Search results for: Medical imaging & processing

Authors: Kapil Dev Sharma, Kirat Pal, Costas Psychalinos

Abstract:

A new first order all-pass filter topology realized using current controlled current conveyors (CCCIIs) is introduced in this paper. Offered benefits are the high-impedance of the input node, the absence of external resistors because of the usage of CCCIIs with positive and negative intrinsic resistances, the presence of only grounded capacitors, and the capability of electronic adjustment of the phase shift through a single bias current. The correct operation of the introduced topology is conformed through simulation results, while its behavior is evaluated through comparison results.

Keywords: Active filters, All-pass filters, Analog signal processing, Current conveyors.

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Authors: Abhishek Neogi, Jayesh Verma, Pinaki Pratim Acharjya

Abstract:

Image segmentation and edge detection is a fundamental section in image processing. In case of noisy images Edge Detection is very less effective if we use conventional Spatial Filters like Sobel, Prewitt, LOG, Laplacian etc. To overcome this problem we have proposed the use of Stochastic Gradient Mask instead of Spatial Filters for generating gradient images. The present study has shown that the resultant images obtained by applying Stochastic Gradient Masks appear to be much clearer and sharper as per Edge detection is considered.

Keywords: Image segmentation, edge Detection, noisy images, spatialfilters, stochastic gradient kernel.

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Authors: Bing-Fei Wu, Yen-Lin Chen, Chung-Cheng Chiu

Abstract:

In this study, a new criterion for determining the number of classes an image should be segmented is proposed. This criterion is based on discriminant analysis for measuring the separability among the segmented classes of pixels. Based on the new discriminant criterion, two algorithms for recursively segmenting the image into determined number of classes are proposed. The proposed methods can automatically and correctly segment objects with various illuminations into separated images for further processing. Experiments on the extraction of text strings from complex document images demonstrate the effectiveness of the proposed methods.1

Keywords: image segmentation, multilevel thresholding, clustering, discriminant analysis

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Authors: A. Alexandru, C. A. Alexandru, D. Coardos, E. Tudora

Abstract:

Big Data (BD) is associated with a new generation of technologies and architectures which can harness the value of extremely large volumes of very varied data through real time processing and analysis. It involves changes in (1) data types, (2) accumulation speed, and (3) data volume. This paper presents the main concepts related to the BD paradigm, and introduces architectures and technologies for BD and BD sets. The integration of BD with the Hadoop Framework is also underlined. BD has attracted a lot of attention in the public sector due to the newly emerging technologies that allow the availability of network access. The volume of different types of data has exponentially increased. Some applications of BD in the public sector in Romania are briefly presented.

Keywords: Big data, big data Analytics, Hadoop framework, cloud computing.

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Authors: Tebogo P. Phetla, Edison Muzenda

Abstract:

This study was carried out to develop a flotation procedure for an oxide copper ore from a Region in Central Africa for producing an 18% copper concentrate for downstream processing at maximum recovery from a 4% copper feed grade. The copper recoveries achieved from the test work were less than 50% despite changes in reagent conditions (multistage sulphidisation, use of RCA emulsion and mixture, use of AM 2, etc). The poor recoveries were attributed to the mineralogy of the ore from which copper silicates accounted for approximately 70% (mass) of the copper minerals in the ore. These can be complex and difficult to float using conventional flotation methods. Best results were obtained using basic sulphidisation procedures, a high flotation temperature and extended flotation residence time.

Keywords: Froth flotation, Sulphidisation, Copper oxide ore, Mineralogy, Recovery

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Authors: Trung Hieu Tran, Hyo-Moon Cho, Sang-Bock Cho

Abstract:

Motion estimation is the most computationally intensive part in video processing. Many fast motion estimation algorithms have been proposed to decrease the computational complexity by reducing the number of candidate motion vectors. However, these studies are for fast search algorithms themselves while almost image and video compressions are operated with software based. Therefore, the timing constraints for running these motion estimation algorithms not only challenge for the video codec but also overwhelm for some of processors. In this paper, the performance of motion estimation is enhanced by using Intel's Streaming SIMD Extension 2 (SSE2) technology with Intel Pentium 4 processor.

Keywords: Motion Estimation, Full Search, Three StepSearch, MMX/SSE/SSE2 Technologies, SIMD.

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Authors: R. Sinthavalai, N. Memongkol, N. Patthanaprechawong, J. Viriyanantavong, C. Choosuk

Abstract:

In Thailand, the practice of pre-hospital Emergency Medical Service (EMS) in each area reveals the different growth rates and effectiveness of the practices. Those can be found as the diverse quality and quantity. To shorten the learning curve prior to speed-up the practices in other areas, story telling and lessons learnt from the effective practices are valued as meaningful knowledge. To this paper, it was to ascertain the factors, lessons learnt and best practices that have impact as contributing to the success of prehospital EMS system. Those were formulized as model prior to speedup the practice in other areas. To develop the model, Malcolm Baldrige National Quality Award (MBNQA), which is widely recognized as a framework for organizational quality assessment and improvement, was chosen as the discussion framework. Remarkably, this study was based on the consideration of knowledge capture; however it was not to complete the loop of knowledge activities. Nevertheless, it was to highlight the recognition of knowledge capture, which is the initiation of knowledge management.

Keywords: Emergency Medical Service, Modeling, MBNQA, Thailand.

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Authors: Seyed Nima Tayarani Bathaie

Abstract:

In this paper, an image-receiving system was designed and implemented through optimization of object detection algorithms using Haar features. This optimized algorithm served as face and eye detection separately. Then, cascading them led to a clear image of the user. Utilization of this feature brought about higher security by preventing fraud. This attribute results from the fact that services will be given to the user on condition that a clear image of his face has already been captured which would exclude the inappropriate person. In order to expedite processing and eliminating unnecessary ones, the input image was compressed, a motion detection function was included in the program, and detection window size was confined.

Keywords: Face detection algorithm, Haar features, Security of ATM.

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Authors: Nuha Omran Abokhdair, Azizah Bt Abdul Manaf

Abstract:

Reversible watermarking is a special branch of image watermarking, that is able to recover the original image after extracting the watermark from the image. In this paper, an adaptive prediction-based reversible watermarking scheme is presented, in order to increase the payload capacity of MRI medical images. The scheme divides the image into two parts, Region of Interest (ROI) and Region of Non-Interest (RONI). Two bits are embedded in each embeddable pixel of RONI and one bit is embedded in each embeddable pixel of ROI. The experimental results demonstrate that the proposed scheme is able to achieve high embedding capacity. This is mainly caused by two reasons. First, the pixels that were excluded from data embedding due to overflow/underflow are used for data embedding. Second, large location map that need to be added to watermark data as overhead is eliminated and thus lower data embedding capacity is prevented. Moreover, the scheme provides good visual quality to the watermarked image.

Keywords: Medical image watermarking, reversible watermarking, Difference Expansion, Prediction-Error Expansion.

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Authors: Manjit Singh

Abstract:

Multiscale entropy (MSE) is an extensively used index to provide a general understanding of multiple complexity of physiologic mechanism of heart rate variability (HRV) that operates on a wide range of time scales. Accurate selection of electrocardiogram (ECG) sampling frequency is an essential concern for clinically significant HRV quantification; high ECG sampling rate increase memory requirements and processing time, whereas low sampling rate degrade signal quality and results in clinically misinterpreted HRV. In this work, the impact of ECG sampling frequency on MSE based HRV have been quantified. MSE measures are found to be sensitive to ECG sampling frequency and effect of sampling frequency will be a function of time scale.

Keywords: ECG, heart rate variability, HRV, multiscale entropy, sampling frequency.

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Authors: Ioannis P. Panapakidis, Marios N. Moschakis

Abstract:

With the continuous increment of smart meter installations across the globe, the need for processing of the load data is evident. Clustering-based load profiling is built upon the utilization of unsupervised machine learning tools for the purpose of formulating the typical load curves or load profiles. The most commonly used algorithm in the load profiling literature is the K-means. While the algorithm has been successfully tested in a variety of applications, its drawback is the strong dependence in the initialization phase. This paper proposes a novel modified form of the K-means that addresses the aforementioned problem. Simulation results indicate the superiority of the proposed algorithm compared to the K-means.

Keywords: Clustering, load profiling, load modeling, machine learning, energy efficiency and quality.

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Authors: Calin Veghes

Abstract:

The concept of privacy, seen in connection to the consumer's private space and personalization, has recently gained a higher importance as a consequence of the increasing marketing efforts of the organizations based on the capturing, processing and usage of consumer-s personal data.Paper intends to provide a definition of the consumer-s private space based on the types of personal data the consumer is willing to disclose, to assess the attitude toward personalization and to identify the means preferred by consumers to control their personal data and defend their private space. Several implications generated through the definition of the consumer-s private space are identified and weighted from both the consumers- and organizations- perspectives.

Keywords: Consumer private space, personalization, privacy.

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Authors: R. Tandlich, S. Hoossein, K. A. Tagwira, M. M. Marais, T. A. Ludwig, R. P. Chidziva, M. N. Munodawafa, W. M. Wrench

Abstract:

Response to the public health-related emergencies is analysed here for a rural university in South Africa. The structure of the designated emergency plan covers all the phases of the disaster management cycle. The plan contains elements of the vulnerability model and the technocratic model of emergency management. The response structures are vertically and horizontally integrated, while the planning contains elements of scenario-based and functional planning. The available number of medical professionals at the Rhodes University, along with the medical insurance rates, makes the staff and students potentially more medically vulnerable than the South African population. The main improvements of the emergency management are required in the tornado response and the information dissemination during health emergencies. The latter should involve the increased use of social media and e-mails, following the Taylor model of communication. Infrastructure must be improved in the telecommunication sector in the face of unpredictable electricity outages.

Keywords: Public health, Rural university, Taylor model of communication.

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Authors: Maha Sharkas, Dahlia R. ElShafie, Nadder Hamdy

Abstract:

Image watermarking has proven to be quite an efficient tool for the purpose of copyright protection and authentication over the last few years. In this paper, a novel image watermarking technique in the wavelet domain is suggested and tested. To achieve more security and robustness, the proposed techniques relies on using two nested watermarks that are embedded into the image to be watermarked. A primary watermark in form of a PN sequence is first embedded into an image (the secondary watermark) before being embedded into the host image. The technique is implemented using Daubechies mother wavelets where an arbitrary embedding factor α is introduced to improve the invisibility and robustness. The proposed technique has been applied on several gray scale images where a PSNR of about 60 dB was achieved.

Keywords: Image watermarking, Multimedia Security, Wavelets, Image Processing.

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Authors: C. C. D. Kulathilake, M. Jayatilake, T. Takahashi

Abstract:

The myocardium is composed of specialized muscle which relies mainly on fatty acid and sugar metabolism and it is widely contribute to the heart functioning. The changes of the cardiac energy-producing system during heart failure have been proved using autoradiography techniques. This study focused on evaluating sugar and fatty acid metabolism in myocardium as cardiac energy getting system using heart-accumulated radiopharmaceuticals. Two sets of autoradiographs of heart cross sections of Lewis male rats were analyzed and the time- accumulation curve obtained with use of the MATLAB image processing software to evaluate fatty acid and sugar metabolic functions.

Keywords: Autoradiographs, fatty acid, radiopharmaceuticals and sugar.

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Authors: Y. Bentoutou

Abstract:

Memory Errors Detection and Correction aim to secure the transaction of data between the central processing unit of a satellite onboard computer and its local memory. In this paper, the application of a double-bit error detection and correction method is described and implemented in Field Programmable Gate Array (FPGA) technology. The performance of the proposed EDAC method is measured and compared with two different EDAC devices, using the same FPGA technology. Statistical analysis of single-event upset (SEU) and multiple-bit upset (MBU) activity in commercial memories onboard the first Algerian microsatellite Alsat-1 is given.

Keywords: Error Detection and Correction, On-board computer, small satellite missions.

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Authors: Uzair Muhammad, Kashif Bilal, Atif Khan, M. Nasir Khan

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Machine Translation (MT 3) of English text to its Urdu equivalent is a difficult challenge. Lot of attempts has been made, but a few limited solutions are provided till now. We present a direct approach, using an expert system to translate English text into its equivalent Urdu, using The Unicode Standard, Version 4.0 (ISBN 0-321-18578-1) Range: 0600–06FF. The expert system works with a knowledge base that contains grammatical patterns of English and Urdu, as well as a tense and gender-aware dictionary of Urdu words (with their English equivalents).

Keywords: Machine Translation, Multiword Expressions, Urdulanguage processing, POS12 Tagging for Urdu, Expert Systems.

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Authors: Gabriela Lindemann, Danilo Schmidt, Thomas Schrader, Dietmar Keune

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The amount and heterogeneity of data in biomedical research, notably in interdisciplinary fields, requires new methods for the collection, presentation and analysis of information. Important data from laboratory experiments as well as patient trials are available but come out of distributed resources. The Charité - University Hospital Berlin has established together with the German Research Foundation (DFG) a new information service centre for kidney diseases and transplantation (Open European Nephrology Science Centre - OpEN.SC). Beside a collaborative aspect to create new research groups every single partner or institution of this science information centre making his own data available is allowed to search the whole data pool of the various involved centres. A core task is the implementation of a non-restricting open data structure for the various different data sources. We decided to use a modern RDF model and in a first phase transformed original data coming from the web-based Electronic Patient Record database TBase©.

Keywords: Medical databases, Resource Description Framework (RDF), metadata repository.

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Authors: Pingping Lin, Xudong Luo

Abstract:

Natural language often conveys emotions of speakers. Therefore, sentiment analysis on what people say is prevalent in the field of natural language process and has great application value in many practical problems. Thus, to help people understand its application value, in this paper, we survey various applications of sentiment analysis, including the ones in online business and offline business as well as other types of its applications. In particular, we give some application examples in intelligent customer service systems in China. Besides, we compare the applications of sentiment analysis on Twitter, Weibo, Taobao and Facebook, and discuss some challenges. Finally, we point out the challenges faced in the applications of sentiment analysis and the work that is worth being studied in the future.

Keywords: Natural language processing, sentiment analysis, application, online comments.

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Authors: Mohsen Zand, Ahmadreza Naghsh Nilchi, S. Amirhassan Monadjemi

Abstract:

Optical character recognition of cursive scripts presents a number of challenging problems in both segmentation and recognition processes in different languages, including Persian. In order to overcome these problems, we use a newly developed Persian word segmentation method and a recognition-based segmentation technique to overcome its segmentation problems. This method is robust as well as flexible. It also increases the system-s tolerances to font variations. The implementation results of this method on a comprehensive database show a high degree of accuracy which meets the requirements for commercial use. Extended with a suitable pre and post-processing, the method offers a simple and fast framework to develop a full OCR system.

Keywords: OCR, Persian, Recognition, Segmentation.

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Authors: Luke S. Carlos A. Thompson

Abstract:

The medical model of disability, though beneficial for the medical professional, is often exclusionary, restrictive and dehumanizing when applied to the lived experience of disability. As a result, a critique of this model was constructed called the social model of disability. Much of the language used to articulate the purpose behind the social model of disability can be summed up within the word inclusion. However, this essay asserts that inclusiveness is an incomplete aspiration. The social model, as it currently stands, does not aid in creating a society where those with impairments actually belong. Rather, the social model aids in lessening the visibility, or negative consequence of, difference. Therefore, the social model does not invite society to welcome those with physical and intellectual impairments. It simply aids society in ignoring the existence of impairment by removing explicit forms of exclusion. Rather than simple inclusion, then, this essay uses John Swinton’s concept of friendship and Jean Vanier’s understanding of belonging to better articulate the intended outcome of the social model—a society where everyone can belong.

Keywords: Belong, community, disability, exclusion, friendship, inclusion.

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Authors: Zong Chen

Abstract:

Motion estimation is a key problem in video processing and computer vision. Optical flow motion estimation can achieve high estimation accuracy when motion vector is small. Three-step search algorithm can handle large motion vector but not very accurate. A joint algorithm was proposed in this paper to achieve high estimation accuracy disregarding whether the motion vector is small or large, and keep the computation cost much lower than full search.

Keywords: Motion estimation, Block Matching, Optical flow, Three step search.

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Authors: M. Mashayekhi, H. H. Ardakani, A. Omidian

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Among various testing methodologies, Built-in Self- Test (BIST) is recognized as a low cost, effective paradigm. Also, full adders are one of the basic building blocks of most arithmetic circuits in all processing units. In this paper, an optimized testable 2- bit full adder as a test building block is proposed. Then, a BIST procedure is introduced to scale up the building block and to generate a self testable n-bit full adders. The target design can achieve 100% fault coverage using insignificant amount of hardware redundancy. Moreover, Overall test time is reduced by utilizing polymorphic gates and also by testing full adder building blocks in parallel.

Keywords: BIST, Full Adder, Polymorphic Gate

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Authors: Shimal Das, Dibyendu Ghoshal

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The effect of directional search using iterated functional system has been studied on four images taken from databases. The images are portioned successively towards smaller dimension. Presented method provides the faster rate of convergence with respect to processing time in the flat region, but the same has been found to be slower at the border of the images and edges. It has also been revealed that the PSNR is lower at the edges and border portions of the image, and it is found to be higher in the uniform gray region, under the same external illumination and external noise environment.

Keywords: Iterated functional system, fractal compression, structural similarity index measure, fractal block coding, affine transformations.

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Authors: Max Ti-Kuang Hou, Hui-Mei Shen, Chiang-Ni Lu, I-Jen Hsu

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We present design, fabrication, and characterization of a small (12 mm × 12 mm × 8 mm) movable railway vehicle for sensor carrying. The miniature railway vehicle (MRV) was mainly composed of a vibrational structure and three legs. A railway was designed and fabricated to power and guide the MRV. It also transmits the sensed data from the MRV to the signal processing unit. The MRV with legs on the railway was moving due to its high-frequency vibration. A model was derived to describe the motion. Besides, FEM simulations were performed to design the legs. Then, the MRV and the railway were fabricated by precision machining. Finally, an infrared sensor was carried and tested. The result shows that the MRV without loading was moving along the railway and its maximum speed was 12.2 mm/s. Moreover, the testing signal was sensed by the MRV.

Keywords: Locomotion, Micro-Robot, Miniature Railway Vehicle, Stick-Slip.

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Authors: Boris Barbolyas, Kristina Buckova, Tomas Volensky, Cyril Belavy, Ladislav Dedik

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Background: Based on statokinezigram, the human balance control is often studied. Approach to human postural reaction analysis is based on a combination of stabilometry output signal with retroreflective marker data signal processing, analysis, and understanding, in this study. The study shows another original application of Method of Developed Statokinesigram Trajectory (MDST), too. Methods: In this study, the participants maintained quiet bipedal standing for 10 s on stabilometry platform. Consequently, bilateral vibration stimuli to Achilles tendons in 20 s interval was applied. Vibration stimuli caused that human postural system took the new pseudo-steady state. Vibration frequencies were 20, 60 and 80 Hz. Participant's body segments - head, shoulders, hips, knees, ankles and little fingers were marked by 12 retroreflective markers. Markers positions were scanned by six cameras system BTS SMART DX. Registration of their postural reaction lasted 60 s. Sampling frequency was 100 Hz. For measured data processing were used Method of Developed Statokinesigram Trajectory. Regression analysis of developed statokinesigram trajectory (DST) data and retroreflective marker developed trajectory (DMT) data were used to find out which marker trajectories most correlate with stabilometry platform output signals. Scaling coefficients (λ) between DST and DMT by linear regression analysis were evaluated, too. Results: Scaling coefficients for marker trajectories were identified for all body segments. Head markers trajectories reached maximal value and ankle markers trajectories had a minimal value of scaling coefficient. Hips, knees and ankles markers were approximately symmetrical in the meaning of scaling coefficient. Notable differences of scaling coefficient were detected in head and shoulders markers trajectories which were not symmetrical. The model of postural system behavior was identified by MDST. Conclusion: Value of scaling factor identifies which body segment is predisposed to postural instability. Hypothetically, if statokinesigram represents overall human postural system response to vibration stimuli, then markers data represented particular postural responses. It can be assumed that cumulative sum of particular marker postural responses is equal to statokinesigram.

Keywords: Center of pressure (CoP), a method of developed statokinesigram trajectory (MDST), a model of postural system behavior, retroreflective marker data.

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Authors: Chanchai Supaartagorn

Abstract:

Structured Query Language (SQL) is the standard de facto language to access and manipulate data in a relational database. Although SQL is a language that is simple and powerful, most novice users will have trouble with SQL syntax. Thus, we are presenting SQL generator tool which is capable of translating actions and displaying SQL commands and data sets simultaneously. The tool was developed based on Model-View-Controller (MVC) pattern. The MVC pattern is a widely used software design pattern that enforces the separation between the input, processing, and output of an application. Developers take full advantage of it to reduce the complexity in architectural design and to increase flexibility and reuse of code. In addition, we use White-Box testing for the code verification in the Model module.

Keywords: MVC, relational database, SQL, White-Box testing.

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Authors: Suriyon Tansuriyavong, Yuuta Suzuki, Boonmee Choompol

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Wheel-running type moving robot has the restriction on the moving range caused by obstacles or stairs. Solving this weakness, we studied the development of moving robot using airship. Our airship robot moves by recognizing arrow marks on the path. To have the airship robot recognize arrow marks, we used edge-based template matching. To control propeller units, we used PID and PD controller. The results of experiments demonstrated that the airship robot can move along the marks and can go up and down the stairs. It is shown the possibility that airship robot can become a robot which can move at wide range facilities.

Keywords: Template matching, moving robot, airship robot, PID control.

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. To approach this problem, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: W.S. Lim, M.V.C. Rao

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In this paper, the processing of sonar signals has been carried out using Minimal Resource Allocation Network (MRAN) and a Probabilistic Neural Network (PNN) in differentiation of commonly encountered features in indoor environments. The stability-plasticity behaviors of both networks have been investigated. The experimental result shows that MRAN possesses lower network complexity but experiences higher plasticity than PNN. An enhanced version called parallel MRAN (pMRAN) is proposed to solve this problem and is proven to be stable in prediction and also outperformed the original MRAN.

Keywords: Ultrasonic sensing, target classification, minimalresource allocation network (MRAN), probabilistic neural network(PNN), stability-plasticity dilemma.

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