in a neighborhood with the highest encoding quality, within a switching window determined by the switching delay constraint. We show that they can achieve performance that is closer or even identical to an off-line MSE-optimized bitstream switching solution, when compared to the algorithm we previously presented in B. Xie et al. (2003). They are especially useful in the scenario of real-time multicasting over heterogeneous networks, where multiple bitstreams with different bitrates are generated on the fly and dynamic bitstream switching is required for individual clients.
High-Order Statistical Modeling Based on a Decision Tree for Distributed Video Coding

Aiming at low-complexity encoding, distributed video coding (DVC) based on the Wyner-Ziv theorem has attracted significant attention. However, there is still a compression performance gap between the state-of-the-art DVC and the conventional video coding. One of the most important factors is the efficient estimation of the source correlation statistics. The first-order Laplacian distribution has been widely used for source correlation modeling, but is not effective enough; high-order statistical modeling is necessary, but needs more context features for the estimation of a source symbol’s conditional probability. How to analyze the strength of the correlation between the source symbol and the context features in order to utilize the features effectively is crucial for such modeling. In this paper, the estimation of the source statistical distribution is first treated as a classification problem. The symbols of the source can be classified into different classes when the relevant context features are given. Then decision tree learning is introduced to analyze the strength of the correlation between the source symbol and the context features. Specifically, by constructing the decision trees composed of the selected context features, the selected context features can be organized effectively to derive the rules to estimate the current symbol’s conditional probability, upon which the high-order statistical modeling is designed. Experimental results show that the proposed model can achieve significant coding gain over existing DVC systems, especially for natural videos with high motion intensity.
An electrical-magnetic hybrid power quality compensation strategy for V/V traction power supply system

To compensate negative sequence current in highspeed railway power supply system, a novel compensation strategy based on railway power conditioner (RPC) and magnetic controlled reactor (MCR) based static var compensator (SVC) is proposed in this paper. As the traditional RPC compensation needs a big capacity, a combination of RPC and magnetic static var compensation (MSVC) is put forward. The electrical models based on fundamental and harmonic domain are analyzed. Furthermore, this paper comes up with the principle of negative current compensation and harmonic current suppression. The control strategy is proposed. The simulation results confirm the correctness of the proposed method.
Compressive sensing based secure multiparty privacy preserving framework for collaborative data-mining and signal processing

In many real-world applications, multiple parties who provide data need to collaboratively perform certain data-mining and signal processing tasks. Security and privacy protection is a critical issue in such application scenarios. In this paper, we propose a compressive sensing (CS) based privacy preserving framework for collaborative data-mining and signal processing using secure multiparty computation (MPC) in which the data-mining and the signal processing are performed in the compressive sensing domain. In our framework, the MPC protocols are used only for compressive sensing transformation and reconstruction while the data-mining/signal processing tasks are de-coupled from MPC operations. So our framework enjoys a great deal of flexibility and scalability when compared to the prior works because the decoupling allows CS transformed data to be reused and many data processing algorithms can be applied in such CS domain. Our framework also enables privacy preserving data storage in the cloud at the same time. Additionally, we develop a MPC based orthogonal matching pursuit algorithm and its corresponding MPC protocol for the CS reconstruction. Our analysis and experimental results demonstrate that the proposed framework is effective in enabling efficient privacy preserving data-mining/signal processing and storage.
Geometry based airborne LIDAR data compression

Airborne LIDAR data often consumes hundreds of gigabytes. Existing LIDAR data compression schemes can compress the file to 5%-23% of the original size. Even after compression, the compressed data size is still in the order of gigabyte, which makes it impractical for many applications. This paper proposes a novel geometry based compression scheme. It first introduces a LIDAR classification method that accurately classifies airborne LIDAR data into tree and non-tree points; different geometry based compression schemes are then applied for different types of data. The proposed method can not only compress LIDAR data significantly, but also extract useful semantic information from the data. Experimental results show that the new approach achieves very high compression ratio, making applications that were not practical before feasible.
Design Issues of the prTorrent File Sharing Protocol

The absence of piece rarity in the BitTorrent Unchoking Algorithm exposes it to various exploitations and hinders optimized performances. prTorrent is a file sharing protocol based on BitTorrent which considers rarity of pieces swapped during un choking for optimized performance within the swarm. This paper discusses the philosophies, issues and structure behind development of the prTorrent p2p protocol from scratch. The protocol was developed in Java to promote portability in simulation as well as emulation. We hope this work is a guide to students and developers planning to build a p2p simulator from the very base and alleviate design differences between simulation and emulation.
Nest: Networked smartphones for target localization

This paper presents Nest, a novel system using wirelessly connected smartphones to localize remote targets based on sound and image inputs. The system has four major components: image-based localization, acoustics-based localization, wireless ad-hoc networking, and middle-ware services for time synchronization and secure communication. Single-image, two-image, and TDOA-acoustics based methods have been developed and a prototype system has been implemented on Google Nexus One smartphones running Android. Experimental results show that the localization accuracies of the single-image-based and two-image-based method are around 94.6% and up to 92.1%, respectively. The localization errors of the acoustics-based method are within 80 centimeters.
Boundary matching detection for recovering erroneously received VQ indexes over noisy channels

This paper addresses the issue of transmitting and reconstructing vector quantization (VQ) coded images over a noisy channel. It presents a novel approach which exploits the spatial contiguity and interpixel correlation of image data sequences. Specifically, a boundary-matching-based detection algorithm (BMDA) is proposed along with a principal-component-splitting-based indexing (PCSBI) scheme which organizes the codebook in a way similar to the GLA-splitting-rule-based indexing scheme, so that some bits of an index are more important than others. Simulation results show that the proposed scheme yields significantly better visual quality and higher signal-to-noise ratio (SNR) than a maximum a posteriori (MAP) detection-based scheme, and has robust performance. It is also shown that incorporation of PCSBI with BMDA greatly reduces the detection complexity, thus facilitating the implementation of BMDA.
On Security Architecture and Functionality of Distributed Multimedia

Traditionally, security and functional features of multimedia applications have been designed largely separately. Various new requirements of and constraints on many emerging distributed multimedia applications, however, have necessitated a joint consideration of the security architecture and functionality of distributed multimedia. In this paper, we highlight the importance of the inter-play between security primitives, signal processing and networking technologies. We provide an overview of several recent approaches that aimed to address this joint design issue, including format-compliant content protection, fully scalable content protection and consumption, and signal-processing based content and network security. We discuss some potential implications in the context of emerging peer-to-peer and ad hoc sensor networks.
Source characteristics based fast bitstream switching

Bitstream switching is an effective way to deal with the bandwidth variation issue in transmitting multimedia over the Internet or wireless networks. This paper proposes a fast intelligent bitstream switching algorithm that avoids the problem of long delay and high complexity that often occurred in prior solutions. We show that it can achieve very close performance as an off-line MSE-optimized bitstream switching solution, with well-controlled quality drift. It is especially useful in the scenario of real-time multicasting over heterogeneous networks, where multiple bitstreams with different bitrates are generated on the fly and dynamic bitstream switching is required for individual clients.
Context-Adaptive Modeling for Wavelet-Domain Distributed Video Coding

The authors propose a bit-level context-adaptive correlation model to exploit high-order statistical correlation for wavelet-domain distributed video coding (DVC). The magnitude and sign of each coefficient are coded separately in a bit-plane fashion. The context for magnitude bit plane are designed based on the side information (SI), the local neighborhood, and the parent coefficient. The sign bit plane takes the sign of the SI as the context. The authors also introduce SI binning to classify the SI based on its quality. The SI's class is then included in the contexts for both magnitude coding and sign coding. Experimental results show that the proposed scheme provides significant coding gain over existing DVC systems.
Power-efficient rate allocation for Slepian-Wolf coding over wireless sensor networks

Power consumption is a critical concern in communications over wireless sensor networks (WSN). In this paper, we address the rate-allocation problem for Slepian-Wolf coding of multiple correlated sources. The goal is to find the optimal rate-point that allows lossless reconstruction of the sources, while minimizing the overall transmission power consumption of the WSN under an exponential cost model. A novel water-filling algorithm to be performed by the receiver is proposed to solve the problem in a recursive manner. The feasibility and optimality of the proposed solution are analyzed mathematically and verified experimentally. Compared to the conventional Lagrangian-multiplier approach, our algorithm achieves dramatic reduction in computational complexity.