Conditional Random Fields with Lasso and Its Application to the Classification of Relationships Between Plant Genes Expression Level and Fungus Genes

The classification problem of Gene Expression Level is a major research area in both statistics and gene expression analysis. There are several classical methods to solve the classification problem, but classical models require that the observations in the dataset should fit the assumption of independence. This assumption is not suitable for the gene expression analysis. To solve the classification problem of Gene Expression Level data, the Conditional Random Field (CRF) is introduced. Moreover, Least Absolute Selection and Shrinkage Operator (LASSO) penalty, a dimensional reduction method, is introduced to improve the CRF model

Efficient and Consistent Bundle Adjustment on Lidar Point Clouds

Bundle Adjustment (BA) refers to the problem of simultaneous determination of sensor poses and scene geometry, which is a fundamental problem in robot vision. This paper presents an efficient and consistent bundle adjustment method for lidar sensors. The method employs edge and plane features to represent the scene geometry, and directly minimizes the natural Euclidean distance from each raw point to the respective geometry feature. A nice property of this formulation is that the geometry features can be analytically solved, drastically reducing the dimension of the numerical optimization. To represent and solve the resultant optimization problem more efficiently, this paper then proposes a novel concept {\it point clusters}, which encodes all raw points associated to the same feature by a compact set of parameters, the {\it point cluster coordinates}. We derive the closed-form derivatives, up to the second order, of the BA optimization based on the point cluster coordinates and show their theoretical properties such as the null spaces and sparsity. Based on these theoretical results, this paper develops an efficient second-order BA solver. Besides estimating the lidar poses, the solver also exploits the second order information to estimate the pose uncertainty caused by measurement noises, leading to consistent estimates of lidar poses. Moreover, thanks to the use of point cluster, the developed solver fundamentally avoids the enumeration of each raw point (which is very time-consuming due to the large number) in all steps of the optimization: cost evaluation, derivatives evaluation and uncertainty evaluation. The implementation of our method is open sourced to benefit the robotics community and beyond.Comment: 30 pages, 15 figure

Design, Analysis and Fabrication of Micro Optical Systems involving UV-Deep Lithography - with an Application in Atomic Physics

Integrated free space optics is a widespread and important field in today's technology. This study outlines one application in atomic physics and quantum optics. Since optimized design requires the adequate mathematical treatment of light propagation in free space, this study deals with the various existing scalar methods of light propagation, including plane wave expansion, the Fresnel approximation, and ray-transfer matrices applied to geometrical optics and the ABCD-law for Gaussian beams. As do other scientific methods, these mathematical treatments have their own prerequisites. Consequently, the application scope of these methods is restricted. This thesis aims at relaxing some prerequisites for conventional methods and also at demonstrating new application aspects. Using a research project in atomic physics as an application example, this thesis is restricted to two main research fields: micro optics and deep lithography. The topic comprises a design tool for minimal optical systems, energy investigation in scalar fields, mask diffraction in thick absorbing resists with partially coherent illumination, a phase reconstruction method using the ambiguity function, lithographic fabrication of alignment structures for a fiber resonator, and fabrication of micro lenses using replication techniques

Performance analysis of Routing Protocol for Low power and Lossy Networks (RPL) in large scale networks

With growing needs to better understand our environments, the Internet-of-Things (IoT) is gaining importance among information and communication technologies. IoT will enable billions of intelligent devices and networks, such as wireless sensor networks (WSNs), to be connected and integrated with computer networks. In order to support large scale networks, IETF has defined the Routing Protocol for Low power and Lossy Networks (RPL) to facilitate the multi-hop connectivity. In this paper, we provide an in-depth review of current research activities. Specifically, the large scale simulation development and performance evaluation under various objective functions and routing metrics are pioneering works in RPL study. The results are expected to serve as a reference for evaluating the effectiveness of routing solutions in large scale IoT use cases

Text-Driven Foley Sound Generation With Latent Diffusion Model

Foley sound generation aims to synthesise the background sound for multimedia content. Previous models usually employ a large development set with labels as input (e.g., single numbers or one-hot vector). In this work, we propose a diffusion model based system for Foley sound generation with text conditions. To alleviate the data scarcity issue, our model is initially pre-trained with large-scale datasets and fine-tuned to this task via transfer learning using the contrastive language-audio pertaining (CLAP) technique. We have observed that the feature embedding extracted by the text encoder can significantly affect the performance of the generation model. Hence, we introduce a trainable layer after the encoder to improve the text embedding produced by the encoder. In addition, we further refine the generated waveform by generating multiple candidate audio clips simultaneously and selecting the best one, which is determined in terms of the similarity score between the embedding of the candidate clips and the embedding of the target text label. Using the proposed method, our system ranks ${1}^{st}$ among the systems submitted to DCASE Challenge 2023 Task 7. The results of the ablation studies illustrate that the proposed techniques significantly improve sound generation performance. The codes for implementing the proposed system are available online.Comment: Submit to DCASE-workshop 2023. arXiv admin note: text overlap with arXiv:2305.1590

A simple integrated single-atom detector

We present a reliable and robust integrated fluorescence detector capable of detecting single atoms. The detector consists of a tapered lensed single-mode fiber for precise delivery of excitation light and a multimode fiber to collect the fluorescence. Both are mounted in lithographically defined SU-8 holding structures on an atom chip. Rb87 atoms propagating freely in a magnetic guide are detected with an efficiency of up to 66%, and a signal-to-noise ratio in excess of 100 is obtained for short integration times.Comment: 3 pages, 3 figure

OPA1 mutation and late-onset cardiomyopathy: mitochondrial dysfunction and mtDNA instability.

BackgroundMitochondrial fusion protein mutations are a cause of inherited neuropathies such as Charcot-Marie-Tooth disease and dominant optic atrophy. Previously we reported that the fusion protein optic atrophy 1 (OPA1) is decreased in heart failure.Methods and resultsWe investigated cardiac function, mitochondrial function, and mtDNA stability in a mouse model of the disease with OPA1 mutation. The homozygous mutation is embryonic lethal. Heterozygous OPA(+/-) mice exhibit reduced mtDNA copy number and decreased expression of nuclear antioxidant genes at 3 to 4 months. Although initial cardiac function was normal, at 12 months the OPA1(+/-) mouse hearts had decreased fractional shortening, cardiac output, and myocyte contraction. This coincided with the onset of blindness. In addition to small fragmented mitochondria, aged OPA1(+/-) mice had impaired cardiac mitochondrial function compared with wild-type littermates.ConclusionsOPA1 mutation leads to deficiency in antioxidant transcripts, increased reactive oxygen species, mitochondrial dysfunction, and late-onset cardiomyopathy