varunr14/newsummary huggingface dataset:
Geometric partial differential equations for curves and surfaces are used in many fields such as computational geometry image processing and computer graphics . In this paper a few differential operators defined on space curves are introduced . Based on these operators several second order and fourth order geometric flows for evolving space curves are constructed . Some properties of the changing rates of the arc length of the evolved curves and areas swept by the curves are discussed . Short term and long term behaviors of the evolved curves are illustrated . 


Summary: Several second and fourth order geometric partial differential equations for space curves are constructed. Changing rates of the arc length of the evolved curves and areas swept by the curves are discussed. Short term and long term behaviors of the evolved curves are illustrated.
Femtocells offer many advantages in wireless networks such as improved cell capacity and coverage in indoor areas . As these femtocells can be deployed in an ad hoc manner by different consumers in the same frequency band the femtocells can interfere with each other . To fully realize the potential of the femtocells it is necessary to allocate resources to them in such a way that interference is mitigated . We propose a distributed resource allocation algorithm for femtocell networks that is modelled after link state routing protocols . Resource allocation using Link State Propagation consists of a graph formation stage where individual femtocells build a view of the network an allocation stage where every femtocell executes an algorithm to assign OFDMA resources to all the femtocells in the network and local scheduling stage where a femtocell assigns resources to all user equipments based on their throughput requirements . Our evaluation shows that RALP performs better than existing femtocell resource allocation algorithms with respect to spatial reuse and satisfaction rate of required throughput . 


Summary: RALP local scheduler RALP uses messages exchanges and a global allocation algorithm to assign allocation units AUs to the various FAPs. In this article we have proposed a local scheduling scheme that each FAP uses to assign AUs to the various user equipments Ues . The algorithm uses the modulation and coding scheme MCS of the AUs to do the assignment. The global allocation algorithm assigns AUs to the various FAPs. However one FAP might require more AUs than what it has been assigned. If the neighboring FAPs are not using all their assigned AUs then this FAP can borrow AUs from the neighboring FAPs and use it to satisfy its requirements. The borrowing algorithm describes how FAPs can borrow AUs from other FAPs. RALP s main disadvantage is its convergence time as the message exchange rounds depend on the neighborhood graph. In this article we introduce the concept of clusters where the data transfer can proceed after a certain number of message exchange rounds.
Multi projector displays allow the realization of large and immersive projection environments by allowing the tiling of projections from multiple projectors . Such tiled displays require real time geometrical warping of the content that is being projected from each projector . This geometrical warping is a computationally intensive operation and is typically applied using high end graphics processing units that are able to process a defined number of projector channels . Furthermore this limits the applicability of such multi projector display systems only to the content that is being generated using desktop based systems . In this paper we propose a platform independent FPGA based scalable hardware architecture for geometric correction of projected content that allows addition of each projector channel at a fractional increase in logic area . The proposed scheme provides real time correction of HD quality video streams and thus enables the use of this technology for embedded and standalone devices . 


Summary: Multi projector rendering allows immersive projection on large projection surfaces. Such multi projector schemes require dedicated GPU based systems to perform rendering. Our work proposes an embedded and standalone system for performing multi projector rendering. The system applied the geometric correction in real time without using LUTs.
This paper addresses the problem of determining the symmetries of a plane or space curve defined by a rational parametrization . We provide effective methods to compute the involution and rotation symmetries for the planar case . As for space curves our method finds the involutions in all cases and all the rotation symmetries in the particular case of Pythagorean hodograph curves . Our algorithms solve these problems without converting to implicit form . Instead we make use of a relationship between two proper parametrizations of the same curve which leads to algorithms that involve only univariate polynomials . These algorithms have been implemented and tested in the Sage system . 


Summary: We provide a deterministic method to detect symmetries of rational curves. The method detects all the symmetries of plane rational curves. The method also finds all the involutions of space rational curves. In the space case the method detects also rotational symmetry of PHR curves.
In a plasma display panel ramp pulse is used for the reset operation . In this case the stability of ramp slope is very important because the variation of ramp slope leads to the reset failure . However the ramp slope is affected by the image load and operation temperature . In this paper the variation of ramp slope is analyzed and a new ramp driver circuit is proposed . In the proposed driver circuit the effect of image load is compensated for by redesigning the current path of the feedback capacitor . The slope variation caused by temperature variation is reduced by compensating for the threshold voltage shift of a MOSFET . The proposed ramp driver circuit provides multiple ramp slopes by adjusting the control signal and guarantees the stability of ramp slope against the changes of image load and temperature . The variation of ramp slope in the proposed method is reduced by 82.7 compared with the previous switched ramp driver circuit . Moreover the additional hardware cost of the proposed driver circuit is minimal . 


Summary: Ramp slope variation by image load and temperature is analyzed. Slope variation caused by image load is compensated for by redesigning feedback current path in the driver circuit. Slope variation caused by VT shift is compensated for by adjusting the gate voltage. A new and cost effective ramp driver circuit for an AC PDP is proposed.
A fundamental goal of datacenter networking is to efficiently interconnect a large number of servers in a cost effective way . Inspired by the commodity servers in today s data centers that come with dual port we consider how to design low cost robust and symmetrical network structures for containerized data centers with dual port servers and low end switches . In this paper we propose a family of such network structure called a DCube including H DCube and M DCube . The DCube consists of one or multiple interconnected sub networks each of which is a compound graph made by interconnecting a certain number of basic building blocks by means of a hypercube like graph . More precisely the H DCube and M DCube utilize the hypercube and 1 m bius cube respectively while the M DCube achieves a considerably higher aggregate bottleneck throughput compared to H DCube . Mathematical analysis and simulation results show that the DCube exhibits graceful performance degradation as the failure rate of server or switch increases . Moreover the DCube significantly reduces the required wires and switches compared to the BCube and fat tree . In addition the DCube achieves a higher speedup than the BCube does for the one to several traffic patterns . The proposed methodologies in this paper can be applied to the compound graph of the basic building block and other hypercube like graphs such as Twisted cube Flip MCube and fastcube . 


Summary: We propose DCube for data centers with dual port servers and low end switches. DCube is a compound graph of a basic building block and hypercube or Mobius graph. DCube significantly reduces the wires and switches compared to BCube and fat tree. The basic ideas also apply if Dcube uses other hypercube like graphs.
In general to achieve high compression efficiency a 2D image or a 2D block is used as the compression unit . However 2D compression requires a large memory size and long latency when input data are received in a raster scan order that is common in existing TV systems . To address this problem a 1D compression algorithm that uses a 1D block as the compression unit is proposed . 1D set partitioning in hierarchical trees is an effective compression algorithm that fits the encoded bit length to the target bit length precisely . However the 1D SPIHT can have low compression efficiency because 1D discrete wavelet transform can not make use of the redundancy in the vertical direction . This paper proposes two schemes for improving compression efficiency in the 1D SPIHT . First a hybrid coding scheme that uses different coding algorithms for the low and high frequency bands is proposed . For the low pass band a differential pulse code modulation variable length coding is adopted whereas a 1D SPIHT is used for the high pass band . Second a scheme that determines the target bit length of each block by using spatial correlation with a minimal increase in complexity is proposed . Experimental results show that the proposed algorithm improves the average peak signal to noise ratio by 2.97dB compared with the conventional 1D SPIHT algorithm . With the hardware implementation the throughputs of both encoder and decoder designs are 6.15Gbps and gate counts of encoder and decoder designs are 42.8K and 57.7K respectively . 


Summary: In the hybrid coding scheme DPCM VLC is used for the low pass band and 1D SPIHT is used for the high pass band. DPCM VLC is improved by the additional sub schemes. Target bit length of each block is determined by the block based bit allocation scheme. Block complexity is estimated by using the coding information of the upper block. The proposed 1D SPIHT algorithm is implemented in hardware design.
Gravitational search algorithm is based on law of gravity and the interaction between masses . In GSA searcher agents are collection of masses and their interactions are based on Newtonian laws of gravity and motion . In this paper to further improve the optimization performance of GSA opposition based learning is employed in opposition based gravitational search algorithm for population initialization and also for generation jumping . In the present work OGSA is applied for the solution of optimal reactive power dispatch of power systems . Traditionally ORPD is defined as the minimization of active power transmission losses by controlling a number of control variables . ORPD is formulated as a non linear constrained optimization problem with continuous and discrete variables . In this work OGSA is used to find the settings of control variables such as generator voltages tap positions of tap changing transformers and amount of reactive compensation to optimize certain objectives . The study is implemented on IEEE 30 57 and 118 bus test power systems with different objectives that reflect minimization of either active power loss or that of total voltage deviation or improvement of voltage stability index . The obtained results are compared to those yielded by the other evolutionary optimization techniques surfaced in the recent state of the art literature including basic GSA . The results presented in this paper demonstrate the potential of the proposed approach and show its effectiveness and robustness for solving ORPD problems of power systems . 


Summary: Gravitational search algorithm GSA is based on law of gravity and the interaction between masses. To further improve the performance of GSA opposition based learning is employed. Opposition based gravitational search algorithm is applied for ORPD problems. The study is implemented on IEEE 30 57 and 118 bus test power systems. The obtained results are compared to those yielded by the other evolutionary optimization techniques.
Evidence shows that a small number of line contingencies in power systems may cause a large scale blackout due to the effects of cascading failures . With the development of new technologies and the growing number of heterogeneous participants a modern smart grid should be able to self heal its internal disturbances by continually performing self assessment to deter detect respond to and restore from unpredictable contingencies . Along this line this research focuses on the problem of how to prevent the occurrence of cascading failures through load shedding by considering heterogeneous shedding costs of grid participants . A fair load shedding algorithm is proposed to solve the problem in a decentralized manner where a load shedding participant need only monitor its own operational status and interact with its neighboring participants . Using an embedded feedback mechanism the fair load shedding algorithm can determine a marginal compensation price for each load shedding participant in real time based on the proportional fairness criterion without knowing the shedding costs of the participants . Such fairly determined compensations can help motivate loaders generators to actively participate in the load shedding in the face of internal disturbances . Finally the properties of the load shedding algorithm are evaluated by carrying out an experimental study on the standard IEEE 30 bus system . The study will offer new insights into emergency planning and design improvement of self healing smart grids . 


Summary: We investigate the problem of how to prevent cascading failures in a smart grid. We present a decentralized control algorithm to achieve fair load shedding. The algorithm takes into consideration the heterogeneity of grid participants. The algorithm can help determine compensations for grid participants in real time. We demonstrate and evaluate the algorithm in standard IEEE 30 bus system.
In this paper we propose a method for estimating the camera pose for an environment in which the intrinsic camera parameters change dynamically. In video see through augmented reality AR technology image based methods for estimating the camera pose are used to superimpose virtual objects onto the real environment. In general video see through based AR cannot change the image magnification that results from a change in the camera s field of view because of the difficulty of dealing with changes in the intrinsic camera parameters. To remove this limitation we propose a novel method for simultaneously estimating the intrinsic and extrinsic camera parameters based on an energy minimization framework. Our method is composed of both online and offline stages. An intrinsic camera parameter change depending on the zoom values is calibrated in the offline stage. Intrinsic and extrinsic camera parameters are then estimated based on the energy minimization framework in the online stage. In our method two energy terms are added to the conventional marker based method to estimate the camera parameters reprojection errors based on the epipolar constraint and the constraint of the continuity of zoom values. By using a novel energy function our method can accurately estimate intrinsic and extrinsic camera parameters. We confirmed experimentally that the proposed method can achieve accurate camera parameter estimation during camera zooming. 


Summary: We propose an intrinsic and extrinsic camera parameter estimation method. We extended a conventional marker based method by adding two energy terms. Camera parameters are estimated accurately using new energy function. The effectiveness of our method is shown in simulated and real environments.
The capability of accessing multiple channels through multiple interfaces improve network capacity and is desirable for future Mobile Ad Hoc Networks . However due to the presence of jammers as well as mobility and ad hoc features MANETs require distributed and efficient resource management for channel assignment . To address the channel assignment problem which is a non deterministic polynomial time hard problem we propose a heuristic algorithm called Channel Assignment and JAmmer Mitigation . The CA JAM algorithm assigns a distinct channel for every interface of one station and then all stations exchange the assignment information through beacon frames on every individual interface . When one station receives a beacon the station organizes the information into tables . Therefore each station distributively uses the table to reduce the number of neighboring stations using the same channel to avoid interference which in turn improves the throughput . The tables are also used to learn the disconnected neighbors due to jamming so as to mitigate the effect of jamming and maintain connectivity . CA JAM is fully distributed with no use of control channel or central entity thus it improves connectivity and reduces interference by balancing stations over the available channels while mitigating jamming effects from multi channel multi interface MANETs . We confirm that CA JAM outperforms existing protocols using the OPNET simulator . 


Summary: working for multi interface multi channel MANETs being totally distributed i.e. no CCC or central entity enhancing throughput and reducing interference improving connectivity by balancing stations that are in the same vicinity and using the same channel performing adaptive channel assignment against jamming
The buffer sizing problem is a big challenge for high speed network routers to reduce buffer cost without throughput loss . The past few years have witnessed debate on how to improve link utilization of high speed networks where the router buffer size is idealized into dozens of packets . Theoretically the buffer size can be shrunk by more than 100 times . Under this scenario widely argued proposals for TCP traffic to achieve acceptable link capacities mandate three necessary conditions over provisioned core link bandwidth non bursty flows and tens of thousands of asynchronous flows . However in high speed networks where these conditions are insufficient TCP traffic suffers severely from routers with tiny buffers . To explore better performance we propose a new congestion control algorithm called Desynchronized Multi Channel TCP that creates a flow with parallel channels . These channels can desynchronize each other to avoid TCP loss synchronization and they can avoid traffic penalties from burst losses . Over a 10 Gb s large delay network ruled by tiny buffer routers our emulation results show that bottleneck link utilization can reach over 80 with much fewer number of flows . Compared with other TCP congestion control variants DMCTCP can also achieve much better performance in high loss rate networks . Facing the buffer sizing challenge our study is a new step towards the deployment of optical packet switching networks . 


Summary: We identified a problem that the current TCP variants suffer from synchronization caused by tiny buffers at high speed networks. We proposed and implement a new TCP that explores parallelism among multiple channels and TCP desynchronization for high speed networks. We evaluated the performance of the new DMCTCP over different networking environment. We analyzed the optimal performance of the proposed DMCTCP based on theoretical analysis.
Having in mind multimedia systems applications we propose a novel model based approach to estimate the clock offset between two nodes on the Internet . Different than current clock offset schemes in the literature which are iterative in nature our scheme is aimed at getting a good non iterative clock offset estimation in real time . In our clock offset estimation approach the One Way Delay measurements are modeled with a shifted gamma distribution representing the current state of the probing link . By using the QQ probability plot technique and linear regression model we estimate the minimum value of the gamma distribution with probability zero . This estimated value represents the clock offset plus network propagation and transmission delay for the corresponding receiving path . End nodes exchange their corresponding minimum estimates and get an improved final clock offset estimate considering the network path asymmetries . Based on real experiments we show that our scheme provides an extremely fast clock offset estimation with lower RMSE and superior stability than NTP and current NTP like state of the art methodologies in the literature Jeske and Sampath Choi and Yoo Adhikari et al . Tsuru et al . . Moreover our proposed scheme is non intrusive easy to implement and targeted as part of more complex real time multimedia distribution protocols requiring a fast and reliable OWD estimates . 


Summary: A new model based scheme for clock offset estimationbetween two nodes is presented. The one way delay is modeled with a gamma distribution representing the actual state of the network link. Real and modeled with zero shift one way delay measurements are QQ plot for the estimation of the clock offset. The proposed model is non intrusive the kernel is not modified and can be implemented at the application layer. The model provides accuracy in the order of 3 5 milliseconds under different traffic conditions.
This paper is devoted to introducing a new approach for computing the topology of a real algebraic plane curve presented either parametrically or defined by its implicit equation when the corresponding polynomials which describe the curve are known only by values . This approach is based on the replacement of the usual algebraic manipulation of the polynomials appearing in the topology determination of the given curve with the computation of numerical matrices . Such numerical matrices arise from a typical construction in Elimination Theory known as the B zout matrix which in our case is specified by the values of the defining polynomial equations on several sample points . 


Summary: The topology of the curve is obtained directly from Lagrange interpolation data. Roots of polynomial matrix determinants are obtained as generalized eigenvalues. The algorithm is very useful when the explicit polynomial expressions are huge.
The human brain is a complex biological neural network characterised by high degrees of connectivity among neurons . Any system designed to simulate large scale spiking neuronal networks needs to support such connectivity and the associated communication traffic in the form of spike events . This paper investigates how best to generate multicast routes for SpiNNaker a purpose built low power massively parallel architecture . The discussed algorithms are an essential ingredient for the efficient operation of SpiNNaker since generating multicast routes is known to be an NP complete problem . In fact multicast communications have been extensively studied in the literature but we found no existing algorithm adaptable to SpiNNaker . The proposed algorithms exploit the regularity of the two dimensional triangular torus topology and the availability of selective multicast at hardware level . A comprehensive study of the parameters of the algorithms and their effectiveness is carried out in this paper considering different destination distributions ranging from worst case to a real neural application . The results show that two novel proposed algorithms can reduce significantly the pressure exerted onto the interconnection infrastructure while remaining effective to be used in a production environment . 


Summary: We implemented 4 multicast routing algorithms for SpiNNaker. The two most complex algorithms allow for different implementation details. We explored the effects of these implementation details. The exploration allowed for more effective implementation of the algorithms. The enhanced implementations are better suited to be used in production.