bluuebunny/crossref_metadata_2025 huggingface dataset:
La competitividad de la economía analuza y sus sectores exportadores
Authors: Belda Álvarez José Ignacio
Published: November 2018

En un mundo cada vez más globalizado, el sector exterior tiene cada vez más importancia para las economías, y la andaluza no es una excepción.

Esta investigación se plantea como objetivo general conocer el comportamiento de las exportaciones andaluzas entre 2006 y 2013 según las bases en las que se asienta su evolución en el territorio y en relación a sus empresas. Para lograr este objetivo, se probó el comportamiento de las exportaciones de mercancías (capítulos arancelarios) andaluzas en términos absolutos y relativos respecto a la UE-28. A continuación, se trata de descubrir el comportamiento competitivo y / o dinámico de los sectores exportadores (capítulos arancelarios) aplicando la técnica shift - share, relacionando los resultados con la cuota de mercado, así como el grado de especialización exportadora de cada sector respecto a la UE-28. Por otro lado, se comprobó el papel desempeñado por las empresas en dicho proceso exportador.

Las principales averiguaciones indican que durante el periodo analizado las exportaciones andaluzas crecieron en términos absolutos y relativos. Este incremento fue posible gracias al proceso de internacionalización del sector empresarial andaluz que incluye un aumento importante del número de empresas exportadoras y de mercados. Y como última conclusión, este crecimiento se debe, sobre todo, al comportamiento de once sectores exportadores que fueron, a la vez de ser dinámicos y competitivos, sectores en los que Andalucía está especializada.
Fusiones en el sector financiero y crédito excesivo
Authors: Peón David , Antelo Manel
Published: November 2018

Se propone un modelo de competencia bancaria que incluye un sesgo de exceso de confianza por parte de algunos gestores. Dos son los principales resultados que se derivan del modelo. Primero, una fusión entre bancos racionales puede cambiar su comportamiento de manera que, tras la fusión, seguirían al banco sesgado en condiciones en las que no lo habrían hecho antes de la fusión, ampliando el volumen de crédito concedido por el mercado bancario. Segundo, los resultados obtenidos resuelven la paradoja de las fusiones, en el sentido de que la fusión sería rentable para los participantes y, por tanto, intrínsecamente estable..
Cash Ratio, Debt to Equity Ratio, Return on Equity, Firm Size dan Net Profit Margin Terhadap Dividen Per Share Perusahaan Consumer Goods Listing BEI Perioder 2011-2014
Authors: Saputra Alex , Walujadi Dedi , Amin Akhmad Bakhtiar
Published: November 2018

From the results of hypothesis testing via t test, showed that partial. there is a positive and significant influence Cash Ratio, Debt to Equity Ratio, Return on Equity, Firm Size and Margin Net Proft against Dividends Per Share. From the results of hypothesis testing through F test showed that simultant there is a positive and significant influence Cash Ratio, Debt to Equity Ratio, Return on Equity, Firm Size and Net Proft Margin against Dividends Per Share In this case, the net profit margin as the dominant predictor of positive and significant impact on Dividend Per Share. Because, the acquisition value of the slope or regression coefficient in the net profit margin is the highest value than Slop or regression coefficient on the Cash Ratio, Debt to Equity Ratio, Return on Equity and Firm Size.

 

 
Strategies for Providing Marketing Staff in Islamic Banks
Authors: Tanjung Hendri
Published: November 2018

Purpose of this paper is to find strategies for providing marketing staff in Islamic Banks. This paper contributes strategies aiming at the fulfillment of human resource of Islamic Banks in Indonesia and at the same time building curriculum for studying Islamic banking at undergraduate level. By using descriptive analysis on yearly statistical data of Islamic banks from 2005 to 2010, three figures obtained as estimation of the need of personnel in Islamic Banks at 2015.
SWOT analysis is performed to identify strength, weakness, opportunity and threat of Islamic Banks. As a result, to recruit the estimated number of Islamic Banking staff, three ways could be employed, i.e. early recruitment program which requires improvement of curriculum at universities, recruiting from conventional banks with some training as addition, and building a new institution called “Institut Bankir Syariah Indonesia”.
Target Costing Implementation Product Design and Product Process Conducted By Yamaha- Motor Kencana Indonesia (YMKI)
Authors: Yahya Johannes
Published: November 2018

The purpose of this study are to know target costing implementation in Yamaha- MotorKencanaIndonesia(YMKI),andevaluatethewayofcompanytomakeproductdesign and process in reaching the target costing after determining price and profit. The firm was success in implementing target costing, this can be seen by good Product functionality and market share achievement.
Product design and product process conducted by Yamaha-Motor Kencana Indonesia (YMKI) was able to sustain product quality, and not only could make stability in market share but olso have got wider market share. The way of company to make product design and process in reaching the target costing after determining price and profit is applying value engineering technique that is a cost reduction and process improvement technique that utulizes information collected about a product, design and process to indentify candidates for improvement efforts.
Gaya Kepemimpinan, Insentif Dan Lingkungan Kerja Terhadap Prestasi Kerja Pegawai Pada Dinas Pekerjaan Umum dan Penataan Ruang Kabupaten Bogor
Authors: Dora Lika
Published: November 2018

This study aims to examine and analyze the Influence of Leadership Style, Incentives and Work Environment on Job Performance in Department of Public Works and Spatial Planning of Bogor Regency. Data collection was done by distributing questionnaires and implemented for 118 employees. Data analysis in this research using SPSS version 24.

The results of this study explain that between leadership style, incentive and work environment have a significant influence on the performance of employees partially and simultaneously. For the variable that has the most dominant influence on the work performance is the style of leadership, so to obtain optimal employee performance hence leadership style factors, incentives and work environment needs to be improved.
Một phương pháp thiết kế ngữ nghĩa dạng tập mờ của từ ngôn ngữ dựa trên đại số gia tử mở rộng và ứng dụng xây dựng FRBS giải bài toán hồi qui
Authors: Dư Nguyễn Đức , Thông Hoàng Văn , Hồ Nguyễn Cát
Published: November 2018

Trong bài báo này, chúng tôi đề xuất một phương pháp thiết kế ngữ nghĩa dạng tập mờ bằng hàm S và đại số gia tử mở rộng cho các từ ngôn ngữ sử dụng trong các hệ dựa trên các luật mờ (FRBS). Áp dụng phương pháp thiết kế này, phương pháp sinh luật từ dữ liệu của C. H. Nguyen và cộng sự và thuật toán tiến hóa (2+2)M-PAES của Knowles và Corne, chúng tôi phát triển một thuật toán xây dựng các FRBS giải bài toán hồi qui. Kết quả thử nghiệm cho thấy thuật toán sinh ra các FRBS có độ chính xác cao hơn các thuật toán được đối sánh. DOI: 10.32913/rd-ict.vol2.no38.527
“Rapt with sweet pleasure”: The Rhetoric of Dance in Sir John Davies’ Orchestra or A Poem of Dancing
Authors: Hudler Melissa
Published: November 2018

This article examines the trope of dance in Orchestra or a Poem of Dancing, specifically the ways in which dance functions as a form of rhetoric and, ultimately, out-performs the seduction rhetoric of Antinous. Presented literally and metaphorically, dance as the subject of Antinous' rhetoric repels Penelope, while the image of dance that appears in Love's mirror enraptures her so strongly that she esteems the weaving and unweaving of bodies above her own weaving and unweaving of thread. This activity of chaste waiting is attended to also in metaphorical terms, as it provides a parallel with the ongoing weaving and simultaneous unweaving of Antinous' argument that Penelope should dance with him. The conclusion reached is that the verbal rhetoric of Antinous, while theoretically sound in its rhetorical characteristics and presentation, fails to sway Penelope. Ultimately, it is dance that proves the successful rhetor, as it performs eloquently and persuasively to move Penelope's mind toward accepting dance as a virtuous and noble activity, indeed moves her to be “rapt with sweet pleasure” at the sight of its measured oration. Framed in a delineation of the shared qualities of rhetoric and dance, this argument relies upon classical and Renaissance rhetoric and dance treatises, as well as the work of modern rhetoric, dance, and literature scholars.
Intimate Relations: Psychoanalysis Deconstruction / La psychanalyse la déconstruction
Authors: Rottenberg Elizabeth
Published: November 2018

This essay will concentrate, somewhat voyeuristically, on a particular and very special textual encounter. For if there is one text in the psychoanalytic tradition that will have caused Derrida to spill more ink than any other – it's Freud's Beyond the Pleasure Principle (1920). For ten years, from 1970–1980, Derrida returns not once but three times, on three separate occasions, in three different contexts, to Freud's text on repetition compulsion and the death drive, each time devoting more time and energy – that is to say, more pages – to it. As we will see in this essay, what emerges from this textual encounter is not only a new kind of pleasure; it is also a chance event of repetition that brings with it something strikingly new.
Measuring the Impact of Financial News and Social Media on Stock Market Modeling Using Time Series Mining Techniques
Authors: Kollintza-Kyriakoulia Foteini , Maragoudakis Manolis , Krithara Anastasia
Published: November 2018

In this work, we study the task of predicting the closing price of the following day of a stock, based on technical analysis, news articles and public opinions. The intuition of this study lies in the fact that technical analysis contains information about the event, but not the cause of the change, while data like news articles and public opinions may be interpreted as a cause. The paper uses time series analysis techniques such as Symbolic Aggregate Approximation (SAX) and Dynamic Time Warping (DTW) to study the existence of a relation between price data and textual information, either from news or social media. Pattern matching techniques from time series data are also incorporated, in order to experimentally validate potential correlations of price and textual information within given time periods. The ultimate goal is to create a forecasting model that exploits the previously discovered patterns in order to augment the forecasting accuracy. Results obtained from the experimental phase are promising. The performance of the classifier shows clear signs of improvement and robustness within the time periods where patterns between stock price and the textual information have been identified, compared to the periods where patterns did not exist.
Rapid Generation of Monoclonal Antibodies from Single B Cells by Ecobody Technology
Authors: Ojima-Kato Teruyo , Morishita Shiomi , Uchida Yoshino , Nagai Satomi , Kojima Takaaki , Nakano Hideo
Published: November 2018

Single B cell sampling following to direct gene amplification and transient expression in animal cells has been recognized as powerful monoclonal antibodies (mAbs) screening strategies. Here we report Ecobody technology which allows mAbs screening from single B cells in two days This technology uses Escherichia coli cell-free protein synthesis (CFPS) for mAb expression. In the CFPS step, we employed our original techniques: (1) ‘Zipbody’ as a modified Fab (fragment of antigen binding) format, in which the active Fab formation is facilitated by adhesive leucine zipper peptides fused at the C-termini of the light and heavy chains; and (2) an N-terminal SKIK peptide tag that can markedly increase protein production. By the Ecobody technology, we demonstrated rapid screening of antigen specific mAbs from immunized rabbits and Epstein-Barr Virus infected human B cells. We further obtained rabbit mAbs in E. coli expression system yielding to 8.5 mg of purified proteins from 1 L bacterial culture.
Isolation and Characterization of Nanobodies against a Zinc-Transporting P-Type ATPase
Authors: Longhin Elena , Grønberg Christina , Hu Qiaoxia , Duelli Annette Susanne , Andersen Kasper Røjkjær , Laursen Nick Stub , Gourdon Pontus
Published: November 2018

P-type ATPases form a large and ubiquitous superfamily of ion and lipid transporters that use ATP (adenosine triphosphate) to carry out their function. The IB subclass (PIB-ATPases) allows flux of heavy metals and are key players in metal detoxification, critical for human health, crops, and survival of pathogens. Nevertheless, PIB-ATPases remain poorly understood at a molecular level. In this study, nanobodies (Nbs) are selected against the zinc-transporting PIB-ATPase ZntA from Shigella sonnei (SsZntA), aiming at developing tools to assist the characterization of the structure and function of this class of transporters. We identify six different Nbs that bind detergent stabilized SsZntA. We further assess the effect of the Nbs on the catalytic function of SsZntA, and find that five nanobodies associate without affecting the function, while one nanobody significantly reduces the ATPase activity. This study paves the way for more refined mechanistical and structural studies of zinc-transporting PIB-ATPases.
First Description of Colistin and Tigecycline-Resistant Acinetobacter baumannii Producing KPC-3 Carbapenemase in Portugal
Authors: Caneiras Cátia , Calisto Filipa , Jorge da Silva Gabriela , Lito Luis , Melo-Cristino José , Duarte Aida
Published: November 2018

Herein, we describe a case report of carbapenem-resistant Acinetobacter baumannii and Klebsiella pneumoniae isolates that were identified from the same patient at a Tertiary University Hospital Centre in Portugal. Antimicrobial susceptibility and the molecular characterization of resistance and virulence determinants were performed. PCR screening identified the presence of the resistance genes blaKPC-3, blaTEM-1 and blaSHV-1 in both isolates. The KPC-3 K. pneumoniae isolate belonged to the ST-14 high risk clone and accumulated an uncommon resistance and virulence profile additional to a horizontal dissemination capacity. In conclusion, the molecular screening led to the first identification of the A. baumannii KPC-3 producer in Portugal with a full antimicrobial resistance profile including tigecycline and colistin.
Antioxidants and Second Messengers of Free Radicals
Authors: Zarkovic Neven
Published: November 2018

In the recent years, numerous research on the pathology of oxidative stress has been completed by intense studies on redox signaling implementing various experimental models and clinical trials. [...]
Using Neural Networks to Determine the Significance of Aggregate Characteristics Affecting the Mechanical Properties of Recycled Aggregate Concrete
Authors: Duan Zhenhua , Hou Shaodan , Poon Chi-Sun , Xiao Jianzhuang , Liu Yun
Published: November 2018

It has been proved that artificial neural networks (ANN) can be used to predict the compressive strength and elastic modulus of recycled aggregate concrete (RAC) made with recycled aggregates from different sources. This paper is a further study of the use of ANN to analyze the significance of each aggregate characteristic and determine the best combinations of factors that would affect the compressive strength and elastic modulus of RAC. The experiments were carried out with 46 mixes with several types of recycled aggregates. The experimental results were used to build ANN models for compressive strength and elastic modulus, respectively. Different combinations of factors were selected as input variables until the minimum error was reached. The results show that water absorption has the most important effect on aggregate characteristics, further affecting the compressive strength of RAC, and that combined factors including concrete mixes, curing age, specific gravity, water absorption and impurity content can reduce the prediction error of ANN to 5.43%. Moreover, for elastic modulus, water absorption and specific gravity are the most influential, and the network error with a combination of mixes, curing age, specific gravity and water absorption is only 3.89%.
Unsteady Stagnation-Point Flow and Heat Transfer Over a Permeable Exponential Stretching/Shrinking Sheet in Nanofluid with Slip Velocity Effect: A Stability Analysis
Authors: Dzulkifli Nor Fadhilah , Bachok Norfifah , Yacob Nor Azizah , Md Arifin Norihan , Rosali Haliza
Published: November 2018

A model of unsteady stagnation-point flow and heat transfer over a permeable exponential stretching/shrinking sheet with the presence of velocity slip is considered in this paper. The nanofluid model proposed by Tiwari and Das is applied where water with Prandtl number 6.2 has been chosen as the base fluid, while three different nanoparticles are taken into consideration, namely Copper, Alumina, and Titania. The ordinary differential equations are solved using boundary value problem with fourth order accuracy (bvp4c) program in Matlab to find the numerical solutions of the skin friction and heat transfer coefficients for different parameters such as stretching/shrinking, velocity slip, nanoparticle volume fraction, suction/injection, and also different nanoparticles, for which the obtained results (dual solutions) are presented graphically. The velocity and temperature profiles are presented to show that the far field boundary conditions are asymptotically fulfilled, and validate the findings of dual solutions as displayed in the variations of the skin friction and heat transfer coefficients. The last part is to perform the stability analysis to determine a stable and physically-realizable solution.
Sparse and Low-Rank Subspace Data Clustering with Manifold Regularization Learned by Local Linear Embedding
Authors: Yang Ye , Hu Yongli , Wu Fei
Published: November 2018

Data clustering is an important research topic in data mining and signal processing communications. In all the data clustering methods, the subspace spectral clustering methods based on self expression model, e.g., the Sparse Subspace Clustering (SSC) and the Low Rank Representation (LRR) methods, have attracted a lot of attention and shown good performance. The key step of SSC and LRR is to construct a proper affinity or similarity matrix of data for spectral clustering. Recently, Laplacian graph constraint was introduced into the basic SSC and LRR and obtained considerable improvement. However, the current graph construction methods do not well exploit and reveal the non-linear properties of the clustering data, which is common for high dimensional data. In this paper, we introduce the classic manifold learning method, the Local Linear Embedding (LLE), to learn the non-linear structure underlying the data and use the learned local geometry of manifold as a regularization for SSC and LRR, which results the proposed LLE-SSC and LLE-LRR clustering methods. Additionally, to solve the complex optimization problem involved in the proposed models, an efficient algorithm is also proposed. We test the proposed data clustering methods on several types of public databases. The experimental results show that our methods outperform typical subspace clustering methods with Laplacian graph constraint.
Orbital Angular Momentum Multiplexed Free-Space Optical Communication Systems Based on Coded Modulation
Authors: Qu Zhen , Djordjevic Ivan B.
Published: November 2018

In this paper, we experimentally investigate the turbulence mitigation methods in free-space optical communication systems based on orbital angular momentum (OAM) multiplexing. To study the outdoor atmospheric turbulence environment, we use an indoor turbulence emulator. Adaptive optics, channel coding, Huffman coding combined with low-density parity-check (LDPC) coding, and spatial offset are used for turbulence mitigation; while OAM multiplexing and wavelength-division multiplexing (WDM) are applied to boost channel capacity.
Extending Characters of Fixed Point Algebras
Authors: Wagner Stefan
Published: November 2018

A dynamical system is a triple ( A , G , α ) consisting of a unital locally convex algebra A, a topological group G, and a group homomorphism α : G → Aut ( A ) that induces a continuous action of G on A. Furthermore, a unital locally convex algebra A is called a continuous inverse algebra, or CIA for short, if its group of units A × is open in A and the inversion map ι : A × → A × , a ↦ a − 1 is continuous at 1 A . Given a dynamical system ( A , G , α ) with a complete commutative CIA A and a compact group G, we show that each character of the corresponding fixed point algebra can be extended to a character of A.
A Review of Performance Specifications and Studies of Trickle Vents
Authors: Biler Ahmet , Unlu Tavil Aslihan , Su Yuehong , Khan Naghman
Published: November 2018

The air quality of indoor spaces is the most significant parameter in providing a healthy living environment. Low indoor air quality (IAQ) leads to Sick Building Syndrome—one of the major reasons for labor loss in office buildings. The fundamental measure to ensure indoor air quality is ventilation, which includes two basic types: mechanical ventilation and natural ventilation. Natural ventilation is an exchange of stale indoor air with fresh outdoor air by means of a pressure difference due to wind and/or stack effect. Trickle Vents, known also as background ventilators, are natural ventilation devices which can be integrated into façades or window systems as an alternative to operable vents, specifically in high-rise buildings. The major design criteria of Trickle Vents are ventilation capacity, controllability, actuation, thermal insulation, air permeability, water tightness, climatic adaptation, security, and acoustic attenuation. Other important parameters in Trickle Vents design are positioning, equivalent area, and control strategy. This paper aims to review all these aspects, particularly with reference to building regulations and commercial products. Furthermore, simulation, experimental, monitoring, and survey studies of Trickle Vents are also discussed. This literature review is presented from the perspective of performance parameters, control strategies, positioning, etc., with an aim to provide a comprehensive overview of such technology.
Durability and Compressive Strength of High Cement Replacement Ratio Self-Consolidating Concrete
Authors: Mohamed Osama
Published: November 2018

This study examines durability and mechanical properties of sustainable self-consolidating concrete (SCC) in which 80% of the cement is replaced with combinations of recycled industrial by-products including fly ash, silica fume, and ground granulated blast furnace slag (GGBS). The water to binder (w/b) ratio of SCC mixes studies was maintained at 0.36. The study proposes empirical relationships to predict 28-day compressive strengths based on the results of three-day and seven-day compressive strengths. In addition, the chloride penetration resistance of the various sustainable SCC mixes was determined after three days, seven days, and 28 days of moist curing of concrete standards. It was concluded that fly ash, silica fume, and GGBS contribute favorably to enhancing strength development, fresh properties, and durability of SCC in comparison to ordinary Portland cement (OPC). The compressive strength of the sustainable SCC mixes falls within ranges suitable for structural engineering applications. Replacing cement with 15% silica fume produced a 28-day average compressive strength of 95.3 MPa, which is 44.2% higher than the control mix. Replacing cement with 15% or 20% silica fume reduced the chloride ion permeability to very low amounts compared to high permeability in a control mix.
In Situ Metalorganic Deposition of Silver Nanoparticles on Gold Substrate and Square Wave Voltammetry: A Highly Efficient Combination for Nanomolar Detection of Nitrate Ions in Sea Water
Authors: Lebon Emilie , Fau Pierre , Comtat Maurice , Kahn Myrtil L. , Sournia-Saquet Alix , Temple-Boyer Pierre , Dubreuil Brigitte , Behra Philippe , Fajerwerg Katia
Published: November 2018

The electro-reduction of nitrate ions in artificial sea water was investigated at a gold substrate (EAu) functionalized by silver nanoparticles (AgNPs). These AgNPs were generated in situ on the gold substrate by the direct decomposition of the metalorganic N,N′-diisopropylacetamidinate silver precursor [Ag(Amd)] in the liquid phase. Very small and well dispersed AgNPs were deposited on the gold electrode and then used as working electrode (EAu/AgNPs). Square wave voltammetry (SWV) was successfully employed to detect nitrate ions (NO3−) with a detection limit (LOD) of 0.9 nmol∙L−1 in artificial sea water (pH = 6.0) without pre-concentration or pH adjustment.
Optimum Redesign of an Agricultural Water Bowser
Authors: Seechurn Yashwantraj , Boodhun Ritish
Published: November 2018

There are many types of agricultural water bowsers on the market, which vary in geometry and size. However, in all such bowsers there are “unused spaces” between the bottom of the tank and the axle. The objective of this research was to design an agricultural water bowser with improved capacity by exploiting the “unused spaces”. This would allow a sufficient amount of water to be supplied to wide areas in a short time. Each concept of agricultural water bowser was generated as an integrated chassis water tank to be hitched to a tractor, and the best concept was chosen using a multi-criteria decision-making methodology (house of quality matrix and Pugh selection matrix). The selected design consisted of an U-shaped angle bent bottom sheet welded to a top circular sheet. The Agreement Dangerous Road (ADR) European standard was used for the sizing of the bowser and the selected material was S275 steel. The resultant forces on the shell of the bowser were calculated using analytical methods. A 3-D model of the bowser was developed in SolidWorks 2015, and the static structural analysis tool was used to examine stresses on the body for various types of loading, roads, and driving maneuvers. The shape and size of the bottom part of the proposed bowser increased the capacity of the tank by 20.3%.
Effect of Annealing on Microstructure and Tensile Behavior of CoCrNi Medium Entropy Alloy Processed by High-Pressure Torsion
Authors: Sathiyamoorthi Praveen , Bae Jae Wung , Asghari-Rad Peyman , Park Jeong Min , Kim Jung Gi , Kim Hyoung Seop
Published: November 2018

Annealing of severely plastic deformed materials is expected to produce a good combination of strength and ductility, which has been widely demonstrated in conventional materials. In the present study, high-pressure torsion processed CoCrNi medium entropy alloy consisting of a single face-centered cubic (FCC) phase with a grain size of ~50 nm was subjected to different annealing conditions, and its effect on microstructure and mechanical behavior was investigated. The annealing of high-pressure torsion processed CoCrNi alloy exhibits partial recrystallization and near full recrystallization based on the annealing temperature and time. The samples annealed at 700 °C for 2 min exhibit very fine grain size, a high fraction of low angle grain boundaries, and high kernel average misorientation value, indicating partially recrystallized microstructure. The samples annealed for a longer duration (>2 min) exhibit relatively larger grain size, a low fraction of low angle grain boundaries, and low kernel average misorientation value, indicating nearly full recrystallized microstructure. The annealed samples with different microstructures significantly influence the uniform elongation, tensile strength, and work hardening rate. The sample annealed at 700 °C for 15 min exhibits a remarkable combination of tensile strength (~1090 MPa) and strain to failure (~41%).
“How Real People Really Need Mathematics in the Real World”—Authenticity in Mathematics Education
Authors: Vos Pauline
Published: November 2018

This paper discusses authenticity from the perspective of mathematics education. Often, school mathematics offers students inauthentic word problems, which don’t show the authentic usefulness of mathematics in real life. In some tasks, authentic aspects are combined with inauthentic ones (e.g., an authentic context, but the question is artificial and different from what people within that context would ask). Several studies show that students are more motivated by authentic questions than by authentic contexts. Embedding these findings, I discuss issues associated with defining authenticity in education. A first issue is that philosophers use the term to characterize a person’s existential expressions (e.g., being true to oneself), whereas in education, we use the term for learning environments, artefacts, etc. Second, some researchers define authentic learning environments according to criteria (being open to different approaches, simulate a real-life activity, etc.), but I will illustrate that inauthentic activities can comply with such criteria as well. Alternatively, I suggest using the term for separate aspects in a learning environment (contexts, questions, etc.), and define authenticity as a social construct rather than as a subjective perception. In this way, a community (teachers, students, out-of-school experts) can reach agreement on the nature of this characteristic. For an aspect to be authentic, it needs to have: (1) an out-of-school origin and (2) a certification of originality (e.g., by bringing artifacts physically into a classroom or by testimony of an expert). This approach is illustrated by a study on students’ project work during an excursion to a mathematics research workplace.
Multi-Object Detection in Traffic Scenes Based on Improved SSD
Authors: Wang Xinqing , Hua Xia , Xiao Feng , Li Yuyang , Hu Xiaodong , Sun Pengyu
Published: November 2018

In order to solve the problem that, in complex and wide traffic scenes, the accuracy and speed of multi-object detection can hardly be balanced by the existing object detection algorithms that are based on deep learning and big data, we improve the object detection framework SSD (Single Shot Multi-box Detector) and propose a new detection framework AP-SSD (Adaptive Perceive). We design a feature extraction convolution kernel library composed of multi-shape Gabor and color Gabor and then we train and screen the optimal feature extraction convolution kernel to replace the low-level convolution kernel of the original network to improve the detection accuracy. After that, we combine the single image detection framework with convolution long-term and short-term memory networks and by using the Bottle Neck-LSTM memory layer to refine and propagate the feature mapping between frames, we realize the temporal association of network frame-level information, reduce the calculation cost, succeed in tracking and identifying the targets affected by strong interference in video and reduce the missed alarm rate and false alarm rate by adding an adaptive threshold strategy. Moreover, we design a dynamic region amplification network framework to improve the detection and recognition accuracy of low-resolution small objects. Therefore, experiments on the improved AP-SSD show that this new algorithm can achieve better detection results when small objects, multiple objects, cluttered background and large-area occlusion are involved, thus ensuring this algorithm a good engineering application prospect.
CGAcc: A Compressed Sparse Row Representation-Based BFS Graph Traversal Accelerator on Hybrid Memory Cube
Authors: Qian Cheng , Childers Bruce , Huang Libo , Guo Hui , Wang Zhiying
Published: November 2018

Graph traversal is widely used in map routing, social network analysis, causal discovery and many more applications. Because it is a memory-bound process, graph traversal puts significant pressure on the memory subsystem. Due to poor spatial locality and the increasing size of today’s datasets, graph traversal consumes an ever-larger part of application execution time. One way to mitigate this cost is memory prefetching, which issues requests from the processor to the memory in anticipation of needing certain data. However, traditional prefetching does not work well for graph traversal due to data dependencies, the parallel nature of graphs and the need to move vast amounts of data from memory to the caches. In this paper, we propose a compressed sparse row representation-based graph accelerator on the Hybrid Memory Cube (HMC), called CGAcc. CGAcc combines Compressed Sparse Row (CSR) graph representation with in-memory prefetching and processing to improve the performance of graph traversal. Our approach integrates the prefetching and processing in the logic layer of a 3D stacked Dynamic Random-Access Memory (DRAM) architecture, based on Micron’s HMC. We selected HMC to implement CGAcc because it can provide quite high bandwidth and low access latency. Furthermore, this device has multiple DRAM layers connected to internal logic to control memory access and perform rudimentary computation. Using the CSR representation, CGAcc deploys prefetchers in the HMC to exploit the short transaction latency between the logic and DRAM layers. By doing this, it can also avoid large data movement costs. In the runtime, CGAcc pipelines the prefetching to fetch data from DRAM arrays to improve memory-level parallelism. To further reduce the access latency, several optimized internal caches are also introduced to hold the prefetched data to be Processed In-Memory (PIM). A comprehensive evaluation shows the effectiveness of CGAcc. Experimental results showed that, compared to a conventional HMC main memory equipped with a stream prefetcher, CGAcc achieved an average 3.51× speedup with moderate hardware cost.
Moving Learning Machine towards Fast Real-Time Applications: A High-Speed FPGA-Based Implementation of the OS-ELM Training Algorithm
Authors: Frances-Villora Jose V.  , Rosado-Muñoz Alfredo , Bataller-Mompean Manuel  , Barrios-Aviles Juan  , Guerrero-Martinez Juan F. 
Published: November 2018

Currently, there are some emerging online learning applications handling data streams in real-time. The On-line Sequential Extreme Learning Machine (OS-ELM) has been successfully used in real-time condition prediction applications because of its good generalization performance at an extreme learning speed, but the number of trainings by a second (training frequency) achieved in these continuous learning applications has to be further reduced. This paper proposes a performance-optimized implementation of the OS-ELM training algorithm when it is applied to real-time applications. In this case, the natural way of feeding the training of the neural network is one-by-one, i.e., training the neural network for each new incoming training input vector. Applying this restriction, the computational needs are drastically reduced. An FPGA-based implementation of the tailored OS-ELM algorithm is used to analyze, in a parameterized way, the level of optimization achieved. We observed that the tailored algorithm drastically reduces the number of clock cycles consumed for the training execution up to approximately the 1%. This performance enables high-speed sequential training ratios, such as 14 KHz of sequential training frequency for a 40 hidden neurons SLFN, or 180 Hz of sequential training frequency for a 500 hidden neurons SLFN. In practice, the proposed implementation computes the training almost 100 times faster, or more, than other applications in the bibliography. Besides, clock cycles follows a quadratic complexity O ( N ˜ 2 ) , with N ˜ the number of hidden neurons, and are poorly influenced by the number of input neurons. However, it shows a pronounced sensitivity to data type precision even facing small-size problems, which force to use double floating-point precision data types to avoid finite precision arithmetic effects. In addition, it has been found that distributed memory is the limiting resource and, thus, it can be stated that current FPGA devices can support OS-ELM-based on-chip learning of up to 500 hidden neurons. Concluding, the proposed hardware implementation of the OS-ELM offers great possibilities for on-chip learning in portable systems and real-time applications where frequent and fast training is required.
Integrated Energy System Configuration Optimization for Multi-Zone Heat-Supply Network Interaction
Authors: Tang Bo , Gao Gangfeng , Xia Xiangwu , Yang Xiu
Published: November 2018

The integrated energy system effectively improves the comprehensive utilization of energy through cascade utilization and coordinated scheduling of various types of energy. Based on the independent integrated energy system, the thermal network interaction between different load characteristic regions is introduced, requiring a minimum thermal grid construction cost, CCHP investment operation cost and carbon emission tax as the comprehensive optimization targets, and making overall optimization to the configuration and operation of the multi-region integrated energy systems. This paper focuses on the planning of equipment capacity of multi-region integrated energy system based on a CCHP system and heat network. Combined with the above comprehensive target and heat network model, a mixed integer linear programming model for a multi-region CCHP system capacity collaborative optimization configuration is established. The integrated energy system, just a numerical model solved with the LINGO software, is presented. Taking a typical urban area in Shanghai as an example, the simulation results show that the integrated energy system with multi-zone heat-suply network interaction compared to the single area CCHP model improved the clean energy utilization of the system, rationally allocates equipment capacity, promotes the local consumption of distributed energy, and provides better overall system benefits.
Driving Cycles Based on Fuel Consumption
Authors: Huertas José I. , Giraldo Michael , Quirama Luis F. , Díaz Jenny
Published: November 2018

Type-approval driving cycles currently available, such as the Federal Test Procedure (FTP) and the Worldwide harmonized Light vehicles Test Cycle (WLTC), cannot be used to estimate real fuel consumption nor emissions from vehicles in a region of interest because they do not describe its local driving pattern. We defined a driving cycle (DC) as the time series of speeds that when reproduced by a vehicle, the resulting fuel consumption and emissions are similar to the average fuel consumption and emissions of all vehicles of the same technology driven in that region. We also declared that the driving pattern can be described by a set of characteristic parameters (CPs) such as mean speed, positive kinetic energy and percentage of idling time. Then, we proposed a method to construct those local DC that use fuel consumption as criterion. We hypothesized that by using this criterion, the resulting DC describes, implicitly, the driving pattern in that region. Aiming to demonstrate this hypothesis, we monitored the location, speed, altitude, and fuel consumption of a fleet of 15 vehicles of similar technology, during 8 months of normal operation, in four regions with diverse topography, traveling on roads with diverse level of service. In every region, we considered 1000 instances of samples made of m trips, where m varied from 4 to 40. We found that the CPs of the local driving cycle constructed using the fuel-based method exhibit small relative differences (<15%) with respect to the CPs that describe the driving patterns in that region. This result demonstrates the hypothesis that using the fuel based method the resulting local DC exhibits CPs similar to the CPs that describe the driving pattern of the region under study.
An Improved OPP Problem Formulation for Distribution Grid Observability
Authors: Shafiullah Md , Abido M. A. , Hossain Md Ismail , Mantawy A. H.
Published: November 2018

Phasor measurement units (PMUs) are becoming popular and populating the power system grids rapidly due to their wide range of benefits and applications. This research paper proposes a comprehensive, effective, and revised formulation of the optimal PMU placement (OPP) problem with a view to minimizing the required number of PMU and ensuring the maximum number of measurement redundancy subjected to the full observability of the distribution grids. The proposed formulation also incorporates the presence of passive measurements/zero injection buses (ZIB) and the channel availability of the installed PMU. Additionally, the formulation is extended to various contingency cases i.e., the single line outage and single PMU loss cases. This paper solves the proposed OPP formulation employing a heuristic technique called backtracking search algorithm (BSA) and tests its effectiveness through different IEEE standard distribution feeders. Additionally, this study compares the obtained results with the mixed integer linear programming (MILP)-based approach and the referenced works. The obtained results demonstrate the superiority of the proposed formulation and solution methodology compared to other methodologies.
Double Layer Dynamic Game Bidding Mechanism Based on Multi-Agent Technology for Virtual Power Plant and Internal Distributed Energy Resource
Authors: Gao Yajing , Zhou Xiaojie , Ren Jiafeng , Wang Xiuna , Li Dongwei
Published: November 2018

As renewable energies become the main direction of global energy development in the future, Virtual Power Plant (VPP) becomes a regional multi-energy aggregation model for large-scale integration of distributed generation into the power grid. It also provides an important way for distributed energy resources (DER) to participate in electricity market transactions. Firstly, the basic concept of VPP is outlined, and various uncertainties within VPP are modeled. Secondly, using multi-agent technology and Stackelberg dynamic game theory, a double-layer nested dynamic game bidding model including VPP and its internal DERs is designed. The lower layer is a bidding game for VPP internal market including DER. VPP is the leader and each DER is a subagent that acts as a follower to maximize its profit. Each subagent uses the particle swarm algorithm (PSA) to determine the optimal offer coefficient, and VPP carries out internal market clearing with the minimum variance of unit profit according to the quoting results. Then, the subagents renew the game to update the bidding strategy based on the outcomes of the external and internal markets. The upper layer is the external market bidding game. The trading center (TC) is the leader and VPP is the agent and the follower. The game is played with the goal of maximum self-interest. The agent uses genetic algorithms to determine the optimal bid strategy, and the TC carries out market clearance with the goal of maximizing social benefits according to the quotation results. Each agent renews the game to update the bidding strategy based on the clearing result and the reporting of the subagents. The dynamic game is repeated until the optimal equilibrium solution is obtained. Finally, the effectiveness of the model is verified by taking the IEEE30-bus system as an example.
The 2018 Woody Crops International Conference, Rhinelander, Wisconsin, USA, 22–27 July 2018
Authors: Gardiner Emile S. , Ghezehei Solomon B. , Headlee William L. , Richardson Jim , Soolanayakanahally Raju Y. , Stanton Brian J. , Zalesny Jr. Ronald S.
Published: November 2018

The 2018 Woody Crops International Conference was held from 22 to 27 July 2018 throughout Minnesota and Wisconsin, USA to unite world-leading short rotation woody crop (SRWC) organizations at a forum designed to enhance information exchange while also building a platform for developing future collaboration around SRWC production systems. The meeting included pre-conference and post-conference tours in Minnesota and Wisconsin and technical sessions in Rhinelander, Wisconsin. Technical sessions were framed under the topics: Genetics and Physiology, Phytotechnologies, Stakeholders, Bioproducts, Harvesting and Logistics, Biomass Production, and Ecosystem Services. This Conference Report provides a compilation of abstracts from each of the 38 oral and poster presentations delivered during the technical program. It should serve to enhance future discussions among scientists, academicians, regulators, and the general public relative to sustainable application of SRWC technologies for a multitude of current objectives.
Quality of Experience in Cyber-Physical Social Systems Based on Reinforcement Learning and Game Theory
Authors: Tsiropoulou Eirini Eleni , Kousis George , Thanou Athina , Lykourentzou Ioanna , Papavassiliou Symeon
Published: November 2018

This paper addresses the problem of museum visitors’ Quality of Experience (QoE) optimization by viewing and treating the museum environment as a cyber-physical social system. To achieve this goal, we harness visitors’ internal ability to intelligently sense their environment and make choices that improve their QoE in terms of which the museum touring option is the best for them and how much time to spend on their visit. We model the museum setting as a distributed non-cooperative game where visitors selfishly maximize their own QoE. In this setting, we formulate the problem of Recommendation Selection and Visiting Time Management (RSVTM) and propose a two-stage distributed algorithm based on game theory and reinforcement learning, which learns from visitor behavior to make on-the-fly recommendation selections that maximize visitor QoE. The proposed framework enables autonomic visitor-centric management in a personalized manner and enables visitors themselves to decide on the best visiting strategies. Experimental results evaluating the performance of the proposed RSVTM algorithm under realistic simulation conditions indicate the high operational effectiveness and superior performance when compared to other recommendation approaches. Our results constitute a practical alternative for museums and exhibition spaces meant to enhance visitor QoE in a flexible, efficient, and cost-effective manner.
Utilization of Recycled Material Sources for Wood-Polypropylene Composites: Effect on Internal Composite Structure, Particle Characteristics and Physico-Mechanical Properties
Authors: Krause Kim , Sauerbier Philipp , Koddenberg Tim , Krause Andreas
Published: November 2018

In this study, various wood material sources were used for the manufacture of wood-polymer composites (WPC). The materials were categorised as virgin wood particles (VWP), reprocessed WPC particles (RWP) and recycled thermoset composite particles (RCP) and derived from two virgin wood sources, three-layer particleboards, medium-density fibreboards (MDF) boards, or two different wood/polypropylene composites. All produced wood-polypropylene compounds contained 60% wood material and were manufactured using a co-rotating extruder. Malleated polypropylene was used as a coupling agent. Specimens were injection moulded and subsequently tested for their physico-mechanical properties. To characterize particles before and after processing, dynamic image analysis (DIA) measurement were performed. Additionally, X-ray micro-computed tomography (XµCT) was used to characterize the internal structure of the composites and to verify the obtained particle’s characteristics. It was found that length and aspect ratio of particles were remarkably different before and after processing (loss in length of 15–70% and aspect ratio of 10–40%). Moreover, there were notably differences between the particle sources (RCP retained the highest length and aspect ratio values, followed by VWP and RWP). The results suggest that increased aspect ratios can indeed significantly improve mechanical properties (up to 300% increase in impact bending strength and 75% increase in tensile strength, comparing WPC based either on virgin spruce or MDF material). This phenomenon is suggested to be partially superimposed by improved dispersion of particles, which is expected due to lower variance and increased mechanical properties of RWP composites. However, no notable alterations were observed for composite density. Reprocessed WPC and, particularly, RCP material have proved to be an appealing raw material substitute for the manufacturing of wood–polymer composites.