Deployment Plan Research Articles

Human–robot collaboration in the MTA SZTAKI learning factory facility at Győr

In recent years, interest has grown in environments where humans and robots collaborate, complementing the strengths and advantages of humans and machines. Design, construction and adjustment of such environments, as well as the training of operating personnel, requires thorough understanding of the nature of human–robot collaboration which previous automation expertise does not necessarily provide. The learning factory currently being constructed by MTA SZTAKI in Győr aims to provide hands-on experience in the design and operation of facilities supporting human–robot collaboration, mainly in assembly tasks. The work-in-progress paper presents design principles, functionalities and structure of the facility, and outlines deployment plans in education, training, research and development in the academic and industrial sectors.

A game theory approach for assessing risk value and deploying search-and-rescue resources after devastating tsunamis

The current early-warning system and tsunami protection measures tend to fall short because they always underestimate the level of destruction, and it is difficult to predict the level of damage by a devastating tsunami on uncertain targets. As we know, the key to minimizing the total number of fatalities after a disaster is the deployment of search and rescue efforts in the first few hours. However, the resources available to the affected districts for emergency response may be limited. This study proposes two game theoretic models that are designed for search-and-rescue resource allocation. First, the interactions between a compounded disaster and a response agent in the affected district are modelled as a non-cooperative game, after which the risk value is derived for each district from the Nash equilibrium. The risk value represents the threat, vulnerability, and consequence of a specific disaster for the affected district. Second, the risk values for fifteen districts are collected for calculation of each district's Shapley value. Then an acceptable plan for resource deployment among all districts is made based on their expected marginal contribution. The model is verified in a simulation based upon 2011 tsunami data. The experimental results show the proposed approach to be more efficient than the proportional division of rescue resources, for dealing with compounded disaster, and is feasible as a method for planning the mobilization of resources and to improve relief efforts against devastating tsunamis.

Research and application of intelligent intrusion detection system with accuracy analysis methodology

As perimeter intrusion detection is of great value to security defense, an innovative intelligent intrusion detection system is analyzed and applied. The system is systematically designed through network topology, consisting of Infrared Image Collection and Pre-processing Module, Data Transmission Module, Intelligent Analysis and Automatic Alarm Module. Infrared Imagery Pre-processing is achieved through innovatively application of FLIR Tau 2336 based on advanced wavelet algorithm, considerably minimizing noises and enhancing details. Besides, synergistic action of intelligent analysis and automatic alarm are achieved through intelligent comparison between extracted imagery and models of pedestrian and vehicle. Moreover, innovative deployment plan of thermal infrared cameras is applied to avoid blind zone of intrusion detection. Through mix deployment of clockwise and anti-clockwise cameras, full coverage of security perimeter is achieved through only 14 thermal cameras, which is of great economic advantage. Finally, accuracy analysis methodology is proposed and test results are obtained - Detection Rate for all test locations is 100%, and more than 90% of test locations are with high alarm accuracy (above 90%). Alarm Accuracy and Missed-Alarm Rates are dependent on the distance between test and cameras, and the best alarm distance is 175.72 m. The proposed intelligent intrusion detection system is applied and its results are acceptable, being of great efficiency and economic advantage.

Application of Policy Deployment and Daily Management in service sector

BackgroundPolicy Deployment and Daily Management are two critical vehicles of Total Quality Management implementation in a company. Integration of these two vehicles has been discussed and adequately addressed in a few companies that have been practicing Total Quality Management for a long time. However, most companies often face challenges and difficulties in ensuring smooth and seamless transfer of Policy Deployment plans into Daily Management activities.Case descriptionThe challenge is even bigger in service sector which embarked on the Total Quality Management journey barely 5–6 years ago. The service sector has traditionally used Balanced Scorecard which has relatively weaker emphasis on the means to achieve the targets. The authors of this report have found a customized and unique model whose success has been demonstrated through deployment in two customer-facing processes in a large life insurance company in India. The traditional approach used in manufacturing industry has been simplified and customized for the effective application in the service sector.Discussions & EvaluationThe traditional approach used in manufacturing industry has been simplified and customised for the effective application in the service sector. A survey was done to identify the issues and the approach was modified and implemented in couple of key customer-facing processes.ConclusionThe phenomenal results have led to a big ‘pull’ from other process owners to replicate this approach across all operational and support processes. Initial ‘reluctant participants’ of the process have now become the ‘champions’ and truly the ‘change catalysts’ for this approach. The process is now being replicated in several other processes across several Industrial sectors.

An ILP and simulation model to optimize search and rescue helicopter operations

Maritime search and rescue (SAR) operations, conducted for rendering aid to the victims in need of help at sea, play a crucial role in dropping the number of causalities. Therefore, it is of high importance to organize SAR operations properly. In this paper, we compose a hybrid methodology which combines optimization and simulation to allocate SAR helicopters. First, we build an integer linear programming (ILP) model to provide an effective deployment plan and use it as an input to a simulation model which includes constraints that the ILP model cannot tackle. Next, using a rule-based algorithm, we generate alternative solutions and seek better plans that exist in the vicinity of the ILP model solution. We perform our methodology on the historical incident data in the Aegean Sea region. Results show that the hybrid methodology we adopted leads to a more effective utilization of resources than the optimization model alone.

Hybrid modeling approach to market deployment planning: an application to a natural disaster relief supply business venture

In today’s fast-paced global economy, entrepreneurs increasingly tend to holistically design their business ventures during the early stages of business creation. This tendency highlights the need for an efficient and systematic approach to market deployment planning due to the dynamic and complex nature of current markets and the evolving significance of global strategic positioning. Traditional market expansion planning is no longer adequate for fast-paced contexts. This paper introduces a hybrid modelling approach in order to develop a market deployment roadmap. Based on market pertinent databases, the proposed approach uses self-organising maps for market clustering and an optimisation model for market deployment road mapping within each cluster. The approach is illustrated through its application to market deployment road mapping for a business venture specialising in natural disaster supply relief. Dealing with real case studies with exploiting the vast database have not received much attention in disaster relief planning context. Hence, this study provides a novel contribution to humanitarian relief planning considering the role of the business ventures in relief operation and their business model simultaneously.

Method of Wireless Sensor Network Node Deployment for the Emergency Environment

Incidents could not always be avoided, resulting in significant losses for the state property and people's safety. Effective monitoring of incidents is becoming more and more important. Wireless sensor networks (WSNs) are widely used in environmental monitoring. On the basis of the existing wireless sensor network node deployment model, a network node deployment model was proposed, which was used in the monitoring of unexpected accidents. The model area was divided into the core area and the evacuation area, and different monitoring nodes deployment plans were applied in different areas. The simulation experiment is carried out by MATLAB, and the simulation results of the node coverage are obtained. Results show that the model for the practical application of the node deployment provides an effective deployment plan, as well as offers a strong basis for real-time monitoring and post-accident emergency evacuation.

Communication-aware planning for robot teams deployment

In the present work we address the problem of deploying a team of robots in a scenario where some locations of interest must be reached. Thus, a planning for a deployment is required, before sending the robots. The obstacles, the limited communication range, and the need of communicating to a base station, constrain the connectivity of the team and the deployment planning. We propose a method consisting of three algorithms: a distributed path planner to obtain communication-aware trajectories; a deployment planner providing dual-use of the robots, visiting primary goals and performing connectivity tasks; and a clustering algorithm to allocate the tasks to robots, and obtain the best goal visit order for the mission.

Full-fold, multi-source acquisition through shot isolation technology and its implications on productivity gains

Shot isolation enabled full-fold, multi-source acquisition is achieved by applying the novel technology of signal apparition to the encoding and decoding of fully superimposed shot records from non-distance separated sources. The introduction of periodically varying shot-to-shot modulation functions for encoding injects energy at predetermined positions within distinct wavenumber ranges, which then enables a deterministic decoding of individual shots in data processing. We demonstrate the method for single vessel operations, first on a dual source configuration for seabed acquisition, extracted from the SEG Advanced Modeling Program (SEAM) Phase I dataset, and then extend the methodology to triple-sources through the use of an emulated marine real data example from the North Sea. With shot isolation enabled multi-source acquisition being successfully applied in a marine and seabed seismic context, scope for significant productivity gains is created. Compared to established acquisition techniques, gains arise from the ability to acquire full-fold data in a shorter time frame without compromising the subsurface bin size. For marine seismic acquisition, this also implies that the number of towed streamers can be reduced, giving leeway to additional strategic considerations on subjects such as capital expenditures and the optimization of vessel deployment plans.

Analysis on the present deployment of large medical equipments in China

Objective To analyze the overall deployment of Class-A large medical equipments in China. Methods Data of Class A large medical equipments deployed from 2007 to 2015 were collected and classified regionally, for the purpose of measuring the overall deployment, growth level and plan performance. Results There were 403 large medical equipments in China, a rapid rise of deployment, yet still far below developed countries in terms of per capita deployment.Regional differences were significant.With PET-CT as an example, the plan performance in the east(92.19%)was much higher than the west of China(68.57%); plan performance of Class-A equipments was better, conducive to regulating the increase and distribution. Conclusions The deployment level of Class-A equipments in China is low in general, and calls for better regulation regardless of the planning and management progress. Key words: Class-A large medical equipment; Deployment planning; Performance; Public medical institutions; Social medical institutions

PRODUCT QUALITY DEVELOPMENT ANALYSIS OF RICE BRAN CAKE BASED ON CONSUMERS’ EXPECTATION

This research analyzes consumer expectations for developing product quality of Rice Bran Cake. Quality Function Deployment (QFD) method is employed to ensure the product that entering the production phase will actually able to satisfy the consumer expectations. There are four phases in QFD method, namely; house of quality, parts deployment, process deployment, and production planning. The results coming from applying the four phases of QFD are: consumers require the quality development of Rice Bran Cake and considered price improvement, the addition of flavor, color, aroma, texture, shape, packaging, legality, durability, and net weight. Company’s response to meet the consumer demand towards Rice Bran Cake that produced in the first phase is the addition of flavors, qualified ingredients, making innovative shapes, price adjustment, the addition of weight and size, packaging design, and no chemical preservatives. In the second phase of part deployment, the priorities which should be improved are natural ingredients usage, procurement of qualified ingredients, the addition of halal label, interested flavor, adjustments with other attributes, and the larger cake pan. The quality development designs of Rice Bran Cake that is produced in accordance with the order of weight values of the highest process planning are supply of raw materials, supply of additional materials, the addition of the appropriate flavors, the addition of food coloring, and packaging. Furthermore, the matrix production planning obtained according to the results of importance weight are making various flavors, the supply of qualified ingredients, legality standardization, designing the forms of packaging, hygiene of tools and materials, and accuracy of production equipment.

Spatiotemporal Adaptive Optimization of a Static-Sensor Network via a Non-Parametric Estimation of Target Location Likelihood

The search for a mobile target is a dynamic spatial and temporal problem. Information gathered during the search, regarding the potential whereabouts of the target, can be used to influence significantly the search strategy employed. In this paper, thus, a novel (wireless) static-sensor network deployment strategy is presented to detect efficiently and effectively a mobile target in an unbounded environment. The proposed strategy deploys the static sensors optimally and in a time-phased manner while adapting in real-time to the availability of new information during the search. An optimal network-deployment plan, herein, refers to a set of optimal sensor-deployment times and locations. The optimal sensor-deployment instances aim to achieve a uniform deployment of search effort over time. Optimal sensor-deployment locations, in turn, are determined according to the highest possible likelihood of detection of the mobile target. The proposed deployment strategy contains two novel contributions: it makes use of a non-parametric approach to estimate effectively the target location likelihood, and it performs an optimization of sensor-placement times to maximize the adaptive characteristic of the deployment plan. Several detailed experiments (in virtual and physical environments) of the proposed strategy for static-sensor network deployment in wilderness search and rescue applications are presented. Furthermore, a comparative study is included to highlight the advantages of our approach versus traditional methods that deploy sensors simultaneously for uniform coverage.

Building Qatar severe respiratory failure ECMO program

Building Qatar severe respiratory failure ECMO program

A change management approach to improving safety and preventing needle stick injuries.

Key drivers for preventing healthcare-associated infection (HCAI) include evidence-based practices and procedures that prevent infection. Among the current guidance for preventing HCAIs is evidence and mandatory requirements for reducing needle stick injuries (NSIs). This article highlights how John Kotter's model for change could help healthcare workers plan for successful and sustained deployment of needle safety devices (NSDs) and ultimately reduce the risk of a NSI.

Improving the electrification rate of the vehicle miles traveled in Beijing: A data-driven approach

Electric vehicles (EV) are promoted as a foreseeable future vehicle technology to reduce dependence on fossil fuels and greenhouse gas emissions associated with conventional vehicles. This paper proposes a data-driven approach to improving the electrification rate of the vehicle miles traveled (VMT) by taxi fleet in Beijing. Specifically, based on the gathered real-time vehicle trajectory data of 46,765 taxis in Beijing, we conduct time-series simulations to derive insights for the public charging station deployment plan, including the locations of public charging stations, the number of chargers at each station and their types. The proposed simulation model defines the electric vehicle charging opportunity from the aspects of time window, charging demand and charger availability, and further incorporates the heterogeneous travel patterns of individual vehicles. Although this study only examines one type of fleet in a specific city, the methodological framework is readily applicable to other cities and types of fleet with similar dataset available, and the analysis results contribute to our understanding on electric vehicle’s charging behavior. Simulation results indicate that: (i) locating public charging stations to the clustered charging time windows is a superior strategy to increase the electrification rate of VMT; (ii) deploying 500 public stations (each includes 30 slow chargers) can electrify 170million VMT in Beijing in two months, if EV’s battery range is 80km and home charging is available; (iii) appropriately combining slow and fast chargers in public charging stations contributes to the electrification rate; (iv) breaking the charging stations into smaller ones and spatially distributing them will increase the electrification rate of VMT; (v) feeding the information of availability of chargers in charging stations to drivers can increase the electrification rate of VMT; (vi) the impact of stochasticity embedded in the trajectory data can be significantly mitigated by adopting the dataset covering a longer period.

Optimal design of autonomous vehicle zones in transportation networks

This paper advocates the need for infrastructure planning to adapt to and further promote the deployment of autonomous vehicle (AV) technology. It is envisioned that in the future government agencies will dedicate certain areas of road networks to AVs only to facilitate the formulation of vehicle platoons to improve throughput and hopefully improve the performance of the whole network. This paper aims to present a mathematical framework for the optimal design of AV zones in a general network. With the presence of AV zones, AVs may apply different routing principles outside of and within the AV zones. A novel network equilibrium model (we refer to it as the “mixed routing equilibrium model”) is thus firstly proposed to capture such mixed-routing behaviors. We then proceed to formulate a mixed-integer bi-level programming model to optimize the deployment plan of AV zones. Numerical examples are presented to demonstrate the performance of the proposed models.

A simulation approach to innovation deployment readiness assessment in manufacturing

Manufacturing companies need to continuously innovate in order to remain competitive. Fostering a successful innovative environment should reflect positively on manufacturing performance, with a premise that companies seek to attain appropriate level of readiness when deploying their innovation. This paper presents an approach to assessing innovation deployment readiness in manufacturing. Deployment is conceptualised as a sequential decision process that involves a deployment plan to be executed sequentially in an uncertain environment. The deployment plan is assessed using simulation to account for risks and uncertainties that may characterise the deployment activities in the target environment and the capabilities put forward in the plan for handling the risks and uncertainties. The approach is illustrated using a simulated manufacturing job shop scenario and the results show that deployment readiness can vary over time. Deployment readiness can be improved by identifying the states in which readiness is weak and taking appropriate actions.

Investigating Time Halo Effects of Mobile Photo Enforcement on Urban Roads

This paper investigates the time halo effects of mobile photo enforcement (MPE) on urban arterial and collector roads. Speed data were continuously recorded at nine locations for five consecutive weeks during the summer months of 2015 in Edmonton, Alberta, Canada. Each location was enforced according to a predefined deployment plan related to the regular working hours of MPE personnel. A time series intervention analysis that used percentages of speed limit violations was conducted to determine and to understand the time halo effects of MPE. The results of the analysis indicate that time halo effects existed at all study locations and that significant reductions in speed limit violations occurred because of MPE. The authors concluded that, on average, if an MPE unit was deployed eight times during a week for 22 h (approximately 2.7 h per visit) at an urban location, it would produce a time halo effect that would extend for approximately 5 days and reduce speed limit violation rates by almost 19%. In addition, the number of enforcement visits per week, the number of enforcement hours per week, and the average hours per visit were found to be strongly correlated to the longevity of the time halo effects and the reduction in speed limit violations. The findings of this study can be used to significantly increase the coverage of MPE programs and the safety benefits associated with MPE operations.

A state of fracking: Building Poland’s national innovation capacity for shale gas

Innovation in energy technology is framed as having the potential to advance renewable energy technologies (RET) towards an environmentally and technologically sustainable energy system. Innovation, however, involves more than RET. New energy technologies include fossil fuels which contribute to a country’s ‘innovativeness.’ The ability of states to foster innovation rests on their regulatory capacity, social acceptability and underlying ecological perspective. In this article a theory of state innovation builds upon National Innovation Capacity (NIC), bringing together state regulatory capacity and the eco-sophistication of society to determine acceptable energy technologies. To frame this investigation, a case study is developed about Poland’s attempt to foster a shale gas industry. Poland is chosen as a case study due to its low ranking for innovation, weak RET deployment plans, and use of coal as a primary energy source; it is a ‘low achiever’ on a comparative basis of states with limited innovation capacity. Poland provides two lessons in relation to state innovation: a) Institutional and regulatory action is underpinned by ecological choices made by society influencing institutional and technology preferences; and b) technology cannot simply be bought and imported, but instead needs to be integrated into an existing NIC and a conducive regulatory system.

Real-time projections of cholera outbreaks through data assimilation and rainfall forecasting

Although treatment for cholera is well-known and cheap, outbreaks in epidemic regions still exact high death tolls mostly due to the unpreparedness of health care infrastructures to face unforeseen emergencies. In this context, mathematical models for the prediction of the evolution of an ongoing outbreak are of paramount importance. Here, we test a real-time forecasting framework that readily integrates new information as soon as available and periodically issues an updated forecast. The spread of cholera is modeled by a spatially-explicit scheme that accounts for the dynamics of susceptible, infected and recovered individuals hosted in different local communities connected through hydrologic and human mobility networks. The framework presents two major innovations for cholera modeling: the use of a data assimilation technique, specifically an ensemble Kalman filter, to update both state variables and parameters based on the observations, and the use of rainfall forecasts to force the model. The exercise of simulating the state of the system and the predictive capabilities of the novel tools, set at the initial phase of the 2010 Haitian cholera outbreak using only information that was available at that time, serves as a benchmark. Our results suggest that the assimilation procedure with the sequential update of the parameters outperforms calibration schemes based on Markov chain Monte Carlo. Moreover, in a forecasting mode the model usefully predicts the spatial incidence of cholera at least one month ahead. The performance decreases for longer time horizons yet allowing sufficient time to plan for deployment of medical supplies and staff, and to evaluate alternative strategies of emergency management.