Hasil untuk "Telecommunication"

Dragoş Niculescu, Badri Nath

Editorial Foreword

The Young Transportation Engineers Conference 2024 was held in Prague, in November 28, 2024. The conference is focused on the presentation of scientific and research work of PhD students and young scientists not only from Czech Technical University in Prague, Faculty of Transportation Sciences. The main objectives of the conference are to present the results of scientific and research activities of PhD students, to raise awareness of ongoing or upcoming research projects within the Faculty of Transportation Sciences and to provide an opportunity to gain experience in presenting in front of a professionally educated audience for newl PhD students. The conference is thus an opportunity to establish new or increase existing personal and professional contacts and a meeting place for doctoral students, practitioners and faculty staff. The conference key topics were following: • transport infrastructure, • transport and vehicle safety, • logistics, • transport economics and management, • information and telecommunication technologies in transport, • air transport operations and management. Scientific comittee: Tomáš Tichý Luboš Nouzovský Martin Jacura Tomáš Doktor Petr Kumpošt Stanislav Novotný Zdeněk Svatý Michal Belák Local organizing comittee: Petr Richter Tomáš Kohout Michal Drábek Jiří Růžička Jan Kruntorád Petr Had Josef Svoboda Veronika Drechslerová Petr Miloslav Kubíska Guarantor of the peer review process: Petr Richter Guarantor of the language editing: Tomáš Kohout

WU Zhenyu, ZHAO Zhanjun, BU Zhonggui et al.

The construction of artificial intelligence inference centers has become a hotspot in the current development of intelligent computing centers. Evaluating the inference business capability of intelligent computing centers solely based on the scale of intelligent computing power is no longer accurate. A quantitative evaluation method for the inference business capability of intelligent computing centers was proposed by establishing three models: a delay-insensitive business model, a delay-sensitive business model, and a user access business model. This approach aims to achieve alignment between construction and requirements during the construction phase, thereby improving investment efficiency.

Md. Fazlul Karim Khondakar, Md. Hasib Sarowar, Mehdi Hasan Chowdhury et al.

Abstract Neuromarketing is an emerging research field that aims to understand consumers’ decision-making processes when choosing which product to buy. This information is highly sought after by businesses looking to improve their marketing strategies by understanding what leaves a positive or negative impression on consumers. It has the potential to revolutionize the marketing industry by enabling companies to offer engaging experiences, create more effective advertisements, avoid the wrong marketing strategies, and ultimately save millions of dollars for businesses. Therefore, good documentation is necessary to capture the current research situation in this vital sector. In this article, we present a systematic review of EEG-based Neuromarketing. We aim to shed light on the research trends, technical scopes, and potential opportunities in this field. We reviewed recent publications from valid databases and divided the popular research topics in Neuromarketing into five clusters to present the current research trend in this field. We also discuss the brain regions that are activated when making purchase decisions and their relevance to Neuromarketing applications. The article provides appropriate illustrations of marketing stimuli that can elicit authentic impressions from consumers' minds, the techniques used to process and analyze recorded brain data, and the current strategies employed to interpret the data. Finally, we offer recommendations to upcoming researchers to help them investigate the possibilities in this area more efficiently in the future.

Liangwei Qi, Jingke Zhang, Zong-Feng Qi et al.

Abstract With the development of modern electronic countermeasure technology, the fight between radar jamming and anti-jamming has become increasingly fierce. Experts have done a lot of highly effective work on radar anti-jamming performance. However, the emergence of various new complex interferences has rendered existing methods unable to meet the needs. In this manuscript, we consider the measurement and evaluation method of radar anti-jamming effectiveness based on principal component analysis and machine learning. Firstly, taking into account the diversity of variables in radar countermeasure experiments and the complexity of constraints between variables, we propose a bipartite covering array for the experimental scheme, which requires that each level combination of any radar parameter and jammer parameter occurs at least once, to ensure the rationality of the experiments. Secondly, according to the characteristics of multiple jammers and the analysis of impacts on radar performances, we combine the existing indicators and use the principal component analysis method to obtain two comprehensive indicators, which better reflect radar performances. Finally, we select the best model as a prediction for radar comprehensive indicators by comparing several machine learning algorithm models, including classification and regression tree, random forest, xgboost, and SVM. Additional experiments verify the effectiveness of the resulted model.

Xuerong Cui, Peihao Yan, Juan Li et al.

Abstract Due to the time-varying and space-varying characteristics of the underwater acoustic channel, the communication process may be seriously disturbed. Thus, the underwater acoustic communication system is facing the challenges of alleviating interference and improving communication quality and communication efficiency through adaptive modulation. In order to select the optimal modulation mode adaptively and maximize the system throughput ensuring that the bit error rate (BER) meets the transmission requirements, this paper introduces deep reinforcement learning (DRL) into orthogonal frequency division multiplexing acoustic communication system. The adaptive modulation is mapped into a Markov decision process with unknown state transition probability. Thereby, the underwater communication channel environment is regarded as the state of DRL, and the modulation mode is regarded as action. The system returns channel state information (CSI) and signal–noise ratio in every time slot through the feedback link. Because the Deep Q-Network optimizes in the changing state space of each time slot, it is suitable for a variety of different CSI. Finally, simulations in different underwater environments (SWellEx-96) show that the proposed adaptive modulation scheme can obtain lower BER and improve the system throughput effectively.

Manuel Sandoval-Barrantes, José Roberto Vega-Baudrit, Gilberto Piedra-Marín et al.

[Objective] From 1988 to 2018, high school students in Costa Rica had to pass a final exam to graduate from high school and be eligible for public university education. In this context, students had to choose a national science test from the areas of physics, chemistry, and biology. Historically, chemistry was the least chosen (4-6 %) of those sciences. On the other hand, there is a need -at the national level- to increase interest in careers related to STEM (Sciences, technology, engineering, and mathematics). [Methodology] Under both premises, in 2016, the first national camp (called Quimi Camp) to promote scientific vocations was held to encourage high school students in Costa Rica to choose chemistry. Quimi Camp is an event supported by the OLCOQUIM National Chemistry Olympiad and the OLCOCI National Science Olympiad, which are in turn organized by the five Costa Rican State universities and the LANOTEC CENAT National Nanotechnology Laboratory at the National Center of High Technology, with the consent of the Ministry of Education (MEP) and the Ministry of Science, Innovation, Technology and Telecommunication (MICITT). The participating students made the final evaluation of this event. [Results] The results showed an excellent perception of the event regarding its organization and content. [Conclusions] Quimi Camp promoted students' vocation for science and engineering and positively influenced the selection of a University Career in STEM.

Yong ZHANG, Dandan LI, Lu HAN et al.

To solve the problem that data privacy leakage of participants under the crowd-sensed data trading model, a privacy-protected crowd-sensed data trading algorithm was proposed.Firstly, to achieve the privacy protection of participants, an aggregation scheme based on differential privacy was designed.Participants were no longer needed to upload raw data, but analyzed and calculated the collected data according to the task requirements, and then sent the analysis results to the platform after adding noise in accordance with the privacy budget allocated by the platform to protect their privacy.Secondly, in order to ensure the credibility of participants, a reputation model of participants was proposed.Finally, in order to encourage consumers and participants to participate in transactions, a data trading optimization model was constructed by considering the consumer’s constraint on the result deviation，the participant’s privacy leakage compensation and platform profit, and a POA based on genetic algorithm was proposed to solve the model.The simulation results show that the POA not only protects the privacy of participants, but also increases the profit of the platform by 29.27% and 20.45% compared to VENUS and DPDT, respectively.

Maryam Imani

Abstract There are two types of important information in a polarimetric synthetic aperture radar (PolSAR) image: spatial features in two dimensions and polarimetric characteristics in the scattering dimension. Considering both polarimetric and spatial information is important for PolSAR image classification. Convolutional kernels show superior performance for extraction of spatial information from two dimensions of an image in convolutional neural networks (CNNs). But learning CNNs needs large enough training sets to achieve the optimum weights of kernels while there are not usually sufficient training samples for PolSAR images. To deal with this difficulty, a convolutional kernel‐based covariance descriptor (CKCD) is introduced for PolSAR image classification in this study. To extract contextual characteristics, compatible with the original image, the fixed‐valued convolutional kernels randomly selected from the image are used, which do not require any learning, and so do not need any training samples. To include more local spatial information and find the relation among the polarimetric features, the covariance descriptor is constructed on the extracted feature maps. Then, the polarimetric‐contextual features are given to a support vector machine with a matrix logarithm‐based kernel. Finally, the guided filter is applied to the initial classification map to result a smoothed classification map with preserved edges. The experiments on three real PolSAR images show superiority of the proposed CKCD method compared to several PolSAR classification methods such as 2DCNN and 3DCNN in small sample size situations.

Tomasz P. Zieliński

Zhiwen Xiong

Abstract Machine learning is a branch of the field of artificial intelligence. Deep learning is a complex machine learning algorithm that has unique advantages in image recognition, speech recognition, natural language processing, and industrial process control. Deep learning has It is widely used in the field of wireless communication. Prediction of geological disasters (such as landslides) is currently a difficult problem. Because landslides are difficult to detect in the early stage, this paper proposes a GPS-based wireless communication continuous detection system and applies it to landslide deformation monitoring to achieve early treatment and prevention. This article introduces the GPS multi-antenna detection system based on deep learning wireless communication, and introduces the time series analysis method and its application. The test results show that the GPS multi-antenna detection system of the wireless communication network has great advantages in response time, with high accuracy and small error. The horizontal accuracy is controlled at 0–2 mm and the vertical accuracy is about 1 mm. The analysis method is simple and efficient, and can obtain good results for short-term deformation prediction.

Marcin Waniek, Kai Zhou, Yevgeniy Vorobeychik et al.

Abstract Our private connections can be exposed by link prediction algorithms. To date, this threat has only been addressed from the perspective of a central authority, completely neglecting the possibility that members of the social network can themselves mitigate such threats. We fill this gap by studying how an individual can rewire her own network neighborhood to hide her sensitive relationships. We prove that the optimization problem faced by such an individual is NP-complete, meaning that any attempt to identify an optimal way to hide one’s relationships is futile. Based on this, we shift our attention towards developing effective, albeit not optimal, heuristics that are readily-applicable by users of existing social media platforms to conceal any connections they deem sensitive. Our empirical evaluation reveals that it is more beneficial to focus on “unfriending” carefully-chosen individuals rather than befriending new ones. In fact, by avoiding communication with just 5 individuals, it is possible for one to hide some of her relationships in a massive, real-life telecommunication network, consisting of 829,725 phone calls between 248,763 individuals. Our analysis also shows that link prediction algorithms are more susceptible to manipulation in smaller and denser networks. Evaluating the error vs. attack tolerance of link prediction algorithms reveals that rewiring connections randomly may end up exposing one’s sensitive relationships, highlighting the importance of the strategic aspect. In an age where personal relationships continue to leave digital traces, our results empower the general public to proactively protect their private relationships.

Yefei CHEN, Xuejun ZHANG, Weidong HUANG

The current researches of evolution model mainly focus on the spread of the individual topics,rarely considering the influential factors between multiple topics.A new topic evolution model was proposed by considering the interference among topics based on SIR model,which characterized by the influence of the similarity of the topic on the probability of propagation.The experimental results show that within the critical value,the similarity degree of positive and negative trends enhance or hinder the process of topic evolution,and the degree of action varies with the degree of interference nodes,which is expressed as evolutionary consistency under positive similarity and the evolutionary separability under negative similarity.When the critical value is exceeded,the effect of strengthening or hindering tends to saturation.

Alberto de Jesús Díaz Ortíz, Alejandro Jesús Morales Pérez

Los avances tecnológicos que en la actualidad surgen en busca de la satisfacción de necesidades científicas y técnicas, ayudan al ser humano a delegar actividades minimizando costos, trabajo, tiempos, y calidad, entre otros. La tecnología cambia el estilo de vida de las personas e incluso crea nuevas necesidades que ella misma pretende cubrir. La creación de múltiples sistemas que automatizan procesos requiere de un control centralizado que ahorre recursos además de un monitoreo constante que permita obtener información de su funcionalidad. Por esta razón surge un proyecto en respuesta a la necesidad de controlar a través de un mismo sistema, algunas aplicaciones de domótica que respondan a la suma de microcontroladores no importando la familia a la que pertenezcan. Este sistema utiliza el ATMEGA16 y el DS80C400, el primero le da a cualquier sistema la posibilidad de manipularlo localmente y el segundo amplia las capacidades incluyendo la manipulación remota. Entre ambos microcontroladores debe existir comunicación por medio de un bus, en este caso el bus SPI incluido en ambos dispositivos.

Blerta Dragusha (Spahija), Elez Osmani

Foreign direct investments are very important for the implementation of strategic reforms, transfer of advanced technologies and managerial methods, thereby stimulating economic growth in developing countries and in particular, transition economies such as Albania is. During the last years, Albania experienced an increase in foreign investors’ interest in a wide range of sectors, with energy generation, telecommunication, cement production, mining, oil and industrial parks heading the list. However, the major obstacle factors for FDI inflows seem to remain the same: pervasive corruption, weak law enforcement, poor rule of law, lack of developed infrastructure, lack of a reliable energy supply and insufficiently defined property rights. Determining the factors that attract FDI, and furthermore identify the main characteristics of the host country’s economy, are essential to understand the reason of FDI inflows to a country or region. In the empirical perspective, various studies give different results. More specifically, this paper has focused on determining the factors for and against FDI in Albania.

Zhen Yang, Minjie Xu, Zhangfeng Liu et al.

As the major part of big data research, the audio frequency's value has not been discovered. The features of big data, and the automatic speech recognition（ASR）technology were studied, and the value was mined through the method that combined with the two technologies. Finally, the application development technical architecture and application process of audio frequency which combined with big data were given.

YANG Pin-lu, HU Ai-qun

In order to reduce the peak-to-average power ratio（PAPR） of orthogonal frequency division multiplexing（OFDM） signals,a piecewise-linear companding transform was proposed.Small amplitudes were multiplied by a scale factor,while large ones were not only multiplied by a scale factor but also added by a shift.The resulting companding transform was piecewise-linear and continuous.It can provide significant PAPR reduction performance with low compu-tational complexity,and has low influence on system performances through piecewise transform.It is shown by theoreti-cal analysis and simulation that,a good trade-off between PAPR reduction and bit-error-rate performances can be achieved by carefully choosing the two scales and the shift.Furthermore,compared with existing linear and nonlinear companding transforms,a better power spectral density performance can be achieved.

Gesbert David, Papadogiannis Agisilaos, Hardouin Eric

<p/> <p>Multicell cooperative processing (MCP) has the potential to boost spectral efficiency and improve fairness of cellular systems. However the typical centralised conception for MCP incurs significant infrastructural overheads which increase the system costs and hinder the practical implementation of MCP. In Frequency Division Duplexing systems each user feeds back its Channel State Information (CSI) only to one Base Station (BS). Therefore collaborating BSs need to be interconnected via low-latency backhaul links, and a Control Unit is necessary in order to gather user CSI, perform scheduling, and coordinate transmission. In this paper a new framework is proposed that allows MCP on the downlink while circumventing the aforementioned costly modifications on the existing infrastructure of cellular systems. Each MS feeds back its CSI to all collaborating BSs, and the needed operations of user scheduling and signal processing are performed in a distributed fashion by the involved BSs. Furthermore the proposed framework is shown to be robust against feedback errors when quantized CSI feedback and linear precoding are employed.</p>

ZHAO Yi, LIU Yuan-an, ZENG Ling-kang et al.

A novel resource allocation algorithm was proposed for dirty-paper coded multi-user multiple-input multi-ple-output （MIMO）-orthogonal frequency division multiplexing （OFDM） systems. The new algorithm can guarantee the proportional fairness among users while achieving large system throughput by local search. Simulation results show that the proposed algorithm provides great fairness among users,with less overall system throughput loss.

Eric Rosenberg