Mobile Ad hoc networks(MANETs) are power constrained since nodes are operated with limited battery. A node not only sends it own packets but also packets of other nodes. However, the energy consumption during routing remains a key challenge. In this paper, we have proposed a multipath routing protocol which is referred here as energy efficient multipath routing (E2MR). The proposed approach uses a cost metric for path selection, which is a function of residual battery power and current traffic load at a node. Through extensive simulation, we have compared the proposed E2MR protocol with a few existing multipath routing protocols. From simulation results, it is observed that the proposed scheme has lower end-to-end delay, higher packet delivery ratio and higher residual energy level than other protocols.
{"title":"A Technique to Enhance the Energy Efficiency of Multipath Routing Protocol for MANETs","authors":"Prasanta Kumar Manohari, Ankit Dubey, N. Ray","doi":"10.1109/CINE.2016.14","DOIUrl":"https://doi.org/10.1109/CINE.2016.14","url":null,"abstract":"Mobile Ad hoc networks(MANETs) are power constrained since nodes are operated with limited battery. A node not only sends it own packets but also packets of other nodes. However, the energy consumption during routing remains a key challenge. In this paper, we have proposed a multipath routing protocol which is referred here as energy efficient multipath routing (E2MR). The proposed approach uses a cost metric for path selection, which is a function of residual battery power and current traffic load at a node. Through extensive simulation, we have compared the proposed E2MR protocol with a few existing multipath routing protocols. From simulation results, it is observed that the proposed scheme has lower end-to-end delay, higher packet delivery ratio and higher residual energy level than other protocols.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"64 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"120941062","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abhijith U, Ashish Kumar, Mohanta Taranisen, Leena Muddi
With the rapid growth of the Hyper Convergence (HC) the use of the Solid State Device (SSDs) as the intelligent Storage Tiering and caching has increased immensely. It plays an important role to provide high throughput and performance with maximum utilization of the SSD storage space considering the life cycle of SSDs and workload. Efficient Utilization of such resources is one of the main criterion of the virtualization technology. By considering the rise of the VDI workload the proposed implementation of a sequential write detection algorithm, we try to maximize the utilization of higher tier storage such as SSDs (Tier 0) by placing the data which fall under the category of sequential writes into the lower tier disks (Tier 1, 2 - n) such as SAS (serial attached SCSI) / SATA (serial advanced technology attachment).
{"title":"The Efficient Use of Storage Resources in SAN for Storage Tiering and Caching","authors":"Abhijith U, Ashish Kumar, Mohanta Taranisen, Leena Muddi","doi":"10.1109/CINE.2016.28","DOIUrl":"https://doi.org/10.1109/CINE.2016.28","url":null,"abstract":"With the rapid growth of the Hyper Convergence (HC) the use of the Solid State Device (SSDs) as the intelligent Storage Tiering and caching has increased immensely. It plays an important role to provide high throughput and performance with maximum utilization of the SSD storage space considering the life cycle of SSDs and workload. Efficient Utilization of such resources is one of the main criterion of the virtualization technology. By considering the rise of the VDI workload the proposed implementation of a sequential write detection algorithm, we try to maximize the utilization of higher tier storage such as SSDs (Tier 0) by placing the data which fall under the category of sequential writes into the lower tier disks (Tier 1, 2 - n) such as SAS (serial attached SCSI) / SATA (serial advanced technology attachment).","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"64 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116721806","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Salam Shuleenda Devi, A. Roy, Manish Sharma, R. Laskar
In this proposed work, k-nearest neighbors (kNN) classifier comprising of three features i.e. area, compactness ratio, aspect ratio is used to separate the isolated and compound erythrocytes present in microscopic images of thin blood smear. In the microscopic image of thin blood smear, blood components such as erythrocytes, platelets etc are available which is used for diagnostic approach to blood disorder. In the microscopic image, both the isolated and compound erythrocytes are also present. Compound erythrocyte is formed due to overlapping of two or more erythrocytes. In malaria diagnosis, parasitaemia estimation is done which define the ratio of infected erythrocytes related to total number of erythrocytes in microscopic image. For proper quantification of erythrocyte, erythrocytes need to be separated as isolated cell and compound cell. As isolated cells directly count in the counting system and compound cells are further analysed to determine number of erythrocytes. The proposed method to separate the isolated and compound cell provides an average accuracy of ~0.942. It is observed that the proposed method can effectively separate the cells in comparison to some of the existing methods.
{"title":"kNN Classification Based Erythrocyte Separation in Microscopic Images of Thin Blood Smear","authors":"Salam Shuleenda Devi, A. Roy, Manish Sharma, R. Laskar","doi":"10.1109/CINE.2016.19","DOIUrl":"https://doi.org/10.1109/CINE.2016.19","url":null,"abstract":"In this proposed work, k-nearest neighbors (kNN) classifier comprising of three features i.e. area, compactness ratio, aspect ratio is used to separate the isolated and compound erythrocytes present in microscopic images of thin blood smear. In the microscopic image of thin blood smear, blood components such as erythrocytes, platelets etc are available which is used for diagnostic approach to blood disorder. In the microscopic image, both the isolated and compound erythrocytes are also present. Compound erythrocyte is formed due to overlapping of two or more erythrocytes. In malaria diagnosis, parasitaemia estimation is done which define the ratio of infected erythrocytes related to total number of erythrocytes in microscopic image. For proper quantification of erythrocyte, erythrocytes need to be separated as isolated cell and compound cell. As isolated cells directly count in the counting system and compound cells are further analysed to determine number of erythrocytes. The proposed method to separate the isolated and compound cell provides an average accuracy of ~0.942. It is observed that the proposed method can effectively separate the cells in comparison to some of the existing methods.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"15 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116192270","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Concept detection plays an important role if there is a huge amount of data available. We know that cluster analysis, topic detection, opinion mining have got a major role in the product marketing, online shopping, E-commerce. In this paper, we have conducted the topic detection and clustering experiments on the News samples which were sourced from online newspapers. Our aim is to find out the topics which also available in the text documents as a group of words and apply a clustering technique using the Singular value decomposition method. Then opinions are extracted from the comments, collected on a particular subject of interest like the comments for Smartphone. Finally, the clustering technique is applied on these sentiments to figure out the opinions of the people towards different features of the Smartphone. The results obtained here are competitive with the technology available.
{"title":"Concept Detection and Cluster Analysis from Newsfeed-Singular Value Decomposition Based Approach","authors":"M. Scholar, Babu B. Sathish, Professor","doi":"10.1109/CINE.2016.30","DOIUrl":"https://doi.org/10.1109/CINE.2016.30","url":null,"abstract":"Concept detection plays an important role if there is a huge amount of data available. We know that cluster analysis, topic detection, opinion mining have got a major role in the product marketing, online shopping, E-commerce. In this paper, we have conducted the topic detection and clustering experiments on the News samples which were sourced from online newspapers. Our aim is to find out the topics which also available in the text documents as a group of words and apply a clustering technique using the Singular value decomposition method. Then opinions are extracted from the comments, collected on a particular subject of interest like the comments for Smartphone. Finally, the clustering technique is applied on these sentiments to figure out the opinions of the people towards different features of the Smartphone. The results obtained here are competitive with the technology available.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"42 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115172066","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Disasters are inevitable aspects of the human civilization and the limitation of extending the medical infrastructure to every corner of the demography is a challenging task. Technology can cater to need of the availability of medical expertise for each affected individual in the disaster virtually. A medical infrastructure can be envisioned using existing LAN and WAN communication technology standards that can be deployed at shortest time interval and intelligent enough to deliver assistance along with virtual availability of the medical expert. The main issues posing challenge in such deployments include load balancing for both WAN network access points and local data gateways by exploiting all available interfaces. The addressing of the actuators directly from the remote sever is another bottleneck in the scenario besides the fairness of the stream schedules and quality of service and/or experience.
{"title":"Aspects of Network Architecture for Remote Healthcare Systems","authors":"R. Mishra, R. Pandey","doi":"10.1109/CINE.2016.16","DOIUrl":"https://doi.org/10.1109/CINE.2016.16","url":null,"abstract":"Disasters are inevitable aspects of the human civilization and the limitation of extending the medical infrastructure to every corner of the demography is a challenging task. Technology can cater to need of the availability of medical expertise for each affected individual in the disaster virtually. A medical infrastructure can be envisioned using existing LAN and WAN communication technology standards that can be deployed at shortest time interval and intelligent enough to deliver assistance along with virtual availability of the medical expert. The main issues posing challenge in such deployments include load balancing for both WAN network access points and local data gateways by exploiting all available interfaces. The addressing of the actuators directly from the remote sever is another bottleneck in the scenario besides the fairness of the stream schedules and quality of service and/or experience.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121854975","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
K. C. Patra, M. Panigrahi, Sushil Kumar Mahapatra, Minu Samantaray
Now a days, brain tumor detection without losing the edge information is very vital field of research, which may save many life. So in our proposed method, we have given emphasis on minimum loss of information in brain tumor MRI image. So we propose a BE-GGMM-EI (Background Estimated-Generalized Gaussian Mixture Model with Edge Information) method for detecting different brain tumors. In our proposed method, the tumor MRI image is first processed for background subtraction then the edge is enhanced with edge maximization technique. After that the image is denoised GGMM. Experimental results authenticate our proposed GGMM method to have better edge information with good PSNR value.
{"title":"An Enhanced BE-GGMM-EI Algorithm for Medical Image Denoising","authors":"K. C. Patra, M. Panigrahi, Sushil Kumar Mahapatra, Minu Samantaray","doi":"10.1109/CINE.2016.17","DOIUrl":"https://doi.org/10.1109/CINE.2016.17","url":null,"abstract":"Now a days, brain tumor detection without losing the edge information is very vital field of research, which may save many life. So in our proposed method, we have given emphasis on minimum loss of information in brain tumor MRI image. So we propose a BE-GGMM-EI (Background Estimated-Generalized Gaussian Mixture Model with Edge Information) method for detecting different brain tumors. In our proposed method, the tumor MRI image is first processed for background subtraction then the edge is enhanced with edge maximization technique. After that the image is denoised GGMM. Experimental results authenticate our proposed GGMM method to have better edge information with good PSNR value.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"5 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115220381","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper presents a novel concept in cross-project software defect prediction. Defects in real world software systems are predicted, using defects data of academic projects as training data. Relevant training data are filtered using patterns by ordered projections algorithm by [14]. A satisfactory Area under curve(AUC) value of at least 0.7 and above is obtained for 12 out the 16 investigated real world software systems with Bayes Network classifier. This result is quite significant in the current scenario where many software startups are being launched by fresh graduates from Universities, particularly in India. At the beginning such startup companies do not have any defects data of real projects and hence defect datasets of academic projects collected at Universities can be really useful.
{"title":"Value and Applicability of Academic Projects Defect Datasets in Cross-Project Software Defect Prediction","authors":"Arvinder Kaur, Kamaldeep Kaur","doi":"10.1109/CINE.2016.34","DOIUrl":"https://doi.org/10.1109/CINE.2016.34","url":null,"abstract":"This paper presents a novel concept in cross-project software defect prediction. Defects in real world software systems are predicted, using defects data of academic projects as training data. Relevant training data are filtered using patterns by ordered projections algorithm by [14]. A satisfactory Area under curve(AUC) value of at least 0.7 and above is obtained for 12 out the 16 investigated real world software systems with Bayes Network classifier. This result is quite significant in the current scenario where many software startups are being launched by fresh graduates from Universities, particularly in India. At the beginning such startup companies do not have any defects data of real projects and hence defect datasets of academic projects collected at Universities can be really useful.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117280792","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Dynamic set point weighting technique is a well established technique reported in leading literature [10, 11]. Here, in this paper a simpler and better design is proposed in dynamic set point weighting technique for performance enhancement. In this proposed scheme the weighting factor is obtained online based on the instantaneous change of error of the process variable. The value of weighting factor is computed through a simple mathematical function depending on the process operating conditions. Performance of the proposed improved dynamic set point weighted PI controller is tested on DC servo position control systems through simulation study as well as real time implementation. Superiority of the proposed technique is demonstrated through performance analysis with the widely reported conventional fixed set point weighting and dynamic set point weighting schemes. Considerable robustness is also observed against model uncertainty with increased dead time and is found to perform satisfactorily in presence of measurement noise.
{"title":"An Improved Dynamic Set Point Weighted PI Controller for Servo Position Control Application","authors":"P. Mitra, C. Dey, R. Mudi","doi":"10.1109/CINE.2016.32","DOIUrl":"https://doi.org/10.1109/CINE.2016.32","url":null,"abstract":"Dynamic set point weighting technique is a well established technique reported in leading literature [10, 11]. Here, in this paper a simpler and better design is proposed in dynamic set point weighting technique for performance enhancement. In this proposed scheme the weighting factor is obtained online based on the instantaneous change of error of the process variable. The value of weighting factor is computed through a simple mathematical function depending on the process operating conditions. Performance of the proposed improved dynamic set point weighted PI controller is tested on DC servo position control systems through simulation study as well as real time implementation. Superiority of the proposed technique is demonstrated through performance analysis with the widely reported conventional fixed set point weighting and dynamic set point weighting schemes. Considerable robustness is also observed against model uncertainty with increased dead time and is found to perform satisfactorily in presence of measurement noise.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"431 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122872008","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
This paper focuses on the classification of motor imagery of the left-right hand movements from a healthy subject. Elliptic Bandpass filters are used to discard the unwanted signals. Our study was on C3 and C4 electrodes particularly for the left-right limb movements. We deployed various feature extraction techniques on the EEG data. Statistical-based, wavelet-based energy-entropy & RMS, PSD based average power and bad power were performed to form the desired feature vectors. Variants of Support Vector Machines (SVM) were employed for classification and the results were also compared with Multi-layered Perceptron (MLP). Empirical results show that both SVM and MLP were suitable for such motor imagery classifications with the accuracy of 85% and 85.71% respectively. Among all employed feature extraction techniques wavelet-based methods specifically the energy-entropy feature set, gave promising results for both the classifiers.
{"title":"EEG Based Motor Imagery Classification Using SVM and MLP","authors":"Rajdeep Chatterjee, T. Bandyopadhyay","doi":"10.1109/CINE.2016.22","DOIUrl":"https://doi.org/10.1109/CINE.2016.22","url":null,"abstract":"This paper focuses on the classification of motor imagery of the left-right hand movements from a healthy subject. Elliptic Bandpass filters are used to discard the unwanted signals. Our study was on C3 and C4 electrodes particularly for the left-right limb movements. We deployed various feature extraction techniques on the EEG data. Statistical-based, wavelet-based energy-entropy & RMS, PSD based average power and bad power were performed to form the desired feature vectors. Variants of Support Vector Machines (SVM) were employed for classification and the results were also compared with Multi-layered Perceptron (MLP). Empirical results show that both SVM and MLP were suitable for such motor imagery classifications with the accuracy of 85% and 85.71% respectively. Among all employed feature extraction techniques wavelet-based methods specifically the energy-entropy feature set, gave promising results for both the classifiers.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"8 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128671943","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Parallel processing is one of the arising concepts that are used to process batch of 'n' numbers of tasks through 'm' numbers of parallel processors. These processors are either identical or uniform or unrelated in nature. Scheduling is the discipline of decision making for executing the tasks through parallel processors. One of the important criteria of good scheduling is the schedule with minimum Waiting Time variance (WTV). Therefore minimizing WTV is an objective of designing schedulers. Minimizing the variance of the tasks waiting time in the scheduler's ready queue is a NP-Hard problem. Achieving the Quality of Service (QoS) in the parallel Processors by minimizing the variance of the tasks waiting time in the scheduler's ready queue is a problem of task scheduling. To enhance the performance of parallel processing, it is required to develop a stable and none overlap scheduler where variance of waiting time of individual tasks should be minimized treated as an important parameter. This paper presents a unique task distribution style among uniform parallel processor and then applies the three heuristic based solutions named as VS, BS and RSS are intended for Q_m |prec|WTV minimization problem. The experimental results are compared with the existing approaches and shows that the proposed approach provides the best performance for the compared approaches and problems tested with large task set. The findings of intended algorithm are shown in the form of graph for consonant problems.
{"title":"A Heuristic for Scheduling of Uniform Parallel Processors","authors":"Satyasundara Mahapatra, R. R. Dash, S. Pradhan","doi":"10.1109/CINE.2016.21","DOIUrl":"https://doi.org/10.1109/CINE.2016.21","url":null,"abstract":"Parallel processing is one of the arising concepts that are used to process batch of 'n' numbers of tasks through 'm' numbers of parallel processors. These processors are either identical or uniform or unrelated in nature. Scheduling is the discipline of decision making for executing the tasks through parallel processors. One of the important criteria of good scheduling is the schedule with minimum Waiting Time variance (WTV). Therefore minimizing WTV is an objective of designing schedulers. Minimizing the variance of the tasks waiting time in the scheduler's ready queue is a NP-Hard problem. Achieving the Quality of Service (QoS) in the parallel Processors by minimizing the variance of the tasks waiting time in the scheduler's ready queue is a problem of task scheduling. To enhance the performance of parallel processing, it is required to develop a stable and none overlap scheduler where variance of waiting time of individual tasks should be minimized treated as an important parameter. This paper presents a unique task distribution style among uniform parallel processor and then applies the three heuristic based solutions named as VS, BS and RSS are intended for Q_m |prec|WTV minimization problem. The experimental results are compared with the existing approaches and shows that the proposed approach provides the best performance for the compared approaches and problems tested with large task set. The findings of intended algorithm are shown in the form of graph for consonant problems.","PeriodicalId":142174,"journal":{"name":"2016 2nd International Conference on Computational Intelligence and Networks (CINE)","volume":"05 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127178271","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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