Miracle-dz/UniFAR-FTUs huggingface dataset:
Prozessorientierte Analyse von konstruktiven Problemlöseprozessen auf Basis von Eye-Tracking-Aufnahmen

Zusammenfassung Konstruktives Problemlosen ist eine spezifische Form des Problemlosens und eine wichtige handlungsorientierte Lernmethode im allgemeinbildenden Technikunterricht. Die damit verbundenen individuellen konstruktiven Problemlosungsprozesse sind auf der Ebene von Schulerinnen und Schulern empirisch schwer zu erfassen und bisher so gut wie unerforscht. Mithilfe mobiler Eye-Tracking-Brillen lassen sich sowohl Daten uber die Informationsaufnahme als auch uber die ausgefuhrten Handlungen eines Probanden im Detail erfassen. In Anlehnung an die Informationsverarbeitende ACT-R Theorie von J. R. Anderson und unter der Berucksichtigung von Konstruktionsphasen wurde eine neue Analysemethodik entwickelt, mit der die Losungsprozesse von 14 Schulern analysiert und die drei Losungsstrategien: Praktisch-orientierte, theoretisch-orientierte sowie Mischstrategie qualitativ ermittelt wurden. Schlusselworter: Konstruieren, Problemlosen, Losungsstrategien, Eye-Tracking-Aufnahmen ___________ Process-oriented analysis of engineering-design problem solving processes based on the eye-tracking recording Abstract Engineering-design problem solving is a specific form of problem solving and an important action-oriented learning method in technology education in general schools. The individual, engineering-design problem-solving processes at the level of pupils are empirically difficult to explore and therefore they are so far almost not researched. Using mobile eye-tracking glasses the data about the perception of information as well as the actions of a subject can be captured. Following the ACT-R theory from J. R. Anderson and considering engineering design phases, a new analytical methodology was developed. The method was used to analyze the solution processes of 14 students and qualitatively determine the three solution strategies: practical-oriented, theoretical-oriented and mixed strategy. Keywords: Engineering-design problems, problem solving, solving strategy, eye-tracking recordings
Metallorganiska ramverksföreningar för koldioxidadsorption

Metal organic frameworks for carbon dioxide adsorption Metal organic frameworks (MOFs) are porous materials consisting of coordination complexes linked together by organic linkers. These materials have shown potential for carbon dioxide separation and this project aims at studying two MOFs, ZIF-8 and MOF-801. They were both synthesized successfully and tested in carbon dioxide adsorption experiments. An attempt was also made to synthesize a new MOF with organic linkers, that possibly can be made from renewable starting material. The characterization indicates that the synthesis of the new MOF made from cobalt and ferulic acid was unsuccessful. It is however likely that an amorphous coordination complex was formed and perhaps a MOF could be created by having different conditions during the synthesis. Both MOF-801 and ZIF-8 were used in adsorption experiments in order to find suitable experimental conditions for measuring CO2-adsorption on MOFs. Through MATLAB-simulations of adsorption with CO2 and N2 on ZIF-8 it was shown using data from literature that N2 competes with CO2 for the binding sites on the MOF. Even if the selectivity for CO2-adsorption is higher, this is going to be a problem for flue gases containing large concentrations of N2. This was confirmed by adsorption measurements on MOF-801 which showed an adsorption heat flow when the flow of CO2 was turned on, and a desorption heat flow immediately after the CO2 was turned off. The enthalpy of adsorption for CO2 on MOF-801 was calculated from the adsorption measurement as -13,1 kJ/mol. This explains the immediate desorption which depends on the low binding energy. The report is written in Swedish.
Do Grammatical and Cognitive Phenotypes Illuminate Each Other? Reflections on Un-Cartesian Linguistics and the Language-ToM Interface

How language and thought interact is a hot topic of debate, and one that is refreshingly revisited by Hinzen in his paper entitled ‘Reference across pathologies: A new linguistic lens on disorders of thought’. The work is situated within the ‘un-Cartesian’ linguistics research program, which seeks to illustrate that the organizational principles of grammar directly configure human-specific thought (Hinzen 2007; Hinzen 2012; 2013; a.o.). The un-Cartesian program may at first glance seem reminiscent of other approaches arguing for an influence of language on thought, however it differs from them in important ways. In contrast to linguistic determinism, for instance, it posits “(n)o unidirectional causal arrow lead(ing) from language to thought” (Section 2.1). In contrast to NeoWhorfianism, un-Cartesian linguistics is concerned with the underlying grammatical principles common to all languages, thus cross-linguistic variations are not expected to give rise to cognitive variations. To sum up, for Hinzen, thinking is ‘languaging’ (Section 2.1) and any human language should arise together with human concepts, such as reference and propositional meaning. In light of this, Hinzen predicts both interand intra-species variations: These concepts should be absent from non-linguistic primates and, crucially, also be affected in instances of grammatical impairments within humans. Grammar, under this un-Cartesian lens, now becomes clinically relevant for cognitive disorders. In this contribution, I will focus on a particular aspect of cognition and its relation to language, namely the ability to think about the thoughts of others, also known as theory of mind (ToM). ToM has been centre-stage of much psycholinguistic research trying to shed light on the role of language in conceptual reasoning (de Villiers and de Villiers 2000; Carruthers 2002). Hinzen remarks: “As a psychological construct, ToM remains described by its broad
First combined search for neutrino point-sources in the southern sky with the ANTARES and IceCube neutrino telescopes

A search for cosmic neutrino point-like sources using the ANTARES and IceCube neutrino telescopes over the Southern Hemisphere is presented. The ANTARES data were collected between January 2007 and December 2012, whereas the IceCube data ranges from April 2008 to May 2011. An unbinned maximum likelihood method is used to search for a localized excess of muon events in the southern sky assuming an E − 2 neutrino source spectrum. A search over a pre-selected list of candidate sources has also been carried out for different source assumptions: spectral indices of 2.0 and 2.5, and energy cutoffs of 1 PeV, 300 TeV and 100 TeV. No significant excess over the background has been found, and upper limits for the candidate sources are presented compared to the individual experiments.
Design and Experimental Study of Dragonfly-Inspired Flexible Blade to Improve Safety of Drones

A flexible blade that is easy to fabricate and repair is presented: It has a low impact load when colliding with obstacles, and can generate enough thrust for drone flight. The flexible blade has a camber structure that mimics the feature of dragonflies to increase wing stiffness. It makes the blade's deformation decline when it receives a lift force and drag force. A commercially available drone that conformed to standards was used to design, fabricate, and test the flexible blade. The flexible blade consists of a pivot column made by three-dimensional printer and a polyethylene film. The design variables were defined as values with thrust and efficiency that were determined to be similar to those of the original blade through experiments. Experiments for safety verification were conducted by comparing the impact and sharpness of the original and the flexible blades. Experimental results show that the flexible blade's impact force is approximately a tenth of the original blade's impact force, and only the original blade damaged a 100-μm film obstacle. In general terms, the suggested flexible blade is safer and more economical than a plastic blade, in addition to having performance close to that of the original blade during flight.
Preparation of Out-of-School Learning Environment based on Science, Technology, Engineering, and Mathematics Education and Investigating its Effects

This research aimed at preparing an out-of-school Science, Technology, Engineering, and Mathematics (STEM) education program for secondary school students and investigating the effects of the program on studentsâ€™ interest in STEM fields. As part of this investigation, this study sought the studentsâ€™ awareness of a career in these fields as well as their comments on the process and the contribution of the process to the 21st century skills. The research was conducted with a mixed methods research design. The participants of the research consisted of 24 secondary school students. The data were collected through STEM career interest survey, STEM perception test, participantsâ€™ STEM diary, observation, and field notes. The studyâ€™s out-of-school STEM education program lasted 8 days. This studyâ€™s findings include students had an increased awareness and perception of building a career in the fields of STEM. It was confirmed that students had fun during the activities, and during the entire process, they made positive comments. Implications from this research highlight how this type of activity may improve the 21st century skills of the students.
Carbon and oxygen isotope composition of organic compounds in the phloem sap provides a short‐term measure for stomatal conductance of European beech (Fagus sylvatica L.)

At eight different dates during the 2000 growing season, d d d 13 C and d 18 O were determined in the phloem of adult beech trees growing in natural beech stands in south-west Germany differing in stand density and local climate. In addition, stand transpiration, precipitation, photosynthetic active radiation, relative air humidity, water pressure deficit of the air, air and soil temperature, soil water potential, and sugar concentration of the phloem sap were determined directly and evaporation and canopy stomatal conductance were modelled. All parameters were related to d 13 C. The study aimed to identify the time integral within which the d d d 13 C of organic compounds transported in the phloem is an indicative measure of these environmental influences. d 13 C of soluble carbon transported in the phloem was well correlated with mean stomatal conductance in a two-day integral prior to phloem sampling but did not depend on either light intensity or soil water availability. A strong positive relationship between d 13 C and d 18 O pointed to observed 13
Wind turbine speed control of a contactless piezoelectric wind energy harvester

ABSTRACT Wind turbine control is an important task to make the electricity generation secure in terms of energy demand and machine safety. It also yields to control the desired power level and optimized energy because of the assignment of turbine speed. The contactless piezoelectric wind energy harvester (CPWEH) used in this study has three piezoelectric layers located around the shaft with 120 degrees apart and they are buckled by the magnetic force without any physical contact. The superiority of this device is to generate energy for low wind speeds such as 1.5 m/s. However, for high speeds, high total harmonic distortions (THDs) govern the waveforms, thus controlling the turbine speed becomes necessary for optimizing the output power. Encouraged by this, a small low inertia dc generator is coupled with the wind turbine, and the generator terminals are connected to a resistor through a power switch to generate a braking torque that opposes to wind speed direction. By controlling the switch properly, turbine speed is ensured to remain within a certain band, which accordingly prevents the turbine from rotating very fast at damaging wind speeds. Several experiments are performed on the developed CPWEH with/without the presented control scheme which prove the existence of promising performance of our proposal.
Improve angular resolution for sparse-view CT with residual convolutional neural network

Sparse-view CT imaging has been a hot topic in the medical imaging field. By decreasing the number of views, dose delivered to patients can be significantly reduced. However, sparse-view CT reconstruction is an illposed problem. Serious streaking artifacts occur if reconstructed with analytical reconstruction methods. To solve this problem, many researches have been carried out to optimize in the Bayesian framework based on compressed sensing, such as applying total variation (TV) constraint. However, TV or other regularized iterative reconstruction methods are time consuming due to iterative process needed. In this work, we proposed a method of angular resolution recovery in projection domain based on deep residual convolutional neural network (CNN) so that projections at unmeasured views can be estimated accurately. We validated our method by a disjointed data set new to trained networks. With recovered projections, reconstructed images have little streaking artifacts. Details corrupted due to sparse view are recovered. This deep learning based sinogram recovery can be generalized to more data insufficient situations.
Visualization in a Climate Computing Centre

The DKRZ’s visualization server is a heterogeneous Linux cluster, currently consisting of 10 state of the art visualization nodes equipped with 96 -256 GB RAM and high end NVidia GPUs. Since the parallel file system of the DKRZ’s supercomputer is directly mounted over a powerful network, the model data can directly be analyzed and visualized. VirtualGL and TurboVNC are used for utilizing the server’s GPUs for 3D rendering, while the TurboVNC client on the user’s local computer continuously displays the resulting video stream. By using this central visualization server instead of a local computer, three main benefits are achieved:
Real-Time Detection of Interharmonics and Harmonics of AC Electric Arc Furnaces on GPU Framework

In this paper, a method based on the multiple synchronous reference frame analysis is recommended and implemented to detect time-varying harmonics and interharmonics of rapidly fluctuating asymmetrical industrial loads. The experimental work has been carried out on a typical three-phase alternating current arc furnace installation. In the recommended method, the reference frame is rotated in both directions at speeds corresponding to the positive and negative sequences of all harmonics and all interharmonics 5 Hz apart. To extract the direct current components of the transformed d–q quantities, a low-pass filter is employed. In order to keep the delay of the filter at zero frequency less than a few ms, Kalman estimation technique has been used. Back transformation is then applied for each harmonic and interharmonic component to obtain their positive- and negative-sequences of the associated harmonic and interharmonic in the actual line current waveforms. Parallel computing technique has been applied for the real-time detection of both the phase and the amplitude of all harmonics and interharmonics. This is achieved on NVDIA Jetson TX1 graphics processing unit framework for a sample industrial plant. The developed system is shown to be useful for fast and accurate generation of reference signals for the controllers of the advanced technology power conditioning systems which successfully compensates interharmonics, harmonics, and flicker of the rapidly fluctuating nonlinear industrial loads.
Comparative Analysis of Methodological Trends in the Management of Software Projects: Identification of the Main Variables

Nowadays, there are many methodological proposals that support the various aspects of software development projects. In general terms, there are two big identifiable trends: traditional and agile. In the first instance, traditional methods are those characterized by privileging detailed planning work to ensure the quality of the final product. On the other hand, agile methodologies put prediction aside and open a space to changes in planning. This article presents the results obtained from the application of a comparative analysis to 12 methodologies for software projects management, and from 149 software development companies surveyed, leading to identify, from a theoretical experimental model, the variables that generate the greatest impact on the success of this type of projects. The importance of studying this topic resided in the impact that the correct application of a management methodology has on the results of a project and thus on its success. Regardless of the methodology used, they all propose a series of common processes, considered good practices, which allow achieving the outlined goals.
Automated Bug Assignment in Software Maintenance Using Graph Databases

Processes involved in maintaining a system play a crucial role in enhancing customer satisfaction and longevity of the system. Maintenance engineers are the most critical resources in Software Maintenance. They play a significant role in fixing bugs and ensuring the normal functioning of systems. Software maintenance is a tedious task for novice engineers who are new to the system domain. The lack of up-to-date documentation makes system comprehension more challenging for inexperienced engineers. Assignment of high priority bugs to novice engineers may lead to inappropriate fixes and delay in the revival of an impacted system. Such issues may degrade customer satisfaction and also poor fixes can have a severe impact on the functioning of the system at a later stage. Our research is focussed on identification of engineers with the right level of experience to fix a given bug. We have used the concept of page ranking and graph databases to compute the importance of bugs and assignees in a graph. A newly reported bug will be scored and matched with bugs that have a similar score in the graph database. Assignees who have fixed a bug that closely maps the score of the reported bug will be assigned the task of fixing the bug. We have implemented this methodology using bug reports from QT framework on neo4j graph database. Our results are promising and will definitely pave way for a new bug assignment strategy in software maintenance.
A robust abnormal detection method for complex structures in UAV images for autonomous O and M system

Abnormal detection using cameras in UAV platform become more and more popular for operation and maintenance, in particularly for large-scale constructions like building, bridge etc. UAV-used detection system could be expected to reduce the cost, ensure the safety and provide stability for O&M on infrastructures. As imaging technology, Image registration and change detection method plays a central role in an abnormal detection system. Two key factors in this respect are needed to be improved. Firstly, due to the near-distance photographing and complex surface composition of structures, a robust plane-level matching method is significant to make high-precision image registration for the change detection. However, as many part of the surface of structures do not have enough feature points, it seems difficult to make a plane matching using homography transformation based on the correspondence feature points. Secondly, plane-level change detection have much noise in the border area because of homography transfer deviation and information redundancy. In order to solve these two problems, a robust method based on a combination of edge detection and geometry constraint is proposed to make plane-level registration and change detection noise reduction. For registration, making good use of pixel information in the border area, we expand the border area to extract each plane regardless of the number of feature points. And for noise reduction, we excise the border information to reduce the effect of information redundancy. Validation experiments were performed with several sets of image pairs. We succeed to extract planes in images with a 92% coverage and 91% precision while the number of noise is reduced as 30% as before for average. The evaluation shows that our proposed method is of high precision with high robustness for abnormal detection system.
Effect of registration on performance of construction subcontractors in Singapore

The construction industries of many countries rely heavily on subcontracting. As a result, the quality of subcontractors is important as it has a direct bearing on the performance of the main contractor on projects. A large proportion of construction work in Singapore is subcontracted. Despite the well‐known and widely regretted deficiencies in the traditional subcontracting system, only recently have attempts been made to reform it. The most significant of these efforts is the Singapore List of Trade Subcontractors (SLOTS). This study sought to investigate whether or not the performance of subcontractors has been improved following the introduction of the SLOTS scheme. The research was based on a survey of project managers of main contractors. A major finding was that the SLOTS‐registered contractors were perceived to perform better than nonregistered ones. Suggestions for improving the SLOTS scheme are offered in this paper.
Multi-objective imperfect preventive maintenance optimisation with NSGA-II

Maintenance optimisation is a multi-objective problem in nature, and it usually needs to achieve a trade-off among the conflicting objectives. In this study, a multi-objective maintenance optimisation (MOMO) model is proposed for electromechanical products, where both the soft failure and hard failure are considered, and minimal repair is performed accordingly. Imperfect preventive maintenance (IPM) is carried out during the preplanned periods, and modelled with a hybrid failure rate model and quasi-renewal coefficient. The initial IPM period and the total number of IPM periods are set as the decision variables, and a MOMO model is developed to optimise the availability and cost rate concurrently. The fast elitist non-dominated sorting genetic algorithm (NSGA-II) is applied to solve the model. A case study of wind turbine’s gearbox is provided. The results show that there are 30 optimal solutions in the MOMO’s Pareto frontier that can maximise the availability and minimise the cost rate simultaneously. Compared with the single-objective maintenance optimisation, it can provide more choices for maintenance decision, and better satisfy the resource constraints and the customer’s preference. The results of the sensitivity analysis show that the effect of age reduction factor on optimisation results is greater than that of failure rate increase factor.
Multi Simulation Platform for Time Domain Diffuse Optical Tomography: An Application to a Compact Hand-Held Reflectance Probe

Time Domain Diffuse Optical Tomography (TD-DOT) enables a full 3D reconstruction of the optical properties of tissue, and could be used for non-invasive and cost-effective in-depth body exploration (e.g., thyroid and breast imaging). Performance quantification is crucial for comparing results coming from different implementations of this technique. A general-purpose simulation platform for TD-DOT clinical systems was developed with a focus on performance assessment through meaningful figures of merit. The platform was employed for assessing the feasibility and characterizing a compact hand-held probe for breast imaging and characterization in reflectance geometry. Important parameters such as hardware gating of the detector, photon count rate and inclusion position were investigated. Results indicate a reduced error (<10%) on the absorption coefficient quantification of a simulated inclusion up to 2-cm depth if a photon count rate ≥ 106 counts per second is used along with a good localization (error < 1 mm down to 25 mm-depth).