Mobile Operators Research Articles

Incidence of type 2 diabetes by occupation – 10-year follow-up of the Gutenberg Health Study

Abstract Background In order to implement targeted type 2 diabetes (T2D) prevention measures for the workplace, it is important to identify high-risk occupations. Most previous studies examine the association between T2D and occupation cross-sectionally, but longitudinal studies are missing. This study aims to investigate the 10-year incidence of T2D in the working population of a German cohort and identify occupations with an increased risk. Methods Data from the population-based Gutenberg Health Study (GHS) were used to examine occupation at baseline (2007-2012) and T2D incidence at the 10-year follow-up. Occupational phases were coded into categories according to the KldB 2010. T2D was defined as either a physician-diagnosed T2D, HbA1c-level ≥6.5% or use of antidiabetic drugs. Age- and sex-standardised incidence and 95% confidence intervals (CI) were calculated for occupational groups based on the age- and sex-distribution of the German population. Standardised incidence ratios (SIR) and 95% CI were calculated using the incidence in the total GHS working population as the reference. Results Of 8130 workers at baseline, 45.2% were female, the mean age was 48.4 years and 4.5% had prevalent T2D. 388 cases occurred between baseline and the 10-year follow-up within the subgroup of persons without prevalent T2D at baseline and with follow-up data (n = 5954). The standardised incidence was 6.9%. “Food production and processing” (20.7%), “cleaners” (16.5%) and “drivers and mobile plant operators” (14.8%) had the highest standardised incidences. Compared to the total working population, we observed a threefold increased SIR for employees in “food production and processing” (3.0, 95% CI 1.8-4.7) and a two times higher SIR for “cleaners” (2.2, 95% CI 1.0-4.7) and “drivers and mobile plant operators” (2.2, 95% CI 1.3-3.3). Conclusions We identified occupations with an increased risk of T2D. Preventive measures and etiological research on work-related risks should focus on these occupations. Key messages • The highest standardised incidence was observed in the occupational groups “food production and processing”, “cleaners” and “drivers and mobile plant operators”. • Targeted prevention measures for type 2 diabetes in the workplace should focus on these occupational groups with increased incidence.

Static analysis framework for permission-based dataset generation and android malware detection using machine learning

Since Android is the popular mobile operating system worldwide, malicious attackers seek out Android smartphones as targets. The Android malware can be identified through a number of established detection techniques. However, the issues presented by modern malware cannot be met by traditional signature or heuristic-based malware detection methods. Previous research suggests that machine-learning classifiers can be utilised to analyse permissions, making it possible to differentiate between malicious and benign applications on the Android platform. There exist machine-learning methods that utilise permission-based attributes to build models for the detection of malware on Android devices. Nevertheless, the performance of these detection methods is dependent on the raw or feature datasets. Android malware research frequently faces a major obstacle due to the lack of adequate and up-to-date raw malware datasets. In this paper, we put forward a systematic approach to generate an Android permission-based dataset using static analysis. To create the dataset, we collect recent raw malware samples (APK files) and focus on the reverse engineering approach and permission-based features extraction. We also conduct a thorough feature analysis to determine the important Android permissions and present a machine-learning-based Android malware detection mechanism. The experimental result of our study demonstrates that with just 48 features, the random forest classifier-based Android malware detection model obtains the best accuracy of 97.5%.

Driving Forces of Strategic Outsourcing in Telecommunication Companies in Tanzania

Abstract This article aims to evaluate the driving forces of outsourcing strategies on the organizational performance of mobile network operators in mainland Tanzania. The objectives are to identify the driving forces of outsourcing and determine the challenges of outsourcing in telecommunication companies. The article adopted a descriptive cross-sectional survey. The selection of mobile companies is based on high market share and operation period. Findings show that customer needs for high-quality services, high-rated change in service, reduction of operational expenditure, and accessing the world’s capability are among the major driving forces for outsourcing. Dependability, loss of security, hidden costs, and selection of competent partners to mention a few are the challenges faced by telecom companies. It is noted that outsourcing enables network operators to advance their organizational performance in terms of operating cost, productivity, profitability, and market share. However, customer satisfaction suffers due to the inconsistency of the quality of service offered. Therefore, it is advised that mobile operators closely monitor outsourcing service providers to ensure that agreed service levels are met, thereby, safeguarding the reputation of the company to customers.

Preventing Overturning of Mobile Cranes Using an Electrical Resistivity Measurement System

Mobile cranes are essential for transporting heavy materials at construction sites, but their operation carries significant safety risks, particularly due to the potential for overturning accidents. These accidents can be classified into two main categories: mechanical accidents, which are caused by factors such as outrigger failure, excessive load weight, and operator skill, and environmental accidents, which arise from ground subsidence due to groundwater and sinkholes. While numerous studies have addressed the causes and prevention of mechanical accidents, there has been a lack of research focusing on the prevention of environmental accidents. This study presents the development of an Electrical Resistivity Measurement System (ERMS) designed to prevent overturning accidents caused by ground subsidence at mobile crane work sites. The ERMS, mounted on a mobile crane, continuously monitors the ground conditions in real time and predicts the likelihood of ground subsidence to prevent accidents. Unlike typical buried electrode methods, the proposed system features a foldable electrode mechanism and a water supply device, thereby making installation and removal more efficient. Furthermore, it uses a ground stability determination algorithm that qualitatively assesses soft ground conditions, which are the primary cause of ground subsidence. The performance of the ERMS was validated through comparisons with commercial equipment, and its applicability was further confirmed through field tests conducted at mobile crane installations. The ERMS is expected to significantly reduce the risk of accidents caused by ground subsidence during mobile crane operations and to contribute to enhancing overall safety in construction environments.

Joint Optimization of Cost and Scheduling for Urban Air Mobility Operation Based on Safety Concerns and Time-Varying Demand

As the value and importance of urban air mobility (UAM) are being recognized, there is growing attention towards UAM. To ensure that urban air traffic can serve passengers to the greatest extent while ensuring safety and generating revenue, there is an urgent need for a transportation scheduling plan based on safety considerations. The region of Beijing–Tianjin–Hebei was selected as the case study in this research. A real-time demand transportation scheduling model for a single day was constructed, with the total service population and total cost as objective functions, and safety intervals, eVTOL performance, and passenger maximum waiting time as constraints. A Joint Optimization of Cost and Scheduling Particle Swarm Optimization (JOCS-PSO) algorithm was utilized to obtain the optimal solution. The optimal solution obtained in this study can serve 138,610,575 passengers during eVTOLs’ entire lifecycle (15 years) with a total cost of CNY 368.57 hundred million, with the cost of CNY 265.9 per passenger. Although it is higher than the driving cost, it saves 1–1.5 h and thus has high cost effectiveness during rush hours.

Development of a total quality management framework for the mobile network operations Centre

Telecommunication is one of the most fast-paced and rapidly changing sectors globally. This study develops a total quality management (TQM) framework for mobile network operation centres (NOC) to aid in network surveillance and fault management processes for a 5G transmission network. A systematic literature review was conducted using academic articles in journals and conference papers sourced from the EBSCOHost database. A fuzzy analytic hierarchical process (FAHP) was used as a multi-criteria decision-making tool to determine which criteria and factors are of the highest ranking for the development of the TQM framework. Data collection and control sheets were ranked higher, making them critical to the framework. This shows that, without good data, no problems can be identified, visualised, analysed, and solved and processes will not be improved. Process improvement is ranked last, showing it is of the lowest priority compared to the other criteria. This however, does not imply that in TQM it is of lower priority, as it is needed to keep meeting the needs of the customers. The framework includes how the TQM tools and techniques can be used in collecting, visualising, analysing, solving problems, and improving processes.

Interactive Marketing Measurement According To Sustainable Competitive Advantage Goals: A Scale Development

Purpose: The objective of this study is to create an interactive marketing model that aligns with the commercial development strategies of mobile phone operators in Iraq. Theoretical framework: Recent literature has reported good results on the new design of the interactive marketing model that is compatible with the development of work in the Iraqi mobile phone companies in the research sample. Design/methodology/approach: Mobile phone companies in Iraq (Asia Cell, Zain, Korek) were chosen as a field for the application, and a purposive research sample consisting of (35) people was chosen from the human resources of the aforementioned companies. Questions prepared for this purpose were adopted as a tool for obtaining data, while the (Atlas-ti) program was used. Statistician in entering and analyzing research data. Findings: The volume of research has been increasing over the past 20 years, although there are only a few reference authors, institutions and journals contributing to the unification of topics. The researchers were able to design an interactive marketing model that simulates the environment and reality of mobile phone companies in Iraq. Research, Practical & Social implications: We suggest a future research agenda by highlighting the contributions made to designing marketing models to suit the environment in which companies of various types operate. Originality/value: Originality/value: The results indicated a proposal for a new interactive marketing model through which we hope to contribute to adding marketing services to companies operating in the Iraqi telecommunications sector.

Foreign migrants in the Moscow agglomeration: spatial and temporal analysis based on data from mobile operators

The article analyzes the modern ethnic landscape of the Moscow agglomeration on the basis of data from mobile operators. The estimation of the number of foreign migrants and its monthly dynamics from October 2021 to October 2022 is made. The main areas of residence of foreigners have been identified, the ethnic diversity of municipalities has been assessed, and the main types of settlement pattern of national-ethnic communities have been identified. The study showed that the total number of foreign migrants in the agglomeration reaches 1.8 million people or 9% of the total population, remaining almost unchanged in spite of events of 2022, including the special military operation. The share of foreigners is minimal in ZATO (below 3%), it is also insignificant in the far suburbs of Moscow and in expensive districts of the capital city. At the same time, the threshold of 17% (the so-called “boiling point”, reflecting a sharp increase in the risks of interethnic conflicts and ghettoization of urban space) was overcome by 8 municipalities in the agglomeration. The two most noticeable areas of increased concentration of foreign migrants are identified in the south-east at the junction of Moscow and Moscow region (Lublino – Kotelniki) and in New Moscow (Mosrentgen – Sosenskoye). The calculation of the Ekkel ethnic mosaic index confirmed the presence of pronounced interethnic contact zones here. Increased index values were also noted in most central and southwest districts of Moscow, which, with a smaller proportion of foreigners living, are associated with a high density of offices, diplomatic institutions and universities. Three types of settlement patterns of national-ethnic groups of migrants, determined by the adaptive capabilities of ethnic communities, were revealed. Diffuse and relatively uniform settlement pattern is characteristic for both the most massive ethnic groups (citizens of Tajikistan, Uzbekistan and Kyrgyzstan) and the most culturally close to the local population (citizens of Ukraine and Belarus). Concentric settlement pattern (in residential areas of Moscow and satellite cities) is typical for relatively large ethnic groups coming from post-Soviet countries (citizens of Azerbaijan, Armenia, Georgia). The local settlement pattern is typical for small ethnic communities that gravitate to specific districts of the capital city.

Experimental Study on LTE Mobile Network Performance Parameters for Controlled Drone Flights

This paper analyzes the quantitative quality parameters of a mobile communication network in a controlled drone logistic use-case scenario. Based on the analysis of standards and recommendations, the values of key performance indicators (KPIs) are set. As the main network-impacting parameters, reference signal received power (RSRP), reference signal received quality (RSRQ), and signal to interference and noise ratio (SINR) were selected. Uplink (UL), downlink (DL), and ping parameters were chosen as the secondary ones, as they indicate the quality of the link depending on primary parameters. The analysis is based on experimental measurements performed using a Latvian mobile operator’s “LMT” JSC infrastructure in a real-life scenario. To evaluate the altitude impact on the selected network parameters, the measurements were performed using a drone as transport for the following altitude values: 40, 60, 90, and 110 m. Network parameter measurements were implemented in automatic mode, allowing switching between LTE4–LTE2 standards, providing the opportunity for more complex analysis. Based on the analysis made, the recommendations for the future mobile networks employed in controlled drone flights should correspond to the following KPI and their values: −100 dBm for RSRP, −16 dB for RSRQ, −5 dB for SINR, 4096 kbps for downlink, 4096 kbps for uplink, and 50 ms for ping. Lastly, recommendations for a network coverage digital twin (DT) model with integrated KPIs are also provided.

Smart whole-body vibration attenuation, cushion for heavy equipment seating: Model and simulation

Off-road mobile machine operators are exposed to whole-body vibration (WBV) which can result in adverse health effects. Seat suspensions are used to reduce WBV exposure, but typical passive seats cannot attenuate frequencies below 1.13 Hz. The proposed device is designed to minimize transmissibility from 0 to 20 Hz because this bandwidth contains the dominant frequency for most off-road vehicles. The semi-active smart device uses bang-bang control and is designed to be installed in place of the seat-pan cushion in OEM passive seats. Modelled as a two degree of freedom system, simulations were performed using a lumped mass model (ωn = 3 Hz; sinusoidal base excitation 0-20 Hz). Using a hexapod robot, a prototype reduced transmissibility compared to a passive OEM seat. The device was up to 5 times more effective than a passive seat in reducing vibration transmissibility. Simulations revealed that operator mass and seat stiffness variations have little effect on device WBV attenuation performance.

An empirical study of impact of customer retention policies on users followed by telecom companies

The objective of this study was to examine the effects of customer retention policies followed by various telecom companies in India. In the modern day, rivalry exists throughout each industry or subject. Therefore, the company must preserve its positive reputation. In light of something similar, the company consistently seeks to draw or keep customers to its identity and offerings by stepping up marketing operations that directly or indirectly impact its development and advancement in a cutthroat industry. For the analysis, the study surveyed 200 telecom customers, including mobile operators and DTHs, to determine their views regarding consumer retention policies and set some parameters against which the survey was conducted.The study revealed that the policy of minimizing attrition affects customer retention in the mobile telecom sector. All these strategies help organizations retain existing consumers and attract potential consumers in one way. This study elaborates the conceptual background and definitions of customer retention, importance, key determinants and strategies for consumer retention and examines the effect and role of consumer retention in telecommunication and the scope of consumer retention in the telecom sector.

A Survey on Mobile Digital Forensic: Taxonomy, Tools, and Challenges

ABSTRACTModern time largely rely on mobile gadgets as a means of communication, and entertainment. These gadgets now plays a vital role in forensic analysis and criminal investigations as it store a plethora of private and sensitive data. Investigating feasible digital incidents and preserving mobile device security became crucial as the proliferation of mobile devices continues to influence modern society. In this survey; mobile threats, investigative process models for mobile forensics, evidence sources, forensics tools, and field problems are all covered in‐depth. Further, a comprehensive analysis examining the capabilities, features, and efficiency of available distinct mobile forensic tools namely Belkasoft, MOBILedit, and Magnet AXIOM for retrieving, analyzing, and presenting digital evidence is being presented. The objective of the study is to assist forensic investigators in choosing the best tool for specific investigations. The findings of our study reveals the complexity of mobile operating systems, investigative process supported with sources of evidence, and forensic tools which makes it clear that the area of mobile forensics is dynamic and require modern skill adaptation along and innovative development in future. Finally, the study presents current challenges encountered during mobile forensic investigations as researchers can enhance their procedures and tactics for mobile device examination and evidence extraction by fostering a greater knowledge of the difficulties involved in mobile forensics.

Characterizing Performance Tradeoffs from Air Traffic Management Services for Advanced Air Mobility

The emergence of Advanced Air Mobility (AAM) has called for novel Air Traffic Management (ATM) solutions to enable the projected high number of operations, particularly in already dense and complex metroplex airspace. Understanding the multidimensional performance impacts of developing air traffic rules, procedures, and services is key to guiding this new traffic management system design. This paper presents a simulation framework to provide a quantitative assessment of the operational performance of ATM services in support of AAM. The framework embeds several modules for high-fidelity modeling of urban air traffic flows based on actual data, ATM service provision, stochastic simulation, and performance quantification. Two key services are analyzed: airspace geofencing and strategic deconfliction. We evaluate the use of these services in a scenario of air mobility operations associated with daily urban commuting in the Sao Paulo metropolitan region. Monte Carlo experiments are performed to simulate the execution of aircraft trajectories managed under different ATM service configurations, allowing for the characterization of operational performance tradeoffs, particularly in terms of safety and efficiency. The work contributes to quantifying the value of novel ATM services for integrating AAM operations in dense metroplex airspace, supporting their design and implementation.

Third-Party Risk Assessment on the Ground for Urban Air Mobility Operations: A Case Study of Seoul Metropolitan City

Third-Party Risk Assessment on the Ground for Urban Air Mobility Operations: A Case Study of Seoul Metropolitan City

Protecting Judicial Decisions in the Age of Artificial Intelligence A New Challenge to the Rule of Law

In a world where a large percentage of children are learning how to interact expertly with electronic devices and navigate mobile operating systems before they can even speak, and have grown up with the non-existence of the idea of “disconnecting” with the constant flow of content on the screen, it is no longer possible to reject development and adapt to the requirements of the new stage as we are on the brink of the fifth industrial revolution [1] in which artificial intelligence technologies merge with the work of the human element, and robots coexist with humans. Whatever the name given to the next technological era, and whatever the number it will be labeled with, it will be the last era of inventions and discoveries that humans alone will accomplish exclusively. This prompts experts in the field to consider that “merging with artificially intelligent technology will be like learning how to live with a new gender” [2]. In recent years in particular, artificial intelligence technology has achieved remarkable successes that have proven its pioneering capabilities, and the discussion about it has not remained confined to academic circles, but has occupied the front rows in the halls of official decision-making, and competing voices have risen around it from the highest platforms [3]. The contributions of AI technologies to combating the coronavirus pandemic are still fresh in our minds. Robots have been used to reduce human contact; there are nursing robots, delivery robots, surveillance drones, sterilizing robots, and mobile robots that detect infected people on the street. Big data technologies are also being used to examine surveillance cameras on the streets to recognize faces, as happened in China, where an algorithm combines the health record, the criminal file, and the public transport travel map to identify all the people who have been in contact with the infected person, and quarantine him as a result [4]. Because this reality has begun to cast its shadow on the judicial systems with the entry of artificial intelligence systems into the justice sector, imposing its challenges on them, and even throwing its problems in their face, the judicial decision has become facing serious challenges that raise legitimate questions on the research table, the answers to which converge with the strategic direction of Oman Vision 2040 in the field of legislation, judiciary, and oversight in terms of strengthening the rule of law in society and achieving community security, and in general, it addresses the application of the foundations of governance in the organization of legislation and judiciary, and revolves around the extent of the benefit of introducing artificial intelligence systems in the stage of preparing the judicial decision and the limits of this benefit on the one hand (section one), and the extent of the possibility of using these systems in the stage of building the judicial decision itself on the other hand (section two).

Energy-aware bio-inspired spiking reinforcement learning system architecture for real-time autonomous edge applications.

Mobile, low-cost, and energy-aware operation of Artificial Intelligence (AI) computations in smart circuits and autonomous robots will play an important role in the next industrial leap in intelligent automation and assistive devices. Neuromorphic hardware with spiking neural network (SNN) architecture utilizes insights from biological phenomena to offer encouraging solutions. Previous studies have proposed reinforcement learning (RL) models for SNN responses in the rat hippocampus to an environment where rewards depend on the context. The scale of these models matches the scope and capacity of small embedded systems in the framework of Internet-of-Bodies (IoB), autonomous sensor nodes, and other edge applications. Addressing energy-efficient artificial learning problems in such systems enables smart micro-systems with edge intelligence. A novel bio-inspired RL system architecture is presented in this work, leading to significant energy consumption benefits without foregoing real-time autonomous processing and accuracy requirements of the context-dependent task. The hardware architecture successfully models features analogous to synaptic tagging, changes in the exploration schemes, synapse saturation, and spatially localized task-based activation observed in the brain. The design has been synthesized, simulated, and tested on Intel MAX10 Field-Programmable Gate Array (FPGA). The problem-based bio-inspired approach to SNN edge architectural design results in 25X reduction in average power compared to the state-of-the-art for a test with real-time context learning and 30 trials. Furthermore, 940x lower energy consumption is achieved due to improvement in the execution time.

Unpacking Mobile Website Aesthetics and Its Effect: A Case of M-commerce Website Offering Search and Experience Goods

ABSTRACT A major challenge for mobile commerce operators is how to attract customers to access their websites displayed on a mobile device screen only twice the size of a palm, so making design of such websites is especially important in order to catch customers’ eyes. Based on S-O-R model, the study developed a research model to explain how aesthetics of m-commerce websites affects customers’ continuing access to the websites. The model was evaluated through a stratified survey of 285 participants on m-commerce websites with varying levels of mobile website aesthetics. Structural equation modeling (SEM) was utilized to analyze the data. The results uphold the applicability of visual aesthetics (VisAWI) scale in m-commerce, which has significant positive effect on websites’ perceived usability. The study also finds that mobile websites selling experience goods have higher demand for website aesthetics than those for search goods. The study offers a well-structured practical instrument based on visual aesthetics (VisAWI) scale, helping mobile website designers understand the effect of specific aesthetic elements on user behavioral intention.

Simulation-Based Optimization for Vertiport Location Selection: A Surrogate Model With Machine Learning Method

We present Vertiport-informed Surrogate-Based Optimization with Machine Learning Surrogates (VinS), a novel framework for solving the vertiport location problem for urban air mobility operations. The primary focus of this work is on the optimization of vertiport locations to facilitate efficient urban air transportation. Our framework helps choose not only the optimal vertiport locations but also the optimal number of vertiports. We develop a simulation model to analyze the impacts of various vertiport location configurations on the efficiency of the transportation network. To expedite the simulation process, a surrogate model is trained using machine learning algorithms, effectively reducing the computational time for evaluating a given vertiport location configuration. With the machine learning surrogate models, we apply a genetic algorithm to find the optimal set of vertiport locations. An empirical study was performed in the San Francisco Bay Area, from which we found that given the optimal set of vertiport locations, we further reduced the total travel time in the entire transportation system in the Bay Area compared with the sampled sets by 0.05% (400 h) on average. We release our framework at: https://github.com/Xuan-1998/LPSim .

EMPIRICAL STUDY OF SIGNAL STRENGTH PATH LOSS IN A UNIVERSITY CAMPUS ENVIRONMENT

Conducting performance analysis can be a valuable tool for mobile network operators (MNO) in optimizing network performance, improving user experience, and ensuring services, such as voice calls, data transmission, and video streaming, as well as to adhere to quality standards. This approach facilitates capacity planning, resource allocation, and the prompt identification and resolution of network congestion, hardware failures, or security breaches. In this paper, the performance of three MNOs around Papua New Guinea University of Technology (PNGUoT) is examined. The downlink frequency signal was measured and collected using the MST207T spectrum analyzer. The allocated frequency spectrum for each mobile network evolution from 3G to 4G-LTE was analyzed and calculated for signal strength path loss utilizing Free Space Path Loss (FSPL) and the Cost 231 Hata Model methods. 5G is not discussed in this paper as the technology is awaiting PNG market entry approval. The findings indicate that Digicel towers exhibit a decrease in downlink signal intensity and quality in areas with poor signal reception. Certain technical issues were observed to be responsible for the identified poor performances, including overcrowding of base stations (BS). The signal strength qualities of Bmobile Vodafone and Telikom exhibit variations, suggesting a moderate to poor level of quality. The data results from the path loss calculation also show an increase in fading signal strength quality. The findings of this empirical study would provide valuable insights for enhancing the efficiency and coverage of mobile communication networks around PNGUoT.

Creation of a System Taxonomy for Advanced Air Mobility Operations

Advanced Air Mobility (AAM) is an emerging field that envisions highly automated, high-tempo, passenger-carrying aircraft operating in urban environments. Numerous stakeholders have emerged in this space, each proposing unique concepts of operation (CONOPS). While this technology will enable a revolutionary leap in modern transportation, many challenges remain unaddressed. Discrepancies exist between envisioned AAM operations, current technology, and outdated federal regulations. This has led to an unclear vision within the industry of the current maturity level of technology and the path of development needed to achieve proposed CONOPS. We seek to fill this gap by integrating multiple proposed conceptual systems into a single, unified path forward for the field. The literature on AAM covers a diverse array of interconnected themes, each containing a multitude of considerations that require extensive exploration and understanding. In the present work, a literature integration was conducted to collate the numerous proposed concepts and envisioned works that exist within the AAM literature. With this information, a comprehensive AAM taxonomy was created to represent this integration of concepts and rectify the inconsistencies within industry CONOPS. This taxonomy will assist future stakeholders in navigating this intricate field while contributing to the safe and efficient development and deployment of AAM.