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Showing results [1885 - 1904] / 3412
  • Authors: Osman, Ahmed I.; Zhang, Yubing; Lai, Zhi Ying;  Advisor: -;  Co-Author: - (2023)

    Traditional fertilizers are highly inefficient, with a major loss of nutrients and associated pollution. Alternatively, biochar loaded with phosphorous is a sustainable fertilizer that improves soil structure, stores carbon in soils, and provides plant nutrients in the long run, yet most biochars are not optimal because mechanisms ruling biochar properties are poorly known. This issue can be solved by recent developments in machine learning and computational chemistry. Here we review phosphorus-loaded biochar with emphasis on computational chemistry, machine learning, organic acids, drawbacks of classical fertilizers, biochar production, phosphorus loading, and mechanisms of phosphoro...
  • Authors: Youngjung, Suh;  Advisor: -;  Co-Author: - (2023)

    Customer churn is a major issue for large enterprises. In particular, in the rental business sector, companies are looking for ways to retain their customers because they are their main source of revenue. The main contribution of our work is to analyze the customer behavior information of actual water purifier rental company, where customer churn occurs very frequently, and to develop and verify the churn prediction model. A machine learning algorithm was applied to a large-capacity operating dataset of rental care service in an electronics company in Korea, to learn meaningful features. To measure the performance of the model, the F-measure and area under curve (AUC) were adopted whe...
  • Authors: Maria, Carannante; Valeria, D’Amato; Paola, Fersini;  Advisor: -;  Co-Author: - (2023)

    In this paper, we contribute to the topic of the non-performing loans (NPLs) business profitability on the secondary market by developing machine learning-based due diligence. In particular, a loan became non-performing when the borrower is unlikely to pay, and we use the ability of the ML algorithms to model complex relationships between predictors and outcome variables, we set up an ad hoc dependent random forest regressor algorithm for projecting the recovery rate of a portfolio of the secured NPLs. Indeed the profitability of the transactions under consideration depends on forecast models of the amount of net repayments expected from receivables and related collection times. Final...
  • Authors: Silvia E., Zieger; Klaus, Koren;  Advisor: -;  Co-Author: - (2023)

    Simultaneous sensing of metabolic analytes such as pH and O2 is critical in complex and heterogeneous biological environments where analytes often are interrelated. However, measuring all target analytes at the same time and position is often challenging. A major challenge preventing further progress occurs when sensor signals cannot be directly correlated to analyte concentrations due to additional effects, overshadowing and complicating the actual correlations. In fields related to optical sensing, machine learning has already shown its potential to overcome these challenges by solving nested and multidimensional correlations. Hence, we want to apply machine learning models to fluor...
  • Authors: Christian, Birchler; Sajad, Khatiri; Bill, Bosshard;  Advisor: -;  Co-Author: - (2023)

    Simulation platforms facilitate the development of emerging Cyber-Physical Systems (CPS) like self-driving cars (SDC) because they are more efficient and less dangerous than field operational test cases. Despite this, thoroughly testing SDCs in simulated environments remains challenging because SDCs must be tested in a sheer amount of long-running test cases. Past results on software testing optimization have shown that not all the test cases contribute equally to establishing confidence in test subjects’ quality and reliability, and the execution of “safe and uninformative” test cases can be skipped to reduce testing effort. However, this problem is only partially addressed in the co...
  • Authors: Xiaoyu, Zhang; Thien Van, Luong; Periklis, Petropoulos;  Advisor: -;  Co-Author: - (2022)

    End-to-end learning systems are conceived for Orthogonal Frequency Division Multiplexing (OFDM)-aided optical Intensity Modulation paired with Direct Detection (IM/DD) communications relying on the Autoencoder (AE) architecture in deep learning. We first propose an AE-aided Layered ACO-OFDM (LACO-OFDM) scheme, termed as LACONet, for exploiting the increased bandwidth efficiency of LACO-OFDM. LACONet employs a Neural Network (NN) at the transmitter for bit-to-symbol mapping, and another NN at the receiver for recovering the data bits, which together form an AE and can be trained in an end-to-end manner for simultaneously minimizing both the BER and PAPR. Moreover, the detection archite...
  • Authors: Xiaoyu, Zhang; Thien, Van Luong; Periklis, Petropoulos; Lajos, Hanzo;  Advisor: -;  Co-Author: - (2022)

    End-to-end learning systems are conceived for Orthogonal Frequency Division Multiplexing (OFDM)-aided optical Intensity Modulation paired with Direct Detection (IM/DD) communications relying on the Autoencoder (AE) architecture in deep learning. We first propose an AE-aided Layered ACO-OFDM (LACO-OFDM) scheme, termed as LACONet, for exploiting the increased bandwidth efficiency of LACO-OFDM. LACONet employs a Neural Network (NN) at the transmitter for bit-to-symbol mapping, and another NN at the receiver for recovering the data bits, which together form an AE and can be trained in an end-to-end manner for simultaneously minimizing both the BER and PAPR. Moreover, the detection archite...
  • Authors: Thanasis, Zoumpekas; Alexander, Leutgeb; Anna, Puig;  Advisor: -;  Co-Author: - (2023)

    The manufacturing domain is regarded as one of the most important engineering areas. Recently, smart manufacturing merges the use of sensors, intelligent controls, and software to manage each stage in the manufacturing lifecycle. Additionally, the increasing use of point clouds to model real products and machining tools in a virtual space facilitates the more accurate monitoring of the end-to-end production lifecycle. Thus, the conjunction of both, intelligent methods and more accurate 3D models allows the prediction of uncertainties and anomalies in the manufacturing process as well as reduces the final production costs. However, the high complexity of the geometrical structures defi...
  • Authors: Ishraq U., Ahmed; Helen M., Byrne; Mary R., Myerscough;  Advisor: -;  Co-Author: - (2023)

    Atherosclerosis is an inflammatory disease characterised by the formation of plaques, which are deposits of lipids and cholesterol-laden macrophages that form in the artery wall. The inflammation is often non-resolving, due in large part to changes in normal macrophage anti-inflammatory behaviour that are induced by the toxic plaque microenvironment. These changes include higher death rates, defective efferocytic uptake of dead cells, and reduced rates of emigration. We develop a free boundary multiphase model for early atherosclerotic plaques, and we use it to investigate the effects of impaired macrophage anti-inflammatory behaviour on plaque structure and growth.
  • Authors: Sebastijan, Kovačič; Katharina, Gruber; Bernd, Fuchsbichler;  Advisor: -;  Co-Author: - (2023)

    In this article, we demonstrate the fabrication of thin and macroporous carbon coatings that adhere to various metal substrates such as nickel- or aluminum-based foils or meshes. The coating process is a combination of emulsion-templating and the doctor-blade method, which allows to prepare up to 350 µm thick poly(dicyclopentadiene) membranes with a polyHIPE (polymerized high internal phase emulsions) architecture. Carbonization of these poly(dicyclopentadiene) membranes directly on the metal substrates resulted in up to 30-µm-thick foamy carbon coatings that retain the highly porous architecture and flexibility. Subsequently, carbon foam-coated Ni-foils were filled with elemental sul...
  • Authors: Arkebe, Oqubay;  Advisor: -;  Co-Author: - (2015)

    Made in Africa presents the findings of original field research into the design, practice, and varied outcomes of industrial policy in different sectors in Ethiopia. The book explores how and why the outcomes of industrial policy are shaped by particular factors in different industries. The findings are discussed against the backdrop of ‘industrial policy’, which has recently found renewed favour among economists and international organizations, and of the history of thought about and practice in industrialization. The book seeks to learn from the failures and successes in the cement, leather and leather products, and floriculture sectors, all of them functioning under the umbrella of...
  • Authors: Carsten D., Schultz; Björn, Gorlas;  Advisor: -;  Co-Author: - (2023)

    Stationary retailers may introduce new technologies, such as augmented reality, to provide product information and recommendations and thus improve shopping experience. Examples of such augmented reality applications are magic mirrors that enable virtual try-on and may induce cross-buying intention. Based on an experimental scenario and the corresponding results from 301 questionnaires, we find that magic mirrors positively impact consumers’ cross-buying intention. Cross-buying behavior depends particularly on price attractiveness and the aesthetic appeal of the products. Further, men place less emphasis on price attractiveness when considering cross-buying options than women.
  • Authors: Das, Raja;  Advisor: Kalappattil, Vijaysankar; Phan, Manh-Huong; Srikanth, Hariharan;  Co-Author: - (2021)

    Magnetite has fascinated researchers for decades, due to its wide range of applications from spintronics to biomedicine. Despite a large body of works aimed at its magnetic properties, no consensus has been reached on the physical origin of the low temperature magnetic anomalies observed in magnetite. Although, a lot of work has been done in studying magnetite nanoparticles, but studies on the low temperature anomalies in those nanoparticles still remains unresearched. We report on the observation of the low temperature magnetic anomalies in highly crystalline, stoichiometric Fe3O4 nanorods and relate them to the coupled electron hopping relaxation process and domain wall motion. Both...
  • Authors: Mahmud, Nafis; Benamor, Abdelbaki;  Advisor: -;  Co-Author: - (2023)

    Magnetic iron oxide/kaolinite (MK) composite was synthesized using co-precipitation method and characterized by XRD, FTIR, SEM/EDX, TGA, XPS, VSM, and zeta potential analyses. The synthesized composite consisting of kaolinite halloysites with small clusters of iron oxide on its outer surface was used in batch experiments to adsorb Congo red dye at different temperatures. The adsorption data were fitted to three different isotherms with Langmuir adsorption isotherm best fitting the adsorption data. The maximum adsorption capacity of MK adsorbent was found to be around 45.59 mg/g. Adsorption kinetics data obtained at three different temperatures were fitted to pseudo-first-order and pse...
  • Authors: Takuhiro, Uto; Nguyen, Huu Tung; Tomoe, Ohta; Yukihiro, Shoyama;  Advisor: -;  Co-Author: - (2022)

    Magnoliae Flos is a traditional herbal medicine used to treat nasal congestion associated with headache, empyema, and allergic rhinitis. In our preliminary screening of crude drugs used in Japanese Kampo formulas for melanin synthesis, the methanol extract of Magnoliae Flos was found to exhibit strong melanin synthesis activity. However, there have been no studies evaluating the effects of Magnoliae Flos or its constituents on melanogenesis. The present study aimed to isolate the active compounds from Magnoliae Flos that activate melanin synthesis in melanoma cells and three-dimensional human skin equivalent, and to investigate the molecular mechanism underlying melanin induction. The...
  • Authors: Takuhiro, Uto; Nguyen, Huu Tung; Tomoe, Ohta; Yukihiro, Shoyama;  Advisor: -;  Co-Author: - (2022)

    Magnoliae Flos is a traditional herbal medicine used to treat nasal congestion associated with headache, empyema, and allergic rhinitis. In our preliminary screening of crude drugs used in Japanese Kampo formulas for melanin synthesis, the methanol extract of Magnoliae Flos was found to exhibit strong melanin synthesis activity. However, there have been no studies evaluating the effects of Magnoliae Flos or its constituents on melanogenesis. The present study aimed to isolate the active compounds from Magnoliae Flos that activate melanin synthesis in melanoma cells and three-dimensional human skin equivalent, and to investigate the molecular mechanism underlying melanin induction. The...
  • Authors: Naoki, Marumo; Takayuki, Okuno; Akiko, Takeda;  Advisor: -;  Co-Author: - (2023)

    A new Levenberg–Marquardt (LM) method for solving nonlinear least squares problems with convex constraints is described. Various versions of the LM method have been proposed, their main differences being in the choice of a damping parameter. In this paper, we propose a new rule for updating the parameter so as to achieve both global and local convergence even under the presence of a convex constraint set. The key to our results is a new perspective of the LM method from majorization-minimization methods. Specifically, we show that if the damping parameter is set in a specific way, the objective function of the standard subproblem in LM methods becomes an upper bound on the original ob...