bluuebunny/crossref_metadata_2025 huggingface dataset:
Table Tennis classes at Junior High Schools utilizing the TPACK-Based Problem-Based Learning Model
Authors: Siregar Samsuddin , Hasibuan Juli Rachmadani , Anggraini Cindy , Marpaung Aidil Arifin , Br Marbun Yohana Dede
Published: January 2022

The  purpose  of  the study. Through the application of the TPACK - based PBL model , it can improve learning outcomes in the aspect of table tennis service material skills for junior high school students.
Materials and methods. The method used is the Action Research Class method with two cycles, each cycle through the stages of planning, action, observation and reflection. The research subjects were 25 students. The data of this research is the result of learning table tennis service and analyzed by using the percentage technique of Sugiyono's theory.
Results. Student learning outcomes in the aspect of skills have increased from cycle one to cycle two. aspects of service learning outcomes at the implementation stage the percentage obtained in the first cycle was only 74.3%, an increase in the second cycle to 97.7%. Likewise, at the final stage of cycle one, it was only 35%. students who complete have increased in the second cycle to 81%.
Conclusions. The TPACK-based learning problem model makes learning more meaningful and the learning outcomes of Junior High School students experience classical mastery.
Six Senses of Critique for Critical Phenomenology
Authors:   Queen’s University, Guenther Lisa
Published: January 2022

What is the meaning of critique for critical phenomenology? Building on Gayle Salamon’s engagement with this question in the inaugural issue of Puncta: A Journal for Critical Phenomenology (2018), I will propose a six-fold account of critique as: 1) the art of asking questions, moved by crisis; 2) a transcendental inquiry into the conditions of possibility for meaningful experience; 3) a quasi-transcendental, historically-grounded study of particular lifeworlds; 4) a (situated and interested) analysis of power; 5) the problematization of basic concepts and methods; and 6) a praxis of freedom that seeks not only to interpret the meaning of lived experience, but also to change the conditions under which horizons of possibility for meaning, action, and relationship are wrongfully limited or foreclosed. While the first two dimensions of critique are alive and well in classical phenomenology, the others help to articulate what is distinctive about critical phenomenology.
On the Sources of Critique in Heidegger and Derrida
Authors:   Concordia University, Fritsch Matthias
Published: January 2022

According to Lisa Guenther’s concise account, critical phenomenology seeks to expose not only the transcendental conditions of seeing and making the world (such as subjectivity, embodiment, and temporality), but the “quasi-transcendental” ones we find in contingent historical and social structures, such as white supremacy, patriarchy, and heteronormativity (2020, 12). This excellent formulation raises the question of its central distinction: from what position would the critical phenomenologist be able to distinguish transcendental from quasi-transcendental conditions, or universal from contingent structures? This question recalls post-Heideggerian treatments of transcendental historicity (Crowell & Malpas 2007) and the possibilities of critical theorizing, e.g., the Habermas-Gadamer debate on lifeworld and critique (How 1995). These issues also remind us of earlier attempts to forge alliances between (post-)phenomenology and critical theory by scholars shuttling between Freiburg (or Paris) and Frankfurt. At times, these went under the label “critical ontology” and often sought to develop a coherent vision out of Western Marxism and phenomenology, with a special focus, it seems, on Adorno and Heidegger (Dallmayr 1991; Guzzoni 1990; Mörchen 1981; Macdonald & Ziarek 2008).
Some results on generalized Euler-type integrals related to the four parameters Mittag-Leffler function
Authors: ABUBAKAR Umar Muhammad
Published: January 2022

Special functions such as hypergeometric, zeta, Bessel, Whittaker, Struve, Airy, Weber-Hermite and Mittag-Leffler functions are obtained as a solution to complex differential equations in engineering, science and technology. In this work, generalized Euler-type integrals involving four parameters Mittag-Leffler function are proposed. Some special cases of this type of generalized integrals that are corresponding to well-known results in the literature are also inferred.
Sustainable Rabbit Production under the Global Warming Conditions in Southern Mediterranean Region
Authors: El Sabry Mohamed I. , Zaki Manal M. , Elgohary Fatma A. , Helal Mostafa M.
Published: January 2022

There is still a wide gap between meat demand and meat production in Egypt. This gap is becoming larger due to the direct and indirect impacts of global warming that negatively influence the grazing area and the performance of livestock. In this context, rabbits are considered as an alternative source for animal-origin meat. In the Southern Mediterranean region, the most obvious problem encountering rabbit production is the hot waves during the summer, especially during the last decades. The narrow thermo-neutral zone of rabbits makes the high temperature hinder the success of commercial production. Different strategies may assist rabbits in coping with heat stress, which are reviewed in the current study, including the improved management practices, development of new breeds, and implementation of different nutritional strategies.
Global Seroprevalence of West Nile Virus in Horses of Morocco
Authors: Hanafi Houoiten Ghizlane , El Berbri Ikhlass , Mahir Wissal , Aalilouch Kaoutar , Bouabid Badaoui , Zientara Stephan , Alyakine Hassan , El Harrak Mehdi , Fassi Fihri Ouafaa
Published: January 2022

West Nile Fever (WNF) is a viral emerging mosquito-borne disease causing mortality and morbidity with varying severity (from mild fever to severe neuroinvasive disease) among human and animal populations in many parts of the world. The current study aimed to confirm the virus circulation and assess the disease seroprevalence in horses of Morocco. A sample of 1171 healthy non-vaccinated (against-WNF) horses, taken from 11 (out of 12) regions of the country during July-December 2016, was primarily tested using competitive ELISA assay (cELISA). All cELISA-reactive positive and doubtful sera (n= 269) were further tested by virus neutralization test (VNT). The results of cELISA test revealed an overall WNF seroprevalence in 21.8% (255/1171) of sampled horses. This rate decreased to 18.8% (220/1171) after the confirmation of VNT. The WNF seroprevalence in the current study varied significantly by age, gender, and breed of the tested horses. Indeed, the higher seropositivity rates were found in the oldest (27.7%), female (22.0%), and saddle (32.1%) horses. However, the origin of animals did not show any significant effect on the West Nile virus infection. The obtained results of the present study, therefore, provided serological and epidemiological evidence of the endemicity of the WNV in horse populations of Morocco.
Recurrent Squamous Cell Carcinoma of the Submandibular Region after Surgery in a Dog: A Case Report
Authors: Lorsirigool Athip , Sudjaroen Yuttana , Kulnides Narong
Published: January 2022

Squamous cell carcinoma (SCC) is a malignant tumor that has been reported in several organs of different dog breeds. An 8-year-old Shih Tzu, an intact male dog, came to an animal clinic in the Thonburi area, Bangkok Province, Thailand, and a mass of 4.5 × 4.5 cm (width × length) by size was found at the submandibular area. Surgical excision to remove the mass and subsequent histological examination identified the mass as SCC. After conducting the surgery and follow-up, the mass was recurrent at the same location after 33 days and a dog died. Therefore, one of the possible reasons for the death of the dog could be SCC metastasis.
Two New Species of Zygosporium Mont. from Indian Subcontinent
Authors: Dubey Rashmi
Published: January 2022

During surveys for the collection of folicolous fungi from the Western Ghats of Maharashtra, two new species of Zygosporium were found, these are described and illustrated as Zygosporium cocos and Zygosporium dilleniae from leaves of Cocos nucifera and Dillenia pentagyna respectively.
The Bag of Words Approach for the Classification of Head and Neck Cancers Using Diffuse Reflectance Spectroscopy
Authors: Karam Eldaly Ahmed , Benezeth Yannick , Flaus Virginie , Duvillard Christian , Bozorg Grayeli Alexis , Marzani Franck
Published: January 2022

Diffuse Reflectance Spectroscopy (DRS) is a leading technique for the detection of head and neck cancers. It can capture information regarding tissue absorption and scattering. In this research work, we propose a novel method for the identification of normal and Squamous Cell Carcinoma (SCC) mucosa tissues using the Bag Of Words (BOW) approach. The study included 70 spectra from normal mucosa tissue sites and 70 spectra from SCC mucosa tissue sites. First, the spectra are preprocessed by extracting the useful wavelength range, denoising and reducing the inter and intra patient variability. Subsequently, features are extracted from each spectrum by continuously sliding a window with a predefined length along each spectrum to extract a group of local segments. Discrete Wavelet transform (DWT) is then employed for each segment. Next, we construct the codebook to represent each spectrum by a histogram of codewords at which each bin in the histogram is a count of a codeword appeared in the spectrum. Finally, the histogram representation is used as input for classification. The maximum accuracy reported is 94.28% with sensitivity and specificity of 91.42% and 97.14% respectively.
Interactive Liver Tumor Segmentation Using Graph-cuts and Watershed
Authors: Stawiaski Jean , Decenciere Etienne , Bidault Francois
Published: January 2022

We present in this paper an application of minimal surfaces and Markov random fields to the segmentation of liver tumors. The originality of the work consists in applying these models to the region adjacency graph of a watershed transform. We detail the assumptions and the approximations introduced in these models by using a region graph instead of a pixel graph. This strategy leads to an interactive method that we use to delineate tumors in 3D CT images. We detail our strategy to achieve relevant segmentations of these structures and compare our results to hand made segmentations done by experienced radiologists. This paper summarizes our participation to the MICCAI 2008 workshop called: “3D segmentation in the clinic : A Grand Challenge II”.
An Automatic Segmentation of T2-FLAIR Multiple Sclerosis Lesions
Authors: Souplet Jean-christophe , Lebrun Christine , Ayache Nicholas , Malandain Gregoire
Published: January 2022

Multiple sclerosis diagnosis and patient follow-up can be helped by an evaluation of the lesion load in MRI sequences. A lot of automatic methods to segment these lesions are available in the literature. The MICCAI workshop Multiple Sclerosis (MS) lesion segmentation Challenge 08 allows to test and compare these algorithms. This paper presents a method designed to detect hyperintense signal area on T2-FLAIR sequence and its results on the Challenge test data. The proposed algorithm uses only three conventional MRI sequences: T1, T2 and T2-FLAIR. First, images are cropped, spatially unbiased and skull-stripped. A segmentation of the brain into its different compartments is performed on the T1 and the T2 sequences. From these segmentations, a threshold for the T2-FLAIR sequence is automatically computed. Then postprocessing operations select the most plausible lesions in the obtained hyperintense signals. Global result on the test data (80/100) is close to the inter-expert variability (90/100).
Principal Curves: a Technique for Preliminary Carotid Lumen Segmentation and Stenosis Grading
Authors: Wong Wilbur C. K. , So Ronald W. K. , Chung Albert C. S.
Published: January 2022

A vessel lumen centerline extraction method is presented. Its preprocessing and initialization for the application to 3D CT angiography (CTA) image volumes are also described. This approach is based upon the theory of principal curves to finding lumen axis. Meanwhile, it also estimates the lumen local width with an 1D intensity model that depicts an ideal lumen cross-sectional profile. We tested the method on 46 CTA datasets supplied with the Carotid Lumen Segmentation and Stenosis Grading Challenge (CLS) of the ``3D Segmentation in the Clinic: a Grade Challenge’’, a 2009 MICCAI Workshop. The evaluation of 31 testing datasets suggests that our method can provide a good basis for post-processing if high accuracy of segmentation and stenosis grading is desired.
MatVTK - 3D Visualization for Matlab
Authors: Birngruber Erich , Donner René , Langs Georg
Published: January 2022

The rapid and ﬂexible visualization of large amounts of com- plex data has become a crucial part in medical image analysis. In re- cent years the Visualization Toolkit (VTK) has evolved as the de-facto standard for open-source medical data visualization. It features a clean design based on a data ﬂow paradigm, which the existing wrappers for VTK (Python, Tcl/Tk, Simulink) closely follow. This allows to elegantly model many types of algorithms, but presents a steep learning curve for beginners. In contrast to existing approaches we propose a framework for accessing VTK’s capabilities from within MATLAB, using a syntax which closely follows MATLAB’s graphics primitives. While providing users with the advanced, fast 3D visualization capabilities MATLAB does not provide, it is easy to learn while being ﬂexible enough to allow for complex plots, large amounts of data and combinations of visualiza- tions. The proposed framework will be made available as open source with detailed documentation and example data sets.
Component-based software for dynamic configuration and control of computer assisted intervention systems
Authors: Kazanzides Peter , Jung Min Yang , Deguet Anton , Vagvolgyi Balazs , Balicki Marcin , Taylor Russell
Published: January 2022

This paper presents the rationale for the use of a component-based architecture for computer-assisted intervention (CAI) systems, including the ability to reuse components and to easily develop distributed systems. We introduce three additional capabilities, however, that we believe are especially important for research and development of CAI systems. The first is the ability to deploy components among different processes (as conventionally done) or within the same process (for optimal real-time performance), without requiring source-level modifications to the component. This is particularly relevant for real-time video processing, where the use of multiple processes could cause perceptible delays in the video stream. The second key feature is the ability to dynamically reconfigure the system. In a system composed of multiple processes on multiple computers, this allows one process to be restarted (e.g., after correcting a problem) and reconnected to the rest of the system, which is more convenient than restarting the entire distributed application and enables better fault recovery. The third key feature is the availability of run-time tools for data collection, interactive control, and introspection, and offline tools for data analysis and playback. The above features are provided by the open-source cisst software package, which forms the basis for the Surgical Assistant Workstation (SAW) framework. A complex computer-assisted intervention system for retinal microsurgery is presented as an example that relies on these features. This system integrates robotics, stereo microscopy, force sensing, and optical coherence tomography (OCT) imaging to transcend the current limitations of vitreoretinal surgery.
Modeling Tumor Cellularity in Newly Diagnosed GBMs using MR Imaging and Spectroscopy
Authors: Constantin Alexandra , Nelson Sarah , Bajcsy Ruzena
Published: January 2022

In this paper, we analyze the relationship between parameters of brain tumors obtained through in vivo magnetic resonance imaging (MRI), in vivo magneticnresonance spectroscopy (MRS), and ex vivo immunohistochemistry (IHC). The goal of our project is to provide a quantitative definition of tumor cellularity based on the in vivo parameters. Biopsy samples obtained from previously untreated patients with a diagnosis of GBM are used to find the link between imaging parameters at the specific biopsy locations and IHC parameters from the corresponding tissue samples. A functional tree (FT) model of tumor cellularity is learned from the in vivo parameters and the remaining histological parameters. The tumor cellularity model is then tested on examples which contain only in vivo parameters, by first estimating the remaining IHC parameters by applying the Expectation Maximization (EM) algorithm, and then using the complete parameter vector for classification.
Segmentation of Carotid Arteries By Graph-Cuts Using Centerline Models
Authors: Gulsun Mehmet Akif , Tek Huseyin
Published: January 2022

In this paper, we present a semi-automtic method for segmenting carotid arteries in contrast enhanced (CE)-CT angiography (CTA) scans. The segmentation algorithm extracts the lumen of carotid arteries between user specfied locations. Specifically, the algorithm first detects the centerline representations between the user placed seed points. This centerline extraction algorithm is based on a minimal path detection algorithm which operates on a {} map. The lumen of corotid arteries is extracted by using the global optimal graph-cuts algorithm~ using the centerlines as input. The radius information contained in the centerline representation is used to normalize the gradient based weights of the graph. It is shown that this algorithm can sucessfully segment the carotid arteries without including calcified and non-calcified plaques in the segmentation results.
Evaluation of the Dynamic Deformable Elastic Template model for the segmentation of the heart in MRI sequences
Authors: Casta Christopher , Clarysse Patrick , Schaerer Joël , Pousin Jérome
Published: January 2022

We introduce a bio-inspired dynamic deformable (DET) model based on the equation of dynamics and including temporal smoothness constraints. The behaviour and characteristics of the dynamic DET model is studied in the context of the semi automatic spatio-temporal segmentation of the left ventricle myocardium in cine-MR images. The segmentation accuracy for endo/epicardium contours at end-diastole and end-systole, and as consequence the performance and limits of the current implementation, is evaluated in the context of the MICCAI LV Segmentation Challenge on a database of 15 multi-slice cine-MRI examinations.
A Multi-atlas Approach for the Automatic Segmentation of Multiple Structures in Head and Neck CT Images
Authors: Chen Antong , Dawant Benoit
Published: January 2022

A multi-atlas approach is proposed for the automatic segmentation of nine different structures in a set of head and neck CT images for radiotherapy. The approach takes advantage of a training dataset of 25 images to build average head and neck atlases of high-quality. By registering patient images with the atlases at the global level, structures of interest are aligned approximately in space, which allowed multi-atlas-based segmentations and correlation-based label fusion to be performed at the local level in the following steps. Qualitative and quantitative evaluations are performed on a set of 15 testing images. As shown by the results, mandible, brainstem and parotid glands are segmented accurately (mean volume DSC>0.8). The segmentation accuracy for the optic nerves is also improved over previously reported results (mean DSC above 0.61 compared with 0.52 for previous results).
Multi-Atlas-based Segmentation with Hierarchical Max-Flow
Authors: Rajchl Martin , Baxter John S. H. , Yuan Jing , Peters Terry M. , Khan Ali
Published: January 2022

This study investigates a method for brain tissue segmentation from 3D T1 weighted (T1w) MR images via convex relaxation with a hierarchical ordering constraint. It employs a multi-atlas-based initialization from 5 training images and is tested on 12 T1w MR images provided by the MICCAI 2013 MRBrainS segmentation challenge. The registered atlas images, fully segmented into eight different brain structures, are used to formulate shape and intensity priors for a Maximum A-Posteriori (MAP) energy that is subsequently minimized with a dual hierarchical max-flow computation. The algorithm makes use of a hierarchical label ordering constraint to regularize label families individually and its inherently globally optimal results guarantee robust segmentations. Major parts of the image processing pipeline are implemented using General-Purpose Programming on Graphics Processing Units (GPGPU) for a substantial increase in computation speed.
Automatic MS Lesion Segmentation by Outlier Detection and Information Theoretic Region Partitioning
Authors: Prastawa Marcel , Gerig Guido
Published: January 2022

Multiple Sclerosis (MS) is a neurodegenerative disease that is associated with brain tissue damage primarily observed as white matter abnormalities such as lesions. We present a novel, fully automatic segmentation method for MS lesions in brain MRI that combines outlier detection and region partitioning. The method is based on an atlas of healthy subjects and detects lesions as outliers, without requiring the use of training data with segmented lesions. In order to segment lesions as spatially coherent objects and avoid spurious lesion detection, we perform classification on regions (connected groups of voxels) instead of individual voxels. Each voxel location is assigned to a region that would maximize overall relative entropy or Kullback-Leibler divergence between neighboring regions. Our proposed method is fully automatic and does not require manual selection or outlining of specific brain regions. The method can also be adapted to MR images obtained from different scanners and scanning parameters as it requires no training.
Segmentation of Liver Metastases in CT Scans by Adaptive Thresholding and Morphological Processing
Authors: Moltz Jan hendrik , Bornemann Lars , Dicken Volker , Peitgen Heinz-Otto
Published: January 2022

This article presents an algorithm for the segmentation of liver metastases in CT scans. It is a hybrid method that combines adaptive thresholding based on a gray value analysis of the ROI with model-based morphological processing. We show the results of the MICCAI liver tumor segmentation competition 2008 which were successful for all ten tumors.
Automatic Mandible Segmentation on CT Images Using Prior Anatomical Knowledge
Authors: Aghdasi Nava , Li Yangming , Berens Angelique , Moe Kris , Hannaford Blake
Published: January 2022

We present a fully automatic method for segmenting mandible in CT images using anatomic landmarks and prior knowledge. The aim is to utilize spatial relationship of anatomic landmarks with image processing techniques to detect mandible robustly and efficiently. Applying prior knowledge and reliable anatomical landmarks to define an optimal Region of Interest (ROI) which contains the mandible is an effective way for fast localization and successful segmentation. This approach can be used to segment other structures such as optic nerves by defining a new set of relevant landmarks. This approach is robust to CT data with different scanner setting and does not require large training data sets.
Segmentation of the Left Ventricle from Cine MR Images Using a Comprehensive Approach
Authors: Huang Su , Liu Jimin , Lee Looi Chow , Venkatesh Sudhakar K , Teo Lynette Li San , Au Christopher , Nowinski Wieslaw L.
Published: January 2022

Segmentation of the left ventricle is important in assessment of cardiac functional parameters. Currently, manual segmentation is the gold standard for acquiring these parameters and can be time-consuming. Therefore, accuracy and automation are two important criteria in improving cardiac image segmentation methods. In this paper, we present a comprehensive approach that utilizes various features of cine MR images and combines multiple image processing methods including thresholding, edge detection, mathematical morphology, deformable model as well as image filtering. The segmentation is performed automatically with minimized interaction to optimize segmentation results. This approach provides cardiac radiologists a practical method for accurate segmentation of the left ventricle.
MS Lesion Segmentation based on Hidden Markov Chains
Authors: Bricq Stephanie , Collet Christophe , Armspach Jean-Paul
Published: January 2022

In this paper, we present a new automatic robust algorithm to segment multimodal brain MR images with Multiple Sclerosis (MS) lesions. The method performs tissue classification using a Hidden Markov Chain (HMC) model and detects MS lesions as outliers to the model. For this aim, we use the Trimmed Likelihood Estimator (TLE) to extract outliers. Furthermore, neighborhood information is included using the HMC model and we propose to incorporate a priori information brought by a probabilistic atlas.
Carotid Lumen Segmentation Based on Tubular Anisotropy and Contours Without Edges
Authors: Mille Julien , Benmansour Fethallah , Cohen Laurent
Published: January 2022

We present a semi-automatic algorithm for Carotid lumen segmentation on CTA images. Our method is based on a variant of the minimal path method that models the vessel as a centerline and boundary. This is done by adding one dimension for the local radius around the centerline. The crucial step of our method is the definition of the local metrics to minimize. We have chosen to exploit the tubular structure of the vessels one wants to extract to built an anisotropic metric giving higher speed on the center of the vessels and also when the minimal path tangent is coherent with the vessel’s direction. Due to carotid stenosis or occlusions on the provided data, segmentation is refined using a region-based level sets.
The Labeling of Cortical Sulci using Multidimensional Scaling
Authors: Mani Meena , Srivastava Anuj , Barillot Christian
Published: January 2022

The task of classifying or labeling cortical sulci is made difficult by the fact that individual sulci may not have unique distinguishing features and usually need to be identified by a multivariate feature set that takes the relative spatial arrangement into account. In this paper, classical multidimensional scaling (MDS), which gives a geometric interpretation to input dissimilarity data, is used to classify 180 sulci drawn from the ten major classes of sulci. Using a leave-one-out validation strategy, we acheive a success rate of 100% in the best case and 78% in the worst case. For these more difficult cases, we propose a second stage of classification using shape based features. One of these features is the geodesic distance between sulcal curves obtained from a new open curve representation in a geometric framework. With MDS, we oﬀer a simple and intuitive approach to a challenging problem. Not only can we easily separate left and right brain sulci, but we also narrow the classification problem from, in this case, a 10-class to a 2-class problem. More generally, we can identify a region-of-interest (ROI) within which one can carry out further classification.
Multi-object Segmentation of Head Bones
Authors: Kainmueller Dagmar , Lamecker Hans , Seim Heiko , Zachow Stefan
Published: January 2022

We present a fully automatic method for 3D segmentation of the mandibular bone from CT data. The method includes an adaptation of statistical shape models of the mandible, the skull base and the midfacial bones, followed by a simultaneous graph-based optimization of adjacent deformable models. The adaptation of the models to the image data is performed according to a heuristic model of the typical intensity distribution in the vincinity of the bone boundary, with special focus on an accurate discrimination of adjacent bones in joint regions. An evaluation of our method based on 18 CT scans shows that a manual correction of the automatic segmentations is not necessary in approx. 60% of the axial slices that contain the mandible.
Semi-automated cardiac segmentation on cine magnetic resonance images using GVF-Snake deformable models
Authors: Constantinides Constantin , Chenoune Yasmina , Kachenoura Nadjia , Roullot Elodie , Mousseaux Elie , Herment Alain , Frouin Frederique
Published: January 2022

The segmentation of left ventricular structures is necessary for the evaluation of the ejection fraction (EF) and the myocardial mass (LVM). A semi-automated 2D algorithm using connected filters and a deformable model allowing an accurate endocardial detection was proposed. The epicardial border was deduced using a deformable model restricted inside a region of interest defined from the endocardial border. Papillary muscles were detected using a fuzzy k-means algorithm. The method was applied to the challenge training and validation databases, consisting of 15 subjects each. The evaluation was performed using the tools provided by the challenge. For both datasets, results show a mean Dice metric of 0.89 for endocardial borders (0.92 for epicardial borders). Overall average perpendicular distance was 2.2 mm. Very good correlation was obtained for the EF and LVM parameters. Visual overall rating given by the challenge’s cardiologist was 1.2. Segmentation was robust and performed successfully on both datasets.
A Minimal Cost Path and Level Set Evolution Approach for Carotid Bifurcation Segmentation
Authors: Krissian Karl , Arencibia Sara
Published: January 2022

We propose a new approach for semi-automatic segmentation of the carotid bifurcation as part of the Carotid Lumen Segmentation and Stenosis Grading Challenge MICCAI’2009 workshop. Three initial points are provided as input, belonging to the Common, the External and the Internal Carotid Arteries. Our algorithm is divided into two main steps: first, two minimal cost paths are tracked between the CCA and both the ECA and the ICA. The cost functions are based on a multiscale vesselness response. Second, after detecting the junction position and cutting or extending the paths based on the requested lengths, a level set segmentation is initialized as a thin tube around the computed paths and evolves until reaching the vessel wall or a maximal evolution time. Results on training and testing datasets are presented and compared to the manual segmentation by three observers, based on a ground truth and using four quality measures.
Simulink Libraries for Visual Programming of VTK and ITK
Authors: Gobbi David , Mousavi Parvin , Li Karen , Xiang Jing , Campigotto Adam , LaPointe Adrien , Fichtinger Gabor , Abolmaesumi Purang
Published: January 2022

We have created open-source Simulink block libraries for ITK and VTK that allow pipelines for these toolkits to be built in a visual, drag-and-drop style within MATLAB. Each block contains an instance of an ITK or VTK class. Any block connections and parameters that the user makes within MATLAB’s Simulink visual environment are converted into connections and parameters for the ITK and VTK pipelines. In addition, we provide conversion of images to and from MATLAB arrays to allow MATLAB image processing blocks to be mixed with ITK and VTK blocks. The code for our block libraries is generated automatically from XML descriptions of the inputs, outputs, and parameters of the ITK and VTK classes. We have used these block libraries to build some example pipelines and believe that they will be useful for developing applications in image analysis and image-guided therapy.
Hubungan Tingkat Pengetahuan Terhadap Sikap Masyarakat Tentang DAGUSIBU Obat Oral di Desa Banyumudal Kecamatan Moga Kabupaten Pemalang tahun 2020
Authors: Puspasari Devi Herdina
Published: January 2022

ABSTRAK

Devi Herdina Puspa Sari

Hubungan Tingkat Pengetahuan Terhadap Sikap Masyarakat Tentang Dagusibu Obat Oral di Desa Banyumudal Kecamatan Moga Kabupaten Pemalang

Pengetahuan dan sikap masyarakat dalam penggunaan obat akan menentukan pengelolaan obat secara benar. DAGUSIBU merupakan singkatan dari Dapatkan, Gunakan, Simpan, dan Buang obat. Dalam masyarakat harus memahami informasi mengenai obat dari mendapatkan, menggunakan, menyimpan sampai membuangnya dengan benar. Undang-Undang Nomor 36 Tahun 2019 tertulis bahwa warga negara berhak mendapatkan pelayanan kesehatan yang baik demi mencapai derajat kesehatan yang setinggi-tingginya. Tujuan dari penelitian ini yaitu untuk mengetahui tingkat pengetahuan dengan sikap masyarakat tentang DAGUSIBU obat oral di Desa Banyumudal Kecamatan Moga Kabupaten Pemalang berdasarkan umur dan tingkat pendidikan. Jenis penelitian ini yaitu deskriptif. Populasi dari penelitian yaitu semua masyarakat yang berdomisili di Desa Banyumudal Kecamatan Moga Kabupaten Pemalang. Sampel yang digunakan berjumlah 99 orang. Teknik pengambilan sampel menggunakan purposive random sampling. Hasil penelitian menunjukkan bahwa tingkat pengetahuan masyarakat tentang DAGUSIBU obat oral di Desa Banyumudal Kecamatan Moga Kabupaten Pemalang yang berpengetahuan kurang berjumlah 24 responden, pengetahuan cukup berjumlah 44 responden dan pengetahuan baik sejumlah 31 responden. Tingkat pengetahuan masyarakat Desa Banyumudal memiliki tingkat pengetahuan yang cukup tentang DAGUSIBU obat oral. Sikap masyarakat Desa Banyumudal termasuk dalam kategori positif yaitu dengan nilai korelasi 0,265. Kesimpulan pada penelitian ini terdapat hubungan antara tingkat pengetahuan dengan sikap masyarakat tentang DAGUSIBU obat oral sehingga alangkah baiknya lebih ditingkatkan dengan memperoleh informasi mengenai DAGUSIBU obat oral di Desa Banyumudal.

 

Kata Kunci : DAGUSIBU Obat, Pengetahuan, Sikap
Alternative Mowing Regimes’ Influence on Native Plants and Deer
Authors: Guyton John , Jones Jeanne C. , Entsminger Edward
Published: January 2022

This study evaluated mowing regimes, changes in native and non-native plant communities, deer presence in the research plots,and public perception of various management practices on ROWs. No significant difference was found in the height of vegetation 3 weeks after each mowing between research plots mowed 4 times per year and plots mowed only once per year in uplands or lowlands. Native plants increased in plots mowed once per year and deer preferred the frequently mowed plots where clovers and vetches had been seeded. Increasing the carrying capacity of the lowlands with more extensive plantings of clover and vetch may attract deer, thus encouraging them to browse and use the underpasses beneath bridges and making the ROWs safer. The public survey found strong support for wildflowers on ROWs and a distaste for litter. Further, respondents would tolerate a less manicured ROW if it saved money, made the roads safer, and hid litter.
PERANCANGAN FLYBACK CONVERTER UNTUK CATU DAYA DRIVER MOTOR BLDC ( BRUSHLESS DIRECT CURRENT )
Authors: Mahendra Agus , Sapril Sapril , Masarrang Maryantho
Published: January 2022

Flyback Converter is an electronic circuit that can increase the output voltage value, the voltage value can be adjusted by changing the value of the duty cycle. This Flyback Converter will be controlled by the Pulse Width Modulation method as the output voltage setting and this research is equipped with a feedback function as monitoring and control of Input Pulse Width Modulation.

This designed flyback converter aims to provide an isolated power supply as a power source for Brushless Direct Current Motor drivers, and this research was conducted to analyze how much power the flyback converter can produce to be able to supply Brushless Direct Current Motor drivers.

The results of the analysis obtained in the research Design of flyback converter for power supply of BLDC (Brushless Direct Current) motor driver that is flyback converter is given an input voltage of 31 VDC and output voltage of 15 VDC, rheostat load with a capacity of 39 Ohm, a frequency of 31 KHz in the form of a box wave duty cycle reaches 70%. Flyback converter designed to produce maximum power of 49.6 watts on 70% duty cycle testing.
Doing Business in the ‘New Normal’: COVID-19 School Leaders’ Language Manners
Authors: Vaneva Marjana , I. Bojadjiev Marjan
Published: January 2022

As the not-so-new-now coronavirus pandemic has affected all walks of life, education has not been an exemption; what is more, it is one of the most severely hit sectors. 

The unknown crisis created unprecedented circumstances for all participants in the education process, and school leaders have had a double job: to navigate their institutions and to look after their employees. The latter is a pretty delicate task - they have had to keep doing business and running their companies while minding the language since physical distancing necessitated the use of electronic communication, thus making room for vagueness and even misinterpretations. Ten education leaders of primary and secondary schools in North Macedonia have been video-interviewed on everyday COVID-19-related situations from their workplace context. Discourse completion tasks (DCTs) have been employed as a data elicitation method. Being given the open-ended, only topically specified scenarios, the respondents are asked to recreate their language reaction to situations that have happened in their newest pandemic work life. The interviews have been transcribed, and the leaders’ language choices have been analyzed. The findings show that, luckily, the leaders have been mindful about their words and have mostly chosen to use positive, calm, and encouraging language.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
A New Proposition of Business Model Innovation: Anteceding Managerial Competencies
Authors: Turulja Lejla , Smajlović Selma
Published: January 2022

Knowledge, competencies, and human capital are the cornerstones of business innovation. Generating innovation alone is not a guarantee of success in the market, but it is necessary to successfully manage innovation, which requires managers' expertise and specific competencies. The paper focused on analyzing the impact of several managerial competencies on improving the new proposition dimensions of the business model innovation. The business model innovation consists of new creation innovation, new proposition innovation, and value capture innovation. This paper analyses the new proposition innovation segment that relates to solutions for customers and how they are offered; it consists of the dimensions of new offerings, new customers and markets, new channels, and new customer relationships. The research was conducted among managers of companies from several industries, who evaluated their competencies, namely analytical and innovative, their ability to recognize opportunities, their tenacity, and passion for work, as well as new proposition innovation of business model innovation. The findings suggest that each of the managerial competencies is influential in some way but that they do not all affect each dimension of a new proposition of business model innovation.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
The Benefits of Enterprise Data Warehouse Implementation in Cloud vs. On-premises
Authors: Golec Darko , Strugar Ivan , Belak Drago
Published: January 2022

When we think about running enterprise applications on-premises, enterprises do two things for their servers, databases, and storage. Enterprises provision for peaks and put a lot of infrastructures to handle peak demand, although a lot of this capacity is not used at normal times. The other thing is a few instances that each application needs to have, typically between five and six. Multiplying this number by many times due to various applications causes a lot of costs and creates capacity that is not used. For such reasons, the enterprise applications in the cloud seem reasonable. In the cloud, two things are possible again. Instead of overprovisioning for peaks, enterprises can scale the capacity on on-demand and spin up instances on demand. This means a certain amount of cost-saving by running at a normal level instead of overprovisioning. In this paper, various factors will be considered, and the benefits for enterprise data warehouse implementation in the cloud vs. on-premises will be stated.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Applying Principles of Management Innovation in Advertising Agencies
Authors: Rubik Andrea
Published: January 2022

With the advertising industry and practice changing significantly in the last decade, it is likely that the existing management practices in advertising agencies also need some transformation. Through exploring management innovation principles and practices, novel practices might be applied by advertising agencies to exploit changes in their environment and enhance organizational performance. This paper explores the application and framework for novel management practices in an advertising agency. A proposed model is based on the principles of management innovation and the activities needed to drive management innovation. The topic is relevant for advertising agencies to understand better management innovation possibilities and enhancement it could create for them to compete in new markets and stay ahead of new competition.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Profitability Analysis of Audit Firms – Evidence from the Republic of Serbia
Authors: Mijić Kristina , Rađo Dijana
Published: January 2022

This paper aims to provide an analysis of the profitability of audit firms in the Republic of Serbia during the period 2016-2018. The analysis is based on the data collected from the financial statements from all audit firms registered in the Republic of Serbia. The profitability analysis includes two goals. This paper will primarily provide a descriptive statistical analysis of the profitability of audit firms measured by return on assets and net income per employee. The following part of the research will answer the question of which factors have a significant impact on the profitability of audit firms. Profitability as a dependent variable is defined as return on assets and net income per employee, while independent variables include market share, current ratio, leverage, size, affiliation to the international network, etc. To answer this question, a regression statistics analysis will be conducted. The research result will indicate which factor can improve the performances of audit firms.

This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Autonomous Navigation Algorithm for RoboCup RRL Maneuvering 2 Field
Authors: Dilaver Mustafa Burak , Cakmak Furkan , Uslu Erkan , Altuntas Nihal , Amasyali Mehmet Fatih , Yavuz Sirma
Published: January 2022

The goal of this project is to develop a robot platform which can autonomously accomplish the track named Maneuvering 2 of the Real Rescue Robot League of one of the most important robotics contest of the world, RoboCup. The mentioned track is made for ground robots. Robots that compete in this track should move on rays which have a contact area that has 5 cm width with their wheels and tracks. Robots may fall when they slide left or right for 5 cm. Because of competition rules, this situation causes competitors to go to the starting point and lose the score that they've earned in this ?eld until that time. Competitors may use the color difference between rays and grounds. The robot platform which is used in this study, is built on ROS framework. Movement commands are produced using the images that are taken by multiple cameras which are on the robot. OpenCV library is used to process these images. In addition to images that are taken by camera, IMU is used in the middle platform where the pass between two rays is made. The software components that generated as a result of this study can be used in a ROS installed robot platform, which had the similar sensors on it, without making any extra development.
Analisis Hubungan Kausalitas Konsumsi Energi (Terbarukan Dan Tidak Terbarukan) Dengan Pertumbuhan Ekonomi Indonesia
Authors: Nurdin Khairunas , Fuady Muhammad Syahrul
Published: January 2022

Penelitian ini bertujuan untuk menganalisis estimasi jangka pendek dan jangka panjang serta hubungan kausalitas antara konsumsi energi terbarukan dan energi tidak terbarukan dengan pertumbuhan ekonomi Indonesia menggunakan data tahunan dari tahun 1990 hingga 2019. Metode Ordinary Least Square (OLS) dan Error Correction Term (ECT) digunakan untuk menganalisis estimasi model jangka pendek maupun jangka panjang. Hasil penelitian menunjukkan bahwa konsumsi energi terbarukan dan energi tidak terbarukan berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi dalam jangka panjang. Dalam jangka pendek, hasil penelitian menunjukkan bahwa konsumsi energi tidak terbarukan berpengaruh positif dan signifikan terhadap pertumbuhan ekonomi, sedangkan konsumsi energi terbarukan berpengaruh negatif dan signifikan terhadap pertumbuhan ekonomi. Hasil uji kausalitas Granger menunjukkan tidak adanya hubungan kausalitas antara konsumsi energi terbarukan dan pertumbuhan ekonomi dalam jangka pendek, serta antara konsumsi energi tidak terbarukan dan pertumbuhan ekonomi baik dalam jangka pendek maupun jangka panjang. Selain itu, terdapat kausalitas dua arah antara konsumsi energi terbarukan dan pertumbuhan ekonomi dalam jangka panjang.
A DIFFERENTIAL EQUATION FOR THE ENTROPY OF RURAL TOURISM IN THE CONTEXT OF COVID-19
Authors:   Lucian Blaga University of Sibiu, Bucur Amelia
Published: January 2022

The tourism industry was one of the world’s greatest markets, until the world was affected by the COVID-19 pandemic. Now, tourism managers have to carefully assess the impact of epidemics on their businesses and develop new risk management methods to cope with the crisis. The current pandemic has created an opportunity for the development of rural tourism. This study aims to present a mathematical modeling of the entropy of rural tourism in the context of COVID-19 and a differential equation verified by this entropy. The model presented in this paper reflects the entropy of the preference for this type of tourism and a differential equation that models its variation. This paper aims to offer a tool to measure uncertainty regarding this topic. The model can be generalized and applied to any epidemic. The model could be used by specialists in quality management and mathematical modeling, managers of rural tourism organizations, local authorities, to estimate the entropy regarding how rural tourism has been and is still impacted by the COVID-19. The results obtained will help policy makers take necessary strategic and operational decisions, along with maximizing the profit of the rural tourism organization as well as the safety of the tourists