A Scheme of Selecting Vehicles to Assist Download Based on WebGIS for VANET

The assisted download is an effective method solving the problem that the coverage range is insufficient when Wi-Fi access is used in VANET. For the low utilization of time-space resource within blind area and unbalanced download services in VANET, this paper proposes an approximate global optimum scheme to select vehicle based on WebGIS for assistance download. For WebGIS, this scheme uses a two-dimensional matrix to respectively define the time-space resource and the vehicle selecting behavior, and uses Markov Decision Process to solve the problem of time-space resource allocation within blind area, and utilizes the communication features of VANET to simplify the behavior space of vehicle selection so as to reduce the computing complexity. At the same time, Euclidean Distance(Metric) and Manhattan Distance are used as the basis of vehicle selection by the proposed scheme so that, in the case of possessing the balanced assisted download services, the target vehicles can increase effectively the total amount of user downloads. Experimental results show that because of the wider access range and platform independence of WebGIS, when user is in the case of relatively balanced download services, the total amount of downloads is increased by more than 20%. Moreover, WebGIS usually only needs to use Web browser (sometimes add some plug-ins) on the client side, so the system cost is greatly reduced.

Implementing Public Accountant Professional Standards to Improve Audit Quality in Public Accountant Firms in East Java, Indonesia

The purpose of this research is to adopt public accounting professional standards in Malang and Surabaya, East Java, Indonesia, in order to improve audit quality. A total of 150 junior and senior auditors, supervisors, managers, and partners from public accounting companies in Malang and Surabaya, Indonesia, were included in the sample. The study's findings revealed that the competency of the auditors performing audits on behalf of the customer had an impact on the audit quality. Recommendations for improving audit quality based on public accountants' professional standards should be maximized and implemented to public accountants' audits on the client side so that auditor quality improves and more assignments are completed.

A Comprehensive Web-based System for Flood Inundation Map Generation and Comparative Analysis Based on Height Above Nearest Drainage

It is critical to obtain accurate flood extent predictions in a timely manner in order to reduce flood-related casualties and economic losses. Running a real-time flood inundation mapping model is a critical step in supporting quick flood response decisions. Most inundation systems, on the other hand, are either overly demanding in terms of data and computing power or have limited interaction and customization with various input and model configurations. This paper describes a client-side web-based real-time inundation mapping system based on the Height Above the Nearest Drainage (HAND) model. The system includes tools for hydro-conditioning terrain data, modifying terrain data, custom inundation mapping, online model performance evaluation, and hydro-spatial analyses. Instead of only being able to work on a few preprocessed datasets, the system is ready to run in any region of the world with limited data needs (i.e., elevation). With the system's multi-depth inundation mapping approach, we can use water depth measurements (sensor-based or crowdsourced) or model predictions to generate more accurate and realistic flood inundation maps based on current or future conditions. All of the system's functions can be performed entirely through a client-side web browser, without the need for GIS software or server-side computing. For decision-makers and the general public with limited technical backgrounds, the system provides a one-stop, easy-to-use flood inundation modeling and analysis tool.

Modelling Building Shadows on Rooftop Generating 3D City Model

3D city models enable us to gain a better grasp of how various city components interact with one another. Advances in geosciences now allow for the automatic creation of high-quality, realistic 3D city models. It is not limited to visualization and navigation, however, also for shadow and solar potential analysis. Solar radiation is an example of a 3D GIS tool that is in high demand. The calculation of solar radiation that reaches 3D objects can be simple, but the shadow effect of nearby buildings is a considerably more challenging issue because some facades or roofs are only partially shadowed. The present study is analyzed into two approaches. The first approach is considered as Visualization (client-side) approach to visualize the 3D city models on the website using NodeJS and CesiumJS. The second approach is considered as Analyzation (Server-side) approach to analyze the solar potential using python for faster processing and deeming the future development aspects.

Sistema de gestión para las inversiones de Suelos del Ministerio de la Agricultura en Granma

Various processes are carried out in the Soil and Fertilizer Department of the Ministry of Agriculture at Granma's province in Cuba, including information management for investment approval. It becomes difficult due to the fact that it is carried out manually and through printed models, leading to insufficiencies in the personnel in charge of recording the information, difficulty in preserving relevant information and delay in the response process. In response to these needs, in this investigation, an informatics system is developed that will enrich the management of the information for the approval of investments of Soils and Fertilizers in Granma. For the development of the system was utilized as methodology of development of software Extreme Programming (XP). PHP 7.3.3 and SQL as server-side, client-side programming languages HTML 5, CSS 3, JavaScript and JQuery 1.2.2. APACHE 2.4.38 web application server, MySQL 5.0.12 as Database manager, CodeIgniter 3.1.10 as Framework and DBDesigner 4 as an aid to database modeling. As a result of investigation, a system validated by means of proofs of software was obtained, which vouch for his correct functioning.

PMHE:A Wearable Medical Sensor Assisted Framework For Health Care Based On Blockchain And Privacy Computing

Nowadays, smart medical cloud platforms have become a new direction in the industry. However, because the medical system involves personal physiological data, user privacy in data transmission and processing is also easy to leak in the smart medical cloud platform. This paper proposed a medical data privacy protection framework named PMHE based on blockchain and fully homomorphic encryption technology. The framework receives personal physiological data from wearable devices on the client side, and uses blockchain as data storage to ensure that the data cannot be tampered with or forged; Besides, it use fully homomorphic encryption method to design a disease prediction model, which was implemented using smart contracts. In PMHE, data is encoded and encrypted on the client side, and encrypted data is uploaded to the cloud platform via the public Internet, preventing privacy leakage caused by channel eavesdropping; Smart contracts run on the blockchain platform for disease prediction, and the operators participating in computing are encrypted user data too, so it avoids privacy and security issues caused by platform data leakage. The client-to-cloud interaction protocol is also designed to overcome the defect that fully homomorphic encryption only supports addition and multiplication by submitting tuples on the client side, to ensure that the prediction model can perform complex computing. In addition, the design of the smart contract is introduced in detail, and the performance of the system is analyzed. Finally, experiments are conducted to verify the operating effect of the system, ensuring that user privacy is not leaked without affecting the accuracy of the model, and realizing a smart medical cloud platform in which data can be used but cannot be borrowed.

Towards Progressive Geospatial Information Processing on Web Systems: A Case Study for Watershed Analysis in Iowa

Geographic Information Systems (GIS) are available as stand-alone desktop applications as well as web platforms for vector- and raster-based geospatial data processing and visualization. While each approach offers certain advantages, limitations exist that motivate the development of hybrid systems that will increase the productivity of users for performing interactive data analytics using multidimensional gridded data. Web-based applications are platform-independent, however, require the internet to communicate with servers for data management and processing which raises issues for performance, data integrity, handling, and transfer of massive multidimensional raster data. On the other hand, stand-alone desktop applications can usually function without relying on the internet, however, they are platform-dependent, making distribution and maintenance of these systems difficult. This paper presents RasterJS, a hybrid client-side web library for geospatial data processing that is built on the Progressive Web Application (PWA) architecture to operate seamlessly in both Online and Offline modes. A packaged version of this system is also presented with the help of Web Bundles API for offline access and distribution. RasterJS entails the use of latest web technologies that are supported by modern web browsers, including Service Workers API, Cache API, IndexedDB API, Notifications API, Push API, and Web Workers API, in order to bring geospatial analytics capabilities to large-scale raster data for client-side processing. Each of these technologies acts as a component in the RasterJS to collectively provide a similar experience to users in both Online and Offline modes in terms of performing geospatial analysis activities such as flow direction calculation with hydro-conditioning, raindrop flow tracking, and watershed delineation. A large-scale case study is included in the study for watershed analysis to demonstrate the capabilities and limitations of the library. The framework further presents the potential to be utilized for other use cases that rely on raster processing, including land use, agriculture, soil erosion, transportation, and population studies.

Real-time user clickstream behavior analysis based on apache storm streaming

This paper presents an approach to analyzing consumers’ e-commerce site usage and browsing motifs through pattern mining and surfing behavior. User-generated clickstream is first stored in a client site browser. We build an ingestion pipeline to capture the high-velocity data stream from a client-side browser through Apache Storm, Kafka, and Cassandra. Given the consumer’s usage pattern, we uncover the user’s browsing intent through n-grams and Collocation methods. An innovative clustering technique is constructed through the Expectation-Maximization algorithm with Gaussian Mixture Model. We discuss a framework for predicting a user’s clicks based on the past click sequences through higher order Markov Chains. We developed our model on top of a big data Lambda Architecture which combines high throughput Hadoop batch setup with low latency real-time framework over a large distributed cluster. Based on this approach, we developed an experimental setup for an optimized Storm topology and enhanced Cassandra database latency to achieve real-time responses. The theoretical claims are corroborated with several evaluations in Microsoft Azure HDInsight Apache Storm deployment and in the Datastax distribution of Cassandra. The paper demonstrates that the proposed techniques help user experience optimization, building recently viewed products list, market-driven analyses, and allocation of website resources.

A Machine Learning-based Approach to Identify Therapists who can Perceive Client-Side Effects in Psychotherapy

Background: Side effects in psychotherapy are sometimes unavoidable. Therapists play a significant role in the side effects of psychotherapy, but there have been few quantitative studies on the mechanisms by which therapists contribute to them. Methods: We designed the Psychotherapy Side Effects Questionnaire-Therapist Version (PSEQ-T) and released it online through an official WeChat account, where 530 therapists participated in the cross-sectional analysis. The therapists were classified into groups with and without perceptions of clients’ side effects. A number of features were selected to distinguish the therapists by category. Six machine learning–based algorithms were selected and trained by our dataset to build classification models. To make the prediction model interpretable, we leveraged the Shapley Additive exPlanations (SHAP) method to quantify the importance of each feature to the therapist categories.Results: Our study demonstrated the following: 1) Of the therapists, 316 perceived the side effects of the clients in the ongoing psychotherapy sessions, with a 59.6% incidence of side effects. Among all 7 perception types of the side effects, the most common type was “make the clients or patients feel bad” (49.8%). 2) A random forest–based machine-learning classifier offered the best predictive performance to distinguish the therapists with and without perceptions of clients’ side effects, with an F1 score of 0.722 and an AUC value of 0.717. 3) When “therapists’ psychological activity” was considered a possible cause of the side effects in psychotherapy by the therapists, it was the most relevant feature for distinguishing the therapist category.Conclusions: Our study revealed that the therapist's mastery of the limitations of psychotherapy technology and theory, especially the awareness and construction of their own psychological states, was the most important factor in predicting the therapist's perception of the side effects of psychotherapy.

PEMANFAATAN Web App BUILDER UNTUK PEMBUATAN SISTEM INFORMASI JALAN DAN JEMBATAN BERBASIS WEB SIG (Studi Kasus : Kabupaten Sumba Tengah)

Kelancaran transportasi merupakan hal yang sangat penting dalam memajukan perekonomian suatu daerahkhususnya dalam mendukung kelancaran pergerakan orang ataupun barang dari satu tempat ke tempat lain.Kabupaten Sumba Tengah sebagai salah satu Kabupaten di Provinsi Nusa Tenggara Timur memiliki potensi daerahyang beragam dan membutuhkan akses transportasi untuk mendukung kegiatan pembangunan agar dapat berjalandengan baik. Kendala yang terjadi terkait tranportasi adalah belum tersedianya data dan informasi dalam bentukdigital yang dapat diakses dengan mudah dan cepat untuk mendukung sistem pengambilan keputusan khususnyadalam pemeliharaan sarana transportasi jalan dan jembatan. Tujuan penelitian ini memiliki fokus untuk membuatsebuah aplikasi yang dapat menyampaikan informasi dalam bentuk WebSIG. WebSIG merupakan metode untukmeyampaikan informasi peta dalam bentuk digital mengunakan layanan internet yang memungkinkan penggunauntuk melakukan interaksi dengan server. Sistem informasi jaringan jalan dan jembatan Kabupaten Sumba Timurdilakukan menggunakan arsitektur WebSIG dengan pendekatan thick client dan client side yang terdiri ataskomponen web server, map server, map application dan database server dengan dukungan perangkat lunak WebApp Builder dan PostgreSQL database. Hasil dari kegitan ini berupa perangkat lunak WebSIG yang memberikaninformasi jaringan jalan dan jembatan berdasarkan Peraturan Menteri Pekerjaan Umum dan Perumahan RumahRakyat Nomor 25/PRT/M/2014 Tentang Penyelengaraan Data dan Informasi Geospasial Infrastruktur BidangPekerjaan Umum dan Perumahan Rakyat. Total panjang ruas jalan kabupaten di Kabupaten Sumba Tengah adalah750.92 Km dengan Jumlah ruas jalan sebanyak 139 ruas dan Jumlah jembatan 73 jembatan. Perangkat lunak WebSIG memiliki fungsi pencarian data berdasarkan atribut yang dimiliki dan fungsi mengubah data vektor dan atribut.