varunr14/newsummary huggingface dataset:
Vehicular Cyber Physical Systems are the most popular systems of the modern era due to their abilities to disseminate the safety related information to the moving vehicles on time . For efficient data dissemination vehicles form a cluster with other vehicles in VCPS environment . But due to high velocity and constant topological changes cluster maintenance is one of the most difficult tasks to be performed in this environment . To address this issue in this paper we propose a novel Learning Automata based hybrid clustering scheme for vehicles in VCPS environment . We have improved our existing solution Energy Efficient Predictive Clustering approach by incorporating the future mobility prediction computed by LA stationed on the vehicles . For this purpose a Predictive Clustering Algorithm using Learning Automata is proposed . Extensive simulations are performed to evaluate the performance of the proposed scheme with respect to various metrics . Results obtained confirm the effectiveness of the proposed scheme in comparison to the existing EEPC scheme . 


Summary: LA based predictive clustering is proposed by predicting the future mobility of the nodes in VANETs. Connecting dominating set is constructed to maintain connectivity of the vehicles. Predictive Clustering Algorithm using LA is proposed. The performance of the proposed scheme is evaluated in different network scenarios with respect to various metrics.
In order to retrieve an image from a large image database the descriptor should be invariant to geometric transformations . It must also have enough discriminating power and immunity to noise for retrieval from a large image database . The Exponent moments descriptor has many desirable properties such as expression efficiency robustness to noise geometric invariance fast computation and multi level representation . In this paper we analyze the rotation scaling and translation invariant property of EMs and propose a content based image retrieval approach using invariant EMs . Experimental results show that the EMs can be used as an effective descriptor of global image content and the proposed retrieval approach yields higher retrieval accuracy than some current state of the art retrieval methods . 


Summary: A new image descriptor namely Exponent moments EMs is introduced. The geometric invariant property of EMs is derived and analyzed. A EMs magnitudes based color image retrieval scheme is presented.
Geometric distortions are more difficult to tackle than other types of attacks . It is a challenging work to design a robust image watermarking scheme against geometric distortions . In this paper we propose a robust digital image watermarking scheme based on local polar harmonic transform . The proposed scheme has the following advantages the stable and uniform image feature points are extracted by the improved speeded up robust feature detector in which the probability density gradient is utilized the affine invariant local feature regions are constructed adaptively according to the variation of local probability density and a new and effective 2D transform named polar harmonic transform is introduced to embed watermark in the digital image . Experiments are carried out on a digital image set of 100 images collected from Internet and the preliminary results show that the proposed image watermarking is not only invisible and robust against common image processing operations such as filtering noise adding and JPEG compression but also robust against the geometric distortions . 


Summary: The stable and uniform image feature points are extracted by the improved SURF detector. The affine invariant local feature regions are constructed adaptively. A new and effective 2D transform is introduced to embed watermark in the digital image.
In this paper a dynamic modeling simulation control and energy management of photovoltaic water pumping network system is presented . A fuzzy logic controller has been proposed for a real time control of the system . The controller generates the reference speeds needed for the pulse width modulation generator to control each DC DC boost converter taking into account the water levels in three tanks and the instantaneous value of the solar radiation . The main objectives of the fuzzy logic controller are the design of an adequate maximum power point tracker to extract the maximum power regulate the water in the three tanks and finally ensure the correct operation for all the conversion strings in order to optimize the quantity of pumped water . The system performance under different scenarios has been checked carrying out Matlab Simulink simulations using a practical load demand profile and real weather data and comparing them to another control algorithm . photovoltaic panel ideal factor normal operating cell temperature rated voltage short circuit current temperature coefficient of ISC constant of proportionality between G and Iph photocurrent PVP output voltage optimal values V electronic charge Boltzmann s constant cell temperature PVP shunt resistance optimal values of I reference of solar radiation temperature coefficient stator voltage stator current stator inductance rotor resistance mutual inductance mechanical speed of the machine electromagnetic torque reference speed of motor i level of tank I output flow of tank I DC link capacity band gap energy maximum power rated current serial cells open circuit voltage parallel cells solar radiation PVP output current ideality factors cell reverse saturation current reverse saturation current PV array series resistance cell reference temperature DC link voltage DC link capacity saturation current for Tr rotor voltage rotor current rotor inductance stator resistance coefficient of friction total inertia of the machine load torque duty cycle of DC inverter i input flow of pump i DC link voltage 


Summary: A modeling and simulation of photovoltaic water pumping network are affected. An energy management and a control strategy of the system are presented. A real time control of photovoltaic water pumping network system is proposed. The optimization of the pumped water and the tanks regulation were ensured. An adequate maximum power point tracker should be controlled.
Recently new families of mixed finite elements have been proposed to address the analysis of linear elastic bodies on regular grids adopting a limited number of degrees of freedom per element . A two dimensional mixed discretization is implemented to formulate an alternative topology optimization problem where stresses play the role of main variables and both compressible and incompressible materials can be dealt with . The structural compliance is computed through the evaluation of the complementary energy whereas the enforcement of stress constraints is straightforward . Numerical simulations investigate the features of the proposed approach comparisons with a conventional displacement based scheme are provided for compressible materials stress constrained solutions for structures made of incompressible media are introduced . 


Summary: A topology optimization problem is formulated in terms of stresses only. An efficient mixed finite element is used to provide robustness and accuracy on regular grids. Stress constrained optimization is dealt with also in case of incompressible media. Stress constrained optimal layouts take advantage of the accuracy of the adopted fem. Peculiar optimal layouts are found in case of incompressible material and plane strain.
In real time collaborative environments address space transformation strategy can be used to achieve consistency maintenance of shared documents . However as for the execution of compound operations they are firstly decomposed into primitive operations the relationships between the referencing objects and referenced objects are lost during the decomposition process . Besides the Undo operations in this environment are targeted at compound operations but not decomposed basic ones . However the traditional algorithms take primitive operation as the manipulation unit thus leading to semantic inconsistencies of compound Undo operations . This paper appends two history buffers to maintain the relationships between the original operations and the decomposed ones and introduces Retrace Undo VT Redo Retrace strategy to realize the consistency maintenance of compound operations . Also this paper introduces the version decomposition strategy describes the main algorithms of the compound Undo operations and analyses the validity of the strategy . Case analysis is given to show the effectiveness of the strategy . 


Summary: We append two history buffers to maintain the relationships between original operations and decomposed ones. Combined with AST method the Retrace Undo VT Redo Retrace strategy is adopted to realize the consistency maintenance of compound operations. Based on multi version strategy the Undo Redo algorithms are proposed with case analyses to verify the effectiveness.
An improved image magnification algorithm for gray and color images is presented in this paper to meet the challenge of preserving high frequency components of an image including both image edges and texture structures . In the proposed algorithm a new edge detection method that uses the well known Otsu automatic optimum thresholding is proposed to distinguish strong edge pixels . The parameters of the original directional cubic convolution interpolation algorithm which were selected based on training were eliminated . As a result our algorithm achieves more accurate edge detection better interpolation results and less computational complexity . Simulation results demonstrate that the improved algorithm can reconstruct the magnified image preserve edges and textures simultaneously and reduce common interpolation artifacts . Furthermore it generates higher visual quality of the magnified images and achieves higher peak signal to noise ratio structural similarity and feature similarity compared with other state of the art methods . 


Summary: An improved version of DCCI algorithm is proposed to magnify gray and color images. A new method to detect strong edge pixels is proposed using Otsu thresholding. Parameters of the DCCI algorithm which selected based on training are eliminated. Visual results show that the proposed algorithm outperforms the compared methods. Better quantitative results in terms of time PSNR SSIM and FSIM are obtained.
Inter Cell Interference from neighboring cells is the major challenge that degrades the performance of Orthogonal Frequency Division Multiple Access cellular mobile systems particularly for cell edge users . An efficient technique to mitigate ICI is the interference coordination . The most commonly ICI Coordination technique is the Fractional Frequency Reuse which effectively mitigates ICI by applying different reuse factors to Users Equipments situated in different regions in each cell . This paper presents a novel Self Organized FFR Resource Allocation scheme that automatically selects the optimal RA to inner and outer regions of the cell based on coordination between neighboring evolved NodeBs through a message passing approach over Long Term Evolution X2 interfaces . The performance of the proposed scheme is evaluated using MATLAB and compared with different combinations of RA as well as with frequency reuse 1 and reuse 3 schemes . Simulation results show that the proposed scheme improves the cell edge performance and achieves high degree of fairness among UEs compared to reference RA schemes . 


Summary: We proposed a self organized dynamic resource allocation SORA scheme using FFR. SORA FFR scheme tracks the variation of UEs distribution through the LTE network. SORA FFR scheme dynamically allocates optimal resources to inner and outer regions. SORA FFR scheme improved throughput of CEUs and fairness performance.
Decimal arithmetic circuits based on IEEE 754 2008 standard commonly use 10 bit densely packed decimal DPD encoding of three binary coded decimal BCD digits. Binary coded chiliad BCC encoding as storage arithmetic efficient as DPD BCD equivalently packs three BCD digits. No unpacking packing to from BCD entailing extra delay power per each arithmetic operation required in case of DPD are necessary for BCC. Therefore while abiding to DPD standard we are motivated to design decimal arithmetic operators that accept BCC operands and produce BCC results. As such DPD data from memory or input devices are converted to BCC manipulated in BCC and stored in the BCC register file during multi operation decimal computations and converted back to DPD only on reporting results to memory or output devices. In this paper following a previous simple mixed BCC binary adder we design and synthesize more efficient ones and compare them with previous relevant BCD and BCC adders to show advantages in area and power. 


Summary: Decimal arithmetic adders that accept BCC radix 1000 encoded operands and produce BCC results are proposed. Six different conditional speculation options are studied. The best proposed design show advantages in area 17 power 13 and PDP 14 measures over the best previous relevant work.
As a part of character recognition character segmentation plays an important role in automatic license plate recognition system . In recent years lots of methods on CS have been proposed and they work well on their own datasets . However it is still challenging to segment characters from images with frame declination and quality degradation because of noises and overlapped connected or fragmented characters . In this paper we propose a two stage segmentation method for Chinese license plate . At the first stage a novel template matching method is presented using a harrow shaped filter bank and minimum response . It finds the locations of the segmenting points between characters roughly . Then the accurate segmentations between connected or overlapped characters are adjusted by a variant of A path finding algorithm at the second stage . Experiments on a challenging dataset including 2334 images demonstrate the effectiveness and efficiency of the proposed method . 


Summary: Characters on license plate with interferences are cut using a two stage method. Plate frame is removed and vertical tilt is corrected before segmentation. A harrow shaped filter with values of 0 and 1 is designed for matching. Boundaries of the remarkable space are located accurately in initial segmentation. A algorithm is used for the precise segmentation of connected characters.
This work is concerned with the development of an efficient and robust isogeometric Reissner Mindlin shell formulation for the mechanical simulation of thin walled structures . Such structures are usually defined by non uniform rational B splines surfaces in industrial design software . The usage of isogeometric shell elements can avoid costly conversions from NURBS surfaces to other surface or volume geometry descriptions . The shell formulation presented in this contribution uses a continuous orthogonal rotation described by Rodrigues tensor in every integration point to compute the current director vector . The rotational state is updated in a multiplicative manner . Large deformations and finite rotations can be described accurately . The proposed formulation is robust in terms of stable convergence behavior in the nonlinear equilibrium iteration for large load steps and geometries with large and arbitrary curvature and in terms of insensitivity to shell intersections with kinks under small angles . Three different integration schemes and their influence on accuracy and computational costs are assessed . The efficiency and robustness of the proposed isogeometric shell formulation is shown with the help of several examples . Accuracy and efficiency is compared to an isogeometric shell formulation with the more common discrete rotational concept and to Lagrange based finite element shell formulations . The competitiveness of the proposed isogeometric shell formulation in terms of computational costs to attain a pre defined error level is shown . 


Summary: A rotation based isogeometric Reissner Mindlin shell formulation which is able to handle finite rotations and large deformations is presented. A continuous rotation of the director vector with multiplicative update ensures robust computations of arbitrarily curved structures. Three integration schemes are presented and compared in terms of computational costs and influence on accuracy. The efficiency of the proposed shell formulation is shown to be competitive to standard Lagrange based finite element shell formulations.
In this paper we propose a cross layer framework for joint routing and rate adaptation in multi rate Multi Channel Multi Radio infrastructure Wireless Mesh Networks . These networks use MCMR capabilities of mesh routers to achieve high performance . However the MCMR nodes introduce interference in the multi hop mesh networks and can degrade QoS . Thus the design of routing metrics to improve the QoS has become an important research issue . Furthermore as the routing metric and rate adaptation decisions are closely related the joint approach is needed to improve the performance of the network . Towards this we analytically derive our routing metric using IEEE 802.11 Distributed Coordination Function basic access mechanism . Using this model we propose Passive Interference and Delay Aware routing metric which estimates the delay and interference by exploiting cross layer information . We extend the work by performing joint routing and rate adaptation . The simulation results using NS2 reveal that proposed framework improves throughput and delay compared to existing approaches with reduced routing overhead . 


Summary: New routing metric is analytically derived using IEEE 802.11 DCF mechanism. Routing metric and rate adaptation decisions are strongly related. Joint routing and rate adaptation framework is proposed by exploiting cross layer information. Link quality is estimated using passive monitoring to minimize routing overhead. NS2 results reveals that joint framework performs better than existing approaches.
Orthogonal Frequency Division Multiplexing system has lead to significant advancement in wireless communication systems . In OFDM system multi carriers are present . During modulation the sub carriers are added together with same phase which increases the value of Peak to Average Power Ratio . High PAPR leads to more interference and reduced resolution of analog to digital converter and digital to analog converter . The Partial Transmit Sequence is a popular technique used for PAPR reduction in OFDM systems . The modified PTS technique proposed in this paper overcomes the drawbacks of Original PTS by making use of Group Phase Weighting Factor and Recursive Phase Weighting Factor along with All Pass Filtering . Simulations show that the proposed scheme performs very well in terms of PAPR and achieves almost the same Bit Error Rate performance under Rayleigh fading channel . 


Summary: The major drawback of OFDM system is its high PAPR. The drawback is overcome by use of GPW and RPW with All Pass Filtering technique. The GPW and RPW generate more optimum phase factors when implemented together. All Pass Filtering technique maintains magnitude response and optimum phase shift.
One of the primary objectives of Wireless Sensor Network is to provide full coverage of a sensing field as long as possible . The deployment strategy of sensor nodes in the sensor field is the most critical factor related to the network coverage . However the traditional deployment methods can cause coverage holes in the sensing field . Therefore this paper proposes a new deployment method based on Multi objective Immune Algorithm and binary sensing model to alleviate these coverage holes . MIA is adopted here to maximize the coverage area of WSN by rearranging the mobile sensors based on limiting their mobility within their communication range to preserve the connectivity among them . The performance of the proposed algorithm is compared with the previous algorithms using Matlab simulation for different network environments with and without obstacles . Simulation results show that the proposed algorithm improves the coverage area and the mobility cost of WSN . 


Summary: A new deployment approach for WSNs based on the multi objective immune algorithm is proposed. The approach rearranges sensors to remit the coverage holes and improves the network coverage. The approach is energy efficient and ensures the connectivity by limiting the mobility cost of sensors. Simulation experiments were completed in MATLAB correctly. The approach has many advantages comparing with other algorithms.
Wireless multimedia sensor networks have been used for sensitive applications such as video surveillance and monitoring applications . In a WMSN storage and transmission become complicated phenomena that can be simplified by the use of compressed sensing which asserts that sparse signals can be reconstructed from very few measurements . In this paper memory efficient measurement matrices are proposed for a discrete wavelet transform discrete cosine transform hybrid approach based video compressed sensing . The performance of the framework is evaluated in terms of PSNR storage complexity transmission energy and delay . The results show that the proposed matrices yield similar or better PSNR and consume less memory for generating the matrix when compared with a Gaussian matrix . The DWT DCT based VCS yields better quality and compression when compared with DCT and DWT approaches . The transmission energy is 50 less and the average delay is 52 less when compared to raw frame transmission . 


Summary: Implemented DWT DCT hybrid based video compressive sensing framework. Proposed and implemented two memory efficient measurement matrices for WMSN. Proposed matrices yields similar or better PSNR compared to Gaussian matrix. Storage and energy complexity is less for proposed matrices compared to Gaussian matrix.
Accurate image retrieval is required to index and retrieve large number of images from huge databases . In this paper an efficient approach is presented to encode the color and textural features of images from the local neighborhood of each pixel . The color features are extracted by quantizing the RGB color space into a single channel with reduced number of shades . The texture information is encoded with structuring patterns generated from the locally structured elements chosen as a basis . Color and textural features are fused together to construct the inherently rotation and scale invariant hybrid image descriptor . This fusion is carried out by extracting textural cues over each shade independently . RSHD has been tested on the Corel dataset and experimental results suggest that RSHD outperforms state of the art descriptors . The performance of the RSHD is promising under rotation and scaling . It can also be effectively used under more complex image transformations . 


Summary: A rotation and scale invariant hybrid descriptor is proposed for content based image retrieval. Color and textural data are used to construct the descriptor. Color is encoded by quantizing RGB color space into 64 shades. Texture is extracted using 5 rotation invariant structuring element.