Animation of Z Specifications By Translation to Prolog

Yazılım geliştirebilmenin formal metodları o yazılım tanımlamasının geçerliliğine bağlıdır. Böyle bir tanımlama genelde 'Z' gibi bir formal dilde ifade edilir. Ancak, geçerli olması için, 'Z' tanımlaması test edilmeli, bunu yapabilmek için de animasyon yapılabilecek ve icra edilebilecek bir forma transfer edilebilmelidir. 'Z' tanımlamalarının animasyonları için kullanılan dillerden birisi Prolog'dur. Bu makalede 'Z' şemalarını Prolog'a çeviren teknikler açıklanmaktadır.Aym zamanda bu tür bir çevirmenin eksikleri ve belirsizlikleri üzerinde durulacaktır.Formal methods of software development rely on the validation of the specification of the software. Such specification is normally expressed in a formal language such as Z. However, in order to be validated the Z specification must be tested, and to achieve this it has to be transformed into a form that can be executed or animated. Prolog was one of the languages used for animation of Z specifications. This paper explains the techniques used for translating Z schemas into Prolog predicates. It also examines some of this translation shortcomings and unreliable features

Selective laser melting of 316L stainless steel and related composites: processing and properties

Unter den verschiedenen additiven Fertigungsverfahren stellt das selektive Laserschmelzen (SLM) eine optimale Technologie für die Herstellung von metallischen Bauteilen mit komplexen Geometrien und hervorragenden Eigenschaften dar. SLM-Bauteile werden Schicht für Schicht mit hochenergetischen Laserstrahlen hergestellt, was das SLM flexibler als konventionelle Produktionstechnologien wie das Gießen macht. Die beim SLM auftretenden schnellen Aufheiz-/Kühlraten können zu deutlich unterschiedlichen Gefügen im Vergleich zu herkömmlichen Herstellungsverfahren führen. Die beim SLM entstehenden Hochtemperaturgradienten können sich weiterhin positiv auf die Gefügeentstehung (Phasenbildung, Morphologie, …) und damit auf die mechanischen Eigenschaften der SLM-Bauteile auswirken. Darüber hinaus können die mit SLM gefertigten Teile mit der Notwendigkeit einer minimalen Nachbearbeitung in den Einsatz genommen werden. Bisher wurden mehrere Studien zu den Parametern: Optimierung oder Verarbeitung von Verbundwerkstoffen mit fehlerfreien Teilen durchgeführt Die Scanstrategie hat dabei einen besonders großen Einfluss bei der Materialbearbeitung durch die additive Fertigung. Die Optimierung der Scanstrategie ist daher von zentraler Bedeutung für die Synthese von Materialien mit verbesserten physikalischen und mechanischen Eigenschaften. Diese Arbeit untersucht die Wirkung von vier verschiedenen Scanning-Strategien auf das Gefüge und das mechanische Verhalten von 316L Edelstahl, synthetisiert durch selektives Laserschmelzen (SLM). Die Ergebnisse deuten darauf hin, dass die Scanstrategie einen vernachlässigbaren Einfluss auf die Phasenbildung und die Art des Gefüges hat, die während der SLM-Verarbeitung entsteht: Austenit ist die einzige Phase, die sich bildet, und alle Proben weisen eine zelluläre Morphologie auf. Die Scanstrategie beeinflusst jedoch erheblich die charakteristische Größe von Zellen und Körnern, die wiederum der Hauptfaktor für die Festigkeit unter Zugbelastung zu sein scheint. Andererseits haben Eigenspannungen offenbar keinen Einfluss auf die quasi-statischen mechanischen Eigenschaften der Proben. Das mit einem Streifenmuster mit Konturstrategie hergestellte Material weist das feinste Gefüge und die beste Kombination mechanischer Eigenschaften auf: Streckgrenze und Bruchdehnung liegen bei 550 MPa und 1010 MPa und die plastische Verformung bei über 50 %. Ein weiterer wichtiger Aspekt für die Anwendung des mittels SLM synthetisierten 316L-Stahls ist seine thermische Stabilität. Daher wurde der Einfluss des Glühens bei verschiedenen Temperaturen (573, 873, 1273, 1373 und 1673 K) auf die Stabilität der Phasen, der Zusammensetzung und des Gefüges des 316L-Edelstahls untersucht, der unter Verwendung des Streifenmuster mit Konturstrategie hergestellt wurde. Darüber hinaus wurden die durch die Wärmebehandlung induzierten Veränderungen genutzt, um die entsprechenden Variationen der mechanischen Eigenschaften der Proben unter Zugbelastung zu verstehen. Das Glühen hat keinen Einfluss auf die Phasenbildung: Bei allen hier untersuchten Proben wird ein einphasiger Austenit beobachtet. Darüber hinaus ändert das Glühen nicht die zufällige kristallographische Orientierung, die im Material nach der Synthese beobachtet wird. Das komplexe zelluläre Gefüge mit feinen Subkornstrukturen, die für die as-SLM-Proben im Ausgangszustand charakteristisch sind, ist bis zu 873 K stabil. Die Zellgröße nimmt mit steigender Glühtemperatur zu, bis das zelluläre Gefüge bei hohen Temperaturen nicht mehr beobachtet werden kann (T ≥ 1273 K). Die Festigkeit der Proben nimmt mit steigender Glühtemperatur durch die mikrostrukturelle Vergröberung ab. Die ausgezeichnete Kombination von Festigkeit und Duktilität des Materials im Ausgangszustand ist auf das komplexe zelluläre Gefüge und die Subkörner sowie die Fehlausrichtung zwischen Körnern, Zellen, Zellwänden und Subkörnern zurückzuführen. Mit dem Ziel, das mechanische Verhalten des 316L-Stahls weiter zu verbessern, wird der Einfluss harter Partikel einer zweiten Phase auf das Gefüge und die damit verbundenen mechanischen Eigenschaften untersucht. Dazu wurde mittels SLM ein Verbund aus einer 316L-Stahlmatrix und 5 Vol.% CeO2-Partikeln hergestellt. Die SLM-Parameter, die zu einer fehlerfreien 316L-Matrix führen, sind für die Herstellung von 316L/CeO2-Verbundproben nicht geeignet. Hochdichte Verbundproben können jedoch durch sorgfältige Einstellung der Laserscangeschwindigkeit unter Beibehaltung der anderen Parameter prozessiert werden. Die Zugabe der CeO2-Verstärkung verändert die Phasenbildung nicht, beeinflusst aber das Gefüge des Verbundwerkstoffs, welches im Vergleich zum partikelfreien 316L-Material deutlich verfeinert ist. Das verfeinerte Gefüge bewirkt eine signifikante Verstärkung im Verbund, ohne die plastische Verformung zu beeinträchtigen. Die Analyse des Einflusses einer zweiten Phase wird fortgesetzt, indem untersucht wird, wie TiB2-Partikel das Gefüge und die mechanischen Eigenschaften eines 316L-Edelstahls beeinflussen, der durch selektives Laserschmelzen hergestellt wird. Das für die unverstärkte 316L-Matrix charakteristische komplexe zelluläre Gefüge mit feinen Subkörnern ist in allen Proben zu finden. Die Zugabe der TiB2-Partikel reduziert die Größe der Körner und Zellen erheblich. Darüber hinaus sind die TiB2-Partikel in der 316L-Matrix homogen dispergiert und bilden kreisförmige Ausscheidungen mit einer Größe von etwa 50-100 nm entlang der Korngrenzen. Diese mikrostrukturellen Merkmale führen zu einer signifikanten Verfestigung im Vergleich zu den unverstärkten 316L-Proben. Diese Ergebnisse belegen, dass SLM erfolgreich zur Synthese von Verbundwerkstoffen aus dem Edelstahl 316L mit herausragenden mechanischen Eigenschaften im Vergleich zu einer unverstärkten 316L-Stahlmatrix eingesetzt werden kann. Dies könnte dazu beitragen, den Einsatz von SLM bei der Herstellung von Stahlmatrix-Verbundwerkstoffen für die Automobilindustrie, die Luft- und Raumfahrt und zahlreiche andere Anwendungen zu erweitern.Among the different additive manufacturing processes, selective laser melting (SLM) represents an optimal choice for the fabrication of metallic components with complex geometries and superior properties. SLM parts are built layer-by-layer using high-energy laser beams, making SLM more flexible than conventional processing techniques, like casting. The fast heating/cooling rates occurring during SLM can result in remarkably different microstructures compared with conventional manufacturing processes. The high-temperature gradients characterising SLM can also have a positive effect on the microstructures and, in turn, on the mechanical properties of the SLM parts. Additionally, the SLM parts can be put into use with the necessity of minimal post-processing treatments. To date, a number of studies have been devoted to the parameters optimization or processing of composite materials with defect-free parts. The scanning strategy is one of the most influential parameters in materials processing by additive manufacturing. Optimization of the scanning strategy is thus of primary importance for the synthesis of materials with enhanced physical and mechanical properties. Accordingly, this thesis examines the effect of four different scanning strategies on the microstructure and mechanical behaviour of 316L stainless steel synthesized by selective laser melting (SLM). The results indicate that the scanning strategy has negligible influence on phase formation and the type of microstructure established during SLM processing: austenite is the only phase formed and all specimens display a cellular morphology. The scanning strategy, however, considerably affects the characteristic size of cells and grains that, in turn, appears to be the main factor determining the strength under tensile loading. On the other hand, residual stresses apparently have no influence on the quasi-static mechanical properties of the samples. The material fabricated using a stripe with contour strategy displays the finest microstructure and the best combination of mechanical properties: yield strength and ultimate tensile strength are about 550 and 1010 MPa and plastic deformation exceeds 50 %. Another important aspect for the application of 316L steel synthesized by SLM is its thermal stability. Therefore, the influence of annealing at different temperatures (573, 873, 1273, 1373 and 1673 K) on the stability of phases, composition and microstructure of 316L stainless steel fabricated by using the stripe with contour strategy has been investigated. Moreover, the changes induced by the heat treatment have been used to understand the corresponding variations of the mechanical properties of the specimens under tensile loading. Annealing has no effect on phase formation: a single-phase austenite is observed in all specimens investigated here. In addition, annealing does not change the random crystallographic orientation observed in the as-synthesized material. The complex cellular microstructure with fine subgrain structures characteristic of the as-SLM specimens is stable up to 873 K. The cell size increases with increasing annealing temperature until the cellular microstructure can no longer be observed at high temperatures (T ≥ 1273 K). The strength of the specimens decreases with increasing annealing temperature as a result of the microstructural coarsening. The excellent combination of strength and ductility exhibited by the as-synthesized material can be ascribed to the complex cellular microstructure and subgrains along with the misorientation between grains, cells, cell walls and subgrains. With the aim of further improving the mechanical behaviour of 316L steel, this works examines the effect of hard second-phase particles on microstructure and related mechanical properties. For this, a composite consisting of a 316L steel matrix and 5 vol.% CeO2 particles was fabricated by SLM. The SLM parameters leading to a defect-free 316L matrix are not suitable for the production of 316L/CeO2 composite specimens. However, highly-dense composite samples can be synthesized by carefully adjusting the laser scanning speed, while keeping the other parameters constant. The addition of the CeO2 reinforcement does not alter phase formation, but it affects the microstructure of the composite, which is significantly refined compared with the unreinforced 316L material. The refined microstructure induces significant strengthening in the composite without deteriorating the plastic deformation. The analysis of the effect of a second phase is continued by investigating how TiB2 particles influence the microstructure and mechanical properties of a 316L stainless steel synthesized by selective laser melting. The complex cellular microstructure with fine subgrains characteristic of the unreinforced 316L matrix is found in all samples. The addition of the TiB2 particles reduces significantly the sizes of the grains and cells. Furthermore, the TiB2 particles are homogeneously dispersed in the 316L matrix and they form circular precipitates with sizes around 50-100 nm along the grain boundaries. These microstructural features induce significant strengthening compared with the unreinforced 316L specimens. These findings prove that SLM can be successfully used to synthesize 316L stainless steel matrix composites with overall superior mechanical properties in comparison with the unreinforced 316L steel matrix. This might help to extend the use of SLM to fabricate steel matrix composites for automotive, aerospace and numerous other applications

Promoting Diversity in Academic Research Communities Through Multivariate Expert Recommendation

Expert recommendation is the process of identifying individuals who have the appropriate knowledge and skills to achieve a specific task. It has been widely used in the educational environment mainly in the hiring process, paper-reviewer assignment, and assembling conference program committees. In this research, we highlight the problem of diversity and fair representation of underrepresented groups in expertise recommendation, factors that current expertise recommendation systems rarely consider. We introduce a novel way to model experts in academia by considering demographic attributes in addition to skills. We use the h-index score to quantify skills for a researcher and we identify five demographic features with which to represent a researcher\u27s demographic profile. We highlight the importance of these features and their role in bias within the academic environment. We utilize these demographic features within an expert recommender system in academia to achieve demographic diversity and increase the exposure of the underrepresented groups using two approaches. In the first approach, we present three different algorithms for scholar recommendation: expertise-based, diversity-based, and a hybrid algorithm that uses a tuning parameter to calibrate the balance between expertise loss and diversity gain. To evaluate the ranking produced by these algorithms, we introduce a modified normalized Discounted Cumulative Gain (nDCG) version that supports multi-dimensional features, and we report diversity gain from each method. Our results show that we can achieve the best possible balance between diversity gain and expertise loss when the tuning parameter value is set around 0.4, giving nearly equal weight to both expertise and diversity. Finally, we explore diversity from the lens of the demographic parity and develop two algorithms to achieve a representative group that reflects the demographics of the recommendation pool. One is inspired by Hill Climbing, a mathematical optimization technique, wherein a solution is built gradually to the problem, and the other one is inspired by the problem of seat allocation in electoral voting systems. We evaluated these algorithms by comparing them to the hybrid algorithm from the previous approach. Our evaluation shows that both approaches provide a better diversity gain as compared to the hybrid algorithm. However, Hill Climbing Diversity is more effective when it comes to expertise savings with a statistically significant result, making it the preferred algorithm to achieve the goal of promoting diversity while maintaining expertise in an expert recommendation process

Animation of Z Specifications By Translation to Prolog

Yazılım geliştirebilmenin formal metodları o yazılım tanımlamasının geçerliliğine bağlıdır. Böyle bir tanımlama genelde 'Z' gibi bir formal dilde ifade edilir. Ancak, geçerli olması için, 'Z' tanımlaması test edilmeli, bunu yapabilmek için de animasyon yapılabilecek ve icra edilebilecek bir forma transfer edilebilmelidir. 'Z' tanımlamalarının animasyonları için kullanılan dillerden birisi Prolog'dur. Bu makalede 'Z' şemalarını Prolog'a çeviren teknikler açıklanmaktadır.Aym zamanda bu tür bir çevirmenin eksikleri ve belirsizlikleri üzerinde durulacaktır.Formal methods of software development rely on the validation of the specification of the software. Such specification is normally expressed in a formal language such as Z. However, in order to be validated the Z specification must be tested, and to achieve this it has to be transformed into a form that can be executed or animated. Prolog was one of the languages used for animation of Z specifications. This paper explains the techniques used for translating Z schemas into Prolog predicates. It also examines some of this translation shortcomings and unreliable features

Akaike Information Criterion to Select the Parametric Detection Function for Kernel Estimator Using Line Transect Data

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the resulting estimators comparing with some existing estimator, particularly the usual kernel estimator when the half normal model is use as a reference to select the smoothing parameter

Akaike Information Criterion to Select the Parametric Detection Function for Kernel Estimator Using Line Transect Data

Among different candidate parametric detection functions, it is suggested to use Akaike Information Criterion (AIC) to select the most appropriate one of them to fit line transect data. Four different detection functions are considered in this paper. Two of them are taken to satisfy the shoulder condition assumption and the other two estimators do not satisfy this condition. Once the appropriate detection function is determined, it also can be used to select the smoothing parameter of the nonparametric kernel estimator. For a wide range of target densities, a simulation results show the reasonable and good performances of the resulting estimators comparing with some existing estimator, particularly the usual kernel estimator when the half normal model is use as a reference to select the smoothing parameter

Channel, Phase Noise, and Frequency Offset in OFDM Systems: Joint Estimation, Data Detection, and Hybrid Cramer-Rao Lower Bound

Oscillator phase noise (PHN) and carrier frequency offset (CFO) can adversely impact the performance of orthogonal frequency division multiplexing (OFDM) systems, since they can result in inter carrier interference and rotation of the signal constellation. In this paper, we propose an expectation conditional maximization (ECM) based algorithm for joint estimation of channel, PHN, and CFO in OFDM systems. We present the signal model for the estimation problem and derive the hybrid Cramer-Rao lower bound (HCRB) for the joint estimation problem. Next, we propose an iterative receiver based on an extended Kalman filter for joint data detection and PHN tracking. Numerical results show that, compared to existing algorithms, the performance of the proposed ECM-based estimator is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high signal-to-noise ratio (SNR). In addition, the combined estimation algorithm and iterative receiver are more computationally efficient than existing algorithms and result in improved average uncoded and coded bit error rate (BER) performance