Showing papers on "Literature survey published in 2017"

Glioblastoma Multiforme: A Review of its Epidemiology and Pathogenesis through Clinical Presentation and Treatment

Abstract: Glioblastoma multiforme (GBM) is one of the most malignant types of central nervous system tumors. Despite advances in treatment modalities it remains largely incurable. The objective of our review is to provide a holistic picture of GBM epidemiology, etiology, pathogenesis, clinical findings and treatment. A literature search was conducted for GBM at PubMed and Google Scholar, with relevant key words like glioblastoma multiforme, pathogenesis, signs and symptoms, treatment etc., and papers published until 2015 were reviewed. It was found that radiation and certain genetic syndromes are the only risk factors identified to date for GBM. Depending on the tumor site patients may present to the clinic with varying symptoms. To confirm the presence and the extent of tumor, various invasive and non-invasive imaging techniques require employment. The literature survey revealed the pathogenesis to involve aberrations of multiple signaling pathways through multiple genetic mutations and altered gene expression. Although several treatment options are available, including surgery, along with adjuvant chemo- and radio-therapy, the disease has a poor prognosis and patients generally succumb within 14 months of diagnosis.

A Survey of Data Mining and Machine Learning Methods for Cyber Security Intrusion Detection

Abstract: Cyber security is that the body of technologies, processes and practices designed to safeguard networks, computers, programs and knowledge from attack, harm or unauthorized access. During a computing context, the term security implies cyber security. This survey paper describes a targeted literature survey of machine learning (ML) and data processing (DM) strategies for cyber analytics in support of intrusion detection. This paper focuses totally on cyber intrusion detection as it applies to wired networks. With a wired network, associate oppose must experience many layers of defense at firewalls and operative systems, or gain physical access to the network. The quality of ML/DM algorithms is addressed, discussion of challenges for victimization ML/DM for cyber security is conferred, and some recommendations on once to use a given methodology area unit provided.

Identification methods in microplastic analysis: a review

Abstract: Microplastics have become a major global environmental issue in recent decades due to their ubiquity in the oceans, bioavailability and ability to carry toxic chemicals. Analysis of microplastics in environmental and experimental samples has become increasingly common. We conducted a literature survey to review the current identification methods for microplastics. The advantages and limitations of each identification method were compared to indicate the best methods for microplastic analysis. Identification of microplastics is based on the physical and chemical characterisation of isolated particles in mixtures of inorganic and organic remnant particles after the extraction and clean-up steps. In addition, novel methods which may possibly be applied to microplastic identification were suggested. Microscopic identification by itself has a high risk of producing both false positive and false negative results in analyses of small microplastics. At present, combinations of physical (e.g., microscopy) and chemical (e.g., spectroscopy) analyses are widely used. However, there is a need to improve and develop new methods to reduce the identification time and effort and to detect sub-micron plastics in environmental samples.

Innovation in education: what works, what doesn’t, and what to do about it?

Abstract: Purpose The purpose of this paper is to present an analytical review of the educational innovation field in the USA. It outlines classification of innovations, discusses the hurdles to innovation, and offers ways to increase the scale and rate of innovation-based transformations in the education system. Design/methodology/approach The paper is based on a literature survey and author research. Findings US education badly needs effective innovations of scale that can help produce the needed high-quality learning outcomes across the system. The primary focus of educational innovations should be on teaching and learning theory and practice, as well as on the learner, parents, community, society, and its culture. Technology applications need a solid theoretical foundation based on purposeful, systemic research, and a sound pedagogy. One of the critical areas of research and innovation can be cost and time efficiency of the learning. Practical implications Several practical recommendations stem out of this paper: how to create a base for large-scale innovations and their implementation; how to increase effectiveness of technology innovations in education, particularly online learning; how to raise time and cost efficiency of education. Social implications Innovations in education are regarded, along with the education system, within the context of a societal supersystem demonstrating their interrelations and interdependencies at all levels. Raising the quality and scale of innovations in education will positively affect education itself and benefit the whole society. Originality/value Originality is in the systemic approach to education and educational innovations, in offering a comprehensive classification of innovations; in exposing the hurdles to innovations, in new arguments about effectiveness of technology applications, and in time efficiency of education.

Unmanned Aerial Vehicle Remote Sensing for Field-Based Crop Phenotyping: Current Status and Perspectives

Abstract: Phenotyping plays an important role in crop science research; the accurate and rapid acquisition of phenotypic information of plants or cells in different environments is helpful for exploring the inheritance and expression patterns of the genome to determine the association of genomic and phenotypic information to increase the crop yield. Traditional methods for acquiring crop traits, such as plant height, leaf color, leaf area index (LAI), chlorophyll content, biomass and yield, rely on manual sampling, which is time-consuming and laborious. Unmanned aerial vehicle remote sensing platforms (UAV-RSPs) equipped with different sensors have recently become an important approach for fast and non-destructive high throughput phenotyping and have the advantage of flexible and convenient operation, on-demand access to data and high spatial resolution. UAV-RSPs are a powerful tool for studying phenomics and genomics. As the methods and applications for field phenotyping using UAVs to users who willing to derive phenotypic parameters from large fields and tests with the minimum effort on field work and getting highly reliable results are necessary, the current status and perspectives on the topic of UAV-RSPs for field-based phenotyping were reviewed based on the literature survey of crop phenotyping using UAV-RSPs in the Web of Science™ Core Collection database and cases study by NERCITA. The reference for the selection of UAV platforms and remote sensing sensors, the commonly adopted methods and typical applications for analyzing phenotypic traits by UAV-RSPs, and the challenge for crop phenotyping by UAV-RSPs were considered. The review can provide theoretical and technical support to promote the applications of UAV-RSPs for crop phenotyping.

Why is Ferrocene so Exceptional

Abstract: The appearance of ferrocene in the middle of the 20th century has revolutionized organometallic chemistry and is now providing applications in areas as varied and sometimes initially unexpected as optical and redox devices, battery and other materials, sensing, catalysis, including asymmetric and enantioselective catalysis, and medicine. The author presents here a general, although personal, view of ferrocene's chemistry, properties, functions, and applications through a literature survey involving both historical and up-to-date trends and including examples of his group's research in a number of these areas. The review gathers together general features of ferrocene chemistry and representative examples of the salient aspects. Its focus is on ferrocene's basic properties, ferrocene-containing ligands, the ferrocene/ferricinium redox couple, ferrocene mixed-valence and average-valence systems, the ferricinium/ferrocene redox shuttle in catalysis, ligand-exchange reactions, ferrocene-containing polymers, ferrocene-containing structures for cathodic battery and other materials, ferrocenes in supramolecular ensembles, liquid crystals, and nonlinear optical materials, ferrocene-containing stars and their electrostatic effects, ferrocene-containing dendrons, dendrimers, and nanoparticles (NPs) and their application in redox sensing and catalysis, and ferrocenes in nanomedicine.

A review on deep convolutional neural networks

Abstract: The success of traditional methods for solving computer vision problems heavily depends on the feature extraction process But Convolutional Neural Networks (CNN) have provided an alternative for automatically learning the domain specific features Now every problem in the broader domain of computer vision is re-examined from the perspective of this new methodology Therefore it is essential to figure-out the type of network specific to a problem In this work, we have done a thorough literature survey of Convolutional Neural Networks which is the widely used framework of deep learning With AlexNet as the base CNN model, we have reviewed all the variations emerged over time to suit various applications and a small discussion on the available frameworks for the implementation of the same We hope this piece of article will really serve as a guide for any neophyte in the area

An Update on Safety and Side Effects of Cannabidiol: A Review of Clinical Data and Relevant Animal Studies

Abstract: Introduction: This literature survey aims to extend the comprehensive survey performed by Bergamaschi et al. in 2011 on cannabidiol (CBD) safety and side effects. Apart from updating the literature, this article focuses on clinical studies and CBD potential interactions with other drugs. Results: In general, the often described favorable safety profile of CBD in humans was confirmed and extended by the reviewed research. The majority of studies were performed for treatment of epilepsy and psychotic disorders. Here, the most commonly reported side effects were tiredness, diarrhea, and changes of appetite/weight. In comparison with other drugs, used for the treatment of these medical conditions, CBD has a better side effect profile. This could improve patients' compliance and adherence to treatment. CBD is often used as adjunct therapy. Therefore, more clinical research is warranted on CBD action on hepatic enzymes, drug transporters, and interactions with other drugs and to see if this mainly lead...

Review of flash sintering: materials, mechanisms and modelling

Abstract: Flash sintering (FS) is an energy efficient sintering technique involving electrical Joule heating, which allows very rapid densification (<60 s) of particulate materials. Since the first publication on flash-sintered zirconia (3YSZ) in 2010, it has been intensively researched and applied to a wide range of materials. Going back more than a century ago, we have found a close similarity between FS of oxides and Nernst glowers developed in 1897. This review provides a comprehensive overview of FS and is based on a literature survey consisting of 88 papers and seven patents. It correlates processing parameters (i.e. electric field magnitude, current density, waveforms (AC, DC) and frequency, furnace temperature, electrode materials/configuration, externally applied pressure and sintering atmosphere) with microstructures and densification mechanisms. Theorised mechanisms driving the rapid densification are substantiated by modelling work, advanced in situ analysis techniques and by established theorie...

Literature survey on the relationships between energy, environment and economic growth

Abstract: The aim of this study is to exhibit an exhaustive survey which is related to the great flight of the literature of energy- environment-growth nexus at the individual and regional scale studies covering the period from 1978 to 2014. The survey takes into consideration the sample (country, region, etc.), periods covering, econometric strategies, and conclusions. Our survey is based on the causality direction among (i) the energy use variables (electricity, nuclear, renewable and non-renewable) and output growth; (ii) between economic growth and environment; and between the three variables at the same time. Globally, these surveys provide paradoxical and not conclusive results which energy consumption can boost economic growth through the productivity enhancement and it can boost also the environmental damages through the enhancement of pollutant emissions. Our survey sheds more the lights on the energy-environment-growth literature by giving an extensive listing (1978–2014) of these causal linkages among the energy use variables, environment and economic growth for both individual and collective cases. There is a unanimous consensus about the importance of dealing with such dynamic relationship, which is seems to be a cornerstone element in setting any ambition strategies (energy, ecological and economics).

Dynamical Modeling and Distributed Control of Connected and Automated Vehicles: Challenges and Opportunities

Abstract: The platooning of connected and automated vehicles (CAVs) is expected to have a transformative impact on road transportation, e.g., enhancing highway safety, improving traffic utility, and reducing fuel consumption. Requiring only local information, distributed control schemes are scalable approaches to the coordination of multiple CAVs without using centralized communication and computation. From the perspective of multi-agent consensus control, this paper introduces a decomposition framework to model, analyze, and design the platoon system. In this framework, a platoon is naturally decomposed into four interrelated components, i.e., 1) node dynamics, 2) information flow network, 3) distributed controller, and 4) geometry formation. The classic model of each component is summarized according to the results of the literature survey; four main performance metrics, i.e., internal stability, stability margin, string stability, and coherence behavior, are discussed in the same fashion. Also, the basis of typical distributed control techniques is presented, including linear consensus control, distributed robust control, distributed sliding mode control, and distributed model predictive control.

Agency theory: Review of Theory and Evidence on Problems and Perspectives:

Abstract: This article intends to review the theoretical aspects and empirical evidences made on agency theory It is aimed to explore the main ideas, perspectives, problems and issues related to the agency theory through a literature survey It discusses the theoretical aspects of agency theory and the various concepts and issues related to it and documents empirical evidences on the mechanisms that diminish the agency cost The conflict of interest and agency cost arises due to the separation of ownership from control, different risk preferences, information asymmetry and moral hazards The literatures have cited many solutions like strong ownership control, managerial ownership, independent board members and different committees can be useful in controlling the agency conflict and its cost This literature survey will enlighten the practitioners and researchers in understanding, analysing the agency problem and will be helpful in mitigating the agency problem

Sensor-Based Assistive Devices for Visually-Impaired People: Current Status, Challenges, and Future Directions

Abstract: The World Health Organization (WHO) reported that there are 285 million visuallyimpaired people worldwide. Among these individuals, there are 39 million who are totally blind. There have been several systems designed to support visually-impaired people and to improve the quality of their lives. Unfortunately, most of these systems are limited in their capabilities. In this paper, we present a comparative survey of the wearable and portable assistive devices for visuallyimpaired people in order to show the progress in assistive technology for this group of people. Thus, the contribution of this literature survey is to discuss in detail the most significant devices that are presented in the literature to assist this population and highlight the improvements, advantages, disadvantages, and accuracy. Our aim is to address and present most of the issues of these systems to pave the way for other researchers to design devices that ensure safety and independent mobility to visually-impaired people.

Optimization strategies for Solid Oxide Fuel Cell (SOFC) application: A literature survey

Abstract: Solid Oxide Fuel Cells (SOFCs) have become the promising energy source for stationary and portable applications. The design of SOFCs including its structure and its operation are an important part to be properly optimized in order to achieve the best performance. The topic on optimization of SOFC has gained tremendous attention recently in line with the growing applications of fuel cell. This paper involves a literature survey of the application of SOFC in particular the optimization strategies. The strategies are reviewed in detail based on five features, which are the decision variable, objective analysis, constraint, method and tools. The future trends of research related to the optimization for SOFC are also discussed to provide better insight for future research work in this area.

Recent Advance in Content-based Image Retrieval: A Literature Survey

Abstract: The explosive increase and ubiquitous accessibility of visual data on the Web have led to the prosperity of research activity in image search or retrieval. With the ignorance of visual content as a ranking clue, methods with text search techniques for visual retrieval may suffer inconsistency between the text words and visual content. Content-based image retrieval (CBIR), which makes use of the representation of visual content to identify relevant images, has attracted sustained attention in recent two decades. Such a problem is challenging due to the intention gap and the semantic gap problems. Numerous techniques have been developed for content-based image retrieval in the last decade. The purpose of this paper is to categorize and evaluate those algorithms proposed during the period of 2003 to 2016. We conclude with several promising directions for future research.

Recent approaches of unit commitment in the presence of intermittent renewable energy resources: A review

Abstract: Unit Commitment (UC) is an optimization problem used to determine the operation schedule of the generating units at every hour interval with varying loads and generations under different generational, environmental and technical constraints. With the significant increase of Renewable Energy Sources (RES) integration into the power networks, effects posed by these system changes to the UC are actively being studied and investigated by global researchers and operation engineers. To this end, this paper firstly provides a literature survey of UC concept, objectives and constraints. Different UC models developed for addressing RES impacts are also reviewed. Moreover, many algorithms have been proposed in the past few decades to optimize the UC problem. This work explores the necessity for alternative optimization approaches for UC solution. In doing that, the work uncovers the advantages and disadvantages of the existing methodologies so that future algorithms could be designed in retaining the advantages of the existing methodologies while avoiding the presented weaknesses. In addition, installation of energy storage devices to balance the fluctuation in power generation and their associated impacts on UC models are reviewed. The contents of this paper provide ready-to-refer and ready-to-use information for the researchers working in the field of UC.

An Overview on Resource Allocation Techniques for Multi-User MIMO Systems

Abstract: Remarkable research activities and major advances have been occurred over the past decade in multiuser multiple-input multiple-output (MU-MIMO) systems. Several transmission technologies and precoding techniques have been developed in order to exploit the spatial dimension so that simultaneous transmission of independent data streams reuse the same radio resources. The achievable performance of such techniques heavily depends on the channel characteristics of the selected users, the amount of channel knowledge, and how efficiently interference is mitigated. In systems where the total number of receivers is larger than the number of total transmit antennas, user selection becomes a key approach to benefit from multiuser diversity and achieve full multiplexing gain. The overall performance of MU-MIMO systems is a complex joint multi-objective optimization problem since many variables and parameters have to be optimized, including the number of users, the number of antennas, spatial signaling, rate and power allocation, and transmission technique. The objective of this literature survey is to provide a comprehensive overview of the various methodologies used to approach the aforementioned joint optimization task in the downlink of MU-MIMO communication systems.

A comprehensive state of the art literature survey on LFC mechanism for power system

Abstract: Over the past few decades, many publications have been made in the area of Load frequency control (LFC) of interconnected power systems. Load frequency control is necessary to develop better control in order to achieve less effect on the frequency and tie line power deviations after a load perturbation. However, number of control strategies has been employed in the design of load frequency controllers in order to achieve a better dynamic response and the exact choice of the LFC controller in a particular case requires sufficient expertise because each controller has its own merits and demerits. Due to this, an appropriate review of load frequency control (LFC) mechanism is essential and a few attempts have been made in this concern. This paper presents a detailed survey on load frequency control (LFC) mechanism. The overall study explores the depth study issues related to LFC mechanism based on different sources of power system models. This paper focused on different control techniques of LFC, which also includes all the recent application of FACTS devices. This review reveals the investigation of soft computing based optimization technique and application of Energy Storage System (ESS) and HVDC-link in LFC. These studies also illustrates conventional power system, deregulated of power environment as well as distributed generation and micro grids. This paper is designed in order to highlight the major traits of Load forecasting and some critical case studies on LFC.

Energy storage planning in electric power distribution networks – A state-of-the-art review

Abstract: In the past decade, energy storage systems (ESSs) as one of the structural units of the smart grids have experienced a rapid growth in both technical maturity and cost effectiveness. These devices propose diverse applications in the power systems especially in distribution networks. Despite offering numerous applications, the ESSs are new devices characterized by high investment costs. Besides technological advancement, optimal ESS planning and scheduling is one of the effective ways to reduce the costs and justifying high investment costs by taking their benefits out as much as possible. During the past few years, various studies have been conducted by the researcher to address the problem of optimal ESS planning in distribution networks. In this context, various models, methods, and considerations have been proposed to enhance the functionality of optimal planning process. The aim of this paper is to review the problem of optimal ESS planning including optimal bus location, power rating, and energy capacity determination in the distribution networks. In order to facilitate continuing and growing research in this field, a comprehensive literature survey and classification of the related studies followed by research gaps and future opportunities is provided.

Global flood depth-damage functions: Methodology and the database with guidelines

Abstract: Assessing potential damage of flood events is an important component in flood risk management. Determining direct flood damage is commonly done using depth-damage curves, which denote the flood damage that would occur at specific water depths per asset or per land-use class. Many countries have developed flood damage models using depth-damage curves based on analysis of past flood events and on expert judgement. However, the fact that such damage curves are not available for all regions hampers damage assessments in some areas. Moreover, due to different methodologies employed for various damage models in different countries, damage assessments cannot be directly compared with each other, obstructing also supra-national flood damage assessments. To address these problems a globally consistent database of depth-damage curves has been developed. This dataset contains damage curves depicting fractional damage as a function of water depth as well as the relevant maximum damage values for a variety of assets and land use classes. Based on an extensive literature survey normalised damage curves have been developed for each continent, while differentiation in flood damage between countries is established by determining maximum damage values at the country scale. These maximum damage values are based on construction cost surveys from multinational construction companies, which provide a coherent set of detailed building cost data across dozens of countries. A consistent set of maximum flood damage values for all countries was computed using statistical regressions with socio-economic World Development Indicators. Further, based on insights from the literature survey, guidance is also given on how the damage curves and maximum damage values can be adjusted for specific local circumstances, such as urban vs. rural locations or use of specific building material. This dataset can be used for consistent supra-national scale flood damage assessments, and guide assessment in countries where no damage model is currently available.

Guidelines for including the grey literature and conducting multivocal literature reviews in software engineering

Abstract: Context: A Multivocal Literature Review (MLR) is a form of a Systematic Literature Review (SLR) which includes the grey literature (e.g., blog posts and white papers) in addition to the published (formal) literature (e.g., journal and conference papers). MLRs are useful for both researchers and practitioners since they provide summaries both the state-of-the art and -practice in a given area. Objective: There are several guidelines to conduct SLR studies in SE. However, given the facts that several phases of MLRs differ from those of traditional SLRs, for instance with respect to the search process and source quality assessment. Therefore, SLR guidelines are only partially useful for conducting MLR studies. Our goal in this paper is to present guidelines on how to conduct MLR studies in SE. Method: To develop the MLR guidelines, we benefit from three inputs: (1) existing SLR guidelines in SE, (2), a literature survey of MLR guidelines and experience papers in other fields, and (3) our own experiences in conducting several MLRs in SE. All derived guidelines are discussed in the context of three examples MLRs as running examples (two from SE and one MLR from the medical sciences). Results: The resulting guidelines cover all phases of conducting and reporting MLRs in SE from the planning phase, over conducting the review to the final reporting of the review. In particular, we believe that incorporating and adopting a vast set of recommendations from MLR guidelines and experience papers in other fields have enabled us to propose a set of guidelines with solid foundations. Conclusion: Having been developed on the basis of three types of solid experience and evidence, the provided MLR guidelines support researchers to effectively and efficiently conduct new MLRs in any area of SE.

Etiology, pathophysiology and biomarkers of interstitial cystitis/painful bladder syndrome.

Abstract: Interstitial cystitis/painful bladder syndrome (IC/PBS) is a chronic pain syndrome and a chronic inflammatory condition prevalent in women that leads to urgency, sleep disruption, nocturia and pain in the pelvic area, to the detriment of the sufferer’s quality of life. The aim of this review is to highlight the newest diagnostic strategies and potential therapeutic techniques. A comprehensive literature review was performed on MEDLINE, PubMed, and Cochrane databases gathering all literature about “Interstitial cystitis” and “Painful Bladder Syndrome”. Visual analogue scales, epidemiological strategies, pain questionnaires and similar techniques were not included in this literature survey. The etiology, exact diagnosis and epidemiology of IC/PBS are still not clearly understood. To date, its prevalence is estimated to be in the range of 45 per 100,000 women and 8 per 100,000 men, whereas joint prevalence in both sexes is 10.6 cases per 100,000. There are no “gold standards” in the diagnosis or detection of IC/PBS, therefore, several etiological theories were investigated, such as permeability, glycosaminoglycans, mast cell, infection and neuroendocrine theory to find new diagnostic strategies and potential biomarkers. Due to the fact that this disease is of an intricate nature, and that many of its symptoms overlap with other concomitant diseases, it could be suggested to classify the patients with emphasis on the phenotype, as well as their symptom clusters, to tailor the diagnostic and management choices according to the observed biomarkers.