Miracle-dz/UniFAR-FTUs huggingface dataset:
Comparison among deterministic methods to design rural mini-grids: effect of operating strategies

Mini-grids are well known to be a suitable solution to foster rural electrification in developing countries, and yet risks and high costs are hampering their spreading. Even though effective tools can help developers to identify the optimal design and operation of a mini-grid, no standard approach have emerged yet. This paper proposes a numerical comparison among deterministic methodologies to optimize a rural minigrid considering the effect of different operating strategies. The typical load-following and cycle-charging strategies are compared to predictive approaches, as rolling-horizon and a one-shot model, which optimizes both the design and operation together. The two latter models allow achieving additional savings compared to traditional operating strategies, but the computational requirements increase sharply. Results suggest that sizing methodologies using load-following or cycle-charging strategies are more suitable for preliminary design, while predictive approaches should be used for the fine tuning of the size of components. This study can provide guidance on design and operating methodologies for rural mini-grids in developing countries.
Gait-Event-Based human intention recognition approach for lower limb

Human intention recognition of lower limb is an important issue for powered lower limb exoskeleton robot. In this paper, a novel approach for representing and recognizing human intention of lower limb is proposed, which includes three steps. First, four gait events, which are defined on the basis of hip joint angles, are detected by measuring the real-time hip angles. Second, the real-time gait cadence and stride length are estimated based on the gait event. Third, the joint trajectories for robot are generated with the gait cadence and stride length. The practical experiments are implemented via the inertial measurement unit(IMU) system, where ten healthy volunteers and two conditions are enrolled to verify the effectiveness of proposed algorithm in recognizing human intention of lower limb.
Electric field and Temperature Distribution along the Polymer Rod Type Suspension Insulator in Polluted Environment

This paper presents a study of the electric field and temperature distribution along the surface of the polymer insulator operating in polluted environment. The study was carried out through the simulations for clean and non-uniformly contaminated insulator surface using finite element tool Comsol Multiphysics software. It has been shown, through the simulation results, that the pollution conductivity significantly affects the heat and electric field propagation along the insulator surface. Area of the insulator surface with lower conductivity value, experiences higher temperatures along with higher electrical field stresses. This indicates that the regions with lower conductivity value become critically over stressed and they contribute to a non-uniform drying process leading to a formation of dry band areas with possible flashover as an epilogue. The main goal is to point out those critical regions resulting as a consequence from different value of the electrical conductivity of the pollution layer.
The LMU Munich Unsupervised Machine Translation System for WMT19

We describe LMU Munich’s machine translation system for German→Czech translation which was used to participate in the WMT19 shared task on unsupervised news translation. We train our model using monolingual data only from both languages. The final model is an unsupervised neural model using established techniques for unsupervised translation such as denoising autoencoding and online back-translation. We bootstrap the model with masked language model pretraining and enhance it with back-translations from an unsupervised phrase-based system which is itself bootstrapped using unsupervised bilingual word embeddings.
Sustainable Islanding System Based on Dual Power Inverters with Cooperative Generator

This paper proposes a sustainable islanding system for microgrid which consists of dual power inverters and a cooperative generator. The system can be separated from the utility grid with two islanding operations, one is normal islanding operation that maintains the stable power supply to all loads, the other is protective islanding operation that protects prior part of the load from the power outage even when the grid fault occurs unexpectedly. These operations are based on a multi-mode control of the inverters between the constant current and constant voltage modes, and the cooperation of the local generator that supports enough power to the voltage mode inverter for the successful islanding operation. In addition, the inverters use the voltage synchronization to reconnect to the grid, which makes the mode transition seamlessly. The islanding operations of the proposed system were verified through the simulations using PSIM tool. The power supply to the prior load was continuous by detecting the grid fault in 10 ms and by changing the voltage source from the grid to the inverter. Then, the other inverter and the generator cooperated to supply power to the other load according to the predefined procedure.
An Energy Saving Management Strategy for Battery-Aided Ship Propulsion Systems

This paper examines the management of ship power systems equipped by energy storage systems. Energy storage in the on-board power system can increase the efficiency of prime movers in order to reduce fuel consumption and pollutant emissions. In this paper, a management strategy for the on-board electrical network is proposed. The strategy optimally balances the charge/discharge of the storage device, the power of the generation system, the loads’ demand of hotels, auxiliaries, and electrical machineries used for propulsion and maneuvering purposes. The optimal approach aims at minimizing the fuel consumption, while technical constraints of the on-board system are considered in terms of both generation system and energy storage system. A case study of a real off-shore supply vessel is proposed. The results of the numerical application are discussed showing the effectiveness of the proposed strategy.
Compartmental EMI Shielding with Jet-Dispensed Material Technology

Device miniaturization continues using System-on-Chip (SoC), System-in-Package (SiP), multichip module (MCM), and heterogeneous integration to deliver a wider range of functionalities without sacrificing valuable space on a substrate. With multiple integrated circuits and MEMS sensors integrated into a thin single module to perform as a full electronic system, the need for more compact and effective electromagnetic interference (EMI) protection between various baseband and wireless, RF, analog, and power management components is greater than ever before. Fortunately, as device miniaturization has accelerated, so has the development of novel shielding technologies to accommodate for the higher density package structures. Jet-dispensed compartment shielding is an integrated package-level solution that allows for much smaller semiconductor form factors and is achieved using a fully automatic assembly process with high performance.
Inductive Links for 3D Stacked Chip-to-Chip Communication

This paper focusses on an experimental inductive link study based on S-parameter measurements up to 67 GHz for 3D stacked chip to chip communication. This is complemented by a calibrated HFSS model for coupling between two chips that is then extended to stacks with up to eight chips. This approach allows for a complete analysis of the inductive link mechanisms between stacked chips and the impact of different parameters. Moreover, a circuit level assessment of the inductive link for a transmitter circuit has been performed using FinFET technology.
Influence of Gender and Age of Teachers of Agriculture on Classroom Diversity Management : The Case of Homa Bay County , Kenya Mbori

Diversity in education encompasses students from different ages and gender. The objective of this study was to examine how gender and age of teachers of agriculture influence how they manage classroom diversity in secondary schools in the county of Homa Bay, Kenya. A sample of 40 teachers and 785 students of agriculture were considered in this study. Three data collection tools were used; two questionnairesone for teachers of Agriculture and the other for Agriculture Students. Face and content validity of the research instruments was ascertained and reliability was established through a test-retest method whereby an acceptable Cronbach's coefficient Alpha of 0.79 was obtained. Data was analysed using basic descriptive statistics in the SPSS Version 25. The findings indicate that there is a statistically significant influence of gender (p= 0.03 <.05) and level of training of teachers (p=0.022 <.05) on their classroom diversity management skills. However, it was also established that differences exist on how teachers of Agriculture support diversity in their classroom in the terms of years of teaching experience (p=0.9 >.05) and age (p=0.24 >.05). These findings may be of significance to the Quality Assurance and Standards Department of the Ministry of Education and other stakeholders.
Robot Service Tasks-oriented Family Environment Cognition Mechanism by Deep Learning*

In order to improve cognition of service robots, a novel cognition mechanism of family environment based on deep learning is presented in this paper. Facing to an unexplored family environment, the robot can comprehend circumstances efficiently and autonomously with the cognition mechanism rather than the more participation of manual work. The cognition mechanism transforms environment vision information into environment knowledge, guiding robots to perform service tasks. Two designed models play an import role in the cognition mechanism, which are multi-stage feature fusion based on ResNet model (MSFF-R) for family scene recognition and single shot multibox detector increase model (SSD-I) for object detection. The outputs of the MSFF-R model and SSD-I model are semantic descriptions of current surroundings, which are fused to be stored in a designed knowledge base of family environment. The knowledge base can offer the knowledge related to service tasks to guide robot and it can be updated dynamically with the changes of the environment. Finally, MSFF-R and SSD-I model are trained on public datasets and experiments in a practical environment have been done to prove the feasibility of the cognition mechanism.
Extending the Reach of Traditional Frequency Control for Fast Responses

This paper investigates the role of grid-level battery energy storage in delivering measured reserve to supplant traditional synchronous units for frequency response support in the context of high renewable generation penetration. Dynamic simulation is performed on a modified 39-Bus New England model to assess and evaluate the impact of embedded storage for fast frequency support. The paper proposes a response strategy for sudden changes in frequency with storage acting in the dual role of limiting frequency nadir excursion while delivering synthetic inertia to the grid.
Microstructures of Pb-Free Solder Joints by Reflow and Thermo-Compression Bonding (TCB) Processes

Differences in microstructures of lead-free solder joints, Sn-Ag-Cu (96.5 wt./3.0 wt./0.5 wt.% SAC-305), made by two different semiconductor packaging processes such as reflow and TCB are discussed. Despite the enormous potential for TCB solder bonding process in microelectronic packaging, there has been few studies regarding the comparative analysis on electro-migration (EM) failure mechanism for the reflow process. We have systematically examined the EM-derived failures of the reflow and TCB-processed solder joints and demonstrated a process-structure-property linkage. This study also includes the analysis performed using generalized spherical harmonics (GSH) representation, a statistical and quantitative measure of material crystallographic informatics, which is novel in this field as to analyzing solder joint microstructures.
Supplier Selection for High-Tech Start-Up Companies Benjamin Löfdahl

The growing need to source manufacturing activities to original equipment manufacturers has presented a strategic challenge for firms in evaluating and selecting supplier partners for their products. Supplier performance evaluation is a well-researched area within supply chain management. Though several authors have contributed with models for supplier selection, there still exist uncertainties regarding how high-tech start-up firms should capitalize on these models. By conducting a case study at AB Realisator Management Consulting currently developing a new firefighting robot concept called FUMOTM, the authors were able to develop a model for supplier selection and test it on a real case scenario. Results indicate that high-tech start-up firms in general should apply the following step-by-step process for selecting suppliers: Align supply chain strategy with product characteristics regarding supply and demand uncertainty, select supplier performance metrics from the comprehensive bank of metrics presented in this thesis related to the supply chain strategy, evaluate suppliers based on the selected performance metrics using the decision making framework Analytic Hierarchy Process (AHP). By following the suggested process step by step, incorporating performance metrics to the AHP structure, high-tech start-up firms will be able to find strategically suitable suppliers to manufacture their products. Key-words: Analytic Hierarchy Process, supplier performance metrics, supplier selection, supply chain strategy. Utvärdering av leverantörer för högteknologiska nystartsföretag En fallstudie av en brandrobot BENJAMIN LÖFDAHL BIRGER SJÖDIN Examensarbete Stockholm, Sverige 2013 Utvärdering av leverantörer för högteknologiska nystartsföretag En fallstudie av en brandrobot
Feasibility Study of Fan-Out Wafer-Level Packaging for Heterogeneous Integrations

The design, materials, process, and fabrication of a heterogeneous integration of 4 chips by a FOWLP (fan-out wafer-level packaging) with chip-first and dies face-down method are investigated in this study. Emphasis is placed on the application of a new assembly process and materials for fabricating the RDLs (redistribution layers) of the heterogeneous integration. The size of the reconstituted wafer is 300mm. The epoxy molding compound (EMC) is a dry-film material and is molded by lamination method. The minimum metal line width and spacing of the RDLs is 5µm.
Tightly coupled Visual Inertial Odometry based on Artificial Landmarks

Motion planning and control of mobile robots rely on high-accuracy estimation of pose and velocity. Many researchers use motion capture system to estimate the robot state, but this system is usually expensive and can only be used indoor. For this reason, this paper proposes an artificial landmarks based cost-effective visual inertial odometry system where Iterative Extended Kalman Filter (IEKF) acts as the back-end optimizer. Since most tags used as artificial landmarks like bar code facing the problem of decoding the information during the detection, we redesign the tag which can simplify the deployment and improve the detection efficiency. The proposed IEKF filter framework makes the measurement of the fisheye monocular camera and the IMU combined to co-estimate the pose of robot, the location of detected corners in tag and the IMU bias. Additionally, on-line calibration of the IMU bias and the extrinsic parameters between IMU and camera can be done during the robot motion. By running our algorithm real-time on unmanned aerial vehicle (UAV) and comparing with the groundtruth data obtained from the Optitrack motion capture system, our algorithm can provide high-precision estimation of the pose and velocity of UAV.
Dual C-X-Band E-Shaped Microstrip Antenna Array 1×8 for Synthetic Aperture Radar on UAV

Unmanned Aerial Vehicle (UAV) is one of the platforms which can support Synthetic Aperture Radar (SAR) to detect a target in C and X band. The technology is relatively cheap and can be operated in any weather condition. However, limited ability of UAV for carrying payload leads researcher to build SAR device as small and light as possible including the sensor, in this term is the antenna. In this research, a dual-band microstrip antenna array $\mathbf{1}\times \mathbf{8}$ at C-band (5.8 GHz) and X-band (9.65 GHz) has been designed and manufactured on FR-4 substrate. E-Shaped patch has been implemented in this antenna to achieve dual response frequency. The antenna element has been arranged into array elements to get higher gain. Both frequencies are used for dual modes SAR system which is able to obtain more data collection. The antenna has been designed with total dimension is $\mathbf{22}\ \mathbf{cm}\ \times \mathbf{5}$ cm, The experiment shows that the antenna has bandwidth more than 50 MHz for each band. The gain achieve 6.39 dBi at C-band and 3.825 dBi at X-band.
A Comparative Study on Feature Selection Based Improvement of Medium-Term Demand Forecast Accuracy

Use of the proper demand forecasting method and data set is very important for reliable system operation and planning. In this study, we compare performances of various feature selection methodforecasting algorithm pairs in terms of forecast accuracy for medium-term demand forecasting case. We utilize correlation, recursive feature elimination, random forest, multivariate adaptive regression splines (MARS), stepwise regression and genetic algorithms as feature selection methods. As for forecasting algorithms, we use linear and non-linear methods such as multiple linear regression (MLR), generalized additive model (GAM), MARS, k-nearest neighbors (KNN), classification and regression trees (CART), neural networks (NN) and support vector machines (SVM) methods. In the end, the MARS and stepwise regression as feature selection methods, and MARS model as the forecasting algorithm are found to be showing superior performance. However, with a suitable feature selection technique such as stepwise regression, linear models can yield satisfactory level of performance considering their low computation requirement.
Simulation and Experimental Validations of EM/TM/SM Physical Reliability for Interconnects Utilized in Stretchable and Foldable Electronics

There are many portable electronic products made by fan-out wafer/panel level package (FOWLP/FOPLP). The redistribution layer(RDL) design with fine pitch to connect inter each application is used. However, the above packaging products usually face the issue of electromigration (EM). Hence, a finite-element-based simulation method to predict the EM/ thermomigration (TM)/ stressmigration (SM) physical reliability and experimental validation are proposed. In this research, the EM simulation method also considers other physical behaviors including stress and temperature effects for future applications such as stretchable and foldable electric products.
A 24.2-30.5GHz Quad-Channel RFIC for 5G Communications including Built-In Test Equipment

A wideband quad-channel beamforming RFIC for worldwide 5G infrastructure applications in 130nm SiGe BiCMOS features an Rx single channel gain and NF of 22 and 4dB respectively at a total power consumption of 1.6W. Tx performance includes a P1dB of 18dBm CW and 11.5dBm RMS output power at 3% EVM and 1.8W total power consumption. Beamforming is based on a temperature invariant lumped true time delay and a phase invariant programmable gain amplifier. Integrated built-in test equipment including LO-generation, signal injection and detection enables low-cost RF production testing and array calibration.
Findings of the WMT 2019 Shared Tasks on Quality Estimation

We report the results of the WMT19 shared task on Quality Estimation, i.e. the task of predicting the quality of the output of machine translation systems given just the source text and the hypothesis translations. The task includes estimation at three granularity levels: word, sentence and document. A novel addition is evaluating sentence-level QE against human judgments: in other words, designing MT metrics that do not need a reference translation. This year we include three language pairs, produced solely by neural machine translation systems. Participating teams from eleven institutions submitted a variety of systems to different task variants and language pairs.
Filling the Gap With Sand: When CMOS reaches THz

Terahertz (THz) radiation ranging from 300 GHz to 10 THz [1] has attracted a growing number of researchers over the past decade. They are enthusiastic about its great potential for biomedical diagnoses, security screening, and highspeed communication. For instance, a THz wave can propagate through dry, nonmetallic, and nonpolar materials with small attenuation. This ability, combined with its small wavelength (versus microwave) and photon energy (versus X-ray), makes a THz wave an ideal option for nonionizing medicalimaging, such as a burn injury assessment [2] or skin cancer diagnosis [3]. A short-range wireless link operating at such an unallocated band is also expected to significantly boost transmission speeds. In [4], a 25-Gb/s link with a 220-GHz carrier was demonstrated over a distance of 50 cm. A higher data rate of 100 Gb/s is anticipated in the near future [5].
Classification of Electrocardiogram Signal Using Support Vector Machine Based on Fractal Extraction by FD

ECG analysis is a major research interest in biomedical signal processing because of the rapid growth in cardiac health care activities all over the world. The rapid progress in computer technology plays an important role in detecting various stages of disease from bio-signals. The assessment process of this technology is more accurate and reliable in clinical therapy. In this paper a method of analysis (ECG) signals using fractal features and support vector machine (SVM) technique has been proposed and some practical experiments have been done to verify this method and it provides a satisfying electronic diagnose paragon for cardiac heart disease so that it can be used by a specialist doctor to diagnose various types of cardiac diseases with an average accuracy of 89.33%. Matter of fact that ECG signals indicate a fractal prototype, it has been tried to discover the fractal dimension (FD) of the ECG time series in a feature extraction phase. Concurrently the Power Spectrum Method (PSM) has been implemented to four kinds of abnormal and normal waveforms. Here PSM can detect abnormal and normal waveforms and all ECG signals has been acquired from the Massachusetts Institute of Technology (BIH) arrhythmia database. Finally, multi-SVM classifier has been constructed and fed by a vector of an ECG signals. The obtained results using SVM classifier confirm the superiority of this classifier for identifying cardiac arrhythmia as compared to conventional one which is analyses of ECG signals based on morphology features and three ECG temporal features, i.e., the complex duration of QRS, the interval between RR and the average interval of RR over last ten beats.