Revised international notation for latex harvest technology

Tapping notation that was revised by Lukman in 1983 is revised again. Raingruarding and gaseous stimulation have been incorporated as new items. For tapping period of less than a year, it is shonrn exactly from starting month to ending month. Number of tappings realized against the possible maximum number of tapping days is shornm as a fraction. Similarly actual number of stimulations given against the scheduled number is also shoum as a fraction. Changes have been brought about in the expressions for cut lengrth and frequency of tapping. Use of arrows for expressing directions of tapping cuts and for change of tapping have been changed to more convenient ones. The terminologry, 'exploitation technology' is changed to 'latex harvest technologry'. (Résumé d'auteur

Artificial minds with consciousness and common sense aspects

The research work presented in this article investigates and explains the conceptual mechanisms of consciousness and common-sense thinking of animates. These mechanisms are computationally simulated on artificial agents as strategic rules to analyze and compare the performance of agents in critical and dynamic environments. Awareness and attention to specific parameters that affect the performance of agents specify the consciousness level in agents. Common sense is a set of beliefs that are accepted to be true among a group of agents that are engaged in a common purpose, with or without self-experience. The common sense agents are a kind of conscious agents that are given with few common sense assumptions. The so-created environment has attackers with dependency on agents in the survival-food chain. These attackers create a threat mental state in agents that can affect their conscious and common sense behaviors. The agents are built with a multi-layer cognitive architecture COCOCA (Consciousness and Common sense Cognitive Architecture) with five columns and six layers of cognitive processing of each precept of an agent. The conscious agents self-learn strategies for threat management and energy level maintenance. Experimentation conducted in this research work demonstrates animate-level intelligence in their problem-solving capabilities, decision making and reasoning in critical situations

Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema

Pneumonia is a dangerous disease that can occur in one or both lungs and is usually caused by a virus, fungus or bacteria. Respiratory syncytial virus (RSV) is the most common cause of pneumonia in children. With the development of pneumonia, it can be divided into four stages: congestion, red liver, gray liver and regression. In our work, we employ the most powerful tools and techniques such as VGG16, an object recognition and classification algorithm that can classify 1000 images in 1000 different groups with 92.7% accuracy. It is one of the popular algorithms designed for image classification and simple to use by means of transfer learning. Transfer learning (TL) is a technique in deep learning that spotlight on pre-learning the neural network and storing the knowledge gained while solving a problem and applying it to new and different information. In our work, the information gained by learning about 1000 different groups on Image Net can be used and strive to identify diseases

The individual and situational factors predicting unethical behaviour in the workplace: a direct and conceptual replication of Jones & Kavanagh (1996)

Intentions to act unethically in the workplace are purported to be driven by a number of situational and individual factors. Across two seminal vignette experiments, Jones and Kavanagh reported inconsistent effect sizes for manager and peer influence and locus of control, consistent significant effects for work quality and Machiavellianism, and consistent non-significant effects for gender. Using an innovative multi-site collaboration, the current Registered Report represents a direct replication of these experiments (N = 2218), and adds a longitudinal conceptual replication capturing self-reported unethical work behaviour (N = 1747). Both replications found a consistent small effect of having a more external locus of control and male identity, and a consistent moderate effect of machiavellianism, for increasing unethical intentions and behaviour. The situational factors, whilst consistent in direction with that of the original study, varied more substantively in effect size. Our results highlight the value of multi-site collaborations and different replication types in developing conceptual, methodological, measurement and theoretical clarity to ensure future works can progress more rapidly to minimize the negative impacts of unethical workplace behaviour and improve individual’s working lives. All materials, code and data for this project can be found here: osf.io/d3arx

Computational Analysis of Base Drag Reduction for a Subsonic Missile Projectile at Different Flow Velocity Conditions

Base drag is arising from flow separation at blunt base of a body. It can be a sizeable fraction of total drag in context of projectiles, missiles and after bodies of fighter aircrafts. The base drag is the major contribution of total drag for low speed regimes, flight tests have shown that the base drag may account for up to 50% of total drag. In this paper an experimental investigation for simple semi-circular flight vehicle body of length 500mm and diameter 50mm was conducted for the purpose of investigating base drag. The base drags for three configurations are calculated and the results are compared with CFD data. The three configurations used for testing are flat base configuration, closed nozzle configuration and boat tail configuration. The evaluation of base drag for three different flow velocities such as (i) 20m/s, (ii) 35m/s and (iii) 50m/s at different angle of attack such as -2, 0 and 2 are experimented and compared.</jats:p

Bronchop Neumonia Detection Using Novel Multilevel Deep Neural Network Schema

Pneumonia is a dangerous disease that can occur in one or both lungs and is usually caused by a virus, fungus or bacteria. Respiratory syncytial virus (RSV) is the most common cause of pneumonia in children. With the development of pneumonia, it can be divided into four stages: congestion, red liver, gray liver and regression. In our work, we employ the most powerful tools and techniques such as VGG16, an object recognition and classification algorithm that can classify 1000 images in 1000 different groups with 92.7% accuracy. It is one of the popular algorithms designed for image classification and simple to use by means of transfer learning. Transfer learning (TL) is a technique in deep learning that spotlight on pre-learning the neural network and storing the knowledge gained while solving a problem and applying it to new and different information. In our work, the information gained by learning about 1000 different groups on Image Net can be used and strive to identify diseases