bluuebunny/crossref_metadata_2025 huggingface dataset:
Hierarchical Sub-Pixel Anomaly Detection Framework for Hyperspectral Imagery
Authors: Wang Wenzheng , Zhao Baojun , Feng Fan , Nan Jinghong , Li Cheng
Published: October 2018

Anomaly detection is an important task in hyperspectral processing. Some previous works, based on statistical information, focus on Reed-Xiaoli (RX), as it is one of the most classical and commonly used methods. However, its performance tends to be affected when anomaly target size is smaller than spatial resolution. Those sub-pixel anomaly target spectra are usually much similar with background spectra, and may results in false alarm for traditional RX method. To address this issue, this paper proposes a hierarchical RX (H-RX) anomaly detection framework to enhance the performance. The proposed H-RX method consists of several different layers of original RX anomaly detector. In each layer, the RX’s output of each pixel is restrained by a nonlinear function and then imposed as a coefficient on its spectrum for the next iteration. Furthermore, we design a spatial regularization layer to enhance the sub-pixel anomaly detection performance. To better illustrate the hierarchical framework, we provide a theoretical explanation of the hierarchical background spectra restraint and regularization process. Extensive experiments on three hyperspectral images illustrate that the proposed anomaly detection algorithm outperforms the original RX algorithm and some other classical methods.
Securing Heterogeneous Wireless Sensor Networks: Breaking and Fixing a Three-Factor Authentication Protocol
Authors: Aghili Seyed Farhad , Mala Hamid , Peris-Lopez Pedro
Published: October 2018

Heterogeneous wireless sensor networks (HWSNs) are employed in many real-time applications, such as Internet of sensors (IoS), Internet of vehicles (IoV), healthcare monitoring, and so on. As wireless sensor nodes have constrained computing, storage and communication capabilities, designing energy-efficient authentication protocols is a very important issue in wireless sensor network security. Recently, Amin et al. presented an untraceable and anonymous three-factor authentication (3FA) scheme for HWSNs and argued that their protocol is efficient and can withstand the common security threats in this sort of networks. In this article, we show how their protocol is not immune to user impersonation, de-synchronization and traceability attacks. In addition, an adversary can disclose session key under the typical assumption that sensors are not tamper-resistant. To overcome these drawbacks, we improve the Amin et al.’s protocol. First, we informally show that our improved scheme is secure against the most common attacks in HWSNs in which the attacks against Amin et al.’s protocol are part of them. Moreover, we verify formally our proposed protocol using the BAN logic. Compared with the Amin et al.’s scheme, the proposed protocol is both more efficient and more secure to be employed which renders the proposal suitable for HWSN networks.
A Smart Pillow for Health Sensing System Based on Temperature and Humidity Sensors
Authors: Li Songsheng , Chiu Christopher
Published: October 2018

The quality of sleep affects the patient’s health, along with the observation of vital life signs such as body temperature and sweat in sleep, is essential in the monitoring of sleep as well as clinical diagnosis. However, traditional methods in recording physiological change amidst sleep is difficult without being intrusive. The smart pillow is developed to provide a relatively easy way to observe one’s sleep condition, employing temperature and humidity sensors by implanting them inside the pillow in strategic positions. With the patient’s head on the pillow, the roles of sensors are identified as main, auxiliary or environmental temperature, based on the differences of value from three temperature sensors, thus the pattern of sleep can be extracted by statistical analysis, and the body temperature is inferred by a specially designed Fuzzy Logic System if the head-on position is stable for more than 15 min. Night sweat is reported on data from the humidity sensor. Therefore, a cloud-based health-sensing system is built in the smart pillow to collect and analyze data. Experiments from various individuals prove that statistical and inferred results reflect normal and abnormal conditions of sleep accurately. The daily sleeping information of patients from the pillow is helpful in the decision-making of diagnoses and treatment, and users can change their habits of sleep gradually by observing the data with their health professional.
Mapping Urban Extent Using Luojia 1-01 Nighttime Light Imagery
Authors: Li Xi , Zhao Lixian , Li Deren , Xu Huimin
Published: October 2018

Luojia 1-01 satellite, launched on 2 June 2018, provides a new data source of nighttime light at 130 m resolution and shows potential for mapping urban extent. In this paper, using Luojia 1-01 and VIIRS nighttime light imagery, we compared several methods for extracting urban areas, including Human Settlement Index (HSI), Simple Thresholding Segmentation (STS) and SVM supervised classification. According to the accuracy assessment, the HSI method using LJ1-01 data had the best performance in urban extent extraction, which presented the largest Kappa Coefficient value, 0.834, among all the results. For the urban areas extracted by VIIRS based HSI method, the largest Kappa Coefficient value was 0.772. In contrast, the largest Kappa Coefficient values obtained by STS method were 0.79 and 0.7512 respectively when using LJ1-01 and VIIRS data, while for SVM method the values were 0.7829 and 0.7486 when using Landsat-LJ and Landsat-VIIRS composite data respectively. The experimented results demonstrated that the utilization of nighttime light imagery can largely improve the accuracy of urban extent extraction and LJ1-01 data, with a higher resolution and more abundant spatial information, can lead to better identification results than its predecessors.
Application of Computational Intelligence Methods for the Automated Identification of Paper-Ink Samples Based on LIBS
Authors: Rzecki Krzysztof , Sośnicki Tomasz , Baran Mateusz , Niedźwiecki Michał , Król Małgorzata , Łojewski Tomasz , Acharya U Rajendra , Yildirim Özal , Pławiak Paweł
Published: October 2018

Laser-induced breakdown spectroscopy (LIBS) is an important analysis technique with applications in many industrial branches and fields of scientific research. Nowadays, the advantages of LIBS are impaired by the main drawback in the interpretation of obtained spectra and identification of observed spectral lines. This procedure is highly time-consuming since it is essentially based on the comparison of lines present in the spectrum with the literature database. This paper proposes the use of various computational intelligence methods to develop a reliable and fast classification of quasi-destructively acquired LIBS spectra into a set of predefined classes. We focus on a specific problem of classification of paper-ink samples into 30 separate, predefined classes. For each of 30 classes (10 pens of each of 5 ink types combined with 10 sheets of 5 paper types plus empty pages), 100 LIBS spectra are collected. Four variants of preprocessing, seven classifiers (decision trees, random forest, k-nearest neighbor, support vector machine, probabilistic neural network, multi-layer perceptron, and generalized regression neural network), 5-fold stratified cross-validation, and a test on an independent set (for methods evaluation) scenarios are employed. Our developed system yielded an accuracy of 99.08%, obtained using the random forest classifier. Our results clearly demonstrates that machine learning methods can be used to identify the paper-ink samples based on LIBS reliably at a faster rate.
Time Sequential Single-Cell Patterning with High Efficiency and High Density
Authors: Liu Yang , Ren Dahai , Ling Xixin , Liang Weibin , Li Jing , You Zheng , Yalikun Yaxiaer , Tanaka Yo
Published: October 2018

Single-cell capture plays an important role in single-cell manipulation and analysis. This paper presents a microfluidic device for deterministic single-cell trapping based on the hydrodynamic trapping mechanism. The device is composed of an S-shaped loop channel and thousands of aligned trap units. This arrayed structure enables each row of the device to be treated equally and independently, as it has row periodicity. A theoretical model was established and a simulation was conducted to optimize the key geometric parameters, and the performance was evaluated by conducting experiments on MCF-7 and Jurkat cells. The results showed improvements in single-cell trapping ability, including loading efficiency, capture speed, and the density of the patterned cells. The optimized device can achieve a capture efficiency of up to 100% and single-cell capture efficiency of up to 95%. This device offers 200 trap units in an area of 1 mm2, which enables 100 single cells to be observed simultaneously using a microscope with a 20× objective lens. One thousand cells can be trapped sequentially within 2 min; this is faster than the values obtained with previously reported devices. Furthermore, the cells can also be recovered by reversely infusing solutions. The structure can be easily extended to a large scale, and a patterned array with 32,000 trap sites was accomplished on a single chip. This device can be a powerful tool for high-throughput single-cell analysis, cell heterogeneity investigation, and drug screening.
Spiral Sound Wave Transducer Based on the Longitudinal Vibration
Authors: Lu Wei , Lan Yu , Guo Rongzhen , Zhang Qicheng , Li Shichang , Zhou Tianfang
Published: October 2018

A spiral sound wave transducer comprised of longitudinal vibrating elements has been proposed. This transducer was made from eight uniform radial distributed longitudinal vibrating elements, which could effectively generate low frequency underwater acoustic spiral waves. We discuss the production theory of spiral sound waves, which could be synthesized by two orthogonal acoustic dipoles with a phase difference of 90 degrees. The excitation voltage distribution of the transducer for emitting a spiral sound wave and the measurement method for the transducer is given. Three-dimensional finite element modeling (FEM)of the transducer was established for simulating the vibration modes and the acoustic characteristics of the transducers. Further, we fabricated a spiral sound wave transducer based on our design and simulations. It was found that the resonance frequency of the transducer was 10.8 kHz and that the transmitting voltage resonance was 140.5 dB. The underwater sound field measurements demonstrate that our designed transducer based on the longitudinal elements could successfully generate spiral sound waves.
Phenology-Based Residual Trend Analysis of MODIS-NDVI Time Series for Assessing Human-Induced Land Degradation
Authors: Chen Hao , Liu Xiangnan , Ding Chao , Huang Fang
Published: October 2018

Land degradation is a widespread environmental issue and an important factor in limiting sustainability. In this study, we aimed to improve the accuracy of monitoring human-induced land degradation by using phenological signal detection and residual trend analysis (RESTREND). We proposed an improved model for assessing land degradation named phenology-based RESTREND (P-RESTREND). This method quantifies the influence of precipitation on normalized difference vegetation index (NDVI) variation by using the bivariate linear regression between NDVI and precipitation in pre-growing season and growing season. The performances of RESTREND and P-RESTREND for discriminating land degradation caused by climate and human activities were compared based on vegetation-precipitation relationship. The test area is in Western Songnen Plain, Northeast China. It is a typical region with a large area of degraded drylands. The MODIS 8-day composite reflectance product and daily precipitation data during 2000–2015 were used. Our results showed that P-RESTREND was more effective in distinguishing different drivers of land degradation than the RESTREND. Degraded areas in the Songnen grasslands can be effectively detected by P-RESTREND. Therefore, this modified model can be regarded as a practical method for assessing human-induced land degradation.
Cascaded-Cavity Fabry-Perot Interferometric Gas Pressure Sensor based on Vernier Effect
Authors: Chen Peng , Dai Yutang , Zhang Dongsheng , Wen Xiaoyan , Yang Minghong
Published: October 2018

An extrinsic Fabry-Perot interferometer (EFPI) composed of double fiber FP cavities in a glass capillary tube to generate Vernier effect has been fabricated and employed for gas pressure sensing. A lead-in single-mode fiber (LSMF) and a reflective single-mode fiber (RSMF) were inserted into the capillary tube to form a FP cavity. Femtosecond (fs) laser was used to ablate openings on a capillary tube for gas passage to the FP cavity. A fusion hole was also drilled on the end face of a SMF by fs laser. The sensitivity of the sensor is enhanced due to Vernier effect. Experimental results show that the sensitivity was as high as 86.64 nm/MPa in the range of 0~0.6 MPa, which is 32.8 times larger than that of an open-cavity EFPI sensor without Vernier effect. The temperature cross-sensitivity of the sensor was measured to be about 5.18 KPa/°C. The proposed sensor was characterized by its high sensitivity, compact structure and ease of fabrication, and would have extensive application prospects in gas sensing fields.
Consensus-Based Filter for Distributed Sensor Networks with Colored Measurement Noise
Authors: Wang Jinran , Dong Peng , Jing Zhongliang , Cheng Jin
Published: October 2018

Consensus filtering is an effective method for distributed state estimation of distributed sensor networks and the assumption of white measurement noise is widely used. However, when the measurement noise is colored, the traditional consensus filter cannot work well. In this paper, we first propose a consensus-based distributed filter for colored measurement noise by augmenting the state to include the colored measurement noise. To improve the efficiency of the filter, only local colored measurement noise is integrated into the augmented state for each local filter. Furthermore, another consensus-based distributed filter based on measurement differencing scheme is developed to eliminate the ill-conditioned computations of the augmented state approach. In addition, this method does not need to augment the state and thus has lower dimension than the augmented state filter. Simulation results demonstrate the superiority of the proposed methods.
IPL: Image-Assisted Person Localization for Underground Coal Mines
Authors: Niu Qiang , Yang Xu , Yin Yuqing
Published: October 2018

Underground personnel localization is highly important in the operations of coal mines. Considering the special underground environment, this paper introduces a novel localization scheme based on step detection and image recognition technologies, which makes use of unique characteristics of the underground environment like the dark environment and the miner’s lamp. Since the underground topology is relatively simple, the miner can be located only by step information. However, the localization with step information always causes the problem of cumulative error. To solve this problem, we rebuild a special base station with a camera in a dark underground environment. A miner’s lamp, which every miner carries, can simply transform to irradiate unique shapes (such as triangles, rectangles, and circles) and every coal miner at the base station can identify these shapes based on image recognition technologies. Thus, we can obtain the miner’s precise position when he/she is passing by a base station. In that way, we can correct the localization results to solve cumulative error. We implemented our algorithm in indoor and underground environments. The experimental results show that 96% of spatial errors were 2.5 m or less.
Assessment of Soil Fertility under Different Land-Use Systems in Dhading District of Nepal
Authors: Kharal Sudarshan , Khanal Babu Ram , Panday Dinesh
Published: October 2018

Unscientific land use and cropping techniques have led high soil erosion and degradation of soil quality in the mid-hills of Nepal. To understand the effects of land use systems for selected soil chemical properties in mid-hills, composite soil samples at 0 cm to 20 cm depth were collected from five different land-use systems: Grassland, forest land, upland, lowland, and vegetable farms from Dhading district of Nepal in 2017. Soil samples were analyzed for soil fertility parameters: Soil pH, organic matter (OM), total nitrogen (N), available phosphorus (P), available potassium (K) and its effect due to different land use systems were compared. Results showed that soil pH was neutral in vegetable farms (6.61), whereas the rest of the land-use systems had acidic soils. Soil OM (3.55%) and N (0.18%) content was significantly higher in forest, but the lowest soil OM (1.26%) and N (0.06%) contents were recorded from upland and lowland farms, respectively. Available P was the highest in the vegetable farm (41.07 mg kg−1) and was the lowest in grazing land (2.89 mg kg−1). The upland farm had significantly higher P levels (39.89 mg kg−1) than the lowland farm (9.02 mg kg−1). Available K was the highest in the vegetable farm (130.2 mg kg−1) and lowest in grazing land (36.8 mg kg−1). These results indicated that the land under traditional mixed cereal-based farming had poor soil health compared with adjacent vegetable, grazing, and forest lands among the study area. The variations in soil fertility parameters suggest the immediate need for improvement in soil health of traditional farmlands.
Products of Hexavalent Chromium Reduction by Green Rust Sodium Sulfate and Associated Reaction Mechanisms
Authors: N. Thomas Andrew , Eiche Elisabeth , Göttlicher Jörg , Steininger Ralph , G. Benning Liane , M. Freeman Helen , Dideriksen Knud , Neumann Thomas
Published: October 2018

The efficacy of in vitro Cr(VI) reduction by green rust sulfate suggests that this mineral is potentially useful for remediation of Cr-contaminated groundwater. Previous investigations studied this reaction but did not sufficiently characterize the intermediates and end products at chromate (CrO42−) concentrations typical of contaminant plumes, hindering identification of the dominant reaction mechanisms under these conditions. In this study, batch reactions at varying chromate concentrations and suspension densities were performed and the intermediate and final products of this reaction were analyzed using X-ray absorption spectroscopy and electron microscopy. This reaction produces particles that maintain the initial hexagonal morphology of green rust but have been topotactically transformed into a poorly crystalline Fe(III) oxyhydroxysulfate and are coated by a Cr (oxy) hydroxide layer that results from chromate reduction at the surface. Recent studies of the behavior of Cr(III) (oxy) hydroxides in soils have revealed that reductive transformation of CrO42− is reversible in the presence of Mn(IV) oxides, limiting the applicability of green rust for Cr remediation in some soils. The linkage of Cr redox speciation to existing Fe and Mn biogeochemical cycles in soils implies that modification of green rust particles to produce an insoluble, Cr(III)-bearing Fe oxide product may increase the efficacy of this technique.
E-Participation, Rural Regime, and Network Governance: A Case of Balien River Conservation
Authors: Lan Cassidy I-Chih , Peng Li-Pei
Published: October 2018

The regime theory has been widely applied to analyze the governing capacity for urban community development. However, it has seldom been translated to the countryside, even though rural communities often reveal some potential for self-governance and a capacity to act. With the emergence of information technology, social network services have become popular and have changed the social interactions between the public and private sectors. By considering the rural case of river conservation in New Taipei City, this paper used the regime theory to investigate the governing capacity of rural collaborative networks and the influence of social network services on coordination. We found that the regime theory can be used to explore rural communities with strong collaborative networks and local identities. The adoption of communication tools based on social network services strengthens informal public-private coordination wherein the power geometry of rural regimes is upgraded from ‘power-to’ to ‘power-amidst’, thus, advancing the solidarity of the community networks and prompting the rise of vital coalitions and the governing capacity of rural actors.
Drivers for Public–Private Partnerships in Sustainable Natural Resource Management—Lessons from the Swedish Mountain Region
Authors: Thellbro Camilla , Bjärstig Therese , Eckerberg Katarina
Published: October 2018

Sweden’s mountain areas are sensitive ecosystems that are used by a wide range of stakeholders, and this raises multiple sustainability concerns. Collaborative governance solutions are becoming increasingly common in such situations to promote more sustainable practices. While the Swedish mountain area is indeed a hot spot for different forms of public–private partnerships (PPPs) related to natural resources management, as yet, little is known about the shaping of participation, leadership, and implementation of these processes. What are the drivers for implementing collaborative environmental partnerships, do the drivers differ, and if so, how? What role does the specific context play in the design of these PPPs? Are the PPPs useful, and if so, for what? To analyze those issues, we conducted 38 semi-structured interviews with project leaders from a sample randomly selected from a database of 245 public–private collaborative projects in the Swedish mountains. Our results indicate that consequential incentives in the form of funding and previous successful collaborations seem to be the major drivers for such partnerships. A critical discussion of the possibilities and limitations of public–private forms of governance in rural mountain areas adds to the ongoing debate on the performance of environmental PPPs in a regional context.
Analyzing the Level of Accessibility of Public Urban Green Spaces to Different Socially Vulnerable Groups of People
Authors: Rahman K M Atikur , Zhang Dunfu
Published: October 2018

This study estimates the factors affecting socially vulnerable groups’ demand for and accessibility levels to green public spaces in Dhaka City, Bangladesh. Dhaka is a high-density city with one of the lowest levels of green space per capita in the world. Dhaka has just 8.5% of tree-covered lands, while an ideal city requires at least 20% of green space. Urban public green space provides a healthy environment to city dwellers as well as ecological soundness. This study aims to examine the effects of population density and size of a community area (Thana) on the social demand for and accessibility to green parks. To determine the socially vulnerable group demand index, this study used demographic data from the National Population and Housing Census 2011 conducted by the Bangladesh Bureau of Statistics. This study used geographical data extracted from Google Earth Pro to measure accessibility levels, and additionally analyzed geographical data with ArcGIS 10.0 and Google Earth Pro. We drew radius circles using Free Map Tools to measure time-distance weighted scores from community areas to urban green spaces. The results show that the large population size of socially vulnerable groups creates very high demand at the score of 0.61 for urban green public parks and small-sized, high-density community areas generate very good accessibility at 2.01% to green public spaces. These findings are highly useful to policymakers, urban planners, landscape engineers, and city governments to make a compact city sustainable, inclusive, and resilient. Moreover, the notion of a “smart city” might be a smart solution in order to manage Dhaka Megacity sustainably in this modern technological age.
Sleep Duration and Sleep Quality as Predictors of Health in Elderly Individuals
Authors: Štefan Lovro , Vučetić Vlatko , Vrgoč Goran , Sporiš Goran
Published: October 2018

The main purpose of the present study was to explore the associations of sleep duration and sleep quality with self-rated health. In this cross-sectional study, participants were 894 elderly individuals. Self-rated health, sleep duration, and sleep quality were self-reported. The associations were examined using multiple logistic regression analyses.After adjusting for sex, physical activity, smoking consumption, alcohol consumption, psychological distress, socioeconomic status, and chronic disease/s, sleeping <6 h (OR (Odds ratio) = 3.21; 95% CI (95 percent confident interval) 1.61 to 6.39), 6–7 h (OR = 2.47; 95% CI 1.40 to 4.36), 8–9 h (OR = 3.26; 95% CI 1.82 to 5.83), and >9 h (OR = 3.62; 95% CI 1.57 to 8.34) and having ‘poor’ sleep quality (≥5 points; OR = 2.33; 95% CI 1.46 to 3.73) were associated with ‘poor’ self-rated health. When sleep duration and sleep quality were entered simultaneously into the model, the same associations remained. Our findings provide evidence that both ‘short’ and ‘long’ sleep and ‘poor’ sleep quality are associated with ‘poor’ self-rated health. Thus, interventions that promote healthy sleep hygiene in the elderly are warranted.
Innovative Forms of Economy and Sustainable Urban Development—Sharing Tourism
Authors: Tescașiu Bianca , Epuran Gheorghe , Tecău Alina Simona , Chițu Ioana Bianca , Mekinc Janez
Published: October 2018

Sharing economy represents a new business model with an increasing impact on economic life by generating consequences for the traditional business sector. Considering its development during the last years, it is important to know how the governance system should react to the new challenges determined by this kind of doing business. The aim of the article is to identify and analyze some general issues regarding the impact on the sharing economy in tourism, based on a study regarding the needs determined by this business model in Brașov. Considering that tourism is a relevant sector for the “sharing” business type, the authors considered it important to get opinions about the way that the local authorities and stakeholders should contribute to the creation of a regulatory framework for sharing tourism, so, two focus-groups were organized. The respondents were chosen so that all kinds of stakeholders involved in tourism were represented. The results of the research revealed that even though there are some provisions regarding this sector, and despite the fact that local and regional authorities are preoccupied about regulations in sharing tourism, the most representative part of this sector is unregistered and it works according to its own rules.
Urban Water Crises under Future Uncertainties: The Case of Institutional and Infrastructure Complexity in Khon Kaen, Thailand
Authors: Friend Richard , Thinphanga Pakamas
Published: October 2018

This paper uses the emerging crises in water management in North East Thailand as a case study to examine the effectiveness of existing institutional structures and processes to adapt to an uncertain future climate. We argue that it is through an analysis of the interface of actors, institutions and physical infrastructure that climate vulnerability can be better understood, and conversely, that climate resilience might be strengthened. This research has global significance as case studies of emerging water crises provide valuable insights into future vulnerabilities and the Thailand experience speaks to similar challenges across the global South. Our findings illustrate that water managers on the front line of dealing with climate variability are constrained by the interaction of infrastructure that was designed for different times and needs, and of institutional structures and processes that have emerged through the interplay of often competing organisational remits and agendas. Water management is further constrained by the ways in which information and knowledge are generated, shared, and then applied. Critically the research finds that there is no explicit consideration of climate change, but rather universally-held assumptions that patterns of water availability will continue as they have in the past. As a result, there is no long-term planning that could be termed adaptive, but rather, a responsive approach that moves from crisis to crisis between seasons and across years.
The Investigation of Consumers’ Behavior Intention in Using Green Skincare Products: A Pro-Environmental Behavior Model Approach
Authors: Chin Jacky , Jiang Bernard C. , Mufidah Ilma , Persada Satria Fadil , Noer Bustanul Arifin
Published: October 2018

Increasing environmental awareness among societies is motivating consumers to use green cosmetic products. Green skincare products are the fastest growing sector in the worldwide market compared with other green cosmetic products. However, compared with general cosmetic products, the market share of green cosmetic products in Indonesia is relatively low. The present research investigated consumers’ purchasing intentions toward green skincare products in Indonesia using the pro-environmental reasoned action (PERA) model. A total of 251 female consumers participated in this study. Structural equation modeling was conducted to reveal the relationships between the five factors in the PERA model. The results indicated that perceived authority support (PAS) has a positive effect on perceived environmental concern (PEC). PAS and PEC have positive effects on attitude (AT) and subjective norms (SN), and AT and SN have positive effects on behavioral intention (BI) to purchase green skincare products, with the key factor being attitude. The PERA model was able to describe 62.6% of the BI to purchase green skincare products. Green skincare companies are recommended to produce more green skincare products and market the products by involving public figures and emphasizing the green attributes. Furthermore, we recommend that green skincare companies produce quality and sustainable products using quality processes, and be involved in pro-environmental activity to increase consumer attention to the green skincare products.
A Scale Development of Retailer Equity
Authors: Lee Seong Ho , Lee Sun-Ho
Published: October 2018

Retailer equity is becoming a very important factor in determining discriminatory competitive advantage under rapidly changing conditions of distribution. This study conceptualizes various retailer equity aspects considered in the retail industry and proposes a measurement scale for retailer equity based on empirical research. Our study aims to reveal how retailer equity sub-dimensions influence customer perception and evaluation of retailers. The primary objective of this research was to develop a measurement scale to facilitate assessments of consumer-based retailer equity. Resulting theoretical and managerial implications of this study are also discussed in detail.
How Blockchain Can Shape Sustainable Global Value Chains: An Evidence, Verifiability, and Enforceability (EVE) Framework
Authors: Nikolakis William , John Lijo , Krishnan Harish
Published: October 2018

Law, regulation, and private standards have evolved to enhance sustainability in value chains. However, the volume of hard and soft laws has created complexity and fragmentation for consumers and firms. In addition, global value chains are increasingly disaggregated, making it difficult for consumers to enforce breaches of sustainability representations. Blockchain, as an immutable and digital record keeping system, is a tool that can deal with this growing complexity in global value chains. Documents verifying sustainability that were once in the private domain and stored in paper copy can now be made accessible in a secure and transparent blockchain platform. Despite a growing interest in the potential of blockchain to transform businesses, there are few concrete examples or scholarly literature showing how blockchain is operationalized in practice. Using a “conceptual framework analysis” approach, we develop an Evidence, Verifiability, and Enforceability (EVE) framework to illustrate how blockchain can enhance sustainability by providing information to consumers on the origin of products, assurances as to the veracity of the information, and a mechanism to enforce representations through the blockchain smart contract function. However, there need to be safeguards put in place for blockchain technology to meet its promise and we discuss some of these challenges.
Exploring Users’ Self-Disclosure Intention on Social Networking Applying Novel Soft Computing Theories
Authors: Chin Yang-Chieh , Su Wen-Zhong , Chen Shih-Chih , Hou Jianing , Huang Yu-Chuan
Published: October 2018

In recent years, users have increasingly focused on the privacy of social networking sites (SNS); users have reduced their self-disclosure intention. To attract users, SNS rely on active platforms that collect accurate user information, even though that information is supposed to be private. SNS marketers must understand the key elements for sustainable operation. This study aims to understand the influence of motivation (extrinsic and intrinsic) and self-disclosure on SNS through soft computing theories. First, based on a survey of 1108 users of SNS, this study used a dominance-based rough set approach to determine decision rules for self-disclosure intention on SNS. In addition, based on 11 social networking industry experts’ perspectives, this study validated the influence between the motivation attributes by using Decision-Making Trial and Evaluation Laboratory (DEMATEL). In this paper, the decision rules of users’ self-disclosure preference are presented, and the influences between motivation attributes are graphically depicted as a flow network graph. These findings can assist in addressing real-world decision problems, and can aid SNS marketers in anticipating, evaluating, and acting in accord with the self-disclosure motivations of SNS users. In this paper, practical and research implications are offered.
Practice Framework for the Management of Post-Disaster Housing Reconstruction Programmes
Authors: Bilau Abdulquadri Ade , Witt Emlyn , Lill Irene
Published: October 2018

Despite an international consensus for housing to be “built back better” (BBB) following disasters, and the considerable resources expended on reconstruction efforts globally, the management of post-disaster housing reconstruction programmes often leaves much to be desired. This research presents a framework for the management of post-disaster housing reconstruction in developing countries based on a comprehensive identification of the issues affecting the management of reconstruction programmes and the management measures which have proved effective in mitigating these issues and achieving the desired BBB outcomes. The framework highlights the strategic importance of preparedness measures that should be taken before the next disaster strikes and the cross-cutting nature of capacity building and beneficiary community engagement measures that are essential to all stages of the post-disaster reconstruction process. The research findings are limited to developing countries, as the evidence on which they are based is almost entirely from post-disaster housing experiences in the developing world. The framework may, however, be adapted to different, specific post-disaster reconstruction contexts. This research has compiled, extended and up-dated current knowledge regarding the management of housing reconstruction programmes and it provides practical guidance for policy makers and practitioners.
Trade-Old-for-Remanufactured Closed-Loop Supply Chains with Carbon Tax and Government Subsidies
Authors: Shu Tong , Huang Chunfen , Chen Shou , Wang Shouyang , Lai Kin Keung
Published: October 2018

The constantly increasing CO2 emissions are threatening the environment tremendously. Facing the pressure of environmental activists and public opinion, businesses and governments are taking action to reduce carbon emissions. Among these endeavors, carbon tax and subsidy policies proposed by governments are widely adopted. Remanufacturing is believed to save manufacturing costs and reduce carbon emissions from the process of enterprise operation, and it is increasingly being accepted by enterprises. However, different consumers’ willingness to pay for remanufactured products and the durability of new products will also affect consumers’ willingness to buy remanufactured products. Therefore, considering the discrepancy between consumer willingness to pay and product durability, we established the trade-old-for-remanufactured (TOR) model for a scenario of carbon tax and government subsidies. Through the analysis of the model, we obtained the optimal pricing and production decisions of manufacturers (remanufacturers) in the case of carbon tax and government subsidies. Our results show that, when there is no carbon tax constraint, the increase in consumer willingness to pay and the adjustment in product durability can stimulate consumers to participate in TOR projects and augment enterprises’ profits. However, it can also lead to a carbon rebound that increases corporate carbon emissions. When there is a carbon tax constraint, the introduction of carbon tax contributes to a reduction in carbon emissions, while enterprises tend to lose profits. In order to achieve a “win-win” between corporate profits and carbon emissions, we considered government subsidy policies. Our numerical examples illustrate that appropriate carbon tax and government subsidies can curb carbon emissions and also increase profits for enterprises.
The Task Assignment of Vehicles for a Production Company
Authors: Jacyna Marianna , Izdebski Mariusz , Szczepański Emilian , Gołda Paweł
Published: October 2018

The article investigates the problem of task assignment of vehicles for a production company. The presented problem is a complex decision-making issue which has not been analyzed in the literature before. Two stages must be passed through in order to solve the task assignment problem of the vehicles for the production company. The first stage is to designate the tasks, the other one is to determine the number of the vehicles that is needed to perform these tasks. The task in the analyzed problem is defined as transporting the cargo from the suppliers to the warehouses and from the warehouses to the production company. The number of the tasks depends on the type of the vehicle which carries out a given task. In order to solve the presented problem, the mathematical model has been developed, i.e., decision variables, constraints, and criterion functions. There are three types of decision variables occurring in the model, which means that this problem is quite complex. The first type of the decision variables determines the volume of the cargo which flows among the facilities on a given working day, the second type of the decision variables determines the use of a given type of the vehicle in the task, and the third type of the decision variables determines the number of the vehicles which perform the task. The criterion functions take the following form: the fuel consumption costs, the transition costs of the cargo via the warehouses, the purchase costs of the cargo, and the task completion time. In order to solve the task assignment problem of the vehicles, a genetic algorithm has been developed. The proposed method of task assignment solution is unique due to the coding method of individuals and related recombination procedures. The construction stages of this algorithm are presented. The algorithm has been verified by the use of the real input data. The developed model and method of its solution are unique in the application to the service of manufacturing enterprises. Due to the high efficiency and multi-aspect approach, it can be applied in enterprises of various industries as support for decision-makers in the optimization of resources.
Hybrid Synchronization Problem of a Class of Chaotic Systems by an Universal Control Method
Authors: Wang Zuoxun , Guo Rongwei
Published: October 2018

The hybrid synchronization problem of a class of chaotic systems is investigated in this paper. Firstly, the existence of hybrid synchronization problems in such systems is proved theoretically by a proposed necessary and sufficient condition. That is, the hybrid synchronization problem is equivalent to solve a group of nonlinear algebraic equations about α . It is interesting that one value of α indicates one type of synchronization. Secondly, all solutions for the hybrid synchronization problem are obtained by finding solutions of all the above equations about α . Thirdly, an universal control method is proposed to realize such hybrid synchronization problems. Finally, illustrative examples are provided to verify the validity and effectiveness of the obtained results.
Efficient Joint Estimation of Carrier Frequency and Sampling Frequency Offsets for MIMO-OFDM ATSC Systems
Authors: Jung Yong-An , You Young-Hwan
Published: October 2018

Multiple-input multiple-output orthogonal frequency division multiplexing (MIMO-OFDM) is appealing for the provision of high spectral efficiency in digital terrestrial broadcast systems. To fully obtain its advantageous features, it is very important to remove the frequency mismatch between the transmitter and the receiver. In this paper, we present the performance analysis of joint estimation of carrier and sampling frequency offsets in the MIMO-OFDM-based advanced television systems committee (ATSC) 3.0 system. In the MIMO-OFDM ATSC system, the continual pilot (CP) is primarily utilized to perform frequency synchronization. To efficiently suppress an unwanted bias introduced by the presence of random-likely located CPs, an optimal pilot subset is selected to form the basis of least squares frequency-offset estimation. A closed-form mean squared error is derived in the context of MIMO-OFDM, considering the multipath fading channel. We show via computer simulations and numerical analysis that the proposed estimation method achieves higher estimation accuracy than the existing estimation method.
Nuclear Magnetic Resonance seq (NMRseq): A New Approach to Peptide Sequence Tags
Authors: Wilson David , Daly Norelle L.
Published: October 2018

Structural analysis of peptides with nuclear magnetic resonance (NMR) spectroscopy generally relies on knowledge of the primary sequence to enable assignment of the resonances prior to determination of the three-dimensional structure. Resonance assignment without knowledge of the sequence is complicated by redundancy in amino acid type, making complete de novo sequencing using NMR spectroscopy unlikely to be feasible. Despite this redundancy, we show here that NMR spectroscopy can be used to identify short sequence tags that can be used to elucidate full-length peptide sequences via database searching. In the current study, we have used this approach to identify conotoxins from the venom of the cone snail Conus geographus and determined the three-dimensional structure of a member of the I3 superfamily. This approach is most likely to be useful for the characterization of disulfide-rich peptides, such as those that were chosen for this study, as they generally have well-defined structures, which enhances the quality of the NMR spectra. In contrast to other sequencing methods, the lack of sample manipulation, such as protease digestion, allows for subsequent bioassays to be carried out using the native sample used for sequence identification.
Investigation of a Scabies Outbreak in Drought-Affected Areas in Ethiopia
Authors: Enbiale Wendemagegn , Ayalew Ashenafi
Published: October 2018

The impact of the severe drought in Ethiopia, attributed to El Niño weather conditions, has led to high levels of malnutrition that have, in turn, increased the potential for disease outbreaks. In 2015, Ethiopia faced a scabies outbreak in drought-affected areas where there was a shortage of safe water for drinking and personal hygiene. Following a house-to-house census to assess the prevalence of scabies, a detailed study was conducted looking at the disease burden. Following the outbreak report, training was provided on scabies identification and management for zonal and district health officials from administrative districts affected by the drought (nutritional hot-spot woredas). The training was cascaded down to the health extension workers in the affected areas. Screening and management guidelines and protocols were also distributed. House-to-house data collection was undertaken by 450 health extension workers (HEWs) to assess the prevalence of scabies. The HEWs used a simplified reporting tool. Subsequently, data were collected and validated in two zones and six woredas from 474 participants who had been diagnosed with scabies using a standardized questionnaire. This was designed to look at the specificity of the diagnosis of scabies, age distribution, severity, duration of illness, secondary infection and other sociodemographic variables as preparation for mass drug administration (MDA). The HEWs screened 1,125,770 people in the 68 districts in Amhara Region and a total of 379,000 confirmed cases of scabies was identified. The prevalence in the different districts ranged from 2% to 67% and the median was 33.5% [interquartile range (IQR) 19–48%]. 49% of cases were school-aged children. The detailed study of 474 individuals who were recorded as scabies cases revealed that the specificity of the diagnosis of scabies by the HEWs was 98.3%. The mean duration of illness was 5 months (SD of ± 2.8). One third of patients were recorded as having severe illness, 75.1% of cases had affected family members, and 30% of affected children were noted to have secondary bacterial infection. Eleven percent of the students had discontinued school due to scabies or/and drought and 85% of these had secondary bacterial infection. These community-based data serve as reliable proxy indicators for community-based burden assessment of the scabies epidemic. This study will also provide a good basis for advocating the use of a community-level clinical diagnostic scheme for scabies using an algorithm with a simple combination of signs and symptoms in resource-poor settings.
On Testing Frame-Dragging with LAGEOS and a Recently Announced Geodetic Satellite
Authors: Iorio Lorenzo
Published: October 2018

Recently, Ciufolini and coworkers announced the forthcoming launch of a new cannonball geodetic satellite in 2019. It should be injected in an essentially circular path with the same semimajor axis a of LAGEOS (Laser Geodynamics Satellite), in orbit since 1976, and an inclination I of its orbital plane supplementary with respect to that of its existing cousin. According to their proponents, the sum of the satellites’ precessions of the longitudes of the ascending nodes Ω should allow one to test the general relativistic Lense–Thirring effect to a ≃0.2% accuracy level, with a contribution of the mismodeling in the even zonal harmonics J ℓ , ℓ = 2 , 4 , 6 , … of the geopotential to the total error budget as little as 0.1 % . Actually, such an ambitious goal seems to be hardly attainable because of the direct and indirect impact of, at least, the first even zonal J 2 . On the one hand, the lingering scatter of the estimated values of such a key geophysical parameter from different recent GRACE/GOCE-based (Gravity Recovery and Climate Experiment/Gravity field and steady-state Ocean Circulation Explorer) global gravity field solutions is representative of an uncertainty which may directly impact the summed Lense–Thirring node precessions at a ≃70–80% in the worst scenarios, and to a ≃3–10% level in other, more favorable cases. On the other hand, the phenomenologically measured secular decay a ˙ of the semimajor axis of LAGEOS (and, presumably, of the other satellite as well), currently known at a σ a ˙ ≃ 0.03 m yr − 1 level after more than 30 yr, will couple with the sum of the J 2 -induced node precessions yielding an overall bias as large as ≃20–40% after 5–10 yr. A further systematic error of the order of ≃2–14% may arise from an analogous interplay of the secular decay of the inclination I ˙ with the oblateness-driven node precessions.