Optical Fish Tracking in Fishways using Neural Networks

One of the main issues in Computer Vision is to extract the movement of one or several points or objects of interest in an image or video sequence to conduct any kind of study or control process. Different techniques to solve this problem have been applied in numerous areas such as surveillance systems, analysis of traffic, motion capture, image compression, navigation systems and others, where the specific characteristics of each scenario determine the approximation to the problem. This paper puts forward a Computer Vision based algorithm to analyze fish trajectories in high turbulence conditions in artificial structures called vertical slot fishways, designed to allow the upstream migration of fish through obstructions in rivers. The suggested algorithm calculates the position of the fish at every instant starting from images recorded with a camera and using neural networks to execute fish detection on images. Different laboratory tests have been carried out in a full scale fishway model and with living fishes, allowing the reconstruction of the fish trajectory and the measurement of velocities and accelerations of the fish. These data can provide useful information to design more effective vertical slot fishways.

FSM-based Recognition of Dynamic Hand Gestures via Gesture Summarization Using Key Video Object Planes

The use of human hand as a natural interface for humancomputer interaction (HCI) serves as the motivation for research in hand gesture recognition. Vision-based hand gesture recognition involves visual analysis of hand shape, position and/or movement. In this paper, we use the concept of object-based video abstraction for segmenting the frames into video object planes (VOPs), as used in MPEG-4, with each VOP corresponding to one semantically meaningful hand position. Next, the key VOPs are selected on the basis of the amount of change in hand shape – for a given key frame in the sequence the next key frame is the one in which the hand changes its shape significantly. Thus, an entire video clip is transformed into a small number of representative frames that are sufficient to represent a gesture sequence. Subsequently, we model a particular gesture as a sequence of key frames each bearing information about its duration. These constitute a finite state machine. For recognition, the states of the incoming gesture sequence are matched with the states of all different FSMs contained in the database of gesture vocabulary. The core idea of our proposed representation is that redundant frames of the gesture video sequence bear only the temporal information of a gesture and hence discarded for computational efficiency. Experimental results obtained demonstrate the effectiveness of our proposed scheme for key frame extraction, subsequent gesture summarization and finally gesture recognition.

The Overall Aspects of E-Leaning Issues, Developments, Opportunities and Challenges

Rapid steps made in the field of Information and Communication Technology (ICT) has facilitated the development of teaching and learning methods and prepared them to serve the needs of an assorted educational institution. In other words, the information age has redefined the fundamentals and transformed the institutions and method of services delivery forever. The vision is the articulation of a desire to transform the method of teaching and learning could proceed through e-learning. E-learning is commonly deliberated to use of networked information and communications technology in teaching and learning practice. This paper deals the general aspects of the e-leaning with its issues, developments, opportunities and challenges, which can the higher institutions own.

130 nm CMOS Mixer and VCO for 2.4 GHz Low-power Wireless Personal Area Networks

This paper describes a 2.4 GHz passive switch mixer and a 5/2.5 GHz voltage-controlled negative Gm oscillator (VCO) with an inversion-mode MOS varactor. Both circuits are implemented using a 1P8M 0.13 μm process. The switch mixer has an input referred 1 dB compression point of -3.89 dBm and a conversion gain of -0.96 dB when the local oscillator power is +2.5 dBm. The VCO consumes only 1.75 mW, while drawing 1.45 mA from a 1.2 V supply voltage. In order to reduce the passives size, the VCO natural oscillation frequency is 5 GHz. A clocked CMOS divideby- two circuit is used for frequency division and quadrature phase generation. The VCO has a -109 dBc/Hz phase noise at 1 MHz frequency offset and a 2.35-2.5 GHz tuning range (after the frequency division), thus complying with ZigBee requirements.

Practical Applications and Connectivity Algorithms in Future Wireless Sensor Networks

Like any sentient organism, a smart environment relies first and foremost on sensory data captured from the real world. The sensory data come from sensor nodes of different modalities deployed on different locations forming a Wireless Sensor Network (WSN). Embedding smart sensors in humans has been a research challenge due to the limitations imposed by these sensors from computational capabilities to limited power. In this paper, we first propose a practical WSN application that will enable blind people to see what their neighboring partners can see. The challenge is that the actual mapping between the input images to brain pattern is too complex and not well understood. We also study the connectivity problem in 3D/2D wireless sensor networks and propose distributed efficient algorithms to accomplish the required connectivity of the system. We provide a new connectivity algorithm CDCA to connect disconnected parts of a network using cooperative diversity. Through simulations, we analyze the connectivity gains and energy savings provided by this novel form of cooperative diversity in WSNs.

Re-Thinking Knowledge-Based Management

This paper challenges the relevance of knowledgebased management research by arguing that the majority of the literature emphasizes information and knowledge provision instead of their business usage. For this reason the related processes are considered valuable and eligible as such, which has led to overlapping nature of knowledge-based management disciplines. As a solution, this paper turns the focus on the information usage. Value of knowledge and respective management tasks are then defined by the business need and the knowledge-user becomes the main actor. The paper analyses the prevailing literature streams and recognizes the need for a more focused and robust understanding of knowledgebased value creation. The paper contributes by synthetizing the existing literature and pinpointing the essence of knowledge-based management disciplines.

Modeling of Crude Oil Blending via Discrete-Time Neural Networks

Crude oil blending is an important unit operation in petroleum refining industry. A good model for the blending system is beneficial for supervision operation, prediction of the export petroleum quality and realizing model-based optimal control. Since the blending cannot follow the ideal mixing rule in practice, we propose a static neural network to approximate the blending properties. By the dead-zone approach, we propose a new robust learning algorithm and give theoretical analysis. Real data of crude oil blending is applied to illustrate the neuro modeling approach.

Data Transmission Reliability in Short Message Integrated Distributed Monitoring Systems

Short message integrated distributed monitoring systems (SM-DMS) are growing rapidly in wireless communication applications in various areas, such as electromagnetic field (EMF) management, wastewater monitoring, and air pollution supervision, etc. However, delay in short messages often makes the data embedded in SM-DMS transmit unreliably. Moreover, there are few regulations dealing with this problem in SMS transmission protocols. In this study, based on the analysis of the command and data requirements in the SM-DMS, we developed a processing model for the control center to solve the delay problem in data transmission. Three components of the model: the data transmission protocol, the receiving buffer pool method, and the timer mechanism were described in detail. Discussions on adjusting the threshold parameter in the timer mechanism were presented for the adaptive performance during the runtime of the SM-DMS. This model optimized the data transmission reliability in SM-DMS, and provided a supplement to the data transmission reliability protocols at the application level.

Strategies for Securing Safety Messages with Fixed Key Infrastructure in Vehicular Network

Vehicular communications play a substantial role in providing safety in transportation by means of safety message exchange. Researchers have proposed several solutions for securing safety messages. Protocols based on a fixed key infrastructure are more efficient in implementation and maintain stronger security in comparison with dynamic structures. These protocols utilize zone partitioning to establish distinct key infrastructure under Certificate Authority (CA) supervision in different regions. Secure anonymous broadcasting (SAB) is one of these protocols that preserves most of security aspects but it has some deficiencies in practice. A very important issue is region change of a vehicle for its mobility. Changing regions leads to change of CA and necessity of having new key set to resume communication. In this paper, we propose solutions for informing vehicles about region change to obtain new key set before entering next region. This hinders attackers- intrusion, packet loss and lessons time delay. We also make key request messages secure by confirming old CA-s public key to the message, hence stronger security for safety message broadcasting is attained.

Non-contact Gaze Tracking with Head Movement Adaptation based on Single Camera

With advances in computer vision, non-contact gaze tracking systems are heading towards being much easier to operate and more comfortable for use, the technique proposed in this paper is specially designed for achieving these goals. For the convenience in operation, the proposal aims at the system with simple configuration which is composed of a fixed wide angle camera and dual infrared illuminators. Then in order to enhance the usability of the system based on single camera, a self-adjusting method which is called Real-time gaze Tracking Algorithm with head movement Compensation (RTAC) is developed for estimating the gaze direction under natural head movement and simplifying the calibration procedure at the same time. According to the actual evaluations, the average accuracy of about 1° is achieved over a field of 20×15×15 cm3.

Octonionic Reformulation of Vector Analysis

According to celebrated Hurwitz theorem, there exists four division algebras consisting of R (real numbers), C (complex numbers), H (quaternions) and O (octonions). Keeping in view the utility of octonion variable we have tried to extend the three dimensional vector analysis to seven dimensional one. Starting with the scalar and vector product in seven dimensions, we have redefined the gradient, divergence and curl in seven dimension. It is shown that the identity n(n - 1)(n - 3)(n - 7) = 0 is satisfied only for 0, 1, 3 and 7 dimensional vectors. We have tried to write all the vector inequalities and formulas in terms of seven dimensions and it is shown that same formulas loose their meaning in seven dimensions due to non-associativity of octonions. The vector formulas are retained only if we put certain restrictions on octonions and split octonions.

Acquiring Contour Following Behaviour in Robotics through Q-Learning and Image-based States

In this work a visual and reactive contour following behaviour is learned by reinforcement. With artificial vision the environment is perceived in 3D, and it is possible to avoid obstacles that are invisible to other sensors that are more common in mobile robotics. Reinforcement learning reduces the need for intervention in behaviour design, and simplifies its adjustment to the environment, the robot and the task. In order to facilitate its generalisation to other behaviours and to reduce the role of the designer, we propose a regular image-based codification of states. Even though this is much more difficult, our implementation converges and is robust. Results are presented with a Pioneer 2 AT on a Gazebo 3D simulator.

Study of the Effectiveness of Outrigger System for High-Rise Composite Buildings for Cyclonic Region

The demands of taller structures are becoming imperative almost everywhere in the world in addition to the challenges of material and labor cost, project time line etc. This paper conducted a study keeping in view the challenging nature of high-rise construction with no generic rules for deflection minimizations and frequency control. The effects of cyclonic wind and provision of outriggers on 28-storey, 42-storey and 57-storey are examined in this paper and certain conclusions are made which would pave way for researchers to conduct further study in this particular area of civil engineering. The results show that plan dimensions have vital impacts on structural heights. Increase of height while keeping the plan dimensions same, leads to the reduction in the lateral rigidity. To achieve required stiffness increase of bracings sizes as well as introduction of additional lateral resisting system such as belt truss and outriggers is required.

Precombining Adaptive LMMSE Detection for DS-CDMA Systems in Time Varying Channels: Non Blind and Blind Approaches

This paper deals with an adaptive multiuser detector for direct sequence code division multiple-access (DS-CDMA) systems. A modified receiver, precombinig LMMSE is considered under time varying channel environment. Detector updating is performed with two criterions, mean square estimation (MSE) and MOE optimization technique. The adaptive implementation issues of these two schemes are quite different. MSE criterion updates the filter weights by minimizing error between data vector and adaptive vector. MOE criterion together with canonical representation of the detector results in a constrained optimization problem. Even though the canonical representation is very complicated under time varying channels, it is analyzed with assumption of average power profile of multipath replicas of user of interest. The performance of both schemes is studied for practical SNR conditions. Results show that for poor SNR, MSE precombining LMMSE is better than the blind precombining LMMSE but for greater SNR, MOE scheme outperforms with better result.

Vision Based Robotic Interception in Industrial Manipulation Tasks

In this paper, a solution is presented for a robotic manipulation problem in industrial settings. The problem is sensing objects on a conveyor belt, identifying the target, planning and tracking an interception trajectory between end effector and the target. Such a problem could be formulated as combining object recognition, tracking and interception. For this purpose, we integrated a vision system to the manipulation system and employed tracking algorithms. The control approach is implemented on a real industrial manipulation setting, which consists of a conveyor belt, objects moving on it, a robotic manipulator, and a visual sensor above the conveyor. The trjectory for robotic interception at a rendezvous point on the conveyor belt is analytically calculated. Test results show that tracking the raget along this trajectory results in interception and grabbing of the target object.

Urban Reforms of Tanzimat: Early Urbanization and Transportation Practices in The Formation Process of Turkish Reconstruction System(1839-1908) in Bursa The First Capital City of Ottoman Empire

Bursa, since the establishment of the Ottoman Empire, being on the important trade roads and having a capital accumulation as a result of silk production, was one of the first cities of modernization activities applied. Bursa maintained its importance even during the Republican Period and became one of the most important cities of the country and today is the fourth biggest and the industrialized city in Turkey. Social, political, economical and cultural changes occured with the reforms starting with the 1839 Edict of Tanzimat that aimed at modernizing the society and the government and centralizing the political power began in the Ottoman Empire. After the Tanzimat Reforms transformation of the city changed and planning processes began in Bursa according to the vision of Governors. The theresholds of the city are very important data for a sustainable planning for the city planners. Main aim of this study is to investigate the changes and transformations of the city according to the changes in the socio-economical and cultural properties for the city planners.

Overhead Estimation over Capacity of Mobile WiMAX

The IEEE802.16 standard which has emerged as Broadband Wireless Access (BWA) technology, promises to deliver high data rate over large areas to a large number of subscribers in the near future. This paper analyze the effect of overheads over capacity of downlink (DL) of orthogonal frequency division multiple access (OFDMA)–based on the IEEE802.16e mobile WiMAX system with and without overheads. The analysis focuses in particular on the impact of Adaptive Modulation and Coding (AMC) as well as deriving an algorithm to determine the maximum numbers of subscribers that each specific WiMAX sector may support. An analytical study of the WiMAX propagation channel by using Cost- 231 Hata Model is presented. Numerical results and discussion estimated by using Matlab to simulate the algorithm for different multi-users parameters.

A Novel Low Power, High Speed 14 Transistor CMOS Full Adder Cell with 50% Improvement in Threshold Loss Problem

Full adders are important components in applications such as digital signal processors (DSP) architectures and microprocessors. In addition to its main task, which is adding two numbers, it participates in many other useful operations such as subtraction, multiplication, division,, address calculation,..etc. In most of these systems the adder lies in the critical path that determines the overall speed of the system. So enhancing the performance of the 1-bit full adder cell (the building block of the adder) is a significant goal.Demands for the low power VLSI have been pushing the development of aggressive design methodologies to reduce the power consumption drastically. To meet the growing demand, we propose a new low power adder cell by sacrificing the MOS Transistor count that reduces the serious threshold loss problem, considerably increases the speed and decreases the power when compared to the static energy recovery full (SERF) adder. So a new improved 14T CMOS l-bit full adder cell is presented in this paper. Results show 50% improvement in threshold loss problem, 45% improvement in speed and considerable power consumption over the SERF adder and other different types of adders with comparable performance.

Combined Beamforming and Channel Estimation in WCDMA Communication Systems

We address the problem of joint beamforming and multipath channel parameters estimation in Wideband Code Division Multiple Access (WCDMA) communication systems that employ Multiple-Access Interference (MAI) suppression techniques in the uplink (from mobile to base station). Most of the existing schemes rely on time multiplex a training sequence with the user data. In WCDMA, the channel parameters can also be estimated from a code multiplexed common pilot channel (CPICH) that could be corrupted by strong interference resulting in a bad estimate. In this paper, we present new methods to combine interference suppression together with channel estimation when using multiple receiving antennas by using adaptive signal processing techniques. Computer simulation is used to compare between the proposed methods and the existing conventional estimation techniques.

Computer Vision Applied to Flower, Fruit and Vegetable Processing

This paper presents the theoretical background and the real implementation of an automated computer system to introduce machine vision in flower, fruit and vegetable processing for recollection, cutting, packaging, classification, or fumigation tasks. The considerations and implementation issues presented in this work can be applied to a wide range of varieties of flowers, fruits and vegetables, although some of them are especially relevant due to the great amount of units that are manipulated and processed each year over the world. The computer vision algorithms developed in this work are shown in detail, and can be easily extended to other applications. A special attention is given to the electromagnetic compatibility in order to avoid noisy images. Furthermore, real experimentation has been carried out in order to validate the developed application. In particular, the tests show that the method has good robustness and high success percentage in the object characterization.