Miracle-dz/UniFAR-FTUs huggingface dataset:
A fuzzy maturity model for care pathways

School of Industrial Engineering Master of Science A fuzzy maturity model for care pathways by BSc. M.B. Schriek Student — 0716663 ID — s090685 Process thinking in healthcare is needed and has several followers in industry and the scientific world. Its objective is to focus on managing processes in a more standardized way and gaining efficiency by doing this. To research the use and to determine the level of maturity of this development, a maturity model is developed. The proposed maturity model in this research is constructed using expert knowledge and literature. The model consist of 5 criteria and 19 indicators, which are weighted and aggregated using fuzzy logic. The advantage of this aggregation and assessment technique of the constructed maturity methodology is to translate the way humans think and reason into a specific maturity level. The resulting maturity methodology is tested in 11 hospitals for the care pathway of threatening mamma carcinoma. As a result of these case studies, an insight in the relation between quality and maturity is given. Besides this, the obtained insights of the model were used in further development of the model as a tool.
Efficient morphological tools for astronomical image processing

Nowadays, many applications rely on a huge quantity of images at high resolution and with high quantity of information per pixel, due either to the technological improvements of the instruments or to the type of measurement observed. This thesis is focused on exploring and developing tools and new methods in the framework of Mathematical Morphology, suitable for automatic image processing of astronomical datasets. Identifying and classifying astronomical objects is a challenging task: many of the structures that astronomers are interested into to understand the evolution of galaxies and stars are faint and near to the noise level. A new method to identify astronomical objects is proposed, based on the expected statistical behaviour of the noise across the image structures. The method works by parsing a hierarchical representation of the image data, called max-tree: it allows for image filtering and object identification in an efficient way. A novel parallel algorithm to build max-tree of 2D images and 3D volumes with very high-dynamic-range values is proposed. Besides astronomy, other application fields, like medical and remote sensing image processing, would benefit from that. Effort is put also in classifying the objects found. A parallel method is developed to compute efficiently the pattern spectra. Those are matrices whose values put in relation area and shape information of selected structures in the image. Such matrices are used both to classify different types of galaxies and to identify building footprints in satellite images.
Optimization of Lightweight Encryption Algorithm (LEA) using Threads and Shared Memory of GPU

As big-data and cloud security technologies become popular, many researchers have recently been conducted on faster and lighter encryption. As a result, National Security Research Institute developed LEA which is lightweight and fast block cipher. To date, there have been various studies on lightweight encryption algorithm (LEA) for speeding up using GPU rather than conventional CPU. However, it is rather difficult to explore any guideline how to manipulate the GPU for the efficient usage of the LEA. Therefore, we introduce a guideline which explains how to implement and design the optimal LEA using GPU.
Hydrochemical Fluxes in Bulk Precipitation, Throughfall, and Stemflow in a Mixed Evergreen and Deciduous Broadleaved Forest

Rainfall is one of the primary sources of chemical inputs in forest ecosystems, and the basis of forest nutrient cycling. Mixed evergreen and deciduous broadleaved forests are currently one of the most threatened ecosystems due to their sensitivity to anthropogenic climate change. As such, understanding the hydrochemical fluxes of these systems is critical for managing their dynamics in the future. We investigate the chemistry of bulk precipitation, stemflow and throughfall in a mixed evergreen and deciduous broadleaved forest in the Shennongjia region of Central China. Mean nutrient concentrations in throughfall and stemflow were higher than in bulk precipitation. Stemflow ion fluxes from deciduous tree species were greater than those for evergreen tree species because of the differences in bark morphology and branch architecture. Throughfall and stemflow chemistry fluctuated dramatically over the growing season. Nitrate nitrogen and ammonium nitrogen were retained, while other elements and compounds were washed off or leached via throughfall and stemflow pathways. Our findings will facilitate a greater understanding of nutrient balance in canopy water fluxes.
To Embed or Not to Embed, that is the Question

In this paper we investigate intelligent tutoring communications in game-based learning platforms and examine its effect on perceived flow and immersion. The technology influencing this research is the open-source Generalized Intelligent Framework for Tutoring (GIFT), a domain-independent architecture used to author, deliver, and evaluate intelligent tutoring technologies. Influenced by theoretical underpinnings associated with flow, the resulting experiment looks at the application of Embodied Pedagogical Agents (EPA) in a game-based training environment used for communicating tutor generated feedback. Conditions were structured to examine tradeoffs between embedding an EPA directly in a game, embedding an EPA in GIFT’s browser-based Tutor-User Interface (TUI), or using audio prompts alone. Statistical analyses are presented examining treatment effects on an individual’s perceived sense of flow during interaction, along with examination of game characteristics required to support immersion. Outcomes support the use of an EPA present in GIFT’s TUI when compared to flow outcomes on audio prompts alone and the game embedded EPA.
INVERSION FOR APPLIED GEOPHYSICS: A TUTORIAL

Throughout this book there are numerous cases where geophysics has been used to help solve practical environmental, geotechnical and exploration problems. The typical scenario is first to identify the physical property that is diagnostic of the sought geologic structure or buried object, for example density, seismic velocity, electrical conductivity, or magnetic susceptibility. The appropriate geophysical survey is then designed and field data are acquired and plotted. In some cases the information needed to solve the problem may be obtained directly from these plots, but in most cases more information about the subsurface is required. As an example, consider the magnetic field anomaly map presented in Figure 2. The existence of a buried object, and also approximate horizontal locations, can be inferred directly from that image. The map however, presents no information about the depth of the object or details regarding its shape. To obtain that information the data need to be inverted to generate a 3D subsurface distribution of the magnetic material.
Effective Course Redesign Strategies to Integrate Collaborative PBL in Senior Computer Engineering/Computer Science Courses

This paper presents the accomplishments and comprehensive findings of the NSF sponsored project, entitled “Enhance Computer Network Curriculum using Remote Collaborative Projectbased Learning”. The focus of the project is to explore Collaborative Project-based Learning (CPBL) as a pedagogical approach to address the learning issues of under-prepared minority students, and seek effective implementation strategy to extend the pedagogy beyond the classroom through a remote learning structure. During the three-year project course, a new pedagogical model named as CPBL-beyond-Classroom was developed and its effectiveness has been thoroughly evaluated in iterative classroom implementation. In this paper, we will analyze this pedagogical model to illustrate how it can address the learning needs of minority students on a commuter campus, describe our course redesign process, and introduce effective implementation strategies to address practical challenges in the implementation process. Concrete examples of course redesign with weekly in-class and after-class instructional activities are provided in the paper and the redesign principles can be applied to other engineering/CS courses. In addition, the paper includes longitudinal study results based on 3-year assessment data to highlight the pedagogical impact on various student learning outcomes. In-depth analysis of qualitative responses also allowed us to develop a better understanding on how different pedagogical components in the CPBL-beyond-Classroom model affected the student learning process. These findings are helpful to other educators who are interested in adopting CPBLbeyond-Classroom to redesign their courses based on the learning needs of their own students.
Diachronic dynamics of Middle English phonotactics provide evidence for analogy effects among lexical and morphonotactic consonant clusters

Consonant clusters that rarely occur lexically (i.e. within morphemes) may function as complexity markers when they span a morpheme boundary, i.e. when they occur morphonotactically. In this study we observe patterns in the diachronic dynamics of Middle English which hint at mutually beneficial effects between morphonotactic and lexical clusters. We suggest that the patterns revealed can be explained by frequency-based analogy effects in language acquisition.
Practical guidelines for choosing GLCM textures to use in landscape classification tasks over a range of moderate spatial scales

ABSTRACT Texture measurements quantitatively describe relationships of DN values of neighbouring pixels. The output is a continuous measure of spatial information that may be used for further processing. Spatial relationships are not necessarily correlated with spectral data for a given class, and including a measure of them improves classification accuracy. This research develops a guideline for choosing among the Haralick (Grey Level Co-occurrence Matrix [GLCM]) set of texture measures. These guidelines are derived using a variety of land covers and spatial scales (window sizes). Principal component analysis (PCA) of eight GLCM measures was performed for three Landsat TM and ETM+ images: a mid-latitude agricultural and natural vegetation scene, a glacier–rock–sea ice scene, and a desert scene with dunes and structurally complex rocks. PCA was performed separately for neighbourhoods consisting of squares with 25, 13, and 5 pixels on a side to demonstrate robustness to different spatial scales. PCA loadings show that contrast (Con), dissimilarity, entropy (Ent), and GLCM variance are most commonly associated with visual edges of land-cover patches; homogeneity, GLCM mean, GLCM correlation (GLCM Cor), and angular second moment are associated with patch interiors. Edge-highlighting textures account for most dataset variance but fail to differentiate among classes. Eigenchannels highlighting patch interior characteristics rely on GLCM mean and to some extent GLCM Cor. These two textures do contribute to distinguishing individual class signatures for classification purposes. Ent does not appear consistently in edge or interior groupings. Ent is interpreted as important to the textures of particular classes, but which classes is not generalized from one scene to another. Con is effective for outlining patch edges and may serve for object formation in geographic object-based image analysis (GEOBIA). For classification purposes, the proposed guideline is a choose Mean and, where a class patch is likely to contain edge-like features within it, Con. Cor is an alternative for Mean in these situations, Dis may similarly be used in place of Con. For more detailed texture study, add Ent. This guideline does not constitute a complete texture analysis but may allow confident use of GLCM texture to enhance the efficiency of Landsat-based classification.
The hydroxyproline content of fish bone gelatin from Indonesian Pangasius catfish by enzymatic hydrolysis for producing the bioactive peptide

Abstract. Atma Y, Lioe HN, Prangdimurti E, Seftiono H, Tahufik M, Fitriani D, Mustopa AZ. 2018. The hydroxyproline content on fish bone gelatin from Indonesian Pangasius catfish by enzymatic hydrolysis for producing of bioactive peptide. Biofarmasi J Nat Prod Biochem 16: 64-68. Gelatins has been widely used in food, medicines, cosmetics, photography industries. In the food industry, gelatin used as food additives and functional foods. The applications of gelatin as a functional food due to their bioactivity in a form of peptides. Bioactive peptides from gelatin are mostly obtained through enzymatic hydrolysis processes. This study was conducted to measure the hydroxyproline content of gelatin bone of Indonesian Pangasius catfish (Pangasius sutchi) before and after enzymatic hydrolysis. The hydroxyproline is one of the dominant amino acids in gelatin. Gelatin hydrolysis was carried out using a flavourzyme at concentration of 6% and the incubation series of 0, 4, 6 and 8 hours. The standard concentration of hydroxyproline was used in range of 0-1 μg. The results showed that the linear curve of the hydroxyproline standard solution was y=0.0554x+0.0406, with the coefficient of determination (R²) = 0.9435. The incubation time of enzymatic hydrolysis (6% enzyme concentration) affected the hydroxyproline content. The hydroxyproline from fish bone gelatin was 18.91±2.87 mg/mL, 63.81±1.28 mg/mL, 46.21±1.28 mg/mL and 37.64 ± 0.64 mg/mL respectively during 0, 4, 6 dan 8 h incubation time. This hydroxyproline content was significantly different at 95% confidence level from each treatment time.
Automatic character detection and segmentation in natural scene images

We present a robust connected-component (CC) based method for automatic detection and segmentation of text in real-scene images. This technique can be applied in robot vision, sign recognition, meeting processing and video indexing. First, a Non-Linear Niblack method (NLNiblack) is proposed to decompose the image into candidate CCs. Then, all these CCs are fed into a cascade of classifiers trained by Adaboost algorithm. Each classifier in the cascade responds to one feature of the CC. Proposed here are 12 novel features which are insensitive to noise, scale, text orientation and text language. The classifier cascade allows non-text CCs of the image to be rapidly discarded while more computation is spent on promising text-like CCs. The CCs passing through the cascade are considered as text components and are used to form the segmentation result. A prototype system was built, with experimental results proving the effectiveness and efficiency of the proposed method.
Learner control, user characteristics, platform difference, and their role in adoption intention for MOOC learning in China

Massive open online course (MOOC) learning attracts more and more attention in both the practice and the research field. Finding out what factors influence learners’ MOOC adoption is of great importance. This study focuses on learner control, user characteristics and platform difference. Hypotheses and a research model are proposed by incorporating perceived learner control, e-learning self-efficacy, and personal innovativeness in information technology (PIIT) into the original technology acceptance model (TAM). With the empirical data from 214 MOOC learners, the effects of perceived learner control on perceived usefulness and perceived ease of use are confirmed. E-Learning self-efficacy is found to have positive influence on perceived learner control and ease of use. While the effect of PIIT on perceived learner control is not supported, PIIT influences learners’ perception of usefulness and ease of use. Furthermore, a comparison between foreign and native MOOC platforms shows the former should emphasize ease of use more, and the latter should emphasize usefulness more, to enhance their attractiveness.
Grade 1 Children in Problem-Posing Contexts: Problem Solving Prior to Completing the Task

With support from undergraduate university students, Grade 1 children (aged 6-7 years) were challenged to pose and then solve their own open-ended tasks. The way in which the children engaged in problem solving prior to formulating or posing a problem was explored. An overview of the types of problems posed by the class is presented, along with two detailed case studies. The case studies show that the children were able to identify and discuss the type of mathematics content and strategies they would need to employ in order to successfully complete the task.
Stratigraphy and chronology of the Lammasmägi site at Kunda

The stratigraphy and chronology of the Lammasmagi site at Kunda in northeastern Estonia was investigated by means of a limited trench excavation in 1992. The methods employed included grain size analysis, organic matter content, calcium carbonate, lipids and proteins, diatoms, pollen, plant macro-fossils and bones, together with phosphate analysis and radiocarbon dating. There are indications that only the lowermost stratigraphic unit is in primary position, and the archaeological material suggests that it dates from the early Mesolithic period. The upper layers were reworked after the Mesolithic, younger material having become incorporated in them. Eight new radiocarbon dates are reported, and these together with the microscopic and macroscopic plant remains indicate that the archaeological material was deposited in a telmatic zone which was occasionally influenced by limnic conditions.
Ferroelectric and Ionic-Conductive Properties of Nonlinear-Optical Vanadate, Ca9Bi(VO4)7.

Structural, chemical, and physical properties of whitlockite-type Ca 9 Bi(VO 4 ) 7 were studied by X-ray powder diffraction (XRD), electron diffraction (ED), second-harmonic generation (SHG), thermogravimetry, differential scanning calorimetry, dielectric, and electrical-conductivity measurements. A new phase-transition of the ferroelectric type was found in Ca 9 Bi(VO 4 ) 7 with a transition temperature, T c , of 1053 ± 3 K. The polar phase, β-Ca 9 Bi(VO 4 ) 7 , is stable below T c down to at least 160 K. The centrosymmetric β'-phase is stable above T c up to 1273 ± 5 K. Above 1273 K, it decomposes to give BiVO 4 and whitlockite-type solid solutions of Ca 9+1.5x Bi 1-x (VO 4 ) 7 . The β ↔ β' phase transition is reversible and of second order. Electrical conductivity of β'-Ca 9 Bi(VO 4 ) 7 is rather high (σ = 0.6 x 10 -3 S/cm at 1200 K) and obeys the Arrhenius law with an activation energy of 1.0 eV. Structure parameters of Ca 9 Bi(VO 4 ) 7 are refined by the Rietveld method from XRD data measured at room temperature (space group R3c; Z = 6; a = 10.8992(1) A, c = 38.1192(4) A, and V = 3921.6(1) A 3 ; R wp = 3.06% and Rp = 2.36%). Bi 3+ ions together with Ca 2+ ions are statistically distributed among the M1, M2, M3, and M5 sites. Ca 9 Bi(VO 4 ) 7 has a SHG efficiency of about 140 times that of quartz. Through the powder SHG measurements, we estimated the nonlinear optical susceptibility, (d), at about 6.1-7.2 pm/V. This value for Ca 9 Bi(VO 4 ) 7 is comparable with that for known nonlinear optical materials such as LiNbO 3 and LiTaO 3 .
Improved roach-based algorithms for global optimization problems.

Optimization of systems plays an important role in various fields including mathematics, economics, engineering and life sciences. A lot of real world optimization problems exist across field of endeavours such as engineering design, space planning, networking, data analysis, logistic management, financial planning, risk management, and a host of others. These problems are constantly increasing in size and complexity, necessitating the need for improved techniques. Many conventional approaches have failed to solve complex problems effectively due to increasingly large solution space. This has led to the development of evolutionary algorithms that draw inspiration from the process of natural evolution. It is believed that nature provides inspirations that can lead to innovative models or techniques for solving complex optimization problems. Among the class of paradigm based on this inspiration is Swarm Intelligence (SI). SI is one of the recent developments of evolutionary computation. A SI paradigm is comprised of algorithms inspired by the social behaviour of animals and insects. SI-based algorithms have attracted interest, gained popularity and attention because of their flexibility and versatility. SIbased algorithms have been found to be efficient in solving real world optimization problems. Examples of SI algorithms include Ant Colony Optimization (ACO) inspired by the pheromone trail-following behaviour of ant species; Particle Swarm Optimization (PSO) inspired by flocking and swarming behaviour of insects and animals; and Bee Colony Optimization (BCO) inspired by bees’ food foraging. Recent emerging techniques in SI includes Roach-based Algorithms (RBA) motivated by cockroaches social behaviour. Two recently introduced RBA algorithms are Roach Infestation Optimization (RIO) and Cockroach Swarm Optimization (CSO) which have been applied to some optimization problems to achieve competitive results when compared to PSO. This study is motivated by the promising results of RBA, which have shown that the algorithms have potentials to be efficient tools for solving optimization problems. Extensive studies of existing RBA were carried out in this work revealing the shortcomings such as slow convergence and entrapment in local minima. The aim of this study is to overcome the identified drawbacks. We investigate RBA variants that are introduced in this work by introducing parameters such as constriction factor and sigmoid function that have proved effective for similar evolutionary algorithms in the literature.
Synthesis and Structure-Activity Relationships of Phaffiaol and Related Antioxidants

Total synthesis of a novel long chain alkyl phenol, phaffiaol (1), a potent antioxidant isolated from Phaffia rhodozyma, was achieved via three reaction steps starting from 3,5-dibromosalicylaldehyde (2). We also prepared several types of long chain alkyl phenol having different aromatic rings or different carbon length, and evaluated their antioxidative activity using the rabbit erythrocyte membrane ghost system. Amongst these compounds, the novel methoxy phenol derivatives (6c, d, 7) having a heptadecyl moiety at the ortho-position to the hydroxy group, were approximately 2 times more active than α-tocopherol. In addition, 4-methoxy-2-pentadecylphenol (10h), which has a 15-carbon length in the side chain moiety, showed the maximum activity.
Heavy fermion scaling: uranium versus cerium and ytterbium compounds

In an effort to explore the differences between rare-earth-based and uranium-based heavy fermion (HF) compounds that reflect the underlying difference between local 4f moments and itinerant 5f moments we analyze scaling laws that relate the low temperature neutron spectra of the primary (‘Kondo-esque’) spin fluctuation to the specific heat and susceptibility. While the scaling appears to work very well for the rare earth intermediate valence (IV) compounds, for a number of key uranium compounds the scaling laws fail badly. There are two main reasons for this failure. First, the presence of antiferromagnetic (AF) fluctuations, which contribute significantly to the specific heat, alters the scaling ratios. Second, the scaling laws require knowledge of the high temperature moment degeneracy, which is often undetermined for itinerant 5f electrons. By making plausible corrections for both effects, better scaling ratios are obtained for some uranium compounds. We point out that, while both the uranium HF compounds and the rare earth IV compounds have spin fluctuation characteristic energies of order 5–25 meV, they differ in that the AF fluctuations that are usually seen in the uranium compounds are never seen in the rare earth IV compounds. This suggests that the 5f itineracy increases the f–f exchange relative to the rare earth case.