Miracle-dz/UniFAR-FTUs huggingface dataset:
Systematic estimation of disassembly difficulties: application to computer monitors

The paper describes a disassembly evaluation scheme that translates form properties of a design into quantitative scores and provides a means of identifying weaknesses in the design and comparing alternatives. The methodology centers around a spreadsheet-like chart where disassembly data is recorded and used for redesign. The disassembly evaluation chart consists of two major components: first, an informative section describes the operations, tools, directions, and other factual information; and second, subjective estimations are given of the degree of difficulty associated with each part-removal operation. The chart is explained and its application to disassembly of computer monitors demonstrated. The evaluation results are discussed and future research directions outlined.
Charge-pump circuits: power-consumption optimization

In this paper, an optimized strategy for designing charge pumps with minimum power consumption is presented. The approach allows designers to define the number of stages that, for a given input, and an output voltage, maximize power efficiency. Capacitor value is then set to provide the current capability required. This approach was analytically developed and validated through simulations and experimental measurements on 0.35-/spl mu/m EEPROM CMOS technology. This approach was then compared with one which minimized the silicon area and it was shown that only a small increase in area is needed to minimize power consumption.
Applied multifocus 3D microscopy

The depth from focus measurement principle relies on the detection of the optimal focusing distance for measuring the depth map of an object and finding its 3D shape. The principle is most effective at microscopic ranges where it is usually found implemented around a z-controlled microscope and sometimes named multifocus 3D microscopy. As such, the method competes with many other 3D measurement methods showing both advantages and disadvantages. Multifocus 3D microscopy is presented and compared to chromatic aberation, confocal microscopy, white light interferometry. Then, this paper discusses two applications of multifocus 3D microscopy for measuring wood respectively metallic parts in the sub-millimeter range. The first application aims at measuring the topography of wood samples for surface quality control. The wood samples surface topography is evaluated with data obtained from both confocal microscopy and multifocus 3D microscopy. The profiles and a standard roughness factor are compared. The second application concerns the measurement of burrs on metallic parts. Possibilities and limits of multifocus 3D microscopy are presented and discussed.
Micro-Lensed Negative-Curvature Fibre Probe for Raman Spectroscopy

We developed a novel miniature micro-lensed fibre probe for Raman spectroscopy. The fibre probe consists of a single negative-curvature fibre (NCF) and a spliced, cleaved, micro-lensed fibre cap. Using a single NCF, we minimized the Raman background generated from the silica and maintained the diameter of the probe at less than 0.5 mm. In addition, the cap provided fibre closure by blocking the sample from entering the hollow parts of the fibre, enabling the use of the probe in in vivo applications. Moreover, the micro-lensed cap offered an improved collection efficiency (1.5-times increase) compared to a cleaved end-cap. The sensing capabilities of the micro-lensed probe were demonstrated by measuring different concentrations of glucose in aqueous solutions.
Upper Body Posture Recognition Using Inertial Sensors and Recurrent Neural Networks

Inadequate sitting posture can cause imbalanced loading on the spine and result in abnormal spinal pressure, which serves as the main risk factor contributing to irreversible and chronic spinal deformity. Therefore, sitting posture recognition is important for understanding people’s sitting behaviors and for correcting inadequate postures. Recently, wearable devices embedded with microelectromechanical systems (MEMs) sensors, such as inertial measurement units (IMUs), have received increased attention in human activity recognition. In this study, a wearable device embedded with IMUs and a machine learning algorithm were developed to classify seven static sitting postures: upright, slump, lean, right and left bending, and right and left twisting. Four 9-axis IMUs were uniformly distributed between thoracic and lumbar regions (T1-L5) and aligned on a sagittal plane to acquire kinematic information about subjects’ backs during static-dynamic alternating motions. Time-domain features served as inputs to a signal-based classification model that was developed using long short-term memory-based recurrent neural network (LSTM-RNN) architecture, and the model’s classification performance was used to evaluate the relevance between sensor signals and sitting postures. Overall results from performance evaluation tests indicate that this IMU-based measurement and LSTM-RNN structural scheme was appropriate for sitting posture recognition.
From small molecules to polymeric probes: recent advancements of formaldehyde sensors

ABSTRACT Formaldehyde is a well-known industrial material regularly used in fishery, vegetable markets, and fruit shops for maintaining their freshness. But due to its carcinogenic nature and other toxic effects, it is very important to detect it in very low concentrations. In recent years, amine-containing fluorescent probes have gained significant attention for designing formaldehyde sensors. However, the major drawbacks of these small molecular probes are low sensitivity and long exposure time, which limits their real-life applications. In this regard, polymeric probes have gained significant attention to overcome the aforementioned problems. Several polymeric probes have been utilized as a coating material, nanoparticle, quartz crystal microbalance (QCM), etc., for the selective and sensitive detection of formaldehyde. The main objective of this review article is to comprehensively describe the recent advancements in formaldehyde sensors based on small molecules and polymers, and their successful applications in various fields, especially in situ formaldehyde sensing in biological systems.
Extrapolation-based Real-time Phasor Data Compression Considering the Two-way Rotation Characteristics of Synchrophasors

To deal with the time delay caused by data compressions for synchrophasors in phasor measurement units (PMUs), an extrapolation-based real-time phasor data compression (ER-PDC) was proposed in this paper. First, the two-way rotation characteristic of synchrophasors was analyzed to enhance the real-time extrapolation of phasor dynamic tracks. Then, the algorithm of phasor data compression and reconstruction was proposed with an accuracy criterion measured by the total vector error (TVE) of phasors. The actual PMU data measured in a low-frequency oscillation incident were used to verify the compression performance of ERPDC, and ERPDC was compared with a phasor swing door trending (PSDT) data compression technique. Enhanced by the extrapolation of the synchrophasor dynamic tracks, the comparative result demonstrates that ERPDC can achieve the real-time data compression with zero delay at the expense of slightly decreased compression ratios.
Lean Six Sigma, creativity, and innovation

Purpose – Creativity and innovation have recently emerged as the latest focus of the popular business media, replacing established approaches, such as Lean Six Sigma (LSS). Some have gone so far as to suggest that LSS inhibits organizations from being creative and innovating. This paper aims to dig beneath the surface of the media reports to examine what creativity and innovation actually are, and how they relate to LSS.Design/methodology/approach – The paper reviews current literature on creativity and innovation, and based on extensive experience implementing LSS, compare and contrast the approaches, searching for common ground.Findings – Not surprisingly, the paper finds that the terms creativity and innovation are typically not well defined in the media, and are used more as “buzzwords. ” In reality, it argues, LSS clearly stimulates creativity. However, it is not the best method for identifying ideas for breakthrough innovation. Therefore, to have a holistic improvement system, organizations must comb.
Are Drug-Free School Zones Effective? Evidence From Matching Schools and School-like Entities

Using a combination of spatial and statistical analysis, this paper focuses on analyzing the effectiveness of drug-free school zones (DFSZ) around K-12 schools in Los Angeles County. A propensity score matching model is employed to match schools and school-like entities to compare the amount of drug crimes in two distinct 1000-foot buffers surrounding them. The model is then compared to a coarsened exact matching model. The average treatment effects (ATE) and average treatment effects on the treated (ATT) are estimated. Our results indicate that there are 2.7 and 1.7 fewer drug crimes and non–marijuana-related drug crimes respectively near schools, as a result of the policy. The total effect of the policy is estimated to reduce drug crime near schools by between 1065 to 1643 fewer incidences per year. Furthermore, we find no significant differences in gang-related drug crimes, gang-related violent crimes, or property crimes as a result of the policy.
Blockchain‐enabled secure communication mechanism for IoT‐driven personal health records

The information system of healthcare operates through various frameworks, like wireless body area network, telecare medical information system, and mobile or electronic healthcare. All these systems need to maintain the personal health records (PHRs) for various users (ie, patients, doctors, and nurses). In such systems, we need to process and store the health related sensitive data (ie, PHRs). In this article, we aim to provide a robust security mechanism to secure exchange and storage of healthcare data, especially PHRs. We present a generic architecture of blockchain‐enabled secure communication mechanism for Internet of Things‐driven personal health records (BIPHRS). We then discuss various threats and security attacks of healthcare system along with different available security mechanisms. The conducted security analysis and detailed comparative study of the state of art blockchain enabled security schemes for PHR systems show that the proposed BIPHRS provides a better security and more functionality features as compared to other similar existing approaches.
A Deep Autoencoder-Based Convolution Neural Network Framework for Bearing Fault Classification in Induction Motors

Fault diagnosis and classification for machines are integral to condition monitoring in the industrial sector. However, in recent times, as sensor technology and artificial intelligence have developed, data-driven fault diagnosis and classification have been more widely investigated. The data-driven approach requires good-quality features to attain good fault classification accuracy, yet domain expertise and a fair amount of labeled data are important for better features. This paper proposes a deep auto-encoder (DAE) and convolutional neural network (CNN)-based bearing fault classification model using motor current signals of an induction motor (IM). Motor current signals can be easily and non-invasively collected from the motor. However, the current signal collected from industrial sources is highly contaminated with noise; feature calculation thus becomes very challenging. The DAE is utilized for estimating the nonlinear function of the system with the normal state data, and later, the residual signal is obtained. The subsequent CNN model then successfully classified the types of faults from the residual signals. Our proposed semi-supervised approach achieved very high classification accuracy (more than 99%). The inclusion of DAE was found to not only improve the accuracy significantly but also to be potentially useful when the amount of labeled data is small. The experimental outcomes are compared with some existing works on the same dataset, and the performance of this proposed combined approach is found to be comparable with them. In terms of the classification accuracy and other evaluation parameters, the overall method can be considered as an effective approach for bearing fault classification using the motor current signal.
When are transmission-line effects important for on-chip interconnections

Short, medium and long on-chip interconnections having line widths of 0.45-52 /spl mu/m are analyzed in a five-metal-layer structure. We study capacitive coupling for short lines, inductive coupling for medium-length lines, inductance and resistance of the current return path in the power buses and line resistive losses for the global wiring. Design guidelines and technology changes are proposed to achieve minimum delay and contain crosstalk for local and global wiring. Conditional expressions are given to determine when transmission-line effects are important for accurate delay and crosstalk prediction.
A frequency reconfigurable bow‐tie slot antenna with wide bandwidth

In this article a wide bandwidth frequency reconfigurable antenna is presented. The basic geometry of the antenna is a microstrip‐fed bow‐tie slot antenna. This type of antenna allows bandwidth to increase and it is modified to mount switches easily as well as to maintain good impedance matching in all operating bands. Both the simulated and measured results show that the proposed antenna has good frequency reconfigurability with wide bandwidth. © 2007 Wiley Periodicals, Inc. Microwave Opt Technol Lett 50: 404–406, 2008; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/mop.23086
Investigations of Energy Separation Effect in Vortex Tube for Natural Gases

This paper aims to investigate fixed composition natural gases including N2, CH4 and C2H4 energy separation effect in vortex tube. Energy separation phenomena of those gases were investigated by means of three-dimensional Computational Fluid Dynamics (CFD) method. Flow fields of natural gases in fixed inlet boundary conditions were simulated. The results main factors were found that affect the energy separation with cold mass fraction being 0.7 and pressure drop ratio being 3.90. At the same time, this paper has illustrated the effects and tendencies of energy separation with gases in the tube under the same cold mass flow fraction and cold pressure ratio. The results show mixture gases total temperature difference effect is unchanged varied with the cold mass fraction; CH4% has no effect on the vortex cold end temperature separation, but varied of CH4% has an influence in total temperature and hot end separation effect; total temperature separation effect of CH4% was divided into two sections, one is0%-80%, and the other 80%-100%.
Computing the cheapest winning coalition in a multi-agent game

To run a company, employers need to hire people to realize a product, a sport coach can motivate some players intend to win a match, a designer have to force synchronization of some parallel processes to avoid deadlocking. In these examples, a device external to the global system tries to force the behavior of some agents, aiming at achieving a global objective. For realism purposes, we assume that forming a coalition has a cost that should be minimal. This cost models the fact that individuals of the coalition may be deviated from their original objective. Game theory is a vast field that addresses this kind of problem. In this work we focus on turn-based games, a simple and broadly explored branch of game theory. Turn-based games offer well-known tools, among which the most famous minmax algorithm where a constrained optimization problem is addressed [19]. The problem we aim at solving is to find a minimal cost coalition which enforces some position in a given set (the goal) to be eventually reached.
The Australian Feeding Infants and Toddlers Study (OzFITS) 2021: Study Design, Methods and Sample Description

(1) Background: Caregiver feeding practices during the first two years of a child’s life influence nutrition, growth, and development, as well as long term taste preferences and dietary patterns. Suboptimal feeding practices lead to poorer health outcomes, such as obesity, that persist into adulthood. Although the importance of early life nutrition is well-established, there are no Australia-wide surveys of dietary intakes of children under two years of age. The 2021 Australian Feeding Infants and Toddlers Study (OzFITS) aims to fill this gap. This paper describes the methods and study sample of OzFITS 2021. (2) Methods: OzFITS 2021 is a cross-sectional study of children aged 0 to 23.9 months of age and their caregiver across Australia. Data were collected between April 2020 and April 2021. A telephone-based survey was completed with a caregiver to obtain information on child and caregiver characteristics and feeding practices. For exclusively breastfed infants, the number of breastfeeds in a 24 h period was reported. Dietary intakes for mixed fed children were estimated using a one-day food record, with 30% of caregivers completing a second food record on a non-consecutive day. (3) Results: We enrolled 1140 caregiver and child dyads. Of those eligible to complete a food record, 853 (87%) completed the food record. Compared to the Australian population, caregivers were more likely to be university-educated (>75%), married or in a de facto relationship (94%), and have a household income >$100,000/y (60%). (4) Conclusions: OzFITS 2021 is the first national study to examine food and nutrient intake in Australian children aged under 2 years. The study will provide information on breastfeeding rates and duration, use of breast milk substitutes, and timing of solid food introduction. Dietary intake data will allow the comparison of core food groups and discretionary food intake to Australian guidelines and estimate the prevalence of inadequate intake of key nutrients, like iron. Healthcare practitioners and policymakers can use the study findings as a source of evidence to inform the next iteration of infant feeding guidelines.
Air movement in houses: a new approach

Air movement in houses is now recognised as a major factor both in condensation risk and in energy efficiency, yet conventional test methods have limitations. Using a multi-channel gas analyser and computer operation, the BRE Scottish Laboratory has extended conventional techniques of testing and of measurement to give a more realistic assessment of the processes at work, as explained here. Field studies have verified the importance of blocking gaps in the ceiling, for 20-30 per cent of the air entering a house will leave via the roof space through these gaps, which are critical for moisture transfer but less important for heat transfer.
Distributed Optimization for Power Distribution Systems with Cyber-Physical Co-Simulation

In power distribution systems, the limitations of centralized optimal power flow (OPF) methods have led to the distributed computing paradigm. However, the primary shortcoming in the existing distributed OPF techniques is a large number of required communication rounds (in the order of 102 ~ 103), i.e., macro-iterations among the distributed computing agents for solving one instance of the optimization problem, which requires expensive communication infrastructures. In this paper, a novel distributed optimization method for unbalanced power distribution networks is proposed to solve optimal power flow (OPF) that requires fewer macro-iterations. The developed innovations reduce the required number of communication-rounds for convergence by an order of magnitude. The algorithm is based on equivalent network approximation, where the radial topology of the distribution network is leveraged. The approach is validated using IEEE 123-bus test systems with both cyber and physical layers simulated using a co-simulation platform. The robustness of the algorithm is verified for different parameters of the communication network. The solutions from the distributed method were found to converge to the centralized OPF solutions.
Magnetic field-induced currents in the human body in proximity of power lines

Electric currents induced due to 60 Hz magnetic fields in a human body placed in close proximity to various high voltage transmission lines are computed. A realistic model of the human body from the anatomical and electrical point of view with resolution of 1.3 cm for the body and 0.665 cm for the head is used. The computations are performed using the impedance method. Three representative configurations of high voltage transmission lines, namely 500 kV, 138 kV and 25 kV are analyzed. The results indicate that the maximum current densities of the order of 0.2 /spl mu/A/cm/sup 2/ can be induced in a lineman working on a 500 kV line (0.5 m away from closest conductors). A good correlation can be seen between the computed magnetic field in the location of the human body and the induced current densities. The induced currents computed here and estimated from measured magnetic fields in various power line environments are compared to those for typical home and office exposures, including appliances.
Study of the tissue volume for spatial-peak mass-averaged SAR evaluation

For being adaptable to the irregular shape of a biological model and for not underestimating the spatial-peak mass-averaged specific absorption rates (SARs) of hand-held wireless telephones, a method of taking a contiguous tissue volume for the SAR-averaging-mass is proposed. The proposed method is to obtain a tissue volume for SAR averaging by summing node massed of the layers enclosing the point in which the averaged SAR is wanted in a body model until the summed mass is closest to the required mass. Therefore, at the skin layer and in the tissue region around the sinuses such as nasal cavities, the averaging volume can follow closely the shape of the region. To investigate the effect of this algorithm on SAR evaluation, SARs have been evaluated numerically for an anatomical head with a simple hand models exposed to a mobile phone, using the proposed method and the previous method of averaging over a cubic tissue volume and the results are compared. The results show that the proposed algorithm is very reasonable and leads to more stable values for spatial-peak mass-averaged SAR evaluation in an irregularly shaped model such as a realistic human model.
A 3D Sequential LiDAR Data Registration Method for Unmanned Ground Vehicle

This paper proposes a 3D point cloud registration method based on light detection and ranging (LiDAR) system. The proposed method consists of three steps: Gaussian-Process based ground segmentation, a novel k-neighbors based dynamic point feature and Iterative Closest Point (ICP) fine registration. The first two steps are the preparation of ICP fine registration. The odometry information from a GPS/IMU system is used to compensate the vehicle's ego-motion. The Gaussian-Process based ground segmentation is adopted to remove ground points. A novel Initial Localization based Dynamic Feature (ILDF) is proposed to detect and remove dynamic points. It is applicable in sequential frames and a proper initial localization without a large dislocation. In experiment results, a large number of dynamic points will be detected and removed by ILDF. The removal of dynamic points improves both accuracy and efficiency of registration algorithm.