Learning non-negativity constrained variation for image denoising and deblurring

This paper presents a heuristic Learning-based Non-Negativity Constrained Variation (L-NNCV) aiming to search the coefficients of variational model automatically and make the variation adapt different images and problems by supervised-learning strategy. The model includes two terms: a problem-based term that is derived from the prior knowledge, and an image-driven regularization which is learned by some training samples. The model can be solved by classical o-constraint method. Experimental results show that: the experimental effectiveness of each term in the regularization accords with the corresponding theoretical proof; the proposed method outperforms other PDE-based methods on image denoising and deblurring.</p

Kesesakan Dan Agresivitas Pada Remaja Di Kawasan Tambak Lorok Semarang

Penelitian ini bertujuan untuk mengetahui hubungan antara kesesakan dengan agresivitas pada remaja yang tinggal di Kawasan Tambak Lorok Semarang. Populasi dalam penelitian ini adalah remaja yang tinggal di Kawasan Tambak Lorok Semarang. Pengumpulan data menggunakan dua buah skala yaitu, Skala Agresivitas (22 aitem; α=0,864) dan Skala Kesesakan (16 aitem; α=0,828). Subjek penelitian berjumlah 230 remaja yang tinggal di Kawasan Tambak Lorok Semarang yang dipilih melalui teknik simple random sampling. Hasil analisis data menggunakan teknik analisis regresi sederhana menunjukkan terdapat hubungan positif antara kesesakan dengan agresivitas pada remaja yang tinggal Kawasan Tambak Lorok Semarang (r=0,578; p=0,000). Semakin tinggi kesesakan yang dirasakan subjek maka semakin tinggi agresivitas. Kesesakan memberikan sumbangan efektif sebesar 33,4% pada agresivitas dan sisanya sebesar 66,6% dipengaruhi oleh faktor lain yang tidak diteliti dalam penelitian ini

Nothing but Being There Matters: Expectancy-Value Motivation Between U.S. and Chinese Middle School Students

Current literature theorizes that culture-induced expectancy beliefs and values in learning may engage learners of varied cultures in differentiated motivational processes. The purpose of the study was to determine the extent to which U.S. and Chinese middle school students differed in expectancy-value motivation in physical education. Middle school students from the U.S. (n = 813, 14 schools) and China (n = 806, 8 schools) provided data on expectancy-value motivation in physical education. A MANOVA with country as the independent factor and grade level as covariate revealed that the U.S. students held higher expectancy beliefs (p =.001, η2=.62), while the Chinese students showed stronger appreciation for the attainment (p =.001, η2=.33) and utility values (p =.001, η2=.35). The students from both countries equally appreciated the intrinsic value (p =.45). A canonical correlation analysis demonstrated that the expectancy-value motivation declined with age/grade increase at the same pace regardless of culture. These findings clarify for us the cultural influence or non-cultural influence on the expectancy-value motivation in middle school students. They inform us about the potential to develop intrinsic-value based across-cultural motivation strategies as well as the cultural sensitivity of applying motivation strategies focusing on expectancy of success, attainment value, and utility value

Luce in arte e cultura. Le applicazioni e tecnologie della luce naturale nei spazi museali

LAUREA SPECIALISTICAQuesta tesi nasce da un tentativo di risistemare l’illuminazione delle Sale Napoleoniche nella Pinacoteca di Brera, l’interno assoluto per eccellenza. La ricerca si è focalizzata sul tema della luce naturale, fondamentale nella vita dell’uomo e in architettura, ed in particolare sulle modalità con cui la luce entra negli spazi museali, definendoli e caratterizzandoli. Gli intenti principali di questa tesi sono quelli di esplorare gli attuali metodi di illuminazione nei grandi interni, di presentare le tecniche attualmente utilizzate e di sottolineare quanto sia importante il ruolo che la luce come form-giver in uno spazio interno . Questa tesi cercherà di fornire anche una risposta su come rendere il processo di illuminazione degli interni più accattivante e stimolante. Dal momento che la luce è un fenomeno visivo “in movimento”, non può essere completamente catturato e inquadrato sotto le linee guida previste scientificamente. Si cercherà quindi di trovare nuovi linguaggi e nuove modalità per rendere evidente il fatto che “la luce non è qualcosa che si aggiunge all’interior design, ma è implicito in ogni decisione di progettazione”. Attraverso il metodo del processo di progettazione, si cercheranno di esprimere le potenzialità, le limitazioni della luce e le sue qualità. Il progetto renderà inoltre evidente come la luce, insieme alla forma architettonica, può essere utilizzato per rinsaldare la potenza dell’esperienza spaziale

OccupancyDETR: Making Semantic Scene Completion as Straightforward as Object Detection

Visual-based 3D semantic occupancy perception (also known as 3D semantic scene completion) is a new perception paradigm for robotic applications like autonomous driving. Compared with Bird's Eye View (BEV) perception, it extends the vertical dimension, significantly enhancing the ability of robots to understand their surroundings. However, due to this very reason, the computational demand for current 3D semantic occupancy perception methods generally surpasses that of BEV perception methods and 2D perception methods. We propose a novel 3D semantic occupancy perception method, OccupancyDETR, which consists of a DETR-like object detection module and a 3D occupancy decoder module. The integration of object detection simplifies our method structurally - instead of predicting the semantics of each voxels, it identifies objects in the scene and their respective 3D occupancy grids. This speeds up our method, reduces required resources, and leverages object detection algorithm, giving our approach notable performance on small objects. We demonstrate the effectiveness of our proposed method on the SemanticKITTI dataset, showcasing an mIoU of 23 and a processing speed of 6 frames per second, thereby presenting a promising solution for real-time 3D semantic scene completion