International Journal of Sensors, Wireless Communications and Control最新文献

{"title":"An Energy-Balance Clustering Routing Protocol for Intra-Body Wireless Nanosensor Networks","authors":"Santhosh S, Vamshi Krishna B, Lakshmi Prasad Mudarakola, Saptarshi Mukherjee, Mannava Yesubabu, Vikas Sharma","doi":"10.2174/0122103279318474240705104252","DOIUrl":"https://doi.org/10.2174/0122103279318474240705104252","url":null,"abstract":"\u0000\u0000Numerous sensor nodes spread out across the surveillance region\u0000form the Wireless-Sensor Network (WSN), a smart, self-organizing network. Since the lumps\u0000can typically only be motorized by batteries, creating a WSN while maintaining an optimal energy\u0000balance and extending the network's lifetime is the biggest issue.\u0000\u0000\u0000\u0000A novel network architecture that integrates nanotechnology with sensor networks is\u0000known as a Wireless-NanoSensor-Network(WNSN). A new area of focus in research is intra-bodyiWNSNs,\u0000which are WNSNs with promising potential applications in biomedicine, damage detection,\u0000and intra-body health monitoring. We suggest an energy-balance-clustering-routing protocol\u0000(EBCR) for iSN nodes that have limited energy storage, short communication range, and low computation\u0000and processing capabilities. The protocol uses a novel hierarchical clustering approach to\u0000lessen the communication burden on nano-nodes.\u0000\u0000\u0000\u0000Cluster nano-nodes can use one-hop routing to send data directly to the Cluster-Head(CH)\u0000nodes, and the CH-nodes can utilize multi-hop routing to send data to the nano control node. In addition,\u0000selecting the next hop node to minimize energy usage while guaranteeing successful data\u0000packet delivery involves balancing distance and channel capacity. The protocol's strengths in energy\u0000efficiency, network-lifetime extension, and data-packet transmission success rate were highlighted\u0000by the simulation results.\u0000\u0000\u0000\u0000It is clear that the EBCR protocol is a viable option for iWNSNs' routing system.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"107 6","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821544","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}

{"title":"Non-orthogonal Multiple Access (NOMA) Channel Estimation for Mobile\u0000& PLC-VLC Based Broadband Communication System","authors":"Manidipa Sarkar, Ankit Nayak, Sarita Nanda, Suprava Patnaik","doi":"10.2174/0122103279310677240606101233","DOIUrl":"https://doi.org/10.2174/0122103279310677240606101233","url":null,"abstract":"\u0000\u0000The paper focuses on enhancing the performance of 5G wireless mobile\u0000communication systems. Furthermore, it addresses the increasing demand for high data rates, improved channel capacity, and spectrum efficiency outlined by the 3rd Generation Partnership Project (3GPP) protocol.\u0000\u0000\u0000\u0000To develop an innovative Non-Orthogonal Multiple Access (NOMA)-based channel estimation (CE) model aimed at improving the performance of 5G wireless mobile communication\u0000systems\u0000\u0000\u0000\u0000A proportionate recursive least squares (PRLS) algorithm is utilized for estimating the\u0000characteristics of practical Rayleigh fading channels. The applicability of the PRLS algorithm is investigated in Lambertian channels for indoor broadband communication systems such as power line\u0000communication (PLC) and visual light communication (VLC) systems.\u0000\u0000\u0000\u0000The assessment of evaluation metrics, including mean square error (MSE), bit error rate\u0000(BER), spectral efficiency (SE), energy efficiency (EE), capacity, and data rate, have been analysed. Faster convergence and higher accuracy compared to existing state-of-the-art approaches\u0000have been demonstrated.\u0000\u0000\u0000\u0000The NOMA-based channel estimation model presents significant promise in enhancing the performance of 5G wireless communication systems. The demands for higher data rates and\u0000improved spectral efficiency as per 3GPP standards have been addressed.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"120 22","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141820810","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}

{"title":"Optimizing Financial Decision Support Systems with Machine LearningDriven Recommendations","authors":"Amit Sharma, J. Amutharaj, N. S. Ram, M. Narender, S. Rajesh, M. Tiwari, K. P. Yuvaraj, Mangala Shetty","doi":"10.2174/0122103279305872240702112248","DOIUrl":"https://doi.org/10.2174/0122103279305872240702112248","url":null,"abstract":"\u0000\u0000The research investigates the utility of cosine similarity as an innovative\u0000recommendation system designed to assist individuals in making financial choices tailored to their\u0000unique preferences and objectives. It embarks on an extensive analysis of diverse datasets encompassing a wide array of financial products, including investment portfolios, credit card offerings, insurance plans, personal loan options, and car loan packages. Each dataset undergoes meticulous feature extraction and preprocessing to optimize the accuracy of the cosine similarity model.\u0000\u0000\u0000\u0000The research then applies cosine similarity to calculate the similarity scores between individual financial products, thereby producing personalized recommendations. These recommendations are predicated on a comprehensive spectrum of input variables. The outcomes of these case\u0000studies demonstrate the potency of cosine similarity as a foundation for the development of tailored\u0000financial guidance systems. Such recommendations empower individuals to make informed decisions that are intrinsically aligned with their distinctive financial aspirations.\u0000\u0000\u0000\u0000Ridge and lasso regression algorithms are deployed to develop predictive models for assessing investment preferences and evaluating potential investment returns.\u0000\u0000\u0000\u0000The study highlights the necessity for financial institutions and advisory platforms to\u0000invest in data quality and algorithmic sophistication to enhance the efficacy and accuracy of these\u0000financial recommendations.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"114 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141821379","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}

{"title":"Unveiling Data Fairness Functional Requirements in Big Data Analytics\u0000Through Data Mapping and Classification Analysis","authors":"P. Hemalatha, J. Lavanya","doi":"10.2174/0122103279312138240625052021","DOIUrl":"https://doi.org/10.2174/0122103279312138240625052021","url":null,"abstract":"\u0000\u0000In the realm of Big Data Analytics, ensuring the fairness of data-driven decisionmaking processes is imperative. This abstract introduces the Learning Embedded Fairness Interpretation (LEFI) Model, a novel approach designed to uncover and address data fairness functional requirements with an exceptional accuracy rate of 97%. The model harnesses advanced data mapping\u0000and classification analysis techniques, employing Explainable-AI (xAI) for transparent insights into fairness within large datasets\u0000\u0000\u0000\u0000The LEFI Model excels in navigating diverse datasets by mapping data elements to discern patterns contributing to biases. Through systematic classification analysis, LEFI identifies potential sources of unfairness, achieving an accuracy rate of 97% in discerning and addressing these\u0000issues. This high accuracy empowers data analysts and stakeholders with confidence in the model's\u0000assessments, facilitating informed and reliable decision-making. Crucially, the LEFI Model's implementation in Python leverages the power of this versatile programming language. The Python\u0000implementation seamlessly integrates advanced mapping, classification analysis, and xAI to provide a robust and efficient solution for achieving data fairness in Big Data Analytics.\u0000\u0000\u0000\u0000This implementation ensures accessibility and ease of adoption for organizations aiming\u0000to embed fairness into their data-driven processes. The LEFI Model, with its 97% accuracy, exemplifies a comprehensive solution for data fairness in Big Data Analytics. Moreover, by combining\u0000advanced technologies and implementing them in Python, LEFI stands as a reliable framework for\u0000organizations committed to ethical data usage.\u0000\u0000\u0000\u0000The model not only contributes to the ongoing dialogue on fairness but also sets a\u0000new standard for accuracy and transparency in the analytics pipeline, advocating for a more equitable future in the realm of Big Data Analytics.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"116 16","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141822115","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}

{"title":"An Intelligent Transport System Using Vehicular Network for Smart Cities","authors":"S. U, Lakshmi Prasad Mudarakola, Raguru Jaya Krishna, B. Prasanthi, Dastagiraiah C, I. Tayubi","doi":"10.2174/0122103279319738240618201043","DOIUrl":"https://doi.org/10.2174/0122103279319738240618201043","url":null,"abstract":"\u0000\u0000The integration of communication tools has allowed for effective\u0000decision-making in smart cities and Internet-of-Things (IoT). One major issue that people who\u0000commute to cities everyday encounter is traffic congestion. Thanks to the progress and backing of\u0000ICTs, transportation solutions have been designed and implemented, leading to the development of\u0000ITSs and the provision of numerous innovative services.\u0000\u0000\u0000\u0000These services include ones that guarantee safety, provide drivers with\u0000useful information, enable greater street movement, and avoid congestion, among many others. In\u0000industrialized nations, traffic data is collected by specialized sensors that can anticipate future patterns.\u0000Commuters are kept informed of any traffic updates through the Internet. When there is little\u0000or no physical infrastructure and Internet connection, these methods become unworkable. Internet\u0000access is still a problem in rural regions, and there are no roadside units in underdeveloped nations.\u0000This article presents an architecture for smart cities' intelligent vehicular networks that can impromptu\u0000accept data from nearby vehicles in real time and use it to choose routes. As embedded\u0000devices in vehicles, we utilized Android-based smartphones with Wi-Fi Direct capabilities. To set\u0000up our smart transportation system, we utilized a vehicular ad hoc network.\u0000\u0000\u0000\u0000Data was collected and processed using separate methods between two major cities in a\u0000developing nation. Resource utilization, transmission delay, packet loss, and total trip time were\u0000measured against several fixed- and dynamic-route-selection algorithms to assess the framework's\u0000performance.\u0000\u0000\u0000\u0000When equated to a conventional fixed-route-selection procedure, our results reveal a\u000033.3% reduction in trip times.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":" 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"141674707","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}

{"title":"Enhancing Indoor Navigation for Visually Impaired Individuals with an\u0000AI Chatbot Utilizing VEO Optimized Nodes and Natural Language\u0000Processing","authors":"Nagaraju Thandu, Murugeswari R","doi":"10.2174/0122103279287315240327115754","DOIUrl":"https://doi.org/10.2174/0122103279287315240327115754","url":null,"abstract":"\u0000\u0000Visually impaired people face numerous challenges when it\u0000comes to indoor navigation. While outdoor navigation benefits from advancements in GPS and related technologies, indoor spaces present intricate, complex, and often less accessible environments\u0000for those with visual impairments.\u0000\u0000\u0000\u0000In response to these challenges, we propose an innovative approach\u0000to enhance indoor navigation for individuals with visual impairments, leveraging the power of an\u0000AI chatbot. Our AI chatbot employs cutting-edge artificial intelligence techniques to provide realtime assistance and guidance, facilitating independent navigation within intricate indoor settings.\u0000By harnessing natural language processing technologies, the chatbot engages in intuitive interactions with users, comprehending their queries and offering detailed instructions for efficient indoor\u0000navigation. The main goal of this research is to enhance the independence of people with visual\u0000impairments by offering them a reliable and easily accessible tool.\u0000\u0000\u0000\u0000This tool, driven by our Volcano Eruption Optimization Network, promises to significantly enhance the independence and overall indoor navigation experience for visually impaired people, ultimately fostering a greater sense of autonomy in navigating complex indoor\u0000spaces.\u0000\u0000\u0000\u0000Self-Attention-Based Multimodality Convolutional Volcano Eruption optimization\u0000\u0000\u0000\u0000Optimizing Weight Parameters with Volcano Eruption-Based Optimization (VEO)\u0000\u0000\u0000\u0000our AI chatbot-based approach presents a promising solution to the pressing issue of indoor navigation for individuals with visual impairments. We have successfully harnessed cutting-edge artificial intelligence techniques, including natural language processing and computer vision, to empower visually impaired users with real-time assistance and guidance within complex indoor environments.\u0000\u0000\u0000\u0000none\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"6 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140697642","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}

{"title":"Design and Implementation of Long Range Wide Area Networks for\u0000Future Industrial IoT Applications","authors":"Ramasamy Mariappan","doi":"10.2174/0122103279297225240329042445","DOIUrl":"https://doi.org/10.2174/0122103279297225240329042445","url":null,"abstract":"\u0000\u0000To design a Low Power Wide Area Network technology to provide long-range connectivity for IIoT applications.\u0000\u0000\u0000\u0000The evolution of Long Range Wide Area Networks ( LoRaWAN) is a potential candidate for next generation networks for managing the massive number of devices in the Industrial Internet of Things (IIoT).\u0000\u0000\u0000\u0000To design a Low Power Wide Area Network technology to provide long-range connectivity for IIoT applications.\u0000\u0000\u0000\u0000In addition to implement LoRaWAN, this research work deploys the proposed LoRaWAN into the 5G communication technology to achieve the massive IIOT use cases.\u0000\u0000\u0000\u0000The deployment of this hybrid LORA network has demonstrated its long range, low power, stability, flexibility, and low deployment cost through extensive performance evaluation carried out.\u0000\u0000\u0000\u0000This paper concludes the feasibility of deploying LoRaWAN technology for the future generation IIOT applications.\u0000\u0000\u0000\u0000No Applicable\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"55 10","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-04-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140730081","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}

{"title":"Federated Learning-Based Black Hole Prevention in the Internet of Things\u0000Environment","authors":"Martin Victor K, I. Jebadurai, G. Paulraj","doi":"10.2174/0122103279285078240212063010","DOIUrl":"https://doi.org/10.2174/0122103279285078240212063010","url":null,"abstract":"\u0000\u0000The Internet of Things offers ubiquitous automation of\u0000things and makes human life easier. Sensors are deployed in the connected environment that sense\u0000the medium and actuate the control system without human intervention. However, the tiny connected\u0000devices are prone to severe security attacks. As the Internet of Things has become evident in\u0000everyday life, it is very important that we secure the system for efficient functioning.\u0000\u0000\u0000\u0000This paper proposes a secure federated learning-based protocol for mitigating BH attacks\u0000in the network.\u0000\u0000\u0000\u0000The experimental result proves that the intelligent network detects BH attacks and segregates\u0000the nodes to improve the efficiency of the network. The proposed techniques show improved\u0000accuracy in the presence of malicious nodes.\u0000\u0000\u0000\u0000The performance is also evaluated by varying the attack frequency time.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"59 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140080124","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}

{"title":"Learning Framework for Joint Optimal Node Placement and Resource Management in Dynamic Fog Environment","authors":"Sheela S, S. M. D. Kumar","doi":"10.2174/0122103279276389240129091937","DOIUrl":"https://doi.org/10.2174/0122103279276389240129091937","url":null,"abstract":"\u0000\u0000With recent improvements in fog computing, it is now feasible to offer\u0000faster response time and better service delivery quality; however, the impending challenge is to\u0000place the fog nodes within the environment optimally. A review of existing literature showcases\u0000that consideration of joint problems such as fog node placement and resource management are less\u0000reported. Irrespective of different available methodologies, it is noted that a learning scheme facilitates\u0000better capability to incorporate intelligence in the network device, which can act as an enabling\u0000technique for superior operation of fog nodes.\u0000\u0000\u0000\u0000The prime objective of the study is\u0000to introduce simplified and novel computational modelling toward the optimal placement of fog\u0000nodes with improved resource allocation mechanisms concerning bandwidth.\u0000\u0000\u0000\u0000Implemented\u0000in Python, the proposed scheme performs predictive operations using the Deep Deterministic Policy\u0000Gradient (DDPG) method. Markov modelling is used to frame the model. OpenAI Gym library is\u0000used for environment modelling, bridging communication between the environment and the learning\u0000agent.\u0000\u0000\u0000\u0000Quantitative results indicate that the proposed scheme performs better than existing\u0000schemes by approximately 30%.\u0000\u0000\u0000\u0000The prime innovative approach introduced is the\u0000implementation of a reinforcement learning algorithm with a Markov chain towards enriching the\u0000predictive analytical capabilities of the controller system with faster service relaying operations a.\u0000a This article is an extension of our paper entitled “Computational Framework for Node Placement\u0000and Bandwidth Optimization in Dynamic Fog Computing Environments\" presented at INDICON-\u00002022, CUSAT, 24-27 November 2022.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"13 12","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140442653","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}

{"title":"Delay and Fairness Analysis of C-RAN for Single and Multi Scheduling Domain Strategies","authors":"Prasanna Dubey, R. Upadhyay, Uma Rathore Bhatt, Vijaylaxmi S. Bhat","doi":"10.2174/0122103279285271240112052931","DOIUrl":"https://doi.org/10.2174/0122103279285271240112052931","url":null,"abstract":"\u0000\u0000Centralized Radio Access Network (C-RAN) is the most promising network\u0000architecture for next-generation communication networks. It meets the need for flexibility on\u0000fronthaul as well as large bandwidth on backhaul of the network. All along, scheduling is very important\u0000for the transmission of information in an organized manner. C-RAN has not been studied\u0000with the scheduling domain strategies yet in the literature.\u0000\u0000\u0000\u0000So, in this work, packet transmission duration, overall transmission time, wait time, and\u0000fairness index parameters have been calculated and analysed for C-RAN architecture for two different\u0000scheduling domains. The total transmission cycle time parameter is calculated for the three\u0000upper functional split options of C-RAN. The overall transmission time is a parameter calculated\u0000for the entire uplink channel.\u0000\u0000\u0000\u0000To implement the network scenario, extensive scripting is done on MATLAB Editor for\u0000single scheduling domain (SSD) and multi-scheduling domain (MSD) for three higher functional\u0000split options of C-RAN. The data traffic generated in the network is considered random.\u0000\u0000\u0000\u0000A closer examination of results reveals the advantages and disadvantages of both algorithms,\u0000as well as trade-offs between them.\u0000\u0000\u0000\u0000The results provide the pros and cons of the two strategies as mentioned in the article.\u0000\u0000\u0000\u0000For quicker data transmission, SSD should be preferred whereas MSD should be preferred\u0000if multiple users want to access resources simultaneously. Lower functional split options of\u0000C-RAN require less transmission cycle time. The MSD technique is fairer than SSD.\u0000","PeriodicalId":37686,"journal":{"name":"International Journal of Sensors, Wireless Communications and Control","volume":"77 ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-01-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140476174","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}