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A field experiment was carried out to evaluate the combined application of organic and inorganic fertilizers on the growth, yield, and physiochemical properties of mustard (Brassica napus L) during the Rabi season 2021-2022 at the experimental field of BINA in Satkhira, Bangladesh. The experiment had 10 treatments viz. T1 = 100% Recommended Dose Chemical Fertilizer (RDCF), T2= 75% RDCF + 3 t ha-1 vermicompost, T3= 50% RDCF + 5 t ha-1 vermicompost, T4= 75% RDCF + 3 t ha-1cow-dung, T5= 50% RDCF + 5 t ha-1cow-dung, T6= Absolute control, T7= 3 t ha-1 cow-dung, T8= 3 t ha-1vermicompost, T9= 5 t ha-1cow-dung, T10= 5 t ha-1 vermicompost with three (3) replications in randomized complete block design (RCBD). The maximum plant height (cm), No. of primary branches plant-1, no. of secondary branches plant-1, total siliqua plant-1, siliqua length (cm), seeds siliqua-1, seeds plant-1, and yield plot-1 were recorded and it was found that the application of 75% RDCF + 3 t ha-1 vermicompost was significant over control. The combined effect of organic and inorganic fertilizers was found significant in the growth, yield, and physio-chemical properties of mustard cultivation. [ABSTRACT FROM AUTHOR]

Machine learning are vulnerable to the threats. The Intruders can utilize the malicious nature of the nodes to attack the training dataset to worsen the process and manipulate the learning and make the over all system with less efficiency and performance. The optimized poison attack procedures are already introduced to estimate the overall bad scenario, design the intrusion as bi‐level optimization and it is considered computational complexity is high and demanding, in contrary the applicability is limited such models deep neural networks. In this research papers, we have proposed, novel proposed system, poisoning attacks against the Machine learning training dataset, including the genuine data points that reduce the accuracy of the classifier in the process of training. The proposed system have 3 components of Generative Adverserial networks (GAN) generator, discriminator, and the target classifier. The proposed system allows to detect the vulnerability easy and it can be found as similar as realistic attacks to detect the area where the underlying data distribution have more possibility of poising attack which cause vulnerability to the network. Our experimentation, proves the claim our that the proposed model is effective on compromising the classifiers uses the machine learning algorithms and also deep learning networks. [ABSTRACT FROM AUTHOR]

Security management is the process of identifying a company's assets (such as people, buildings, equipment, systems, and information assets) and then developing, documenting, and implementing policies and procedures to secure those assets. Meanwhile, artificial intelligence (AI) applications are flourishing thanks to advances in deep learning and numerous hardware architecture improvements based on cloud edge computing (CEC) issues are associated with the Internet of Things (IoT), including inadequate security measures, user ignorance, and the dreaded active monitoring. Therefore, a 6G wireless communication‐assisted security management using artificial intelligence (WC‐SM‐AI) has been introduced to enhance security. The energy‐efficient 6G real‐time communication framework and the enhanced deep neural network security module are key components of this architecture. The first module optimizes network lifespan and spectral efficiency while reducing energy consumption and latency. Another module offers a more secure network connection while increasing privacy, data integrity, and access. For this reason, this article discusses how AI can strengthen the security of 6G networks while promoting strategy problems and solutions. [ABSTRACT FROM AUTHOR]

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Success stories that encompass entirely from callus induction to fruit bearing of tomato are very limited. Here, this study uncovers an optimized protocol for in vitro regeneration of BARI Tomato-15 which successfully leads to fruit bearing. First leaf and epicotyls were used as explant in MS medium with different concentrations of Indol-3 acetic acid (IAA) and 6-Benzyl amino purin (BAP) for regeneration. MS media containing 0.5 mg L-1 IAA + 0.5 mg L-1 BAP and 0.5 mg L-1 IAA + 2.0 mg L-1 BAP performed best and exhibited the highest frequencies of callus formation and regeneration from first leaves and epicotyl. A combination of 0.5 mg L-1 BAP and 0.5 mg L-1 IAA exhibited the longest shoot (11.33 cm) and root (7.00 cm) length at in vitro conditions. Plants derived from the same combination produced the highest number of leaves (22) and plant height (8.33 cm), and accelerated early flowering and increased fruit bearing (134-plant) with satisfactory yield (5.71 kg-plant) after acclimatization at field condition. Therefore, MS media containing 0.5 mg L-1 IAA + 0.5 mg L-1 BAP could be an effective combination for regeneration and development of an early maturing tomato cultivar. [ABSTRACT FROM AUTHOR]