There is, I think, something ethereal about i —the square root of minus one. I remember first hearing about it at school. It seemed an odd beast at that time—an intruder hovering on the edge of reality.

Usually familiarity dulls this sense of the bizarre, but in the case of i it was the reverse: over the years the sense of its surreal nature intensified. It seemed that it was impossible to write mathematics that described the real world in …

I and i

Data Mining Practical Machine Learning Tools and Techniques

Matrix Factorization Techniques for Recommender Systems

With the invention of the low-cost Microsoft Kinect sensor, high-resolution depth and visual (RGB) sensing has become available for widespread use. The complementary nature of the depth and visual information provided by the Kinect sensor opens up new opportunities to solve fundamental problems in computer vision. This paper presents a comprehensive review of recent Kinect-based computer vision algorithms and applications. The reviewed approaches are classified according to the type of vision problems that can be addressed or enhanced by means of the Kinect sensor. The covered topics include preprocessing, object tracking and recognition, human activity analysis, hand gesture analysis, and indoor 3-D mapping. For each category of methods, we outline their main algorithmic contributions and summarize their advantages/differences compared to their RGB counterparts. Finally, we give an overview of the challenges in this field and future research trends. This paper is expected to serve as a tutorial and source of references for Kinect-based computer vision researchers.

Enhanced Computer Vision With Microsoft Kinect Sensor: A Review

mental representations a dual coding approach is available in our digital library an online access to it is set as public so you can download it instantly. Our digital library saves in multiple countries, allowing you to get the most less latency time to download any of our books like this one. Kindly say, the mental representations a dual coding approach is universally compatible with any devices to read.

Mental Representations A Dual Coding Approach

In this paper, the potential field principle is applied to several UAVs (Unmanned Aerial Vehicles) for optimal path planning. Each UAV has its own goals and it is used the attractive potential field to reach the goals. On the contrary, each UAV is considered as obstacle for other UAVs that must be avoided. In this research, there are two types of obstacles, i.e the static and dynamic. The repulsive potential field principle is used to avoid for both static and dynamic obstacles. The whole method is implemented into Parrot AR Drone 2.0 Quadcopter model of UAV and simulated in Gazebo Simulator by Robot Operating System (ROS). The results of this research are to control the thrust of quadcopter so that it is in flying position, the value of value of roll (α) or pitch (β) must set to not equal or approaching 90° or −90° and not between −180° and 180° or between −90° and 90°. Based on the dynamic obstacle performance test with parameter tuning, the optimal avoidance is when the η value is 7.8 while when in static and dynamic test with parameter tuning, the optimal avoidance is when the η value is 7.9 noted by the fastest time and the shortest path.

UAV obstacle avoidance using potential field under dynamic environment

Multiple layer data hiding scheme based on difference expansion of quad

The ratio of accidents caused by drowsiness, increases slightly year by year. The most victims of this case are young adult and mostly happens in developed country. Therefore, to reduce the number of accidents caused by drowsiness, researchers around the world develope some methods for detecting drowsiness on driver's face automatically. They propose various features such as visual, non-visual, and vehicular. Visual features are extracted from driver's face and recorded by camera. Non-visual features are signals emerged from driver's body and to acquire those signals, they use special sensor attached to driver's body. Vehicular features are obtained by observing the behavior of driver during driving. From those features which are propsed by researchers, we discussed 3 ideas that can be considered as guidance to lead researcher in developing drowsiness detection. The first idea is creating the dataset of drowsiness facial expression because it can predict drowsiness and fatigue. Second idea is to combine visual, non-visual, and vehicular features into one for better detection. And last one is developing wearable hardwares such as smartwatch for drowsiness detection which are easy to use and user friendly.

A review on driver drowsiness based on image, bio-signal, and driver behavior

At recent time, the statistical based language model and neural based language model are still dominating the researches in the field of machine translation. The statistical based machine translation today is the fastest one but it has a weakness in term of accuracy. In contrast, the neural based network has higher accuracy but has a very slow computation process. In this research, a comparison between neural based network that adopts Recurrent Neural Network (RNN) and statistical based network with n-gram model for two-way English-Indonesian Machine Translation (MT) is conducted. The perplexity value evaluation of both models show that the use of RNN obtains a more excellent result. Meanwhile, Bilingual Evaluation Understudy (BLEU) and Rank-based Intuitive Bilingual Evaluation Score (RIBES) values increase by 1.1 and 1.6 higher than the results obtained using statistical based.

Recurrent neural network language model for English-Indonesian Machine Translation: Experimental study

Potential-field-based control strategy for path planning and formation control of multi
Quadrotor systems is proposed in this work. The potential field is used to attract the
Quadrotor to the goal location as well as avoiding the obstacle. The algorithm to solve
the so called local minima problem by utilizing the wall-following behavior is also proposed.
The resulted path planning via potential function strategy is then used to design
formation control algorithm. Using the virtual leader approach, the formation control
strategy by means of potential function is formulated. Each Quadrotor is assigned attractive
potential to reach its desired position in formation. Each Quadrotor is also
treated as moving obstacle which induces repulsive potential to the others in order to
prevent inter-robot collision. The desired position for each Quadrotor in certain configuration
is calculated based on the virtual leaderâ��s current position. To get smooth
movement, the virtual leader is set as unicycle robot. The repulsive potential is also
attached to each agent in case it moves in the region inside the obstacleâ��s influence. The
overall strategy has been successfully applied to the Quadrotorâ��s model of Parrot AR
Drone 2.0 in Gazebo simulator programmed using Robot Operating System.

Teguh Bharata Adji

Papers

UAV obstacle avoidance using potential field under dynamic environment

Multiple layer data hiding scheme based on difference expansion of quad

A review on driver drowsiness based on image, bio-signal, and driver behavior

Recurrent neural network language model for English-Indonesian Machine Translation: Experimental study

Path planning and formation control via potential function for UAV Quadrotor