Search results for: sensing dictionary.

Authors: H. Ucar, U. Aridogan

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Composite structures become intriguing for the design of aerospace, automotive and marine applications due to weight reduction, corrosion resistance and radar signature reduction demands and requirements. Studies on piezoelectric ceramic transducers (PZT) for diagnostics and health monitoring have gained attention for their sensing capabilities, however PZT structures are prone to fail in case of heavy operational loads. In this paper, we develop a piezo-based Glass Fiber Reinforced Polymer (GFRP) composite finite element (FE) model, validate with experimental setup, and identify the applicability and limitations of PZTs for a marine application. A case study is conducted to assess the piezo-based sensing capabilities in a representative marine composite structure. A FE model of the composite structure combined with PZT patches is developed, afterwards the response and functionality are investigated according to the sea conditions. Results of this study clearly indicate the blockers and critical aspects towards industrialization and wide-range use of PZTs for marine composite applications.

Keywords: FRP, marine composite, piezoelectric transducer, sea state, wave-induced loads.

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Authors: Julien Romieux, Fabio Verdicchio

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Wireless Sensor Networks (WSNs), which sense environmental data with battery-powered nodes, require multi-hop communication. This power-demanding task adds an extra workload that is unfairly distributed across the network. As a result, nodes run out of battery at different times: this requires an impractical individual node maintenance scheme. Therefore we investigate a new Cooperative Sensing approach that extends the WSN operational life and allows a more practical network maintenance scheme (where all nodes deplete their batteries almost at the same time). We propose a novel cooperative algorithm that derives a piecewise representation of the sensed signal while controlling approximation accuracy. Simulations show that our algorithm increases WSN operational life and spreads communication workload evenly. Results convey a counterintuitive conclusion: distributing workload fairly amongst nodes may not decrease the network power consumption and yet extend the WSN operational life. This is achieved as our cooperative approach decreases the workload of the most burdened cluster in the network.

Keywords: Cooperative signal processing, power management, signal representation, signal approximation, wireless sensor networks.

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Authors: Ruiheng Li, Amir Parsa Anvar, Amir M. Anvar, Tien-Fu Lu

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High redundancy and strong uncertainty are two main characteristics for underwater robotic manipulators with unlimited workspace and mobility, but they also make the motion planning and control difficult and complex. In order to setup the groundwork for the research on control schemes, the mathematical representation is built by using the Denavit-Hartenberg (D-H) method [9]&[12]; in addition to the geometry of the manipulator which was studied for establishing the direct and inverse kinematics. Then, the dynamic model is developed and used by employing the Lagrange theorem. Furthermore, derivation and computer simulation is accomplished using the MATLAB environment. The result obtained is compared with mechanical system dynamics analysis software, ADAMS. In addition, the creation of intelligent artificial skin using Interlink Force Sensing ResistorTM technology is presented as groundwork for future work

Keywords: Manipulator System, Robot, AUV, Denavit- Hartenberg method Lagrange theorem, MALTAB, ADAMS, Direct and Inverse Kinematics, Dynamics, PD Control-law, Interlink Force Sensing ResistorTM, intelligent artificial skin system.

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Authors: Reza Mohammadi, Mahmod R. Sahebi, Mehrnoosh Omati, Milad Vahidi

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Classification of high resolution polarimetric Synthetic Aperture Radar (PolSAR) images plays an important role in land cover and land use management. Recently, classification algorithms based on Bag of Visual Words (BOVW) model have attracted significant interest among scholars and researchers in and out of the field of remote sensing. In this paper, BOVW model with pixel based low-level features has been implemented to classify a subset of San Francisco bay PolSAR image, acquired by RADARSAR 2 in C-band. We have used segment-based decision-making strategy and compared the result with the result of traditional Support Vector Machine (SVM) classifier. 90.95% overall accuracy of the classification with the proposed algorithm has shown that the proposed algorithm is comparable with the state-of-the-art methods. In addition to increase in the classification accuracy, the proposed method has decreased undesirable speckle effect of SAR images.

Keywords: Bag of Visual Words, classification, feature extraction, land cover management, Polarimetric Synthetic Aperture Radar.

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Authors: Weishou Shen, Dong Liu, Di Ji, Haoyun Shen, Naifeng Lin

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Based on the field investigation and long term remote sensing data, the dynamics of the alpine wetland in the river basin and their response to climate change were studied. Results showed the alpine wetlands accounted for 3.73% of total basin in 2010. Lake and river appeared an increasing trend in the past 30 years, with an increase of 34.36 % and 24.57%. However, swamp exhibited a tendency of decreasing with 233.74 km2. Annual average temperature, maximum temperature, minimum temperature and precipitation in the river basin all exhibited an increasing trend, whereas relative humidity exhibited a decreasing trend. Ice and snow melting are main reasons of lake and river area enhancement and swamp area descend. There existed 91.78%-97.86% of reduced swamp converted into lakes on the basis of remote sensing image interpretation. China-s government policy of implementing development in the river basin is the major driving force of artificial wetland growth.

Keywords: alpine wetland dynamics, climate change, Yarlung Zangbo River basin

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Authors: Ki-Tae Park, Young-Joon Yu, Chin-Hyung Lee, Woosang Lee

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Recently, as the scale of construction projects has increases, more ground excavation for foundations is carried out than ever before. Consequently, damage to underground ducts (gas, water/sewage or oil pipelines, communication cables or power cable ducts) or superannuated pipelines frequently cause serious accidents resulting in damage to life and property. (In Korea, the total length of city water pipelines was approximately 2,000 km as of the end of 2009.) In addition, large amounts of damage caused by fractures, water and gas leakage caused by superannuation or damage to underground ducts in construction has been reported. Therefore, a system is required to precisely detect defects and deterioration in underground pipelines and the locations of such defects, for timely and accurate maintenance or replacement of the ducts. In this study, a system was developed which can locate underground structures (gas and water pipelines, power cable ducts, etc.) in 3D-coordinates and monitor the degree and position of defects using an Inertial Measurement Unit (IMU) sensing technique. The system can prevent damage to underground ducts and superannuated pipelines during construction, and provide reliable data for maintenance. The utility of the IMU sensing technique used in aircraft and ships in civil applications was verified.

Keywords: IMU, Pipelines, 3D-Coordinate, monitor.

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Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek

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Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.

Keywords: Distributed optical strain sensing, geotechnical monitoring, rock bolt stain measurement, bedding shear displacement.

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Authors: Sankaran Rajendran

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Remote sensing plays a vital role in mapping of resources and monitoring of environments of the earth. In the present research study, mapping and monitoring of clay siltations occurred in the Alkhod Dam of Muscat, Sultanate of Oman are carried out using low-cost multispectral Landsat and ASTER data. The dam is constructed across the Wadi Samail catchment for ground water recharge. The occurrence and spatial distribution of siltations in the dam are studied with five years of interval from the year 1987 of construction to 2014. The deposits are mainly due to the clay, sand and silt occurrences derived from the weathering rocks of ophiolite sequences occurred in the Wadi Samail catchment. The occurrences of clays are confirmed by minerals identification using ASTER VNIR-SWIR spectral bands and Spectral Angle Mapper supervised image processing method. The presence of clays and their spatial distribution are verified in the field. The study recommends the technique and the low-cost satellite data to similar region of the world.

Keywords: Alkhod Dam, ASTER Siltation, Landsat, Remote Sensing, Oman.

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Authors: Melis Inalpulat, Levent Genc, Unal Kizil, Tugce Civelek

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Livestock production is one of the most important components of rural economy. Due to the urban expansion, rural areas close to expanding cities transform into urban districts during the time. However, the legislations have some restrictions related to livestock farming in such administrative units since they tend to create environmental concerns like odor problems resulted from excessive manure production. Therefore, the existing animal operations should be moved from the settlement areas. This paper was focused on determination of suitable lands for livestock production in Canakkale province of Turkey using remote sensing (RS) data and GIS techniques. To achieve the goal, Formosat 2 and Landsat 8 imageries, Aster DEM, and 1:25000 scaled soil maps, village boundaries, and village livestock inventory records were used. The study was conducted using suitability analysis which evaluates the land in terms of limitations and potentials, and suitability range was categorized as Suitable (S) and Non-Suitable (NS). Limitations included the distances from main and crossroads, water resources and settlements, while potentials were appropriate values for slope, land use capability and land use land cover status. Village-based S land distribution results were presented, and compared with livestock inventories. Results showed that approximately 44230 ha area is inappropriate because of the distance limitations for roads and etc. (NS). Moreover, according to LULC map, 71052 ha area consists of forests, olive and other orchards, and thus, may not be suitable for building such structures (NS). In comparison, it was found that there are a total of 1228 ha S lands within study area. The village-based findings indicated that, in some villages livestock production continues on NS areas. Finally, it was suggested that organized livestock zones may be constructed to serve in more than one village after the detailed analysis complemented considering also political decisions, opinion of the local people, etc.

Keywords: GIS, livestock, LULC, remote sensing, suitable lands.

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Authors: Siddhartha Chauhan, Kumar S. Pandey, Prateek Chandra

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One of the key research issues in wireless sensor networks (WSNs) is how to efficiently deploy sensors to cover an area. In this paper, we present a Fishnet Based Dispatch Scheme (FiBDS) with energy aware mobility and interest based sensing angle. We propose two algorithms, one is FiBDS centralized algorithm and another is FiBDS distributed algorithm. The centralized algorithm is designed specifically for the non-time critical applications, commonly known as non real-time applications while the distributed algorithm is designed specifically for the time critical applications, commonly known as real-time applications. The proposed dispatch scheme works in a phase-selection manner. In this in each phase a specific constraint is dealt with according to the specified priority and then moved onto the next phase and at the end of each only the best suited nodes for the phase are chosen. Simulation results are presented to verify their effectiveness. 

Keywords: Dispatch Scheme, Energy Aware Mobility, Interest based Sensing, Wireless Sensor Networks (WSNs).

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Authors: Hoda Zolfagharnejad, Behnam Kamkar, Omid Abdi

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Crop coefficient (Kc) is an important factor contributing to estimation of evapotranspiration, and is also used to determine the irrigation schedule. This study investigated and determined the monthly Kc of winter wheat (Triticum aestivum L.) using five vegetation indices (VIs): Normalized Difference Vegetation Index (NDVI), Difference Vegetation Index (DVI), Soil Adjusted Vegetation Index (SAVI), Infrared Percentage Vegetation Index (IPVI), and Ratio Vegetation Index (RVI) of four basins in Golestan province, Iran. 14 Landsat-8 images according to crop growth stage were used to estimate monthly Kc of wheat. VIs were calculated based on infrared and near infrared bands of Landsat 8 images using Geographical Information System (GIS) software. The best VIs were chosen after establishing a regression relationship among these VIs with FAO Kc and Kc that was modified for the study area by the previous research based on R² and Root Mean Square Error (RMSE). The result showed that local modified SAVI with R²= 0.767 and RMSE= 0.174 was the best index to produce monthly wheat Kc maps.

Keywords: Crop coefficient, remote sensing, vegetation indices, wheat.

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Authors: Rustam Asnawi, Wan Fatimah Wan Ahmad

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Currently electronic slide (e-slide) is one of the most common styles in educational presentation. Unfortunately, the utilization of e-slide for the visually impaired is uncommon since they are unable to see the content of such e-slides which are usually composed of text, images and animation. This paper proposes a model for presenting e-slide in multimodal presentation i.e. using conventional slide concurrent with voicing, in both languages Malay and English. At the design level, live multimedia presentation concept is used, while at the implementation level several components are used. The text content of each slide is extracted using COM component, Microsoft Speech API for voicing the text in English language and the text in Malay language is voiced using dictionary approach. To support the accessibility, an auditory user interface is provided as an additional feature. A prototype of such model named as VSlide has been developed and introduced.

Keywords: presentation, self-learning, slide, visually impaired

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Authors: A. Junpen, S. Garivait, S. Bonnet, A. Pongpullponsak

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The forest fires in Thailand are annual occurrence which is the cause of air pollutions. This study intended to estimate the emission from forest fire during 2005-2009 using MODerateresolution Imaging Spectro-radiometer (MODIS) sensor aboard the Terra and Aqua satellites, experimental data, and statistical data. The forest fire emission is estimated using equation established by Seiler and Crutzen in 1982. The spatial and temporal variation of forest fire emission is analyzed and displayed in the form of grid density map. From the satellite data analysis suggested between 2005 and 2009, the number of fire hotspots occurred 86,877 fire hotspots with a significant highest (more than 80% of fire hotspots) in the deciduous forest. The peak period of the forest fire is in January to May. The estimation on the emissions from forest fires during 2005 to 2009 indicated that the amount of CO, CO2, CH4, and N2O was about 3,133,845 tons, 47,610.337 tons, 204,905 tons, and 6,027 tons, respectively, or about 6,171,264 tons of CO2eq. They also emitted 256,132 tons of PM10. The year 2007 was found to be the year when the emissions were the largest. Annually, March is the period that has the maximum amount of forest fire emissions. The areas with high density of forest fire emission were the forests situated in the northern, the western, and the upper northeastern parts of the country.

Keywords: Emissions, Forest fire, Remote sensing information.

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Authors: Linyu Wang, Furui Huo, Jianhong Xiang

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The Doppler shift generated by high-speed movement and multipath effects in the channel are the main reasons for the generation of a time-frequency doubly-selective (DS) channel. There is severe inter-carrier interference (ICI) in the DS channel. Channel estimation for an orthogonal frequency division multiplexing (OFDM) system over a DS channel is very difficult. The simultaneous orthogonal matching pursuit (SOMP) algorithm under distributed compressive sensing theory (DCS-SOMP) has been used in channel estimation for OFDM systems over DS channels. However, the reconstruction accuracy of the DCS-SOMP algorithm is not high enough in the low Signal-to-Noise Ratio (SNR) stage. To solve this problem, in this paper, we propose an improved DCS-SOMP algorithm based on the inner product difference comparison operation (DCS-DCSOMP). The reconstruction accuracy is improved by increasing the number of candidate indexes and designing the comparison conditions of inner product difference. We combine the DCS-DCSOMP algorithm with the basis expansion model (BEM) to reduce the complexity of channel estimation. Simulation results show the effectiveness of the proposed algorithm and its advantages over other algorithms.

Keywords: OFDM, doubly selective, channel estimation, compressed sensing

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Authors: Sadia Iqbal, Faheem Iqbal, Furqan Iqbal

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Efficient utilization of existing water is a pressing need for Pakistan. Due to rising population, reduction in present storage capacity and poor delivery efficiency of 30 to 40% from canal. A study to evaluate an irrigation system in the cotton-wheat zone of Pakistan, after the watercourse lining was conducted. The study is made on the basis of cropping pattern and salinity to evaluate the system. This study employed an index-based approach of using Geographic information system with field data. The satellite images of different years were use to examine the effective area. Several combinations of the ratio of signals received in different spectral bands were used for development of this index. Near Infrared and Thermal IR spectral bands proved to be most effective as this combination helped easy detection of salt affected area and cropping pattern of the study area. Result showed that 9.97% area under salinity in 1992, 9.17% in 2000 and it left 2.29% in year 2005. Similarly in 1992, 45% area is under vegetation it improves to 56% and 65% in 2000 and 2005 respectively. On the basis of these results evaluation is done 30% performance is increase after the watercourse improvement.

Keywords: Salinity, remote sensing index, salinity index, cropping pattern.

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Authors: Mahesh Pal

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In recent years, a number of works proposing the combination of multiple classifiers to produce a single classification have been reported in remote sensing literature. The resulting classifier, referred to as an ensemble classifier, is generally found to be more accurate than any of the individual classifiers making up the ensemble. As accuracy is the primary concern, much of the research in the field of land cover classification is focused on improving classification accuracy. This study compares the performance of four ensemble approaches (boosting, bagging, DECORATE and random subspace) with a univariate decision tree as base classifier. Two training datasets, one without ant noise and other with 20 percent noise was used to judge the performance of different ensemble approaches. Results with noise free data set suggest an improvement of about 4% in classification accuracy with all ensemble approaches in comparison to the results provided by univariate decision tree classifier. Highest classification accuracy of 87.43% was achieved by boosted decision tree. A comparison of results with noisy data set suggests that bagging, DECORATE and random subspace approaches works well with this data whereas the performance of boosted decision tree degrades and a classification accuracy of 79.7% is achieved which is even lower than that is achieved (i.e. 80.02%) by using unboosted decision tree classifier.

Keywords: Ensemble learning, decision tree, remote sensingclassification.

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Authors: Bernard Kumi-Boateng, Issaka Yakubu

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Forest fire, which is, an uncontrolled fire occurring in nature has become a major concern for the Forestry Commission of Ghana (FCG). The forest fires in Ghana usually result in massive destruction and take a long time for the firefighting crews to gain control over the situation. In order to assess the effect of forest fire at local scale, it is important to consider the role fire plays in vegetation composition, biodiversity, soil erosion, and the hydrological cycle. The occurrence, frequency and behaviour of forest fires vary over time and space, primarily as a result of the complicated influences of changes in land use, vegetation composition, fire suppression efforts, and other indigenous factors. One of the forest zones in Ghana with a high level of vegetation stress is the Goaso forest area. The area has experienced changes in its traditional land use such as hunting, charcoal production, inefficient logging practices and rural abandonment patterns. These factors which were identified as major causes of forest fire, have recently modified the incidence of fire in the Goaso area. In spite of the incidence of forest fires in the Goaso forest area, most of the forest services do not provide a cartographic representation of the burned areas. This has resulted in significant amount of information being required by the firefighting unit of the FCG to understand fire risk factors and its spatial effects. This study uses Remote Sensing and Geographic Information System techniques to develop a fire risk hazard model using the Goaso Forest Area (GFA) as a case study. From the results of the study, natural forest, agricultural lands and plantation cover types were identified as the major fuel contributing loads. However, water bodies, roads and settlements were identified as minor fuel contributing loads. Based on the major and minor fuel contributing loads, a forest fire risk hazard model with a reasonable accuracy has been developed for the GFA to assist decision making.

Keywords: Forest risk, GIS, remote sensing, Goaso.

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Authors: Ahmad Sharif Ahmadi, Yoshitaka Kajita

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With massive population expansion and fast economic development in last decade, urban land has increasingly expanded and formed high informal development territory in Kabul city. This paper investigates integrated urbanization trends in Kabul city since the formation of the basic structure of the present city using GIS and remote sensing. This study explores the spatial and temporal difference of urban land expansion and land use categories among different time intervals, 1964-1978 and 1978-2008 from 1964 to 2008 in Kabul city. Furthermore, the goal of this paper is to understand the extent of urban land expansion and the factors driving urban land expansion in Kabul city. Many factors like population expansion, the return of refugees from neighboring countries and significant economic growth of the city affected urban land expansion. Across all the study area urban land expansion rate, population expansion rate and economic growth rate have been compared to analyze the relationship of driving forces with urban land expansion. Based on urban land change data detected by interpreting land use maps, it was found that in the entire study area the urban territory has been expanded by 14 times between 1964 and 2008.

Keywords: GIS, Kabul city, land use, urban land expansion, urbanization.

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Authors: F. F. Howard, C. B. Boye, I. Yakubu, J. S. Y. Kuma

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One of the ways that could be used for the production of land use and land cover maps by a procedure known as image classification is the use of the remote sensing technique. Numerous elements ought to be taken into consideration, including the availability of highly satisfactory Landsat imagery, secondary data and a precise classification process. The goal of this study was to classify and map the land use and land cover of the study area using remote sensing and Geospatial Information System (GIS) analysis. The classification was done using Landsat 8 satellite images acquired in December 2020 covering the study area. The Landsat image was downloaded from the USGS. The Landsat image with 30 m resolution was geo-referenced to the WGS_84 datum and Universal Transverse Mercator (UTM) Zone 30N coordinate projection system. A radiometric correction was applied to the image to reduce the noise in the image. This study consists of two sections: the Land Use/Land Cover (LULC) and Accuracy Assessments using the confusion and contingency matrix and the Kappa coefficient. The LULC classifications were vegetation (agriculture) (67.87%), water bodies (0.01%), mining areas (5.24%), forest (26.02%), and settlement (0.88%). The overall accuracy of 97.87% and the kappa coefficient (K) of 97.3% were obtained for the confusion matrix. While an overall accuracy of 95.7% and a Kappa coefficient of 0.947 were obtained for the contingency matrix, the kappa coefficients were rated as substantial; hence, the classified image is fit for further research.

Keywords: Confusion Matrix, contingency matrix, kappa coefficient, land used/ land cover, accuracy assessment.

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Authors: Xi Wang, Xiaoming Tao, Raymond C. H. So

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As one of the convenient and noninvasive sensing approaches, the automatic limb girth measurement has been applied to detect intention behind human motion from muscle deformation. The sensing validity has been elaborated by preliminary researches but still need more fundamental studies, especially on kinetic contraction modes. Based on the novel fabric strain sensors, a soft and smart limb girth measurement system was developed by the authors’ group, which can measure the limb girth in-motion. Experiments were carried out on elbow isometric flexion and elbow isokinetic flexion (biceps’ isokinetic contractions) of 90°/s, 60°/s, and 120°/s for 10 subjects (2 canoeists and 8 ordinary people). After removal of natural circumferential increments due to elbow position, the joint torque is found not uniformly sensitive to the limb circumferential strains, but declining as elbow joint angle rises, regardless of the angular speed. Moreover, the maximum joint torque was found as an exponential function of the joint’s angular speed. This research highly contributes to the application of the automatic limb girth measuring during kinetic contractions, and it is useful to predict the contraction level of voluntary skeletal muscles.

Keywords: Fabric strain sensor, muscle deformation, isokinetic contraction, joint torque, limb girth strain.

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Authors: Aqsa Ali, Aleem Mushtaq, Attaullah Memon, Monna

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In this paper, we present a low cost design for a smart glove that can perform sign language recognition to assist the speech impaired people. Specifically, we have designed and developed an Assistive Hand Gesture Interpreter that recognizes hand movements relevant to the American Sign Language (ASL) and translates them into text for display on a Thin-Film-Transistor Liquid Crystal Display (TFT LCD) screen as well as synthetic speech. Linear Bayes Classifiers and Multilayer Neural Networks have been used to classify 11 feature vectors obtained from the sensors on the glove into one of the 27 ASL alphabets and a predefined gesture for space. Three types of features are used; bending using six bend sensors, orientation in three dimensions using accelerometers and contacts at vital points using contact sensors. To gauge the performance of the presented design, the training database was prepared using five volunteers. The accuracy of the current version on the prepared dataset was found to be up to 99.3% for target user. The solution combines electronics, e-textile technology, sensor technology, embedded system and machine learning techniques to build a low cost wearable glove that is scrupulous, elegant and portable.

Keywords: American sign language, assistive hand gesture interpreter, human-machine interface, machine learning, sensing glove.

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Authors: Yanchao Wang, Rajshekhar Sunderraman

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This paper presents an algebraic approach to optimize queries in domain-specific database management system for protein structure data. The approach involves the introduction of several protein structure specific algebraic operators to query the complex data stored in an object-oriented database system. The Protein Algebra provides an extensible set of high-level Genomic Data Types and Protein Data Types along with a comprehensive collection of appropriate genomic and protein functions. The paper also presents a query translator that converts high-level query specifications in algebra into low-level query specifications in Protein-QL, a query language designed to query protein structure data. The query transformation process uses a Protein Ontology that serves the purpose of a dictionary.

Keywords: Domain-Specific Data Management, Protein Algebra, Protein Ontology, Protein Structure Data.

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Authors: Arash Habibi Lashkari, Azizah Abdul Manaf, Maslin Masrom

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In today's day and age, one of the important topics in information security is authentication. There are several alternatives to text-based authentication of which includes Graphical Password (GP) or Graphical User Authentication (GUA). These methods stems from the fact that humans recognized and remembers images better than alphanumerical text characters. This paper will focus on the security aspect of GP algorithms and what most researchers have been working on trying to define these security features and attributes. The goal of this study is to develop a fuzzy decision model that allows automatic selection of available GP algorithms by taking into considerations the subjective judgments of the decision makers who are more than 50 postgraduate students of computer science. The approach that is being proposed is based on the Fuzzy Analytic Hierarchy Process (FAHP) which determines the criteria weight as a linear formula.

Keywords: Graphical Password, Authentication Security, Attack Patterns, Brute force attack, Dictionary attack, Guessing Attack, Spyware attack, Shoulder surfing attack, Social engineering Attack, Password Entropy, Password Space.

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Authors: Sanaeinejad, S. H.; A. Astaraei, . P. Mirhoseini.Mousavi, M. Ghaemi,

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One of the main environmental problems which affect extensive areas in the world is soil salinity. Traditional data collection methods are neither enough for considering this important environmental problem nor accurate for soil studies. Remote sensing data could overcome most of these problems. Although satellite images are commonly used for these studies, however there are still needs to find the best calibration between the data and real situations in each specified area. Neyshaboor area, North East of Iran was selected as a field study of this research. Landsat satellite images for this area were used in order to prepare suitable learning samples for processing and classifying the images. 300 locations were selected randomly in the area to collect soil samples and finally 273 locations were reselected for further laboratory works and image processing analysis. Electrical conductivity of all samples was measured. Six reflective bands of ETM+ satellite images taken from the study area in 2002 were used for soil salinity classification. The classification was carried out using common algorithms based on the best composition bands. The results showed that the reflective bands 7, 3, 4 and 1 are the best band composition for preparing the color composite images. We also found out, that hybrid classification is a suitable method for identifying and delineation of different salinity classes in the area.

Keywords: Soil salinity, Remote sensing, Image processing, ETM+, Nyshaboor

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Authors: Kjersti Engan, Karl Skretting, Jostein Herredsvela, Thor Ole Gulsrud

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Texture classification is an important image processing task with a broad application range. Many different techniques for texture classification have been explored. Using sparse approximation as a feature extraction method for texture classification is a relatively new approach, and Skretting et al. recently presented the Frame Texture Classification Method (FTCM), showing very good results on classical texture images. As an extension of that work the FTCM is here tested on a real world application as detection of abnormalities in mammograms. Some extensions to the original FTCM that are useful in some applications are implemented; two different smoothing techniques and a vector augmentation technique. Both detection of microcalcifications (as a primary detection technique and as a last stage of a detection scheme), and soft tissue lesions in mammograms are explored. All the results are interesting, and especially the results using FTCM on regions of interest as the last stage in a detection scheme for microcalcifications are promising.

Keywords: detection, mammogram, texture classification, dictionary learning, FTCM

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Authors: Sanaz Seraj, Shohre Rouhani

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Recently, graphene has gained much attention because of its unique optical, mechanical, electrical, and thermal properties. Graphene has been used as a key material in the technological applications in various areas such as sensors, drug delivery, super capacitors, transparent conductor, and solar cell. It has a superior quenching efficiency for various fluorophores. Based on these unique properties, the optical sensors with graphene materials as the energy acceptors have demonstrated great success in recent years. During quenching, the emission of a fluorophore is perturbed by a quencher which can be a substrate or biomolecule, and due to this phenomenon, fluorophore-quencher has been used for selective detection of target molecules. Among fluorescence dyes, 1,8-naphthalimide is well known for its typical intramolecular charge transfer (ICT) and photo-induced charge transfer (PET) fluorophore, strong absorption and emission in the visible region, high photo stability, and large Stokes shift. Derivatives of 1,8-naphthalimides have found applications in some areas, especially fluorescence sensors. Herein, the fluorescence quenching of graphene oxide has been carried out on a naphthalimide dye as a fluorescent probe model. The quenching ability of graphene oxide on naphthalimide dye was studied by UV-VIS and fluorescence spectroscopy. This study showed that graphene is an efficient quencher for fluorescent dyes. Therefore, it can be used as a suitable candidate sensing platform. To the best of our knowledge, studies on the quenching and absorption of naphthalimide dyes by graphene oxide are rare.

Keywords: Fluorescence, graphene oxide, naphthalimide dye, quenching.

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Authors: Akella Amarendra Babu, Rama Devi Yellasiri, Natukula Sainath

Abstract:

Where human beings can easily learn and adopt pronunciation variations, machines need training before put into use. Also humans keep minimum vocabulary and their pronunciation variations are stored in front-end of their memory for ready reference, while machines keep the entire pronunciation dictionary for ready reference. Supervised methods are used for preparation of pronunciation dictionaries which take large amounts of manual effort, cost, time and are not suitable for real time use. This paper presents an unsupervised adaptation model for building agile and dynamic pronunciation dictionaries online. These methods mimic human approach in learning the new pronunciations in real time. A new algorithm for measuring sound distances called Dynamic Phone Warping is presented and tested. Performance of the system is measured using an adaptation model and the precision metrics is found to be better than 86 percent.

Keywords: Pronunciation variations, dynamic programming, machine learning, natural language processing.

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Authors: Mohd Hasmadi Ismail, Kamaruzaman Jusoff

Abstract:

In order to develop forest management strategies in tropical forest in Malaysia, surveying the forest resources and monitoring the forest area affected by logging activities is essential. There are tremendous effort has been done in classification of land cover related to forest resource management in this country as it is a priority in all aspects of forest mapping using remote sensing and related technology such as GIS. In fact classification process is a compulsory step in any remote sensing research. Therefore, the main objective of this paper is to assess classification accuracy of classified forest map on Landsat TM data from difference number of reference data (200 and 388 reference data). This comparison was made through observation (200 reference data), and interpretation and observation approaches (388 reference data). Five land cover classes namely primary forest, logged over forest, water bodies, bare land and agricultural crop/mixed horticultural can be identified by the differences in spectral wavelength. Result showed that an overall accuracy from 200 reference data was 83.5 % (kappa value 0.7502459; kappa variance 0.002871), which was considered acceptable or good for optical data. However, when 200 reference data was increased to 388 in the confusion matrix, the accuracy slightly improved from 83.5% to 89.17%, with Kappa statistic increased from 0.7502459 to 0.8026135, respectively. The accuracy in this classification suggested that this strategy for the selection of training area, interpretation approaches and number of reference data used were importance to perform better classification result.

Keywords: Image Classification, Reference Data, Accuracy Assessment, Kappa Statistic, Forest Land Cover

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Authors: Md. Asraful Haque, Babbar Imam

Abstract:

Information Security is the most describing problem in present times. To cop up with the security of the information, the passwords were introduced. The alphanumeric passwords are the most popular authentication method and still used up to now. However, text based passwords suffer from various drawbacks such as they are easy to crack through dictionary attacks, brute force attacks, keylogger, social engineering etc. Graphical Password is a good replacement for text password. Psychological studies say that human can remember pictures better than text. So this is the fact that graphical passwords are easy to remember. But at the same time due to this reason most of the graphical passwords are prone to shoulder surfing. In this paper, we have suggested a shoulder-surfing resistant graphical password authentication method. The system is a combination of recognition and pure recall based techniques. Proposed scheme can be useful for smart hand held devices (like smart phones i.e. PDAs, iPod, iPhone, etc) which are more handy and convenient to use than traditional desktop computer systems.

Keywords: Authentication, Graphical Password, Text Password, Information Security, Shoulder-surfing.

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Authors: Umm-e- Kalsoom, M. Arshad, Sadia Iqbal, M. Usman, M. Adnan

Abstract:

The research study evaluated the performance of irrigation system by using special scientific tools like Remote Sensing and GIS technology, so that proper measurements could be taken for the sustainable agriculture and water management. Different performance evaluation parameters had been calculated for the purposed data was gathered from field investigation and different government and private organizations. According to the calculations, organic matter ranges from 0.19% (low value) to 0.76% (high value). In flat irrigation system for wheat yield ranges from 3347.16 to 5260.39 kg/ha, while the total water applied to wheat crop ranges from 252.94 to 279.19 mm and WUE ranges from 13.07 to 18.37 kg/ha/mm. For rice yield ranges from 3347.47 to 5433.07 kg/ha with total water supplied to rice crop ranges from 764.71 to 978.15 mm and WUE ranges from 3.49 to 5.71 kg/ha/mm. Similarly, in raised bed system wheat yield ranges from 4569.13 to 6008.60 kg/ha, total water supplied ranges from 158.87 to 185.09 mm and WUE ranges from 27.20 to 33.54 kg/ha/mm while in rice crop, yield ranges from 5285.04 to 6716.69 kg/ha, total water supplied ranges from 600.72 to 755.06 mm and WUE ranges from 6.41 to 10.05 kg/ha/mm. Almost 51.3% water saving is observed in bed irrigation system as compared to flat system. Less water supplied to beds is more affective as its WUE value is higher than flat system where more water is supplied in both the seasons. Similarly, RWS values show that maximum water deficit while minimum area is getting adequate water supply. Greater yield is recorded in bed system as plant per square meter is more in bed system in comparison of flat system Thus, the integration of GIS tools to regularly compute performance indices could provide irrigation managers with the means for managing efficiently the irrigation system.

Keywords: Field survey, Relative Water Supply (RWS), Remote sensing maps, Water Use Efficiency (WUE).

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