bluuebunny/crossref_metadata_2025 huggingface dataset:
A Clutter-Analysis-Based STAP for Moving FOD Detection on Runways
Authors: Yang Xiaoqi , Huo Kai , Zhang Xinyu , Jiang Weidong , Chen Yong
Published: January 2019

Security risks and economic losses of civil aviation caused by Foreign Object Debris (FOD) have increased rapidly. Synthetic Aperture Radars (SARs) with high resolutions potentially have the capability to detect FODs on the runways, but the target echo is hard to be distinguished from strong clutter. This paper proposes a clutter-analysis-based Space-time Adaptive Processing (STAP) method in order to obtain effective clutter suppression and moving FOD indication, under inhomogeneous clutter background. Specifically, we first divide the radar coverage into equal scattering cells in the rectangular coordinates system rather than the polar ones. We then measure normalized RCSs within the X-band and employ the acquired results to modify the parameters of traditional models. Finally, we describe the clutter expressions as responses of the scattering cells in space and time domain to obtain the theoretical clutter covariance. Experimental results at 10 GHz show that FODs with a reflection higher than −30 dBsm can be effectively detected by a Linear Constraint Minimum Variance (LCMV) filter in azimuth when the noise is −60 dBm. It is also validated to indicate a −40 dBsm target in Doppler. Our approach can obtain effective clutter suppression 60dB deeper than the training-sample-coupled STAP under the same conditions.
Electromagnetic Modeling and Structure Optimization of a Spherical Force Sensing System
Authors: Yan Liang , Liu Yinghuang , Jiao Zongxia
Published: January 2019

Force sensing system (FSS) is widely used to simulate the control force of aircrafts for pilots. Conventional FSS employs multiple single-axis motors and complex transmission mechanisms to achieve multiple degree-of-freedom (DOF) force output of joystick, which may cause mismatched inertia and affect the output performance of FSS significantly. Therefore, one novel FSS with multiple DOF direct-drive spherical actuator is proposed in this paper to reduce the simulator’s extra inertia. To analyze its output performance systematically, a hybrid modeling method is proposed to formulate both Ampere torque and cogging torque mathematically. Equivalent current method along with Ampere force law is used to obtain the Ampere torque due to irregular structure of magnet and coil poles. The cogging torque is then obtained from airgap flux density via Maxwell stress method. From the derived analytical model, an adaptive particle swarm optimization (PSO) algorithm based on expectation (the average value of minimum errors) is proposed for multiple-parameter structure optimization. It can avoid local optimization effectively. The study shows that the optimized value greatly helps to improve the torque generation. Then, one research prototype and one testbed is developed. The comparison between experimental result and analytical model shows that the two sets of data fit with each other well. Therefore, the analytical model could be employed for motion control of the system at the next stage.
Spatial Reorganization of Myoelectric Activities in Extensor Digitorum for Sustained Finger Force Production
Authors: Gao Zhixian , Tang Shangjie , Wu Xiaoying , Fu Qiang , Fan Xingyu , Zhao Yun , Hu Lintao , Chen Lin , Hou Wensheng
Published: January 2019

The study aims to explore the spatial distribution of multi-tendinous muscle modulated by central nervous system (CNS) during sustained contraction. Nine subjects were recruited to trace constant target forces with right index finger extension. Surface electromyography (sEMG) of extensor digitorum (ED) were recorded with a 32-channel electrode array. Nine successive topographic maps (TM) were obtained. Pixel wise analysis was utilized to extract subtracted topographic maps (STM), which exhibited inhomogeneous distribution. STMs were characterized into hot, warm, and cool regions corresponding to higher, moderate, and lower change ranges, respectively. The relative normalized area (normalized to the first phase) of these regions demonstrated different changing trends as rising, plateauing, and falling over time, respectively. Moreover, the duration of these trends were found to be affected by force level. The rising/falling periods were longer at lower force levels, while the plateau can be achieved from the initial phase for higher force output (45% maximal voluntary contraction). The results suggested muscle activity reorganization in ED plays a role to maintain sustained contraction. Furthermore, the decreased dynamical regulation ability to spatial reorganization may be prone to induce fatigue. This finding implied that spatial reorganization of muscle activity as a regulation mechanism contribute to maintain constant force production.
CDSP: A Solution for Privacy and Security of Multimedia Information Processing in Industrial Big Data and Internet of Things
Authors: Yang Xu , Hou Yumin , Ma Junping , He Hu
Published: January 2019

With the widespread nature of wireless internet and internet of things, data have bloomed everywhere. Under the scenario of big data processing, privacy and security concerns become a very important consideration. This work focused on an approach to tackle the privacy and security issue of multimedia data/information in the internet of things domain. A solution based on Cryptographical Digital Signal Processor (CDSP), a Digital Signal Processor (DSP) based platform combined with dedicated instruction extension, has been proposed, to provide both programming flexibility and performance. We have evaluated CDSP, and the results show that the algorithms implemented on CDSP all have good performance. We have also taped out the platform designed for privacy and security concerns of multimedia transferring system based on CDSP. Using TSMC 55 nm technology, it could reach the speed of 360 MHz. Benefiting from its programmability, CDSP can be easily expanded to support more algorithms in this domain.
Analyzing of Gender Behaviors from Paths Using Process Mining: A Shopping Mall Application
Authors: Dogan Onur , Bayo-Monton Jose-Luis , Fernandez-Llatas Carlos , Oztaysi Basar
Published: January 2019

The study presents some results of customer paths’ analysis in a shopping mall. Bluetooth-based technology is used to collect data. The event log containing spatiotemporal information is analyzed with process mining. Process mining is a technique that enables one to see the whole process contrary to data-centric methods. The use of process mining can provide a readily-understandable view of the customer paths. We installed iBeacon devices, a Bluetooth-based positioning system, in the shopping mall. During December 2017 and January and February 2018, close to 8000 customer data were captured. We aim to investigate customer behaviors regarding gender by using their paths. We can determine the gender of customers if they go to the men’s bathroom or women’s bathroom. Since the study has a comprehensive scope, we focused on male and female customers’ behaviors. This study shows that male and female customers have different behaviors. Their duration and paths, in general, are not similar. In addition, the study shows that the process mining technique is a viable way to analyze customer behavior using Bluetooth-based technology.
Data Association for Multi-Object Tracking via Deep Neural Networks
Authors: Yoon Kwangjin , Kim Du Yong , Yoon Young-Chul , Jeon Moongu
Published: January 2019

With recent advances in object detection, the tracking-by-detection method has become mainstream for multi-object tracking in computer vision. The tracking-by-detection scheme necessarily has to resolve a problem of data association between existing tracks and newly received detections at each frame. In this paper, we propose a new deep neural network (DNN) architecture that can solve the data association problem with a variable number of both tracks and detections including false positives. The proposed network consists of two parts: encoder and decoder. The encoder is the fully connected network with several layers that take bounding boxes of both detection and track-history as inputs. The outputs of the encoder are sequentially fed into the decoder which is composed of the bi-directional Long Short-Term Memory (LSTM) networks with a projection layer. The final output of the proposed network is an association matrix that reflects matching scores between tracks and detections. To train the network, we generate training samples using the annotation of Stanford Drone Dataset (SDD). The experiment results show that the proposed network achieves considerably high recall and precision rate as the binary classifier for the assignment tasks. We apply our network to track multiple objects on real-world datasets and evaluate the tracking performance. The performance of our tracker outperforms previous works based on DNN and comparable to other state-of-the-art methods.
Towards Establishing Cross-Platform Interoperability for Sensors in Smart Cities
Authors: Chaturvedi Kanishk , Kolbe Thomas H.
Published: January 2019

Typically, smart city projects involve complex distributed systems having multiple stakeholders and diverse applications. These applications involve a multitude of sensor and IoT platforms for managing different types of timeseries observations. In many scenarios, timeseries data is the result of specific simulations and is stored in databases and even simple files. To make well-informed decisions, it is essential to have a proper data integration strategy, which must allow working with heterogeneous data sources and platforms in interoperable ways. In this paper, we present a new lightweight web service called InterSensor Service allowing to simply connect to multiple IoT platforms, simulation specific data, databases, and simple files and retrieving their observations without worrying about data storage and the multitude of different APIs. The service encodes these observations “on-the-fly” according to the standardized external interfaces such as the OGC Sensor Observation Service and OGC SensorThings API. In this way, the heterogeneous observations can be analyzed and visualized in a unified way. The service can be deployed not only by the users to connect to different sources but also by providers and stakeholders to simply add further interfaces to their platforms realizing interoperability according to international standards. We have developed a Java-based implementation of the InterSensor Service, which is being offered free as open source software. The service is already being used in smart city projects and one application for the district Queen Elizabeth Olympic Park in London is shown in this paper.
A Two-Dimensional Adaptive Target Detection Algorithm in the Compressive Domain
Authors: Cao Wenhuan , Huang Shucai
Published: January 2019

By applying compressive sensing to infrared imaging systems, the sampling and transmitting time can be remarkably reduced. Therefore, in order to meet the real-time requirements of infrared small target detection tasks in the remote sensing field, many approaches based on compressive sensing have been proposed. However, these approaches need to reconstruct the image from the compressive domain before detecting targets, which is inefficient due to the complex recovery algorithms. To overcome this drawback, in this paper, we propose a two-dimensional adaptive threshold algorithm based on compressive sensing for infrared small target detection. Instead of processing the reconstructed image, our algorithm focuses on directly detecting the target in the compressive domain, which reduces both the time and memory requirements for image recovery. First, we directly subtract the spatial background image in the compressive domain of the original image sampled by the two-dimensional measurement model. Then, we use the properties of the Gram matrix to decode the subtracted image for further processing. Finally, we detect the targets by employing the advanced adaptive threshold method to the decoded image. Experiments show that our algorithm can achieve an average 100% detection rate, with a false alarm rate lower than 0.4%, and the computational time is within 0.3 s, on average.
A Common Assessment Space for Different Sensor Structures
Authors: Wen Wei , Kajínek Ondřej , Khatibi Siamak , Chadzitaskos Goce
Published: January 2019

The study of the evolution process of our visual system indicates the existence of variational spatial arrangement; from densely hexagonal in the fovea to a sparse circular structure in the peripheral retina. Today’s sensor spatial arrangement is inspired by our visual system. However, we have not come further than rigid rectangular and, on a minor scale, hexagonal sensor arrangements. Even in this situation, there is a need for directly assessing differences between the rectangular and hexagonal sensor arrangements, i.e., without the conversion of one arrangement to another. In this paper, we propose a method to create a common space for addressing any spatial arrangements and assessing the differences among them, e.g., between the rectangular and hexagonal. Such a space is created by implementing a continuous extension of discrete Weyl Group orbit function transform which extends a discrete arrangement to a continuous one. The implementation of the space is demonstrated by comparing two types of generated hexagonal images from each rectangular image with two different methods of the half-pixel shifting method and virtual hexagonal method. In the experiment, a group of ten texture images were generated with variational curviness content using ten different Perlin noise patterns, adding to an initial 2D Gaussian distribution pattern image. Then, the common space was obtained from each of the discrete images to assess the differences between the original rectangular image and its corresponding hexagonal image. The results show that the space facilitates a usage friendly tool to address an arrangement and assess the changes between different spatial arrangements by which, in the experiment, the hexagonal images show richer intensity variation, nonlinear behavior, and larger dynamic range in comparison to the rectangular images.
Cigarette Smoking Detection with An Inertial Sensor and A Smart Lighter
Authors: Senyurek Volkan , Imtiaz Masudul , Belsare Prajakta , Tiffany Stephen , Sazonov Edward
Published: January 2019

In recent years, a number of wearable approaches have been introduced for objective monitoring of cigarette smoking based on monitoring of hand gestures, breathing or cigarette lighting events. However, non-reactive, objective and accurate measurement of everyday cigarette consumption in the wild remains a challenge. This study utilizes a wearable sensor system (Personal Automatic Cigarette Tracker 2.0, PACT2.0) and proposes a method that integrates information from an instrumented lighter and a 6-axis Inertial Measurement Unit (IMU) on the wrist for accurate detection of smoking events. The PACT2.0 was utilized in a study of 35 moderate to heavy smokers in both controlled (1.5–2 h) and unconstrained free-living conditions (~24 h). The collected dataset contained approximately 871 h of IMU data, 463 lighting events, and 443 cigarettes. The proposed method identified smoking events from the cigarette lighter data and estimated puff counts by detecting hand-to-mouth gestures (HMG) in the IMU data by a Support Vector Machine (SVM) classifier. The leave-one-subject-out (LOSO) cross-validation on the data from the controlled portion of the study achieved high accuracy and F1-score of smoking event detection and estimation of puff counts (97%/98% and 93%/86%, respectively). The results of validation in free-living demonstrate 84.9% agreement with self-reported cigarettes. These results suggest that an IMU and instrumented lighter may potentially be used in studies of smoking behavior under natural conditions.
Testing for Equality of Parameters from Different Load-Sharing Systems
Authors: Bedbur Stefan , Kamps Udo
Published: January 2019

In reliability, sequential order statistics serve as a model for the component lifetimes of k-out-of-n systems, which are operating as long as k out of n components are operating. In contrast to modelling with order statistics, load-sharing effects and other impacts of failures on the performance of the remaining components may be taken into consideration. Inference for associated load-sharing parameters, as well as for the underlying baseline distribution, is then of particular interest. In a setup of multiple samples of sequential order statistics modelling the component lifetimes of possibly differently structured k-out-of-n systems, we provide exact statistical tests to check for common load-sharing or common baseline-distribution parameters. In the two-sample case, critical values for the corresponding test statistics are tabulated for small sample sizes, and the asymptotic distributions of the test statistics under the null hypotheses are derived. Based on a simulation study, power comparisons are addressed. The proposed tests may be applied to detect significant differences between systems or to decide whether a meta-analysis of the data may be conducted to increase the performance of subsequent inferential procedures.
Spatial Explicit Assessment of Urban Vitality Using Multi-Source Data: A Case of Shanghai, China
Authors: Yue Wenze , Chen Yang , Zhang Qun , Liu Yong
Published: January 2019

Identifying urban vitality in large cities is critical for optimizing the urban fabric. While great attention has been paid to urban vitality in developed countries, related studies have been rarely conducted in developing countries. In this study, we defined urban vitality as the capacity of an urban built environment to boost lively social activities and developed a framework for measuring urban vitality using the dimensions of built environment, human activities, and human–environment interaction. Taking Shanghai, China as a case, we conducted a measurement of urban vitality using multi-source data. The results show that Shanghai follows a monocentric vital pattern within the outer ring road, with urban vitality declining from the central urban core to the city periphery. While the old urban cores tend to show high urban vitality, Pudong New Area is mostly dominated by low vitality. Three clusters with high urban vitality were identified: the old urban area, the Lujiazui CBD, and residential agglomeration areas. We conducted validation of the measuring results using phone usage density. Urban vitality showed a positive correlation with phone usage density, indicating a high accuracy of assessment. We also discovered that European-style block planning, zoning plan, mixed-functional development, urban renewal regulation, and migrant concentration were playing leading role in urban vitality of Shanghai.
Sustainable Reuse of Groundwater Treatment Iron Sludge for Organic Matter Removal from River Neris Water
Authors: Albrektienė Ramunė , Karaliūnas Karolis , Bazienė Kristina
Published: January 2019

The most important advances in sustainability in the water industry are focused on the reuse of water treatment sludge. The Antaviliai Water Supply Plant, which is located in Lithuania, treats groundwater by removing iron and manganese from it. This technology does not produce water waste, as the iron sludge is used for recycling. In this study, iron sludge received from groundwater treatment is used to remove natural organic matter from river Neris water, which can be used as drinking water. Twelve doses (from 1 to 6 g/L and from 0.1 g/L to 0.9 g/L) of iron sludge powder, with acid and without it, were used. The most effective removal of organic compounds (55.51%) and reduction in water colour (53.12%) were observed when 0.3 g of iron sludge powder and 8 ml of 0.95% H2SO4 solution were added to the tested water. It was found that the use of a conventional coagulant (Al2(SO4)3*17H2O), with and without iron sludge powder, decreased the concentration of organic compounds and water colour from 2.8 to 28.2% compared with the use of a pure coagulant (Al2(SO4)3*17H2O) alone..
Simulation of Drainage Capacity in a Coastal Nuclear Power Plant under Extreme Rainfall and Tropical Storm
Authors: Wang Shuangling , Zhang Wanshun , Chen Fajin
Published: January 2019

To ensure the safety of coastal nuclear power plants, accurately simulating water depth due to flooding resulting from heavy rainfall and tropical storms is important. In this paper, a combined model is developed to analyze and simulate the drainage capacity in a coastal nuclear power plant under the combined action of extreme rainfall and wave overtopping. The combined model consist of a surface two-dimensional flood-routing model, a pipe network model, and an offshore wave model. The method of predictive correction calculation is adopted to calculate the node return flow. The inundated water depth varying with time for different design rainstorm return periods (p = 0.1 and 1%) was simulated and analyzed by the combined model. The maximum inundated water depth is calculated for the important entrances of the workshop. The model was validated and calibrated with the data of the rainfall, outflow discharge, and flow velocity measured on 23 June 2016 in plant. Modeling indicates that the simulated depths are consistent with the observed depths. The results show that the water depths in the left and right of the nuclear power plant are 0.2–0.4 m and 0.3–0.8 m, respectively. The water depth increases of Monitoring Point 22 are the largest in different design rainstorm return periods (p = 0.1 and 1%), which increase by 16% for a rainstorm once every thousand years compared to events occurring once in one hundred years. The main factor influencing water accumulation is wave overtopping, and the seawall, revetments, and pipe system play an important role in decreasing the inundated water depth. Through scientific analysis, a certain decision-making basis has been provided for flood disaster management and a certain security guarantee has also been provided for regional sustainable development.
Planning of the Charging Station for Electric Vehicles Utilizing Cellular Signaling Data
Authors: Jia Jianmin , Liu Chenhui , Wan Tao
Published: January 2019

Electric Vehicles (EVs), by reducing the dependency on fossil fuel and minimizing the traffic-related pollutants emission, are considered as an effective component of a sustainable transportation system. However, the massive penetration of EVs brings a big challenge to the establishment of charging infrastructures. This paper presents the approach to locate charging stations utilizing the reconstructed EVs trajectory derived from the Cellular Signaling Data (CSD). Most previous work focused on the commute trips estimated from the number of jobs and households between traffic analysis zones (TAZs). This paper investigated the large-scale CSD and illustrated the method to generate the 24-hour travel demand for each EV. The complete trip in a day for EV was reconstructed through merging the time sequenced trajectory derived from simulation. This paper proposed a two-step model that grouped the charging demand location into clusters and then identified the charging station site through optimization. The proposed approach was applied to investigate the charging behavior of medium-range EVs with Cellular Signaling Data collected from the China Unicom in Tianjin. The results indicate that over 50% of the charging stations are located within the central urban area. The developed approach could contribute to the planning of future charging stations.
Developing Harvest Strategies to Achieve Ecological, Economic and Social Sustainability in Multi-Sector Fisheries
Authors: Pascoe Sean , Cannard Toni , Dowling Natalie , Dichmont Catherine , Breen Sian , Roberts Tom , Pears Rachel , Leigh George
Published: January 2019

Ecosystem based fisheries management (EBFM) provides a framework to achieve ecological, economic and social sustainability in fisheries. However, developing harvest strategies to achieve these multiple objectives is complex. This is even more so in multi-sector multi-species fisheries. In our study, we develop such harvest strategies for the multi-species Coral Reef Fin Fish Fishery (CRFFF) operating in the waters of Australia’s Great Barrier Reef. The fishery includes recreational, charter and commercial sectors, and is a provider of regional employment and supplier of seafood to both local and export markets. We convened a series of stakeholder workshops and conducted surveys to identify stakeholder objectives and priorities, as well as potential harvest strategy frameworks for the fishery. These potential harvest strategies were assessed against the objectives using a further qualitative impact survey. The analysis identified which frameworks were preferred by different stakeholder groups and why, taking into account the different objective priorities and tradeoffs in outcomes. The new feature of the work was to qualitatively determine which harvest strategies are perceived to best address triple bottom line objectives. The approach is therefore potentially applicable in other complex fisheries developing harvest strategies which, by design, strive to achieve ecological, economic and social sustainability.
Cultural Ecosystem Services Provided by Urban Green Change along an Urban-Periurban Gradient
Authors: Riechers Maraja , Strack Micha , Barkmann Jan , Tscharntke Teja
Published: January 2019

Urbanization by densification is globally increasing and endangers maintenance of urban green and associated social-ecological systems. Cultural ecosystem services play a crucial role in human well-being, especially in urban areas. We analyzed perceived importance of cultural ecosystem services provided by green space in Berlin along an urban-periurban gradient. Based on extensive pretests, we designed a standardized questionnaire and conducted 558 face-to-face interviews. B using multiple regressions and principal component analysis, we show that perceived importance of cultural ecosystem services and patterns of urban green use are affected by an urbanization gradient and associated changes in population density. Important cultural ecosystem services decreases in urban core areas with higher population density, whereas people in periurban areas with more available green spaces exhibit a greater valuation of nature. In contrast, social relations and cultural diversity had the highest importance in the urban core, while cultural heritage, education, natural awareness, recreation, and aesthetical appreciation were higher valued in the less populated periurban areas, suggesting two bundles of cultural ecosystem services.
Influence of Extreme Events in Electric Energy Consumption and Gross Domestic Product
Authors: Vieira Fabrício , Ribeiro Maurício Aparecido , Francisco Antonio Carlos de , Gonçalves Lenzi Giane
Published: January 2019

The objective of this paper was to identify how extreme events can indicate periods of economic instability in variables from the economic and environmental context (per capita Gross Domestic Product (GDP), per capita electric energy consumption, and per capita carbon dioxide (CO2) emission). The research is limited to the population of the country (Brazil) and five cities of Paraná (Curitiba, Londrina, Maringá, Ponta Grossa, and Cascavel). Therefore, the major research interest was focused on finding information related to extreme events and other techniques that are used for interpretation of complex systems currently. The development was based on data collection. The results indicated that extreme events have influence in periods of economic instability. They also evidenced that there is greater correlation in GDP data/electric energy consumption than in GDP data/CO2 emissions or electric energy consumption/CO2 emissions.
“These Grandmas Drove Me Mad. It Was Brilliant!”—Promising Starting Points to Support Citizen Competence for Sustainable Consumption in Adults
Authors: Di Giulio Antonietta , Ruesch Schweizer Corinne , Defila Rico , Hirsch Philipp , Burkhardt-Holm Patricia
Published: January 2019

The article addresses citizen competence for sustainable consumption in adults. It discusses whether it is possible to develop educational offerings for adults (being by nature short and isolated) that effectively promote this competence and whether it makes a difference if sustainable consumption is approached by focusing on good life (quality of life) and justice or by focusing on natural resources and environment (as is suggested by, e.g., environmental literacy approaches). Taking the case of energy policy, it presents an educational intervention (EdIn) developed, implemented, and investigated by the authors. In data-analysis, three approaches were adopted (methodological triangulation), one analysing the deliberations’ cognitive structure, one analysing the participants’ perception, one analysing the participants’ reaction (in terms of the knowledge/concepts and values/concerns they voiced). The results show, firstly, that the didactical design of EdIn was successful with a view to supporting citizen competence in participants. Secondly, they show that in adult civic education sustainable consumption should be approached by focusing on good life and justice. Thirdly, they indicate that people do not necessarily perceive themselves to be part of societal decision-making, leading from the question of the design and content of civic educational activities to the question of their necessity.
Energy Management and Optimization of a PV/Diesel/Battery Hybrid Energy System Using a Combined Dispatch Strategy
Authors: Aziz Ali , Tajuddin Mohammad , Adzman Mohd , Ramli Makbul , Mekhilef Saad
Published: January 2019

In recent years, the concept of hybrid energy systems (HESs) is drawing more attention for electrification of isolated or energy-deficient areas. When optimally designed, HESs prove to be more reliable and economical than single energy source systems. This study examines the feasibility of a combined dispatch (CD) control strategy for a photovoltaic (PV)/diesel/battery HES by combining the load following (LF) strategy and cycle charging (CC) strategy. HOMER software is used as a tool for optimization analysis by investigating the techno-economic and environmental performance of the proposed system under the LF strategy, CC strategy, and combined dispatch CD strategy. The simulation results reveal that the CD strategy has a net present cost (NPC) and cost of energy (COE) values of $110,191 and $0.21/kWh, which are 20.6% and 4.8% lower than those of systems utilizing the LF and CC strategies, respectively. From an environmental point of view, the CD strategy also offers the best performance, with CO2 emissions of 27,678 kg/year. Moreover, the results show that variations in critical parameters, such as battery minimum state of charge, time step, solar radiation, diesel price, and load growth, exert considerable effects on the performance of the proposed system.
Corporate Attitudes towards Big Data and Its Impact on Performance Management: A Qualitative Study
Authors: Pugna Irina Bogdana , Duțescu Adriana , Stănilă Oana Georgiana
Published: January 2019

This paper investigates the organizational challenges raised by Big Data and its impact on the business environment with a focus on performance management. We investigate managers’ perceptions, understanding, and attitudes relating to Big Data and its analytics, in terms of opportunities, extent, limitations, challenges, and implications, with specific reference to performance management. The research methodology we adopt is grounded theory: we develop a reflection guide based on research questions covering the impact and challenges of a data-driven culture on business, and the impact on performance management and the decision-making process. The results obtained from senior executives from 21 Romanian companies leads to a conceptual model that distils the major areas arising from the responses and the interrelationships between them. These reveal several key areas of managerial relevance and suggest fruitful action. In particular, we find that the most critical areas requiring intervention lie in the area of awareness and understanding, goal setting, assessing benefits and limitations, learning to trust data, and commitment to an embedded data-driven culture. In addition to changes within organizations themselves, there are also implications for other stakeholders, such as education providers.
Climate Change Adaptation in the Delta Nile Region of Egypt: Implications for Agricultural Extension
Authors: Kassem Hazem S. , Bello Abdel Raouf Suleiman , Alotaibi Bader M. , Aldosri Fahd O. , Straquadine Gary S.
Published: January 2019

This study used quantitative and qualitative methods to collect data, using questionnaires and interviews, from 792 randomly-selected farmers in two of the governorates in the Nile Delta Region, Egypt. A workshop was organized for 59 extension professionals working in the two governorates, looking at how the adaptive capacity of the agricultural sector towards climate change was being guided by policy-makers. Two focus groups were used: one with senior officials from the regional governorates and the other with central government administrators from the Ministry of Agriculture and Land Reclamation. The study findings suggested that 51.9% of the investigated farmers at the two targeted governorates had no knowledge about the climate change phenomenon. Maximizing the use of manure, changing crop patterns, and crop rotation were the adaptation measures most commonly adopted by aware respondents against climate change. Results of a probit model analysis indicated that farmers’ ability to adapt to climate change was influenced by education level, farm size, diversity of production, and membership of a Water User Association. The study recommended some extension interventions to raise awareness of the anticipated effects of climate change.
Optimism of the Will. Antonio Gramsci Takes in Max Weber
Authors: Sommer Doris , Sacco Pier Luigi
Published: January 2019

Responding to Max Weber’s dour predictions, we enlist Antonio Gramsci’s optimism to suggest how culture can spike development. Weber’s sociological focus took culture to mean shared beliefs and practices. As a culture that derives from the Protestant Ethic, capitalism waged a “war on pleasure.” Weber warned that this unfeeling rationality would generate an “iron cage” to trap our humanity, but his book has been read, paradoxically, as a manual for the lock down. Gramsci, on the contrary, understood culture in its humanistic sense, as a field of aesthetic pleasure, innovation, and debate. For him, a precondition for transformational social change was the broad engagement of masses as empowered collectives (Weber favored charismatic leaders); and pleasure in idiosyncratic forms of artistic as well as rooted expression was the fuel for participating in personal and shared advances. This pleasure in art and collective interpretation contrasts with the exclusionary rituals of commodified pleasure typical of capitalist consumerism. Gramsci’s confidence in the transformational role of creative culture provides a framework for understanding a new wave of inclusive artistic practices that originate in the Global South and that revive the arts as vehicles for active citizenship. Participatory art can re-enchant today’s sorely disenchanted socio-cultural world of mature capitalism.
Does the Role of Media and Founder’s Past Success Mitigate the Problem of Information Asymmetry? Evidence from a UK Crowdfunding Platform
Authors: Usman Sardar Muhammad , Bukhari Farasat Ali Shah , Usman Muhammad , Badulescu Daniel , Sial Muhammad Safdar
Published: January 2019

Crowdfunding is an innovative concept for a new start-ups seeking financial support for their distinctive and novel projects. Despite their popularity, crowdfunding platforms face several key challenges amongst which is information asymmetry between entrepreneurs and influential backers, where credible information must be disclosed by the founders (entrepreneurs) to the potential “backers” in order to assess the potentiality of the project. In order to fill this gap, we developed and tested a model that examines the signaling interaction between the founder and a potential backer through media and the founders’ past success. This model also examines how these two signals (i.e., media and past success) interact so as to mitigate the problem of information asymmetry and to make the project successful. A total of 14,887 projects were extracted from a reward-based platform named Crowdfunder. The data was analyzed by performing Tobit and logistic regression and the model was validated by using the robustness technique. The results strongly mitigate the problem of information asymmetry which improves the rate of success in projects floated on the Crowdfunder platform. We believe that our study will significantly contribute to this nascent yet developing research area by probing for information mechanisms to succeed in crowdfunding.
Optimal Order Policies for Dual-Sourcing Supply Chains under Random Supply Disruption
Authors: Yan Rongfang , Kou Dejun , Lu Bin
Published: January 2019

In this paper, we investigate inventory and order strategies of a two-echelon supply chain, which is composed of two unreliable suppliers that are subject to random disruption. We develop the gross weighted profit benchmark model and the service level constrained model of the supply chain, respectively. We derive the retailer’s optimal order quantity and analyze the retailer’ optimal order policy and also obtain the analytical closed-form solutions. In addition, some numerical examples are provided to illustrate the effect of disruption time, disruption probability and fill rate on the optimal decisions and expected profit.
Time-Frequency Energy Distribution of Ground Motion and Its Effect on the Dynamic Response of Nonlinear Structures
Authors: Tao Dongwang , Lin Jiali , Lu Zheng
Published: January 2019

The ground motion characteristics are essential for understanding the structural seismic response. In this paper, the time-frequency analytical method is used to analyze the time-frequency energy distribution of ground motion, and its effect on the dynamic response of nonlinear structure is studied and discussed. The time-frequency energy distribution of ground motion is obtained by the matching pursuit decomposition algorithm, which not only effectively reflects the energy distribution of different frequency components in time, but also reflects the main frequency components existing near the peak ground acceleration occurrence time. A series of artificial ground motions with the same peak ground acceleration, Fourier amplitude spectrum, and duration are generated and chosen as the earthquake input of the structural response. By analyzing the response of the elasto-perfectly-plastic structure excited by artificial seismic waves, it can be found that the time-frequency energy distribution has a great influence on the structural ductility. Especially if there are even multiple frequency components in the same ground motion phrase, the plastic deformation of the elasto-perfectly-plastic structure will continuously accumulate in a certain direction, resulting in a large nonlinear displacement. This paper reveals that the time-frequency energy distribution of a strong ground motion has a vital influence on the structural response.
The Impact of Fairness Concerns on the Formation of Retailers Alliance with Consideration of Transshipment
Authors: Yu Xiaohong , Wang Sujuan , Zhang Xindong
Published: January 2019

This paper investigated the impact of fairness concerns on the formation of the inventory transshipment strategy alliance through its impact on the ordering decisions and profits of two retailers. The paper introduced reference point dependency to describe the retailer’s fairness concerns utility function, and modeled the strategic alliance system consisting of two retailers involved in transshipment. The conditions for the existence of Nash equilibrium solutions were given. The paper solved the impact of the fairness parameters on order quantities and profits by the implicit function theorem. Based on the theoretical analysis and numerical examples, this paper investigated the formation of a strategic alliance under asymmetric and symmetric fairness concerns. The results are as follows: (1) under asymmetric fairness concerns, when the transshipment price of the retailer with no fairness concerns is no more than the transshipment price of the retailer with fairness concerns, an inventory transshipment strategy alliance can be formed. Otherwise the retailer with no fairness concerns may need to pay the retailer with fairness concerns certain fees in order to form a strategic alliance; (2) under symmetric fairness concerns, two completely symmetric retailers can form strategic alliances.
Green to Gold: Beneficial Impacts of Sustainability Certification and Practice on Tour Enterprise Performance
Authors: Hellmeister André , Richins Harold
Published: January 2019

A growing number of managers in tourism recognize the importance of sustainability to their business success. However, as the majority of tourism enterprises consist of small and medium-sized enterprises that are generally less likely to invest in sustainability practices due to a lack of financial resources, time, and perceived cost-saving opportunities, an industry-wide dissemination of sustainability practices is hampered. This paper explores the benefits of adapting sustainability practices and provides evidence for making the case for incorporating sustainability practices to benefit business success. This study examined sustainability-certified tour enterprises, focusing on the perceived impact that the commitment to sustainable practices through certification has had on tangible financial aspects (potential benefits of increased revenue and decreased operational costs) and intangible benefits (customer satisfaction and employee satisfaction). Also explored were the influence of strategic choices related to sustainable practices (extent of commitment, product range, facilities and equipment, and the application of relevant marketing practices). Study findings were encouraging, identifying cost-savings, increased revenue, enhanced reputation, and customer and employee satisfaction. Energy-savings as well as a greater connection to the community were found to be beneficial outcomes of sustainable practices. Despite its acknowledged dependency on the natural environment as well as cultural assets nature and culture, the tourism industry is perhaps still in its infancy in moving towards industry-wide sustainability success. While academic literature has attributed this to the lack of awareness and low dedication to take action, this study found an indication of a positive relationship between sustainability commitment and financial and non-financial firm performance. The findings extend previous research that focused on larger and more facility-dependent enterprises and suggest that sustainability is a beneficial path to follow regardless of company size and budget.
A Yield-Related Agricultural Drought Index Reveals Spatio-Temporal Characteristics of Droughts in Southwestern China
Authors: Wu Lu , Feng Liping , Li Yizhuo , Wang Jing , Wu Lianhai
Published: January 2019

Southwestern China (SWC), one of the major rain-fed wheat production zones in China, has become vulnerable to drought in recent years under global climate change. To quantify drought severity during the wheat growing season and its impact on yield loss, we selected the Agricultural Production Systems sIMulator (APSIM) model to simulate wheat growth between 1961 and 2010 in SWC. A new drought index was developed considering different weighting factors of drought for yield loss in three growing phases. The index was shown to be reliable in assessing drought severity in the region. On average, an abnormal drought mainly occurred in mid-west Guizhou with a frequency of 10–30%. Central SWC was subjected to moderate drought with a frequency of 10–30%, whereas severe drought often occurred in Southern Sichuan and the middle of Yunnan with a frequency >50%. Temporally, drought severity fluctuated before 1990, but increased significantly afterwards. Our assessment suggested that irrigation during the period from floral initiation to flowering would help to ameliorate the effects of water stress under climatic variability in the region.
E-Commerce Liability and Security Breaches in Mobile Payment for e-Business Sustainability
Authors: Chun Se-Hak
Published: January 2019

This study investigates liability issues in electronic transactions when security or privacy breaches occur. As data is transferred using various devices, such as PCs, mobile phones, tablets, sensors, smart meters, and cars, and various architecture, such as the cloud, IoT, as well as in well-defined network structures in electronic commerce, privacy and security breaches happen. These have become a major hindrance to the development and use of commercial activities on the Internet. There have been many security breach cases, such as those of Target Corporation’s security and payment system (2013), eBay’s cyberattack (2014), Uber’s hacking incident (2016), Facebook’s personal data use and privacy breach (2018), and many others. Therefore, when a dispute regarding electronic transactions arises between a customer and a firm, the allocation of liability is very important for the sustainability of e-businesses. Many cases show that firms are held liable for those incidents. However, the liability allocation rule tends to vary slightly from country to country depending on the application areas. EU countries seem to favor customers. In the United States, there are actually no uniform federal laws relating to business cybersecurity. Also, in the case of cryptocurrency, liability tends to lie with customers. Why is the ruling different? In this regard, this paper analyses the legal framework for security and privacy breaches for sustainable e-businesses. In particular, this paper focuses on the optimal liability in terms of enhancing social welfare when considering both sides—the customer and the firm (or service provider). This paper shows that liability can be generally imposed on the firm’s side when the possibility of security or privacy breaches is high, and the customer’s loss is relatively large. However, the liability depends on the customer’s attitude towards risk, customer’s losses, and the efficiency of security investment.
A Novel Method to Identify Initial Values of Chaotic Maps in Cybersecurity
Authors: Anees Amir , Hussain Iqtadar
Published: January 2019

Chaos theory has applications in several disciplines and is focusing on the behavior of dynamical systems that are highly sensitive to initial conditions. Chaotic dynamics are the impromptu behavior displayed by some nonlinear dynamical frameworks and have been used as a source of diffusion in cybersecurity for more than two decades. With the addition of chaos, the overall strength of communication security systems can be increased, as seen in recent proposals. However, there is a major drawback of using chaos in communication security systems. Chaotic communication security systems rely on private keys, which are the initial values and parameters of chaotic systems. This paper shows that these chaotic communication security systems can be broken by identifying those initial values through the statistical analysis of standard deviation and variance. The proposed analyses are done on the chaotic sequences of Lorenz chaotic system and Logistic chaotic map and show that the initial values and parameters, which serve as security keys, can be retrieved and broken in short computer times. Furthermore, the proposed model of identifying the initial values can also be applied on other chaotic maps as well.