Showing papers on "Literature survey published in 2018"
TL;DR: This paper attempts to present a comprehensive review of AI algorithms in rotating machinery fault diagnosis, from both the views of theory background and industrial applications.
1,287 citations
TL;DR: The paper presents a brief overview of smart cities, followed by the features and characteristics, generic architecture, composition, and real-world implementations ofSmart cities, and some challenges and opportunities identified through extensive literature survey on smart cities.
925 citations
TL;DR: This article describes the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning, and provides insights into widespread and emerging modeling approaches to civil applications of UAVs.
Abstract: Unmanned aerial vehicles (UAVs), or aerial drones, are an emerging technology with significant market potential. UAVs may lead to substantial cost savings in, for instance, monitoring of difficult-to-access infrastructure, spraying fields and performing surveillance in precision agriculture, as well as in deliveries of packages. In some applications, like disaster management, transport of medical supplies, or environmental monitoring, aerial drones may even help save lives. In this article, we provide a literature survey on optimization approaches to civil applications of UAVs. Our goal is to provide a fast point of entry into the topic for interested researchers and operations planning specialists. We describe the most promising aerial drone applications and outline characteristics of aerial drones relevant to operations planning. In this review of more than 200 articles, we provide insights into widespread and emerging modeling approaches. We conclude by suggesting promising directions for future research.
576 citations
TL;DR: A comprehensive survey of instance retrieval over the last decade, presenting milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods.
Abstract: In the early days, content-based image retrieval (CBIR) was studied with global features. Since 2003, image retrieval based on local descriptors ( de facto SIFT) has been extensively studied for over a decade due to the advantage of SIFT in dealing with image transformations. Recently, image representations based on the convolutional neural network (CNN) have attracted increasing interest in the community and demonstrated impressive performance. Given this time of rapid evolution, this article provides a comprehensive survey of instance retrieval over the last decade. Two broad categories, SIFT-based and CNN-based methods, are presented. For the former, according to the codebook size, we organize the literature into using large/medium-sized/small codebooks. For the latter, we discuss three lines of methods, i.e., using pre-trained or fine-tuned CNN models, and hybrid methods. The first two perform a single-pass of an image to the network, while the last category employs a patch-based feature extraction scheme. This survey presents milestones in modern instance retrieval, reviews a broad selection of previous works in different categories, and provides insights on the connection between SIFT and CNN-based methods. After analyzing and comparing retrieval performance of different categories on several datasets, we discuss promising directions towards generic and specialized instance retrieval.
554 citations
TL;DR: It is evident from the literature survey that decolorization by the adsorption shows a great promise for the removal of color from dyehouse effluent and if biomasses want to compete with the established ion-exchange resins and activated carbon, their dye binding capacity will need to be substantially improved.
449 citations
TL;DR: This finding indicates that the implementation of the ecological restoration projects in China has significantly increased ecosystem C sequestration across the country and demonstrates that these restoration projects have substantially contributed to CO2 mitigation in China.
Abstract: The long-term stressful utilization of forests and grasslands has led to ecosystem degradation and C loss. Since the late 1970s China has launched six key national ecological restoration projects to protect its environment and restore degraded ecosystems. Here, we conducted a large-scale field investigation and a literature survey of biomass and soil C in China's forest, shrubland, and grassland ecosystems across the regions where the six projects were implemented (∼16% of the country's land area). We investigated the changes in the C stocks of these ecosystems to evaluate the contributions of the projects to the country's C sink between 2001 and 2010. Over this decade, we estimated that the total annual C sink in the project region was 132 Tg C per y (1 Tg = 1012 g), over half of which (74 Tg C per y, 56%) was attributed to the implementation of the projects. Our results demonstrate that these restoration projects have substantially contributed to CO2 mitigation in China.
400 citations
TL;DR: In this article, a literature survey reveals that different extracts such as leaf, root, stem, bark, pulp, fruit, etc. have been effectively employed as sustainable inhibitors for the corrosion of different metals and alloys.
318 citations
TL;DR: In this paper, a literature survey was conducted on the machinability properties and related approaches for carbon fiber reinforced polymer (CFRP) and GFRP composite materials, among other fiber reinforced materials, have been increasingly replacing conventional materials with their excellent strength and low specific weight properties, also their high fatigue, toughness and high temperature wear and oxidation resistance capabilities render these materials an excellent choice in engineering applications.
309 citations
TL;DR: In this article, the concept of green roofs and facades is comprehensively analyzed in a holistic and thematic way, and the results achieved from the literature survey clearly indicate that green roofs are key solutions to mitigate building-related energy consumptions and greenhouse gas emissions in a renewable, sustainable, energyefficient and cost effective way.
Abstract: Based on United Nations Environment Program (UNEP), building sector accounts for 40% of total energy consumption. In European countries, 36% of total greenhouse gas emissions is attributed to buildings. In this respect, green roofs are considered to be one of the most appropriate sustainable solutions to resolve the urban heat island-related issues. Roofs account for nearly 20–25% of overall urban surface areas. Energy saving, thermal insulation, shading and evapotranspiration features highlight the key role of green roofs in overall thermal performance of buildings and microclimatic conditions of indoor environments. Within the scope of this research, the concept of green roofs and facades is comprehensively analysed in a holistic and thematic way. Following a historical overview of the technology, the research is split into various subfields such as energy saving in buildings through greenery systems, multifunctional thermal benefits including evapotranspiration, thermal insulation, shading and thermal comfort features, evaporative cooling for reducing cooling demand and minimising wind driven convection losses. The results achieved from the literature survey clearly indicate that green roofs and facades are key solutions to mitigate building-related energy consumptions and greenhouse gas emissions. According to the previous works, heat flow through the building roofs in summer can be reduced by approximately 80% via green roofs. The green roofs are reported to consume less energy in the range of 2.2–16.7% than traditional roofs during summer time. A similar tendency is observed for the winter season depending on regional and climatic conditions. The temperature difference between conventional and greens roofs in winter is found to be about 4 °C, which is remarkable. Energy demand of buildings in summer is highly dependent on the plant intensity as it is reported to be 23.6, 12.3 and 8.2 kWh/m2/year for extensive, semi-intensive and intensive greenery surface, respectively. Greenery systems are also capable of providing thermally comfortable indoor and outdoor conditions. It is underlined that the annual average accumulation of CO2 reaches the level of 13.41–97.03 kg carbon/m2 for 98 m2 of vertical greenery system. The results of this research can be useful for dwellers, builders, architects, engineers and policy makers to have a good understanding about the potential of green roofs and facades to mitigate building-related energy consumptions and carbon emissions in a renewable, sustainable, energy-efficient and cost effective way.
301 citations
TL;DR: This review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.
Abstract: Satellite time series with high spatial resolution is critical for monitoring land surface dynamics in heterogeneous landscapes. Although remote sensing technologies have experienced rapid development in recent years, data acquired from a single satellite sensor are often unable to satisfy our demand. As a result, integrated use of data from different sensors has become increasingly popular in the past decade. Many spatiotemporal data fusion methods have been developed to produce synthesized images with both high spatial and temporal resolutions from two types of satellite images, frequent coarse-resolution images, and sparse fine-resolution images. These methods were designed based on different principles and strategies, and therefore show different strengths and limitations. This diversity brings difficulties for users to choose an appropriate method for their specific applications and data sets. To this end, this review paper investigates literature on current spatiotemporal data fusion methods, categorizes existing methods, discusses the principal laws underlying these methods, summarizes their potential applications, and proposes possible directions for future studies in this field.
274 citations
TL;DR: This paper presents a comprehensive literature survey on the topic of LFC, and investigates the used LFC models for diverse configurations of power systems and proposes proposed control strategies for LFC for both conventional and future smart power systems.
Abstract: Power systems are the most complex systems that have been created by men in history To operate such systems in a stable mode, several control loops are needed Voltage frequency plays a vital role in power systems which need to be properly controlled To this end, primary and secondary frequency control loops are used to control the frequency of the voltage in power systems Secondary frequency control, which is called Load Frequency Control (LFC), is responsible for maintaining the frequency in a desirable level after a disturbance Likewise, the power exchanges between different control areas are controlled by LFC approaches In recent decades, many control approaches have been suggested for LFC in power systems This paper presents a comprehensive literature survey on the topic of LFC In this survey, the used LFC models for diverse configurations of power systems are firstly investigated and classified for both conventional and future smart power systems Furthermore, the proposed control strategies for LFC are studied and categorized into different control groups The paper concludes with highlighting the research gaps and presenting some new research directions in the field of LFC
TL;DR: A review of the recent developments of unsymmetrically-substituted multidentate Schiff bases whose steric and electronic characteristics are easily manipulated by selecting suitable condensing aldehydes or ketones and primary amines, and on their metal complexes can be found in this article.
TL;DR: In this paper, a detailed literature survey of published studies on selective emitter structures for daytime and nighttime cooling purposes is presented and a detailed energy analysis is performed identifying key performance indicators and evaluating the cooling performance under various conditions.
TL;DR: This study reviews the literature on data envelopment analysis (DEA) applications in sustainability using citation-based approaches and constructs a directional network based on citation relationships among DEA papers published in journals indexed by the Web of Science database from 1996 to March 2016.
TL;DR: In this paper, the authors reviewed the prospects of four major renewable energy sources (hydro, solar, wind and biomass) for each of the three leading countries in Africa namely South Africa, Egypt and Nigeria.
Abstract: Despite its vast natural resources, African is facing serious challenges in sustainable development in an energy sector, if addressed with dispatch could not only check its indispensable needs, but also mitigate some global phenomenon at stake, such as desertification, environmental degradation and green house emission. This paper reviews the prospects of four major renewable energy sources-hydro, solar, wind and biomass- for each of the three leading countries in Africa namely South Africa, Egypt and Nigeria. Based on literature survey of energy efficiency, all the three countries encourage energy efficiency in varying degrees. In the course of this review, several national energy policy frameworks of these countries were looked into, especially on how African countries could overcome the persistent energy crisis in the continent by utilizing the naturally gifted renewable energy sources. This could only be achievable if proper technology, awareness and skills for harnessing the resources are provided. Also lingering energy challenges such as energy efficiency measures, needs for grid extension, energy storage technology and seasonal variation were carefully highlighted.
TL;DR: It can be concluded on the basis of an extensive literature survey that the adsorbent materials (especially hybrids nanocomposites) containing carboxyl, hydroxyl and amine groups offered efficient La removal over a wide range of pH with higher adsorption capacity as compared to other adsorbents.
TL;DR: A review of 119 papers on ship detection and classification from optical satellite shows an exponential growth in the number of papers from 1978 to March 2017, promising rapid advances in new observation and processing capabilities.
TL;DR: In this paper, the authors classify the facial landmark detection algorithms into three major categories: holistic methods, constrained local model (CLM) methods, and regression-based methods, which differ in the ways to utilize the facial appearance and shape information.
Abstract: The locations of the fiducial facial landmark points around facial components and facial contour capture the rigid and non-rigid facial deformations due to head movements and facial expressions. They are hence important for various facial analysis tasks. Many facial landmark detection algorithms have been developed to automatically detect those key points over the years, and in this paper, we perform an extensive review of them. We classify the facial landmark detection algorithms into three major categories: holistic methods, Constrained Local Model (CLM) methods, and the regression-based methods. They differ in the ways to utilize the facial appearance and shape information. The holistic methods explicitly build models to represent the global facial appearance and shape information. The CLMs explicitly leverage the global shape model but build the local appearance models. The regression-based methods implicitly capture facial shape and appearance information. For algorithms within each category, we discuss their underlying theories as well as their differences. We also compare their performances on both controlled and in the wild benchmark datasets, under varying facial expressions, head poses, and occlusion. Based on the evaluations, we point out their respective strengths and weaknesses. There is also a separate section to review the latest deep learning-based algorithms.
The survey also includes a listing of the benchmark databases and existing software. Finally, we identify future research directions, including combining methods in different categories to leverage their respective strengths to solve landmark detection "in-the-wild".
TL;DR: This review article explores utilization of banana waste as precursor materials to produce an adsorbent, and its application against environmental pollutants such as heavy metals, dyes, organic pollutants, pesticides, and various other gaseous pollutants.
TL;DR: Increase in prepotent motor activity on individual no-go trials was accompanied by greater frontocentral P3 amplitudes, confirming it as an index of inhibition, and inhibition-related activity showed a 75% reduction in slow-paced, equiprobable go/no-go tasks compared to fast- paced, rare no- go versions.
Abstract: Inhibitory control enables humans to stop prepotent motor activity, and is commonly studied using go/no-go or stop-signal tasks. In stop-signal tasks, prepotent motor activity is elicited by delaying stop signals relative to go signals. In go/no-go tasks, however, trials include only one signal-go or no-go. Hence, prepotent motor activity has to be ensured differently-for example, by using rare no-go trials and short trial durations. However, a literature survey shows that ∼40% of studies use equiprobable go/no-go trials and ∼20% use long stimulus-stimulus intervals (> 4 s). It is unclear whether such slow-paced, equiprobable go/no-go tasks elicit prepotent motor activity and probe inhibitory control. We recorded EEG during four go/no-go tasks, varying in no-go probability and trial duration. We quantified prepotent motor activity on successfully inhibited no-go trials using the lateralized readiness potential. Only fast-paced go/no-go tasks with rare no-go trials reliably evoked such activity. We then used a stop-signal task and independent component analysis to isolate an established neural signature of inhibitory control, and investigated this signature's activity across the go/no-go tasks. Across tasks, increased prepotent motor activity on individual no-go trials was accompanied by greater frontocentral P3 amplitudes, confirming it as an index of inhibition. Crucially, this inhibition-related activity showed a 75% reduction in slow-paced, equiprobable go/no-go tasks compared to fast-paced, rare no-go versions. Therefore, since many common go/no-go task configurations do not reliably evoke prepotent motor activity, their inhibitory requirements are greatly reduced. This has major implications for the usage of go/no-go tasks in psychological experiments.
TL;DR: A survey of research on how oil prices affect stock returns can be found in this paper, where the authors highlight the key themes researched, main findings and identify key challenges and suggest an agenda for future research on the interaction between oil prices and stock returns.
TL;DR: In this article, a taxonomy of methods that distinguish between direct and indirect, as well as supervised and unsupervised, methods for the collection of data on skills is presented.
Abstract: In recent decades, a growing body of literature has emerged to illustrate the strong pressure on higher education institutions to prepare graduates for the world of work. This paper examines studies that attempt to incorporate the concept of employability skills in the empirical analysis. It thus focuses on the conceptual discussion and methodological options to show how researchers cope empirically with the assumptions associated with employability skills. This literature survey offers a taxonomy of methods that distinguishes between direct and indirect, as well as supervised and unsupervised, methods for the collection of data on skills. Although the underlying premise of the available research is that higher education institutions and policymakers should be provided with information on employability skills, the studies examined in this paper suggest that the identification of those skills is an impossible endeavour. Agreement is only found on some cognitive, technical, and relational skills. More importantly, it is argued that the supply-side approach overlooks economic and social processes that might affect employability. The problem of graduates’ employability transcends higher education institutions’ provision of useful and matched skills.
TL;DR: A scalable protocol is introduced to prepare crystal phase and orientation controlled Pd3S nanoparticles supported on carbon nitride, exhibiting unparalleled semi-hydrogenation performance due to a high density of active and selective ensembles.
Abstract: Ensemble control has been intensively pursued for decades to identify sustainable alternatives to the Lindlar catalyst (PdPb/CaCO3) applied for the partial hydrogenation of alkynes in industrial organic synthesis. Although the geometric and electronic requirements are known, a literature survey illustrates the difficulty of transferring this knowledge into an efficient and robust catalyst. Here, we report a simple treatment of palladium nanoparticles supported on graphitic carbon nitride with aqueous sodium sulfide, which directs the formation of a nanostructured Pd3S phase with controlled crystallographic orientation, exhibiting unparalleled performance in the semi-hydrogenation of alkynes in the liquid phase. The exceptional behavior is linked to the multifunctional role of sulfur. Apart from defining a structure integrating spatially-isolated palladium trimers, the active ensembles, the modifier imparts a bifunctional mechanism and weak binding of the organic intermediates. Similar metal trimers are also identified in Pd4S, evidencing the pervasiveness of these selective ensembles in supported palladium sulfides.
TL;DR: In this article, the authors present records of unstable operations in grid-connected photovoltaic generation plants and possible causes of the instabilities are discussed based on the literature survey.
Abstract: This letter presents records of unstable operations in grid-connected photovoltaic generation plants. The instabilities involve a wide range of frequencies from tens to thousands of Hertz. Possible causes of the instabilities are discussed based on the literature survey. This letter suggests new industry standards or grid codes for photovoltaic generation integration should consider such practical challenges.
TL;DR: In this paper, a taxonomy of cyber-harms encountered by organisations is presented, which comprises five broad themes: physical or digital harm, economic harm, psychological harm, reputational harm, and social and societal harm.
Abstract: Technological advances have resulted in organisations digitalizing many parts of their operations. The threat landscape of cyber-attacks is rapidly changing and the potential impact of such attacks is uncertain, because there is a lack of effective metrics, tools and frameworks to understand and assess the harm organisations face from cyber-attacks. In this paper, we reflect on the literature on harm, and how it has been conceptualised in disciplines such as criminology and economics, and investigate how other notions such as risk and impact relate to harm. Based on an extensive literature survey and on reviewing news articles and databases reporting cyber-incidents, cybercrimes, hacks and other attacks, we identify various types of harm and create a taxonomy of cyber-harms encountered by organisations. This taxonomy comprises five broad themes: physical or digital harm; economic harm; psychological harm; reputational harm; and social and societal harm. In each of these themes we present several cyber-harms that can result from cyber-attacks. To provide initial indications about how these different types of harm are connected and how cyber-harm in general may propagate, this article also analyses and draws insight from four real-world case studies, involving Sony (2011 and 2014), JPMorgan and Ashley Madison. We conclude by arguing for the need for analytical tools for organisational cyber-harm, which can be based on a taxonomy such as the one we propose here. These would allow organisations to identify corporate assets, link these to different types of cyber-harm, measure those harms and, finally, consider the security controls needed for the treatment of harm.
TL;DR: An extensive study of aerial vehicles and manipulation/interaction mechanisms in aerial manipulation is presented and the shortcomings of current aerial manipulation research are highlighted and a number of directions for future research are suggested.
TL;DR: An extensive literature survey was carried out to get an idea on the geographical distribution of ECs in various environmental matrices and biological samples by dividing the entire subcontinent into six zones based on climatic, geographical and cultural features and it is found that studies on the screening ofECs are scarce and concentrated in certain geological locations.
TL;DR: The potential benefits derived by implementing DSM in electrical power networks are presented and an extensive literature survey on the impacts of DSM on the reliability of electrical power systems is provided for the first time.
Abstract: Electricity demand has grown over the past few years and will continue to grow in the future. The increase in electricity demand is mainly due to industrialization and the shift from a conventional to a smart-grid paradigm. The number of microgrids, renewable energy sources, plug-in electric vehicles and energy storage systems have also risen in recent years. As a result, future electricity grids have to be revamped and adapt to increasing load levels. Thus, new complications associated with future electrical power systems and technologies must be considered. Demand-side management (DSM) programs offer promising solutions to these issues and can considerably improve the reliability and financial performances of electrical power systems. This paper presents a review of various initiatives, techniques, impacts and recent developments of the DSM of electrical power systems. The potential benefits derived by implementing DSM in electrical power networks are presented. An extensive literature survey on the impacts of DSM on the reliability of electrical power systems is also provided for the first time. The research gaps within the broad field of DSM are also identified to provide directions for future work.
TL;DR: A literature survey on the Pumped Thermal Electricity Storage technology is presented with the aim of analysing its actual configurations and state of development in this article, which is the most promising one due to its long cycle life, no geographical limitations, no need of fossil fuel streams and capability of being integrated into conventional fossil-fuelled power plants.
Abstract: A large penetration of variable intermittent renewable energy sources into the electric grid is stressing the need of installing large-scale Energy Storage units. Pumped Hydro Storage, Compressed Air Energy Storage and Flow Batteries are the commercially available large-scale energy storage technologies. However, these technologies suffer of geographical constrains (such as Pumped Hydro Storage and Compressed Air Energy Storage), require fossil fuel streams (like Compressed Air Energy Storage) or are characterised by low cycle life (Flow Batteries). For this reason, there is the need of developing new large-scale Energy Storage Technologies which do not suffer of the above-mentioned drawbacks. Among the in-developing large-scale Energy Storage Technologies, Pumped Thermal Electricity Storage or Pumped Heat Energy Storage is the most promising one due to its long cycle life, no geographical limitations, no need of fossil fuel streams and capability of being integrated into conventional fossil-fuelled power plants. Based on these evidences, in the present work, a literature survey on the Pumped Thermal Electricity Storage technology is presented with the aim of analysing its actual configurations and state of development.
TL;DR: A systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose is presented.
Abstract: In this paper we present the findings of a systematic literature review covering the articles published in the last two decades in which the authors described the application of a machine learning technique and method to an orthopedic problem or purpose. By searching both in the Scopus and Medline databases, we retrieved, screened and analyzed the content of 70 journal articles, and coded these resources following an iterative method within a Grounded Theory approach. We report the survey findings by outlining the articles' content in terms of the main machine learning techniques mentioned therein, the orthopedic application domains, the source data and the quality of their predictive performance.