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Disentangling Disparate Communication Streams and Recovering Underlying Structure

Disentangling Disparate Communication Streams and Recovering...

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international conference on Social Networks Analysis, Management and Security (SNAMS)

作者： Eisha Nathan Center for Applied Scientific Computing Lawrence Livermore National Laboratory Livermore CA USA

ISBN: (数字)9798331518349

ISBN: (纸本)9798331518356

In this paper we present various approaches for the tasks of disentanglement (or automatic forum identification) and structure recovery (or prediction of message replies) in online discussion forums such as Reddit and Stack Exchange. For the disentanglement task we present a fine-tuned BERT model. By leveraging transfer learning from a pre-trained BERT (Bidi-rectional Encoder Representations from Transformers) model, given the message content, our approach achieves accuracies of 83–92% in predicting where a message originated. For the task of structure recovery, we propose a novel neural network architecture that leverages deep learning techniques to model the sequential relationship between messages to predict if one message follows another with accuracies over 80%. Additionally we present few-shot learning strategies for both tasks of disentanglement and structure recovery. Given the sparse availability of limited samples for training in real data, few-shot learning, or the ability to train without needed large amounts of labeled data, is necessary. Experimental results demonstrate the effectiveness of our proposed architecture and methods in capturing contextual dependencies and improving prediction accuracy in such diverse online forums for both tasks and our few-shot architectures achieve comparable accuracies to the case when large training data is available.

关键词： Context Accuracy Discussion forums Social networking (online) Semantics Neural networks Oral communication Predictive models Encoding Few shot learning

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An Energy Consumption Optimization Strategy for Mobile Edge Networks

An Energy Consumption Optimization Strategy for Mobile Edge ...

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Information Technology: IoT and Smart City (ITIoTSC), international conference on

作者： Hua Qu Xing Li Jihong Zhao Yucheng Xue Qian Gao School of Software Engineering Xi'an Jiaotong University Xi'an China School of Electronic and Information Engineering Xi'an Jiaotong University Xi'an China School of Communication and Information Engineering Xi'an University of Posts & Telecommuniccations Xi'an China

ISBN: (数字)9798350328349

ISBN: (纸本)9798350328356

Edge computing involves shifting computational and storage capabilities from centralized cloud computing centers to the edge of the network, allowing edge servers deployed at the edge to respond to user requests. this approach eliminates the need for users to traverse the uplink from the edge network to the cloud computing center when initiating a business request, as well as the downlink from the cloud computing center when returning the computed results, significantly reducing transmission time. However, as latency requirements continue to increase, meeting higher latency demands will inevitably lead to the deployment of a large number of edge servers. the consequent energy consumption problem has become a pressing issue for service providers today. Studies have shown that user business requests are unevenly distributed over time, with periods of high and low demand. To cope with the uncertainty of user business requests and respond quickly, many edge servers remain idle or operate at low business volume, leading to significant energy consumption even when idle. this paper proposes a centralized server-controlled edge device hibernation strategy based on upper and lower thresholds, aiming to minimize the overall energy consumption of all edge servers in the system while meeting user latency requirements. By dividing time slots under upper and lower threshold monitoring, the paper analyzes the load conditions of each edge server in the system during each time slot and assigns computing task migration through the central server to reduce the number of idle and low-business volume edge servers, ultimately achieving the minimization of overall system energy consumption.

关键词： Energy consumption Cloud computing Uncertainty Smart cities Search methods Servers Quadratic programming

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Delay Optimisation for Multimedia Application in a Wireless Network Control System (WNCS)

Delay Optimisation for Multimedia Application in a Wireless ...

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international conference and Workshop on computing and Communication (IEMCON)

作者： Oche A. Egaji Alison Griffiths Mohammad S. Hasan The Centre of Excellence in Mobile and Emerging Technologies University of South Wales United Kingdom Faculty of Computing Engineering and Sciences Staffordshire University United Kingdom

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

this paper mathematically modelled email, voice, Internet Browsing traffic (using inter-arrival rates and packet size) individually and then in a shared network (a combination of the Voice, Internet Browsing and Email to the same network/queue) in congested and non-congested conditions under scheduled and unscheduled state. the traffic is then modelled with wireless nodes with the UDP/IP protocol stack. When scheduling is applied, packets arriving from different sources are distributed evenly over time; this is most effective with constant arriving packets but should help with other traffic types. this paper aims to determine the effectiveness of evenly distributed packet arrival times on different traffic types under congested and non-congested network condition. Also, the paper analysed how closely the measured simulated queuing delay and queue size replicates the theoretical estimation. the results show that the measured simulated delated was close to theoretical for the Voice application. However, the margin of error increases with increasing network load. the network performance improved when scheduling was applied. the measured delay and queue size for Internet Browsing is challenging to predict theoretically because of the bursty nature of the traffic. However, it performs better when scheduling was applied. Moreso, the combined traffic of Voice, email, and internet browsing in a shared network performed better after scheduling was applied.

关键词： Open systems Size measurement Delays Internet Queueing analysis Mobile ad hoc networks Load modeling

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Cascading Hypergraph Convolution Networks for Multi-Behavior Sequential Recommendation*

Cascading Hypergraph Convolution Networks for Multi-Behavior...

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international conference on Behavior, Economic and Social computing (BESC)

作者： Dan Lu Hao Zhang Lijie Li Shiqing Wu Guandong Xu Harbin Engineering University Harbin China University of Technology Sydney Sydney Australia The Education University of Hong Kong Hong Kong SAR China

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

In current research on recommendation systems, exploring multi-behavior sequence recommendation has become a crucial topic. It is well known that user interactions on online platforms (such as social media websites, news aggregation applications) involve not only singular actions like reading or clicking but also various other behaviors such as commenting, sharing, and bookmarking. these diverse interactions reflect different facets of user preferences in item interaction sequences. therefore, understanding and integrating these diverse behaviors to effectively represent user preferences personalized is essential. To better utilize temporal information, we propose a Cascading Hypergraph Convolution Networks For Multi-Behavior Sequential Recommendation (CHMSR) framework. CHMSR aims to capture the underlying behavioral preferences in user sequence interactions and predict future user behaviors through cascading neural networks. Specifically, CHMSR first independently encodes each behavior sequence to extract user interests from the complex behavior relationships in the sequences. then, it aggregates user preferences for different items through hypergraph convolution to capture global preferences. Furthermore, we employ cascading neural networks in behavior chains to capture directional feature dependencies in multi-behavior sequences, propagating messages from upstream to downstream behaviors. In this way, CHMSR can comprehensively consider user interests in multi-behavior sequences and global preferences for items, thus providing more accurate and personalized recommendations. Our experimental results demonstrate that CHMSR significantly outperforms existing recommendation methods on various datasets, validating its effectiveness and practicality

关键词： Social computing Accuracy Convolution Social networking (online) Aggregates Neural networks Feature extraction Convolutional neural networks Recommender systems

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Using Artificial Neural Network in Diagnosis of Polycystic Ovary Syndrome

Using Artificial Neural Network in Diagnosis of Polycystic O...

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Mediterranean conference on Embedded computing (MECO)

作者： Amila Ahmetaš ević Lejla Alič elebić Berina Bajrić Ervina Beč ić Alisa Smajović Amar Deumić Faculty of Pharmacy University of Sarajevo Sarajevo Bosnia and Herzegovina Faculty of Engineering and Natural Sciences International Burch University Sarajevo Bosnia and Herzegovina

ISBN: (数字)9781665468282

ISBN: (纸本)9781665468299

this paper focuses on the problem of diagnosing polycystic ovary syndrome (PCOS), which is one of the leading disorders of the female endocrine system. Although the incidence of this syndrome is quite high, physicians and patients still often encounter problems in their detection, as well as with the ineffectiveness of prescribed therapy. For the development of expert system, a database containing following parameters was used: oligo ovulation, anovulation, free testosterone, free androgen index (FAI), calculated bioavailable testosterone, androstendione, dehydroepiandrosterone, ovarian volume, number of follicles, obesity. the presented dataset contains 1000 samples distributed in two categories: (1) heatlhy subjects and (2) subjects with disease. the purpose of the developed system is to classify instances with polycystic ovary syndrome using artificial neural networks (ANN s). the overall performance evaluation of the system resulted with accuracy of96.1 %, sensitivity of96.8% and specificity of90% indicating significant potential of ANNs in this field. Since the system predicted a total of 157 positive and 23 negative, this leads us to the result that the sensitivity of our system is 96.8%, specificity 90% and accuracy 96.1 %.

关键词： Performance evaluation Heating systems Obesity Sensitivity Hospitals Endocrine system Artificial neural networks

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Performance of 802.11P in VANET at 5G Frequencies for Different Channel Models

Performance of 802.11P in VANET at 5G Frequencies for Differ...

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international conference and Workshop on computing and Communication (IEMCON)

作者： Harsha Puttagunta Dharma P. Agrawal Center for Distributed and Mobile Computing University of Cincinnati Cincinnati USA

ISBN: (数字)9781728184166

ISBN: (纸本)9781728184173

A combination of 5G and VANET will result in an intelligent transportation system. Relaying of 5G data from the cellular network to highly underutilized VANET could reduce the load on the mobile network. Dedicated short-range communication is based on 802.11p which is already widely available. Keeping in mind the future, VANET should support the 5G environment to be widely utilized. We have analyzed the 802.11P protocol at mmWave frequency range which is expected to provide better connectivity in dense urban regions with Rayleigh and Lee Microcell channel models. We have simulated the throughput of the Rayleigh and Lee Microcell using EstiNet simulator and compared their performance in urban dense regions that have better conditions like slow-moving and densely packed vehicle traffic. the urban environment gives us the added benefit of better performance in V2X, V2V network as compared to fast-moving, sparsely populated highway traffic. If VANET made capable of relaying 5G, each car could act as a mobile cell tower in a downtown area.

关键词： 5G mobile communication Urban areas Vehicular ad hoc networks Microcell networks throughput Channel models Vehicle-to-everything

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A Pervasive Community Detection Method through Modular Decomposition of Markov Chain for Social Media Analysis

A Pervasive Community Detection Method Through Modular Decom...

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international Symposium on Soft computing and Intelligent Systems (SCIS)

作者： Takeshi Matsui Antonio O. N. Rene Faculty of Social and Information Studies Gunma University Maebashi Japan Faculty of Engineering Toyama Prefectural University Imizu Japan

ISBN: (数字)9781728197326

ISBN: (纸本)9781728197333

In a network structure, a subset with a dense link is called a community. Many networks in the real world are composed of loosely linked multiple communities. Individual communities are compatible with a functional unit constituting a complex system represented by the network. therefore, if the community structure of the network is clarified, it can be seen how the entire complex system is composed of individual functional units. Clarifying the community structure is a fundamental and essential task for understanding complex systems expressed in networks. Many researchers have been studying to detect communities from networks effectively and efficiently. Meanwhile, the connection density of water pipes affects the failure rate. therefore, the connection of water pipes is regarded as a network, it is possible to estimate the trouble spot through an application of community detection. Clarifying a community of members is to demonstrate a link between members. However, autonomously formed communities in the real world have a ubiquitous (pervasive) structure. If a community has a ubiquitous structure, it implies pervasive overlapping between communities. though studies on the community detection method (modularity maximization and infomap method divide communities into the partition that do not overlap with each other. It follows that each member belongs to only one community. Under these circumstances, in this research, we propose a new community detection method through the modular decomposition of Markov chain method for social network activity.

关键词： Social networking (online) Markov processes Sociology Physics Graph theory Data visualization Data mining

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Centered Low-Intelligence Subjects with Appropriate Noise Enhance Coordination in Networks

Centered Low-Intelligence Subjects with Appropriate Noise En...

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international conference on Behavior, Economic and Social computing (BESC)

作者： Jinwei Miao Xiao Sun Jun Qian Yueting Chai Yi Liu Department of Automation National Engineering Laboratory for E-Commerce Technologies Tsinghua University Beijing China Faculty of Information Technology Beijing University of Technology Beijing China

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

In the era of intelligent interconnection of all things, society gradually forms a system composed of numerous in-telligent entities that collaborate and evolve through division of labor. However, in reality, high-intelligence individuals often fail to achieve high system efficiency after interacting to form intelligent groups. the relationship between interactions among intelligent individuals and the emergence of system efficiency remains to be explored and answered. In this study, we use color coordination game as the basic scenario to investigate the impact of decision error rates of different types of intelligent individuals, the proportion of the same type of intelligent individuals, and the differences in decision error rates within structured groups on problem-solving. through simulation experiments, we find that in high-intelligence groups, adding an appropriate number of relatively low-intelligence individuals can optimize and stabilize problem-solving. Conversely, adding lower-intelligence individuals to a low-intelligence group will decrease overall performance. Notably, when the added lower-intelligence indi-viduals are at the center of the group, their impact on problem-solving efficiency becomes more pronounced. Additionally, we discover that having significant intelligence differences within high-intelligence groups and moderate intelligence differences within low-intelligence groups can also enhance overall group efficiency. this research provides an explanation for the typical phenomenon of mismatch between individual intelligence and system efficiency in collaborative processes and offers guidance for improving system efficiency in real-world social scenarios.

关键词： Error analysis Social networking (online) Robot kinematics Working environment noise Noise Collaboration Games Color Behavioral sciences Problem-solving

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System Aspects of Direct Localization of Multiple Acoustic Sources Using distributed Sensor Networks

System Aspects of Direct Localization of Multiple Acoustic S...

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Electrical, Electronic and computing Engineering (IcETRAN), international conference on

作者： Miljko Erić Nenad Vukmirović Petar Djurić School of Electrical Engineering University of Belgrade Belgrade Serbia School of Electrical Engineering and Innovation Center of the School of Electrical Engineering University of Belgrade Belgrade Serbia Department of Electrical and Computer Engineering Stony Brook University Stony Brook NY USA

ISBN: (数字)9798350386998

ISBN: (纸本)9798350387001

When commonly used two-step localization techniques, such as TOA/TDOA (Time-Of-Arrival, Time-Difference-of-Arrival), DOA (Direction-of-Arrival) or RSSI (Received-Signal-Strength-Indication)/Fingerprint-based, are applied to localization in multiple signal scenarios, there is a so called data association problem. this problem is complex and complicated to solve. Data association problem is referred to grouping of localization parameters for a set of sensors (TOAs, TDOAs, DOAs, RSSI/Fingerprints) into subsets, each corresponding to a single source. With single-step (or direct) localization techniques, this problem does not exist. these techniques are of more recent date, and being numerically more demanding and complex compared to the two-step methods, they are used less frequently than two-step methods. However, they significantly outperform the two-step techniques in terms of localization accuracy and resolution properties. We present a comparative study of direct localization of acoustic signal and radio signal sources using distributed sensor networks. this study examines generic system models, generic signal models, direct localization methods, and theoretical Cramér-Rao bound (CRB) limits of location estimation error. We also include two case studies of applying direct localization of acoustic signal sources in indoor environments. these case studies involve detecting two moving e-Puck educational mobile mini-robots and detecting an acoustic signal source using a functional model of an acoustic camera. We also provide theoretical CRB limits of error estimation for these system models.

关键词： Location awareness Analytical models Cameras Acoustic arrays Acoustics Mathematical models Microphone arrays Sensors Numerical models Sensor arrays

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FLBC-DSS: Federated Learning-Enabled Blockchain-Based Data Sharing Scheme for IIoT

FLBC-DSS: Federated Learning-Enabled Blockchain-Based Data S...

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international conference on Behavior, Economic and Social computing (BESC)

作者： Yan Yao Guangshun Li Huihui Zhang Shanshan Feng Biwei Yan Jian Cao School of Computer Science Qufu Normal University Rizhao China Rizhao-Qufu Normal University Joint Technology Transfer Center Rizhao China School of Computer Engineering Weifang University Weifang China Shandong Academy of Sciences Qilu University of Technology Jinan China School of Information Science and Engineering Shandong Normal University Jinan China School of Computer Scienceand Technology Shandong University Qingdao Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China

ISBN: (数字)9798331531904

ISBN: (纸本)9798331531911

this paper introduces the Federated Learning-Empowered Blockchain-based Data Sharing Scheme (FLBC-DSS), a novel framework designed to enhance data security and efficiency in Industrial Internet of things (IIoT) environments. By integrating federated learning with blockchain technology, FLBC-DSS addresses the critical challenges of data privacy and unauthorized access, promoting secure, decentralized data sharing across various industrial sectors. Utilizing zk-SNARKs, the scheme provides a mechanism for anonymous data verification without compromising data integrity. Performance evaluations conducted using Hyperledger Fabric and SecureBoost demonstrate significant improvements in prediction accuracy and computational efficiency compared to traditional approaches. the implementation of non-cooperative game theory further illustrates the economic benefits of FLBC-DSS, highlighting its potential to increase profitability through strategic data sharing. the results affirm the effectiveness of FLBC-DSS in leveraging advanced cryptographic and machine learning techniques to foster a secure, transparent, and efficient digital ecosystem for IIoT.

关键词： Social computing Machine learning algorithms Accuracy distributed ledger Profitability Scalability Prediction algorithms Fabrics Blockchains Industrial Internet of things

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