bluuebunny/crossref_metadata_2025 huggingface dataset:
Ice-Crystal Nucleation in Water: Thermodynamic Driving Force and Surface Tension. Part I: Theoretical Foundation
Authors: Hellmuth Olaf , Schmelzer Jürn W. P. , Feistel Rainer
Published: January 2020

A recently developed thermodynamic theory for the determination of the driving force of crystallization and the crystal–melt surface tension is applied to the ice-water system employing the new Thermodynamic Equation of Seawater TEOS-10. The deviations of approximative formulations of the driving force and the surface tension from the exact reference properties are quantified, showing that the proposed simplifications are applicable for low to moderate undercooling and pressure differences to the respective equilibrium state of water. The TEOS-10-based predictions of the ice crystallization rate revealed pressure-induced deceleration of ice nucleation with an increasing pressure, and acceleration of ice nucleation by pressure decrease. This result is in, at least, qualitative agreement with laboratory experiments and computer simulations. Both the temperature and pressure dependencies of the ice-water surface tension were found to be in line with the le Chatelier–Braun principle, in that the surface tension decreases upon increasing degree of metastability of water (by decreasing temperature and pressure), which favors nucleation to move the system back to a stable state. The reason for this behavior is discussed. Finally, the Kauzmann temperature of the ice-water system was found to amount T K = 116 K , which is far below the temperature of homogeneous freezing. The Kauzmann pressure was found to amount to p K = − 212 MPa , suggesting favor of homogeneous freezing on exerting a negative pressure on the liquid. In terms of thermodynamic properties entering the theory, the reason for the negative Kauzmann pressure is the higher mass density of water in comparison to ice at the melting point.
Explanation of Experimentally Observed Phenomena in Hot Tokamak Plasmas from the Nonequilibrium Thermodynamics Position
Authors: Razumova Ksenia A. , Andreev Valerii F. , Kasyanova Nadezhda V. , Lysenko Sergey E.
Published: January 2020

In studying the hot plasma behavior in tokamak devices, the classical approach for collisional processes is traditionally used. This approach leaves unexplained a number of phenomena observed in experiments related to plasma energy confinement. Further, it is well known that tokamak plasma is always turbulent and self-organized. In the present paper, we show that the nonequilibrium thermodynamics approach allows us to explain many observed dependences and paradoxes; for example, puffing of impurities results in confinement improvement if zones of plasma cooling by impurities and additional plasma heating are not overlapped. The analysis of the experimental results shows the important role of radiation losses at the plasma edge in the processes determining its total energy confinement. It is shown that the generally accepted dependence of energy confinement on plasma density is not quite adequate because it is a consequence of dependence on radiation losses. The phenomenon of the appearance of internal transport barriers and magnetic islands can also be explained by plasma self-organization. The obtained results may be taken into account when calculating the operation of a future tokamak reactor.
Estimation of Dynamic Networks for High-Dimensional Nonstationary Time Series
Authors: Xu Mengyu , Chen Xiaohui , Wu Wei Biao
Published: January 2020

This paper is concerned with the estimation of time-varying networks for high-dimensional nonstationary time series. Two types of dynamic behaviors are considered: structural breaks (i.e., abrupt change points) and smooth changes. To simultaneously handle these two types of time-varying features, a two-step approach is proposed: multiple change point locations are first identified on the basis of comparing the difference between the localized averages on sample covariance matrices, and then graph supports are recovered on the basis of a kernelized time-varying constrained L 1 -minimization for inverse matrix estimation (CLIME) estimator on each segment. We derive the rates of convergence for estimating the change points and precision matrices under mild moment and dependence conditions. In particular, we show that this two-step approach is consistent in estimating the change points and the piecewise smooth precision matrix function, under a certain high-dimensional scaling limit. The method is applied to the analysis of network structure of the S&P 500 index between 2003 and 2008.
Representations and Concepts of Borders in Digital Strategy Games and Their Potential for Political Education in Geography Teaching
Authors: Seidel Sebastian , Bettinger Patrick , Budke Alexandra
Published: January 2020

In Germany, 93% of young people between the ages of 10 and 18 play video games daily. Political geography, in particular popular geopolitics, have found that video games can help to establish and develop people’s understanding of geopolitics. Consequently, this affects geography education, providing both challenges and opportunities for teaching. Geography teaching is an integral part of political education as students need to understand how boundaries and territories create spaces with regards to social power and become the object of political conflict. Reflection plays a central role in understanding and deconstructing such spatial constructions. In this article, we examine representations and concepts of borders in digital strategy games and the perception and reflection of these by the players. The results provide an outlook on the potential and the challenges of digital strategy games for political education in geography lessons in secondary schools as well as for teacher training at universities. For this reason, possible approaches for education and training will be outlined on the basis of the results.
Measuring Experiential Learning: An Approach Based on Lessons Learned Mapping
Authors: Bertoni Marco , Bertoni Alessandro
Published: January 2020

Fostering ‘experiential learning’ in real-life situations is a critical task for engineering educators when creating constructively aligned learning activities. The paper proposes an approach to measure the students’ perception of learning in Conceive-Design-Implement-Operate activities conducted outside the classroom. The approach is based on the opportunity of gathering and analyzing lessons learned from the student reflection reports at the end of a team-based innovation project performed in collaboration with company partners. The approach is intended to provide a basis for the future development of innovation projects with engineering students, supporting the definition of learning outcomes that are relevant for the CDIO Syllabus 2.0, and of constructively aligned learning experiences. The paper exemplifies the approach with regards to a master course named Value Innovation and presents the findings obtained at the third and second level of the CDIO Syllabus 2.0. The results of the course implementation show how short team-based innovation projects largely contributed in developing social and communication-related skills in engineering students, going beyond the mere application of their technical skills.
‘Nature Is Something We Can’t Replace’: Mexican Students’ Views of the Landscape They Want to Conserve
Authors: Yli-Panula Eija , Jeronen Eila , Rodriguez-Aflecht Gabriela
Published: January 2020

The primary aim of this qualitative study was to identify the landscapes that 7−12-year old Mexican students (n = 440) would like to conserve by analysing their drawings. Another aim was to determine the environmental relationship and environmental values of 5th and 6th graders (n = 152) by studying their texts. The data were analysed using mixed methods. In this study, landscape is understood as a visual experience of the environment, comprising the visible features of an area. Based on the results, all of the three main landscapes—nature, social and built—were deemed worth conserving. Beyond students’ immediate environment, the polar regions, North America, Australia and Africa were mentioned; Europe and Asia were not. The landscape drawings were realistic and carefully made, and the descriptions attached to them were clearly written. The environmental approach was mainly humanistic, and aesthetic values were appreciated by both genders. Utilitarian values were mentioned more often by boys than girls. The students’ descriptions reflected their environmental relationship, e.g., concern about nature, showing causal relationships, appreciation and affection. Concern or worry was often accompanied by the mention of human’s responsibility in the students’ texts, but they seldom considered their own activities in relation to the environment. The students depicted threats to nature, but they externalized themselves from the mechanisms threatening nature. In addition, they did not show familiarity with natural processes and scientific terminology. The study reveals that it is not only theoretically important to have distinct values, but these also need to be recognized by individuals. If the humans’ pro-environmental actions are to be promoted through education, it is important to study students’ values, as they may be important barriers to behavioral change. As students showed concern about preserving nature, teachers can discuss environmental values and different ways to take action and make changes with them, in order to avoid anxiety.
The Impacts of Different Sorts of Art Education on Pupils’ Preference for 20th-Century Art Movements
Authors: Kardum Goran , Kuščević Dubravka , Brajčić Marija
Published: January 2020

The research presented here aims to determine how art education influences students’ preferences for the 20th-century art movements. An educational experiment that spanned through one school year was conducted on 200 primary school students. It included three types of intervention: observing works of art from the 20th century, introducing works of art using a puppet, and the students’ art activities/artwork based on the 20th-century art movements. The results show that the model of art education is an important factor in changing students’ preferences for the 20th century art movements. Students reacted positively to each kind of education, as evidenced in the wider acceptance of 20th-century art (abstract, fauvism, cubism, pop art, and surrealism). The type of education did not influence preferences (as much) when it came to classical art and visual works without artistic value. We concluded that puppets and independent creative work should be used more often in art education.
A Novel Control Method of Clutch During Mode Transition of Single-Shaft Parallel Hybrid Electric Vehicles
Authors: Ding Jingang , Jiao Xiaohong
Published: January 2020

The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor starting engine and the clutch control problem have an important influence on driving quality, and solutions have a bit of room for improving dynamic performance. In this paper, a novel mode transition control method is proposed to guarantee a fast and smooth mode transition process in this regard. First, an adaptive sliding mode control (A-SMC) strategy is presented to obtain the desired torque trajectory of the clutch transmission. Second, a proportional-integral (PI) observer is designed to estimate the actual transmission torque of the clutch. Meanwhile, a fractional order proportional-integral-differential (FOPID) controller with the optimized control parameters by particle swarm optimization (PSO) is employed to realize the accurate position tracking of the direct current (DC) motor clutch so as to ensure clutch transmission torque tracking. Finally, the effectiveness and adaptability to system parameter perturbation of the proposed control approach are verified by comparison with the traditional control strategy in a MATLAB environment. The simulation results show that the driving quality of the closed-loop system using the proposed control approach is obviously improved due to fast and smooth mode transition process and better adaptability.
Imaging of the Internal Structure of Permafrost in the Tibetan Plateau Using Ground Penetrating Radar
Authors: Wang Yao , Fu Zhihong , Lu Xinglin , Qin Shanqiang , Wang Haowen , Wang Xiujuan
Published: January 2020

The distribution of the permafrost in the Tibetan Plateau has dramatically changed due to climate change, expressed as increasing permafrost degradation, thawing depth deepening and disappearance of island permafrost. These changes have serious impacts on the local ecological environment and the stability of engineering infrastructures. Ground penetrating radar (GPR) is used to detect permafrost active layer depth, the upper limit of permafrost and the thawing of permafrost with the season’s changes. Due to the influence of complex structure in the permafrost layer, it is difficult to effectively characterize the accurate structure within the permafrost on the radar profile. In order to get the high resolution GPR profile in the Tibetan Plateau, the reverse time migration (RTM) imaging method was applied to GPR real data. In this paper, RTM algorithm is proven to be correct through the groove’s model of forward modeling data. In the Beiluhe region, the imaging result of GPR RTM profiles show that the RTM of GPR makes use of diffracted energy to properly position the reflections caused by the gravels, pebbles, cobbles and small discontinuities. It can accurately determine the depth of the active layer bottom interface in the migration section. In order to prove the accuracy of interpretation results of real data RTM section, we set up the three dielectric constant models based on the real data RTM profiles and geological information, and obtained the model data RTM profiles, which can prove the accuracy of interpretation results of three-line RTM profiles. The results of three-line RTM bears great significance for the study of complex structure and freezing and thawing process of permafrost at the Beiluhe region on the Tibetan Plateau.
3-D Synapse Array Architecture Based on Charge-Trap Flash Memory for Neuromorphic Application
Authors: Choi Hyun-Seok , Park Yu Jeong , Lee Jong-Ho , Kim Yoon
Published: January 2020

In order to address a fundamental bottleneck of conventional digital computers, there is recently a tremendous upsurge of investigations on hardware-based neuromorphic systems. To emulate the functionalities of artificial neural networks, various synaptic devices and their 2-D cross-point array structures have been proposed. In our previous work, we proposed the 3-D synapse array architecture based on a charge-trap flash (CTF) memory. It has the advantages of high-density integration of 3-D stacking technology and excellent reliability characteristics of mature CTF device technology. This paper examines some issues of the 3-D synapse array architecture. Also, we propose an improved structure and programming method compared to the previous work. The synaptic characteristics of the proposed method are closely examined and validated through a technology computer-aided design (TCAD) device simulation and a system-level simulation for the pattern recognition task. The proposed technology will be the promising solution for high-performance and high-reliability of neuromorphic hardware systems.
Interference of Spread-Spectrum EMI and Digital Data Links under Narrowband Resonant Coupling
Authors: Crovetti Paolo , Musolino Francesco
Published: January 2020

In this paper, the effects of electromagnetic interference (EMI) coupled to a radio-frequency (RF) communication channel by resonant mechanisms are investigated and described in the framework of Shannon information theory in terms of an equivalent channel capacity loss so that to analyze and compare the effects of non-modulated and random Spread Spectrum (SS) modulated EMI. The analysis reveals a higher EMI-induced capacity loss for SS-modulated compared to non modulated EMI under practical values of the quality factor Q, while a modest improvement in the worst case capacity loss is observed only for impractical values of Q. Simulations on a 4-quadrature amplitude modulation (4-QAM) digital link featuring Turbo coding under EMI resonant coupling reveal that SS-modulated EMI gives rise to higher bit error rate (BER) at lower EMI power compared non-modulated EMI in the presence of resonant coupling for practical values of Q, thus suggesting a worse interfering potential of SS-modulated EMI.
Low-Frequency AC Power Transmission and Distribution for Subsea Application Using Hexverter
Authors: Safder Muhammad Umair , Rizvi Syed Tahir Hussain , Meng Yongqing , Javed Muhammad Yaqoob , Jaffery Mujtaba Hussain , Hassan Muhammad Sarmad
Published: January 2020

Environmental goals set by world leaders to normalize climate changes are quite difficult to achieve without renewable power generation and suitable transmission technologies like low-frequency AC transmission (LFAC). The LFAC is nowadays becoming a popular choice for long-distance power transmission due to its high efficiency and low losses. This research work investigates the feasibility of employing the LFAC system for subsea transmission and distribution of 58 MW power. In this paper, the simulation model of the LFAC-based subsea transmission and distribution system is presented. This model is composed of several parts such as hexverter as a frequency converter, where a novel control strategy to optimize its zero-sequence circulating current is employed. Detailed mathematical modeling based on active, reactive power constraints and DQ transformation is performed to achieve the control strategy for zero-sequence current optimization. An offshore wind farm is proposed to be integrated with the LFAC subsea system to fulfill the compatibility requirements of the system. The control system of both the grid side and the machine-side inverter of the wind farm is designed to eliminate the real-time disturbances such as wind speed fluctuations and harmonics due to heavy inductive load operating at 16 Hz. To drive the subsea pump, a vector control-based variable-speed drive is employed for the heavy induction motor. A 5 MW, 16 Hz RL load is also added in the model to analyze the effect of general-purpose load. Each component of this system is carefully designed to make it as close to real-time as possible. The whole system is designed for 16 Hz and is compared with the standard 50 Hz system to validate this design.
Reduced Active Components Count Electronically Adjustable Fractional-Order Controllers: Two Design Examples
Authors: Kapoulea Stavroula , Bizonis Vassilios , Bertsias Panagiotis , Psychalinos Costas , Elwakil Ahmed , Petráš Ivo
Published: January 2020

This paper deals with fractional-order controller implementations, which can be constructed by electronically controlled building blocks fully integrated on a single chip. The proposed DC motor controller structure offers 50% reduction of the active components count, compared to the corresponding already published counterpart. The proposed liquid level of the two-interacting-tank controller scheme is the first one in the literature offering the aforementioned features. Simulation results, based on the 0.35 μ m Austria Mikro Systeme technology process, confirm the correct operation of both proposed controllers.
Detecting and Localizing Anomalies in Container Clusters Using Markov Models
Authors: Samir Areeg , Pahl Claus
Published: January 2020

Detecting the location of performance anomalies in complex distributed systems is critical to ensuring the effective operation of a system, in particular, if short-lived container deployments are considered, adding challenges to anomaly detection and localization. In this paper, we present a framework for monitoring, detecting and localizing performance anomalies for container-based clusters using the hierarchical hidden Markov model (HHMM). The model aims at detecting and localizing the root cause of anomalies at runtime in order to maximize the system availability and performance. The model detects response time variations in containers and their hosting cluster nodes based on their resource utilization and tracks the root causes of variations. To evaluate the proposed framework, experiments were conducted for container orchestration, with different performance metrics being used. The results show that HHMMs are able to accurately detect and localize performance anomalies in a timely fashion.
Robust H∞ Design for Resonant Control in a CVCF Inverter Application over Load Uncertainties
Authors: Bueno-Contreras Holman , Ramos Germán Andrés , Costa-Castelló Ramon
Published: January 2020

CVCF (constant voltage, constant frequency) inverters are electronic devices used to supply AC loads from DC storage elements such as batteries or photovoltaic cells. These devices are used to feed different kinds of loads; this uncertainty requires that the controller fulfills robust stability conditions while keeping required performance. To address this, a robust H ∞ design is proposed based on resonant control to track a pure sinusoidal voltage signal and to reject the most common harmonic signals in a wide range of loads. The design is based on the definition of performance bounds in error signal and weighting functions for covering most uncertainty ranges in loads. Experimentally, the H ∞ controller achieves high-quality output voltage signal with a total harmonic distortion less than 2%.
Single Residential Load Forecasting Using Deep Learning and Image Encoding Techniques
Authors: Estebsari Abouzar , Rajabi Roozbeh
Published: January 2020

The integration of more renewable energy resources into distribution networks makes the operation of these systems more challenging compared to the traditional passive networks. This is mainly due to the intermittent behavior of most renewable resources such as solar and wind generation. There are many different solutions being developed to make systems flexible such as energy storage or demand response. In the context of demand response, a key factor is to estimate the amount of load over time properly to better manage the demand side. There are many different forecasting methods, but the most accurate solutions are mainly found for the prediction of aggregated loads at the substation or building levels. However, more effective demand response from the residential side requires prediction of energy consumption at every single household level. The accuracy of forecasting loads at this level is often lower with the existing methods as the volatility of single residential loads is very high. In this paper, we present a hybrid method based on time series image encoding techniques and a convolutional neural network. The results of the forecasting of a real residential customer using different encoding techniques are compared with some other existing forecasting methods including SVM, ANN, and CNN. Without CNN, the lowest mean absolute percentage of error (MAPE) for a 15 min forecast is above 20%, while with existing CNN, directly applied to time series, an MAPE of around 18% could be achieved. We find the best image encoding technique for time series, which could result in higher accuracy of forecasting using CNN, an MAPE of around 12%.
The Integrated Design of a Novel Secondary Control and Robust Optimal Energy Management for Photovoltaic-Storage System Considering Generation Uncertainty
Authors: Xu Shiyun , Sun Huadong , Zhao Bing , Yi Jun , Hayat Tasawar , Alsaedi Ahmed , Dou Chunxia , Zhang Bo
Published: January 2020

Due to the generation uncertainty of photovoltaic (PV) power generation, it has been posing great challenges and difficulties in maintaining the stability, security, and reliability of PV-storage systems (one kind of microgrid). To overcome these challenges and difficulties, this paper is concerned with secondary control and robust energy management for PVs in a grid-connected microgrid (MG) considering uncertainty. In our designs, to maintain the stable operation of PVs in MG, a novel secondary control method combining an event-triggered finite time sliding mode controller (FTSMC) and consensus controllers is proposed. Furthermore, a robust optimization framework is established to minimize the total cost of grid-connected MG involving the operation cost of multi-battery Energy Storage Systems (BESSes) and the electricity purchased from the main grid. To eliminate the effects of PV uncertainty, the optimization problem with uncertain constraints is converted into a new optimization problem with only deterministic constraints by using the box theory to represent the PV outputs. In other words, the robust optimization strategy makes uncertain boundaries easier to be represented by setting all uncertain parameters into an uncertain domain involving all typical extreme cases. Then, a particle swarm optimization (PSO) method is employed to solve the newly converted optimization problem. Finally, the experimental results validate the effectiveness of the proposed integrated framework.
Donor/Acceptor Heterojunction Organic Solar Cells
Authors: Cusumano Pasquale , Arnone Claudio , Giambra Marco Angelo , Parisi Antonino
Published: January 2020

The operation and the design of organic solar cells with donor/acceptor heterojunction structure and exciton blocking layer is outlined and results of their initial development and assessment are reported. Under halogen lamp illumination with 100 mW/cm2 incident optical power density, the devices exhibits an open circuit voltage VOC = 0.45 V, a short circuit current density JSC between 2 and 2.5 mA/cm2 with a fill factor FF ≈ 50%, an external quantum efficiency (electrons/s over incident photons/s) EQE ≈ 5% and a power conversion efficiency of about 0.5%. Measurements of the photoelectrical characteristics with time are also reported, confirming that non encapsulated organic solar cells have limited stability in ambient atmosphere.
4-Port MIMO Antenna with Defected Ground Structure for 5G Millimeter Wave Applications
Authors: Khalid Mahnoor , Iffat Naqvi Syeda , Hussain Niamat , Rahman MuhibUr , Fawad  , Mirjavadi Seyed Sajad , Khan Muhammad Jamil , Amin Yasar
Published: January 2020

We present a 4-port Multiple-Input-Multiple-Output (MIMO) antenna array operating in the mm-wave band for 5G applications. An identical two-element array excited by the feed network based on a T-junction power combiner/divider is introduced in the reported paper. The array elements are rectangular-shaped slotted patch antennas, while the ground plane is made defected with rectangular, circular, and a zigzag-shaped slotted structure to enhance the radiation characteristics of the antenna. To validate the performance, the MIMO structure is fabricated and measured. The simulated and measured results are in good coherence. The proposed structure can operate in a 25.5–29.6 GHz frequency band supporting the impending mm-wave 5G applications. Moreover, the peak gain attained for the operating frequency band is 8.3 dBi. Additionally, to obtain high isolation between antenna elements, the polarization diversity is employed between the adjacent radiators, resulting in a low Envelope Correlation Coefficient (ECC). Other MIMO performance metrics such as the Channel Capacity Loss (CCL), Mean Effective Gain (MEG), and Diversity gain (DG) of the proposed structure are analyzed, and the results indicate the suitability of the design as a potential contender for imminent mm-wave 5G MIMO applications.
Distributed Blockchain-Based Message Authentication Scheme for Connected Vehicles
Authors: Noh Jaewon , Jeon Sangil , Cho Sunghyun
Published: January 2020

Vehicular ad-hoc networks (VANETs) have several security issues such as privacy preservation, secure authentication, and system reliability. In the VANET, a vehicle communicates with other vehicles or infrastructures using broadcasting messages. These messages contain not only normal traffic information, but also identification information of sender. In general, the identification information remains encrypted to ensure privacy. However, the conventional centralized system can decrypt the identification information using private information of the sender vehicle. As a result, the central server can often be targeted by adversaries. We propose a message authentication scheme for anonymity and decentralization of information using blockchain technology. Here, we introduce public-private key and message authentication code (MAC) for secure authentication. In this paper, we adopt consensus algorithms for composing blockchain system such as the proof of work (PoW) and Practical Byzantine Fault Tolerance (PBFT) into the proposed authentication process. Finally, we demonstrate that the proposed method is secure from the attacks which include impersonation from internal attacker as well as typical attacks.
Modified Modulation Strategy of 1: 1: 2 Asymmetric Nine-Level Inverter and Its Power Balance Method
Authors: Ye Manyuan , Wei Qiwen , Ren Wei , Song Guizhi
Published: January 2020

The three unit nine-level inverter can output more voltage levels with fewer h-bridge units, while having better output waveform quality. However, in the conventional hybrid frequency modulation strategy, only one low-voltage unit adopts pulse width modulation (PWM), which causes the problem of switching loss and uneven heat distribution between the two low-voltage units. At the same time, the output power of the conventional modulation strategy is unbalanced. Aiming to resolve the above problems, a modified hybrid modulation strategy and a power balance control method under the strategy is proposed in this paper. The modulation strategy achieves output power balance between the three units and an even distribution of switching losses between the two low voltage units while maintaining the same output power quality. Simulation and experimental results verify the feasibility of the modulation strategy.
Low-Speed Performance Improvement of Direct Torque Control for Induction Motor Drives Fed by Three-Level NPC Inverter
Authors: Hakami Samer , Mohd Alsofyani Ibrahim , Lee Kyo-Beum
Published: January 2020

Classical direct torque control (DTC) is considered one of the simplest and fastest control algorithms in motor drives. However, it produces high torque and flux ripples due to the implementation of the three-level hysteresis torque regulator (HTR). Although, increasing the level of HTR and utilizing multilevel inverters has a great contribution in torque and flux ripples reduction, stator flux magnitude of induction motor (IM) droops at every switching sector transition, particularly at low-speed operation. This problem occurs due to the utilization of a zero voltage vector, where the domination of stator resistance is very high. A simple flux regulation strategy (SFRS) is applied for low-speed operation for DTC of IM. The proposed DTC-SFRS modifies the output status of the five-level HTR depending on the flux error, torque error, and stator flux position. This method regulates the stator flux for both forward and reverse rotational directions of IM with retaining the basic structure of classical DTC. By using the proposed algorithm, the stator flux is regulated, hence pure sinusoidal current waveform is achieved, which results in lower total harmonics distortion (THD). The effectiveness of the proposed DTC-SFRS is verified through simulation and experimental results.
Improvement of an Equivalent Circuit Model for Li-Ion Batteries Operating at Variable Discharge Conditions
Authors: Lozito Gabriele Maria , Lucaferri Valentina , Riganti Fulginei Francesco , Salvini Alessandro
Published: January 2020

A real time simulation of battery conditions is an essential step in the development of energy harvesting devices. Since it is not possible to have a direct measurement, the battery information, such as the remaining charge, need to be estimated by means of model-based estimation algorithms. Most of the existing models describing battery behaviour, are suitable only for a constant discharge current. This paper proposes a study of the dependence of the equivalent circuit model parameters on different discharge conditions. The model presented provides a powerful tool to represent the batteries’ behaviour in energy harvesting systems, involving continuous charge and discharge cycles. The extraction of parameters was performed, starting from a set of reference curves generated in Matlab Simulink environment, referring to Li-ion technology batteries. The parameters were extracted by means of a cascade of global and local search identification algorithms. Finally, the relations describing parameters’ behaviours as functions of the discharge current are presented.
LOCOFloat: A Low-Cost Floating-Point Format for FPGAs.: Application to HIL Simulators
Authors: Sanchez Alberto , de Castro Angel , Martínez-García Maria Sofía , Garrido Javier
Published: January 2020

One of the main decisions when making a digital design is which arithmetic is going to be used. The arithmetic determines the hardware resources needed and the latency of every operation. This is especially important in real-time applications like HIL (Hardware-in-the-loop), where a real-time simulation of a plant—power converter, mechanical system, or any other complex system—is accomplished. While a fixed-point gets optimal implementations, using considerably fewer resources and allowing smaller simulation steps, its use is very restricted to very specific applications, as its design effort is quite high. On the other side, IEEE-754 floating-point may have resolution problems in case of the 32-bit version, and excessive hardware usage in case of the 64-bit version. This paper presents LOCOFloat, a low-cost floating-point format designed for FPGA applications. Its key features are soft normalization of the results, using significand and exponent fields in two’s complement. This paper shows the implementation of addition, subtraction and multiplication of the proposed format. Both IEEE-754 versions and LOCOFloat are compared in this paper, implementing a HIL model of a buck converter. Although the application example is a HIL simulator, other applications could take benefit from the proposed format. Results show that LOCOFloat is as accurate as 64-bit floating-point, while reducing the use of DSPs blocks by 84 % .
A Study on Input Power Factor Compensation Capability of Matrix Converters
Authors: Nguyen Huu-Nhan , Nguyen Minh-Khai , Duong Truong-Duy , Tran Tan-Tai , Lim Young-Cheol , Choi Joon-Ho
Published: January 2020

In practice, the input filter is an important component in matrix converter (MC) systems for removing high harmonic components from input currents. Due to the input filter, the input power factor (IPF) at the main power supply does not always achieve unity. To investigate the behavior of the IPF, this paper analyzes the IPF compensation capacity of MCs with an LC input filter based on space vector theory and the conservation of energy law. The study shows that the range of voltage transfer ratio (VTR) to achieve unity IPF depends strongly on the quality factor, which is determined by the system parameters. If the quality factor is greater than 0.375, the MC can never achieve unity IPF for the whole range of VTR. If the quality factor is lower than 0.375, the MC can only achieve unity IPF for a certain range of VTR, except at a very low or very high VTR. Experimental results are provided to confirm the correctness of the study.
Design of an Intrinsically Safe Series-Series Compensation WPT System for Automotive LiDAR
Authors: Cardoso Luiz , Monteiro Vítor , Pinto José , Nogueira Miguel , Abreu Adérito , Afonso José , Afonso João
Published: January 2020

The earliest and simplest impedance compensation technique used in inductive wireless power transfer (WPT) design is the series-series (SS) compensation circuit, which uses capacitors in series with both primary and secondary coils of an air-gapped transformer. Despite of its simplicity at the resonant condition, this configuration exhibits a major sensitivity to variations of the load attached to the secondary, especially when higher coupling coefficients are used in the design. In the extreme situation that the secondary coil is left at open circuit, the current at the primary coil may increase above the safety limits for either the power converter driving the primary coil or the components in the primary circuit, including the coil itself. An approach often used to minimize this problem is detuning, but this also reduces the electrical efficiency of the power transfer. In low power, fixed-distance stationary WPT, a fair trade-off between efficiency and safety must be verified. This paper aims to consolidate a simple design procedure for such a SS-compensation, exemplifying its use in the prototype of a WPT system for automotive light detection and ranging (LiDAR) equipment. The guidelines herein provided should equally apply to other low power applications.
Estimation of Web Proxy Response Times in Community Networks Using Matrix Factorization Algorithms
Authors: Gómez-Sánchez Eduardo , Bores-Quijano Diego , Bote-Lorenzo Miguel L. , Meseguer-Pallarés Roc
Published: January 2020

In community networks, users access the web using a proxy selected from a list, normally without regard to its performance. Knowing which proxies offer good response times for each client would improve the user experience when navigating, but would involve intensive probing that would in turn cause performance degradation of both proxies and the network. This paper explores the feasibility of estimating the response times for each client/proxy pair by probing only a few of the existing pairs and then using matrix factorization. To do so, response times are collected in a community network emulated on a testbed platform, then a small part of these measurements are used to estimate the remaining ones through matrix factorization. Several algorithms are tested; one of them achieves estimation accuracy with low computational cost, which renders its use feasible in real networks.
Comparison of FPGA and Microcontroller Implementations of an Innovative Method for Error Magnitude Evaluation in Reed–Solomon Codes
Authors: Bianchi Valentina , Bassoli Marco , De Munari Ilaria
Published: January 2020

Reed–Solomon (RS) codes are one of the most used solutions for error correction logic in data communications. RS decoders are composed of several blocks: among them, many efforts have been made to optimize the error magnitude evaluation module. This paper aims to assess the performance of an innovative algorithm introduced in the literature by Lu et al. under different systems configurations and hardware platforms. Several configurations of the encoded message chosen between those typically used in different applications have been designed to be run on an FPGA (field programmable gate array) device and an MCU (microcontroller unit). The performances have been evaluated in terms of resource usage and output delay for the FPGA and in terms of code execution time for the MCU. As a benchmark in the analysis, the well-established Forney’s method is exploited: it has been implemented in the same configurations and on the same hardware platforms for a proper comparison. The results show that the theoretical finding are fully confirmed only in the MCU implementation, while on FPGA, the choice of one method with respect to the other depends on the optimization feature (i.e., time or area) that has been decided as a preference in the specific application.
Blockage Detection in Pipeline Based on the Extended Kalman Filter Observer
Authors: Jafari Raheleh , Razvarz Sina , Vargas-Jarillo Cristóbal , Gegov Alexander
Published: January 2020

Currently numerous approaches with various applicability have been generated in order to detect damage in pipe networks. Pipeline faults such as leaks and partial or complete blockages usually create serious problems for engineers. The model-based leak, as well as block detection methods for the pipeline systems gets more and more attention. Among these model-based methods, the state observer and state feedback based methods are usually used. While the observability, as well as controllability, are taken to be the prerequisites for utilizing these techniques. In this work, a new technique based on the extended Kalman filter observer is proposed in order to detect and locate the blockage in the pipeline. Furthermore, the analysis of observability and controllability in the pipe networks is investigated. Important theorems are given for testing the observability as well as controllability of the pipeline system.
A Blockchain-Based Smart Contract System for Healthcare Management
Authors: Khatoon Asma
Published: January 2020

Blockchain is evolving to be a secure and reliable platform for secure data sharing in application areas such as the financial sector, supply chain management, food industry, energy sector, internet of things and healthcare. In this paper, we review existing literature and applications available for the healthcare system using blockchain technology. Besides, this work also proposes multiple workflows involved in the healthcare ecosystem using blockchain technology for better data management. Different medical workflows have been designed and implemented using the ethereum blockchain platform which involves complex medical procedures like surgery and clinical trials. This also includes accessing and managing a large amount of medical data. Within the implementation of the workflows of the medical smart contract system for healthcare management, the associated cost has been estimated for this system in terms of a feasibility study which has been comprehensively presented in this paper. This work would facilitate multiple stakeholders who are involved within the medical system to deliver better healthcare services and optimize cost.
A Closed-Loop Optogenetic Stimulation Device
Authors: Edward Epsy S. , Kouzani Abbas Z.
Published: January 2020

Closed-loop optogenetic stimulation devices deliver optical stimulations based on real-time measurement and analysis of neural responses to stimulations. However, the use of large bench-top and tethered devices hinders the naturalistic test environment, which is crucial in pre-clinical neuroscience studies involving small rodent subjects. This paper presents a tetherless, lightweight and miniaturized head-mountable closed-loop optogenetic stimulation device. The device consists of three hardware modules: a hybrid electrode, an action potential detector, and an optogenetic stimulator. In addition, the device includes three software modules: a feature extractor, a control algorithm, and a pulse generator. The details of the design, implementation, and bench-testing of the device are presented. Furthermore, an in vitro test environment is formed using synthetic neural signals, wherein the device is validated for its closed-loop performance. During the in vitro validation, the device was able to identify abnormal neural signals, and trigger optical stimulation. On the other hand, it was able to also distinguish normal neural signals and inhibit optical stimulation. The overall power consumption of the device is 24 mW. The device measures 6 mm in radius and weighs 0.44 g excluding the power source.
Applications in Security and Evasions in Machine Learning: A Survey
Authors: Sagar Ramani , Jhaveri Rutvij , Borrego Carlos
Published: January 2020

In recent years, machine learning (ML) has become an important part to yield security and privacy in various applications. ML is used to address serious issues such as real-time attack detection, data leakage vulnerability assessments and many more. ML extensively supports the demanding requirements of the current scenario of security and privacy across a range of areas such as real-time decision-making, big data processing, reduced cycle time for learning, cost-efficiency and error-free processing. Therefore, in this paper, we review the state of the art approaches where ML is applicable more effectively to fulfill current real-world requirements in security. We examine different security applications’ perspectives where ML models play an essential role and compare, with different possible dimensions, their accuracy results. By analyzing ML algorithms in security application it provides a blueprint for an interdisciplinary research area. Even with the use of current sophisticated technology and tools, attackers can evade the ML models by committing adversarial attacks. Therefore, requirements rise to assess the vulnerability in the ML models to cope up with the adversarial attacks at the time of development. Accordingly, as a supplement to this point, we also analyze the different types of adversarial attacks on the ML models. To give proper visualization of security properties, we have represented the threat model and defense strategies against adversarial attack methods. Moreover, we illustrate the adversarial attacks based on the attackers’ knowledge about the model and addressed the point of the model at which possible attacks may be committed. Finally, we also investigate different types of properties of the adversarial attacks.
Modified Echo State Network Enabled Dynamic Duty Cycle for Optimal Opportunistic Routing in EH-WSNs
Authors: Rathore Rajkumar Singh , Sangwan Suman , Adhikari Kabita , Kharel Rupak
Published: January 2020

Minimizing energy consumption is one of the major challenges in wireless sensor networks (WSNs) due to the limited size of batteries and the resource constrained tiny sensor nodes. Energy harvesting in wireless sensor networks (EH-WSNs) is one of the promising solutions to minimize the energy consumption in wireless sensor networks for prolonging the overall network lifetime. However, static energy harvesting in individual sensor nodes is normally limited and unbalanced among the network nodes. In this context, this paper proposes a modified echo state network (MESN) based dynamic duty cycle with optimal opportunistic routing (OOR) for EH-WSNs. The proposed model is used to act as a predictor for finding the expected energy consumption of the next slot in dynamic duty cycle. The model has adapted a whale optimization algorithm (WOA) for optimally selecting the weights of the neurons in the reservoir layer of the echo state network towards minimizing energy consumption at each node as well as at the network level. The adapted WOA enabled energy harvesting model provides stable output from the MESN relying on optimal weight selection in the reservoir layer. The dynamic duty cycle is updated based on energy consumption and optimal threshold energy for transmission and reception at bit level. The proposed OOR scheme uses multiple energy centric parameters for selecting the relay set oriented forwarding paths for each neighbor nodes. The performance analysis of the proposed model in realistic environments attests the benefits in terms of energy centric metrics such as energy consumption, network lifetime, delay, packet delivery ratio and throughput as compared to the state-of-the-art-techniques.