33 research outputs found
Improved Naive Bayes with Mislabeled Data
Labeling mistakes are frequently encountered in real-world applications. If
not treated well, the labeling mistakes can deteriorate the classification
performances of a model seriously. To address this issue, we propose an
improved Naive Bayes method for text classification. It is analytically simple
and free of subjective judgements on the correct and incorrect labels. By
specifying the generating mechanism of incorrect labels, we optimize the
corresponding log-likelihood function iteratively by using an EM algorithm. Our
simulation and experiment results show that the improved Naive Bayes method
greatly improves the performances of the Naive Bayes method with mislabeled
data
AceGPT, Localizing Large Language Models in Arabic
This paper explores the imperative need and methodology for developing a
localized Large Language Model (LLM) tailored for Arabic, a language with
unique cultural characteristics that are not adequately addressed by current
mainstream models like ChatGPT. Key concerns additionally arise when
considering cultural sensitivity and local values. To this end, the paper
outlines a packaged solution, including further pre-training with Arabic texts,
supervised fine-tuning (SFT) using native Arabic instructions and GPT-4
responses in Arabic, and reinforcement learning with AI feedback (RLAIF) using
a reward model that is sensitive to local culture and values. The objective is
to train culturally aware and value-aligned Arabic LLMs that can serve the
diverse application-specific needs of Arabic-speaking communities.
Extensive evaluations demonstrated that the resulting LLM called `AceGPT' is
the SOTA open Arabic LLM in various benchmarks, including instruction-following
benchmark (i.e., Arabic Vicuna-80 and Arabic AlpacaEval), knowledge benchmark
(i.e., Arabic MMLU and EXAMs), as well as the newly-proposed Arabic cultural \&
value alignment benchmark. Notably, AceGPT outperforms ChatGPT in the popular
Vicuna-80 benchmark when evaluated with GPT-4, despite the benchmark's limited
scale. % Natural Language Understanding (NLU) benchmark (i.e., ALUE)
Codes, data, and models are in https://github.com/FreedomIntelligence/AceGPT.Comment: https://github.com/FreedomIntelligence/AceGP
Compositional Design of Analog Systems Using Contracts
This work addresses the problem of assembling analog integrated systems out of pre-designed IP components. Efficient system-level design is increasingly relying on hierarchical design-space exploration, as well as compositional methods, to shorten time-to-market, leverage design re-use, and achieve optimal performances. However, in analog electronic systems, circuit behaviors are so tightly dependent on their interface conditions that accurate system performance estimations based on characterizations of individual stand-alone circuits is a hard task. Since there is no general solution to this problem, analog system integration has traditionally used ad-hoc solutions heavily dependent on designers' experience and detailed knowledge of the target application.A system composition method is proposed that build upon the analog platform-based design (APBD) methodology by exploiting assume-guarantee reasoning, contracts, to enforce correct-by-construction system-level composition. Contracts intuitively capture the thought process of a designer, who aims at guaranteeing circuit performance only under specific assumptions (e.g. interface loading or dynamic range). Contracts can be broadly classified into two categories: horizontal contracts between components of the same abstraction level and vertical contracts between a system at level l + 1 and the components that make up the system from level l. Horizontal contracts can be used to ensure that correct component behavior by constraining the external environment settings to be within the assumed range. Vertical contracts capture assumptions that system-level designers introduce by leveraging knowledge about the system architecture, which is not available at the component-level. Contracts can be naturally incorporated into the APBD design flow to ensure accurate design space explorations and correct design implementations.The methodology is applied to several case studies to demonstrate the value of our approach. First, an ultra-wide band receiver front-end is composed using horizontal contracts to preserve the correct behavior of pre-designed IP components in composition and to allow design decisions to be reliably made at a higher abstraction level, both key factors to improve designer productivity. In another case study for composition of an analog feedback systems, the Sallen-Key cell, I show the application of both horizontal and vertical contracts so that the performance of a composition of circuit blocks not only preserves component behavior, but also satisfies system specifications and requirements. Finally, the methodology is applied to the complete design study of the UWB receiver chain for the Intelligent Tire System to demonstrate hierarchical design space exploration using analog contracts. The study shows that given a library of components, an optimized system can be quickly realized through hierarchical construction of subsystems and propagation of contracts. The works featured are seminal to further advancements in bridging the gap between system-level and circuit-level design in the analog/mixed-signal domain
A Platform-Based Methodology for System-Level Mixed-Signal Design
The complexity of today's embedded electronic systems as well as their demanding performance and reliability requirements are such that their design can no longer be tackled with ad hoc techniques while still meeting tight time to-market constraints. In this paper, we present a system level design approach for electronic circuits, utilizing the platform-based design (PBD) paradigm as the natural framework for mixed-domain design formalization. In PBD, a meet-in-the-middle approach allows systematic exploration of the design space through a series of top-down mapping of system constraints onto component feasibility models in a platform library, which is based on bottom-up characterizations. In this framework, new designs can be assembled from the precharacterized library components, giving the highest priority to design reuse, correct assembly, and efficient design flow from specifications to implementation. We apply concepts from design centering to enforce robustness to modeling errors as well as process, voltage, and temperature variations, which are currently plaguing embedded system design in deep-submicron technologies. The effectiveness of our methodology is finally shown on the design of a pipeline A/D converter and two receiver front-ends for UMTS and UWB communications
DataSheet_1_An efficient Agrobacterium-mediated transient transformation system and its application in gene function elucidation in Paeonia lactiflora Pall.docx
Paeonia lactiflora Pall. is known as the king of herbaceous flowers with high ornamental and precious medicinal value. However, the lack of a stable genetic transformation system has greatly affected the research of gene function in P. lactiflora. The Agrobacterium-mediated transient gene expression is a powerful tool for the characterization of gene function in plants. In this study, the seedlings of P. lactiflora were used as the transformation receptor materials, and the efficient transient transformation system with a GUS reporter gene was successfully established by Agrobacterium harboring pCAMBIA1301. To optimize the system, we investigated the effects of germination time, Agrobacterium cell density, infection time, acetosyringone (AS) concentration, co-culture time, negative pressure intensity, Tween-20 concentration and different receptor materials on the transient transformation efficiency of P. lactiflora. The results showed that the highest transient transformation efficiency (93.3%) could be obtained when seedlings in 2-3 cm bud length were subjected to 12 h infection of resuspension solution comprising 1.2 OD600Agrobacterium, 200 μM AS and 0.01% Tween-20 under 10 of negative pressure intensity followed by 3 days of co-culture in darkness condition. This method is more suitable for the study of gene function in P. lactiflora. Subsequently, stress resistance genes PlGPAT, PlDHN2 and PlHD-Zip were used to verify the effectiveness of this transformation system. These results can provide critical information for identification of key genes in non-model plants, such as P. lactiflora, and promote the development of molecular biology research for P. lactiflora.</p
An Alginate Hybrid Sponge with High Thermal Stability: Its Flame Retardant Properties and Mechanism
The worldwide applications of polyurethane (PU) and polystyrene (PS) sponge materials have been causing massive non-renewable resource consumption and huge loss of property and life due to its high flammability. Finding a biodegradable and regenerative sponge material with desirable thermal and flame retardant properties remains challenging to date. In this study, bio-based, renewable calcium alginate hybrid sponge materials (CAS) with high thermal stability and flame retardancy were fabricated through a simple, eco-friendly, in situ, chemical-foaming process at room temperature, followed by a facile and economical post-cross-linking method to obtain the organic-inorganic (CaCO3) hybrid materials. The microstructure of CAS showed desirable porous networks with a porosity rate of 70.3%, indicating that a great amount of raw materials can be saved to achieve remarkable cost control. The sponge materials reached a limiting oxygen index (LOI) of 39, which was greatly improved compared with common sponge. Moreover, with only 5% calcium carbonate content, the initial thermal degradation temperature of CAS was increased by 70 °C (from 150 to 220 °C), compared to that of calcium alginate, which met the requirements of high-temperature resistant and nonflammable materials. The thermal degradation mechanism of CAS was supposed based on the experimental data. The combined results suggest promising prospects for the application of CAS in a range of fields and the sponge materials provide an alternative for the commonly used PU and PS sponge materials
High sensitivity air-coupled MHz frequency ultrasound detection using on-chip microcavities
Owing to their dual-resonance enhanced sensitivity, cavity optomechanical
systems provide an ideal platform for ultrasound sensing. In this work, we
realize high sensitivity air-coupled ultrasound sensing from kilohertz (kHz) to
megahertz (MHz) frequency range based on whispering gallery mode microcavities.
Using a 57 um-diameter microtoroid with high optical Q factor (~10^7) and
mechanical Q factor (~700), we achieve sensitivities of 46 uPa Hz^{-1/2}-10 mPa
Hz^{-1/2} in a frequency range of 0.25-3.2 MHz. Thermal-noise-limited
sensitivity is realized around the mechanical resonance at 2.56 MHz, in a
frequency range of 0.6 MHz. We also observe the second- and third-order
mechanical sidebands, and quantitatively study the intensities of each
mechanical sideband as a function of the mechanical displacement. Measuring the
combination of signal to noise ratios at all sidebands has the potential to
extend the dynamic range of ultrasound sensing. In addition, to improve the
ultrasound sensitivity in the kHz frequency range, we use a microdisk with a
diameter of 200 um, and achieve sensitivities of 1.83 uPa Hz^{-1/2}-10.4 mPa
Hz^{-1/2} in 30 kHz-1.65 MHz range
Bagging Strategy and Identification of Coloring Mode of ‘Xinqihong’ Pear
‘Xinqihong’ is a recently selected and well-colored red pear (Pyrus bretschneideri Rehd.) cultivar that is popular in the marketplace owing to the bright red color and high quality of the fruit. The red pigmentation is strongly associated with the light signal. However, its responses to bagging treatment and to light exposure after shading are unknown. In this study, the fruit were treated with three types of fruit bags. ’Xinqihong’ fruit colored rapidly in response to light stimulation. A white fruit bag was optimal for bagging of ‘Xinqihong’ fruit. To ensure satisfactory red pigmentation, the fruit required exposure to 30 days of light after bag removal. A transcriptome analysis was conducted to screen light-signal-related genes and identify their possible functions. PbCRY1 activated the promoter of PbHY5.2 and enhanced its expression. PbHY5.2 activated the promoter activity of PbUFGT and induced anthocyanin synthesis, and also showed self-activation characteristics. Both PbCRY2 and PbPHY1 induced anthocyanin accumulation. Thus, blue-light receptors played an important role in anthocyanin synthesis. This study provides a theoretical basis for the bagging cultivation of new varieties of ‘Xinqihong’, and lays a foundation for the study of the mechanisms of red pear fruit coloring in response to light signals