DeviceNet reliability assessment using physical and data link layer parameters

Since the 1990s, the increasing deployments of networked automation systems led to increased manufacturing productivity, improved interchangeability of devices from different vendors, facilitated flexibility and reconfigurability for various applications and improved reliability, while reducing installation and maintenance costs. However, the reliability of a network has great impact on the reliability of a networked automation system. This paper presents a novel network reliability assessment method that provides diagnostic and prognostic information for DeviceNet. This work proposes a hybrid network error analysis method using combined physical and datalink layer features to provide complete communication log information. Furthermore, a network/node time to failure (bus-off) prediction algorithm was developed based on the analysis of the patterns of the interrupted packets on the network. The method developed in this study can be used for network reliability evaluation and diagnosis, facilitating better network maintenance decision making. A laboratory testbed was constructed and the experiments on network and node time to failure were conducted to demonstrate the concept. Experimental results show that the proposed method can fully reconstruct the communication log, and predict the network/node bus-off time successfully. Copyright © 2010 John Wiley & Sons, Ltd.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/78241/1/1131_ftp.pd

Mutual Composite Fermion and composite Boson approaches to balanced and imbalanced bilayer quantum Hall system: an electronic analogy of the Helium 4 system

We use both Mutual Composite Fermion (MCF) and Composite Boson (CB) approach to study balanced and im-balanced Bi-Layer Quantum Hall systems (BLQH) and make critical comparisons between the two approaches. We find the CB approach is superior to the MCF approach in studying ground states with different kinds of broken symmetries. In the phase representation of the CB theory, we first study the Excitonic superfluid state (ESF). The theory puts spin and charge degree freedoms in the same footing, explicitly bring out the spin-charge connection and classify all the possible excitations in a systematic way. Then in the dual density representation of the CB theory, we study possible intermediate phases as the distance increases. We propose there are two critical distances $d_{c1} < d_{c2}$ and three phases as the distance increases. When $0 < d < d_{c1}$, the system is in the ESF state which breaks the internal $U(1)$ symmetry, when $d_{c1} < d < d_{c2}$, the system is in an Pseudo-spin density wave (PSDW) state which breaks the translational symmetry, there is a first order transition at $d_{c1}$ driven by the collapsing of magneto-roton minimum at a finite wavevector in the pseudo-spin channel. When $d_{c2} < d < \infty$, the system becomes two weakly coupled $\nu =1/2$ Composite Fermion Fermi Liquid (FL) state. There is also a first order transition at $d= d_{c2}$. We construct a quantum Ginzburg Landau action to describe the transition from ESF to PSDW which break the two completely different symmetries. By using the QGL action, we explicitly show that the PSDW takes a square lattice and analyze in detail the properties of the PSDW at zero and finite temperature.Comment: 29 PRB pages, 18 figures, 2 tables, REVTEX

ENInst: Enhancing Weakly-supervised Low-shot Instance Segmentation

We address a weakly-supervised low-shot instance segmentation, an annotation-efficient training method to deal with novel classes effectively. Since it is an under-explored problem, we first investigate the difficulty of the problem and identify the performance bottleneck by conducting systematic analyses of model components and individual sub-tasks with a simple baseline model. Based on the analyses, we propose ENInst with sub-task enhancement methods: instance-wise mask refinement for enhancing pixel localization quality and novel classifier composition for improving classification accuracy. Our proposed method lifts the overall performance by enhancing the performance of each sub-task. We demonstrate that our ENInst is 7.5 times more efficient in achieving comparable performance to the existing fully-supervised few-shot models and even outperforms them at times.Comment: Accepted at Pattern Recognition (PR

Conjugated polymer nanoparticles for effective siRNA delivery to tobacco BY-2 protoplasts

<p>Abstract</p> <p>Background</p> <p>Post transcriptional gene silencing (PTGS) is a mechanism harnessed by plant biologists to knock down gene expression. siRNAs contribute to PTGS that are synthesized from mRNAs or viral RNAs and function to guide cellular endoribonucleases to target mRNAs for degradation. Plant biologists have employed electroporation to deliver artificial siRNAs to plant protoplasts to study gene expression mechanisms at the single cell level. One drawback of electroporation is the extensive loss of viable protoplasts that occurs as a result of the transfection technology.</p> <p>Results</p> <p>We employed fluorescent conjugated polymer nanoparticles (CPNs) to deliver siRNAs and knockdown a target gene in plant protoplasts. CPNs are non toxic to protoplasts, having little impact on viability over a 72 h period. Microscopy and flow cytometry reveal that CPNs can penetrate protoplasts within 2 h of delivery. Cellular uptake of CPNs/siRNA complexes were easily monitored using epifluorescence microscopy. We also demonstrate that CPNs can deliver siRNAs targeting specific genes in the cellulose biosynthesis pathway (<it>NtCesA-1a </it>and <it>NtCesA-1b)</it>.</p> <p>Conclusions</p> <p>While prior work showed that <it>NtCesA-1 </it>is a factor involved in cell wall synthesis in whole plants, we demonstrate that the same gene plays an essential role in cell wall regeneration in isolated protoplasts. Cell wall biosynthesis is central to cell elongation, plant growth and development. The experiments presented here shows that <it>NtCesA </it>is also a factor in cell viability. We show that CPNs are valuable vehicles for delivering siRNAs to plant protoplasts to study vital cellular pathways at the single cell level.</p

TextManiA: Enriching Visual Feature by Text-driven Manifold Augmentation

We propose TextManiA, a text-driven manifold augmentation method that semantically enriches visual feature spaces, regardless of class distribution. TextManiA augments visual data with intra-class semantic perturbation by exploiting easy-to-understand visually mimetic words, i.e., attributes. This work is built on an interesting hypothesis that general language models, e.g., BERT and GPT, encompass visual information to some extent, even without training on visual training data. Given the hypothesis, TextManiA transfers pre-trained text representation obtained from a well-established large language encoder to a target visual feature space being learned. Our extensive analysis hints that the language encoder indeed encompasses visual information at least useful to augment visual representation. Our experiments demonstrate that TextManiA is particularly powerful in scarce samples with class imbalance as well as even distribution. We also show compatibility with the label mix-based approaches in evenly distributed scarce data.Comment: Accepted at ICCV 2023. [Project Pages] https://textmania.github.io

Exploiting Synthetic Data for Data Imbalance Problems: Baselines from a Data Perspective

We live in a vast ocean of data, and deep neural networks are no exception to this. However, this data exhibits an inherent phenomenon of imbalance. This imbalance poses a risk of deep neural networks producing biased predictions, leading to potentially severe ethical and social consequences. To address these challenges, we believe that the use of generative models is a promising approach for comprehending tasks, given the remarkable advancements demonstrated by recent diffusion models in generating high-quality images. In this work, we propose a simple yet effective baseline, SYNAuG, that utilizes synthetic data as a preliminary step before employing task-specific algorithms to address data imbalance problems. This straightforward approach yields impressive performance on datasets such as CIFAR100-LT, ImageNet100-LT, UTKFace, and Waterbird, surpassing the performance of existing task-specific methods. While we do not claim that our approach serves as a complete solution to the problem of data imbalance, we argue that supplementing the existing data with synthetic data proves to be an effective and crucial preliminary step in addressing data imbalance concerns

Integrable Impurity Model with Spin and Flavour: Model Inspired by Resonant Tunneling in Quantum Dot

We introduce an integrable impurity model in which both electrons and impurity have spin and flavour degrees of freedom. This model is a generalization of the multi-channel Kondo model and closely related with resonant tunneling through quantum dot. The Hamiltonian is exactly diagonalized by means of the Bethe ansatz.Comment: 1 reference is adde

The Formation of Colonial Landscape and Its Sociocultural Meanings in Korean Rural Society: A Case Study of Hwaho Village, North Chŏlla

Translated from the article published in Korean Cultural Anthropology vol. 43, no. 1, 2010, with permission from the Korean Society for Cultural Anthropology.This paper will delineate the historical and cultural meanings of the colonial landscape formed during Japanese colonization in the village of Hwaho in North Chŏlla province. The Japanese began arriving in Korea starting in the early 1900s. Once Japan colonized Korea officially in 1910, the Japanese moved in on a larger scale. They established Japanese communities in the midst of Korean communities regardless of what type of Korean community was already established, be it village, town, or city. The newly-formed Japanese communities in Korea looked exotic and authoritative to the colonized people. They began to be viewed as symbols of colonial domination. In addition to residential houses there were also administrative buildings and commercial shops. In rural areas, particularly those in the North Chŏlla plains which were known to be one of Koreas granary regions, rich Japanese landlords purchased vast tracts of agricultural land and established large farms along with offices, residences, storage facilities, commercial shops, schools and religious institutions. These new Japanese communities were seen as quite different from the Korean communities in both structure and form. I selected the village of Hwaho in North Chŏlla as the location for my fieldwork because the Japanese community still remains intact, including the old buildings, houses, school, as well as other sites and fields. More importantly, some old villagers in their 80s experienced the colonialism. Many studies on the colonial landscape in Korea have focused on cities such as the capital, Kyŏngsŏng (Seoul), and four other cities, Inchŏn, Pusan, Mokpo, and Kunsan, which were frontier cities in terms of both modernization and colonialism since they were treaty (open) ports to foreign vessels in the late 19th century. In comparison to scholarly attention to cities, the colonial modernization of farming areas attracts far less attention even though the farming villages actually experienced colonial modernization to a greater extent than cities. Aware of the importance of farming villages colonial modernization seen through the colonial landscape, I decided to study the village of Hwaho. I will examine study four aspects of colonial modernism in a Korean farming village: 1) the formation of the Japanese community and its socio-economic background, 2) the specific characteristics of colonial landscape of Hwaho, 3) the newly established socio-economic hierarchy in the village upon the arrival of Japanese immigrants including big and small capitalists and petty farmers, and 4) cultural meanings of the colonial landscape and its effect on the Korean villagers. Lastly, I discuss the characteristics of colonial modernity based on what the villagers experienced