Miracle-dz/UniFAR-FTUs huggingface dataset:
Quality Monitoring and Analysis of Xinjiang ‘Korla’ Fragrant Pear in Cold Chain Logistics and Home Storage with Multi-Sensor Technology

Korla fragrant pear is prestigious for its special texture and unique flavor but suffers storage and supply chain difficulties for its deterioration-prone properties. In order to improve the storage quality of Korla fragrant pears during the whole cold chain from the orchard to the customers, the paper deeply researches multiple influencing factors of cold chain logistics and home storage of Korla fragrant pears with multi-sensor technology (MST), such as the temperature, relative humidity, concentrations of oxygen (O2), carbon dioxide (CO2) and ethylene (C2H4). Cold chain logistics are assessed by sensory evaluation and physiological index measurement, and home storage environments are classified by using back propagation neural network (BPNN) in both refrigerators and ordinary rooms. Experimental results show that the MST-based detectors can improve the accuracy of continuous sensor data acquisition, such that the preservation quality of Korla fragrant pears is effectively enhanced by data analysis on gas contents, firmness, pH, and total soluble solids. These results indicate that Korla fragrant pears stored in refrigerators have a higher acceptance for customers.
A Comprehensive Review of Driver Behavior Analysis Utilizing Smartphones

Human factors are the primary catalyst for traffic accidents. Among different factors, fatigue, distraction, drunkenness, and/or recklessness are the most common types of abnormal driving behavior that leads to an accident. With technological advances, modern smartphones have the capabilities for driving behavior analysis. There has not yet been a comprehensive review on methodologies utilizing only a smartphone for drowsiness detection and abnormal driver behavior detection. In this paper, different methodologies proposed by different authors are discussed. It includes the sensing schemes, detection algorithms, and their corresponding accuracy and limitations. Challenges and possible solutions such as integration of the smartphone behavior classification system with the concept of context-aware, mobile crowdsensing, and active steering control are analyzed. The issue of model training and updating on the smartphone and cloud environment is also included.
Compartmentalization Strategy for the Optimal Economic Operation of a Hybrid AC/DC Microgrid

In this paper, a compartmentalization strategy is proposed for the economic operation of a hybrid AC/DC microgrid. The hybrid AC/DC microgrid will be compartmentalized into several independently controlled and coordinated AC and DC nanogrids. Accordingly, the optimal economic operation of the microgrid consists of two segments, including the optimal power sharing among local DERs in individual nanogrids and the optimal power sharing among interconnected nanogrids. For each AC/DC nanogrid, the optimal power sharing and frequency/voltage restoration are realized simultaneously without the need for any real-time communication. In the compartmentalized microgrid, each nanogrid will communicate with neighboring nanogrids through a sparse communication network to regulate power exchanges among nanogrids. In islanded mode, incremental costs of nanogrids are unified for realizing the optimal economic operation of the microgrid. In grid-connected mode, the external electricity price (i.e., purchase/sale electricity price set by the utility grid) is the desired incremental cost, which would be imposed on some pinned nanogrids and propagated among the remaining nanogrids. Then, the optimal power sharing of nanogrids within the grid-connected microgrid would be modeled as a pinning synchronization problem. The proposed compartmentalization strategy ensures that the optimal economic operation of the hybrid AC/DC microgrid is achieved under both island and grid-connected modes while the utilized communication structure is simplified and the dependency on communication networks is reduced. The performance of the proposed compartmentalization strategy is tested and verified through time-domain simulations in PSCAD/EMTDC for a hybrid AC/DC microgrid located at Illinois Institute of Technology (IIT).
Optimal Rate-Adaptive Data Dissemination in Vehicular Platoons

In intelligent transportation systems, wireless connected vehicles moving in platoons can improve roads’ throughput. For managing driving status of the platoon, a lead vehicle transmits driving information to following autonomous vehicles by using multi-hop data dissemination. We study a novel data dissemination protocol which investigates a chain-based transmit rate control to reduce data dissemination latency. The optimal resource allocation algorithm is formulated to minimize the total dissemination latency of the platoon under guaranteed bit error rates, and can be judiciously reformulated and solved using standard optimization techniques. A novel dynamic programming algorithm is presented to solve the platooning resource allocation optimization, which uses backward induction to significantly reduce the resource allocation complexity. In addition, we interpret the vehicular platoon as one-dimensional Markov chain, and derive a closed form of dissemination latency. Simulations are carried out to evaluate the performance of the proposed dynamic programming algorithm. The numerical results show that our algorithm achieves optimal solutions with cutting off the complexity by orders of magnitude, while improving dissemination rate in the vehicular platoon.
A PZT Actuated 6-DOF Positioning System for Space Optics Alignment

Due to limitations in the fabrication technology, the large aperture space optical mirror is always spliced into several small segments rather than fabricated monolithically. To guarantee the imaging quality of the system, each segment needs to be aligned at micron-level precision with millimeter-level range. For this purpose, a PZT actuated six-axis high-precision positioning system, which consists of three serially connected parallel mechanisms is proposed in this article. Compared with previous 6-DOF positioning solutions, such as a Stewart platform, the proposed design features a relatively compact structure and straightforward kinematics. To realize long stroke and fine resolution simultaneously, bridge-type amplifiers are employed to enhance the stroke of the PZT actuation, and the flexure hinges are utilized to eliminate friction and backlash. The performance of the amplifier under two kinds of external loads are analyzed so that the amplifiers could be designed according to the application conditions. Furthermore, it can be found that the displacement sensors must be employed at the output end of the actuation module to eliminate the input coupling that commonly exists in the compliant mechanisms. The feasibility of the design is validated by finite-element analysis and experiment study. The maximum stroke is 2.1 mm in the Z-axis, and the finest resolution is 0.5 μm in X- and Y-axis.
The optimal control of par-tially observable Markov processes

A fluorescence spectrophotometer having a beam splitter placed between an exit slit of an excitation monochromator and a specimen. Part of the excitation radiation is conducted to a first light quantum meter by said beam splitter and a reference photomultiplier is provided for receiving fluorescence from said first light quantum meter. A second light quantum meter is placed at the position normally occupied by a specimen cell and first and second absorbing cells are disposed in front of said first and second light quantum meters, respectively.
Analysis Of Transformer Insulation Parameters Using Polarization And Depolarization Current Method And Frequency Domain Spectroscopy

Dielectric is an essential indicator for developing the ageing effect of transformer as they change their characteristics due to various stresses on transformer such as mechanical, chemical and electrical. The changes in dielectric property of oil-impregnated paper highly influence the transformer disaster. The basic intent of this paper is to be enlightened about the transformer health by analyzing the parameters of dielectric. This is evaluated by using a time domain test by deriving the polarization and depolarization currents of given dielectric under external field. The frequency domain is used to quantify the dielectric loss factor and complex capacitance, which is helpful to understand the transformer behavior. This paper also supports the comparison the proposed system with existing parameters of other existing system to get the knowledge about system health.
High-resolution signal-in-space measurements of VHF omnidirectional ranges using UAS

Abstract. In this paper, we describe measurement results of the signal-in-space of very high frequency (VHF) omnidirectional range (VOR) facilities. In aviation VOR are used to display the current course of the aircraft in the cockpit. To understand the influence of wind turbines (WT) on the signal integrity of terrestrial navigation and radar signals, the signal content and its changes, respectively, must be investigated. So far, only numerical simulations have been carried out on the frequency-modulation (FM) part of the Doppler-VOR (DVOR) signal to estimate the influence of WT on DVOR. Up to now, the amplitude-modulated (AM) part of the DVOR was not assessed at all. In 2016, we presented an unmanned aerial system (UAS) as a carrier for state-of-the-art radio-frequency (RF) measurement instrumentation (Schrader et al., 2016a, c; Bredemeyer et al., 2016), to measure and to record the true signal-in-space (both FM and AM signal) during the flight. The signal-in-space (which refers to time-resolved signal content and field strength, respectively) is measured and sampled without loss of information and, furthermore, synchronously stored with time stamp and with precise position in space, where the measurements were taken.
Multilevel Voltage-Source Converter Topologies With Internal Parallel Modularity

This article presents a new multilevel converter topology synthesis concept—the internal parallel converter (IPC). In the IPC concept, each phase of an IPC topology consists of one low switching frequency part and several parallel-connected high switching frequency (HSF) modules. Compared to existing topology synthesis principles, the IPC topologies feature the merits such as reduced device current stress, modularity, hybrid utilization of different types of devices, etc. Also, by interleaving the HSF modules, the number of output voltage levels can be increased without complicating the control of the converter. Detailed discussions on the advantages of the IPC concept are presented in this article. Two example topologies are introduced and adopted in simulation and experiment. The results of the interleaving operation show that the number of output voltage levels can be effectively increased, demonstrating the functionalities of the proposed IPC topologies.
Implementation and Evaluation of Maximum Power Point Tracking (MPPT) Based on Adaptive Neuro-Fuzzy Inference System for Photovoltaic PV System

The conversion of energy of sunlight into electricity is done using photovoltaic (PV) cells. This paper introduces, comparing, analyzing and evaluating the performance of the PV systems which are operating with MPPTs that work by adaptive neuro fuzzy interference system (ANFIS) technique with other MPPT algorithms such as Perturb and Observe (P&O) algorithm, Fuzzy Logic Control (FLC) algorithm and Artificial Neural Network (ANN) algorithm. These algorithms work to control the duty cycle (D) of the pulse signal that goes to the switch of the DC-DC converter for maximizing the power generated by the solar panel. The paper also introduces simulating and modeling a general PV panel with some adjustable parameters for modelling any real PV model using its electrical data sheet. In addition, the work tests the model for the influence of changing in operation solar irradiation and operation temperature on I-V and P-V curves. MPPT algorithms are implemented using boost DC-DC converter with constant resistive load. All systems are analyzed and simulated by using MATLAB-Simulink program. Simulation results show that the ANFIS and ANN based MPPT method gives faster response to archive the MPP and is more efficient than FLC MPPT and the P&O MPPT methods .
Design and Analysis of a Novel Two-Degree-of-Freedom Voice Coil Motor

Two-degree-of-freedom (2-DOF) actuators capable of producing linear/swing motion are significant for end-effectors in multidimensional complex motion platforms. This paper proposes a novel 2-DOF voice coil motor (VCM) featuring simple structure, small size, and great force properties. The structure of this novel VCM and the distribution of magnetic field are first described, the modeling of linear-thrust and swing-torque is accomplished, force properties of this 2-DOF VCM and stress analyses of the mover brackets are conducted by finite element method (FEM). Then, a prototype of this 2-DOF VCM was manufactured and tested to validate its theoretical features. In order to indicate the improvements of this proposed VCM, the force features of this motor are contrasted with the ones of a linear-swing VCM we designed previously; the simulation and experimental results of the two VCM are compared. Conclusion is drawn as that the proposed VCM has lower ripple ratios of linear-thrust and swing-torque, meanwhile, higher average values of linear-thrust and swing-torque are achieved. This paper provides a theoretical reference and experimental data of this novel 2-DOF VCM for multidimensional complex motion systems.
An Open-Source Simulator Applied to Prism Coupling Sensors Based on Kretschmann's Configuration

In this letter, we present an open-source simulator applied to design and to analyze prism coupling sensors considering surface plasmon resonance (SPR) effect based on Kretschmann's configuration. The open-source simulator is called Sim-SPR and takes into account principles of software engineering. For comparison purposes and to validate our results, we considered two simulation tools already consolidated in the literature and performed an experimental setup for detecting resonant angle in a prism-based SPR sensor. The sensor design was based on optical prism (BK7 glass) as well as Au thin film. The results show that Sim-SPR provides reflectance curves that present a minimum in the resonance condition, resulting in a good agreement when compared with simulation and experimental data. Sim-SPR provides new insights and it has great promise for possible applications in the field of biosensors.
Sustainability in Architectural Design: Smart Systems and Traditional Materials

When discussing about sustainability in buildings we usually refer to the Brundtland Report, to the energy consumption that has increased dramatically, to the planet’s resources that are decreasing, to the wild life that must be preserved. We take into consideration the environmental – natural and anthropic - agents, resources – human as well as materials – life service of the building etc. Less is discussed about sustainability in architectural design and detailing, although the details are the ones that, beyond paper drawings, keep the building together and ensure the expected service life and the life cycle of the building. “God is in the details”- as Mies van der Rohe stated more than 50 years ago – applies to a less spectacular side of our profession but, nevertheless, the one that contributes significantly to the character of the architectural object (if applied in buildings, of course). This paper refers to sustainable architectural concepts and details and their history.
Systems theory: forgotten legacy and future prospects

Systems theory has long informed theoretical developments in employment relations and HRM. There is a rich and interdisciplinary underpinning to systems logic stretching back to classic research in work and organisations (Burns and Stalker, 1961), Dunlop’s (1958) Industrial Relations Systems, and foundational organisation theory (Katz and Kahn, 1966). Today, systems theory is still frequently theoretically invoked, if less empirically employed. This chapter will present an overview of systems theory and its purpose before tracing its historical antecedents and key domain assumptions. The chapter will then review some valuable applications of system thinking in employment relations and HRM, before evaluating limitations and future prospects. Overall, the chapter surfaces the long standing tensions between the intuitive appeal of systems logic and difficulty surrounding its application. The chapter concludes that, despite these challenges, the changing nature of work as characterized by fragmentation, flexibility, feminisation and finacialization (Rubery, 2015) provide a strong mandate for a system theory renaissance in HRM and employment relations.
Phytochemical Analysis And Antioxidant Activity Of Leaves Extracts Of Endemic Plant Jahe Balikpapan (Etlingera Balikpapanensis A.D. Poulsen)

Jahe Balikpapan (Etlingera balikpapanensis A.D.Poulsen) is an endemic plant which can be found in East Kalimantan, Indonesia and potentially to be used as a medicinal plant. This research was held to screen phytochemicals and antioxidant activity of different extract (ethanol, hexane, and ethyl acetate) of E. balikpapanensis. The phytochemical test was held towards alkaloids, phenolics, flavonoids, tannins, saponin, steroids, and triterpenoid. Total phenolic content (TPC) and total flavonoid content (TFC) were determined spectrophotometrically by using Folin-Ciocalteu’s reagent and aluminum chloride (AlCl3) method, respectively. Antioxidant activity was evaluated by using the 2,2-diphenyl-1-picrylhydrazyl (DPPH) method. The screening of phytochemical revealed the presence of alkaloids, phenolics, flavonoids, and steroids. Ethyl acetate extract showed the highest TPC (109.8 ± 0.011 mg GAE/gr) followed by ethanol extract (57.6 ± 0.004 mg GAE/gr) whereas hexane extract showed the least TPC (29.0 ± 0.009 mg GAE/gr). Hexane extract showed the highest TFC (268.4 ± 0.05 mg CE/gr) followed by ethanol extract (200.4 ± 0.02 mg CE/gr) whereas ethyl acetate extract showed the least TFC (141.8 ± 0.03 mg CE/gr). The highest antioxidant activity was observed in ethyl acetate extract (IC50 = 7.59 g mL -1 ) followed by ethanol extract (IC50 = 74.80 g mL -1 ) and hexane extract (IC50 = 189.89 g mL -1 ). This result exhibited that the leaves extract of E. balikpapanensis is very potential to be used as a medicinal plant and as a natural antioxidant.
Multimode Modulation With ZVS for a Single-Phase Single-Stage Inverter

This article presents a modulation with zero-voltage switching (ZVS) for a single-phase, single-stage inverter intended for photovoltaic applications. In single-stage inverters, the dc-ac conversion stage is merged with the active power pulsation buffer stage. The proposed architecture uses a flying capacitor to handle the difference between the instantaneous input and output power, instead of the traditional bulky input capacitor. In this single-stage inverter, both the input current and the output voltage are controlled by the current of a single inductor. The inductor is operated in variable frequency boundary conduction mode. Multiple operation modes are used along the line cycle, all of them with ZVS in all transitions. The operation mode and control times are determined by the target input current, target inductor current, input voltage, output voltage, and flying capacitor voltage through equations that model the inductor waveform. These equations are solved with a fixed-point iteration method in a field-programmable gate array (FPGA). The modulation and control are validated in a 1 kVA prototype with 400 V input and 240 Vrms, 60 Hz output.
Target detection with deep learning in polarimetric imaging

Polarimetric imaging techniques demonstrate enhanced capabilities in advanced object detection tasks with their capability to discriminate man-made objects from natural background surfaces. While spectral signatures carry information only about material properties, the polarization state of an optical field contains information related to surface features of objects, such as, shape and roughness. With these additional benefits, polarimetric imaging reveal physical properties operable for advanced object detection tasks which are not possible to acquire by using conventional imaging. In this work, the primary objective is to utilize the state-of-the-art deep learning models designed for object detection tasks using images obtained by polarimetric systems. In order to train deep learning models, it is necessary to have a sufficiently large dataset consisting of polarimetric images with various classes of objects in them. We started by constructing such dataset with adequate number of visual and infrared (SWIR) polarimetric images obtained using polarimetric imaging systems and masking relevant parts for object detection models. We managed to achieve a high performance score while detecting vehicles with metallic surfaces using polarimetric imaging. Even with limited number of training samples, polarimetric imaging demonstrated superior performance comparing to models trained using conventional imaging techniques. We observed that using models trained with both polarimetric and conventional imaging techniques in parallel gives the best performance score since these models were able to compensate for each other's lacking points. In the subsequent stages, we plan to expand the study to the application of spiking neural network (SNN) architectures for implementing the detection/classification tasks.
Analysis of White Blood Cell Segmentation Techniques and Classification Using Deep Convolutional Neural Network for Leukemia Detection

Leukemia is a blood cancer which results due to inundation of abnormal white blood cells in human. Digital pathology is a dynamic condition that empowers extraction of precise and detailed information of amount and condition of WBCs from patient’s blood smear. Digital pathology methods along with machine learning is gaining importance speedily as a proven and essential technology for investigation of new features of leukemia patients histological information, providing the reduced laboratory expenses, improved operational efficiency, diagnosis. This paper highlights emerging methods to automatically diagnose leukemia from cytological-histological & morphological analyses. In this study, we have performed comparative analysis of white blood cells segmentation techniques and evaluated the performance of pretrained deep CNN with multiclass models for Support Vector Machine (ECOC) as feature extractors towards classification of WBC to assist in improved screening of leukemia with classification accuracy of 93.94%.
Method for WSN node current measurement and energy budget calculation

In the designing of Wireless Sensors Networks, one of the key aspects is the energy consumption of each individual node that composes it. Instead of which kind of energy source would be used in the network deployment, the characterization of the power consumption in each mode of operation should be made for determine the autonomy of each individual node, allowing the appliance of a diversity of techniques and strategies for increasing the entire network reliability. This paper explains the description of a method that allows the measuring of the sensor node current consumption, for the later calculation of the power consumption and energy budget that the node requires for its normal