User Configuration Research Articles

IMSIS: An instrumented microphysiological system with integrated sensors for monitoring cellular metabolic activities

Well plates are widely used in biological experiments, particularly in pharmaceutical sciences and cell biology. Its popularity stems from its versatility to support a variety of fluorescent markers for high throughput monitoring of cellular activities. However, using fluorescent markers in traditional well plates has its own challenges, namely, they can be potentially toxic to cells, and thus, may perturb their biological functions; and it is difficult to monitor multiple analytes concurrently and in real-time inside each well. This paper presents a fully instrumented microphysiological system with integrated sensors (IMSIS) with a similar well format. Each well in the microphysiological system has a set of sensors for monitoring multiple metabolic analytes in real-time. The IMSIS platform is supported by integrated bioelectronic circuits and a graphical user interface for easy user configuration and monitoring. The system has integrated microfluidics to maintain its microphysiological environment within each well. The IMSIS platform currently incorporates O2, H2O2, and pH sensors inside each well, allowing up to six wells to perform concurrent measurements in real-time. Furthermore, the architecture is scalable to achieve an even higher level of throughput. The miniaturized design ensures portability, suitable for small offices and field applications.The IMSIS platform was successfully used to monitor in real-time the mitochondrial functions of live bovine embryos in O2 consumption, H2O2 release as an indication of ROS production, and extracellular acidity changes before and after the introduction of external substrates.

Autonomous integration of TSN-unaware applications with QoS requirements in TSN networks

Modern industrial networks transport both best-effort and real-time traffic. Time-Sensitive Networking (TSN) was introduced by the IEEE TSN Task Group as an enhancement to Ethernet to provide high quality of service (QoS) for real-time traffic. In a TSN network, applications signal their QoS requirements to the network before transmitting data. The network then allocates resources to meet these requirements. However, TSN-unaware applications can neither perform this registration process nor profit from TSN’s QoS benefits.The contributions of this paper are twofold. First, we introduce a novel network architecture in which an additional device acts as a central user configuration (CUC) for TSN-unaware applications and autonomously signals their QoS requirements to the network. Second, we propose a processing method to detect real-time streams in a network and extract the necessary information for the TSN stream signaling. It leverages a Deep Recurrent Neural Network (DRNN) to detect periodic traffic, extracts an accurate traffic description, and uses traffic classification to determine the source application. As a result, our proposal allows TSN-unaware applications to benefit from TSNs QoS guarantees. Our evaluations underline the effectiveness of the proposed architecture and processing method.

Access and triage in contemporary general practice: A novel theory of digital candidacy

To access contemporary healthcare, patients must find and navigate a complex socio-technical network of human and digital actors linked in multi-modal pathways. Asynchronous, digitally-mediated triage decisions have largely replaced synchronous conversations between humans. In this paper, we draw on a large qualitative dataset from a multi-site study of remote and digital technologies in general practice to understand widening inequities of access.We theorise our data by bringing together traditional candidacy theory (in particular, concepts of self-assessment, help-seeking, adjudication and negotiation) and socio-technical and technology structuration theories (in particular, concepts of user configuration, articulation, distanciation, disembedding, and recursivity), thus producing a novel theory of digital candidacy.We propose that both human and technological actors (in different ways) embody social structures which affect how they ‘act’ in social situations. Digital technologies contain inbuilt assumptions about users' capabilities, needs, rights, and skills. Patients' ability to self-assess as sick, access digital platforms, self-advocate, and navigate multiple stages in the pathway, including adapting to and compensating for limitations in the technology, vary widely and are markedly patterned by disadvantage. Not every patient can craft an accurate digital facsimile on which the subsequent adjudication decision will be made; those who create incomplete, flawed or unpersuasive digital facsimiles may be deprioritised or misdirected. Staff who know about such patients may use articulation measures to ensure a personalised and appropriate access package, but they cannot identify or fully mitigate all such cases. The decisions and actions of human and technological agents at the time of an attempt to access care can significantly influence, disrupt, and reconstitute candidacy both immediately and recursively over time, and also recursively shape the system itself.These findings underscore the need for services to be (co-)designed with attention to the exclusionary tendencies of digital technologies and technology-supported processes and pathways.

Reinvent 4: Modern AI-driven generative molecule design.

REINVENT 4 is a modern open-source generative AI framework for the design of small molecules. The software utilizes recurrent neural networks and transformer architectures to drive molecule generation. These generators are seamlessly embedded within the general machine learning optimization algorithms, transfer learning, reinforcement learning and curriculum learning. REINVENT 4 enables and facilitates de novo design, R-group replacement, library design, linker design, scaffold hopping and molecule optimization. This contribution gives an overview of the software and describes its design. Algorithms and their applications are discussed in detail. REINVENT 4 is a command line tool which reads a user configuration in either TOML or JSON format. The aim of this release is to provide reference implementations for some of the most common algorithms in AI based molecule generation. An additional goal with the release is to create a framework for education and future innovation in AI based molecular design. The software is available from https://github.com/MolecularAI/REINVENT4 and released under the permissive Apache 2.0 license. Scientific contribution. The software provides an open-source reference implementation for generative molecular design where the software is also being used in production to support in-house drug discovery projects. The publication of the most common machine learning algorithms in one code and full documentation thereof will increase transparency of AI and foster innovation, collaboration and education.

Enabling applications for variable vehicle configurations with Software-defined Vehicle and Service-oriented Architecture

Modern vehicle applications must be able to handle variable vehicle configurations, including the vehicle sales configuration, feature-as-a-service and subscription configurations, as well as user configuration preferences. How can the foundations for modern vehicle applications – service-oriented architecture and software-defined vehicle – be utilized to enable such variable configurations? This paper is introducing the “passenger welcome” case to discuss different implementation options.

CHIP-KNNv2: AConfigurable andHigh-PerformanceK-NearestNeighbors Accelerator on HBM-based FPGAs

The k-nearest neighbors (KNN) algorithm is an essential algorithm in many applications, such as similarity search, image classification, and database query. With the rapid growth in the dataset size and the feature dimension of each data point, processing KNN becomes more compute and memory hungry. Most prior studies focus on accelerating the computation of KNN using the abundant parallel resource on FPGAs. However, they often overlook the memory access optimizations on FPGA platforms and only achieve a marginal speedup over a multi-thread CPU implementation for large datasets.In this article, we design and implement CHIP-KNN: an HLS-based, configurable, and high-performance KNN accelerator. CHIP-KNN optimizes the off-chip memory access on modern HBM-based FPGAs such as the AMD/Xilinx Alveo U280 FPGA board. CHIP-KNN is configurable for all essential parameters used in the algorithm, including the size of the search dataset, the feature dimension and data type representation of each data point, the distance metric, and the number of nearest neighbors - K. In terms of design architecture, we explore and discuss the tradeoffs between two design versions: CHIP-KNNv1 (Ping-Pong buffer based) and CHIP-KNNv2 (streaming-based). Moreover, we investigate the routing congestion issue in our accelerator design, implement hierarchical structures to shorten critical paths, and integrate an open-source floorplanning optimization tool called TAPA/AutoBridge to eliminate the place-and-route issues. To explore the design space and balance the computation and memory access performance, we also build an analytical performance model. Given a user configuration of the KNN parameters, our tool can automatically generate TAPA HLS C code for the optimal accelerator design and the corresponding host code, on the HBM-based FPGA platform.Our experimental results on the Alveo U280 show that, compared to a 48-thread CPU implementation, CHIP-KNNv2 achieves a geomean performance speedup of 15×, with a maximum speedup of 45×. Additionally, we show that CHIP-KNNv2 achieves up to 2.1× performance speedup over CHIP-KNNv1 while increasing configurability. Compared with the state-of-the-art Facebook AI Similarity Search (FAISS) [23] GPU implementation running on a Nvidia Tesla V100 GPU, CHIP-KNNv2 achieves an average latency reduction of 30.6× while requiring 34.3% of GPU power consumption.

Attacks and vulnerabilities of Wi-Fi Enterprise networks: User security awareness assessment through credential stealing attack experiments

Enterprise Wi-Fi networks are essential for businesses and public administrations as they provide a perfectly scalable and secure system. In the university environment, they are often deployed to offer services to students. One of the most famous university Wi-Fi Enterprise networks is Eduroam, which stands for education roaming; it is a worldwide Wi-Fi access and roaming service widely adopted by the international research and education community. It is based on 802.1x mechanisms that use TLS tunnels for achieving mutual authentication goals, and, as such, it requires careful configuration of mobile devices and responsible users’ behaviors to avoid trivial attacks carried out with rogue Access Points (APs). Differently than employees in a corporate network whose devices are properly configured by ICT teams, the user base of Eduroam consists of (likely) millions of students and professors around the world, with a myriad of different and uncontrolled devices. To assess the security of 802.1x in general, and more specifically that of Eduroam, we ran attacks against two communities of students of increasing size in order to test how users (and their devices) react when rogue 802.1x APs appear in the list of available networks. We then focused our attention on devices, and investigated their detailed dependence on different WPA-Enterprise configurations and certificate settings. The aftermath is that, even with a completely passive attack (users are keeping devices in their pockets), it is possible to steal credentials from more than one-third of the students. While most of the 802.1x vulnerabilities employed in this work should be considered somewhat known (being disclosed in former technical papers), our work appears to raise a threefold concern: (i) most pragmatic 802.1x configurations appear to be grossly insecure; (ii) no Apple’s iPhone felt in our attack unless explicitly forced by the user, owing to its reduced possibility for a user to misconfigure the terminal; and (iii) the awareness of Wi-Fi authentication threats even in relatively skilled end users is close to zero.

ARGem: a new metagenomics pipeline for antibiotic resistance genes: metadata, analysis, and visualization.

Antibiotic resistance is of crucial interest to both human and animal medicine. It has been recognized that increased environmental monitoring of antibiotic resistance is needed. Metagenomic DNA sequencing is becoming an attractive method to profile antibiotic resistance genes (ARGs), including a special focus on pathogens. A number of computational pipelines are available and under development to support environmental ARG monitoring; the pipeline we present here is promising for general adoption for the purpose of harmonized global monitoring. Specifically, ARGem is a user-friendly pipeline that provides full-service analysis, from the initial DNA short reads to the final visualization of results. The capture of extensive metadata is also facilitated to support comparability across projects and broader monitoring goals. The ARGem pipeline offers efficient analysis of a modest number of samples along with affordable computational components, though the throughput could be increased through cloud resources, based on the user's configuration. The pipeline components were carefully assessed and selected to satisfy tradeoffs, balancing efficiency and flexibility. It was essential to provide a step to perform short read assembly in a reasonable time frame to ensure accurate annotation of identified ARGs. Comprehensive ARG and mobile genetic element databases are included in ARGem for annotation support. ARGem further includes an expandable set of analysis tools that include statistical and network analysis and supports various useful visualization techniques, including Cytoscape visualization of co-occurrence and correlation networks. The performance and flexibility of the ARGem pipeline is demonstrated with analysis of aquatic metagenomes. The pipeline is freely available at https://github.com/xlxlxlx/ARGem.

Analysis of Adolescents’ Head to Shoulder Region during Tablet Use from Sagittal and Frontal RGB Images

As schools go digital, the use of tablet computers is increasing. Concerns are raised that the extensive use of tablets and the associated bent-over posture may negatively affect the individual’s health. In order to analyse the possible effects of prolonged tablet use on physical health, a detailed analysis of the posture during tablet use is needed so that appropriate preventive measures can be taken to prevent degenerative changes. Therefore, the aim of this study was to measure and report the posture of 56 students while working with a tablet computer and compare it with an upright posture. Sagittal and frontal images were used for measurements of the subjects’ postures while seated, using the tablet, and in a neutral sitting position looking straight ahead. The body position during tablet use was recorded in two different user configurations: tablet flat on the table and tablet in individual freely chosen user configuration. After appropriate annotation of the data, the following parameters were evaluated in different planes. The craniovertebral angle (CVA), head tilt angle (HTA), and forward shoulder angle (FSA) are measurements that describe the extent to which the head bends forward and downward and how the shoulders are aligned in the sagittal plane. On the other hand, the head shoulder angle (HSA), lateral head tilt angle (LHTA), and trunk flexion angle (TFA) are angles measured in the frontal plane, which indicate the degree of head tilt and trunk bending to the right or left side. The measurement results clearly showed that the use of a tablet had a pronounced effect on the positions and rotations of the participants’ head, neck, and shoulders. This was evident through strong deviations observed in the angles measured between the sitting straight posture and the postures while using the tablet. For example, depending on the body posture class, the mean CVA values were 45.76° for straight sitting posture, 28.25° for holding the tablet individually posture, and 26.04° for the posture adopted while using a tablet placed flat on the table.

Spatial Modulation Aided Physical Layer Security for NOMA-VLC Systems

We consider the physical layer security (PLS) problem in multi-user non-orthogonal multiple access (NOMA) enabled multiple-input multiple-output (MIMO) visible light communication systems intercepted by a passive eavesdropper (Eve). We propose a novel transmit precoding scheme based on receive spatial modulation (RSM) to degrade the signal-to-interference-noise ratio (SINR) of Eve by exploiting only the slow-fading characteristics of the visible light channel of the legitimate users (Bobs). The proposed PLS precoder is reinforced with secret parameter exchange with Bobs and a CSI acquisition model is proposed to reduce the PLS algorithm's computational load substantially at the transmitter. The closed-form expressions for the achievable secrecy rates and their upper and lower bounds are derived. Via Monte Carlo simulations, we confirm that Bobs can successfully decode their information in various user configurations while Eve's received SINR is significantly worsened by the jamming signal induced by the proposed precoder with secret key exchange. It is also shown that Eve's bit error rate (BER) is increased to the 0.5-level for almost any position in the considered indoor environment. Finally, we corroborate the derived secrecy expressions by computer simulations and show that the proposed scheme provides PLS for Bobs.

Securing Cloud Application using SHA-256 Hash Algorithm and Antiforgery Token

The cloud supplier has no proposals for cloud data and information that is put away anyplace in the cloud and served around the world. Encryption technology generally serves as the foundation for privacy protection strategies. There are numerous ways of safeguarding security by keeping information from being moved to the cloud. A cloud-based three-tier storage structure is what we propose. The proposed structure is secure and able to make full use of cloud storage. The Hash-Solomon code, which is intended to divide the data into various parts, is utilized in this algorithm. We have lost data-related information in the event that just one piece of data is missing. In this design, we use calculations in light of the idea of containers and information assurance, and afterward can show the security and adequacy of our plan. Additionally, this algorithm is capable of calculating the cloud, cloud, and local computer distribution ratios, respectively, in terms of computational intelligence. SaaS (software as a service): A customer provides a hosted application that can be accessed by a variety of clients over a network. utilized by users With the possible exception of a few user configuration settings, the underlying cloud infrastructure is not managed or controlled by the customer. Examples of SaaS include Microsoft Office 365 and Google Apps

Configuring augmented reality users: analysing YouTube commercials to understand industry expectations

ABSTRACT Commercial videos are often used to familiarise potential buyers and users with new technologies and their possibilities. In addition, presenting visions of future applications is a way to configure users and define social worlds of technology use. We analyse 30 YouTube videos featuring augmented reality (AR) devices in industrial manufacturing and construction, to explore how these commercial videos situate AR technology and future users by showcasing techno-euphoric promises and imagined use cases. With a video analysis based on Grounded Theory and Situational Analysis, we untangle the promises of AR for manufacturing and construction work; second, we present two prevailing configurations of AR users: ‘experts in situ’ and ‘smart dummies’; and third, we discuss how YouTube videos put forward developmental expectations. In addition, we identify discrepancies between expectations and foreseeable requirements in construction work. Finally, our research could contribute to a more holistic understanding of workplaces and socially robust AR applications.

Особливості управління правами користувачів у корпоративних IT-системах

Today, there is no workplace at any enterprise where employees don’t use information technol-ogies. Automation provided by information technologies has already covered all the aspects of company’s activity: document flow, accounting, warehouse accounting, financial accounting, analytical accounting, and enterprise management. To work efficiently, employees need access to systems the use of which is required by their positions. The management and control of user accounts in corporate IT systems are serious tasks for the IT department or information security service. Since the systems are weakly integrated with each other, each of them requires a sepa-rate configuration of user accounts and corresponding access rights. The main directions in the management of access to corporate IT systems are the identification of accounts, the manage-ment of user accounts, and compliance with the requirements of authorized access rights. The modern concept of work with corporate systems consists in the formation of a service model based on the used IT systems. From the point of view of the service model, the company pro-vides an employee with a certain service based on the existing corporate systems. The organiza-tion of the effective management of user rights in corporate IT systems requires automation. A step forward in access management automation is the creation of self-service portals, where employees can familiarize themselves with the list of corporate services available to them and request access to them in the automated mode. The automation of the process of giving and changing user accounts in the corporate IT systems allows you to reduce the time it takes to cre-ate or change access rights, create prerequisites for controlling access rights to systems, and in-crease the efficiency of the IT department as a whole.

The Design of a Python Library for the Automatic Definition and Simulation of Transient Ionization Fronts

In recent years, the interest in nonthermal plasma dynamics has grown significantly, within both industry and research. This has been driven by the development of several novel cold plasma technologies across a wide range of different fields, for example, for plasma medicine, chemical processing, pollution control, and surface treatment. The optimization of these technologies relies heavily upon the understanding of gas discharge plasmas: their generation, electrical characteristics, and interaction with their surroundings. Moreover, the manifestation of nonthermal plasmas in the form of streamers is of high relevance and critical importance to high voltage insulation technology, and has further significance to geophysical research concerning atmospheric discharges. The present work describes the development of the StrAFE (Streamers on Adaptive Finite Elements) package, a dedicated Python library built atop the popular open-source FEniCS finite element software, designed with the objective to simplify and to automate the solution of ionization front models. The library features support for mesh adaptivity, distributed memory parallelism, and an intuitive programming interface, while providing an exceptionally high level of user configurability. This article presents the software implementation, describes its features, and presents several code verification studies performed within simple and complex domains. It is concluded that the numerical results gained from this open-source framework are comparable to other well-established software in terms of accuracy. Therefore, it further demonstrates the great potential for open-source software to make significant contributions to technologies involving nonthermal plasmas, ionization fronts, and gas discharges.

Structures Surrounding the ‘User’ in User Engagement: Gender-based Violence Design Engagements

User engagement is a dynamic social process influenced by who is involved and how. Here we argue that designers must account for the structural conditions of users’ lives, as they may have safety, accountability, and political implications. We review current scholarship in the area of user configuration and engagement from a ‘structural’ viewpoint of gender-based violence (GBV), to better understand such considerations. We propose three dimensions that might support designers in deepening their engagement in this area, namely: construction of the user, engagement within the context, and the designers’ position. We combine these dimensions as a framework to review and compare examples of designed outcomes for GBV prevention. This article suggests thoughts and questions to be considered by designers for thinking more structurally about GBV design, and for other contexts involving people experiencing vulnerability.

Leveraging Structured Trusted-Peer Assessments to Combat Misinformation

Platform operators have devoted significant effort to combating misinformation on behalf of their users. Users are also stakeholders in this battle, but their efforts to combat misinformation go unsupported by the platforms. In this work, we consider three new user affordances that give social media users greater power in their fight against misinformation: (1) the ability to provide structured accuracy assessments of posts, (2) user-specified indication of trust in other users, and (3) and user configuration of social feed filters according to assessed accuracy. To understand the potential of these designs, we conducted a need-finding survey of 192 people who share and discuss news on social media, finding that many already act to limit or combat misinformation, albeit by repurposing existing platform affordances that lack customized structure for information assessment. We then conducted a field study of a prototype social media platform that implements these user affordances as structured inputs to directly impact how and whether posts are shown. The study involved 14 participants who used the platform for a week to share news while collectively assessing their accuracy. We report on users' perception and use of these affordances. We also provide design implications for platforms and researchers based on our empirical observations.

WEBSITE NETWORK AUTOMATION DESIGN AND IMPLEMENTATION IN RT RW NET SENDEN DUSUN MAGELANG WITH DJANGO FRAMEWORK

RT RW NET is part of the Internet facilities owned by the hamlet of Senden Magelang, whose purpose is to provide cheap Internet facilities.However, behind the existing facilities several problems emerged, based on a statement from the hamlet of sending that the problem that arose was the configuration process for adding new users, which took a long time due to manual configuration in each RT (Rukun Tetangga) and RW (Rukun Warga) alley. Therefore, in this study, a website-based network automation application was created using the Django framework and developed using the Waterfall method, thus providing easy access and fast configuration when configuring new users. After designing the network automation website, the website will be operated by the network administrator, who hopes to simplify and shorten the time for new user configurations.

The Configuration of Older Users as Drivers of Innovation in the Design of Digital Technologies

This paper develops hypotheses on the discovery of older people as "users" in the publicly funded development of digital technologies and underlying innovation policy motives. We then describe the effects of this innovation policy on the development of products and older people as their users in the context of Ambient Assisted Living (AAL). To this end, we reconstruct the involvement of users in two AAL funding programs, one at the European level and one at the national level (Germany). Based on this, we discuss the resulting consequences by describing how older people are configured as users in technology development with a focus on the concept of user-centered design (UCD) and what this configuration means for the developed technologies as well as for the older users. We describe how the participation of older people in technology development projects is a complex task that is not without controversy in social science research on user participation. We conclude by arguing for alternative technology development strategies and funding practices.

Interactive Similarity-Based Search of Clinical Trials.

The rapid growth of clinical trials launched in recent years poses significant challenges for accurate and efficient trial search. Keyword-based clinical trial search engines require users to construct effective queries, which can be a difficult task given complex information needs. In this study, we present an interactive clinical trial search interface that retrieves trials similar to a target clinical trial. It enables user configuration of 13 clinical trial features and 4 metrics (Jaccard similarity, semantic-based similarity, temporal overlap and geographical distance) to measure pairwise trial similarities. Among 1,007 coronavirus disease 2019 (COVID-19) trials conducted in the United States, 91.9% were found to have similar trials with the similarity threshold being 0.85 and 43.8% were highly similar with the threshold 0.95. A simulation study using 3 groups of similar trials curated by COVID-19 clinical trial reviews demonstrates the precision and recall of the search interface.

VNGuarder: An Internal Threat Detection Approach for Virtual Network in Cloud Computing Environment

Edge-assisted Internet of things applications often need to use cloud virtual network services to transmit data. However, the internal threats such as illegal management and configuration to cloud platform intentionally or unintentionally will lead to virtual network security problems such as malicious changes of user network and hijacked data flow. It will eventually affect edge-assisted Internet of things applications. We propose a virtual network internal threat detection method called VNGuarder in a cloud computing environment, which can effectively monitor whether the virtual network configuration of legitimate users under the IaaS cloud platform has been maliciously changed or destroyed by insiders. First, based on the life cycle of cloud virtual network services, we summarized two types of internal attacks involving illegal use of virtualization management tools and illegal invocation of virtual network-related processes. Second, based on normal behavior of tenants, a hierarchical trusted call correlation scheme is proposed to provide a basis for discovering that insiders illegally call virtualized management tools and virtual network-related processes on the controller node of the cloud platform or the network node and compute node. Third, a trace-enable mechanism combining real-time monitoring and log analysis is introduced. By collecting and recording the complete call process of virtual network management and configuration in the cloud platform, and comparing it with the result of the hierarchical trusted call correlation, abnormal operations can be reported to the tenants in time. Comprehensive simulation experiments on the Openstack platform show that VNGuarder can effectively detect illegal management and configuration of virtual networks by insiders without significantly affecting the creation time of tenant networks and the utilization of CPU and memory.