Journal articles on the topic 'Graph Gateway'

The identification of parameters in the Hamiltonian that describes complex many-body quantum systems is generally a very hard task. Recent attention has focused on such problems of Hamiltonian tomography for networks constructed with two-level systems. For open quantum systems, the fact that injected signals are likely to decay before they accumulate sufficient information for parameter estimation poses additional challenges. In this paper, we consider use of the gateway approach to Hamiltonian tomography \cite{Burgarth2009,Burgarth2009a} to complex quantum systems with a limited set of state preparation and measurement probes. We classify graph properties of networks for which the Hamiltonian may be estimated under equivalent conditions on state preparation and measurement. We then examine the extent to which the gateway approach may be applied to estimation of Hamiltonian parameters for network graphs with non-trivial topologies mimicking biomolecular systems.

In wireless sensor network (WSN), the energy of sensor nodes is limited. Designing efficient routing method for reducing energy consumption and extending the WSN’s lifetime is important. This paper proposes a novel energy-efficient, static scenario-oriented routing method of WSN based on edge computing named the NEER, in which WSN is divided into several areas according to the coverage of gateway (or base station), and each of the areas is regarded as an edge area network (EAN). Each edge area network is abstracted into a weighted undirected graph model combined with the residual energy of the sensor nodes. The base station (or a gateway) calculates the optimal energy consumption path for all sensor nodes within its coverage, and the nodes then perform data transmission through their suggested optimal paths. The proposed method is verified by the simulations, and the results show that the proposed method may consume about 37% less energy compared with the conventional WSN routing protocol and can also effectively extend the lifetime of WSN.

With the construction of smart grid, increasing number of smart devices will be connected to the power communication network. Therefore, how to allocate the resources of access devices has become an urgent problem to be solved in smart grid. However, due to the diversity and time-variability of access devices at the edge of the power grid, such dynamic changes may lead to untimely and unbalanced resource allocation of the power grid and additional system overhead, resulting in reducing the efficiency of power grid operation, unbalanced workload and other problems. In this paper, a grid resource allocation scheme based on Gauss optimization is proposed. The grid virtualization application resources are managed through three main steps: decomposition, combination and exchange, so as to realize the reasonable allocation of grid resources. Considering the time-variability of the grid topology and the diversity of the access device, the computational complexity of the traditional data analysis model is too high to be suitable for time-sensitive power network structure. This paper proposes an MPNN framework combined with the Graph Convolutional Network (GCN) to enhance the calculation efficiency and realize the rapid allocation of network resources. Since the smart gateway connected by the grid terminal has certain computation ability, the cloud computing used in distribution model in deep learning to find the optimal solution can be distributed in the cloud and edge computing gateway. In this way, The entire electricity network can efficiently manage and orchestrate virtual services to maximize the utility of grid virtual resources. Furthermore, this paper also adopt the GG-NN (Gated Graph Neural Network) which is based on the MPNN framework in the training. Finally, we carry out simulation for the Gauss optimization scheme and the MPNN-based scheme to verify that the convolutional diagram neural network is suitable for virtual resource allocating in multi-access power Internet-of –Things (IoTs).

Forests are an enduring component of the natural world and perform a vital role in protecting the environment. Forests are valuable resources to control global warming and provide oxygen for the survival of human life, including wood for households. Forest fires have recently emerged as a major threat to biological processes and the ecosystem. Unfortunately, almost every year, fire damages millions of hectares of forest land due to late and inefficient detection of fire. However, it is important to identify the forest fire at the initial level before it spreads to vast areas and destroys natural resources. In this paper, a formal model of the Internet of Things (IoT) and drone-based forest fire detection and counteraction system is presented. The proposed system comprises network maintenance. Sensor deployment is on trees, the ground, and animals in the form of subnets to transmit sensed data to the control room. All subnets are connected to the control room through gateway nodes. Alarms are being used to alert human beings and animals to save their lives, which will help to initially protect them from fire. The embedded sensors collect the information and transfer it to the gateways. Drones are being used for real-time visualization of fire-affected areas and to perform actions to control fires because they play a vital role in disasters. Graph theory is used to construct an efficient model and to show the connectivity of the network. To identify failures and develop recovery procedures, the algorithm is designed through the graph-based model. The model is developed by the Vienna Development Method-Specification Language (VDM-SL), and the correctness of the model is ensured using various VDM-SL toolbox facilities.

AbstractBackgroundAnabolic-androgenic steroid (AAS) use is known to be associated with other psychiatric disorders, such as body image disorders, conduct disorder/sociopathy, and other substance use disorders (SUD) – but the causal pathways among these conditions remain poorly delineated.MethodsWe created a directed acyclic graph to diagram hypothesized relationships among AAS use and dependence, body image disorder (BID), conduct disorder/sociopathy, and other SUD. Using proportional hazards models, we then assessed potentially causal relationships among these variables, using a dataset of 233 male weightlifters, of whom 102 had used AAS.ResultsBID and conduct disorder/sociopathy both strongly contributed to the development of AAS use, but did not appear to contribute further to the progression from AAS use to AAS dependence. Other SUD beginning prior to first AAS use – whether broadly defined or restricted only to opioids – failed to show an effect on AAS use or progression to AAS dependence. Conversely, AAS use contributed significantly to the subsequent first-time development of opioid use disorders but did not significantly increase the risk for first-time development of non-opioid SUD, taken as a whole.ConclusionsOur analysis suggests that AAS use and other SUD are mutually attributable to underlying conduct disorder/sociopathy. SUD do not appear to represent a ‘gateway’ to subsequent AAS use. AAS use may represent a gateway to subsequent opioid use disorder, but probably not to other SUD.

The emergence of the Industrial Internet of Things (IIoT) has accelerated the adoption of Industrial Wireless Sensor Networks (IWSNs) for numerous applications. Effective communication in such applications requires reduced end-to-end transmission time, balanced energy consumption and increased communication reliability. Graph routing, the main routing method in IWSNs, has a significant impact on achieving effective communication in terms of satisfying these requirements. Graph routing algorithms involve applying the first-path available approach and using path redundancy to transmit data packets from a source sensor node to the gateway. However, this approach can affect end-to-end transmission time by creating conflicts among transmissions involving a common sensor node and promoting imbalanced energy consumption due to centralised management. The characteristics and requirements of these networks encounter further complications due to the need to find the best path on the basis of the requirements of IWSNs to overcome these challenges rather than using the available first-path. Such a requirement affects the network performance and prolongs the network lifetime. To address this problem, we adopt a Covariance-Matrix Adaptation Evolution Strategy (CMA-ES) to create and select the graph paths. Firstly, this article proposes three best single-objective graph routing paths according to the IWSN requirements that this research focused on. The sensor nodes select best paths based on three objective functions of CMA-ES: the best Path based on Distance (PODis), the best Path based on residual Energy (POEng) and the best Path based on End-to-End transmission time (POE2E). Secondly, to enhance energy consumption balance and achieve a balance among IWSN requirements, we adapt the CMA-ES to select the best path with multiple-objectives, otherwise known as the Best Path of Graph Routing with a CMA-ES (BPGR-ES). A simulation using MATALB with different configurations and parameters is applied to evaluate the enhanced graph routing algorithms. Furthermore, the performance of PODis, POEng, POE2E and BPGR-ES is compared with existing state-of-the-art graph routing algorithms. The simulation results reveal that the BPGR-ES algorithm achieved 87.53% more balanced energy consumption among sensor nodes in the network compared to other algorithms, and the delivery of data packets of BPGR-ES reached 99.86%, indicating more reliable communication.

Abstract Objective: Using graph theoretical analysis, the current study explores network properties of highly associated brain areas during initiation and inhibition. Method: The current study utilized a publicly available dataset of functional connectivity matrices generated during initiation and inhibition (go/nogo paradigm) in 144 healthy adults between the age of 20 and 86 who were recruited from the greater Toronto area (Jenny R Rieck et. al, 2021). The researcher selected brain areas (ROIs) that showed high correlation (>0.75) from each participant's matrices and input high incidents of functional connectivity among all participants into an incidental matrix which was used to generate a network graph for each task. ROIs are presented as nodes (vertices) while their connections are edges. Core measures, such as degree distribution, mean distance, within module degree z score, and gateway coefficient, were analyzed. Results: The analysis showed a disconnected network across several brain regions and several common connections among somatomotor, default A, and peripheral visual networks. For the initiation task, the medial prefrontal cortex on both hemispheres are more frequently activated. A high betweenness was found in different brain areas for the inhibition and initiation across visual and default networks. Further analysis showed the extra-striate cortex appears to be the “hub” for initiation while the extra-striate superior cortex appears to be the “hub” for inhibition. Conclusion(s): The present study showed several common brain areas that are activated during both initiation and inhibition, highlighted differences in activation between the two tasks and explored several areas that could be a “hub” during each task.

Abstract Background informal carers of people with dementia are at greater risk of anxiety and depressive disorders if they find caregiving to be a burden. The aim of this study was to use a network analysis of cross-sectional data to investigate the relationships between anxiety and depressive symptoms in family carers of older people with dementia who experience burden. Methods sixty family carers exhibiting high levels of burden using the Zarit Burden Interview were included in the study. Participants completed the Hospital Anxiety and Depression Scale. The network analysis identified the depression and anxiety symptom network using features including a topological graph, network centrality metrics and community analysis. The network was estimated through the graphical LASSO technique in combination with a walktrap algorithm to obtain the clusters within the network and the connections between the nodes (symptoms). A directed acyclic graph was generated to model symptom interactions. Results the resulting network architecture shows important bridges between depression and anxiety symptoms. Lack of pleasure and loss of enjoyment were identified as potential gateway symptoms to other anxiety and depression symptoms and represent possible therapeutic targets for psychosocial interventions. Fear and loss of optimism were highly central symptoms, indicating their importance as warning signs of more generalised anxiety and depression. Conclusions this network analysis of depressive and anxiety symptoms in overburdened family carers provides important insights as to what symptoms may be the most important targets for behavioural interventions.

With the development of electronic technology and sensor technology, more and more intelligent electronic devices integrate micro inertial sensors, which makes the research of human action recognition based on action sensing data have great application value. Data-based action recognition is a new research direction in the field of pattern recognition, which is essentially a process of action data acquisition, feature extraction, feature extraction, and recognition, the process of classification and recognition. Inertial motion information includes acceleration and angular velocity information, which is ubiquitous in daily life. Compared with motion recognition based on visual information, it can more directly reflect the meaning of action. This study mainly discusses the method of analyzing and managing volleyball action by using the action sensor of mobile device. Based on the motion recognition algorithm of support vector machine, the motion recognition process of support vector machine is constructed. When the data terminal and gateway of volleyball players are not in the same LAN, the classification algorithm classifies the samples to be tested through the characteristic data, which directly affects the recognition results. In this paper, the support vector machine algorithm is selected as the data classification algorithm, and the calculation of the classification process is reduced by designing an appropriate kernel function. For multiclass problems, the hierarchical structure of directed acyclic graph is optimized to improve the recognition rate. We need to bind motion sensors to human joints. In order to realize real-time recognition of human motion, mobile devices need to add windows to the motion capture data, that is, divide the data into a small sequence of specified length, and provide more application scenarios for the device. This method of embedding motion sensors into devices to read motion information is widely used, which provides a convenient data acquisition method for human motion pattern recognition based on motion information. The multiclassification support vector machine algorithm is used to train the classification algorithm model with action data. When the signal strength of the sensor is 90 t and the speed is 2.0 m/s and 0.5 m/s, the detection accuracy of the adaptive threshold is 93% and 95%, respectively. The results show that the SVM method based on hybrid kernel function can greatly improve the recognition accuracy of volleyball stroke, and the recognition time is short.

In recent years, the use of security gateways (SG) located within the electrical grid distribution network has become pervasive. SGs in substations and renewable distributed energy resource aggregators (DERAs) protect power distribution control devices from cyber and cyber-physical attacks. When encrypted communications within a DER network is used, TCP/IP packet inspection is restricted to packet header behavioral analysis which in most cases only allows the SG to perform anomaly detection of blocks of time-series data (event windows). Packet header anomaly detection calculates the probability of the presence of a threat within an event window, but fails in such cases where the unreadable encrypted payload contains the attack content. The SG system log (syslog) is a time-series record of behavioral patterns of network users and processes accessing and transferring data through the SG network interfaces. Threatening behavioral pattern in the syslog are measurable using both anomaly detection and graph theory. In this paper, it will be shown that it is possible to efficiently detect the presence of and classify a potential threat within an SG syslog using light-weight anomaly detection and graph theory.

Abstract The article deals with the actual aspects of practical mathematical modeling of hydro-dynamic processes in the chambers of navigational locks. The use of direct and inverse Fourier transforms has been tested to obtain the representations of non-stationary graphs acceptable for analysis. Cross-sections of the water flow filling the chamber of a typical lock in the Volga-Don shipping channel were used as reference data (VDSC). The control sections in the flow were selected with a qualitatively different hydrodynamic nature of motion. A two-dimensional array of non-stationary data results were decomposed into Fourier series. The resulting graph of the amplitude-frequency spectrum was analyzed by the harmonics forming it. Its amplitude was taken as the criterion for the harmonics’ selection. After zeroing the insignificant harmonics, the inverse Fourier transform was performed. The quality of the data array approximation was controlled by visual overlay of the original graphs on the processed one. In all cases, it was possible to obtain the acceptable approximation results. This created a reliable basis for the scientific analysis and development of engineering measures for the implementation of safe ship passage through gateways. At the end of the article, a number of the data processing specific features are presented, caused by a variety of hydrodynamic features of the flow in various sections.

In this paper, we consider the problem of gathering information in a gateway in a radio mesh access network. Due to interferences, calls (transmissions) cannot be performed simultaneously. This leads us to define a round as a set of non-interfering calls. Following the work of Klasing, Morales and Pérennes, we model the problem as a Round Weighting Problem (RWP) in which the objective is to minimize the overall period of non-interfering calls activations (total number of rounds) providing enough capacity to satisfy the throughput demand of the nodes. We develop tools to obtain lower and upper bounds for general graphs. Then, more precise results are obtained considering a symmetric interference model based on distance of graphs, called the distance-[Formula: see text] interference model (the particular case [Formula: see text] corresponds to the primary node model). We apply the presented tools to get lower bounds for grids with the gateway either in the middle or in the corner. We obtain upper bounds which in most of the cases match the lower bounds, using strategies that either route the demand of a single node or route simultaneously flow from several source nodes. Therefore, we obtain exact and constructive results for grids, in particular for the case of uniform demands answering a problem asked by Klasing, Morales and Pérennes.

Public streams of geo-located social media information have provided researchers with a rich source of information from which to draw patterns of urban-scale human-mobility. However, most of the literature relies on assumptions over the spatial distribution of this data (e.g., by considering only a uniform grid division of space). In this work the authors present a method that does not rely on such assumptions. They followed the social media activity of 24,135 Twitter users from Mexico City over a period of seven months (June 2013 - February 2014). The authors' method clusters user's geo-locations into a 19 zone data-driven division of Mexico City. These results can be interpreted from a graph theory-based perspective, by representing each division as nodes, and the edges between them as the number of people traveling between locations. Graph centrality reveals city's infrastructural key points. Without these gateways the authors can argue that mobility would either be radically transformed or break the city apart.

<p><span>This paper traces the evolution of the South Gate (Sungnye-mun) as a must-see destination representing the antiquity, beauty and patrimony of Seoul, the former capital of the 600 year-old Chosŏn dynasty of Korea (1392-1910). Using the case study of the Republic of Korea's premier national treasure, this paper traces the preservation methods, educational, and commercial agendas of the producers, managers, and promoters of heritage remains. The earliest photographic records date back to the late nineteenth century when travel photo- graphs taken by stereo-view companies, photo-studios, and diplomats were recycled in newspapers, postcards, and guidebooks, giving foreigners the first glimpses into the “Hermit Kingdom.” The analysis relies on CRM archives such as photographs, guidebooks, architectural surveys, excavation reports, and material resources compiled by the Cultural Heritage Administration (CHA) during the five years of excavations and construction of a replica to replace the original destroyed in an arson fire in 2008. The paper concludes with the grand re-opening ceremony to celebrate not only the resurrection of South Gate but to showcase the successes of the government's centralized heritage management policies, and conservation methods dedicated to preserving the city's architectural heritage.</span></p>

Compared with traditional statistics, only a few social scientists employ Bayesian analyses. The existing software programs for implementing Bayesian analyses such as OpenBUGS, WinBUGS, JAGS, and rstanarm can be daunting given that their complex computer codes involve a steep learning curve. In contrast, this paper introduces a new open software for implementing Bayesian network modelling and analysis: the bayesvl R package. The package aims at providing an intuitive gateway for beginners of Bayesian statistics to construct and analyse mathematical models in social sciences. To achieve this aim, the bayesvl package integrates three core functions seamlessly: (i) designing Bayesian network models using directed acyclic graphs (DAGs) of bnlearn, (ii) generating attractive visualization of ggplot2, and (iii) simulating data and computing posterior distribution using the Markov chain Monte Carlo (MCMC) algorithms of rstan and rethinking. A case example illustrates how the bayesvl package helps leverage users’ intuition in creating and evaluating mathematical models of their social scientific problems while minimizing the daunting aspect of writing complex computer codes.

The use of information technology gives the advantage of open access for its users, but a new problem arises that there is a threat from unauthorized users. Intrusion Detection System (IDS) is applied to assist administrator to monitoring network security. IDS displays illegal access information in a raw form which is require more time to read the detected threats. This final project aims to design an IDS with web application which is made for pulling information on IDS sensor database, then processing and representing them in tables and graphs that are easy to understand. The web application also has IpTables firewall module to block attacker's IP address. The hardware used is Cisco IPS 4240, two computers Compaq Presario 4010F as client and gateway, and Cisco Catalyst 2960 switch. The software used is Ubuntu 12.0 LTS Precise operating system, BackTrack 5 R1 operating system, PHP 5.4 programming language, MySQL 5 database, and web-based system configuration tool Webmin. Testing is done using several BackTrack applications with the aim of Cisco IPS 4240 is capable of detecting accordance with the applicable rules. Each events of any attack attempt or threat was obtained from IDS sensor database in XML form. XML file is sent using Security Device Event Exchange (SDEE) protocol. The web application is tested by looking at the output tables and graphs that displays the appropriate results of sensor detection. This study generated an intrusion detection system that is easier to monitor. Network packets copied by the Cisco 2960 switch and then forwarded to the sensor. Intruder detection is done by Cisco IPS 4240 sensor. Log detection processed by the web application into tables and graphs. Intrusion detection systems are intended to improve network security.

A cognitive networking approach to the anycast routing problem for delay-tolerant networking (DTN) is proposed. The method is suitable for the space–ground and other domains where communications are recurrently challenged by diverse link impairments, including long propagation delays, communication asymmetry, and lengthy disruptions. The proposed method delivers data bundles achieving low delays by avoiding, whenever possible, link congestion and long wait times for contacts to become active, and without the need of duplicating data bundles. Network gateways use a spiking neural network (SNN) to decide the optimal outbound link for each bundle. The SNN is regularly updated to reflect the expected cost of the routing decisions, which helps to fine-tune future decisions. The method is decentralized and selects both the anycast group member to be used as the sink and the path to reach that node. A series of experiments were carried out on a network testbed to evaluate the method. The results demonstrate its performance advantage over unicast routing, as anycast routing is not yet supported by the current DTN standard (Contact Graph Routing). The proposed approach yields improved performance for space applications that require as-fast-as-possible data returns.

Spatial and urban planning are directed towards achieving territorial cohesion as one of the sustainable development goals. Considering the hybrid concept of green infrastructure, this paper aims to provide an “ecological model” of achieving territorial cohesion in spatial and urban planning. Based on the connectivity level analysis between green infrastructure elements (green infrastructure hubs, nodes, gateways and dots), application of the GI concept guides the development of spatial planning scenarios. The application of Voronoi diagrams and landscape graph-based principles contribute to defining the shortest distances between green infrastructure elements, which resulted in the definition of the significance of structural and functional arrangement of green infrastructure dots in the matrix of the urban rural continuum in the territory of the urban-rural landscape of three case studies in Vojvodina, Serbia (Novi Sad, Subotica, Zrenjanin). As a result of this study, green infrastructure dots showed a great potential of application at the local level by developing them through landscape design with creative and artistic elements in order to achieve higher level of cohesion through visual attractivity, multifunctionality and recreation. The level of connectivity between elements of green infrastructure should be considered as an indicator of the sustainable spatial development goals achievement, in the field of nature conservation and territorial and social cohesion.

The recent proliferation of multimedia information on the web enhances user information need from simple textual lookup to multi-modal exploration activities. The current search engines act as major gateways to access the immense amount of multimedia data. However, access to the multimedia content is provided by aggregating disjoint multimedia search verticals. The aggregation of the multimedia search results cannot consider relationships in them and are partially blended. Additionally, the search results’ presentation is via linear lists, which cannot support the users’ non-linear navigation patterns to explore the multimedia search results. Contrarily, users’ are demanding more services from search engines. It includes adequate access to navigate, explore, and discover multimedia information. Our discovery approach allow users to explore and discover multimedia information by semantically aggregating disjoint verticals using sentence embeddings and transforming snippets into conceptually similar multimedia document groups. The proposed aggregation approach retains the relationship in the retrieved multimedia search results. A non-linear graph is instantiated to augment the users’ non-linear information navigation and exploration patterns, which leads to discovering new and interesting search results at various aggregated granularity levels. Our method’s empirical evaluation results achieve 99% accuracy in the aggregation of disjoint search results at different aggregated search granularity levels. Our approach provides a standard baseline for the exploration of multimedia aggregation search results.

This paper presents a new method for decomposing environments of complex geometry into a navigation mesh represented by bounding geometry and a connectivity graph for real-time agent usage in virtual worlds. This is accomplished by the generation of a well-defined and high-coverage set of convex navigable regions and the connected gateways between them. The focus of this paper is a new automated algorithm developed for decomposing a 2D representation of world-space into arbitrary sided high-order polygons. The DEACCON (Decomposition of Environments for the Creation of Convex-region Navigation-meshes) algorithm works by seeding a 2D polygonal representation of world-space with a series of quads. Each quad is then provided with the opportunity to grow to its maximum extent before encountering an obstruction. DEACCON implements an automatic subdividing system to convert quads into higher-order polygons while still maintaining the convex property. This allows for the generation of navigation meshes with high degrees of coverage while still allowing the use of large navigation regions, providing for easier agent navigation in virtual worlds. Compared to the Space-filling Volumes and Hertel-Mehlhorn navigation mesh decomposition methods, DEACCON provides more complete coverage, controllable mesh sizes, and better overall algorithmic control to desired decomposition quality with an improvement in agent navigation speed due to better decompositions.

Nowadays, with the continuous integration of production network and business network, more and more Industrial Internet of Things and Internal Office Network have been interconnected and evolved into a large-scale enterprise-level intraindustry network. Terminal devices are the basic units of internal network. Accurate identification of the type of device corresponding to the IP address and detailed description of the communication behavior of the device are of great significance for conducting network security risk assessment, hidden danger investigation, and threat warning. Traditional cyberspace surveying and mapping techniques take the form of active measurement, but they cannot be transplanted to large-scale intranet. Resources or specific targets in internal networks are often protected by firewalls, VPNs, gateways, and other technologies, so they are difficult to analyze and determine by active measurement. In this paper, a passive measurement method is proposed to identify and characterize devices in the network through real traffic data. Firstly, a new graph structure mining method is used to determine the server-like devices and host-like devices; then, the NAT-like devices are determined by quantitative analysis of traffic; finally, by qualitative analysis of the NAT-like device traffic, it is determined whether there are server-like devices behind the NAT-like device. This method will prove to be useful in identifying all kinds of devices in network data traffic, detecting unauthorized NAT-like devices and whether there are server-like devices behind the NAT-like devices.

<p>The Kaligawe Genuk area is the main route for the North Coast (Pantura) of Java.<br />The area is the gateway to the city of Semarang from the east direction. Since 2005,<br />this area has frequently had floods caused by tides (tidal floods) and rainfall. The<br />Central Government, supported by the Semarang City Government, built the Kali<br />Tenggang and Sringin Polder systems from 2016 to 2019. In terms of capacity, this<br />system is not yet perfect for dealing with floods, and it requires efforts so that the<br />system can be operated optimally. This study activity aims to simulate rainfall flow<br />rate, the pump capacity, and the retention pond. The simulation results will become<br />the basis for the development of the polder system operational manual. The<br />implementation method collects secondary rainfall data, reviewing the condition of<br />a catchment area, retention pond, and pump station. Focus group discussion with<br />stakeholders done in the Kaligawe Genuk area. The location of the activity is more<br />focused on the Kali Sringin area. This study produces tables and graphs of pump<br />capacity simulation, retention ponds, and an operational manual for the Sringin<br />Polder system. It is hoped that this guideline will become the basis for the polder<br />system's sustainable operations.</p>

Purpose The purpose of this paper is to provide perspective on whether and why global metro house prices have become more synchronized, and perspective on the limited implications of this for investing in international real estate. Design/methodology/approach This paper reviews main findings from the literature on house price determination, reviews the emerging literature on global synchronization, and provides graphs to illustrate main points and trends. Findings House prices have become somewhat more synchronized likely reflecting greater correlation in long-term interest rates and macroeconomic cycles related to trends in globalization and international portfolio diversification. Nevertheless, this trend has not been continuous, reflecting that house prices depend on other fundamentals, which are not uniform across areas. Theory and evidence indicate that the more common are fundamentals, the more synchronized are house price cycles and the more substitution effects may matter. Also, real estate markets that are open to immigration and foreign investment have become more sensitive to shifts in the international demand for property by migrants or investors. Research limitations/implications Changes in international house price synchronization stem from variation in two categories of key drivers of house prices. The first are traditional supply and demand fundamentals. The second include international capital flows and immigration. Both sets of factors are sensitive to the economic environment and public policy. Increased synchronization of business cycles, the Euro currency union, and more common monetary policy strategies and tactics have fostered greater correlation of real interest rates across countries, which tend to increase house price synchronization. These effects can be amplified by the tendency for property owners to use extrapolative expectations of future house prices. Practical implications Shifts in prospective returns and the synchronization of international property returns not only on arbitrage of general property price differentials but also on underlying factors driving those differentials. Investors need to be mindful of the risks that metro prices sometimes reflect bubble-builder dynamics that can give rise to over-shooting of house prices. Observing simple correlations and changes in those correlations does not do away with the need for careful analysis of property investment, and if anything, warrant analysis of both how and why one may observe changes in the extent to which international house prices is synchronized. Social implications Despite the rise of globalization and of new technologies, the author has seen substantial divergences in house prices emerge across gateway cities and metros in less vibrant areas within countries. These reflect not only the impact of stronger income and population in more tech, educated and global oriented cities but also changes in the demand for amenities toward more culturally appealing cities, often – but not exclusively in – warmer or coastal areas where the supply elasticity of housing is often limited. Further complicating investment decisions are potential shifts in housing or immigration policy that can notably affect the demand for housing. Originality/value The paper provides practical perspective on why different groups of international cities have seen their house prices become more sychronized. Nevertheless, increased synchronization has occurred within an elite set of major cities, but in an environment house prices have diverged across gateway cities and metros in less vibrant areas within countries. The paper helps investors make sense of some recent patterns and recent prospects for investing in international real estate.

Abstract This study was conducted to measure major indices for composting of livestock manure using a real-time ICT equipment. The equipment can receive the data such as temperature, humidity, and electrical conductivity every minute from a compost. Collected data were stored in the server via the wireless sensor nodes and gateways, and automatically visualized to observe the status of compost as graphs. A total of 9 fixed ventilation type vessels (height, 200 cm; diameter, 30 cm; thickness, 2 cm) made of PVC material were designed to inject external air using a ring blower (KJB1-1500, KIJEONSA Co., Republic of Korea) through the vent at lower part of vessel. Cattle manure that piled approximately 75 kg into each vessel, with injecting external air as 15 L/min and the change of each factor was measured and recorded for 15 days. Sensors (5TE, METER Group Inc., USA) were put through holes at 20, 105, and 190 cm from the bottom of each vessel. The measured values were different depending on the position of the sensor. For example, at 17:00 on September 15, 2018, the humidity in the Vessel 1 was top 1.4 %, middle 47.7 %, and bottom 91.1 %. The electrical conductivity was top zero, middle 4.69 dS/m and bottom 13.24 dS/m, and the temperature was top 46.0 ℃, middle 31.7 ℃ and bottom was 22.9 ℃ at 13:15 on September 9, 2018. Because differences were detected by the measurement position in the same compost during the composting period, the location of the sensor was important for measurement of composting. Overall, continuous and real-time monitoring was possible to measure fermentation parameters during the composting process by the real-time ICT equipment. Therefore, this system can be utilized for monitoring for optimal livestock manure decomposition model.

Nurul SDIT Istiqlal Klaten an Islamic-based elementary school that has a high awareness of the importance of the monitoring and evaluation of student learning in order to know the level of success of the learning process is running. In order to maximize the process it created an information system of monitoring and evaluation of student learning web-based and SMS-gateway. This information system can display a list of values of each student in each subject and grade of teaching a teacher with grouping based on the criteria of the KKM. Moreover, it can display a graph of the percentage of the value of grouping results. Values that have been added can be disseminated to parents / guardians of the students. This information system will display a graph the value of each student for all four test scores. System design using the Context Diagram, Hierarchy Process Input Output, Data Flow Diagrams, input design, output design, and database design. The result of this research is the information system of monitoring and evaluation of student learning which has an input in the form of student data, teacher data subject, the data homeroom, the data subject, class data, the data teacher, materials, values and information. While the results of the output of a graph of the results of grouping value, sms information listed value value with KKM and the average grade and disseminated the text contains some information. Based on the calculation of the questionnaire, obtained persentase 84,00% so that it can be concluded that the information system is feasible to implemention in SDIT Nurul Istiqlal Klaten. Keywords: Monitoring, PHP, SMS-Gateway

The paper represents a small controller with wireless connection, which measures air temperature, air humidity and soil humidity. As an output action it can switch on and off an irrigation pump. Monitoring is realized over Wi-Fi connection to a gateway and cloud service. The service allows database storage and graph representation of the input values via desktop or mobile device browser. Sensors choice is also explained in details with advantages and disadvantages of the possible solutions. Developed device allows fine tuning, according to the target plants, can be duplicated many times in the range of the hothouse. It is one of the cheapest solutions which provides very stable work as a result of the specific implementation.

AbstractThe focus of this paper is on base functionalities required for UAV-based rapid deployment of an ad hoc communication infrastructure in the initial phases of rescue operations. The main idea is to use heterogeneous teams of UAVs to deploy communication kits that include routers, and are used in the generation of ad hoc Wireless Mesh Networks (WMN). Several fundamental problems are considered and algorithms are proposed to solve these problems. The Router Node Placement problem (RNP) and a generalization of it that takes into account additional constraints arising in actual field usage is considered first. The RNP problem tries to determine how to optimally place routers in a WMN. A new algorithm, the RRT-WMN algorithm, is proposed to solve this problem. It is based in part on a novel use of the Rapidly Exploring Random Trees (RRT) algorithm used in motion planning. A comparative empirical evaluation between the RRT-WMN algorithm and existing techniques such as the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) and Particle Swarm Optimization (PSO), shows that the RRT-WMN algorithm has far better performance both in amount of time taken and regional coverage as the generalized RNP problem scales to realistic scenarios. The Gateway Node Placement Problem (GNP) tries to determine how to locate a minimal number of gateway nodes in a WMN backbone network while satisfying a number of Quality of Service (QoS) constraints.Two alternatives are proposed for solving the combined RNP-GNP problem. The first approach combines the RRT-WMN algorithm with a preexisting graph clustering algorithm. The second approach, WMNbyAreaDecomposition, proposes a novel divide-and-conquer algorithm that recursively partitions a target deployment area into a set of disjoint regions, thus creating a number of simpler RNP problems that are then solved concurrently. Both algorithms are evaluated on real-world GIS models of different size and complexity. WMNbyAreaDecomposition is shown to outperform existing algorithms using 73% to 92% fewer router nodes while at the same time satisfying all QoS requirements.

Abstract Graphical models such as brain connectomes derived from functional magnetic resonance imaging (fMRI) data are considered a prime gateway to understanding network-type processes. We show, however, that standard methods for graphical modeling can fail to provide accurate graph recovery even with optimal tuning and large sample sizes. We attempt to solve this problem by leveraging information that is often readily available in practice but neglected, such as the spatial positions of the measurements. This information is incorporated into the tuning parameter of neighborhood selection, for example, in the form of pairwise distances. Our approach is computationally convenient and efficient, carries a clear Bayesian interpretation, and improves standard methods in terms of statistical stability. Applied to data about Alzheimer’s disease, our approach allows us to highlight the central role of lobes in the connectivity structure of the brain and to identify an increased connectivity within the cerebellum for Alzheimer’s patients compared to other subjects.

In many real-world wireless IoT networks, the application dictates the location of the nodes and therefore the link characteristics are inhomogeneous. Furthermore, nodes may in many scenarios only communicate with the Internet-attached gateway via multiple hops. If an energy-efficient short-range modulation scheme is used, nodes that are reachable only via high-path-loss links cannot communicate. Using a more energy-demanding long-range modulation allows connecting more nodes but would be inefficient for nodes that are easily reachable via low-path-loss links. Combining multiple modulations is challenging as low-power radios usually only support the use of a single modulation at a time. In this paper, we present the Long-Short-Range (LSR) protocol which supports low-power multi-hop communication using multiple modulations and is suited for networks with inhomogeneous link characteristics. To reduce the inherent redundancy of long-range modulations, we present a method to determine the connectivity graph of the network during regular data communication without adding significant overhead. In simulations, we show that LSR allows for reducing power consumption significantly for many scenarios when compared to a state-of-the-art multi-hop communication protocol using a single long-range modulation. We demonstrate the applicability of LSR with an implementation on real hardware and a testbed with long-range links.

Modular organization is an emergent property of brain networks, responsible for shaping communication processes and underpinning brain functioning. Moreover, brain networks are intrinsically multilayer since their attributes can vary across time, subjects, frequency, or other domains. Identifying the modular structure in multilayer brain networks represents a gateway toward a deeper understanding of neural processes underlying cognition. Electroencephalographic (EEG) signals, thanks to their high temporal resolution, can give rise to multilayer networks able to follow the dynamics of brain activity. Despite this potential, the community organization has not yet been thoroughly investigated in brain networks estimated from EEG. Furthermore, at the state of the art, there is still no agreement about which algorithm is the most suitable to detect communities in multilayer brain networks, and a way to test and compare them all under a variety of conditions is lacking. In this work, we perform a comprehensive analysis of three algorithms at the state of the art for multilayer community detection (namely, genLouvain, DynMoga, and FacetNet) as compared with an approach based on the application of a single-layer clustering algorithm to each slice of the multilayer network. We test their ability to identify both steady and dynamic modular structures. We statistically evaluate their performances by means of ad hoc benchmark graphs characterized by properties covering a broad range of conditions in terms of graph density, number of clusters, noise level, and number of layers. The results of this simulation study aim to provide guidelines about the choice of the more appropriate algorithm according to the different properties of the brain network under examination. Finally, as a proof of concept, we show an application of the algorithms to real functional brain networks derived from EEG signals collected at rest with closed and open eyes. The test on real data provided results in agreement with the conclusions of the simulation study and confirmed the feasibility of multilayer analysis of EEG-based brain networks in both steady and dynamic conditions.

Whenever a user browses the internet, the content he sends or receives takes the form a Protocol Data Unit as packets according to the OSI (Open Systems Interconnection) layers. These packets travel from the source to the destination through the path chosen by the routing protocols as OSPF (Open Shortest Path First) and BGP (Border Gateway Protocol). OSPF is used for interior routing within an AS (Autonomous System) and BGP is used for exterior routing between two external AS. Some customers are dual-homed where they have connections to two AS with one as the primary and the other one as secondary. Such diversed enormous traffic generated by the end users and the Internet Service Providers (ISP) have to be efficiently managed and monitored for the purpose of billing, security, QoS (Quality of Service) and SLA(Service Level Agreement) parameters. Hence the existing routing algorithms need to provide intelligent routing. The Simple Network Management Protocol (SNMP) generates the corresponding packets called SNMP traps. These specific packets are exchanged between the server and the appropriate interfaces of the routers when they are being polled. This polling technique generates a utilization graph which indicates the incoming and outgoing traffic at the core layer, distribution layer and access layer. The last mile traffic also has to be examined for checking the the bandwidth utilization. The traditional SNMP also has to incorporate the machine learning technique. This paper focuses on implementing intelligent network management in an Internet of Things environment.

Abstract Purpose Seaports are regarded as significant actors in global logistics and supply chains since a large part of the cargoes carried over the globe are being processed there. When the cold chain broken down during transport and storage in the ports, the humidity, nutrition, temperature and time conditions to be required for the growth of the bacteria occur, and rapid reproduction occurs and the properties of the products are rapidly deteriorating. It is imperative that especially medicines, some chemical substances and foodstuffs need to be transported without breaking the cold chain in the logistics. The monitoring and control of the temperature and humidity level is important in the time period between the loading of these containers in special areas in ports, the loading of freight in open areas, or the loading of freight on roads and railway carriages. For this reason, precise monitoring and control of the system is vital in the port logistics management. Method In this study, an IoT-enabled system is designed for Container Ports by developing software, interface and equipment that will enable remote monitoring of temperature, humidity and other necessary key status parameters. Findings The developed IoT-based system provides audible and visual warning, e-mail and SMS communication, similar to a monitoring screen such as a heart graph monitor, when the instant values of the refrigerated container are transmitted to the database, when the defined upper and lower values are approached. All these data and major change information are archived in the database and retrospective situation analysis and data analysis can be performed. Conclusion Using technologies such as Wireless Sensor Network (WSN) and RFID, an IoT-enabled Cold Chain Logistics system has been proposed that provides real-time monitoring of products in containers at ports, providing DS services to logistics providers and customers. In this context, it was explained how the ambient parameter values were collected in real time using WSN and IEEE 802.15.4, how the collected data was sent to the server via the GSM gateway. In the port scenario, activation devices such as IEEE 802.15.4 and RFID were modeled using the OPNET simulator. The developed model was carried out in accordance with the principles of EPCglobal Gen 2. With the proposed approach, smart solutions provide a smarter flow of information. The results show that IoT- enabled cold chain systems have a great potential for managing, monitoring, receiving and determining abnormal events related to temperature-sensitive products in real time.

In this paper, we present a methodology for quantifying the decentralization degree of a blockchain network. To accomplish this, we use two well-known graph models of Erdös-Rény and Barabási–Albert in order to study the blockchain network topology. We then quantify the decentralization degree using the clustering coefficient of our network models. We validate our approach through extensive simulations and analyze the decentralization degree with respect to network parameters such as the number of connections per node and the peer selection algorithm. Our results expose the trade-off between the average shortest path and the decentralization degree. Furthermore, we observe the impact of the average shortest path on the network speed and traffic overhead. Finally, we demonstrate that the presence of hub-like nodes such as relay gateways negatively impacts the decentralization degree of blockchain networks.

The World Register of Marine Species (WoRMS) is an authoritative classification and catalogue of marine names. The WoRMS portal and available web-services are a gateway to access a treasure-chest of information, not only on taxon names themselves, but also on their mutual relations (e.g., original names, accepted versus unaccepted names, taxonomic classification), and related information such as ecological traits, distributions and linked literature. Over its fifteen years of existence, WoRMS has not only been growing in content and quality, thanks to the voluntary efforts of more than 300 experts worldwide, it has also kept a technical trajectory that involves adapting to new standards and technologies. Although WoRMS has always been relatively easily accessible through its portal and web services, and applied the basic data-sharing principles of FAIR (Findable, Accessible, Interoperable, and Reusable), there is still room for improvement. The recently growing call for globally uniform identifiers coming from the application of the FAIR data sharing principles, and the growing investment into globally open and interlinked "digital twin" representations of our oceans and the organisms found in them, have introduced the fundamentals for growing a marine knowledge graph, and as a consequence, has directed some technical attention towards applying semantic web technologies. WoRMS plays a key role in the field of (marine) biodiversity, as this research field strongly relies on the correct usage of species names, and understanding the taxonomic relationships between taxon names. As WoRMS is regarded as the authoritative resource for marine names, it is also heavily used as a quality-control tool for the correct usage of taxon names within various European and global initiatives. WoRMS provides support to global databases and infrastructures that use (or are in need of) a marine taxonomic backbone, such as the LifeWatch Species Information Backbone, the Ocean Biodiversity Information System (OBIS) and the Global Ocean Observing System (GOOS), as well as improves the content and strengthens relationships with environment-independent initiatives and infrastructures such as the Catalogue of Life (COL), the Barcode of Life Data System (BoLD) & GenBank. In addition to the taxonomic value of WoRMS, it is also highly valued for its available information on species traits, which form a critical component in ecological marine research. In its role as a marine taxonomic backbone, along with being linked to numerous other environment-independent initiatives and infrastructures, WoRMS has always required an adaptability towards the challenging new ways specific applications and concrete research have been choosing to apply the identifiers affixed by WoRMS. It is in this tradition we now announce and describe our approach to publish the content of the register as fully linked open data, using semantic web technologies. We describe in some detail the choices made to select and apply specific vocabularies that already exist for the description and interconnected linking of taxon names, to address the tension between hanging on to an historic (URN) persistent identifier and providing a dereferenceable URI that supports the appreciated "follow your nose" property, to link to other relevant registries, to design meaningful predicates for inbound links to the register and, more technically to divide the available content into meaningful sub-sections for retrieval of optional detail, and to provide a roadmap for meaningful fragmentations of the full register to allow for an effective consumption of the relevant (e.g., newly updated) parts into specific data-consumption scenarios. to select and apply specific vocabularies that already exist for the description and interconnected linking of taxon names, to address the tension between hanging on to an historic (URN) persistent identifier and providing a dereferenceable URI that supports the appreciated "follow your nose" property, to link to other relevant registries, to design meaningful predicates for inbound links to the register and, more technically to divide the available content into meaningful sub-sections for retrieval of optional detail, and to provide a roadmap for meaningful fragmentations of the full register to allow for an effective consumption of the relevant (e.g., newly updated) parts into specific data-consumption scenarios. We believe this work to be an important step towards achieving some future goals. It should further facilitate the production of automated, managed or hybrid crosswalks between various taxonomic registers and classifications. To be especially considered here, is helping to make omics taxonomic references more meaningfully comparable with WoRMS. In the process of others linking their digital objects (e.g., services, datasets, publications, experts) to taxon IDs in WoRMS, they are effectively also linking to each other, which opens the doors between apparently unconnected bodies. Its continuing use as a global standard and trustworthy reference of community-accepted names for biological taxa becomes the essential glue connecting all sorts of services, initiatives, communities.

Purpose In a hospital, to provide quality healthcare to a patient, it should be imperative in maintaining an optimal environment. Another important factor is also monitoring the temperature of cold storage equipment such as refrigerators and freezers, as these are crucial in maintaining a constant temperature for medicines, vaccines, blood banks, tissue samples, surgical equipment, etc and if any of these are affected by the change in temperature, it would also lead to a negative impact on the patient’s healthcare. For this purpose, we are going to monitor the environmental conditions such as temperature and humidity of key areas in the hospital as well as cold storage equipment and analyse the number of times an alarm has been raised if the room temperature, as well as cold storage equipment, has not been maintained within a specific range. Methods The methodology involves the installation of the devices in key areas within the healthcare facility for environmental monitoring. The gateway is used to communicate real-time data to an IoT Platform called Ubidots. API keys are used for integrating another platform called Zoho Creator into an IoT platform, which also allows for viewing the real-time environmental data in KPIs and dashboards via Analytics. Results and Discussion The data collected was displayed in reports and analysed with the help of pictorial representations such as graphs and dashboards. Zoho Analytics, another platform under Zoho, allows us to visualize the data and understand the environmental effects of temperature & humidity. Conclusion From this paper, we can see that as the temperature and humidity have been detected to be out of range for a certain time interval, alarms are activated and a telegram message is delivered to the individual in charge of maintaining the appropriate temperature, to address the critical issue as soon as possible. Hence this highlights the importance of environmental monitoring, even more so strengthening the purpose that incorporating IoT technologies in healthcare systems will not only benefit but also revolutionise the methods of addressing other issues related to healthcare in real-time.

This article reflects on part of a three-year battle over the redevelopment of an iconic Melbourne music venue, the Palace-Metro Nightclub (the Palace), involving the tactical use of Facebook Page data at trial. We were invited by the Save the Palace group, Melbourne City Council and the National Trust of Australia to provide Facebook Page data analysis as evidence of the social value of the venue at an appeals trial heard at the Victorian Civil Administration Tribunal (VCAT) in 2016. We take a reflexive ethnographic approach here to explore the data production, collection and analysis processes as these represent and constitute a “data public”.Although the developers won the appeal and were able to re-develop the site, the court accepted the validity of social media data as evidence of the building’s social value (Jinshan Investment Group Pty Ltd v Melbourne CC [2016] VCAT 626, 117; see also Victorian Planning Reports). Through the case, we elaborate on the concept of data publics by considering the “affordising” (Pollock) processes at play when extracting, analysing and visualising social media data. Affordising refers to the designed, deliberate and incidental effects of datafication and highlights the need to attend to the capacities for data collection and processing as they produce particular analytical outcomes. These processes foreground the compositional character of data publics, and the unevenness of data literacies (McCosker “Data Literacies”; Gray et al.) as a factor of the interpersonal and institutional capacity to read and mobilise data for social outcomes.We begin by reconsidering the often-assumed connection between social media data and their publics. Taking onboard theoretical accounts of publics as problem-oriented (Dewey) and dynamically constituted (Kelty), we conceptualise data publics through the key elements of a) consequentiality, b) sufficient connection over time, c) affective or emotional qualities of connection and interaction with the events. We note that while social data analytics may be a powerful tool for public protest, it equally affords use against public interests and introduces risks in relation to a lack of transparency, access or adequate data literacy.Urban Protest and Data Publics There are many examples globally of the use of social media to engage publics in battles over urban development or similar issues (e.g. Fredericks and Foth). Some have asked how social media might be better used by neighborhood organisations to mobilise protest and save historic buildings, cultural landmarks or urban sites (Johnson and Halegoua). And we can only note here the wealth of research literature on social movements, protest and social media. To emphasise Gerbaudo’s point, drawing on Mattoni, we “need to account for how exactly the use of these media reshapes the ‘repertoire of communication’ of contemporary movements and affects the experience of participants” (2). For us, this also means better understanding the role that social data plays in both aiding and reshaping urban protest or arming third sector groups with evidence useful in social institutions such as the courts.New modes of digital engagement enable forms of distributed digital citizenship, which Meikle sees as the creative political relationships that form through exercising rights and responsibilities. Associated with these practices is the transition from sanctioned, simple discursive forms of social protest in petitions, to new indicators of social engagement in more nuanced social media data and the more interactive forms of online petition platforms like change.org or GetUp (Halpin et al.). These technical forms code publics in specific ways that have implications for contemporary protest action. That is, they provide the operational systems and instructions that shape social actions and relationships for protest purposes (McCosker and Milne).All protest and social movements are underwritten by explicit or implicit concepts of participatory publics as these are shaped, enhanced, or threatened by communication technologies. But participatory protest publics are uneven, and as Kelty asks: “What about all the people who are neither protesters nor Twitter users? In the broadest possible sense this ‘General Public’ cannot be said to exist as an actual entity, but only as a kind of virtual entity” (27). Kelty is pointing to the porous boundary between a general public and an organised public, or formal enterprise, as a reminder that we cannot take for granted representations of a public, or the public as a given, in relation to Like or follower data for instance.If carefully gauged, the concept of data publics can be useful. To start with, the notions of publics and publicness are notoriously slippery. Baym and boyd explore the differences between these two terms, and the way social media reconfigures what “public” is. Does a Comment or a Like on a Facebook Page connect an individual sufficiently to an issues-public? As far back as the 1930s, John Dewey was seeking a pragmatic approach to similar questions regarding human association and the pluralistic space of “the public”. For Dewey, “the machine age has so enormously expanded, multiplied, intensified and complicated the scope of the indirect consequences [of human association] that the resultant public cannot identify itself” (157). To what extent, then, can we use data to constitute a public in relation to social protest in the age of data analytics?There are numerous well formulated approaches to studying publics in relation to social media and social networks. Social network analysis (SNA) determines publics, or communities, through links, ties and clustering, by measuring and mapping those connections and to an extent assuming that they constitute some form of sociality. Networked publics (Ito, 6) are understood as an outcome of social media platforms and practices in the use of new digital media authoring and distribution tools or platforms and the particular actions, relationships or modes of communication they afford, to use James Gibson’s sense of that term. “Publics can be reactors, (re)makers and (re)distributors, engaging in shared culture and knowledge through discourse and social exchange as well as through acts of media reception” (Ito 6). Hashtags, for example, facilitate connectivity and visibility and aid in the formation and “coordination of ad hoc issue publics” (Bruns and Burgess 3). Gray et al., following Ruppert, argue that “data publics are constituted by dynamic, heterogeneous arrangements of actors mobilised around data infrastructures, sometimes figuring as part of them, sometimes emerging as their effect”. The individuals of data publics are neither subjugated by the logics and metrics of digital platforms and data structures, nor simply sovereign agents empowered by the expressive potential of aggregated data (Gray et al.).Data publics are more than just aggregates of individual data points or connections. They are inherently unstable, dynamic (despite static analysis and visualisations), or vibrant, and ephemeral. We emphasise three key elements of active data publics. First, to be more than an aggregate of individual items, a data public needs to be consequential (in Dewey’s sense of issues or problem-oriented). Second, sufficient connection is visible over time. Third, affective or emotional activity is apparent in relation to events that lend coherence to the public and its prevailing sentiment. To these, we add critical attention to the affordising processes – or the deliberate and incidental effects of datafication and analysis, in the capacities for data collection and processing in order to produce particular analytical outcomes, and the data literacies these require. We return to the latter after elaborating on the Save the Palace case.Visualising Publics: Highlighting Engagement and IntensityThe Palace theatre was built in 1912 and served as a venue for theatre, cinema, live performance, musical acts and as a nightclub. In 2014 the Heritage Council decided not to include the Palace on Victoria’s heritage register and hence opened the door for developers, but Melbourne City Council and the National Trust of Australia opposed the redevelopment on the grounds of the building’s social significance as a music venue. Similarly, the Save the Palace group saw the proposed redevelopment as affecting the capacity of Melbourne CBD to host medium size live performances, and therefore impacting deeply on the social fabric of the local music scene. The Save the Palace group, chaired by Rebecca Leslie and Michael Raymond, maintained a 36,000+ strong Facebook Page and mobilised local members through regular public street protests, and participated in court proceedings in 2015 and February 2016 with Melbourne City Council and National Trust Australia. Joining the protesters in the lead up to the 2016 appeals trial, we aimed to use social media engagement data to measure, analyse and present evidence of the extent and intensity of a sustained protest public. The evidence we submitted had to satisfy VCAT’s need to establish the social value of the building and the significance of its redevelopment, and to explain: a) how social media works; b) the meaning of the number of Facebook Likes on the Save The Palace Page and the timing of those Likes, highlighting how the reach and Likes pick up at significant events; and c) whether or not a representative sample of Comments are supportive of the group and the Palace Theatre (McCosker “Statement”). As noted in the case (Jinshan, 117), where courts have traditionally relied on one simple measure for contemporary social value – the petition – our aim was to make use of the richer measures available through social media data, to better represent sustained engagement with the issues over time.Visualising a protest public in this way raises two significant problems for a workable concept of data publics. The first involves the “affordising” (Pollock) work of both the platform and our data analysis. This concerns the role played by data access and platform affordances for data capture, along with methodological choices made to best realise or draw out the affordances of the data for our purposes. The second concerns the issue of digital and data literacies in both the social acts that help to constitute a data public in the first place, and the capacity to read and write public data to represent those activities meaningfully. That is, Facebook and our analysis constitutes a data public in certain ways that includes potentially opaque decisions or processes. And citizens (protesters or casual Facebook commenters alike) along with social institutions (like the courts) have certain uneven capacity to effectively produce or read public protest-oriented data. The risk here, which we return to in the final section, lies in the potential for misrepresentation of publics through data, exclusions of access and ownership of data, and the uneven digital literacies at each stage of data production, analysis and sensemaking.Facebook captures data about individuals in intricate detail. Its data capture strategies are geared toward targeting for the purposes of marketing, although only a small subset of the data is publicly available through the Facebook Application Programming Interface (API), which is a kind of data “gateway”. The visible page data tells only part of the story. The total Page Likes in February 2016 was 36,828, representing a sizeable number of followers, mainly located in Melbourne but including 45 countries in total and 38 different languages. We extracted a data set of 268,211 engagements with the Page between February 2013 and August 2015. This included 45,393 post Likes and 9,139 Comments. Our strategy was to demarcate a structurally defined “community” (in the SNA sense of that term as delineating clusters of people, activities and links within a broader network), by visualising the interactions of Facebook users with Posts over time, and then examine elements of intensity of engagement. In other words, we “affordised” the network data using SNA techniques to most clearly convey the social value of the networked public.We used a combination of API access and Facebook’s native Insights data and analytics to extract use-data from that Page between June 2013 and December 2015. Analysis of a two-mode or bipartite network consisting of users and Posts was compiled using vosonSML, a package in the R programming language created at Australian National University (Graham and Ackland) and visualised with Gephi software. In this network, the nodes (or vertices) represent Facebook users and Facebook Posts submitted on the Page, and ties (or edges) between nodes represent whether a user has commented on and/or liked a post. For example, a user U might have liked Post A and commented on Post B. Additionally, a weight value is assigned for the Comments ties, indicating how many times a user commented on a particular post (note that users can only like Posts once). We took these actions as demonstrating sufficient connection over time in relation to an issue of common concern.Figure 1: Network visualisation of activity on the Save the Palace Facebook Page, June 2013 to December 2015. The colour of the nodes denotes which ‘community’ cluster they belong to (computed via the Infomap algorithm) and nodes are sized by out-degree (number of Likes/Comments made by users to Posts). The graph layout is computed via the Force Atlas 2 algorithm.Community detection was performed on the network using the Infomap algorithm (Rosvall and Bergstrom), which is suited to large-scale weighted and directed networks (Henman et al.). This analysis reveals two large and two smaller clusters or groups represented by colour differences (Fig. 1). Broadly, this suggests the presence of several clusters amongst a sustained network engaging with the page over the three years. Beyond this, a range of other colours denoting smaller clusters indicates a diversity of activity and actors co-participating in the network as part of a broader community.The positioning of nodes within the network is not random – the visualisation is generated by the Force Atlas 2 algorithm (Jacomy et al.) that spatially sorts the nodes through processes of attraction and repulsion according to the observed patterns of connectivity. As we would expect, the two-dimensional spatial arrangement of nodes conforms to the community clustering, helping us to visualise the network in the form of a networked public, and build a narrative interpretation of “what is going on” in this online social space.Social value for VCAT was loosely defined as a sense of connection, sentiment and attachment to the venue. While we could illustrate the extent of the active connections of those engaging with the Page, the network map does not in itself reveal much about the sentiment, or the emotional attachment to the Save the Palace cause. This kind of affect can be understood as “the energy that drives, neutralizes, or entraps networked publics” (Papacharissi 7), and its measure presents a particular challenge, but also interest, for understanding a data public. It is often measured through sentiment analysis of content, but we targeted reach and engagement events – particular moments that indicated intense interaction with the Page and associated events.Figure 2: Save the Palace Facebook Page: Organic post reach November—December 2014The affective connection and orientation could be demonstrated through two dimensions of post “reach”: average reach across the lifespan of the Page, and specific “reach-events”. Average reach illustrates the sustained engagement with the Page over time. Average un-paid reach for Posts with links (primarily news and legal updates), was 12,015 or 33% of the total follower base – a figure well above the standard for Community Page reach at that time. Reach-events indicated particular points of intensity and illustrates the Page’s ability to resonate publicly. Figure 2 points to one such event in November 2015, when news circulated that the developers were defying stop-work orders and demolishing parts of The Palace. The 100k reach indicated intense and widespread activity – Likes, Shares, Comments – in a short timeframe. We examined Comment activity in relation to specific reach events to qualify this reach event and illustrate the sense of outrage directed toward the developers, and expressions of solidarity toward those attempting to stop the redevelopment. Affordising Data Publics and the Transformative Work of AnalyticsEach stage of deriving evidence of social value through Page data, from building public visibility and online activity to analysis and presentation at VCAT, was affected by the affordising work of the protesters involved (particularly the Page Admins), civil society groups, platform features and data structures and our choices in analysis and presentation. The notion of affordising is useful here because, as Pollock defines the term, it draws attention to the transformative work of metrics, analytics, platform features and other devices that re-package social activity through modes of datafication and analysis. The Save the Palace group mobilised in a particular way so as to channel their activities, make them visible and archival, to capture the resonant effects of their public protest through a platform that would best make that public visible to itself. The growth of the interest in the Facebook Page feeds back on itself reflexively as more people encounter it and participate. Contrary to critiques of “clicktivism”, these acts combine digital-material events and activities that were to become consequential for the public protest – such as the engagement activities around the November 2015 event described in Figure 2.In addition, presenting the research in court introduced particular hurdles, in finding “the meaningful data” appropriate to the needs of the case, “visualizing social data for social purposes”, and the need to be “evocative as well as accurate” (Donath, 16). The visualisation and presentation of the data needed to afford a valid and meaningful expression of the social significance the Palace. Which layout algorithm to use? What scale do we want to use? Which community detection algorithm and colour scheme for nodes? These choices involve challenges regarding legibility of visualisations of public data (McCosker and Wilken; Kennedy et al.).The transformative actions at play in these tactics of public data analysis can inform other instances of data-driven protest or social participation, but also leave room for misuse. The interests of developers, for example, could equally be served by monitoring protesters’ actions through the same data, or by targeting disagreement or ambiguity in the data. Similarly, moves by Facebook to restrict access to Page data will disproportionately affect those without the means to pay for access. These tactics call for further work in ethical principles of open data, standardisation and data literacies for the courts and those who would benefit from use of their own public data in this way.ConclusionsWe have argued through the case of the Save the Palace protest that in order to make use of public social media data to define a data public, multiple levels of data literacy, access and affordising are required. Rather than assuming that public data simply constitutes a data public, we have emphasised: a) the consequentiality of the movement; b) sufficient connection over time; and c) affective or emotional qualities of connection and interaction with public events. This includes the activities of the core members of the Save the Palace protest group, and the tens of thousands who engaged in some way with the Page. It also involves Facebook’s data affordances as these allow for the extraction of public data, alongside our choices in analysis and visualisation, and the court’s capacity and openness to accept all of this as indicative of the social value (connections, sentiment, attachment) it sought for the case. The Senior Member and Member presiding over the case had little knowledge of Facebook or other social media platforms, did not use them, and hence themselves had limited capacity to recognise the social and cultural nuances of activities that took place through the Facebook Page. This does not exclude the use of the data but made it more difficult to present a picture of the relevance and consequence of the data for understanding the social value evident in the contested building. While the court’s acceptance of the analysis as evidence is a significant starting point, further work is required to ensure openness, standardisation and ethical treatment of public data within public institutions like the courts. ReferencesBruns, A., and J. Burgess. “The Use of Twitter Hashtags in the Formation of Ad Hoc Publics.” 6th European Consortium for Political Research General Conference, University of Iceland, Reykjavík, 25-27 August 2011. 1 Aug. 2018 <http://eprints.qut.edu.au/46515/>.Baym, N.K., and d. boyd. “Socially Mediated Publicness: An Introduction.” Journal of Broadcasting & Electronic Media 56.3 (2012): 320-329.Dewey, J. The Public and Its Problems: An Essay in Political Inquiry. Athens, Ohio: Swallow P, 2016 [1927].Donath, J. The Social Machine: Designs for Living Online. Cambridge: MIT P, 2014.Fredericks, J., and M. Foth. “Augmenting Public Participation: Enhancing Planning Outcomes through the Use of Social Media and Web 2.0.” Australian Planner 50.3 (2013): 244-256.Gerbaudo, P. Tweets and the Streets: Social Media and Contemporary Activism. New York: Pluto P, 2012.Gibson, J.J. The Ecological Approach to Visual Perception. Boston: Houghton Mifflin Harcourt, 1979.Graham, T., and R. Ackland. “SocialMediaLab: Tools for Collecting Social Media Data and Generating Networks for Analysis.” CRAN (The Comprehensive R Archive Network). 2018. 1 Aug. 2018 <https://cran.r- project.org/web/packages/SocialMediaLab/SocialMediaLab.pdf>.Gray J., C. Gerlitz, and L. Bounegru. “Data Infrastructure Literacy.” Big Data & Society 5.2 (2018). 1 Aug. 2018 <https://doi.org/10.1177/2053951718786316>.Halpin, T., A. Vromen, M. Vaughan, and M. Raissi. “Online Petitioning and Politics: The Development of Change.org in Australia.” Australian Journal of Political Science (2018). 1 Aug. 2018 <https://doi.org/10.1080/10361146.2018.1499010>.Henman, P., R. Ackland, and T. Graham. “Community Structure in e-Government Hyperlink Networks.” Proceedings of the 14th European Conference on e-Government (ECEG ’14), 12-13 June 2014, Brasov, Romania.Ito, M. “Introduction.” Networked Publics. Ed. K. Varnelis. Cambridge, MA.: MIT P, 2008. 1-14.Jacomy M., T. Venturini, S. Heymann, and M. Bastian. “ForceAtlas2, a Continuous Graph Layout Algorithm for Handy Network Visualization Designed for the Gephi Software.” PLoS ONE 9.6 (2014): e98679. 1 Aug. 2018 <https://doi.org/10.1371/journal.pone.0098679>.Jinshan Investment Group Pty Ltd v Melbourne CC [2016] VCAT 626, 117. 2016. 1 Aug. 2018 <https://bit.ly/2JGRnde>.Johnson, B., and G. Halegoua. “Can Social Media Save a Neighbourhood Organization?” Planning, Practice & Research 30.3 (2015): 248-269.Kennedy, H., R.L. Hill, G. Aiello, and W. Allen. “The Work That Visualisation Conventions Do.” Information, Communication & Society, 19.6 (2016): 715-735.Mattoni, A. Media Practices and Protest Politics: How Precarious Workers Mobilise. Burlington, VT: Ashgate, 2012.McCosker, A. “Data Literacies for the Postdemographic Social Media Self.” First Monday 22.10 (2017). 1 Aug. 2018 <http://firstmonday.org/ojs/index.php/fm/article/view/7307/6550>.McCosker, A. “Statement of Evidence: Palace Theatre Facebook Page Analysis.” Submitted to the Victorian Civil Administration Tribunal, 7 Dec. 2015. 1 Aug. 2018 <https://www.academia.edu/37130238/Evidence_Statement_Save_the_Palace_Facebook_Page_Analysis_VCAT_2015_>.McCosker, A., and M. Esther. "Coding Labour." Cultural Studies Review 20.1 (2014): 4-29.McCosker, A., and R. Wilken. “Rethinking ‘Big Data’ as Visual Knowledge: The Sublime and the Diagrammatic in Data Visualisation.” Visual Studies 29.2 (2014): 155-164.Meikle, G. Social Media: Communication, Sharing and Visibility. New York: Routledge, 2016.Papacharissi, Z. Affective Publics: Sentiment, Technology, and Politics. Oxford: Oxford UP, 2015.Pollock, N. “Ranking Devices: The Socio-Materiality of Ratings.” Materiality and Organizing: Social Interaction in a Technological World. Eds. P.M. Leonardi, Bonnie A. Nardi, and J. Kallinikos. Oxford: Oxford UP, 2012. 91-114.Rosvall, M., and C.T. Bergstrom. “Maps of Random Walks on Complex Networks Reveal Community Structure.” Proceedings of the National Academy of Sciences of the United States of America 105.4 (2008): 1118-1123.Ruppert E. “Doing the Transparent State: Open Government Data as Performance Indicators.” A World of Indicators: The Making of Governmental Knowledge through Quantification. Eds. R. Rottenburg S.E. Merry, S.J. Park, et al. Cambridge: Cambridge UP, 2015. 1–18.Smith, N., and T. Graham. “Mapping the Anti-Vaccination Movement on Facebook.” Information, Communication & Society (2017). 1 Aug. 2018 <https://doi.org/10.1080/1369118X.2017.1418406>.Victorian Planning Reports. “Editorial Comment.” VCAT 3.16 (2016). 1 Aug. 2018 <https://www.vprs.com.au/394-past-editorials/vcat/1595-vcat-volume-3-no-16>.