Smart Handling Research Articles

AI-Driven solid-state device to enable natural control of upper-extremity robotic exoskeletons

The paper introduces the ‘Smart Handle’, a compact, lightweight, fully solid-state control device based on machine learning (ML) models, enabling intuitive manipulation across all three degrees-of-freedom (DOF) of translation and orientation. This handle-type control device utilizes low-cost, easily accessible sensors and materials. It addresses the need for natural control mechanisms in upper-extremity exoskeletons used in rehabilitation and occupational settings, offering position and orientation trajectories crucial for kinematic models. Additionally, individuals with motor difficulties using mobility chairs could benefit from its ability to learn and interpret diverse inputs as control commands. Through empirical study, it was demonstrated that the device adeptly learns and outputs continuous translation and rotation information from training sets focused on single DOF motions. Personalized calibration enables consistent movement classification with over 95% accuracy. Successful proof-of-concept experiments were conducted in exoskeleton and wheeled robot control applications, showcasing the Smart Handle's adaptability and reliability in diverse settings. This research underscores the device's potential across multiple domains, providing a foundation for enhanced intuitive control mechanisms in various technological applications.

Enhancing QoS of Telecom Networks through Server Load Management in Software-Defined Networking (SDN)

In the modern era, with the emergence of the Internet of Things (IoT), big data applications, cloud computing, and the ever-increasing demand for high-speed internet with the aid of upgraded telecom network resources, users now require virtualization of the network for smart handling of modern-day challenges to obtain better services (in terms of security, reliability, scalability, etc.). These requirements can be fulfilled by using software-defined networking (SDN). This research article emphasizes one of the major aspects of the practical implementation of SDN to enhance the QoS of a virtual network through the load management of network servers. In an SDN-based network, several servers are available to fulfill users’ hypertext transfer protocol (HTTP) requests to ensure dynamic routing under the influence of the SDN controller. However, if the number of requests is directed to a specific server, the controller is bound to follow the user-programmed instructions, and the load on that server is increased, which results in (a) an increase in end-to-end user delay, (b) a decrease in the data transfer rate, and (c) a decrease in the available bandwidth of the targeted server. All of the above-mentioned factors will result in the degradation of network QoS. With the implementation of the proposed algorithm, dynamic active sensing server load management (DASLM), on the SDN controller, the load on the server is shared based on QoS control parameters (throughput, response time, round trip time, etc.). The overall delay is reduced, and the bandwidth utilization along with throughput is also increased.

Digital Citizenship and its Role in Achieving the Vision of Kingdom of Saudi Arabia 2030

Digital citizenship is the set of rules, controls, standards, norms, ideas and principles followed in the optimal and correct use of technology, which citizens need in order to contribute to the advancement of the country. Digital citizenship in short is guidance, guidance and protection, guidance and guidance towards the benefits of modern technologies, and protection from their dangers. In short, it is the smart handling of technology. This paper sheds light on digital citizenship and its role in supporting the educational process in accordance with the vision of the Kingdom of Saudi Arabia 2030, given that in today's world and with the development of the world in various fields and the emergence of technological openness and the emergence of digital programs and the spread of modern means of mass communication and its wide range and ease of access to all, I started The importance of digital citizenship, its dimensions, and its effects are clearly evident, as the digital citizen is considered a patriot’s helper, and it is a mirror of his homeland, through which he reflects his values, customs, and traditions. Therefore, he became responsible to everyone in what he says and what he does, and everyone represents the country through his digital personality that he creates himself through his behaviors, participation, and cultures that he creates. He roams around the globe and communicates with others smoothly and easily, in a monitored and documented manner, as if it were a biography of this person. Based on the foregoing, it has become necessary to provide ideal positive models on how to properly use the means of technology in order to set a good example, by spreading the culture of digital citizenship and security awareness among members of society in light of the current scientific developments and their challenges, by encouraging desirable behaviors and fighting unpopular behaviors. In digital transactions, to be the forearms of a patriot, producers, creators, and officials in the digital space, preserving societal values, and practicing positive digital citizenship. To verify the objective of the study, we have used the digital citizenship study questionnaire which was made available electronically, and the number of distributed questionnaires reached 172. After reviewing and checking, we obtained 159 questionnaires valid for statistical analysis according to the target group, who are students. The five-point Likert scale was used as well as the direct questions (yes, no). The five-point Likert scale is characterized by the level measurement (high, above average, average, below average, poor). The analysis of the results using SPSS to measure the arithmetic mean and the recurrence rate showed a number of results that help the researcher to identify the most important skills that need to be strengthened and developed through education and training, to achieve the optimal use of technology and enhance intellectual security, in light of digital citizenship to prepare a valid digital citizen.

Wearables, telemedicine, and artificial intelligence in arrhythmias and heart failure: Proceedings of the European Society of Cardiology Cardiovascular Round Table.

Digital technology is now an integral part of medicine. Tools for detecting, screening, diagnosis, and monitoring health-related parameters have improved patient care and enabled individuals to identify issues leading to better management of their own health. Wearable technologies have integrated sensors and can measure physical activity, heart rate and rhythm, and glucose and electrolytes. For individuals at risk, wearables or other devices may be useful for early detection of atrial fibrillation or sub-clinical states of cardiovascular disease, disease management of cardiovascular diseases such as hypertension and heart failure, and lifestyle modification. Health data are available from a multitude of sources, namely clinical, laboratory and imaging data, genetic profiles, wearables, implantable devices, patient-generated measurements, and social and environmental data. Artificial intelligence is needed to efficiently extract value from this constantly increasing volume and variety of data and to help in its interpretation. Indeed, it is not the acquisition of digital information, but rather the smart handling and analysis that is challenging. There are multiple stakeholder groups involved in the development and effective implementation of digital tools. While the needs of these groups may vary, they also have many commonalities, including the following: a desire for data privacy and security; the need for understandable, trustworthy, and transparent systems; standardized processes for regulatory and reimbursement assessments; and better ways of rapidly assessing value.

Weak Jordan *-derivations of prime rings

Let * be an involution of a non-commutative prime ring [Formula: see text] with the maximal symmetric ring of quotients and the extended centroid of [Formula: see text] denoted by [Formula: see text] and [Formula: see text], respectively. Consider [Formula: see text] be an additive map, if [Formula: see text] for all [Formula: see text], then such a map [Formula: see text] is termed as a weak Jordan *-derivation. With the smart handling of the FI-theory and facing the challenging case of low dimensions, we prove that every weak Jordan *-derivation of [Formula: see text] is [Formula: see text]-inner unless [Formula: see text]. Moreover, if * is of the first kind, then every weak Jordan *-derivation [Formula: see text] of [Formula: see text] is [Formula: see text]-inner if and only if [Formula: see text] is [Formula: see text]-linear.

Setting Privacy “by Default” in Social IoT: Theorizing the Challenges and Directions in Big Data Research

The social Internet of Things (SIoT) shares large amounts of data that are then processed by other Internet of Thing (IoT) devices, which results in the generation, collection, and treatment of databases to be analyzed afterwards with Big Data techniques. This paradigm has given rise to users' concerns about their privacy, particularly with regard to whether users have to use a smart handling (self-establishment and self-management) in order to correctly install the SIoT, ensuring the privacy of the SIot-generated content and data. In this context, the present study aims to identify and explore the main perspectives that define user privacy in the SIoT; our ultimate goal is to accumulate new knowledge on the adoption and use of the concept of privacy “by default” in the scientific literature. To this end, we undertake a literature review of the main contributions on the topic of privacy in SIoT and Big Data processing. Based on the results, we formulate the following five areas of application of SIoT, including 29 key points relative to the concept of privacy “by default”: (i) SIoT data collection and privacy; (ii) SIoT security; (iii) threats for SIoT devices; (iv) SIoT devices mandatory functions; and (v) SIoT and Big Data processing and analytics. In addition, we outline six research propositions and discuss six challenges for the SIoT industry. The results are theorized for the future development of research on SIoT privacy by “default” and Big Data processing.

A Machine Learning Approach to Hand-Arm Motion Prediction for Active Upper Extremity Occupational Exoskeleton Devices

Exoskeleton devices are currently being utilized in a variety of occupational settings to reduce musculoskeletal efforts to lower fatigue, improve performance, and minimize work-related injuries associated with musculoskeletal disorders (MSDs). The intrinsic challenges that accompany the development of fully supporting and active upper extremity multi-degrees of freedom (DOF) devices include not only the mechanical design, but also lack of an intuitive way to control and operate these devices. A proof-of-concept instrumented handle consisting an embedded sensor network was developed with the intention to utilize artificial neural networks (ANN) to properly identify the intended motion of the user and to estimate the motion intensity. Results show this method is feasible and delivers useful insight into developing the next stages of the “smart handle” technology that will include the remaining hand motions, correctly classifying combination of intended motions and using the handle output to control complex multi-DOF upper extremity exoskeletons devices.

TissUUmaps: interactive visualization of large-scale spatial gene expression and tissue morphology data.

MotivationVisual assessment of scanned tissue samples and associated molecular markers, such as gene expression, requires easy interactive inspection at multiple resolutions. This requires smart handling of image pyramids and efficient distribution of different types of data across several levels of detail.ResultsWe present TissUUmaps, enabling fast visualization and exploration of millions of data points overlaying a tissue sample. TissUUmaps can be used both as a web service or locally in any computer, and regions of interest as well as local statistics can be extracted and shared among users.Availability and implementationTissUUmaps is available on github at github.com/wahlby-lab/TissUUmaps. Several demos and video tutorials are available at http://tissuumaps.research.it.uu.se/howto.html.Supplementary information Supplementary data are available at Bioinformatics online.

Macroeconomic forecast accuracy in a data‐rich environment

SummaryThe performance of six classes of models in forecasting different types of economic series is evaluated in an extensive pseudo out‐of‐sample exercise. One of these forecasting models, regularized data‐rich model averaging (RDRMA), is new in the literature. The findings can be summarized in four points. First, RDRMA is difficult to beat in general and generates the best forecasts for real variables. This performance is attributed to the combination of regularization and model averaging, and it confirms that a smart handling of large data sets can lead to substantial improvements over univariate approaches. Second, the ARMA(1,1) model emerges as the best to forecast inflation changes in the short run, while RDRMA dominates at longer horizons. Third, the returns on the S&P 500 index are predictable by RDRMA at short horizons. Finally, the forecast accuracy and the optimal structure of the forecasting equations are quite unstable over time.

Parametric Design and Analysis of the Arc Motion of a User-Interactive Rollator Handlebar with Hall Sensors

Most user-interactive rollator handles fabricated so far have had errors in classifying users’ walking intentions due to the structure not considering gravity, in addition to their usage not being intuitive. Here, we introduce a smart handle based on ‘arc motion’ horizontal to the ground to classify the user’s walking intentions accurately. In designing the handle, the limit of grip angle is adopted considering the arc motion. This minimizes the deflection of the handle by gravity and can allow the handle to be optimized for the grip motion. Moreover, we applied the results of our analysis of users’ walking intentions in the arc motion to machine learning. In understanding the user’s intentions to walk, we created two support vector machine classifiers from handle data collected through four Hall sensors. This combination of the arc motion and machine learning has significantly reduced classification errors. As a result, we ensured an accuracy of 0.95, which is a widely used standard in control.

Research on Smart Handling Robot for Nuclear Reactor

Smart handling is more and more important to the core of nuclear power plant (NPP)- nuclear reactor. Refueling of nuclear fuel was mainly relied on NPP operators in the past. The potential risk always exists. The smart handling robot is developed so as to reduce the related risk. The research method of the robot development and key point is introduced in the paper. The smart handling robot for nuclear reactor will have broad prospects in China.

Elastic Resistance Effectiveness on Increasing Strength of Shoulders and Hips.

Picha, KJ, Almaddah, MR, Barker, J, Ciochetty, T, Black, WS, and Uhl, TL. Elastic resistance effectiveness on increasing strength of shoulders and hips. J Strength Cond Res 33(4): 931-943, 2019-Elastic resistance is a common training method used to gain strength. Currently, progression with elastic resistance is based on the perceived exertion of the exercise or completion of targeted repetitions; exact resistance is typically unknown. The objective of this study was to determine whether knowledge of load during elastic resistance exercise will increase strength gains during exercises. Participants were randomized into 2 strength training groups, elastic resistance only and elastic resistance using a load cell (LC) that displays force during exercise. The LC group used a Smart Handle (Patterson Medical Supply, Chicago, IL, USA) to complete all exercises. Each participant completed the same exercises 3 times weekly for 8 weeks. The LC group was provided with a set load for exercises, whereas the elastic resistance only group was not. The participant's strength was tested at baseline and program completion, measuring isometric strength for shoulder abduction (SAb), shoulder external rotation (SER), hip abduction (HAb), and hip extension (HEx). Independent t-tests were used to compare the normalized torques between groups. No significant differences were found between groups. Shoulder strength gains did not differ between groups (SAb p > 0.05; SER p > 0.05). Hip strength gains did not differ between groups (HAb p > 0.05; HEx p > 0.05). Both groups increased strength because of individual supervision, constantly evaluating degree of difficulty associated with exercise and providing feedback while using elastic resistance. Using an LC is as effective as supervised training and could provide value in a clinical setting when patients are working unsupervised.

Macroeconomic Forecast Accuracy in Data-Rich Environment

The performance of six classes of models in forecasting different types of economic series is evaluated in an extensive pseudo out‐of‐sample exercise. One of these forecasting models, regularized data‐rich model averaging (RDRMA), is new in the literature. The findings can be summarized in four points. First, RDRMA is difficult to beat in general and generates the best forecasts for real variables. This performance is attributed to the combination of regularization and model averaging, and it confirms that a smart handling of large data sets can lead to substantial improvements over univariate approaches. Second, the ARMA(1,1) model emerges as the best to forecast inflation changes in the short run, while RDRMA dominates at longer horizons. Third, the returns on the S&P 500 index are predictable by RDRMA at short horizons. Finally, the forecast accuracy and the optimal structure of the forecasting equations are quite unstable over time.

Development of Real-Time Driver's Health Detection System by Using Smart Handle

The number of vehicle accidents due to driver's drowsiness continues to increase. Therefore, prompt and effective detection for driver's health during driving is crucial to improvement of traffic safety. A set of real-time healthdetection system built-in a smart handle for driver is proposed in the research. By monitoring driver’s biological signals, including respiration, hand gripping force, photoplethysmogram (PPG), and electrocardiogram (ECG), driver's health condition (drowsiness) is able to be detected via the developed algorithm. Meanwhile the driver's state of arrhythmia can be diagnosed too. The test results indicate that the developed real-time driver’s health detection system can effectively monitor not only the state of vigilance but also the state of arrhythmia of a driver.

Development of the All-Surface Plated Smart Handle Through In-Vapor Deposition Technology

Development of the All-Surface Plated Smart Handle Through In-Vapor Deposition Technology

An efficient iterative link transmission model

In this paper a novel iterative algorithm is presented for the link transmission model, a fast macroscopic dynamic network loading scheme. The algorithm's solutions are defined on a space–time discretized grid. Unlike previous numerical schemes there is no hard upper limit on the time step size for the algorithm to be numerically stable, leaving only the trade-off between accuracy and interpolation errors. This is a major benefit because mandatory small time steps in existing algorithm (required for numerical tractability) are undesirable in most strategic analyses. They lead to highly increased memory costs on larger network instances and unnecessary complex behaviour. In practice results are often aggregated for storage or analysis, which leads to the loss of computationally expensive detailed information and to the introduction of inconsistencies. The novel iterative scheme is consistent with the modelling assumptions independent of the numerical time step. A second contribution of the iterative procedure is the smart handling of repeated runs, which can be initialized (or warm started) by an earlier solution. For applications, repeatedly loading a network is often needed when evaluating traffic states under changing variables or adjusted parameter settings, or in optimization and equilibration procedures. In these cases the iterative algorithm is initialized with the solution of a previous run and iterations are performed to find a new consistent solution. Pseudo-code is provided for both a basic upwind iterative scheme and an extended algorithm that significantly accelerates convergence. The most important computational gains are achieved by ordering and reducing calculations to that part of the network which has changed (most). The properties of the algorithm are demonstrated on a theoretical network as well as on some real-world networks.

Simulation of Motorcycle Smart Handling With Addition Gyroscopic Component

Motorcycle in its operation needs high stability. To improve a stability of motorcycle especially in turning direction is done by many methods. The handling turn inclination angle of motorcycle with addition gyroscopic component will be discussed in this research. Gyroscopic is systems which have function to against from Centrifugal (Fc) force. The aim of using Gyroscopic is to control and handling turn inclination angle to avoid skidding.This research uses of simulation model with input of design and dynamic parameter. Speed variable to be used are 40, 50, 60, 70, 80, 90, 100 km/hour. The simulation is processed by Matlab 7.0.1. The result of research is concluded as : the Gyroscopic has controlled skid performance and inclination angle of motorcycle about 11%.

Where Skipping Lambkins Feed: Christopher Smart's Hymns for the Amusement of Children

It is difficult to find any clear meaning that would be available to a child in these lines, particularly in the last stanza. It is one thing to tell the child that gratitude is something men owe to God, but quite another to try to impress upon him that gratitude (since God's delightful voice is the Word made flesh) is in fact God himself. Smart would have the child understand not only that he must give thanks, but also that he must be grateful the ability to do so, since man would be incapable of gratitude were it not Christ's sacrifice. But the paradox of the fortunate fall is rather subtle doctrine a child, and Smart's handling of it does more to obscure than simplify. Not all the hymns are so complex, but many of them are—enough to make us wonder whether Smart was unwilling or merely unable to keep himself within the little prattler's range of comprehension.2 Another serious obstacle arises when we consider even the simplest poems in the collection, these hymns are not merely lisping thoughts to be sung to a benevolent Father. In the eighteenth century, for children was apparently synonymous with for the children's moral in-