nils-herrmann/clean_scirepeval huggingface dataset:
Agent-Based Self-Adaptable Context-Aware Network Vulnerability Assessment

Immunology inspired computer security has attracted enormous attention as its potential impacts on the next generation service-oriented network operation system. In this paper, we propose a new agent-based threat awareness assessment strategy inspired by the human immune system to dynamically adapt against attacks. Specifically, this approach is based on the dynamic reconfiguration of the file access right for system calls or logs (e.g., file rewritability) with balanced adaptability and vulnerability. Based on an information-theoretic analysis on the coherently associations of adaptability, autonomy as well as vulnerability, a generic solution is suggested to break down their coherent links. The principle is to maximize context-situation awared systems' adaptability and reduce systems' vulnerability simultaneously. Experimental results show the efficiency of the proposed biological behaviour-inspired vulnerability awareness system.
No-reference quality assessment of 3D videos based on human visual perception

Broadcasting of high definition stereoscopic 3D videos is growing rapidly because of greater demand in the mass consumer market. In spite of increasing consumer interest, poor quality, crosstalk or side effects and visual quality degradation due to packet loss during transmission has hampered the advancement of 3D visualization. The quality assessment of distorted 3D video is a crucial element in designing and arranging advanced immersive media distribution platforms. A widely accepted no-reference quality metric to measure 3D video considering the human visual system (HVS) is yet to be developed. In this paper we have proposed a quality assessment (QA) criterion that can be measured without the original video. At first, we proposed a disparity index, that is measured by region based similarity matching and then edge magnitude difference is detected for visually significant areas of the image. Finally, an assessment metric is generated to measure the 3D videos focusing on human perception. Experimental analysis with common video datasets and comparison with different algorithms shows the efficiency of the proposed algorithm for 3D stereoscopic videos in terms of perceptual characteristics.
Accurate depth estimation using structured light and passive stereo disparity estimation

In this paper we propose a new approach to depth estimation which combines structured light and passive stereo disparity estimation techniques to generate accurate disparity maps in both textured and textureless areas of a scene. We project a structured light pattern with adaptive colors onto the scene and simultaneously capture stereo images with a pair of cameras. By matching points in the projected pattern and the left image we first acquire a sparse disparity map. This sparse disparity map is interpolated and used to initialize a passive stereo disparity algorithm to improve disparity accuracy in textured areas. Finally, this map is interpolated in the textureless areas. By comparing our final map with efficient belief propagation and the initial interpolated disparity map, we show our approach performs better than using passive-only or active-only techniques.
Computer-aided interactive filter design using templates

Particular properties of symmetric lattices provide a convenient basis for the development of an empirical approach, based on templates, to the design of analog filters. These templates can be used for the design of filters with demanding specifications for attenuation and phase responses, and also for the design of equalisers. The authors present an effective interactive computer tool as part of a computer-aided approach to this problem, and presents significant extensions to the theory to enable the designer to determine the transfer function by specifying the desired attenuation at a number of points. The design leads to reactance functions that define the arms of a symmetric lattice. The transfer function of the filter is also produced, and can be used to give other realisations.
An adaptive block matching algorithm for efficient motion estimation

A new fast search algorithm for block matching motion estimation is presented in this paper. The new algorithm, called the adaptive search length (ASL) algorithm, allows the maximum number of searches for each block of the image to vary according to the difficulty in finding the optimum motion vector. The PSNR of the decoded images produced by a video coder operating with the ASL algorithm were compared with those produced by a coder operating with the full search block matching algorithm. The results presented show that, for a PSNR of within .25 dB of the full search PSNR, the ASL algorithm requires only 10% of the searches required by the full search algorithm.
Scale and rotation invariant texture features from the dual-tree complex wavelet transform

Image segmentation can be viewed as the process of classifying regions in a picture into groups with common properties (e.g., texture). A difficulty arising is that a common texture can be classified differently when viewed at different scales and rotated viewpoints. The paper presents a feature vector based on the DT-CWT (dual-tree complex wavelet transform) (Kingsbury, N., Applied and Computational Harmonic Anal., vol.10, p.234-53, 2001) that is invariant to scale and rotation. The promising image segmentation results (without cleaning misclassified regions) demonstrate the suitability of this feature vector in representing texture.
Transform-domain super resolution for improved motion-compensated prediction

This paper introduces a new approach to motion compensated prediction for video compression. A two-way motion compensation approach is utilized in which the motion compensated prediction is generated either from a super resolution mosaic accumulated using a number of previously decoded frames or from a low-resolution reference frame. The super resolution mosaic is constructed using our improved global motion estimation technique. Experimental results show that the two-way motion compensation provides a better coding gain compared with a standard motion compensation approach and moreover, in the process of super resolution mosaic construction, our robust global motion estimation process outperforms other recent motion estimation techniques when utilizing the same compression framework.
Determination of path attenuation values for hardware emulation of tactical radio networks

Modern tactical networks play an important role in success on the battlefield. Unfortunately, performance evaluation of tactical networks is cumbersome because of the scale and complexity of the underlying systems involved and the cost of deploying large numbers of systems and personnel. Simulation of the tactical network system is sound in theory; but in practice it is extremely difficult to build a suitable model for a large-scale tactical network and hence simulation often fails to approximate the system with good fidelity. An alternative is to emulate the tactical channels carrying signals from real radios. This can conveniently be implemented in a laboratory environment using one or more multiport radio frequency (RF) hubs with variable attenuation on each port to be able to emulate the radio path loss between any two radios. The problem in this emulation approach is the determination of the appropriate port attenuation to match the multi-dimensional link losses (signal attenuations) between multiple radios of a real tactical network. A tactical network with N radios has N(N-1)/2 network links which are characterised by their respective link losses. The emulator network with N radios has N connections between the multiport hub and N radios of the network. The problem is therefore selecting the set of N attenuation values of the N port hub to match N(N-1)/2 link losses of tactical networks. This is a constraint satisfaction problem (CSP). We describe an algorithm based on Freuder's solution synthesis to find the solution to the CSP.
Routing challenges and solutions for underwater networks

Routing is one of the fundamental concerns in any communication network. Over the last two decades, a significant amount of attention has been given to the design of terrestrial routing protocols. However, the distinctive properties of the underwater communication channel - such as distance-dependent bandwidth, large propagation delay and time-varying mulitpath - render the existing terrestrial routing protocols implausible for underwater networks. In this paper we explore the challenges in developing a suitable routing protocol for underwater networks. We also look at existing routing protocols designed for both terrestrial and underwater networks, identify their shortcomings and finally lay out some guidelines for the design of routing protocols suitable for next generation underwater networks/applications.
A Hybrid Distance-measurement/Angle-of-arrival Approach to Localization

Localization has received considerable attention because many wireless sensor network applications require accurate knowledge of the locations of the sensors in the network. The two main localization techniques are distance measurement and angle-of-arrival measurement. The former requires extensive calculations to resolve sign ambiguities in calculated angles, while the latter requires careful calibration to provide high accuracy. In this paper, we describe a hybrid technique, in which low-accuracy estimates of the angle-of-arrival are used to resolve the sign ambiguity in distance measurements. In many practical situations, the ambiguity can be resolved with a high probability of success even with an RMS error as high as 30 degrees in the line-of-bearing estimate, which avoids the need for calibration. Early resolution of this sign ambiguity can be used to develop lower-complexity localization techniques using distance measurement.
A robust codec for transmission of very low bit-rate video over channels with bursty errors

We describe a robust codec for the transmission of very low bit-rate video over channels with a variety of errors, including random and bursty bit errors and packet loss. The codec exploits adaptivity to give good performance with a low overhead. By only protecting macroblocks which would otherwise be poorly concealed by the decoder the codec allows adaptive selection of the parts of video to protect. For protection, it uses multiple description codes which indirectly provide frequency-based adaptivity by protecting the more significant DCT coefficients. Simulations show significant improvements in the performance of the codec when compared to codecs which use intra macroblock updating (raster scan and random) at the same overhead. The codec is efficient in its use of bits and has good error resilience properties both objectively and subjectively over a wide range of conditions. Further, transcoding of the received bit stream to the standard H.263 syntax is relatively easy.
Experimental investigation of Signal-to-Noise Ratio gain and stochastic resonance for filtered signals in static nonlinearities

It has been shown that certain static nonlinearities that display stochastic resonant behaviour can be used as Signal-to-Noise Ratio amplifiers for a sinusoidal signal corrupted by noise, and that such nonlinearities can serve as pre-processors for further linear processing. We demonstrate that by swapping the roles of pre-processor and processor, i.e. by using a linear filter as a pre-processor for the nonlinearity, the resonant character of the curves is preserved, but with significant improvements of SNR gain. This is demonstrated on nonlinearities otherwise incapable of producing SNR gain greater than unity.
Quality tradeoffs for packet video over differentiated services networks

Differentiated services networks can only function effectively if an appropriate mix of traffic can be maintained in all service classes using a practical pricing model. Previous work has noted that the same video sequence being distributed to clients who are prepared to pay different amounts for the service results in traffic distributions that vary considerably between those clients. It is shown that this variation can be reduced by trading off coding distortion and the amount of protection given to packets. As a result, a simple pricing model provides stable traffic distributions over a wide range of network conditions and client budgets.
Self-provisioning of network services with quantum-inspired reinforcement learning and adaptation

In this paper, a quantum-inspired reinforcement learning (QiRL) algorithm is proposed for self-configuring network services in next generation networks. A new learning and adaptation scheme based on QiRL facilitates the optimal operation for multiple classes of managed elements on a network Operations Support Systems (OSSs). QiRL algorithm adopts a probabilistic action selection policy and a new reinforcement strategy inspired by amplitude amplification in quantum computation. It is also characterized by learning and adaptation capabilities against dynamic environment changes and uncertainties. The algorithm is adapted to be suitable for the network service configuration process, which is simply redefined as: the managed elements represented as graphic nodes, and aware of the environment, select nodes with the minimum cost constraints until the eligible network elements are located along near-optimal paths; the located elements are those needed for the configuration or activation of a particular product and service. The results demonstrate the effectiveness of the proposed method.
Undersea electromagnetic networking

The variation of through-water electromagnetic wave propagation parameters with frequency and conductivity is discussed together with wideband signal distortion caused by dispersion. Environmental electromagnetic noise and its limitation on the underwater communication range of various antennas are examined. Submarine communication and heuristic models of antenna types are presented, together with supporting experimental validation, and practical comment is made on potential range and bandwidth capabilities of generic antenna systems, and on current directions of research and development, including high frequency and dual mode subsea communications.
Asynchronous test hardware for Null Convention Logic

Asynchronous design is predicted to have a significant place in the future due to benefits of speed, power consumption, and design. Null Convention Logic (NCL) is a subcategory of asynchronous design that results in the most reliable and low-power asynchronous hardware. However, test strategies are not adopted to match the characteristics of this important asynchronous method, and the existing test methods for NCL use synchronous test hardware. In this paper asynchronous test hardware is proposed for testing NCL-based circuits to avoid problems of synchronous design as well as the need for asynchronous-synchronous interfaces and clock trees. The proposed test hardware is implemented in HDL and synthesised to define design characteristic and improvements over previous work.
Two-shot sparse depth estimation using adaptive structured light

Presented is a low-cost two-shot approach employing a projector and a camera to recover an object's sparse shape. The algorithm is based on projecting a grid pattern of adaptive colours which vary with the object and then matching grid points between the projected pattern and the image captured under this adaptive structured light. Results show the performance of this adaptive colours approach is superior to using constant colours in shape recovery of real-world objects with strong colours and textures under ambient light conditions.
Escape from stable equilibria in blind adaptive equalizers

The authors apply diffusion modeling and large deviations theory to obtain information about the behavior of blind adaptive equalizers when leaving local equilibria. In particular, they obtain estimates of the asymptotic behavior of the expected value of the exit time, and also about which trajectories are likely when an exit occurs. The conclusions drawn are that the residence times for local equilibria are (exponentially) much shorter than for the global minimum, the principal factors dictating this exponent being the step size of the adaptive process and prediction error variance at the equilibrium point. Some simulation results are included to support the theory.<<ETX>>
Simultaneous tracking and registration in a multisensor surveillance system

In this paper, we present a multisensor surveillance system that consists of an optical sensor and an infrared sensor. In this system, a background subtraction method based on zero-order statistics is utilized for the moving object segmentation. Additionally, we propose a generic approach to simultaneous object tracking and multisensor image registration. An efficient face detection system is shown as an application that will have enhanced performance from the registration and fusion of the information from the two sensors. Experimental results show the efficacy of the proposed system.
A Low-Complexity Image Registration Algorithm for Global Motion Estimation

An important recent application of image registration is the estimation of global motion parameters for object-based video coding. However, the main disadvantage of standard approaches to global motion estimation (GME) is the increased computational complexity with the higher degree of motion models when compared to block-based local motion estimation approaches. In this paper, we propose a new low complexity GME algorithm. In our proposed algorithm, full-precision images are replaced with 1 bit-per-pixel images which allows many of the arithmetic operations in the standard GME approach to be replaced with logic operations. Experimental results show that our proposed algorithm achieves the same registration accuracy as the standard GME approach but with significantly reduced computational complexity. Our results also demonstrate the superior performance of the proposed algorithm when compared with previously proposed low-complexity GME approaches.
Efficient multi-image registration with illumination and lens distortion correction

In this paper, we propose some extensions of an efficient gradient-based image registration method called the inverse compositional algorithm. Specifically, these extensions include cumulative multi-image registration and incorporations of illumination change and lens distortion correction. By combining these extensions, we propose efficient cumulative multi-image registration methods with illumination and lens distortion correction. It is shown that high efficiency can still be achieved for multiple images using the proposed methods. Some experimental results show the efficacy of the proposed methods.
An architectural framework for modern tactical communications systems

This paper develops an architectural framework to define an appropriate tactical communications system for modern land forces. It begins by outlining key design drivers that shape the architecture of a tactical communications system. Options for a mobile tactical communications system are then examined and it is concluded that, whilst it is essential that the tactical communications system provides a single logical network, it is not possible to provide a single physical network. The range of candidate technologies available to provide access to mobile users constrains the physical architecture to the provision of five major sub-systems. The underlying infrastructure of the organic network is provided by the tactical trunk sub-system and the combat radio sub-system. To extend the range of these two sub-systems in dispersed operations, a tactical airborne sub-system is required. Additionally, there is not sufficient capacity in the combat radio sub-system (in particular) to cope with the high volume of data transfer required to support real-time situational awareness for commanders of combat forces-this need is met by the tactical data distribution sub-system. A local subsystem is proposed to simplify the user interface to the other communications sub-systems.
Image Segmentation using Invariant Texture Features from the Double Dyadic Dual-Tree Complex Wavelet Transform

In this paper we propose a new texture segmentation technique that produces segmentation results which more closely match the manual segmentation that would be performed by a human operator. To perform this type of segmentation, we propose a new texture feature based on the double dyadic dual-tree complex wavelet transform (D3T-CWT) which provides the ability to analyse a signal at and between dyadic scales. This new texture feature is invariant to shift, rotation and scale and hence can group the texture features in a single object (which may have different sizes and orientations) into a single more meaningful segment. When compared with other texture segmentation approaches, the proposed approach provides segmentation results which more closely match the semantically meaningful objects in the scene.
Estimating the Number and Distribution of the Neighbors in an Underwater Communication Network

Here we present a procedure for estimating the number and distribution of neighbors (nodes withindirect transmission range) with a specified accuracy for an underwater communication network (UCN). The capture effect can degrade the performance of a neighbor-counting procedure, so our estimation procedure is based on a property that is not affected by the capture effect. The procedure for estimating the neighbor's distribution is derived with the help of the capture effect. The two procedures are carried out concurrently. The time taken for estimation is independent of the number of neighbors and the procedure is therefore suitable for networks of all sizes. We further show by a performance and sensitivity analysis that the procedure of estimating the distribution is robust and is applicable to both UCNs and terrestrial communications networks (TCNs).
Arobust approach to super-resolution sprite generation

In this paper, we propose a robust approach to super-resolution static sprite generation from multiple low-resolution images. Considering both short-term and long-term motion influences, a hybrid global motion estimation technique is first presented for sprite generation. An iterative super-resolution reconstruction algorithm is then proposed for the super-resolution sprite construction. This algorithm is robust to outliers and results in a sprite image with high visual quality. In addition, the generated super-resolution sprite can provide better reconstructed images than a conventional low-resolution sprite. Experimental results demonstrate the effectiveness of the proposed methods.