Level set segmentation using non-negative matrix factorization with application to brain MRI

We address the problem of image segmentation using a new deformable model based on the level set method (LSM) and non-negative matrix factorization (NMF). We describe the use of NMF to reduce the dimension of large images from thousands of pixels to a handful of metapixels or regions. In addition, the exact number of regions is discovered using the nuclear norm of the NMF factors. The proposed NMF-LSM characterizes the histogram of the image, calculated over the image blocks, as nonnegative combinations of basic histograms computed using NMF (V ~ W H). The matrix W represents the histograms of the image regions, whereas the matrix H provides the spatial clustering of the regions. NMF-LSM takes into account the bias field present particularly in medical images. We define two local clustering criteria in terms of the NMF factors. The first criterion defines a local intensity clustering property based on the matrix W by computing the average intensity and standard deviation of every region. The second criterion defines a local spatial clustering using the matrix H. The local clustering is then summed over all regions to give a global criterion of image segmentation. In LSM, these criteria define an energy minimized w.r.t. LSFs and the bias field to achieve the segmentation. The proposed method is validated on synthetic binary and gray-scale images, and then applied to real brain MRI images. NMF-LSM provides a general approach for robust region discovery and segmentation in heterogeneous images

PENGARUH KEBIJAKAN DIVIDEN, LEVERAGE, PERTUMBUHAN PERUSAHAAN DAN TINGKAT KESULITAN KEUANGAN PERUSAHAAN TERHADAP PENERAPAN AKUNTANSI KONSERVATIF (Studi Empiris pada Perusahaan Subsektor Properti dan Real Estate yang terdaftar di Bursa Efek Indonesia pada Tahun 2011-2013)

ABSTRAK Penelitian ini bertujuan untuk meneliti secara empiris mengenai pengaruh kebijakan dividen, leverage, pertumbuhan perusahaan dan tingkat kesulitan keuangan perusahaan terhadap penerapan akuntansi konservatif pada perusahaan subsektor properti dan real estate yang terdaftar di Bursa Efek Indonesia periode 2011-2013. Teknik sampling yang diginakan dalam penelitian ini adalah purposive sampling dengan kriteria: perusahaan subsektor property dan real estate yang terdaftar di Bursa Efek Indonesia, mempublikasikan laporan keuangan tiga tahun berturut-turut sejak tahun 2011 sampai 2013 dan berakhir setiap 31 Desember, membagikan dividen secara berturut-turut selama tiga tahun, dan mengalami kenaikan laba bersih perusahaan setiap tahunnya. Data diperoleh dari Bursa Efek Indonesia dan Saham Ok sejak 2011 sampai dengan 2013. Sampel yang diperoleh yaitu sebanyak 9 perusahaan. Teknik analisa yang digunakan dalam penelitian ini adalah regresi logistik dan uji hipotesis yang digunakan adalah uji parsial (uji wald). Hasil penelitian menunjukkan bahwa varibel leverage dan tingkat kesulitan keuangan perusahaan berpengaruh terhadap penerapan akuntansi konservatif. Sedangkan variabel kebijakan dividen dan pertumbuhan perusahaan tidak berpengaruh terhadap penerapan akuntansi konservatif. Hasil uji simultan menunjukkan kebijakan dividen, leverage, pertumbuhan perusahaan dan tingkat kesulitan keuangan perusahaan berpengaruh terhadap penerapan akuntansi konservatif. Hasil penelitian ini diharapkan dapat menjadi pedoman, baik oleh pihak perusahaan dalam menerapkan prinsip akuntansi dalam menyusun laoran keuangan perusahaan. Kata kunci : Kebijakan Divide, Leverage, Pertumbuhan Perusahaan, Tingkat Kesulitan Keuangan, Akuntansi Konservatif

Evaluating the success of e-learning systems : the case of Moodle LMS at the University of Warwick

E-learning is a direct result of the integration of education and technology, and is increasingly considered as a powerful medium for learning. The undeniable significance of e-learning in education has led to a large growth of e-learning courses and systems offering different types of service. Thus, evaluation of e-learning systems is vital in ensuring successful delivery, effective use, and positive impact on learners. In recent studies, the vast majority of universities report having adopted varieties of e-learning systems and platforms to facilitate the students’ learning process. However, while adopting e-learning systems is useful, it is not an end in itself. In reviewing the literature, studies have revealed many problems with these systems, such as meeting users’ requirements and the suitability of these systems for targeted users. In order to improve the current systems to satisfy users’ needs, it is important to understand the different aspects that influence the quality and success of these systems. Hence, a new model for evaluating the success of e-learning systems is introduced in this research. Based on an intensive review of the literature, four approaches were identified and analysed as a theoretical basis for the research: DeLone and McLean’s information systems success model; the Technology Acceptance Model; the User Satisfaction Models; and the E-learning Quality Models. In order to provide a general comprehensive definition of e-learning success measurements, the four approaches found in the literature were considered in developing our model. The proposed model includes eleven constructs: technical system quality; information quality; service quality; educational system quality; support system quality; learner quality; instructor quality; perceived satisfaction; perceived usefulness; system use; and benefits. The model is comprehensive, and not based on the number of constructs, but on the intention to provide a holistic picture and different levels of success related to a broad range of success determinants, rather than focusing on a specific construct. As such, it forms an original contribution to knowledge. To test the model, an empirical study was conducted. First, an instrument was designed to assess the perceptions of students towards e-learning system success. Second, an expert study with 30 e-learning experts was carried out to confirm the measurements and indicators. The model was then tested in the context of the University of Warwick by fitting the model to data collected from 563 students engaged with an e-learning system. Both quantitative and qualitative data were analysed. The results confirm that the model proposed in this study is valid and reliable. Thus, the study contributes to the growing body of knowledge with a valid and reliable model and an instrument to evaluate e-learning systems success (EESS model). Further, the study sheds light on important issues and recommendations that should be taken into consideration to improve the perceptions of satisfaction, usefulness, use, and benefits of the e-learning systems. The study further provides practitioners with several practical contributions

Approximately Efficient Online Mechanism Design

Online mechanism design (OMD) addresses the problem of sequential decision making in a stochastic environment with multiple self-interested agents. The goal in OMD is to make value-maximizing decisions despite this self-interest. In previous work we presented a Markov decision process (MDP)-based approach to OMD in large-scale problem domains. In practice the underlying MDP needed to solve OMD is too large and hence the mechanism must consider approximations. This raises the possibility that agents may be able to exploit the approximation for selfish gain. We adopt sparse-sampling-based MDP algorithms to implement efficient policies, and retain truth-revelation as an approximate Bayesian-Nash equilibrium. Our approach is empirically illustrated in the context of the dynamic allocation of WiFi connectivity to users in a coffeehouse.Engineering and Applied Science

ANALISIS KINERJA KEUANGAN DITINJAU DARI RASIO KEUANGAN PADA CV SARANA USAHA MANDIRI DI PALEMBANG

Laporan akhir ini bertujuan untuk mengetahui kinerja keuangan CV Sarana Usaha Mandiri Palembang. Objek penelitian dalam penulisan akhir berlokasi di jalan inspektur marzuki No 2553 pakjo Palembang. Manfaat dari penulisan laporan akhir ini adalah memberikan masukan kepada pihak manajemen mengenai pentingnya analisis rasio keuangan bagi perusahaan serta sebagai sarana mempraktikan teori-teori yang telah diperoleh atas masalah-masalah nyata yang dialami perusahaan, khususnya dalam bidang analisis laporan keuangan. Dalam hal pengumpulan data, penulis menggunakan teknik triangulasi, yaitu teknik yang menggabungkan dari berbagai teknik pengumpulan data berupa wawancara dan dokumentasi. Berdasarkan data dan informasi yang diperoleh, dapat diketahui bahwa terjadi penurunan penjualan diikuti dengan tingginya biaya operasi serta terjadinya penumpukan piutang dalam perusahaan. Masalah pokok yang ada pada perusahaan ini yaitu bagaimana kinerja keuangan perusahaan ditinjau dari rasio keuangan selama 3 periode. Berdasarkan masalah tersebut, penulis menyarankan agar perusahaan lebih memperhatikan nilai aset yang dimiliki sebagai pertimbangan atas kemampuan perusahaan dalam memenuhi utangnya, melakukan pengevaluasian terhadap turunnya penjualan dan pembengkakan biaya, serta melakukan peninjauan kembali terhadap pemberian kredit sehingga perusahaan dapat menekan biaya operasional serta dapat menghasilkan laba yang lebih optimal

Evaluating E-learning systems success : an empirical study

E-learning, as a direct result of the integration of technology and education, has emerged as a powerful medium of learning particularly using Internet technologies. The undeniable significance of e-learning in education has led to a massive growth in the number of e-learning courses and systems offering different types of services. Thus, evaluation of e-learning -systems is vital to ensure successful delivery, effective use, and positive impacts on learners. Based on an intensive review of the literature, a comprehensive model has been developed which provides a holistic picture and identifies different levels of success related to a broad range of success determinants. The model has been empirically validated by fitting the model to data collected from 563 students engaged with an e-learning system in one of the UK universities through a quantitative method of Partial Least Squares - Structural Equation Modelling (PLS-SEM). The determinants of e-learning perceived satisfaction are technical system quality, information quality, service quality, support system quality, learner quality, instructor quality, and perceived usefulness, which together explain 71.4% of the variance of perceived satisfaction. The drivers of perceived usefulness are technical system quality, information quality, support system quality, learner quality, and instructor quality, and these explain 54.2% of the variance of perceived usefulness. Four constructs were found to be the determinants of e-learning use, namely educational system quality, support system quality, learner quality, and perceived usefulness, and together they account for 34.1%. Finally, 64.7% of the variance of e-learning benefits was explained by perceived usefulness, perceived satisfaction, and use

Evaluation of flexural strength of multilayer zirconia under three loading configurations

OBJECTIVE: Flexural strength values of multilayer zirconia may vary depending upon the specimen dimension, layers distribution, especially the layer in maximum tension side, i.e., loading configuration. Although the previous studies have examined flexural strength of the separate layers in one zirconia disc, capturing flexural strength across all layers of multilayer zirconia is still challenging yet important for their clinical indications. The objective of this study aimed to evaluate the flexural strength of multilayer graded translucent zirconia by three loading configurations with the full thickness of layers. MATERIALS AND METHODS: Four types of zirconia materials were selected namely KATANA Yttria Multi Layered (KATANA YML, Kuraray Noritake), IPS e.max ZirCAD Prime (ZirCAD Prime, Ivoclar Vivadent), and Origin Beyond + Hybrid (Origin Beyond, B&D Dental Technologies) multilayer zirconia, as well as monolithic InCoris translucent zirconia (inCoris TZI, Dentsply Sirona). The bar specimens were prepared by sectioning the zirconia discs with diamond blade to get the dimensions of 31.0 mm x 4.6 mm x 11.0 mm for KATANA YML and Origin Beyond, 42.0 mm x 6.4 mm x 13.1 mm for ZirCAD Prime, and 31.0 mm x 4.2 mm x 10.0 mm for inCoris TZI. The specimens were sintered with a Zircar high temperature furnace by following the protocols of manufacturers accordingly. The four longitudinal surfaces of all bar specimens for all materials were polished with diamond discs in a sequence of 125, 70, 45, 15, and 6 mm, and down to 0.5 mm finish. All polished specimens were subjected to the annealing treatment at 1000 oC for 15 min before mechanical testing. The three-point bend testing with three loading configuration was performed for flexural strength on the Universal Testing Machine (Instron 5566A) with a loading rate of 0.5 mm/min. The fracture surfaces of these bar specimens were examined by a field emission scanning electron microscope. The yttria (Y2O3) and hafnia (HfO2) concentrations were analyzed by energy disperse spectroscopy on polished surfaces. RESULTS: The highest mean 3 point bending flexural strength for all layers direction was for inCoris TZI with 786.55 MPa, whereas the lowest for Origin Beyond with 505.36 MPa. The inCoris TZI had overall highest flexural strength with vertical (enamel or dentin layer in tension) of 845.18 MPa. ZirCAD Prime had overall highest flexural strength with the loading configuration of dentin layer in tension of 906.22 MPa while Origin Beyond had the lowest flexural strength of 686.79 MPa. Under the loading configuration of enamel layer in tension, the flexural strength of all three multilayer materials ZirCAD Prime, Origin Beyond and KATANA YML had no significant difference, having a strength value range of 498-504 MPa. The dentin layer had the lowest yttria concentration while the enamel had the largest one, and the transition layer was between them. The distribution of hafnia concentration of different layers for all multilayer materials was consistent. CONCLUSION: Within the limitations of this in vitro study, we can conclude that material, and loading configurations as well as the interaction between material and loading configurations had a significant effect on flexural strength of multilayer zirconia. ZirCAD Prime showed a significantly higher flexural strength than KATANA YML whereas Origin Beyond had the lowest flexural strength. The flexural strength of dentin layer in tension was significantly higher than all layers in tension, while the flexural strength of all layers was significantly higher than enamel layer in tension. The yttria concentration of multilayer zirconia gradually increased from dentin layer to enamel layer whereas the hafnia concentration was consistent across different layers. These findings in this study could enrich the knowledge of clinicians when selecting the multilayer zirconia materials in the clinical settings.

Estudio del comportamiento frente a la tribocorrosión de aleaciones biomédicas de titanio en electrolitos que simulan el suero humano mediante técnicas electroquímicas

[ES] En la presente Tesis Final de Máster se analiza la caracterización triboelectroquímica de varias aleaciónes biomédicas de titanio para aplicaciones médicas. Para explicar los mecanismos de tribocorrosion implicados en los procesos de degradación de las aleaciónes biomédicas se utiliza un tribómetro bola-sobre-disco bajo condiciones electroquimicas[EN] In the present Thesis we discuss the triboelectrochemical characterization of various titanium biomedical alloys for medical applications. To explain the mechanisms of fretting corrosion processes involved in degradation of biomedical alloys using a tribometer ball-on-disc under electrochemical conditionsKareem Dimah, M. (2012). Estudio del comportamiento frente a la tribocorrosión de aleaciones biomédicas de titanio en electrolitos que simulan el suero humano mediante técnicas electroquímicas. http://hdl.handle.net/10251/19220Archivo delegad

Xpert MTB/RIF for rapid detection of rifampicin-resistant Mycobacterium tuberculosis from pulmonary tuberculosis patients in Southwest Ethiopia

AbstractObjective/backgroundAccurate and rapid detection of drug-resistant strains of tuberculosis (TB) is critical for early initiation of treatment and for limiting the transmission of drug-resistant TB. Here, we investigated the accuracy of Xpert MTB/RIF for detection of rifampicin (RIF) resistance, and whether this detection predicts the presence of multidrug resistant (MDR) TB in Southwest Ethiopia.MethodsSmear- or culture-positive sputa obtained from TB patients with increased suspicion of drug resistance were included in this study. GenoType MTBDRplus line-probe assays (LPAs) and Xpert MTB/RIF tests were performed on smear-positive sputum specimens and on cultured isolates for smear-negative specimens. We performed routine drug-susceptibility testing using LPA as the reference standard for confirmation of RIF and isoniazid (INH) resistance.ResultsFirst-line drug-susceptibility results were available for 67 Mycobacterium tuberculosis complex-positive sputum specimens using the LPA test, with our preliminary results indicating that 30% (20/67) were MDR-TB, 3% (2/67) were RIF monoresistant, 6% (4/67) were INH monoresistant, and 61% (41/67) were susceptible to both RIF and INH. Relative to routine RIF-susceptibility testing (LPA), Xpert MTB/RIF detected all RIF resistance correctly, with 100% sensitivity and 97.8% specificity and a positive-predictive value of 95.7%. Of the 23 RIF-resistant strains according to Xpert MTB/RIF, 87% (20/23) were resistant to both RIF and INH (MDR), 8.7% (2/23) were RIF monoresistant, and 4.3% (1/23) were sensitive to RIF according to the LPA test. A high proportion of RIF resistance was documented among patients previously categorized as failure cases (50%, 10/20), followed by relapse cases (31.6%, 6/19) and defaulters (28.6%, 2/7).ConclusionXpert MTB/RIF was highly effective at identifying RIF-resistant strains in smear- or culture-positive samples. RIF resistance based on Xpert MTB/RIF results could be used to estimate MDR and allow rapid initiation of MDR-TB treatment in regions with high levels of drug-resistant TB

Failure Detection in Deep Neural Networks for Medical Imaging

Deep neural networks (DNNs) have started to find their role in the modern healthcare system. DNNs are being developed for diagnosis, prognosis, treatment planning, and outcome prediction for various diseases. With the increasing number of applications of DNNs in modern healthcare, their trustworthiness and reliability are becoming increasingly important. An essential aspect of trustworthiness is detecting the performance degradation and failure of deployed DNNs in medical settings. The softmax output values produced by DNNs are not a calibrated measure of model confidence. Softmax probability numbers are generally higher than the actual model confidence. The model confidence-accuracy gap further increases for wrong predictions and noisy inputs. We employ recently proposed Bayesian deep neural networks (BDNNs) to learn uncertainty in the model parameters. These models simultaneously output the predictions and a measure of confidence in the predictions. By testing these models under various noisy conditions, we show that the (learned) predictive confidence is well calibrated. We use these reliable confidence values for monitoring performance degradation and failure detection in DNNs. We propose two different failure detection methods. In the first method, we define a fixed threshold value based on the behavior of the predictive confidence with changing signal-to-noise ratio (SNR) of the test dataset. The second method learns the threshold value with a neural network. The proposed failure detection mechanisms seamlessly abstain from making decisions when the confidence of the BDNN is below the defined threshold and hold the decision for manual review. Resultantly, the accuracy of the models improves on the unseen test samples. We tested our proposed approach on three medical imaging datasets: PathMNIST, DermaMNIST, and OrganAMNIST, under different levels and types of noise. An increase in the noise of the test images increases the number of abstained samples. BDNNs are inherently robust and show more than 10% accuracy improvement with the proposed failure detection methods. The increased number of abstained samples or an abrupt increase in the predictive variance indicates model performance degradation or possible failure. Our work has the potential to improve the trustworthiness of DNNs and enhance user confidence in the model predictions