War was and remains one of the main instruments for the practice of international relations, and has always been a major focus of the study of international relations. War, such as diplomacy, propaganda, etc., is an instrument of national politics. States have used wars to achieve their goals and aspirations and achieve their national interests. War and peace issues are essential to understanding international relations. They are questions that involve the problem of survival.

Today the term "war" is used in many different ways. We talk about Cold War, Hot War, Limited War, Total War, Conventional War, Unconventional War, Civil War, Gang War, Preventive War etc. However, the war continued to exist, and took various forms.

Biosignal analysis is one of the most important topics that researchers have tried to develop during the last century to understand numerous human diseases. Electroencephalograms (EEGs) are one of the techniques which provides an electrical representation of biosignals that reflect changes in the activity of the human brain. Monitoring the levels of anesthesia is a very important subject, which has been proposed to avoid both patient awareness caused by inadequate dosage of anesthetic drugs and excessive use of anesthesia during surgery. This article reviews the bases of these techniques and their development within the last decades and provides a synopsis of the relevant methodologies and algorithms that are used to analyze EEG sig

The analytical study of optical bistability is concerned in a fully
optimized laser Fabry-Perot system. The related phenomena of
switching dynamics and optimization procedure are also included.
From the steady state of optical bistability equation can plot the
incident intensity versus the round trip phase shift (φ) for different
values of dark mistuning 
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12
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6
,
3
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1.5
0 , o
   
 or finesse (F= 1, 5, 20,
100). In order to obtain different optical bistable loops. The inputoutput
characteristic for a nonlinear Fabry-Perot etalon of a different
values of finesse (F) and using different initial detuning (φ0) are used
in this rese

In this work, a new development of predictive voltage-tracking control algorithm for Proton Exchange Membrane Fuel Cell (PEMFCs) model, using a neural network technique based on-line auto-tuning intelligent algorithm was proposed. The aim of proposed robust feedback nonlinear neural predictive voltage controller is to find precisely and quickly the optimal hydrogen partial pressure action to control the stack terminal voltage of the (PEMFC) model for N-step ahead prediction. The Chaotic Particle Swarm Optimization (CPSO) implemented as a stable and robust on-line auto-tune algorithm to find the optimal weights for the proposed predictive neural network controller to improve system performance in terms of fast-tracking de

<p>Vehicular ad-hoc networks (VANET) suffer from dynamic network environment and topological instability that caused by high mobility feature and varying vehicles density. Emerging 5G mobile technologies offer new opportunities to design improved VANET architecture for future intelligent transportation system. However, current software defined networking (SDN) based handover schemes face poor handover performance in VANET environment with notable issues in connection establishment and ongoing communication sessions. These poor connectivity and inflexibility challenges appear at high vehicles speed and high data rate services. Therefore, this paper proposes a flexible handover solution for VANET networks by integrating SDN and

Transportability refers to the ease with which people, goods, or services may be transferred. When transportability is high, distance becomes less of a limitation for activities. Transportation networks are frequently represented by a set of locations and a set of links that indicate the connections between those places which is usually called network topology. Hence, each transmission network has a unique topology that distinguishes its structure. The most essential components of such a framework are the network architecture and the connection level. This research aims to demonstrate the efficiency of the road network in the Al-Karrada area which is located in the Baghdad city. The analysis based on a quantitative evaluation using graph th

Bipedal robotic mechanisms are unstable due to the unilateral contact passive joint between the sole and the ground. Hierarchical control layers are crucial for creating walking patterns, stabilizing locomotion, and ensuring correct angular trajectories for bipedal joints due to the system’s various degrees of freedom. This work provides a hierarchical control scheme for a bipedal robot that focuses on balance (stabilization) and low-level tracking control while considering flexible joints. The stabilization control method uses the Newton–Euler formulation to establish a mathematical relationship between the zero-moment point (ZMP) and the center of mass (COM), resulting in highly nonlinear and coupled dynamic equations. Adaptiv

     Recently Tobit  Quantile Regression(TQR) has emerged as an important tool in statistical analysis . in order to improve the parameter estimation in (TQR) we proposed Bayesian hierarchical model with double adaptive elastic net technique  and Bayesian hierarchical model with adaptive ridge regression technique .

 in double adaptive elastic net technique we assume  different penalization parameters  for penalization different regression coefficients in both parameters λ₁and  λ₂  , also in adaptive ridge regression technique we assume different  penalization parameters for penalization different regression coefficients i