Low Cost Real-Time Communication Braille Hand-Glove for Visually Impaired Using Slot Sensors and Vibration Motors

Visually impaired people find it extremely difficult to acquire basic and vital information necessary for their living. Therefore, they are at a very high risk of being socially excluded as a result of poor access to information. In recent years, several attempts have been made in improving the communication methods for visually impaired people which involve tactile sensation such as finger Braille, manual alphabets and the print on palm method and several other electronic devices. But, there are some problems which arise in such methods such as lack of privacy and lack of compatibility to computer environment. This paper describes a low cost Braille hand glove for blind people using slot sensors and vibration motors with the help of which they can read and write emails, text messages and read e-books. This glove allows the person to type characters based on different Braille combination using six slot sensors. The vibration in six different positions of the glove which matches to the Braille code allows them to read characters.

Detecting and Locating Wormhole Attacks in Wireless Sensor Networks Using Beacon Nodes

This paper focuses on wormhole attacks detection in wireless sensor networks. The wormhole attack is particularly challenging to deal with since the adversary does not need to compromise any nodes and can use laptops or other wireless devices to send the packets on a low latency channel. This paper introduces an easy and effective method to detect and locate the wormholes: Since beacon nodes are assumed to know their coordinates, the straight line distance between each pair of them can be calculated and then compared with the corresponding hop distance, which in this paper equals hop counts × node-s transmission range R. Dramatic difference may emerge because of an existing wormhole. Our detection mechanism is based on this. The approximate location of the wormhole can also be derived in further steps based on this information. To the best of our knowledge, our method is much easier than other wormhole detecting schemes which also use beacon nodes, and to those have special requirements on each nodes (e.g., GPS receivers or tightly synchronized clocks or directional antennas), ours is more economical. Simulation results show that the algorithm is successful in detecting and locating wormholes when the density of beacon nodes reaches 0.008 per m2.

On the EM Algorithm and Bootstrap Approach Combination for Improving Satellite Image Fusion

This paper discusses EM algorithm and Bootstrap approach combination applied for the improvement of the satellite image fusion process. This novel satellite image fusion method based on estimation theory EM algorithm and reinforced by Bootstrap approach was successfully implemented and tested. The sensor images are firstly split by a Bayesian segmentation method to determine a joint region map for the fused image. Then, we use the EM algorithm in conjunction with the Bootstrap approach to develop the bootstrap EM fusion algorithm, hence producing the fused targeted image. We proposed in this research to estimate the statistical parameters from some iterative equations of the EM algorithm relying on a reference of representative Bootstrap samples of images. Sizes of those samples are determined from a new criterion called 'hybrid criterion'. Consequently, the obtained results of our work show that using the Bootstrap EM (BEM) in image fusion improve performances of estimated parameters which involve amelioration of the fused image quality; and reduce the computing time during the fusion process.

[Ca(2,2'-bipyridine)3]2+ -Montmorillonite: A Potentiometric Sensor for Sulfide ion

Sulfide ion (S2-) is one of the most important ions to be monitored due to its high toxicity, especially for aquatic organisms. In this work, [Ca(2,2'-bipyridine)3]2+-intercalated montmorillonite was prepared and used as a sensor to construct a potentiometric electrode to measure sulfide ion in solution. The formation of [Ca(2,2'- bipyridine)3]2+ in montmorillonite was confirmed by Fourier Transform Infrared spectra. The electrode worked well at pH 4-12 and 4-10 in sulfide solution 10-2 M and 10-3 M, respectively, in terms of Nernstian slope. The sensor gave good precision and low cost.

Panoramic Sensor Based Blind Spot Accident Prevention System

There are many automotive accidents due to blind spots and driver inattentiveness. Blind spot is the area that is invisible to the driver's viewpoint without head rotation. Several methods are available for assisting the drivers. Simplest methods are — rear mirrors and wide-angle lenses. But, these methods have a disadvantage of the requirement for human assistance. So, the accuracy of these devices depends on driver. Another approach called an automated approach that makes use of sensors such as sonar or radar. These sensors are used to gather range information. The range information will be processed and used for detecting the collision. The disadvantage of this system is — low angular resolution and limited sensing volumes. This paper is a panoramic sensor based automotive vehicle monitoring..

RP-ADAS: Relative Position-Advanced Drive Assistant System based on VANET (GNSS)

Few decades ago, electronic and sensor technologies are merged into vehicles as the Advanced Driver Assistance System(ADAS). However, sensor-based ADASs have limitations about weather interference and a line-of-sight nature problem. In our project, we investigate a Relative Position based ADAS(RP-ADAS). We divide the RP-ADAS into four main research areas: GNSS, VANET, Security/Privacy, and Application. In this paper, we research the GNSS technologies and determine the most appropriate one. With the performance evaluation, we figure out that the C/A code based GPS technologies are inappropriate for 'which lane-level' application. However, they can be used as a 'which road-level' application.

Sensor Optimisation via H∞ Applied to a MAGLEV Suspension System

In this paper a systematic method via H∞ control design is proposed to select a sensor set that satisfies a number of input criteria for a MAGLEV suspension system. The proposed method recovers a number of optimised controllers for each possible sensor set that satisfies the performance and constraint criteria using evolutionary algorithms.

Security Architecture for At-Home Medical Care Using Sensor Network

This paper proposes a novel architecture for At- Home medical care which enables senior citizens, patients with chronic ailments and patients requiring post- operative care to be remotely monitored in the comfort of their homes. This architecture is implemented using sensors and wireless networking for transmitting patient data to the hospitals, health- care centers for monitoring by medical professionals. Patients are equipped with sensors to measure their physiological parameters, like blood pressure, pulse rate etc. and a Wearable Data Acquisition Unit is used to transmit the patient sensor data. Medical professionals can be alerted to any abnormal variations in these values for diagnosis and suitable treatment. Security threats and challenges inherent to wireless communication and sensor network have been discussed and a security mechanism to ensure data confidentiality and source authentication has been proposed. Symmetric key algorithm AES has been used for encrypting the data and a patent-free, two-pass block cipher mode CCFB has been used for implementing semantic security.

Insights into Smoothies with High Levels of Fibre and Polyphenols: Factors Influencing Chemical, Rheological and Sensory Properties

Attempts to add fibre and polyphenols (PPs) into popular beverages present challenges related to the properties of finished products such as smoothies. Consumer acceptability, viscosity and phenolic composition of smoothies containing high levels of fruit fibre (2.5-7.5 g per 300 mL serve) and PPs (250-750 mg per 300 mL serve) were examined. The changes in total extractable PP, vitamin C content, and colour of selected smoothies over a storage stability trial (4°C, 14 days) were compared. A set of acidic aqueous model beverages were prepared to further examine the effect of two different heat treatments on the stability and extractability of PPs. Results show that overall consumer acceptability of high fibre and PP smoothies was low, with average hedonic scores ranging from 3.9 to 6.4 (on a 1-9 scale). Flavour, texture and overall acceptability decreased as fibre and polyphenol contents increased, with fibre content exerting a stronger effect. Higher fibre content resulted in greater viscosity, with an elevated PP content increasing viscosity only slightly. The presence of fibre also aided the stability and extractability of PPs after heating. A reduction of extractable PPs, vitamin C content and colour intensity of smoothies was observed after a 14-day storage period at 4°C. Two heat treatments (75°C for 45 min or 85°C for 1 min) that are normally used for beverage production, did not cause significant reduction of total extracted PPs. It is clear that high levels of added fibre and PPs greatly influence the consumer appeal of smoothies, suggesting the need to develop novel formulation and processing methods if a satisfactory functional beverage is to be developed incorporating these ingredients.

The Optimization of an Intelligent Traffic Congestion Level Classification from Motorists- Judgments on Vehicle's Moving Patterns

We proposed a technique to identify road traffic congestion levels from velocity of mobile sensors with high accuracy and consistent with motorists- judgments. The data collection utilized a GPS device, a webcam, and an opinion survey. Human perceptions were used to rate the traffic congestion levels into three levels: light, heavy, and jam. Then the ratings and velocity were fed into a decision tree learning model (J48). We successfully extracted vehicle movement patterns to feed into the learning model using a sliding windows technique. The parameters capturing the vehicle moving patterns and the windows size were heuristically optimized. The model achieved accuracy as high as 99.68%. By implementing the model on the existing traffic report systems, the reports will cover comprehensive areas. The proposed method can be applied to any parts of the world.

Profile Controlled Gold Nanostructures Fabricated by Nanosphere Lithography for Localized Surface Plasmon Resonance

Localized surface plasmon resonance (LSPR) is the coherent oscillation of conductive electrons confined in noble metallic nanoparticles excited by electromagnetic radiation, and nanosphere lithography (NSL) is one of the cost-effective methods to fabricate metal nanostructures for LSPR. NSL can be categorized into two major groups: dispersed NSL and closely pack NSL. In recent years, gold nanocrescents and gold nanoholes with vertical sidewalls fabricated by dispersed NSL, and silver nanotriangles and gold nanocaps on silica nanospheres fabricated by closely pack NSL, have been reported for LSPR biosensing. This paper introduces several novel gold nanostructures fabricated by NSL in LSPR applications, including 3D nanostructures obtained by evaporating gold obliquely on dispersed nanospheres, nanoholes with slant sidewalls, and patchy nanoparticles on closely packed nanospheres, all of which render satisfactory sensitivity for LSPR sensing. Since the LSPR spectrum is very sensitive to the shape of the metal nanostructures, formulas are derived and software is developed for calculating the profiles of the obtainable metal nanostructures by NSL, for different nanosphere masks with different fabrication conditions. The simulated profiles coincide well with the profiles of the fabricated gold nanostructures observed under scanning electron microscope (SEM) and atomic force microscope (AFM), which proves that the software is a useful tool for the process design of different LSPR nanostructures.

A Novel Machining Signal Filtering Technique: Z-notch Filter

A filter is used to remove undesirable frequency information from a dynamic signal. This paper shows that the Znotch filter filtering technique can be applied to remove the noise nuisance from a machining signal. In machining, the noise components were identified from the sound produced by the operation of machine components itself such as hydraulic system, motor, machine environment and etc. By correlating the noise components with the measured machining signal, the interested components of the measured machining signal which was less interfered by the noise, can be extracted. Thus, the filtered signal is more reliable to be analysed in terms of noise content compared to the unfiltered signal. Significantly, the I-kaz method i.e. comprises of three dimensional graphical representation and I-kaz coefficient, Z∞ could differentiate between the filtered and the unfiltered signal. The bigger space of scattering and the higher value of Z∞ demonstrated that the signal was highly interrupted by noise. This method can be utilised as a proactive tool in evaluating the noise content in a signal. The evaluation of noise content is very important as well as the elimination especially for machining operation fault diagnosis purpose. The Z-notch filtering technique was reliable in extracting noise component from the measured machining signal with high efficiency. Even though the measured signal was exposed to high noise disruption, the signal generated from the interaction between cutting tool and work piece still can be acquired. Therefore, the interruption of noise that could change the original signal feature and consequently can deteriorate the useful sensory information can be eliminated.

Effect of Oxygen Annealing on the Surface Defects and Photoconductivity of Vertically Aligned ZnO Nanowire Array

Post growth annealing of solution grown ZnO nanowire array is performed under controlled oxygen ambience. The role of annealing over surface defects and their consequence on dark/photo-conductivity and photosensitivity of nanowire array is investigated. Surface defect properties are explored using various measurement tools such as contact angle, photoluminescence, Raman spectroscopy and XPS measurements. The contact angle of the NW films reduces due to oxygen annealing and nanowire film surface changes from hydrophobic (96°) to hydrophilic (16°). Raman and XPS spectroscopy reveal that oxygen annealing improves the crystal quality of the nanowire films. The defect band emission intensity (relative to band edge emission, ID/IUV) reduces from 1.3 to 0.2 after annealing at 600 °C at 10 SCCM flow of oxygen. An order enhancement in dark conductivity is observed in O2 annealed samples, while photoconductivity is found to be slightly reduced due to lower concentration of surface related oxygen defects.

Drafting the Design and Development of Micro- Controller Based Portable Soil Moisture Sensor for Advancement in Agro Engineering

Moisture is an important consideration in many aspects ranging from irrigation, soil chemistry, golf course, corrosion and erosion, road conditions, weather predictions, livestock feed moisture levels, water seepage etc. Vegetation and crops always depend more on the moisture available at the root level than on precipitation occurrence. In this paper, design of an instrument is discussed which tells about the variation in the moisture contents of soil. This is done by measuring the amount of water content in soil by finding the variation in capacitance of soil with the help of a capacitive sensor. The greatest advantage of soil moisture sensor is reduced water consumption. The sensor is also be used to set lower and upper threshold to maintain optimum soil moisture saturation and minimize water wilting, contributes to deeper plant root growth ,reduced soil run off /leaching and less favorable condition for insects and fungal diseases. Capacitance method is preferred because, it provides absolute amount of water content and also measures water content at any depth.

Design and Implementation of Cricket-based Location Tracking System

In this paper, we present a novel approach to location system under indoor environment. The key idea of our work is accurate distance estimation with cricket-based location system using A* algorithm. We also use magnetic sensor for detecting obstacles in indoor environment. Finally, we suggest how this system can be used in various applications such as asset tracking and monitoring.

Development of the Algorithm for Detecting Falls during Daily Activity using 2 Tri-Axial Accelerometers

Falls are the primary cause of accidents in people over the age of 65, and frequently lead to serious injuries. Since the early detection of falls is an important step to alert and protect the aging population, a variety of research on detecting falls was carried out including the use of accelerators, gyroscopes and tilt sensors. In exiting studies, falls were detected using an accelerometer with errors. In this study, the proposed method for detecting falls was to use two accelerometers to reject wrong falls detection. As falls are accompanied by the acceleration of gravity and rotational motion, the falls in this study were detected by using the z-axial acceleration differences between two sites. The falls were detected by calculating the difference between the analyses of accelerometers placed on two different positions on the chest of the subject. The parameters of the maximum difference of accelerations (diff_Z) and the integration of accelerations in a defined region (Sum_diff_Z) were used to form the fall detection algorithm. The falls and the activities of daily living (ADL) could be distinguished by using the proposed parameters without errors in spite of the impact and the change in the positions of the accelerometers. By comparing each of the axial accelerations, the directions of falls and the condition of the subject afterwards could be determined.In this study, by using two accelerometers without errors attached to two sites to detect falls, the usefulness of the proposed fall detection algorithm parameters, diff_Z and Sum_diff_Z, were confirmed.

Retina Based Mouse Control (RBMC)

The paper presents a novel idea to control computer mouse cursor movement with human eyes. In this paper, a working of the product has been described as to how it helps the special people share their knowledge with the world. Number of traditional techniques such as Head and Eye Movement Tracking Systems etc. exist for cursor control by making use of image processing in which light is the primary source. Electro-oculography (EOG) is a new technology to sense eye signals with which the mouse cursor can be controlled. The signals captured using sensors, are first amplified, then noise is removed and then digitized, before being transferred to PC for software interfacing.

Analyzing The Effect of Variable Round Time for Clustering Approach in Wireless Sensor Networks

As wireless sensor networks are energy constraint networks so energy efficiency of sensor nodes is the main design issue. Clustering of nodes is an energy efficient approach. It prolongs the lifetime of wireless sensor networks by avoiding long distance communication. Clustering algorithms operate in rounds. Performance of clustering algorithm depends upon the round time. A large round time consumes more energy of cluster heads while a small round time causes frequent re-clustering. So existing clustering algorithms apply a trade off to round time and calculate it from the initial parameters of networks. But it is not appropriate to use initial parameters based round time value throughout the network lifetime because wireless sensor networks are dynamic in nature (nodes can be added to the network or some nodes go out of energy). In this paper a variable round time approach is proposed that calculates round time depending upon the number of active nodes remaining in the field. The proposed approach makes the clustering algorithm adaptive to network dynamics. For simulation the approach is implemented with LEACH in NS-2 and the results show that there is 6% increase in network lifetime, 7% increase in 50% node death time and 5% improvement over the data units gathered at the base station.

Soft-Sensor for Estimation of Gasoline Octane Number in Platforming Processes with Adaptive Neuro-Fuzzy Inference Systems (ANFIS)

Gasoline Octane Number is the standard measure of the anti-knock properties of a motor in platforming processes, that is one of the important unit operations for oil refineries and can be determined with online measurement or use CFR (Cooperative Fuel Research) engines. Online measurements of the Octane number can be done using direct octane number analyzers, that it is too expensive, so we have to find feasible analyzer, like ANFIS estimators. ANFIS is the systems that neural network incorporated in fuzzy systems, using data automatically by learning algorithms of NNs. ANFIS constructs an input-output mapping based both on human knowledge and on generated input-output data pairs. In this research, 31 industrial data sets are used (21 data for training and the rest of the data used for generalization). Results show that, according to this simulation, hybrid method training algorithm in ANFIS has good agreements between industrial data and simulated results.

Enhancing Visual Basic GUI Applications using VRML Scenes

Rapid Application Development (RAD) enables ever expanding needs for speedy development of computer application programs that are sophisticated, reliable, and full-featured. Visual Basic was the first RAD tool for the Windows operating system, and too many people say still it is the best. To provide very good attraction in visual basic 6 applications, this paper directing to use VRML scenes over the visual basic environment.