Hasil untuk "Cellular telephone services industry. Wireless telephone industry"

Junjun Wu

This study develops a two-element biconical deformed printed dipole omnidirectional antenna comprising a radiating arm, a feed line, and a magnetic ring. The antenna gain is improved by two elements grouped in an array, and at the same time, controlling the feed phase reduces the ground hitting level, effectively suppressing the floor reflection multipath effect. In addition, a magnetic loop is added to the coaxial line for choking, stabilizing the radiation pattern, and achieving good impedance matching. The simulated and measured results demonstrate that the developed antenna achieves 48.2% frequency bandwidth for VSWR ≤ 2, horizontal plane gain ≥ 3 dBi, and unroundness ≤ 3 dB at 1.1–1.8 GHz.

Jiancheng Ye, Michelle Ma, Malak Abuhashish

Objectives: The integration of Artificial Intelligence (AI) in healthcare promises to revolutionize patient care, diagnostics, and treatment protocols. Collaborative efforts among healthcare systems, research institutions, and industry are pivotal to leveraging AI's full potential. This study aims to characterize collaborative networks and stakeholders in AI healthcare initiatives, identify challenges and opportunities within these collaborations, and elucidate priorities for future AI research and development. Methods: This study utilized data from the Chinese Society of Radiology and the Chinese Medical Imaging AI Innovation Alliance. A national cross-sectional survey was conducted in China (N = 5,142) across 31 provincial administrative regions, involving participants from three key groups: clinicians, institution professionals, and industry representatives. The survey explored diverse aspects including current AI usage in healthcare, collaboration dynamics, challenges encountered, and research and development priorities. Results: Findings reveal high interest in AI among clinicians, with a significant gap between interest and actual engagement in development activities. Despite the willingness to share data, progress is hindered by concerns about data privacy and security, and lack of clear industry standards and legal guidelines. Future development interests focus on lesion screening, disease diagnosis, and enhancing clinical workflows. Conclusion: This study highlights an enthusiastic yet cautious approach toward AI in healthcare, characterized by significant barriers that impede effective collaboration and implementation. Recommendations emphasize the need for AI-specific education and training, secure data-sharing frameworks, establishment of clear industry standards, and formation of dedicated AI research departments.

Emily L. Tucker, Mohammadhossein Mohammadisiahroudi

Quantum computing is rapidly emerging as a new computing paradigm with the potential to improve decision-making, optimization, and simulation across industries. For industrial engineering (IE) and operations research (OR), this shift introduces both unprecedented opportunities and substantial challenges. The learning curve is high, and to help researchers navigate the emerging field of quantum operations research, we provide a road map of the current field of quantum operations research. We introduce the foundational principles of quantum computing, outline the current hardware and software landscape, and survey major algorithmic advances relevant to IE/OR, including quantum approaches to linear algebra, optimization, machine learning, and stochastic simulation. We then highlight applied research directions, including the importance of problem domains for driving long-term value of quantum computers and how existing classical OR models can be reformulated for quantum hardware. Recognizing the steep learning curve, we propose pathways for IE/OR researchers to develop technical fluency and engage in this interdisciplinary domain. By bridging theory with application, and emphasizing the interplay between hardware and research development, we argue that industrial engineers are uniquely positioned to shape the trajectory of quantum computing for practical problem-solving. Ultimately, we aim to lower the barrier to entry into quantum computing, motivate new collaborations, and chart future directions where quantum technologies may deliver tangible impact for industry and academia.

James Fant-Male, Roel Pieters

The shift in research focus from Industry 4.0 to Industry 5.0 (I5.0) promises a human-centric workplace, with social and well-being values at the centre of technological implementation. Human-Robot Collaboration (HRC) is a core aspect of I5.0 development, with an increase in adaptive and personalised interactions and behaviours. This review investigates recent advancements towards personalised HRC, where user-centric adaption is key. There is a growing trend for adaptable HRC research, however there lacks a consistent and unified approach. The review highlights key research trends on which personal factors are considered, workcell and interaction design, and adaptive task completion. This raises various key considerations for future developments, particularly around the ethical and regulatory development of personalised systems, which are discussed in detail.

Ronnie de Souza Santos, Maria Teresa Baldassarre, Cesar França

Quantum software testing introduces new challenges that differ fundamentally from those in classical software engineering. Aims: This study investigates how the quantum software industry defines testing roles and what skills are expected from professionals in these positions. Method: We analyzed 110 job postings from organizations involved in quantum software and hardware development, identifying activities, competencies, and skill requirements related to testing. Results: The findings show that testing in quantum contexts combines traditional software quality assurance with experimental validation, emphasizing calibration, control, and hybrid quantum-classical verification. Employers seek professionals who integrate programming and automation expertise with quantum-specific technical knowledge and interdisciplinary collaboration skills. Conclusions: Quantum software testing remains at an early but rapidly evolving stage that bridges software engineering and experimental physics, highlighting the need for educational and research efforts that align testing practices with industrial realities.

Michael Mayr, Georgios C. Chasparis, Josef Küng

Central to the digital transformation of the process industry are Digital Twins (DTs), virtual replicas of physical manufacturing systems that combine sensor data with sophisticated data-based or physics-based models, or a combination thereof, to tackle a variety of industrial-relevant tasks like process monitoring, predictive control or decision support. The backbone of a DT, i.e. the concrete modelling methodologies and architectural frameworks supporting these models, are complex, diverse and evolve fast, necessitating a thorough understanding of the latest state-of-the-art methods and trends to stay on top of a highly competitive market. From a research perspective, despite the high research interest in reviewing various aspects of DTs, structured literature reports specifically focusing on unravelling the utilized learning paradigms (e.g. self-supervised learning) for DT-creation in the process industry are a novel contribution in this field. This study aims to address these gaps by (1) systematically analyzing the modelling methodologies (e.g. Convolutional Neural Network, Encoder-Decoder, Hidden Markov Model) and paradigms (e.g. data-driven, physics-based, hybrid) used for DT-creation; (2) assessing the utilized learning strategies (e.g. supervised, unsupervised, self-supervised); (3) analyzing the type of modelling task (e.g. regression, classification, clustering); and (4) identifying the challenges and research gaps, as well as, discuss potential resolutions provided.

M. Gundall, J. Schneider, H. D. Schotten et al.

The increasing demand for highly customized products, as well as flexible production lines, can be seen as trigger for the "fourth industrial revolution", referred to as "Industrie 4.0". Current systems usually rely on wire-line technologies to connect sensors and actuators. To enable a higher flexibility such as moving robots or drones, these connections need to be replaced by wireless technologies in the future. Furthermore, this facilitates the renewal of brownfield deployments to address Industrie 4.0 requirements. This paper proposes representative use cases, which have been examined in the German Tactile Internet 4.0 (TACNET 4.0) research project. In order to analyze these use cases, this paper identifies the main challenges and requirements of communication networks in Industrie 4.0 and discusses the applicability of 5th generation wireless communication systems (5G).

Ronnie de Souza Santos, Luiz Fernando de Lima, Maria Teresa Baldassarre et al.

Context: This study explores how software professionals identify and address biases in AI systems within the software industry, focusing on practical knowledge and real-world applications. Goal: We aimed to understand the strategies employed by practitioners to manage bias and their implications for fairness debt. Method: We used a qualitative research method, gathering insights from industry professionals through interviews and employing thematic analysis to explore the collected data. Findings: Professionals identify biases through discrepancies in model outputs, demographic inconsistencies, and issues with training data. They address these biases using strategies such as enhanced data management, model adjustments, crisis management, improving team diversity, and ethical analysis. Conclusion: Our paper presents initial evidence on addressing fairness debt and provides a foundation for developing structured guidelines to manage fairness-related issues in AI systems.

Hatef Shamshiri, Ashok Tripathi, Shola Oyedeji et al.

Agile software development is gaining popularity among software developers due to its benefits. As the interest in agile software development grows, there is an increasing focus on investigating sustainability within this field. This study aimed to explore sustainability within agile software development in the Finnish software industry and, through gathered experiences, contribute to the software engineering roadmap 2030. Using an interview approach, we conducted an empirical study within the Finnish software industry to achieve this goal. The findings indicate a growing interest among experts in integrating sustainability into agile software development. The results show that the Scrum methodology is the most popular approach in the Finnish software industry, and addressing different sustainability dimensions can have a ripple effect on each other. The study proposes three key elements to be considered in the software engineering roadmap 2030: integrating sustainability into software engineering education, creating sustainability tools and frameworks, and assessing the energy efficiency of libraries used in software development.

Patrick Mukala

The Information and Communication sector has undoubtedly played a pivotal role in changing the way people live nowadays. Almost every area of our lives is affected by the presence and the use of the new information and communication technologies. In this regard, many researchers' attention has been attracted by the influence or the significant impact of these technologies on economic growth and development. Although the history of South Africa has had some drawbacks that could constitute a big obstacle to the emergence of a successful economic environment, the actual status of the country regarding its economy and the role that it plays in Africa towards the rest of the African countries is a vital example of an emerging economic force in Africa. This paper examines the crucial role that ICT has played and is still playing in the South African economy growth and more specifically the significance of the economic effects of the software industry. It makes use of the framework used by Heavin et al. (2003) to investigate the Irish software industry in order to analyze the impact of endogenous factors -- national, enterprise and individual -- on the software industry and its implication on the economic growth in South Africa.

Timotheus Kampik, Mathias Weske

This paper presents the results of an industry expert survey about event log generation in process mining. It takes academic assumptions as a starting point and elicits practitioner's assessments of statements about process execution, process scoping, process discovery, and process analysis. The results of the survey shed some light on challenges and perspectives around event log generation, as well as on the relationship between process models and process execution, and derive challenges for event log generation from it. The responses indicate that particularly relevant challenges exist around data integration and quality, and that process mining can benefit from a systematic integration with more traditional and wide-spread business intelligence approaches.

Silvan Mertes, Andreas Margraf, Steffen Geinitz et al.

Visual inspection software has become a key factor in the manufacturing industry for quality control and process monitoring. Semantic segmentation models have gained importance since they allow for more precise examination. These models, however, require large image datasets in order to achieve a fair accuracy level. In some cases, training data is sparse or lacks of sufficient annotation, a fact that especially applies to highly specialized production environments. Data augmentation represents a common strategy to extend the dataset. Still, it only varies the image within a narrow range. In this article, a novel strategy is proposed to augment small image datasets. The approach is applied to surface monitoring of carbon fibers, a specific industry use case. We apply two different methods to create binary labels: a problem-tailored trigonometric function and a WGAN model. Afterwards, the labels are translated into color images using pix2pix and used to train a U-Net. The results suggest that the trigonometric function is superior to the WGAN model. However, a precise examination of the resulting images indicate that WGAN and image-to-image translation achieve good segmentation results and only deviate to a small degree from traditional data augmentation. In summary, this study examines an industry application of data synthesization using generative adversarial networks and explores its potential for monitoring systems of production environments. \keywords{Image-to-Image Translation, Carbon Fiber, Data Augmentation, Computer Vision, Industrial Monitoring, Adversarial Learning.

Fangyu Ren, Huotao Gao, Lijuan Yang et al.

This paper establishes a distributed multistatic sky-wave over-the-horizon radar (DMOTHR) model and proposes a semidefinite relaxation positioning (SDP) algorithm to locate marine ship targets. In the DMOTHR, it is difficult to locate the target due to the complexity of the signal path propagation. Therefore, this paper uses the ionosphere as the reflector to convert the propagation path from a polyline to a straight line for establishing the model, and then the SDP algorithm will be used to transform a highly nonlinear positioning optimization problem into a convex optimization problem. Finally, it is concluded through the simulations that the SDP algorithm can obtain better positioning accuracy under a certain Doppler frequency error and ionospheric measurement error.

Silong Wang, Yulong Liu, Terry Tao Ye

UHF RFID tags need to be attached or embedded into various objects. Unlike traditional free-standing antennas, UHF antenna shapes and form factors may vary significantly. There have been no systematic methods that facilitate the design practice of antenna with unconventional shapes. In this paper, using the geometries of 26 English letters (in capital) as examples, we explore the general methodology of shape-specific antenna design. More specifically, we show that 26 letter geometries can be categorized into 9 groups, and the antennas in each group can be divided and conquered into standard baseline geometries. Through prototypes and measurements, we demonstrate that each letter-shaped antenna, although exhibiting different gains and radiations, can achieve satisfactory performance, as compared to standard UHF dipole antennas. Specifically, letters “M” and “J” achieve the longest reading range of more than 20 meters with a good radiation pattern, which is comparable or even better than many commercial UHF RFID tags.

Song Xue, Kaitong Ma, Congsi Wang et al.

The purpose of this paper is to investigate a large radio telescope support point number effect on its pointing accuracy and provide a useful guideline for the large radio telescope design engineer. In a large radio telescope system, the azimuth track is used to support the whole telescope structure and the mounting error as well as the telescope wheel-track contact in a long term can cause unevenness on the azimuth track, which can further deteriorate the telescope pointing accuracy. Even though various compensation methods have been proposed to compensate for this pointing error, it remains as one of the challenges for the telescope pointing error reduction. In this paper, a general telescope pointing error estimation formula has been proposed to investigate different telescope support-point number designs on its pointing accuracy. In this approach, the azimuth track unevenness has been modelled as the Fourier function using the least square method after the raw track profile has been measured. Next, the elevation position matrix, azimuth position matrix, and the azimuth profile matrix can be constructed for different telescope support point numbers, and the telescope pointing error can then be obtained based on the proposed general formula. The telescope pointing error root mean square (RMS) value is used to quantify the effect of the telescope support point number on the pointing accuracy. Two interesting results can be observed in the numerical example. The first one is that the telescope pointing error curves have different dominant peaks during one azimuth track rotation, which is corresponding to the support point number. Another interesting finding is that the RMS value experienced a complex trend with the support point number change, and they are not a simple monotonous increasing or decreasing relationship with the support number. All the results in this paper can provide a useful guideline for reducing the telescope pointing error in the initial design stage.

Peter Fettke, Wolfgang Reisig

Modern and next generation digital infrastructures are technically based on service oriented structures, cloud services, and other architectures that compose large systems from smaller subsystems. The composition of subsystems is particularly challenging, as the subsystems themselves may be represented in different languages, modelling methods, etc. It is quite challenging to precisely conceive, understand, and represent this kind of technology, in particular for a given level of abstraction. To capture refinement and abstraction principles, various forms of "technology stacks" and other semi-formal or natural language based on presentations have been suggested. Generally, useful concepts to compose such systems in a systematic way are even more rare. Heraklit provides means, principles, and unifying techniques to model and to analyze digital infrastructures. Heraklit integrates composition and hierarchies of subsystems, concrete and abstract data structures, as well as descriptions of behaviour. A distinguished set of means supports the modeler to express their ideas. The modeller is free to choose the level of abstraction, as well as the kind of composition. Heraklit integrates new concepts with tried and tested ones. Such a framework provides the foundation for a comprehensive Systems Mining as the next step after Process Mining.

Florian Hofer, Martin Sehr, Alberto Sangiovanni-Vincentelli et al.

Industry 4.0 is changing fundamentally data collection, its storage and analysis in industrial processes, enabling novel application such as flexible manufacturing of highly customized products. Real-time control of these processes, however, has not yet realized its full potential in using the collected data to drive further development. Indeed, typical industrial control systems are tailored to the plant they need to control, making reuse and adaptation a challenge. In the past, the need to solve plant specific problems overshadowed the benefits of physically isolating a control system from its plant. We believe that modern virtualization techniques, specifically application containers, present a unique opportunity to decouple control from plants. This separation permits us to fully realize the potential for highly distributed, and transferable industrial processes even with real-time constraints arising from time-critical sub-processes. In this paper, we explore the challenges and opportunities of shifting industrial control software from dedicated hardware to bare-metal servers or (edge) cloud computing platforms using off-the-shelf technology. We present a migration architecture and show, using a specifically developed orchestration tool, that containerized applications can run on shared resources without compromising scheduled execution within given time constraints. Through latency and computational performance experiments we explore limits of three system setups and summarize lessons learned.

Moonhee Lee, Taeho Son

In this study, a thin coaxial antenna for microwave ablation (MWA) is proposed. A helical slot is added between two slots in order to overcome the disadvantage of the radiation range extending to the unwanted part in the conventional single-slot and double-slot applicators. By adding a helical slot, the specific absorption rate (SAR) pattern is more concentrated near the slot as compared with the conventional slot. Experiments were conducted using the simulation, and a liver phantom was made and heated up using microwaves. Based on the results on the liver phantom, experiments were conducted using swine liver which is similar to human liver. Applied frequency and microwave average input power were assumed as 2.45 GHz and 50 W (47 dBm), respectively. As a result of the experiment, return loss was −23.09 dB, and the temperature reached 60°C after 90 seconds of exposition. Based on the phantom experiments of the swine liver, necrotic lesions of the tissue at a distance of 3.5–4 cm from the microwave antenna were observed.

Irem Bor-Yaliniz, Amr El-Keyi, Halim Yanikomeroglu

Agile networking can reduce over-engineering, costs, and energy waste. Towards that end, it is vital to exploit all degrees of freedom of wireless networks efficiently, so that service quality is not sacrificed. In order to reap the benefits of flexible networking, we propose a spatial network configuration scheme (SNC), which can result in efficient networking; both from the perspective of network capacity, and profitability. First, SNC utilizes the drone-base-stations (drone-BSs) to configure access points. Drone-BSs are shifting paradigms of heterogeneous wireless networks by providing radically flexible deployment opportunities. On the other hand, their limited endurance and potential high cost increase the importance of utilizing drone-BSs efficiently. Therefore, secondly, user mobility is exploited via user-in-the-loop (UIL), which aims at influencing users' mobility by offering incentives. The proposed uncoordinated SNC is a computationally efficient method, yet, it may be insufficient to exploit the synergy between drone-BSs and UIL. Hence, we propose joint SNC, which increases the performance gain along with the computational cost. Finally, semi-joint SNC combines benefits of joint SNC, with computational efficiency. Numerical results show that semi-joint SNC is two orders of magnitude times faster than joint SNC, and more than 15 percent profit can be obtained compared to conventional systems.

Rémi Brageu

Dans le monde de la muséographie, la photogrammétrie (Réf 1 et 2) remporte de plus en plus de succès. C'est en effet une méthode qui permet d'obtenir, assez simplement, une représentation en trois dimensions d'un objet, que celui-ci soit très lourd, très imposant, très petit ou extrêmement fragile. Le matériau constitutif de l'objet muséal, qu'ils soient de bois, d'or, de cristal ou de plumes, pose beaucoup moins de souci quant à sa reproduction