The structure of the interrogation process in cross-examinations is said to be diverse and complex in terms of question-response typology. This is because the counsel has to extract truth from an opposing party’s witness whose views are expected to advocate that party's views regarding the case. Accordingly, the study which is basically quantitative in nature aims to investigate what the examining party intends to obtain out of these questions and which of these questions are the most prevalently used. It also aims to measure the amount of cooperativity in witnesses' responses. Accordingly, three transcripts of cross-examination have been analyzed, using a pragmatically-oriented approach. The approach draws on Stenstorm (1984) and Arch

  Breast cancer is the most common cancer among women over the world. To reducing reoccurrence and mortality rates, adjuvant hormonal therapy (AHT) is used for a long period. The major barrier to the effectiveness of the treatment is adherence. Adherence to medicines among patients is challenging. Patient beliefs in medications can be positively or negatively correlated to adherence. Objectives: To investigate the extent of adherence and factors affecting adherence, as well as to investigate the association between beliefs and adherence in women with breast cancer taking AHT. Method: A cross-sectional study included 124 Iraqi women with breast cancer recruited from Middle Euphrates

planning is among the most significant in the field of robotics research.  As it is linked to finding a safe and efficient route in a cluttered environment for wheeled mobile robots and is considered a significant prerequisite for any such mobile robot project to be a success. This paper proposes the optimal path planning of the wheeled mobile robot with collision avoidance by using an algorithm called grey wolf optimization (GWO) as a method for finding the shortest and safe. The research goals in this study for identify the best path while taking into account the effect of the number of obstacles and design parameters on performance for the algorithm to find the best path. The simulations are run in the MATLAB environment to test the

Anomaly detection is still a difficult task. To address this problem, we propose to strengthen DBSCAN algorithm for the data by converting all data to the graph concept frame (CFG). As is well known that the work DBSCAN method used to compile the data set belong to the same species in a while it will be considered in the external behavior of the cluster as a noise or anomalies. It can detect anomalies by DBSCAN algorithm can detect abnormal points that are far from certain set threshold (extremism). However, the abnormalities are not those cases, abnormal and unusual or far from a specific group, There is a type of data that is do not happen repeatedly, but are considered abnormal for the group of known. The analysis showed DBSCAN using the

A new modified differential evolution algorithm DE-BEA, is proposed to improve the reliability of the standard DE/current-to-rand/1/bin by implementing a new mutation scheme inspired by the bacterial evolutionary algorithm (BEA). The crossover and the selection schemes of the DE method are also modified to fit the new DE-BEA mechanism. The new scheme diversifies the population by applying to all the individuals a segment based scheme that generates multiple copies (clones) from each individual one-by-one and applies the BEA segment-wise mechanism. These new steps are embedded in the DE/current-to-rand/bin scheme. The performance of the new algorithm has been compared with several DE variants over eighteen benchmark functions including sever

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone with a slun

The need for quick airborne transportation is critical, especially in emergencies. Drones with suspended payloads might be used to accomplish quick airborne transportation. Due to the environment or the drone's motion, the slung load may oscillate and lead the drone to fall. The altitude and attitude controls are the backbones of the drone's stability, and they must be adequately designed. Because of their symmetrical and simple structure, quadrotor helicopters are one of the most popular drone classes. In this work, a genetic algorithm with two weighted terms fitness function is used to adjust a Proportional-Integral-Derivative (PID) controller to compensate for the altitude and attitude controllers in a quadrotor drone

The biggest problem of structural materials for fusion reactor is the damage caused by the fusion product neutrons to the structural material. If this problem is overcomed, an important milestone will be left behind in fusion energy. One of the important problems of the structural material is that nuclei forming the structural material interacting with fusion neutrons are transmuted to stable or radioactive nuclei via (n, x) (x; alpha, proton, gamma etc.) reactions. In particular, the concentration of helium gas in the structural material increases through deuteron- tritium (D-T) and (n, α) reactions, and this increase significantly changes the microstructure and the properties of the structural materials. T

In this study, a traumatic spinal cord injury (TSCI) classification system is proposed using a convolutional neural network (CNN) technique with automatically learned features from electromyography (EMG) signals for a non-human primate (NHP) model. A comparison between the proposed classification system and a classical classification method (k-nearest neighbors, kNN) is also presented. Developing such an NHP model with a suitable assessment tool (i.e., classifier) is a crucial step in detecting the effect of TSCI using EMG, which is expected to be essential in the evaluation of the efficacy of new TSCI treatments. Intramuscular EMG data were collected from an agonist/antagonist tail muscle pair for the pre- and post-spinal cord lesi