The text classification algorithm's knowledge base processing method utilizes existing data from the knowledge base to guide the construction and training of the classification model. In practical application, the...
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Data breach is a serious issue as it leaks the personal information of more than billions of users and their privacy is compromised. More than 77% of organizations do not have a Cyber Security Incident Response plan. ...
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In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), ther...
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In wireless communications, the Ambient Backscatter Communication (AmBC) technique is a promisingapproach, detecting user presence accurately at low power levels. At low power or a low Signal-to-Noise Ratio(SNR), there is no dedicated power for the users. Instead, they can transmit information by reflecting the ambientRadio Frequency (RF) signals in the spectrum. Therefore, it is essential to detect user presence in the spectrum forthe transmission of data without loss or without collision at a specific time. In this paper, the authors proposed anovel Spectrum Sensing (SS) detection technique in the Cognitive Radio (CR) spectrum, by developing the *** Matched Filter Detection with Inverse covariance (MFDI), Cyclostationary Feature Detection with Inversecovariance (CFDI) and Hybrid Filter Detection with Inverse covariance (HFDI) approaches are used with AmBCto detect the presence of users at low power levels. The performance of the three detection techniques is measuredusing the parameters of Probability of Detection (PD), Probability of False Alarms (Pfa), Probability of MissedDetection (Pmd), sensing time and throughput at low power or low SNR. The results show that there is a significantimprovement via the HFDI technique for all the parameters.
In the Field of computer science, artificial intelligence (AI) is a broad field, which is concerned with structuring smart products and machines able to perform tasks which require the intellectual capability of human...
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Although Split Federated Learning (SFL) effectively enables knowledge sharing among resource-constrained clients, it suffers from low training performance due to the neglect of data heterogeneity and catastrophic forg...
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This study focuses on the optimization of Traffic Light System (TLS) control through the use of adaptive agents. The performance of adaptive cycle TLS was compared with fixed cycle TLS. Two different adaptive cycle TL...
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Advanced persistent threat (APT) is a serious concern in cyber-security that has matured and grown over the years with the advent of technology. The main aim of this study is to establish an effective identification m...
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The dataflow model is gradually becoming the de facto standard for big data applications. While many popular frameworks are built around this model, very little research has been done on understanding its inner workin...
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Speech is one of the natural ways of communication between humans, later extended as a means for human–computer interaction. It helps visually impaired people to read electronic texts and is used in information retri...
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Speech is one of the natural ways of communication between humans, later extended as a means for human–computer interaction. It helps visually impaired people to read electronic texts and is used in information retrieval and language education. This paper proposed the development of a text-to-speech synthesizer for Afan Oromo (Oromo Language), using unit selection speech synthesizer approaches. Although several works have been conducted in the area of text-to-speech synthesis for technologically favored languages for many years, every language has its own unique features. So, speech synthesizer systems developed for one language cannot be used for another language, because the structures of one language are not presumably representative of others. It is clear that each program is based on the system corresponding to the phonetic rules of a certain language. Besides, the existing text-to-speech synthesizer for Afan Oromo was reviewed in this study and the result of developed prototype results are showing promising, however, still, their performance needs a lot of improvement in terms of intelligibility and naturalness using novel approaches and quality of corpus. Therefore, this research was initiated to develop the possibility of developing a prototype text-to-speech synthesizer to improve the performance of the text-to-speech synthesizer. In this study, Afan Oromo corpus was collected from genuine sources and prepared speech datasets both text and audio in collaboration with Afan Oromo experts. The performance of the synthesizer was tested by proper users for its intelligibility and naturalness using Mean Opinion Scale (MOS). The obtained result of naturalness of the prototype is 4.44 (very good) out of 5, which indicated that the result obtained is encouraging and better performance than the existing TTS of Afan Oromo in terms of intelligibility and naturalness. But the result scored in terms of intelligibility still needs further work. The main challenge is Afan
Breast cancer remains a leading cause of mortality among women, with millions of new cases diagnosed annually. Early detection through screening is crucial. Using neural networks to improve the accuracy of breast canc...
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