dataesr/scientific-paragraphs-categorization huggingface dataset:
Conclusion and Perspectives In the microcontroller context, new microprocessors have enabled the recording of the execution of embedded software as a trace. Analyzing execution traces may help in embedded software debugging, which represents a large part of the cost of their development. However, collected traces contains a huge amount of data, making the analysis difficult and tedious. For both manual and automatic analysis of the trace, it seems opportune to have a compact and analyzable representation of the trace. In this paper, we propose a trace compression method that aims at facilitating trace analysis. The method relies on a grammar-based compression named Cyclitur built upon the Sequitur algorithm [?]. Our approach starts by dividing a trace into cycles, where each cycle is an execution of the active main loop.
The second step consists in discovering and compressing similarities in the trace. Our approach is evaluated to compare its compression rate to the existing Sequitur algorithm. The experimental evaluation shows that our approach generates an equivalent or better compression than Sequitur on execution traces. On microcontroller execution traces, Cyclitur compression ratios were better than Sequitur compression ratios from 12% to 42%. In addition, Cyclitur may help in identifying and locating important details in an execution trace. While Cyclitur is not aimed at competing with compression ratio of compression schemes in general, it would be interesting to compare Cyclitur with value predictor-based compressions [?,?]. Also, we intend to help locating faults in embedded software by analyzing compressed traces and adapting dynamic validation and data mining techniques [?].
Measurement data base In the framework of the PARTICULES project (AIRPARIF-LSCE), daily (from 00:00 to 23:59 LT) PM 2. 5 chemical mass closure measurements have been performed in the Paris region and its surroundings during a whole year period, from the 11 September 2009 to the 10 September 2010. Six sites have been documented, including an urban background site (PAR) and three rural background sites, respectively, in the northeast (RNE), south (RUS), and northwest (RNW) of Paris. Bressi et al. (2013)  have described in details the sampling and analytical setup and have presented the experimental database obtained from this campaign. At each site, PM 2. 5 has been collected by two Leckel samplers, one equipped with Teflon filters for gravimetric and ions measurements, the other with quartz filters for carbon measurements.
Aerosol module description The main processes affecting the aerosol size distribution and chemical speciation are represented in the CHIMERE aerosol module. This includes emissions, nucleation, coagulation, condensation, and dry and wet deposition. Through a sectional representation within eight bins of size (diameter ranging from about 40 nm to 10 µm), the module takes into account various chemical species: primary material -including primary organic aerosol (POA), EC and the so-called mineral particulate matter (MPM) corresponding to the remaining part -, nitrate, sulfate, ammonium, water, and SOA compounds. Primary species (POA, EC, MPM) are treated as inert species that can only deposit by wet and/or dry processes. The SOA scheme consists of a single-step oxidation of anthropogenic and biogenic VOC lumped species, giving directly semi-volatile organic compounds that partition between gaseous and particulate phases.
Model configuration Simulations are performed with the ESMERALDA operational modeling platform. Three nested domains -a large (LAR), a medium (MED) and a fine (FIN) one -are considered with horizontal resolution progressively increasing from 0. 5 • (roughly 50 km) to 15 km to 3 km (see Fig. 1  and description in Table  2 ), each with eight vertical levels, from 40 m to about 5 km height. Meteorological inputs come from PSU/NCAR MM5 simulations  (Dudhia, 1993) , performed over three nested domains with increasing resolutions of 45, 15 and 5 km, respectively, and using Final Analyses (FNL) data from the National Centers for Environmental Prediction (NCEP) as boundary conditions and large scale data. Anthropogenic emissions come from the 1×1 km-resolved local ESMERALDA inventory, which was developed by local agencies over the so-called ESM area (delimited by administrative borders, see Fig.
1 ), e. g. , AIRPARIF (2010) for the Paris region and mainly derived from a bottom-up approach. Following the methodology developed in the European FP7/HEAVEN project, traffic emissions are computed from traffic data, fleet description and emission factors using the COPERT IV approach  (EEA, 2013). Fuel evaporation emissions are also taken into account. However, road, tire and brake abrasion emissions are ignored, as well as road dust resuspension. So far, ammonia traffic emissions are not taken into account. The inventory includes emissions from other means of transport (aircraft, shipping, railway). Industrial sector emissions are derived from official statements when they exist or are computed from various types of data (e. g. , national raw material consumptions, national productions).
Conclusions An original approach to evaluate chemistry-transport models in terms of advected and local contributions rather than concentrations is described. Based on observations at both urban and rural background stations, the estimation of advected contributions consists of the choice of the appropriate rural site considering back-trajectories data to localize the air masses origin, while local production is then simply deduced from the urban concentration by subtraction. The methodology is applied to the CHIMERE model in the Paris region with a one-year daily measurements database of PM 2. 5 and its speciation, in the framework of the PARTIC-ULES project. On an annual basis, about 71 % of the Paris urban background fine PM is related to imports from outside, mainly from the northeast. These air masses advect 87 % of the inorganic secondary compounds, 69 % of the OM and 26 % of the EC.
Acknowledgements. This work is funded by a  PhD DIM (domaine d'intérêt majeur) grant  from the  Ile-de-France region. The  PARTICULES  project has been funded by the  French state , the  Ile-de-France region  and the Paris city. The authors gratefully acknowledge  Jean-Charles Dupont  and the SIRTA (sirta. ipsl. fr)for the useful boundary layer height data. Meteorological data have been kindly provided by  METEO France. Edited by:  A. Kerkweg.
In this technique, the monitoring node has two detection engines identified as local agent and global agent. The former monitors only their own communication (e. g. , sent and received messages and sensed data), and the latter observes the neighbors' communication. The global agent uses a rule-based approach with two-hop neighbor knowledge for the anomaly detection, and it sends alarms to the CH when the intrusion occurs. Both monitoring nodes use signature-based detection, which are computed and generated by the CH. The authors attempt to provide a cooperative mechanism between IDS agents that is based on trust priority in order to reduce the false alerts raised by the intruder. Nevertheless, the drawback of this scheme is the large increase of the size of the signature database, which in turn leads to an overload of the node.
Cluster (medium) level intrusion detection Inspired by the work of authors in  [6] , our clustering algorithm, which was implemented under TOSSIM Simulator  [25] , elects at each cluster a CH that has more power resources to manage and aggregate data received from the cluster members. As illustrated in Figure  4  (CH agent), this powerful node comprises three modules: data gathering, anomaly detection, and reputation modules. They are detailed in the following: (1) Data gathering module. This module is responsible to collect the CHECK messages sent by the IDS agent. This message includes the address of the Each CH trains the SVM locally, then computes a set of data vectors called support vectors that are generally less in number than the input data used during the learning process. These vectors will be sent to an adjacent CH that is located in the same radio range.
PERFORMANCE EVALUATION In our experiment, we used TOSSIM simulator  [25] , a simulator for TINYOS application. The main advantage of this simulator, compared with other tools such as NS2  [28] , is the fact that we can easily embed the source code written in NESC on real sensor nodes (with TINYOS operating system). However, the TOSSIM simulator does not have the ability to model the energy dissipated during the execution of the application. To this end, an improved version of the tool was proposed by Harvard University called POWERTOSSIM  [29]  allowing the simulation of nodes' energy consumption and hence the determination of the network's lifetime.
Beyond the difficulties brought by these factors, the evaluation of user experience for iTV is complex, as the system to be evaluated consists of multiple components: the TV screen, (a set of) remote controls, (possibly) a set top box (i. e. the hardware device connecting the TV to the IP network) and potentially other devices in the living room (e. g. surround sound system). One of the characteristics of the iTV domain is also the multiple goals of the users aiming at being entertained and informed. We have been applying various UX methods in the area of iTV  [5, 44, 45]  which otherwise has received only limited attention. These studies have been carried out in close cooperation with one of the industry leaders in hardware and software systems for iTV. However, even though the evaluation results were iteratively fed into the development process of the systems, customer feedback reported by our client were exhibiting users' frustration and dissatisfaction, demonstrating a user experience far below expectations.
Procedure and Participants To validate the initial version of the iTV-UX questionnaire, the questionnaire was distributed online using the online survey tool surveymonkey. com. Participants were invited using e-mail, social networks, word of mouth and by personal invitation. The iTV-UX questionnaire had a brief introductory section, including obligatory statements on data anonymity, followed by a series of demographic questions (age, gender) and questions regarding the TV system used (reception, type of set-top box, media usage frequency). The sections of the questionnaireintroduction, demographics and media usage, UX scales, and debriefing -were represented on individual (web) pages. The questionnaire parts addressing the UX scales additionally had a brief introductory text to highlight that participants should evaluate the most recent 20 or more minutes usage of their TV system.
At the end of the questionnaire, a standard usability scale was added. Questionnaire items were randomly inverted to avoid fill-in patterns like "1111". No monetary incentives were given to questionnaire participants. Overall, the fulfillment of the whole questionnaire lasted 10 minutes on average. Over a three week period, 106 complete datasets were retrieved. 65 participants were between 20 and 29 years, 21 participants were between 30 and 39 years, and 20 participants were older than 40 years. 59. 6 % were male, 40. 4 % female (2 participants did not name their gender). The number of persons living in the household of the person filling in the questionnaire ranged from one to six persons. 15. 2 % were living in single households, 46. 7% of the participants lived in 2-person-households, 24.
Another research project, the European PLAY project proposes an adaptation recommender service  [9]  which allows to adapt the ongoing processes on pre-determined milestones, through the addition of relevant pieces of processes (extracted from a knowledge database). The Agility Service in the SocEDA project is a tool designed to adapt the dynamic of the situation, i. e. processes, to the evolution of the context. In this section, we will detail the mechanisms of the Agility Service. The adopted approach of agility in our research work is given by the formula below (which is close to the definition given by  [10] ): Agility = (Detection + Adaptation)*Reactivity. (1) • Detection: this step consists in detecting an evolution of the situation that could not be solved by the ongoing processes or making the running processes not relevant to the current situation, • Adaptation: when an evolution is detected, the adaptation step is executed to modify the ongoing processes in order to make them relevant to the current situation, • Reactivity: detection and adaptation steps have to be done as fast as possible (and real-time if possible).
Participants Data were collected from three vocational education schools in the Netherlands. Out of the 44 students who were approached to participate in the mEMA study, 30/44 students (68%) participated for 7 consecutive days (17/30, 57% were female), of which 17 students (aged 16-21 years) completed the online evaluation (regarding feasibility and usability of the mEMA app) after their 7 days of participation. Participatory incentives of ten €20 coupons were randomly distributed to the students at the end of the study. Those who participated for 7 days and filled in the online evaluation form doubled their chance of winning. All students consented to take part in the study and students aged ≤17 were provided with a passive consent form for their parents to complete. All procedures were approved by The Ethical Committee of Psychology (Maastricht University).
Mobile Ecological Momentary Assessment App Use Prior to the use of the mEMA app, students completed an online questionnaire regarding their DI or PA during the preceding 7 days. Data from this online questionnaire were collected for other study purposes. After completion, students who possessed a smartphone that operated on iOS (iPhone version 5. 0), BlackBerry OS (version 6. 0 or 7. 0), or Android (version 2. 2 and over) systems were eligible for participation, and downloaded the mEMA app from the BlackBerry OS, iOS, or Android app store (n=30). Students who possessed a smartphone with other operating systems or who did not own a smartphone were exempted from further participation. The students were invited to use the mEMA app for 7 consecutive days and gave their consent for participation.
Data Analysis SPSS version 20 was used for data analyses. Data from the mEMA app were transported from the smartphone into a secure computer system when participants had access to a Wi-Fi connection. Next, data from the computer system were converted to an SPSS database. With SPSS, descriptive statistics were generated (means and percentages) and compliance rates were calculated for the exploration of response patterns. Furthermore, a t test was done in order to examine gender differences in the perceived usability of the mEMA app. Prior to the analyses, normality was tested by means of Q-Q plots. Mean differences were analyzed using t tests when normally distributed and Mann-Whitney U test when they were non-normally distributed.
CIMOSA (Computer Integrated Manufacturing Open System Architecture) is a methodology used for designing CIM open system architecture, for defining a set of concepts and rules for facilitating the realization of future manufacturing systems and for aiding the reimplementation of existing systems. This methodology has been developed within the framework of the European strategic programme ESPRIT. It is architecture for describing enterprises by giving characteristics for modelling production systems on three levels: definition of requirements, design specification, and implementation description  [CHEN, E. ET AL. 2008]. CIMOSA is a reference architecture which supports the description of the enterprise from the management level to the shop floor level (Fig. 1 ). CIMOSA consists of an enterprise modelling framework, an enterprise modelling language and an integrated infrastructure.
This methodology is useful for the improvement of enterprise performance at the local level. In our researches CIMOSA is used for improving enterprises locally. The results of the previous studies are presented in paper  [PAWLEWSKI, P. 2011 ]. These results consisted in planning the process taking place in an enterprise characterized by the manufacture of complex products (machine building). The idea is based on the so-called domains of the CIMOSA concept which has been used for the modelling. A planning process based on the multi-agent architecture called VLPRO-GRAPH. Agent-based system is defined in the present section as a multiagent system that acts as a support tool and utilizes the databases of main system (ERP system). Multiagent system is a collection of heterogeneous, encapsulated applications (agents) that participate in the decision making process [PECHOUCEK, M.
ET AL. 2003 ]. The architecture of the tool (VLPRO-GRAPH -Very Long Process Graph) is based on the assumption that the system will support the master production schedules (MPS) creation in ERP system and will be plugged in to ERP system database by for example java connector. A production process based on CIMOSA domains is presented in figure  2  where domains are [PAWLEWSKI, P. 2011]: -D1 -order and management planning, -D2 -license documentation, -D3 -loads planning -D4 -Sales and production planning, scheduling for strategic machines, -D6 -procurement, -D7 -quality, process and costs control, -D8 -production sub-process 1, -D9 -production sub-process 2, -D10 -production sub-process 3. Special Issue #1 http://adcaj. usal. es planning process which is described at three layers (see Fig. 3 ) reflecting to [PAWLEWSKI, P.
Thinking in ABS paradigms gives potential to propose solution for these situations. The emergence of ABS as a technique in Operational Research is timely. Globalised business is a highly complex management process, and making decisions in this environment is not well supported by the current set of tools, including DES [NORTH, M. J. & MACAL C. M. 2007]. In table 1 is presented list of selected agent systems. This list includes systems which originate really from agent based approach. Apart from presented list there are available many systems based on Java like: iGen, ICARO-T, JABM, JAMEL, JANUS, JAS, JASA , JCA-Sim, Madkit, Mason, Moduleco, Sugarscape, VSEit. There is a number of excellent academically developed tools, the commercially available software is limited to AnyLogic (but Anylogic origins are from DES so we classified it as DES system which included ABS approach), and all of these products expect knowledge of object oriented programming techniques and the modeller needs to be comfortable with Java.
It is difficult to find an agent system which has possibilities to combine agent based and DES. Some systems offer possibilities to combine DES with ABS. the first is AnyLogic. AnyLogic supports agents in a continuous or discrete environment and also supports sophisticated animation capabilities to visualize agent behaviours. It contains a graphical modelling language and also allows the user to extend simulation models with Java code. The Java nature of AnyLogic allows model extensions via Java coding as well as the creation of Java applets which can be opened with any standard browser. The second system is Simio. The Simio framework is a graphical object-oriented modelling framework as opposed to simply a set of classes in an object-oriented programming language that are useful for simulation modelling.
Reducing the amount of java code to be written is a must [SIEBERS, P. ET. AL. 2010]:. Based on our researches we decided to choose Flexsim as our main simulation tool for three reasons. The first one is that in Flexsim the ability to combine any number of models together provides unlim-ited scalability, such that in principle, any size of agent model can be constructed. This can be especially important when agent based models have the possibility to become computationally intensive. Flexsim is able to represent agents with objects and can describe the state models of each agent object in it's own modelling language or c++. The 3D virtual reality environment of Flexsim allows the agents to operate in a detailed world where geometry, shapes and motion exist. Rapid development of agent models is facilitated through the built in flexscript language engine which does not require compilation steps, and if more simulation execution power is required, the same code can be promoted seamlessly to c++ for optimal performance.
Implementation details The criteria of choice of a ray-tracer are: an unbiased estimation, a reasonable computation time (real-time is however out of scope), open source software to allow modifications, a good control through physically pertinent parameters. For these reasons, we chose to use the GPL physically-based renderer LuxRender, that is based on PBRT (Physically-Based Ray-Tracing)  (Pharr and Humphreys, 2004). In order to fasten the convergence of the estimation (5), LuxRender uses importance sampling to drive the stochastic choice of the reflection direction; the BRDF values are used as a probability density function (pdf ). When evaluating the radiance coming directly from the light sources, the pdf takes into account the BRDF and the angular distribution of light sources (multiple importance sampling  (Veach, 1997) ).
(2005)  in order to reduce pressure gradient errors. The ROMSTOOLS package  (Penven et al. , 2008 , http://www. romsagrif. org) was used to build the model grid, atmospheric forcing, and initial and boundary conditions. The Namibian configuration used in this study is a small domain which is a subdomain of the SAfE HR climatological configuration  (Veitch et al. , 2009)  (Fig. 1 ). For temperature, salinity, free surface, and the velocity (zonal and meridional components), the initial conditions come from the 1 January of the 10th year of SAfE HR  (Veitch et al. , 2009) ; the open boundary conditions are also provided by the 10th year of this simulation for which variables were averaged every 5 days. A 1/2 • resolution QuikSCAT  (Liu et al. , 1998)  monthly climatological wind stress (courtesy of N.
Phytoplankton (P S and P L ) is a function of Chl a derived from SeaWiFS climatology and vertically extrapolated from the surface values using  Morel and Berthon (1989)  parameterization. For zooplankton (Z S and Z L ), we applied a cross-shore profile following in situ observations, with low concentrations offshore (based on  Koné et al. , 2005)  and increasing concentrations onshore. N 2 O is a function of O 2 from the CARS database (  2006 ) using the parameterization of  Suntharalingam et al. (2000 Suntharalingam et al. ( , 2012)). For other biogeochemical tracers, initial and lateral boundary conditions are established using a vertical constant profile (for D S and D L ) or exponential profile (for NO - 2 , NH + 4 and DON) (see Table 1) based on  Koné et al. (2005). The simulation is run for a total of 19 yr.
L. Søerensen, National Environmental Research Institute, Denmark) at different stations and along a vertical section. The AMT 17 cruise in November 2005 estimated DON concentrations in the southern Benguela. For the first time in the Namibian upwelling system, N 2 O samples were collected off Walvis Bay at around 23 • S during the FRS Africana cruise in December 2009 within the framework of the GENUS project (Geochemistry and Ecology of the Namibian upwelling system). The collected samples were poisoned with mercuric chloride onboard and measurements were done after the cruise at IFM-GEOMAR, Germany, by using the static equilibration method according to  Walter et al. (2006). All data enumerated above will be compared to simulations outputs for the same geographical positions (except for DON because there are no available measurements in the Namibian upwelling system) and the same climatological months.