scholarly journals Dynamic Diverse Summarisation in Heterogeneous Graph Streams: a Comparison between Thesaurus/Ontology-based and Embeddings-based Approaches

2020 ◽  
Vol 1 (1) ◽  
pp. 70-94
Author(s):  
Niki Pavlopoulou
Keyword(s):  
Data Streams ◽  
Smart Cities ◽  
Dynamic Environment ◽  
Limited Resource ◽  
High Volume ◽  
Performance Comparison ◽  
Limited Resources ◽  
Dynamic Graph ◽  
Graph Streams ◽  
Available Information

Nowadays, there is a lot of attention drawn in smart environments, like Smart Cities and Internet of Things. These environments generate data streams that could be represented as graphs, which can be analysed in real-time to satisfy user or application needs. The challenges involved in these environments, ranging from the dynamism, heterogeneity, continuity, and high-volume of these real-world graph streams create new requirements for graph processing algorithms. We propose a dynamic graph stream summarisation system with the use of embeddings that provides expressive graphs while ensuring high usability and limited resource usage. In this paper, we examine the performance comparison between our embeddings-based approach and an existing thesaurus/ontology-based approach (FACES) that we adapted in a dynamic environment with the use of windows and data fusion. Both approaches use conceptual clustering and top-k scoring that can result in expressive, dynamic graph summaries with limited resources. Evaluations show that sending top-k fused diverse summaries, results in 34% to 92% reduction of forwarded messages and redundancy-awareness with an F-score ranging from 0.80 to 0.95 depending on the k compared to sending all the available information without top-k scoring. Also, the summaries' quality follows the agreement of ideal summaries determined by human judges. The summarisation approaches come with the expense of reduced system performance. The thesaurus/ontology-based approach proved 6 times more latency-heavy and 3 times more memory-heavy compared to the most expensive embeddings-based approach while having lower throughput but provided slightly better quality summaries.

scholarly journals Concept Drift Adaptation Techniques in Distributed Environment for Real-World Data Streams

Smart Cities ◽  
2021 ◽  
Vol 4 (1) ◽  
pp. 349-371
Author(s):  
Hassan Mehmood ◽  
Panos Kostakos ◽  
Marta Cortes ◽  
Theodoros Anagnostopoulos ◽  
Susanna Pirttikangas ◽  
...  
Keyword(s):  
Real World ◽  
Data Streams ◽  
Smart City ◽  
Smart Cities ◽  
Concept Drift ◽  
Distributed Environment ◽  
Real World Data ◽  
Unique Challenge ◽  
World Data ◽  
Concept Drift Detection

Real-world data streams pose a unique challenge to the implementation of machine learning (ML) models and data analysis. A notable problem that has been introduced by the growth of Internet of Things (IoT) deployments across the smart city ecosystem is that the statistical properties of data streams can change over time, resulting in poor prediction performance and ineffective decisions. While concept drift detection methods aim to patch this problem, emerging communication and sensing technologies are generating a massive amount of data, requiring distributed environments to perform computation tasks across smart city administrative domains. In this article, we implement and test a number of state-of-the-art active concept drift detection algorithms for time series analysis within a distributed environment. We use real-world data streams and provide critical analysis of results retrieved. The challenges of implementing concept drift adaptation algorithms, along with their applications in smart cities, are also discussed.

Multiagent coordination and cooperation in a distributed dynamic environment with limited resources

1995 ◽  
Vol 9 (3) ◽  
pp. 229-238 ◽  
Author(s):  
Nicholas V. Findler ◽  
Gregory D. Elder
Keyword(s):  
Dynamic Environment ◽  
Limited Resources ◽  
Multiagent Coordination

scholarly journals Analysis of Data Stream Processing At Edge Layer for Internet of Things

2020 ◽  
Vol 2 (1) ◽  
pp. 26-37
Author(s):  
Dr. Pasumponpandian
Keyword(s):  
Internet Of Things ◽  
Data Streams ◽  
Data Stream ◽  
Smart Cities ◽  
Stream Processing ◽  
Middle Layer ◽  
Cloud Services ◽  
Decentralized Systems ◽  
Data Stream Processing ◽  
Edge Layer

The progress of internet of things at a rapid pace and simultaneous development of the technologies and the processing capabilities has paved way for the development of decentralized systems that are relying on cloud services. Though the decentralized systems are founded on cloud complexities still prevail in transferring all the information’s that are been sensed through the IOT devices to the cloud. This because of the huge streams of information’s gathered by certain applications and the expectation to have a timely response, incurring minimized delay, computing energy and enhanced reliability. So this kind of decentralization has led to the development of middle layer between the cloud and the IOT, and was termed as the Edge layer, meaning bringing down the service of the cloud to the user edge. The paper puts forth the analysis of the data stream processing in the edge layer taking in the complexities involved in the computing the data streams of IOT in an edge layer and puts forth the real time analytics in the edge layer to examine the data streams of the internet of things offering a data- driven insight for parking system in the smart cities.

scholarly journals Consensus for Treatment of Metastatic Castration-Sensitive Prostate Cancer: Report From the First Global Prostate Cancer Consensus Conference for Developing Countries (PCCCDC)

2021 ◽  
pp. 550-558
Author(s):  
Fernando Cotait Maluf ◽  
Felipe Moraes Toledo Pereira ◽  
Pedro Luiz Serrano Uson ◽  
Diogo Assed Bastos ◽  
Diogo Augusto Rodrigues da Rosa ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Developing Countries ◽  
Androgen Deprivation Therapy ◽  
Best Practice ◽  
Specific Antigen ◽  
Limited Resource ◽  
Consensus Conference ◽  
Androgen Deprivation ◽  
Limited Resources ◽  
Resource Limited

PURPOSE International guideline recommendations may not always be extrapolated to developing countries where access to resources is limited. In metastatic castration-sensitive prostate cancer (mCSPC), there have been successful drug and imaging advancements that were addressed in the Prostate Cancer Consensus Conference for Developing Countries for best-practice and limited-resource scenarios. METHODS A total of 24 out of 300 questions addressed staging, treatment, and follow-up for patients with mCSPC both in best-practice settings and resource-limited settings. Responses were compiled and presented in percentage of clinicians supporting each response. Questions had 4-8 options for response. RESULTS Recommendations for staging in mCSPC were split but there was consensus that chest x-ray, abdominal and pelvic computed tomography, and bone scan should be used where resources are limited. In both de novo and relapsed low-volume mCSPC, orchiectomy alone in limited resources was favored and in relapsed high-volume disease, androgen deprivation therapy plus docetaxel in limited resources and androgen deprivation therapy plus abiraterone in high-resource settings were consensus. A 3-weekly regimen of docetaxel was consensus among voters. When using abiraterone, a regimen of 1,000 mg plus prednisone 5 mg/d is optimal, but in limited-resource settings, half the panel agreed that abiraterone 250 mg with fatty foods plus prednisone 5 mg/d is acceptable. The panel recommended against the use of osteoclast-targeted therapy to prevent osseous complications. There was consensus that monitoring of patients undergoing systemic treatment should only be conducted in case of prostate-specific antigen elevation or progression-suggestive symptoms. CONCLUSION The treatment recommendations for most topics addressed differed between the best-practice setting and resource-limited setting, accentuating the need for high-quality evidence that contemplates the effect of limited resources on the management of mCSPC.

Secure Image Processing and Transmission Schema in Cluster-Based Wireless Sensor Network

2017 ◽  
pp. 1022-1040 ◽  
Author(s):  
Mohamed Elhoseny ◽  
Ahmed Farouk ◽  
Josep Batle ◽  
Abdulaziz Shehab ◽  
Aboul Ella Hassanien
Keyword(s):  
Image Processing ◽  
Homomorphic Encryption ◽  
Dynamic Environment ◽  
Image Transmission ◽  
Sensor Nodes ◽  
Wireless Sensor ◽  
Limited Resources ◽  
Military Applications ◽  
Secure Data Transmission ◽  
Computing Platforms

WSN as a new category of computer-based computing platforms and network structures is showing new applications in different areas such as environmental monitoring, health care and military applications. Although there are a lot of secure image processing schemas designed for image transmission over a network, the limited resources and the dynamic environment make it invisible to be used with Wireless Sensor Networks (WSNs). In addition, the current secure data transmission schemas in WSN are concentrated on the text data and are not applicable for image transmission's applications. Furthermore, secure image transmission is a big challenging issue in WSNs especially for the application that uses image as its main data such as military applications. The reason why is because the limited resources of the sensor nodes which are usually deployed in unattended environments. This chapter introduces a secure image processing and transmission schema in WSN using Elliptic Curve Cryptography (ECC) and Homomorphic Encryption (HE).

scholarly journals IoT Technology Applications-Based Smart Cities: Research Analysis

Electronics ◽  
2020 ◽  
Vol 9 (8) ◽  
pp. 1246 ◽  
Author(s):  
Mariana-Daniela González-Zamar ◽  
Emilio Abad-Segura ◽  
Esteban Vázquez-Cano ◽  
Eloy López-Meneses
Keyword(s):  
Smart Cities ◽  
Scientific Activity ◽  
Urban Environments ◽  
Scientific Production ◽  
Future Research ◽  
Iot Applications ◽  
Technology Applications ◽  
Future Research Directions ◽  
Available Information ◽  
Electronic Sensors

The development of technologies enables the application of the Internet of Things (IoT) in urban environments, creating smart cities. Hence, the optimal management of data generated in the interconnection of electronic sensors in real time improves the quality of life. The objective of this study is to analyze global research on smart cities based on IoT technology applications. For this, bibliometric techniques were applied to 1232 documents on this topic, corresponding to the period 2011–2019, to obtain findings on scientific activity and the main thematic areas. Scientific production has increased annually, so that the last triennium has accumulated 83.23% of the publications. The most outstanding thematic areas were Computer Science and Engineering. Seven lines have been identified in the development of research on smart cities based on IoT applications. In addition, the study has detected seven new future research directions. The growing trend at the global level of scientific production shows the interest in developing aspects of smart cities based on IoT applications. This study contributes to the academic, scientific, and institutional discussion to improve decision making based on the available information.

scholarly journals Smart Campus: An Experimental Performance Comparison of Collaborative and Cooperative Schemes for Wireless Sensor Network

Energies ◽  
2019 ◽  
Vol 12 (16) ◽  
pp. 3135 ◽  
Author(s):  
Carolina Del-Valle-Soto ◽  
Leonardo J. Valdivia ◽  
Ramiro Velázquez ◽  
Luis Rizo-Dominguez ◽  
Juan-Carlos López-Pimentel
Keyword(s):  
Energy Consumption ◽  
Sensor Networks ◽  
Performance Metrics ◽  
Smart Cities ◽  
Performance Comparison ◽  
Wireless Sensor ◽  
University Campus ◽  
Multiple Sensors ◽  
Energy Consumption Analysis ◽  
Wireless Environment

Presently, the Internet of Things (IoT) concept involves a scattered collection of different multipurpose sensor networks that capture information, which is further processed and used in applications such as smart cities. These networks can send large amounts of information in a fairly efficient but insecure wireless environment. Energy consumption is a key aspect of sensor networks since most of the time, they are battery powered and placed in not easily accessible locations. Therefore, and regardless of the final application, wireless sensor networks require a careful energy consumption analysis that allows selection of the best operating protocol and energy optimization scheme. In this paper, a set of performance metrics is defined to objectively compare different kinds of protocols. Four of the most popular IoT protocols are selected: Zigbee, LoRa, Bluethooth, and WiFi. To test and compare their performance, multiple sensors are placed at different points of a university campus to create a network that can accurately simulate a smart city. Finally, the network is analyzed in detail using two different schemes: collaborative and cooperative.

scholarly journals A Survey on Blockchain Consensus with a Performance Comparison of PoW, PoS and Pure PoS

Mathematics ◽  
2020 ◽  
Vol 8 (10) ◽  
pp. 1782
Author(s):  
Cristian Lepore ◽  
Michela Ceria ◽  
Andrea Visconti ◽  
Udai Pratap Rao ◽  
Kaushal Arvindbhai Shah ◽  
...  
Keyword(s):  
High Volume ◽  
Performance Comparison ◽  
New Paradigm ◽  
Cryptographic Primitives ◽  
Blockchain Technology ◽  
The Way ◽  
A Performance

Blockchain technology started as the backbone for cryptocurriencies and it has emerged as one of the most interesting technologies of the last decade. It is a new paradigm able to modify the way how industries transact. Today, the industries’ concern is about their ability to handle a high volume of data transactions per second while preserving both decentralization and security. Both decentralization and security are guaranteed by the mathematical strength of cryptographic primitives. There are two main approaches to achieve consensus: the Proof-of-Work based blockchains—PoW—and the Proof-of-Stake—PoS. Both of them come with some pros and drawbacks, but both rely on cryptography. In this survey, we present a review of the main consensus procedures, including the new consensus proposed by Algorand: Pure Proof-of-Stake—Pure PoS. In this article, we provide a framework to compare the performances of PoW, PoS and the Pure PoS, based on throughput and scalability.

Assessing geographical representativeness of crowdsourced urban mobility data: An empirical investigation of Australian bicycling

2019 ◽  
pp. 239980831989433 ◽  
Author(s):  
Scott N Lieske ◽  
Simone Z Leao ◽  
Lindsey Conrow ◽  
Chris Pettit
Keyword(s):  
Spatial Autocorrelation ◽  
Smart Cities ◽  
High Volume ◽  
Urban Mobility ◽  
Flow Data ◽  
Rapid Urbanization ◽  
Validity Assessment ◽  
Planning And Management ◽  
Crowdsourced Data ◽  
Interaction Matrices

In an era of data-driven smart cities, the possibility of using crowdsourced big data to support evidence-based planning and decision-making remains a challenge. Along with the increased availability and potential utility of crowdsourced data, there is a clear need to assess the validity of these data in order to determine their appropriate use for planning and management. Moreover, with growth and rapid urbanization in many cities, there are increasing challenges associated with urban mobility. The goal of this research is to develop an understanding of the geographical representativeness of crowdsourced data in the context of urban mobility through investigation of bicycling in Australian cities. In order to leverage both the geographic distribution and high volume of crowdsourced data for validity assessment, we present a two-stage statistical approach. First, we evaluate flow data through correlation between spatial interaction matrices in the presence of spatial autocorrelation. The second stage evaluates the quantity of information available within the interaction matrices. The approach is demonstrated with crowdsourced bicycling commuting routes recorded by the RiderLog app from 2010 to 2014 that are then correlated with census bicycling journey to work data. Data are from four of Australia’s state capital cities: Adelaide, Brisbane, Melbourne and Perth. These methods assess the representativeness of individual bicycle routes that address the full pattern of flows within multiorigin multidestination systems and incorporate spatial autocorrelation. Results indicate that these crowdsourced data are geographically representative of regional travel where there are higher data volumes, generally in central business districts and occasionally in outlying areas. This research provides insights into both methods for statistical comparison of flow data and the use of crowdsourced bicycling routes for urban planning and management.

scholarly journals Triangle Counting in Dynamic Graph Streams

Algorithmica ◽  
2015 ◽  
Vol 76 (1) ◽  
pp. 259-278 ◽  
Author(s):  
Laurent Bulteau ◽  
Vincent Froese ◽  
Konstantin Kutzkov ◽  
Rasmus Pagh
Keyword(s):  
Dynamic Graph ◽  
Triangle Counting ◽  
Graph Streams
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