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Geometric backtracking for combined task and motion planning in robotic systems
بازخوانی هندسی برای کارهای ترکیبی و برنامه ریزی حرکت در سیستم های رباتیک-2017
Article history:Received in revised form 10 February 2015 Accepted 21 March 2015Available online 14 May 2015Keywords:Combined task and motion planning Task planningAction planning Path planning RoboticsGeometric reasoning Hybrid reasoning Robot manipulationPlanners for real robotic systems should not only reason about abstract actions, but also about aspects related to physical execution such as kinematics and geometry. We present an approach to hybrid task and motion planning, in which state-based forward-chaining task planning is tightly coupled with motion planning and other forms of geometric reasoning. Our approach is centered around the problem of geometric backtracking that arises in hybrid task and motion planning: in order to satisfy the geometric preconditions of the current action, a planner may need to reconsider geometric choices, such as grasps and poses, that were made for previous actions. Geometric backtracking is a necessary condition for completeness, but it may lead to a dramatic computational explosion due to the large size of the space of geometric states. We explore two avenues to deal with this issue: the use of heuristics based on different geometric conditions to guide the search, and the use of geometric constraints to prune the search space. We empirically evaluate these different approaches, and demonstrate that they improve the performance of hybrid task and motion planning. We demonstrate our hybrid planning approach in two domains: a real, humanoid robotic platform, the DLR Justin robot, performing object manipulation tasks; and a simulated autonomous forklift operating in a warehouse. 2015 Elsevier B.V. All rights reserved.
Keywords:Combined task and motion planning | Task planning | Action planning | Path planning | Robotics | Geometric reasoning | Hybrid reasoning | Robot manipulation
The future of online social networks (OSN): A measurement analysis using social media tools and application
آینده شبکه های اجتماعی آنلاین (OSN): تجزیه و تحلیل اندازه گیری با استفاده از ابزارها و برنامه های رسانه های اجتماعی-2017
The explosion of online social networks (OSN) has created an interactive and communica tive global phenomenon that has enabled billions of users to connect to other individuals on Facebook and Twitter but also with media sharing platforms such as Instagram and Pinterest. This study examines the current use of social media platforms and explores the factors that help define the long term implications of social media. The study employed a nationwide survey collected from 2012 to 2013 and is available from the PEW Internet research center of more than 2000 American citizens’ behaviour towards OSNs. The results revealed strong predictors of OSN that form the connections among users; and the core significant predictors: age, gender and access to mobile Internet that foster the adoption and usage of OSN in the future. Furthermore, online activities such as posting video content on social networks also highlighted the online usage patterns and trends of using social media to actively engage with other users more willingly than text. This is due to the viral nature of online media sharing on social media and as part of the video viewing and creating experience. An outline of practical implications of the findings and areas for future research is also discussed.
Keywords: Social media | Online social networks | Social network analysis | Video sharing | Photo sharing | Future of social media
Chinas R&D explosion—Analyzing productivity effects across ownership types and over time
R & D انفجار تجزیه و تحلیل اثرات بهره وری چین در میان انواع مالکیت و در طول زمان-2016
Article history:Received 21 January 2015Received in revised form 3 June 2015 Accepted 24 July 2015Keywords: Productivity R&DChina Ownership type PatentsJEL classiﬁcation:O32 O33In the past years, Chinese ﬁrms increased their spending on R&D substantially and worked on achieving a higher quality level of R&D. We analyze whether different R&D activities show a positive inﬂuence on total factor productivity (TFP) for ﬁrms of different ownership types and across two time periods. Our panel dataset with annual information allows us to study listed ﬁrms over the two time periods 2001–2006 and 2007–2011. Privately owned enterprises (POEs) not only obtain higher returns from own R&D than majority and minority state-owned enterprises (SOEs), they are also able to increase their leading position. Overall strong increases in the size of patent stocks are related to a decreasingly positive or even vanishing inﬂuence on TFP. POEs not only produce R&D of the highest quality but are also the only ownership type proﬁting from higher quality. Up to now research collaborations allow almost no beneﬁt with the only exception stemming from domestic collaborations with individuals. Our comprehensive analysis depicts strengths but also weaknesses of the corporate sector in China. We derive implications for the further development of economic policies.© 2015 Elsevier B.V. All rights reserved.
Productivity | R&D | China| Ownership type | Patents
Experimental study on the minimum ignition temperature of coal dust clouds in oxy-fuel combustion atmospheres
مطالعه تجربی بر روی حداقل درجه حرارت اشتعال ابرهای گرد و غبار ذغال سنگ در اتمسفر احتراق سوخت اکسیژن-2016
Article history:Received 24 October 2015 Received in revised form 22 December 2015Accepted 26 December 2015Available online 31 December 2015Keywords:Ignition temperature Oxygen richO2 /CO2 ambient BAM furnace Ignition mechanismBAM furnace apparatus tests were conducted to investigate the minimum ignition temperature of coal dusts (MITC) in O2 /CO2 atmospheres with an O2 mole fraction from 20 to 50%. Three coal dusts: Indone- sian Sebuku coal, Pittsburgh No.8 coal and South African coal were tested. Experimental results showed that the dust explosion risk increases signiﬁcantly with increasing O2 mole fraction by reducing the min- imum ignition temperature for the three tested coal dust clouds dramatically (even by 100 ◦ C). Compared with conventional combustion, the inhibiting effect of CO2 was found to be comparatively large in dust clouds, particularly for the coal dusts with high volatile content. The retardation effect of the moisture content on the ignition of dust clouds was also found to be pronounced. In addition, a modiﬁed steady- state mathematical model based on heterogeneous reaction was proposed to interpret the observed experimental phenomena and to estimate the ignition mechanism of coal dust clouds under minimum ignition temperature conditions. The analysis revealed that heterogeneous ignition dominates the igni- tion mechanism for sub-/bituminous coal dusts under minimum ignition temperature conditions, but the decrease of coal maturity facilitates homogeneous ignition. These results improve our understanding of the ignition behaviour and the explosion risk of coal dust clouds in oxy-fuel combustion atmospheres.© 2015 Elsevier B.V. All rights reserved.
Keywords: Ignition temperature | Oxygen rich | O2/CO2 ambient | BAM furnace | Ignition mechanism
Experimental investigations of the minimum ignition energy and the minimum ignition temperature of inert and combustible dust cloud mixtures
تحقیقات تجربی از حداقل انرژی اشتعال و حداقل درجه حرارت اشتعال مخلوط ابر گرد و غبار بی اثر و احتراق-2016
Article history:Received 8 October 2015Received in revised form 6 January 2016 Accepted 8 January 2016Available online 12 January 2016Keywords:Minimum ignition energy Minimum ignition temperature Dust explosionIgnition sensitivity Inert materialsThe risks associated with dust explosions still exist in industries that either process or handle combustible dust. This explosion risk could be prevented or mitigated by applying the principle of inherent safety (moderation). This is achieved by adding an inert material to a highly combustible material in order to decrease the ignition sensitivity of the combustible dust. The presented paper deals with the experimental investigation of the inﬂuence of adding an inert dust on the minimum ignition energy and the minimum ignition temperature of the combustible/inert dust mixtures. The experimental investigation was done in two laboratory scale equipment: the Hartmann apparatus and the Godbert-Greenwald furnace for the minimum ignition energy and the minimum ignition temperature test respectively. This was achieved by mixing various amounts of three inert materials (magnesium oxide, ammonium sulphate and sand) and six combustible dusts (brown coal, lycopodium, toner, niacin, corn starch and high density polyethylene). Generally, increasing the inert materials concentration increases the minimum ignition energy as well as the minimum ignition temperatures until a threshold is reached where no ignition was obtained. The permissible range for the inert mixture to minimize the ignition risk lies between 60 to 80%.© 2016 Elsevier B.V. All rights reserved.
Keywords:Minimum ignition energy | Minimum ignition temperature | Dust explosion | Ignition sensitivity | Inert materials
Experimental investigation of the minimum auto-ignition temperature (MAIT) of the coal dust layer in a hot and humid environment
بررسی تجربی حداقل دمای خودکار احتراق (MAID) از لایه گرد و غبار ذغال سنگ در یک محیط گرم و مرطوب-2016
Ventilation Air Methane (VAM) abatement technology is recognized as a promising and value adding technique for reducing fugitive methane emissions, however, it also increases the potential ﬁre and explosion risks of overheated coal dust. To eliminate these risks from the abatement systems it is ne- cessary to determine the critical combustion characteristics of the minimum auto ignition temperature (MAIT) for a coal dust layer.This study investigates the auto-ignition behavior of coal dust layers in a humid environment with Relative Humidity (RH) 4 80%. The MAIT of four different coal dust samples (Australian coal) with particle sizes below 212 μm and dust layer thicknesses of 5, 12 and 15 mm were measured using a dust layer auto ignition temperature apparatus in accordance with the ASTM E2021 standard.It was concluded that the MAIT of the coal dust layer signiﬁcantly decreases with decreasing particle size. The MAIT for the coal samples with a smaller D50 size were observed to be lower in comparison with samples with a larger D50 size. The dust layer thickness was shown to signiﬁcantly impact on the MAIT. The MAIT increased proportionally with the increasing thickness of the coal dust layer. The effect of the coal dust moisture content and humidity on the MAIT for compacted dust layers was noticeable, whereas, this effect was less important with loose dust layers. In addition, this work investigated and compared the MAIT for a typical coal dust sample based on the existing ASTM and International Elec- trotechnical Commission (IEC) standard procedures for ignition of coal dust layers.& 2016 Elsevier Ltd. All rights reserved.
Keywords: Dust layer | Coal ignition | Explosion | Volatile matter | MAIT | VAM
An Adaptive Information-Theoretic Approach for Identifying Temporal Correlations in Big Data Sets
رویکرد تطبیقی اطلاعات نظری برای شناسایی موقت همبستگی در مجموعه داده های بزرگ-2016
In the past two decades, new developments in computing, sensing and crowdsourced data have resulted in an explosion in the availability of quantitative information. The possibilities of analyzing this so-called “big data” to inform research and the decision-making process are virtually endless. In general analyses have to be done across multiple data sets in order to bring out the most value of big data. A first important step is to identify temporal correlations between data sets. Given the characteristics of big data in term of volume and velocity, techniques that identify correlations not only need to be scalable, but also need to help users in ordering the correlation across temporal resolutions so that they can focus on important relationships. There is a large body of work in this area, however, most of them either only deal with small data sets, using a fixed temporal resolution, or does not provide a quantifiable measure of a correlation significance. In this paper, we present a method based on mutual information to identify correlations in large data sets. Discovered correlations are suggested to users in an order based on their significance. Our method supports an adaptive streaming technique that minimizes duplicated computation and is implemented on top of Apache Spark for scalability using big data platforms. We also provide a comprehensive evaluation using real-world data sets from NYC Open Data, and compare our findings against a recent study.
Keywords: temporal correlation | mutual information | BigData | adaptive sliding window | streaming
Concise Essence-Preserving Big Data Representation
مراقبت مختصر از بازنمائی داده بزرگ-2016
Controversially, more data is not necessary better than less data. The explosion of the data lead to a number of interesting practical and theoretical problems. Among those problems are the need to filter, process, verify, index, distribute, protect and make redundant copies of the data. This data “massaging” usually take a lot of time and processing power. However, the quantity of the collected data does not necessary mean quality, as a lot of data is repetitive or does not contain any new information. Nevertheless, it still has to be processed, filtered, consumes high communication volume, has to be protected from breaches and from storage failures. In this position paper we propose to perform data reduction techniques on the collected (big) data prior to gathering of the data in a single location. In many cases (exemplified by two use-cases), especially in Internetof-Things (IoT), those techniques might save tremendous amounts of power, processing time and network traffic.
Index Terms: Big Data | Data Reduction | Big Data Analysis | Big Data Performance
Effects of ignition energy on fire and explosion characteristics of dilute hybrid fuel in ventilation air methane
اثر انرژی اشتعال در آتش سوزی و ویژگی های انفجار سوخت ترکیبی رقیق در تهویه متان هوا-2016
Deﬂagration explosions of coal dust clouds and ﬂammable gases are a major safety concern in coal mining industry. Accidental ﬁre and explosion caused by coal dust cloud can impose substantial losses and damages to people and properties in underground coal mines. Hybrid mixtures of methane and coal dust have the potential to reduce the minimum activation energy of a combustion reaction. In this study the Minimum Explosion Concentration (MEC), Over Pressure Rise (OPR), deﬂagration index for gas and dust hybrid mixtures (Kst) and explosive region of hybrid fuel mixtures present in Ventilation Air Methane (VAM) were investigated. Experiments were carried out according to the ASTM E1226-12 guideline utilising a 20 L spherical shape apparatus speciﬁcally designed for this purpose.Results: obtained from this study have shown that the presence of methane signiﬁcantly affects explo- sion characteristics of coal dust clouds. Dilute concentrations of methane, 0.75e1.25%, resulted in coal dust clouds OPR increasing from 0.3 bar to 2.2 bar and boosting the Kst value from 10 bar m s—1 to 25 bar m s—1. The explosion characteristics were also affected by the ignitors’ energy; for instance, for a coal dust cloud concentration of 50 g m—3 the OPR recorded was 0.09 bar when a 1 kJ chemical ignitor was used, while, 0.75 bar (OPR) was recorded when a 10 kJ chemical ignitor was used.For the ﬁrst time, new explosion regions were identiﬁed for diluted methane-coal dust cloud mixtures when using 1, 5 and 10 kJ ignitors. Finally, the Le-Chatelier mixing rule was modiﬁed to predict the lower explosion limit of methane-coal dust cloud hybrid mixtures considering the energy of the ignitors.© 2015 Elsevier Ltd. All rights reserved.
Keywords: Hybrid mixture | Deflagration index | Pressure rise | Explosion characteristics | ASTM E2021 | Coal dust | Methane | Explosion | Dust cloud
Behaviour of cylindrical steel drums under blast loading conditions
رفتاربا طبل های فلزی استوانه ای تحت شرایط بار انفجار-2016
The Buncefield incident in the UK in 2005 involved an explosion of 240,000 m3 of vapour cloud which resulted in considerable damage to properties in the surrounding area. A number of objects that can be used as overpressure indicators such as standard steel drums were located at various points around the site. These were found deformed to different levels after the explosion. These overpressure sensitive objects were used to assess the overpressure level at the locations of the objects during the incident. This study describes full scale validation tests and numerical simulations of far-field air blast loading acting on de formable steel drums in order to investigate possible forensic methods to aid the incident investigation. Subsequently, a number of numerical models are developed in order to simulate the tests. Two models with varying complexity are used in the simulations: uncoupled Eulerian–Lagrangian model and coupled Eulerian–Lagrangian approaches. These models are validated against the test data from gas detonation explosion. Comparison between the numerical and experimental results suggests that both approaches tend to over-predict the deformation of drums due to identified inaccuracies from test measurements and numerical methods. However, both methods can comparatively capture the different levels of damage arising from blast loads with various intensities. These comparative levels are in general agreement with observations from test data. Parametric studies using the validated techniques are also carried out to further examine the response of steel drums. The results are summarised in the form of pressure–impulse dia grams, and typical residual shapes of drum models are selected to complement the pressure–impulse diagrams. The methods and results presented in this paper offer a very useful tool which could be em ployed to aid forensic investigations of future explosion incidents involving steel drums or similar field objects.
Blast tests | Numerical simulation | Buncefield incident | Dynamic response | Vapour cloud explosions