bluuebunny/crossref_metadata_2025 huggingface dataset:
Crystal Growth in Gels from the Mechanisms of Crystal Growth to Control of Polymorphism: New Trends on Theoretical and Experimental Aspects
Authors: Velásquez-González Omar , Campos-Escamilla Camila , Flores-Ibarra Andrea , Esturau-Escofet Nuria , Arreguin-Espinosa Roberto , Stojanoff Vivian , Cuéllar-Cruz Mayra , Moreno Abel
Published: August 2019

A gel can be considered to be a two-phase (liquid and solid) system, which lacks flow once it reaches a stationary state. The solid phase is usually a tridimensional polymeric mesh, while the liquid phase is usually found in three forms: contained in great cavities, retained in the capillary pores between micelles, or adsorbed on the surface of a micelle. The influence of the use of gels in crystal growth is diverse and depends on the type of gel being used. A decrease in solubility of any solute in the liquid may occur if the solvent interacts extensively with the polymeric section, hence, the nucleation in gels in these cases apparently occurs at relatively low supersaturations. However, if the pore size is small enough, there is a possibility that a higher supersaturation is needed, due to the compartmentalization of solvents. Finally, this may also represent an effect in the diffusion of substances. This review is divided into three main parts; the first evaluates the theory and practice used for the obtainment of polymorphs. The second part describes the use of gels into crystallogenesis of different substances. The last part is related to the particularities of protein crystal polymorphism, as well as modern trends in gel growth for high-resolution X-ray crystallography.
Total-Evidence Framework Reveals Complex Morphological Evolution in Nightbirds (Strisores)
Authors: Chen Albert , White Noor D. , Benson Roger B.J. , Braun Michael J. , Field Daniel J.
Published: August 2019

Strisores is a clade of neoavian birds that include diurnal aerial specialists such as swifts and hummingbirds, as well as several predominantly nocturnal lineages such as nightjars and potoos. Despite the use of genome-scale molecular datasets, the phylogenetic interrelationships among major strisorean groups remain controversial. Given the availability of next-generation sequence data for Strisores and the clade’s rich fossil record, we reassessed the phylogeny of Strisores by incorporating a large-scale sequence dataset with anatomical data from living and fossil strisoreans within a Bayesian total-evidence framework. Combined analyses of molecular and morphological data resulted in a phylogenetic topology for Strisores that is congruent with the findings of two recent molecular phylogenomic studies, supporting nightjars (Caprimulgidae) as the extant sister group of the remainder of Strisores. This total-evidence framework allowed us to identify morphological synapomorphies for strisorean clades previously recovered using molecular-only datasets. However, a combined analysis of molecular and morphological data highlighted strong signal conflict between sequence and anatomical data in Strisores. Furthermore, simultaneous analysis of molecular and morphological data recovered differing placements for some fossil taxa compared with analyses of morphological data under a molecular scaffold, highlighting the importance of analytical decisions when conducting morphological phylogenetic analyses of taxa with molecular phylogenetic data. We suggest that multiple strisorean lineages have experienced convergent evolution across the skeleton, obfuscating the phylogenetic position of certain fossils, and that many distinctive specializations of strisorean subclades were acquired early in their evolutionary history. Despite this apparent complexity in the evolutionary history of Strisores, our results provide fossil support for aerial foraging as the ancestral ecological strategy of Strisores, as implied by recent phylogenetic topologies derived from molecular data.
A Multireference-Based Whole Genome Assembly for the Obligate Ant-Following Antbird, Rhegmatorhina melanosticta (Thamnophilidae)
Authors: Coelho Laís , Musher Lukas , Cracraft Joel
Published: August 2019

Current generation high-throughput sequencing technology has facilitated the generation of more genomic-scale data than ever before, thus greatly improving our understanding of avian biology across a range of disciplines. Recent developments in linked-read sequencing (Chromium 10×) and reference-based whole-genome assembly offer an exciting prospect of more accessible chromosome-level genome sequencing in the near future. We sequenced and assembled a genome of the Hairy-crested Antbird (Rhegmatorhina melanosticta), which represents the first publicly available genome for any antbird (Thamnophilidae). Our objectives were to (1) assemble scaffolds to chromosome level based on multiple reference genomes, and report on differences relative to other genomes, (2) assess genome completeness and compare content to other related genomes, and (3) assess the suitability of linked-read sequencing technology for future studies in comparative phylogenomics and population genomics studies. Our R. melanosticta assembly was both highly contiguous (de novo scaffold N50 = 3.3 Mb, reference based N50 = 53.3 Mb) and relatively complete (contained close to 90% of evolutionarily conserved single-copy avian genes and known tetrapod ultraconserved elements). The high contiguity and completeness of this assembly enabled the genome to be successfully mapped to the chromosome level, which uncovered a consistent structural difference between R. melanosticta and other avian genomes. Our results are consistent with the observation that avian genomes are structurally conserved. Additionally, our results demonstrate the utility of linked-read sequencing for non-model genomics. Finally, we demonstrate the value of our R. melanosticta genome for future researchers by mapping reduced representation sequencing data, and by accurately reconstructing the phylogenetic relationships among a sample of thamnophilid species.
NILMPEds: A Performance Evaluation Dataset for Event Detection Algorithms in Non-Intrusive Load Monitoring
Authors: Pereira Lucas
Published: August 2019

Datasets are important for researchers to build models and test how these perform, as well as to reproduce research experiments from others. This data paper presents the NILM Performance Evaluation dataset (NILMPEds), which is aimed primarily at research reproducibility in the field of Non-intrusive load monitoring. This initial release of NILMPEds is dedicated to event detection algorithms and is comprised of ground-truth data for four test datasets, the specification of 47,950 event detection models, the power events returned by each model in the four test datasets, and the performance of each individual model according to 31 performance metrics.
Preoperative MRI Parameters Predict Urinary Continence after Robot-Assisted Laparoscopic Prostatectomy in Prostatic Cancer Patients
Authors: Fukui Shinji , Kagebayashi Yoriaki , Iemura Yusuke , Matsumura Yoshiaki , Samma Shoji
Published: August 2019

We aimed to investigate whether preoperative MRI findings could predict the bladder neck location on postoperative cystography and recovery of urinary incontinence after robot-assisted laparoscopic radical prostatectomy (RALP). We retrospectively reviewed 270 consecutive patients who had complete preoperative data, including MRI, and underwent postoperative observation for more than three months. Preoperative MRI parameters consisted of the membranous urethral length (MUL) and pubic symphysis-prostate apex length (PAL) on sagittal images. The bladder neck location on a postoperative cystography was defined as the lowest extension of the tapering contrast medium in the bladder, and its relation to the pubic symphysis (above (higher group) and below (lower group) the middle of the pubic symphysis height) was evaluated. Those who required no pad or a safety pad were defined as being continent. PAL was significantly shorter in the higher group than that in the lower group (25.5 vs. 29.1 mm; p < 0.0001). The continent group at three months had a significantly longer MUL and shorter PAL than those in the incontinent group (8.1 vs. 6.7 mm; p < 0.05, and 26.0 vs. 28.1 mm; p < 0.05, respectively). Preoperative MRI parameters could predict the bladder neck location on postoperative cystograms and the recovery of urinary incontinence after RALP.
Diagnostic Performance of a Support Vector Machine for Dermatofluoroscopic Melanoma Recognition: The Results of the Retrospective Clinical Study on 214 Pigmented Skin Lesions
Authors: Szyc Łukasz , Hillen Uwe , Scharlach Constantin , Kauer Friederike , Garbe Claus
Published: August 2019

The need for diagnosing malignant melanoma in its earliest stages results in an increasing number of unnecessary excisions. Objective criteria beyond the visual inspection are needed to distinguish between benign and malignant melanocytic tumors in vivo. Fluorescence spectra collected during the prospective, multicenter observational study (“FLIMMA”) were retrospectively analyzed by the newly developed machine learning algorithm. The formalin-fixed paraffin-embedded (FFPE) tissue samples of 214 pigmented skin lesions (PSLs) from 144 patients were examined by two independent pathologists in addition to the first diagnosis from the FLIMMA study, resulting in three histopathological results per sample. The support vector machine classifier was trained on 17,918 fluorescence spectra from 49 lesions labeled as malignant (1) and benign (0) by three histopathologists. A scoring system that scales linearly with the number of the “malignant spectra” was designed to classify the lesion as malignant melanoma (score > 28) or non-melanoma (score ≤ 28). Finally, the scoring algorithm was validated on 165 lesions to ensure model prediction power and to estimate the diagnostic accuracy of dermatofluoroscopy in melanoma detection. The scoring algorithm revealed a sensitivity of 91.7% and a specificity of 83.0% in diagnosing malignant melanoma. Using additionally the image segmentation for normalization of lesions’ region of interest, a further improvement of sensitivity of 95.8% was achieved, with a corresponding specificity of 80.9%.
Identification of Leukemia Subtypes from Microscopic Images Using Convolutional Neural Network
Authors: Ahmed Nizar , Yigit Altug , Isik Zerrin , Alpkocak Adil
Published: August 2019

Leukemia is a fatal cancer and has two main types: Acute and chronic. Each type has two more subtypes: Lymphoid and myeloid. Hence, in total, there are four subtypes of leukemia. This study proposes a new approach for diagnosis of all subtypes of leukemia from microscopic blood cell images using convolutional neural networks (CNN), which requires a large training data set. Therefore, we also investigated the effects of data augmentation for an increasing number of training samples synthetically. We used two publicly available leukemia data sources: ALL-IDB and ASH Image Bank. Next, we applied seven different image transformation techniques as data augmentation. We designed a CNN architecture capable of recognizing all subtypes of leukemia. Besides, we also explored other well-known machine learning algorithms such as naive Bayes, support vector machine, k-nearest neighbor, and decision tree. To evaluate our approach, we set up a set of experiments and used 5-fold cross-validation. The results we obtained from experiments showed that our CNN model performance has 88.25% and 81.74% accuracy, in leukemia versus healthy and multi-class classification of all subtypes, respectively. Finally, we also showed that the CNN model has a better performance than other well-known machine learning algorithms.
Thermodynamics and Steady State of Quantum Motors and Pumps Far from Equilibrium
Authors: Bustos-Marún Raúl A. , Calvo Hernán L.
Published: August 2019

In this article, we briefly review the dynamical and thermodynamical aspects of different forms of quantum motors and quantum pumps. We then extend previous results to provide new theoretical tools for a systematic study of those phenomena at far-from-equilibrium conditions. We mainly focus on two key topics: (1) The steady-state regime of quantum motors and pumps, paying particular attention to the role of higher order terms in the nonadiabatic expansion of the current-induced forces. (2) The thermodynamical properties of such systems, emphasizing systematic ways of studying the relationship between different energy fluxes (charge and heat currents and mechanical power) passing through the system when beyond-first-order expansions are required. We derive a general order-by-order scheme based on energy conservation to rationalize how every order of the expansion of one form of energy flux is connected with the others. We use this approach to give a physical interpretation of the leading terms of the expansion. Finally, we illustrate the above-discussed topics in a double quantum dot within the Coulomb-blockade regime and capacitively coupled to a mechanical rotor. We find many exciting features of this system for arbitrary nonequilibrium conditions: a definite parity of the expansion coefficients with respect to the voltage or temperature biases; negative friction coefficients; and the fact that, under fixed parameters, the device can exhibit multiple steady states where it may operate as a quantum motor or as a quantum pump, depending on the initial conditions.
Dynamic Shannon Performance in a Multiobjective Particle Swarm Optimization
Authors: Pires E. J. Solteiro , Machado J. A. Tenreiro , Oliveira P. B. de Moura
Published: August 2019

Particle swarm optimization (PSO) is a search algorithm inspired by the collective behavior of flocking birds and fishes. This algorithm is widely adopted for solving optimization problems involving one objective. The evaluation of the PSO progress is usually measured by the fitness of the best particle and the average fitness of the particles. When several objectives are considered, the PSO may incorporate distinct strategies to preserve nondominated solutions along the iterations. The performance of the multiobjective PSO (MOPSO) is usually evaluated by considering the resulting swarm at the end of the algorithm. In this paper, two indices based on the Shannon entropy are presented, to study the swarm dynamic evolution during the MOPSO execution. The results show that both indices are useful for analyzing the diversity and convergence of multiobjective algorithms.
Quantum Adiabatic Pumping in Rashba- Dresselhaus-Aharonov-Bohm Interferometer
Authors: Tokura Yasuhiro
Published: August 2019

We investigate the quantum adiabatic pumping effect in an interferometer attached to two one-dimensional leads. The interferometer is subjected to an Aharonov-Bohm flux and Rashba-Dresselhaus spin-orbit interaction. Using Brouwer’s formula and rigorous scattering eigenstates, we obtained the general closed formula for the pumping Berry curvatures depending on spin for general interferometers when the external control parameters only modulate the scattering eigenstates and corresponding eigenvalues. In this situation, pumping effect is absent in the combination of the control parameters of Aharonov-Bohm flux and spin-orbit interaction strength. We have shown that finite pumping is possible by modulating both Rashba and Dresselhaus interaction strengths and explicitly demonstrated the spin-pumping effect in a diamond-shaped interferometer made of four sites.
The Effect of Compressible Flow on Heat Transfer Performance of Heat Exchanger by Computational Fluid Dynamics (CFD) Simulation
Authors: Yu Chao , Qin Sicheng , Chai Bosen , Huang Sen , Liu Yang
Published: August 2019

As a part of vehicle thermal management, water-cooled intercoolers play an important role in engine efficiency. The incompressible simulation model was usually applied to estimate the performance of water-cooled intercoolers. In this paper, the computational fluid dynamics (CFD) compressible model is taken to analyze more accurate prediction models. The rate of section change, heat exchange, and the surface friction coefficient are used as the comparison basis of the compressible flow model and incompressible model on the pressurized air side of the water-cooled intercooler. By comparing the simulation results of the air side, it was found that the compressible simulation is closer to the experimental value than the incompressible simulation. Compared with the experiment, the compressible model heat transfer maximum value of deviation is 6.5%, and the pressure loss maximum deviation is 7.5%. This provides guidance to optimize the design of heat exchangers, in order to save on costs and shorten development times.
Canonical Divergence for Flat α-Connections: Classical and Quantum
Authors: Felice Domenico , Ay Nihat
Published: August 2019

A recent canonical divergence, which is introduced on a smooth manifold M endowed with a general dualistic structure ( g , ∇ , ∇ * ) , is considered for flat α -connections. In the classical setting, we compute such a canonical divergence on the manifold of positive measures and prove that it coincides with the classical α -divergence. In the quantum framework, the recent canonical divergence is evaluated for the quantum α -connections on the manifold of all positive definite Hermitian operators. In this case as well, we obtain that the recent canonical divergence is the quantum α -divergence.
Cryogenic Cooling in Wireless Communications
Authors: Markiewicz Tomasz G. , Wesołowski Krzysztof W.
Published: August 2019

Improving the capacity and performance of communication systems is typically achieved by either using more bandwidth or enhancing the effective signal-to-noise ratio (SNR). Both approaches have led to the invention of various transmission techniques, such as forward error correction (FEC), multiple-input multiple-output (MIMO), non-orthogonal multiple access (NOMA), and many, many others. This paper, however, focuses on the idea that should be immediately apparent when looking at Shannon’s channel capacity formula, but that somehow remained less explored for decades, despite its (unfortunately only in theory) limitless potential. We investigate the idea of improving the performance of communication systems by means of cryogenic cooling of their RF front-ends; the technique, although widely-known and used in radio astronomy for weak signal detection, has attracted limited interest when applied to wireless communications. The obtained results, though mainly theoretical, are promising and lead to a substantial channel capacity increase, implying an increase in spectral efficiency, potential range extension, or decreasing the power emitted by mobile stations. We see its applications in base stations (BSs) of machine-type communication (MTC) and Internet of Things (IoT) systems.
Statistics of the Bifurcation in Quantum Measurement
Authors: Eriksson Karl-Erik , Lindgren Kristian
Published: August 2019

We model quantum measurement of a two-level system μ . Previous obstacles for understanding the measurement process are removed by basing the analysis of the interaction between μ and the measurement device on quantum field theory. This formulation shows how inverse processes take part in the interaction and introduce a non-linearity, necessary for the bifurcation of quantum measurement. A statistical analysis of the ensemble of initial states of the measurement device shows how microscopic details can influence the transition to a final state. We find that initial states that are efficient in leading to a transition to a final state result in either of the expected eigenstates for μ , with ensemble averages that are identical to the probabilities of the Born rule. Thus, the proposed scheme serves as a candidate mechanism for the quantum measurement process.
Reversible Data Hiding in JPEG Images Using Quantized DC
Authors: Kim Suah , Huang Fangjun , Kim Hyoung Joong
Published: August 2019

Reversible data hiding in JPEG images has become an important topic due to the prevalence and overwhelming support of the JPEG image format these days. Much of the existing work focuses on embedding using AC (quantized alternating current coefficients) to maximize the embedding capacity while minimizing the distortion and the file size increase. Traditionally, DC (quantized direct current coefficients) are not used for embedding, due to the assumption that the embedding in DCs cause more distortion than embedding in ACs. However, for data analytic which extracts fine details as a feature, distortion in ACs is not acceptable, because they represent the fine details of the image. In this paper, we propose a novel reversible data hiding method which efficiently embeds in the DC. The propose method uses a novel DC prediction method to decrease the entropy of the prediction error histogram. The embedded image has higher PSNR, embedding capacity, and smaller file size increase. Furthermore, proposed method preserves all the fine details of the image.
Hardware-Accelerated, Short-Term Processing Voice and Nonvoice Sound Recognitions for Electric Equipment Control
Authors: Tsai Wen-Chung , Shih You-Jyun , Huang Nien-Ting
Published: August 2019

We proposed and implemented a sound recognition system for electric equipment control. In recent years, industry 4.0 has propelled a rapid growth in intelligent human–machine interactions. User acoustic voice commands for machine control have been examined the most by researchers. The targeted machine can be controlled through voice without the use of any hand-held device. However, compared with human voice recognition, limited research has been conducted on nonhuman voice (e.g., mewing sounds) or nonvoice sound recognition (e.g., clapping). Processing of such short-term, biometric nonvoice sounds for electric equipment control requires a rapid response with correct recognition. In practice, this could lead to a trade-off between recognition accuracy and processing performance for conventional software-based implementations. Therefore, we realized a field-programmable gate array-based embedded system, such a hardware-accelerated platform, can enhance information processing performance using a dynamic time warping accelerator. Furthermore, information processing was refined for two specific applications (i.e., mewing sounds and clapping) to enhance system performance including recognition accuracy and execution speed. Performance analyses and demonstrations on real products were conducted to validate the proposed system.
Bouncer: A Resource-Aware Admission Control Scheme for Cloud Services
Authors: Abbasi Aaqif Afzaal , Al-qaness Mohammed A. A. , Elaziz Mohamed Abd , Khalil Hassan A. , Kim Sunghwan
Published: August 2019

Cloud computing is a paradigm that ensures the flexible, convenient and on-demand provisioning of a shared pool of configurable network and computing resources. Its services can be offered by either private or public infrastructures, depending on who owns the operational infrastructure. Much research has been conducted to improve a cloud’s resource provisioning techniques. Unfortunately, sometimes an abrupt increase in the demand for cloud services results in resource shortages affecting both providers and consumers. This uncertainty of resource demands by users can lead to catastrophic failures of cloud systems, thus reducing the number of accepted service requests. In this paper, we present Bouncer—a workload admission control scheme for cloud services. Bouncer works by ensuring that cloud services do not exceed the cloud infrastructure’s threshold capacity. By adopting an application-aware approach, we implemented Bouncer on software-defined network (SDN) infrastructure. Furthermore, we conduct an extensive study to evaluate our framework’s performance. Our evaluation shows that Bouncer significantly outperforms the conventional service admission control schemes, which are still state of the art.
Neural Network Control Design for an Unmanned Aerial Vehicle with a Suspended Payload
Authors: Luo Cai , Du Zhenpeng , Yu Leijian
Published: August 2019

Unmanned aerial vehicles (UAVs) demonstrate excellent manoeuvrability in cluttered environments, which makes them a suitable platform as a data collection and parcel delivering system. In this work, the attitude and position control challenges for a drone with a package connected by a wire is analysed. During the delivering task, it is very difficult to eliminate the external unpredictable disturbances. A robust neural network-based backstepping sliding mode control method is designed, which is capable of monitoring the drone’s flight path and desired attitude with a suspended cable attached. The convergence of the position and attitude errors together with the Lyapunov function are employed to attest to the robustness of the nonlinear transportation platform. The proposed control system is tested with a simulation and in an outdoor environment. The simulation and open field test results for the UAV transportation platform verify the controllers’ reliability.
Highly Sensitive Signal Processing Devices for Capacitive Transducers of Micromechanical Accelerometers
Authors: Ryndin Eugeny , Konoplev Boris , Lysenko Igor , Kulikova Irina , Popov Artyom
Published: August 2019

In this paper, the principles of the open-loop frequency-based signal processing devices for capacitive MEMS accelerometers are used to develop three CMOS IP-core (Intellectual Property core) projects of highly sensitive signal processing devices with frequency output. Signal processing devices designed in accordance with the considered method form an output of rectangular pulses whose frequencies equal a difference of signal frequencies from two identical generators with micromechanical accelerometer capacitive transducers in their frequency control circuits. First, the analog project scheme uses two harmonic LC oscillators and an analog mixer to form an output rectangular-shape differential-frequency signal, the frequency of which is dependent on the measured acceleration. Second, the digital project is fully scalable for various CMOS-technologies due to oscillators of rectangular pulses and a digital mixer. Third, the mixed-signal project combines the advantages of the analog and digital projects. The signal processing device projects were developed, modeled and compared to comprehensively solve the problems of increasing sensitivity, dynamic range, noise immunity and resistance to destabilizing factors (e.g., to temperature changes).
Specific Emitter Identification Using IMF-DNA with a Joint Feature Selection Algorithm
Authors: Wu Longwen , Zhao Yaqin , Feng Mengfei , Abdalla Fakheraldin Y. O. , Ullah Hikmat
Published: August 2019

Specific emitter identification (SEI) is a technique to distinguish among different emitters of the same type using weak individual characteristics instead of conventional modulation parameters. The biggest challenge in SEI is to not only distinguish the different emitters with close modulation parameters but also to identify a specific emitter when its modulation parameters change significantly. For this paper, individual differences in pulse envelopes were investigated and four types of pulse envelopes were modeled. To exploit the individual features along with the pulse envelope for the identification of a specific emitter, an intrinsic mode function distinct native attribute (IMF-DNA) feature extraction algorithm and a joint feature selection (JFS) algorithm were proposed, which together constitute the final proposed SEI technique. Compared with four other feature selection methods, the proposed feature selection algorithm performed better for finding the most useful features for classification, which greatly helps in the reduction of feature dimension. Compared with radio frequency DNA (RF-DNA), IMF-DNA had a far superior correct emitter identification rate under similar conditions. A real data verification method was developed to verify the performance of IMF-DNA for specific emitter identification. The method achieved a correct identification rate of 85.3% at a sampling rate of 200 MHz and had an estimated signal-to-noise ratio (SNR) of approximately 10 dB.
A Novel Authentication Protocol with Strong Security for Roaming Service in Global Mobile Networks
Authors: Liu Shanpeng , Li Xiong , Wu Fan , Liao Junguo , Wang Jin , Lin Dingbao
Published: August 2019

In today’s society, Global Mobile Networks (GLOMONETs) have become an important network infrastructure that provides seamless roaming service for mobile users when they leave their home network. Authentication is an essential mechanism for secure communication among the mobile user, home network, and foreign network in GLOMONET. Recently, Madhusudhan and Shashidhara presented a lightweight authentication protocol for roaming application in GLOMONET. However, we found their protocol not only has design flaws, but is also vulnerable to many attacks. To address these weaknesses, this paper proposes a novel authentication protocol with strong security for GLOMONET based on previous work. The fuzzy verifier technique makes the protocol free from smart card breach attack, while achieving the feature of local password change. Moreover, the computational intractability of the Discrete Logarithm Problem (DLP) guarantees the security of the session key. The security of the protocol is verified by the ProVerif tool. Compared with other related protocols, our protocol achieves a higher level of security at the expense of small increases in computational cost and communication cost. Therefore, it is more suitable for securing the roaming application in GLOMONET.
Distributed Ledger Technologies for Peer-to-Peer Local Markets in Distribution Networks
Authors: Troncia Matteo , Galici Marco , Mureddu Mario , Ghiani Emilio , Pilo Fabrizio
Published: August 2019

The newest Distributed Ledger Technology platforms, which delegate the execution of complex tasks in the form of Smart Contracts, make it possible to devise novel local electricity market frameworks, which are performed in a fully automated fashion. This paper proposes a novel fully automated platform for energy and ancillary service markets in distribution networks, able to run in a decentralized fashion, bypassing the need for a physical central authority. The proposed platform, able to perform the role of Virtual Decentralized Market Authority, shows excellent potential applications in the management of local ancillary service markets in local energy communities of various sizes. The proposed Virtual Decentralized Market Authority showed reasonable running costs and comparable technical management capabilities with respect to a physical, centralized managing authority.
Efficient Methods of Market Pricing in Power Industry within the Context of System Integration of Renewable Energy Sources
Authors: Lisin Evgeny , Kurdiukova Galina , Okley Pavel , Chernova Veronika
Published: August 2019

Currently, the majority of world economies (even those located in the sunbelt (+/− 35 degrees of latitude with good sunshine with low seasonality) uses various types of fossil fuels as the main source of energy for their economies. However, this represents a very volatile and unsustainable strategy, since according to various estimates, the fossil fuel era will inevitably end as all carbon fuels are going to be spent in the next few centuries. Unlike traditional energy, renewable energy sources (RES) are not based on energy resources, but rather rely upon natural energy flows. With regard to its unique property, there has been an active construction of power plants of renewable energy and their gradual integration into national energy supply systems in recent decades. At the same time, the existing models of electricity markets were unprepared for their wide distribution. Hence, determination of the market value of energy generated by power plants using renewable energy sources becomes a particularly significant issue. This market value has to take into account the prevention of costs from the use of fossil fuels, as well as the resulting environmental benefits. Our paper proposes methods for solving this problem, contributing to the increase of economic efficiency of investment projects for the construction of renewable energy facilities and the formation of economic incentives for their propagation in energy supply systems. The proposed methods are based on the dynamic differentiation of tariffs for consumers with renewable energy sources depending on their structure of electricity consumption. Its effectiveness is demonstrated by calculating the cost of electricity for households located in the Krasnodar region using renewable energy sources. It is shown that this approach to the formation of tariffs for consumers allows the household to receive additional savings from the efficient use of energy installations on RES and energy storage devices in terms of alignment of the energy consumption schedule. This creates a significant incentive for households to use them and contributes to increasing the effectiveness of government renewable energy support programs, including by solving the acute problem of raising electricity tariffs from the grid.
A Different Voltage-Source Power Inverter with Carrier Based SPWM for Open-End Connection Loads
Authors: Suroso  , Tri Nugroho Daru , Noguchi Toshihiko
Published: August 2019

This paper presents a new configuration of voltage source inverter with a simplified circuit for generating five-level pulse width modulation (PWM) voltage waveform. Compared with conventional inverter configuration, this circuit is drastically able to simplify the structure and reduce the required number of active switch components. The new inverter circuit is very suitable for the use of open-end connection loads such as open-end winding ac motor drive application. Instead of using separated dc power sources, the new inverter circuit configuration is also possible to utilize only one dc voltage source, so the power supply circuits can be made simpler. Furthermore, to reduce ripples of dc capacitor voltages, the voltage stabilizing circuit of capacitors at the input side was proposed and applied. The stabilizing circuit is capable to work reducing the size of dc capacitors, and maintaining voltage stability of capacitors through charging and discharging operation modes. The working principles of inverter circuit were evaluated and examined by means of computer simulations using PSIM software. In addition, experimental test results of the prototype were also provided. Test results proved that the new five-level PWM inverter operated well generating five-level output waveform with smaller distortion and less voltage ripples of dc capacitors.
On the Kaiser Effect of Rock under Cyclic Loading and Unloading Conditions: Insights from Acoustic Emission Monitoring
Authors: Meng Qingbin , Chen Yanlong , Zhang Mingwei , Han Lijun , Pu Hai , Liu Jiangfeng
Published: August 2019

The Kaiser effect reflects the memory of the loaded rock to the irreversible damage and deformation. The stress level, loading rate and lithology are the main factors affecting the Kaiser effect of the rock. To identify the accurate stress point of the Kaiser effect, the MTS 816 rock mechanics testing system and the DS5-A acoustic emission testing and analysis system were adopted. The uniaxial cyclic loading–unloading and acoustic emission characteristic test of 90 rock specimens from three types of rocks under different stress level and loading rate was carried out. The evolution of acoustic emission under uniaxial compression of the rock corresponds to the compaction stage, elastic stage, yield stage and post-peak stress drop stage of the rock deformation and failure process and is divided into the quiet period, transition period, active period and decay period of the acoustic emission. The larger the hardness of rock is, the earlier the stress point of the Kaiser effect appears. The loading stress level (σA) has appreciable influence on the Kaiser effect of the rock. When σA ≥ 0.7σc, the Kaiser effect disappears. Usually, the dilatancy stress (crack initiation stress) does not exceed 70% of the uniaxial compressive strength (σc) of the rock, and the stress point can be the threshold to determine whether the Kaiser effect occurs. The influence of loading rate (lr) on Felicity rate (FR) is relatively large when lr < 0.01 mm/s, and FR rapidly grows with increase of the loading rate. When lr ≥ 0.01 mm/s, the influence of the loading rate on FR is relatively small. The findings facilitate the future application of the Kaiser effect and improvement of the accuracy of the acoustic emission data interpretation.
Solving Scheduling Problem in a Distributed Manufacturing System Using a Discrete Fruit Fly Optimization Algorithm
Authors: Zhang Xiaohui , Liu Xinhua , Tang Shufeng , Królczyk Grzegorz , Li Zhixiong
Published: August 2019

This study attempts to optimize the scheduling decision to save production cost (e.g., energy consumption) in a distributed manufacturing environment that comprises multiple distributed factories and where each factory has one flow shop with blocking constraints. A new scheduling optimization model is developed based on a discrete fruit fly optimization algorithm (DFOA). In this new evolutionary optimization method, three heuristic methods were proposed to initialize the DFOA model with good quality and diversity. In the smell-based search phase of DFOA, four neighborhood structures according to factory reassignment and job sequencing adjustment were designed to help explore a larger solution space. Furthermore, two local search methods were incorporated into the framework of variable neighborhood descent (VND) to enhance exploitation. In the vision-based search phase, an effective update criterion was developed. Hence, the proposed DFOA has a large probability to find an optimal solution to the scheduling optimization problem. Experimental validation was performed to evaluate the effectiveness of the proposed initialization schemes, neighborhood strategy, and local search methods. Additionally, the proposed DFOA was compared with well-known heuristics and metaheuristics on small-scale and large-scale test instances. The analysis results demonstrate that the search and optimization ability of the proposed DFOA is superior to well-known algorithms on precision and convergence.
Evaluating the Environmental Impacts and Energy Performance of a Wind Farm System Utilizing the Life-Cycle Assessment Method: A Practical Case Study
Authors: Gomaa Mohamed R. , Rezk Hegazy , Mustafa Ramadan J. , Al-Dhaifallah Mujahed
Published: August 2019

The ever-increasing popularity of finding alternative forms of renewable energy has seen an increased interest and utilization of wind energy. The objective of this research therefore, is to evaluate the environmental impacts and energy performance of wind farms. This study was operationalized in Jordan using a life-cycle assessment (LCA) method. The environmental impact is evaluated through lifecycle emissions that include all emissions during various phases of the project. The energy performance is illustrated by the energy indicators. The latter is the energy payback ratio (EPR) and the energy payback time (EPT). This study was conducted on a 38 Vestas V112 3-MW wind turbine located in the southern region of Tafilah in Jordan that is host to the country’s first wind farm. SimaPro 7.1 software was used as the modeling platform. Data for this study were collated from various sources, including, manufacturers, the wind turbine farm, and local subcontractors. A software database was used for the modeling process, and the data obtained modeled in accordance with ISO 14040 standards. The findings of this study indicate that the impacts of the transportation and installation phases were moderate, with the largest negative environmental impact deriving from the manufacturing phase. To remedy some of the negative impacts in these phases, green cement was used for the turbine foundation to limit the environmental impacts to be had during the installation phase, while the transportation phase saw the utilization of locally-manufactured turbines. Furthermore, an evaluation of the study’s results revealed that the energy payback period of the wind farm is approximately 0.69 year (8 months), while the payback ratio is 29, and the annual CO2 saving estimated to be at 2.23 × 108 kg, 3.02 × 108 kg, 3.10 × 108 kg for an annual generated power of 371, 501, and 515 GWh/year.
Development of Global Optimization Algorithm for Series-Parallel PHEV Energy Management Strategy Based on Radau Pseudospectral Knotting Method
Authors: Zhao Kegang , Bei Jinghao , Liu Yanwei , Liang Zhihao
Published: August 2019

The powertrain model of the series-parallel plug-in hybrid electric vehicles (PHEVs) is more complicated, compared with series PHEVs and parallel PHEVs. Using the traditional dynamic programming (DP) algorithm or Pontryagin minimum principle (PMP) algorithm to solve the global-optimization-based energy management strategies of the series-parallel PHEVs is not ideal, as the solution time is too long or even impossible to solve. Chief engineers of hybrid system urgently require a handy tool to quickly solve global-optimization-based energy management strategies. Therefore, this paper proposed to use the Radau pseudospectral knotting method (RPKM) to solve the global-optimization-based energy management strategy of the series-parallel PHEVs to improve computational efficiency. Simulation results showed that compared with the DP algorithm, the global-optimization-based energy management strategy based on the RPKM improves the computational efficiency by 1806 times with a relative error of only 0.12%. On this basis, a bi-level nested component-sizing method combining the genetic algorithm and RPKM was developed. By applying the global-optimization-based energy management strategy based on RPKM to the actual development, the feasibility and superiority of RPKM applied to the global-optimization-based energy management strategy of the series-parallel PHEVs were further verified.
A Photovoltaic Greenhouse with Passive Variation in Shading by Fixed Horizontal PV Panels
Authors: Moretti Simona , Marucci Alvaro
Published: August 2019

The traditional shading systems that greenhouses use cause some of the solar radiation that is reflected or absorbed to be lost and, therefore, not used by the plants under cultivation. An interesting solution to these problems is to position photovoltaic (PV) panels on the roofs of greenhouses. All of the photovoltaic greenhouses that have been realized in Mediterranean areas are characterized by a fixed position of the PV panels and excessive shading, especially in autumn and winter. The purpose of this study is to describe a prototype of a photovoltaic greenhouse with both fixed and horizontal PV panels that exploit the natural variation in the elevation angle of the sun’s rays during the year to allow for “passive” variation in shading. The considerable variation in the elevation angle of the sun’s rays (from 24.4° to 71.1°) results in a high variation in shading (from 39.4% to 72.6%), with the highest values in the summer months and the lowest values in the winter months. This trend is favorable for meeting the photosynthetically active radiation (PAR) needs of greenhouse plants. If the plants under cultivation require more solar energy, it is necessary to increase the distance between the panels. We implement a specific mathematical relationship to define the precise distance to be assigned to the photovoltaic panels on the roof pitch.
Analyzing Scenarios for the Integration of Renewable Energy Sources in the Mexican Energy System—An Application of the Global Energy System Model (GENeSYS-MOD)
Authors: Sarmiento Luis , Burandt Thorsten , Löffler Konstantin , Oei Pao-Yu
Published: August 2019

This paper uses numerical techno-economic modelling to analyse the effect of current national renewable targets and climate goals on the cost and structural composition of the Mexican energy system. For this, we construct a scenario base analysis to compare current policies with two alternative states of the world—one without climate policies and one attaining full decarbonization. Furthermore, an additional iterative routine allows us to estimate the cost-optimal share of renewable technologies in the energy sector and the effect that deviating from this share has on total discounted system costs, emissions and the structure of the energy mix. In general, model results exhibit three key insights—(1) A marked dependence of the energy system on photovoltaics and natural gas; (2) The 2050 cost-optimal share of renewables for the production of electricity, transportation and industrial heating is respectively 75%, 90% and 5%; and (3) As national renewable targets for the power sector are lower than the cost-optimal share of renewables, equivalent to the shares in an scenario without climate policies and completely disconnected from national climate goals, these should be modified.
Optimization of Air Distribution to Reduce NOx Emission and Unburned Carbon for the Retrofit of a 500 MWe Tangential-Firing Coal Boiler
Authors: Jo Hyunbin , Kang Kiseop , Park Jongkeun , Ryu Changkook , Ahn Hyunsoo , Go Younggun
Published: August 2019

The use of separated overfire air (SOFA) has become a standard technique of air staging for NOx reduction in the coal-fired boiler and can also be applied to existing boilers by retrofit. This study was to optimize the air distribution for the proposed SOFA installation in a 500 MWe tangential-firing boiler that has 20 identical units in Korea. Using computational fluid dynamics (CFD) incorporating advanced coal combustion submodels, the reference case was established in good agreement with the design data, and different flow ratios of burner secondary air, close-coupled OFA (CCOFA), and SOFA were evaluated. Increasing the total OFA ratio effectively suppressed NO formation within the burner zone but had a negative impact on the boiler performance. With moderate air staging, NO reduction became active between the CCOFA and SOFA levels and, therefore, the OFA distribution could be optimized for the overall boiler performance. For total OFA ratios of 25% and 30% with respective burner zone stoichiometric ratios of 0.847 and 0.791, increasing the SOFA ratio to 15% and 20%, respectively, was ideal for decreasing the unburned carbon release and ash slagging as well as NO emission. Too high or low SOFA ratios rapidly increased the unburned carbon because of inefficient mixing between the strong air jets and char particles. Based on these ideal cases, the actual air distribution can be adjusted depending on the coal properties such as the ash slagging propensity.
Analysis of Subsynchronous Resonance Characteristics and Influence Factors in a Series Compensated Transmission System
Authors: He Chengbing , Sun Dakang , Song Lei , Ma Li
Published: August 2019

Series capacitor compensation is used to improve the utilization of existing power systems. Subsynchronous resonance (SSR) can be caused by series compensated lines, which would lead to turbogenerator shaft breakdown. A novel approach was presented in this paper to analyze the characteristics and influence factors of SSR in a series compensated transmission system. The system model of SSR, including the various modules of the electromechanical network, was established, and the eigenvalue results under 70% series compensation level were analyzed by eigenvalue analysis method for the the institute of electrical and electronics engineers (IEEE) first benchmark model (FBM). Compared with the results of the power systems computer-aided design (PSCAD) modeling and simulation, the effectiveness of eigenvalue analysis method was proven. After that, the eigenvalue analysis method was used to study, in detail, the effects of system series compensation levels, synchronous generator parameters, speed governing system parameters, and excitation system parameters on SSR characteristics. The research results show that the series compensation level has the greatest influence on the torsional mode damping of the system. The parameters of generator reactance, speed governing system, and excitation system have some effect on the torsional mode damping. The parameters of excitation system significantly affect the low-frequency oscillation damping.