varunr14/newsummary huggingface dataset:
Removal of noise and restoration of images has been one of the most interesting researches in the field of image processing in the past few years. Existing filter based methods can remove image noise however they cannot preserve image quality and information such as lines and edges. The proposed noise reduction image restoration technique initially performs noise removal by employing a hybrid denoising filter with an adaptive genetic algorithm. The performance of the proposed technique is evaluated by comparing the result for the proposed technique with existing denoising filters and genetic algorithm and particle swarm optimisation methods. The comparison results show that the proposed method achieves higher quality denoising and a high restoration ratio for noisy images than the existing methods. 


Summary: We modelled a Hybrid filter with AGA to remove the noise from the images. The noisy free images are restored by shining the pixel values using AGA. The performance is analysed by taking number of images and comparing the result with existing technique.
Service oriented architecture is a self contained service with a collection of services . Services communicate with each other using a web service . Web services use a collection of open protocols and standards for communication between different web services and their applications . In today s environment users are not satisfied with a single web service . To fulfill the users needs two or more atomic services must be combined to provide a single complex service . Hence several atomic web services must be orchestrated based on user preference by using a multi agent system . In the traditional approach the orchestration of web services is a manual process . The proposed system reduces human intervention and supports the orchestration of atomic web services into a complex service by using a multi agent system . Therefore this paper addresses the automatic orchestration by using a multi agent i.e . two agents . The first agent is used to select an appropriate web service from the available atomic service . The second agent is used to orchestrate the selected web services to form a complex service based on a user s requirement and quality of service . 


Summary: The proposed approach uses a multi agent system to automate the process. It increases the overall system performance over traditional approach. It supports several QoS parameter such as reliability throughput response time and reusability. The graph depicts the response time between proposed and traditional approach.
Steganography has become a hot topic in information hiding and the reversibility technology allows the recovery of the original image without distortion when the embedded secret information is extracted . In this paper a high payload image steganographic scheme based on an extended interpolating method is proposed . In the premise of image quality assurance the proposed scheme increases the capacity by maximizing the difference between neighboring pixels . Meanwhile it has low complexity and retains good image quality . Extensive experiments on images have been conducted and the experimental results demonstrate that the proposed approach performs better than several state of the art methods . 


Summary: By analysis of statistical properties of adjacent pixels as well as image interpolation techniques a novel interpolation method is put forward. Under the conditions of ensuring the image quality the proposed image interpolation method maximizes the difference values between neighboring pixels and improves the capacity. The proposed scheme still has the advantage of lower computing complexity and better results between interpolating pixels. The experimental results show that the performance of the proposed method is superior to several state of the art methods.
We propose a new optical reconfigurable Network on Chip named ReFaT ONoC . ReFaT is a dynamically reconfigurable architecture which customizes the topology and routing paths based on the application characteristics . ReFaT as an all optical NoC routes optical packets based on their wavelengths . For this purpose we propose a novel architecture for the optical switch which eliminates the need for optical resource reservation and thus avoids the corresponding latency and area overheads . As a key idea for dynamic reconfiguration each application is mapped to a specific set of wavelengths and utilizes its dedicated routing algorithm . We compare the proposed reconfigurable optical NoC with traditional electrical NoCs as well as non reconfigurable optical NoCs in terms of data transmission delay power consumption and energy dissipation . The simulation results show that on average ReFaT reduces power and energy consumption by 54.75 and 40 respectively compared to the non reconfigurable ONoC . 


Summary: ReFaT enables run time reconfiguration of network topology and routing algorithm. ReFaT adopts wavelength routing and avoids electrical control packets. ReFaT utilizes a novel wavelength assignment approach to map various topologies. ReFaT architecture facilitates simultaneous multicast and unicast data transmission. ReFaT improves power and energy efficiency compared to non reconfigurable topologies.
The traditional approach for energy detection ED consists in the comparison of the energy received against a fixed detection threshold estimated according to an expected noise level. However the noise power is not a static parameter since it varies as a function of the random sources of noise and interference present in the network. This random nature of the noise power originates the so called noise uncertainty problem which adversely affects the performance of the ED. In this paper we propose and evaluate by means of computer simulation an adaptive energy detector that incorporates a noise power estimation strategy for adjusting the detection threshold according to the noise power present at each sensing epoch. As it can be proved by simulation results our strategy helps in reducing the sensing errors and to improve the ED s sensitivity by alleviating the negative effects of the noise uncertainty. 


Summary: Noise uncertainty in energy detection is counteracted by adapting detection threshold. Multiple receiver architecture is exploited for maximum likelihood estimation. Threshold adaptation allows maintaining a constant and low false alarm rate. The probability of detection is improved in the low SNR regime without increasing sensing time.
Affine Transform is widely used in high speed image processing systems . This transform plays an important role in various high speed image processing applications . AT an important process during the intensity based image registration is applied iteratively during the registration . This is also used for the analysis of the interior of an organ and to get a better view of the organs from various angles in 3D coordinate system . Hence for real time medical image registration and visualization of the acquired volumetric images acceleration of AT is very much sought for . In this paper a parallel and pipelined architecture of the proposed AT algorithm has been presented . This will accelerate the transform process and reduce the processing time of medical image registration . The architecture is mapped in Field Programmable Gate Array for prototyping and verification . The results show that the computational complexity of the proposed parallel algorithm is almost 4 times better than that of the conventional algorithm . 


Summary: In the proposed algorithm simultaneously 4 pixel voxel locations can be transformed to compute AT of the entire image. The proposed architecture requires only relevant frames instead of all the frames simultaneously. The faster implementation of the affine transform is useful during image registration of the 3D bio medical images.
This paper studies sectorization increase in horizontal and vertical plane . We have simulated downlink macro long term evolution network using three dimensional antenna and propagation models . New network layouts have been proposed based on 4 sector site deployment . The challenge was to offer lower network cost and complexity . Simulation results have showed good tradeoff between capacity and mobility performance in comparison to known sectorization schemes . Besides carrier aggregation and active antenna system have been used to exploit the sector vertical plane . Low frequency band improves coverage and indoor signal penetration in urban environment . Our proposed sectorization schemes give multi objective network quality of service . 


Summary: Radio site design with four horizontal and four vertical sectors is proposed. Vertical sectorization is applied using active antennas. Low band carrier aggregation and sectorization boosted radio performance. Throughput and mobility performance tradeoff is maintained.
The number of wireless sensor network deployments for real life applications has rapidly increased in recent years . However power consumption is a critical problem affecting the lifetime of wireless sensor networks . A number of techniques have been proposed to solve this power problem . Among the proposed techniques data compression scheme is one that can be used to reduce the volume of data to be transmitted . This paper therefore proposes a fast and efficient lossless adaptive compression scheme for WSNs . FELACS was proposed to enable a fast and low memory compression algorithm for WSNs . FELACS generates its coding tables on the fly and compresses data very fast . FELACS is lightweight robust to packet losses and has very low complexity . FELACS achieved compression rates of 4.11 bits per sample . In addition it achieved power savings up to 70.61 using the real world test datasets . 


Summary: A fast and low memory data compression scheme is proposed for WSNs. The scheme performs compression losslessly using 8 variable length code options. The scheme which uses a very simple data model is fast and computationally simple. The scheme is efficient and requires no coding dictionary. The scheme achieve better compression performance than previously proposed schemes.
A number of mobile payment studies have been proposed in recently years . Most of the schemes are largely focused on transaction security not on users privacy . In this paper we propose an Unlinkable Anonymous Payment Scheme to provide a secure and anonymous mobile commerce environment . In the proposed protocol a user applies an anonymous virtual credit card from a trusted service manager . The sensitive information of the applied credit card is stored in the secure elements of user s mobile device . Our proposed protocol ensures various imperative security properties such as anonymity unlinkability and non repudiation etc . 


Summary: We propose an anonymous mobile payment protocol to protect users privacy. Using anonymizing schemes to improve anonymity and unlinkability in a mobile transaction. Users can use mobile phones with NFC to perform commercial transactions.
As a typical media access protocol S MAC has drawn much attention in the past decades . However most of the attention focuses on energy efficiency but fails to guarantee QoS performance . Firstly we develop one state machines model and elaborate on the states transition processes of S MAC . Secondly combining our state machines with the specific parameters of S MAC we propose an analytical probabilistic model to investigate the latency and stability performances of S MAC employing three different mechanisms without sleeping mechanism with sleeping mechanism and with adaptive listening mechanism . Also we analyze the latency and stability performances of S MAC with different dutyCycle values . This research shows two interesting results 1 Sleeping mechanism inside S MAC does have negative impacts on its latency and stability fortunately adaptive listening mechanism can optimize them to some extent . 2 Latency and stability performances of S MAC can be further improved through manipulating dutyCycle values . The simulations in NS2 exhibit consistent results with those obtained from our analytical probabilistic model . 


Summary: We propose one state machines model for S MAC protocol. We use a probabilistic model to analyze the latency and stability performances. Sleeping mechanism does have negative impacts on the latency and stability performances. Adaptive listening mechanism does optimize the latency and stability performances. Appropriate dutyCycle can be used to further improve the latency and stability.
Graphical abstract Image graphical abstract stator rotor and load resistive respectively stator rotor and magnetizing inductance respectively the area swept by the blades of the wind turbine in m terminal excitation capacitance the load current along the d axis and q axis respectively direct axis stator rotor current respectively quadrature axis stator rotor current respectively the inertia of the rotor in constants representing initial induced voltages along the d axis and q axis respectively due to the remaining magnetic flux in the core . d dt the number of poles the wind turbine power the sweep diameter of the wind turbine . the wind turbine torque in the capacitor voltage along the d axis and q axis respectively the wind speed m s the angular velocity of the wind turbine rad s. the electrical angular velocity of the rotor air density in Kg m quadrature axis stator rotor flux linkage respectively direct axis stator rotor flux linkage respectively tip speed ratio 


Summary: Nonlinearity and asymmetry characteristics of the load are described mathematically. The dynamic study of the isolated wind turbine based SEIG under nonlinear resistive load is included. Detailed Mathematical model of wind turbine SEIG and nonlinear load are presented.
Diabetic retinopathy is a condition that occurs in individuals with several years of diabetes mellitus and causes a characteristic group of lesions in the retina and progressively damages it . Detecting retinal fundus diseases in advance helps ophthalmologists to apply proper treatments that may cure the disease or decrease its severity and thus protect patients from vision loss . Diabetic retinopathy is usually diagnosed by ophthalmologists using dilated images that are captured by pouring a chemical solution into the patient s eye which causes inconvenience and irritation to the patient . In this paper we propose a method to detect lesion exudates automatically with the aid of a non dilated retinal fundus image to help ophthalmologists diagnose the disease . The exudates from the low contrast images are detected and localised using a neighbourhood based segmentation technique . A support vector machine and probabilistic neural network classifiers are proposed to assess the severity of the disease and the results are compared with the same segmentation technique . The average classification accuracy for the SVM and PNN classifiers are determined to be 97.89 and 94.76 respectively . 


Summary: A method for investigating the severity of diabetic retinopathy is proposed. Earlier diagnosis of the disease prevents vision loss in diabetic patients. The exudates are the major symptoms and are detected via a segmentation algorithm. The degree of severity is assessed using the SVM and PNN classifier algorithms. The SVM classifier is found to provide better results than the PNN classifier.
MapReduce is considered the key behind the success of cloud computing because it not only makes a cluster highly scalable but also allows applications to use resources in a cluster . However MapReduce achieves this simplicity at the expense of flexibility for data partitioning localization and processing procedures by handling all issues on behalf of application developers . Unfortunately MapReduce currently has no solution capable of giving application developers flexibility in customizing data partitioning localization and processing procedures . To address the aforementioned flexibility constraints of MapReduce we propose an architecture called Flexible Architecture for Cluster Evolution which is both language independent and platform independent . FACE allows a MapReduce cluster to be designed to match various application requirements by customizing data partitioning localization and processing procedures . We compare the performance of FACE with that of a general MapReduce system and then demonstrate performance improvements with our implemented procedures . 


Summary: FACE supports system primitives that allow application developers to develop various applications in clouds. FACE allows application developers to customize data partitioning localization and processing procedures. FACE designs its system primitives in a language independent and platform independent way. FACE makes extensible the Master of a MapReduce system by application developers.
This paper proposes an alternative for building a data hiding algorithm into digital images . The method is based on chaos theory and the least significant bit technique for embedding a secret message in a image . Specifically the Bernoulli s chaotic maps are used to perform the following processes encrypt the bits of the message before embedding them into the cover image a random selection of the image s compositions must be performed and the insertion of the secret message in a random way to rows and columns of the image . Several experimental results are shown under different evaluation criteria such as entropy autocorrelation homogeneity contrast energy peak signal to noise ratio mean squared error and maximum absolute squared deviation . Experimental results show a good improvement in the peak signal to noise ratio and Image Fidelity value of the proposed algorithm in comparison to the results obtained from similar algorithms . 


Summary: A steganographic method for hiding information is proposed using four Bernoulli s chaotic maps. It is applied a two step scheme Pixel selection and masking of sensitive information. A module function is applied to the chaotic maps considering an iterated process. There is no evidence of periodicity in the sequences produced by the modified Bernoulli s maps. It is assumed that each map uses two 64 bits variables and the key space has been estimated in 2508.
Set Partitioning In Hierarchical Tree SPIHT is considered one of the most important algorithms for reducing the size of the vision data collected by the sensor node within wireless multimedia sensor network WMSN . The traditional SPIHT algorithm suffers from image coders complexity due to large memory requirement. This is an essential problem for the implementation on limited resource environments such as WMSN. The main objective of this paper is to introduce a listless pipelined strip based SPIHT for WMSN to reduce system complexity and minimize processing time and memory usage. The proposed algorithm is implemented using discrete wavelet transform DWT lifting based instead of DWT convolution based filter. The experimental results show the superiority of the proposed algorithm in terms of peak signal to noise ratio PSNR which reaches 1 dB for all bit rates. In addition the memory requirement is reduced to 71 with 27 of energy saving. 


Summary: Proposed a modified listless strip based zero tree structure LZT based on SPIHT. Image quality in terms of signal to noise ratio is improved besides memory reduction obtained. Decreasing processing time reduces system complexity and power consumption.
Wireless multimedia sensor networks are capable of retrieving audio image and video data in addition to scalar sensor data . The lifetime of these networks is mainly dependent on the communication and computational energy consumption of the node . In this paper compressed sensing based image transmission is proposed to reduce the energy consumption considerably with acceptable image quality . A unique encoding algorithm is formulated for the CS measurements attained with the Bernoulli measurement matrix . The proposed CS method produces better results at a lower sparsity range . Experimental analysis is performed using the Atmega 128 processor of Mica2 to compute the execution time and energy consumption in the hardware platform . The proposed CS method has a considerable reduction in energy consumption and better image quality than the conventional CS method . The simulation results show the efficiency of the proposed method . 


Summary: Energy efficient CS methodology for image transmission in WMSNs is proposed. Unique encoding algorithm for CS measurements with the Bernoulli matrix is formulated. Experimental analysis in the Atmega 128 of Mica2 to compute the execution time. Optimal range of communication distance for the proposed methodology is evaluated.
In this paper we propose a systematic rateless erasure code namely systematic Random code based on Random code for short messages transmission . Given a message of k symbols the sender will first send the message to the receiver as Part I coded symbols . The rest of coded symbols starting from th onwards are termed as Part II coded symbols and they are generated by adding the message symbols randomly . The receiver reconstructs the original message instantly if all the Part I coded symbols are received intact . Otherwise the receiver reconstructs the original message from any 10 coded symbols of Part I and II with high probability of complete decoding i.e . 99.9 success probability . Though SYSR code inherits the high decoding complexity of Random code i.e . both analysis and simulation results show that SYSR code achieves better PCD and fewer decoding steps than Random code . 


Summary: Systematic Random code reconstruct the original message with zero extra coded symbols if the first k coded symbols are received intact. Reconstruct the original message with 99.9 success probability using extra ten overhead symbols. In channels of low erasure probability systematic Random code outperforms Random code in term of lesser extra coded symbols and decoding steps to achieve complete decoding.
In order to reduce aquaculture risks and optimize the operation of water quality management in prawn engineering culture ponds this paper proposes a novel water temperature forecasting model based on empirical mode decomposition and back propagation neural network . First the original water temperature datasets are decomposed into a collection of intrinsic mode functions and a residue by EMD yields relatively stationary sub series that can be readily modeled by BPNN . Second both IMF components and residue is applied to establish the corresponding BPNN models . Then each sub series is predicted using the corresponding BPNN . Finally the prediction values of the original water temperature datasets are calculated by the sum of the forecasting values of every sub series . The proposed hybrid model was applied to predict water temperature in prawn culture ponds . Compared with traditional models the simulation results of the hybrid EMD BPNN model demonstrate that de noising and capturing non stationary characteristics of water temperature signals after EMD comprise a very powerful and reliable method for predicting water temperature in intensive aquaculture accurately and quickly . 


Summary: The novel model which combines EMD and BPNN algorithm is presented to predict water temperature in intensive aquaculture.. Using EMD technology adaptively decomposed the original water temperature data into a finite set of IMFs and a residue. EMD BPNN has higher prediction accuracy and better generalization performance than standard BPNN and standard SVR. EMD BPNN can be used as a suitable and effective modeling tool for predicting water temperature in intensive aquaculture.