Search results for: automatic processing
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 4353

Search results for: automatic processing

2343 Functionalized PU Foam for Water Filtration

Authors: Nidal H. Abu-Zahra, Subhashini Gunashekar

Abstract:

Polyurethane foam is functionalized with Sulfonic acid groups to remove lead ions (Pb2+) from drinking water through a action exchange process. The synthesis is based on addition polymerization of the -NCO groups of an isocyanine with the –OH groups of a polio to form the urethane. Toluene-diisocyanateis reacted with Polypropylene glycol to form a linear pre-polymer, which is further polymerized using a chain extender, N, N-bis(2-hydorxyethyl)-2-aminoethane-sulfonic acid (BES). BES acts as a functional group site to exchange Pb2+ ions. A set of experiments was designed to study the effect of various processing parameters on the performance of the synthesized foam. The maximum Pb2+ ion exchange capacity of the foam was found to be 47ppb/g from a 100ppb Pb2+ solution over a period of 60 minutes. A multistage batch filtration process increased the lead removal to 50-54ppb/3g of foam over a period of 90 minutes.

Keywords: adsorption, functionalized, ion exchange, polyurethane, sulfonic

Procedia PDF Downloads 241
2342 Channel Estimation for LTE Downlink

Authors: Rashi Jain

Abstract:

The LTE systems employ Orthogonal Frequency Division Multiplexing (OFDM) as the multiple access technology for the Downlink channels. For enhanced performance, accurate channel estimation is required. Various algorithms such as Least Squares (LS), Minimum Mean Square Error (MMSE) and Recursive Least Squares (RLS) can be employed for the purpose. The paper proposes channel estimation algorithm based on Kalman Filter for LTE-Downlink system. Using the frequency domain pilots, the initial channel response is obtained using the LS criterion. Then Kalman Filter is employed to track the channel variations in time-domain. To suppress the noise within a symbol, threshold processing is employed. The paper draws comparison between the LS, MMSE, RLS and Kalman filter for channel estimation. The parameters for evaluation are Bit Error Rate (BER), Mean Square Error (MSE) and run-time.

Keywords: LTE, channel estimation, OFDM, RLS, Kalman filter, threshold

Procedia PDF Downloads 349
2341 Performance Analysis with the Combination of Visualization and Classification Technique for Medical Chatbot

Authors: Shajida M., Sakthiyadharshini N. P., Kamalesh S., Aswitha B.

Abstract:

Natural Language Processing (NLP) continues to play a strategic part in complaint discovery and medicine discovery during the current epidemic. This abstract provides an overview of performance analysis with a combination of visualization and classification techniques of NLP for a medical chatbot. Sentiment analysis is an important aspect of NLP that is used to determine the emotional tone behind a piece of text. This technique has been applied to various domains, including medical chatbots. In this, we have compared the combination of the decision tree with heatmap and Naïve Bayes with Word Cloud. The performance of the chatbot was evaluated using accuracy, and the results indicate that the combination of visualization and classification techniques significantly improves the chatbot's performance.

Keywords: sentimental analysis, NLP, medical chatbot, decision tree, heatmap, naïve bayes, word cloud

Procedia PDF Downloads 67
2340 Development of Immersive Virtual Reality System for Planning of Cargo Loading Operations

Authors: Eugene Y. C. Wong, Daniel Y. W. Mo, Cosmo T. Y. Ng, Jessica K. Y. Chan, Leith K. Y. Chan, Henry Y. K. Lau

Abstract:

The real-time planning visualisation, precise allocation and loading optimisation in air cargo load planning operations are increasingly important as more considerations are needed on dangerous cargo loading, locations of lithium batteries, weight declaration and limited aircraft capacity. The planning of the unit load devices (ULD) can often be carried out only in a limited number of hours before flight departure. A dynamic air cargo load planning system is proposed with the optimisation of cargo load plan and visualisation of planning results in virtual reality systems. The system aims to optimise the cargo load planning and visualise the simulated loading planning decision on air cargo terminal operations. Adopting simulation tools, Cave Automatic Virtual Environment (CAVE) and virtual reality technologies, the results of planning with reference to weight and balance, Unit Load Device (ULD) dimensions, gateway, cargo nature and aircraft capacity are optimised and presented. The virtual reality system facilities planning, operations, education and training. Staff in terminals are usually trained in a traditional push-approach demonstration with enormous manual paperwork. With the support of newly customized immersive visualization environment, users can master the complex air cargo load planning techniques in a problem based training with the instant result being immersively visualised. The virtual reality system is developed with three-dimensional (3D) projectors, screens, workstations, truss system, 3D glasses, and demonstration platform and software. The content will be focused on the cargo planning and loading operations in an air cargo terminal. The system can assist decision-making process during cargo load planning in the complex operations of air cargo terminal operations. The processes of cargo loading, cargo build-up, security screening, and system monitoring can be further visualised. Scenarios are designed to support and demonstrate the daily operations of the air cargo terminal, including dangerous goods, pets and animals, and some special cargos.

Keywords: air cargo load planning, optimisation, virtual reality, weight and balance, unit load device

Procedia PDF Downloads 340
2339 Digital Cinema Watermarking State of Art and Comparison

Authors: H. Kelkoul, Y. Zaz

Abstract:

Nowadays, the vigorous popularity of video processing techniques has resulted in an explosive growth of multimedia data illegal use. So, watermarking security has received much more attention. The purpose of this paper is to explore some watermarking techniques in order to observe their specificities and select the finest methods to apply in digital cinema domain against movie piracy by creating an invisible watermark that includes the date, time and the place where the hacking was done. We have studied three principal watermarking techniques in the frequency domain: Spread spectrum, Wavelet transform domain and finally the digital cinema watermarking transform domain. In this paper, a detailed technique is presented where embedding is performed using direct sequence spread spectrum technique in DWT transform domain. Experiment results shows that the algorithm provides high robustness and good imperceptibility.

Keywords: digital cinema, watermarking, wavelet DWT, spread spectrum, JPEG2000 MPEG4

Procedia PDF Downloads 247
2338 Road Vehicle Recognition Using Magnetic Sensing Feature Extraction and Classification

Authors: Xiao Chen, Xiaoying Kong, Min Xu

Abstract:

This paper presents a road vehicle detection approach for the intelligent transportation system. This approach mainly uses low-cost magnetic sensor and associated data collection system to collect magnetic signals. This system can measure the magnetic field changing, and it also can detect and count vehicles. We extend Mel Frequency Cepstral Coefficients to analyze vehicle magnetic signals. Vehicle type features are extracted using representation of cepstrum, frame energy, and gap cepstrum of magnetic signals. We design a 2-dimensional map algorithm using Vector Quantization to classify vehicle magnetic features to four typical types of vehicles in Australian suburbs: sedan, VAN, truck, and bus. Experiments results show that our approach achieves a high level of accuracy for vehicle detection and classification.

Keywords: vehicle classification, signal processing, road traffic model, magnetic sensing

Procedia PDF Downloads 312
2337 Constructing the Density of States from the Parallel Wang Landau Algorithm Overlapping Data

Authors: Arman S. Kussainov, Altynbek K. Beisekov

Abstract:

This work focuses on building an efficient universal procedure to construct a single density of states from the multiple pieces of data provided by the parallel implementation of the Wang Landau Monte Carlo based algorithm. The Ising and Pott models were used as the examples of the two-dimensional spin lattices to construct their densities of states. Sampled energy space was distributed between the individual walkers with certain overlaps. This was made to include the latest development of the algorithm as the density of states replica exchange technique. Several factors of immediate importance for the seamless stitching process have being considered. These include but not limited to the speed and universality of the initial parallel algorithm implementation as well as the data post-processing to produce the expected smooth density of states.

Keywords: density of states, Monte Carlo, parallel algorithm, Wang Landau algorithm

Procedia PDF Downloads 402
2336 Food Safety Aspects of Pesticide Residues in Spice Paprika

Authors: Sz. Klátyik, B. Darvas, M. Mörtl, M. Ottucsák, E. Takács, H. Bánáti, L. Simon, G. Gyurcsó, A. Székács

Abstract:

Environmental and health safety of condiments used for spicing food products in food processing or by culinary means receive relatively low attention, even though possible contamination of spices may affect food quality and safety. Contamination surveys mostly focus on microbial contaminants or their secondary metabolites, mycotoxins. Chemical contaminants, particularly pesticide residues, however, are clearly substantial factors in the case of given condiments in the Capsicum family including spice paprika and chilli. To assess food safety and support the quality of the Hungaricum product spice paprika, the pesticide residue status of spice paprika and chilli is assessed on the basis of reported pesticide contamination cases and non-compliances in the Rapid Alert System for Food and Feed of the European Union since 1998.

Keywords: spice paprika, Capsicum, pesticide residues, RASFF

Procedia PDF Downloads 384
2335 New Approaches for the Handwritten Digit Image Features Extraction for Recognition

Authors: U. Ravi Babu, Mohd Mastan

Abstract:

The present paper proposes a novel approach for handwritten digit recognition system. The present paper extract digit image features based on distance measure and derives an algorithm to classify the digit images. The distance measure can be performing on the thinned image. Thinning is the one of the preprocessing technique in image processing. The present paper mainly concentrated on an extraction of features from digit image for effective recognition of the numeral. To find the effectiveness of the proposed method tested on MNIST database, CENPARMI, CEDAR, and newly collected data. The proposed method is implemented on more than one lakh digit images and it gets good comparative recognition results. The percentage of the recognition is achieved about 97.32%.

Keywords: handwritten digit recognition, distance measure, MNIST database, image features

Procedia PDF Downloads 454
2334 Investigation of the Effects of Visually Disabled and Typical Development Students on Their Multiple Intelligence by Applying Abacus and Right Brain Training

Authors: Sidika Di̇lşad Kaya, Ahmet Seli̇m Kaya, Ibrahi̇m Eri̇k, Havva Yaldiz, Yalçin Kaya

Abstract:

The aim of this study was to reveal the effects of right brain development on reading, comprehension, learning and concentration levels and rapid processing skills in students with low vision and students with standard development, and to explore the effects of right and left brain integration on students' academic success and the permanence of the learned knowledge. A total of 68 students with a mean age of 10.01±0.12 were included in the study, 58 of them with standard development, 9 partially visually impaired and 1 totally visually disabled student. The student with a total visual impairment could not participate in the reading speed test due to her total visual impairment. The following data were measured in the participant students before the project; Reading speed measurement in 1 minute, Reading comprehension questions, Burdon attention test, 50 questions of math quiz timed with a stopwatch. Participants were trained for 3 weeks, 5 days a week, for a total of two hours a day. In this study, right-brain developing exercises were carried out with the use of an abacus, and it was aimed to develop both mathematical and attention of students with questions prepared with numerical data taken from fairy tale activities. Among these problems, the study was supported with multiple-choice, 5W (what, where, who, why, when?), 1H (how?) questions along with true-false and fill-in-the-blank activities. By using memory cards, students' short-term memories were strengthened, photographic memory studies were conducted and their visual intelligence was supported. Auditory intelligence was supported by aiming to make calculations by using the abacus in the minds of the students with the numbers given aurally. When calculating the numbers by touching the real abacus, the development of students' tactile intelligence is enhanced. Research findings were analyzed in SPSS program, Kolmogorov Smirnov test was used for normality analysis. Since the variables did not show normal distribution, Wilcoxon test, one of the non-parametric tests, was used to compare the dependent groups. Statistical significance level was accepted as 0.05. The reading speed of the participants was 83.54±33.03 in the pre-test and 116.25±38.49 in the post-test. Narration pre-test 69.71±25.04 post-test 97.06±6.70; BURDON pretest 84.46±14.35 posttest 95.75±5.67; rapid math processing skills pretest 90.65±10.93, posttest 98.18±2.63 (P<0.05). It was determined that the pre-test and post-test averages of students with typical development and students with low vision were also significant for all four values (p<0.05). As a result of the data obtained from the participants, it is seen that the study was effective in terms of measurement parameters, and the findings were statistically significant. Therefore, it is recommended to use the method widely.

Keywords: Abacus, reading speed, multiple intelligences, right brain training, visually impaired

Procedia PDF Downloads 175
2333 Analysis of Shrinkage Effect during Mercerization on Himalayan Nettle, Cotton and Cotton/Nettle Yarn Blends

Authors: Reena Aggarwal, Neha Kestwal

Abstract:

The Himalayan Nettle (Girardinia diversifolia) has been used for centuries as fibre and food source by Himalayan communities. Himalayan Nettle is a natural cellulosic fibre that can be handled in the same way as other cellulosic fibres. The Uttarakhand Bamboo and Fibre Development Board based in Uttarakhand, India is working extensively with the nettle fibre to explore the potential of nettle for textile production in the region. The fiber is a potential resource for rural enterprise development for some high altitude pockets of the state and traditionally the plant fibre is used for making domestic products like ropes and sacks. Himalayan Nettle is an unconventional natural fiber with functional characteristics of shrink resistance, degree of pathogen and fire resistance and can blend nicely with other fibres. Most importantly, they generate mainly organic wastes and leave residues that are 100% biodegradable. The fabrics may potentially be reused or re-manufactured and can also be used as a source of cellulose feedstock for regenerated cellulosic products. Being naturally bio- degradable, the fibre can be composted if required. Though a lot of research activities and training are directed towards fibre extraction and processing techniques in different craft clusters villagers of different clusters of Uttarkashi, Chamoli and Bageshwar of Uttarakhand like retting and Degumming process, very little is been done to analyse the crucial properties of nettle fiber like shrinkage and wash fastness. These properties are very crucial to obtain desired quality of fibre for further processing of yarn making and weaving and in developing these fibers into fine saleable products. This research therefore is focused towards various on-field experiments which were focused on shrinkage properties conducted on cotton, nettle and cotton/nettle blended yarn samples. The objective of the study was to analyze the scope of the blended fiber for developing into wearable fabrics. For the study, after conducting the initial fiber length and fineness testing, cotton and nettle fibers were mixed in 60:40 ratio and five varieties of yarns were spun in open end spinning mill having yarn count of 3s, 5s, 6s, 7s and 8s. Samples of 100% Nettle 100% cotton fibers in 8s count were also developed for the study. All the six varieties of yarns were tested with shrinkage test and results were critically analyzed as per ASTM method D2259. It was observed that 100% Nettle has a least shrinkage of 3.36% while pure cotton has shrinkage approx. 13.6%. Yarns made of 100% Cotton exhibits four times more shrinkage than 100% Nettle. The results also show that cotton and Nettle blended yarn exhibit lower shrinkage than 100% cotton yarn. It was thus concluded that as the ratio of nettle increases in the samples, the shrinkage decreases in the samples. These results are very crucial for Uttarakhand people who want to commercially exploit the abundant nettle fiber for generating sustainable employment.

Keywords: Himalayan nettle, sustainable, shrinkage, blending

Procedia PDF Downloads 232
2332 Adaptive Filtering in Subbands for Supervised Source Separation

Authors: Bruna Luisa Ramos Prado Vasques, Mariane Rembold Petraglia, Antonio Petraglia

Abstract:

This paper investigates MIMO (Multiple-Input Multiple-Output) adaptive filtering techniques for the application of supervised source separation in the context of convolutive mixtures. From the observation that there is correlation among the signals of the different mixtures, an improvement in the NSAF (Normalized Subband Adaptive Filter) algorithm is proposed in order to accelerate its convergence rate. Simulation results with mixtures of speech signals in reverberant environments show the superior performance of the proposed algorithm with respect to the performances of the NLMS (Normalized Least-Mean-Square) and conventional NSAF, considering both the convergence speed and SIR (Signal-to-Interference Ratio) after convergence.

Keywords: adaptive filtering, multi-rate processing, normalized subband adaptive filter, source separation

Procedia PDF Downloads 426
2331 Design and Implementation of 2D Mesh Network on Chip Using VHDL

Authors: Boudjedra Abderrahim, Toumi Salah, Boutalbi Mostefa, Frihi Mohammed

Abstract:

Nowadays, using the advancement of technology in semiconductor device fabrication, many transistors can be integrated to a single chip (VLSI). Although the growth chip density potentially eases systems-on-chip (SoCs) integrating thousands of processing element (PE) such as memory, processor, interfaces cores, system complexity, high-performance interconnect and scalable on-chip communication architecture become most challenges for many digital and embedded system designers. Networks-on-chip (NoCs) becomes a new paradigm that makes possible integrating heterogeneous devices and allows many communication constraints and performances. In this paper, we are interested for good performance and low area for implementation and a behavioral modeling of network on chip mesh topology design using VHDL hardware description language with performance evaluation and FPGA implementation results.

Keywords: design, implementation, communication system, network on chip, VHDL

Procedia PDF Downloads 370
2330 A Novel Approach to Design of EDDR Architecture for High Speed Motion Estimation Testing Applications

Authors: T. Gangadhararao, K. Krishna Kishore

Abstract:

Motion Estimation (ME) plays a critical role in a video coder, testing such a module is of priority concern. While focusing on the testing of ME in a video coding system, this work presents an error detection and data recovery (EDDR) design, based on the residue-and-quotient (RQ) code, to embed into ME for video coding testing applications. An error in processing Elements (PEs), i.e. key components of a ME, can be detected and recovered effectively by using the proposed EDDR design. The proposed EDDR design for ME testing can detect errors and recover data with an acceptable area overhead and timing penalty.

Keywords: area overhead, data recovery, error detection, motion estimation, reliability, residue-and-quotient (RQ) code

Procedia PDF Downloads 425
2329 Inspection of Railway Track Fastening Elements Using Artificial Vision

Authors: Abdelkrim Belhaoua, Jean-Pierre Radoux

Abstract:

In France, the railway network is one of the main transport infrastructures and is the second largest European network. Therefore, railway inspection is an important task in railway maintenance to ensure safety for passengers using significant means in personal and technical facilities. Artificial vision has recently been applied to several railway applications due to its potential to improve the efficiency and accuracy when analyzing large databases of acquired images. In this paper, we present a vision system able to detect fastening elements based on artificial vision approach. This system acquires railway images using a CCD camera installed under a control carriage. These images are stitched together before having processed. Experimental results are presented to show that the proposed method is robust for detection fasteners in a complex environment.

Keywords: computer vision, image processing, railway inspection, image stitching, fastener recognition, neural network

Procedia PDF Downloads 444
2328 Affective Robots: Evaluation of Automatic Emotion Recognition Approaches on a Humanoid Robot towards Emotionally Intelligent Machines

Authors: Silvia Santano Guillén, Luigi Lo Iacono, Christian Meder

Abstract:

One of the main aims of current social robotic research is to improve the robots’ abilities to interact with humans. In order to achieve an interaction similar to that among humans, robots should be able to communicate in an intuitive and natural way and appropriately interpret human affects during social interactions. Similarly to how humans are able to recognize emotions in other humans, machines are capable of extracting information from the various ways humans convey emotions—including facial expression, speech, gesture or text—and using this information for improved human computer interaction. This can be described as Affective Computing, an interdisciplinary field that expands into otherwise unrelated fields like psychology and cognitive science and involves the research and development of systems that can recognize and interpret human affects. To leverage these emotional capabilities by embedding them in humanoid robots is the foundation of the concept Affective Robots, which has the objective of making robots capable of sensing the user’s current mood and personality traits and adapt their behavior in the most appropriate manner based on that. In this paper, the emotion recognition capabilities of the humanoid robot Pepper are experimentally explored, based on the facial expressions for the so-called basic emotions, as well as how it performs in contrast to other state-of-the-art approaches with both expression databases compiled in academic environments and real subjects showing posed expressions as well as spontaneous emotional reactions. The experiments’ results show that the detection accuracy amongst the evaluated approaches differs substantially. The introduced experiments offer a general structure and approach for conducting such experimental evaluations. The paper further suggests that the most meaningful results are obtained by conducting experiments with real subjects expressing the emotions as spontaneous reactions.

Keywords: affective computing, emotion recognition, humanoid robot, human-robot-interaction (HRI), social robots

Procedia PDF Downloads 222
2327 Development of Pasta Production by Using of Hard and Soft Domestic Sorts of Wheat

Authors: A.N. Zhilkaidarov, G.K. Iskakova, V.Y. Chernyh

Abstract:

High-qualified and not-expensive products of daily usage have a big demand on food products’ market. Moreover, it is about independent and irreplaceable product as pasta. Pasta is a product, which represents itself the conserved dough from wheat flour made through special milling process. A wide assortment of the product and its pleasant taste properties allow to use pasta products in very different combinations with other food products. Pasta industry of Kazakhstan has large perspectives of development. There are many premises for it, which includes first an importance of pasta as a social product. Due to for its nutritional and energetically value pasta is the part of must have food. Besides that, the pasta production in Kazakhstan has traditional bases, and nowadays the market of this product develops rapidly as in quantity as well as in quality aspects. Moreover, one of the advantages of this branch is an economical aspect – pasta is the product of secondary processing, and therefore price for sailing is much higher as its own costs.

Keywords: pasta, new wheat sorts, domesic sorts of wheat, macaronic flour

Procedia PDF Downloads 520
2326 Extracting Actions with Improved Part of Speech Tagging for Social Networking Texts

Authors: Yassine Jamoussi, Ameni Youssfi, Henda Ben Ghezala

Abstract:

With the growing interest in social networking, the interaction of social actors evolved to a source of knowledge in which it becomes possible to perform context aware-reasoning. The information extraction from social networking especially Twitter and Facebook is one of the problems in this area. To extract text from social networking, we need several lexical features and large scale word clustering. We attempt to expand existing tokenizer and to develop our own tagger in order to support the incorrect words currently in existence in Facebook and Twitter. Our goal in this work is to benefit from the lexical features developed for Twitter and online conversational text in previous works, and to develop an extraction model for constructing a huge knowledge based on actions

Keywords: social networking, information extraction, part-of-speech tagging, natural language processing

Procedia PDF Downloads 300
2325 Computational Study on Traumatic Brain Injury Using Magnetic Resonance Imaging-Based 3D Viscoelastic Model

Authors: Tanu Khanuja, Harikrishnan N. Unni

Abstract:

Head is the most vulnerable part of human body and may cause severe life threatening injuries. As the in vivo brain response cannot be recorded during injury, computational investigation of the head model could be really helpful to understand the injury mechanism. Majority of the physical damage to living tissues are caused by relative motion within the tissue due to tensile and shearing structural failures. The present Finite Element study focuses on investigating intracranial pressure and stress/strain distributions resulting from impact loads on various sites of human head. This is performed by the development of the 3D model of a human head with major segments like cerebrum, cerebellum, brain stem, CSF (cerebrospinal fluid), and skull from patient specific MRI (magnetic resonance imaging). The semi-automatic segmentation of head is performed using AMIRA software to extract finer grooves of the brain. To maintain the accuracy high number of mesh elements are required followed by high computational time. Therefore, the mesh optimization has also been performed using tetrahedral elements. In addition, model validation with experimental literature is performed as well. Hard tissues like skull is modeled as elastic whereas soft tissues like brain is modeled with viscoelastic prony series material model. This paper intends to obtain insights into the severity of brain injury by analyzing impacts on frontal, top, back, and temporal sites of the head. Yield stress (based on von Mises stress criterion for tissues) and intracranial pressure distribution due to impact on different sites (frontal, parietal, etc.) are compared and the extent of damage to cerebral tissues is discussed in detail. This paper finds that how the back impact is more injurious to overall head than the other. The present work would be helpful to understand the injury mechanism of traumatic brain injury more effectively.

Keywords: dynamic impact analysis, finite element analysis, intracranial pressure, MRI, traumatic brain injury, von Misses stress

Procedia PDF Downloads 154
2324 The Challenges of Irrigated Tomato Production in Kano State, Nigeria

Authors: I. K. Adamu, J. O. Adefila

Abstract:

The paper examines the challenges of irrigated tomato growers in Kano State. Materials used for the study are sourced from newspapers, books, internet and field surveys. Questionnaires were also used to sample the opinion of the tomato farmers in the state. The purposive and snow ball sampling techniques were used to select knowledgeable individual farmers in the study areas. The sample size was based on a five percent (0.05) of the identified members of tomato farmers. Data analysis was achieved using cross-tabulation, percentage, and SWOT analysis. The study reveals that irrigated tomato farmers in Kano State faces a lot of challenges. The study offers some recommendations such as establishment of storage facilities on ground, establishment of processing industries in the state, and introduction of high yield varieties of tomato seeds instead of the outdated UC82B.

Keywords: SWOT, irrigated tomato production, tomato farmers, Nigeria

Procedia PDF Downloads 387
2323 Improve Divers Tracking and Classification in Sonar Images Using Robust Diver Wake Detection Algorithm

Authors: Mohammad Tarek Al Muallim, Ozhan Duzenli, Ceyhun Ilguy

Abstract:

Harbor protection systems are so important. The need for automatic protection systems has increased over the last years. Diver detection active sonar has great significance. It used to detect underwater threats such as divers and autonomous underwater vehicle. To automatically detect such threats the sonar image is processed by algorithms. These algorithms used to detect, track and classify of underwater objects. In this work, divers tracking and classification algorithm is improved be proposing a robust wake detection method. To detect objects the sonar images is normalized then segmented based on fixed threshold. Next, the centroids of the segments are found and clustered based on distance metric. Then to track the objects linear Kalman filter is applied. To reduce effect of noise and creation of false tracks, the Kalman tracker is fine tuned. The tuning is done based on our active sonar specifications. After the tracks are initialed and updated they are subjected to a filtering stage to eliminate the noisy and unstable tracks. Also to eliminate object with a speed out of the diver speed range such as buoys and fast boats. Afterwards the result tracks are subjected to a classification stage to deiced the type of the object been tracked. Here the classification stage is to deice wither if the tracked object is an open circuit diver or a close circuit diver. At the classification stage, a small area around the object is extracted and a novel wake detection method is applied. The morphological features of the object with his wake is extracted. We used support vector machine to find the best classifier. The sonar training images and the test images are collected by ARMELSAN Defense Technologies Company using the portable diver detection sonar ARAS-2023. After applying the algorithm to the test sonar data, we get fine and stable tracks of the divers. The total classification accuracy achieved with the diver type is 97%.

Keywords: harbor protection, diver detection, active sonar, wake detection, diver classification

Procedia PDF Downloads 234
2322 Authentication Based on Hand Movement by Low Dimensional Space Representation

Authors: Reut Lanyado, David Mendlovic

Abstract:

Most biological methods for authentication require special equipment and, some of them are easy to fake. We proposed a method for authentication based on hand movement while typing a sentence with a regular camera. This technique uses the full video of the hand, which is harder to fake. In the first phase, we tracked the hand joints in each frame. Next, we represented a single frame for each individual using our Pose Agnostic Rotation and Movement (PARM) dimensional space. Then, we indicated a full video of hand movement in a fixed low dimensional space using this method: Fixed Dimension Video by Interpolation Statistics (FDVIS). Finally, we identified each individual in the FDVIS representation using unsupervised clustering and supervised methods. Accuracy exceeds 96% for 80 individuals by using supervised KNN.

Keywords: authentication, feature extraction, hand recognition, security, signal processing

Procedia PDF Downloads 121
2321 SciPaaS: a Scientific Execution Platform for the Cloud

Authors: Wesley H. Brewer, John C. Sanford

Abstract:

SciPaaS is a prototype development of an execution platform/middleware designed to make it easy for scientists to rapidly deploy their scientific applications (apps) to the cloud. It provides all the necessary infrastructure for running typical IXP (Input-eXecute-Plot) style apps, including: a web interface, post-processing and plotting capabilities, job scheduling, real-time monitoring of running jobs, and even a file/case manager. In this paper, first the system architecture is described and then is demonstrated for a two scientific applications: (1) a simple finite-difference solver of the inviscid Burger’s equation, and (2) Mendel’s Accountant—a forward-time population genetics simulation model. The implications of the prototype are discussed in terms of ease-of-use and deployment options, especially in cloud environments.

Keywords: web-based simulation, cloud computing, Platform-as-a-Service (PaaS), rapid application development (RAD), population genetics

Procedia PDF Downloads 582
2320 Performance Analysis and Optimization for Diagonal Sparse Matrix-Vector Multiplication on Machine Learning Unit

Authors: Qiuyu Dai, Haochong Zhang, Xiangrong Liu

Abstract:

Diagonal sparse matrix-vector multiplication is a well-studied topic in the fields of scientific computing and big data processing. However, when diagonal sparse matrices are stored in DIA format, there can be a significant number of padded zero elements and scattered points, which can lead to a degradation in the performance of the current DIA kernel. This can also lead to excessive consumption of computational and memory resources. In order to address these issues, the authors propose the DIA-Adaptive scheme and its kernel, which leverages the parallel instruction sets on MLU. The researchers analyze the effect of allocating a varying number of threads, clusters, and hardware architectures on the performance of SpMV using different formats. The experimental results indicate that the proposed DIA-Adaptive scheme performs well and offers excellent parallelism.

Keywords: adaptive method, DIA, diagonal sparse matrices, MLU, sparse matrix-vector multiplication

Procedia PDF Downloads 125
2319 Evaluation of Different Liquid Scintillation Counting Methods for 222Rn Determination in Waters

Authors: Jovana Nikolov, Natasa Todorovic, Ivana Stojkovic

Abstract:

Monitoring of 222Rn in drinking or surface waters, as well as in groundwater has been performed in connection with geological, hydrogeological and hydrological surveys and health hazard studies. Liquid scintillation counting (LSC) is often preferred analytical method for 222Rn measurements in waters because it allows multiple-sample automatic analysis. LSC method implies mixing of water samples with organic scintillation cocktail, which triggers radon diffusion from the aqueous into organic phase for which it has a much greater affinity, eliminating possibility of radon emanation in that manner. Two direct LSC methods that assume different sample composition have been presented, optimized and evaluated in this study. One-phase method assumed direct mixing of 10 ml sample with 10 ml of emulsifying cocktail (Ultima Gold AB scintillation cocktail is used). Two-phase method involved usage of water-immiscible cocktails (in this study High Efficiency Mineral Oil Scintillator, Opti-Fluor O and Ultima Gold F are used). Calibration samples were prepared with aqueous 226Ra standard in glass 20 ml vials and counted on ultra-low background spectrometer Quantulus 1220TM equipped with PSA (Pulse Shape Analysis) circuit which discriminates alpha/beta spectra. Since calibration procedure is carried out with 226Ra standard, which has both alpha and beta progenies, it is clear that PSA discriminator has vital importance in order to provide reliable and precise spectra separation. Consequentially, calibration procedure was done through investigation of PSA discriminator level influence on 222Rn efficiency detection, using 226Ra calibration standard in wide range of activity concentrations. Evaluation of presented methods was based on obtained efficiency detections and achieved Minimal Detectable Activity (MDA). Comparison of presented methods, accuracy and precision as well as different scintillation cocktail’s performance was considered from results of measurements of 226Ra spiked water samples with known activity and environmental samples.

Keywords: 222Rn in water, Quantulus1220TM, scintillation cocktail, PSA parameter

Procedia PDF Downloads 193
2318 Thickness Measurement and Void Detection in Concrete Elements through Ultrasonic Pulse

Authors: Leonel Lipa Cusi, Enrique Nestor Pasquel Carbajal, Laura Marina Navarro Alvarado, José Del Álamo Carazas

Abstract:

This research analyses the accuracy of the ultrasound and the pulse echo ultrasound technic to find voids and to measure thickness of concrete elements. These mentioned air voids are simulated by polystyrene expanded and hollow containers of thin thickness made of plastic or cardboard of different sizes and shapes. These targets are distributed strategically inside concrete at different depths. For this research, a shear wave pulse echo ultrasonic device of 50 KHz is used to scan the concrete elements. Despite the small measurements of the concrete elements and because of voids’ size are near the half of the wavelength, pre and post processing steps like voltage, gain, SAFT, envelope and time compensation were made in order to improve imaging results.

Keywords: ultrasonic, concrete, thickness, pulse echo, void

Procedia PDF Downloads 322
2317 Cloning and Expression a Gene of β-Glucosidase from Penicillium echinulatum in Pichia pastoris

Authors: Amanda Gregorim Fernandes, Lorena Cardoso Cintra, Rosalia Santos Amorim Jesuino, Fabricia Paula De Faria, Marcio José Poças Fonseca

Abstract:

Bioethanol is one of the most promising biofuels and able to replace fossil fuels and reduce its different environmental impacts and can be generated from various agroindustrial waste. The Brazil is in first place in bioethanol production to be the largest producer of sugarcane. The bagasse sugarcane (SCB) has lignocellulose which is composed of three major components: cellulose, hemicellulose and lignin. Cellulose is a homopolymer of glucose units connected by glycosidic linkages. Among all species of Penicillium, Penicillium echinulatum has been the focus of attention because they produce high quantities of cellulase and the mutant strain 9A02S1 produces higher enzyme levels compared to the wild. Among the cellulases, the cellobiohydrolases enzymes are the main components of the cellulolytic system of fungi, and are also responsible for most of the potential hydrolytic in enzyme cocktails for the industrial processing of plant biomass and several cellobiohydrolases Penicillium had higher specific activity against cellulose compared to CBH I from Trichoderma reesei. This fact makes it an interesting pattern for higher yields in the enzymatic hydrolysis, and also they are important enzymes in the hydrolysis of crystalline regions of cellulose. Therefore, finding new and more active enzymes become necessary. Meanwhile, β-glycosidases act on soluble substrates and are highly dependent on cellobiohydrolases and endoglucanases action to provide the substrate in the hydrolysis of the biomass, but the cellobiohydrolases and endoglucanases are highly dependent β-glucosidases to maintain efficient hydrolysis. Thus, there is a need to understand the structure-function relationships that govern the catalytic activity of cellulolytic enzymes to elucidate its mechanism of action and optimize its potential as industrial biocatalysts. To evaluate the enzyme β-glucosidase of Penicillium echinulatum (PeBGL1) the gene was synthesized from the assembly sequence from a library in induction conditions and then the PeBGL1 gene was cloned in the vector pPICZαA and transformed into P. pastoris GS115. After processing, the producers of PeBGL1 were analyzed for enzyme activity and protein profile where a band of approximately 100 kDa was viewed. It was also carried out the zymogram. In partial characterization it was determined optimum temperature of 50°C and optimum pH of 6,5. In addition, to increase the secreted recombinant PeBGL1 production by Pichia pastoris, three parameters of P. pastoris culture medium were analysed: methanol, nitrogen source concentrations and the inoculum size. A 23 factorial design was effective in achieving the optimum condition. Altogether, these results point to the potential application of this P. echinulatum β-glucosidase in hydrolysis of cellulose for the production of bioethanol.

Keywords: bioethanol, biotechnology, beta-glucosidase, penicillium echinulatum

Procedia PDF Downloads 237
2316 Information Retrieval for Kafficho Language

Authors: Mareye Zeleke Mekonen

Abstract:

The Kafficho language has distinct issues in information retrieval because of its restricted resources and dearth of standardized methods. In this endeavor, with the cooperation and support of linguists and native speakers, we investigate the creation of information retrieval systems specifically designed for the Kafficho language. The Kafficho information retrieval system allows Kafficho speakers to access information easily in an efficient and effective way. Our objective is to conduct an information retrieval experiment using 220 Kafficho text files, including fifteen sample questions. Tokenization, normalization, stop word removal, stemming, and other data pre-processing chores, together with additional tasks like term weighting, were prerequisites for the vector space model to represent each page and a particular query. The three well-known measurement metrics we used for our word were Precision, Recall, and and F-measure, with values of 87%, 28%, and 35%, respectively. This demonstrates how well the Kaffiho information retrieval system performed well while utilizing the vector space paradigm.

Keywords: Kafficho, information retrieval, stemming, vector space

Procedia PDF Downloads 49
2315 Deep Learning-Based Liver 3D Slicer for Image-Guided Therapy: Segmentation and Needle Aspiration

Authors: Ahmedou Moulaye Idriss, Tfeil Yahya, Tamas Ungi, Gabor Fichtinger

Abstract:

Image-guided therapy (IGT) plays a crucial role in minimally invasive procedures for liver interventions. Accurate segmentation of the liver and precise needle placement is essential for successful interventions such as needle aspiration. In this study, we propose a deep learning-based liver 3D slicer designed to enhance segmentation accuracy and facilitate needle aspiration procedures. The developed 3D slicer leverages state-of-the-art convolutional neural networks (CNNs) for automatic liver segmentation in medical images. The CNN model is trained on a diverse dataset of liver images obtained from various imaging modalities, including computed tomography (CT) and magnetic resonance imaging (MRI). The trained model demonstrates robust performance in accurately delineating liver boundaries, even in cases with anatomical variations and pathological conditions. Furthermore, the 3D slicer integrates advanced image registration techniques to ensure accurate alignment of preoperative images with real-time interventional imaging. This alignment enhances the precision of needle placement during aspiration procedures, minimizing the risk of complications and improving overall intervention outcomes. To validate the efficacy of the proposed deep learning-based 3D slicer, a comprehensive evaluation is conducted using a dataset of clinical cases. Quantitative metrics, including the Dice similarity coefficient and Hausdorff distance, are employed to assess the accuracy of liver segmentation. Additionally, the performance of the 3D slicer in guiding needle aspiration procedures is evaluated through simulated and clinical interventions. Preliminary results demonstrate the effectiveness of the developed 3D slicer in achieving accurate liver segmentation and guiding needle aspiration procedures with high precision. The integration of deep learning techniques into the IGT workflow shows great promise for enhancing the efficiency and safety of liver interventions, ultimately contributing to improved patient outcomes.

Keywords: deep learning, liver segmentation, 3D slicer, image guided therapy, needle aspiration

Procedia PDF Downloads 39
2314 1G2A IMU\GPS Integration Algorithm for Land Vehicle Navigation

Authors: O. Maklouf, Ahmed Abdulla

Abstract:

A general decline in the cost, size, and power requirements of electronics is accelerating the adoption of integrated GPS/INS technologies in consumer applications such Land Vehicle Navigation. Researchers are looking for ways to eliminate additional components from product designs. One possibility is to drop one or more of the relatively expensive gyroscopes from microelectromechanical system (MEMS) versions of inertial measurement units (IMUs). For land vehicular use, the most important gyroscope is the vertical gyro that senses the heading of the vehicle and two horizontal accelerometers for determining the velocity of the vehicle. This paper presents a simplified integration algorithm for strap down (ParIMU)\GPS combination, with data post processing for the determination of 2-D components of position (trajectory), velocity and heading. In the present approach we have neglected earth rotation and gravity variations, because of the poor gyroscope sensitivities of the low-cost IMU and because of the relatively small area of the trajectory.

Keywords: GPS, ParIMU, INS, Kalman filter

Procedia PDF Downloads 510