Softwarized resource allocation in digital twins-empowered networks for future quantum-enabled consumer applications

Network softwarization (NetSoft), recognized as crucial attribute of 6G networks, promises to provide enhanced and advanced services, including future quantum-enabled consumer applications. Softwarized resource allocation is the core issue in NetSoft concept. Digital twins (DT) guarantees to generate the corresponding digital world that reflects and interacts with the original physical world seamlessly. With DT empowering, the digital replica of softwarized networks can be generated to predict, simulate, analyze the softwarized resource allocation in more economical, convenient and scalable methods.In this paper, we research the softwarized resource allocation of requested services, usually, called as slices, in DT-empowered networks for future quantum-enabled consumer applications. We focus on developing efficient softwarized resource allocation algorithm. At first, we present models of the DT-empowered networks and service requests by using graph theory and hypergraph theory. Then, we design one softwarized resource management framework, labeled as DT-Slice-Soft-6G. This framework has the functions of managing softwarized resources, calculating resource allocation solution in digital replica and sending the calculated solution back to softwarized 6G networks. Thereafter, one efficient and fine-grained softwarized resource allocation algorithm, inserted in DT-Slice-Soft-6G, is detailed. This algorithm is labeled as Heu-DT-Slice-6G and is proposed based on efficient heuristic methods. To validate the highlights of DT-Slice-Soft-6G and Heu-DT-Slice-6G, we conduct the simulation work in our self-developed simulator

Factors Influencing Households’ Intention to Adopt Solar PV : A Systematic Review

Rising energy needs, concerns of energy security, mitigating greenhouse gas emissions, climate change phenomenon and a push to utilize indigenous sources for energy generation purposes has encouraged the use of solar photovoltaics (PV). The technological advancements of the recent past, improvement in technologies’ performance, reduction in the prices, policy and regulatory support, and its applicability at household level has made solar energy as a preferred form of energy generation. However, despite its rapid diffusion, it is widely believed that its current application is insignificant compared to its potential. This leads us to ask why solar PV has not been adopted to the level it should have. The existing literature has highlighted a number of factors affecting solar PV adoption. This paper systematically reviews the literature to identify the factors that have been instrumental to solar PV adoption. By exploring the Scopus database, this research identifies 39 articles matching the study objectives. Findings of this research will help academics, technology companies and policymakers in understanding the factors influencing the process and proposing solutions to address these.©2020 Springer. This is a post-peer-review, pre-copyedit version of an article published in Advances in Human Factors, Business Management and Leadership. AHFE 2020. The final authenticated version is available online at: http://dx.doi.org/10.1007/978-3-030-50791-6_36fi=vertaisarvioitu|en=peerReviewed

Smoking cessation advice: the self-reported attitudes and practice of primary health care physicians in a military community, central Saudi Arabia

Mohammed AlAteeq,1 Abdulaziz M Alrashoud,2 Mohammed Khair,2 Mahmoud Salam3 1Department of Family Medicine, 2College of Medicine, King Saud bin Abdulaziz University for Health Sciences, 3King Abdullah International Medical Research Center, Ministry of National Guard Health Affairs, Riyadh, Saudi Arabia Background: Brief advice on smoking cessation from primary health care (PHC) physicians reduces smoking prevalence. However, few studies have investigated the provision of such advice by PHC physicians providing services to military communities. The aim of this study was to evaluate PHC physicians’ attitudes toward and practice of delivering smoking cessation advice to smokers in a military community in central Saudi Arabia.Methods: A self-reported survey of PHC physicians was conducted in 2015 using a previously validated tool. The age, sex, educational level, job title, experience and previous smoking cessation training of each physician was recorded. Attitude (ten statements) and practice (six statements) were evaluated on a five-point Likert scale. Scoring system was applied and percentage mean scores (PMS) were calculated. Descriptive/statistical analyses were applied to identify factors that were significantly associated with a positive attitude and favorable practice (PMS >65 each). P-values <0.05 were considered to be significant.Results: Response rate was 73/150 (48.6%), of which equal sex distribution (52%:48%) was observed, with a mean age of 35.3±9.6 years. General practitioners constituted 71.4%, followed by consultants (17.9%) and specialists (10.7%). Those with a postgraduate education formed 49.3%, while experience averaged 9.5±9.2 years. Approximately 56% had not attended a smoking cessation educational program in the previous year. Approximately 75% of physicians had a positive attitude (PMS =72.4±11.2), while 64.4% reported favorable practice (PMS =65.3±27.7). Higher education levels were significantly more associated with positive attitude than lower education levels (adj. odds ratio [OR] 95% confidence interval [CI] =17.9 [1.3-242.3]; adj. P=0.03). More experienced physicians (adj. OR [95% CI] =9.5 [1.6–54.6]) and those with positive attitude (adj. OR [95% CI] =6.1 [1.6–23.3]) were more likely to report a favorable practice, compared to the less experienced (adj. P=0.012) and physicians with a negative attitude (adj. P=0.008).Conclusion: Provision of smoking cessation advice by primary health care physicians serving a military community is significantly associated with their attitude and years of experience. Patients who are seeking smoking cessation advice should be referred to physicians with higher levels of education. Routinely scheduled training on proper delivery of smoking cessation advice may increase physicians’ confidence; improve their attitude, and subsequently, their practice. Keywords: smoking cessation advice, primary health care, attitude, practice, Saudi Arabi

An Efficient Spam Detection Technique for IoT Devices Using Machine Learning

The Internet of Things (IoT) is a group of millions of devices having sensors and actuators linked over wired or wireless channel for data transmission. IoT has grown rapidly over the past decade with more than 25 billion devices expected to be connected by 2020. The volume of data released from these devices will increase many-fold in the years to come. In addition to an increased volume, the IoT devices produces a large amount of data with a number of different modalities having varying data quality defined by its speed in terms of time and position dependency. In such an environment, machine learning (ML) algorithms can play an important role in ensuring security and authorization based on biotechnology, anomalous detection to improve the usability, and security of IoT systems. On the other hand, attackers often view learning algorithms to exploit the vulnerabilities in smart IoT-based systems. Motivated from these, in this article, we propose the security of the IoT devices by detecting spam using ML. To achieve this objective, Spam Detection in IoT using Machine Learning framework is proposed. In this framework, five ML models are evaluated using various metrics with a large collection of inputs features sets. Each model computes a spam score by considering the refined input features. This score depicts the trustworthiness of IoT device under various parameters. REFIT Smart Home data set is used for the validation of proposed technique. The results obtained proves the effectiveness of the proposed scheme in comparison to the other existing schemes

IoT-Based Medical Image Monitoring System Using HL7 in a Hospital Database

In recent years, the healthcare system, along with the technology that surrounds it, has become a sector in much need of development. It has already improved in a wide range of areas thanks to significant and continuous research into the practical implications of biomedical and telemedicine studies. To ensure the continuing technological improvement of hospitals, physicians now also must properly maintain and manage large volumes of patient data. Transferring large amounts of data such as images to IoT servers based on machine-to-machine communication is difficult and time consuming over MQTT and MLLP protocols, and since IoT brokers only handle a limited number of bytes of data, such protocols can only transfer patient information and other text data. It is more difficult to handle the monitoring of ultrasound, MRI, or CT image data via IoT. To address this problem, this study proposes a model in which the system displays images as well as patient data on an IoT dashboard. A Raspberry Pi processes HL7 messages received from medical devices like an ultrasound machine (ULSM) and extracts only the image data for transfer to an FTP server. The Raspberry Pi 3 (RSPI3) forwards the patient information along with a unique encrypted image data link from the FTP server to the IoT server. We have implemented an authentic and NS3-based simulation environment to monitor real-time ultrasound image data on the IoT server and have analyzed the system performance, which has been impressive. This method will enrich the telemedicine facilities both for patients and physicians by assisting with overall monitoring of data