Diversity in Shareholder Protection in Common Law Countries

Aktionär, Anlegerschutz, Common Law, Shareholders, Investor protection

Computation of optimal singular controls

Computation of optimal singular control

Behaviour of traffic on a link with traffic light boundaries

This paper considers a single link with traffic light boundary conditions at both ends, and investigates the traffic evolution over time with various signal and system configurations. A hydrodynamic model and a modified stochastic domain wall theory are proposed to describe the local density variation. The Nagel-Schreckenberg model (NaSch), an agent based stochastic model, is used as a benchmark. The hydrodynamic model provides good approximations over short time scales. The domain wall model is found to reproduce the time evolution of local densities, in good agreement with the NaSch simulations for both short and long time scales. A systematic investigation of the impact of network parameters, including system sizes, cycle lengths, phase splits and signal offsets, on traffic flows suggests that the stationary flow is dominated by the boundary with the smaller split. Nevertheless, the signal offset plays an important role in determining the flow. Analytical expressions of the flow in relation to those parameters are obtained for the deterministic domain wall model and match the deterministic NaSch simulations. The analytic results agree qualitatively with the general stochastic models. When the cycle is sufficiently short, the stationary state is governed by effective inflow and outflow rates, and the density profile is approximately linear and independent of time

MRI Tumor Segmentation with Densely Connected 3D CNN

Glioma is one of the most common and aggressive types of primary brain tumors. The accurate segmentation of subcortical brain structures is crucial to the study of gliomas in that it helps the monitoring of the progression of gliomas and aids the evaluation of treatment outcomes. However, the large amount of required human labor makes it difficult to obtain the manually segmented Magnetic Resonance Imaging (MRI) data, limiting the use of precise quantitative measurements in the clinical practice. In this work, we try to address this problem by developing a 3D Convolutional Neural Network~(3D CNN) based model to automatically segment gliomas. The major difficulty of our segmentation model comes with the fact that the location, structure, and shape of gliomas vary significantly among different patients. In order to accurately classify each voxel, our model captures multi-scale contextual information by extracting features from two scales of receptive fields. To fully exploit the tumor structure, we propose a novel architecture that hierarchically segments different lesion regions of the necrotic and non-enhancing tumor~(NCR/NET), peritumoral edema~(ED) and GD-enhancing tumor~(ET). Additionally, we utilize densely connected convolutional blocks to further boost the performance. We train our model with a patch-wise training schema to mitigate the class imbalance problem. The proposed method is validated on the BraTS 2017 dataset and it achieves Dice scores of 0.72, 0.83 and 0.81 for the complete tumor, tumor core and enhancing tumor, respectively. These results are comparable to the reported state-of-the-art results, and our method is better than existing 3D-based methods in terms of compactness, time and space efficiency

Phase decorrelation, streamwise vortices and acoustic radiation in mixing layers

Several direct numerical simulations were performed and analyzed to study various aspects of the early development of mixing layers. Included are the phase jitter of the large-scale eddies, which was studied using a 2-D spatially-evolving mixing layer simulation; the response of a time developing mixing layer to various spanwise disturbances; and the sound radiation from a 2-D compressible time developing mixing layer

Colloidal diffusion and hydrodynamic screening near boundaries

The hydrodynamic interactions between colloidal particles in small ensembles are measured at varying distances from a no-slip surface over a range of inter-particle separations. The diffusion tensor for motion parallel to the wall of each ensemble is calculated by analyzing thousands of particle trajectories generated by blinking holographic optical tweezers and by dynamic simulation. The Stokesian Dynamics simulations predict similar particle dynamics. By separating the dynamics into three classes of modes: self, relative and collective diffusion, we observe qualitatively different behavior depending on the relative magnitudes of the distance of the ensemble from the wall and the inter-particle separation. A simple picture of the pair-hydrodynamic interactions is developed, while many-body-hydrodynamic interactions give rise to more complicated behavior. The results demonstrate that the effect of many-body hydrodynamic interactions in the presence of a wall is much richer than the single particle behavior and that the multiple-particle behavior cannot be simply predicted by a superposition of pair interactions

Konsiderasi Pengintegrasian Teknik Rekayasa Nilai Dan Manajemen Resiko Proyek Tahap Konstruksi – Pengaruhnya Pada Pencapaian Sasaran Dan Kesuksesan Proyek Studi Kasus Pembangunan Pengaman Pantai Di Kabupaten Minahasa Raya

Penelitian ini dimaksudkan untuk menganalisis penerapan pengintegrasian teknik Manajemen Resiko (MR) dan Rekayasa Nilai (RN) secara simultan dalam satu proses khususnya pada tahap konstruksi, kaitannya dengan pencapaian sasaran dan kesuksesan proyek. MR dan RN masih dilaksanakan secara terpisah, namun pengintegrasian keduanya sudah diakui sebagai metodologi yang praktis dan terbaik. Pengintegrasian sudah digunakan secara luas untuk memfasilitasi kesuksesan pengadaan proyek. Proyek-proyek Pembangunan Pengaman Pantai Balai Wilayah Sungai Sulawesi - I, mengalami masalah dalam pencapaian target yang sudah direncanakan (biaya, waktu penyelesaian, dan kualitas). Untuk itu, penelitian ini difokuskan pada proyek-proyek tersebut yang tersebar di 9 (sembilan) lokasi. Pengumpulan data dilakukan dengan cara menyebar questionaire berikut interview di lokasi - lokasi tersebut. Data diproses menggunakan metode Factor analysis, untuk ekstraksi. Untuk verifikasi hubungan antar variabel, metode yang digunakan adalah Structural Equation Modeling (SEM) dengan program Amos 22. Hasil analisis menunjukkan bahwa MR dan RN berhubungan secara positif dengan sasaran dan kesuksesan proyek melalui pengintegrasian MR dan RN. Hasil analisis memperlihatkan adanya hubungan positif antara MR dengan sasaran proyek dan variable - variabel kontrol (Komitmen & Tanggung Jawab; Aspek Sosial; Pengalaman) juga berdampak pada sasaran dan kesuksesan proyek (positif dan negatif). Data hasil observasi menunjang model dengan menggunakan kriteria kesesuaian model (model fits) seperti dalam “model fit summary.” Dalam proses pengintegrasian pada tahap konstruksi, kejelasan dalam mengidentifikasi MR dan RN secara individual sangat diperlukan. Esensi dalam penelitian adalah pengintegrasian RM dan RN secara simultan dan mengintegrasikannya pada tahap konstruksi dapat dipertimbangkan dan difasilitasi, khususnya, pada pada tahap konstruksi proyek-proyek pengaman pantai