bluuebunny/crossref_metadata_2025 huggingface dataset:
Outdoor Target Positioning Using Wii Remote IR Camera and Signal Modulation
Authors: Lin Michael , Lee Kooktae
Published: April 2020

This paper investigates the use of the Wii remote IR (infrared) camera for outdoor target positioning. The Wii remote IR camera is widely used in various applications because of its capability of detection of up to four IR light sources with a fast frame rate (100 Hz) and a relatively low price. However, previous applications are limited to indoor uses due to the obvious reason of sunlight interference for outdoor applications. In this paper, a signal modulation technique is introduced, which enables the IR camera to look for a particular pattern encoded in an IR beacon. In this way, the IR camera can distinguish the IR beacon from the sunlight interference. The irradiance of the sunlight reflection is also analyzed to guarantee that the IR camera can detect the IR beacon even under extremely sunny weather conditions. As the Wii remote IR camera sensor is overloaded under an extremely bright condition that blocks the camera to see any light sources, we propose the use of a filter to dim the camera. Experimental results for outdoor tests are provided to validate the proposed methods.
Few-Shot Personalized Saliency Prediction Based on Adaptive Image Selection Considering Object and Visual Attention
Authors: Moroto Yuya , Maeda Keisuke , Ogawa Takahiro , Haseyama Miki
Published: April 2020

A few-shot personalized saliency prediction based on adaptive image selection considering object and visual attention is presented in this paper. Since general methods predicting personalized saliency maps (PSMs) need a large number of training images, the establishment of a theory using a small number of training images is needed. To tackle this problem, although finding persons who have visual attention similar to that of a target person is effective, all persons have to commonly gaze at many images. Thus, it becomes difficult and unrealistic when considering their burden. On the other hand, this paper introduces a novel adaptive image selection (AIS) scheme that focuses on the relationship between human visual attention and objects in images. AIS focuses on both a diversity of objects in images and a variance of PSMs for the objects. Specifically, AIS selects images so that selected images have various kinds of objects to maintain their diversity. Moreover, AIS guarantees the high variance of PSMs for persons since it represents the regions that many persons commonly gaze at or do not gaze at. The proposed method enables selecting similar users from a small number of images by selecting images that have high diversities and variances. This is the technical contribution of this paper. Experimental results show the effectiveness of our personalized saliency prediction including the new image selection scheme.
An 8.8 ps RMS Resolution Time-To-Digital Converter Implemented in a 60 nm FPGA with Real-Time Temperature Correction
Authors: Song Zhipeng , Zhao Zhixiang , Yu Hongsen , Yang Jingwu , Zhang Xi , Sui Tengjie , Xu Jianfeng , Xie Siwei , Huang Qiu , Peng Qiyu
Published: April 2020

This paper presented a non-uniform multiphase (NUMP) time-to-digital converter (TDC) implemented in a field-programmable gate array (FPGA) with real-time automatic temperature compensation. NUMP-TDC is a novel, low-cost, high-performance TDC that has achieved an excellent performance in Altera Cyclone V FPGA. The root mean square (RMS) for the intrinsic timing resolution was 2.3 ps. However, the propagation delays in the delay chain of some FPGAs (for example, the Altera Cyclone 10 LP) vary significantly as the temperature changes. Thus, the timing performances of NUMP-TDCs implemented in those FPGAs are significantly impacted by temperature fluctuations. In this study, a simple method was developed to monitor variations in propagation delays using two registers deployed at both ends of the delay chain and compensate for changes in propagation delay using a look-up table (LUT). When the variations exceeded a certain threshold, the LUT for the delay correction was updated, and a bin-by-bin correction was launched. Using this correction approach, a resolution of 8.8 ps RMS over a wide temperature range (5 °C to 80 °C) had been achieved in a NUMP-TDC implemented in a Cyclone 10 LP FPGA.
A Data-Driven Adaptive Sampling Method Based on Edge Computing
Authors: Lou Ping , Shi Liang , Zhang Xiaomei , Xiao Zheng , Yan Junwei
Published: April 2020

The rise of edge computing has promoted the development of the industrial internet of things (IIoT). Supported by edge computing technology, data acquisition can also support more complex and perfect application requirements in industrial field. Most of traditional sampling methods use constant sampling frequency and ignore the impact of changes of sampling objects during the data acquisition. For the problem of sampling distortion, edge data redundancy and energy consumption caused by constant sampling frequency of sensors in the IIoT, a data-driven adaptive sampling method based on edge computing is proposed in this paper. The method uses the latest data collected by the sensors at the edge node for linear fitting and adjusts the next sampling frequency according to the linear median jitter sum and adaptive sampling strategy. An edge data acquisition platform is established to verify the validity of the method. According to the experimental results, the proposed method is more effective than other adaptive sampling methods. Compared with constant sampling frequency, the proposed method can reduce the edge data redundancy and energy consumption by more than 13.92% and 12.86%, respectively.
2D-DOD and 2D-DOA Estimation for a Mixture of Circular and Strictly Noncircular Sources Based on L-Shaped MIMO Radar
Authors: Fang Jiaxiong , Liu Yonghong , Jiang Yifang , Lu Yang , Zhang Zehao , Chen Hua , Wang Laihua
Published: April 2020

In this paper, a joint diagonalization based two dimensional (2D) direction of departure (DOD) and 2D direction of arrival (DOA) estimation method for a mixture of circular and strictly noncircular (NC) sources is proposed based on an L-shaped bistatic multiple input multiple output (MIMO) radar. By making full use of the L-shaped MIMO array structure to obtain an extended virtual array at the receive array, we first combine the received data vector and its conjugated counterpart to construct a new data vector, and then an estimating signal parameter via rotational invariance techniques (ESPRIT)-like method is adopted to estimate the DODs and DOAs by joint diagonalization of the NC-based direction matrices, which can automatically pair the four dimensional (4D) angle parameters and solve the angle ambiguity problem with common one-dimensional (1D) DODs and DOAs. In addition, the asymptotic performance of the proposed algorithm is analyzed and the closed-form stochastic Cramer–Rao bound (CRB) expression is derived. As demonstrated by simulation results, the proposed algorithm has outperformed the existing one, with a result close to the theoretical benchmark.
Combining SDAE Network with Improved DTW Algorithm for Similarity Measure of Ultra-Weak FBG Vibration Responses in Underground Structures
Authors: Li Sheng , Zuo Xiang , Li Zhengying , Wang Honghai , Sun Lizhi
Published: April 2020

Quantifying structural status and locating structural anomalies are critical to tracking and safeguarding the safety of long-distance underground structures. Given the dynamic and distributed monitoring capabilities of an ultra-weak fiber Bragg grating (FBG) array, this paper proposes a method combining the stacked denoising autoencoder (SDAE) network and the improved dynamic time wrapping (DTW) algorithm to quantify the similarity of vibration responses. To obtain the dimensionality reduction features that were conducive to distance measurement, the silhouette coefficient was adopted to evaluate the training efficacy of the SDAE network under different hyperparameter settings. To measure the distance based on the improved DTW algorithm, the one nearest neighbor (1-NN) classifier was utilized to search the best constraint bandwidth. Moreover, the study proposed that the performance of different distance metrics used to quantify similarity can be evaluated through the 1-NN classifier. Based on two one-dimensional time-series datasets from the University of California, Riverside (UCR) archives, the detailed implementation process for similarity measure was illustrated. In terms of feature extraction and distance measure of UCR datasets, the proposed integrated approach of similarity measure showed improved performance over other existing algorithms. Finally, the field-vibration responses of the track bed in the subway detected by the ultra-weak FBG array were collected to determine the similarity characteristics of structural vibration among different monitoring zones. The quantitative results indicated that the proposed method can effectively quantify and distinguish the vibration similarity related to the physical location of structures.
Imaging the Three-Dimensional Ionospheric Structure with a Blob Basis Functional Ionospheric Tomography Model
Authors: Wen Debao , Mei Dengkui , Du Yanan
Published: April 2020

A new ionospheric tomography model is presented in this work. In the new model, the traditional voxel basis function is replaced by the blob basis function. Due to the overlapping nature of their rotational symmetric basis functions, the new model introduces certain weighting from nearby tomographic spherical blobs. To confirm the feasibility of the new tomography model, a numerical simulation scheme is devised, and the simulation demonstrates that the reconstructed quality of the blob basis tomographic model is higher than that of the voxel basis tomographic model. Meanwhile, the variable blob radius is adopted in order to improve the efficiency of the new model. Finally, the new ionospheric tomography model is applied to reconstruct the temporal-spatial distribution of ionospheric electron density using actual global navigation satellite system observations. The comparisons between the tomographic profiles and those obtained from ionosonde data further demonstrate the reliability and the superiority of the new ionospheric tomography model.
Design and Experiments of a Water Color Remote Sensing-Oriented Unmanned Surface Vehicle
Authors: Li Yong , Tian Liqiao , Li Wenkai , Li Jian , Wei Anna , Li Sen , Tong Ruqing
Published: April 2020

Integrated and intelligent in situ observations are important for the remote sensing monitoring of dynamic water environments. To meet the field investigation requirements of ocean color remote sensing, we developed a water color remote sensing-oriented unmanned surface vehicle (WC-USV), which consisted of an unmanned surface vehicle platform with ground control station, data acquisition, and transmission modules. The WC-USV was designed with functions, such as remote controlling, status monitoring, automatic obstacle avoidance, and water and meteorological parameter measurement acquisition, transmission, and processing. The key data acquisition module consisted of four parts: A floating optical buoy (FOBY) for collecting remote sensing reflectance ( R r s ) via the skylight-blocked approach; a water sample autocollection system that can collect 12 1-L bottles for analysis in the laboratory; a water quality measurement system for obtaining water parameters, including Chlorophyll-a (Chl-a), turbidity, and water temperature, among others; and meteorological sensors for measuring wind speed and direction, air pressure, temperature, and humidity. Field experiments were conducted to validate the performance of the WC-USV on 23–28 March 2018 in the Honghu Lake, which is the seventh largest freshwater lake in China. The tests proved the following: (1) The WC-USV performed well in terms of autonomous navigation and obstacle avoidance; (2) the mounted FOBY-derived R r s showed good precision in terms of the quality assurance score (QAS), which was higher than 0.98; (3) the Chl-a and suspended matters (SPM) as ocean color parameters measured by the WC-USV were highly consistent with laboratory analysis results, with determination coefficients (R2) of 0.71 and 0.77, respectively; and (4) meteorological parameters could be continuously and stably measured by WC-USV. Results demonstrated the feasibility and practicability of the WC-USV for automatic in situ observations. The USV provided a new way of thinking for the future development of intelligent automation of the aquatic remote sensing ground verification system. It could be a good option to conduct field investigations for ocean color remote sensing and provide an alternative for highly polluted and/or shallow high-risk waters which large vessels have difficulty reaching.
Smart Sensors for Smart Grid Reliability
Authors: Alonso Monica , Amaris Hortensia , Alcala Daniel , Florez R. Diana M.
Published: April 2020

Sensors for monitoring electrical parameters over an entire electricity network infrastructure play a fundamental role in protecting smart grids and improving the network’s energy efficiency. When a short circuit takes place in a smart grid it has to be sensed as soon as possible to reduce its fault duration along the network and to reduce damage to the electricity infrastructure as well as personal injuries. Existing protection devices, which are used to sense the fault, range from classic analog electro-mechanics relays to modern intelligent electronic devices (IEDs). However, both types of devices have fixed adjustment settings (offline stage) and do not provide any coordination among them under real-time operation. In this paper, a new smart sensor is developed that offers the capability to update its adjustment settings during real-time operation, in coordination with the rest of the smart sensors spread over the network. The proposed sensor and the coordinated protection scheme were tested in a standard smart grid (IEEE 34-bus test system) under different short circuit scenarios and renewable energy penetration. Results suggest that the short-circuit fault sensed by the smart sensor is improved up to 80% and up to 64% compared with analog electromechanics relays and IEDs, respectively.
Method for Improved Performance of Fixed-Gain Self-Alignment in the Temperature Stabilizing State
Authors: Lee Inseop , Oh Juhyun , Yu Haesung , Kim Cheonjoong , Lee Sang Jeong
Published: April 2020

Self-alignment (or initial alignment) is the process by which the Inertial Navigation System (INS) is aligned using only measurements from the inertial sensors and the reference navigation information in the stationary state. The main purpose of self-alignment is to calculate the initial attitude of the INS. The accuracy of self-alignment is determined by the performance grade of the inertial sensors, for instance, the accuracy of the horizontal attitude by the horizontal accelerometer and the accuracy of the vertical attitude by the East-axis gyro. Therefore, uncertain errors in the inertial sensors degrade the performance of self-alignment. The focus of this paper is the temperature stabilizing error of accelerometers, a form of uncertain error. An analysis is presented of how the temperature stabilizing error affect the accuracy of self-alignment. From the analysis, a method is proposed to improve performance by curve fitting the horizontal control rates. This is then verified experimentally.
Towards a Remote Monitoring of Patient Vital Signs Based on IoT-Based Blockchain Integrity Management Platforms in Smart Hospitals
Authors: Jamil Faisal , Ahmad Shabir , Iqbal Naeem , Kim Do-Hyeun
Published: April 2020

Over the past several years, many healthcare applications have been developed to enhance the healthcare industry. Recent advancements in information technology and blockchain technology have revolutionized electronic healthcare research and industry. The innovation of miniaturized healthcare sensors for monitoring patient vital signs has improved and secured the human healthcare system. The increase in portable health devices has enhanced the quality of health-monitoring status both at an activity/fitness level for self-health tracking and at a medical level, providing more data to clinicians with potential for earlier diagnosis and guidance of treatment. When sharing personal medical information, data security and comfort are essential requirements for interaction with and collection of electronic medical records. However, it is hard for current systems to meet these requirements because they have inconsistent security policies and access control structures. The new solutions should be directed towards improving data access, and should be managed by the government in terms of privacy and security requirements to ensure the reliability of data for medical purposes. Blockchain paves the way for a revolution in the traditional pharmaceutical industry and benefits from unique features such as privacy and transparency of data. In this paper, we propose a novel platform for monitoring patient vital signs using smart contracts based on blockchain. The proposed system is designed and developed using hyperledger fabric, which is an enterprise-distributed ledger framework for developing blockchain-based applications. This approach provides several benefits to the patients, such as an extensive, immutable history log, and global access to medical information from anywhere at any time. The Libelium e-Health toolkit is used to acquire physiological data. The performance of the designed and developed system is evaluated in terms of transaction per second, transaction latency, and resource utilization using a standard benchmark tool known as Hyperledger Caliper. It is found that the proposed system outperforms the traditional health care system for monitoring patient data.
Storage Management Strategy in Mobile Phones for Photo Crowdsensing
Authors: Wang En , Qu Zhengdao , Liang Xinyao , Meng Xiangyu , Yang Yongjian , Li Dawei , Meng Weibin
Published: April 2020

In mobile crowdsensing, some users jointly finish a sensing task through the sensors equipped in their intelligent terminals. In particular, the photo crowdsensing based on Mobile Edge Computing (MEC) collects pictures for some specific targets or events and uploads them to nearby edge servers, which leads to richer data content and more efficient data storage compared with the common mobile crowdsensing; hence, it has attracted an important amount of attention recently. However, the mobile users prefer uploading the photos through Wifi APs (PoIs) rather than cellular networks. Therefore, photos stored in mobile phones are exchanged among users, in order to quickly upload them to the PoIs, which are actually the edge services. In this paper, we propose a utility-based Storage Management strategy in mobile phones for Photo Crowdsensing (SMPC), which makes a sending/deleting decision on a user’s device for either maximizing photo delivery ratio (SMPC-R) or minimizing average delay (SMPC-D). The decision is made according to the photo’s utility, which is calculated by measuring the impact of reproducing or deleting a photo on the above performance goals. We have done simulations based on the random-waypoint model and three real traces: roma/taxi, epfl, and geolife. The results show that, compared with other storage management strategies, SMPC-R gets the highest delivery ratio and SMPC-D achieves the lowest average delay.
Effects of a Traditional versus an Alternative Strengthening Exercise Program on Shoulder Pain, Function and Physical Performance in Individuals with Subacromial Shoulder Pain: A Randomized Controlled Trial
Authors: Schedler Simon , Brueckner Dennis , Hagen Marco , Muehlbauer Thomas
Published: April 2020

A manual shoulder-training device may represent an alternative training device to improve symptoms and function in patients with subacromial shoulder pain by strengthening the external rotators. Thus, we examined the effects of a traditional versus an alternative strengthening exercise program on shoulder pain/function and physical performance in individuals with subacromial shoulder pain. Fifty-six adults with subacromial shoulder pain were randomly assigned to a passive control group (CON; n = 20), a traditional training group (TRA; n = 19), or an alternative training group (ALT; n = 17). Both training groups conducted a progressive home-based strengthening exercise program for the external rotators for eight weeks using elastic bands only (TRA group) or in combination with the shoulder-training device (Schulterhilfe®) (ALT group). Pre- and post-training assessment included measures of shoulder pain/function (i.e., shoulder pain and disability index (SPADI)) and physical performance (i.e., shoulder flexibility, maximal isometric strength, and strength endurance). We found significant test × group interactions in most of the investigated variables. Post hoc analyses showed significant training-related improvements for proxies of shoulder pain/function, shoulder flexibility, maximal isometric strength, and strength endurance in favor of the ALT and TRA group in comparison to the CON group. Further, larger and more frequent effects were found for the ALT compared to the TRA group. Measures of shoulder pain/function and physical performance can be significantly improved by both training regimens in individuals with subacromial shoulder pain. However, strength training using elastic bands with the manual shoulder device (ALT group) as compared to elastic bands (TRA group) only was more effective and may thus be a recommendable alternative in order to mitigate subacromial shoulder pain.
Depth Induced Regression Medians and Uniqueness
Authors: Zuo Yijun
Published: April 2020

The notion of median in one dimension is a foundational element in nonparametric statistics. It has been extended to multi-dimensional cases both in location and in regression via notions of data depth. Regression depth (RD) and projection regression depth (PRD) represent the two most promising notions in regression. Carrizosa depth D C is another depth notion in regression. Depth-induced regression medians (maximum depth estimators) serve as robust alternatives to the classical least squares estimator. The uniqueness of regression medians is indispensable in the discussion of their properties and the asymptotics (consistency and limiting distribution) of sample regression medians. Are the regression medians induced from RD, PRD, and D C unique? Answering this question is the main goal of this article. It is found that only the regression median induced from PRD possesses the desired uniqueness property. The conventional remedy measure for non-uniqueness, taking average of all medians, might yield an estimator that no longer possesses the maximum depth in both RD and D C cases. These and other findings indicate that the PRD and its induced median are highly favorable among their leading competitors.
Sustainable and Religion Food Consumer Segmentation: Focusing on Korean Temple Food Restaurants
Authors: Park Junkyu , Bonn Mark A. , Cho Meehee
Published: April 2020

As demand for temple food has significantly grown, this study’s objective was to conduct a market segmentation analysis of temple food consumer motives in order to develop effective marketing strategies. The study identified six motives specific to Korean temple food consumption representing “health-oriented,” “ethical vegetarianism,” “meditative mindfulness,” “educational experience,” “taste,” and “environment protection.” Motives were then used to generate four distinct temple food groups named Highly Motivated, Vegetarian, Environment-Oriented and Minimally Motivated. This study provided useful information for the application of Korean temple food marketing strategies for destinations featuring this growing trend in culinary tourism.
Implementation of Detection System for Drowsy Driving Prevention Using Image Recognition and IoT
Authors: Jang Seok-Woo , Ahn Byeongtae
Published: April 2020

In recent years, the casualties of traffic accidents caused by driving cars have been gradually increasing. In particular, there are more serious injuries and deaths than minor injuries, and the damage due to major accidents is increasing. In particular, heavy cargo trucks and high-speed bus accidents that occur during driving in the middle of the night have emerged as serious social problems. Therefore, in this study, a drowsiness prevention system was developed to prevent large-scale disasters caused by traffic accidents. In this study, machine learning was applied to predict drowsiness and improve drowsiness prediction using facial recognition technology and eye-blink recognition technology. Additionally, a CO2 sensor chip was used to detect additional drowsiness. Speech recognition technology can also be used to apply Speech to Text (STT), allowing a driver to request their desired music or make a call to avoid drowsiness while driving.
Analysis of Consumer Preference for Milk Produced through Sustainable Farming: The Case of Mountainous Dairy Farming
Authors: Nam Kyungsoo , Lim Heesun , Ahn Byeong-il
Published: April 2020

As income is rising and urbanization progressing, the consumption of meat and dairy products is increasing, especially in developing countries. However, increasing livestock production leads to challenges that need to be addressed, such as yielding environmental pollution and causing climate change. Due to these circumstances, the importance of sustainable livestock farming has been highlighted in order to effectively utilize natural resources and to protect the environment. We analyzed consumers’ preference and willingness to pay for milk, one of the representative dairy products, which was produced in a sustainable way. Among the various attributes of milk, marginal willingness to pay for “performing sustainability” through mountainous farming was estimated to be the biggest. The willingness to pay was revealed to be higher for the consumer group with a high awareness of sustainable farming than the consumer group with low awareness. The empirical results in this study suggest that it is important to consider the economic feasibility of dairy farming by forming a consensus with consumers through publicity and changing the production pattern to promote sustainability.
Spatial Differentiation of Land Use and Landscape Pattern Changes in the Beijing–Tianjin–Hebei Area
Authors: Wang Yafei , Zhao Xiaoli , Zuo Lijun , Zhang Zengxiang , Wang Xiao , Yi Ling , Liu Fang , Xu Jinyong
Published: April 2020

Landscape pattern analysis based on geometric features effectively reflects the spatial patterns of land use. Based on the administrative boundaries of prefecture-level cities, the Beijing–Tianjin–Hebei collaborative development area is divided into three sub-regions, according to ecological–production–living functions. We used remote sensing data of long time series land-use change from late 1980 to 2015, and analyzed landscape pattern changes and spatial differentiation in the past 30 years. The results show that: (1) The main type of land-use change was the flow of cultivated land to urban construction land, and the urbanization process was significant. (2) The urban construction land was the landscape type with the highest degree of fragmentation and maximum land-use change in the region. (3) The patch density in the Beijing–Tianjin–Hebei area increased while the average patch area decreased, and the entire landscape tended towards significant fragmentation. The Shannon diversity and evenness indexes continued to increase, indicating that the overall landscape in this region is heterogeneous and diversified. The ecological and environmental protection measures implemented in this region so far have achieved results, but require more stringent measures to ensure the total diversification of land use in the region.
A Sustainable Solution to Overtourism in the Social Media Era: An Exploratory Analysis on the Roles and Functions of Place–Visitor Relationship (PVR)
Authors: Lee Hyung Min , Park Jinwoo , Nam Yoonjae
Published: April 2020

As overtourism has become a serious threat to the tourism industry in recent years, this study attempts to extend the theoretical framework of organization-public relationship (OPR) developed in the public relations scholarship to the context of overtourism. To that end, the concept of place–visitor relationship (PVR) is theoretically suggested and empirically tested in a structural equation model. Also, statistical reliability and validity of PVR are put under investigation. The findings helped confirm the roles and functions of PVR as a potential solution to overtourism in the social media era. As an antecedent, visitors’ affective tour experiences stemming from exposure to social media information significantly influenced PVR. PVR, on the other hand, significantly affected attitudes toward a place and, further, behavioral intentions toward measures against overtourism. In addition, the findings revealed that PVR consists of two sub-factors: Loyalty and relational attachment. Relationship strategies as a solution to the issue of overtourism are discussed in light of PVR.
Crisis Response and Supervision System for Food Security: A Comparative Analysis between Mainland China and Taiwan
Authors: Ma Chun-Chieh , Chen Han-Shen , Chang Hsiao-Ping
Published: April 2020

In Mainland China, major food security incidents have occurred with high frequency, of which the number and degree of harm are both increasing. At the same time, Taiwan’s food security crisis has also been spreading. For these reasons, this article makes a comparative analysis of food security issues between Mainland China and Taiwan from a legal point of view and identifies the blind spots of the legal system and supervision using official documents and research papers regarding the most typical incidents in the period of 2008–2019. The results indicate that, compared with Mainland China, Taiwan has a better food security supervision system, and its experience with the supervision system, specific rules, social supervision, and responsibility is worth investigating. However, while there are loopholes in criminal law in Mainland China, which has not formed a complete system, criminal law in Taiwan is also weak in terms of regulation of food security incidents. Based on the results, this article puts forward suggestions with the expectation that, in the face of an increasingly severe food security crisis, Mainland China and Taiwan will strengthen their cooperation in constructing legal systems for food security supervision and inspection, exchange experience, cooperate in inspection, and share food security information to avoid rumors of food insecurity circulating in popular science. It is expected that the results and suggestions of this study will be helpful in the crisis response, as well as in the supervision systems in Mainland China and Taiwan for guarding food security. Although the comparative analysis is specific to the two regions, its characteristics are typical of food security globally, especially in Asia.
Geographical Indications and Price Volatility Dynamics of Lamb Prices in Spain
Authors: Ferrer-Pérez Hugo , Abdelradi Fadi , Gil José M.
Published: April 2020

For decades, food quality standards have attracted the interest of governance institutions and regulation authorities, who have responded to the increasing and demanding societal challenges. In addition, the open debate on significant variability and unusually high levels of agrifood prices recorded in 2007 and later in 2011 affect the behavior of the chain actors involved. As an attempt to bring together these wide concerns within a quantitative framework, a comparative analysis of the performance of the price volatility dynamics allowing for asymmetric behavior along the supply chain of a protected geographical indication (PGI)-certified lamb and its corresponding non-PGI counterpart, both located in the same region of Spain, was undertaken using weekly farm-retail prices for the period 2011–2018. The results indicate the existence of significant volatilities and an asymmetric transmission mechanism along the non-PGI-certified lamb supply chain, whereas the PGI-certified supply chain is impacted by volatility effects, yet characterized by symmetric behavior, which may suggest a high degree of relative market efficiency.
The Whole Lifecycle Management Efficiency of the Public Sector in PPP Infrastructure Projects
Authors: Wang Nannan , Ma Minxun , Liu Yunfei
Published: April 2020

The management role of the public sector in public–private partnership PPP infrastructure projects has been extensively expanded to the whole lifecycle rather than in the traditional infrastructure projects. The performance of the public sector in a PPP is the key for the PPP to achieve sustainability; however, there is a lack of research on the whole lifecycle management efficiency of the public sector in a PPP. This research aims to examine the governance role of the public sector in PPP projects, and therefore evaluate their whole lifecycle management efficiency. An evaluation framework is developed through the lens of governmentality to evaluate the performance of the public sector. Multiple case studies on PPP infrastructure projects in China have identified loopholes during the whole lifecycle of a PPP at the local governmental level. On the basis of the findings of case studies, a conceptual model is proposed to demonstrate ways for the public sector to improve efficiency through integrated governance of PPP projects. The research findings benefit both the central government in terms of evaluation and decision making and the local government by improving their efficiency in PPP infrastructure projects for the purpose of achieving sustainability. According to the findings, policy strategies are provided for the central government on how to further regulate the PPP market and address the loopholes, including further standardizing regulations and instruction, providing unified quantitative calculation or measurement tools, training, and education for the public sector to integrate whole lifecycle project management, and quality control of consultancy for the PPP infrastructure projects.
What Are the Conflicting Tensions in an Italian Cooperative and How Do Members Manage Them? Business Goals’, Integrated Management, and Reduction of Waste within a Fruit and Vegetables Supply Chain
Authors: Pellegrini Giustina , Annosi Maria Carmela , Contò Francesco , Fiore Mariantonietta
Published: April 2020

Social enterprise is a model of hybrid organization driven by the need to generate positive externalities by reinvesting their surplus for social and environmental objectives. One of the biggest problems arising from joining financial goals with social goals is the presence of increasing tensions between the members and stakeholders involved. Nevertheless, there has not been enough focus on how managers, employees, and stakeholders respond to the tensions caused by contradictions and how they try to reach a balance between financial, environmental, and social goals. Therefore, the present study is aimed at investigating how members of an agricultural cooperative in the Apulia region (Italy) try to join the organizational forms of business and social values, namely, the sustainable practices related to CO2 emission reduction, resource use efficiency, and food waste mitigation. Additionally, the study goes further and explores whether and how these contradictory pressures are solved. Starting from the sensemaking approach, the study carried out an inductive case study through the use of a multiple case study design and in-depth interviews. The findings highlight the following two novel aspects: (1) Managers prefer to adopt a cumulative mitigating hybridization approach and (2) a weak integration can be noticed between social and commercial dimensions, originating from a lack of holistic perspective and poor interorganizational communication.
Chinese Demand for Agritourism in Rural America
Authors: Wu Tong , Henneberry Shida Rastegari , Ng’ombe John N. , Melstrom Richard T.
Published: April 2020

China is one of the largest sources of outbound tourists coming to the United States. We used data from a choice experiment to determine whether Chinese tourists are interested and willing to pay for agritourism tour packages in which the U.S. state of Oklahoma is the rural destination. Our research is important because agritourism is a growing source of farm revenue, international tourists have potential to accelerate this growth, and China is the largest market for international tourism. Results suggest that, from various agritourism packages offered to them, Chinese travelers are price conscious but willing to pay significant amounts for packages that provide more local foods, that allow them to visit more event and recreation sites, and stay in cabins rather than farmstead accommodations. We also find evidence of significant heterogeneity in Chinese willingness to pay for agritourism attributes.
Application of Affordance Factors for User-Centered Smart Homes: A Case Study Approach
Authors: Cho Younjoo , Choi Anseop
Published: April 2020

Smart homes improve quality of life by providing various services based on information and communication technologies. However, smart home systems are complicated and user interfaces for the interaction between smart home and user are often not user-friendly, causing potential difficulties and inconvenience for the user. Therefore, in order for smart homes to become user-centered, usability needs to be improved. This study aims to present guidelines for improving the usability of smart homes based on the concept of affordance, which is highly meaningful in user-centered design. To do this, firstly, the affordance factors that could be applied to improve the usability of active devices and user interfaces in smart homes were extracted, secondly, a case study was conducted to analyze the application of affordance factors, focusing on active devices (e.g., control devices and smart appliances) and user interfaces that directly interact with users in smart homes. Lastly, guidelines on the application of affordance factors were presented by combining case analysis results with relevant guidelines. Active devices and user interfaces should provide users with appropriate cognitive, physical, functional, and sensory affordances so that users can use the smart home services easily and conveniently.
Cruise Tourism for Sustainability: An Exploration of Value Chain in Shenzhen Shekou Port
Authors: Liu Yanhong , Dong Erwei , Li Shiqi , Jie Xiaowen
Published: April 2020

Based on the support of governmental policies and the rapid growth of China’s economic development, residents’ living standards, and tourism consumption demand, cruise tourism has continuously developed and its service level has gradually improved, which have become the main driving forces for the sustainable growth of China’s cruise tourism industry. This paper took Shenzhen Shekou Port (SSP) as a research site and used an online text analysis method by Rost Content Mining 6 software to analyze 2552 Ctrip travel network, and then did further study through face to face interviews from the perspective of “tourists source” and “procurement” in the value chain theory. Only by understanding the developing trend of cruise tourists can we cultivate cruise culture, expand cruise tourism market, and finally realize the benign development of cruise tourism. The research results show that the cruise business in Shenzhen should strengthen the senior citizens market and marketing to kids and parents, and improve the satisfaction of cruise passengers in terms of enriching entertainment facilities, elevating service quality, and upgrading duty-free shopping centers. This paper not only focused on the study of cruise tourists in Southern China, but also enriches the research of the cruise value chain.
Efficiency Analysis of Water Conservation Measures in Sanitary Infrastructure Systems by Means of a Systemic Approach
Authors: Richter Karoline , Santos Daniel Costa dos , Schmid Aloísio Leoni
Published: April 2020

The challenges of urban water management and sanitary infrastructure (water supply (WSS), sewage (SS), urban drainage (UDS) systems) are increasingly frequent in Brazilian cities whether as a combined result of overcrowding and/or a lack governmental interest and hence investments, in the sector. Such an increase in environmental pressure reflects directly on population welfare and well-being related to the availability of drinking water, wastewater treatment, and access to effective drainage systems in order to minimize, or at least reduce, the occurrence of urban flooding and associated public health risks. Thus, alternatives with an integrated approach to urban water management are interesting to the reality of countries such as Brazil. The urban water use (UWU) model is a strategic planning tool with integrated way of thinking, which selects measures to mitigate the urban impacts in sanitary infrastructure and buildings. In this sense, the objective of this research is to apply the UWU model in a case study in Curitiba/Brazil to demonstrate the effect of the systematic approach and its intrinsic synergies in the systems in question, promoting water conservation in urban areas. The results are favorable to integrated systems with synergy use, evidencing quantitatively a greater efficiency in them.
Framework of Spatial Flood Risk Assessment for a Case Study in Quang Binh Province, Vietnam
Authors: Luu Chinh , Tran Hieu Xuan , Pham Binh Thai , Al-Ansari Nadhir , Tran Thai Quoc , Duong Nga Quynh , Dao Nam Hai , Nguyen Lam Phuong , Nguyen Huu Duy , Thu Ta Huong , Le Hiep Van , Meding Jason von
Published: April 2020

Vietnam has been extensively affected by floods, suffering heavy losses in human life and property. While the Vietnamese government has focused on structural measures of flood defence such as levees and early warning systems, the country still lacks flood risk assessment methodologies and frameworks at local and national levels. In response to this gap, this study developed a flood risk assessment framework that uses historical flood mark data and a high-resolution digital elevation model to create an inundation map, then combined this map with exposure and vulnerability data to develop a holistic flood risk assessment map. The case study is the October 2010 flood event in Quang Binh province, which caused 74 deaths, 210 injuries, 188,628 flooded properties, 9019 ha of submerged and damaged agricultural land, and widespread damages to canals, levees, and roads. The final flood risk map showed a total inundation area of 64,348 ha, in which 8.3% area of low risk, 16.3% area of medium risk, 12.0% area of high risk, 37.1% area of very high risk, and 26.2% area of extremely high risk. The holistic flood risk assessment map of Quang Binh province is a valuable tool and source for flood preparedness activities at the local scale.
Circular Economy Concept in the Context of Economic Development in EU Countries
Authors: Sverko Grdic Zvonimira , Krstinic Nizic Marinela , Rudan Elena
Published: April 2020

The need has arisen to implement a circular economic model that enables economic growth and prosperity in accordance with environmental protection and sustainable development because of the current unsustainable linear means of production in the economy. The aim of this paper is to determine the application of the circular economy concept in member countries of the European Union from 2008 to 2016. The purpose is to analyse whether economic development measured by GDP (gross domestic product) affects the analysed circular economy variables. Based on the hypotheses set, an econometric model was formed where GDP was identified as an independent variable, while the dependent variables were the production of municipal waste per capita, the recycling rate of municipal waste, the recycling rate of packaging waste by type of packaging, the recycling of bio-waste, and the recycling rate of e-waste. The first part of the statistical analysis conducted using the Stata software package shows the Pearson correlation between the abovestated variables, while the second part explores the univariate regression model. The results point towards the conclusion that the application of the circular economy concept can ensure economic growth and GDP growth while reducing the use of natural resources and ensuring greater environmental protection.
MOOC Video Personalized Classification Based on Cluster Analysis and Process Mining
Authors: Zhang Feng , Liu Di , Liu Cong
Published: April 2020

In the teaching based on MOOC (Massive Open Online Courses) and flipped classroom, a teacher needs to understand the difficulty and importance of MOOC videos in real time for students at different knowledge levels. In this way, a teacher can be more focused on the different difficulties and key points contained in the videos for students in a flipped classroom. Thus, the personalized teaching can be implemented. We propose an approach of MOOC video personalized classification based on cluster analysis and process mining to help a teacher understand the difficulty and importance of MOOC videos for students at different knowledge levels. Specifically, students are first clustered based on their knowledge levels through question answering data. Then, we propose the process model of a group of students which reflects the overall video watching behavior of these students. Next, we propose to use the process mining technique to mine the process model of each student cluster by the video watching data of the involved students. Finally, we propose an approach to measure the difficulty and importance of a video based on a process model. With this approach, MOOC videos can be classified for students at different knowledge levels according to difficulty and importance. Therefore, a teacher can carry out a flipped classroom more efficiently. Experiments on a real data set show that the difficulty and importance of videos obtained by the proposed approach can reflect students’ subjective evaluation of the videos.
Evaluation of the Importance of Some East Asian Tree Species for Refinement of Air Quality by Estimating Air Pollution Tolerance Index, Anticipated Performance Index, and Air Pollutant Uptake
Authors: Kwak Myeong Ja , Lee Jong Kyu , Park Sanghee , Lim Yea Ji , Kim Handong , Kim Kyeong Nam , Je Sun Mi , Park Chan Ryul , Woo Su Young
Published: April 2020

Potentials of tree species as biofilters depend on appropriate selection based on their tolerance to air pollution, which is usually evaluated by the air pollution tolerance index (APTI) and anticipated performance index (API). Thus, these index values need as a means of scientific understanding to assess the role of urban trees for better greenspace planning/management to mitigate impacts of gaseous air pollution such as ozone (O3) and sulfur dioxide (SO2). O3 exposure to Chionanthus retusus, Pinus densiflora, and Ginkgo biloba showed higher stomatal O3 flux than the others, finally resulting in both favoring stomatal movement and maintaining carbon fixation. In contrast, despite the whole tree enhanced SO2 uptake under excess SO2 exposure, the carbon assimilation capacity was only found in Taxus cuspidata and Zelkova serrata as a consequence of no stomatal sluggishness. On the basis of API, P. densiflora and Prunus × yedoensis were good performers for developing greenspace, while Z. serrata and G. biloba were moderate performers; however, C. retusus and T. cuspidata were estimated to be poor and very poor performers, respectively, for reducing the air quality injury caused by air pollutants. The present study suggests that an integration of both APTI and API based on stomatal absorption flux is needed for selecting sound tree-species in greenspace planning/construction to control gaseous air pollutions.