Medication adherence manager and its clinical application.

Mobile cloud storage provides benefits for educational institutions. Several researchers have researched cloud computing adoption, but only a few studies related to how users experience using Personal Cloud Storage Services. This research aims to investigate the adoption of the mobile cloud storage factors following the theory, as well as research that has been previously proven related to user interest in using mobile cloud storage among higher education students. This quantitative research uses data analysis techniques using GSCA to prove the theory and achieve the research goals. The research methodology consists of five main stages, namely the stage of model development and research design, the stage of preparing the instrument and its measurement, the stage of testing the instrument, the stage of survey and results, as well as the stages of analysis and discussion as well as conclusions. Five variables are investigated in this research: knowledge sharing, perceived usefulness, attitude toward using a system, trust, and intention to use. The results of hypothesis testing were conducted using GSCA; three proposed hypotheses were accepted, and one was rejected. The variables the research model can explain are 68%, and the remaining 32% are other variables not used in this study. The characteristics of respondents can provide several ways to increase the adoption of mobile cloud computing by linking research results from inferential analysis and descriptive analysis. Future research can focus on extracting these variables through user interviews regarding students' intentions to use mobile cloud computing.

Real-time monitoring of radiation levels at uranium mining sites is mandatory to ensure environmental and human safety. Ionizing radiation like Gamma rays, Alpha particles, Beta particles are likely to be produced during uranium decay have major threats to human health such as lung cancer, tumor, and eventually death. Thus there have been several different means of monitoring uranium mining using radiation survey meters and other radiation detectors. However, frequent traveling to the uranium mining site to measure the radiation level is time-consuming and cost full to the regulatory bodies. Thus this study aims to present a system for real-time monitoring the radiation level at uranium mining sites using internet of things (IoT) technology. The system was programmed by using ESP 32 microcontroller board, through the inbuilt Wi-Fi it was able to send radiation data to the Message Queuing Telemetry Transport (MQTT) broker for cloud data storage. The MQTT protocol facilitated remote visualization of radiation levels from the cloud storage and mobile application. The end-users monitored radiation data in real-time and received the notification message and alarm in case of excess radiation through the mobile application. The ESP 32 microcontroller board and internet of things technology facilitated the system to send the data to the cloud allowing the end-users to visualize and monitor radiation levels anytime and anywhere via the internet.

Efficient personalized search over encrypted data for mobile edge-assisted cloud storage

To assess the impact of gender and orthodontic qualification length on the awareness, knowledge and usage of orthodontic diagnostic mobile applications, non-diagnostic mobile applications and social media platforms among orthodontic clinicians. Cross-sectional questionnaire-based study. The Republic of Croatia. A total of 92 orthodontic specialists, members of the Croatian Dental Chamber. This study was conducted using a questionnaire distributed via email to orthodontic clinicians between May and July 2022. In total, 92 respondents were divided into groups according to sex and median orthodontic qualification length: more recently qualified (MRQ) with ⩽12 years; and longer qualified (LQ) with >12 years. Nearly one-third of respondents did not have any prior knowledge of mobile applications used as an orthodontic diagnostic tool. MRQ respondents were more interested in using mobile apps as opposed to computer software for digital analysis (P < 0.05). This interest was in a negative correlation with orthodontic qualification length (P < 0.01) and was more prevalent among female respondents (P < 0.001). About one-third (32.6%) of respondents did not use non-diagnostic mobile applications and 44.6% did not use social media platforms. Nearly two-thirds (62%) of the respondents did not promote their work through social media. Male respondents and LQ promoted their work more frequently than others (P < 0.05). The usage of other mobile applications was in a positive correlation with the knowledge and awareness of orthodontic mobile applications (P < 0.05). Orthodontic clinicians lacked knowledge, awareness and the usage of orthodontic diagnostic mobile applications according to sex and orthodontic qualification length. One-third used non-diagnostic mobile applications and less than half used social platforms in daily clinical work.

Outsourcing heavy storage and computation to the cloud servers now becomes more and more popular. How to secure share the cloud storage is an important problem for many mobile users. Proxy re-encryption is such a cryptographic primitive which can be used to secure share cloud data. Until now there are many kinds of proxy re-encryption schemes with various properties, such as conditional proxy re-encryption, proxy re-encryption with keyword search etc. However until now there exists no work focus on proxy re-encryption for mobile cloud storage sharing. In mobile cloud storage, almost all the users are mobile ones, they only have resource-restricted equipments. In this paper we try to initialize this research, we give a very basic outsourced online/offline proxy re-encryption scheme for mobile cloud storage sharing and leave many interesting open problems as the future work.

Objective: To explore existing evidence of economic burden of esophageal cancer in China over the past 20 years. Methods: Based on PubMed, CNKI and Wanfang, literatures published from 1996 to 2015 were retrieved with the key words such as " economic burden" , "cost of illness" and so on. Then the information excerpted from those literatures were analyzed after several exclusionary procedures for non-esophageal cancer related literatures. The information about subjects and data source, methodology, main results were structurally abstracted and then analyzed. Quality assessments were conducted independently by two investigators using an 11-item instrument recommended by the Agency for Healthcare Research and Quality (AHRQ) for cross-sectional studies. All the expenditure data were calculated according to year-specific personal health care consumer price index (CPI) of China, the annual growth rate was calculated according to the average speed of growth. Results: A total of 23 studies (21 individual surveys and 2 population-based surveys) were included in the analysis, in which 12 were published over the past 5 years. Among the 21 individual surveys, 17 were hospital-based and the data were obtained through medical record review, and most of which only considered the direct medical economic burden (including the average overall expenditure per patient, per time and per diem). The median expenditure per patient during 1996-2011 ranged from 7 463 to 37 647 yuan (RMB) and the average growth rate was 7.68%. The median medical expenditure per clinical visit during 1996-2013 ranged from 6 851 to 57 554 yuan (RMB) and the average growth rate was 11.89%. The median medical expenditure per diem during 1996-2010 ranged from 225 to 1 319 yuan (RMB) and the average growth rate was 12.53%. The direct medical expenditure per clinical visit varied greatly with area, which were much higher in Beijing, Shanxi and Hubei. In both individual survey and population-based survey, less data about the direct non-medical expenditure and the influence of indirect expenditure on the economic burden were reported. Conclusion: Less data are available on economic burden of esophageal cancer in China over the past 20 years and the data's comparability are poor, especially in terms of population level or indirect burden. Direct medical expenditure is on the rise, and regional differences.

Fuel load is a crucial parameter for evaluating design fires for buildings. However, the availability of fuel load data is currently hindered by the lack of an efficient on-site data collection method. This research develops a new methodology for fuel load surveys that can facilitate the collection, storage, and analysis of fuel load data for a variety of building occupancies. The new survey method harnesses recent developments in mobile electronic devices, cloud storage, and machine vision to efficiently complete fuel load surveys in buildings. A four-step method is developed comprising digital inventory, data organization, item matching through computer vision, and fuel load estimation. The method is completed through an interactive electronic surveying form accessible on any mobile device with an internet connection, such as a tablet. The application allows taking digital measurements and pictures of the room and content, which are stored, and later searched through retail search engines using image recognition. Automatic matching of the picture with an online catalogue item gives access to further information about this item which are then used to evaluate the item fuel load, using a table of materials calorific values coded in the application. A wide adoption of this method could provide benefits by progressively populating such digital fuel load database. The results can then be used to provide design guidelines for fuel load density in codes and standards, for application in performance-based design of structures in fire.

PurposeCloud computing becomes mobile when a mobile device tries to access the shared pool of computing resources provided by the cloud, on demand. Mobile applications may enrich their functionality by delegating heavy tasks to the clouds as the remote processing and storage have become possible by adding asynchronous behavior in the communication. However, developing mobile cloud applications involves working with services and APIs from different cloud vendors, which mostly are not interoperable across clouds. Moreover, by adding asynchronicity, mobile applications must rely on push mechanisms which are considered to be moderately reliable, and thus not recommended in scenarios that require high scalability and quality of service (QoS). To counter these problems, and the purpose of this paper, is to design a middleware framework, Mobile Cloud Middleware (MCM), which handles the interoperability issues and eases the use of process‐intensive services from smartphones by extending the concept of mobile host.Design/methodology/approachMCM is developed as an intermediary between the mobile and the cloud, which hides the complexity of dealing with multiple cloud services from mobiles. Several applications are presented to show the benefits of mobiles going cloud‐aware. Moreover, to verify the scalability of MCM, load tests are performed on the hybrid cloud resources using well known load balancing mechanisms like HAProxy and Tsung.FindingsFrom the study it was found that it is possible to handle hybrid cloud services from mobiles by using MCM. The analysis demonstrated that the MCM shows reasonable performance levels of interaction with the user, thus validating the proof of concept. Moreover, MCM decreases the effort in developing mobile cloud applications and helps in keeping soft‐real time responses by using its asynchronous approach.Originality/valueMCM fosters the utilization of different types of cloud services rather than the traditional mobile cloud services based on data synchronization. By offloading heavy tasks to the clouds, the framework extends the processing power and storage space capabilities of the constrained smart phones. The applications mentioned in the paper bring an added value by being success stories for mobile cloud computing domain in general.

Smart sensor-equipped mobile devices sense, collect, and process data generated by the edge network to achieve intelligent control, but such mobile devices usually have limited storage and computing resources. Mobile cloud storage provides a promising solution owing to its rich storage resources, great accessibility, and low cost. But it also brings a risk of information leakage. The encryption of sensitive data is the basic step to resist the risk. However, deploying a high complexity encryption and decryption algorithm on mobile devices will greatly increase the burden of terminal operation and the difficulty to implement the necessary privacy protection algorithm. In this paper, we propose ENSURE (EfficieNt and SecURE), an efficient and secure encrypted search architecture over mobile cloud storage. ENSURE is inspired by edge computing. It allows mobile devices to offload the computation intensive task onto the edge server to achieve a high efficiency. Besides, to protect data security, it reduces the information acquisition of untrusted cloud by hiding the relevance between query keyword and search results from the cloud. Experiments on a real data set show that ENSURE reduces the computation time by 15% to 49% and saves the energy consumption by 38% to 69% per query.

Leveraging Microsoft׳s mobile usability guidelines: Conceptualizing and developing scales for mobile application usability

Vegetarian diets and lifestyle have been shown to reduce the risk of many chronic non-communicable diseases, which now accounts for the major global burden of diseases. We aimed to determine the contribution of vegetarian diets and lifestyle to the actual direct medical cost in a population-based study. Through linkage to the National Health Insurance Research Database of Taiwan, we compared the health care utilization and medical expenditure of 2166 vegetarians and 4332 age-sex-matched omnivores recruited from the Buddhist Tzu Chi Foundation. Diet and lifestyle questionnaires were self-administered and prospectively collected. We used the general linear model to estimate the 5-year average medical expenditure in vegetarians versus omnivores while adjusting for age, sex, education, exercise habits, smoking, and alcohol drinking. Medical expenses related to non-diet associated lifestyle factors (smoking, alcohol drinking, active community volunteering, and religious emotional support) were estimated through a comparison with the published population medical cost data standardized to match the age and sex characteristics of the cohort. Tzu Chi vegetarians had significantly lower outpatient visits. This translated into 13% lower outpatient (p = 0.007) and 15% lower total medical expenditures (p = 0.008) when compared with the Tzu Chi omnivores, who had an additional 10% lower medical expenditure when compared with the general population. No difference in dental visits and expenses were found between diet groups. Vegetarian diets are associated with significantly lower medical care expenditure and could be an effective strategy to alleviate the medical–economic burden in selected populations.

Background and Aims The presence of chronic kidney disease (CKD) in patients with type 2 diabetes mellitus (T2DM) leads to elevated medical and economic burden, and with CKD progression, the medical expenditure increases substantially. Information about healthcare utilization and medical expenditures of this patient population is limited in China. This study aims to describe the medical cost and healthcare utilization of patients with CKD and T2DM in a regional database in China. Method A retrospective, regional EHR-based serial cross-sectional study was conducted in Yinzhou Regional Healthcare Database (YRHCD), Ningbo, China. All adult patients (age &amp;gt; = 18 years) with CKD and T2DM were collected between 1st Jan 2017 and 31st Dec 2020, patients were excluded if they did not have serum creatinine (SCr) values or initiated renal replacement therapy. Eligible patients were identified at each calendar year and categorified by CKD stages (G1-G5). Data on demographics, comorbidities and drug prescription were presented for all included patients at baseline and from 2017 to 2020. Annual medical costs and healthcare utilization were described among different CKD stages. Two-part models were built to estimate the medical costs and healthcare utilization in each CKD stage. Results A total of 16,521 patients with CKD and T2DM were included with a substantial increase between 2017 and 2020. Among all patients, the majority of them were classified in CKD stage 1 and 2. Over 70% of patients aged 65 years or older and approximately 55% were female. &amp;gt;90% of patients had hypertension, followed by peripheral vascular diseases, which increased from 69.2% in 2017 to 82.2% in 2020. Renin–angiotensin system inhibitors (RASI) were the most prescribed medication and metformin ranked the second. In general, the age, proportion of having comorbidities and proportion of drug prescription presented an increasing trend from 2017 to 2020. The proportion of eGFR value &amp;gt; = 25 and &amp;lt; = 75 mL/min/1.73m2 in G1 to G4 was 64.4% for baseline and decreased from 58.2% in 2017 to 48.7% in 2020. The general trend of medical costs in all CKD stages increased from 2017 to 2020; for healthcare utilization, the average number of outpatient visits per person per year was over 10.0 times per each CKD stage. The medical cost and healthcare utilization increased substantially in patients with more advanced CKD stages. Mean annual medical costs per patients were 6,084, 8,675, 14,291, 24,971 and 42,580 CNY (908, 1,294, 2,132, 3,726 and 6,353 USD) and the mean length of stay were 2.2, 3.3, 6.2, 12.6 and 16.1 days for G1-5 patients respectively in 2020. Patients in G1 and G2 had more outpatient visits compared with hospitalization, the cost of hospitalization raised dramatically in patients with G4-G5 and became a main contributor of total medical cost. Conclusion Our contemporary study revealed the medical cost and use of healthcare resources increased moderately over time in earlier CKD stages but grew remarkably from G4 stage onwards. The estimates suggested significant correlation between CKD stages and medical costs and healthcare utilization. Our findings further suggest earlier CKD identification and timely treatment may reduce the overall medical and economic burden in this population.

Most people nowadays are always occupied with their mobile devices. Mobile devices were utilized not just as a means of communication but also to launch applications installed to aid routine activities. The deployment of cloud storage applications to access cloud storage accounts is one of the most popular uses. Consumers have rapidly adopted cloud storage services from mobile devices, often available over the internet. However, this situation allows criminals to engage in illegal acts such as child pornography and violence. Since cloud services are virtual, non-local, and primarily proprietary technologies, digital forensics investigators encounter a significant challenge in resolving such issues. For investigators, data from mobile devices is vital. It will be stored on the mobile device and provide an overview of the user's cloud storage contents. This study focuses on Android devices and employs the MediaFire and Sync.com applications along with 20 data sets in various formats as samples. The mobile device will then be extracted using MSAB XRY under various circumstances (after the process of file modification, data cleanup, cache clearance, and application removal). The study contributes to the design of a data extraction framework guided by NIST 800–101 rev 1 and SWGDE Best Practices, as well as the documentation of the extraction procedure, as a step in ensuring that the data extraction process adheres to digital forensics standards. This research is projected to offer a fundamental reference for conducting digital forensic investigations of mobile cloud storage services.

With the proliferation of new mobile devices, mobile cloud computing technology has emerged to provide rich computing and storage functions for mobile users. The explosive growth of mobile data has led to an increased demand for solutions that conserve storage resources. Data deduplication is a promising technique that eliminates data redundancy for storage. For mobile cloud storage services, enabling the deduplication of encrypted data is of vital importance to reduce costs and preserve data confidentiality. However, recently proposed solutions for encrypted deduplication lack the desired level of security and efficiency. In this paper, we propose a novel scheme for serverless efficient encrypted deduplication (SEED) in mobile cloud computing environments. Without the aid of additional servers, SEED ensures confidentiality, data integrity, and collusion resistance for outsourced data. The absence of dedicated servers increases the effectiveness of SEED for mobile cloud storage services, in which user mobility is essential. In addition, noninteractive file encryption with the support of lazy encryption greatly reduces latency in the file-upload process. The proposed indexing structure (D-tree) supports the deduplication algorithm and thus makes SEED much more efficient and scalable. Security and performance analyses prove the efficiency and effectiveness of SEED for mobile cloud storage services.

Attribute-based encryption (ABE) is suitable for mobile cloud storage to protect data confidentiality and realize fine-grained data access control. It is essential for ABE schemes to achieve attribute revocation as users’ attributes may be changed frequently. Keyword search over encrypted data also needs to be solved in the mobile cloud storage. In addition, computational efficiency is a consideration for the resource-constrained mobile device. Focusing on the above-mentioned problems, an efficiently revocable and searchable ABE (RSABE) scheme for the mobile cloud storage is proposed. In our scheme, the function of attribute revocation is efficiently achieved by delegating the update of secret key and ciphertext to the powerful cloud server. Keyword search is also supported, in which data owners and users can generate the keywords index and search trapdoor, respectively, without relying on always online trusted authority. Furthermore, an outsourced decryption technology is used to reduce the computational load of decryption on user side. Our RSABE scheme is proven to be semantically secure against selective ciphertext policy and chosen plaintext attack, and to be secure against chosen keyword attack in the random oracle model. Finally, performance evaluation demonstrates that our scheme is highly efficient.