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Edge Analytics and Artificial Intelligence are important features of the current smart connected living community. In a society where people, homes, cities, and workplaces are simultaneously connected through various devices, primarily through mobile devices, a considerable amount of data is exchanged, and the processing and storage of these data are laborious and difficult tasks. Edge Analytics allows the collection and analysis of such data on mobile devices, such as smartphones and tablets, without involving any cloud-centred architecture that cannot guarantee real-time responsiveness. Meanwhile, Artificial Intelligence techniques can constitute a valid instrument to process data, limiting the computation time, and optimising decisional processes and predictions in several sectors, such as healthcare. Within this field, in this article, an approach able to evaluate the voice quality condition is proposed. A fully automatic algorithm, based on Deep Learning, classifies a voice as healthy or pathological by analysing spectrogram images extracted by means of the recording of vowel /a/, in compliance with the traditional medical protocol. A light Convolutional Neural Network is embedded in a mobile health application in order to provide an instrument capable of assessing voice disorders in a fast, easy, and portable way. Thus, a straightforward mobile device becomes a screening tool useful for the early diagnosis, monitoring, and treatment of voice disorders. The proposed approach has been tested on a broad set of voice samples, not limited to the most common voice diseases but including all the pathologies present in three different databases achieving F1-scores, over the testing set, equal to 80%, 90%, and 73%. Although the proposed network consists of a reduced number of layers, the results are very competitive compared to those of other “cutting edge” approaches constructed using more complex neural networks, and compared to the classic deep neural networks, for example, VGG-16 and ResNet-50.

IoT and the Cloud are among the most disruptive changes in the way we use data today. These changes have not significantly influenced practices in condition monitoring for shipping. This is partly due to the cost of continuous data transmission. Several vessels are already equipped with a network of sensors. However, continuous monitoring is often not utilised and onshore visibility is obscured. Edge computing is a promising solution but there is a challenge sustaining the required accuracy for predictive maintenance. We investigate the use of IoT systems and Edge computing, evaluating the impact of the proposed solution on the decision making process. Data from a sensor and the NASA-IMS open repository were used to show the effectiveness of the proposed system and to evaluate it in a realistic maritime application. The results demonstrate our real-time dynamic intelligent reduction of transmitted data volume by without sacrificing specificity or sensitivity in decision making. The output of the Decision Support System fully corresponds to the monitored system's actual operating condition and the output when the raw data are used instead. The results demonstrate that the proposed more efficient approach is just as effective for the decision making process.

As in other STEM disciplines, early computing courses tend to stress individual assignments and discourage collaboration. This can lead to negative learning experiences that compel some students to give up. According to social learning theory, one way to improve students’ learning experiences is to help them form and participate actively in vibrant social learning communities. Building on social learning theory, we have designed a set of software interventions (scaffolds and prompts) that leverage automatically collected learning process data to promote increased social interactions and better learning outcomes in individual programming assignments, which are a key component of early undergraduate computing courses. In an empirical study, we found that students’ interaction with the interventions was correlated with increased social activity, improved attitudes toward peer learning, more closely coupled social networks, and higher performance on programming assignments. Our work contributes a theoretically motivated technological design for social programming interventions; an understanding of computing students’ willingness to interact with the interventions; and insights into how students’ interactions with the interventions are associated with their social behaviors, attitudes, connectedness with others in the class, and their course outcomes.

Biotechnological processes development is challenging due to the sheer variety of process parameters. For efficient upstream development parallel cultivation systems have proven to reduce costs and associated timelines successfully, while offering excellent process control. However, the degree of automation of such small scale systems is comparably low and necessary sample analysis requires manual steps. Although the subsequent analysis can be performed in a high-throughput manner, the integration of analytic devices remains challenging. Especially, when cultivation and analysis laboratories are spatially separated. Mobile robots offer a potential solution, but the implementation in research laboratories is not widely adopted. Our approach demonstrates the integration of a small scale cultivation system into a liquid handling station for an automated sample procedure. The samples are transferred via a mobile robotic lab assistant and subsequently analysed by a high-throughput analyzer. The process data is stored in a centralized database. The mobile robotic workflow guarantees a flexible solution for device integration and facilitates automation. Restrictions regarding spatial separation of devices are circumvented, enabling a modular platform throughout different laboratories. The presented cultivation platform is evaluated based on industrial relevant E. coli BW25113 high cell density fed-batch cultivation. Here its suitability for accelerating bioprocess development is proven. The necessary magnesium addition for reaching high cell densities in mineral salt medium is automated via a feedback operation loop. The feedback operation loop demonstrates the possibility for advanced control options. This study sets the foundation for a fully integrated facility with different cultivation scales sharing the same data infrastructure, where the mobile robotic lab assistant physically connects the devices.

Nowadays, colleges and universities have a large amount of information about political thought and education in addition to complex student data. Like big data, it has the characteristics of large capacity, high speed, and diversity. The ideological and political education in colleges and universities urgently needs scientific decision-making and the ability to predict possible problems ahead of time. It also perfectly matches the technical advantages of big data technology that can efficiently process data, analyze and extract information, as well as propose solutions. The traditional higher education model can no longer meet the needs of current international higher education. Under the new background, universities must explore a new model of postgraduate international education, which is practical, multi-channel, and comprehensive, on a deeper level. According to data on graduate students’ interest, psychology, and behavior, higher education teachers can purposefully innovate the methods and approaches to higher education. The integration of international graduate education with big data has been examined in this research, and a series of cultural exchanges has been carried out for foreign students at Central South University. This kind of introduction seems to have effectively boosted the attractiveness of ideological and political education, improved the research level of international graduate students, and deepened the role of campus cultural activities in educating people on a deeper level.

PDDIKTI Feeder as a business intelligence application is used as an information center in higher education, containing master data of each student and lecturer, learning process data, reporting graduate data and lecturer activities in teaching for decision making. Paradoxically, through the empirical data there are many problems in implementing business intelligence systems in private universities, related to the maturity of information technology, data quality and information culture. Addressing this gap, we present a descriptive verification analysis research on 40 private universities in Bandung city, Indonesia, using the Partial Least Square Model. We conclude there is a positive influence of information technology maturity, data quality and information culture on the quality of the business intelligence system.

The of monitoring the Internet of Things (IoT) in the cold chain allows process data, including packaging data, to be more easily accessible. Proper optimization modelling is the core driving force towards the green and low-carbon operation of cold chain logistics, laying the necessary foundation for the development of a data-driven modelling system. Since efficient packaging is necessary for loss control in the cold chain, its final efficiency during circulation is important for realizing continuous loss prevention and efficient supply. Thus, it is urgent to determine how to utilize these continuously acquired data and how to formulate a more accurate packaging efficiency control methodology in the agri-products cold chain. Through continuous monitoring, we examined the feasibility of this topic by focusing on the concept of data-driven evaluation modelling and the dynamic formation mechanism of comprehensive packaging efficiency in cold chain logistics. The packaging efficiency in the table grape cold chain was used as an example to evaluate the comprehensive efficiency evaluation index system and data-driven evaluation framework proposed in this paper. Our results indicate that the established methodology can adapt to the continuity of comprehensive packaging efficiency, also reflecting the comprehensive efficiency evaluation of the packaging for different times and distances. Through the evaluation of our results, the differences and the dynamic processes between different final packaging efficiencies at different moments are effectively displayed. Thus, the continuous improvement of a low-carbon system in cold chain logistics could be realized.

Background: Older people are among the most vulnerable patients in acute care hospitals. The hospitalisation process can result in newly acquired functional or cognitive deficits termed hospital associated decline (HAD).  Prioritising fundamental care including mobilisation, nutrition, and cognitive engagement can reduce HAD risk. Aim: The Frailty Care Bundle (FCB) intervention aims to implement and evaluate evidence-based principles on early mobilisation, enhanced nutrition and increased cognitive engagement to prevent functional decline and HAD in older patients. Methods: A hybrid implementation science study will use a pragmatic prospective cohort design with a pre-post mixed methods evaluation to test the effect of the FCB on patient, staff, and health service outcomes.  The evaluation will include a description of the implementation process, intervention adaptations, and economic costs analysis. The protocol follows the Standards for Reporting Implementation Studies (StaRI). The intervention design and implementation strategy will utilise the behaviour change theory COM-B (capability, motivation, opportunity) and the Promoting Action on Research Implementation in Health Services (i-PARIHS). A clinical facilitator will use a co-production approach with staff. All patients will receive care as normal, the intervention is delivered at ward level and focuses on nurses and health care assistants (HCA) normative clinical practices. The intervention will be delivered in three hospitals on six wards including rehabilitation, acute trauma, medical and older adult wards. Evaluation: The evaluation will recruit a volunteer sample of 180 patients aged 65 years or older (pre 90; post 90 patients). The primary outcomes are measures of functional status (modified Barthel Index (MBI)) and mobilisation measured as average daily step count using accelerometers. Process data will include ward activity mapping, staff surveys and interviews and an economic cost-impact analysis. Conclusions: This is a complex intervention that involves ward and system level changes and has the potential to improve outcomes for older patients.

Small and medium enterprises (SMEs) are depending more on their ICT framework however they do not possess the ability to direct it reasonably because of monetary impediments, limited assets, and insufficient specialized expertise. A sizeable number of SME executives expect that ICT security per remote access in their organizations is only like introducing a firewall and refreshing the antivirus program as frequently on a case by case basis. Remote access initiatives, against hacking systems and approaches, remote access controls, and numerous other related aspects are only investigated solely after security breaches. To improve remote access security in an organization comprehensively, four aspects including organizational, work process, data, and technical aspects must be figured out. With SMEs’ limited spending plans and more requirements for remote employees, it is exceptionally evident that they will remain easy prey for attackers since they cannot bear the cost of the typical secure remote access technologies and solutions. This paper explored a more ideal solution that will fit into the usual SME low remote access security financial plans but at the same time sufficiently powerful to protect them from digital and other IT attacks.

Background: Progressing technology in the world need to fast and accurate information in the hospital agencies as the basis for appropriate making decision. The inpatient daily census reporting of system Bhayangkara Hospital Bengkulu don't have utilized the Inpatient Daily census system electronically and still uses a manual system, so that the processing of report data is less than optimal. There are still a lot of inputting errors, inaccurate data, and inefficient time and energy. This study to aim design system information inpatient daily census reporting application at the Bhayangkara hospital to existing problems solving.Methods: The method used in designing and making this application is by utilizing software development methods, namely the waterfall method which includes identification, analysis, design or design, implementation and maintenance of the system.Results: The results this study is creation of an application to facilitys the processing of data into an inpatient daily census report that is needed and to overcome the problems that arise because of the report processing system manually. Design and Creation of Inpatient Daily Census Applications with Visual Basic 6.0 Programming at Bhayangkara Bengkulu Hospital have been made with the results of an analysis of existing systems and according to the method used, and the design of the forms that have been made in accordance with the manual form or home party needs sick and can simplify filling out forms and processing the data.Conclusions: At Bhayangkara Bengkulu Hospital still uses a manual inpatient daily census system, and not on time for reporting daily cencus patient data. The data structure contained in the ledger consists of patient identity, patient diagnosis, and others. There are three processes in the stage of analyzing the needs of the inpatient daily census system, namely the data input process, data processing and data output processes. ledger, patient data consisting of patient identity, doctor's name, patient diagnosis, treatment room, and treatment class. In designing the daily inpatient census system at Bhayangkara Bengkulu Hospit consists of patient data forms, incoming patients, outgoing patients, and patients moving. The implementation of the daily inpatient census system at the Bhayangkara Bengkulu Hospital  has carried out socialization and discussions about the user interface design to officers or users of the electronic daily census system. And the maintenance of the daily inpatient census system is carried out in several stages (1) corrective, by correcting design and errors in the program, (2) adaptive, by modifying the system according to user needs, (3) perfective, namely processing census data computerized.