Reviewerly/exHarmony huggingface dataset:
References

This textbook provides future data analysts with the tools, methods, and skills needed to answer data-focused, real-life questions; to carry out data analysis; and to visualize and interpret results to support better decisions in business, economics, and public policy. Data wrangling and exploration, regression analysis, machine learning, and causal analysis are comprehensively covered, as well as when, why, and how the methods work, and how they relate to each other. As the most effective way to communicate data analysis, running case studies play a central role in this textbook. Each case starts with an industry-relevant question and answers it by using real-world data and applying the tools and methods covered in the textbook. Learning is then consolidated by 360 practice questions and 120 data exercises. Extensive online resources, including raw and cleaned data and codes for all analysis in Stata, R, and Python, can be found at www.gabors-data-analysis.com.
Automatic Source Code Summarization using Semantics and Stereotypes

In Software industries developers and testers spend most of the time in code maintainability than in developing or testing the code. Even after spending lot of time in analyzing the code the final analysis will serve only 50% of their purpose. The analysis involves many complex tasks like code comprehension, code extensibility and code portability. The traditional approach is to analyze the code manually, which is a tedious and time consuming task. Existing techniques does not provide the required summary, most of them are complex and they are not in natural language format. In this paper we propose a novel summarization technique that summarizes the source code similar to natural language text. The proposed system provides summary is based on the semantic content in the source code, in case the source code does not contain semantic contents it uses the java stereotypes to get the semantic content. The proposed system delivers the summaries which simplifies the task of the developer and provides the required summary.
A Decentralized Accountability Framework For Enhancing Secure Data Sharing Through Icm In Cloud

The Cloud substitutes a computing criterion where shared configurable resources are afforded as an on-demand service over the Internet. Moreover, the cloud environment provides resources to the users on the basis of services like SaaS, PaaS and IaaS. Generally, a cloud can be referred as private cloud or public cloud. When a Cloud Service Provider (CSP) imposes upon public cloud resources to compile their private cloud, the result is demonstrated as a virtual private cloud. Private or public, the imperious intent of cloud computing is to provide simplistic, reliable usage of various computing resources. One of the significant features of cloud is that the outsourced data are accessed through any anonymous machines over the Internet. On the other hand, it creates an issue that user’s fear of unknown access of data, which can become a major difficulty to the wide implementation of cloud. In this paper, a decentralized accountability framework is developed to monitor the actual usage and access of the data that is shared on cloud. For that, a logging mechanism that includes authentication for each user to access the data has also been provided. Moreover, some procedures for providing the data under the control of data owner includes Integrity Checking Mechanism (ICM) have also been developed. The overall process strengthens the security constraints over cloud. And the experimental results reveal that the approach affords secure and scalable data sharing with reduced memory utilization and processing time.
Energy Efficient Routing in Iot Based on Chronological Atom Search Optimization Algorithm

Start-up industry, start-up companies go into the moldy lifestyle of young people to form a community to help solve more specific community problems and accurate results. Application testing on community applications is used as alpha 1 before the final release. It is prioritized that the concepts, components and application resolution of serious problems be alleviated. Until the performance. This test is not just an application but a hardware device created by Blueprint. The application of testing uses the framework of Katsinov, up to level 6 where each level explains the concepts, components, completion, enthusiasm or market potential, competition, technology development.
Video Stabilization for Sea Scenes via Low-Rank Alignment and effective Visual Cues

Video stabilization(VS), as a fundamental video pre-processing task, benefits not only for human observers to have a good look at the scene, but also for many subsequent vision tasks to be properly tackled. However, numerous methods for video stabilization rely heavily on extracting enough features for matching. This requirement is difficult to meet in some adverse conditions, say sea-surface scene with dynamic and repetitive texture. In this paper, we propose a video stabilization method for sea scenes to deal with the above issue. Our method utilizes two visual cues, the sea-sky line and the Maximum Stable Extremal Region (MSER), to identify the sky and sea areas and use MSER features within the sea area to predict the camera path to obtain a coarse stabilization result. In further, a low-rank alignment model (LRA) is further employed to significantly boost the accuracy of the preceding stabilization result by enforcing a temporal low-rank restriction on image data. We also construct a sea-surface VS dataset for validation and deeper investigations. Experiments on the constructed dataset show that the proposed method outperforms mainstreaming VS methods under sea-surface scenes. Also, additional experiments on the public datasets manifest that our method can stabilize commonly natural scene videos and has a comparable performance with some conventional approaches.
Data Dissemination Techniques using DBSCAN and DD-Rtree for Spatial Data Mining

In today’s scenario where data volumes are growing on enormous speed over cloud or internet, we want to limit this growing data size. This can be achieved by data processing methods where data processing can be done in parallel. To make the data processing done in parallel, various clustering sampling methodologies are in use such as Slink, DBSCAN, and Optics and so on. The power accomplished by various methodologies which already exist will be focusing to the preservation of three-dimensional surroundings such as grid tree, grid files, quad tree and tree like k-d-tree, etc. This all compartmentalization constructions are generally done in static way which is a fix way. Since this data volume size is very big, this results in a high cost of information sharing and clustering. Hence through this research work we want to analyze various clustering algorithms both on static level and at dynamic level. For doing this we are majorly comparing the dynamic distribution using DBSCAN and DD-Rtree algorithm by proposing a DD-Rtree will help us to preserver the spatial vicinity. In addition, DD-Rtree is not static but more than that it is dynamic, i.e. it will create build the data as we progress with clustering. DD-Rtree methodologies are based on R-Tree concepts which analyses the data at dynamic random way. We tend to compare DD-RTree’s information distribution norm with one of the clustering system recently published, DBSCAN. On the side of the potential of DBSCAN formula, we tend to distinguish the potential of queries managed by these compartmentalization structures. Numerous applications requires such kind of implementation at dynamic level of spatial database system such as satellite images, X-Ray crystallography, metrological department or other such atomic equipment’s spatial datasets. Our research work will help to implements spatial data dynamically using DDR-tree mechanism.https://doi.org/
A Semi-Fragile Watermarking Scheme for Integrity Checking of Relational Databases

Extensive use of the Internet coupled with tremendous growth in database applications have created a huge demand for database security. The concepts of e-governance, e-commerce, e-business, e-learning, and digital libraries are already in place and evolving across poles. This raises various concomitant threats such as illegal copying, illegal redistribution, tampering, forgery and authentication of copyrighted digital assets. Digital Watermarking is an effective technique which can be introduced for solving the above mentioned threats. Based on the detection of the Watermark, the ownership and the integrity of the data can be asserted. Database Watermarking techniques are generally classified into two: i.e., Robust or Fragile. Robust watermarking techniques are designed for copyright protection and fragile watermarking techniques are for authentication or integrity checking of data. Watermarking schemes for relational databases authentication are almost fragile in nature. These algorithms do not allow any legitimate modification of the data. In most of the cases, innocent distortions such as tuple and/or attribute sorting may be considered as tampering. In this paper, the research work proposes a novel semi-fragile watermarking technique for tamper detection of relational databases. The new semi-fragile scheme can detect and localize malicious modifications, while allowing authorized updates. Theoretical analysis and experimental results demonstrate that common database attacks can be detected with high rate of success.
Fuzzy Relational Scattered Distance Based Clustering Method for Sparsely Distributed High Dimensional Data Objects

Clustering is one of the most significant ideas in data mining. It is an unsupervised learning model. Clustering technique in handling high dimensional data is more complex due to intrinsic sparsity nature of high dimensional data. Though, existing methods to reduce immaterial clusters were based on spectral clustering algorithm and graph-based learning algorithm, whose lack of sparsity and polynomial time complexity compromises their efficiency when applied to sparse high dimensional data. This paper concentrates to cluster the sparsely distributed high dimensional data objects. Fuzzy Relational Scattered Distance Based Clustering (FRSDBC) method is developed with three models such as Geometric Median Based Fuzzy model, Scattered Distance measure model, Grid based clustered sparse data representation model. Geometric Median Based Fuzzy model calculates the geometric median of similar sparse data and then the non similar sparse data objects to fitting the relational fuzziness across data points. It involves in the subspace reduction of data objects. Scattered Distance measure model is used to measure the distance between the inner and outer object. Grid based clustering is used to calculate the area of the cluster in FRSDBC method. The main idea of the FRSDBC method is to clustering data points over sparsely distributed data within limited processing time. The Clustering Time, Clustering Accuracy and Space Complexity of each method is analyzed. The result of the FRSDBC method is compared with other techniques, the results obtained are more accurate, easy to understand and the clustering time was substantially low in FRSDBC method. It is widely used in many practical applications such as weather forecast, share trading, medical data analysis and aerial data analysis.
Elliptic Curve and Homomorphic ElGamal Hybrid Based Mutual Authentication Framework for Security in Cloud Computing

Cloud computing is an extensive technology from which the client could access several services through a remote server. Authentication of the remote services needs a common key between the client and the server in a secured manner. The existing key agreement protocols utilized various techniques for the preservation of the data security. The proposed work attempted to provide a high secure data by optimizing the key generation for encryption and decryption process. Hybridization of a novel ECC (Elliptic Curve Cryptography) algorithm and homomorphic ElGamal algorithm for encryption and decryption and also employment of a bio-inspired Genetic algorithm for the generation of maximum secured key is performed. A random 128 bit hash have been developed for the generation of two input points to run the homomorphic property in the ElGamal algorithm secures the key and make it as a non breakable one. The integrated property of ECC and the ElGamal associated with the Genetic algorithm makes the key more stabilized and a confidential one that is more resistant to the various kinds of attacks. The performance analysis depicted that the proposed technique outperform the existing with respect to computational time.
Improvements of satellite observations through data merging: status and challenges

Earth and Space Science Open Archive PosterOpen AccessYou are viewing the latest version by default [v1]Improvements of satellite observations through data merging: status and challengesAuthorsSeokhyeonKimiDRunzeZhangiDAshishSharmaVenkataramanLakshmiSee all authors Seokhyeon KimiDCorresponding Author• Submitting AuthorUniversity of New South WalesiDhttps://orcid.org/0000-0002-1819-8022view email addressThe email was not providedcopy email addressRunze ZhangiDUniversity of VirginiaiDhttps://orcid.org/0000-0001-5546-2518view email addressThe email was not providedcopy email addressAshish SharmaUniversity of New South Walesview email addressThe email was not providedcopy email addressVenkataraman LakshmiUniversity of Virginiaview email addressThe email was not providedcopy email address
Genetic algorithm-based intelligent multiagent architecture for extracting information from hidden web databases

Though there are enormous amount of information available in the web, only very small portion of the available information is visible to the users. Due to the non-visibility of huge information, the traditional search engines cannot index or access all information present in the web. The main challenge in the mining of the relevant information from a huge hidden web database is to identify the entry points to access the hidden web databases. The existing web crawlers cannot retrieve all information from the hidden web databases. To retrieve all the relevant information from the hidden web, this paper proposes an architecture that uses genetic algorithm and intelligent agents for accessing hidden web databases. The proposed architecture is termed as genetic algorithm-based intelligent multi-agent system (GABIAS). The experimental results show that the proposed architecture provides better precision and recall than the existing web crawlers.
Performance Evaluation of Hybrid Round Robin Algorithm and Modified Round Robin Algorithm in Cloud Computing

The scheduling Round Robin (RR) is an impartial algorithm that schedules cloud resources by giving static time quantum to all processes. Time quantum selection is very crucial as it determines performance of algorithms. This research paper suggests an approach to improve RR scheduling algorithm in cloud computing by considering the quantum to be equal to burst time of start request, which dynamically vary after each execution of a request. And also, if the remaining burst time of CPU for currently executing process is lesser than time quantum, then the CPU will be allocated again to the executing process for rest of CPU burst time. MatLAb was used to implement the planned algorithm and benchmarked against MRRA available in literature. In comparison with the planned algorithm, Average Turnaround Time (ATAT) and minimal Average Waiting Time (AWT) was recorded. Based on the obtained simulated outcome, the planned algorithm should be preferred over modified round robin algorithm as it significantly improves the system efficiency.
Visualizing Metric Trends for Software Portfolio Quality Management

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Charityhowto.com webinar offers tips for running virtual events

The nonprofit resources website Charityhowto.com will host a webinar titled Nonprofit Virtual Events: How to Set up and Run Virtual Events: Step‐By‐Step Guide on Dec. 2 and Dec. 10 at 3:00 p.m. EST and 1:00 p.m. EST, respectively.
Visually Analyzing the Code Quality of Component-based Web Applications

The ninth IEEE Working Conference on Software Visualization (VISSOFT 2021) builds upon the success of the previous eight editions of VISSOFT, which in turn followed after six editions of the IEEE International Workshop on Visualizing Software for Understanding and Analysis (VISSOFT) and five editions of the ACM Sympo0sium on Software Visualization (SOFTVIS). In 2021, VISSOFT will take place and be co-located with ICSME.
Human Distance Estimation using Quadcopter for Surveillance Purpose

Nowadays, quadcopters are commonly used. Quadcopters are unmanned aerial vehicles with four propellers to provide lift to fly and hover above ground. Quadcopter nowadays is a very common commercial item in everyday life. Some quadcopters are designed to do 3D or 2D mapping of a certain area or to take videos or just for entertainment purposes. Quadcopter is a very versatile item and is able to change into anything for example a quadcopter can also be used for security purposes to decrease the crime rate of our country. The objective of this study is to design and develop a quadcopter with image processing system to have the ability to measure the distance of a human from the drone itself. The quadcopter is designed to be small in size and have a mini computer like Raspberry Pi on top of it to compute the algorithm to calculate the distance of the human by using image processing technique through the camera which is setup on the drone. Human detecting algorithm YOLO and software Open CV is chosen to detect human and calculate the distance from the quadcopter. The results show that the system is quite limited by the capabilities of the hardware. The system shows an accuracy of more than 90 percent when the human is standing within a certain range. Both the accuracy of the distance sensing and human recognizing system is affected by the limitation of the hardware.
Moving Object Detection and Tracking under Different Occlusion Conditions in Video Sequences

This paper proposed a novel method for the detection and tracking of hand-thrown object in a video sequence in real time sports events. This paper mainly aimed to detect regions of the object in a set of outdoor and indoor videos in different occlusion conditions, and used Kalman filter to detect object on different trajectories over a fixed time window. This approach proved that the thrown object is successfully detected in various cases under occlusion and non-occlusion conditions with different backgrounds. To evaluate the accuracy, two different types of performance evaluations metrics are used based on object detection and tracking. The results shows that significant performance, the average accuracy of the object detecting is 97.89% and tracking is 98.35%.
A Framework for Moving Target Defence with Data Encryption Standard

Moving Target Defence (MTD) became an important research area in the wake of increased cyber security threats. As the attackers are gaining knowledge on existing methods, it is essential to have more dynamic approach that can defeat plans of attackers. As improving systems with higher level of security is a never ending process, MTD has got significance in military and other applications where critical digital infrastructure needs to be protected from adversaries. When attack surface is dynamically evolving with mutation strategy, it can lead to realization of MTD. As MTD increases complexity and uses dynamic encryption mechanism, the attack surface evolves from time to time confusing attacker. Traditional approaches like AES and DES alone will have their limitations. However, when they are used along with the concept of MTD strategies, it is possible to provide highly secure environment. In this paper, we proposed a framework with an underlying algorithm which ensures MTD with dynamically evolving attack surface and dynamic encryption standards based on DES. The experimental results revealed that the proposed scheme is effective and shows improved performance over its predecessor.
Penerapan Metode Certainty Factor untuk Mendiagnosa Penyakit THT

Expert system is a system that seeks to adopt human knowledge into computers, so that computers can solve problems like experts do. ENT (ears, nose, and throat) are organs that are closely interconnected. Abnormalities in these organs are diagnosed and treated by a specialist doctor. One of the functions of these organs such as the ear. The ear is an organ for hearing and balance consisting of the outer ear, middle ear and inner ear. The function of the nose, the nose is the olfactory organ and the main way in and out of air, the nose also provides additional sound resonance and is a place for paranasal sinuses and tear ducts. While the function of the throat is a muscular duct where the food goes to the esophagus and where the air travels to the lungs. In this study, an expert system was built to detect and be equipped with a certainty value of the diagnosis. The certainty value is obtained using the Certainty Factor (CF) method.
ADR Briefs

Alternatives to the High Cost of LitigationVolume 37, Issue 8 p. 119-122 ADR Briefs ADR Briefs Savannah Billingham-Hemminger, Savannah Billingham-HemmingerSearch for more papers by this authorRuss Bleemer, Russ BleemerSearch for more papers by this authorBrian Chihera, Brian ChiheraSearch for more papers by this authorHew Zhan Tze, Hew Zhan TzeSearch for more papers by this author Savannah Billingham-Hemminger, Savannah Billingham-HemmingerSearch for more papers by this authorRuss Bleemer, Russ BleemerSearch for more papers by this authorBrian Chihera, Brian ChiheraSearch for more papers by this authorHew Zhan Tze, Hew Zhan TzeSearch for more papers by this author First published: 03 September 2019 https://doi.org/10.1002/alt.21804Read 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 Volume37, Issue8September 2019Pages 119-122 RelatedInformation