Event-based Approach Research Articles

An Event-based Approach to Fragments as TP Ellipsis

An Event-based Approach to Fragments as TP Ellipsis

A disaggregated, probabilistic, high resolution method for assessment of domestic occupancy and electrical demand

An integrated domestic occupancy and demand model with a 1-min resolution has been developed which better captures the influence of different occupant behaviours than previous models. The occupancy model includes the fundamental link between occupancy and demand, and differentiates between different types and sizes of households. In particular, the likelihood of daytime occupancy is captured by age and employment differentiators. A novel method for identifying appliance use events and linking use to an occupancy profile has been developed that accounts for household specific appliance usage using an event-based approach calibrated directly from measured data. The method has been shown to perform better than both per-timestep probability models and models calibrated from time-use survey activity diaries. To further capture individual household behaviours, the demand model incorporates additional factoring to account for income and random behavioural influences. Whilst improving differentiation of individual household energy usage, due to limitations in the available data, the model incorporates some occupancy and use behaviour factors that are a composite of multiple households, leading to some behaviour averaging in the model output; consequently the model is best employed for energy demand assessment of multiple households.

A unified event-based control approach for FOPTD and IPTD processes based on the filtered Smith predictor

A new unified design of an event-based PID control architecture for self-regulating and integral processes is investigated in this work. The design is based on the symmetrical-send-on-delta (SSOD) sampling technique and on the filtered Smith predictor (FSP). In particular, the conditions to achieve robust stability to limit cycles are studied from the point of view of the filter parameters through the describing functions theory. In this context, a simple frequency domain-based tuning methodology to address the cases of first-order-plus-dead-time and integrator-plus-dead-time processes is proposed. With this method, the properties of the filter parameters are also explored to cope with the set-point tracking and the load disturbance rejection tasks. The effectiveness of the general approach is evaluated by simulations and experimental tests.

Co-occurrence of early forms of vocal and motor actions in infants

The present study examined the co-occurrence of vocal and motor actions, in order to understand the nature of this link in typically developing infants using an event-based approach. Participants included nine infants who were longitudinally studied for 10 months, between 3 and 12 months of age. The infants were observed for four types of vocal behaviours (vegetative, vocalic, syllabic and verbal) and seven types of motor actions (hand, face, leg, head, torso, whole body and gaze) across three developmental time frames (3–5 months, 6–8 months & 9–12 months), and a measure of rate of co-occurrence was calculated. Results indicated that co-occurrence of vocal and motor actions was present from the young age of 3 months, with a possible change in the relationship as they grew older.

GLODERS-S: a simulator for agent-based models of criminal organisations

Computer simulation has recently been recognised by criminologists as a useful tool for bridging the gap between theoretical and empirical analyses of organised crime and for supplementing their weaknesses. GLODERS-S is an innovative and configurable agent-based simulator specialised in reproducing the dynamics of a specific type of criminal organisations: protection racketeering groups. The simulator adopts an event-based approach that provides a more realistic operation of the agents, which integrated with its configurability provides policy-makers with a highly flexible platform for analysing multiple scenarios and assessing policies to counter organised crime. In this paper, we describe the principles of the simulator design, its features and limitations, and possible applications.

Evaluation of event-based irrigation system control scheme for tomato crops in greenhouses

This work presents a study and evaluation of an event-based predictive control system for a greenhouse irrigation process. The control system objective is to maintain the desired substrate humidity level, keeping the water usage as low as possible. The event-based control scheme uses a crop transpiration model to determine the volume of water required to compensate for the irrigation system and a water content model to trigger the irrigation system events. First, simulation experiments were performed to analyze the behavior of the designed system and to study the water supply dynamics to the substrate and subsequent drainage and evaporation. Secondly, the proposed event-based controller was evaluated in an experimental greenhouse, located in southeast of Spain, in real operation conditions. The resulting control system is able to adapt the actuation rate to the state of the plant providing the efficient way of water consumption. The obtained results show that the application of proposed event-based approach for the greenhouse irrigation system allows to improve the control performance and to reduce the water usage (about 20% of required water for the same performance obtained for commonly used on/off) being an important issue in intensive agriculture. The improved control performance is obtained due to event-based approach and the inclusion of information about the plant dynamic response for water supply and transpiration effect.

Non-Intrusive Load Disaggregation Using Graph Signal Processing

With the large-scale roll-out of smart metering worldwide, there is a growing need to account for the individual contribution of appliances to the load demand. In this paper, we design a graph signal processing (GSP)-based approach for non-intrusive appliance load monitoring (NILM), i.e., disaggregation of total energy consumption down to individual appliances used. Leveraging piecewise smoothness of the power load signal, two GSP-based NILM approaches are proposed. The first approach, based on total graph variation minimization, searches for a smooth graph signal under known label constraints. The second approach uses the total graph variation minimizer as a starting point for further refinement via simulated annealing. The proposed GSP-based NILM approach aims to address the large training overhead and associated complexity of conventional graph-based methods through a novel event-based graph approach. Simulation results using two datasets of real house measurements demonstrate the competitive performance of the GSP-based approaches with respect to traditionally used hidden Markov model-based and decision tree-based approaches.

An Event-Based Resource Management Framework for Distributed Decision-Making in Decentralized Virtual Power Plants

The Smart Grid incorporates advanced information and communication technologies (ICTs) in power systems, and is characterized by high penetration of distributed energy resources (DERs). Whether it is the nation-wide power grid or a single residential building, the energy management involves different types of resources that often depend on and influence each other. The concept of virtual power plant (VPP) has been proposed to represent the aggregation of energy resources in the electricity market, and distributed decision-making (DDM) plays a vital role in VPP due to its complex nature. This paper proposes a framework for managing different resource types of relevance to energy management for decentralized VPP. The framework views VPP as a hierarchical structure and abstracts energy consumption/generation as contractual resources, i.e., contractual offerings to curtail load/supply energy, from third party VPP participants for DDM. The proposed resource models, event-based approach to decision making, multi-agent system and ontology implementation of the framework are presented in detail. The effectiveness of the proposed framework is then demonstrated through an application to a simulated campus VPP with real building energy data.

Computer Simulation of Einstein-Podolsky-Rosen-Bohm Experiments

We review an event-based simulation approach which reproduces the statistical distributions of quantum physics experiments by generating detection events one-by-one according to an unknown distribution and without solving a wave equation. Einstein-Podolsky-Rosen-Bohm laboratory experiments are used as an example to illustrate the applicability of this approach. It is shown that computer experiments that employ the same post-selection procedure as the one used in laboratory experiments produce data that is in excellent agreement with quantum theory.

A qualitative event-based approach to multiple fault diagnosis in continuous systems using structural model decomposition

Multiple fault diagnosis is a difficult problem for dynamic systems, and, as a result, most multiple fault diagnosis approaches are restricted to static systems, and most dynamic system diagnosis approaches make the single fault assumption. Within the framework of consistency-based diagnosis, the challenge is to generate conflicts from dynamic signals. For multiple faults, this becomes difficult due to the possibility of fault masking and different relative times of fault occurrence, resulting in many different ways that any given combination of faults can manifest in the observations. In order to address these challenges, we develop a novel multiple fault diagnosis framework for continuous dynamic systems. We construct a qualitative event-based framework, in which discrete qualitative symbols are generated from residual signals. Within this framework, we formulate an online diagnosis approach and establish definitions of multiple fault diagnosability. Residual generators are constructed based on structural model decomposition, which, as we demonstrate, has the effect of reducing the impact of fault masking by decoupling faults from residuals, thus improving diagnosability and fault isolation performance. Through simulation-based multiple fault diagnosis experiments, we demonstrate and validate the concepts developed here, using a multi-tank system as a case study.

Event-based S-transform approach for nonintrusive load monitoring

In this study, a nonintrusive load monitoring system is developed by analyzing the power signal obtained from a single point of power meter installation to detect ON/OFF load activities. A mathematically designed model with backpropagation neural network is utilized in load pattern recognition to decompose the load operation. Leveraging its unique load signature profile, the S-transform approach is employed to extract the features from the aggregate power signal and analyze the detection of load start-up transient from signal processing. To improve the accuracy of load identification for unknown data, the power factor is used as an additive feature with 99.32% load recognition accuracy.

A high dynamic range linear vision sensor with event asynchronous and frame-based synchronous operation

We present a novel High-Dynamic-Range (HDR) image sensor with linear output. Photogenerated charge is continuously every pixel without saturating. Each time the integrated at photodiode voltage reaches a programmable threshold, the pixel resets and starts over integrating charge again. With an eventbased approach, it is possible to count the number of times (if any) that a pixel has saturated during exposure. Pixel illumination is represented with a 20-bit word. The most significant 12b represent the number of times that a pixel has saturated during exposure. The least significant 8b are the result of an analog-todigital conversion in the end of exposure. Thus, pixels provide linear outputs proportional to light intensity. A dynamic range of 120dB is expected. The maximum dynamic range that can be measured is limited by the maximum event rate that the chip peripheral circuitry can handle and by the space dedicated on memory to store the event information. Pixel pitch is 25μm. A prototype sensor with 128 x 96 pixels has been implemented in the AMS 180nm CMOS-HV technology. In this article, the pixel operation will be explained. Preliminary experimental results and snapshots will be also provided.

Sociometric network structure and its association with methamphetamine use norms among homeless youth

Homeless youths' social networks are consistently linked with their substance use. Social networks influence behavior through several mechanisms, especially social norms. This study used sociometric analyses to understand whether social norms of drug use behaviors are clustered in network structures and whether these perceived norms (descriptive and injunctive) influence youths' drug use behaviors. An event-based approach was used to delineate boundaries of the two sociometric networks of homeless youth, one in Los Angeles, CA (n = 160) and the other in Santa Monica, CA (n = 130). Network characteristics included centrality (i.e., popularity) and cohesiveness (location in dense subnetworks). The primary outcome was recent methamphetamine use. Results revealed that both descriptive and injunctive norms influenced methamphetamine use. Network cohesion was found to be associated with perception of both descriptive and injunctive norms in both networks, however in opposite directions. Network interventions therefore might be effective if designed to capitalize on social influence that naturally occurs in cohesive parts of networks.

An Event-Based Approach to Design a Teamwork Training Scenario and Assessment Tool in Surgery

Simulation is a technique recommended for teaching and measuring teamwork, but few published methodologies are available on how best to design simulation for teamwork training in surgery and health care in general. The purpose of this article is to describe a general methodology, called event-based approach to training (EBAT), to guide the design of simulation for teamwork training and discuss its application to surgery. The EBAT methodology draws on the science of training by systematically introducing training exercise events that are linked to training requirements (i.e., competencies being trained and learning objectives) and performance assessment. The EBAT process involves: Of the 4 teamwork competencies endorsed by the Agency for Healthcare Research Quality and Department of Defense, "communication" was chosen to be the focus of our training efforts. A total of 5 learning objectives were defined based on 5 validated teamwork and communication techniques. Diagnostic laparoscopy was chosen as the clinical context to frame the training scenario, and 29 KSAs were defined based on review of published literature on patient safety and input from subject matter experts. Critical events included those that correspond to a specific phase in the normal flow of a surgical procedure as well as clinical events that may occur when performing the operation. Similar to the targeted KSAs, targeted responses to the critical events were developed based on existing literature and gathering input from content experts. Finally, a 29-item EBAT-derived checklist was created to assess communication performance. Like any instructional tool, simulation is only effective if it is designed and implemented appropriately. It is recognized that the effectiveness of simulation depends on whether (1) it is built upon a theoretical framework, (2) it uses preplanned structured exercises or events to allow learners the opportunity to exhibit the targeted KSAs, (3) it assesses performance, and (4) it provides formative and constructive feedback to bridge the gap between the learners' KSAs and the targeted KSAs. The EBAT methodology guides the design of simulation that incorporates these 4 features and, thus, enhances training effectiveness with simulation.

India, China, and the World: A Connected History by Tansen Sen

Reviewed by: India, China, and the World: A Connected History by Tansen Sen B. R. Deepak (bio) Tansen Sen. India, China, and the World: A Connected History. Lanham, MD: Rowman & Littlefield, 2017. xviii, 541 pp. Paperback $39.00, isbn 978-1-5381-1172-7. India, China, and the World: A Connected History by Tansen Sen, director of the Center for Global Asia and professor of history at New York University (NYU) Shanghai, is a critical and non-judgemental yet stimulating analysis of the relationship between India and China during the ancient, modern, and contemporary periods. It is thoroughly and scintillatingly argumentative, for in relying on the theoretical framework of circulatory connections between India and China and the world, he has challenged the nation-state's forced narratives of civilizational dialogue, geo-civilizational paradigm, and the more recent notion of Chindia, which according to him has diverted attention away from the contentious issues between the two on the one hand and made use of selective historical sources to glorify their past connections on the other. The book could be regarded as a sequel to his earlier works, especially Buddhism, Diplomacy, and Trade: The Realignment of Sino-Indian Relations, 600–1400 (2003) and further develops the line of argument on the basis of interpretations and conclusions drawn in this book. It was perhaps coincidence that the book was launched roughly at the time when India and China came dangerously close to another armed conflict during the Doklam faceoff that lasted for 73 days and further vindicated the author's narrative that beneath the selective interpretation of historical sources to build a civilizational state narrative of the relationship lies a dangerous nation-state nationalistic agenda. He takes a long-term view of the relationship rather than adopting a linear and event-based approach to interpret the circulation of ideas and objects and argues that the pre-twentieth century interactions between the two should not be construed within the framework of [End Page 300] modern nation-states. Methodologically based on a mass of primary Chinese and non-Chinese sources, archival documents across the world, as well as secondary sources, this is a fascinating ground-breaking study. The author's mastery in classical and modern Chinese gives him a unique advantage akin to adding wings to a tiger enabling him to put the circulation of ideas, peoples, and objects between India and China and beyond into a kaleidoscopic perspective, thus making it a compelling study. The book is well-structured into five chapters, each chapter divided into sections and sub sections, which is helpful as it provides the reader a guideline of events mostly within a chronological setting but with extremely diverse themes which the author has intelligently interwoven with his main argument and theoretical framework. The first two chapters and the first section of the third chapter essentially compliment and are built on his earlier research Buddhism, Diplomacy, and Trade, where he argues that the Buddhist connections were multi-directional and multi-locational circulatory interactions that resulted in the dissemination of geographical, philosophical, and technological knowledge not only between India and China but also across the Eurasian and African landmasses and the Indian Ocean world. The knowledge that was transferred got intermingled as it travelled from one node of connection to another, albeit there remained misperceptions regarding the geographical locations of various polities inside tianzhu (ancient Chinese name for India) or in South Asia and their connections with tianzhu as such in the minds of the Chinese (p. 71). Equally stimulating and refreshing is the construct of "The Imperial Connections" in chapter 3. Here again, he challenges the notion of Zheng He as a peace-loving imperial envoy; Sen argues that even though China did not launch large scale occupation of foreign territories, it did intervene in local disputes and exert influence over strategic maritime choke points as demonstrated by Zheng He's voyages in the Indian Ocean (pp. 206–207). Early discourses on India by Qing visitors such as Huang Maocai, Ma Jianzhong, Wu Guangpei, and Kang Youwei perhaps were instrumental in building the present mainstream Chinese perceptions about colonial India, all of whom except Huang portrayed India as a failed state and...

Event-based selective control strategy for raceway reactor: A simulation study

This work presents a simulation study of an event-based selective control strategy for a raceway reactor. The control system aims are to maintain simultaneously a pH and dissolved oxygen within specific limits. In the analyzed control scheme, the pH value is prioritized over the dissolved oxygen, since it has a critical influence on the process performance. Besides, the dissolved oxygen also influences the photosynthesis rate and should be kept within the limits. The control structure is evaluated through simulation, where a nonlinear model for microalgae culture in the raceway photobioreactor is used. Analysis of different configurations allows to determine the most adequate control system setup to achieve the desired goals. The obtained results show that combination of an event-based approach with selective control allows to increase the overall productivity as well as to address effective CO2 utilization and aeration system energy minimization.

Revisiting the Link Between Political and Financial Crises in Africa

There is an important information deficit on political and financial risks in Africa. This paper fills this gap by compiling a unique database of financial (sovereign, banking, currency, expropriation) and political crises (regime changes, ethnic and revolutionary wars, genocides, armed conflicts) covering 53 African countries between 1965 and 2008. We employ a new methodological framework to disentangle cross-crisis from temporal contagion effects. This allows us to extend to Africa a number of insights from the literature on financial crises (e.g., the mutual contagion effects between banking and currency meltdowns). Importantly, and critically for a study devoted to Africa, political upheavals are of modest relevance to predict financial crises. These results may be reconciled with previous literature given our original focus on Africa and our event-based approach of financial and political risks.

Event-Based Proof of the Mutual Exclusion Property of Peterson’s Algorithm

Summary Proving properties of distributed algorithms is still a highly challenging problem and various approaches that have been proposed to tackle it [1] can be roughly divided into state-based and event-based proofs. Informally speaking, state-based approaches define the behavior of a distributed algorithm as a set of sequences of memory states during its executions, while event-based approaches treat the behaviors by means of events which are produced by the executions of an algorithm. Of course, combined approaches are also possible. Analysis of the literature [1], [7], [12], [9], [13], [14], [15] shows that state-based approaches are more widely used than event-based approaches for proving properties of algorithms, and the difficulties in the event-based approach are often emphasized. We believe, however, that there is a certain naturalness and intuitive content in event-based proofs of correctness of distributed algorithms that makes this approach worthwhile. Besides, state-based proofs of correctness of distributed algorithms are usually applicable only to discrete-time models of distributed systems and cannot be easily adapted to the continuous time case which is important in the domain of cyber-physical systems. On the other hand, event-based proofs can be readily applied to continuous-time / hybrid models of distributed systems. In the paper [2] we presented a compositional approach to reasoning about behavior of distributed systems in terms of events. Compositionality here means (informally) that semantics and properties of a program is determined by semantics of processes and process communication mechanisms. We demonstrated the proposed approach on a proof of the mutual exclusion property of the Peterson’s algorithm [11]. We have also demonstrated an application of this approach for proving the mutual exclusion property in the setting of continuous-time models of cyber-physical systems in [8]. Using Mizar [3], in this paper we give a formal proof of the mutual exclusion property of the Peterson’s algorithm in Mizar on the basis of the event-based approach proposed in [2]. Firstly, we define an event-based model of a shared-memory distributed system as a multi-sorted algebraic structure in which sorts are events, processes, locations (i.e. addresses in the shared memory), traces (of the system). The operations of this structure include a binary precedence relation ⩽ on the set of events which turns it into a linear preorder (events are considered simultaneous, if e 1 ⩽ e 2 and e 2 ⩽ e 1), special predicates which check if an event occurs in a given process or trace, predicates which check if an event causes the system to read from or write to a given memory location, and a special partial function “val of” on events which gives the value associated with a memory read or write event (i.e. a value which is written or is read in this event) [2]. Then we define several natural consistency requirements (axioms) for this structure which must hold in every distributed system, e.g. each event occurs in some process, etc. (details are given in [2]). After this we formulate and prove the main theorem about the mutual exclusion property of the Peterson’s algorithm in an arbitrary consistent algebraic structure of events. Informally, the main theorem states that if a system consists of two processes, and in some trace there occur two events e 1 and e 2 in different processes and each of these events is preceded by a series of three special events (in the same process) guaranteed by execution of the Peterson’s algorithm (setting the flag of the current process, writing the identifier of the opposite process to the “turn” shared variable, and reading zero from the flag of the opposite process or reading the identifier of the current process from the “turn” variable), and moreover, if neither process writes to the flag of the opposite process or writes its own identifier to the “turn” variable, then either the events e 1 and e 2 coincide, or they are not simultaneous (mutual exclusion property).

Online 4-Dimensional Reconstruction of Time-Slices in the CBM Experiment

The main focus of the CBM experiment (FAIR, Darmstadt, Germany) is the measurement of very rare probes, which require interaction rates of up to 10 MHz. It makes it mandatory to perform the full online event reconstruction at the first level trigger and to operate with huge data rates of up to 1 TB/s. CBM will have a continuous beam without bunch structure, that means collisions may overlap in time, making the traditional event-based approach not applicable. It requires full online event reconstruction and selection to be done in 4D, including time. The standalone First Level Event Selection (FLES) package has been created for the CBM experiment. It contains all reconstruction stages: track finding, track fitting, short-lived particles finding and event selection. For track reconstruction the Cellular Automaton (CA) method is used, that allows to resolve tracks from a time-slice in event-corresponding groups. The algorithm is intrinsically local and the implementation is both vectorized within a core and parallelized between CPU cores. The CA track finder shows a strong scalability on many-core systems. The speed-up factor of 10.6 was achieved on a CPU with 10 physical cores using hyper-threading.

Incorporating seasonality into event-based joint probability methods for predicting flood frequency: A hybrid causative event approach

Summary Flood extremes are driven by highly variable and complex climatic and hydrological processes. Observational evidence has identified that seasonality of climate variables has a major impact on flood peaks. However, event-based joint probability approaches for predicting the flood frequency distribution (FFD), which are commonly used in practice, do not commonly incorporate climate seasonality. This study presents an advance in event-based joint probability approaches by incorporating seasonality using the hybrid causative events (HCE) approach. The HCE was chosen because it uses the true causative events of the floods of interest and is able to combine the accuracy of continuous simulation with the computational efficiency of event-based approaches. The incorporation of seasonality is evaluated using a virtual catchment approach at eight sites over a wide range of Australian climate zones, including tropical, temperature, Mediterranean and desert climates (virtual catchment data for the eight sites is freely available via digital repository). The seasonal HCE provided accurate predictions of the FFD at all sites. In contrast, the non-seasonal HCE significantly over-predicted the FFD at some sites. The need to include seasonality was influenced by the magnitude of the seasonal variation in soil moisture and its coherence with the seasonal variation in extreme rainfall. For sites with a low seasonal variation in soil moisture the non-seasonal HCE provided reliable estimates of the FFD. For the remaining sites, it was found difficult to predict a priori whether ignoring seasonality provided a reliable estimate of the FFD, hence it is recommended that the seasonal HCE always be used. The practical implications of this study are that the HCE approach with seasonality is an accurate and efficient event-based joint probability approach to derive the flood frequency distribution across a wide range of climatologies.