Real-life Usage Research Articles

Detecting rumor outbreaks in online social networks

Social media platforms are broadly used to exchange information by milliards of people worldwide. Each day people share a lot of their updates and opinions on various types of topics. Moreover, politicians also use it to share their postulates and programs, shops to advertise their products, etc. Social media are so popular nowadays because of critical factors, including quick and accessible Internet communication, always available. These conditions make it easy to spread information from one user to another in close neighborhoods and around the whole social network located on the given platform. Unfortunately, it has recently been increasingly used for malicious purposes, e.g., rumor propagation. In most cases, the process starts from multiple nodes (users). There are numerous papers about detecting the real source with only one initiator. There is a lack of solutions dedicated to problems with multiple sources. Most solutions that meet those criteria need an accurate number of origins to detect them correctly, which is impossible to obtain in real-life usage. This paper analyzes the methods to detect rumor outbreaks in online social networks that can be used as an initial guess for the number of real propagation initiators.

Speech Models Training Technologies Comparison Using Word Error Rate

The main purpose of this work is to analyze and compare several technologies used for training speech models, including traditional approaches as Hidden Markov Models (HMMs) and more recent methods as Deep Neural Networks (DNNs). The technologies have been explained and compared using word error rate metric based on the input of 1000 words by a user with 15 decibel background noise. Word error rate metric has been ex- plained and calculated. Potential replacements for com- pared technologies have been provided, including: Atten- tion-based, Generative, Sparse and Quantum-inspired models. Pros and cons of those techniques as a potential replacement have been analyzed and listed. Data analyzing tools and methods have been explained and most common datasets used for HMM and DNN technologies have been described. Real life usage examples of both methods have been provided and systems based on them have been ana- lyzed.

Safety of Real-life Usage of Advanced Hybrid Closed-Loop System MiniMed 780G in Children With Type 1 Diabetes Younger Than 7 Years Old.

Safety of Real-life Usage of Advanced Hybrid Closed-Loop System MiniMed 780G in Children With Type 1 Diabetes Younger Than 7 Years Old.

Real-life experience with IV fosfomycin in Canada: Results from the Canadian LEadership on Antimicrobial Real-life usage (CLEAR) registry

Data on the use of IV fosfomycin in Canada are limited. We report the use of IV fosfomycin in Canadian patients using data captured by the CLEAR registry. The CLEAR registry uses the web-based data management program, REDCapTM (online survey https://rcsurvey.radyfhs.umanitoba.ca/surveys/?s=F7JXNDFXEF) to facilitate clinicians entering details associated with their clinical experiences using IV fosfomycin. Data were available for 59 patients treated with IV fosfomycin. The most common infections treated were: bacteremia or sepsis (25.4% of patients), complicated UTI (20.3%), ventilator-associated bacterial pneumonia (18.6%), and hospital-acquired pneumonia (13.6%). IV fosfomycin was used to treat Gram-negative (88.1%) or Gram-positive (10.2%) infections. The most common pathogens treated were carbapenem-resistant Enterobacterales (CRE) (44.1%), MDR Pseudomonas aeruginosa (18.6%), vancomycin-resistant Enterococcus faecium (VRE) (5.1%), and MRSA (3.4%). IV fosfomycin was primarily used due to resistance to initially prescribed therapies (69.5%) and frequently in combination with other agents (86.4%). Microbiological success (eradication/presumed eradication) occurred in 77.4% and clinical success (clinical cure/improvement) occurred in 62.5% of patients; overall, 15.3% of patients died due to their infection. Adverse effects were not documented in 73.1% of patients and no patient discontinued therapy due to an adverse effect. In Canada, IV fosfomycin is used primarily as directed therapy to treat a variety of severe infections caused by Gram-negative and Gram-positive bacteria. It is primarily used in patients infected with bacteria resistant to other agents and as part of combination therapy. Its use is associated with relatively high microbiological and clinical cure rates, and an excellent safety profile.

Performance Mapping of a Firm under Green Supply Chain Architectures-Integrated Operations

Objective: To measure the GSCM-Overall Fuzzy Performance Index (GSCMOFPI) of industry under integrated operations based GSCM module. Method: The author aids the Green Entrepreneurs (GEs) with Overall Fuzzy Performance Index (OFPI) approach to estimation the GSCM-OFPI of industry in the terms of Generalized Trapezoidal Fuzzy Set (GTFs), Crisp Value (CV) and % under proposed module. Finding: A hypothetical case research of gear manufacturing industry is exhibited to reveal the real life usage of presented research work. The GEs proposed the ideal limit of GSCM-OFPI such as 1 or 100% for benchmarking perspective. The findings are synchronized only with computation of GSCM-OFPI i.e., 0.80 in the terms of CV and 80 in %. GE is advised to accelerate GSCM-OFPI=0.20 to maintain future GSCM-OFPI. Work model is useful for finding GSCM-OFPI and work is limited only for mapping GSCM-OFPI of an individual firm. Novelty: A novel approach has been proposed to evaluate the GSCM-OFPI of a case study firm by overcoming the drawbacks of previous presented research forum, which added the unique features in research work. Keywords: Module; Linguistic Information; Performance Measurement (PM); Overall Fuzzy Performance Index (OFPI); Green Supply Chain (GSC)

Labeling Out-of-View Objects in Immersive Analytics to Support Situated Visual Searching.

Augmented Reality (AR) embeds digital information into objects of the physical world. Data can be shown in-situ, thereby enabling real-time visual comparisons and object search in real-life user tasks, such as comparing products and looking up scores in a sports game. While there have been studies on designing AR interfaces for situated information retrieval, there has only been limited research on AR object labeling for visual search tasks in the spatial environment. In this article, we identify and categorize different design aspects in AR label design and report on a formal user study on labels for out-of-view objects to support visual search tasks in AR. We design three visualization techniques for out-of-view object labeling in AR, which respectively encode the relative physical position (height-encoded), the rotational direction (angle-encoded), and the label values (value-encoded) of the objects. We further implement two traditional in-view object labeling techniques, where labels are placed either next to the respective objects (situated) or at the edge of the AR FoV (boundary). We evaluate these five different label conditions in three visual search tasks for static objects. Our study shows that out-of-view object labels are beneficial when searching for objects outside the FoV, spatial orientation, and when comparing multiple spatially sparse objects. Angle-encoded labels with directional cues of the surrounding objects have the overall best performance with the highest user satisfaction. We discuss the implications of our findings for future immersive AR interface design.

Aspects Related to the Design and Manufacturing of an Original and Innovative Marker Support System for Use in Clinical Optometry

The compliant mechanism studied in this paper is used in the structure of an assembly necessary for the temporary mounting of visual markers on glasses frames. Proper correction of vision defects in patients is a field of study in healthcare that has grown in complexity, along with all aspects of technology, over the past decades. As such, along with better lenses and frames, including custom solutions, the devices used to determine the patient’s specific parameters need to be more complex and precise. However, this is only part of the problem: while many devices exist that take measurements such as interpupillary distance with great precision, these come at a very high cost and do not take into account aspects related to real-life usage of the lenses, such as the patient’s position, angle, etc. Given the considerations above, this paper approaches the design, simulation, realization and testing of a working model of a frame used to support markers used in the optometry process. The design proposed in this paper assumes that the system used can be used while the glasses are mounted on the patient’s face, without influencing in any way their position in front of the patient’s eyes. Furthermore, the system must allow assembly and disassembly with minimal effort, to allow the patient to perform some movements without changing the position of the frame, as well as the easy access to the markers mounted on the spectacle frame. The main scope of the paper is to design and choose the correct constructive solution of a compliant mechanism for this important clinical optometric application in terms of geometric parameters, material and technology used to obtain appropriate performances. The authors highlight how the parameters and manufacturing technology for the device were chosen, and a finite element analysis is used to simulate the mechanical behaviour of the mechanism and to choose the optimal variant in terms of the desired displacement between three proposed materials for the given application. After justifying the choice of the constructive solution, several physical models of optometric support markers were realised using Fused Deposition Modeling (FDM), and Polyethylene terephthalate glycol (PETG) or polylactic acid as materials. Furthermore, an electro-pneumatic experimental test stand was developed to simulate and test the functionality of the device and to validate the proposed model.

A strategy for predicting waste production and planning recycling paths in e-logistics based on improved EMD-LSTM.

With the rapid development of e-commerce, express delivery has been chosen and accepted by consumers, and a large number of express packages have resulted in serious waste of resources and environmental pollution. Because of the irregularity of online goods purchases by users in real life, logistics parks are unable to accurately judge the recycling needs of various regions. In order to solve this problem, we propose an improved empirical mode decomposition (IEMD) algorithm combined with a long-short-term memory (LSTM) network to deal with the addresses and categories in logistics data, analyze the distribution of recyclable logistics waste in the logistics park service area and in the express recycling station within the logistics park, judge the value of recyclable logistics waste, optimize the best path for recycling vehicles and improve the success rate of logistics waste recycling. In order to better research and verify the IEMD-LSTM prediction model, we model and simulate the algorithm behavior of the express waste packaging recycling prediction model system, and compare it with other classification methods through specific logistics data experiments. The prediction accuracy, stability and advantages of the four algorithms are analyzed and compared, and the application reliability of the algorithm proposed in this paper to the logistics waste recycling process is verified. The application in the actual express logistics packaging recycling case shows the feasibility and effectiveness of the waste recycling scheme proposed in this paper.

Reliability of Self-Screening for Intrinsic Capacity Impairments Using the ICOPE Monitor App.

To verify the inter-rater agreement of the Integrated Care for Older People (ICOPE) STEP 1 screening tool using the ICOPE Monitor app, comparing self-assessment to a screening performed by a health professional. We compared the results of the ICOPE Step 1 obtained by self-screening with those obtained by a professional screening using Gwet's agreement coefficient in two studies. Study 1 tested inter-rater reliability in participants to the INSPIRE-T cohort who agreed to undergo the self-and the professional screening on the same day. Study 2 used data from the INSPIRE-ICOPE care cohort. We included real-life users of the French health system whose first ICOPE Step 1 was a self-assessment followed by a professional Step 1within 130 days (mean=76 days, SD=60). Study 1 included 79 participants (45 aged less than 60, 34 aged 60 and over, 60% female, mean (SD) age of 54.5 (18.5) years). Of the 207 participants in Study 2, 49 were less than 60, and 158 were 60 and over (54% female, mean (SD) age 67 (16.1) years). Agreement coefficients in Study 1 ranged from 0.49 (CI95% 0.24; 0.66) in the cognition domain - moderate agreement) to 0.99 (CI95% 0.96;1.00) in the nutrition domain - very good agreement); and in Study 2 from 0.36 (CI95% 0.23;0.49) in the cognition domain to 0.97 (95% 0.95;1.00) in the nutrition domain. The agreement coefficients for the cognition and hearing domains were higher for the participants aged <60 than those aged 60 and over. The time orientation items (cognition) showed high reliability. Our study supports using ICOPE Step 1 as a self-assessment screening tool. High reliability was found for intrinsic capacity's nutrition, psychological, and locomotion domains, regardless of age. We discuss aspects of the self-assessment of cognition, vision, and hearing domains when using the ICOPE monitor app in older adults.

BLEselect

Spontaneous selection of IoT devices from the head-mounted device is key for user-centered pervasive interaction. BLEselect enables users to select an unmodified Bluetooth 5.1 compatible IoT device by nodding at, pointing at, or drawing a circle in the air around it. We designed a compact antenna array that fits on a pair of smart glasses to estimate the Angle of Arrival (AoA) of IoT and wrist-worn devices' advertising signals. We then developed a sensing pipeline that supports all three selection gestures with lightweight machine learning models, which are trained in real-time for both hand gestures. Extensive characterizations and evaluations show that our system is accurate, natural, low-power, and privacy-preserving. Despite the small effective size of the antenna array, our system achieves a higher than 90% selection accuracy within a 3 meters distance in front of the user. In a user study that mimics real-life usage cases, the overall selection accuracy is 96.7% for a diverse set of 22 participants in terms of age, technology savviness, and body structures.

Self-Pumping Janus Hydrogel with Aligned Channels for Accelerating Diabetic Wound Healing.

Excessive exudate secreted from diabetic wounds often results in skin overhydration, severe infections, and secondary damage upon dressing changes. However, conventional wound dressings are difficult to synchronously realize the non-maceration of wound sites and rapid exudate transport due to their random porous structure. Herein, a self-pumping Janus hydrogel with aligned channels (JHA) composed of hydrophilic poly (ethylene glycol) diacrylate (PEGDA) hydrogel layer and hydrophobic polyurethane (PU)/graphene oxide (GO)/polytetrafluoroethylene (PTFE) layer is designed to rapidly export exudate and accelerate diabetic wound healing. In the design, the ice-templating process endows the hydrophilic hydrogel layer with superior liquid transport ability and mechanical strength due to the formation of aligned channel structure. The hydrophobic layer with controlled thickness functions as an effective barrier to prevent exudate from wetting the skin surface. Experiments in diabetic rat model show that JHA can significantly promote re-epithelialization and collagen deposition, shorten the inflammation phase, and accelerate wound healing. This unique JHA dressing may have great potential for real-life usage in clinical patients.

Improving User Environment Detection Using Context-Aware Multi-Task Deep Learning in Mobile Networks

Cognition of user behavior can make future mobile networks more intelligent and flexible. Knowledge about users’ habits can be used to personalize services and intelligently manage network resources. However, inferring this key information with a low-cost signaling implementation, and avoiding constant user interaction, is crucial for Mobile Network Operators (MNOs). With this motivation, this paper investigates the detection of the real-life mobile user environment using context-aware detection via multi-task learning (MTL). We propose models that are able to automatically detect up to eight distinct real-life user environments. We also improve the detection accuracy with the assistance of the mobility state profiling task. We associate both environment and mobility tasks because they correspond to the main attributes of user behavior and, additionally, both of them are correlated. Using MTL, the task of detecting environment corresponds to simultaneously answering the questions: “how and where mobile user consumes mobile services?”. We build models using real-life radio data which is already available in network. This data has been massively gathered from multiple diversified situations of mobile users. Simulation results support our claim to detect several environment classes in network infrastructure with improved UED accuracy.

(Invited) Plasma Technology in Surface Engineering: From Super-Hydrophilic to Super-Hydrophobic Materials

Materials surface wettability is a fundamental property of a solid. Wettability plays a paramount role in the everyday applications of solid materials in many fields of science and technology. Numerous examples include advanced membranes (from water purification to biopharmaceuticals), energy storage devices, windows, raincoats, roofs, disposable diapers, microfluidics, bandages, tissue scaffolds, and bio-implants. With the continuous development of modern society, the demand for advanced functional materials with the desirable surface wettability is increasing faster than ever before. This is why precise control over surface wettability is expected to provide materials with superior properties for unprecedented applications in diverse fields.Over the past decade, conventional wet chemistry approaches have been among the most frequently used methods for surface wettability control. However, they are often energy-inefficient, pollute the environment, and rely on harsh synthesis conditions. Recently, low-temperature plasma processing has attracted major attention in surface wettability control. The reason for this particular interest is because plasma processing is highly-selective, environmentally friendly, and low-cost. Plasma processing can uniquely modify both the surface chemistry and surface topography for a wide range of materials. Moreover, it can be operated at very mild conditions such as room temperature, atmospheric pressure, and open-air environments.Plasma can be used as a controlled reactive physicochemical environment for surface activation, coating deposition, and nanostructuring of diverse materials. The unique plasma-specific conditions and effects allow precise control over microscopic surface chemical composition and surface nanostructures by adjusting the macroscopical energy input. Accordingly, effective control over surface wettability can be achieved for a broad range of hard and soft materials. An environmentally friendly, large scale and low-cost wetting control method that does not result in bulk damage, would result in improvement of industrial applications. A possible solution to this wetting control problem is atmospheric-pressure plasma (APP), especially the plasma generated in open-air due to the benefits of solvent-free treatment, requiring no vacuum systems and suitable for in-line processes. In the current work, we will give a comprehensive overview of different atmospheric pressure plasma processes capable to change the surface properties of the polymers with little or no change of the bulk. Two main approaches: (i) plasma activation introducing oxygen-containing groups into the material surface; (ii) plasma polymerization directed to the change of the surface composition will be highlighted and background will be explained.Recently our team developed a new approach based on the use of a combination of plasma activation and plasma polymerization, two different plasma techniques in a single process to achieve different surface wetting properties from hydrophilic to hydrophobic, with the high long-term stability of the coatings in water. Such a type of research approach realized in one plasma source was not yet applied for wettability control and has very promising application potential in the industrial processing of polymers. For surface engineering, and easy to scale-up the radio frequency (RF) plasma system was adopted to perform both plasma activation and plasma polymerization on PET substrate in the atmospheric pressure in the open air. Different characterization methods including WCA measurements, Fourier-transform infrared spectroscopy (FT-IR), XPS, and atomic force microscopy (AFM) were applied to get an insight into surface chemistry and morphology and the effect of the combination of the plasma activation with plasma polymerization.The developed approach has shown the capability of stable coatings deposition with the use of acrylic acid, HMDSO or fluorine-containing precursors PFDA. We demonstrate a single-step, fast, green, cheap, and universal plasma-based approach with potential for large-scale production of oil/water separation membranes, namely aerosol-assisted plasma deposition (AAPD). A hydrophobic polyester membrane is exposed to an in-line atmospheric pressure plasma coupled with an aerosol of a 2-hydroxyethyl methacrylate (HEMA) monomer. A plasma polymerized HEMA thin film is thus successfully coated on the membrane, resulting in an superhydrophilic/underwater superoleophobic surface. With created coating, the water pre-wetted plasma-functionalized polyester membrane shows an ultrahigh separation efficiency above 97.8% towards various oil/water mixtures and a superb water flux above 35.6 L m-2 s-1. Importantly, it also exhibits excellent performance in anti-oil-fouling, recyclability, and durability, indicating its high potential in real-life usage. To further examine the universality of the proposed approach, another hydrophilic monomer (acrylic acid) is also used to functionalize the polyester membranes. The obtained functionalized membranes can also efficiently separate diversified oil/water mixtures. Therefore, this study demonstrates the capability of plasma-based surface engineering methods to manipulate surface properties of materials in a very wide range from superhydrophobic to hydrophilic and even super-hydrophilic which opens new areas of applications.

Study on the Recommended Placement and Air Distribution of Split Floor-Standing Room Air Conditioners

In recent years, split floor-standing room air conditioners have been widely used in civil and office buildings because of their high cooling capacity and easy installation, and the air draft sensation has attracted more and more attention. In this study, a target air supply evaluation index for regional thermal comfort evaluation in the work area, the air velocity target value, is proposed. A computational fluid dynamics model for common office is established, and a total of 204 working conditions are numerically simulated for each combination of different positions, different rotation angles, and different air supply velocities (1 m/s, 2 m/s and 3 m/s) of air conditioners in the room. The influence of the rotation angle of the air conditioner on the indoor air distribution was studied, and the distribution of the indoor velocity flow field at different positions was analyzed. The air-conditioning rotation angle that makes the velocity target value of the five preset planes in the room smaller under different conditions is summarized as the recommended rotation angle. The numerical simulation results were verified by experimental means and found to be consistent with the measured results. This study can provide theoretical guidance and reference for the placement of indoor air conditioning units for users in real life.

Accurate classification of frost thickness using visual information in a domestic refrigerator

Due to the intensive use of the domestic refrigerator based on vapor compression and the particular design of the no-frost type, it is essential to propose economic and light strategies to optimize the refrigerator’s energy consumption. When a large amount of frost accumulates on the evaporator, heat exchange decreases, affecting the cooling capacity. The amount of frost accumulation on the evaporator surface plays a critical role in optimizing frost removal. For this reason, this paper presents a novel method that uses visual information to classify the frost accumulated on the evaporator surface accurately. This method has two parts: a data acquisition system based on an RGB sensor and an intelligent model that processes the visual information and classifies the frost accumulated on the evaporator surface. The data acquisition system creates the datasets for the training and validation of the intelligent model. This smart model is based on convolutional neural networks. Many tests were performed on a pair of different domestic refrigerators using typical usage habits for data collection. Each test was performed continuously for 24 h, emulating real-life usage. One of the main contributions of this work is a new, accurate, and low-cost method to classify the amount of frost accumulated on the evaporator surface. Furthermore, one advantage of the proposed method is the ease of integrating into any domestic refrigerator. The results indicate that this proposed method can classify with an accuracy as high as 99.75 % four different levels of frost accumulated on the evaporator surface of a domestic refrigerator.

Enhanced engineering design behaviour using chatbots with user experience

ABSTRACT In recent years, both industrialists and scholars have come to believe that involving users in the design process is the basis for ensuring design innovation and successful product development. However, practical restrictions of time, budget, and location may inhibit users’ long-term participation at teaching sites. With the development of emergent chatbot technology, the aim of this study is to investigate the feasibility that students practice interacting with chatbots who incorporate multiple real-life users’ experiences with products and product-specific knowledge in the classroom for exempting from time and accessibility constraints. We conducted an experiment using a design workshop to compare the student groups with respect to their interactions with chatbots, with target customers, and with no users while they generated design concepts. The quality of the three student groups’ design concepts and the differences of their design behaviours were compared. The outcomes of this study indicate that the chatbot group exhibited more significant transitions of engineering design behaviours and better design concept score than that the target-user and no-user group did. Chatbots incorporate user experience may provide students with opportunities to practice extracting information from users with the aim of promoting the success of the design process.

Proposed nonparametric runs rules Lepage and synthetic Lepage schemes

The average daily customer waiting time in a service centre is one of the most important metrics to measure performance or service quality. The average daily waiting time should meet a prespecified quality standard. Therefore, it is crucial to monitor such waiting times at regular intervals to maintain and improve the service quality. Similar problems arise in many time-between-event monitoring problems. This paper suggests two improved nonparametric Lepage schemes supplemented with runs rules, i.e., the 2-of-3 runs rules Lepage and the synthetic Lepage schemes. We show the real-life usage of the suggested schemes in monitoring the average daily customer waiting time of a service centre in Australia. The distribution-free nature of the suggested schemes allows broader applicability irrespective of the underlying process density. Moreover, the proposed schemes can jointly monitor the process location and scale parameters. We demonstrate the superiority of the suggested runs rules schemes to those without runs rules, i.e., the Shewhart-Lepage (SL) scheme through computer-intensive Monte-Carlo simulation. In general, we recommend the 2-of-3 runs rules Lepage scheme due to its efficiency and simplicity.

Best in Glow

DXOMARK has made a name for itself ranking the quality of devices like smartphone displays. But to do so requires a complex knowledge of how to replicate real-life user conditions in a lab.

Antipsychotic treatment patterns in Alzheimer’s disease patients with agitation: a cohort study using the UK clinical practice research datalink

Objectives There is a lack of robust epidemiological evidence on antipsychotic (AP) use in patients with agitation in Alzheimer’s disease (AD). Authors studied AP use in patients with AD and agitation and compared their use with patients with other or no neuropsychiatric symptoms (NPS). Methods A retrospective cohort study in the UK Clinical Practice Research Datalink, included patients with AD between January 1st, 2015, and December 31st, 2017. AP use was compared between patients with agitation, other types of NPS and no NPS. Results There were 24,464 patients with AD, median follow-up of 1.1 years (interquartile range [IQR] 0.5–2.1), and median age 83 years (78–88). A larger percentage of patients with agitation (n = 2432) were prescribed APs (38.2%) than other NPS (n = 13,076, 20.4%) and no NPS (n = 11,816, 12.2%). Compared to patients with no NPS, adjusted hazard ratios for AP use were 3.45 (95% CI 2.86–4.17) for patients with agitation and 1.31 (95% CI 1.19–1.44) for patients with other NPS. Among users of APs, the treatment discontinuation rate at six months was 44.8% in patients with agitation (other NPS 57.1%; no NPS 63.5%). Conclusions Patients with AD and agitation were frequently prescribed APs and for long periods in routine clinical practice in the UK. The high real-life usage of APs suggests that physicians prefer using APs for the treatment of agitation despite recommendations against their long-term use. These data support a need for AP therapies that better address known safety concerns with currently used APs to treat agitation in elderly patients with AD.

Гедонические ценовые индексы: опыт применения к российскому рынку

In this paper discussed is the question of using the hedonic method when constructing price indices adjusted for changes in the quality level of goods on the Russian market. In the first part of the paper several foreign works devoted to the application of the method to various groups of goods are reviewed. Also, there is a short review of real-life usage of the method by BLS, Census bureau and BEA.In the second part an example of the application of the hedonic approach to Russian data based on information on prices and characteristics of mobile phones according to the Yandex. Mar­ket portal in the period from July 2019 to September 2021 is described. It is shown that the hedonic method is applicable in Russian conditions and shows statistically significant differences between the observed price change and the estimated adjusted indices. However, the lack of the necessary statistical information does not make it possible to adjust official price indices by the quality of goods.