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

Ming-An Chung, Chia-Wei Lin, Chih-Wei Yang

The paper presents a substrate-integrated waveguide array antenna with power divider structure. The antenna is composed of four mirrored inverted triangular slotted antennas, which allow the radiation pattern to converge. The SIW array antennas with this power divider structure have the same radiation field pattern, reflection coefficient, simulation results, and measurement results. The frequency band covers 28.4–29.8 GHz. The substrate is Rogers RT5880 with an antenna size of 36 × 46 mm. Considering the application of millimeter-wave antennas in wearable devices in the future, the evaluation of the electromagnetic energy absorption ratio complies with the specifications formulated by the Federal Communications Commission. The 11.6-dBi peak main beam gain and good directivity of the radiating field pattern make this antenna very competitive for applications in the n257 and partial coverage of the upper n261 band 1.

Gauthier Roussilhe, Thibault Pirson, David Bol et al.

Growing attention is given to the environmental impacts of the digital sector, exacerbated by the increase of digital products and services in our globalized societies. The materiality of the digital sector is often presented through the environmental impacts of mining activities to point out that digitization does not mean dematerialization. Despite its importance, such a narrative is often restricted to a few minerals (e.g., cobalt, lithium) that have become the symbols of extractive industries. In this paper, we further explore the materiality of the digital sector with an approach based on the diversity of elements and their purity requirements in the semiconductor industry. Semiconductors are responsible for manufacturing the key building blocks of the digital sector, i.e., microchips. Given that the need for ultra-high purity materials is very specific to the semiconductor industry, a few companies around the world have been studied, revealing new critical actors in complex supply chains. This highlights strong dependencies towards other industrial sectors with mass production and the need for a deeper investigation of interactions with the chemical industry, complementary to the mining industry.

Hanqiao Zhang

Neighborhood characteristics have been broadly studied with different firm behaviors, e.g. birth, entry, expansion, and survival, except for firm exit. Using a novel dataset of foreign-invested enterprises operating in Shenzhen's electronics manufacturing industry from 2017 to 2021, I investigate the spillover effects of firm exits on other firms in the vicinity, from both the industry group and the industry class level. Significant neighborhood effects are identified for the industry group level, but not the industry class level.

Tierui Gong, Aveek Chandra, Chau Yuen et al.

The Rydberg atomic quantum receivers (RAQR) are emerging quantum precision sensing platforms designed for receiving radio frequency (RF) signals. It relies on creation of Rydberg atoms from normal atoms by exciting one or more electrons to a very high energy level, thereby making the atom sensitive to RF signals. RAQRs realize RF-to-optical conversions based on light-atom interactions relying on the so called electromagnetically induced transparency (EIT) and Aulter-Townes splitting (ATS), so that the desired RF signal can be read out optically. The large dipole moments of Rydberg atoms associated with rich choices of Rydberg states and various modulation schemes facilitate an ultra-high sensitivity ($\sim$ nV/cm/$\sqrt{\text{Hz}}$) and an ultra-broadband tunability (direct-current to Terahertz). RAQRs also exhibit compelling scalability and lend themselves to the construction of innovative, compact receivers. Initial experimental studies have demonstrated their capabilities in classical wireless communications and sensing. To fully harness their potential in a wide variety of applications, we commence by outlining the underlying fundamentals of Rydberg atoms, followed by the principles and schemes of RAQRs. Then, we overview the state-of-the-art studies from both physics and communication societies. Furthermore, we conceive Rydberg atomic quantum single-input single-output (RAQ-SISO) and multiple-input multiple-output (RAQ-MIMO) schemes for facilitating the integration of RAQRs with classical wireless systems. Finally, we conclude with a set of potent research directions.

Bohang Zhang, Zhaoujun Nan, Sheng Zhou et al.

The introduction of 5G has changed the wireless communication industry. Whereas previous generations of cellular technology are mainly based on communication for people, the wireless industry is discovering that 5G may be an era of communications that is mainly focused on machine-to-machine communication. The application of Ultra Reliable Low Latency Communication in factory automation is an area of great interest as it unlocks potential applications that traditional wired communications did not allow. In particular, the decrease in the inter-device distance has led to the discussion of coding schemes for these interference-filled channels. To meet the latency and accuracy requirements of URLLC, Non-orthogonal multiple access has been proposed but it comes with associated challenges. In order to combat the issue of interference, an enhanced version of Sliding window superposition coding has been proposed as a method of coding that yields performance gains in scenarios with high interference. This paper examines the abilities of this coding scheme in a broadcast network in 5G to evaluate its robustness in situations where interference is treated as noise in a factory automation setting. This work shows improvements of enhanced sliding window superposition coding over benchmark protocols in the high-reliability requirement regions of block error rates $\approx 10^{-6}$.

Giovanni Morrone, Samuele Cornell, Luca Serafini et al.

Recent works show that speech separation guided diarization (SSGD) is an increasingly promising direction, mainly thanks to the recent progress in speech separation. It performs diarization by first separating the speakers and then applying voice activity detection (VAD) on each separated stream. In this work we conduct an in-depth study of SSGD in the conversational telephone speech (CTS) domain, focusing mainly on low-latency streaming diarization applications. We consider three state-of-the-art speech separation (SSep) algorithms and study their performance both in online and offline scenarios, considering non-causal and causal implementations as well as continuous SSep (CSS) windowed inference. We compare different SSGD algorithms on two widely used CTS datasets: CALLHOME and Fisher Corpus (Part 1 and 2) and evaluate both separation and diarization performance. To improve performance, a novel, causal and computationally efficient leakage removal algorithm is proposed, which significantly decreases false alarms. We also explore, for the first time, fully end-to-end SSGD integration between SSep and VAD modules. Crucially, this enables fine-tuning on real-world data for which oracle speakers sources are not available. In particular, our best model achieves 8.8% DER on CALLHOME, which outperforms the current state-of-the-art end-to-end neural diarization model, despite being trained on an order of magnitude less data and having significantly lower latency, i.e., 0.1 vs. 1 s. Finally, we also show that the separated signals can be readily used also for automatic speech recognition, reaching performance close to using oracle sources in some configurations.

Pierre Béaur, Jarkko Kari

Many decision problems concerning cellular automata are known to be decidable in the case of algebraic cellular automata, that is, when the state set has an algebraic structure and the automaton acts as a morphism. The most studied cases include finite fields, finite commutative rings and finite commutative groups. In this paper, we provide methods to generalize these results to the broader case of group cellular automata, that is, the case where the state set is a finite (possibly non-commutative) finite group. The configuration space is not even necessarily the full shift but a subshift -- called a group shift -- that is a subgroup of the full shift on Z^d, for any number d of dimensions. We show, in particular, that injectivity, surjectivity, equicontinuity, sensitivity and nilpotency are decidable for group cellular automata, and non-transitivity is semi-decidable. Injectivity always implies surjectivity, and jointly periodic points are dense in the limit set. The Moore direction of the Garden-of-Eden theorem holds for all group cellular automata, while the Myhill direction fails in some cases. The proofs are based on effective projection operations on group shifts that are, in particular, applied on the set of valid space-time diagrams of group cellular automata. This allows one to effectively construct the traces and the limit sets of group cellular automata. A preliminary version of this work was presented at the conference Mathematical Foundations of Computer Science 2020.

Peng Chen, Dan Wang, Lu Liu et al.

In this paper, a wearable ultra-wideband (UWB) microstrip antenna is designed to meet the demand for Wireless Body Area Network (WBAN). This is a wearable textile antenna, which was formed on a jeans fabric substrate to reduce surface-wave losses. The single-fed circular strip monopole antenna provides good impedance matching over the entire UWB frequency range of 2.9∼10.6 GHz. The dielectric constant εr  = 2.2, and the loss tangent tan  δ  = 0.04 of the jean substrates are measured by using the coaxial ring method. The proposed antenna consists of an improved circular radiation patch with the defective ground structure to expand the frequency band of the antenna and improve the radiation characteristics of the antenna with small dimensions of 20×30×1.4 mm3. In addition, structural deformation of the proposed antenna is performed to analyze the flexibility of the proposed antenna. The simulated SAR values follow the FCC limit, making it most suitable for wearable applications.

Xiaohang Zhao, Xiao Fang, Jing He et al.

Industry assignment, which assigns firms to industries according to a predefined Industry Classification System (ICS), is fundamental to a large number of critical business practices, ranging from operations and strategic decision making by firms to economic analyses by government agencies. Three types of expert knowledge are essential to effective industry assignment: definition-based knowledge (i.e., expert definitions of each industry), structure-based knowledge (i.e., structural relationships among industries as specified in an ICS), and assignment-based knowledge (i.e., prior firm-industry assignments performed by domain experts). Existing industry assignment methods utilize only assignment-based knowledge to learn a model that classifies unassigned firms to industries, and overlook definition-based and structure-based knowledge. Moreover, these methods only consider which industry a firm has been assigned to, but ignore the time-specificity of assignment-based knowledge, i.e., when the assignment occurs. To address the limitations of existing methods, we propose a novel deep learning-based method that not only seamlessly integrates the three types of knowledge for industry assignment but also takes the time-specificity of assignment-based knowledge into account. Methodologically, our method features two innovations: dynamic industry representation and hierarchical assignment. The former represents an industry as a sequence of time-specific vectors by integrating the three types of knowledge through our proposed temporal and spatial aggregation mechanisms. The latter takes industry and firm representations as inputs, computes the probability of assigning a firm to different industries, and assigns the firm to the industry with the highest probability.

Jürgen Dobaj, Andreas Riel, Georg Macher et al.

Industrial Product-Service Systems (IPSS) are increasingly dominant in several sectors. Predominant value-adding services provided for industrial assets such as production systems, electric power plants, and car fleets are remote asset maintenance, monitoring, control, and reconfiguration. IPSS designers lack methods and tools supporting them in systematically deriving technical design requirements for the underlying Cyber-Physical System (CPS) IPSS services. At the same time, the use of Digital Twins (DTs) as digital representations of CPS as-sets is becoming increasingly feasible thanks to powerful, networked information technology (IT) and operation technology (OT) infrastructures and the ubiquity of sensors and data. This paper proposes a method for guiding IPSS designers in the specification and implementation of DT instances to serve as the key enablers of IPSS services. The systematic mapping of the continuous IT design-build-deployment cycle concept to the OT domain of CPS is at the heart of the applied methodology, which is complemented by a stakeholder-driven requirements elicitation. The key contribution is a structured method for deriving technical design requirements for DT instances as IPSS. This method is validated on real-world use cases in an evaluation environment for distributed CPS IPSS.

Man Zhang, Andrea Arcuri, Yonggang Li et al.

With several microservice architectures comprising of thousands of web services, used to serve 630 million customers, companies like Meituan face several challenges in the verification and validation of their software. This paper reports on our experience of integrating EvoMaster (a search-based white-box fuzzer) in the testing processes at Meituan over almost 2 years. Two user studies were carried out in 2021 and in 2023 to evaluate two versions of EvoMaster, respectively, in tackling the test generation for industrial web services which are parts of a large e-commerce microservice system. The two user studies involve in total 321,131 lines of code from five APIs and 27 industrial participants at Meituan. Questionnaires and interviews were carried out in both user studies with employees at Meituan. The two user studies demonstrate clear advantages of EvoMaster (i.e., code coverage and fault detection) and the urgent need to have such a fuzzer in industrial microservices testing. To study how these results could generalize, a follow up user study was done in 2024 with five engineers in the five different companies. Our results show that, besides their clear usefulness, there are still many critical challenges that the research community needs to investigate to improve performance further.

Jason Ceci, Jonah Stegman, Hassan Khan

Electronics repair and service providers offer a range of services to computing device owners across North America -- from software installation to hardware repair. Device owners obtain these services and leave their device along with their access credentials at the mercy of technicians, which leads to privacy concerns for owners' personal data. We conduct a comprehensive four-part study to measure the state of privacy in the electronics repair industry. First, through a field study with 18 service providers, we uncover that most service providers do not have any privacy policy or controls to safeguard device owners' personal data from snooping by technicians. Second, we drop rigged devices for repair at 16 service providers and collect data on widespread privacy violations by technicians, including snooping on personal data, copying data off the device, and removing tracks of snooping activities. Third, we conduct an online survey (n=112) to collect data on customers' experiences when getting devices repaired. Fourth, we invite a subset of survey respondents (n=30) for semi-structured interviews to establish a deeper understanding of their experiences and identify potential solutions to curtail privacy violations by technicians. We apply our findings to discuss possible controls and actions different stakeholders and regulatory agencies should take to improve the state of privacy in the repair industry.

Yongzhi Yu, Jianming Wang, Limin Guo

The massive multiple-input multiple-output (MIMO) technology is one of the core technologies of 5G, which can significantly improve spectral efficiency. Because of the large number of massive MIMO antennas, the computational complexity of detection has increased significantly, which poses a significant challenge to traditional detection algorithms. However, the use of deep learning for massive MIMO detection can achieve a high degree of computational parallelism, and deep learning constitutes an important technical approach for solving the signal detection problem. This paper proposes a deep neural network for massive MIMO detection, named Multisegment Mapping Network (MsNet). MsNet is obtained by optimizing the prior detection networks that are termed as DetNet and ScNet. MsNet further simplifies the sparse connection structure and reduces network complexity, which also changes the coefficients of the residual structure in the network into trainable variables. In addition, this paper designs an activation function to improve the performance of massive MIMO detection in high-order modulation scenarios. The simulation results show that MsNet has better symbol error rate (SER) performance and both computational complexity and the number of training parameters are significantly reduced.

Yi Liu, Qi Qi, Xinyuan Cao et al.

To efficiently solve the electromagnetic scattering problems over a wide incident angle, a novel scheme by introducing the two-dimensional compressive sensing theory into the wavelet method of moments is proposed. In this scheme, a linear system of equations with multiple right-hand sides in wavelet domain is formed firstly, and one side of the bilateral sparse transform to the induced current matrix is simultaneously accomplished and then the bilateral measurement of the induced current matrix is operated by the linear superposition of the right-hand side vectors a few times and the extraction of rows from the impedance matrix. Finally, after completing the other side of the bilateral sparse transform, the wide-angle problems can be solved rapidly by two times of recovery algorithm with prior knowledge. The basic principle is elaborated in detail, and the effectiveness is demonstrated by numerical experiments.

Anandlogesh R R, Breasha Gupta, Divika Agarwal et al.

The story of the Chemical Industry in India is one of outperformance and promise. A consistent value creator, the chemical industry remains an attractive hub of opportunities, even in an environment of global uncertainty. This paper aims to analyze the various driving factors, the performance of the key players over fundamental analysis, and the various trends that would shape the performance of the industry due to the various geopolitical and macroeconomic trends in the post-pandemic world.

Furqan Jameel, Muhammad Awais Javed, Sherali Zeadally et al.

Cellular vehicle-to-everything (V2X) communication is expected to herald the age of autonomous vehicles in the coming years. With the integration of blockchain in such networks, information of all granularity levels, from complete blocks to individual transactions, would be accessible to vehicles at any time. Specifically, the blockchain technology is expected to improve the security, immutability, and decentralization of cellular V2X communication through smart contract and distributed ledgers. Although blockchain-based cellular V2X networks hold promise, many challenges need to be addressed to enable the future interoperability and accessibility of such large-scale platforms. One such challenge is the offloading of mining tasks in cellular V2X networks. While transportation authorities may try to balance the network mining load, the vehicles may select the nearest mining clusters to offload a task. This may cause congestion and disproportionate use of vehicular network resources. To address this issue, we propose a game-theoretic approach for balancing the load at mining clusters while maintaining fairness among offloading vehicles. Keeping in mind the low-latency requirements of vehicles, we consider a finite channel blocklength transmission which is more practical compared to the use of infinite blocklength codes. The simulation results obtained with our proposed offloading framework show improved performance over the conventional nearest mining cluster selection technique.

D. Cox

Huiliang Jin, Jianhui Huang, Qian Ye et al.

The efficiency of a reflector antenna highly depends on its surface shape. In order to ensure a good convergence, the conventional phase retrieval based shape detection schemes require that several far-field intensities be scanned, focused, or defocused. For large reflector antennas, the scanning process is time consuming. This paper proposes a new shape detection method that requires only single far-field intensity. Unlike existing shape detection methods, it retrieves both the amplitude and the phase, based on the fact that a deformed shape causes change not only in the aperture phase but also in the aperture amplitude. Through even-odd decomposition analysis, it is found that in the case of small and smooth deformation, “odd-phase” and “even-amplitude” can be directly recovered from one focused far-field intensity. This leads to the recovery of both the odd and the even parts of the antenna surface shape simultaneously. By combining amplitude retrieval and phase retrieval, this work achieves for the first time the shape detection with only one scan.

Lu Bai, Chenglie Du

Based on multisource wireless signal fusion technology, the autonomous positioning systems of robots have been widely employed. How to design a compact compostable antenna array for indoor robot positioning is still a problem. In this study, we proposed a compact ultrathin antenna unit that effectively reduces the mutual coupling between any adjacent units, while covering most of the existing communication bands, including 2G/3G/4G/Wi-Fi, which will greatly reduce the size of the positioning antenna array. The proposed antenna system has been employed for positioning purpose with high-gain, wide-frequency band and limited size. It necessarily improves the accuracy of positioning signal from various unknown sources and finally accomplishes its autonomous positioning function.

Markus Pagitz

This postdoctoral thesis starts by reviewing the historic development of airplane structures and high lift devices from an engineering point of view. However, the main purpose of this document is the development of a novel concept for shape changing, gapless high lift devices that is inspired by the nastic movement of plants. A particular focus is put on the efficient simulation and optimization of compliant pressure actuated cellular structures.