This paper describes a database designed to evaluate the performance of speech recognition algorithms in noisy conditions. The database may either be used for the evaluation of front-end feature extraction algorithms using a defined HMM recognition back-end or complete recognition systems. The source speech for this database is the TIdigits, consisting of connected digits task spoken by American English talkers (downsampled to 8kHz) . A selection of 8 different real-world noises have been added to the speech over a range of signal to noise ratios and special care has been taken to control the filtering of both the speech and noise. The framework was prepared as a contribution to the ETSI STQ-AURORA DSR Working Group [1]. Aurora is developing standards for Distributed Speech Recognition (DSR) where the speech analysis is done in the telecommunication terminal and the recognition at a central location in the telecom network. The framework is currently being used to evaluate alternative proposals for front-end feature extraction. The database has been made publicly available through ELRA so that other speech researchers can evaluate and compare the performance of noise robust algorithms. Recognition results are presented for the first standard DSR feature extraction scheme that is based on a cepstral analysis.
Aiming at the problems of intensified air port competition conflicts and uncontrollable transmission delay caused by the dense deployment of multiple access points in the fiber-to-the-room (FTTR) C-WAN2.0 architecture, a collaboration-enhanced distributed channel access (Co-EDCA) mechanism with multi-AP was proposed. The interference domain isolation was achieved through conflict graph modeling and time slot allocation, and the competition window was dynamically adjusted using reinforcement learning to optimize the competitive behavior of multiple SFUs. Simulation results show that the proposed mechanism can reduce the conflict probability by 23%, improve the system throughput by 98%, and reduce the transmission delay by 57% in SFU-dense scenarios, effectively solving the resource competition and quality of service guarantee problems under the C-WAN2.0 architecture.
The purpose of the study is to identify the impact of information and communication technologies and measures taken by telecommunications companies in China, Japan and South Korea on the environment of these countries.Materials and methods. Indexes of the ecological footprint (based on the Global Footprint Network data) and greenhouse gas emissions (based on the International Energy Agency data) for these countries are used as a measure of environmental assessment. Based on the Sustainability Reports of telecommunication companies in these countries (China Mobile, SK Telekom, KDDI and others), their strategies for environmental protection and achieving a zero carbon footprint are examined. The impact of information and communication technologies is assessed using indexes of the number of Internet users, fixed Internet access, mobile communications users per 100 people of the country’s population, the share of ICT goods and services in the total exports and imports of countries, as well as the growth index of IT investments in the private sector for Japan. For each country, a correlation matrix was constructed depending on the level of the logarithm of the ecological footprint (Y) on the logarithms of the listed indexes; the factors that most influence Y and are not multicollinear were selected. Based on the selected indexes, multiple regression models were developed for each country and their parameters were assessed.Results. For China and South Korea, a positive elasticity of the ecological footprint was obtained for the number of mobile phone users (for China) and fixed broadband Internet access (for South Korea). In addition, the import of ICT goods into a country reduces its environmental footprint, and the export of ICT services from the country leads to an increase in the index. For Japan, negative elasticities of the ICT sector indexes for the country’s ecological footprint were obtained, which is associated with measures taken by telecommunication companies to reduce their own consumption of electricity and other resources, as well as the widespread use of digital technologies for energy saving in other sectors of the Japanese economy.Conclusion. For China and South Korea, significant dependences of the country’s ecological footprint on the spread of digital technologies were obtained, and their diffusion entails an increase in the index. While this impact is not very large, the widespread adoption of 5G mobile communications in these countries should be taken into account, which could significantly increase the share of the ICT sector in the countries’ environmental footprint. At the same time, Japanese telecommunication companies are promoting environmental protection
Atchariya Wonginchan, Juraporn Tangpukdee, Suphasak Wonginchan
et al.
Background. Thailand tends to have more access to online media. In 2020, the northeastern region had the highest usage rate. Especially school-age children have the highest usage rate. If misused for a long time, the consequences can adversely affect health in many aspects. Their parents should closely supervise and monitor them for this health problem. However, parents have limitations in caring because they have to work a lot. The aim was to study factors that influence working-age parents in holistic health care (HHC) of school-age children using online media in northeast Thailand. Materials and Methods. This research was a descriptive study, with a sample of parent amount 222. The questionnaire performed an item-objective congruence (IOC) = 0.60–1.00, the content validity index (CVI) = 0.90, and the Cronbach’s alpha coefficient was 0.93. The data collected then include the characteristics, use of online media, health problems, and health care. Finally, data were analyzed using descriptive statistics, frequency, percentage, standard deviation, and multiple regressions. Result. The results of the study are factors that influenced HHC with statistical significance (p≤.001) including the child’s gender, the child’s age, the child’s class, the type of internet, activities, the device, and the device owner. In addition, it was holistic health problems of school-age children such as physical, emotional, social, and intellectual. Importantly, these could explain the variation for HHC of 21.2% (adjusted R2 = 0.212), and the standard error in the model estimation was 25.06 (SEE = 25.06). Conclusion. Factors that influence school-age children’s health care are beneficial to preventing and solving health problems by using online media. Parents or health care professionals can use it as a guide to develop more effective health care strategies and policies. Ultimately, it will help to promote better health for children in an ever-changing digital world.
Abstract Automatic speech recognition (ASR) has been widely used in the field of customer service, but the performance of general ASR in dialect transcription is not satisfactory, especially in Guangdong Province. Targeted training of ASR transcription engine will produce effect, but the training cost is high, and it is not suitable for small‐scale training with multiple dialects and frequencies. The complaint problems in the customer service field have obvious clustering and are suitable for few‐shot and multi‐frequency training. In view of this, in the actual engineering application, the method of ASR transcribed into the dialect error correction thesaurus is tried to be used to replace the wrong words, and have achieved good results. The optimization technology after automatic speech transcription proposed in this study can improve the recognition accuracy of general ASR by 13.75% for dialect words.
Transport activities and citizen mobility have a deep impact on enlarged smart cities. By analyzing Big Data streams generated through Internet of Things (IoT) devices, this paper aims to show the efficiency of using IoT analytics, as an agile optimization input for solving real-time problems in smart cities. IoT analytics has become the main core of large-scale Internet applications, however, its utilization in optimization approaches for real-time configuration and dynamic conditions of a smart city has been less discussed. The challenging research topic is how to reach real-time IoT analytics for use in optimization approaches. In this paper, we consider integrating IoT analytics into agile optimization problems. A realistic waste collection problem is modeled as a dynamic team orienteering problem with mandatory visits. Open data repositories from smart cities are used for extracting the IoT analytics to achieve maximum advantage under the city environment condition. Our developed methodology allows us to process real-time information gathered from IoT systems in order to optimize the vehicle routing decision under dynamic changes of the traffic environments. A series of computational experiments is provided in order to illustrate our approach and discuss its effectiveness. In these experiments, a traditional static approach is compared against a dynamic one. In the former, the solution is calculated only once at the beginning, while in the latter, the solution is re-calculated periodically as new data are obtained. The results of the experiments clearly show that our proposed dynamic approach outperforms the static one in terms of rewards.
Mohamed Yehia Habash, Nabil Mohamed Abd Elfatah Ayad, Abd Elhady Abd Elazim Ammar
In nuclear facilities, the reading of the sensors is very important in the assessments of the system state. The existence of an abnormal state could be caused by a failure in the sensor itself instead of a failure in the system. So, being unable to identify the main cause of the “abnormal state” and take proper actions may end in unnecessary shutdown for the nuclear facility that may have expensive economic consequences. That is why, it is extremely important for a supervision and control system to identify the case where the failure in the sensor is the main cause for the existence of an abnormal state. In this paper, a system based on a wireless sensor network is proposed to monitor the radiation levels around and inside a nuclear facility. A new approach for validating the sensor readings is proposed and investigated using the Castalia simulator.
The paper assesses vulnerability of the EU exports to Ukraine to the current COVID-19 pandemic, which became the major challenge for societies and economies. The main current trends affecting the bilateral trade are discussed. A regression analysis is used to estimate the effects of demand and supply shocks, and changes in price competitiveness. The EU exports of fuels and road vehicles are the most sensitive to changes in the Ukraine's GDP, the exports of chemical products and telecommunication equipment - to devaluation of hryvnia. The most resilient EU exports to Ukraine included medicinal and pharmaceutical products, beverages and tobacco. The changes in consumption patterns under the quarantine measures also favoured stability of food and IT-services exports. The post-factum verification of results with the resent data confirmed most sector-specific effects. On average the EU exports to Ukraine turned out to be more resilient than to other countries.
Loading methods for wireline and wireless transmission systems are explained and reviewed to allow examination of fundamental equivalences between approaches to optimum transmission with linear cross-dimensional interference. Shannon’s famous water-filling method is then re-interpreted by examining the difference between mutual information and the constellation size used on each tone. Results reinforce that highest performance in all methods retains use of Shannon’s water-filling. However, results also find that a constant-size constellation on all energized water-filling dimensions, when used with a good code and an appropriate joint maximum-likelihood decoder, is sufficient to approximate this highest performance. This means that tone-dependent constellation variation is not necessary, which increases receiver complexity but reduces the need for channel-state feedback. This then leads to some adaptive MCS (modulation and coding scheme) equivalent loading methods that can be applied generally to wireline and wireless transmission.
Telecommunication, Transportation and communications
In consideration of this situation,a technical scheme based on Beidou satellite system was proposed,which could realize the collection of power consumption information and could safely bring Beidou terminal onto concentrators and main station systems.At the same time,it was compatible with the original power consumption collection system to achieve effective coverage of the blind zone.A technology of Beidou short message partition and composition was proposed,which made the transmission of long data packets in the power 376.1 protocol come true.Meanwhile,the platform implements the Beidou multi-card management and pre-buffering mechanism to solve the problems of the delay in issuing commands and data query response.And some mechanisms such as active reporting and timing motion tween call instructions in multi period was introduced in order to make up the packet loss problem in the area of Beidou communication.The technology has been tested,which shows that the success rate of data collection under the situation of equipment normal operation can be up to above 99% and demonstrates the high reliability and safety.
To solve the problem that the blockchain-based traceability algorithm mainly used homomorphic encryption and zero-knowledge proof for privacy protection,making it difficult to achieve dynamic sharing of traceability information,a blockchain data traceability algorithm based on attribute encryption was proposed.In order to realize the dynamic protection of transaction privacy,the strategy update algorithm applicable to block chain was designed based on the CP-ABE scheme proposed by Waters to achieve dynamic protection of transaction privacy.In order to realize the dynamic update of the visibility about block content,based on the strategy update algorithm,the block structure was designed to achieve the dynamic update about the content visibility of the block.The security and experimental simulation analysis show that the proposed algorithm can realize the dynamic sharing of traceability information while completing the protection transaction privacy.
Energy harvesting (EH) has been considered as a promising technology to solve the constrained energy problem in the devices of IoT with its advantages of flexible deployment and sustainable energy supply.For multiple access channel with energy harvesting,a hybrid energy storage structure model composed by super capacitor and battery was proposed for the devices of IoT.According to the peculiarities of medium access channel and energy harvesting system,an optimized energy allocation strategy with exponential-type decline (ETD) was presented,the upper and lower bounds of the average throughput were deduced,in particular,the gap of two bounds was derived to be a constant.The channel capacity was further obtained by utilizing the relationship between the average throughput and the channel capacity.In the simulations,the effect of harvested energy,storage capacity and the number of nodes on the channel capacity were analyzed respectively.Experiment results show that compared with the conventional wireless node with single battery storage,the proposed hybrid energy storage structure can improve the harvested energy value and increase the multiple access channel capacity by using adaptive modulation scheme when transmitting the signals.