Search results for: minimum distance technique

Authors: Aman Agarwal, Georg Klepp

Abstract:

Impinging jets are used in various industrial areas as a cooling and drying technique. The current research is concerned with the means of improving the heat transfer for configurations with a minimum distance of the nozzle to the impingement surface. The impingement heat transfer is described using numerical methods over a wide range of parameters for an array of planar jets. These parameters include varying jet flow speed, width of nozzle, distance of nozzle, angle of the jet flow, velocity and geometry of the impingement surface. Normal pressure and shear stress are computed as additional parameters. Using dimensionless characteristic numbers the parameters and the results are correlated to gain generalized equations. The results demonstrate the effect of the investigated parameters on the flow.

Keywords: Heat Transfer Coefficient, Minimum distance jet impingement, Numerical simulation, Dimensionless coefficients.

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Authors: Ali Gholami, M.Esfadiari, M.H.Masihabadi

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In this research three methods of Maximum Likelihood, Mahalanobis Distance and Minimum Distance were analyzed in the Western part of Isfahan province in the Iran country. For this purpose, the IRS satellite images and various land preparation uses in region including rangelands, irrigation farming, dry farming, gardens and urban areas were separated and identified. In these methods, matrix error and Kappa index were calculated and accuracy of each method, based on percentages: 53.13, 56.64 and 48.44, were obtained respectively. Considering the low accuracy of these methods to separate land uses due to spread of the land uses, it-s suggested the visual interpretation of the map, to preparing the land use map in this region. The map prepared by visual interpretation is in high accuracy if it will be accompany with the visit of the region.

Keywords: Aghche Region, land use map, MaximumLikelihood, Mahalanobis Distance and Minimum Distance.

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Authors: Velappa Ganapathy, Kok Leong Liew

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Advancement in Artificial Intelligence has lead to the developments of various “smart" devices. Character recognition device is one of such smart devices that acquire partial human intelligence with the ability to capture and recognize various characters in different languages. Firstly multiscale neural training with modifications in the input training vectors is adopted in this paper to acquire its advantage in training higher resolution character images. Secondly selective thresholding using minimum distance technique is proposed to be used to increase the level of accuracy of character recognition. A simulator program (a GUI) is designed in such a way that the characters can be located on any spot on the blank paper in which the characters are written. The results show that such methods with moderate level of training epochs can produce accuracies of at least 85% and more for handwritten upper case English characters and numerals.

Keywords: Character recognition, multiscale, backpropagation, neural network, minimum distance technique.

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Authors: Randle O. A., Olugbara, O. O., Lall M.

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In this paper we describe a hybrid technique of Minimax search and aggregate Mahalanobis distance function synthesis to evolve Awale game player. The hybrid technique helps to suggest a move in a short amount of time without looking into endgame database. However, the effectiveness of the technique is heavily dependent on the training dataset of the Awale strategies utilized. The evolved player was tested against Awale shareware program and the result is appealing.

Keywords: Minimax Search, Mahalanobis Distance, Strategic Game, Awale

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Authors: Khunsa Fatima, Umar K. Khattak, Allah Bakhsh Kausar

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Satellite images interpretation and analysis assist geologists by providing valuable information about geology and minerals of an area to be surveyed. A test site in Fatejang of district Attock has been studied using Landsat ETM+ and ASTER satellite images for lithological mapping. Five different supervised image classification techniques namely maximum likelihood, parallelepiped, minimum distance to mean, mahalanobis distance and spectral angle mapper have been performed upon both satellite data images to find out the suitable classification technique for lithological mapping in the study area. Results of these five image classification techniques were compared with the geological map produced by Geological Survey of Pakistan. Result of maximum likelihood classification technique applied on ASTER satellite image has highest correlation of 0.66 with the geological map. Field observations and XRD spectra of field samples also verified the results. A lithological map was then prepared based on the maximum likelihood classification of ASTER satellite image.

Keywords: ASTER, Landsat-ETM+, Satellite, Image classification.

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Authors: Tudor Barbu

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We provide a supervised speech-independent voice recognition technique in this paper. In the feature extraction stage we propose a mel-cepstral based approach. Our feature vector classification method uses a special nonlinear metric, derived from the Hausdorff distance for sets, and a minimum mean distance classifier.

Keywords: Text-independent speaker recognition, mel cepstral analysis, speech feature vector, Hausdorff-based metric, supervised classification.

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Authors: Patsaraporn Somboonsak, Mud-Armeen Munlin

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The P-Bigram method is a string comparison methods base on an internal two characters-based similarity measure. The edit distance between two strings is the minimal number of elementary editing operations required to transform one string into the other. The elementary editing operations include deletion, insertion, substitution two characters. In this paper, we address the P-Bigram method to sole the similarity problem in DNA sequence. This method provided an efficient algorithm that locates all minimum operation in a string. We have been implemented algorithm and found that our program calculated that smaller distance than one string. We develop PBigram edit distance and show that edit distance or the similarity and implementation using dynamic programming. The performance of the proposed approach is evaluated using number edit and percentage similarity measures.

Keywords: Edit distance, String Matching, String Similarity

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Authors: M. S. Manikandan, K. V. Nithish Kumar, M. Krishnamoorthi, V. Ganesh

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The Automobile Braking System has a crucial role for safety of the passenger and riding quality of the vehicle. The braking force mainly depends on normal reaction on the wheel and the co-efficient of friction between the tire and the road surface. Whenever a vehicle is loaded, the normal reaction on the rear wheel is increased. Thus the amount of braking force required to halt the vehicle with minimum stopping distance, is based on the pillion load on the vehicle. In this work, in order to vary the braking force in two wheelers, the mechanical leverage which operates the master cylinder is varied based on the pillion load. Thus the amount of braking force developed between ground and tire is varied. This optimum braking force on the disc brake helps in attaining the minimum vehicle stopping distance. In addition to that, it also helps in preventing sliding. Thus the system results in reducing the stopping distance of the two wheelers and providing a better braking efficiency than the conventional braking system.

Keywords: Braking force, Master cylinder, Mechanical leverage, Minimum stopping distance.

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Authors: J. Yang, Y. Ma, X. Zhang, S. Li, Y. Zhang

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The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.

Keywords: Degree, initial cluster center, k-means, minimum spanning tree.

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Authors: Yiqiong Yuan, Jun Sun, Dongmei Zhou, Jianan Sun

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In this paper, we presented a Multi-Objective Random Drift Particle Swarm Optimization algorithm (MORDPSO-CD) based on RDPSO and crowding distance sorting to improve the convergence and distribution with less computation cost. MORDPSO-CD makes the most of RDPSO to approach the true Pareto optimal solutions fast. We adopt the crowding distance sorting technique to update and maintain the archived optimal solutions. Introducing the crowding distance technique into MORDPSO can make the leader particles find the true Pareto solution ultimately. The simulation results reveal that the proposed algorithm has better convergence and distribution.

Keywords: Multi-objective optimization, random drift particle swarm optimization, crowding distance, Pareto optimal solution.

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Authors: Wipassorn Vinicchayakul, Pichaya Supanakoon, Sathaporn Promwong

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A human’s hand localization is revised by using radar cross section (RCS) measurements with a minimum root mean square (RMS) error matching algorithm on a touchless keypad mock-up model. RCS and frequency transfer function measurements are carried out in an indoor environment on the frequency ranged from 3.0 to 11.0 GHz to cover federal communications commission (FCC) standards. The touchless keypad model is tested in two different distances between the hand and the keypad. The initial distance of 19.50 cm is identical to the heights of transmitting (Tx) and receiving (Rx) antennas, while the second distance is 29.50 cm from the keypad. Moreover, the effects of Rx angles relative to the hand of human factor are considered. The RCS input parameters are compared with power loss parameters at each frequency. From the results, the performance of the RCS input parameters with the second distance, 29.50 cm at 3 GHz is better than the others.

Keywords: Radar cross section (RCS), fingerprint-based localization, minimum root mean square (RMS) error matching algorithm, touchless keypad model.

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Authors: Loai AbdAllah, Ilan Shimshoni

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Missing values in data are common in real world applications. Since the performance of many data mining algorithms depend critically on it being given a good metric over the input space, we decided in this paper to define a distance function for unlabeled datasets with missing values. We use the Bhattacharyya distance, which measures the similarity of two probability distributions, to define our new distance function. According to this distance, the distance between two points without missing attributes values is simply the Mahalanobis distance. When on the other hand there is a missing value of one of the coordinates, the distance is computed according to the distribution of the missing coordinate. Our distance is general and can be used as part of any algorithm that computes the distance between data points. Because its performance depends strongly on the chosen distance measure, we opted for the k nearest neighbor classifier to evaluate its ability to accurately reflect object similarity. We experimented on standard numerical datasets from the UCI repository from different fields. On these datasets we simulated missing values and compared the performance of the kNN classifier using our distance to other three basic methods. Our  experiments show that kNN using our distance function outperforms the kNN using other methods. Moreover, the runtime performance of our method is only slightly higher than the other methods.

Keywords: Missing values, Distance metric, Bhattacharyya distance.

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Authors: Sasadhar Bera, Indrajit Mukherjee

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Ant colony optimization (ACO) and its variants are applied extensively to resolve various continuous optimization problems. As per the various diversification and intensification schemes of ACO for continuous function optimization, researchers generally consider components of multidimensional state space to generate the new search point(s). However, diversifying to a new search space by updating only components of the multidimensional vector may not ensure that the new point is at a significant distance from the current solution. If a minimum distance is not ensured during diversification, then there is always a possibility that the search will end up with reaching only local optimum. Therefore, to overcome such situations, a Mahalanobis distance-based diversification with Nelder-Mead simplex-based search scheme for each ant is proposed for the ACO strategy. A comparative computational run results, based on nine nonlinear standard test problems, confirms that the performance of ACO is improved significantly with the integration of the proposed schemes in the ACO.

Keywords: Ant Colony Optimization, Diversification Scheme, Intensification, Mahalanobis Distance, Nelder-Mead Simplex.

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Authors: Omid Adibi, Nategheh Najafpour, Bijan Farhanieh, Hossein Afshin

Abstract:

Energy transmission pipelines are one of the most vital parts of each country which several strict laws have been conducted to enhance the safety of these lines and their vicinity. One of these laws is the safety distance around high pressure gas pipelines. Safety distance refers to the minimum distance from the pipeline where people and equipment do not confront with serious damages. In the present study, safety distance around high pressure gas transmission pipelines were determined by using numerical methods. For this purpose, gas leakages from cracked pipeline and created jet fires were simulated as continuous ignition, three dimensional, unsteady and turbulent cases. Numerical simulations were based on finite volume method and turbulence of flow was considered using k-ω SST model. Also, the combustion of natural gas and air mixture was applied using the eddy dissipation method. The results show that, due to the high pressure difference between pipeline and environment, flow chocks in the cracked area and velocity of the exhausted gas reaches to sound speed. Also, analysis of the incident radiation results shows that safety distances around 42 inches high pressure natural gas pipeline based on 5 and 15 kW/m² criteria are 205 and 272 meters, respectively.

Keywords: Gas pipelines, incident radiation, numerical simulation, safety distance.

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Authors: Ana Horvat, Maja Krsmanovic, Mladen Djuric

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Rapid growth of distance learning resulted in importance to conduct research on students- satisfaction with distance learning because differences in students- satisfaction might influence educational opportunities for learning in a relevant Web-based environment. In line with this, this paper deals with satisfaction of students with distance module at Faculty of organizational sciences (FOS) in Serbia as well as some factors affecting differences in their satisfaction . We have conducted a research on a population of 68 first-year students of distance learning studies at FOS. Using statistical techniques, we have found out that there is no significant difference in students- satisfaction with distance learning module between men and women. In the same way, we also concluded that there is a difference in satisfaction with distance learning module regarding to student-s perception of opportunity to gain knowledge as the classic students.

Keywords: distance learning, students' satisfaction

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Authors: V. Tawiwat, P. Jumnong

Abstract:

Both the minimum energy consumption and smoothness, which is quantified as a function of jerk, are generally needed in many dynamic systems such as the automobile and the pick-and-place robot manipulator that handles fragile equipments. Nevertheless, many researchers come up with either solely concerning on the minimum energy consumption or minimum jerk trajectory. This research paper proposes a simple yet very interesting when combining the minimum energy and jerk of indirect jerks approaches in designing the time-dependent system yielding an alternative optimal solution. Extremal solutions for the cost functions of the minimum energy, the minimum jerk and combining them together are found using the dynamic optimization methods together with the numerical approximation. This is to allow us to simulate and compare visually and statistically the time history of state inputs employed by combining minimum energy and jerk designs. The numerical solution of minimum direct jerk and energy problem are exactly the same solution; however, the solutions from problem of minimum energy yield the similar solution especially in term of tendency.

Keywords: Optimization, Dynamic, Linear Systems, Jerks.

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Authors: Mohammad Shoyaib, M. Abdullah-Al-Wadud, Oksam Chae

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In this paper an effective approach for segmenting human skin regions in images taken at different environment is proposed. The proposed method uses a color distance map that is flexible enough to reliably detect the skin regions even if the illumination conditions of the image vary. Local image conditions is also focused, which help the technique to adaptively detect differently illuminated skin regions of an image. Moreover, usage of local information also helps the skin detection process to get rid of picking up much noisy pixels.

Keywords: Color Distance map, Reference skin color, Regiongrowing, Skin segmentation.

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Authors: José M. Merigó, Anna M. Gil-Lafuente

Abstract:

Different types of aggregation operators such as the ordered weighted quasi-arithmetic mean (Quasi-OWA) operator and the normalized Hamming distance are studied. We introduce the use of the OWA operator in generalized distances such as the quasiarithmetic distance. We will call these new distance aggregation the ordered weighted quasi-arithmetic distance (Quasi-OWAD) operator. We develop a general overview of this type of generalization and study some of their main properties such as the distinction between descending and ascending orders. We also consider different families of Quasi-OWAD operators such as the Minkowski ordered weighted averaging distance (MOWAD) operator, the ordered weighted averaging distance (OWAD) operator, the Euclidean ordered weighted averaging distance (EOWAD) operator, the normalized quasi-arithmetic distance, etc.

Keywords: Aggregation operators, Distance measures, Quasi- OWA operator.

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Authors: M. M. M. Jaradat, M. K. Al-Qeyyam

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The length of a cycle basis of a graph is the sum of the lengths of its elements. A minimum cycle basis is a cycle basis with minimum length. In this work, a construction of a minimum cycle basis for the wreath product of wheels with stars is presented. Moreover, the length of minimum cycle basis and the length of its longest cycle are calculated.

Keywords: Cycle space, minimum cycle basis, wreath product.

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Authors: Ke Lu, Tetsuya Furukawa

Abstract:

Data objects are usually organized hierarchically, and the relations between them are analyzed based on a corresponding concept hierarchy. The relation between data objects, for example how similar they are, are usually analyzed based on the conceptual distance in the hierarchy. If a node is an ancestor of another node, it is enough to analyze how close they are by calculating the distance vertically. However, if there is not such relation between two nodes, the vertical distance cannot express their relation explicitly. This paper tries to fill this gap by improving the analysis method for data objects based on hierarchy. The contributions of this paper include: (1) proposing an improved method to evaluate the vertical distance between concepts; (2) defining the concept horizontal distance and a method to calculate the horizontal distance; and (3) discussing the methods to confine a range by the horizontal distance and the vertical distance, and evaluating the relation between concepts.

Keywords: Concept Hierarchy, Horizontal Distance, Relation Analysis, Vertical Distance

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Authors: Fatma A. Karkory, Ali A. Abudalmola

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The travelling salesman problem (TSP) is a combinatorial optimization problem in which the goal is to find the shortest path between different cities that the salesman takes. In other words, the problem deals with finding a route covering all cities so that total distance and execution time is minimized. This paper adopts the nearest neighbor and minimum spanning tree algorithm to solve the well-known travelling salesman problem. The algorithms were implemented using java programming language. The approach is tested on three graphs that making a TSP tour instance of 5-city, 10 –city, and 229–city. The computation results validate the performance of the proposed algorithm.

Keywords: Heuristics, minimum spanning tree algorithm, Nearest Neighbor, Travelling Salesman Problem (TSP).

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Authors: José M. Merigó, Anna M. Gil-Lafuente

Abstract:

We study different types of aggregation operators such as the ordered weighted averaging (OWA) operator and the generalized OWA (GOWA) operator. We analyze the use of OWA operators in the Minkowski distance. We will call these new distance aggregation operator the Minkowski ordered weighted averaging distance (MOWAD) operator. We give a general overview of this type of generalization and study some of their main properties. We also analyze a wide range of particular cases found in this generalization such as the ordered weighted averaging distance (OWAD) operator, the Euclidean ordered weighted averaging distance (EOWAD) operator, the normalized Minkowski distance, etc. Finally, we give an illustrative example of the new approach where we can see the different results obtained by using different aggregation operators.

Keywords: Aggregation operators, Minkowski distance, OWA operators, Selection of strategies.

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Authors: Wen-Haw Chen, Sheng-Gwo Chen

Abstract:

The distance between two objects is an important problem in CAGD, CAD and CG etc. It will be presented in this paper that a simple and quick method to estimate the distance between a point and a Bezier curve on a Bezier surface.

Keywords: Geodesic-like curve, distance, projection, Bezier.

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Authors: Mohamed Zakaulla, A. R. Anwar Khan

Abstract:

Al6061 alloy base matrix, reinforced with particles of silicon carbide (10 wt %) and Graphite powder (1wt%), known as hybrid composites have been fabricated by liquid metallurgy route (stir casting technique) and optimized at different parameters like applied load, sliding speed and sliding distance by taguchi method. A plan of experiment generated through taguchi technique was used to perform experiments based on L27 orthogonal array. The developed ANOVA and regression equations are used to find the optimum coefficient of friction and wear under the influence of applied load, sliding speed and sliding distance. On the basis of “smaller the best” the dry sliding wear resistance was analysed and finally confirmation tests were carried out to verify the experimental results.

Keywords: Analysis of variance, dry sliding wear, Hybrid composite, orthogonal array, Taguchi technique.

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Authors: Paolo Fantozzi, Luigi Laura, Umberto Nanni

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The problem of Entity relation discovery in structured data, a well covered topic in literature, consists in searching within unstructured sources (typically, text) in order to find connections among entities. These can be a whole dictionary, or a specific collection of named items. In many cases machine learning and/or text mining techniques are used for this goal. These approaches might be unfeasible in computationally challenging problems, such as processing massive data streams. A faster approach consists in collecting the cooccurrences of any two words (entities) in order to create a graph of relations - a cooccurrence graph. Indeed each cooccurrence highlights some grade of semantic correlation between the words because it is more common to have related words close each other than having them in the opposite sides of the text. Some authors have used sliding windows for such problem: they count all the occurrences within a sliding windows running over the whole text. In this paper we generalise such technique, coming up to a Weighted-Distance Sliding Window, where each occurrence of two named items within the window is accounted with a weight depending on the distance between items: a closer distance implies a stronger evidence of a relationship. We develop an experiment in order to support this intuition, by applying this technique to a data set consisting in the text of the Bible, split into verses.

Keywords: Cooccurrence graph, entity relation graph, unstructured text, weighted distance.

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Authors: Martin Henkel

Abstract:

Different forms of interaction are an integral part of modern courses. Traditional courses held on-campus might focus on teacher-student interaction, or student-student interaction, or both. However when these traditional on-campus courses are to be held as distance courses there is a risk that these well-designed interactions will be difficult or impossible to uphold. For example, studentstudent interaction in traditional project assignments might not work well if the students are scattered across the world. Thus, even a welldesigned traditional on-site course cannot without modification be turned into a distance course. Traditional on-site courses simply have to be redesigned to become true distance courses. This paper describes a structured approach which facilitates the redesign of a traditional course into a distance course. The approach is based on that the desired forms of course flexibility are identified, and thereafter that the course activities are redesigned to facilitate interaction in a distance course. The approach is making use of known patterns of pedagogic interaction and existing guidelines for distance education design. The approach is illustrated with an example course in the field of information systems design.

Keywords: Distance education, interaction in education, course design.

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Authors: John Mark Lampos, Virgilio Sison

Abstract:

Two constructions of unit-memory binary convolutional codes from linear block codes over the finite semi-local ring F2r +vF2r , where v2 = v, are presented. In both cases, if the linear block code is systematic, then the resulting convolutional encoder is systematic, minimal, basic and non-catastrophic. The Hamming free distance of the convolutional code is bounded below by the minimum Hamming distance of the block code. New examples of binary convolutional codes that meet the Heller upper bound for systematic codes are given.

Keywords: Convolutional codes, semi-local ring, free distance, Heller bound.

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Authors: C. S. Sastry, Saurabh Jain, Ashish Mishra

Abstract:

Image retrieval is a topic where scientific interest is currently high. The important steps associated with image retrieval system are the extraction of discriminative features and a feasible similarity metric for retrieving the database images that are similar in content with the search image. Gabor filtering is a widely adopted technique for feature extraction from the texture images. The recently proposed sparsity promoting l1-norm minimization technique finds the sparsest solution of an under-determined system of linear equations. In the present paper, the l1-norm minimization technique as a similarity metric is used in image retrieval. It is demonstrated through simulation results that the l1-norm minimization technique provides a promising alternative to existing similarity metrics. In particular, the cases where the l1-norm minimization technique works better than the Euclidean distance metric are singled out.

Keywords: l1-norm minimization, content based retrieval, modified Gabor function.

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Authors: Tawiwat V., Phermsak S., Noppasit C.

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This paper deals with under actuator dynamic systems such as spring-mass-damper system when the number of control variable is less than the number of state variable. In order to apply optimal control, the controllability must be checked. There are many objective functions to be selected as the goal of the optimal control such as minimum energy, maximum energy and minimum jerk. As the objective function is the first priority, if one like to have the second goal to be applied; however, it could not fit in the objective function format and also avoiding the vector cost for the objective, this paper will illustrate the problem of under actuator dynamic systems with the easiest to deal with comparing between minimum energy and minimum jerk.

Keywords: Under actuator, Dynamic optimal control, Minimumjerk, Minimum energy.

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Authors: Loai AbdAllah, Mahmoud Kaiyal

Abstract:

Missing values in real-world datasets are a common problem. Many algorithms were developed to deal with this problem, most of them replace the missing values with a fixed value that was computed based on the observed values. In our work, we used a distance function based on Bhattacharyya distance to measure the distance between objects with missing values. Bhattacharyya distance, which measures the similarity of two probability distributions. The proposed distance distinguishes between known and unknown values. Where the distance between two known values is the Mahalanobis distance. When, on the other hand, one of them is missing the distance is computed based on the distribution of the known values, for the coordinate that contains the missing value. This method was integrated with Wikaya, a digital health company developing a platform that helps to improve prevention of chronic diseases such as diabetes and cancer. In order for Wikaya’s recommendation system to work distance between users need to be measured. Since there are missing values in the collected data, there is a need to develop a distance function distances between incomplete users profiles. To evaluate the accuracy of the proposed distance function in reflecting the actual similarity between different objects, when some of them contain missing values, we integrated it within the framework of k nearest neighbors (kNN) classifier, since its computation is based only on the similarity between objects. To validate this, we ran the algorithm over diabetes and breast cancer datasets, standard benchmark datasets from the UCI repository. Our experiments show that kNN classifier using our proposed distance function outperforms the kNN using other existing methods.

Keywords: Missing values, distance metric, Bhattacharyya distance.

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