bluuebunny/crossref_metadata_2025 huggingface dataset:
The Scholarly Evaluation of Ahadi’th Prescribed for Secondary School Certificate Part-I
Authors: Majid Dr. Muhammad , Bangash Dr. Arshad Khan
Published: January 2019

Islamic Studies is included as a compulsory subject in the Syllabi taught in Schools, Colleges and Universities of Pakistan. While preparing the prescribed courses intended for Islamic Studies (compulsory) special emphasis is placed on focusing the entire religion i.e Beliefs ,Worship, Ethics etc in the course. Translation and Tafsir of Qur’inic verses and Hadi’th is also made part of the curriculam. Along with the moderen education a student can also be informed about Islam , so that a young generation with a sound knowledge on all lines emerges from educational institutions to meet the future challenges. To achieve this goal great attention is paid to the preperation of the curricula by using experties in the field, but even then errors do ocure in the form of incorrect wording of the Ahadiths and inclusion of less authentic sayings of the holy prophet (SAW) which amounts to commiting a great sin by misguieding the youth regarding the factual position of the divine knowledge thus leaving the mind ill informed about their religion which might prove disastreous for the society in future as the young mind carries with him whatever he learns at school and his formative years. There is a great demand for judging the validity of the less authentic sayings of the holy prophet (SAW) and the need for passing them through research filters is being felt in the educational circles. The article under consideration here aims at probing into the details of the origin of the Ahadiths prescribed for the1st part of the Secondary School Certificate Course.

Keywords: Ahadi’th, Text Book, Matric, Mustadrak, Ibn e Maja
Exploring teacher–student communication in senior-education contexts in Taiwan: A communication accommodation approach
Authors: Chen Chin-Hui
Published: January 2019

This study investigated the language-accommodation strategies used by Taiwanese teachers when communicating with older adults in senior-education contexts. First, the interview phase identified various communication strategies and their underlying rationales; second, the survey phase verified the degree to which the identified communication strategies were used, as well as their associations with teachers’ age differences. The identified communication strategies were divided into four broad categories: secondary baby talk, mitigation of references to death or illness, politeness strategies and code selection (use of the dialect preferred by older students). The underlying considerations included older students’ perceived age-related physical or cognitive decrements, their social backgrounds and socio-psychological needs, as well as the teachers’ self-determined relational positioning or priority in the communication process. Young and middle-aged teachers were more likely to experience a deep-rooted conflict and power struggle arising from the fact that a teacher in Taiwan is traditionally endowed with greater power than his or her students, whereas younger people are expected to show respect to their elders. Hence, they frequently chose to address older students using forms that implied intergenerational relationships and to use code-switching to converge their own communication with their older students’ preferred dialects. Implications for older-adult education and possible directions for further research are discussed in the conclusion.
Comparative Environmental and Cost Analysis of Alternative Production Scenarios Associated with a Helicopter’s Canopy
Authors: Katsiropoulos Christos V. , Loukopoulos Andreas , Pantelakis Spiros G.
Published: January 2019

In the present work the carbon footprint and the financial viability of different materials, manufacturing scenarios, as well as recycling scenarios, associated with the production of aeronautical structural components are assessed. The materials considered were carbon fiber reinforced epoxy and carbon fiber reinforced PEEK (polyetheretherketone). The manufacturing techniques compared were the autoclave, resin transfer molding (RTM) and cold diaphragm forming (CDF). The recycling scenarios included mechanical recycling and pyrolysis. For this purpose, Life Cycle Analysis (LCA) and Life Cycle Costing (LCC) models were developed and implemented for the case of a helicopter’s canopy production. The results of the study pointed out that producing the canopy by using carbon fiber reinforced thermosetting composites and involving RTM as the manufacturing process is the optimal route both in terms of environmental and financial efficiency. The environmental and financial efficiency of the scenarios including thermoplastic composites as the material of choice is impaired from both the high embodied energy and raw material cost of PEEK. The scenarios investigated do not account for potential benefits arising from the recyclability and the improved reusability of thermoplastic matrices as compared to thermosetting ones. This underlines the need for a holistic aircraft structural optimization approach including not only performance and weight but also cost and environmental criteria.
Structural and Biochemical Insights into the Reactivity of Thioredoxin h1 from Chlamydomonas reinhardtii
Authors: Marchand Christophe H. , Fermani Simona , Rossi Jacopo , Gurrieri Libero , Tedesco Daniele , Henri Julien , Sparla Francesca , Trost Paolo , Lemaire Stéphane D. , Zaffagnini Mirko
Published: January 2019

Thioredoxins (TRXs) are major protein disulfide reductases of the cell. Their redox activity relies on a conserved Trp-Cys-(Gly/Pro)-Pro-Cys active site bearing two cysteine (Cys) residues that can be found either as free thiols (reduced TRXs) or linked together by a disulfide bond (oxidized TRXs) during the catalytic cycle. Their reactivity is crucial for TRX activity, and depends on the active site microenvironment. Here, we solved and compared the 3D structure of reduced and oxidized TRX h1 from Chlamydomonas reinhardtii (CrTRXh1). The three-dimensional structure was also determined for mutants of each active site Cys. Structural alignments of CrTRXh1 with other structurally solved plant TRXs showed a common spatial fold, despite the low sequence identity. Structural analyses of CrTRXh1 revealed that the protein adopts an identical conformation independently from its redox state. Treatment with iodoacetamide (IAM), a Cys alkylating agent, resulted in a rapid and pH-dependent inactivation of CrTRXh1. Starting from fully reduced CrTRXh1, we determined the acid dissociation constant (pKa) of each active site Cys by Matrix-assisted laser desorption/ionization-time of flight (MALDI-TOF) mass spectrometry analyses coupled to differential IAM-based alkylation. Based on the diversity of catalytic Cys deprotonation states, the mechanisms and structural features underlying disulfide redox activity are discussed.
Healthcare Workers Occupationally Exposed to Ionizing Radiation Exhibit Altered Levels of Inflammatory Cytokines and Redox Parameters
Authors: Ahmad Iman M. , Abdalla Maher Y. , Moore Tiffany A. , Bartenhagen Lisa , Case Adam J. , Zimmerman Matthew C.
Published: January 2019

Studies have shown an increased risk for a variety of cancers, specifically brain cancer, in healthcare workers occupationally exposed to ionizing radiation. Although the mechanisms mediating these phenomena are not fully understood, ionizing radiation-mediated elevated levels of reactive oxygen species (ROS), oxidative DNA damage, and immune modulation are likely involved. A group of 20 radiation exposed workers and 40 sex- and age-matched non-exposed control subjects were recruited for the study. We measured superoxide (O2•−) levels in whole blood of healthcare workers and all other measurements of cytokines, oxidative DNA damage, extracellular superoxide dismutase (EcSOD) activity and reduced/oxidized glutathione ratio (GSH/GSSG) in plasma. Levels of O2•− were significantly higher in radiation exposed workers compared to control. Similarly, a significant increase in the levels of interleukin (IL)-6, IL-1α and macrophage inflammatory protein (MIP)-1α in radiation exposed workers compared to control was observed, while there was no significance difference in the other 27 screened cytokines. A significant positive correlation was found between MIP-1α and O2•− levels with no correlation in either IL-6 or IL-1α. Further, a dose-dependent relationship with significant O2•− production and immune alterations in radiation exposed workers was demonstrated. There was no statistical difference between the groups in terms of oxidative DNA damage, GSH/GSSG levels, or EcSOD activity. Although the biologic significance of cytokines alterations in radiation exposed workers is unclear, further studies are needed for determining the underlying mechanism of their elevation.
Prototype System of Rocking-Chair Zn-Ion Battery Adopting Zinc Chevrel Phase Anode and Rhombohedral Zinc Hexacyanoferrate Cathode
Authors: Chae Munseok S. , Hong Seung-Tae
Published: January 2019

Zinc-ion batteries (ZIBs) have received attention as one type of multivalent-ion batteries due to their potential applications in large-scale energy storage systems. Here we report a prototype of rocking-chair ZIB system employing Zn2Mo6S8 (zinc Chevrel phase) as an anode operating at 0.35 V, and K0.02(H2O)0.22Zn2.94[Fe(CN)6]2 (rhombohedral zinc Prussian-blue analogue) as a cathode operating at 1.75 V (vs. Zn/Zn2+) in ZnSO4 aqueous electrolyte. This type of cell has a benefit due to its intrinsic zinc-dendrite-free nature. The cell is designed to be positive-limited with a capacity of 62.3 mAh g−1. The full-cell shows a reversible cycle with an average discharge cell voltage of ~1.40 V, demonstrating a successful rocking-chair zinc-ion battery system.
Doppler Radar-Based Non-Contact Health Monitoring for Obstructive Sleep Apnea Diagnosis: A Comprehensive Review
Authors: Tran Vinh Phuc , Al-Jumaily Adel Ali , Islam Syed Mohammed Shamsul
Published: January 2019

Today’s rapid growth of elderly populations and aging problems coupled with the prevalence of obstructive sleep apnea (OSA) and other health related issues have affected many aspects of society. This has led to high demands for a more robust healthcare monitoring, diagnosing and treatments facilities. In particular to Sleep Medicine, sleep has a key role to play in both physical and mental health. The quality and duration of sleep have a direct and significant impact on people’s learning, memory, metabolism, weight, safety, mood, cardio-vascular health, diseases, and immune system function. The gold-standard for OSA diagnosis is the overnight sleep monitoring system using polysomnography (PSG). However, despite the quality and reliability of the PSG system, it is not well suited for long-term continuous usage due to limited mobility as well as causing possible irritation, distress, and discomfort to patients during the monitoring process. These limitations have led to stronger demands for non-contact sleep monitoring systems. The aim of this paper is to provide a comprehensive review of the current state of non-contact Doppler radar sleep monitoring technology and provide an outline of current challenges and make recommendations on future research directions to practically realize and commercialize the technology for everyday usage.
α-Ketoglutaric Acid-Modified Carbonate Apatite Enhances Cellular Uptake and Cytotoxicity of a Raf-Kinase Inhibitor in Breast Cancer Cells through Inhibition of MAPK and PI-3 Kinase Pathways
Authors: Hossain Sultana Mehbuba , Shetty Jayalaxmi , Tha Kyi Kyi , Chowdhury Ezharul Hoque
Published: January 2019

AZ628 is a hydrophobic Raf-kinase inhibitor (rapidly accelerated fibrosarcoma) currently in clinical trial of various cancer. The physicochemical properties of hydrophobic drugs that affect the drug-particle interactions and cause aggregation of drugs and particles might be the key aspect to impede effective drug delivery. Retaining smaller particle size is the prerequisite to overcome the opsonization and improve cytotoxicity in the targeted region. Carbonate apatite (CA), an attractive biodegradable vector, has been used to carry both hydrophilic and hydrophobic drugs and release the payloads inside the cells following endocytosis. We incorporated AZ628 into CA and also modified it with α-ketoglutaric acid (α-KA) for reducing particle growth kinetics and increasing total surface area to improve the delivery of AZ628 by enhancing cellular uptake by breast cancer cells. AZ628-loaded nanoparticles of CA and α-KA-modified CA (α-KAMCA) were synthesized and evaluated in MCF-7 and 4T1 cell lines by measuring cytotoxicity and cellular uptake analysis. HPLC (high-performance liquid chromatography) assay was performed to quantify the binding affinity of the nanocarriers towards the drug. Western blot analysis was done to see the activation and expression levels of Akt, MAPK (mitogen-activated protein kinase) pathways and Caspase-3. Zetasizer was used to measure the particle size along with the surface charge. α-KAMCA showed almost 88% encapsulation efficacy for AZ628 with around 21% enhanced cellular uptake of the drug in two different breast cancer cell lines. These findings suggest that α-KAMCA could be a promising therapeutic tool to carry AZ628 for breast cancer treatment.
An Overview of the Recent Progress in the Synthesis and Applications of Carbon Nanotubes
Authors: Rahman Gul , Najaf Zainab , Mehmood Asad , Bilal Salma , Shah Anwar , Mian Shabeer , Ali Ghulam
Published: January 2019

Carbon nanotubes (CNTs) are known as nano-architectured allotropes of carbon, having graphene sheets that are wrapped forming a cylindrical shape. Rolling of graphene sheets in different ways makes CNTs either metals or narrow-band semiconductors. Over the years, researchers have devoted much attention to understanding the intriguing properties CNTs. They exhibit some unusual properties like a high degree of stiffness, a large length-to-diameter ratio, and exceptional resilience, and for this reason, they are used in a variety of applications. These properties can be manipulated by controlling the diameter, chirality, wall nature, and length of CNTs which are in turn, synthesis procedure-dependent. In this review article, various synthesis methods for the production of CNTs are thoroughly elaborated. Several characterization methods are also described in the paper. The applications of CNTs in various technologically important fields are discussed in detail. Finally, future prospects of CNTs are outlined in view of their commercial applications.
Chest Compressions in the Delivery Room
Authors: Garcia-Hidalgo Catalina , Schmölzer Georg M.
Published: January 2019

Annually, an estimated 13–26 million newborns need respiratory support and 2–3 million newborns need extensive resuscitation, defined as chest compression and 100% oxygen with or without epinephrine in the delivery room. Despite such care, there is a high incidence of mortality and neurologic morbidity. The poor prognosis associated with receiving chest compression alone or with medications in the delivery room raises questions as to whether improved cardiopulmonary resuscitation methods specifically tailored to the newborn could improve outcomes. This review discusses the current recommendations, mode of action, different compression to ventilation ratios, continuous chest compression with asynchronous ventilations, chest compression and sustained inflation optimal depth, and oxygen concentration during cardiopulmonary resuscitation.
Integrating Satellite and Ground Measurements for Predicting Locations of Extreme Urban Heat
Authors: Shandas Vivek , Voelkel Jackson , Williams Joseph , Hoffman Jeremy
Published: January 2019

The emergence of urban heat as a climate-induced health stressor is receiving increasing attention among researchers, practitioners, and climate educators. However, the measurement of urban heat poses several challenges with current methods leveraging either ground based, in situ observations, or satellite-derived surface temperatures estimated from land use emissivity. While both techniques contain inherent advantages and biases to predicting temperatures, their integration may offer an opportunity to improve the spatial resolution and global application of urban heat measurements. Using a combination of ground-based measurements, machine learning techniques, and spatial analysis, we addressed three research questions: (1) How much do ambient temperatures vary across time and space in a metropolitan region? (2) To what extent can the integration of ground-based measurements and satellite imagery help to predict temperatures? (3) What landscape features consistently amplify and temper heat? We applied our analysis to the cities of Baltimore, Maryland, and Richmond, Virginia, and the District of Columbia using geocomputational machine learning processes on data collected on days when maximum air temperatures were above the 90th percentile of historic averages. Our results suggest that the urban microclimate was highly variable across all of the cities—with differences of up to 10 °C between coolest and warmest locations at the same time—and that these air temperatures were primarily dependent on underlying landscape features. Additionally, we found that integrating satellite data with ground-based measures provided highly accurate and precise descriptions of temperatures in all three study regions. These results suggest that accurately identifying areas of extreme urban heat hazards for any region is possible through integrating ground-based temperature and satellite data.
Effects of Splat Interfaces, Monoclinic Phase and Grain Boundaries on the Thermal Conductivity of Plasma Sprayed Yttria-Stabilized Zirconia Coatings
Authors: Guo Xiaojie , Zhao Weiwei , Zeng Yi , Lin Chucheng , Zhang Jimei
Published: January 2019

Microstructure has a significant influence on the thermal conductivity of thermal barrier coating (TBC) systems. In this work, the microstructures including splat interface, monoclinic phase and grain boundaries in the YSZ air plasma spraying (APS) TBC systems are investigated. A finite element simulation model based on electron backscatter diffraction (EBSD) images is established. It is found that the simulation results of thermal conductivity are in good agreement with the experimental results. Using this model, the effect coefficient of splat interface, monoclinic phase and grain boundaries on thermal conductivity are calculated. Results show that the splat interface influences the thermal conductivity of the TBCs. Those results provide important guidance for reducing the thermal conductivity of thermal barrier coatings.
Sentiment Analysis of Lithuanian Texts Using Traditional and Deep Learning Approaches
Authors: Kapočiūtė-Dzikienė Jurgita , Damaševičius Robertas , Woźniak Marcin
Published: January 2019

We describe the sentiment analysis experiments that were performed on the Lithuanian Internet comment dataset using traditional machine learning (Naïve Bayes Multinomial—NBM and Support Vector Machine—SVM) and deep learning (Long Short-Term Memory—LSTM and Convolutional Neural Network—CNN) approaches. The traditional machine learning techniques were used with the features based on the lexical, morphological, and character information. The deep learning approaches were applied on the top of two types of word embeddings (Vord2Vec continuous bag-of-words with negative sampling and FastText). Both traditional and deep learning approaches had to solve the positive/negative/neutral sentiment classification task on the balanced and full dataset versions. The best deep learning results (reaching 0.706 of accuracy) were achieved on the full dataset with CNN applied on top of the FastText embeddings, replaced emoticons, and eliminated diacritics. The traditional machine learning approaches demonstrated the best performance (0.735 of accuracy) on the full dataset with the NBM method, replaced emoticons, restored diacritics, and lemma unigrams as features. Although traditional machine learning approaches were superior when compared to the deep learning methods; deep learning demonstrated good results when applied on the small datasets.
On the Impossibility of Learning the Missing Mass
Authors: Mossel Elchanan , Ohannessian Mesrob I.
Published: January 2019

This paper shows that one cannot learn the probability of rare events without imposing further structural assumptions. The event of interest is that of obtaining an outcome outside the coverage of an i.i.d. sample from a discrete distribution. The probability of this event is referred to as the “missing mass”. The impossibility result can then be stated as: the missing mass is not distribution-free learnable in relative error. The proof is semi-constructive and relies on a coupling argument using a dithered geometric distribution. Via a reduction, this impossibility also extends to both discrete and continuous tail estimation. These results formalize the folklore that in order to predict rare events without restrictive modeling, one necessarily needs distributions with “heavy tails”.
Trapezoidal Motion Profile to Suppress Residual Vibration of Flexible Object Moved by Robot
Authors: Yoon Hyun Joong , Chung Seong Youb , Kang Han Sol , Hwang Myun Joong
Published: January 2019

The residual vibration when a robot manipulator is operated at high speed needs to be suppressed. These vibrations are generated by the resonance of a flexible object being moved by the robot, and research on control algorithms and motion profiles is ongoing to reduce them. In this paper, we propose a method to reduce the residual vibration of an object moved by a robot manipulator by optimizing the acceleration/deceleration time calculated using the object’s natural frequency. The relationship between acceleration/deceleration time and the residual vibration in a trapezoidal velocity profile is considered by analyzing the scenario when the jerking motion characteristic of such vibrations occurs. The results of experiments using a commercial robot show that residual vibrations can be reduced by the proposed method without the need for an additional feedback control algorithm while transferring a flexible object over small and large distances.
Perturbed Point-to-Point Reaching Tasks in a 3D Environment Using a Portable Haptic Device
Authors: Scalona Emilia , Hayes Darren , Del Prete Zaccaria , Palermo Eduardo , Rossi Stefano
Published: January 2019

In this paper, we propose a new protocol, integrating Virtual Reality with the Novint Falcon, to evaluate motion performance during perturbed 3D reaching tasks. The protocol consists of six 3D point-to-point reaching tasks, performed using Falcon with six opposing force fields. Twenty subjects were enrolled in the study. During each task, subjects reached 80 targets and the protocol was repeated over three different days. The trajectories of the end-effector were recorded to calculate: duration of movement, length ratio, lateral deviation, aiming angle, speed metric, and normalized jerk. The coefficient of variation was calculated to study the intra-subject variability and the intra-class correlation coefficient to assess the reliability of the indices. Two-way repeated measurement ANOVA tests were performed for all indices in order to ascertain the effects of force and direction on the trajectories. Duration of movement, length ratio and speed metric have proven to be the most repeatable and reliable indices. Considering the force fields, subjects were able to optimize the trajectory in terms of duration and accuracy but not in terms of smoothness. Considering the directions, the best motor performance occurred when the trajectories were performed in the upper quadrant compared to those performed in the lower quadrant.
Low-Cost Portable Reader for Frequency Domain Chipless Tags: Architecture and Experimental Results on Depolarizing Tags
Authors: Boggioni Luca , Monti Lorenzo , Terranova Sergio , Costa Filippo , Genovesi Simone , Manara Giuliano
Published: January 2019

In this paper, a low-cost chipless reader for detecting depolarizing tags is described. The reader operates in the frequency band (2–2.5) GHz, and it is compact and integrated in a single board. The reader architecture and its transmitting and receiving antennas are presented. Reader antennas comprise of two orthogonally placed, E-shaped patches with a decoupling below −35 dB. The reader performance is evaluated on a four-bit tag formed by four obliquely placed dipoles on top of a metallic ground plane.
Design of Electroporation Process in Irregularly Shaped Multicellular Systems
Authors: Mescia Luciano , Chiapperino Michele Alessandro , Bia Pietro , Lamacchia Claudio Maria , Gielis Johan , Caratelli Diego
Published: January 2019

Electroporation technique is widely used in biotechnology and medicine for the transport of various molecules through the membranes of biological cells. Different mathematical models of electroporation have been proposed in the literature to study pore formation in plasma and nuclear membranes. These studies are mainly based on models using a single isolated cell with a canonical shape. In this work, a space–time (x,y,t) multiphysics model based on quasi-static Maxwell’s equations and nonlinear Smoluchowski’s equation has been developed to investigate the electroporation phenomenon induced by pulsed electric field in multicellular systems having irregularly shape. The dielectric dispersion of the cell compartments such as nuclear and plasmatic membranes, cytoplasm, nucleoplasm and external medium have been incorporated into the numerical algorithm, too. Moreover, the irregular cell shapes have been modeled by using the Gielis transformations.
A Multichannel FRA-Based Impedance Spectrometry Analyzer Based on a Low-Cost Multicore Microcontroller
Authors: Sanchez-Gonzalez Arturo , Medrano Nicolas , Calvo Belen , Martinez Pedro A.
Published: January 2019

Impedance spectrometry (IS) is a characterization technique in which a voltage or current signal is applied to a sample under test to measure its electrical behavior over a determined frequency range, obtaining its complex characteristic impedance. Frequency Response Analyzer (FRA) is an IS technique based on Phase Sensitive Detection (PSD) to extract the real and imaginary response of the sample at each input signal, which presents advantages compared to FFT-based (Fast Fourier Transform) algorithms in terms of complexity and speed. Parallelization of this technique has proven pivotal in multi-sample characterization, reducing the instrumentation size and speeding up analysis processes in, e.g., biotechnological or chemical applications. This work presents a multichannel FRA-based IS system developed on a low-cost multicore microcontroller platform which both generates the required excitation signals and acquires and processes the output sensor data with a minimum number of external passive components, providing accurate impedance measurements. With a suitable configuration, the use of this multicore solution allows characterizing several impedance samples in parallel, reducing the measurement time. In addition, the proposed architecture is easily scalable.
A Dynamic Bayesian Network for Vehicle Maneuver Prediction in Highway Driving Scenarios: Framework and Verification
Authors: Li Junxiang , Dai Bin , Li Xiaohui , Xu Xin , Liu Daxue
Published: January 2019

Accurate maneuver prediction for surrounding vehicles enables intelligent vehicles to make safe and socially compliant decisions in advance, thus improving the safety and comfort of the driving. The main contribution of this paper is proposing a practical, high-performance, and low-cost maneuver-prediction approach for intelligent vehicles. Our approach is based on a dynamic Bayesian network, which exploits multiple predictive features, namely, historical states of predicting vehicles, road structures, as well as traffic interactions for inferring the probability of each maneuver. The paper also presents algorithms of feature extraction for the network. Our approach is verified on real traffic data in large-scale publicly available datasets. The results show that our approach can recognize the lane-change maneuvers with an F1 score of 80% and an advanced prediction time of 3.75 s, which greatly improves the performance on prediction compared to other baseline approaches.
Improved ISRJ-Based Radar Target Echo Cancellation Using Frequency Shifting Modulation
Authors: Wu Qihua , Zhao Feng , Wang Junjie , Liu Xiaobin , Xiao Shunping
Published: January 2019

Target echo cancellation is an ingenious method that protects the target of interest (TOI) from being detected by radar. Interrupted-sampling repeater jamming (ISRJ) is a novel deception jamming method for linear frequency modulation (LFM) radar countermeasures, which has been applied in target echo cancellation recently. Compared with the conventional cancellation method, not only can the target echo be successfully cancelled at radar receiver, but a train of false targets is also produced and forms deception jamming by applying the ISRJ technique. In this paper, an improved radar target echo cancellation method based on ISRJ is proposed that utilizes an extra frequency shifting modulation on the intercepted LFM radar signal. The jammer power is more efficiently utilized by the proposed method. Moreover, more flexible multi-false-target deception jamming can be obtained by adjusting the interrupted sampling frequency. The real target remains effectively protected by the false preceding target in the presence of amplitude mismatch of cancellation signal and target echo. Numerical simulations and measured data experiments are conducted to demonstrate the effectiveness of the proposed method.
A Novel Multicomponent PSO Algorithm Applied in FDE–AJTF Decomposition
Authors: Yu Lei , Lao Guochao , Li Chunsheng , Sun Yang , Li Yingying
Published: January 2019

The echo of maneuvering targets can be expressed as a multicomponent polynomial phase signal (mc-PPS), which should be processed by time frequency analysis methods, while, as a modified maximum likelihood (ML) method, the frequency domain extraction-based adaptive joint time frequency (FDE–AJTF) decomposition method is an effective tool. However, the key procedure in the FDE–AJTF method is searching for the optimal parameters in the solution space, which is essentially a multidimensional optimization problem with different extremal solutions. To solve the problem, a novel multicomponent particle swarm optimization (mc-PSO) algorithm is presented and applied in the FDE–AJTF decomposition with the new characteristic that can extract several components simultaneously based on the feature of the standard PSO, in which the population is divided into three groups and the neighborhood of the best particle in the optimal group is set as the forbidden area for the suboptimal group, and then two different independent components can be obtained and extracted in one extraction. To analyze its performance, three simulation tests are carried out and compared with a standard PSO, genetic algorithm, and differential evolution algorithm. According to the tests, it is verified that the mc-PSO has the best performance in that the convergence, accuracy, and stability are improved, while its searching times and computation are reduced.
Numerical Study on the Effect of Tunnel Aspect Ratio on Evacuation with Unsteady Heat Release Rate Due to Fire in the Case of Two Vehicles
Authors: Park Younggi , Lee Youngman , Na Junyoung , Ryou Hong Sun
Published: January 2019

In this study, the characteristics of fires in case of two vehicles in a tunnel are analyzed by Computational Fluid Dynamics analysis for varying tunnel aspect ratios. Unsteady heat release rates over time are set as the input conditions of fire sources considering real phenomena. Unsteady heat release rate values are obtained from experiments. As a result, the smoke velocities above the fire source appear faster in the case of tunnels with a large aspect ratio because the higher the height of the tunnel, the faster the smoke velocity caused by buoyancy forces. The smoke velocity in the longitudinal direction increases quickly. However, the temperature distribution in the vicinity of the ceiling is low when the tunnel aspect ratio is large because the height of the tunnel is not directly affected by the flames. Also, the higher the height of the tunnel, the lower the visibility distance due to the heat and smoke coming down along the wall surface. However, in the tunnels represented in this study, it is considered that the visibility of evacuees is sufficiently secured.
Applications of a Strong Track Filter and LDA for On-Line Identification of a Switched Reluctance Machine Stator Inter-Turn Shorted-Circuit Fault
Authors: Xiao Li , Sun Hexu , Zhang Liyi , Niu Feng , Yu Lu , Ren Xuhe
Published: January 2019

Reliability is pivotal significance for switched reluctance machine drives (SRD) applied to safety essential transportation and industrial fields. An inter-turn shorted-circuit fault (ISCF) could incite the machine to operate in unbalanced status, resulting in the noise increases. In the event such a fault remains untreated, the fault will further destroy the rest of the normal phases, even leading to a tragic incident for the entire drive application. To improve the reliability of SRD, an efficient on-line fault diagnosis method for ISCF should be proposed. This paper is focused on employing the strong track filter (STF) to achieve real-time phase resistance differences between before and after ISCF, which are used as features to diagnose the fault occurrence and the fault phase. Furthermore, a classification namely as linear discriminant analysis (LDA) is selected to estimate fault severity. Finally, simulation and experiments correspond to various running statuses are executed and their results can verify that the diagnosis method has accuracy and robustness.
Development and Evaluation of a Degree of Hybridisation Identification Strategy for a Fuel Cell Supercapacitor Hybrid Bus
Authors: Wu Wei , Partridge Julius , Bucknall Richard
Published: January 2019

Fuel cells (FC) are a clean energy source that are capable of powering a vehicle’s electrical energy requirements whilst providing zero operating emissions. In this study, a full-scaled computer model FC/supercapacitor (SC) hybrid has been developed to investigate the performance of the hybrid propulsion system under real-world performance conditions. A control strategy focused on maintaining a constant FC output at a user-defined value has been developed and applied to the FC/SC hybrid model. Driving cycles collected from a practical double-decker bus have been utilised to evaluate the developed model. It has been demonstrated that the proposed control strategy is capable of maintaining a constant and stable FC output while meeting a real world dynamic load. Based on the obtained results, a general strategy to identify the degree of hybridisation between the FC and the SC in a FC hybrid system has been developed and demonstrated.
Improvement of Heat Dissipation Characteristics of Cu Bus-Bar in the Switchboards through Shape Modification and Surface Treatment
Authors: Kim Min-Jun , Bak Sang-Hwan , Jung Woo-Chul , Hur Deog-Jae , Ko Dong-Shin , Kong Man-Sik
Published: January 2019

In order to improve energy efficiency by increasing heat dissipation performance of bus-bar which distributes the current in high-power switchboard, the heat dissipation effects of the shape modification and surface treatment of Cu bus-bar were studied. The surface temperatures of the conventional plate-type bus-bar, and the improved tunnel-type bus-bar were compared by using electromagnetic and thermal analyses. The optimum thickness of tunnel-type bus-bar and the spacing and array among three bus-bars were calculated; and the surface temperature of tunnel-type bus-bar showed 7.9 °C lower than that of plate-type bus-bar in a 3-phase array condition. In addition, the surface and internal temperatures of the uncoated, CNT (Carbon nanotube)-coated, and BN (Boron nitride)-coated Cu bus-bars were measured with thermal imaging camera and the experiment using a hot plate. It was confirmed that the difference in the internal temperature between uncoated and BN-coated Cu was 19.4 °C. The application of the bus-bar improved from this study might contribute to the increase in power energy efficiency.
Multi-Step-Ahead Carbon Price Forecasting Based on Variational Mode Decomposition and Fast Multi-Output Relevance Vector Regression Optimized by the Multi-Objective Whale Optimization Algorithm
Authors: Xiong Shenghua , Wang Chunfeng , Fang Zhenming , Ma Dan
Published: January 2019

The accurate and stable forecasting of carbon prices is vital for governors to make policies and essential for market participants to make investment decisions, which is important for promoting the development of carbon markets and reducing carbon emissions in China. However, it is challenging to improve the carbon price forecasting accuracy due to its non-linearity and non-stationary characteristics, especially in multi-step-ahead forecasting. In this paper, a hybrid multi-step-ahead forecasting model based on variational mode decomposition (VMD), fast multi-output relevance vector regression (FMRVR), and the multi-objective whale optimization algorithm (MOWOA) is proposed. VMD is employed to extract the primary mode for the carbon price. Then, FMRVR, which is used as the forecasting module, is built on the preprocessed data. To achieve high accuracy and stability, the MOWOA is utilized to optimize the kernel parameter and input the lag of the FMRVR. The proposed hybrid forecasting model is applied to carbon price series from three major regional carbon emission exchanges in China. Results show that the proposed VMD-FMRVR-MOWOA model achieves better performance compared to several other multi-output models in terms of forecasting accuracy and stability. The proposed model can be a potential and effective technique for multi-step-ahead carbon price forecasting in China’s three major regional emission exchanges.
Single and Multi-Sequence Deep Learning Models for Short and Medium Term Electric Load Forecasting
Authors: Bouktif Salah , Fiaz Ali , Ouni Ali , Serhani Mohamed Adel
Published: January 2019

Time series analysis using long short term memory (LSTM) deep learning is a very attractive strategy to achieve accurate electric load forecasting. Although it outperforms most machine learning approaches, the LSTM forecasting model still reveals a lack of validity because it neglects several characteristics of the electric load exhibited by time series. In this work, we propose a load-forecasting model based on enhanced-LSTM that explicitly considers the periodicity characteristic of the electric load by using multiple sequences of inputs time lags. An autoregressive model is developed together with an autocorrelation function (ACF) to regress consumption and identify the most relevant time lags to feed the multi-sequence LSTM. Two variations of deep neural networks, LSTM and gated recurrent unit (GRU) are developed for both single and multi-sequence time-lagged features. These models are compared to each other and to a spectrum of data mining benchmark techniques including artificial neural networks (ANN), boosting, and bagging ensemble trees. France Metropolitan’s electricity consumption data is used to train and validate our models. The obtained results show that GRU- and LSTM-based deep learning model with multi-sequence time lags achieve higher performance than other alternatives including the single-sequence LSTM. It is demonstrated that the new models can capture critical characteristics of complex time series (i.e., periodicity) by encompassing past information from multiple timescale sequences. These models subsequently achieve predictions that are more accurate.
A Combined Study of TEM-EDS/XPS and Molecular Modeling on the Aging of THPP, ZPP, and BKNO3 Explosive Charges in PMDs under Accelerated Aging Conditions
Authors: Kim Kyung Min , Lee Junwoo , Choi Sung Il , Ahn Gil Hwan , Paik Jong Gyu , Ryu Byung Tae , Kim Yong Ha , Won Yong Sun
Published: January 2019

The aging mechanism of explosive charges in pyrotechnic mechanical devices (PMDs) is pre-oxidations of their fuels (TiH2 for THPP, Zr for ZPP, and B for BKNO3) by external oxygen. The effect of water on the aging of explosive charges was thus investigated by TEM-EDS/XPS and DFT-based molecular modeling under accelerated aging with 71 °C and 100% relative humidity. The formation of oxide shell and its thickness on the surface of fuels by the aging were observed by TEM-EDS. It failed to detect any oxide on the surface of TiH2 (no sign of Ti-O peaks in XPS) regardless of the aging time, while the thickness of oxide shell increases linearly with the time for ZPP and is saturated at a certain point for BKNO3. It suggested that THPP is highly robust to aging compared to the others (the order of THPP >> BKNO3 > ZPP). Then, DFT-based vacuum slab calculations visualized the diffusion of oxygen from the surface of fuels into the interior, confirming that the activation barrier for the oxygen diffusion is much lower for Zr and B than TiH2 (37, 107, and 512 kcal/mol for Zr, B, and TiH2, respectively), in agreement with experimental results.
Robust Design Optimization with Penalty Function for Electric Oil Pumps with BLDC Motors
Authors: Yoon Keun-Young , Baek Soo-Whang
Published: January 2019

In this paper, we propose and evaluate a robust design optimization (RDO) algorithm for the shape of a brushless DC (BLDC) motor used in an electric oil pump (EOP). The components of the EOP system and the control block diagram for driving the BLDC motor are described. Although the conventional deterministic design optimization (DDO) method derives an appropriate combination of design goals and target performance, DDO does not allow free searching of the entire design space because it is confined to preset experimental combinations of parameter levels. To solve this problem, we propose an efficient RDO method that improves the torque characteristics of BLDC motors by considering design variable uncertainties. The dimensions of the stator and the rotor were selected as the design variables for the optimal design and a penalty function was applied to address the disadvantages of the conventional Taguchi method. The optimal design results obtained through the proposed RDO algorithm were confirmed by finite element analysis, and the improvement in torque and output performance was confirmed through experimental dynamometer tests of a BLDC motor fabricated according to the optimization results.
A Holistic Review on Biomass Gasification Modified Equilibrium Models
Authors: Ferreira Sérgio , Monteiro Eliseu , Brito Paulo , Vilarinho Cândida
Published: January 2019

Biomass gasification is realized as a settled process to produce energy in a sustainable form, between all the biomass-based energy generation routes. Consequently, there are a renewed interest in biomass gasification promoting the research of different mathematical models to enlighten and comprehend gasification process complexities. This review is focused on the thermodynamic equilibrium models, which is the class of models that seems to be more developed. It is verified that the review articles available in the literature do not address non-stoichiometric methods, as well as an ambiguous categorization of stoichiometric and non-stoichiometric methods. Therefore, the main purpose of this article is to review the non-stoichiometric equilibrium models and categorize them, and review the different stoichiometric equilibrium model’s categorization available in the literature. The modeling procedures adopted for the different modeling categories are compared. Conclusion can be drawn that almost all equilibrium models are modified by the inclusion of empirical correction factors that improves the model prediction capabilities but with loss of generality.
Color Stabilization of Siberian and European Larch Wood Using UVA, HALS, and Nanoparticle Pretreatments
Authors: Oberhofnerová Eliška , Pánek Miloš , Podlena Milan , Pavelek Miloš , Štěrbová Irena
Published: January 2019

Reducing discoloration of wood due to photodegradation caused by ultraviolet (UV) and visible (VIS) radiation enhances its aesthetical value and prolongs the overall service life of protective coatings. In this study, the efficiency of pretreatments with different active ingredients to reduce degradation and stabilize the color of Siberian (Larix sibirica Ledeb.) and European larch (Larix decidua Mill) wood was investigated. UV absorbers (UVA), hindered amine light stabilizers (HALS) and zinc oxide nanoparticles were used in twenty different pretreatments. The ability to protect wood surface against radiation was evaluated via color and gloss change measurements during artificial ageing. The efficiency of tested color-stabilizing pretreatments differed for Siberian and European larch and not all of them reduced discoloration. The most effective pretreatments were based on a combination of UVA and HALS in a synergistic effect. Overall, the best efficiency from tested variants for larch wood generally was observed for combination of Eversorb 80 on benzotriazole basis + Eversorb 93 on a piperidinyl basis. The pretreatments did not significantly affect the gloss values. The results revealed convenient variants of stabilizers for Siberian and European larch wood and confirmed different compatibility between specific wood species and color stabilizers.
Effect of Various Pretreatment Methods on Bioethanol Production from Cotton Stalks
Authors: Dimos Konstantinos , Paschos Thomas , Louloudi Argiro , Kalogiannis Konstantinos G. , Lappas Angelos A. , Papayannakos Nikolaos , Kekos Dimitris , Mamma Diomi
Published: January 2019

Cotton stalks (CS) are considered a good candidate for fuel-ethanol production due to its abundance and high carbohydrate content, but the direct conversion without pretreatment always results in extremely low yields due to the recalcitrant nature of lignocelluloses. The present study was undertaken to investigate the effect of various chemical and physicochemical pretreatment methods, i.e., alkali, microwave-assisted acid, organosolv, hydrothermal treatment, and sequentially organosolv and hydrothermal pretreatment, on chemical composition of CS and subsequent ethanol production applying pre-hydrolysis and simultaneous saccharification and fermentation (PSSF) at high solid loading. The best results in terms of ethanol production were achieved by the sequential combination of organosolv and hydrothermal pretreatment (32.3 g/L, using 15% w/v substrate concentration and 6 h pre-hydrolysis) with an improvement of 32% to 50% in ethanol production compared to the other pretreatments. Extending pre-hydrolysis time to 14 h and increasing substrate concentration to 20% w/v, ethanol production reached 47.0 g/L (corresponding to an ethanol yield of 52%) after 30 h of fermentation.