Efficient and customizable WebGIS system based on edge computing

WebGIS currently has a wide range of application requirements and can generate greater economic value. Therefore, there are many units that need to build their own WebGIS system. At present, the way to build a system is usually to purchase professional software and hire professionals to complete the development. Such a construction method requires a high cost, and many of the WebGIS system applications are the same or similar, and repeated construction is also a waste of resources. In order to solve this problem, a WebGIS system based on edge computing is proposed. Comprehensive use of SAAS mode and edge computing methods to solve the needs of users can customize the system. And the system load is reasonably distributed between the server and the browser, which improves the performance of the system. In addition, the system uses edge computing to share map tiles among WebGIS users, reducing the pressure on the server and increasing the speed of use of the WebGIS system. Therefore, the WebGIS system based on edge computing can not only be personalized and customized, but also has good usability and can deal with a large number of visits. After experimental verification, in the case of more than 5 concurrent user requests per second, the system response speed increased by more than 38.6%.

Concurrent Daily and Non-Daily Use of Heated Tobacco Products with Combustible Cigarettes: Findings from the 2018 ITC Japan Survey

Use of heated tobacco products (HTPs) among current smokers is becoming increasingly popular in Japan. This study aims to compare characteristics and tobacco-related behaviors among concurrent users of HTPs and combustible cigarettes (n = 644) with exclusive smokers (n = 3194) or exclusive HTP users (n = 164). The secondary aim was to explore heterogeneity within concurrent use subgroups. Data were from Wave 1 of the ITC Japan Survey, a nationally representative web survey conducted from February to March 2018. Concurrent cigarette-HTP users were younger and wealthier than exclusive smokers. However, there were no difference in the frequency of smoking, number of cigarettes per day, and smoking cessation behaviors between the two groups, suggesting that HTPs reinforce nicotine dependence. Compared to exclusive HTP users, concurrent cigarette-HTP users reported higher frequency of non-daily HTP use, and lower number of tobacco-containing inserts per day. Almost all concurrent cigarette-HTP users smoked every day (93.9%); 48.4% both smoked and used HTPs daily (dual daily users, n = 396), while 45.5% were daily smokers and non-daily HTP users (predominant smokers, n = 213). Concurrent user subgroups differed from each other on age, tobacco use behaviors, and quit intention. Alongside heterogeneity between concurrent and exclusive product users, differences across concurrent use subgroups highlight the importance of considering frequency of use in characterizing poly-tobacco users.

Directional Forgetting for Stable Co-Adaptation in Myoelectric Control

Conventional myoelectric controllers provide a mapping between electromyographic signals and prosthetic functions. However, due to a number of instabilities continuously challenging this process, an initial mapping may require an extended calibration phase with long periods of user-training in order to ensure satisfactory performance. Recently, studies on co-adaptation have highlighted the benefits of concurrent user learning and machine adaptation where systems can cope with deficiencies in the initial model by learning from newly acquired data. However, the success remains highly dependent on careful weighting of these new data. In this study, we proposed a function driven directional forgetting approach to the recursive least-squares algorithm as opposed to the classic exponential forgetting scheme. By only discounting past information in the same direction of the new data, local corrections to the mapping would induce less distortion to other regions. To validate the approach, subjects performed a set of real-time myoelectric tasks over a range of forgetting factors. Results show that directional forgetting with a forgetting factor of 0.995 outperformed exponential forgetting as well as unassisted user learning. Moreover, myoelectric control remained stable after adaptation with directional forgetting over a range of forgetting factors. These results indicate that a directional approach to discounting past training data can improve performance and alleviate sensitivities to parameter selection in recursive adaptation algorithms.

Multiple-beamline operation of SACLA

The SPring-8 Ångstrom Compact free-electron LAser (SACLA) began parallel operation of three beamlines (BL1–3) in autumn 2017 to increase the user beam time of the X-ray free-electron laser. The success of the multiple-beamline operation is based on two technological achievements: (i) the fast switching operation of the SACLA main linear accelerator, which provides BL2 and BL3 with pulse-by-pulse electron beams, and (ii) the relocation and upgrade of the SPring-8 Compact SASE Source for BL1, for the generation of a soft X-ray free-electron laser. Moreover, the photon beamlines and experimental stations were upgraded to facilitate concurrent user experiments at the three beamlines and accommodate more advanced experiments.

Performance Analysis of Aes and 3des for Implementing Multi Level Authentication in Cloud Through Rest Api

Last couple of decades, internet usage has been changed each and every technology domain. This has lead to implementation and accommodation of cloud computing. As the Cloud has the nature of sharing the data, it led to various types of security attacks. Hence security mechanisms which has various features/types are needed and hence security breaches can be prevented. Authentication is one of the vital techniques playing a major role in security part. Cloud Computing verifies the identification of a user during the process of accessing the services from cloud servers. Different authentication techniques are used to verify the user’s identity before granting the access to them. This paper analyze the performance of AES and 3DES algorithms and find out the best suit for implementing multi level authentication in cloud. Based on execution time, request and response time against the concurrent user load and file size, AES is faster, more secure and safer than 3DES.

Towards Update-Efficient and Parallel-Friendly Content-Based Indexing Scheme in Cloud Computing

The sheer volume of contents generated by today’s Internet services is stored in the cloud. The effective indexing method is important to provide the content to users on demand. The indexing method associating the user-generated metadata with the content is vulnerable to the inaccuracy caused by the low quality of the metadata. While the content-based indexing does not depend on the error-prone metadata, the state-of-the-art research focuses on developing descriptive features and misses the system-oriented considerations when incorporating these features into the practical cloud computing systems. We propose an Update-Efficient and Parallel-Friendly content-based indexing system, called Partitioned Hash Forest (PHF). The PHF system incorporates the state-of-the-art content-based indexing models and multiple system-oriented optimizations. PHF contains an approximate content-based index and leverages the hierarchical memory system to support the high volume of updates. Additionally, the content-aware data partitioning and lock-free concurrency management module enable the parallel processing of the concurrent user requests. We evaluate PHF in terms of indexing accuracy and system efficiency by comparing it with the state-of-the-art content-based indexing algorithm and its variances. We achieve the significantly better accuracy with less resource consumption, around 37% faster in update processing and up to 2.5[Formula: see text] throughput speedup in a multi-core platform comparing to other parallel-friendly designs.