This paper presents a novel inverse kinematics solution for robotic arm based on artificial neural network (ANN) architecture. The motion of robotic arm is controlled by the kinematics of ANN. A new artificial neural network approach for inverse kinematics is proposed. The novelty of the proposed ANN is the inclusion of the feedback of current joint angles configuration of robotic arm as well as the desired position and orientation in the input pattern of neural network, while the traditional ANN has only the desired position and orientation of the end effector in the input pattern of neural network. In this paper, a six DOF Denso robotic arm with a gripper is controlled by ANN. The comprehensive experimental results proved the appl

A novel method for Network Intrusion Detection System (NIDS) has been proposed, based on the concept of how DNA sequence detects disease as both domains have similar conceptual method of detection. Three important steps have been proposed to apply DNA sequence for NIDS: convert the network traffic data into a form of DNA sequence using Cryptography encoding method; discover patterns of Short Tandem Repeats (STR) sequence for each network traffic attack using Teiresias algorithm; and conduct classification process depends upon STR sequence based on Horspool algorithm. 10% KDD Cup 1999 data set is used for training phase. Correct KDD Cup 1999 data set is used for testing phase to evaluate the proposed method. The current experiment results sh

Neural cryptography deals with the problem of “key exchange” between two neural networks by using the mutual learning concept. The two networks exchange their outputs (in bits) and the key between two communicating parties ar eventually represented in the final learned weights, when the two networks are said to be synchronized. Security of neural synchronization is put at risk if an attacker is capable of synchronizing with any of the two parties during the training process.

Home Computer and Information Science 2009 Chapter The Stochastic Network Calculus Methodology Deah J. Kadhim, Saba Q. Jobbar, Wei Liu & Wenqing Cheng Chapter 568 Accesses 1 Citations Part of the Studies in Computational Intelligence book series (SCI,volume 208) Abstract The stochastic network calculus is an evolving new methodology for backlog and delay analysis of networks that can account for statistical multiplexing gain. This paper advances the stochastic network calculus by deriving a network service curve, which expresses the service given to a flow by the network as a whole in terms of a probabilistic bound. The presented network service curve permits the calculation of statistical end-to-end delay and backlog bounds for broad

Due to the huge variety of 5G services, Network slicing is promising mechanism for dividing the physical network resources in to multiple logical network slices according to the requirements of each user. Highly accurate and fast traffic classification algorithm is required to ensure better Quality of Service (QoS) and effective network slicing. Fine-grained resource allocation can be realized by Software Defined Networking (SDN) with centralized controlling of network resources. However, the relevant research activities have concentrated on the deep learning systems which consume enormous computation and storage requirements of SDN controller that results in limitations of speed and accuracy of traffic classification mechanism. To fill thi

In addition to the primary treatment, biological treatment is used to reduce inorganic and organic components in the wastewater. The separation of biomass from treated wastewater is usually important to meet the effluent disposal requirements, so the MBBR system has been one of the most important modern technologies that use plastic tankers to transport biomass with wastewater, which works in pure biofilm, at low concentrations of suspended solids. However, biological treatment has been developed using the active sludge mixing process with MBBR. Turbo4bio was established as a sustainable and cost-effective solution for wastewater treatment plants in the early 1990s and ran on minimal sludge, and is easy to maintain. This

Roller Compacted Concrete is a type of concrete that is environmentally friendly and more economical than traditional concrete. Roller Compacted Concrete is typically used for heavy-duty and specialist constructions, such as hydraulic structures and pavements, because of its coarse surface. The main difference between RCC and conventional concrete mixtures is that RCC has a more significant proportion of fine aggregates that allow compaction and tight packing. In recent years, it has been estimated that several million tons of waste demolished material (WDM) produced each year are directed to landfills worldwide without being recycled for disposal. This review aimed to study the literature about creating a Roller-Comp

Some species, such as the Eurasian Collared-Dove (S. decaocto) are fast expanding around the planet, while others, such as the European Turtle-Dove (S. turtur), are experiencing precipitous population declines. Climate change, habitat loss, greater cultivated areas, and hunting pressure are the major threats to the diversity of Streptopelia. A few species require urgent conservation action. Priority for subsequent research should be to redress outstanding taxonomic uncertainties, ascertain the effect of climate change on distributions, and put in place conservation measures for declining taxa. We provide here a detailed review on how it is possible to understand the diversity of Streptopelia and how such an understanding can con