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344 research outputs found
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Enhancing vehicle detection in intelligent transportation systems via autonomous UAV platform and YOLOv8 integration
No full textThis study highlights the evolving landscape of object detection methodologies, emphasizing the superiority of deep learning-based approaches over traditional methods. Particularly in intelligent transportation systems-related applications requiring robust image processing techniques, such as vehicle identification, localization, tracking, and counting within traffic scenarios, deep learning has gained substantial traction. The YOLO algorithm, in its various iterations, has emerged as a popular choice for such tasks, with YOLOv5 garnering significant attention. However, a more recent iteration, YOLOv8, was introduced in early 2023, ushering in a new phase of exploration and potential innovation in the field of object detection. Consequently, due to its recent emergence, the number of studies on YOLOv8 is extremely limited, and an application in the field of Intelligent Transportation Systems (ITS) has not yet found its place in the existing literature. In light of this gap, this study makes a noteworthy contribution by delving into vehicle detection using the YOLOv8 algorithm. Specifically, the focus is on targeting aerial images acquired through a modified autonomous UAV, representing a unique avenue for the application of this cutting-edge algorithm in a practical context. The dataset employed for training and testing the algorithm was curated from a diverse collection of traffic images captured during UAV missions. In a strategic effort to enhance the variability of vehicle images, the study systematically manipulated flight patterns, altitudes, orientations, and camera angles through a custom-designed and programmed drone. This deliberate approach aimed to bolster the algorithm's adaptability across a wide spectrum of scenarios, ultimately enhancing its generalization capabilities. To evaluate the performance of the algorithm, a comprehensive comparative analysis was conducted, focusing on the YOLOv8n and YOLOv8x submodels within the YOLOv8 series. These submodels were subjected to rigorous testing across diverse lighting and environmental conditions using the dataset. Through tests, it was observed that YOLOv8n achieved an average precision of 0.83 and a recall of 0.79, whereas YOLOv8x attained an average precision of 0.96 and a recall of 0.89. Furthermore, YOLOv8x also outperformed YOLOv8n in terms of F1 score and mAP, achieving values of 0.87 and 0.83 respectively, compared to YOLOv8n's 0.81 and 0.79. These outcomes of the evaluation illuminated the relative strengths and weaknesses of YOLOv8n and YOLOv8x, leading to the conclusion that YOLOv8n is well-suited for real-time ITS applications, while YOLOv8x exhibits superior detection capabilities.Q10012825738000012-s2.0-8519978994
An S-Box construction from exponentiation in finite fields and its application in RGB color image encryption
No full textIn this study, the utilization of exponentiation in finite fields is investigated for the purpose of generating pseudo-random sequences which have a crucial role in cryptographic applications. More precisely, a novel method for generating pseudo-random sequences is proposed to construct an initial S-Box which is a key component in various encryption schemes. In addition to that, a shuffling algorithm that leverages the pseudo-random sequences is developed to enhance the effectiveness of the initial S-Box. The utilization of the proposed S-Box is applied to the RGB color images to showcase its performance and robustness in an image encryption scheme.Q20010839788000042-s2.0-8517379692
Dualities over the cross product of the cyclic groups of order 2
No full textWe determine the number of symmetric dualities on the s-fold cross product of the cyclic group of order 2, which is the additive group of the finite field F2s. We show that the ratio of symmetric dualities over all dualities goes to 0 as s goes to infinity.We also prove a surprising result that given any two binary codes C and D of the same length n with |C||D| = 2n, then viewing them as groups there is a symmetric duality M with CM = D, which also relates their weight enumerators as additive codes in a group via the MacWilliams relations. Using this theorem we show that any additive code in this setting can be viewed as an additive complementary dual code of length 1 with respect to some duality.Q30009408989000012-s2.0-8519926387
Functionality modulation of starch from lotus rhizome using single and dual physical modification
No full textThe effects of ultrasonication (US) assisted by pre- and post-treatment of heat-moisture treatment (HMT) on physicochemical, rheological, pasting, digestive, and thermal properties of lotus rhizome (LR) starch were investigated in this study. All treatments decreased the swelling power, amylose content, and peak viscosity except for the ultrasonicated sample when compared with native LR starch. All treatments showed similar diffraction patterns with different intensities. FTIR spectra characteristic peaks did not emerge or disappear after single and dual modifications. Storage modulus (G′) is greater than loss modulus (G″) for all LR starch gel samples demonstrating their elastic character. Moreover, ΔHgel (253.1–303.7 J/g) increased in all treatments. Dual modification (HMT & US) significantly enhanced resistant starch and reduced SDS in LR starches. These results could be beneficial for promoting ultrasound processing for potential uses in the food industry and starch production.Q12-s2.0-8520159850
2D hyperchaotic Styblinski-Tang map for image encryption and its hardware implementation
No full textA novel 2D chaotic system is presented, which is inspired by Styblinski Tang (ST) function employed as optimization test function. It is a challenge function because of having many local optima. The performance of the chaotic system namely 2D Styblinski Tang (2D-ST) map is corroborated through an extensive comparison with the literature in terms of the sensitive chaos metrics as well as its randomness is verified over TestU0. The 2D-ST map manifests the best hyperchaotic behavior due to higher ergodicity and complexity characteristics. Moreover, the 2D-ST map is implemented to a microcontroller hardware, and it is seen that the results manifests that the proposed 2D-ST can be a potential practical candidate thanks to excellent hyperchaotic performance.Q10010760190000122-s2.0-8517276021
Utilizing Ant Colony Optimization to Construct an S-Box Based on the 2D Logistic-Sine Coupled Map
No full textACO is a combinatorial optimization method that draws inspiration from food searching, pheromone trails, and heuristic information employed by ants. The Substitution Box (S-Box) holds significant importance within symmetric key cryptography algorithms, notably in block ciphers. A secure S-Box requires high non-linearity, resistance to algebraic attacks, and diffusion of input changes to output changes. This study investigates the utilization of ACO for constructing an S-Box, employing the 2D Logistic-Sine Coupled Map (2D-LSCM) as the underlying framework. More precisely, a version of ACO for continuous optimization is used for optimizing the parameters of 2DLSCM. This chaotic map is used for an effective shuffling of an S-Box component and in the permutation of an image encryption. The analyses of results and security provide evidence that S-Box exhibits a high level of security suitable for an image encryption scheme
Index-based simultaneous permutation-diffusion in image encryption using two-dimensional price map
No full textThis paper proposes an index-based simultaneous permutation-diffusion image encryption algorithm (ISPD-IEA) based on chaos theory and a permutation-diffusion coupled encryption mechanism. The proposed method introduces a novel two-dimensional (2D) Price map derived from the Price function and classical maps, exhibiting superior chaotic dynamical properties compared to existing alternatives. By integrating the permutation-diffusion process, ISPD-IEA effectively diffuses minor changes in pixel values while altering their positions, enhancing both encryption efficiency and resistance against differential analysis attacks. Experimental results and thorough security analysis confirm the outstanding security and high encryption efficiency of ISPD-IEA. The algorithm not only achieves excellent encryption performance but also demonstrates its ability to resist various attacks commonly encountered in image encryption scenarios.Q10011857128000042-s2.0-8517010159
Exploring the brain with fMRI and EEG techniques in neurostrategic management: A study on export decision makers
No full textİş dünyasının dinamik yapısı içerisinde strateji, işletmelerin varlık nedenini belirleyen, karmaşık sorunları çözen ve rekabet avantajı elde etmelerini sağlayan kilit bir unsurdur. Strateji oluşturma sürecinde karar vericilerin beynindeki bilişsel değişkenleri keşfetmek ve strateji oluşturma sürecindeki dinamikleri anlamak, işletme yönetiminde devrim niteliğinde bir gelişmedir. Buradan hareketle bu tez çalışması, strateji oluşturma sürecinde Bilişsel Okul perspektifini benimseyerek, karar vericilerin beyin aktivitelerini incelemek suretiyle strateji oluşturma sürecini derinlemesine ele almaya odaklanmaktadır. Bu doğrultuda, bakliyat ve yaş meyve sebze sektöründe ihracat gerçekleştiren iki kadın ve iki erkek olmak üzere dört katılımcının elektroensefalografi (EEG) ve fonksiyonel manyetik rezonans görüntüleme (fMRI) teknikleriyle nörostratejik yönetim süreçleri incelenmiştir. İlk aşama olan EEG ile katılımcıların en yüksek düzeyde kaygı ve stres duyduğu ihracat riskleri belirlenmiş olup, akabinde her bir katılımcıya özgü örnek vaka hazırlanmıştır. İkinci aşamada ise katılımcıların örnek vakalara ilişkin oluşturdukları stratejileri, fMRI ile tespit edilmiştir. EEG sonuçlarına göre, bakliyat sektöründe ihracat gerçekleştiren erkek katılımcının lojistik ve dağıtım riski ile finansal risklere; yaş meyve sebze sektöründe ihracat gerçekleştiren erkek katılımcının ise lojistik ve dağıtım riskine ilişkin en yüksek düzeyde kaygı ve stres duyduğu gözlemlenmiştir. Bakliyat ile yaş meyve sebze sektöründe ihracat gerçekleştiren kadın katılımcıların ise devlet kısıtlaması/ihracat kısıtlaması riskine ilişkin en yüksek düzeyde kaygı ve stres duyduğu tespit edilmiştir. Katılımcıların fMRI bulgularına göre, dört katılımcıda da bilateral oksipital düzeylerde, optik sinirler ve ekstrakonal adaleler trasesinde aktivasyon ile uyumlu sinyallerin var olduğu kaydedilmiştir. Bu bulgular, ihracat gerçekleştiren karar vericilerin nörostratejik yönetim sürecinde geçmiş deneyimlerini, pazar analizlerini ve ticaret stratejilerini görsel hafıza kullanarak değerlendirdiklerini ortaya koymaktadır
Multiobjective Design of 2D Hyperchaotic System Using Leader Pareto Grey Wolf Optimizer
No full textA chaotic system is a mathematical model exhibiting random and unpredictable behavior. However, existing chaotic systems suffer from suboptimal parameters regarding chaotic indicators. In this study, a novel leader Pareto grey wolf optimizer (LP-GWO) is proposed for multiobjective (MO) design of 2D parametric hyperchaotic system (2D-PHS). The MO capability of LP-GWO is improved by integrating a LP solution within the Pareto optimal set. The effectiveness of LP-GWO is corroborated through a comparison with regular MO versions of grey wolf optimizer (GWO), artificial bee colony, particle swarm optimization, and differential evolution. Additionally, the validation extends to the exploration of LP-GWO's performance across four variants of the 2D-PHS optimized by the compared algorithms. A 2D-PHS model with eight parameters is conceived and then optimized using LP-GWO by ensuring tradeoff between two objectives: Lyapunov exponent (LE) and Kolmogorov entropy (KE). A globally optimal design is chosen for freely improving the two objectives. The chaotic performance of 2D-PHS significantly outperforms existing systems in terms of precise chaos indicators. Therefore, the 2D-PHS has the best ergodicity and erraticity due to optimal parameters provided by LP-GWO.Q10012429997000012-s2.0-8519538671
An application of a virus optimization algorithm to the problem of computing binary self-dual and LCD codes
No full textIn this paper, we employ a virus optimization (VO) algorithm, which is one of the metaheuristic optimization techniques, and a known construction method to compute many new binary [72, 36, 12] self-dual codes and optimal/near-optimal linear complementary dual (LCD) codes. In particular, we obtain 39 Type I and 19 Type II codes of length 72, with parameters in their weight enumerators that were not known in the literature before, and 85 new binary LCD codes that are either optimal or near-optimal. We also present the generator matrix of extended Golay code [24, 12, 8] by a cyclic group matrix ring element.Q3WOS:00093605390000