AN ANALYSIS OF THE STUDENTS’ CONVERSATION PERFORMANCE OF EIGHT GRADE STUDENTS OF SMPS KATOLIK AURORA KEFAMENANU

This study concerned speaking, especially in the English conversation. It aims at knowing the students’ speaking English ability in conversation and the students’ difficulties in English conversation. The population of this study is the second-year students of SMPS Katolik Aurora, Kefamenanu and the sample of this study is 20 students. The research design uses a descriptive quantitative method to provide a clear description of students’ speaking ability in conversation. The instrument of this research is a conversation test for students to perform. The result shows that the students’ speaking English ability in conversation is good because the average score is 74.89. The students’ difficulties in English conversation in terms of; vocabulary is 85.25 %, pronunciation is 74 %, fluency is 73.5%, and grammar is 72 %

An Impacting Descent Probe for Europa and the other Galilean Moons of Jupiter

We present a study of an impacting descent probe that increases the science return of spacecraft orbiting or passing an atmosphere-less planetary body of the solar system, such as the Galilean moons of Jupiter. The descent probe is a carry-on small spacecraft (< 100 kg), to be deployed by the mother spacecraft, that brings itself onto a collisional trajectory with the targeted planetary body in a simple manner. A possible science payload includes instruments for surface imaging, characterisation of the neutral exosphere, and magnetic field and plasma measurement near the target body down to very low-altitudes (~1 km), during the probe's fast (~km/s) descent to the surface until impact. The science goals and the concept of operation are discussed with particular reference to Europa, including options for flying through water plumes and after-impact retrieval of very-low altitude science data. All in all, it is demonstrated how the descent probe has the potential to provide a high science return to a mission at a low extra level of complexity, engineering effort, and risk. This study builds upon earlier studies for a Callisto Descent Probe (CDP) for the former Europa-Jupiter System Mission (EJSM) of ESA and NASA, and extends them with a detailed assessment of a descent probe designed to be an additional science payload for the NASA Europa Mission.Comment: 34 pages, 11 figure

Towards non-parametric fiber-specific T1T_1 relaxometry in the human brain

Purpose: To estimate fiber-specific $T_1$ values, i.e. proxies for myelin content, in heterogeneous brain tissue. Methods: A diffusion-$T_1$ correlation experiment was carried out on an in vivo human brain using tensor-valued diffusion encoding and multiple repetition times. The acquired data was inverted using a Monte-Carlo inversion algorithm that retrieves non-parametric distributions $\mathcal{P}(\mathbf{D},R_1)$ of diffusion tensors and longitudinal relaxation rates $R_1 = 1/T_1$. Orientation distribution functions (ODFs) of the highly anisotropic components of $\mathcal{P}(\mathbf{D},R_1)$ were defined to visualize orientation-specific diffusion-relaxation properties. Finally, Monte-Carlo density-peak clustering (MC-DPC) was performed to quantify fiber-specific features and investigate microstructural differences between white-matter fiber bundles. Results: Parameter maps corresponding to $\mathcal{P}(\mathbf{D},R_1)$'s statistical descriptors were obtained, exhibiting the expected $R_1$ contrast between brain-tissue types. Our ODFs recovered local orientations consistent with the known anatomy and indicated possible differences in $T_1$ relaxation between major fiber bundles. These differences, confirmed by MC-DPC, were in qualitative agreement with previous model-based works but seem biased by the limitations of our current experimental setup. Conclusions: Our Monte-Carlo framework enables the non-parametric estimation of fiber-specific diffusion-$T_1$ features, thereby showing potential for characterizing developmental or pathological changes in $T_1$ within a given fiber bundle, and for investigating inter-bundle $T_1$ differences.Comment: 11 pages, 6 figures, submitted to Magnetic Resonance in Medicine (MRM) on the 14th of June 202

Economic Implications of Additive Manufacturing and the Contribution of MIS

This is the author accepted manuscript. The final version is available from Springer at http://link.springer.com/article/10.1007%2Fs12599-015-0374-4

Real-Time Big Data Analytics in Smart Cities from LoRa-Based IoT Networks

The currently burst of the Internet of Things (IoT) tech-nologies implies the emergence of new lines of investigation regarding not only to hardware and protocols but also to new methods of pro-duced data analysis satisfying the IoT environment constraints: a real-time and a big data approach. The Real-time restriction is about the continuous generation of data provided by the endpoints connected to an IoT network; due to the connection and scaling capabilities of an IoT network, the amount of data to process is so high that Big data tech-niques become essential. In this article, we present a system consisting of two main modules. In one hand, the infrastructure, a complete LoRa based network designed, tested and deployment in the Pablo de Olavide University and, on the other side, the analytics, a big data streaming sys-tem that processes the inputs produced by the network to obtain useful, valid and hidden information.Ministerio de Economía y Competitividad TIN2017-88209-C2-1-

Prototype of the gas chromatograph-mass spectrometer to investigate volatile species in the lunar soil for the Luna-Resurs mission

In preparation for the Russian Luna-Resurs mission we combined our compact time-of-flight mass spectrometer (TOF-MS) with a chemical pre-separation of the species by gas chromatography (GC). Coupled measurements with both instruments were successfully performed with the prototype of the mass spectrometer and a flight-like gas chromatograph. The system was tested with two test gas mixtures, a mixture of hydrocarbons and a mixture of noble gases. Due to its capability to record mass spectra over the full mass range at once with high sensitivity and a dynamic range of up to 10(6) within 1 s, the TOF-MS system is a valuable extension of the GC analytical system. Based on the measurements with calibration gases performed with the combined GC-MS prototype and under assumption of mean characteristics for the Moon's regolith, the detection limit for volatile species in a soil sample is estimated to 2.10(-10) by mass for hydrocarbons and 2.10(-9) by mass for noble gases. (C) 2015 Elsevier Ltd. All rights reserved

Digitalized manufacturing logistics in engineer-to-order operations

This is a post-peer-review, pre-copyedit version of an article published in Advances in Production Management Systems. Production Management for the Factory of the Future. APMS 2019. IFIP Advances in Information and Communication Technology, vol. 566. The final authenticated version is available online at: https://doi.org/10.1007/978-3-030-30000-5_71. The high complexity in Engineer-To-Order (ETO) operations causes major challenges for manufacturing logistics, especially in complex ETO, i.e. one-of-a-kind production. Increased digitalization of manufacturing logistics processes and activities can facilitate more efficient coordination of the material and information flows for manufacturing operations in general. However, it is not clear how to do this in the ETO environment, where products are highly customized and production is non-repetitive. This paper aims to investigate the challenges related to manufacturing logistics in ETO and how digital technologies can be applied to address them. Through a case study of a Norwegian shipyard, four main challenges related to manufacturing logistics are identified. Further, by reviewing recent literature on ETO and digitalization, the paper identifies specific applications of digital technologies in ETO manufacturing. Finally, by linking manufacturing logistics challenges to digitalization, the paper suggests four main features of digitalized manufacturing logistics in ETO: (i) seamless, digitalized information flow, (ii) identification and interconnectivity, (iii) digitalized operator support, and (iv) automated and autonomous material flow. Thus, the paper provides valuable insights into how ETO companies can move towards digitalized manufacturing logistics

Digital Work Design

Erworben im Rahmen der Schweizer Nationallizenzen (http://www.nationallizenzen.ch)More and more academic studies and practitioner reports claim that human work is increasingly disrupted or even determined by information and communication technology (ICT) (Cascio and Montealegre 2016). This will make a considerable share of jobs currently performed by humans susceptible to automation (e.g., Frey and Osborne 2017; Manyika et al. 2017). These reports often sketch a picture of ‘machines taking over’ traditional domains like manufacturing, while ICT advances and capabilities seem to decide companies’ fate. Consequently, ICT is often put at the core of innovative efforts. While this applies to nearly all areas of workplace design, a recent popular example of increasing technology centricity is ‘Industry 4.0’, which is often delineated as ‘machines talking to computers’

Managing changes initiated by industrial big data technologies : a technochange management model

With the adoption of Internet of Things and advanced data analytical technologies in manufacturing firms, the industrial sector has launched an evolutionary journey toward the 4th industrial revolution, or so called Industry 4.0. Industrial big data is a core component to realize the vision of Industry 4.0. However, the implementation and usage of industrial big data tools in manufacturing firms will not merely be a technical endeavor, but can also lead to a thorough management reform. By means of a comprehensive review of literature related to Industry 4.0, smart manufacturing, industrial big data, information systems (IS) and technochange management, this paper aims to analyze potential changes triggered by the application of industrial big data in manufacturing firms, from technological, individual and organizational perspectives. Furthermore, in order to drive these changes more effectively and eliminate potential resistance, a conceptual technochange management model was developed and proposed. Drawn upon theories reported in literature of IS technochange management, this model proposed four types of interventions that can be used to copy with changes initiated by industrial big data technologies, including human process intervention, techno-structural intervention, human resources management intervention and strategic intervention. This model will be of interests and value to practitioners and researchers concerned with business reforms triggered by Industry 4.0 in general and by industrial big data technologies in particular