bluuebunny/crossref_metadata_2025 huggingface dataset:
Sucrosomial® Iron Supplementation in Mice: Effects on Blood Parameters, Hepcidin, and Inflammation
Authors: Asperti Michela , Gryzik Magdalena , Brilli Elisa , Castagna Annalisa , Corbella Michela , Gottardo Rossella , Girelli Domenico , Tarantino Germano , Arosio Paolo , Poli Maura
Published: September 2018

Sucrosomial® Iron is a recently developed formulation to treat iron deficiency based on ferric pyrophosphate covered by a matrix of phospholipids plus sucrose esters of fatty acids. Previous data indicated that Sucrosomial® Iron is efficiently absorbed by iron-deficient subjects, even at low dosage, and without side effects. Its structural properties may suggest that it is absorbed by an intestinal pathway which is different to the one used by ionic iron. Although, studies in vitro showed that Sucrosomial® Iron is readily absorbed, no animal models have been established to study this important aspect. To this aim, we induced iron deficient anemia in mice by feeding them with a low-iron diet, and then we treated them with either Sucrosomial® Iron or sulfate iron by gavage for up to two weeks. Both iron formulations corrected anemia and restored iron stores in a two-week period, but with different kinetics. Ferrous Sulfate was more efficient during the first week and Sucrosomial® Iron in the second week. Of note, when given at the same concentrations, Ferrous Sulfate induced the expression of hepcidin and four different inflammatory markers (Socs3, Saa1, IL6 and CRP), while Sucrosomial® Iron did not. We conclude that anemic mice are interesting models to study the absorption of oral iron, and that Sucrosomial® Iron is to be preferred over Ferrous Sulfate because of similar absorption but without inducing an inflammatory response.
Blood Fatty Acid Status and Clinical Outcomes in Dialysis Patients: A Systematic Review
Authors: Khor Ban-Hock , Narayanan Sreelakshmi Sankara , Chinna Karuthan , Gafor Abdul Halim Abdul , Daud Zulfitri Azuan Mat , Khosla Pramod , Sundram Kalyana , Karupaiah Tilakavati
Published: September 2018

Blood fatty acids (FAs) are derived from endogenous and dietary routes. Metabolic abnormalities from kidney dysfunction, as well as cross-cultural dietary habits, may alter the FA profile of dialysis patients (DP), leading to detrimental clinical outcomes. Therefore, we aimed to (i) summarize FA status of DP from different countries, (ii) compare blood FA composition between healthy controls and DP, and (iii) evaluate FA profile and clinical endpoints in DP. Fifty-three articles from 1980 onwards, reporting FA profile in hemodialysis and peritoneal DP, were identified from PubMed, Embase, and the Cochrane library. Studies on pediatric, predialysis chronic kidney disease, acute kidney injury, and transplant patients were excluded. Moderate to high levels of n-3 polyunsaturated fatty acids (PUFA) were reported in Japan, Korea, Denmark, and Sweden. Compared to healthy adults, DP had lower proportions of n-3 and n-6 PUFA, but higher proportion of monounsaturated fatty acids. Two studies reported inverse associations between n-3 PUFAs and risks of sudden cardiac death, while one reported eicosapentaenoic acid + docosahexaenoic acid)/arachidonic acid ratio was inversely associated with cardiovascular events. The relationship between all-cause mortality and blood FA composition in DP remained inconclusive. The current evidence highlights a critical role for essential FA in nutritional management of DP.
Changes in the Understanding of Work in Religious Zionist Thought: Rabbi T.I. Thau as a Case Study
Authors: Mashiach Amir
Published: September 2018

In Jewish religious texts, Torah study is placed at the top of the hierarchy of values. This suggests that work as such is of no religious significance; work is rather a prerequisite for the real essentials of life. The Mizrachi religious Zionist movement, founded in 1902 by R. Yitzhak Yaakov Reines (1839–1915), introduced a markedly different view. The movement upheld a concept of work as a religious value, not only an existential need. Later religious Zionist thinkers developed a dialectical notion of the mutual integration of the Torah and labor; this eventually became the motto of the Bnei Akiva youth movement that they inspired. With time, the theological approach of R. Kook the Elder (ReAYaH) and of R. Kook the Younger (RTziYaH) became dominant in religious Zionism. R. Kook the Elder founded the yeshivah at Merkaz ha-rav in Jerusalem, which he also headed; his son eventually succeeded him. To date, the yeshivah has produced a great number of students and rabbis, who made the teaching of the two Rabbis Kook the legacy of the religious Zionist community as a whole. The aim of the present article is to trace the changes taking place in the religious Zionist attitude toward work as this is articulated in the thought of a student of the two Rabbis, Kook whom many regard as the continuator of their teaching today. This is Rabbi Tzvi Israel Thau (b. 1937), one of the most influential rabbinic figures associated with religious Zionism, President of Yeshivat har ha-mor and the spiritual leader of the Torah academies referred to as “yeshivot of the line [ha-kav]”.
Monitoring Retreat of Coastal Sandy Systems Using Geomatics Techniques: Somo Beach (Cantabrian Coast, Spain, 1875–2017)
Authors: De Sanjosé Blasco José , Gómez-Lende Manuel , Sánchez-Fernández Manuel , Serrano-Cañadas Enrique
Published: September 2018

The dynamics and evolution of a coastal sandy system over the last 142 years (1875–2017) were analyzed using geomatics techniques (historical cartography, photogrammetry, topography, and terrestrial laser scanning (TLS)). The continuous beach–dune system is a very active confining sand barrier closing an estuarine system where damage is suffered by coastal infrastructures and houses. The techniques used and documentary sources involved historical cartography, digitalizing the 5-m-level curve on the maps of 1875, 1908, 1920, 1950, and 1985; photogrammetric flights of 1985, 1988, and 2001 without calibration certificates, digitalizing only the upper part of the sandy front; photogrammetric flights of 2005, 2007, 2010, and 2014, using photogrammetric restitution of the 5-m-level curve; topo-bathymetric profiles made monthly between 1988 and 1993 using a total station; a terrestrial laser scanner (TLS) since 2011 by means of two annual measurements; and the meteorological data for the period of 1985–2017. The retreat of the sandy complex was caused by winter storms with large waves and swells higher than 6 m, coinciding with periods demonstrating a high tidal range of over 100 and periods with a large number of strong storms. The retreat was 8 m between December 2013 and March 2014. The overall change of the coastline between 1875 and 2017 was approximately 415 m of retreat at Somo Beach. The erosive processes on the foredune involved the outcrop of the rock cliff in 1999 and 2014, which became a continuous rocky cliff without sands. To know the recent coastal evolution and its consequences on the human environment, the combined geomatic techniques and future TLS data series may lead to the improvement in the knowledge of shoreline changes in the context of sea level and global changes.
Deep Learning-Based Caution Area Traffic Prediction with Automatic Identification System Sensor Data
Authors: Kim Kwang-Il , Lee Keon Myung
Published: September 2018

In a crowded harbor water area, it is a major concern to control ship traffic for assuring safety and maximizing the efficiency of port operations. Vessel Traffic Service (VTS) operators pay much attention to caution areas like ship route intersections or traffic congestion area in which there are some risks of ship collision. They want to control the traffic of the caution area at a proper level to lessen risk. Inertial ship movement makes swift changes in direction and speed difficult. It is hence important to predict future traffic of the caution area earlier on so as to get enough time for control actions on ship movements. In the harbor area, VTS stations collect a large volume of Automatic Identification Service (AIS) sensor data, which contain information about ship movement and ship attributes. This paper proposes a new deep neural network model called Ship Traffic Extraction Network (STENet) to predict the medium-term traffic and long-term traffic of the caution area. The STENet model is trained with AIS sensor data. The STENet model is organized into a hierarchical architecture in which the outputs of the movement and contextual feature extraction modules are concatenated and fed into a prediction module. The movement module extracts the features of overall ship movements with a convolutional neural network. The contextual modules consist of five separated fully-connected neural networks, each of which receives an associated attribute. The separation of feature extraction modules at the front phase helps extract the effective features by preventing unrelated attributes from crosstalking. To evaluate the performance of the proposed model, the developed model is applied to a real AIS sensor dataset, which has been collected over two years at a Korean port called Yeosu. In the experiments, four methods have been compared including two new methods: STENet and VGGNet-based models. For the real AIS sensor dataset, the proposed model has shown 50.65% relative performance improvement on average for the medium-term predictions and 57.65% improvement on average for the long-term predictions over the benchmark method, i.e., the SVR-based method.
Resource Allocation in Wireless Powered IoT System: A Mean Field Stackelberg Game-Based Approach
Authors: Su Jingtao , Xu Haitao , Xin Ning , Cao Guixing , Zhou Xianwei
Published: September 2018

The IoT system has become a significant component of next generation networks, and drawn a lot of research interest in academia and industry. As the sensor nodes in the IoT system are always battery-limited devices, the power control problem is a serious problem in the IoT system which needs to be solved. In this paper, we research the resource allocation in the wireless powered IoT system, which includes one hybrid access point (HAP) and many wireless sensor nodes, to obtain the optimal power level for information transmission and energy transfer simultaneously. The relationship between the HAP and the sensor nodes are formulated as the Stackelberg game, and the dynamic variations of the energy for both the HAP and IoT devices are formulated through the dynamic game with mean field control. Then the power control in the wireless powered IoT system is formulated as a mean field Stackelberg game model. We aim to minimize the transmission cost for each sensor node based on optimally power resource allocation. Meanwhile, we attempt to minimize the energy transfer cost based on power control. As a result, the optimal solutions based on the mean field control of the sensor nodes and the HAP are achieved through dynamic programming theory and the law of large numbers, and ε -Nash equilibriums can be obtained. The energy variations for both the sensor nodes and HAP after the control of resource allocation based on the proposed approach are verified based on the simulation results.
Planar Inverted-F Antenna (PIFA) Using Microfluidic Impedance Tuner
Authors: Lee Minjae , Lim Sungjoon
Published: September 2018

This paper proposes a microfluidic impedance tuner that is applied to a planar inverted-F antenna (PIFA). The proposed microfluidic impedance tuner is designed while using a simple double-stub and the impedance is changed by tuning the stub length. In this work, the stub length can be tuned by injecting a liquid metal alloy to the microfluidic channels. Initially, the PIFA operates at 900 MHz with impedance matching of 50 Ω. The impedance is mismatched when a hand is placed close to the antenna. The mismatched impedance is matched to 50 Ω by injecting the liquid metal alloy. The antenna is fabricated on the FR-4 substrate, and the impedance tuner is fabricated on polydimethylsiloxane (PDMS). In order to inject the liquid metal alloy, a piezoelectric micropump and microprocessor are used in the measurement. At 900 MHz, the return loss is successfully tuned from 4.69 dB to 18.4 dB when a hand is placed 1 mm above the antenna.
Self-Adaption Matched Filter and Bi-Directional Difference Method for Moving Target Detection
Authors: Zhu Shitao , Chen Xiaoming , Pan Xuehan , Dong Xiaoli , Shi Hongyu , Zhang Anxue , Xu Zhuo
Published: September 2018

In this paper, a self-adaption matched filter (SMF) and bi-directional difference techniques are proposed to detect a small moving target in urban environments. Firstly, the SMF technique is proposed to improve the signal-to-interference-noise ratio (SINR) by using the power factor. The properties of the transmitting signal, the target echoes and the interference and noise are considered during the power factor generation. The amplitude coherent accumulation technique that extracts the coherent amplitude information of echoes after being processed by the SMF, is used to improve the SINR based on multiple measurements. Finally, the bi-directional difference technique is proposed to distinguish the target echoes and the interference/noise. Simulations and experiments are conducted to validate and demonstrate that small moving targets can be detected with high probability using the proposed method in urban environments, even with just one measurement.
An Automation System for Controlling Streetlights and Monitoring Objects Using Arduino
Authors: Mumtaz Zain , Ullah Saleem , Ilyas Zeeshan , Aslam Naila , Iqbal Shahid , Liu Shuo , Meo Jehangir Arshad , Madni Hamza Ahmad
Published: September 2018

We present an Arduino-based automation system to control the streetlights based on solar rays and object’s detection. We aim to design various systems to achieve the desired operations, which no longer require time-consuming manual switching of the streetlights. The proposed work is accomplished by using an Arduino microcontroller, a light dependent resistor (LDR) and infrared-sensors while, two main contributions are presented in this work. Firstly, we show that the streetlights can be controlled based on the night and object’s detection. In which the streetlights automatically turn to DIM state at night-time and turn to HIGH state on object’s detection, while during day-time the streetlights will remain OFF. Secondly, the proposed automated system is further extended to skip the DIM condition at night time, and streetlights turn ON based on the objects’ detection only. In addition, an automatic door system is introduced to improve the safety measurements, and most importantly, a counter is set that will count the number of objects passed through the road. The proposed systems are designed at lab-scale prototype to experimentally validate the efficiency, reliability, and low-cost of the systems. We remark that the proposed systems can be easily tested and implemented under real conditions at large-scale in the near future, that will be useful in the future applications for automation systems and smart homes.
Extended Line Map-Based Precise Vehicle Localization Using 3D LIDAR
Authors: Im Jun-Hyuck , Im Sung-Hyuck , Jee Gyu-In
Published: September 2018

An Extended Line Map (ELM)-based precise vehicle localization method is proposed in this paper, and is implemented using 3D Light Detection and Ranging (LIDAR). A binary occupancy grid map in which grids for road marking or vertical structures have a value of 1 and the rest have a value of 0 was created using the reflectivity and distance data of the 3D LIDAR. From the map, lines were detected using a Hough transform. After the detected lines were converted into the node and link forms, they were stored as a map. This map is called an extended line map, of which data size is extremely small (134 KB/km). The ELM-based localization is performed through correlation matching. The ELM is converted back into an occupancy grid map and matched to the map generated using the current 3D LIDAR. In this instance, a Fast Fourier Transform (FFT) was applied as the correlation matching method, and the matching time was approximately 78 ms (based on MATLAB). The experiment was carried out in the Gangnam area of Seoul, South Korea. The traveling distance was approximately 4.2 km, and the maximum traveling speed was approximately 80 km/h. As a result of localization, the root mean square (RMS) position errors for the lateral and longitudinal directions were 0.136 m and 0.223 m, respectively.
Three Landmark Optimization Strategies for Mobile Robot Visual Homing
Authors: Ji Xun , Zhu Qidan , Ma Junda , Lu Peng , Yan Tianhao
Published: September 2018

Visual homing is an attractive autonomous mobile robot navigation technique, which only uses vision sensors to guide the robot to the specified target location. Landmark is the only input form of the visual homing approaches, which is usually represented by scale-invariant features. However, the landmark distribution has a great impact on the homing performance of the robot, as irregularly distributed landmarks will significantly reduce the navigation precision. In this paper, we propose three strategies to solve this problem. We use scale-invariant feature transform (SIFT) features as natural landmarks, and the proposed strategies can optimize the landmark distribution without over-eliminating landmarks or increasing calculation amount. Experiments on both panoramic image databases and a real mobile robot have verified the effectiveness and feasibility of the proposed strategies.
A Plasmonic Chip-Scale Refractive Index Sensor Design Based on Multiple Fano Resonances
Authors: Wen Kunhua , Chen Li , Zhou Jinyun , Lei Liang , Fang Yihong
Published: September 2018

In this paper, multiple Fano resonances preferred in the refractive index sensing area are achieved based on sub-wavelength metal-insulator-metal (MIM) waveguides. Two slot cavities, which are placed between or above the MIM waveguides, can support the bright modes or the dark modes, respectively. Owing to the mode interferences, dual Fano resonances with obvious asymmetrical spectral responses are achieved. High sensitivity and high figure of merit are investigated by using the finite-difference time-domain (FDTD) method. In view of the development of chip-scale integrated photonics, two extra slot cavities are successively added to the structure, and consequently, three and four ultra-sharp Fano peaks with considerable performances are obtained, respectively. It is believed that this proposed structure can find important applications in the on-chip optical sensing and optical communication areas.
Developing Efficient Thin Film Temperature Sensors Utilizing Layered Carbon Nanotube Films
Authors: Sarma Shrutidhara , Lee Jang Ho
Published: September 2018

In this paper, we present the fabrication of an efficient thin film temperature sensor utilizing chemical vapor deposited carbon nanotube (CNT) film as the sensing element on Si substrates, with diamond-like carbon (DLC):Ni as a catalyst in assisting CNT growth. The fabricated sensor showed good electrical response with change in temperature. Relative linear change in resistance of 18.4% for an increase in temperature from 22 °C to 200 °C was achieved. Various characterizing techniques, such as scanning electron microscopy (SEM) and Raman spectroscopy, were used to characterize the films. In an effort to study device performance, van der Pauw and Hall measurements were carried out to study the dependence of resistance on temperature and magnetic fields. Temperature coefficient of resistance of the sensor was calculated as 1.03 × 10−3/°C. All implications arising from the study are presented. The results establish the aptness of the as-grown CNT film to be used as an active sensing material in thin film temperature sensors.
Philosophy and Application of High-Resolution Temperature Sensors for Stratified Waters
Authors: Van Haren Hans
Published: September 2018

Every application may have its specifically designed sensor. For studying the effects of short-term temperature variations on life in water, a high-resolution sensor has been designed with low noise level <0.1 mK. Pro and cons of the design include its adequacy for use in large heat-capacity environments like water but less in air. The sensor can be used under high static environmental pressure of >1000 Bar (>108 N m−2) in the deepest ocean regions. Its response time of 0.5 s in water allows quantitative studies of internal wave turbulent mixing effects, e.g., on the redistribution of matter and on nearly completely submerged human bodies. In a chain of >100 sensors, clocks are synchronized to sample within 0.02 s and a verified range of 600 m.
Development of Organic-Inorganic Hybrid Optical Gas Sensors for the Non-Invasive Monitoring of Pathogenic Bacteria
Authors: Kladsomboon Sumana , Thippakorn Chadinee , Seesaard Thara
Published: September 2018

Hybrid optical gas sensors, based on different organic and inorganic materials, are proposed in this paper, with the aim of using them as optical artificial nose systems. Three types of organic and inorganic dyes, namely zinc-porphyrin, manganese-porphyrin, and zinc-phthalocyanine, were used as gas sensing materials to fabricate a thin-film coating on glass substrates. The performance of the gas sensor was enhanced by a thermal treatment process. The optical absorption spectra and morphological structure of the sensing films were confirmed by UV-Vis spectrophotometer and atomic force microscope, respectively. The optical gas sensors were tested with various volatile compounds, such as acetic acid, acetone, ammonia, ethanol, ethyl acetate, and formaldehyde, which are commonly found to be released during the growth of bacteria. These sensors were used to detect and discriminate between the bacterial odors of three pathogenic species (Staphylococcus aureus, Escherichia coli and Pseudomonas aeruginosa) grown in Luria-Bertani medium. Based on a pattern recognition (PARC) technique, we showed that the proposed hybrid optical gas sensors can discriminate among the three pathogenic bacterial odors and that the volatile organic compound (VOC) odor pattern of each bacterium was dependent on the phase of bacterial growth.
Secure Authentication Protocol for Wireless Sensor Networks in Vehicular Communications
Authors: Yu SungJin , Lee JoonYoung , Lee KyungKeun , Park KiSung , Park YoungHo
Published: September 2018

With wireless sensor networks (WSNs), a driver can access various useful information for convenient driving, such as traffic congestion, emergence, vehicle accidents, and speed. However, a driver and traffic manager can be vulnerable to various attacks because such information is transmitted through a public channel. Therefore, secure mutual authentication has become an important security issue, and many authentication schemes have been proposed. In 2017, Mohit et al. proposed an authentication protocol for WSNs in vehicular communications to ensure secure mutual authentication. However, their scheme cannot resist various attacks such as impersonation and trace attacks, and their scheme cannot provide secure mutual authentication, session key security, and anonymity. In this paper, we propose a secure authentication protocol for WSNs in vehicular communications to resolve the security weaknesses of Mohit et al.’s scheme. Our authentication protocol prevents various attacks and achieves secure mutual authentication and anonymity by using dynamic parameters that are changed every session. We prove that our protocol provides secure mutual authentication by using the Burrows–Abadi–Needham logic, which is a widely accepted formal security analysis. We perform a formal security verification by using the well-known Automated Validation of Internet Security Protocols and Applications tool, which shows that the proposed protocol is safe against replay and man-in-the-middle attacks. We compare the performance and security properties of our protocol with other related schemes. Overall, the proposed protocol provides better security features and a comparable computation cost. Therefore, the proposed protocol can be applied to practical WSNs-based vehicular communications.
Real-Time Traffic Sign Detection and Recognition Method Based on Simplified Gabor Wavelets and CNNs
Authors: Shao Faming , Wang Xinqing , Meng Fanjie , Rui Ting , Wang Dong , Tang Jian
Published: September 2018

Traffic sign detection and recognition plays an important role in expert systems, such as traffic assistance driving systems and automatic driving systems. It instantly assists drivers or automatic driving systems in detecting and recognizing traffic signs effectively. In this paper, a novel approach for real-time traffic sign detection and recognition in a real traffic situation was proposed. First, the images of the road scene were converted to grayscale images, and then we filtered the grayscale images with simplified Gabor wavelets (SGW), where the parameters were optimized. The edges of the traffic signs were strengthened, which was helpful for the next stage of the process. Second, we extracted the region of interest using the maximally stable extremal regions algorithm and classified the superclass of traffic signs using the support vector machine (SVM). Finally, we used convolution neural networks with input by simplified Gabor feature maps, where the parameters were the same as the detection stage, to classify the traffic signs into their subclasses. The experimental results based on Chinese and German traffic sign databases showed that the proposed method obtained a comparable performance with the state-of-the-art method, and furthermore, the processing efficiency of the whole process of detection and classification was improved and met the real-time processing demands.
Preparation and Optimization of Optical pH Sensor Based on Sol-Gel
Authors: Zhang Jianxin , Zhou Lei
Published: September 2018

Making use of the sol-gel technique, an optical pH sensor was prepared, which was made from an organic carrier with four indictors including congo red, bromophenol blue, cresol red, and chlorophenol red, cross-linked by tetraethyl orthosilicate (TEOS) and cellulose acetate. The actual detection range of the optical pH sensor is 2.5–11.0. The optimal ratio of ethyl orthosilicate, absolute ethanol, deionized water, and hydrochloric acid in glue precursor of the sensor-sensitive membrane was explored. The orthogonal experiment was designed to optimize the dosage of cellulose acetate, N,N-dimethylformamide (DMF), indicator, hydrochloric acid, and precursor glue in preparing the sensor-sensitive membrane. The linearity, measurement accuracy, repeatability, stability, and response time of the prepared pH sensor were tested. The measurement results were analyzed using a support vector machine and linear regression. The experimental results show that the optical pH sensor has a measurement accuracy of up to 0.2 pH and better stability and repeatability than the traditional pH glass electrode.
Effect of Electrode Shape and Flow Conditions on the Electrochemical Detection with Band Microelectrodes
Authors: Al Khatib Maher , Bellini Marco , Pogni Rebecca , Giaccherini Andrea , Innocenti Massimo , Vizza Francesco , Lavacchi Alessandro
Published: September 2018

In this work, we report the analysis of the electrochemical detection of electroactive species with band microelectrodes that operate under controlled convection. The study focuses on the determination of the collection efficiency of the analyte as a function of inlet flow velocity and microband geometry (inlaid, bumped and recessed), also providing a straightforward method for the theoretical determination of the lower detection limit. The analysis has been carried out by simulating the dimensionless mass transport with the finite element method, delivering the stationary limiting current density. Simulations have been performed on systems consisting of single and double band electrodes to investigate the trail effect on the electrochemical detection. We show that the obtained dimensionless results can be easily turned into dimensional data, providing a tool for the design of devices. The proposed method is general and can easily be extended to systems with different geometry.
Spoofing Detection Algorithm Based on Pseudorange Differences
Authors: Liu Ke , Wu Wenqi , Wu Zhijia , He Lei , Tang Kanghua
Published: September 2018

Intentional spoofing interference can cause damage to the navigation terminal and threaten the security of a global navigation satellite system (GNSS). For spoofing interference, an anti-spoofing algorithm based on pseudorange differences for a single receiver is proposed, which can be used to detect simplistic and intermediate spoofing attacks, as well as meaconing attacks. Double-difference models using the pseudorange of two adjacent epochs are established followed by the application of Taylor expansion to the position relationship between the satellite and the receiver (or the spoofer). The authenticity of the signal can be verified by comparing the results of the proposed spoofing detection algorithm with the traditional least squares method. The results will differ when spoofing is present. The parameter setting of the proposed algorithm is introduced. The algorithm has the advantage of both simplicity and efficiency and needs only a single receiver and pseudorange data. A NovAtel receiver is adopted for the actual experiments. The Texas spoofing test battery (TEXBAT), as well as two other simulation experiments are used to verify the performance of the algorithm. The simulation results validate the feasibility and effectiveness of the algorithm.
Difficulties and Challenges of Anomaly Detection in Smart Cities: A Laboratory Analysis
Authors: Garcia-Font Victor , Garrigues Carles , Rifà-Pous Helena
Published: September 2018

Smart cities work with large volumes of data from sensor networks and other sources. To prevent data from being compromised by attacks or errors, smart city IT administrators need to apply attack detection techniques to evaluate possible incidents as quickly as possible. Machine learning has proven to be effective in many fields and, in the context of wireless sensor networks (WSNs), it has proven adequate to detect attacks. However, a smart city poses a much more complex scenario than a WSN, and it has to be evaluated whether these techniques are equally valid and effective. In this work, we evaluate two machine learning algorithms (support vector machines (SVM) and isolation forests) to detect anomalies in a laboratory that reproduces a real smart city use case with heterogeneous devices, algorithms, protocols, and network configurations. The experience has allowed us to show that, although these techniques are of great value for smart cities, additional considerations must be taken into account to effectively detect attacks. Thus, through this empiric analysis, we point out broader challenges and difficulties of using machine learning in this context, both for the technical complexity of the systems, and for the technical difficulty of configuring and implementing them in such environments.
Does Sustainability Engagement Affect Stock Return Volatility? Evidence from the Chinese Financial Market
Authors: Zhang Junru , Djajadikerta Hadrian Geri , Zhang Zhaoyong
Published: September 2018

This paper examines the impact of firms’ sustainability engagement on their stock returns and volatility by employing the EGARCH and FIGARCH models using data from the major financial firms listed in the Chinese stock market. We find evidence of a positive association between sustainability engagement and stock returns, suggesting firms’ sustainability news release in favour of the market. Although volatility persistence can largely be explained by news flows, the results show that sustainability news release has the significant and largest drop in volatility persistence, followed by popularity in Google search engine and the general news. Sustainability news release is found to affect positively stock return volatility. We also find evidence that market expectation can be driven by the dominant social paradigm when sustainability is included. These findings have important implications for market efficiency and effective portfolio management decisions.
Study on Added-Value Sharing Ratio of Large EPC Hydropower Project Based on Target Cost Contract: A Perspective from China
Authors: Ding Jiyong , Chen Chen , An Xiaowei , Wang Na , Zhai Wujuan , Jin Chenhao
Published: September 2018

Engineering, procurement, and construction (EPC) has been applied in China’s hydropower projects for its value-added advantages compared with traditional project delivery systems in theory. However, the actual performance of large EPC hydropower projects has been challenged by the complexity of the stakeholders’ interest demands and conflicts. The increasing use of target cost contracts (TCC) in the construction industry has provided a pain/gain share mechanism for the owners to incentivize contractors to complete projects within cost budgets. The added-value sharing ratio is the core element of TCC, and it predetermines how much proportion of savings the contractor can get paid if the actual cost is below the target cost, and how much proportion of overspend the contractor has to pay if the actual cost is higher than the target cost. In this paper, we consider the added-value sharing ratio under the framework of TCC based on the principal-agent theory, and look at how the added-value sharing ratio is influenced by various factors and how it affects the owner and the contractor in large EPC hydropower projects. Determination of the added-value sharing ratio in both discrete and continuous conditions are discussed, respectively. It is found that the added-value sharing ratio is relatively explicit in the discrete case, while the optimal added-value sharing model in the continuous case is more complex, which can be used to analyze the relationship between the added-value sharing ratio and the key influencing factors. Our research conclusions can provide both theoretical guidance and practical suggestions to contract design in the implementation of EPC hydropower projects, to some extent.
An Optimization Model Fitting the Neighborhood Sustainability Assessment Tools
Authors: Gargiulo Carmela , Sforza Antonio , Sterle Claudio , Zucaro Floriana
Published: September 2018

The phenomenon of rapid and unplanned urban growth, driven by the migration from rural to urban areas, has hindered healthy urbanization and undermined sustainable development. Sustainability assessment has become one of the popular terms in different fields, especially in architecture and urban planning, and world leading urban sustainability assessment tools have been proposed. Each tool is based on a set of weighted evaluation parameters, related to some main sustainability dimension (environment, economy, society …), and requires to reach a sustainability threshold. In this paper, after a brief review of the state of the art, a linear optimization model is presented, which aimed to find the minimum set of parameters needed to guarantee the sustainability threshold for each tool, taking into account all the sustainability dimensions. The model has been positively experienced with 144 input parameters belonging to five assessment tools. The tests prove that this procedure is able to summarize and overcome the choices made by the certifying bodies. Indeed the proposed optimization model selected 26 parameters of the five tools. The majority of the selected parameters are related to the environmental emergency that in recent decades has characterized—and still affects—urban systems.
Critical Thinking Development—A Necessary Step in Higher Education Transformation towards Sustainability
Authors: Straková Zuzana , Cimermanová Ivana
Published: September 2018

Education for sustainable development has been addressed by professionals, authorities, and a number of research studies in the last decades, and yet the results are not clearly visible. Teachers as agents of a new mindset do not seem to understand the ways of approaching raising awareness of the issues of global challenges. This study investigated the possibility of raising the extent of applying critical thinking to the problem-solving issues of a group of student teachers in their initial training. The sample consisted of 48 student teachers. Both qualitative and quantitative methods were used: namely, a questionnaire, content analysis, and focus group interviews. An archive of the students’ materials was also used for content analysis. In the data analysis, inter-rater reliability, as well as parametric (t-test) and non-parametric tests (Mann–Whitney U test) were applied. The results of the study provide evidence of the positive impact of the use of case studies in teaching pre-service teachers on the development of their critical thinking skills. It can be concluded that it should not be taken for granted that teachers automatically know how to develop the competencies that are necessary for sustainable development (SD). Instead, teacher education institutions need to incorporate thorough training that focusses on education for sustainable development (ESD) into the entire teacher programme in order to make sure that the teachers leave their initial training well prepared for guaranteeing Sustainable Development Goals (SDGs).
Effects of Quartz Powder on the Microstructure and Key Properties of Cement Paste
Authors: Lin Run-Sheng , Wang Xiao-Yong , Zhang Gui-Yu
Published: September 2018

This paper compares the effects of the water-to-binder (w/b) ratio and quartz contents on the properties of cement–quartz paste. The w/b ratios of the paste mixtures specimens are 0.5 and 0.2, and the quartz powder contents are 0, 10, and 20%. At the age of 1, 3, 7, and 28 days, compressive strength test, X-ray fluorescence (XRF) spectroscopy, X-ray diffraction (XRD), mercury intrusion porosimetry (MIP), scanning electron microscopy (SEM), isothermal calorimetry, and thermogravimetric (TG) analysis were performed. The experimental results show that the quartz powder mainly has the dilution effect and crystal nucleation effect on cement hydration, and the addition of quartz powder does not change the type of hydration product. The effect of quartz powder on cement hydration is closely related to the w/b ratio. In the case of a low w/b ratio of 0.2, the addition of quartz powder did not impair the compressive strength of paste. For different w/b ratios (0.5 and 0.2) and various quartz powder contents (0, 10, and 20%) at different ages (1, 3, 7, and 28 days), there is a uniform linear relationship between strength and porosity. Similarly, there is a uniform linear relationship between chemically bound water and calcium hydroxide, between heat of hydration and compressive strength, and between chemically bound water and compressive strength. At the same time, the effect of the partial replacement of cement by quartz powder on sustainability is considered in this paper.
Climate Adaptability Construction Technology of Historic Conservation Areas: The Case Study of the Chinese–Baroque Historic Conservation Area in Harbin
Authors: Jin Hong , Zhao Jing , Liu Siqi , Kang Jian
Published: September 2018

In recent years, the conflict between human activities and the natural environment has led to global warming and extreme weather, which has provoked people into thinking about the climate adaptability of buildings. Historical blocks are usually built and designed based on the social environment and climatic conditions at that time; therefore, they generally contain the construction techniques relevant to dealing with the local climate. The study aims to study the microclimate characteristics of a historic conservation area in a severe cold region and to explore how it attempted to achieve climate adaptation. Taking the Chinese–Baroque historic conservation area in Harbin as an example, this paper analyzed and studied the climate adaptability technology and excavated the suitable technology for the block to deal with a severe cold climate through research, field measurements, and numerical simulation. The results showed that compared with a certain modern urban area in the city, the Chinese–Baroque historic conservation area had better ability to resist wind and cold. The compact layout of the block could reduce heat loss and keep out the cold by effectively resisting the cold wind from permeating inside. Compared with the T-shaped and L-shaped courtyards, the rectangular courtyard occupies the largest proportion and a rectangular courtyard enclosed by buildings on all sides had better windbreak performance. Furthermore, when the courtyard space was enclosed by four sides and the courtyard width was the same, when the plane aspect ratio was smaller, the maximum wind speed of the inner courtyard was smaller. The squares in the block had a good performance in cold resistance. At the same scale, the higher the degree of enclosure of the square, the lower the internal wind speed. This study will provide a reference for urban planning and architectural design in severe cold regions.
Adoption of Conservation Agriculture in Uganda: A Case Study of the Lango Subregion
Authors: Kaweesa Sara , Mkomwa Saidi , Loiskandl Willibald
Published: September 2018

Conservation agriculture (CA) is based on three principles: minimum soil disturbance, maintaining a soil cover through mulching with crop residues or planting cover crops, and practicing crop rotations. CA is practiced in many parts of the world for its benefits to soil and ability to improve yields, among others. There is little documented information on the status of CA adoption in the Lango region in mid-Northern Uganda. This study aimed at determining the extent of CA adoption in relation to the socioeconomic status of the farming population and suggesting relevant strategies for accelerating CA uptake specific to this region. A non-discriminative snowball-sampling technique was used to gather data from 417 households spread over three districts. Semi-structured interviews were conducted using household questionnaires. Farmers’ uptake of CA was related to information gained from training and the benefits that were observed in their fields. Some farm-level constraints in the region included the diminutive ratio of shared tools and equipment; the minimum presence and involvement of extension services; and seasonal rural markets that are dominated by middlemen. The impact that was attributed to the use of CA at the household level was improved yields. The strategy that was used to spread CA information to farmers also played a key role in increasing CA uptake in the region. This information is important for increasing CA adoption in this context given the socioeconomic status of the region.
Synergy of National Agricultural Innovation Systems
Authors: Wang Dan , Du Xu , Sun Jian , Guo Xiangyu , Chen Yao
Published: September 2018

Synergy among the various components of national agricultural innovation systems (AISs) promotes agricultural development. This paper investigated the innovation synergy among the various innovation elements of national AISs. First, we developed a synergy analysis model consisting of three innovation variables (innovation allocation, innovation output, and innovation potentiality) and one control variable (government policy supports). Secondly, a broad set of innovation indicators was selected to describe the innovation variables and the control variable, and the solutions of the order parameter equation were then calculated to investigate the self-organized synergistic patterns of a panel of the Group of Twenty (G20) countries. The empirical results indicated the following. (1) All of the G20 countries’ national AISs had the potential to evolve into more advanced self-organized synergistic states under current government policy support. Furthermore, all of the developing countries were in the active period of synergy, showing stronger synergistic rising powers. However, most of the developed countries were in the stable or general period of synergy, in which synergistic rising powers were relatively weaker; (2) Stronger government policy supports played a positive role in promoting the interaction and collaboration among innovation elements and promoted the national AIS to evolve into a more advanced self-organized synergistic state. This study has important implications for understanding the complex innovation synergy of national AISs, as well as for the design and implementation of agricultural innovation strategies for policy-makers.
Strategies for Implementing Public Service Electric Bus Lines by Charging Type in Daegu Metropolitan City, South Korea
Authors: Bak Dan-Bi , Bak Jae-Seok , Kim Sung-Yul
Published: September 2018

The large-scale adoption of electric vehicles in the public sector is essential for achieving emission reduction targets for transportation. In particular, the replacement of buses with internal combustion engines, which travel long distances and produce massive greenhouse gas emissions, by their electric counterparts can drastically reduce emissions. A variety of electric buses with different power supply systems are currently available, and their performance, charging type, battery capacity, and operating environment are related parameters that must be addressed for their successful and massive adoption. For instance, the appropriate charging type of electric buses depends on conditions, such as the operating environment. In this study, we determined the optimum capacity of electric bus batteries by considering the electric bus range, battery depth of discharge, and deterioration cost while using ADVISOR, which is a MATLAB-based electric vehicle simulator. In addition, we assessed the energy consumed and charging time according to the operating environments of electric buses. Finally, an economic efficiency analysis allowed for determining the appropriated charging type for electric buses. By integrating these data and analyses, we propose a comprehensive plan for selecting the most appropriate charging type according to the operating environment of these electric vehicles. We expect that the proposed plan will contribute to the adoption of electric buses and achieve the greenhouse gas reduction targets set by South Korea.
Astrape: An Efficient Concurrent Cloud Attestation with Ciphertext-Policy Attribute-Based Encryption
Authors: Ba Haihe , Zhou Huaizhe , Mei Songzhu , Qiao Huidong , Hong Tie , Wang Zhiying , Ren Jiangchun
Published: September 2018

Cloud computing emerges as a change in the business paradigm that offers pay-as-you-go computing capability and brings enormous benefits, but there are numerous organizations showing hesitation for the adoption of cloud computing due to security concerns. Remote attestation has been proven to boost confidence in clouds to guarantee hosted cloud applications’ integrity. However, the state-of-the-art attestation schemes do not fit that multiple requesters raise their challenges simultaneously, thereby leading to larger performance overheads on the attester side. To address that, we propose an efficient and trustworthy concurrent attestation architecture under multi-requester scenarios, Astrape, to improve efficiency in the integrity and confidentiality protection aspects to generate an unforgeable and encrypted attestation report. Specifically, we propose two key techniques in this paper. The first one—aggregated attestation signature—reliably protects the attestation content from being compromised even in the presence of adversaries who have full control of the network, therefore successfully providing attestation integrity. The second one—delegation-based controlled report—introduces a third-party service to distribute the attestation report to requesters in order to save computation and communication overload on the attested party. The report is encrypted with an access policy by using attribute-based encryption and accessed by a limited number of qualified requesters, hence supporting attestation confidentiality. The experimental results show that Astrape can take no more than 0.4 s to generate an unforgeable and encrypted report for 1000 requesters and deliver a throughput speedup of approximately 30 × in comparison to the existing attestation systems.