Reviewerly/exHarmony huggingface dataset:
Research on the Evaluation of Dangerous Goods Sources in Air Transportation Based on Principle Component Analysis (Pca) of Matlab

With the vigorous development of civil aviation transportation industry, the transportation volume of dangerous goods is increasing.However, the aviation unsafe events caused by dangerous goods are also increasing.In order to find out the important sources of dangerous goods that affect air transportation, seven dangerous goods sources that affect dangerous goods unsafe events are selected basing on the data statistics of dangerous goods unsafe events in 2010-2017.By fully understanding the principal component analysis method, matlab is to be realized the calculation process to carry out systematic research.The first four principal dangerous goods sources are extracted through the principal component analysis method.According to the Principal component analysis of MATLAB, the results show that the main sources of dangerous goods in air transportation are classified into types of dangerous goods, types of airlines, transportation area and transportation mode.In addition, the corresponding preventive measures are given for the four important dangerous goods sources.These preventive measures including enhancing the management of consigning and agency, strengthening the training of relevant personnel and increasing the publicity in all aspects, can provide guidance for the safety management of dangerous goods in air transportation.It is of great value to effectively control the probability of dangerous goods unsafe events and improve the level of safety management.
Planning Storage in the Cloud

This Chapter includes guidelines for choosing storage solutions for different kinds of requirements. When planning cloud storage, consider the types of storage systems and types of data models. The storage systems provide the hardware and basic organizational structure used for storing data. The data models organize data into logical structures that determine how data is stored and queried within a database. The main storage systems available in GCP are Memorystore, a managed cache service, and persistent disks, which are network-accessible disks for VMs in Compute Engine and Kubernetes Engine. Cloud Storage is GCP's object storage system. The primary data models are object, relational, and NoSQL. NoSQL databases in GCP are further subdivided into document and wide-column databases. Cloud Storage uses an object data model. Cloud SQL and Cloud Spanner use relational databases for transaction processing applications. BigQuery uses a relational model for data warehouse and analytic applications. Datastore and Firebase are document databases. Bigtable is a wide-column table.
Genetic Programming with Image-Related Operators and A Flexible Program Structure for Feature Learning in Image Classification

IEEE Feature extraction is essential for solving image classification by transforming low-level pixel values into high-level features. However, extracting effective features from images is challenging due to high variations across images in scale, rotation, illumination, and background. Existing methods often have a fixed model complexity and require domain expertise. Genetic programming with a flexible representation can find the best solution without the use of domain knowledge. This paper proposes a new genetic programming-based approach to automatically learning informative features for different image classification tasks. In the new approach, a number of image-related operators, including filters, pooling operators and feature extraction methods, are employed as functions. A flexible program structure is developed to integrate different functions and terminals into a single tree/solution. The new approach can evolve solutions of variable depths to extract various numbers and types of features from the images. The new approach is examined on 12 different image classification tasks of varying difficulty and compared with a large number of effective algorithms. The results show that the new approach achieves better classification performance than most benchmark methods. The analysis of the evolved programs/solutions and the visualisation of the learned features provide deep insights on the proposed approach.
SP-035: Deformable image registration - Commissioning and QA – Challenges

ESTRO meets Asia 2019 S15 delivery.Immunotherapy, and in particular immunecheckpoint inhibitors targeting the PD-1/PD-L1 axis, gained wide popularity for NSCLC in light of the positive findings of several trials in metastatic disease (1, 2).Radiation therapy combined with immunotherapy represent a new therapeutic opportunity, given the role of RT in reversing immunosuppressive barriers within the tumour microenvironment (3).The growing enthusiasm for immune-oncology and its possible applications in radiation oncology led to a remarkable expansion of pre-clinical and clinical studies testing various combinations of immunotherapeutic agents and radiation.Stage III unresectable NSCLC is an interesting setting for the combined use of chemo-radiation and immunotherapy, also considering the multiple experimental evidences in favor of a synergistic effect between radiation and immune checkpoint inhibitors, with the potential of enhancing immuno-modulating effects and overcoming resistance.Antonia et al, in PACIFIC trial (PD-L1 inhibitor Durvalumab vs placebo, unresectable stage III NSCLC who did not progress following concurrent platinum-based chemo-radiotherapy) showed a major improvement in 2year PFS (primary endpoint), especially when Durvalumab was administered within 2 weeks from end of RT (HR0.39 vs HR 0.63) (4).This finding suggests some positive effect of chemoradiotherapy on the efficacy of durvalumab.In the updated analysis, the PFS benefit has translated to a significant prolongation in OS, with a 24-month OS rate of 66.3% in the treatment group, compared with 55.6% in the placebo group (p =0.0025) (5).Based on these results, Durvalumab was approved for the treatment of patients with unresectable stage III NSCLC whose disease had not progressed after platinum-based CT-RT.In the PACIFIC trial post-hoc analysis, this survival benefit was prominent in the PD-L1-positive subgroup of patients (PD-L1 expression ≥1%), but no survival benefit was evident in the PD-L1-negative subgroup (PD-L1 expression <1%), suggesting that PD-L1 expression levels would probably be necessary to stratify patients (6).Even the use of Pembrolizumab (anti-PD-1 agent) is under investigation in a series of trials, while due to results of a phase I trial , criteria were met for advancement to part II of the study where Atezolizumab (another anti PD-L1 antibody) would be added to CT-RT followed by consolidation Atezolizumab, Carboplatin, and Paclitaxel.(7) Regarding the optimal timing when combining immunotherapy and CT-RT, considering the possibility to improve this synergism even further, more evidence is awaited from several ongoing trials.(2)
Precise Locating Algorithm by Modified Least Square Method for CES Switch Operating

Accurate positioning method of three dimensional pose of space circle is a typical problem of binocular vision. The correlation algorithm is particularly important for the positioning accuracy in the case of strong interference of edge feature information. According to the precise positioning requirements of the distribution cabinet handcart in the distribution room, this paper establishes the elliptic curve optimization method based on the European distance minimization feature. Based on the least square method, the information model of the outside edge of the switch is established by using the circular contour of the cylindrical groove, and the three-dimensional pose positioning method of the spatial circle is studied. Finally, the effectiveness of the algorithm is verified by a case study.
How Smart is Your Automatic Target Recognizer?

When we ask: “How smart is your ATR?” we mean: “How well can this machine perform some of the tasks performed by the well-trained human pilot, soldier, sailor, Marine or analyst?” If we arrive at the point where a machine can do all of the tasks of humans, then what are the implications? These types of questions have a surprisingly long history of discussion and analysis.
Deduplication for Cloud based on AES Algorithm

This paper provides and analyses a new scheme to address the issue of everlasting cloud storage access systems by providing AES Algorithm based solution. Addressing the issue of Data storage in the recent times is the aim of the paper and is being done using the recent AES Algorithm. Data security and time constraint for data retrival from the cloud server is also taken into account while implementing the scheme
Re-Expressing Variables

Using numerous examples with real data, this textbook closely integrates the learning of statistics with the learning of R. It is suitable for introductory-level learners, allows for curriculum flexibility, and includes, as an online resource, R-code script files for all examples and figures included in each chapter, for students to learn from and adapt and use in their future data analytic work. Other unique features created specifically for this textbook include an online R tutorial that introduces readers to data frames and other basic elements of the R architecture, and a CRAN library of datasets and functions that is used throughout the book. Essential topics often overlooked in other introductory texts, such as data management, are covered. The textbook includes online solutions to all end-of-chapter exercises and PowerPoint slides for all chapters as additional resources, and is suitable for those who do not have a strong background in mathematics.
Image De-Blurring Based on Constraint Conditional Model

Image capturing is more vulnerable to the various physical limitations such as defocus, low lighting and camera shaking; this makes the image blurry and noisy. Moreover De-blurring is the process to recover the original image from the given degraded image. De-blurring technique uses the estimated blur kernel for achieving the optimal restored image with the sharp features, however the accuracy has been one of the major concern , hence in this paper we use Constrained Conditional model (CCM) for restoring the image. Moreover, here two different methods are integrated i.e. conditional model and convergence operator, these two combined learns the model and efficiently and provides the better results. In order to evaluate the proposed model, Levin dataset is used by considering the two eminent model metric i.e. PSNR and SSIM and CCM based model outperforms the other state-of-art technique.
Adaptive Fuzzy Sliding Mode Controller for Robot Manipulator: Effect on External Interferences

In the previous decades, the SMC approach has attained unique consideration as this technique offers a systematic model to maintain robust performance and asymptotic stability. As robotic manipulators turn out to be gradually more significant in industrial automation, robotic manipulators by means of SMC have raised as a significant region of research. Hence, this paper intends to model and establish an adaptive sliding mode controller (SMC) for robotic manipulator. As it is not feasible to match up the SMC functions with the system model each time, this paper implements a Fuzzy Inference System (FIS) to replace the system model. It effectively achieves the experimentation in two phases. Accordingly, in the first phase, it attains the accurate features of the system model based on varied samples to characterize the robotic manipulator. Consequently, it derives the obtained features as fuzzy rules. In the subsequent phase, it signifies the derived fuzzy rules depending on adaptive fuzzy membership functions. Moreover, it establishes the self-adaptiveness using Grey Wolf Optimization (GWO) to attain the adaptive fuzzy membership functions. The analysis distinguishes the efficiency of the adopted technique with the optimal investigational scheme and the traditional schemes such as SMC, Fuzzy SMC (FSMC) and GWO-SMC. Moreover, the comparative analysis is also performed by including the external disturbances and noise and validates the effectiveness of the proposed and conventional models.
2019_editorial_v2

Computer Graphics ForumVolume 39, Issue 1 p. 5-6 Editorial 2019_editorial_v2 Helwig Hauser, Helwig HauserSearch for more papers by this authorBedrich Benes, Bedrich BenesSearch for more papers by this author Helwig Hauser, Helwig HauserSearch for more papers by this authorBedrich Benes, Bedrich BenesSearch for more papers by this author First published: 27 February 2020 https://doi.org/10.1111/cgf.13901Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume39, Issue1February 2020Pages 5-6 RelatedInformation
Code Knowledge Acquisition for Knowledge Management Trajectory Framework

Knowledge and its related techniques cater the need of many tools and frameworks for software development, testing and management. Accurate usage of code according to the software requirement is prevalent in this regard, as inappropriate development of code with conceptual misunderstanding might lead to waste of time and effort. This paper describes a new approach to automate code acquisition task. This gives the advantage of using the coding knowledge that is already encoded which in turn reduces developer s task and their knowledge and effort could be utilized for further enhancement of their work. Using the existing coding knowledge eradicate the errors which are introduced at the time of naïve development activity. Furthermore, this technique can be utilized by software development applications. In this paper, a new knowledge execution technique to acquire code knowledge from software application is implemented. Code extraction gathers code segments from projects organize and logs it for future use. Here, Source Code Extraction algorithm is described that captures code.
Stochastic Optimal Control with Application in Visual Servoing

In this thesis, a new inference-based solution to stochastic optimal control (SOC) for general nonlinear systems is developed. This novel method applies to standard SOC problem, as well as robust and risk-seeking variations. The presented approach uniﬁes many existing works, and makes possible, inference-based approximations to be applied to robust, risk-seeking, and standard SOC problems. Thus, an approximate method based on extended Kalman ﬁltering is developed and tested on the inverted pendulum problem, and compared with existing methods. As an application, the developed algorithm was adapted to a practically important problem in visual control in robotics known as image-based visual servoing (IBVS). The proposed control methodology for visual servoing was implemented for real-time experiments, and was compared with the standard IBVS methodology. The experimental results show that the proposed method can improve the myopic behaviors of standard IBVS methodology.
uncertainty appear differently at different stages (pre- and post-impact periods) ?

In this manuscript, the authors developed a revised IHA method by using the projection pursuit (PP) and real-coded accelerated genetic algorithm (RAGA).The data reliability was analyzed by using length of record (LOR) method.The cumulative impacts of cascade reservoirs on flow regime were analyzed in the Jinsha River Basin.It seems that the improved method has good reliability, and the authors also considered the impact of the data length on the evaluation results, making the evaluation results more scientific and reliable.Â ȃIn the section of discussing the reliability of data length, we could see that the evaluation results of different data lengths showed obvious uncertainties.Therefore, does this uncertainty appear differently at different stages (pre-and post-impact periods) ?
Accent Detection Task to Classify Accented and Non-Accented Speech

This paper presents a brief survey on accent detection, accent identification, and accent classification. Speech processing has becoming more popular and inspiring expanses lately in signal processing area. It is because speech is one of the most natural form of human communication. However, in processing speech signals intrinsically show many variations even without background noise. Two different person can produce different spectrograms when saying the same sentence. Dialect or Accent is one of the most important factors that can influence the Automatic Speech Recognition or ASR performance besides gender (Unsupervised accent class). Many researches show that dialect or accent in speech can significantly affect the speech system performance. Various methods have been used to increase the accuracy of ASR with accent detection, accent identification, and accent classification. Fused i-vector and Phonotactic are the latest technique that shows a significant degree of accuracy. The purpose of this paper is to briefly survey on accent detection, accent identification, and accent classification and discuss the major improvements made in the past almost 10 years of research.
A collusion-resistant public auditing scheme for shared cloud data

With the increasing popularity of collaboration in the cloud, shared data have become a new branch of cloud data, which also brings new challenges for remote integrity auditing. To address the concerns, this paper presents a novel public auditing scheme for shared data. Differing from the existing works, we introduce a new entity called local authentication server to finalise the block tags of shared data, which can thereby prevent the collusion attack effectively. Moreover, thanks to the new mechanism of tag generation, our scheme relieves the user manager of the burden of management and largely reduces the computation and communication overheads. In addition, we extend the scheme to support batch auditing by employing the aggregate BLS signature technique. The theoretical proof and experimental evaluation demonstrate that the proposed scheme can provide excellent security and outperform the previous ones in computational costs in the user revocation phase.
Public-Key-Kryptographie

No AccessAngewandte KryptographieNov 2019Public-Key-KryptographieWolfgang Ertel, Ekkehard LöhmannWolfgang ErtelSearch for more papers by this author, Ekkehard LöhmannSearch for more papers by this authorhttps://doi.org/10.3139/9783446463530.005SectionsAboutPDF ToolsAdd to FavoritesDownload CitationTrack CitationsCopy LTI LinkPDF key 'share (en)' returned an object instead of string.FacebookTwitterEmailLinkedIn previous chapternext chapter FiguresReferencesRelatedDetails 2019Pages: 77-96Print ISBN: 978-3-446-46313-4eISBN: 978-3-446-46353-0 Copyright & Permissions© 2020 Carl Hanser Verlag GmbH & Co. KGPDF downloadLoading ...
Implementation and Evaluation of User Activity System as a Web Service

Web service is a service which allows different systems to connect with each other via World Wide Web (www). It uses technology like Http (Hyper Text Markup Language). It was originally designed for human to machine communication, but now used for machine to machine communication. We have to develop an application that is platform independent and can be availed by anyone from anywhere, it would be only possible if it is platform independent that is there is no restriction of the language which is to be used for running the application as it will be using web services to fetch the data and showing the desired results and we would be showing the comparison between the Standalone and the web based services. Developing file service as web services have many benefits such as interoperability, low cost of communication, supports remote procedure calls, supports document exchange etc. In this thesis file services efficiency measured with the help of performance criteria non as Fmeasure
Learn to Develop Emotional Intelligence

Nonprofit Communications ReportVolume 19, Issue 6 p. 7-7 Effective Communications Learn to Develop Emotional Intelligence First published: 06 May 2021 https://doi.org/10.1002/npcr.31738Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinkedInRedditWechat No abstract is available for this article. Volume19, Issue6June 2021Pages 7-7 RelatedInformation
Deepening knowledge of online child sexual victimisation

This concluding chapter calls for greater clarity and agreement on definitions and measurement practices concerning online child sexual victimisation (OCSV). First, there is a need for agreed definitions of OCSV that distinguish between normative childhood sexuality and sexual violence, both on- and offline. Second, research, policy, and practices must reflect that the child is only one element that requires protection. Taking a cybersecurity asset approach, the chapter emphasises the need for coordinated action to enhance and protect social goods, such as trust in technology, law enforcement resources, and fundamental rights. Finally, it recommends that guardianship responsibility is extended to children themselves and considers some of the technical tools that might assist their participation.
A Mechanism for Sketch Based Image Retrievals using Generalized Gamma Mixture Model (GGMM) and Relevance Feedback Mechanism

The exponential growth of multimedia technologies facilitated the ease of developing various images having different shapes and scales. With the advent of mobile technologies, these messages so generated are being transmitted across the globe in different formats for different purposes. With these advancements methodologies thus developed for identifying or expressing subjects (individuals) their views by means of sketches. These sketch based images have many advantages, in particular, these images can be well considered in situations where the narration and capturing becomes difficult. The present article underlines a mechanism to interpret the images and also addresses the retrieval of such sketch based images using Generalized Gamma Mixture Model. The relevance feedback mechanism is utilized to retrieve more relevant to sketch based images based on the query image. The efficiency of the proposed word is evaluated using metrics like precision, recall, error rate, and retrieval accuracy.