Miracle-dz/UniFAR-FTUs huggingface dataset:
A Framework for Transferring Surface Finishing Skills to New Surface Geometries

This paper presents a framework for transferring surface finishing skills to new surface geometries while preserving the surface finish quality. The main idea is to estimate the contact area between the workpiece and the tool by using 3D point cloud approach and replicate a given material removal rate and the accumulated material removal, as these quantities are the main parameters for quality. The grinding motion trajectory is generated by solving a constrained optimization problem that minimizes the maximal point-wise deviation between actual and desired material removal and simultaneously minimizes the average deviation between actual and desired material removal rate. The proposed approach is verified in simulation to show the difference between direct replication of force/motion and the proposed replication of material removal. Finally, experimental results confirm that the quality of a surface finishing task can be transferred to new surface geometries with the proposed method.
From ink bottles to e-beams: a historical perspective on diffractive optic technology

The history of diffractive optic technology is traced from the first hand-drawn computer-generated holograms created by Adolf Lohmann and Byron Brown to elements fabricated using electron beams that are smaller than a human hair. The influence of Adolf Lohmann on the field is recounted, as are the major developments in fabrication and computation. In particular we highlight the influence of technology on design techniques showing how the availability of computer plotters in the 1960s lead to early encoding techniques. The transition in the 1970s to photolithographic fabrication changed the nature of diffractive design from cell-oriented to point-oriented encoding. At the same time optimization routines were developed that incorporated these new fabrication constraints. The introduction of electron beam writing in the fabrication of diffractive optics in the 1980s brought diffractive design in the 1990s full circle to techniques that are again cell-oriented. Shrinking-features have also changed the applications for diffractive elements. First used primarily as filters for optical correlators, diffractive elements will play a critical role in telecommunications systems that are nearing deployment. However, the most visible impact of Adolf Lohmann's contributions are pattern generators sold with laser pointers. This history is dedicated to Adolf Lohmann on the occassion of his seventy-fifth birthday.
A novel adaptive bimorph focusing mirror and wavefront corrector with sub-nanometre dynamical figure control

We present the design, fabrication and characterization of a novel adaptive X-ray optic by bringing together bimorph adaptive technology and the novel Elastic Emission Machining "super-polishing" technique. This super-polished adaptive mirror provides variable focal distance and local figure control in the sub-nm range. The optic has the potential to generate distortion-free beams, and enable wavefront control.
Trajectory optimization using dynamic programming and Q-learning

This paper presents route optimization in Markov Decision Process (MDP) environment using dynamic programming (DP) and Q-learning, and compares features of two algorithms. Since DP uses recursive function, coding is simple and easy to implement. However, all cases should be calculated to implement DP. Due to this characteristic, the unnecessary calculation rate increases as the model grows for implementation of DP. In this paper, learning is applied to DP for reduction of calculation complexity. Same MDP problem is solved by DP and Q-learning and results of each case are compared and analyzed in this paper.
An Ensemble Learning to Predict Glucose Level of Patient by Urine Sample

All areas of our lives are evolving and growing with machine learning (ML) including the healthcare system. In healthcare systems, diabetes is one of the extremely deadly diseases that could cause patients multiple organ failures, if we cannot take significant action on time. In this paper, we are using the ensemble learning technique of ML with stacking to predict the glucose(mg/dL) level of diabetic patients by using a urine dataset. For the experimental evaluation we utilized Support Vector Regressor (SVR), Decision Tree Regressor (DT), KNeighbors Regressor (KN) models, and evaluation metrics like Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Average Precision (MAP) is used to evaluate the outcomes. Throughout the assessment, it is assessed that the Ensemble model predicts the glucose level (mg/dL) with the lowest 0.09 RMSE, 0.22 MSE, and 3.1 MAP.
A Survey on Emerging Technologies in Wireless Body Area Network

The Wireless Body Area Networks plays an important aspect in daily life, improves the intelligence and capabilities of healthcare domain. It senses for a particular person by continuous health monitoring in any health issues without any constraints. In this paper, we discuss about the benefits and challenges of Wireless Body Area Network (WBAN) integrated with many emerging technologies based on parameters such as energy consumption, low latency, high throughput and Hardware connectivity, as well as we examine recent advancements in medical sensors in the healthcare system. Compare to all other technologies and considering the feature of medical domain is a really difficult task for increasing sensor technology capabilities. The most common features encompass technologies for edge, fog, mobile cloud computing (MCC) and cloud computing are emphasized when utilized in WBANs. Finally, a comparison among each technique is observed to make the most of medical sensor technology potential and advantages.
The Radiative Effects of Martian Water Ice Clouds on the Local Atmospheric Temperature Profile

Abstract Mars Pathfinder made numerous discoveries, one of which was a deep temperature inversion that extended from about 15 km down to 8 km above the surface. It has been suggested by Haberle et al. (1999. J. Geophys. Res.104, 8957–8974.) that radiative cooling by a water ice cloud may generate such an inversion. Clouds can strongly affect the local air temperature due to their ability to radiate efficiently in the infrared and due to the low air mass of the martian atmosphere, which allows the temperature to change during the relatively short lifetime of a cloud. We utilize a time-dependent microphysical aerosol model coupled to a radiative–convective model to explore the effects water ice clouds have on the local martian temperature profile. We constrain the dust and water vapor abundance using data from the Viking Missions and Mars Pathfinder. Water ice clouds with visible optical depths of τ≥0.1 form readily in these simulations. These clouds alter the local air temperature directly, through infrared cooling, and indirectly, by redistributing atmospheric dust. With this model we are able to reproduce the temperature inversions observed by Mars Pathfinder and Mars Global Surveyor.
Efficient Terahertz Parametric Source Using Flat Pump Beam

A flat pump beam was used to improve efficiency and miniaturize an injection-seeded terahertz-wave parametric generator (is-TPG). The improved power density of the pump beam and interaction length of the terahertz-wave reduced the required pump beam energy by > 85% compared with the conventional system. The reduced generation threshold made it possible to construct is-TPG spectroscopic systems with pump beams of ≤ 3 mJ.
Biomechanical Design Optimization of Passive Exoskeletons through Surrogate Modeling on Industrial Activity Data

Passive exoskeletons are unpowered wearable robotic devices aimed at providing biomechanical assistance. They can be applied in industries such as manufacturing, construction and logistics to reduce repetitive stress injuries among workers. Their design process typically considers a static user, with muscle outputs computed later during dynamic tasks to evaluate performance. Attempting to reduce human muscle effort at this stage requires manual redesign. Instead, we propose a parameter optimization approach that minimizes muscle effort rates during realistic dynamic tasks in the design stage itself. We extract human kinematics in assembly tasks from an industry-oriented motion capture dataset, and compute the induced joint torques. Using a passive exoskeleton for shoulder joint gravity compensation from the literature as a baseline, we optimize its design parameters through a multi-objective Pareto Local Search, minimizing the muscle effort rates during these tasks. As the estimation of muscle outputs through biomechanical simulation techniques is computation-ally expensive, we train ensemble regression models for each muscle of interest during the task motions. These models serve as surrogates for the objective function in the design optimization procedure, speeding up search in the parameter space. The resulting exoskeleton with optimized design param-eters reduces estimated muscle effort rates by an average of 5.73% and peak of 35.1 % compared to default parameters, and an average of 14.5% and peak of 32.2% compared to not wearing an exoskeleton in overhead assembly tasks. A larger peak reduction compared to default parameters may be due to hindrance in motion caused by device. This approach may be adapted to other exoskeletons and applications, improving biomechanical assistance by design.
Effects of buoyancy on turbulent premixed V-flames by large-eddy simulation

Buoyancy effects on turbulent premixed V-flames are investigated under normal gravity (+g) and reversed gravity (–g). Numerical simulations employ large eddy simulation (LES) with a dynamic model for sub-grid scale stress. With the assumption of fast chemistry combustion, a progress variable c-equation is applied to describe the flame front propagation. The equations are solved using a projection-based fractional step method in two dimensions for low-Mach number flows. Computed LES results of buoyancy effects on flame angle and flame brush thickness are consistent with those obtained from experiments. In both +g and –g conditions, the effects of buoyancy become important with increase in Richardson number (Ri). Buoyancy force tends to close up the flame under +g, but has the opposite effect under –g. Buoyancy force also suppresses flame wrinkling in +g and enhances wrinkling in –g. While there is a lack of experimental data available, computed axial velocity is shown to be significantly affected by buoyancy downstream from the flame holder under moderate Reynolds number.
RECCraft System: Towards Reliable and Efficient Collective Robotic Construction

This research presents a novel Collective Robotic Construction (CRC) system named RECCraft. The RECCraft hardware system is composed of the mobile manipulation vehicles, the cubic blocks, and the folding ramp blocks. Solid connection and easy removal of the blocks are achieved by an electropermanent magnet and silicon steel sheets. With one degree of freedom (DOF) lifting manipulator, the robot can carry a block 3.7 times its volume. An active folding ramp block can provide a robust passage to the upper level for the robot. Our study focuses on systemic improvement of the construction speed and reliability of the robotic construction system. Visual perception system realized by Apritag is adopted, featured by convenient deployment and high precision, to provide a reliable guarantee for robotic construction. RL-based planner provides end-to-end solution for planning tasks of building multi-layer constructions, which is validated by simulation platform and real prototype. Compared with construction speed of existing robotic construction systems, our proposed RECCraft system achieves state-of-the-art level. The robot builds a 2-layer construction by RL-based planner in 4 minutes and 16 seconds, which achieves construction volumetric throughput of 6.7×105 mm3/s.
Three-dimensional compositional analysis of quantum dots

A simulation program has been set up, which calculates the x-ray profiles of x-ray line scans taken across features of arbitrary structural and compositional geometries embedded in a matrix. The simulated scan intensities are compared to experimental scan intensities, obtained in an analytical scanning transmission electron microscope. The program is applied to calculate x-ray profiles of InAs quantum dots embedded in GaAs and to SiGe quantum dots embedded in Si in a thin foil in cross-sectional [011] projection. With the help of simulations of the indium L line scan intensities for the case of the InAs dots it is demonstrated how sensitively the x-ray profiles depend on the position of the dot in the thin foil. For the case of the SiGe dots, a full quantitative composition analysis is carried out by adjusting the model geometry and model composition distribution until the best match with the experimental germanium K line scan intensity profile is achieved.
Curve Path Tracking Method of Independent Two In-Wheel Motor Driven Vehicle

This paper presents a novel curved path tracking method for the independent two in-wheel BLDC motor-driven surveillance vehicles. In the autonomous self-driving vehicle type robot, the absolute position and the relative position of the vehicle may be estimated by a GPS (Geometric Positioning System), which is a pre-fixed absolute position, and an installed position sensor. However, GPS cannot be used indoors, and when a location sensor is used, additional costs are incurred and the complexity of system increases. If these sensors are not used, the position of the vehicle depends on the distance traveled by the rotation of the motor. However, the estimated vehicle position based on the integrated motor position is not same as the actual position due to the irregularities of the driving path and the slipping of the wheels. Accordingly, a serious error occurs in the stop position of the vehicle after tracking the curved path in the target position according to the driving path condition. In order to solve this problem, a real-time position error correction method using a direction angle error estimated based on a simple IMU (Inertial Measurement Unit) is introduced. The proposed method calculates the required real-time azimuth of the vehicle on a predetermined driving path. Then, the real-time position error during the driving route can be compensated for as a directional angle error between the required directional angle and the directional angle estimated by the IMU sensor. The performance of the proposed method was verified through experiments.
Deep Reinforcement Learning Algorithms for Machine-to-Machine Communications: A Review

Automated data transfer and measurement between multiple devices are accomplished through Machine- to-machine (M2M) communications, which rely on zero or minimal human intervention. M2M communication offers a plethora of benefits and opportunities, including the ability to handle a wide range of data and large volumes, the ability to learn on their own, and better decision making. In spite of these advantages, M2M faces major challenges such as communication delay, data acquisition mismatching, the requirement of additional resources, and is highly susceptible to errors. To handle these challenges, in this work, we discuss various state-of-the-art deep reinforcement learning (DRL) algorithms. Deep Q-learning (DQN), dueling DQN, multi-step DQN, actor-critic (AC), advantage AC, REINFORCE, trustregion policy optimization (TRPO), and proximal policy optimization (PPO) algorithms are investigated.
Optimisation and fabrication of grating beamsplitters

Optimisation of certain holographic 1 to N and 1 to N*N beamsplitters (Dammann gratings) with the aid of simulated annealing and damped least-squares algorithms is considered. Structures with N=5 to 53 uniform beams have been calculated. A photolithographic technique for fabrication of these elements is also presented, and its accuracy analysed with the aid of numerical simulations and actual test results.
Displacement measurement of large structures using nonoverlapping field of view multi‐camera systems under six degrees of freedom ego‐motion

In this work, a non‐overlapping field of view (FOV) multi‐camera system (MCS) has been proposed to realize the motion self‐compensation, which can be flexibly arranged according to the field situation. The challenges of ensuring a complete fixed measurement platform owing to the self‐weight, unexpected collisions, and adjacent engineering constructions have been addressed in this study. MCS can be fixed on an unstable platform and employ two or more correcting cameras, without an overlapping FOV, to measure and compensate the six degrees of freedom (6‐DOF) ego‐motion of the platform, with high accuracy. The numerical simulation results show that, under the same configuration conditions, the 6‐DOF motion estimation accuracy of the proposed method is better than that of the Perspective‐n‐Points methods, especially for the estimation accuracy of the out‐of‐plane motion and the roll motion of the camera. The field demonstration has been performed on a suspension bridge, and the results demonstrate that the deflection measurements provided by the proposed MCS are consistent with those provided by the Robotic Total Station. The proposed MCS, which is not restrained by a strictly stable platform, proves to be an effective method to compensate for the errors induced by the platform ego‐motion, and it can meet the requirements of the displacement measurement of large structures needing high precision.
Ultrasensitive quartz crystal microbalance with porous gold electrodes

The quartz crystal microbalance is a sensitive thickness monitor used in a variety of technological applications. It is also a versatile research tool for chemical sensor, nanotribology, wetting transition, and superfluid transition studies. By replacing the conventional gold electrodes with porous gold electrodes, the effective adsorbing surface area and hence sensitivity was enhanced by a factor of 40 with no sacrifice of the mechanical quality factor or the stability in the resonant frequency.
Prognostic value of post thaw semen quality parameters, mitochondrial integrity and cholesterol content of sperm membrane vis-à-vis conception rate in Frieswal bulls

The present study aimed to analyze the quantitative relationship of membrane cholesterol content (Chol content), mitochondrial integrity (Δψm), and quality parameters of spermatozoa (SQP) at post-thaw stage with conception rate (CR) and estimated relative conception rate (ERCR) in Frieswal bulls. For the experiment, frozen semen straws (32) were collected from the SF laboratory and CR (Total insemination 3482) was obtained from Field Progeny Testing units. Based on the CR, bulls were grouped into low, medium or high groups (G I, G II and G III, respectively). SQP, viz. viability (Eosin Nigrosin), post thaw motility, biochemical integrity of the membrane (HOS res), acrosome integrity (Giemsa, and fluorochromes fluorescein isothiocyanate Pisum sativum agglutinin and propidium iodide, respectively), chol-content, and Δψm using fluorescent probe JC-1 (5,5’,6,6’-tetrachloro- 1,1’,3,3’-tetraethylbenzimi-dazolylcarbocyanine iodide) were determined. The values thus obtained were subjected to the stepwise regression analysis using the least squares principles for each group, and the CR and ERCR were regressed on the various SQP. Pearson’s correlation coefficients were estimated between the CR and ERCR values and the various SQPs. The coefficient of determination (R2) moderately higher for all the models and ranged from 63.70–93.40% (high and medium group, respectively). High R2 value of the prediction equation for the herd and bulls with medium CR (75.9 and 93.4%, respectively) reveal their suitability to predict the CR and ERCR potential of the cryopreserved semen. Study results point to inclusion of cholesterol content and Δψm estimation in routine semen analysis before long-term storage or usage for insemination purposes.
Osteochondral regenerative engineering: challenges, state-of-the-art and translational perspectives

Abstract Despite quantum leaps, the biomimetic regeneration of cartilage and osteochondral regeneration remains a major challenge, owing to the complex and hierarchical nature of compositional, structural and functional properties. In this review, an account of the prevailing challenges in biomimicking the gradients in porous microstructure, cells and extracellular matrix (ECM) orientation is presented. Further, the spatial arrangement of the cues in inducing vascularization in the subchondral bone region while maintaining the avascular nature of the adjacent cartilage layer is highlighted. With rapid advancement in biomaterials science, biofabrication tools and strategies, the state-of-the-art in osteochondral regeneration since the last decade has expansively elaborated. This includes conventional and additive manufacturing of synthetic/natural/ECM-based biomaterials, tissue-specific/mesenchymal/progenitor cells, growth factors and/or signaling biomolecules. Beyond the laboratory-based research and development, the underlying challenges in translational research are also provided in a dedicated section. A new generation of biomaterial-based acellular scaffold systems with uncompromised biocompatibility and osteochondral regenerative capability is necessary to bridge the clinical demand and commercial supply. Encompassing the basic elements of osteochondral research, this review is believed to serve as a standalone guide for early career researchers, in expanding the research horizon to improve the quality of life of osteoarthritic patients affordably.
Multi-Phase Multi-Modal Haptic Teleoperation

Virtual Fixtures facilitate teleoperation, for in-stance by guiding the human operator. Developing these Virtual Fixtures in tasks with tight tolerances remains challenging. Fixtures with a high stiffness allow for more precise guidance, whereas a lower stiffness is required to allow for corrections. We observed that many assembly operations can be split into different phases - approaching, positioning, in-contact manipulation - each with different accuracy requirements. Therefore, we propose to use multi-modal fixtures, satisfying the different requirements of these phases: i.e. a position-based Trajectory Fixture for approaching and a more accurate Visual Servoing Fixture for the positioning phase. A state estimation and arbitration component ensures smooth transitions between the fixtures to provide optimal support for the operator and to achieve global availability paired with local precision at the same time. It also allows a high stiffness to be used throughout, thus achieving good guidance for all phases. The approach is validated in an application from a space scenario, consisting of the assembly of a CubeSat subsystem. The empirical results from a pilot study on this task show that our approach is faster and requires less interaction force from the operator than the baseline method.
Exploring Factors That Customers' Concerns When Using the E-commerce Platform in Thailand

Thailand has one of Asia's fastest-growing economies, but many people are still unfamiliar with E-Commerce. because of the covid-19 pandemic, which forces many customers to use E-Commerce platforms. The purpose of this study is to look into the factors that influence a company's decision to adopt online shopping in Thailand. The goal of this study is to look into the factors that influence customers' concerns when using an E-Commerce platform in Thailand, as well as the types of customers who use online platforms during the COVID-19 pandemic. EFA used data collection and process interviews as qualitative and data analysis techniques in this study. The sample for this study was derived from a survey of customers who use E-Commerce platforms. The result showed 5 groups of component factors, consisting of 1. Customer trust and Transportation, 2. Product review and quality, 3. Promotion, 4. Commercial images and Financial, and 5 Advertising media.