Miracle-dz/UniFAR-FTUs huggingface dataset:
Localization with Laser Range Finder in a Metrically Inconsistent Map from Monocular SLAM

Due to the lack of a fixed baseline between frames, scale drift of the map from a monocular vision-based SLAM system is almost inevitable. It is difficult for a robot with range-based sensors to localize itself on such a metrically inconsistent map. In this paper, we propose a scale-aware localization method, which allows a robot with 2D LRF to achieve the purpose of localizing itself on a map from monocular SLAM. The scales of drifted local maps will also be corrected at the same time. In this work, we firstly present a technique to extract 2D structure from the 3D point cloud established by a monocular camera. And then, by employing an alternative to Particle Filter Localization algorithm, our approach is able to estimate both the poses of the robot and the local scales of the map. Finally, the performance of our approach has been evaluated on a public dataset.
Regional homogeneity of brain in generalized anxiety disorder:a resting-state functional MRI study

Objective:To investigate regional homogeneity(ReHo)of brain in patients with generalized anxiety disorder(GAD)using resting-state functional MRI(rs-fMRI). Methods:24patients with GAD and 24age-,gender-,and education-matched healthy volunteers(control group)were included and all of them underwent rs-fMRI.The rs-fMRI data were analyzed with the regional homogeneity method after data conversion.The raw ReHo values were subjected to t-test of voxel wised comparison to derive the resting-state brain function differences between the two groups.The correlation between ReHo values of abnormal regions found in GAD group and the scores obtained according to the Self-Rating Anxiety Scale(SAS)and Hamilton Anxiety Scale(HAMA)was analyzed.Results:Compared with the control group,the GAD group showed significantly decreased ReHo value in the right thalamus,right middle occipital gyrus,left middle frontal gyrus,right fusiform gyrus,and increased ReHo value in the right inferior frontal gyrus,right precuneus,right precentral gyrus,left middle frontal gyrus and left superior frontal gyrus(P0.001,cluster size10voxels). The ReHo value of right thalamus in GAD group had a negative correlation with HAMA score(r=-0.637,P=0.001). Conclusion:Resting-state fMRI with ReHo method can reflect the abnormal brain activity in the patients with generalized anxiety disorder.
CÉLULAS-TRONCO FETAIS DE MEMBRANA AMNIÓTICA: O FUTURO DA MEDICINA REGENERATIVA AMNIOTIC MEMBRANE FETAL STEM CELLS: THE FUTURE OF REGENERATIVE MEDICINE

Celulas- tronco (CT) sao celulas indiferenciadas com capacidade de auto-renovacao ilimitada e potencial de diferenciacao que lhes confere um papel primordial e vital. A terapia celular com CT parece ser uma estrategia de tratamento promissor. Devido as questoes eticas, encontramos dificuldades na utilizacao de celulas-tronco embrionarias (CTE). Ja as celulas-tronco adultas (CTA) por apresentarem baixa plasticidade se tornam pouco promissoras. Com isso, ha um crescente interesse em outras fontes de CT como as celulas-tronco fetais (CTF) que representam uma fonte de CT ainda pouco explorada. Elas sao facilmente acessiveis e isoladas a partir de tecidos extra-embrionarios, como a placenta e a membrana amniotica, tornando um fonte interessante ja que geralmente esses tecidos sao descartados apos o nascimento. Essas celulas apresentam um crescimento rapido e alta plasticidade. Estudos com celulas-tronco de Membrana Amniotica (CTMA) demonstram seu facil cultivo, alem de baixa resposta imunologica, propriedades anti-inflamatorias e anti-bacterianas. Com isso a membrana amniotica pode ser considerada como uma nova e conveniente fonte de obtencao de CT. Palavras chave: membrana amniotica; celulas-tronco; celulas-tronco fetais; placenta; anexos fetais; terapia celular. ABSTRACT Stem cells (SC) are undifferentiated cells capable of unlimited self-renewal and high differentiation potential, which grants them a vital and leading role. Cell therapy with SC seems to be a promising treatment strategy. Due to difficulties surrounding the use of embryonic stem cells (ESC) because of ethical issues associated with these cells and the relationship of low plasticity of adult stem cells (ASC) there is a growing interest in other sources of SC. Fetal stem cells (FSC) represent a source of SC yet unexplored. They are easily accessible and isolable from extra-embryonic tissues such as placenta and amniotic membrane, which are usually discarded after birth. They have rapid growth and good plasticity. Researches using amniotic membrane stem cell (AMSC) showcase theirs easy cultivation and high plasticity in addition to low immune response, anti-inflammatory and anti-bacterial properties. So, the amniotic membrane (AM) might be considered as a new and convenient source of SC. Keywords: amniotic membrane; stem cells; fetal stem cells; placenta; fetal annexes; cell therapy.
Comparative analysis of comparators in 90nm CMOS Technology

Analog to digital converter (ADC) is a very useful device for extracting the digital signal from the analog one. Technically successive approximation type ADC processing speed depends largely on the fast operation of the comparator, which is one of the vital part of such structure. In today’s digital ultra-tech world, speed and low power consumption are major factors that are taken under consideration. In this paper, the propagation delays, power dissipation of different comparators will be analyzed dependent on different temperature points. The readers can easily draw an analytical expression for the performance of the comparator by considering these comparisons. To design a low power and low voltage comparator voltage supply, propagation delay, power dissipation must be considered which are represented in this paper to find a better comparator which will act ideally in real environment without changing its characteristics. This paper represents a comparison of different comparators such as circuit complexity, length, CMOS technology, voltage supply etc. Simulations have been performed by using SPICE in 90 nm CMOS technology.
Monitoring Machine Tool Based on External Physical Characteristics of the Machine Tool Using Machine Learning Algorithm

Using the three-dimensional acceleration sensor and the current sensor to collect vibration data and current data to get information from machine tools without Programmable Logic Controller(PLC) is the direct method. Processing the data by characteristic extraction engineering, and building models by machine learning algorithms. So it can identify the status of machine tools from this models accurately. Then, it can help the small-and medium sized enterprises to monitor machine tools with high scalability and portability.
Optimal filtering for noise reduction in myoelectric signals on an embedded system

Electromyography (EMG) signals are used to diagnose muscular pathologies and are also employed as inputs for electronic applications. However, a major disadvantage in detecting this signal is the noise that can be derived from diverse sources such as power supplies, incorrect placement of the electrodes, and the environment. To reduce the noise in the signal a filter must be incorporated in the system. The aim of this paper is to reduce the noise generated in the muscular signals through an embedded system, using an optimal filter configured with different frequencies and numbers of samples values. A real-time application was implemented using an Olimex SHIELD-EKG-EMG shield and a SAM V71 board. The shield was used to obtain the signal using the ADC of the SAM V71 board and the filter was programmed on the board. A correct configuration of the frequency and number of samples is crucial to compute an optimal filter on an embedded application. The noise reduction results are presented.
Constant on/off-Time Hybrid Modulation in Digital Current-Mode Control Using Event-Based Sampling

Ripple-based constant <sc>on</sc>-time and <sc>off</sc>-time control techniques can achieve fast step-down and step-up transient performance along with an improved light-load efficiency. However, they suffer from varying switching frequency at the steady state and often require a phase-locked loop for frequency regulation. This paper proposes a constant <sc>on/off</sc>-time hybrid modulation technique in a digitally current-mode controlled synchronous buck converter. The proposed technique considers an event-based sampling mechanism using one sample per switching cycle, which makes it useful for high-frequency implementation. This requires a monoshot timer and a digital voltage controller <inline-formula><tex-math notation="LaTeX">$G_c(z)$</tex-math></inline-formula>. The proposed technique can be configured to a constant <sc>on</sc>-time or <sc>off</sc>-time modulator with seamless transition because of sharing <inline-formula><tex-math notation="LaTeX">$G_c(z)$</tex-math></inline-formula>; thus, improved step-up/down transient performance can be retained. Furthermore, a discrete-time framework is proposed for fast-scale stability analysis, and the effects of finite sampling and practical parasitics are discussed. Discrete-time small-signal models are derived for the direct digital control design with enhanced stability and performance. A frequency adaptation method is discussed to customize the switching frequency in real time. A buck converter prototype is tested, and the usefulness of the proposed modulation technique is verified experimentally.
Dynamic Characters of Liquid Sloshing in Partly-filled Spacecraft under Micro-gravity

Liquid propellant sloshing in partly-filled tank under micro-gravity is researched. Suppose the tank is rigid, ADINA and Fluent are used to analyze liquid sloshing in different-shape tanks under various fulfilling ratios and vibrating frequencies. The disciplines of each variable’s change are summarized, and then common disciplines can be obtained and analyzed.
African American children's literature: past and present

Annie L. Freeman African American Children's Literature: Past and Present, 1997; Thesis advisor Or Lymne Levy This thesis examines and analyzes the history of African American children's literature, which began in the 1890s, and highlighted negative stories written by whites about African Americans. It progresses to the 1990s, and highlights warm, nch, stones with similar background experiences, written by and about African Americans. This thesis discusses the lack of African American children's literature, and the dlfftculy in finding it in quantities: in librares. bookstores, Or book reviews. Because of the lack of ciltural literature in abundance forAfrican American children, social portraits experienced by African American children in children's literature are generally representative of those expressed by white American authors. For this reason, an annotated bibliography of African American children's literature books, written by African American authors, is also included. These books are listed in two specific categories: 1) African American children's literature books for the elementay student, and 2) African American children's literature books for the middle school student. This thesis also includes an author's index, which names many African American children's authors.
An Optimized Kurtogram Method for Early Fault Detection of Rolling Element Bearings Using Acoustic Emission

Bearings are the basic components of rotating machinery and their integrity is the key to ensuring the operational stability and work reliability of machines. Compared with traditional vibration analysis, acoustic emission (AE) has some unique advantages, such as higher sensitivity to low-speed rotating mechanical defect detection and more potential for early fault detection. However, the AE signals collected from bearing with incipient fault always include heavy noise levels, reducing the capability of early defect detection. Therefore, this paper proposes an optimized Kurtogram method for incipient defect detection of bearings, which combines autocorrelation function, Shannon entropy and Kurtogram to identify early localized defects in AE signals. The major innovations are as follows: (i) The autocorrelation function (ACF) is adopted to process the envelope of all wavelet packet node signals to highlight the periodic pattern in the AE signal, (ii) kurtosis-to-Shannon entropy ratio (KSR) is introduced to improve the capability to detect bearing fault characteristics in low signal-to-noise ratio (SNR) signals. Simulated AE signals and real bearing fault signals were used to evaluate the effectiveness of the proposed method. The results show that the proposed method can detect early defects of bearings and is superior to other Kurtogram-based approaches.
Stability Analysis of SAPF by Viewing DFT as Cluster of BPF for Selective Harmonic Suppression and Resonance Damping

This paper addresses the stability analysis of a shunt active power filter (SAPF) with capacitive load for selective harmonic suppression and resonance damping. If the capacitive load current is measured as part of harmonic suppression current reference, the SAPF with conventional selective harmonic suppression would amplify the corresponding harmonic beyond the resonance frequency. Previous studies could not clearly explain this harmonic amplification phenomenon without the selective harmonic extraction model in stability analysis. By viewing the discrete Fourier transform (DFT) as a cluster of band-pass filter (BPF), the modeling process is taken into consideration and is well simplified. The stability condition for suppressing and damping each selected harmonic can be easily estimated with the help of Nyquist stability criterion or root locus method in different SAPF control scenarios. To avoid the instability and compensate the harmonic current, a novel combined control strategy of the SAPF is carried out to simultaneously suppress the harmonics whose frequencies are lower than the resonance frequency and mitigate the rest of the harmonics by a resonance damping method. Experiments have been performed to verify the effectiveness of the proposed strategy.
An Empirical Evaluation of Ten Depth Cameras: Bias, Precision, Lateral Noise, Different Lighting Conditions and Materials, and Multiple Sensor Setups in Indoor Environments

Over the last few years, novel color and depth sensors have pushed the boundaries of robot perception significantly. Today, several new depth-sensing products are replacing the earlier, wellexamined red-green-blue-depth (RGBD) sensors, which have reached the end of their product life cycle and are no longer available. The properties of the new sensors have not yet been investigated, and it is unclear how they will compare to earlier RGBD sensors.
Height Adjustment of 3-D Axisymmetric Microumbrella Shells for Tailoring Wineglass Frequency

This paper proposes to adjust shell heights of slim-stemmed microumbrella shells by a low-cost foaming process for regulating wineglass frequency. Titanium hydride (TiH2) is used as the foaming agents. They are sealed in the cavities of the bonded glass and silicon wafers and release H2 to drive the softened wafer glass into axisymmetric microumbrella shells at high temperatures. An analytical model coupled with a finite-element model is built to relate the mass of foaming agents to shell height. Results show that the difference between the analytical model and the finite-element model for the mass of foaming agents of shaping a hemispherical umbrella shell is within 15%. The finite-element model for the shell height exhibits <12% errors with the foaming experiments. The $n = 2$ wineglass frequency of glass umbrella shells with different aspect ratios (shell height/shell radius) is predicted to be from 10 to 50 kHz, demonstrating nonnegligible impact of shell heights on the frequencies. Experiment results indicate that changing aspect ratios of the umbrella shells by the foaming process is an effective way to obtain the desirable working frequency. With a combination of selecting thicknesses of the micromachined glass layer and changing shell heights, this foaming process can achieve a broader spectrum of resonant frequencies, which makes the axisymmetric umbrella shells suitable for a wide range of vibration applications.
Robust Global Structure From Motion Pipeline With Parallax on Manifold Bundle Adjustment and Initialization

In this letter, we present a novel global structure from motion (SfM) pipeline that is particularly effective in dealing with low-parallax scenes and camera motion collinear with the features that represent the environment structure. It is therefore particularly suitable in Urban SLAM, in which frequent road-facing motion poses many challenges to conventional SLAM algorithms. Our pipeline includes a recently explored bundle adjustment (BA) method that exploits a feature parameterization using Parallax angle between on-Manifold observation rays (PMBA). It is demonstrated that this BA stage has a consistently stable optimization configuration for features with any parallax and therefore low-parallax features can stay in reconstruction without pre-filtering. To allow practical usage of PMBA, we provide a compatible initialization stage in the SfM to initialize all camera poses simultaneously, exhibiting friendliness to collinear motion. This is achieved by simplifying PMBA into a hybrid graph problem of high connectivity yet small node set size, solved using a robust linear programming technique. Using simulations and a series of publicly available real datasets including “KITTI” and “Bundle Adjustment in the Large,” we demonstrate the robustness of the position initialization stage in handling collinear motion and outlier matches, superior convergence performance of the BA stage in the presence of low-parallax features, and effectiveness of our pipeline to handle many sequential or out-of-order urban scenes.
Pedestrian Detection Based on YOLO-D Network

In view of the poor robustness of pedestrian detector based on artificial extraction feature, a novel pedestrian detection method is proposed by referring to the research results of state-of-the-art object detection. Based on the YOLOv2 network and inspired by the DenseNet, we pass the low-level feature maps of YOLOv2 to the higher layers in turn. By combining the feature maps of different convolutional layers, we propose a novel network architecture, namely YOLO-D network, to make detector performance better. In order to solve the occlusion problem, we introduced a Head-Shoulders model and also reduced computer calculations. The experimental results show that compared with the original YOLOv2 network pedestrian detection method, this paper reduces the missed rate and false rate, improves the localization precision, and the detection speed meets the real-time requirements.
A Hazard Analysis Method for Software-Controlled Systems Based on System-Theoretic Accident Modeling and Process

Hazard analysis is critical for safety assurance of smart systems which is usually controlled by software. As a novel causality model, Systems-Theoretic Accident Modeling and Processes (STAMP) has been used in various areas to obtain more causal factors during hazard analysis. However, the application of STAMP thus far is ad-hoc with no rigorous procedure to analyze the system hazards effectively, and the quality of the analysis results can't be guaranteed. Furthermore, the temporal factor as an important cause of hazards has been paid little attention in STAMP based analysis. With the purpose of overcoming these limitations, this paper presents a systematic method for hazard analysis based on STAMP. And the Hazardous Control Action Tree (HCAT) is proposed to model and analyze all the situations should be considered for hazard analysis. Also, several rules are given to guide the hazard analysis of temporal conditions in the control processes. Finally, a case study is used to illustrate the feasibility and availability of proposed method.
Real-Time Optimized N-Gram for Mobile Devices

With the increasing number of mobile devices, there has been continuous research on generating optimized Language Models (LMs) for soft keyboard. In spite of advances in this domain, building a single LM for low-end feature phones as well as high-end smartphones is still a pressing need. Hence, we propose a novel technique, Optimized N-gram (Op-Ngram), an end-to-end N-gram pipeline that utilises mobile resources efficiently for faster Word Completion (WC) and Next Word Prediction (NWP). Op-Ngram applies Stupid Backoff [1] and pruning strategies to generate a light-weight model. The LM loading time on mobile is linear with respect to model size. We observed that Op-Ngram gives 37% improvement in Language Model (LM)-ROM size, 76% in LM-RAM size, 88% in loading time and 89% in average suggestion time as compared to Sorted array variant of BerkeleyLM[2]. Moreover, our method shows significant performance improvement over KenLM[3] as well.
An Optical Flow based Tunnel Navigation Algorithm for a Flying Robot*

In this paper, we propose an optical flow based tunnel navigation algorithm. In the proposed algorithm, we consider an under-actuated non-holonomic flying robot equipped with a visual camera. The main idea of this algorithm is to use the changes of the optical flow field over time to estimate the deviation of the robot's heading from the tunnel axis. The main advantage of the proposed method is that the sensor we considered is only a visual camera, which is more economical and easier to apply in flying robots. The presented computer simulation confirms the performance of the proposed algorithm.
Air Quality Monitoring Platform with the Integration of Dual Sensor Redundancy Mechanism through Internet of Things

Air Pollution is an environmental and a social problem which has harmful effects on ecosystems, climate, life expectancy and quality of life. It is counted in the largest environmental health hazards in the Philippines especially in the nation’s urban areas. This study developed a platform that can monitor air quality in the Philippines wherein the environmental parameters being monitored are ambient temperature, humidity, particulate matter and carbon monoxide concentration levels. This study applies Dual Sensor Redundancy Mechanism to examine the validity of the sensor readings. Using Wi-Fi technology, the data obtained from the microcomputer is sent to the Cloud based Web Server. The output of the system which involves sensor readings and Graphical Representation with respect to time is displayed on the mobile application. After validating the prototypes, the percent difference obtained fall under 5% mark and by conducting Two-tailed T-test, it is determined that the prototypes are functioning correctly. The platform is also implemented in two remote areas and environmental conditions are compared using the data obtained during the monitoring process.
Graph-Based Semantic Learning, Representation and Growth from Text: A Systematic Review

TheVector Space Model (VSM), is the main technique to model the semantics from the text. However, the VSM model suffers from notable limitations. The main alternative model for VSM model is a graph-based model. This paper presents a systematic review on the graph-based processes of Semantic Learning, Representing and Growth (SLRG) from the text. Then it describes a new branch in graph-based SLRG modeling, inspired from the cognitive-semantics.