Search results for: driven pendulum

Authors: Farshad Ghassemi Toosi, Nikola S. Nikolov

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We present a visualization technique for radial drawing of trees consisting of two slightly different algorithms. Both of them make use of node-link diagrams for visual encoding. This visualization creates clear drawings without edge crossing. One of the algorithms is suitable for real-time visualization of large trees, as it requires minimal recalculation of the layout if leaves are inserted or removed from the tree; while the other algorithm makes better utilization of the drawing space. The algorithms are very similar and follow almost the same procedure but with different parameters. Both algorithms assign angular coordinates for all nodes which are then converted into 2D Cartesian coordinates for visualization. We present both algorithms and discuss how they compare to each other.

Keywords: Radial drawing, Visualization, Algorithm, Use of node-link diagrams

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Authors: Sayor Ajfar Aaron, Sajjat Hossain Abir, Ashif Newaz, Mushfiqur Rahman

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Investigating the convergence of blockchain technology and artificial intelligence, this paper examines their synergistic effects on data integrity and decision-making within smart contracts. By implementing AI-driven analytics on blockchain-based platforms, the research identifies improvements in automated contract enforcement and decision accuracy. The paper presents a framework that leverages AI to enhance transparency and trust while blockchain ensures immutable record-keeping, culminating in significantly optimized operational efficiencies in various industries.

Keywords: artificial intelligence, blockchain, data integrity, smart contracts

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Authors: Aitana Alonso-Nogueira, Helia Estévez-Fernández, Isaías García

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This paper presents an approach to reduce some of its current flaws in the requirements phase inside the software development process. It takes the software requirements of an application, makes a conceptual modeling about it and formalizes it within JSON documents. This formal model is lodged in a NoSQL database which is document-oriented, that is, MongoDB, because of its advantages in flexibility and efficiency. In addition, this paper underlines the contributions of the detailed approach and shows some applications and benefits for the future work in the field of automatic code generation using model-driven engineering tools.

Keywords: conceptual modelling, JSON, NoSQL databases, requirements engineering, software development

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Authors: W. Y. Zhu, X. L. Yan, Y. Zhou

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Sulfonamides (SAs) are extensively used antibiotics; photocatalysis is an effective, way to remove the SAs from water driven by solar energy. Here we used WO3 nanoplates and their Ag heterogeneous as photocatalysts to investigate their photodegradation efficiency against sulfanilamide (SAM) which is the precursor of SAs. Results showed that WO3/Ag composites performed much better than pure WO3 where the highest removal rate was 96.2% can be achieved under visible light irradiation. Ag as excellent antibacterial agent also endows certain antibacterial efficiency to WO3, and 100% removal efficiency could be achieved in 2 h under visible light irradiation for all WO3/Ag composites. Generally, WO3/Ag composites are very effective photocatalysts with potentials in practical applications which mainly use cheap, clean and green solar energy as energy source.

Keywords: antibacterial, photocatalysis, semiconductor, sulfanilamide

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Authors: Kemi Olalekan Oduntan

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Transformation is a strong word that portends a radical, structural and basic reappraisal of the basic assumptions that underline our economic reform and developmental efforts. The challenges before government are how to move the nation away from an oil-dominated economy, institute the basics for a private sector-driven economy, build the local economy on international best practices, transform a passive oil industry to a more pro-active one and reposition the country along the lines of a more decentralized federalism. But beyond this, Nigeria is faced with management and leadership challenges to contend with building an efficient and effective polity, inspiring a shared vision, remodeling a corrupt polity, redefining the essentials of transformational leadership and creating Nigerian dream that will inspire patriotism and commitment in the citizenry.

Keywords: economic, economic growth, patriotism, polity, transformational

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Authors: Jagoda Bruni, Jan Müller-Lucanus, Gernot Stöger-Knes

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The purpose of this article is to demonstrate modern project management approaches in the SAP S/R Hana surrounding a programming environment composed of multiple focus-diversified projects. We would like to propose innovative and goal-oriented management standards based on the specificity of the SAP transformations and customer-driven expectations. Due to the regular sprint-based controlling and management tools' application, it has been data-proven that extensive analysis of productive hours of the employees as much as a thorough review of the project progress (per GAP, per business process, and per Lot) within the whole program, can have a positive impact on customer satisfaction and improvement for projects' budget. This has been a collaborative study based on real-life experience and measurements in collaboration with our customers.

Keywords: project management, program management, SAP, controlling

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Authors: Yining Yu, Miaolei Jia, Bingjie Li

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While researchers have begun to investigate how ambient elements affect consumers’ choices between healthy and unhealthy food, the role of ambient temperature is relatively unknown. In this study, we find that ambient coldness increases consumers’ preference for unhealthy food. This effect is driven by the increased need for energy automatically activated in a cold ambiance. Consequently, consumers are more inclined to choose calorie-rich unhealthy food. This effect is diminished when the unhealthy food is cold because cold dish cannot provide the energy consumers need in the cold ambiance. We conclude with a discussion of our theoretical contributions to the literature of temperature effects and food consumption. We also offer practical takeaways for restaurant managers.

Keywords: ambient temperature, cold ambiance, food choice, need for energy

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Authors: Derwin K. C. Chan, Alfred S. Y. Lee

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The integrated model of self-determination theory and the theory of planned behaviour has been successfully applied to explain individuals’ adherence to health behaviours, including behavioural adherence toward rehabilitation. This study was a randomised controlled trial that examined the effectiveness of an mHealth intervention (i.e., mobile application) developed based on this integrated model in promoting treatment adherence of patients of anterior cruciate ligament rupture during their post-surgery home-based rehabilitation period. Subjects were 67 outpatients (aged between 18 and 60) who undertook anterior cruciate ligament (ACL) reconstruction surgery for less than 2 months for this study. Participants were randomly assigned either into the treatment group (who received the smartphone application; N = 32) and control group (who receive standard treatment only; N = 35), and completed psychological measures relating to the theories (e.g., motivations, social cognitive factors, and behavioural adherence) and clinical outcome measures (e.g., subjective knee function (IKDC), laxity (KT-1000), muscle strength (Biodex)) relating to ACL recovery at baseline, 2-month, and 4-month. Generalise estimating equation showed the interaction between group and time was significant on intention was only significant for intention (Wald x² = 5.23, p = .02), that of perceived behavioural control (Wald x² = 3.19, p = .07), behavioural adherence (Wald x² = 3.08, p = .08, and subjective knee evaluation (Wald x² = 2.97, p = .09) were marginally significant. Post-hoc between-subject analysis showed that control group had significant drop of perceived behavioural control (p < .01), subjective norm (p < .01) and intention (p < .01), behavioural adherence (p < .01) from baseline to 4-month, but such pattern was not observed in the treatment group. The treatment group had a significant decrease of behavioural adherence (p < .05) in the 2-month, but such a decrease was not observed in 4-month (p > .05). Although the subjective knee evaluation in both group significantly improved at 2-month and 4-month from the baseline (p < .05), and the improvements in the control group (mean improvement at 4-month = 40.18) were slightly stronger than the treatment group (mean improvement at 4-month = 34.52). In conclusion, the findings showed that the theory driven mobile application ameliorated the decline of treatment intention of home-based rehabilitation. Patients in the treatment group also reported better muscle strength than control group at 4-month follow-up. Overall, the mobile application has shown promises on tackling the problem of orthopaedics outpatients’ non-adherence to medical treatment.

Keywords: self-determination theory, theory of planned behaviour, mobile health, orthopaedic patients

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Authors: Iñaki Aliende, Tom Webb, Lorenzo Escot

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There is a concern about the decrease in football referees globally. A study in Spain has analyzed the factors affecting a referee's career over the past 30 years through a survey of 758 referees. Results showed the impact of factors such as threats, education, initial vocation, and dependents on a referee's career. To improve the situation, the federation needs to provide better information, support young referees, monitor referees, and raise public awareness of violence toward referees. The study also formed a comprehensive model for federations to enhance their officiating policies by means of data-driven techniques that can serve other federations to improve referees' careers.

Keywords: data science, football referees, sport management, sport careers, survival analysis

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Authors: Kwan Hee Han, Jun Woo Lee, Sung Moon Bae, Twae Kyung Park

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ECA (Event-Condition-Action) languages are largely adopted for event processing since they are an intuitive and powerful paradigm for programming reactive systems. However, there are some limitations about ECA rules for processing of complex events such as coupling of event producer and consumer. The objective of this paper is to propose an ECA rule pattern to improve the current limitations of ECA rule, and to develop a prototype system. In this paper, conventional ECA rule is separated into 3 parts and each part is extended to meet the requirements of CEP. Finally, event processing logic is established by combining the relevant elements of 3 parts. The usability of proposed extended ECA rule is validated by a test scenario in this study.

Keywords: complex event processing, ECA rule, Event processing system, event-driven architecture, internet of things

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Authors: Boumediene Hamzi, Turky N. AlOtaiby, Saleh AlShebeili, Arwa AlAnqary

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We introduce a data-driven method for seizure detection drawing on recent progress in Machine Learning. The method is based on embedding probability measures in a high (or infinite) dimensional reproducing kernel Hilbert space (RKHS) where the Maximum Mean Discrepancy (MMD) is computed. The MMD is metric between probability measures that are computed as the difference between the means of probability measures after being embedded in an RKHS. Working in RKHS provides a convenient, general functional-analytical framework for theoretical understanding of data. We apply this approach to the problem of seizure detection.

Keywords: kernel methods, maximum mean discrepancy, seizure detection, machine learning

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Authors: Roman Kalvin, Anam Nadeem, Saba Arif

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Turbocharger is a device that is driven by the turbine and increases efficiency and power output of the engine by forcing external air into the combustion chamber. This study focused on the distribution of stress on the turbine blades and total deformation that may occur during its working along with turbocharger to carry out its static structural analysis of turbine blades. Structural steel was selected as the material for turbocharger. Assembly of turbocharger and turbine blades was designed on PRO ENGINEER. Furthermore, the structural analysis is performed by using ANSYS. This research concluded that by using structural steel, the efficiency of engine is improved and by increasing number of turbine blades, more waste heat from combustion chamber is emitted.

Keywords: turbocharger, turbine blades, structural steel, ANSYS

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Authors: Arun Prasad Jaganathan

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In today's rapidly evolving technological landscape, the need for efficient and proactive maintenance management solutions has become increasingly evident across various industries. Traditional approaches often suffer from drawbacks such as reactive strategies, leading to potential downtime, increased costs, and decreased operational efficiency. In response to these challenges, this paper proposes an AI-enabled approach to object-based maintenance management aimed at enhancing reliability and efficiency. The paper contributes to the growing body of research on AI-driven maintenance management systems, highlighting the transformative impact of intelligent technologies on enhancing object reliability and operational efficiency.

Keywords: AI, machine learning, predictive maintenance, object-based maintenance, expert team scheduling

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Authors: Andrus Pedai, Igor Astrov

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The focus of this paper is to compare common approaches for Systems of Innovation (SI) and identify proactive alternatives for driving the innovation. Proactive approaches will also consider short and medium term perspectives with developments in the field of Computer Technology and Artificial Intelligence. Concerning computer technology and large connected information systems, it is reasonable to predict that during current or the next century, intelligence and innovation will be separated from the constraints of human-driven management. After this happens, humans will no longer be driving the innovation and there is possibility that SI for new intelligent systems will set its own targets and exclude humans. Over long time scale, these developments could result in a scenario, which will lead to the development of larger, cross galactic (universal) proactive SI and Intelligence.

Keywords: artificial intelligence, DARPA, Moore’s law, proactive innovation, singularity, systems of innovation

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Authors: Yayun Hsu, Henry Horng-Shing Lu

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This paper proposes a data-driven, biology-inspired neural segmentation method of 3D drosophila Brainbow images. We use Bayesian Sequential Partitioning algorithm for probabilistic modeling, which can be used to detect somas and to eliminate cross talk effects. This work attempts to develop an automatic methodology for neuron image segmentation, which nowadays still lacks a complete solution due to the complexity of the image. The proposed method does not need any predetermined, risk-prone thresholds since biological information is inherently included in the image processing procedure. Therefore, it is less sensitive to variations in neuron morphology; meanwhile, its flexibility would be beneficial for tracing the intertwining structure of neurons.

Keywords: brainbow, 3D imaging, image segmentation, neuron morphology, biological data mining, non-parametric learning

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Authors: Dangut Maren David, Skaf Zakwan

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Adequate monitoring of vehicle component in other to obtain high uptime is the goal of predictive maintenance, the major challenge faced by businesses in industries is the significant cost associated with a delay in service delivery due to system downtime. Most of those businesses are interested in predicting those problems and proactively prevent them in advance before it occurs, which is the core advantage of Prognostic Health Management (PHM) application. The recent emergence of industry 4.0 or industrial internet of things (IIoT) has led to the need for monitoring systems activities and enhancing system-to-system or component-to- component interactions, this has resulted to a large generation of data known as big data. Analysis of big data represents an increasingly important, however, due to complexity inherently in the dataset such as imbalance classification problems, it becomes extremely difficult to build a model with accurate high precision. Data-driven predictive modeling for condition-based maintenance (CBM) has recently drowned research interest with growing attention to both academics and industries. The large data generated from industrial process inherently comes with a different degree of complexity which posed a challenge for analytics. Thus, imbalance classification problem exists perversely in industrial datasets which can affect the performance of learning algorithms yielding to poor classifier accuracy in model development. Misclassification of faults can result in unplanned breakdown leading economic loss. In this paper, an advanced approach for handling imbalance classification problem is proposed and then a prognostic model for predicting aircraft component replacement is developed to predict component replacement in advanced by exploring aircraft historical data, the approached is based on hybrid ensemble-based method which improves the prediction of the minority class during learning, we also investigate the impact of our approach on multiclass imbalance problem. We validate the feasibility and effectiveness in terms of the performance of our approach using real-world aircraft operation and maintenance datasets, which spans over 7 years. Our approach shows better performance compared to other similar approaches. We also validate our approach strength for handling multiclass imbalanced dataset, our results also show good performance compared to other based classifiers.

Keywords: prognostics, data-driven, imbalance classification, deep learning

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Authors: Aydin Azizi, Aburrahman Tanira

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The main source of energy used in this modern age is fossil fuels. There is a myriad of problems that come with the use of fossil fuels, out of which the issues with the greatest impact are its scarcity and the cost it imposes on the planet. Fossil fuels are the only plausible option for many vital functions and processes; the most important of these is transportation. Thus, using this source of energy wisely and as efficiently as possible is a must. The aim of this work was to explore utilising mathematical modelling and artificial intelligence techniques to enhance fuel consumption in passenger cars by focusing on the speed at which cars are driven. An artificial neural network with an error less than 0.05 was developed to be applied practically as to predict the rate of fuel consumption in vehicles.

Keywords: mathematical modeling, neural networks, fuel consumption, fossil fuel

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Authors: Akkouche Karim, Nekmouche Aghiles, Bouzid Leyla

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This study focuses on the development of a multifunctional Expert System (ES) called post-seismic damage inspection tool (PSDIT), a powerful tool which allows the evaluation, the processing and the archiving of the collected data stock after earthquakes. PSDIT can be operated by two user types; an ordinary user (engineer, expert or architect) for the damage visual inspection and an administrative user for updating the knowledge and / or for adding or removing the ordinary user. The knowledge acquisition is driven by a hierarchical knowledge model, the Information from investigation reports and those acquired through feedback from expert / engineer questionnaires are part.

Keywords: buildings, earthquake, seismic damage, damage assessment, expert system

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Authors: Tina Ternes, Florian Kleinau

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The study investigates the content and triggers of mind wandering (MW) in readers of fictional texts. It asks whether readers’ MW is productive (text-related) or unproductive (text-unrelated). Methodologically, it bridges the gap between narratological and data-driven approaches by utilizing a sentence-by-sentence self-paced reading paradigm combined with thought probes in the reading of an excerpt of A. L. Kennedy’s “Baby Blue”. Results show that the contents of MW can be linked to text properties. We validated the role of self-reference in MW and found prediction errors to be triggers of MW. Results also indicate that the content of MW often travels along the lines of the text at hand and can thus be viewed as productive and integral to interpretation.

Keywords: narratology, mind wandering, reading fiction, meta cognition

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Authors: Evgeny Kozubenko, Dmitry Shaposhnikov, Mikhail Petrushan

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This work is focused on the study of the binocular characteristics of the phenomenon of perisaccadic suppression in humans when perceiving visual objects. This phenomenon manifests in a decrease in the subject's ability to perceive visual information during saccades, which play an important role in purpose-driven behavior and visual perception. It was shown that the impairment of perception of visual information in the post-saccadic time window is stronger (p < 0.05) in the ipsilateral eye (the eye towards which the saccade occurs). In addition, the observed heterogeneity of post-saccadic suppression in the contralateral and ipsilateral eyes may relate to depth perception. Taking the studied phenomenon into account is important when developing ergonomic control panels in modern operator systems.

Keywords: eye movement, natural vision, saccadic suppression, visual perception

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Authors: Martins Onyekwelu Onuorah, Jnr Dahiru Usman

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Introduction: In the realm of public health, the threat posed by Monkeypox continues to elicit concern, prompting rigorous studies to understand its dynamics and devise effective containment strategies. Particularly significant is its recurrence in variable populations, such as the observed outbreak in Nigeria in 2022. In light of this, our study undertakes a meticulous analysis, employing a data-driven approach to explore, validate, and propose optimized intervention strategies tailored to the distinct dynamics of Monkeypox within varying demographic structures. Utilizing a deterministic mathematical model, we delved into the intricate dynamics of Monkeypox, with a particular focus on a variable population context. Our qualitative analysis provided insights into the disease-free equilibrium, revealing its stability when R0 is less than one and discounting the possibility of backward bifurcation, as substantiated by the presence of a single stable endemic equilibrium. The model was rigorously validated using real-time data from the Nigerian 2022 recorded cases for Epi weeks 1 – 52. Transitioning from qualitative to quantitative, we augmented our deterministic model with optimal control, introducing three time-dependent interventions to scrutinize their efficacy and influence on the epidemic's trajectory. Numerical simulations unveiled a pronounced impact of the interventions, offering a data-supported blueprint for informed decision-making in containing the disease. A comprehensive cost-effectiveness analysis employing the Infection Averted Ratio (IAR), Average Cost-Effectiveness Ratio (ACER), and Incremental Cost-Effectiveness Ratio (ICER) facilitated a balanced evaluation of the interventions’ economic and health impacts. In essence, our study epitomizes a holistic approach to understanding and mitigating Monkeypox, intertwining rigorous mathematical modeling, empirical validation, and economic evaluation. The insights derived not only bolster our comprehension of Monkeypox's intricate dynamics but also unveil optimized, cost-effective interventions. This integration of methodologies and findings underscores a pivotal stride towards aligning public health imperatives with economic sustainability, marking a significant contribution to global efforts in combating infectious diseases.

Keywords: monkeypox, equilibrium states, stability, bifurcation, optimal control, cost-effectiveness

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Authors: M. Chen, S-Q. Zhang, X. Wang, D. Tate

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This paper presents a numerical solution, namely limit and shakedown analysis, to predict the safety state of smart structures made of heterogeneous materials under unknown cyclic loadings, for instance, the flexure hinge in the micro-positioning stage driven by piezoelectric actuator. In combination of homogenization theory and finite-element method (FEM), the safety evaluation problem is converted to a large-scale nonlinear optimization programming for an acceptable bounded loading as the design reference. Furthermore, a general numerical scheme integrated with the FEM and interior-point-algorithm based optimization tool is developed, which makes the practical application possible.

Keywords: limit state, shakedown analysis, homogenization, heterogeneous structure

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Authors: Sharjeel Aslam, Vassil Vassilev, Karim Ouazzane

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Ontologies and various semantic repositories became a convenient approach for implementing model-driven architectures of distributed systems on the Web. SPARQL is the standard query language for querying such. However, although SPARQL is well-established standard for querying semantic repositories in RDF and OWL format and there are commonly used APIs which supports it, like Jena for Java, its parallel option is not incorporated in them. This article presents a complete framework consisting of an object algebra for parallel RDF and an index-based implementation of the parallel query engine capable of dealing with the distributed RDF ontologies which share common vocabulary. It has been implemented in Java, and for validation of the algorithms has been applied to the problem of organizing virtual exhibitions on the Web.

Keywords: distributed ontologies, parallel querying, semantic indexing, shared vocabulary, SPARQL

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Authors: Maximilian Winkens, Peter Nyhuis

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Components with sensory properties such as gentelligent components developed at the Collaborative Research Center 653 offer a new angle on the full utilization of the remaining service life in case of a preventive maintenance. The developed methodology of component status driven maintenance analyses the stress data obtained during the component's useful life and on the basis of this knowledge assesses the type of maintenance called for in this case. The procedure is derived from the case-based reasoning method and will be elucidated in detail. The method's functionality is demonstrated with real-life data obtained during test runs of a racing car prototype.

Keywords: gentelligent component, preventive maintenance, case-based reasoning, sensory

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Authors: Danish Laidin, Peter Gostomski, Aaron Marshall, Carlo Carere

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Groundwater contamination of nitrate (NO3-) is becoming more prevalent in regions of intensive and extensive agricultural activities. Household nitrate removal involves using ion exchange membranes and reverse osmosis (RO) systems, whereas industrial nitrate removal may use organic carbon substrates (e.g. methanol) for heterotrophic microbial denitrification. However, these approaches both require high capital investment and operating costs. In this study, denitrification was demonstrated using bio-electrochemical systems (BESs) inoculated from sediments and microbial enrichment cultures. The BES reactors were operated continuously as microbial electrolytic cells (MECs) with a poised potential of -0.7V and -1.1V vs Ag/AgCl. Three parallel MECs were inoculated using hydrogen-driven denitrifying enrichments, stream sediments, and biofilm harvested from a denitrifying biotrickling filter, respectively. These reactors were continuously operated for over a year as various operating conditions were investigated to determine the optimal conditions for electroactive denitrification. The mass loading rate of nitrate was varied between 10 – 70 mg NO3-/d, and the maximum observed nitrate removal rate was 22 mg NO3- /(cm2∙d) with a current of 2.1 mA. For volumetric load experiments, the dilution rate of 1 mM NO3- feed was varied between 0.01 – 0.1 hr-1 to achieve a nitrate loading rate similar to the mass loading rate experiments. Under these conditions, the maximum rate of denitrification observed was 15.8 mg NO3- /(cm2∙d) with a current of 1.7mA. Hydrogen (H2) was supplied intermittently to investigate the hydrogenotrophic potential of the denitrifying biofilm electrodes. H2 supplementation at 0.1 mL/min resulted in an increase of nitrate removal from 0.3 mg NO3- /(cm2∙d) to 3.4 mg NO3- /(cm2∙d) in the hydrogenotrophically subcultured reactor but had no impact on the reactors which exhibited direct electron transfer properties. Results from this study depict the denitrification performance of the immobilized biofilm electrodes, either by direct electron transfer or hydrogen-driven denitrification, and the contribution of the planktonic cells present in the growth medium. Other results will include the microbial community analysis via 16s rDNA amplicon sequencing, varying the effect of poising cathodic potential from 0.7V to 1.3V vs Ag/AgCl, investigating the potential of using in-situ electrochemically produced hydrogen for autotrophic denitrification and adjusting the conductivity of the feed solution to mimic groundwater conditions. These findings highlight the overall performance of sediment inoculated MECs in removing nitrate and will be used for the future development of sustainable solutions for the treatment of nitrate polluted groundwater.

Keywords: bio-electrochemical systems, groundwater, electroactive denitrification, microbial electrolytic cell

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Authors: Mohamed Shawki Elamir, Heinrich Gotzig, Raoul Zoellner, Patrick Maeder

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In this work, a methodology is presented for identifying the optimal digitization parameters for the analog signal of ultrasonic sensors. These digitization parameters are the resolution of the analog to digital conversion and the sampling rate. This is accomplished through the derivation of characteristic curves based on Fano inequality and the calculation of the mutual information content over a given dataset. The mutual information is calculated between the examples in the dataset and the corresponding variation in the feature that needs to be estimated. The optimal parameters are identified in a manner that ensures optimal estimation performance while preventing inefficiency in using unnecessarily powerful analog to digital converters.

Keywords: analog to digital conversion, digitization, sampling rate, ultrasonic

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Authors: Anupriya Sharma, Sapna Narula

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Over the past decade, sustainability has gone mainstream as more people are worried about environment-related issues than ever before. These issues are of even more concern for industries which leave a significant impact on the environment. Following these ecological issues, corporates are beginning to comprehend the impact on their business. Many such initiatives have been made to address these emerging issues in the consumer-driven textile industry. Demand from customers, local communities, government regulations, etc. are considered some of the major factors affecting environmental decision-making. Research also shows that motivations to go green are inevitably determined by the way top managers perceive environmental issues as managers personal values and ethical commitment act as a motivating factor towards corporate social responsibility. Little empirical research has been conducted to examine the relationship between top managers’ personal environmental attitudes and corporate environmental behaviors for the textile industry in the Indian context. The primary purpose of this study is to determine the current state of environmental management in textile industry and whether the attitude of textile firms’ top managers is significantly related to firm’s response to environmental issues and their perceived benefits of environmental management. To achieve the aforesaid objectives of the study, authors used structured questionnaire based on literature review. The questionnaire consisted of six sections with a total length of eight pages. The first section was based on background information on the position of the respondents in the organization, annual turnover, year of firm’s establishment and so on. The other five sections of the questionnaire were based upon (drivers, attitude, and awareness, sustainable business practices, barriers to implementation and benefits achieved). To test the questionnaire, a pretest was conducted with the professionals working in corporate sustainability and had knowledge about the textile industry and was then mailed to various stakeholders involved in textile production thereby covering firms top manufacturing officers, EHS managers, textile engineers, HR personnel and R&D managers. The results of the study showed that most of the textile firms were implementing some type of environmental management practice, even though the magnitude of firm’s involvement in environmental management practices varied. The results also show that textile firms with a higher level of involvement in environmental management were more involved in the process driven technical environmental practices. It also identified that firm’s top managers environmental attitudes were correlated with perceived advantages of environmental management as textile firm’s top managers are the ones who possess managerial discretion on formulating and deciding business policies such as environmental initiatives.

Keywords: attitude and awareness, Environmental management, sustainability, textile industry

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Authors: Ila Thakur, Atul Srivastava, Shyamprasad Karagadde

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The phenomenon of double-diffusive convection is driven by density gradients created by two different components (e.g., temperature and concentration) having different molecular diffusivities. The evolution of horizontal double-diffusive layers (DDLs) is one of the outcomes of double-diffusive convection occurring in a laterally/vertically cooled rectangular cavity having a pre-existing vertically stable composition field. The present work mainly focuses on different characteristics of the formation and merging of double-diffusive layers by imposing lateral/vertical thermal gradients in a vertically stable compositional field. A CFD-based twodimensional fluent model has been developed for the investigation of the aforesaid phenomena. The configuration containing vertical thermal gradients shows the evolution and merging of DDLs, where, elements from the same horizontal plane move vertically and mix with surroundings, creating a horizontal layer. In the configuration of lateral thermal gradients, a specially oriented convective roll was found inside each DDL and each roll was driven by the competing density change due to the already existing composition field and imposed thermal field. When the thermal boundary layer near the vertical wall penetrates the salinity interface, it can disrupt the compositional interface and can lead to layer merging. Different analytical scales were quantified and compared for both configurations. Various combinations of solutal and thermal Rayleigh numbers were investigated to get three different regimes, namely; stagnant regime, layered regime and unicellular regime. For a particular solutal Rayleigh number, a layered structure can originate only for a range of thermal Rayleigh numbers. Lower thermal Rayleigh numbers correspond to a diffusion-dominated stagnant regime. Very high thermal Rayleigh corresponds to a unicellular regime with high convective mixing. Different plots identifying these three regimes, number, thickness and time of existence of DDLs have been studied and plotted. For a given solutal Rayleigh number, an increase in thermal Rayleigh number increases the width but decreases both the number and time of existence of DDLs in the fluid domain. Sudden peaks in the velocity and heat transfer coefficient have also been observed and discussed at the time of merging. The present study is expected to be useful in correlating the double-diffusive convection in many large-scale applications including oceanography, metallurgy, geology, etc. The model has also been developed for three-dimensional geometry, but the results were quite similar to that of 2-D simulations.

Keywords: double diffusive layers, natural convection, Rayleigh number, thermal gradients, compositional gradients

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Authors: Evelyn Castle, Adam Thompson

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Background: In 2013, the Kano State Primary Health Care Management Board redesigned its Routine immunization supply chain from diffused pull to direct delivery push. It addressed issues around stockouts and reduced time spent by health facility staff collecting, and reporting on vaccine usage. The health care board sought the help of a 3PL for twice-monthly deliveries from its cold store to 484 facilities across 44 local governments. eHA’s Health Delivery Systems group formed a 3PL to serve 326 of these new facilities in partnership with the State. We focused on designing and implementing a technology system throughout. Basic methodologies: GIS Mapping: - Planning the delivery of vaccines to hundreds of health facilities requires detailed route planning for delivery vehicles. Mapping the road networks across Kano and Bauchi with a custom routing tool provided information for the optimization of deliveries. Reducing the number of kilometers driven each round by 20%, - reducing cost and delivery time. Direct Delivery Information System: - Vaccine Direct Deliveries are facilitated through pre-round planning (driven by health facility database, extensive GIS, and inventory workflow rules), manager and driver control panel customizing delivery routines and reporting, progress dashboard, schedules/routes, packing lists, delivery reports, and driver data collection applications. Move: Last Mile Logistics Management System: - MOVE has improved vaccine supply information management to be timely, accurate and actionable. Provides stock management workflow support, alerts management for cold chain exceptions/stock outs, and on-device analytics for health and supply chain staff. Software was built to be offline-first with user-validated interface and experience. Deployed to hundreds of vaccine storage site the improved information tools helps facilitate the process of system redesign and change management. Findings: - Stock-outs reduced from 90% to 33% - Redesigned current health systems and managing vaccine supply for 68% of Kano’s wards. - Near real time reporting and data availability to track stock. - Paperwork burdens of health staff have been dramatically reduced. - Medicine available when the community needs it. - Consistent vaccination dates for children under one to prevent polio, yellow fever, tetanus. - Higher immunization rates = Lower infection rates. - Hundreds of millions of Naira worth of vaccines successfully transported. - Fortnightly service to 326 facilities in 326 wards across 30 Local Government areas. - 6,031 cumulative deliveries. - Over 3.44 million doses transported. - Minimum travel distance covered in a round of delivery is 2000 kms & maximum of 6297 kms. - 153,409 kms travelled by 6 drivers. - 500 facilities in 326 wards. - Data captured and synchronized for the first time. - Data driven decision making now possible. Conclusion: eHA’s Vaccine Direct delivery has met challenges in Kano and Bauchi State and provided a reliable delivery service of vaccinations that ensure t health facilities can run vaccination clinics for children under one. eHA uses innovative technology that delivers vaccines from Northern Nigerian zonal stores straight to healthcare facilities. Helped healthcare workers spend less time managing supplies and more time delivering care, and will be rolled out nationally across Nigeria.

Keywords: direct delivery information system, health delivery system, GIS mapping, Northern Nigeria, vaccines

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Authors: Pius A. Onobhayedo, Eugene A. Ohu

Abstract:

Nigeria has one of the fastest growing mobile telecommunications industry in the world. In the absence of fixed connection access to the Internet, access to the Internet is primarily via mobile devices. It, therefore, provides a test case for how to penetrate the mobile market in an emerging economy. We also hope to contribute to a sparse literature on strategies employed in building successful data-driven mobile businesses in emerging economies. We, therefore, sought to identify and analyse the strategic approach taken in a successful locally born mobile data-driven business in Nigeria. The analysis was carried out through the framework of strategic intent and competitive advantages developed from the conception of the company to date. This study is based on an exploratory investigation of an innovative digital company based in Nigeria specializing in the mobile advertising business. The projected growth and high adoption of mobile in this African country, coinciding with the smartphone revolution triggered by the launch of iPhone in 2007 opened a new entrepreneurial horizon for the founder of the company, who reached the conclusion that ‘the future is mobile’. This dream led to the establishment of three digital businesses, designed for convergence and complementarity of medium and content. The mobile Ad subsidiary soon grew to become a truly African network with operations and campaigns across West, East and South Africa, successfully delivering campaigns in several African countries including Nigeria, Kenya, South Africa, Ghana, Uganda, Zimbabwe, and Zambia amongst others. The company recently declared a 40% year-end profit which was nine times that of the previous financial year. This study drew from an in-depth interview with the company’s founder, analysis of primary and secondary data from and about the business, as well as case studies of digital marketing campaigns. We hinge our analysis on the strategic intent concept which has been proposed to be an engine that drives the quest for sustainable strategic advantage in the global marketplace. Our goal was specifically to identify the strategic intents of the founder and how these were transformed creatively into processes that may have led to some distinct competitive advantages. Along with the strategic intents, we sought to identify the respective absorptive capacities that constituted favourable antecedents to the creation of such competitive advantages. Our recommendations and findings will be pivotal information for anybody wishing to invest in the world’s fastest technology business space - Africa.

Keywords: Africa, competitive advantage, competitive strategy, digital, mobile business, marketing, strategic intent

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