Species identification for Indian seafood markets: A machine learning approach with a fish dataset.

The Indian sea fish market is a dynamic and significant sector, contributing to both the domestic economy and the global seafood trade. This fish dataset is specifically curated for machine learning applications in the Indian seafood industry. It includes a comprehensive collection of images representing eight commercially significant fish species native to Indian waters, comprising a total of 8488 images.

A secure and energy-efficient routing using coupled ensemble selection approach and optimal type-2 fuzzy logic in WSN.

Wireless sensor networks (WSNs) are imperative to a huge range of packages, along with environmental monitoring, healthcare structures, army surveillance, and smart infrastructure, however they're faced with numerous demanding situations that impede their functionality, including confined strength sources, routing inefficiencies, security vulnerabilities, excessive latency, and the important requirement to keep Quality of Service (QoS). Conventional strategies generally goal particular troubles, like strength optimization or improving QoS, frequently failing to provide a holistic answer that effectively balances more than one crucial elements concurrently. To deal with those challenges, we advocate a novel routing framework that is both steady and power-efficient, leveraging an Improved Type-2 Fuzzy Logic System (IT2FLS) optimized by means of the Reptile Search Algorithm (RSA).

Field emission performance of graphene-incorporated aluminum-based metal matrix composite.

The 'close proximity' configuration was used for field emission analysis of graphene-incorporated aluminum (Al) composites. The turn-on field was found to be 2 V μm for the AlGr1 (1% graphene (by weight) inside the Al matrix) composite compared to 4.75 V μm for the pristine aluminum sample.

The Kondo effect in superparamagnetic 30% Co-Ni/NiO nanocomposites: detailed transport and magnetic investigations.

Nanocomposites of 20% and 30% Co-doped Ni/NiO were synthesized using a microwave-assisted sol-gel auto-combustion method. The 30% Co-doped Ni/NiO nanocomposite exhibited negative magnetoresistance (M-R) at various temperatures, including 2 K, 10 K, 80 K, 100 K, and 250 K. This behavior is interpreted as indicative of a Kondo-like scattering effect.

A dataset revolutionizing Indian bay leaf analysis.

Indian bay leaf is a crucial spice in Indian cuisine. However, its quality and authenticity are often compromised. To address this, we introduce The Digital Indian Bay leaf dataset, a comprehensive collection of high-resolution 5696 images capturing diverse bay leaf samples under controlled conditions.