Search results for: George Thomas

Authors: Li Long, Thomas Ortlepp

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The transport properties of carriers in polycrystalline silicon film affect the performance of polycrystalline silicon-based devices. They depend strongly on the grain structure, grain boundary trap properties and doping concentration, which in turn are determined by the film deposition and processing conditions. Based on the properties of charge carriers, phonons, grain boundaries and their interactions, the thermoelectric properties of polycrystalline silicon are analyzed with the relaxation time approximation of the Boltz- mann transport equation. With this approach, thermal conductivity, electrical conductivity and Seebeck coefficient as a function of grain size, trap properties and doping concentration can be determined. Experiment on heavily doped polycrystalline silicon is carried out and measurement results are compared with the model.

Keywords: conductivity, polycrystalline silicon, relaxation time approximation, Seebeck coefficient, thermoelectric property

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Authors: Robert K. Hillyard, Jonathan Thomas, Brett A. Story

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Compressed Stabilized Earth Blocks (CSEB) are masonry units that combine soil, sand, stabilizer, and water under pressure to form an earth block. These CSEB’s offer a cost-effective building solution for remote construction, using local resources and labor to minimize transportation and material costs. However, CSEB’s, and earthen construction generally have not been widely adopted as standardized construction materials. One shortcoming is the difficulty in standardizing strength values of CSEB units and systems due to the inherent variations in mix design, including production compression. This research presents findings on compressive strengths of full-scale CSEB’s from 60 different mix designs as a function of the amount of cement, sand, soil, and water added to the mixture. The full-scale results are compared with CSEB cylinder cores.

Keywords: CSEB, compressive strength, earth construction, mix design

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Authors: Thomas Ogilegwu Orohu

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This paper highlights the effect of education on farmers’ productivity in rural Nigeria which includes potential to obtain paid employment or generate income through self-help employment using skills learnt in school. The paper emphasizes that education help farmers’ in agro-processing units in production to reduce post harvest wastage. It highlights the benefits of schooling for farmers’ productivity, particularly in terms of efficiency gains and increased farm productivity. As technological innovation spread more widely within the country, the importance of formal education in farm production ought to become more apparent. Education help farmers to improve attitudes, beliefs and habits that may lead to greater willingness to accept risk, adopts innovation, save investment and generally to embrace productive practices. Finally factors affecting farmers’ education and appropriate recommendation were given with the hope that if resolutely implemented would bring the attainment of desired farm education to farmers to improve farm productivity outputs.

Keywords: benefit, education, effect, productivity

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Authors: Aline M. C. Santoro, João C. Pantoja, Eduardo P. Rossetti

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While the aim of the modernist movement was to deny known typology, the creation of a new formal language also gave it new meaning, which was now related to Form. This is specifically true in the modern capital of Brazil, where Niemeyer sought to demonstrate the manner in which the new materials available, such as reinforced concrete, were able to produce innovative forms. With this study, we aim to demonstrate the relationship between Niemeyer’s forms and the topological typology known as tessellation, through the presentation of two case studies, the Monument to Caxias and the Saint George Orthodox Church. At a first glance, our purpose is to present the definition of Form, especially with relationship to the works of Niemeyer, seeking to identify in them the concepts presented by Moussavi. Afterwards, we will use a computer-based approach to study and model the forms of two of his buildings with the McNeel Rhinoceros program, where, with the aid of diagrams and renderings, we will be able to clearly and legibly represent their organic forms and further understand their structural systems. When we recognise the concept of typology as a starting point for structural form, it can be concluded that the case studies presented here are encompassed by the typology presented by Moussavi since they derive from his basic structural systems.

Keywords: form, Niemeyer, structure, typology, topology

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Authors: Hyu Sang Jo, Gyo Woo Lee

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In this study, the evaluation of thermal stability of the micrometer-sized silica particle reinforced epoxy composite was carried out through the measurement of thermal expansion coefficient and Young’s modulus of the specimens. For all the specimens in this study from the baseline to those containing 50 wt% silica filler, the thermal expansion coefficients and the Young’s moduli were gradually decreased down to 20% and increased up to 41%, respectively. The experimental results were compared with filler-volume-based simple empirical relations. The experimental results of thermal expansion coefficients correspond with those of Thomas’s model which is modified from the rule of mixture. However, the measured result for Young’s modulus tends to be increased slightly. The differences in increments of the moduli between experimental and numerical model data are quite large.

Keywords: thermal stability, silica-reinforced, epoxy composite, coefficient of thermal expansion, empirical model

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Authors: Cherity A. Ysquierdo, Pia U. Olafson, Donald B. Thomas

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Musca domestica L. were collected from cattle diagnosed with bovine ringworm to evaluate the potential of the house fly to disseminate Trichophyton verrucosum E. Bodin, a fungal dermatophyte that is the causative agent for ringworm in cattle. Fungal isolates were cultured from 45 individual flies on supplemented Sabouraud dextrose agar, and isolates were identified using morphological and microscopic approaches. Each isolate was further identified by PCR amplification of the ribosomal DNA locus with fungal specific primers and subsequent amplicon sequencing. No T. verrucosum were identified using these approaches. However, 36 different fungal species representing 17 genera were cultured from these flies, including several allergenic and pathogenic species. Several species within the fungal orders Hypocreales, Microascales, Onygenales, Saccharomycetales, Xylaniales, and Agaricales were observed for the first time on house flies. The most frequent fungus recovered was Cladosporium cladosporoides, which is known to be a ubiquitous, airborne allergen.

Keywords: bovine ringworm, Cladosporium, dermatophyte, Musca domestica

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Authors: Thomas Yeboah, Gifty Akouko Sarpong

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Every learner has a specific learning style that helps him/her to study best. This means that any learning method (e-learning method or traditional face-to-face method) a learner chooses should address the learning style of the learner. Therefore, the main purpose of this research is to investigate whether learners’ grade achievement in e-learning environment is improved for learners with a particular learning style. In this research, purposive sampling technique was employed for selecting the sample size of three hundred and twenty (320) students studying a course UGRC 140 Science and Technology in our Lives at Christian Service University College. Data were analyzed by using, percentages, T -test, and one-way ANOVA. A thorough analysis was done on the data collected and the results revealed that learners with the Assimilator learning style and the converger learning style obtained higher grade achievement than both diverger learning style and accommodative learning style. Again, the results also revealed that accommodative learning style was not good enough for e-learning method.

Keywords: e-learning, learning style, grade achievement, accomodative, divergent, convergent, assimilative

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Authors: Sachin Singh, Thomas Penzel, Dinesh Nandan

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Accurate identification of Sleep Apnea Hypopnea Syndrom Diagnosis is difficult problem for human expert because of variability among persons and unwanted noise. This paper proposes the diagonosis of Sleep Apnea Hypopnea Syndrome (SAHS) using airflow, ECG, Pulse and SaO2 signals. The features of each type of these signals are extracted using statistical methods and ANN learning methods. These extracted features are used to approximate the patient's Apnea Hypopnea Index(AHI) using sample signals in model. Advance signal processing is also applied to snore sound signal to locate snore event and SaO2 signal is used to support whether determined snore event is true or noise. Finally, Apnea Hypopnea Index (AHI) event is calculated as per true snore event detected. Experiment results shows that the sensitivity can reach up to 96% and specificity to 96% as AHI greater than equal to 5.

Keywords: neural network, AHI, statistical methods, autoregressive models

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Authors: Aitor Barbero-López, Soumaya Chibily, Gerhard Scheepers, Thomas Grahn, Martti Venäläinen, Antti Haapala

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Wood decay is addressed continuously within the wood industry through use and development of wood preservatives. The increasing awareness on the negative effects of many chemicals towards the environment is causing political restrictions in their use and creating more urgent need for research on green alternatives. This paper discusses some of the possible natural extracts for wood preserving applications and compares the analytical methods available for testing their behavior and efficiency against decay fungi. The results indicate that natural extracts have interesting chemical constituents that delay fungal growth but vary in efficiency depending on the chemical concentration and substrate used. Results also suggest that presence and redistribution of preservatives in wood during exposure trials can be assessed by spectral imaging methods although standardized methods are not available. This study concludes that, in addition to the many standard methods available, there is a need to develop new faster methods for screening potential preservative formulation while maintaining the comparability and relevance of results.

Keywords: analytics, methods, preservatives, wood decay

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Authors: Wilhelm Hoeflinger, Thomas Laminger, Johannes Wolfslehner

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For vacuum cleaned dust filters, used e. g. in textile industry, there exist no calculation methods to determine design parameters (e. g. traverse speed of the nozzle, filter area...). In this work a method to calculate the optimum traverse speed of the nozzle of an industrial-size flat dust filter at a given mean pressure drop and filter face velocity was elaborated. Well-known equations for the design of a cleanable multi-chamber bag-house-filter were modified in order to take into account a continuously regeneration of a dust filter by a nozzle. Thereby, the specific filter medium resistance and the specific cake resistance values are needed which can be derived from filter tests under constant operation conditions. A lab-scale filter test rig was used to derive the specific filter media resistance value and the specific cake resistance value for vacuum cleaned filter operation. Three different filter media were tested and the determined parameters were compared to each other.

Keywords: design of dust filter, dust removing, filter regeneration, operation parameters

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Authors: A. Abiodun, G. George, B. Longo-Mbenza, E. Blanco-Blanco

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Objective: To determine the prevalence and determinants of iron-deficiency anaemia in pregnant Xhosa women practising geophagia. Methods: This cross-sectional study was conducted among pregnant Xhosa women from rural areas of Mthatha, South Africa, according to socio-demographic, geophagia, haematologic and iron metabolism profiles using univariate and multivariate analyses. Anaemia was defined by haemoglobin <11 g/dL and iron deficiency was defined by serum ferritin < 12 ug/L. Results: Out of 210 pregnant women (mean age =23±5.3 for geophagic and 25.6±5.3 for non-geophagic), 51.4% (n = 108) had iron deficiency anaemia (50.9% geophagic and 49.1% non-geophagic). After adjusting for confounders, only geophagia (OR=2.1 95% CI 1.1-4.2; P=0.029) and mean corpuscular haemoglobin concentration categories (< 30.5 g/dL with OR=16.6 95% CI 6.8-40.2; P < 0.0001; 30.5-31.5 g/dL with OR=2.9 95% CI 1.4-6.1; P=0.006; and ≥ 31.5 g/dL with OR=1) were identified as the most important significant and independent determinants of iron deficiency anaemia. Conclusion: The study results point to the potential harm geophagia can cause in pregnant women. The prevalence of iron deficiency anaemia is unacceptably high. Geophagic behaviour, low MCHC presented as particular risk factors of iron deficiency anaemia in this study. Education and counselling about appropriate diet during pregnancy and prevention of geophagic behaviour (and health consequences) are needed among pregnant Xhosa women.

Keywords: geophagia, pregnancy, iron deficiency anaemia, Xhosa

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Authors: Luong A. Nguyen, Elihu Deneke, Thomas L. Harman

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This paper describes a multibody dynamics algorithm formulated for parallel implementation on multiprocessor computing platforms using the divide-and-conquer approach. The system of interest is a general topology of rigid and elastic articulated bodies with or without loops. The algorithm is an extension of Featherstone’s divide and conquer approach to include the flexible-body dynamics formulation. The equations of motion, configured for the International Space Station (ISS) with its robotic manipulator arm as a system of articulated flexible bodies, are implemented in separate computer processors. The performance of this divide-and-conquer algorithm implementation in multiple processors is compared with an existing method implemented on a single processor.

Keywords: multibody dynamics, multiple processors, multithreading, divide-and-conquer algorithm, computational efficiency, flexible body dynamics

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Authors: Jameela Ali Alkrimi, Abdul Rahim Ahmad, Azizah Suliman, Loay E. George

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Red blood cells (RBCs) are among the most commonly and intensively studied type of blood cells in cell biology. The lack of RBCs is a condition characterized by lower than normal hemoglobin level; this condition is referred to as 'anemia'. In this study, a software was developed to isolate RBCs by using a machine learning approach to classify anemic RBCs in microscopic images. Several features of RBCs were extracted using image processing algorithms, including principal component analysis (PCA). With the proposed method, RBCs were isolated in 34 second from an image containing 18 to 27 cells. We also proposed that PCA could be performed to increase the speed and efficiency of classification. Our classifier algorithm yielded accuracy rates of 100%, 99.99%, and 96.50% for K-nearest neighbor (K-NN) algorithm, support vector machine (SVM), and neural network ANN, respectively. Classification was evaluated in highly sensitivity, specificity, and kappa statistical parameters. In conclusion, the classification results were obtained for a short time period with more efficient when PCA was used.

Keywords: red blood cells, pre-processing image algorithms, classification algorithms, principal component analysis PCA, confusion matrix, kappa statistical parameters, ROC

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Authors: Merle Bischoff, Thomas Gries, Gunnar Seide

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Nanocomposites have become more and more important as the implementation of nanoparticles in polymer allows additional functions in common industrial parts. Especially in the fabrication of filaments or fibres nanomodification is important, as only very small fillers can be added to the very fine fibres (common diameter is 20 µm, fine filament are 1 µm). Discharging fibres, conductive fibres, and many other functional fibres raise in their importance nowadays. Especially the dispersion quality is essential for the final enhancement of the filament propertied. In this paper, the dispersion of carbon nanoparticles in polymer melt is enhanced by a newly developed sonication unit of ITA and BANDELIN electronic GmbH & Co. KG. The first development steps of the unit fabrication, as well as the first experimental results of the modification of the dispersion, are shown. Special focus will be laid on the sealing of the new sonication unit as well as the positioning and equipment size when being implemented in an existing melt spinning unit. Furthermore, the influence on the thereby manufactured nano-modified filaments will be shown.

Keywords: dispersion, sonication, carbon nanoparticles, filaments

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Authors: M. V. Manoj Kumar, Likewin Thomas, Annappa

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Process mining provides methods and techniques for analyzing event logs recorded in modern information systems that support real-world operations. While analyzing an event-log, state-of-the-art techniques available in process mining believe that the operational process as a static entity (stationary). This is not often the case due to the possibility of occurrence of a phenomenon called concept drift. During the period of execution, the process can experience concept drift and can evolve with respect to any of its associated perspectives exhibiting various patterns-of-change with a different pace. Work presented in this paper discusses the main aspects to consider while addressing concept drift phenomenon and proposes a method for detecting and localizing the sudden concept drifts in control-flow perspective of the process by using features extracted by processing the traces in the process log. Our experimental results are promising in the direction of efficiently detecting and localizing concept drift in the context of process mining research discipline.

Keywords: abrupt drift, concept drift, sudden drift, control-flow perspective, detection and localization, process mining

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Authors: Justin Reverdi, Sixin Zhang, Serge Gratton, Said Aoues, Thomas Pellegrini

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In Vapor Cycle Systems, the flow sensor plays a key role in different monitoring and control purposes. However, physical sensors can be expensive, inaccurate, heavy, cumbersome, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor based on other standard sensors is a good alternative. In this paper, a data-driven model using a Convolutional Neural Network is proposed to estimate the flow of the compressor. To fit the model to our dataset, we tested different loss functions. We show in our application that a Dynamic Time Warping based loss function called DILATE leads to better dynamical performance than the vanilla mean squared error (MSE) loss function. DILATE allows choosing a trade-off between static and dynamic performance.

Keywords: deep learning, dynamic time warping, vapor cycle system, virtual sensor

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Authors: Dimitris E. Kontaxis, George Litainas, Dimitris P. Ptochos

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Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real-time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination, and sustainability of the supply chain procedures. The technology, the features, and the characteristics of a complete, proprietary system, including hardware, firmware, and software tools -developed in the context of a co-funded R&D programme- are addressed and presented in this paper.

Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform

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Authors: Glykeria A. Visvini, George Ν. Mathioudakis, Amaia Soto Beobide, George A. Voyiatzis

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Polymer nanocomposites are materials in which a polymer matrix is reinforced with nanoscale inclusions, such as nanoparticles, nanoplates, or nanofibers. These nanoscale inclusions can significantly enhance the mechanical, thermal, electrical, and other properties of the polymer matrix, making them attractive for a wide range of industrial applications. These properties can be tailored by adjusting the type and the concentration of the nanoinclusions, which provides a high degree of flexibility in their design and development. An important property that polymeric membranes can exhibit is water vapor permeability (WVP). This can be accomplished by various methods, including the incorporation of micro/nano-fillers into the polymer matrix. In this way, a micro/nano-pore network can be formed, allowing water vapor to permeate through the membrane. At the same time, the membrane can be stretched uni- or bi-axially, creating aligned or cross-linked micropores in the composite, respectively, which can also increase the WVP. Nowadays, in industry, stretched films reinforced with CaCO3 develop micro-porosity sufficient to give them breathability characteristics. Carbon-based nanomaterials, such as graphene oxide (GO), are tentatively expected to be able to effectively improve the WVP of corresponding composite polymer films. The presence in the GO structure of various functional oxidizing groups enhances its ability to attract and channel water molecules, exploiting the unique large surface area of graphene that allows the rapid transport of water molecules. Polypropylene (PP) is widely used in various industrial applications due to its desirable properties, including good chemical resistance, excellent thermal stability, low cost, and easy processability. The specific properties of PP are highly influenced by its crystalline behavior, which is determined by its processing conditions. The development of the β-crystalline phase in PP, in combination with stretching, is anticipating improving the microporosity of the polymer matrix, thereby enhancing its WVP. The aim of present study is to create breathable PP composite membranes using carbon-based nanomaterials, such as graphene oxide (GO), reduced graphene oxide (rGO), and graphene nanoplatelets (GNPs). Unlike traditional methods that rely on the drawing process to enhance the WVP of PP, this study intents to develop a low-cost approach using melt mixing with β-nucleating agents and carbon fillers to create highly breathable PP composite membranes. The study aims to investigate how the concentration of these additives affects the water vapor transport properties of the resulting PP films/membranes. The presence of β-nucleating agents and carbon fillers is expected to enhance β-phase growth in PP, while an alternation between β- and α-phase is expected to lead to improved microporosity and WVP. Our ambition is to develop highly breathable PP composite films with superior performance and at a lower cost compared to the benchmark. Acknowledgment: This research has been co‐financed by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship and Innovation, under the call «Special Actions "AQUACULTURE"-"INDUSTRIAL MATERIALS"-"OPEN INNOVATION IN CULTURE"» (project code: Τ6YBP-00337)

Keywords: carbon based nanomaterials, nanocomposites, nucleating agent, polypropylene, water vapor permeability

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Authors: Elaheh Hosseini, Otmar Bock, Monika Thomas

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The purpose of the present study was to determine the effect of climbing therapy on the components of attention of children with attention-deficit hyperactivity disorder (ADHD). Forty children with ADHD were assigned to either an intervention group or a control group. The exercise group participated in a climbing therapy program for ten weeks, whereas no intervention was administered to the control group. All two groups were then assessed with the same battery of attention tests used in our earlier study. We found that compared to the ‘intervention’ group, performance was higher in the ‘control’ group on tests of sustained, divided and distributed attention, on all four tests. The intervention group showed a significant improvement in components of attention after ten weeks. From this we conclude that climbing therapy can improve the attention of children with ADHD and can be considered as a promising intervention and a standalone treatment for children with ADHD.

Keywords: ADHD, climbing therapy, distributed attention, divided attention, selective attention, sustained attention

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

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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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Authors: Eman A. Gani, Loay E. George, Faisel G. Mohammed, Kamal H. Sager

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Digital retinal images are more appropriate for automatic screening of diabetic retinopathy systems. Unfortunately, a significant percentage of these images are poor quality that hinders further analysis due to many factors (such as patient movement, inadequate or non-uniform illumination, acquisition angle and retinal pigmentation). The retinal images of poor quality need to be enhanced before the extraction of features and abnormalities. So, the segmentation of retinal image is essential for this purpose, the segmentation is employed to smooth and strengthen image by separating the background and damaged areas from the overall image thus resulting in retinal image enhancement and less processing time. In this paper, methods for segmenting colored retinal image are proposed to improve the quality of retinal image diagnosis. The methods generate two segmentation masks; i.e., background segmentation mask for extracting the background area and poor quality mask for removing the noisy areas from the retinal image. The standard retinal image databases DIARETDB0, DIARETDB1, STARE, DRIVE and some images obtained from ophthalmologists have been used to test the validation of the proposed segmentation technique. Experimental results indicate the introduced methods are effective and can lead to high segmentation accuracy.

Keywords: retinal images, fundus images, diabetic retinopathy, background segmentation, damaged areas segmentation

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Authors: Michael Bellas, George Voulgaridis

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This paper refers to the world known mega - landslide induced at the community of Ropoto, belonging to the Municipality of Trikala, in the Central part of Greece. The landslide affected the debris as well as the colluvium mantle of the flysch, and makes up a special case of study in engineering geology and geotechnical engineering not only because of the size of the domain affected by the landslide (approximately 750m long), but also because of the geostructure’s global behavior. Due to the landslide, the whole community’s infrastructure massively collapsed and human lives were put in danger. After the complete simulation of the coupled Seepage - Deformation phenomenon due to the extreme rainfall, and by closely examining the slope’s global behavior, both the mitigation of the landslide, as well as, an advanced surveillance method (Fiber Bragg Grating) using fiber optics were further studied, in order both to retain the geostructure and to monitor its health by creating an early warning system, which would serve as a complete safety net for saving both the community’s infrastructure as well as the lives of its habitats.

Keywords: landslide, remediation measures, the finite element method (FEM), Fiber Bragg Grating (FBG) sensing method

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Authors: Ani Thomas

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Every narrative is a temporal construct. Every narrative creates a qualitative experience of time for the viewer. The paper argues for the concept of a qualified time that emerges from the interaction between the narrative and the audience. The paper also challenges the conventional understanding of narrative time as either story time, real time or discourse time. Looking at narratives through the medium of Cinema, the study examines how narratives create and manipulate duration or durée, the qualitative experience of time as theorized by Henri Bergson. The paper further analyzes how Cinema and, by extension, narratives are nothing but Durée and the filmmaker, the artist of durée, who shape and manipulate the perception and emotions of the viewer through the manipulation and construction of durée. The paper draws on cinematic works to look at the techniques to demonstrate how filmmakers use, for example, editing, sound, compositional and production narratives etc., to create various modes of durée that challenge, amplify or unsettle the viewer’s sense of time. Bringing together the Viewer’s durée and exploring its interaction with the narrative construct, the paper explores the emergence of the new qualitative time, the narrative durée, that defines the audience experience.

Keywords: cinema, time, bergson, duree

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

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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

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Authors: Fiona Tan, Cheryl Tan, Thomas Wong, Remesh

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Background: An increasing number of working adults undergo knee arthroplasty in Singapore. There is limited data concerning Southeast Asian patients returning to work (RTW) following knee replacement surgery. Our aim was to identify and study factors influencing patients' RTW following total knee arthroplasty (TKA) or unicompartmental knee arthroplasty (UKA). Methods: Patients who underwent TKA or UKA between August 2017 to March 2020 in our center were included in this study. Outcomes include RTW and duration prior to RTW. Results: 441 patients underwent TKA (295 women, 146 men, mean age 67.3 years), and 69 underwent UKA (48 women, 21 men, mean age 61.1 years). Patients who underwent TKA returned to work earlier (mean 83.7 ± 27.1 days) compared to UKA (mean 94.4 ± 42.3 days). 90.0% of TKA patients RTW compared to 95.5% who underwent UKA. Of patients who RTW, 94.3% of the TKA group returned to employment of the same nature compared to 92.9% of UKA patients. Patients who RTW were of a younger age (p = 0.03), white-collared workers (p = 0.04), and had independent preoperative ambulatory status (p <0.01). Conclusion: Younger and independently ambulating patients may have a better capacity for rehabilitation and RTW post-arthroplasty surgery.

Keywords: return to work, total knee arthroplasty, unilateral knee arthroplasty, employment

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Authors: Thomas Ogilegwu Orohu

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This paper presents agricultural education as a vocational study, an impetus for youths, economic empowerment. The survival of Nigeria’s agriculture rests squarely on the youth who are the farmers and leaders of tomorrow. Hitherto, the teaching and learning of agriculture has proceeded in such a manner that graduates of such programs have failed to make the successful launch into the world of agricultural enterprises (entrepreneurship). Major constraints that predisposed this anomalous situation were identified to include poor policy framework, socio-economic pressures, undue parental and peer influences, improper value orientation and of course, the nature of curricula. In response to the situation, some programs and/or initiatives aimed at inculcating entrepreneurial skills were proposed by this paper with identified target beneficiaries. The initiatives bordered on curricular reorientation that integrate entrepreneurship/enterprise education, retraining of graduates, financial support system among others.

Keywords: Program initiatives. vocational agriculture, youths’ empowerment, introduction

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Authors: Christoph Linse, Thomas Martinetz

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Recent findings have shown that Neural Networks generalize also in over-parametrized regimes with zero training error. This is surprising, since it is completely against traditional machine learning wisdom. In our empirical study we fortify these findings in the domain of fine-grained image classification. We show that very large Convolutional Neural Networks with millions of weights do learn with only a handful of training samples and without image augmentation, explicit regularization or pretraining. We train the architectures ResNet018, ResNet101 and VGG19 on subsets of the difficult benchmark datasets Caltech101, CUB_200_2011, FGVCAircraft, Flowers102 and StanfordCars with 100 classes and more, perform a comprehensive comparative study and draw implications for the practical application of CNNs. Finally, we show that VGG19 with 140 million weights learns to distinguish airplanes and motorbikes with up to 95% accuracy using only 20 training samples per class.

Keywords: convolutional neural networks, fine-grained image classification, generalization, image recognition, over-parameterized, small data sets

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Authors: Sharmila Pradhan, Ralf Lach, George Michler, Jean Mark Saiter, Rameshwar Adhikari

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Ethylene/1-octene copolymer was modified incorporating three types of nanofillers differed in their dimensionality in order to investigate the effect of filler dimensionality on mechanical properties, for instance, tensile strength, microhardness etc. The samples were prepared by melt mixing followed by compression moldings. The microstructure of the novel material was characterized by Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD) method and Transmission electron microscopy (TEM). Other important properties such as melting, crystallizing and thermal stability were also investigated via differential scanning calorimetry (DSC) and Thermogravimetry analysis (TGA). The FTIR and XRD results showed that the composites were formed by physical mixing. The TEM result supported the homogeneous dispersion of nanofillers in the matrix. The mechanical characterization performed by tensile testing showed that the composites with 1D nanofiller effectively reinforced the polymer. TGA results revealed that the thermal stability of pure EOC is marginally improved by the addition of nanofillers. Likewise, melting and crystallizing properties of the composites are not much different from that of pure.

Keywords: copolymer, differential scanning calorimetry, nanofiller, tensile strength

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Authors: E. O. George, P. Ojeaga, D. Odejimi, O. Mattehws

Abstract:

Has macroeconomic management succeeded in making privatization promote growth in Africa? What are the probable strategies that should accompany the privatization reform process to promote growth in Africa? To what extent has the privatization process succeeded in attracting foreign direct investment to Africa? The study investigates the relationship between macroeconomic management and privatization. Many African countries have embarked on one form of privatization reform or the other since 1980 as one of the stringent conditions for accessing capital from the IMF and the World Bank. Secondly globalization and the gradually integration of the African economy into the global economy also means that Africa has to strategically develop its domestic market to cushion itself from fluctuations and probable contagion associated with global economic crisis that are always inevitable Stiglitz. The methods of estimation used are the OLS, linear mixed effects (LME), 2SLS and the GMM method of estimation. It was found that macroeconomic management has the capacity to affect the success of the privatization reform process. It was also found that privatization was not promoting growth in Africa; privatization could promote growth if long run growth strategies are implemented together with the privatization reform process. Privatization was also found not to have the capacity to attract foreign investment to many African countries.

Keywords: Africa, political economy, game theory, macroeconomic management and privatization

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Authors: Martin Doran, Roy Sterritt, George Wilkie

Abstract:

The majority of today’s mobile robots are very dependent on battery power. Mobile robots can operate untethered for a number of hours but eventually they will need to recharge their batteries in-order to continue to function. While computer processing and sensors have become cheaper and more powerful each year, battery development has progress very little. They are slow to re-charge, inefficient and lagging behind in the general progression of robotic development we see today. However, batteries are relatively cheap and when fully charged, can supply high power output necessary for operating heavy mobile robots. As there are no cheap alternatives to batteries, we need to find efficient ways to manage the power that batteries provide during their operational lifetime. This paper proposes the use of autonomic principles of self-adaption to address the behavioral changes a battery experiences as it gets older. In life, as we get older, we cannot perform tasks in the same way as we did in our youth; these tasks generally take longer to perform and require more of our energy to complete. Batteries also suffer from a form of degradation. As a battery gets older, it loses the ability to retain the same charge capacity it would have when brand new. This paper investigates how we can adapt the current state of a battery charge and cycle count, to the requirements of a mobile robot to perform its tasks.

Keywords: autonomic, self-adaptive, self-optimising, degradation

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