varunr14/newsummary huggingface dataset:
Collaboration between mobile nodes is significant in Mobile Ad Hoc Networks . The great challenges of MANETs are their vulnerabilities to various security attacks . Because of the lack of centralized administration secure routing is challenging in MANETs . Effective secure routing is quite essential to protect nodes from anonymous behaviours . Game theory is currently employed as a tool to analyse formulate and solve selfishness issues in MANETs . This work uses a Dynamic Bayesian Signalling Game to analyse strategy profiles for regular and malicious nodes . We calculate the Payoff to nodes for motivating the particular nodes involved in misbehaviour . Regular nodes monitor continuously to evaluate their neighbours by using the belief evaluation and belief updating system of the Bayes rule . Simulation results show that the proposed scheme could significantly minimize the misbehaving activities of malicious nodes and thereby enhance secure routing . 


Summary: Collaboration between mobile nodes is significant in Mobile Ad Hoc Networks. Dynamic Bayesian Signalling Game model is proposed to enhance secure routing and motivate effective cooperation among nodes. A novel scheme of payoff formulation is developed to motivate the misbehaving nodes. We used a belief updating system to update a node s belief in terms of action chosen message sent and strategy chosen. The proposed scheme could significantly minimize the misbehaving activities of malicious nodes and thereby enhance secure routing.
This paper presents an analysis of a mobile manipulator movement executing a pick up task . The robot has to reach a target point with its end effector . The configuration of the manipulator and the pose of the mobile robot define the inputs of the problem . The random profile approach is applied to deal with the aforementioned issue . The trajectory which minimizes the execution time of the task is generated . Furthermore the manipulability index is introduced in the optimization process in order to allow a comfortable configuration of the manipulator to reach the target point . The obtained results in free and cluttered environments are presented and discussed . The feasibility of the computed trajectories is also validated against experimentation in the case of the RobuTER mobile robot carrying the Ultra Light Manipulator . 


Summary: Reaching Target point by the end effector of a mobile manipulator. The optimized trajectory minimizing the execution time of the task is generated. Introduction of manipulability index for configuring the manipulator far from singularities. The feasibility of the computed trajectories is validated against experimentation on a real robot.
Indefinite and uncontrollable growth of cells leads to tumors in the brain . The early diagnosis and proper treatment of brain tumors are essential to prevent permanent damage to the brain or even patient death . Accurate data regarding the position of the tumor and its size are essential for effective treatment . Hence an entirely computerized automatic system to provide accurate tumor data is compulsory for physicians . Such developments are necessary to diagnose brain tumors during brain surgery . Brain magnetic resonance images are proposed for the detection and segmentation of the tumor region via a completely automatic and highly accurate method . The approach discussed in this paper employs an adaptive neuro fuzzy inference system based on the automatic seed point selection range . The pixels intensity of the proposed algorithm is not dependent on the tumor type . The tumor s segmentation results are evaluated based on various criteria including similarity index overlap fraction extra fraction and positive predictive value which corresponded to values of 0.817 0.817 0.182 and 0.817 respectively in this study . These results indicate that the approach proposed in this study performs better compared to many conventional processes . The significance of this work is the differentiation of brain abnormalities from the healthy brain tissue . 


Summary: Diagnosis and proper treatment of brain tumors are essential to prevent permanent damage to the brain or even patient death. The brain magnetic resonance MR images are used to detect the severities of tumor detections. The performance analysis is measured on various criteria. This work is the differentiation of brain abnormalities from the healthy brain tissue.
This study presents a new weak signal detection method based on the van der Pol Duffing oscillator . The principle of the proposed method is described . A weak signal is detected through the transition from the chaotic to the periodic state . Numerical simulation shows that the van der Pol Duffing oscillator is sensitive to a weak signal under strong noise conditions . Several aspects of the proposed method including the noise influence influence of different frequency signals and influence of the phase shift are studied in detail . Results indicate that the application of the van der Pol Duffing oscillator to weak signal detection is feasible . 


Summary: Proposed van der Pol Duffing oscillator based weak signal detection method. The signal to noise ratio of the weak signal can be detected 45dB. Compared to Duffing oscillator more robust against the different frequency signal.
Image contrast enhancement and brightness preservation are fundamental requirements for many vision based applications . However these are two conflicting objectives when the image is processed by histogram equalization approaches . Current available methods may not provide results simultaneously satisfying both requirements . In this work a pipelined approach including color channel stretching histogram averaging and re mapping is developed . By using stretching color information from a scene is restored . Averaging against a uniform distribution enables the output image to recover the information lost . Furthermore histogram re mapping reduces artifacts that often arise from the equalization procedure . The technique also employs a search process to find optimal algorithmic parameters such that the mean brightness difference between the input and output images is minimized . The effectiveness of the proposed method was tested with a set of images captured in adverse environments and compared against available methods . High performing qualitative and quantitative results were obtained . 


Summary: A histogram equalization method is proposed to preserve original image brightness. A histogram averaging technique is developed to recover image information lost. A histogram remapping technique is used to reduce artifacts introduced to images. An optimization minimizes the brightness change between input and output images. Results show that image brightness is preserved while image contrast is enhanced.
This paper presents our ongoing efforts toward the development of a multi agent distributed framework for autonomous control of mobile manipulators . The proposed scheme assigns a reactive agent to control each degree of freedom of the manipulator a hybrid agent to control the mobile base and a supervisory agent to coordinate and synchronize the work of the control agents . Each control agent implements a Simulation Verification technique to optimize locally and independently from the other agents a predefined objective function . The final goal consists of bringing the end effector as close as possible to imposed operational targets . Different simulation scenarios are described and carried out for the case of RobuTER ULM robot with and without considering failures of some articulations of the manipulator or the mobile base . Results show that the main advantage of the proposed approach is that the system pledges a fault tolerant response to some breakdowns without needing any specific additional treatment . it represents the situation of the imposed Target it represents the initial current situation of the end effector of the robot in the absolute frame . The first three values are the position of the end effector the last three represent its orientation angles it corresponds to the new situation of the end effector after the Move Up Move Down movement of the joint i of the manipulator it represents the new situation of the end effector of the robot after the forward backward turn left turn right movement of the mobile base it represents the initial current final situation of the mobile base it represents the new situation of the mobile base after the forward backward turn left turn right movement carried out by the Mobile base agent it corresponds to the initial current final configuration of the manipulator joints it corresponds to the new configuration of the manipulator joints after the Move Up Move Down movement carried out by the Joint agent it represents the initial current final value of the objective function 


Summary: We propose a generic multi agent control architecture for mobile manipulators. Robot complex mathematical models are not required so computing time is reduced. The strategy is fault tolerant to breakdowns without needing specific treatments. The proposed approach works in 3D environments with high dof mobile manipulators. Accuracy of the proposed approach is good comparatively to classical approaches.
In this paper a new approach of edge based quantization for the compression of gray scale images using an Adaptive Block Truncation Coding technique is proposed to improve the compression ratio with high picture quality . Quantization is done based on the edge information contained in each block of pixels of the image . Conventional BTC method retains the visual quality of the reconstructed image but it shows some artifacts near the edges . In conventional BTC and variants same quantization is done for all pixel values with different block sizes so that CR is static for images with a fixed block size . But in the case of proposed method since the quantization is done based on the edge information CR become dynamic and consequently achieves better visual quality with better CR . The experimental analysis based on subjective and quantitative analysis proved that the proposed method outperforms other BTC variants . 


Summary: An Adaptive block truncation coding technique ABTC EQ is proposed. Edge image is taken from the input image and divides it into blocks of pixels. Quantization is done based on the edge information of each of these blocks. Bi clustering is done for the non edge block and tri clustering for the edge block. Experimental analysis shows that ABTC EQ outperforms BTC and its variants.
Sample variations are one of the main problems associated with speaker recognition . Most approaches use multiple templates in the gallery database . But this requires enormous memory space . In order to minimize classification errors and intra class variations adaptive online and offline template update methods using vector quantization and Gaussian mixture model are proposed . Online and offline feature update as well as model update techniques are considered here . Feature update utilizes the vector quantization approach while Gaussian mixture model approach is considered for model updating . The proposed methods automatically update the feature in accordance with the biometric sample variations over time and they continually adapt the templates based on semi supervised learning strategies . Experiments with 50 subjects reveal that the proposed template update strategies improve the recognition accuracy and reduce the classification errors for voice recognition systems even under sample variations . 


Summary: Created a new database for speaker template updating. MFCC super template for speaker recognition is proposed. Proposed an online and offline MFCC feature and GMM based model update. Secondary template for speaker template model update is also suggested.
Manycore CMP systems are expected to grow to tens or even hundreds of cores . In this paper we show that the effective co design of both the network on chip and the coherence protocol improves performance and power meanwhile total area resources remain bounded . We propose a snoopy aware network on chip topology made of two mesh of tree topologies . Reducing the complexity of the coherence protocol and hence its resources and moving this complexity to the network leads to a global decrease in power consumption meanwhile area is barely affected . Benefits of our proposal are due to the high throughput and low delay of the network but also due to the simplicity of the coherence protocol . The proposed network and protocol minimizes communication amongst cores when compared to traditional solutions based either on 2D mesh topologies or in directory based protocols . 


Summary: A high throughput low latency network for snoop based cache coherence protocol is proposed. Execution time and power consumption are reduced meanwhile area over head is kept low. Benefits rely on the synergy between the snoop protocol and the high throughput network.
Recently audio steganography has become an important covert communications technology . This technology hides secret data in a cover audio without perceptual modification of the cover audio . Most of the existing audio steganography techniques are unsuitable for real time communication . Although field programmable logic array technologies offer parallel processing in hardware that can improve the speed of steganographic systems the research activities in this area are very limited . This paper presents a parallel hardware architecture for dual mode audio steganography based FPGA technology . The proposed DMAS reconfigures the same hardware blocks in both hiding and recovery modes to reduce the hardware requirements . It has been successfully implemented on a Xilinx XC6SLX16 FPGA board to occupy only 97 slices . Furthermore it processes data simultaneously at an operating frequency of up to 58.82MHz and accomplishes full message retrieval at an embedding rate of 25 with an audio quality above 45dB in terms of signal to noise ratio . 


Summary: We propose concurrent hardware architecture for real time audio steganography. We implement and test the proposed hardware on Xilinx XC6SLX16 FPGA board. The implemented hardware requires only 97 slices and consumes less than 148mW. The implemented hardware processes data simultaneously with frequency up to 58.82. Full data retrieval at embedding rate of 25 of the cover audio size.
This work presents an analysis on efficiency of solar energy harvesting circuits focused on low power low voltage sensor platforms . Two different approaches were tested in order to operate a solar panel closely to its maximum power point . The first circuit precisely matches the solar cells with the batteries . The second one is based on a Maximum Power Point Tracker chip . The paper addresses the circuits design and evaluation . Two tests were performed outdoors under two different irradiance conditions . Although the MPPT chip may be efficient for a variety of low power devices experiments have shown that it did not extract more energy from the environment than the directly coupled circuit . A mathematical energy consumption analysis shows that in both cases the directly coupled circuit is more efficient . Therefore this work shows that there is still a lack of industry solutions for low power low voltage solar harvesting circuits . 


Summary: Two solar energy harvesting circuits have been tested for low power applications. The directly coupling technique has been compared with an MPPT integrated circuit. A mathematical energy consumption analysis shows both circuits efficiency. For all tests performed the directly coupled circuit has been more efficient. Solar cell s input current simulations have confirmed the experimental results.
This paper introduces a new scheme for encrypting images with a few details based on wavelet fusion . In this scheme the image with a few details to be encrypted is fused with another image that is rich in details utilizing the Discrete Wavelet Transform prior to encryption . The fusion is a pre processing step to change the homogeneity of flat areas in the images having a few details . RC6 or chaotic Baker map encryption are then performed on the fused image . Encryption with chaotic Baker map is just a permutation algorithm that can not perform well on flat areas of the images because the permutation yields approximately the same intensities . So circular shifts on pixels are performed on the fused image prior to chaotic encryption to remove flat areas or reduce the degree of homogeneity . Chaotic encryption is then performed in the wavelet domain to increase the degree of diffusion . Several metrics are used in this paper for performance evaluation of the suggested ciphering schemes like visual inspection histogram test encryption quality analysis and diffusion analysis . The robustness of the suggested image ciphering schemes is tested in the presence of noise before decryption . Simulation results demonstrated that the suggested image ciphering schemes provide a secure and effective way for encrypting images with few details . 


Summary: This paper introduces a new scheme for encrypting images with few details based on wavelet fusion.. The fusion is a pre processing step to change the homogeneity of flat areas in the images having a few details. RC6 or chaotic Baker map encryption are then performed on the fused image. Encryption with chaotic Baker map is just a permutation algorithm that cannot perform well on flat areas of the images because the permutation yields approximately the same intensities. So circular shifts on pixels are performed on the fused image prior to chaotic encryption to remove flat areas or reduce the degree of homogeneity. The robustness of the suggested image ciphering schemes is tested in the presence of noise before decryption. Simulation results demonstrated that the suggested image ciphering schemes provide a secure and effective way for encrypting images with few details.
In this study the Quality of Service needed to support service continuity in heterogeneous networks is achieved by a Distributed Multi Agent Scheme based on cooperation concepts and an awareness algorithm . A set of problem solving agents autonomously process local tasks and cooperatively interoperate via an in cloud blackboard system to provide QoS and mobility information . A Q Learning awareness algorithm calculates the exceptive rewards of a handoff to all access networks . These rewards are then used by problem solving agents to determine what actions must be performed . Agents located in the integrated IMS 4G Cloud networks handle service continuity by using a handoff mechanism . Through operations and cooperation among active agents these phases select a policy for predictive and anticipated IP Multimedia Subsystem handoff management . Compared with conventional IMS handoff management the proposed DMAS scheme achieves shorter handoff delay and better QoS for real time service applications . 


Summary: Quality of Service supports service continuity in heterogeneous networks is achieved by agent based concepts. The shorter handoff delay and better QoS for real time service applications is proposed. The QoS mechanism and the intelligent agent are required for cooperative QoS awareness networking. The QoS management mechanism based on agents develops a cost effective manner in IMS 4G Cloud network.
Wireless body area networks WBANs consist of tiny sensors that enable monitoring the health status of a person. quality of service QoS is a major challenge for WBANs due to the importance of vital sign information. Therefore many QoS based medium access control MAC protocols and technologies have been developed to overcome this problem. Standardization of various technologies and protocols must be addressed. ISO IEEE 11073 personal health data standards aim to provide interoperability between healthcare devices and technologies. This paper presents a new QoS aware cross layer MAC protocol based on the ISO IEEE 11073 standards that employs a slot allocation scheme multi channel architecture priority mechanism admission control and cross layer solution. The proposed MAC protocol has been modeled and simulated by OPNET Modeler. In addition the proposed MAC protocol is compared with standard technologies and recent protocols in the literature and it achieves better results for end to end delay packet loss ratio and throughput parameters. 


Summary: The proposed MAC protocol guarantees QoS requirements of all subscribers as described in the ISO IEEE 11073 standards. A slot allocation scheme priority classification admission control mechanism and channel allocation with bit error rate reduction mechanism are described to ensure QoS. The proposed MAC protocol is compared with standard technologies and recent protocols in the literature and it achieves better results for end to end delay packet loss ratio and throughput parameters.
Ubiquitous environments are often considered as highly dynamic environments and contextual information can change at runtime . The user interface should provide the right information for a given user considering runtime context . Such an objective can be achieved only when we deduce the user s requirements in terms of information and present it to the user according to his current context of use . The overall objective of our research is to generate a user interface adapted to the current context of use for critical fields . This paper explores some key issues related to the architecture of context aware applications . A formal approach for the analysis of pervasive Human Computer System is presented . XML Petri nets are used to model the pervasive HCS . The proposed approach is illustrated with a case study which presents a hypoglycemic diabetic patient in a smart hospital . 


Summary: We propose a formal approach for specification of pervasive user interface. We define a Petri nets modeling language for pervasive Human Computer System. We demonstrate that the accuracy of the generated interface depends on the context and task s validity. We demonstrate the validity of our approach by a case study in a medical domain. We propose a system for monitoring diabetic patient in smart hospital.
This study develops a hierarchical scheme with three processing layers for human behavior recognition . The proposed scheme is an audio based approach that employs a microphone array of the Kinect sensor for sensing and acquiring acoustic data to classify human behavior . The three processing layers namely the feature layer acoustic event classification layer and specific behavior recognition layer are interrelated and the sensing data fusion Gaussian mixture model with a classification tree and state machine diagram to regulate human behavior are employed in these three layers respectively . With enhanced performance of the feature and acoustic event classification layers the proposed scheme exhibits increased human behavior classification accuracy . Human behavior recognition experiments were conducted in a research office and three specific office behavior modes namely Laboratory meeting Classmate chatting and Laboratory study interaction were effectively classified using the proposed method . 


Summary: Proposed three layered hierarchical human behavior recognition uses only audio data. The use of Kinect sensor microphone array for data capture and fusion is explored. The proposed scheme increased recognition robustness compared with conventional GMM.