948 research outputs found
A Modular Logic Approach for Expressing Web Services in XML Applying Dynamic Rules in XML
Get PDFRuleML is considered to be a markup language for the semantic web. It allows the enrichment of web ontologies by adding definitions of derived concepts and it enhances interoperability among different systems and tools by publishing rules in an XML format. Moreover the in-creasing demand for interfaces that enhance information sharing has given rise to XML doc-uments that include embedded calls to web services. In this paper we propose a variation of RuleML that is based on modular logic programming. Our approach is based in a two level architecture. In the first level a modular logic language, called M-log, is presented. This lan-guage encompasses several mechanisms for invoking web services. In the second level we ex-ploit the semantics of M-log to present a variation of RuleML with rich modeling capabilities. Formal foundations for this variation are given through direct translation to M-log semantics.Knowledge Management, XML, Modular Logic Programming, E-Services
Movement data set for trust assessment (Drapebot robot cell/DLR)
No full text<p>In the Drapebot project, a worker collaborates with a large industrial manipulator in two tasks: collaborative transport of carbon fibre patches and collaborative draping. To realize data-driven trust assessement, the worker is equipped with a motion tracking suit and the body movement data is labeled with the trust scores from two standard Trust questionnaire (1. Trust perception scale - HRI, Schaefer 2016; 2. Trust in industrial human robo collaboration, Charalambous, et.al. 2016).</p>
<p>For this data set, data has been collected for the draping task from 21 participants all familiar with working with large industrial manipulators. For all sessions, body tracking was performed using the Xsens MVN Awinda tracking suit. It consists of a tight-fitting shirt, gloves, headband, and a series of straps used to attach 17 IMUs to the participant. After calibration the system uses inverse kinematics to track and log the movements of the participant at a rate of 60 Hz. The measurements include linear and angular speed, velocity, and acceleration of every skeleton tracking point (see <a href="https://www.xsens.com/hubfs/Downloads/Manuals/MVN_real-time_network_streaming_protocol_specification.pdf">XSENS manual</a> for a detailed description of avaiable measurements).</p>
<p><strong>Data organization</strong></p>
<p>There are 21 files for 21 participants. The name of the files is PID01, where the number 01 is the participant. Each file contains all the data that was generated from the XSENS motion capture system. The files are xlsx files and for each sheet inside the excel file there are different types of data:</p>
<ul>
<li>Segment Orientation - Quat</li>
<li>Segment Orientation - Euler</li>
<li>Segment Position</li>
<li>Segment Velocity</li>
<li>Segment Acceleration</li>
<li>Segment Angular Velocity</li>
<li>Segment Angular Acceleration</li>
<li>Joint Angles ZXY</li>
<li>Joint Angles XZY</li>
<li>Ergonomic Joint Angles ZXY</li>
<li>Ergonomic Joint Angles XZY</li>
<li>Center of Mass</li>
<li>Sensor Free Acceleration</li>
<li>Sensor Magnetic Field</li>
<li>Sensor Orientation - Quat</li>
<li>Sensor Orientation - Euler</li>
</ul>
<p>See also: <a href="https://base.movella.com/s/article/Output-Parameters-in-MVN-1611927767477?language=en_US">https://base.movella.com/s/article/Output-Parameters-in-MVN-1611927767477?language=en_US</a></p>
<p>For more information on each specific data and/or sensors please see the xsens manual (Link above)</p>
<p><strong>Data Annotation</strong></p>
<p>In each .xlsx file the first tab (sheet) is called "Markers". It annotates the starting frame of the individual tasks. The annotations are pickup, draping, return and some files may contain a also a "fail" annotation. Failed attempts should not be taken into consideration for model training.</p>
<p>The file trustscores.xlsx includes the results of the trust questionaires for each participant (scores for the individual items as well as the calculated overall trust scores).</p>
<p>Items for Trust perception scale - HRI, Schaefer 2016:</p>
<ul>
<li>Which % of time does the robot
<ul>
<li>Function successfully</li>
<li>Act consistently</li>
<li>Communicate with people</li>
<li>Provide feedback</li>
<li>Malfunction</li>
<li>Follow directions</li>
<li>Meet the needs of the mission</li>
<li>Perform exactly as instructed</li>
<li>Have errors</li>
</ul>
</li>
<li>Which % of the time is the robot:
<ul>
<li>Unresponsive</li>
<li>Dependable</li>
<li>Reliable</li>
<li>Predictable</li>
</ul>
</li>
</ul>
<p>Items for Trust in industrial human robo collaboration, Charalambous, et.al. 2016:</p>
<ul>
<li>The way the robot moved made me uncomfortable</li>
<li>I felt I could rely on the robot to do what it was supposed to do </li>
<li>The speed at which the gripper picked up and released the components made me uneasy </li>
<li>I felt safe interacting with the robot</li>
<li>I knew the gripper would not drop the components</li>
<li>The size of the robot did not intimidate me</li>
<li>The robot gripper did not look reliable</li>
<li>I was comfortable the robot would not hurt me</li>
<li>I trusted that the robot was safe to cooperate with</li>
<li>The gripper seemed like it could be trusted</li>
</ul>
<p> </p>
<p>K. E. Schaefer, Measuring Trust in Human Robot Interactions: Development of the “Trust Perception Scale-HRI”. Boston, MA: Springer US, 2016, pp. 191–218.</p>
<p>G. Charalambous, S. Fletcher, and P. Webb, “The development of a scale to evaluate trust in industrial human-robot collaboration,” International Journal of Social Robotics, vol. 8, pp. 193–209, 2016.</p>
Movement data set for trust assessment (Drapebot robot cell/Dallara)
No full text<p>In the Drapebot project, a worker collaborates with a large industrial manipulator in two tasks: collaborative transport of carbon fibre patches and collaborative draping. To realize data-driven trust assessement, the worker is equipped with a motion tracking suit and the body movement data is labeled with the trust scores from two standard Trust questionnaire (1. Trust perception scale - HRI, Schaefer 2016; 2. Trust in industrial human robo collaboration, Charalambous, et.al. 2016).</p>
<p>For this data set, data has been collected for the draping task in a near-production setting from 5 participants all familiar with carbon-fibre draping. For all sessions, body tracking was performed using the Xsens MVN Awinda tracking suit. It consists of a tight-fitting shirt, gloves, headband, and a series of straps used to attach 17 IMUs to the participant. After calibration the system uses inverse kinematics to track and log the movements of the participant at a rate of 60 Hz. The measurements include linear and angular speed, velocity, and acceleration of every skeleton tracking point (see <a href="https://www.xsens.com/hubfs/Downloads/Manuals/MVN_real-time_network_streaming_protocol_specification.pdf">XSENS manual</a> for a detailed description of avaiable measurements).</p>
<p><strong>Data organization</strong></p>
<p>There are 5 files for 5 participants. The name of the files is PID01, where the number 01 is the participant. Each file contains all the data that was generated from the XSENS motion capture system. The files are xlsx files and for each sheet inside the excel file there are different types of data:</p>
<ul>
<li>Segment Orientation - Quat</li>
<li>Segment Orientation - Euler</li>
<li>Segment Position</li>
<li>Segment Velocity</li>
<li>Segment Acceleration</li>
<li>Segment Angular Velocity</li>
<li>Segment Angular Acceleration</li>
<li>Joint Angles ZXY</li>
<li>Joint Angles XZY</li>
<li>Ergonomic Joint Angles ZXY</li>
<li>Ergonomic Joint Angles XZY</li>
<li>Center of Mass</li>
<li>Sensor Free Acceleration</li>
<li>Sensor Magnetic Field</li>
<li>Sensor Orientation - Quat</li>
<li>Sensor Orientation - Euler</li>
</ul>
<p>See also: <a href="https://base.movella.com/s/article/Output-Parameters-in-MVN-1611927767477?language=en_US">https://base.movella.com/s/article/Output-Parameters-in-MVN-1611927767477?language=en_US</a></p>
<p>For more information on each specific data and/or sensors please see the xsens manual (Link above)</p>
<p><strong>Data Annotation</strong></p>
<p>In each .xlsx file the first tab (sheet) is called "Markers". It annotates the starting frame of the individual tasks. The annotations are pickup, draping, return and some files may contain a also a "fail" annotation. Failed attempts should not be taken into consideration for model training.</p>
<p>The file trustscores.xlsx includes the results of the trust questionaires for each participant (scores for the individual items as well as the calculated overall trust scores).</p>
<p>Items for Trust perception scale - HRI, Schaefer 2016:</p>
<ul>
<li>Which % of time does the robot
<ul>
<li>Function successfully</li>
<li>Act consistently</li>
<li>Communicate with people</li>
<li>Provide feedback</li>
<li>Malfunction</li>
<li>Follow directions</li>
<li>Meet the needs of the mission</li>
<li>Perform exactly as instructed</li>
<li>Have errors</li>
</ul>
</li>
<li>Which % of the time is the robot:
<ul>
<li>Unresponsive</li>
<li>Dependable</li>
<li>Reliable</li>
<li>Predictable</li>
</ul>
</li>
</ul>
<p>Items for Trust in industrial human robo collaboration, Charalambous, et.al. 2016:</p>
<ul>
<li>The way the robot moved made me uncomfortable</li>
<li>I felt I could rely on the robot to do what it was supposed to do </li>
<li>The speed at which the gripper picked up and released the components made me uneasy </li>
<li>I felt safe interacting with the robot</li>
<li>I knew the gripper would not drop the components</li>
<li>The size of the robot did not intimidate me</li>
<li>The robot gripper did not look reliable</li>
<li>I was comfortable the robot would not hurt me</li>
<li>I trusted that the robot was safe to cooperate with</li>
<li>The gripper seemed like it could be trusted</li>
</ul>
<p> </p>
<p>K. E. Schaefer, Measuring Trust in Human Robot Interactions: Development of the “Trust Perception Scale-HRI”. Boston, MA: Springer US, 2016, pp. 191–218.</p>
<p>G. Charalambous, S. Fletcher, and P. Webb, “The development of a scale to evaluate trust in industrial human-robot collaboration,” International Journal of Social Robotics, vol. 8, pp. 193–209, 2016.</p>
Pomological and phenological characteristics of the main pistachio cultivars in Greece
Get PDFThe present study aimed to evaluate the pomological and phenological traits, as well as kernel antioxidant potential of the dominant Greek pistachio cultivars, ‘Aegina’ and ‘Pontikis’ (Pistacia vera L.). Blooming of ‘Aegina’ cultivar occurred from early to mid of April, and nut maturation at middle to late of August. Production started at 6 to 7 years from grafting and full production observed at year 13. Blooming and nut maturation of ‘Pontikis’ occurred about 1 to 2 days later than ‘Aegina’ and production started 6 to 7 years from grafting, with full production observed in the 14th year. Mean tree yields reached 18.0 ± 1.0 kg and 17.4 ± 1.1 kg of dry nuts, in ‘Aegina’ and ‘Pontikis’ cultivar, respectively. ‘Aegina’ cultivar presented intermediate tree vigour and spreading growth habit, whereas ‘Pontikis’ high tree vigour and semi-erect growth habit. ‘Aegina’ nut had a narrowly cordate shape and the percentage of split nut was found at 78.5 ± 6.5. ‘Pontikis’ nut had ovoid shape and the percentage of split nut was 84.1 ± 6.2. In ‘Aegina’ cultivar 100 nuts weighted 101.0 g and in ‘Pontikis’ 114.4 g. Color of kernel was green externally and green to green-white internally, greener in ‘Pontikis’. The antioxidant potential of pistachio kernel measured by FRAP assay, total polyphenolic substances, flavonoids, flavanols and hydroxycinnamic acids content, did not differ (P > 0.05) between cultivars. Evaluation of ‘Aegina’ and ‘Pontikis’ pistachio cultivars revealed that both are high yielding, with large nut sizes of acceptable appearance and high quality
Ioannis Dallaei De imaginibus libri IV.
No full textIncludes errata at end.Signatures: *⁸ A-2L⁸ 2M⁴ chi².Woodcut printer's device on t.p. Head- and tail-pieces, initials.Scanned copy bound with: Joannis Dallaei Apologia pro ecclesiis reformatis. Amstelodami : Apud Jodocum Jansonium, 1652.Mode of access: Internet.Binding: vellum. Author & titles written at head of spine.With his: Apologia pro ecclesiis reformatis (Amsterdam : J. Janson, 1652)
Ioannis Metaxas: Speech on the occasion of the inauguration of public works
No full textTitle: Λόγος κατά τα εγκαίνια των έργων του Σελινούντος Αιγιαλείας (Speech on the occasion of the inauguration of the public works at Selinous, Egialia) Originally published: Delivered at Selinous on 31 October 1937. Language: Greek The excerpts used are from Ioannis Metaxas, Λόγοι και Ομιλίες (Athens: Ερμής, 1992), pp. 247–255. About the author Ioannis Metaxas [1871, Ithaca (Ionian Islands)–1941, Athens]: military officer and politician. He was born into a well-known aristocratic family. In ..
Literary Recants of a Tenth-Century Scholar: The Case of Ioannis Kaminiates
Get PDFThis paper seeks to interpret the attitude of Ioannis Kaminiates towards Homer, for while initially criticising his literary predecessor, the author of On the Capture of Thessaloniki later adopts many of his turns of phrase
My journey
No full textTitle: Τό ταξίδι μου (My journey) Originally published: Αθήνα, n. p., 1888 Language: Greek The excerpts used are from Ἰωάννης Ψυχάρης, Τό ταξίδι μου, ed. by Alkis Agelou (Athens: Ἐστία: Νεοελληνική Βιβλιοθήκη, 1993), pp. 37–39, 64–67, 75–76, 89. About the author Ioannis (Jean) Psicharis [1854, Odessa – 1929, Paris]: writer, linguist and critic. Psicharis was born to a well-off family. After his mother’s early death his father brought him to Istanbul in 1860, where he spent his childhood. His ..
Of this great idea
No full textTitle: Τῆς Μεγάλης αυτής Ἰδέας (Of this Great Idea) Originally published: Ιt was published in Ἠ τῆς τρίτης Σεπτεµβρίου ἐν Άθήναις Ἐθνική Συνέλευσις, Athens, Βουλή των Ελλήνων, 1844 Language: Greek The excerpts used are from Constantinos Th. Dimaras, Ελληνικός Ρωµαντισµός (Athens: Ερµής, 1985), pp. 405–406. About the author Ioannis Kolettis [1773, Sirako (Epirus) – 1847, Athens]: medical doctor, politician and writer. He was educated in his hometown of Sirako and in nearby Kalarites, both pros..
Gramática, traducción y lengua en Ioannis Vilarás (1771-1823)
Get PDFThe author presents in this article Velaras’s brief treatise The Romeic Language, Corfu, 1814, a key guide on the vindication of spoken Greek. His linguistic proposals, as well as the stylistic and translation decisions of the author are succinctly analyzed and commented on in order to defend its importance for Greek studies.La autora presenta en este artículo el opúsculo de Ioannis Vilarás, La lengua romeica, Corfú, 1814, obra de referencia sobre la defensa de la lengua griega hablada. Se analizan sucintamente las propuestas lingüísticas, estilísticas y traductoras del autor que se desprenden de esta obra así como su trascendencia en las letras neogriegas
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