Plowing During the Sangam Period

In ancient days the word labour is connected both with life and land. They believed that their life will be based on the land which they live. They had the best policy. The first grammar book in Tamil is Tolkappiyam and it not only lays down the rules for grammar in writing and speaking but it also tells people how to lead a better life in accordance with nature. Through this text we come to know know that during the Sangam period all industries were based on five types of landforms. All the industries related to life are food production industry and material production industry. Apart from these, other industries also existed in ancient times. Valluvar's in his poem states that there is no world for those who do not have material things. Material is essential for life. The production, accumulation and distribution of goods depends on the economic system of a society. Economy deals with the production that take place in a country and trading the left over to other countrie

Information and Communication-Based Collaborative Learning and Behavior Modeling Using Machine Learning Algorithm

Rapid growth of smart phone industries has led people to use more technology and thus aided in adoption of information and communication technology (ICT) in educational purposes for enhancing students? performance. This chapter shows that students use social media platform or virtual environment for learning, especially in Open University or online learning system. In such environment, the students? drop rate is extremely high. This work primarily aims at reducing students? dropout or students? fails to finish course within prerequisite time using student behavior styles. For addressing research problems, this research aims in building efficient student behavior learning model for improving the performance of student applying machine learning (ML) models. The behavior extraction and study have been carried utilizing decision tree (DT) ML algorithm. Further, a model has been proposed for provisioning student contextual information to different students utilizing VLE platform interaction (collaborative learning) using DT algorithm which considered bagging. The DT with bagging is an ensemble learning (EL) model that depicts bootstrap aggregating (BA), which is modeled for enhancing accuracies and stabilities of every distinct predictive trees. Bagging aids DT in influencing overfitting problems and minimizes its variance. The proposed method is efficient in extracting learning styles and intrinsic behavior of students

Performance of frame with Viscoelastic Dampers as an Alternative to Coupled Shear Wall

706-710Coupled shear wall is one of the widely adopted lateral force resisting structural scheme for earthquake resistant design. On the other hand, numerous research activities are carried out for passive energy dissipation with different types of damping devices for damage mitigation of structures due to earthquake. In the present study, performance of twenty storey coupled shear wall building has been compared with performance of the same building wherein the coupled shear walls at the edges are replaced with frames with viscoelastic dampers(VED). Ten different cases with viscoelastic dampers varying in number and position are considered and linear dynamic time history analysis are carried out for four different earthquakes. From the responses obtained from linear time history analyses, all the configurations are observed to give equivalent response as that of building with shear wall case. Further to assess the performance of different configurations in nonlinear range, nonlinear static analyses are carried out and capacity curves are obtained. From the comparisons of results, building with viscoelastic devices are observed to be having more ductility and lesser base shear demand compared to building with coupled shearwall and hence VED can be adopted as an alternative to coupled shear wall

An Efficient Stator Inter-Turn Fault Diagnosis Tool for Induction Motors

Induction motors constitute the largest proportion of motors in industry. This type ofmotor experiences different types of failures, such as broken bars, eccentricity, and inter-turn failure.Stator winding faults account for approximately 36% of these failures. As such, condition monitoringis used to protect motors from sudden breakdowns. This paper proposes the use of neural networks as anefficient diagnostic tool for estimating the percentage of stator winding shorted turns in three-phaseinduction motors. A MATLAB-based model was developed and simulated under different fault-loadcombination cases for different sizes of motors. The motor’s developed electromechanical torque wasselected as a fault indicator. For the design and training of the neural network, the mean, variance, max,min, and F120 time based on statistical and frequency-related features were found to be very distinct forcorrelating the captured electromechanical torque with its corresponding percentage of shorted turns. Inthe training phase of the neural network, five different motors were used and are referred to as seenmotors. On the other hand, for testing the efficiency of the developed diagnostic tool, theelectromechanical torque under different fault-load combination cases, previously never seen from thefirst five motors and those of two new motors (referred to as unseen), was used. Testing results revealedaccuracy in the range of 88–99%

3-Methyl-5-(3-phenoxy­phen­yl)cyclo­hex-2-enone

In the title mol­ecule, C19H18O2, the cyclo­hexene ring adopts an envelope conformation, with all substituents equatorial. The dihedral angle between the benzene and phenyl rings is 83.75 (16)°. No classical hydrogen bonds are found in the crystal structure

A Federated Consensus for Proof of Authority in IoT-Blockchain Applications

The growing adoption of Internet of Things (IoT) devices and the need for secure and scalable blockchain applications pose significant challenges in the realm of consensus protocols. This paper proposes a novel consensus mechanism called Federated Consensus for Proof of Authority (Fed-PoA), which combines the advantages of Proof of Authority (PoA) and federated learning to achieve secure and scalable IoT-Blockchain applications. The Fed-PoA ensures efficient data sharing, privacy preservation, and decentralized operation. Performance evaluation of this model in a simulated environment demonstrates superior convergence and memory usage compared to a representative work in this context

3-Methyl-5-(4-methyl­phen­yl)cyclo­hex-2-enone

In the title mol­ecule, C14H16O, the cyclo­hexene ring adopts an envelope conformation, with all substituents equatorial. Mol­ecules are linked by C—H⋯O hydrogen bonds. A C—H⋯π inter­action involving the benzene ring is also found in the crystal structure. The H atoms of both methyl groups are disordered equally over two positions

5-(4-Chloro­phen­yl)-1-methyl-3-oxocyclo­hexa­necarbonitrile

In the title mol­ecule, C14H14ClNO, the cyclo­hexane ring adopts a chair conformation. The cyano group and the methyl group have axial and equatorial orientations, respectively. The benzene ring has an equatorial orientation. A C—H⋯π inter­action involving the benzene ring is found in the crystal structure

Synthesis of Newly Formulated Aluminium Composite through Powder Metallurgy using Waste Bone Material

The increasing concern for sustainable materials and waste management has led to innovative approaches in material science. This study explores the potential benefit of aggregate waste in the production of aluminum composites practicing powder metallurgy techniques. The aim is to investigate the feasibility of incorporating bone material into aluminium matrices to enhance the composite’s mechanical properties. The research involves several key steps. Firstly, waste bone material is collected and processed to obtain a fine powder suitable for powder metallurgy. Various techniques such as grinding, milling, or pulverization are employed to achieve the desired particle size distribution. Next, the bone powder is mixed with aluminium powder in predetermined ratios to create composite blends. The composite blends are then subjected to compaction using powder metallurgy techniques, including cold pressing and sintering. The compaction process aims to consolidate the powders and facilitate the formation of a solid composite structure. The aluminum composites mechanical characteristics are then assessed. The effects of incorporating bone material are assessed using tests on tensile strength, ductility, hardness, and other relevant mechanical properties. Comparative analysis is performed between the composites with bone material and traditional aluminium composites to assess any improvements or changes in performance