Modern Mobile Devices Research Articles

Optimal Scaling Appraisal of Maturity Status of Nigerian Polytechnic Education in Industry 4.0

The first industrial revolution in the 18th century is related to the transformation to mechanization by using hydro power and steam power to second, third and a new concept referred to as Cyber-Physical Systems (CPS) that combine Internet of Things (IoT) technologies with the manufacturing which is seen as a significant paradigm shift in industrial manufacturing, named as Industry 4.0 (4IR). This study explored the perspectives of people on the lingering issue of maturity of Nigerian Polytechnics in terms of 4th industrial revolution; thus, the paper aimed at appraising the maturity status of Nigerian polytechnics in the industry 4.0 using Optimal Categorical Scaling Regression (Catreg). Data collection was cross-region in Nigeria. This research used the stratified sampling method to ensure a proper spread and it was designed in line with descriptive survey, systematically examining the maturity status of their institution on 4IR through the primary data collected with the aid of questionnaire and focus group discussion from the stakeholders in private and public Nigerian polytechnics. The data were sourced from 18 Polytechnics, 1 each from federal, state and private in each geographical zone. Inferential statistical tools of optimal scaling regression analysis were deployed. The analysis inferred that eagerness of leaders and competence as well as modern ICT and mobile devices are fully mature but implementation of 4IR road-map, decentralization, modelling and simulation, sharing knowledge and open innovation, ICT competence and openness to new technology are still maturing. It is recommended that the educational policy and a blueprint of education for Industry 4.0 should be formulated and implemented to meet the global standard of education.

Booster: A Benchmark for Depth From Images of Specular and Transparent Surfaces.

Estimating depth from images nowadays yields outstanding results, both in terms of in-domain accuracy and generalization. However, we identify two main challenges that remain open in this field: dealing with non-Lambertian materials and effectively processing high-resolution images. Purposely, we propose a novel dataset that includes accurate and dense ground-truth labels at high resolution, featuring scenes containing several specular and transparent surfaces. Our acquisition pipeline leverages a novel deep space-time stereo framework, enabling easy and accurate labeling with sub-pixel precision. The dataset is composed of 606 samples collected in 85 different scenes, each sample includes both a high-resolution pair (12 Mpx) as well as an unbalanced stereo pair (Left: 12 Mpx, Right: 1.1 Mpx), typical of modern mobile devices that mount sensors with different resolutions. Additionally, we provide manually annotated material segmentation masks and 15 K unlabeled samples. The dataset is composed of a train set and two test sets, the latter devoted to the evaluation of stereo and monocular depth estimation networks. Our experiments highlight the open challenges and future research directions in this field.

Assessing Stress with Mobile Systems: A Design Science Approach

ABSTRACT Psychological stress is detrimental to individuals’ health and incurs immense societal costs. A prerequisite for effective assistance in stress management is assessing individuals’ stress. The sensing capabilities of modern mobile devices can aid in stress assessment and form a foundation for mobile stress assessment systems. These systems provide insights into user stress levels, provide targeted feedback, and enable stress management and coping efforts. Following design science research methodology, we iteratively designed and developed five mobile stress assessment system prototypes. In addition, we reviewed the existing literature on mobile stress assessment. By combining learnings from prototyping and reviewing existing approaches, we developed design knowledge for mobile stress assessment systems. We subjected this design knowledge to an applicability check involving qualitative interviews with research, system design, and work practice experts. The design knowledge we present in this article comprises six design requirements, seven design principles, and six design features. From a practical point of view, we identified and discussed the trade-offs that system designers may face when implementing mobile stress assessment systems.

Application of mobile digital recording and GIS analysis of archaeological surface survey finds in the MapFarm project

Recent technological developments in the field of mobile devices have influenced the way archaeological surveys are conducted. The collection, management and analysis of archaeological data have been enriched through the use of new digital applications and devices. This paper presents a case study of the application of a technique for digital recording of archaeological surface finds in the MapFarm project, along with the subsequent analysis. This technique relies on the capabilities of modern mobile devices and web technologies, combined with the application of Geographic Information Systems (GIS). It enables the direct digital recording of the exact location of artefacts in the field, using the GNSS receiver of smartphones, allowing the rapid extraction of collected data and their analysis with GIS. The technique was applied during the systematic archaeological survey of selected prehistoric settlements in Aegean Thrace, in the context of the research project MapFarm, which aims to expand our knowledge about the Neolithic settlers of Aegean Thrace. The implementation of this technique has significantly reduced the time required for recording in the field, ensuring at the same time a more efficient and precise analysis of data. In addition, more firm conclusions emerged regarding the distribution of the archaeological finds in the context of the intra-site level and the site’s extent, by comparison to older surface survey techniques. Analyses performed through the GIS digital tools provided an improved approach to the distribution of surface finds at the settlements under investigation.

An interactive augmented reality software for facial reconstructive surgeries

Background and ObjectiveSurgical trainees need a lot of training and practice before being able to operate independently. The current approach of surgical education mainly involves didactic teaching and psychomotor training through physical models or real tissue. Due to the unavailability of physical resources and lack of objective ways of evaluation, there is a demand for developing alternative training methods for surgeons. In this paper, we present an application that provides additional training opportunities to surgical trainees in the field of facial reconstructive surgeries. MethodsWe built a mobile augmented reality application that helps the user to visualize important concepts and experiment with different surgical plans for facial reconstructive surgeries. The application can overlay relaxed skin tension lines on a live video input or a patient's photo, which serve as bases for aligning a skin flap. A surgical trainee can interactively compare different skin flap design choices with estimated final scars on a photo of a patient. Data collection capability is also added to the application, and we performed a Monte Carlo experiment with simulated users (five classes of 100 users each) as an example of objectively measuring user performance. ResultsThe application can overlay relaxed skin tension lines on a patient's face in real time on a modern mobile device. Accurate overlays were achieved in over 91% as well as 84% and 88% out of 263 generated face images, depending on the method. Visual comparisons of the three overlay methods are presented on sample faces from different population groups. From the Monte Carlo experiment, we see that user actions in each class follow a normal distribution with a distinct set of parameters. ConclusionsThis application can serve as a basis for teaching surgical trainees the fundamentals of different facial reconstructive procedures, especially concepts related to relaxed skin tension lines and skin flaps. It can objectively evaluate the performance of surgical trainees in a course. This setup focuses on illustrating the relationship between the orientation of skin flaps and relaxed skin tension lines, which is a prerequisite of minimizing scarring in patients in addition to good surgical techniques.

Neck pain, disability and mobile phone usage among physiotherapy students - a cross-sectional study.

Modern mobile devices have become tools used for educational, research, business or recreational purposes. Incorrect position during excessive use of a smartphone can lead to biomechanical changes, the most visible of which is the position of the head in protraction, characterized by the protrusion of the head and neck forward in relation to the shoulder girdle and trunk. The aim of the study was to analyze the relationship between disability, neck pain (NP), use of phones before bedtime, and hours of using smartphones. The study involved 146 physiotherapy students aged 18-26. Students were asked to complete pain surveys (VAS pain scale), and Neck Disability Index (NDI). Participants were also asked if their pain lasted longer than 3 months, how long they used their smartphone during the day, and whether they used it before bedtime. Statistically significant differences were found between groups with and without neck pain regarding NDI score (p<0.001). Participants who suffered from neck pain longer than 3 months had greater NDI scores (p=0.03), greater intensity of symptoms (p=0.04), greater problems with reading (p<0.01) and driving (p=0.04) than participants who experienced pain for less than 3 months. Using phones before bedtime was related to problems with focusing (p<0.01). There were statistically significant correlations between the time of phone use and disability in terms of reading (p=0.04), focusing (p<0.001), work (p<0.001) and sleeping (p=0.02). Dysfunctions associated with pain in the cervical section may affect the learning abilities of students and thus the acquisition of professional competencies. Not using a smartphone before bedtime is recommended, as it causes poorer concentration. The longer the time spent using the phone, the more significant the disability.

Smartphone obsession linked behavioural changes among Indian adolescents.

The best technological gifts of the 21st century are mobile phones, which are especially well-liked to adolescents. Infinite resources with numerous uses and applications are available on modern mobile devices. Adolescents have behavioral changes as a result of its excessive use. Therefore, it is of interest to explore the connection between smartphone obsession and potential behavioral changes. A School based, co relational study was conducted among 100 adolescents at selected schools at Tamil Nadu. Samples were selected by simple random sampling technique. Data were collected to assess the mobile addiction by using Smartphone Addiction Scale - Short Version (SVSAC) and Pediatric symptom checklist - 17was used to evaluate the behavioral changes. Collected data were analyzed by using descriptive and inferential statistics. The Study shows that 52 adolescents had a high smartphone Obsession, in that 37 had negative behavioral changes due to overuse of the smart phone and also had slight positive correlation between smartphone obsession and behavioral changes. A significant relationship was seen between smart phone obsession with behavioral changes (p<0.001) among adolescents. The study concluded that smart phone obsession and behavioral changes having strong connection in adolescents was significantly associated with their behaviors.

Spatial Threat Level Analysis

In the material the authors consider methods for the analysis of spatially-defined states, which are an indicator of certain threats. One such threat is the evolving COVID-19 epidemic. An essential part of the countermeasures, especially in the early stages, is the warning not to enter areas with an increased risk of infection, or in the case of partially quarantined persons - a warning not to leave the perimeter approved for movement. Modern mobile devices, smartphones, are a natural tool for personal alerting a person when entering a territorial area with undesirable consequences. Traditional methods for localization are considered, as well as a method for determining the coordinates of a mobile object using network stations of mobile operators. The mathematical bases are presented and an analysis is performed to evaluate the effect of the spatial analysis.

Unified Scaling-Based Pure-Integer Quantization for Low-Power Accelerator of Complex CNNs

Although optimizing deep neural networks is becoming crucial for deploying the networks on edge AI devices, it faces increasing challenges due to scarce hardware resources in modern IoT and mobile devices. This study proposes a quantization method that can quantize all internal computations and parameters in the memory modification. Unlike most previous methods that primarily focused on relatively simple CNN models for image classification, the proposed method, Unified Scaling-Based Pure-Integer Quantization (USPIQ), can handle more complex CNN models for object detection. USPIQ aims to provide a systematic approach to convert all floating-point operations to pure-integer operations in every model layer. It can significantly reduce the computational overhead and make it more suitable for low-power neural network accelerator hardware consisting of pure-integer datapaths and small memory aimed at low-power consumption and small chip size. The proposed method optimally calibrates the scale parameters for each layer using a subset of unlabeled representative images. Furthermore, we introduce a notion of the Unified Scale Factor (USF), which combines the conventional two-step scaling processes (quantization and dequantization) into a single process for each layer. As a result, it improves the inference speed and the accuracy of the resulting quantized model. Our experiment on YOLOv5 models demonstrates that USPIQ can significantly reduce the on-chip memory for parameters and activation data by ~75% and 43.68%, respectively, compared with the floating-point model. These reductions have been achieved with a minimal loss in mAP@0.5—at most 0.61%. In addition, our proposed USPIQ exhibits a significant improvement in the inference speed compared to ONNX Run-Time quantization, achieving a speedup of 1.64 to 2.84 times. We also demonstrate that USPIQ outperforms the previous methods in terms of accuracy and hardware reduction for 8-bit quantization of all YOLOv5 versions.

With What and on What Can Musician Write in the Digital Age: Analysis of Modern Mobile Devices

With What and on What Can Musician Write in the Digital Age: Analysis of Modern Mobile Devices

Multipath QUIC for Access Traffic Steering Switching and Splitting in 5G Advanced

The proliferation of modern mobile devices equipped with several wireless interfaces (multi-homed), along with the increasing demand for high-throughput and ultra-reliable connectivity, motivated 3GPP to specify a solution that enables multi-access communication, called access traffic steering, switching, and splitting (ATSSS). Based on this solution, a mobile device can exchange data traffic with the 5G core network by simultaneously using different access networks (e.g., WiFi and 5G-NR). Consequently, data flows can enjoy aggregated bandwidth and also reduced delay and increased reliability. In this article, we briefly present the key concepts and functionality of ATSSS, and we focus on the ATSSS enhancements considered for 5G Advanced (i.e., in 3GPP Rel-18). In particular, we present a new steering functionality that is based on the QUIC protocol and its multipath extensions. We discuss the motivation for this steering functionality, its features and user-plane operation, and we explain how it can be applied to proxy UDP traffic over HTTP.

FEATURES OF THE USE OF AUGMENTATIVE AND ALTERNATIVE COMMUNICATION METHODS IN PSYCHOLOGICAL SUPPORT OF CHILDREN WITH AUTISM SPECTRUM DISORDER

The article analyzes and substantiates the peculiarities of the implementation of modern methods of auxiliary and alternative communication in the process of psychological support of children with autism spectrum disorders. Modern experience shows that in the conditions of early intervention, the development of children with autism spectrum disorder acquires stable positive dynamics. Assistance to children with autism spectrum disorder is most successfully provided in the paradigm of complex support. In children with autism spectrum disorders, disorders in the field of social communication and language pragmatics are found in all without exception, regardless of age and level of development. An analysis of the views of various researchers on the problem of communication and speech disorders in children with autism spectrum disorders suggests that the introduction of alternative and auxiliary communication means is an effective intervention that gives quick results and has a positive effect on the development of communication and language. The best result is achieved in a situation where the child's environment supports the practice of using alternative and auxiliary communication tools, knows how to respond correctly to the child's communicative initiatives, create situations in which he could use alternative and auxiliary communication tools and conduct training in the process of everyday interaction. Accordingly, the authors of the article actualize the issue of finding alternative opportunities to build a communicative space between the child and parents, as well as the implementation of auxiliary communication methods using modern mobile applications and devices. When choosing means of additional communication, the level of communicative development, communicative capabilities and abilities of the child are assessed. As part of an empirical study, the positive results of the implementation of modern software for mobile devices are demonstrated in order to optimize the construction of a constructive communicative space between a child with autism spectrum disorder and significant adults.

The influence of modern mobile devices on the performance of medical students

The modern smartphones attract teachers and students with their opportunities to develop competencies with numerous applications, and at the same time, the obvious and yet insufficiently studied threats associated with smartphones cause concern and concern. Having a huge potential for use in the educational environment, the phone becomes a cause of conflict, a hindrance in lessons and a competitor to productive pastime. The paucity and inconsistency of data on the impact of the phone on academic achievement, psychological well-being, and interpersonal relationships require further research. The study among junior students of the Institute considered the issues of productive and problematic use of mobile phones. The survey method was used to obtain information about the use of a mobile phone. One of the manifestations of the construct “problematic mobile phone use” is the presence of problems in various spheres of life, including problems related to school. As a result of the study, the positive and negative effects of mobile phones on educational activities were identified.

FORECASTING THE STATE OF TELECOMMUNICATION NETWORKS USING QUANTILE AND LOGISTIC REGRESSION METHODS

In today's modern world, the ubiquity of information technology has intertwined telecommunications systems with every facet of human life. It's challenging to fathom a world where you're disconnected from the "World Wide Web" or unable to exchange data instantly via the intricate web of modern mobile devices. The vitality of staying connected online cannot be overstated, and ensuring the smooth functioning of telecommunications systems is paramount. This paper delves into the pivotal task of predicting and managing the performance of these networks, employing quantile and logical regression techniques. Our study leverages real-world data from telecommunication network operations to construct a predictive model capable of anticipating network conditions in advance. This predictive capability serves as the linchpin for intelligent decision-making systems, facilitating real-time network management. By implementing machine learning methods, specifically quantile regression, we achieve a sophisticated understanding of how various factors influence network performance. Our research doesn't just stop at forecasting; it extends to the realms of intellectual decision-making systems, where the insights gained from regression analysis play a pivotal role. These intelligent systems are equipped to make data-driven decisions on network resource allocation, maintenance schedules, and preemptive problem resolution. In essence, they act as the custodians of network stability, ensuring that telecommunication systems remain robust and responsive to the ever-evolving demands of modern society. This article sheds light on the indispensable role of regression methods in proactively managing the state of telecommunications networks. By harnessing the power of machine learning and data-driven insights, we pave the way for a future where network disruptions are minimized, and the seamless connectivity we've come to rely on remains a constant presence in our lives.

The Use of Wireless Networks and Mobile Applications in the Control of Electric Machines

The paper presents the implementation possibilities of remote control by use of wireless communication and mobile application dedicated to controlling systems of power electronics converters. The article focuses on Bluetooth and Wi-Fi technologies as they are currently the most commonly used in modern mobile devices. The authors wanted to check the usefulness of those methods in the application of a classic drive set with a DC motor. The MIT App Inventor programming environment, which allows quick prototyping of the mobile graphical interface, was used to develop the mobile application. The developed prototype of the mobile application is the second thread of the article, the aim of which is to propose a mobile application interface that enables safe control of the electric drive in an open loop. By repeated testing of the graphical structure of the application and the controls used, the authors obtained the final form of the interface, which, in their opinion, is absolutely required when developing such programs. The evaluated control strategy has been also used to control the rotational speed of a permanent magnet DC motor supplied by a three-phase thyristor rectifier. This paper’s research results have shown the proposed solutions’ advantages and disadvantages.

Development of technology for control of the operation of solid mineral fertilizers and the quality of their distribution

The article reviews the problem of setting up and calibrating centrifugal solid mineral fertilizer distributors. A review and analysis of the most common methods offered by domestic and foreign manufacturers of equipment in this segment has been carried out. The advantages and disadvantages of existing methods for quality control of the distribution of solid mineral fertilizers over the field area are revealed. The positive experience of advanced developments is taken into account and is the basis of the proposed assessment method. The developed method formed the basis of a software package for determining the uniformity of fertilizer distribution over the field and consists in using EVA - mats 50 by 50 cm in size, with cells in the form of a regular hexagon with a facet of 8 mm and a cell depth of 10 mm, which allows most of those falling into the area to linger mat of granules of solid mineral fertilizers. A detailed algorithm for the operation of an application written for mobile devices with the ability to install applications and equipped with a camera has been developed and presented. The proposed solution reduces labor and time costs by eliminating several operations from standard techniques and allows one person to perform the procedure with a modern mobile device equipped with a camera.

Examining the Current Status and Emerging Trends in Continuous Authentication Technologies through Citation Network Analysis

Continuous Authentication (CA) technologies enable users to be authenticated beyond just the point of entry. In this article, we conduct a comprehensive review of over 2,300 articles to (a) identify the main components of CA research to date, and (b) explore the current gaps and future research directions. Through a Citation Network Analysis (CNA), we identified that there are currently three primary focus research areas on CA - Keystroke Dynamics; Mouse Movements; and Mobile Device Touch, as well as identify an emerging trend in more recent studies on multi-modal CA authentication which utilises the numerous sensors that are embedded in modern mobile devices. This study also highlights the current gaps in the literature such as the need for a consensus over how to evaluate the application and utility of CA, and the need to examine the feasibility of CA technologies that currently exist based on more use case studies.

The influence of modern mobile devices on the performance of students

The influence of modern mobile devices on the performance of students

ADC-DL: Communication-efficient distributed learning with hierarchical clustering and adaptive dataset condensation

The rapid growth of modern mobile devices leads to a large number of distributed data, which is extremely valuable for learning models. Unfortunately, model training by collecting all these original data to a centralized cloud server is not applicable due to data privacy and communication costs concerns, hindering artificial intelligence from empowering mobile devices. Moreover, these data are not identically and independently distributed (Non-IID) caused by their different context, which will deteriorate the performance of the model. To address these issues, we propose a novel Distributed Learning algorithm based on hierarchical clustering and Adaptive Dataset Condensation, named ADC-DL, which learns a shared model by collecting the synthetic samples generated on each device. To tackle the heterogeneity of data distribution, we propose an entropy topsis comprehensive tiering model for hierarchical clustering, which distinguishes clients in terms of their data characteristics. Subsequently, synthetic dummy samples are generated based on the hierarchical structure utilizing adaptive dataset condensation. The procedure of dataset condensation can be adjusted adaptively according to the tier of the client. Extensive experiments demonstrate that the performance of our ADC-DL is more outstanding in prediction accuracy and communication costs compared with existing algorithms.

Driver Fatigue Level Prediction

Public transport networks (PTNs) are difficult to use when the user is unfamiliar with the area they are traveling to. This is true for both infrequent users (including visitors) and regular users who need to travel to areas with which they are not acquainted. In these situations, adequate on-trip navigation information can substantially ease the use of public transportation and be the driving factor in motivating travellers to prefer it over other modes of transportation. However, estimating the localization of a user is not trivial, although it is critical for providing relevant information. I assess relevant design issues for a modular cost-efficient user-friendly on-trip Navigation service that uses position sensors. By helping travellers move from single occupancy vehicles to public transportation systems, communities can reduce traffic congestion as well as its environmental impact. Here, I describe our efforts to increase the satisfaction of current public transportation users and help motivate more people to ride. I can help existing riders and encourage new riders by enhancing the usability of public transportation through good transit traveller information systems. The motivation for every location-based information system is: “To assist with the exact information, at right place in real time with personalized setup and location sensitiveness”. LOCATION-BASED services are increasingly important for modern mobile devices such as the Smartphone. An important feature of a modern mobile device is that it can position itself. Not only for use on the device but also for remote applications that require tracking of the device. Furthermore, tracking has to robustly deliver position updates when faced with changing conditions such as delays due to positioning and communication, and changing positioning accuracy. The realized system tracks pedestrian targets equipped with GPS-enabled devices. The face, an important part of the body, conveys a lot of information. When a driver is in a state of fatigue, the facial expressions, e.g., the frequency of blinking, are different from those in the normal state. In this project, we propose a system called DriCare, which detects the drivers’ fatigue status, such as blinking, and duration of eye closure, using video images, without equipping their bodies with devices. Owing to the shortcomings of previous algorithms, we introduce a new face-tracking algorithm to improve the tracking accuracy. Further, we designed a new detection method for facial regions based on 68 key points. Then we use these facial regions to evaluate the drivers’ state. By combining the features of the eyes and mouth, DriCare can alert the driver using a fatigue warning.