Recursive Newton-Euler formulation of manipulator dynamics

A recursive Newton-Euler procedure is presented for the formulation and solution of manipulator dynamical equations. The procedure includes rotational and translational joints and a topological tree. This model was verified analytically using a planar two-link manipulator. Also, the model was tested numerically against the Walker-Orin model using the Shuttle Remote Manipulator System data. The hinge accelerations obtained from both models were identical. The computational requirements of the model vary linearly with the number of joints. The computational efficiency of this method exceeds that of Walker-Orin methods. This procedure may be viewed as a considerable generalization of Armstrong's method. A six-by-six formulation is adopted which enhances both the computational efficiency and simplicity of the model

Polar Codes for Arbitrary Classical-Quantum Channels and Arbitrary cq-MACs

We prove polarization theorems for arbitrary classical-quantum (cq) channels. The input alphabet is endowed with an arbitrary Abelian group operation and an Ar{\i}kan-style transformation is applied using this operation. It is shown that as the number of polarization steps becomes large, the synthetic cq-channels polarize to deterministic homomorphism channels which project their input to a quotient group of the input alphabet. This result is used to construct polar codes for arbitrary cq-channels and arbitrary classical-quantum multiple access channels (cq-MAC). The encoder can be implemented in $O(N\log N)$ operations, where $N$ is the blocklength of the code. A quantum successive cancellation decoder for the constructed codes is proposed. It is shown that the probability of error of this decoder decays faster than $2^{-N^{\beta}}$ for any $\beta<\frac{1}{2}$.Comment: 30 pages. Submitted to IEEE Trans. Inform. Theory and in part to ISIT201

DETERRING NON-STATE ACTORS: APPROACHES TO DETER THE POPULAR MOBILIZATION FORCES (PMF) IN IRAQ

Since its creation in 2014, the Popular Mobilization Forces (PMF) has played a critical role in Iraq’s political, security, and social environments. Working concurrently with the Iranian Revolutionary Guards Corps (IRGC) promotes its role as a regional actor within the Iranian Threat Network (ITN). Moreover, the PMF’s asymmetric activities create a deterrence trap in which responding or binding to self-restraint results in undesired outcomes. This research intends to describe the deterrence trap against the PMF and seeks approaches to stable deterrence. The research argues that creating change in the deterrence social structure can result in defusing the deterrence trap. The research finds that dismantling the conflict’s complexity, building shared deterrence knowledge, and minimizing the PMF’s ability to influence Iraq’s security, political and social environment can diminish its advantages. It suggests three policy options for deterring the PMF. The first option is through understanding the PMF’s internal factionalism. Exploiting the PMF’s sub-militias’ competing interests may enhance the fragmentation of the PMF. Secondly, strengthening the Iraqi security forces outside of the PMF is necessary to balance against militia forces. Finally, continuing to endorse deterrence by denial and punishment vis-à-vis enforcing legal and financial accountability on the PMF’s activities.Raid, Royal Saudi Land ForceApproved for public release. Distribution is unlimited

Analysis and object oriented implementation of the Kovacic algorithm

This paper gives a detailed overview and a number of worked out examples illustrating the Kovacic \cite{Kovacic86} algorithm for solving second order linear differential equation ${A(x) y"+ B(x) y' + C(x) y=0}$ where $A,B,C$ are rational functions with complex coefficients in the independent variable $x$. All three cases of the algorithm were implemented in a software package based on an object oriented design and complete source code listing given in the appendix with usage examples. Implementation used the Maple computer algebra language. The complete Kovacic package in one mpl file accompany the arXiv version of this paper. This package was then used to analyze the distribution of Kovacic algorithm cases on $3000$ differential equationsComment: 74 pages, 5 figures. Software packag

Lung Cancer Detection Using Artificial Neural Network

In this paper, we developed an Artificial Neural Network (ANN) for detect the absence or presence of lung cancer in human body. Symptoms were used to diagnose the lung cancer, these symptoms such as Yellow fingers, Anxiety, Chronic Disease, Fatigue, Allergy, Wheezing, Coughing, Shortness of Breath, Swallowing Difficulty and Chest pain. They were used and other information about the person as input variables for our ANN. Our ANN established, trained, and validated using data set, which its title is “survey lung cancer”. Model evaluation showed that the ANN model is able to detect the absence or presence of lung cancer with 96.67 % accuracy