5862 research outputs found
Sort by
Deepfake Detection Using Deep Learning Methods: a Systematic and Comprehensive Review
No full textHeidari, Arash/0000-0003-4279-8551; Unal, Mehmet/0000-0003-1243-153XDeep Learning (DL) has been effectively utilized in various complicated challenges in healthcare, industry, and academia for various purposes, including thyroid diagnosis, lung nodule recognition, computer vision, large data analytics, and human-level control. Nevertheless, developments in digital technology have been used to produce software that poses a threat to democracy, national security, and confidentiality. Deepfake is one of those DL-powered apps that has lately surfaced. So, deepfake systems can create fake images primarily by replacement of scenes or images, movies, and sounds that humans cannot tell apart from real ones. Various technologies have brought the capacity to change a synthetic speech, image, or video to our fingers. Furthermore, video and image frauds are now so convincing that it is hard to distinguish between false and authentic content with the naked eye. It might result in various issues and ranging from deceiving public opinion to using doctored evidence in a court. For such considerations, it is critical to have technologies that can assist us in discerning reality. This study gives a complete assessment of the literature on deepfake detection strategies using DL-based algorithms. We categorize deepfake detection methods in this work based on their applications, which include video detection, image detection, audio detection, and hybrid multimedia detection. The objective of this paper is to give the reader a better knowledge of (1) how deepfakes are generated and identified, (2) the latest developments and breakthroughs in this realm, (3) weaknesses of existing security methods, and (4) areas requiring more investigation and consideration. The results suggest that the Conventional Neural Networks (CNN) methodology is the most often employed DL method in publications. According to research, the majority of the articles are on the subject of video deepfake detection. The majority of the articles focused on enhancing only one parameter, with the accuracy parameter receiving the most attention. This article is categorized under:Technologies > Machine LearningAlgorithmic Development > MultimediaApplication Areas > Science and Technolog
Multimodal Language in Child-Directed Versus Adult-Directed Speech
No full textSpeakers design their multimodal communication according to the needs and knowledge of their interlocutors, phenomenon known as audience design. We use more sophisticated language (e.g., longer sentences with complex grammatical forms) when communicating with adults compared with children. This study investigates how speech and co-speech gestures change in adult-directed speech (ADS) versus child-directed speech (CDS) for three different tasks. Overall, 66 adult participants (Mage = 21.05, 60 female) completed three different tasks (story-reading, storytelling and address description) and they were instructed to pretend to communicate with a child (CDS) or an adult (ADS). We hypothesised that participants would use more complex language, more beat gestures, and less iconic gestures in the ADS compared with the CDS. Results showed that, for CDS, participants used more iconic gestures in the story-reading task and storytelling task compared with ADS. However, participants used more beat gestures in the storytelling task for ADS than CDS. In addition, language complexity did not differ across conditions. Our findings indicate that how speakers employ different types of gestures (iconic vs beat) according to the addressee’s needs and across different tasks. Speakers might prefer to use more iconic gestures with children than adults. Results are discussed according to audience design theory. © Experimental Psychology Society 2023
Improving Non-Line Situations in Indoor Positioning With Ultra-Wideband Sensors Via Federated Kalman Filter
No full textUltra-wideband (UWB) technology is renowned for its exceptional performance in fast data transmission and precise positioning. However, it faces sensitivity challenges when the tagged object is not in direct line of sight, resulting in position inaccuracies. Applying the federated Kalman filter (FKF), this research focuses on mitigating position deviation induced by non-line-of-sight (NLOS) scenarios in UWB technology. The utilization of the FKF in NLOS scenarios has demonstrated a noteworthy reduction in position deviation. This study uses the FKF to analyze measurements taken under line-of-sight (LOS) and NLOS conditions within indoor settings. The outcomes of this study provide a promising foundation for future research endeavors in the field of UWB technology, emphasizing the potential for improved performance and accuracy in challenging operational environments. © 2024 Institute of Advanced Engineering and Science. All rights reserved
Detection of Change Points in a Nonstationary Time Series Via Graph Laplacian
No full textBu çalışma, durağan olmayan zaman serisi verilerinde değişim noktası tespiti problemine bir çözüm önermektedir. Literatürdeki genel yaklaşımların ötesinde, veri dinamiğine dayalı bir çözüm tasarlamak tahmin kalitesini artırabilmektedir. Bu çalışmada veri dinamiğine bağlı iki grafik tabanlı değişim noktası tespit algoritması önerilmektedir. İlk yaklaşımda Laplacian grafiği oluşturulur ve tespit için eşikten düşük özdeğerlerin sayısı kullanılır. İkinci yaklaşımda Fiedler vektörlerinin işaretleri kümeler halinde gruplandırılarak tespitte kullanılır. Önerilen algoritmaların asıl amacı veri özelliklerindeki değişimi tespit etmektir. Önerilen çözümlerin çıktıları gözlemlenerek değişikliklerin tespiti için başarılı tahminler yapılır. Bu çalışma, optimal bir sayısal algoritma kullanan bir özdeğer çözücü ile endüstriyel bir ortam için çevrimiçi değişim noktası tespit mekanizmasına uyarlanabilir.This study proposes a solution for the problem of change point detection in nonstationary time-series data. Beyond general approaches in the literature, designing a solution based on the dynamics of the data can improve the estimation quality. This study suggests two graph-based change point detection algorithms, which depend on data dynamics. In the first approach, the graph Laplacian is constructed, and the number of eigenvalues lower than the threshold is used for detection. In the second approach, the signs of Fiedler vectors are grouped as clusters and used in detection. The main effort of the suggested algorithms is to detect the change in data characteristics. By observing the outputs of the proposed solutions, successful predictions are made to detect the changes. Using an optimal numerical algorithm, this study can be adapted to an online change point detection mechanism for an industrial environment with an eigenvalue solver
Art and Collective Healing Sarkis Zabunyan and the Politics of Denial
No full textSarkis Zabunyan, one of the prominent figures in Turkish contemporary art, was selected to represent the Turkish pavilion in the Venice Biennale in 2015. Since 2015 was the centennial of the Armenian Genocide, a genocide that has not been recognized by the Turkish Republic for more than a hundred years, and Sarkis being an Istanbul Armenian born and raised in Turkey, the selection caused quite a stir and sparked a public discussion on art and collective healing when it was announced. As a result, the catalog of Sarkis’s work Respiro was subjected to censorship. Through this censorship case, this article scrutinizes various reconciliation discourses developed in Turkey in the early 2000s regarding the Armenian Genocide and how contemporary art could possibly engage/disengage with those discourses. © 2024 Duke University Press.Calouste Gulbenkian Foundation, CGF; Turkish–Armenian Relation
A Nano-Scale Design of a Multiply-Accumulate Unit for Digital Signal Processing Based on Quantum Computing
No full textDigital signal processing (DSP) is used in computer processing to conduct different signal-processing tasks. The DSPs are used in the series numbers representing a continuous variable in a domain such as time, area, or frequency. The multiply-accumulate (MAC) unit is crucial in various DSP applications, including convolution, discrete cosine transform (DCT), Fourier Transform, etc. Thus, all DSPs contain a critical MAC unit in signal processing. The MAC unit conducts multiplication and accumulation operations for continuous and complicated DSP application processes. On the other hand, in the MAC structure, the stability of the circuit and the occupied area pose some significant challenges. However, high-performance quantum technology can easily overcome all the previous shortcomings. Hence, this paper suggests an efficient MAC for DSP applications using a Vedic multiplier, half adder, and accumulator based on quantum technology. All the proposed structures have used a single-layer layout without rotated cells. The suggested architecture is designed and validated based on the QCADesigner 2.0.3 tool. The findings revealed that all the developed circuits have a simple architecture with fewer quantum cells, optimal area, and low latency
A New Design of a Digital Filter for an Efficient Field Programmable Gate Array Using Quantum Dot Technology
No full textAhmed, Suhaib/0000-0003-3496-8856Digital filtering algorithms are most frequently used to implement generic-based Field-programmable gate arrays (FPGAs) chips, which are used for higher sampling rates. In the filtering structure, delay and occupied areas play a vital role. Since the existing structures suffered from shortcomings such as high delay and high occupied area, implementing a high-performance digital filter circuit with high speed and low occupied area based on unique technology can significantly improve the performance of whole FPGA structures. One of the best technologies to implement this vital structure to solve these shortcomings is quantum-dot cellular automata (QCA) technology. This paper presents several new efficient full adders for digital filter applications based on quantum technology, including a multiplier, AND gate, and accumulator. The QCADesigner 2.0.3 tool is used to create and validate the suggested designs. According to the results, all designed circuits have simple structures with few quantum cells, low area, and low latency
The Statistics of <i>q</I>-statistics
No full textTIRNAKLI, Ugur/0000-0002-1104-0847Almost two decades ago, Ernesto P. Borges and Bruce M. Boghosian embarked on the intricate task of composing a manuscript to honor the profound contributions of Constantino Tsallis to the realm of statistical physics, coupled with a concise exploration of q-Statistics. Fast-forward to Constantino Tsallis' illustrious 80th birthday celebration in 2023, where Deniz Eroglu and Ugur Tirnakli delved into Constantino's collaborative network, injecting renewed vitality into the project. With hearts brimming with appreciation for Tsallis' enduring inspiration, Eroglu, Boghosian, Borges, and Tirnakli proudly present this meticulously crafted manuscript as a token of their gratitude.We sincerely thank Tsallis for his long-standing and ongoing encouragement and support throughout many years. D.E., U.T., and E.P.B. express their gratitude to the organizers of the Conference on Tsallis' 80th birthday, especially E. M. F. Curado, where they were graciously hosted and had the opportunity to engage in enriching discussions with all participants, reminiscing about memorable moments with Constantino, delving into the diffusion of q-Statistics ideas, and exploring the complexity of Tsallis' collaboration network structure. U.T. is a member of the Science Academy, Bilim Akademisi, Turkey.Science Citation Index Expande
