Search results for: Michael Alexander Rubhausen
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 923

Search results for: Michael Alexander Rubhausen

683 Spectral Anomaly Detection and Clustering in Radiological Search

Authors: Thomas L. McCullough, John D. Hague, Marylesa M. Howard, Matthew K. Kiser, Michael A. Mazur, Lance K. McLean, Johanna L. Turk

Abstract:

Radiological search and mapping depends on the successful recognition of anomalies in large data sets which contain varied and dynamic backgrounds. We present a new algorithmic approach for real-time anomaly detection which is resistant to common detector imperfections, avoids the limitations of a source template library and provides immediate, and easily interpretable, user feedback. This algorithm is based on a continuous wavelet transform for variance reduction and evaluates the deviation between a foreground measurement and a local background expectation using methods from linear algebra. We also present a technique for recognizing and visualizing spectrally similar clusters of data. This technique uses Laplacian Eigenmap Manifold Learning to perform dimensional reduction which preserves the geometric "closeness" of the data while maintaining sensitivity to outlying data. We illustrate the utility of both techniques on real-world data sets.

Keywords: radiological search, radiological mapping, radioactivity, radiation protection

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682 Research and Innovation Centre

Authors: Krasimir Ivanov, Tonyo Tonev, Nguyen Nguyen, Alexander Peltekov, Anyo Mitkov

Abstract:

Maize is among the most economically important crops and at the same time one of the most sensitive to soil deficiency in zinc. In this paper, the impact of the foliar zinc application in the form of zinc hydroxy nitrate suspension on the micro and macro elements partitioning in maize leaves and grain was studied during spring maize season, 2017. The impact of the foliar zinc fertilization on the grain yield and quality was estimated too. The experiment was performed by the randomized block design with 8 variants in 3 replications. Seven suspension solutions whit different Zn concentration were used, including ZnO suspension and zinc hydroxyl nitrate alone or nixed with other nutrients. Fertilization and irrigation were the same for all variants. The Zn content and the content of selected micro (Cu, Fe) and macro (Ca, Mg, P and K) elements in maize leaves were determined two weeks after the first spraying (5-6 sheets), two weeks after the second spraying (9-10 sheets) and after harvesting. It was concluded that the synthesized zinc hydroxy nitrate demonstrates potential as the long-term foliar fertilizer. A significant (p < 0.05) effect of zinc accumulation in maize leaves by foliar zinc application during the first growth stage was found, followed by its reutilization to other plants organs during the second growth stage. Significant export of Cu, P, and K from lower and middle leaves was observed. The content of Ca and Mg remains constant in the whole longevity period, while the content of Fe decreases sharply.

Keywords: foliar fertilization, zinc hydroxy nitrate, maize, zinc

Procedia PDF Downloads 134
681 Performance of Neural Networks vs. Radial Basis Functions When Forming a Metamodel for Residential Buildings

Authors: Philip Symonds, Jon Taylor, Zaid Chalabi, Michael Davies

Abstract:

With the world climate projected to warm and major cities in developing countries becoming increasingly populated and polluted, governments are tasked with the problem of overheating and air quality in residential buildings. This paper presents the development of an adaptable model of these risks. Simulations are performed using the EnergyPlus building physics software. An accurate metamodel is formed by randomly sampling building input parameters and training on the outputs of EnergyPlus simulations. Metamodels are used to vastly reduce the amount of computation time required when performing optimisation and sensitivity analyses. Neural Networks (NNs) are compared to a Radial Basis Function (RBF) algorithm when forming a metamodel. These techniques were implemented using the PyBrain and scikit-learn python libraries, respectively. NNs are shown to perform around 15% better than RBFs when estimating overheating and air pollution metrics modelled by EnergyPlus.

Keywords: neural networks, radial basis functions, metamodelling, python machine learning libraries

Procedia PDF Downloads 419
680 Experimental Investigation of Cold-Formed Steel-Timber Board Composite Floor Systems

Authors: Samar Raffoul, Martin Heywood, Dimitrios Moutaftsis, Michael Rowell

Abstract:

This paper comprises an experimental investigation into the structural performance of cold formed steel (CFS) and timber board composite floor systems. The tests include a series of small-scale pushout tests and full-scale bending tests carried out using a refined loading system to simulate uniformly distributed constant load. The influence of connection details (screw spacing and adhesives) on floor performance was investigated. The results are then compared to predictions from relevant existing models for composite floor systems. The results of this research demonstrate the significant benefits of considering the composite action of the boards in floor design. Depending on connection detail, an increase in flexural stiffness of up to 40% was observed in the floor system, when compared to designing joists individually.

Keywords: cold formed steel joists, composite action, flooring systems, shear connection

Procedia PDF Downloads 107
679 Environmental Pollution and Health Risks of Residents Living near Ewekoro Cement Factory, Ewekoro, Nigeria

Authors: Michael Ajide Oyinloye

Abstract:

The natural environment is made up of air, water and soil. The release of emission of industrial waste into anyone of the components of the environment causes pollution. Industrial pollution significantly threatens the inherent right of people, to the enjoyment of a safe and secure environment. The aim of this paper is to assess the effect of environmental pollution and health risks of residents living near Ewekoro Cement factory. The research made use of IKONOS imagery for Geographical Information System (GIS) to buffer and extract buildings that are less than 1 km to the plant, within 1 km to 5 km and above 5 km to the factory. Also, a questionnaire was used to elicit information on the socio-economic factors, the effect of environmental pollution on residents and measures adopted to control industrial pollution on the residents. Findings show that most buildings that between less than 1 km and 1 km to 5 km to the factory have high health risk in the study area. The study recommended total relocation for the residents of the study area to reduce risk health problems.

Keywords: environmental pollution, health risk, GIS, satellite imagery, ewekoro

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678 Optimization of Technical and Technological Solutions for the Development of Offshore Hydrocarbon Fields in the Kaliningrad Region

Authors: Pavel Shcherban, Viktoria Ivanova, Alexander Neprokin, Vladislav Golovanov

Abstract:

Currently, LLC «Lukoil-Kaliningradmorneft» is implementing a comprehensive program for the development of offshore fields of the Kaliningrad region. This is largely associated with the depletion of the resource base of land in the region, as well as the positive results of geological investigation surrounding the Baltic Sea area and the data on the volume of hydrocarbon recovery from a single offshore field are working on the Kaliningrad region – D-6 «Kravtsovskoye».The article analyzes the main stages of the LLC «Lukoil-Kaliningradmorneft»’s development program for the development of the hydrocarbon resources of the region's shelf and suggests an optimization algorithm that allows managing a multi-criteria process of development of shelf deposits. The algorithm is formed on the basis of the problem of sequential decision making, which is a section of dynamic programming. Application of the algorithm during the consolidation of the initial data, the elaboration of project documentation, the further exploration and development of offshore fields will allow to optimize the complex of technical and technological solutions and increase the economic efficiency of the field development project implemented by LLC «Lukoil-Kaliningradmorneft».

Keywords: offshore fields of hydrocarbons of the Baltic Sea, development of offshore oil and gas fields, optimization of the field development scheme, solution of multicriteria tasks in oil and gas complex, quality management in oil and gas complex

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677 Dynamics of Museum Visitors’ Experiences Studies: A Bibliometric Analysis

Authors: Tesfaye Fentaw Nigatu, Alexander Trupp, Teh Pek Yen

Abstract:

Research on museums and the experiences of visitors has flourished in recent years, especially after museums became centers of edutainment beyond preserving heritage resources. This paper aims to comprehensively understand the changes, continuities, and future research development directions of museum visitors’ experiences. To identify current research trends, the paper summarizes and analyses research article publications from 1986 to 2023 on museum visitors' experiences. Bibliometric analysis software VOSviewer and Harzing POP (Publish or Perish) were used to analyze 407 academic articles. The articles were generated from the Scopus database. The study attempted to map new insights for future scholars and academics to expand the scope of museum visitors’ experience studies by analyzing keywords, citation patterns, influential articles in the field, publication trends, collaborations between authors, institutions, and clusters of highly cited articles. Accessibility to museums, social media usage within museums, aesthetics in museum settings, mixed reality experiences, sustainability issues, and emotions have emerged as key research areas in the study of museum visitors' experiences. The results benefit stakeholders and researchers in advancing the collective progress of considering recent research trends to stay informed about the latest developments and breakthroughs in the global academic landscape and visitors’ experiences development in the museum.

Keywords: bibliometric analysis, museum, network analysis, visitors’ experiences, visual analysis

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676 Microstructure and Excess Conductivity of Bulk, Ag-Added FeSe Superconductors

Authors: Michael Koblischka, Yassine Slimani, Thomas Karwoth, Anjela Koblischka-Veneva, Essia Hannachi

Abstract:

On bulk FeSe superconductors containing different additions of Ag, a thorough investigation of the microstructures was performed using optical microscopy, SEM and TEM. The electrical resistivity was measured using four-point measurements in the temperature range 2 K ≤ T ≤ 150 K. The data obtained are analyzed in the framework of the excess conductivity approach using the Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), onedimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuation regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), the lower and upper critical magnetic fields (Bc1 and Bc2), the critical current density (Jc) and numerous other superconducting parameters were estimated with respect to the Ag content in the samples. The data reveal a reduction of the resistivity and a strong decrease of ξc(0) when doping the 11-samples with silver. The optimum content of the Ag-addition is found at 4 wt.-% Ag, yielding the highest critical current density.

Keywords: iron-based superconductors, FeSe, Ag-addition, excess conductivity, microstructure

Procedia PDF Downloads 123
675 Topical Negative Pressure for Autologous Fat Grafting in Breast Augmentation

Authors: Mohamed Eftal Bin Mohamed Ebrahim, Alexander Varey

Abstract:

Aim: Topical negative pressure has been shown to enhance angiogenesis during wound healing, both for open and closed wounds. Since angiogenesis is a key requirement for successful fat grafting, there may be a role for topical negative pressure as a means of enhancing the take rate during autologous fat grafting to breasts. Here we present a systematic review of the literature on this topic. Methods: Ovid and Embase were utilized, with searches ranging between 1960 – 2019. Terms (“Liposculpting” OR “Fat grafting” OR “Lipofilling” OR “Lipograft” OR “Fat transfer”) AND (“Negative Pressure” OR “Brava” OR “Kiwi”) AND (“Breast”) were merged as keywords. Inclusion criteria were females, autologous fat graft to breast with topical negative pressure prior to the procedure. Studies were excluded if there was no primary endpoint or non-original article. Results: Upon reviewing 219 articles, 2 met inclusion criteria. A total of 565 and 46 breasts in each article were treated respectively using the negative pressure device BRAVA®, with each cohort having different pre-and post-operative pressure settings. Khouri et al. cohort had higher graft survival (79%) compared to Del Vecchio et al. cohort (64%); however, the latter had fewer complications compared to Khouri’s cohort, e.g., fat necrosis, pneumothorax and infection. Conclusion: There is limited evidence regarding the use of topical negative pressure for fat grafting to the breasts. However, in the two studies published, the reported rates of success are high, suggesting there may be a benefit. Consequently, a randomized controlled trial on this area is required.

Keywords: fat grafting, lipograft, negative pressure, breast, breast augmentation, brava

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674 Characteristics of Business Models of Industrial-Internet-of-Things Platforms

Authors: Peter Kress, Alexander Pflaum, Ulrich Loewen

Abstract:

The number of Internet-of-Things (IoT) platforms is steadily increasing across various industries, especially for smart factories, smart homes and smart mobility. Also in the manufacturing industry, the number of Industrial-IoT platforms is growing. Both IT players, start-ups and increasingly also established industry players and small-and-medium-enterprises introduce offerings for the connection of industrial equipment on platforms, enabled by advanced information and communication technology. Beside the offered functionalities, the established ecosystem of partners around a platform is one of the key differentiators to generate a competitive advantage. The key question is how platform operators design the business model around their platform to attract a high number of customers and partners to co-create value for the entire ecosystem. The present research tries to answer this question by determining the key characteristics of business models of successful platforms in the manufacturing industry. To achieve that, the authors selected an explorative qualitative research approach and created an inductive comparative case study. The authors generated valuable descriptive insights of the business model elements (e.g., value proposition, pricing model or partnering model) of various established platforms. Furthermore, patterns across the various cases were identified to derive propositions for the successful design of business models of platforms in the manufacturing industry.

Keywords: industrial-internet-of-things, business models, platforms, ecosystems, case study

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673 A Constitutional Theory of the American Presidency

Authors: Elvin Lim

Abstract:

This article integrates the debate about presidential powers with the debate about federalism, arguing that there are two ways of exercising presidential powers, one working in tandem with expanding federal powers, and the other working against it. Alexander Hamilton and Thomas Jefferson—the former a Federalist and the latter echoing the views of many Anti-Federalists—disagreed not only on the constitutional basis of prerogative, but also on the ends for which it should be deployed. This tension has always existed in American politics, and is reproduced today. Modern Democrats and Republicans both want a strong executive, but the Democrats who want a strong executive to pass legislation to expand the reach of the federal government; naturally, they must rely on an equally empowered Congress to do so. Republicans generally do not want an intrusive federal government, which is why their defense of a strong presidency does not come alongside a call for a strong Congress. This distinction cannot be explained without recourse to foundational yet opposing views about the appropriate role of federal power. When we bring federalism back in, we see that there are indeed two presidencies; one neo-Federalist, in favor of moderate presidential prerogative alongside a robust Congress directed collectively to a national state-building agenda and expanding the federal prerogative; another, neo-Anti-Federalist, in favor of expansive presidential prerogative and an ideologically sympathetic Congress equally suspicious of federal power to retard or roll back national state-building in favour of states rights.

Keywords: US presidency, federalism, prerogative, anti-federalism

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672 Defective Autophagy Leads to the Resistance to PP2 in ATG5 Knockout Cells Generated by CRISPR-Cas9 Endonuclease

Authors: Sung-Hee Hwang, Michael Lee

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Upregulated Src activity has been implicated in a variety of cancers. Thus, Src family tyrosine kinase (SFK) inhibitors are often effective cancer treatments. Here, we investigate the role of autophagy in ATG5 knockout cell lines generated by the Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)/Cas mediated genome editing. The CRISPR-associated protein Cas9 is an RNA-guided DNA endonuclease that uses RNA–DNA complementarity to identify target sites for sequence specific double-stranded DNA (dsDNA) cleavage. Interestingly, ATG5 KO cells clearly showed a greater proliferation rate than WT NIH 3T3 cells, implying that autophagy induction is cytotoxic. Also, the clonogenic survival of ATG5 KO cells was greater than WT cells. The MTT assay revealed that the cytotoxic effect of PP2 was weaker on ATG5 knockout cells than that WT cells. The conversion of non-autophagic LC3-I to autophagic LC3-II and RT-PCR confirmed the functional gene knockout. Furthermore, Cyto-ID autophagy assay also revealed that PP2 failed to induce autophagy in ATG5 knockout cells. Together, our findings suggest that the resistance to PP2 in ATG5 knockout cells is associated with defective autophagy.

Keywords: ATG5 knockout, Autophagy, CRISPR/Cas9, PP2

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671 Future Student Service Organization - Road Map

Authors: Michael Postert

Abstract:

The Studierendenwerke are legally independent public foundations with a one-century-old history in the German university community. Like the French CROUS, the Italian ANDISU or the Japanese University COOPs, they are set-up to serve the university and student needs. They are legally independent of their client institutions and student stakeholders. Initially set up as a support organization by students for students they have evolved to public business institutions with an annual turnover of EUR 100 Million or more. They are usually engaged in business areas such as student housing, restaurants, student grants, governmental scholarships and counselling services. These institutions are facing major changes over the next few years. The COVID19 pandemic and its impact on the educational system will unavoidably have an immense impact on the German student service organizations (Studierendenwerke). Issues such as digitalization and sustainability will have a huge impact on how the future business model of the Studierendenwerke will look like. The paper will discuss the aims and challenges of this development that started already before the COVID19 pandemic. In light of the way the educational system of the future will look like, the Studierendenwerke have to develop as well.

Keywords: business model, digitalization, education, student services

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670 Cordyceps and Related Fungi from Nigeria

Authors: Sami Michael Ayodele

Abstract:

Cordyceps are members of the fungi family Cordycepitaceae which are formally in Clavicipitaceae. They parasitize the larvae and adults of different susceptible arthropods. They are highly priced and have been reported to be highly medicinal. Cordyceps have been used for centuries in traditional medicine in China and other Asian countries. Survey studies were carried out to determine the presence of Cordyceps and another entomopathogenic fungal floral in North Central Nigeria for two consecutive years. Thirty samples were collected, twenty-eight were identified, and two were unidentified. Most identified species belong to Ophiocordyceps species (20samples), Cordyceps species (4samples) and Isaria species (4samples). The species identified were: Cordyceps pseudomilitaris, Cordyceps tuberculata, Cordyceps cylindrical, Ophiocordyceps nutans, O. criminals, O. oxycephala, O. kniphofioides and Isaria sinclairii. The morphological and microscopic features of the collected and identified species were similar to those reported in other countries. This is the first official report on the presence of Cordyceps species in Nigeria. Further collections from different ecological regions of Nigeria will show the richness of the floral diversity of these entomopathogenic and medicinal mushrooms in Nigeria.

Keywords: cordyceps, entomopathogenic, medicinal, North Central, Nigeria

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669 Ultra-Fast pH-Gradient Ion Exchange Chromatography for the Separation of Monoclonal Antibody Charge Variants

Authors: Robert van Ling, Alexander Schwahn, Shanhua Lin, Ken Cook, Frank Steiner, Rowan Moore, Mauro de Pra

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Purpose: Demonstration of fast high resolution charge variant analysis for monoclonal antibody (mAb) therapeutics within 5 minutes. Methods: Three commercially available mAbs were used for all experiments. The charge variants of therapeutic mAbs (Bevacizumab, Cetuximab, Infliximab, and Trastuzumab) are analyzed on a strong cation exchange column with a linear pH gradient separation method. The linear gradient from pH 5.6 to pH 10.2 is generated over time by running a linear pump gradient from 100% Thermo Scientific™ CX-1 pH Gradient Buffer A (pH 5.6) to 100% CX-1 pH Gradient Buffer B (pH 10.2), using the Thermo Scientific™ Vanquish™ UHPLC system. Results: The pH gradient method is generally applicable to monoclonal antibody charge variant analysis. In conjunction with state-of-the-art column and UHPLC technology, ultra fast high-resolution separations are consistently achieved in under 5 minutes for all mAbs analyzed. Conclusion: The linear pH gradient method is a platform method for mAb charge variant analysis. The linear pH gradient method can be easily optimized to improve separations and shorten cycle times. Ultra-fast charge variant separation is facilitated with UHPLC that complements, and in some instances outperforms CE approaches in terms of both resolution and throughput.

Keywords: charge variants, ion exchange chromatography, monoclonal antibody, UHPLC

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668 Detectability of Malfunction in Turboprop Engine

Authors: Tomas Vampola, Michael Valášek

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On the basis of simulation-generated failure states of structural elements of a turboprop engine suitable for the busy-jet class of aircraft, an algorithm for early prediction of damage or reduction in functionality of structural elements of the engine is designed and verified with real data obtained at dynamometric testing facilities of aircraft engines. Based on an expanding database of experimentally determined data from temperature and pressure sensors during the operation of turboprop engines, this strategy is constantly modified with the aim of using the minimum number of sensors to detect an inadmissible or deteriorated operating mode of specific structural elements of an aircraft engine. The assembled algorithm for the early prediction of reduced functionality of the aircraft engine significantly contributes to the safety of air traffic and to a large extent, contributes to the economy of operation with positive effects on the reduction of the energy demand of operation and the elimination of adverse effects on the environment.

Keywords: detectability of malfunction, dynamometric testing, prediction of damage, turboprop engine

Procedia PDF Downloads 61
667 Medical Examiner Collection of Comprehensive, Objective Medical Evidence for Conducted Electrical Weapons and Their Temporal Relationship to Sudden Arrest

Authors: Michael Brave, Mark Kroll, Steven Karch, Charles Wetli, Michael Graham, Sebastian Kunz, Dorin Panescu

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Background: Conducted electrical weapons (CEW) are now used in 107 countries and are a common law enforcement less-lethal force practice in the United Kingdom (UK), United States of America (USA), Canada, Australia, New Zealand, and others. Use of these devices is rarely temporally associated with the occurrence of sudden arrest-related deaths (ARD). Because such deaths are uncommon, few Medical Examiners (MEs) ever encounter one, and even fewer offices have established comprehensive investigative protocols. Without sufficient scientific data, the role, if any, played by a CEW in a given case is largely supplanted by conjecture often defaulting to a CEW-induced fatal cardiac arrhythmia. In addition to the difficulty in investigating individual deaths, the lack of information also detrimentally affects being able to define and evaluate the ARD cohort generally. More comprehensive, better information leads to better interpretation in individual cases and also to better research. The purpose of this presentation is to provide MEs with a comprehensive evidence-based checklist to assist in the assessment of CEW-ARD cases. Methods: PUBMED and Sociology/Criminology data bases were queried to find all medical, scientific, electrical, modeling, engineering, and sociology/criminology peer-reviewed literature for mentions of CEW or synonymous terms. Each paper was then individually reviewed to identify those that discussed possible bioelectrical mechanisms relating CEW to ARD. A Naranjo-type pharmacovigilance algorithm was also employed, when relevant, to identify and quantify possible direct CEW electrical myocardial stimulation. Additionally, CEW operational manuals and training materials were reviewed to allow incorporation of CEW-specific technical parameters. Results: Total relevant PUBMED citations of CEWs were less than 250, and reports of death extremely rare. Much relevant information was available from Sociology/Criminology data bases. Once the relevant published papers were identified, and reviewed, we compiled an annotated checklist of data that we consider critical to a thorough CEW-involved ARD investigation. Conclusion: We have developed an evidenced-based checklist that can be used by MEs and their staffs to assist them in identifying, collecting, documenting, maintaining, and objectively analyzing the role, if any, played by a CEW in any specific case of sudden death temporally associated with the use of a CEW. Even in cases where the collected information is deemed by the ME as insufficient for formulating an opinion or diagnosis to a reasonable degree of medical certainty, information collected as per the checklist will often be adequate for other stakeholders to use as a basis for informed decisions. Having reviewed the appropriate materials in a significant number of cases careful examination of the heart and brain is likely adequate. Channelopathy testing should be considered in some cases, however it may be considered cost prohibitive (aprox $3000). Law enforcement agencies may want to consider establishing a reserve fund to help manage such rare cases. The expense may stay the enormous costs associated with incident-precipitated litigation.

Keywords: ARD, CEW, police, TASER

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666 Effectuation in Production: How Production Managers Can Apply Decision-Making Techniques of Successful Entrepreneurs

Authors: Malte Brettel, David Bendig, Michael Keller, Marius Rosenberg

Abstract:

What are the core competences necessary in order to sustain manufacturing in high-wage countries? Aspiring countries all over the world gain market share in manufacturing and rapidly close the productivity and quality gap that has until now protected some parts of the industry in Europe and the United States from dislocation. However, causal production planning and manufacturing, the basis for productivity and quality, is challenged by the ever-greater need for flexibility and customized products in an uncertain business environment. This article uses a case-study-based approach to assess how production managers in high-wage countries can apply decision-making principals from successful entrepreneurs. 'Effectuation' instead of causal decision making can be applied to handle uncertainty of mass customization, to seek the right partners in alliances and to advance towards virtual production. The findings help managers to use their resources more efficiently and contribute to bridge the gap between production research and entrepreneurship.

Keywords: case studies, decision-making behavior, effectuation, production planning

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665 Business-to-Business Deals Based on a Co-Utile Collaboration Mechanism: Designing Trust Company of the Future

Authors: Riccardo Bonazzi, Michaël Poli, Abeba Nigussie Turi

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This paper presents an applied research of a new module for the financial administration and management industry, Personalizable and Automated Checklists Integrator, Overseeing Legal Investigations (PACIOLI). It aims at designing the business model of the trust company of the future. By identifying the key stakeholders, we draw a general business process design of the industry. The business model focuses on disintermediating the traditional form of business through the new technological solutions of a software company based in Switzerland and hence creating a new interactive platform. The key stakeholders of this interactive platform are identified as IT experts, legal experts, and the New Edge Trust Company (NATC). The mechanism we design and propose has a great importance in improving the efficiency of the financial business administration and management industry, and it also helps to foster the provision of high value added services in the sector.

Keywords: new edge trust company, business model design, automated checklists, financial technology

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664 Microstructure and Mechanical Properties of A201 Alloys with Additions of Si

Authors: Suzan Abd El Majid, Menachem Bamberger, Alexander Katsman

Abstract:

Two Al-4 wt. % Cu based alloys, A201 and A201+Si were investigated in the as-cast, solution treated and aged conditions. The addition of Si was used to improve the castability of the basic alloy. The all investigated alloys in the as-cast condition contained a eutectic structure along grain boundaries (GBs) with the composition Al-50at. %Cu that was found by HRSEM EDS. Addition of Si refined the grain structure and changed the amount of the eutectic regions, their size and shape. Additionally, the A201+Si microstructure contained Si rods and small amount of Al6Mn4Cu3Fe2Si-phase. Solution treatment (ST) at 550°C for ~ 20 hours resulted in a slight dissolution of the eutectic structure in the A201 alloy while substantial dissolution and change of the eutectic composition was detected in the A201+Si alloy. After ST, the A201alloy contained θ-Al2Cu, Al5Cu2Mn3 and Al9Cu7Mn3(Fe) phases associated to the GBs, while the ST A201+Si alloy contained θ-Al2Cu, Al6Mn4Cu3(Fe,Si) and Si94Mn3Al2Cu phases. Precipitation hardening during aging at 170°C was investigated for both alloys. The microhardness of the ST A201alloy increased during aging and reached the maximum value ~ 140 HV after 2 h of aging. Initial microhardness of the ST A201+Si alloy was distinctly higher than one of the ST A201 alloy, but it decreased during the first hour of aging, then increased and reached the same maximum value ~ 140 HV after ~ 4 h of aging. It was concluded that the Si addition influenced the precipitation sequence and slowed down the age hardening process. The Si induced grain refining and evolution of the eutectic structure during the heat treatments applied are discussed.

Keywords: A201 alloys, castability, microstructure, micro-hardness

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663 A Topological Approach for Motion Track Discrimination

Authors: Tegan H. Emerson, Colin C. Olson, George Stantchev, Jason A. Edelberg, Michael Wilson

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Detecting small targets at range is difficult because there is not enough spatial information present in an image sub-region containing the target to use correlation-based methods to differentiate it from dynamic confusers present in the scene. Moreover, this lack of spatial information also disqualifies the use of most state-of-the-art deep learning image-based classifiers. Here, we use characteristics of target tracks extracted from video sequences as data from which to derive distinguishing topological features that help robustly differentiate targets of interest from confusers. In particular, we calculate persistent homology from time-delayed embeddings of dynamic statistics calculated from motion tracks extracted from a wide field-of-view video stream. In short, we use topological methods to extract features related to target motion dynamics that are useful for classification and disambiguation and show that small targets can be detected at range with high probability.

Keywords: motion tracks, persistence images, time-delay embedding, topological data analysis

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662 Dimensionality and Superconducting Parameters of YBa2Cu3O7 Foams

Authors: Michael Koblischka, Anjela Koblischka-Veneva, XianLin Zeng, Essia Hannachi, Yassine Slimani

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Superconducting foams of YBa2Cu3O7 (abbreviated Y-123) were produced using the infiltration growth (IG) technique from Y2BaCuO5 (Y-211) foams. The samples were investigated by SEM (scanning electron microscopy) and electrical resistivity measurements. SEM observations indicated the specific microstructure of the foam struts with numerous tiny Y-211 particles (50-100 nm diameter) embedded in channel-like structures between the Y-123 grains. The investigation of the excess conductivity of different prepared composites was analyzed using Aslamazov-Larkin (AL) model. The investigated samples comprised of five distinct fluctuation regimes, namely short-wave (SWF), one-dimensional (1D), two-dimensional (2D), three-dimensional (3D), and critical (CR) fluctuations regimes. The coherence length along the c-axis at zero-temperature (ξc(0)), lower and upper critical magnetic fields (Bc1 and Bc2), critical current density (Jc) and numerous other superconducting parameters were estimated from the data. The analysis reveals that the presence of the tiny Y-211 particles alters the excess conductivity and the fluctuation behavior observed in standard YBCO samples.

Keywords: Excess conductivity, Foam, Microstructure, Superconductor YBa2Cu3Oy

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661 Simplifying the Migration of Architectures in Embedded Applications Introducing a Pattern Language to Support the Workforce

Authors: Farha Lakhani, Michael J. Pont

Abstract:

There are two main architectures used to develop software for modern embedded systems: these can be labelled as “event-triggered” (ET) and “time-triggered” (TT). The research presented in this paper is concerned with the issues involved in migration between these two architectures. Although TT architectures are widely used in safety-critical applications they are less familiar to developers of mainstream embedded systems. The research presented in this paper began from the premise that–for a broad class of systems that have been implemented using an ET architecture–migration to a TT architecture would improve reliability. It may be tempting to assume that conversion between ET and TT designs will simply involve converting all event-handling software routines into periodic activities. However, the required changes to the software architecture are, in many cases rather more profound. The main contribution of the work presented in this paper is to identify ways in which the significant effort involved in migrating between existing ET architectures and “equivalent” (and effective) TT architectures could be reduced. The research described in this paper has taken an innovative step in this regard by introducing the use of ‘Design patterns’ for this purpose for the first time.

Keywords: embedded applications, software architectures, reliability, pattern

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660 Self-Supervised Pretraining on Sequences of Functional Magnetic Resonance Imaging Data for Transfer Learning to Brain Decoding Tasks

Authors: Sean Paulsen, Michael Casey

Abstract:

In this work we present a self-supervised pretraining framework for transformers on functional Magnetic Resonance Imaging (fMRI) data. First, we pretrain our architecture on two self-supervised tasks simultaneously to teach the model a general understanding of the temporal and spatial dynamics of human auditory cortex during music listening. Our pretraining results are the first to suggest a synergistic effect of multitask training on fMRI data. Second, we finetune the pretrained models and train additional fresh models on a supervised fMRI classification task. We observe significantly improved accuracy on held-out runs with the finetuned models, which demonstrates the ability of our pretraining tasks to facilitate transfer learning. This work contributes to the growing body of literature on transformer architectures for pretraining and transfer learning with fMRI data, and serves as a proof of concept for our pretraining tasks and multitask pretraining on fMRI data.

Keywords: transfer learning, fMRI, self-supervised, brain decoding, transformer, multitask training

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659 Iron Recovery from Red Mud as Zero-Valent Iron Metal Powder Using Direct Electrochemical Reduction Method

Authors: Franky Michael Hamonangan Siagian, Affan Maulana, Himawan Tri Bayu Murti Petrus, Widi Astuti

Abstract:

In this study, the feasibility of the direct electrowinning method was used to produce zero-valent iron from red mud. The bauxite residue sample came from the Tayan mine, Indonesia, which contains high hematite (Fe₂O₃). Before electrolysis, the samples were characterized by various analytical techniques (ICP-AES, SEM, XRD) to determine their chemical composition and mineralogy. The direct electrowinning method of red mud suspended in NaOH was introduced at low temperatures ranging from 30 - 110 °C. Variations of current density, red mud: NaOH ratio and temperature were carried out to determine the optimum operation of the direct electrowinning process. Cathode deposits and residues in electrochemical cells were analyzed using XRD, XRF, and SEM to determine the chemical composition and current recovery. The low-temperature electrolysis current efficiency on Redmud can reach 20% recovery at a current density of 920,945 A/m². The moderate performance of the process was investigated with red mud, which was attributed to the troublesome adsorption of red mud particles on the cathode, making the reduction far less efficient than that with hematite.

Keywords: red mud, electrochemical reduction, Iron production, hematite

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658 Ab Initio Approach to Generate a Binary Bulk Metallic Glass Foam

Authors: Jonathan Galvan-Colin, Ariel Valladares, Renela Valladares, Alexander Valladares

Abstract:

Both porous materials and bulk metallic glasses have been studied due to their potential applications and their exceptional physical and chemical properties. However, each material presents certain drawbacks which have been thought to be overcome by generating bulk metallic glass foams (BMGF). Although some experimental reports have been performed on multicomponent BMGF, still no ab initio works have been published, as far as we know. We present an approach based on the expanding lattice (EL) method to generate binary amorphous nanoporous Cu64Zr36. Starting from two different configurations: a 108-atom crystalline cubic supercell (cCu64Zr36) and a 108-atom amorphous supercell (aCu64Zr36), both with an initial density of 8.06 g/cm3, we applied EL method to halve the density and to get 50% of porosity. After the lattice expansion the supercells were subject to ab initio molecular dynamics for 500 steps at constant room temperature. Then, the samples were geometry-optimized and characterized with the pair and radial distribution functions, bond-angle distributions and a coordination number analysis. We found that pores appeared along specific spatial directions different from one to another and that they differed in size and form as well, which we think is related to the initial structure. Due to the lack of experimental counterparts our results should be considered predictive and further studies are needed in order to handle a larger number of atoms and its implication on pore topology.

Keywords: ab initio molecular dynamics, bulk mettalic glass, porous alloy

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657 Recurrent Neural Networks with Deep Hierarchical Mixed Structures for Chinese Document Classification

Authors: Zhaoxin Luo, Michael Zhu

Abstract:

In natural languages, there are always complex semantic hierarchies. Obtaining the feature representation based on these complex semantic hierarchies becomes the key to the success of the model. Several RNN models have recently been proposed to use latent indicators to obtain the hierarchical structure of documents. However, the model that only uses a single-layer latent indicator cannot achieve the true hierarchical structure of the language, especially a complex language like Chinese. In this paper, we propose a deep layered model that stacks arbitrarily many RNN layers equipped with latent indicators. After using EM and training it hierarchically, our model solves the computational problem of stacking RNN layers and makes it possible to stack arbitrarily many RNN layers. Our deep hierarchical model not only achieves comparable results to large pre-trained models on the Chinese short text classification problem but also achieves state of art results on the Chinese long text classification problem.

Keywords: nature language processing, recurrent neural network, hierarchical structure, document classification, Chinese

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656 A Real-Time Snore Detector Using Neural Networks and Selected Sound Features

Authors: Stelios A. Mitilineos, Nicolas-Alexander Tatlas, Georgia Korompili, Lampros Kokkalas, Stelios M. Potirakis

Abstract:

Obstructive Sleep Apnea Hypopnea Syndrome (OSAHS) is a widespread chronic disease that mostly remains undetected, mainly due to the fact that it is diagnosed via polysomnography which is a time and resource-intensive procedure. Screening the disease’s symptoms at home could be used as an alternative approach in order to alert individuals that potentially suffer from OSAHS without compromising their everyday routine. Since snoring is usually linked to OSAHS, developing a snore detector is appealing as an enabling technology for screening OSAHS at home using ubiquitous equipment like commodity microphones (included in, e.g., smartphones). In this context, this study developed a snore detection tool and herein present the approach and selection of specific sound features that discriminate snoring vs. environmental sounds, as well as the performance of the proposed tool. Furthermore, a Real-Time Snore Detector (RTSD) is built upon the snore detection tool and employed in whole-night sleep sound recordings resulting to a large dataset of snoring sound excerpts that are made freely available to the public. The RTSD may be used either as a stand-alone tool that offers insight to an individual’s sleep quality or as an independent component of OSAHS screening applications in future developments.

Keywords: obstructive sleep apnea hypopnea syndrome, apnea screening, snoring detection, machine learning, neural networks

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655 Decoding Gender Disparities in AI: An Experimental Exploration Within the Realm of AI and Trust Building

Authors: Alexander Scott English, Yilin Ma, Xiaoying Liu

Abstract:

The widespread use of artificial intelligence in everyday life has triggered a fervent discussion covering a wide range of areas. However, to date, research on the influence of gender in various segments and factors from a social science perspective is still limited. This study aims to explore whether there are gender differences in human trust in AI for its application in basic everyday life and correlates with human perceived similarity, perceived emotions (including competence and warmth), and attractiveness. We conducted a study involving 321 participants using a two-subject experimental design with a two-factor (masculinized vs. feminized voice of the AI) multiplied by a two-factor (pitch level of the AI's voice) between-subject experimental design. Four contexts were created for the study and randomly assigned. The results of the study showed significant gender differences in perceived similarity, trust, and perceived emotion of the AIs, with females rating them significantly higher than males. Trust was higher in relation to AIs presenting the same gender (e.g., human female to female AI, human male to male AI). Mediation modeling tests indicated that emotion perception and similarity played a sufficiently mediating role in trust. Notably, although trust in AIs was strongly correlated with human gender, there was no significant effect on the gender of the AI. In addition, the study discusses the effects of subjects' age, job search experience, and job type on the findings.

Keywords: artificial intelligence, gender differences, human-robot trust, mediation modeling

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654 Evaluation Methods for Question Decomposition Formalism

Authors: Aviv Yaniv, Ron Ben Arosh, Nadav Gasner, Michael Konviser, Arbel Yaniv

Abstract:

This paper introduces two methods for the evaluation of Question Decomposition Meaning Representation (QDMR) as predicted by sequence-to-sequence model and COPYNET parser for natural language questions processing, motivated by the fact that previous evaluation metrics used for this task do not take into account some characteristics of the representation, such as partial ordering structure. To this end, several heuristics to extract such partial dependencies are formulated, followed by the hereby proposed evaluation methods denoted as Proportional Graph Matcher (PGM) and Conversion to Normal String Representation (Nor-Str), designed to better capture the accuracy level of QDMR predictions. Experiments are conducted to demonstrate the efficacy of the proposed evaluation methods and show the added value suggested by one of them- the Nor-Str, for better distinguishing between high and low-quality QDMR when predicted by models such as COPYNET. This work represents an important step forward in the development of better evaluation methods for QDMR predictions, which will be critical for improving the accuracy and reliability of natural language question-answering systems.

Keywords: NLP, question answering, question decomposition meaning representation, QDMR evaluation metrics

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