Miracle-dz/UniFAR-FTUs huggingface dataset:
IoT Enabled an Open Framework for Air Pollution Monitoring System

Blessing with fresh air to breathe is one of the primary living requirements of the Human being. Nowadays, majority of the countries in the world are suffering from the problem of Air pollution. This problem is getting worse day by day because of rapid economic growth, industrialization, urbanization and the resulting rise in energy demand. Air pollution has been become one of the primary concern in Sri Lanka. In most of the Sri Lankan cities, the primary cause for the air pollution is the lack of the prevalence of proper environmental regulations. Although the scientific evaluation of such technologies and systems is generally recognized as a significant facet of open source technologies and their implementation, it is often underexplored in science. This research provides an integrated approach to the development of an Environmental Monitoring System prototype based on open source hardware and software and to track the reliability of the system in terms of data accuracy. This system is able to measure six environmental parameters namely air temperature, air CO Percentage, air NO2 percentage, air O3 percentage, air PM percentage and air SO2 percentage. This research has shown a promising way to create a dense coverage for more cost-effective monitoring of environmental phenomena. Most of the existing monitoring systems for air pollution have inferior accuracy, low sensitivity and require laboratory study. Our implemented system is a three-phase air pollution monitoring system, which have drastically shown improvements over the existing methodologies combining with the Internet of Things (IOT).
A Vision-guided Methodology for the Automation of Biological Cell Injection

Microinjection is a technique in which a foreign material is introduced into the biological cell using micropipettes. Vision sensing and servoing play a crucial role in the automation of various microinjection operations in medical devices. This study proposes a vision-based technique that has been developed towards the automation of microinjection applications. This study provides a comprehensive algorithm that can detect the injection and holding pipette as a part of the injection system and then automatically align them in three orthogonal axes. The tip of the injection pipette was successfully measured at various magnifications. The zebrafish embryo as a biological model is automatically detected and positioned within the field of view (FOV) of the microscope in real-time regardless of its initial position. The algorithm has been examined and verified for the proposed technique to successfully conduct full operations including alignment of the pipettes, detection of the tip position of the injection pipette at various magnifications and positioning the zebrafish embryo to the FOV of the microscope.
Experimentally Constrained Design Parameters Approach for PMSM and BLDC Motor

This study deals with design parameters of electrical motor to provide facilities to design Brushless DC and Permanent Magnet Synchronous Motor. The parameters are declared according to the design flow chart process, in this paper additionally the important and critical parameters and terms some experimentally constrained parameters in a specific range value are highlighted with referring many references and manufacturing experiences from the motor producing companies. These parameters are including dimensional length e.g. stator inside diameter and stator slot, material properties e.g. electrical lamination steel and permanent magnet, electromagnetically e.g. airgap flux density and electrically ranges e.g. current density and rated torque per volume, they are all expressed step by step in next sections.
Congestion Pattern Prediction for a Busy Traffic Zone Based on the Hidden Markov Model

Congestion pattern in a busy traffic zone would not always be a single state. The scenario of congestion occurring in multiple connected road links may be shifted to the scenario of whole zone network paralyzation immediately. It is necessary to dynamically predict the congestion pattern for a busy traffic zone rather than a road link, which could provide information for network system decision making. Considering the close connection between the upstream and downstream traffic flow, this study proposes a congestion pattern prediction model for a busy traffic zone based on the hidden Markov model (HMM). The model establishes a correlation between the external road traffic state (observation state) and internal road traffic state (hidden state) of a busy traffic zone. We acquire these traffic states by cleaning and mining floating vehicle trajectory data. With these data, we calibrate the HMM and predict the zone congestion pattern. This article demonstrates the validity and rationality of the model by taking a hospital area in Ningbo City as an example. The prediction accuracy can reach 83.4%, which is 5.8% higher than that of the autoregressive moving average model. This case result illustrates the feasibility and effectiveness of our approach in the field of congestion pattern prediction for busy traffic zone.
Secrecy Outage Probability of Relay Selection Based Cooperative NOMA for IoT Networks

As an important partner of fifth generation (5G) communication, the internet of things (IoT) is widely used in many fields with its characteristics of massive terminals, intelligent processing, and remote control. In this paper, we analyze security performance for the cooperative non-orthogonal multiple access (NOMA) networks for IoT, where the multi-relay Wyner model with direct link between the base station and the eavesdropper is considered. In particular, secrecy outage probability (SOP) for two kinds of relay selection (RS) schemes (i.e., single-phase RS (SRS) and two-phase RS (TRS)) is developed in the form of closed solution. As a benchmark for comparison, the SOP for random RS (RRS) is also obtained. To gain more meaningful insights, approximate derivations of SOP under the high signal-to-noise ratio (SNR) region are provided. Results of statistical simulation confirm the theoretical analysis and testify that: i) Compared with RRS scheme, SRS and TRS may improve secure performance because of obtaining smaller SOPs; ii) There exists secrecy performance floor for the SOP in strong SNR regime, which is dominated by NOMA protocol; iii) The security performance can be enhanced by augmenting the quantity of relays for SRS and TRS strategies. The purpose of this work is to provide theoretical basis for the analysis and design of anti-eavesdropping for NOMA systems in IoT.
Compact Diplexers With Folded Circular SIW Cavity Filters

This work presents diplexers realized with folded circular substrate integrated waveguide (FCSIW) cavity filters. The properties of such cavities are analyzed, and empirical equations for calculating the resonant frequencies are given. The analysis relies on an even-/odd-mode decomposition. A 10-GHz filter is designed based on this approach. In the second step, its size is reduced, still maintaining the passband behavior. An asymmetric taper is used to connect two such filters to realize a diplexer. Two diplexers with center frequencies of 10/15 and 12/13.5 GHz are presented. The diplexers are several times more compact than comparable devices reported in the literature. The components are manufactured, and the functionality is demonstrated by simulation and measurements.
Smart Building: A Literature Review

The work of the paper aims to provide a literature review of how smart buildings operate to managing various features that can be adapt in the built environment. Based on the literature review, the focus on this paper will be dealing with a definition of a smart building, management energy, occupant comfort, heating, ventilation, and air conditioning operation planning, visualization using Building Information Modelling (BIM) as one of another way to share and exchange building information. Many features that adapt to smart buildings should fulfill to be compatible with the context of a smart city. The evaluation process always exists based on the level of human comfort and improving the quality of life in the future. Many works shows us how regulatory bodies try to replace the traditional of building management system by smart building concept with the benefit use of smart technology that can addressing information sharing, fulfill user needs, aims for the challenges of digital society, more transparency, and become openness deals to increase the value of properties.
Silicon Mode (de)Multiplexer Based on Cascaded Particle-Swarm-Optimized Counter-Tapered Couplers

In this paper, a design of a silicon mode (de)multiplexer based on cascaded counter-tapered couplers is proposed and investigated. By using the particle swarm optimization algorithm and finite difference time domain method, structural parameters of each counter-tapered coupler in our proposed mode (de)multiplexer are optimized so that high conversion efficiencies can be obtained and coupling lengths can be significantly shortened. The coupling lengths of counter-tapered couplers in the proposed silicon four-mode (de)multiplexer operating in transverse-electric polarization are 8 μm, 9 μm, and 10 μm. The corresponding conversion efficiencies are respectively 98.98%, 99.98%, and 98.68%. Experimental results show that, the fabricated device exhibits a demultiplexed crosstalk of −32.76 dB, −27.10 dB, −32.45 dB, or −33.29 dB at 1550 nm wavelength, when the fundamental transverse-electric mode is respectively launched into the ports Input0, Input1, Input2, or Input3. The measured demultiplexed crosstalk is less than −15.15 dB from 1525 to 1596 nm and lower than −18.12 dB from 1525 to 1561 nm.
Energy-Efficient Coordinated Electric Truck-Drone Hybrid Delivery Service Planning

Recent works have shown that a coordinated delivery strategy in which a drone collaborates with a truck using it as a moving depot is quite effective in improving the performance and energy efficiency of the delivery process. As most of these works come from the research community of logistics and transportation, they are instead focused on the optimality of the algorithms, and neglect two critical issues: (1) they consider only a planar version of the problem ignoring the geographic information along the delivery route, and (2) they use a simplified battery model, truck, and drone power consumption model as they are mostly focused on optimizing delivery time alone rather than energy efficiency.In this work, we propose a greedy heuristic algorithm to deter-mine the most energy-efficient sequence of deliveries in which a drone and an EV truck collaborate in the delivery process, while accounting for the two above aspects. In our scenario, a drone delivers packages starting from the truck and returns to the truck after the delivery, while the truck continues on its route and possibly delivers other packages. Results show that, by carefully using the drone’s energy along the truck delivery route, we can achieve 43-69% saving of the truck battery energy on average over a set of different delivery sets and different drone battery sizes. We also compared two "common-sense" heuristics, concerning which we saved up to 42%.
Secrecy Performance of a Multi-NOMA-MIMO System in the UEH Relaying Network Using the PSO Algorithm

In this paper, we investigate the secrecy performance of the nonorthogonal multiple access (NOMA) system in an untrusted relaying energy harvesting (UEH) network with the multiple-input multiple-output (MIMO) architecture using the maximum ratio transmission (MRT) and maximal ratio combining (MRC) techniques. In this network, a source communicates with users with the help of a relaying network composed of multiple untrusted components using the amplify-and-forward (AF) protocol. These untrusted relay nodes are equipped with a single antenna and employ the power-splitting (PS) protocol to harvest energy from received signals. Moreover, to improve the secrecy outage performance and protect the confidential information from the untrusted relaying network, the source acts as the jammer to generate artificial noise (AN). To evaluate the secrecy performance of each user and the overall system, we derive the closed-form expressions of the secrecy outage probability (SOP) over the Rayleigh fading channels and use a Monte Carlo simulation to verify the accuracy of these analytical results. Moreover, to analyze the secrecy data rate, the maximization problem of the sum secrecy rate (SSR) of the system is solved by applying the particle swarm optimization (PSO) algorithm based on power allocation (PA). These results are also validated with the optimal exhaustive search method. Furthermore, we compare the MIMO/NOMA and MIMO/OMA systems and examine the effects of various system parameters to characterize the secrecy effectiveness of both systems.
Spectroscopic Analysis of the Interface Between Si and Its Thermally Grown Oxide

Spectroscopic ellipsometric data from 1.5–5.8 eV has been analyzed to determine the in situ optical response of the interface between Si and its thermally grown oxide. Results for , , and sample orientations show an interface of width consisting of atomically mixed Si and O of average stoichiometry . The optical data are not consistent with either microroughness at the interface or an abrupt transition between crystalline Si and or a significant accumulation of amorphous Si at the interface, but rather support a gradual transition region. The thickness and the average λ5461 refractive index of this region are in agreement with the fixed‐wavelength results, and , of Taft and Cordes. The oxide on the surface is shown to have a density about 1.2% less than that of corresponding oxides on and surfaces.
Comparative study between Interior Point and Particle Swarm methods for Optimal Renewable Distributed Generation location

This paper presents an optimal location of Renewable Distributed Generation (RDG) problem. For this, interior point method (IPM) and particle swarm optimization (PSO) have been used to locate three RDG plants in their optimal location. RDG represent 10.5% of the total load. First, two types of RDG are separately considered: those that inject only active power and ones that inject active power and consume reactive power on the grid. Secondly both types are considered together. The proposed methods are tested on 33 kV distribution busbars from the standard IEEE-30 bus system. Total generation cost has been chosen as the Fitness function allowing the power system to operate under technical and safety conditions. The results obtained are compared with these reported in the literature. They showed that the optimization of the DG position minimizes the cost of generation while reducing active power losses.
Bandwidth Enhancement for Wireless Power Transfer System Employing Non-Linear Resonator

In order to enhance the tolerance of frequency misalignment and solve the amplitude-bandwidth limitation issue of the traditional linear resonance wireless power transfer (WPT) system, this paper proposes a non-linear resonance WPT (NLR-WPT) system which is mainly composed of high frequency power supply, primary linear resonator, secondary non-linear resonator, and load. Such non-linear resonator can be implemented with passive linear capacitor and magnetic saturation inductor, and it can be described by Duffing equation. It has been shown that the bandwidth of NLR-WPT system in the nonlinear state is 1.7 times larger than that in the linear state. In addition, the output voltage basically stabilizes at the same level, the voltage fluctuation is less than 5% over the power frequency ranging from 25.6 kHz to 31.8 kHz, and high overall efficiency of 86.5% can be achieved under a wide range of frequency (27.5 kHz-30.1 kHz). Furthermore, the range of frequency can be extended significantly over which the output voltage is maintained even while the compensate capacitance, load, or coupling coefficient values vary in a certain range. The experimental results agree well with the theoretical analysis and verify the validity of the NLR-WPT system with non-linear resonator. This paper provides a simple and effective scheme to suppress the fluctuation of output voltage, which is suitable for the applications of constant voltage charging such as moving devices or electric vehicles.
Importance of Long-lifetime n-GaInP for High-efficiency GaInP Solar Cells Grown by MBE

We present a systematic photoluminescence (PL) study on the effects of doping and rapid thermal annealing (RTA) conditions on n- and p-GaInP double-heterostructures (DHs) grown by molecular beam epitaxy (MBE). The steady-state photoluminescence (SSPL) intensity of lightly doped n- and p-GaInP both improve significantly after RTA, while in contrast, heavily doped n-GaInP degrades sharply with RTA. Front-junction (FJ) GaInP cells with this heavily doped $n$-GaInP emitter were severely damaged after RTA, as expected. Replacing the emitter with lightly doped $n$-GaInP may help to alleviate the degradation and lead to improved MBE-grown GaInP solar cells.
Extreme Learning Machine Based on Maximum Weighted Mean Discrepancy for Unsupervised Domain Adaptation

Extreme Learning Machine (ELM) has shown fast learning speed and good generalization property in single-domain problems, such as classification and regression. However, the assumption that the training and testing data are subject to identical distribution often leads to significant performance degradation of ELM in cross-domain problems. To cope with unsupervised domain adaptation problems by ELM, we propose a novel method called Extreme Learning Machine based on Maximum Weighted Mean Discrepancy (ELM-MWMD) in this paper, which learns an adaptive ELM classifier with both labeled source data and unlabeled target data. Firstly, the cross-domain weight coefficients are specifically designed and assigned for each sample in source and target domains, fully considering the effects of individual information. Then the source classifier is adapted to the target domain by minimizing the distribution discrepancy between the two domains, both the marginal distribution and conditional distribution are simultaneously reduced to obtain a more accurate target classifier. Moreover, the predicted results for target data are utilized as pseudo labels to further improve the classification accuracy in multiple iterations. Extensive experiments on public image datasets demonstrate that ELM-MWMD performs better than several existing state-of-the-art domain adaptation methods by computation efficiency and classification accuracy.
Influence of the Alloying Elements on Pitting Corrosion of Stainless Steels : A Modeling Approach

Modeling of corrosion pit chemistry in applied polarization mode is carried out using finite element method calculations. The results lead to the formulation of critical conditions for pit stabilization in terms of the pit geometry and the applied potential. More detailed computing is performed to compare the behavior of both ferritic and austenitic stainless steels. The results fairly predict the beneficial effects of nickel on pitting resistance of 304 stainless steels, attributed to nickel-induced changes in dissolution laws.
Can Fullerene Analogues be the Carriers of the Diffuse Interstellar Bands?

Abstract Fullerenes and their derivatives are amongst the most stable carbonaceous species known and have therefore been proposed as ideal candidates to carry some of the diffuse interstellar bands (DIBs). Evidence for these species in space first came from a few DIBs that have been tentatively identified with electronic transitions of C60+; in recent years, infrared observations have furthermore revealed fullerenes in a variety of circumstellar and interstellar environments. With the presence of the fullerene family in space established, we review what is known about cosmic fullerenes and their derivatives and what role they could play as potential DIB carriers.
Epipolar Plane Image-Based Lossless and Near-Lossless Light Field Compression

Recent advances in the computer technology has enabled many theoretical ideas in computer vision to become practical also within camera technology. Light field technology aims at replacing the traditional camera design by acquiring the intensity of light rays to realize advanced applications in media and medical industries. The abundant amount of information poses high processing, transmission and storage requirements. Therefore, a need for efficient compression has gained researchers attention in this area. We present EPIC, an efficient lossless compression scheme for light field images which extends CALIC by exploiting light field structure. We have shown that the proposed scheme achieves around 6% improvement in compression performance relative to HEVC-lossless anchor with a significant reduction in the encoding time. We have also extended the proposed method for the near-lossless case which achieves similar rate-distortion performance as HEVC-lossy anchor in addition to a high encoding efficiency and a guaranteed-error bound.
Designing and Evaluating Multimodal Interactions for Facilitating Visual Analysis With Dashboards

Exploring and analyzing data using visualizations is at the heart of many decision-making tasks. Typically, people perform visual data analysis using mouse and touch interactions. While such interactions are often easy to use, they can be inadequate for users to express complex information and may require many steps to complete a task. Recently natural language interaction has emerged as a promising technique for supporting exploration with visualization, as the user can express a complex analytical question more easily. In this paper, we investigate how to synergistically combine language and mouse-based direct manipulations so that the weakness of one modality can be complemented by the other. To this end, we have developed a novel system, named Multimodal Interactions System for Visual Analysis (MIVA), that allows user to provide input using both natural language (e.g., through speech) and direct manipulation (e.g., through mouse or touch) and presents the answer accordingly. To answer the current question in the context of past interactions, the system incorporates previous utterances and direct manipulations made by the user within a finite-state model. The uniqueness of our approach is that unlike most previous approaches which typically support multimodal interactions with a single visualization, MIVA enables multimodal interactions with multiple coordinated visualizations of a dashboard that visually summarizes a dataset. We tested MIVA’s applicability on several dashboards including a COVID-19 dashboard that visualizes coronavirus cases around the globe. We further empirically evaluated our system through a user study with twenty participants. The results of our study revealed that MIVA system enhances the flow of visual analysis by enabling fluid, iterative exploration and refinement of data in a dashboard with multiple-coordinated views.
Single Pulse Avalanche Robustness and Analysis for 1200-V SiC Junction Barrier Schottky Diode

In this paper, the single pulse avalanche robustness of 1.2kV 4H-SiC Junction Barrier Schottky (JBS) diode with different designs is investigated. The unclamped inductive switching (UIS) tests are carried out to obtain avalanche energy capability. It is found that the JBS diode with the narrower spacing of the P+ region exhibits higher avalanche robustness (around 5%~8.5% improvement in this paper). Simulation analysis reveals that there is a current crowding in avalanche mode, which will be more severe with the increasing spacing of P+ regions. The localized current crowding and unbalanced current distribution can lead to a reduced effective power dissipation area and a higher junction temperature, which is adverse for the device avalanche robustness. Therefore, in the process of device design and optimization, avalanche robustness can be improved by alleviating the issue of the current crowding, which is beneficial to enhance the product's competitiveness and expand the application of the device.