Miracle-dz/UniFAR-FTUs huggingface dataset:
Gas production from pig manure fed at different loading rates to polyethylene tubular biodigesters

Pig manure was fed at different loading rates (0.66 , 1.33, 2, 2.66 kg dry matter/m 3digester liquid volume/day) to four plug-flow plastic tube biodiges ter of 1.5 m3 liquid volume. The design was a 4*4 Latin square arrangement. The hydraulic retenti on me was 30 days and each experimental period was 8 weeks, the first 7 weeks for adaptatio n to the chosen loading rate and the last week for measurements. The temperature in the digester v aried from 25.3 to 27.3 oC and loading concentrations were 2, 4, 6, 8% of dry matter in th e constant daily liquid imput of 50 litres. The gas and methane yields increased linearly with increase in the loading rate (P<0.001) but the efficiency or gas production (gas or methane production per un it of manure dry matter loaded into the digester) was highest with the 2 kg DM / m 3 loading rate. The temperature of the effluent was higher than in the input material (P<0.05) but inle t and effluent temperature, and pH of inlet and effluent were not affected by loading rate.
Health inequalities , welfare state regimes and economic crisis : A comparative analysis in Sweden , Greece and Poland

Introduction: The aim of this paper is to explore individual-level determinants of health inequalities across three European countries (Sweden, Greece and Poland) with different welfare systems and differently affected by the recent economic crisis. Methods: The data derived from an original cross-national survey conducted in the context of the EU-funded LIVEWHAT project. The Chi-Square Test of Independence was used to examine potential differences in specific demographic traits, in socio-economic status and living conditions as well as in bridging and bonding social capital between individuals reporting poor health across Sweden, Greece and Poland. Binary logistic regression models were used to predict poor self-rated health based on the aforementioned predictors in the three countries under study. Results: Poor self-rated health was more prevalent in Poland (42.8%), the lowest prevalence rate was in Sweden (30.4%) followed by Greece (31.9%). The Chi-Square Test of Independence indicated significant differences between respondents reporting having poor health across the three countries with respect to their demographic characteristics, socio-economic status, socio-economic living conditions, and bridging social capital. The binary logistic regression analysis showed that specific indicators of lower socio-economic status and of adverse living conditions were more strongly associated with poor self-rated health in Greece and Poland, whereas individual traits associated with socio-economic living conditions were less important in predicting poor self-rated health in Sweden when taking into account individuals’ bridging and bonding social capital. Overall the lack of different forms of social capital was more strongly related to poor self-rated health in Sweden than in the other two countries. Discussion and Conclusion: Material explanations might be relatively more important in elucidating health outcomes in contexts with less generous welfare states, which were more severely affected by the recent economic crisis such as Greece and Poland, whereas social capital might be more decisive for health outcomes in a wealthy country with a universal welfare state such as Sweden. Journal of Health and Social Sciences 2019; 4,2:213-232
Energy Efficient Scheduling Algorithms for Problems with Relative Deadlines

Energy efficiency and invulnerability of the timing properties are two important issues spanning over distributed embedded systems. This paper deals with non-preemptive time-triggered scheduling problem with temporal constraints and the Energy Efficiency criterion. The temporal constraints allow to model end-to-end deadlines, release dates, absolute deadlines and synchronization of tasks that are executed on dedicated resources (processors and networks). The scheduling problem, classified as RCPS/TC, is solved by three different algorithms: Particle Swarm Optimization (PSO) with original repair function, Genetic Algorithm (GA) and GPSO as a combination of PSO and Genetic Algorithm. Performance of the three algorithms PSO, GPSO and GA with various configurations are compared and evaluated on computational experiments.
Interfacing a Battery Energy Storage System (BESS) with a Wind Farm with DC Collector System via a Flyback DC-DC Converter: Modelling, Control Strategy and Performance Analysis

Because of the intermittent nature of wind farm output power, large developments of grid-connected wind farms involve large fluctuations of the frequency, power and voltage in the grid. Thus, the output power of wind farms has to be controlled to limit these fluctuations. Integrating a battery energy storage system (BESS) into a wind farm can improve the wind farm- output dynamic properties. The simulation model of a grid-connected DC wind farm employing BESS is presented in this paper. The interface between DC wind farm and BESS is provided through an isolated flyback DC-DC converter. The dynamic performance and control strategy of the combined system, i.e. "BESS, flyback DC-DC converter and DC wind farm" is investigated. Through a proper coordination of the charging and discharging processes of BESS using the flyback DC-DC converter, it is demonstrated that the DC wind farm’s output voltage and power can be controlled to a constant value. Several simulations are carried out using MATLAB and show that the proposed DC grid configuration has the potential to significantly improve the wind farm’s output performance.
Integration of deep learning-based object recognition and robot manipulator for grasping objects

Many industrial robots have been applied relatively simple operation that requires repeatable tasks. However, through the rapid development of deep learning with 4th industrial revolution, it prospects that a role of robots will be extended, and the robots are expected to do task that a human can do. For example, in the service robotics, it is being studied about shelf-stocking and replenishment of many types of products such as food or cleaning rooms at home automatically. In this paper, we integrated object recognition system using deep learning approach with grasping system which has a serial manipulator and gripper for the basis of these future technology.We conduct a bin-picking, the bin-picking is to pick-up some objects and move to bin using an integrated system. In this task, we adopt the Mask R-CNN [3], which is widely used in the field of object segmentation, to determine the kind and shape of an object. After this segmentation on the image, we obtain poses of objects using center of gravity and a simple algorithm for orientation. We assume that the objects exist on not 3D space but a plane, so we only determine the direction of rotation of the object in a plane. Also, in order to position the camera flexibly, a marker is attached to the robot and the transformation between the camera and the robot is registered using this marker. Bin-picking experiments on four household objects took an average of 30 seconds per object. Although this time could be shortened, the speed of the manipulator was limited in consideration of safety.Through these experiments, we were able to verify an effectiveness of this integration which has an object recognition using deep learning and grasping system. On the future work, we aim to complete the 6D pose estimation for sophisticated work.
60 GHz Recessed Ground Plane Microstrip Patch Antenna Array with Improved Bandwidth and Gain

This work presents a two-element microstrip patch antenna array using recessed ground at 60 GHz. The use of recessed ground is demonstrated to enhance the bandwidth and gain of an antenna array at 60 GHz. Prototypes of a conventional and recessed ground patch antenna array are fabricated on 0.127 mm thick alumina ceramic substrate with $\boldsymbol{\varepsilon}_{\mathbf{r}}=9.8$. Measured results indicate that, an enhancement in −10 dB impedance bandwidth by 10.24% (57.8 to 64.6 GHz) and in gain by 1.25 dB over conventional patch antenna array is achieved at 60.1 GHz with recessed ground plane. The measured and simulated results agree reasonably with each other and suggests the proposed antenna to be suitable for indoor environment wireless applications at 60 GHz ISM band.
Impact of Reactive Current Injection by Islanding Detection Techniques on the Voltage Quality of Distributed Generation

Many active islanding detection techniques uses current injection through q-axis current controller of grid side converter (GSC) for islanding detection of distributed generation (DG). This paper studies the impact of injection of current on voltage quality of DG. The voltage quality of the DG is investigated by measuring the total harmonic distortion (THD) of voltage at the point of common coupling (PCC). The THD curves are plotted to suggest and help in selecting the amplitude and frequency of q-axis injection current for designing the q-axis injection current based islanding detection technique (IDT). The studies are carried out on a partial converter based small wind energy system on per unit basis to have generalized conclusions. Computer simulations are carried out in MATLAB.
Challenges of Big Data Implementation in a Public Hospital

The digitalization of the healthcare system has resulted in a huge amount of data in medicine. These data help healthcare organizations improve health-process efficiency, enhance healthcare quality, and reduce healthcare cost. In Thailand, several private hospitals obtain numerous benefits by utilizing big data analytics. However, public hospitals might encounter with some difficulties for implementing big data technology. This paper presents challenges of big data implementation in a case study public hospital. According to the analysis, challenges are discussed in aspects of technology, data, human, and organization. The recommendation for implementing big data is proposed as a guideline for big data implementation in the public hospital.
Efficient Synthesis of Scanned Conformal Arrays with Chebyschev Patterns

Standard synthesis approaches for linear arrays offer coefficients that can be applied to isotropic elements in free space. In the context of mm wave communication for 5G, conformal arrays with moderate number of elements are likely to be deployed for beam steering to achieve better utilization of resources. Only directive elements such as microstrip patch antennas will be useful here. A fast iterative algorithm was proposed by our group to address this. While digital controls offer easy implementation of such beam steering arrays, these pose an additional challenge in optimization of beam characteristics. An approach to correct the scanned main beam characteristics in these situations is discussed here.
Heterogeneous Activation Function Extraction for Training and Optimization of SNN Systems

Energy-efficiency and computation capability characteristics of analog/mixed-signal spiking neural networks offer capable platform for implementation of cognitive tasks on resource-limited embedded platforms. However, inherent mismatch in analog devices severely influence accuracy and reliability of the computing system. In this paper, we devise efficient algorithm for extracting of heterogeneous activation functions of analog hardware neurons as a set of constraints in an off-line training and optimization process, and examine how compensation of the mismatch effects influence synchronicity and information processing capabilities of the system.
Interactive Demand Response in a Locality of Smart Power System

Demand response programs in smart grid environment encourage the energy consumer to interact directly with the grid so that they can participate in electricity market actively. In this paper, a locality in smart power system is considered, where each consumer is intending to reduce the energy consumption cost by jointly scheduling their electric appliances. Non-cooperative game theory is applied to frame the distributed load scheduling game, where the consumers are considered as the players and the energy consumption schedules of their appliances as strategies. Genetic Algorithm (GA) is used as the optimization tool for individual consumer load scheduling to minimize the electricity bill. Interactive scheduling is done using both simultaneous method and sequential method.
A Compact Statistical Model for the Low-Frequency Noise in Halo-Implanted MOSFETs: Large RTN Induced by Halo Implants

In this paper, we propose a novel compact statistical model for the low-frequency noise (LFN) of MOS devices with halo implants. The compact model is suited for the incorporation in modern models, such as BSIM, PSP, and EKV, and can be used to predict the dependence of the LFN of halo-implanted MOSFETs with bias, temperature, geometry, and technological parameters. This compact model is based on the physics-based random telegraph noise (RTN) model, previously published by our group. The previous model was simplified in analytical expressions dependent on parameters and on physical quantities already calculated in modern compact models. Following the physics-based model, the LFN compact model predicts the large bias dependence of the LFN statistics induced by the halo implants in long-channel devices. Moreover, we show for the first time that the halo implants also induce a large temperature dependence of the LFN statistics for devices operated near the weak inversion or saturation, and the proposed compact model predicts this dependence.
Generalized DC-DC-AC MMC Structure for MVDC and HVDC Applications

A generalized modular multilevel converter (MMC) chain-link structure is presented that allows independent power transfer between two dc systems and one ac system. This chain-link structure is shown to give rise to two new dc-dc-ac MMC topologies suitable for MVDC and HVDC applications. Simultaneous dc-dc and dc-ac conversion is achieved by exploiting a center-tap transformer connection where the windings can carry both dc and ac currents, without leading to increased transformer rating or size when compared to a conventional two-winding ac transformer for a standard dc-ac MMC. A unified control scheme is proposed to independently control dc and ac terminals power transfers while maintaining balanced capacitor voltages for both topologies. Converter operation and the proposed dynamic controls are validated by real-time simulations obtained from RTDS system using FPGA-based low-level valve firing control.
An Ensemble Approach to Utterance Level Multimodal Sentiment Analysis

The primary objective of sentiment analysis system is to automatically discover and analyze people’s attitude, opinion, or position towards a product, a topic, a person or an entity. A huge amount of multimedia content is being posted on social websites such as YouTube, Flicker, and Twitter on every day. To cope up with such multimedia data, there is a need for state-of-the-art multimodal sentiment analysis framework that can extract information from multimodal data. The purpose of this research work is to improve the accuracy of sentiment prediction by analyzing the textual features along with facial expressions. We examine what people say and their facial expressions when they are saying it. Bag-of-words representation is used to create textual features. Facial expressions and audio features were extracted using open source tools such as OpenFace and OpenSmile respectively. Unimodal, bimodal, trimodal and ensemble approaches were used for classification. Our results demonstrate proposed ensemble approach outperforms other base models.
Hybrid Precoding Based on MMSE-EDS for Multi-user Multi-stream Massive MIMO Systems

Hybrid analog/digital precoding architecture is a combination of analog and digital processing that reduces the number of RF chains while enabling beamforming and spatial multiplexing gain. Existing mean squared errors (MSE) hybrid precoding algorithm can minimize the sum of MSE, however, do not guarantee that the MSE of each data stream minimized. In this paper, we propose a hybrid precoding method based on the minimum mean square error of each data stream (MMSE-EDS) for multi-user multi-stream Massive multi-input multi-output (MIMO) system. Through calculating the optimal baseband precoding and analog precoding pairs for each data stream, the proposed hybrid precoding ensures minimization of the MSE of each data stream, thus minimizing the sum of the mean square error (MSE) of all data streams. The proposed precoder/combiner can be easily obtained by Lagrangian algorithm. The performance advantages of our proposed hybrid precoding in spectral efficiency (SE) and bit error rate (BER) have been simulated.
Impact of Camera Parameters on the OCC based Indoor Positioning System

We investigate the effect of camera parameters on the performance of an image sensor or camera based indoor visible light positioning (VLP)system. In this paper, we use 6 light emitting diodes (LEDs)mounted on the ceiling and a camera based receiver for localization and estimate the location using the view angles between LEDs in the image plane. We show that, the accuracy of localization using camera can be affected by the camera parameters such as the lens distortion and the resolution of the image sensor. We also investigate the effect of field of view (FOV)of the camera on the positioning errors for the proposed VLP system.
Fully Integrated Wideband Doherty PA with Additive-Voltage Supported Load-Modulation in CMOS 130nm

This work introduces the first CMOS integrated Doherty power amplifier (DPA) with additive-voltage supported continuous load-modulation. Key features of the architecture are the wideband behaviour and low AM-PM distortion. Owing to the transformer based architecture, it is area efficient and highly suitable for integrated technologies. A prototype has been implemented in CMOS 130 nm. The complete chip size including input matching and the proposed load modulation network is less than 1.2 mm2. Measured peak output power of 25 dBm is reached at 2.4 GHz with 27.6 % power added efficiency (PAE) and 24 % PAE at 6 dB backoff. The DPA delivers more than 24 dBm output power from 2.2 GHz to 3 GHz and thus, covers 31 % of bandwidth. Measured AM-PM distortion of less than 3◦ is obtained.
Linear Array Pattern Synthesis Using Multi-Objective Optimization Algorithm Based on Reference Vectors

In this paper, non-dominated sorting genetic algorithm based on reference vectors (NSGA-II/BRV) is proposed to minimize the Peak Sidelobe Level (PSL) and the Average Broad Null Level (ABNL) for the pattern synthesis of linear array. Here, NSGA-II/BRV mainly focuses on the convergence and diversity of the obtained solutions for multi-objective problems. In order to get a better distribution and convergence of the obtained solutions, the members close to the uniformly distributed reference vectors will be selected. Compared with MOPSO, numerical examples demonstrate that NSGA-II/BRV applied to array pattern synthesis can obtains higher performance and better distribution of the final solutions.
A Thinned Array Solution for an ISOFLUX Antenna from Geostationary Satellite

A Thinned array configuration has been successfully designed and demonstrated implementing an ISOFLUX pattern profile from on-board geostationary platform. A Fourier synthesis procedure was efficiently utilized to obtain the element excitations. Array thinning performed by excluding elements receiving less than −12.5dB of the input signal, thus reducing total feeder loss. Sequential rotation across array quadrant used to suppress the cross-polarization by almost 40dB. Close agreement of measured results validate the proposed design and synthesis technique.
A Modular Architecture for Wide Scan Angle Phased Array Antenna for K/Ka Mobile SATCOM

In this paper a low cost/complexity modular architecture for electronically scanned active phased array antenna (A-PAA) for high throughput K/Ka-band mobile satellite communication (SATCOM) is presented. With this approach, A-PAAs of any size, shape, and configuration can be built of intelligent building blocks (active sub-array modules) to minimize the design complexity and fabrication cost. The design and fabrication aspects of K/Ka A-PAA with wide scanning angle range is presented. The measured results of the modular array show that the antenna main beam can be steered to ± 70º off the boresight at 20/30 GHz. Furthermore, the antenna is able to achieve EVM ~ 7.60 % during the constellation test for 16 QAM and 1.2 Gb/s.
Exploiting Graphene Quantum Capacitance in Subharmonic Parametric Downconversion

This work presents for the first time the unique properties of graphene quantum capacitance (CQ) in parametric circuits. The combination of the CQ and parametric operation results in a distinct topology which enables the realisation of RF powered, receiver and transmitter frontends, with high conversion gain (GC) and relaxed local oscillator (LO) requirements. The presented prospect is discussed in details for the down-conversion case. Feasibility of the proposed approach is validated by designing a heterodyne RF receiver frontend centered at 29 GHz. A Verilog-A behavioural model, extracted from S-parameter measurements of a graphene varactor on flexible kapton foil is employed in the verification. Simulation results provide a positive GC of 20 dB and a noise figure (NF) of 4.7 dB without the need for DC bias. The results agree with the presented theoretical analysis of the proposed concept.
PERFORMANCE RESULTS USING DATA QUALITY ENCAPSULATION (DQE) AND BEST SOURCE SELECTION (BSS) IN AERONAUTICAL TELEMETRY ENVIRONMENTS

Flight test telemetry environments can be particularly challenging due to RF shadowing, interference, multipath propagation, antenna pattern variations, and large operating ranges. In cases where the link quality is unacceptable, applying multiple receiving assets to a single test article can significantly improve the overall link reliability. The process of combining multiple received streams into a single consolidated stream is called Best Source Selection (BSS). Recent developments in BSS technology include a description of the maximum likelihood detection approach for combining multiple bit sources, and an efficient protocol for providing the real-time data quality metrics necessary for optimal BSS performance. This approach is being standardized and will be included in Appendix 2G of IRIG-106-17. This paper describes the application of this technology and presents performance results obtained during flight testing.