Pengembangan Aplikasi Sistem Pelayanan Masyarakat Berbasis Android (Studi Kasus : Kecamatan Payaraman Ogan Ilir)

In public administration services almost every day requests for incoming letters, both requests for business place permits, SK Domicile and other documents. The data collection of letters requested by residents of Payaraman District will be handled directly through the admin where the data will be entered into the request list using a computer, then the letter will be printed for signature, residents have to wait for the letter with uncertain terms. This problem was raised due to the large number of public complaints in issuing a decree that had been signed by the sub-district head. This research uses extreme programming method in development by using CI framework for admin and flutter framework for users. The results of the study are that residents of Payaraman District can access the application to request a letter request which will contain identities such as ID cards and permits or decrees that will be sent back via the web admin to the application according to the request of residents who access/request a letter.

Research on Mobile English Learning System Based on iOS

In order to improve the use experience of mobile learning and reduce the response delay caused by the slow positioning of system resources, research on mobile English learning systems based on iOS is proposed. Firstly, the value of realizing mobile learning is objectively analyzed, and the practical significance of the research is clarified from the perspectives of social development and learning conditions. On this basis, taking the intelligent client equipped with an iOS operating system as the hardware condition of the system, the system architecture, including data access layer, business logic layer, and presentation layer, is constructed by MVC. In the model module, it is divided into ten difficulty levels by using the frequency of vocabulary, the length of words, and the number of syllables of a single word. The learning resources of the reading class are uniformly represented by the vector space model, and the improved TF-IDF is used to calculate the weight of eigenvalues in the resources. According to the calculation results, the resources are also divided into ten difficulty levels, and the divided resources correspond to their respective databases and use regular expressions to find the learning resources that match the access request. Finally, with the support of the iOS protocol, the feedback mechanism between each module is constructed by Express.js. By analyzing the access requests sent and received by the view, the timely call to the target database resources is realized to improve the response rate of the system. The test results show that the function of the designed system can be realized stably, and the module response delay time is stable within 1s; under the ideal network environment, the buffer delay is in the range of 0.4–0.6 s, and the loading delay is no more than 1.8 s when the network speed is 3 Mpbs, which has a good user experience.

Research-ready data for multi-cohort analyses: The Dementias Platform UK (DPUK) C-Surv data model

Research-ready data (that curated to a defined standard) increases scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following user consultation, a standard data model (C-Surv), optimised for data discovery, was developed using data from 12 Dementias Platform UK (DPUK) population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. It was concluded that developing and applying a standard data model (C-Surv) for research cohort data is feasible and useful.

Research-ready data for multi-cohort analyses: The Dementias Platform UK (DPUK) C-Surv data model

Research-ready data (that curated to a defined standard) increases scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following user consultation, a standard data model (C-Surv), optimised for data discovery, was developed using data from 12 Dementias Platform UK (DPUK) population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The data model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. It was concluded that developing and applying a standard data model (C-Surv) for research cohort data is feasible and useful.

Research-ready data for multi-cohort analyses: The Dementias Platform UK (DPUK) C-Surv data model

Research-ready data (that curated to a defined standard) increases scientific opportunity and rigour by integrating the data environment. The development of research platforms has highlighted the value of research-ready data, particularly for multi-cohort analyses. Following user consultation, a standard data model (C-Surv), optimised for data discovery, was developed using data from 12 population and clinical cohort studies. The model uses a four-tier nested structure based on 18 data themes and 137 domains selected according to user behaviour or technology. Standard variable naming conventions are applied to uniquely identify variables within the context of longitudinal studies. The model was used to develop a harmonised dataset for 11 cohorts. This dataset populated the Cohort Explorer data discovery tool for assessing the feasibility of an analysis prior to making a data access request. It was concluded that developing and applying a standard data model (C-Surv) for research cohort data is feasible and useful.

Combining IOTA and Attribute-Based Encryption for Access Control in the Internet of Things

Unauthorized resource access represents a typical security threat in the Internet of things (IoT), while distributed ledger technologies (e.g., blockchain and IOTA) hold great promise to address this threat. Although blockchain-based IoT access control schemes have been the most popular ones, they suffer from several significant limitations, such as high monetary cost and low throughput of processing access requests. To overcome these limitations, this paper proposes a novel IoT access control scheme by combining the fee-less IOTA technology and the Ciphertext-Policy Attribute-Based Encryption (CP-ABE) technology. To control the access to a resource, a token, which records access permissions to this resource, is encrypted by the CP-ABE technology and uploaded to the IOTA Tangle (i.e., the underlying database of IOTA). Any user can fetch the encrypted token from the Tangle, while only those who can decrypt this token are authorized to access the resource. In this way, the proposed scheme enables not only distributed, fee-less and scalable access control thanks to the IOTA but also fine-grained attribute-based access control thanks to the CP-ABE. We show the feasibility of our scheme by implementing a proof-of-concept prototype system using smart phones (Google Pixel 3XL) and a commercial IoT gateway (NEC EGW001). We also evaluate the performance of the proposed scheme in terms of access request processing throughput. The experimental results show that our scheme enables object owners to authorize access rights to a large number of subjects in a much (about 5 times) shorter time than the existing access control scheme called Decentralized Capability-based Access Control framework using IOTA (DCACI), significantly improving the access request processing throughput.

Risk Reduction Privacy Preserving Approach for Accessing Electronic Health Records

In the healthcare field, preserving privacy of the patient's electronic health records has been an elementary issue. Numerous techniques have been emerged to maintain privacy of the susceptible information. Acting as a first line of defence against illegal access, traditional access control schemes fall short of defending against misbehaviour of the already genuine and authoritative users: a risk that can harbour overwhelming consequences upon probable data release or leak. This paper introduces a novel risk reduction strategy for the healthcare domain so that the risk related with an access request is evaluated against the privacy preferences of the patient who is undergoing for the medical procedure. The proposed strategy decides the set of data objects that can be safely uncovered to the healthcare service provider such that unreasonably repeated tests and measures can be avoided and the privacy preferences of the patient are preserved.

Siblings and Discordant Eligibility for Gene Therapy Research: Considering Parental Requests for Non-Trial "Compassionate Use”

Deciding whether to grant an expanded access request for a child whose sibling is enrolled in a gene therapy trial involves a number of complex factors: considering the best interests of the child, the psychosocial and economic impact on the family, and the concerns and obligations of researchers. Despite the challenges in coming to a substantively fair outcome in cases of discordant eligibility, creating a procedurally fair decision-making process to adjudicate requests is essential.

Gone fishing: legal professional privilege and data subject access requests in trust law Dawson-Damer v Taylor Wessing LLP [2020] EWCA Civ 352

Following a data subject access request made in 2014, the Court of Appeal has recently taken the opportunity to consider the nature of joint privilege. By affirming that joint privilege is a procedural issue, rather than a substantive element of trust law, the court removed it from the remit of offshore restrictions upon trustee disclosure duties. However, the Data Protection Act 2018 may yet frustrate future attempts by beneficiaries to use subject access requests to pursue fishing expeditions.

Understanding enterprise data warehouses to support clinical and translational research

Objective Among National Institutes of Health Clinical and Translational Science Award (CTSA) hubs, adoption of electronic data warehouses for research (EDW4R) containing data from electronic health record systems is nearly ubiquitous. Although benefits of EDW4R include more effective, efficient support of scientists, little is known about how CTSA hubs have implemented EDW4R services. The goal of this qualitative study was to understand the ways in which CTSA hubs have operationalized EDW4R to support clinical and translational researchers. Materials and Methods After conducting semistructured interviews with informatics leaders from 20 CTSA hubs, we performed a directed content analysis of interview notes informed by naturalistic inquiry. Results We identified 12 themes: organization and data; oversight and governance; data access request process; data access modalities; data access for users with different skill sets; engagement, communication, and literacy; service management coordinated with enterprise information technology; service management coordinated within a CTSA hub; service management coordinated between informatics and biostatistics; funding approaches; performance metrics; and future trends and current technology challenges. Discussion This study is a step in developing an improved understanding and creating a common vocabulary about EDW4R operations across institutions. Findings indicate an opportunity for establishing best practices for EDW4R operations in academic medicine. Such guidance could reduce the costs associated with developing an EDW4R by establishing a clear roadmap and maturity path for institutions to follow. Conclusions CTSA hubs described varying approaches to EDW4R operations that may assist other institutions in better serving investigators with electronic patient data.