Search results for: distance measurement error

Authors: Mostafa Mohammadpour, Christoph Kapeller, Christy Li, Josef Scharinger, Christoph Guger

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Interictal spikes provide valuable information on electrocorticography (ECoG), which aids in surgical planning for patients who suffer from refractory epilepsy. However, the shape and temporal dynamics of these spikes remain unclear. The purpose of this work was to analyze the shape of interictal spikes and measure their distance to the seizure onset zone (SOZ) to use in epilepsy surgery. Thirteen patients' data from the iEEG portal were retrospectively studied. For analysis, half an hour of ECoG data was used from each patient, with the data being truncated before the onset of a seizure. Spikes were first detected and grouped in a sequence, then clustered into interictal epileptiform discharges (IEDs) and non-IED groups using two-step clustering. The distance of the spikes from IED and non-IED groups to SOZ was quantified and compared using the Wilcoxon rank-sum test. Spikes in the IED group tended to be in SOZ or close to it, while spikes in the non-IED group were in distance of SOZ or non-SOZ area. At the group level, the distribution for sharp wave, positive baseline shift, slow wave, and slow wave to sharp wave ratio was significantly different for IED and non-IED groups. The distance of the IED cluster was 10.00mm and significantly closer to the SOZ than the 17.65mm for non-IEDs. These findings provide insights into the shape and spatiotemporal dynamics of spikes that could influence the network mechanisms underlying refractory epilepsy.

Keywords: spike propagation, spike pattern, clustering, SOZ

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Authors: Po-Hui Yang, Jing-Min Chen, Po-Yu Kuo, Chia-Chun Wu

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This paper proposed a high resolution Vernier Delay Line (VDL) measurement circuit with coarse and fine detection mechanism, which improved the trade-off problem between high resolution and less delay cells in traditional VDL circuits. And the measuring time of proposed measurement circuit is also under the high resolution requests. At first, the testing range of input signal which proposed high resolution delay line is detected by coarse detection VDL. Moreover, the delayed input signal is transmitted to fine detection VDL for measuring value with better accuracy. This paper is implemented at 0.18μm process, operating frequency is 100 MHz, and the resolution achieved 2.0 ps with only 16-stage delay cells. The test range is 170ps wide, and 17% stages saved compare with traditional single delay line circuit.

Keywords: vernier delay line, D-type flip-flop, DFF, metastable phenomenon

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Authors: Qianhua He, Weili Zhou, Aiwu Chen

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A sparse representation speech denoising method based on adapted stopping residue error was presented in this paper. Firstly, the cross-correlation between the clean speech spectrum and the noise spectrum was analyzed, and an estimation method was proposed. In the denoising method, an over-complete dictionary of the clean speech power spectrum was learned with the K-singular value decomposition (K-SVD) algorithm. In the sparse representation stage, the stopping residue error was adaptively achieved according to the estimated cross-correlation and the adjusted noise spectrum, and the orthogonal matching pursuit (OMP) approach was applied to reconstruct the clean speech spectrum from the noisy speech. Finally, the clean speech was re-synthesised via the inverse Fourier transform with the reconstructed speech spectrum and the noisy speech phase. The experiment results show that the proposed method outperforms the conventional methods in terms of subjective and objective measure.

Keywords: speech denoising, sparse representation, k-singular value decomposition, orthogonal matching pursuit

Procedia PDF Downloads 499

Authors: Joo-Hack Lee, Jin-Seung Choi, Dong-Won Kang, Jeong-Woo Seo, Ju-Young Kim, Dae-Hyeok Kim, Seung-Tae Yang, Gye-Rae Tack

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For cycling, the analysis of the pedal force is one of the important factors in the study of exercise ability assessment and overuse injuries. In past studies, a two-axis measurement sensor was used at the sagittal plane to measure the force only in the anterior, posterior, and vertical directions and to analyze the loss of force and the injury on the frontal plane due to the forces in the right and left directions. In this study, which is a basic study on diverse analyses of the pedal force that consider the forces on the sagittal plane and the frontal plane, a three-axis pedal force measurement sensor was developed to measure the anterior-posterior (Fx), medio-lateral (Fz), and vertical (Fy) forces. The sensor was fabricated with a size and shape similar to those of the general flat pedal, and had a 550g weight that allowed smooth pedaling. Its measurement range was ±1000 N for Fx and Fz and ±2000 N for Fy, and its non-linearity, hysteresis, and repeatability were approximately 0.5%. The data were sampled at 1000 Hz using a signal collector. To use the developed sensor, the pedaling efficiency (index of efficiency, IE) and the range of left and right (medio-lateral, ML) forces were measured with two seat heights (low and high). The results of the measurement showed that the IE was higher and the force range in the ML direction was lower with the high position than with the low position. The developed measurement sensor and its application results will be useful in understanding and explaining the complicated pedaling technique, and will enable diverse kinematic analyses of the pedal force on the sagittal plane and the frontal plane.

Keywords: cycling, pedal force, index of effectiveness, measuring

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Authors: Nasar Aldian Ambark Shashoa

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Classification with a dimension reduction based on Bayesian approach is proposed in this paper . The first step is to generate a sample (parameter) of fault-free mode class and faulty mode class. The second, in order to obtain good classification performance, a selection of important features is done with the discrete karhunen-loeve expansion. Next, the Bayes test for minimum error is used to classify the classes. Finally, the results for simulated data demonstrate the capabilities of the proposed procedure.

Keywords: analytical redundancy, fault detection, feature extraction, Bayesian approach

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Authors: Mehrdad Mahmudizad, Roya Ahmadi Ahangar

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This paper presents the method of designing the type 2 fuzzy PID controllers in order to solve the problem of Load Frequency Control (LFC). The Harmony Search (HS) algorithm is used to regulate the measurement factors and the effect of uncertainty of membership functions of Interval Type 2 Fuzzy Proportional Integral Differential (IT2FPID) controllers in order to reduce the frequency deviation resulted from the load oscillations. The simulation results implicitly show that the performance of the proposed IT2FPID LFC in terms of error, settling time and resistance against different load oscillations is more appropriate and preferred than PID and Type 1 Fuzzy Proportional Integral Differential (T1FPID) controllers.

Keywords: load frequency control, fuzzy-pid controller, type 2 fuzzy system, harmony search algorithm

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Authors: Mina Jafari, Kobra Hamraee, Saied Hossein Hosseini

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The prediction of breast cancer disease is one of the challenges in medicine. In this paper we collected 528 records of women’s information who live in Kabul including demographic, life style, diet and pregnancy data. There are many classification algorithm in breast cancer prediction and tried to find the best model with most accurate result and lowest error rate. We evaluated some other common supervised algorithms in data mining to find the best model in prediction of breast cancer disease among afghan women living in Kabul regarding to momography result as target variable. For evaluating these algorithms we used Cross Validation which is an assured method for measuring the performance of models. After comparing error rate and accuracy of three models: Decision Tree, Naive Bays and Rule Induction, Decision Tree with accuracy of 94.06% and error rate of %15 is found the best model to predicting breast cancer disease based on the health care records.

Keywords: decision tree, breast cancer, probability, data mining

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Authors: Tahir Nawaz Cheema, Dumitru Baleanu, Ali Raza

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In this research work, we design intelligent computing through Bayesian Regularization artificial neural networks (BRANNs) introduced to solve the mathematical modeling of infectious diseases (Covid-19). The dynamical transmission is due to the interaction of people and its mathematical representation based on the system's nonlinear differential equations. The generation of the dataset of the Covid-19 model is exploited by the power of the explicit Runge Kutta method for different countries of the world like India, Pakistan, Italy, and many more. The generated dataset is approximately used for training, testing, and validation processes for every frequent update in Bayesian Regularization backpropagation for numerical behavior of the dynamics of the Covid-19 model. The performance and effectiveness of designed methodology BRANNs are checked through mean squared error, error histograms, numerical solutions, absolute error, and regression analysis.

Keywords: mathematical models, beysian regularization, bayesian-regularization backpropagation networks, regression analysis, numerical computing

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Authors: Cheng-Hao Jiang, Mu-Xuan Tao

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The rigid diaphragm model may cause errors in the calculation of internal forces due to neglecting the in-plane deformation of the diaphragm. This paper thus studies the effects of different diaphragm in-plane models (including in-plane rigid model and in-plane flexible model) on the seismic performance of structures. Taking an actual industrial plant as an example, the seismic performance of the structure is predicted using different floor diaphragm models, and the analysis errors caused by different diaphragm in-plane models including deformation error and internal force error are calculated. Furthermore, the influence of the aspect ratio on the analysis errors is investigated. Finally, the code rationality is evaluated by assessing the analysis errors of the structure models whose floors were determined as rigid according to the code’s criterion. It is found that different floor models may cause great differences in the distribution of structural internal forces, and the current code may underestimate the influence of the floor in-plane effect.

Keywords: industrial plant, diaphragm, calculating error, code rationality

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Authors: Wan Nur'ashiqin Wan Mohamad, Zarina Othman, Mohd Azman Abas, Azizah Ya'acob, Rozmel Abdul Latiff

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Effective doctor-patient interaction is vital to both doctor and patient relationship. It is the cornerstone of good practice and an integral quality of a healthcare institution. This paper presented the hierarchy of the communication elements in doctor-patient interaction during medical consultations in a medical centre in Malaysia. This study adapted The Picker Patient Experience Questionnaire (2002) to obtain the information from patients. The questionnaire survey was responded by 100 patients between the ages of 20 and 50. Data collected were analysed using Rasch Measurement Model to yield the hierarchy of the communication elements in doctor-patient interaction. The findings showed that the three highest ranking on the doctor-patient interaction were doctor’s treatment, important information delivery and patient satisfaction of doctor’s responses. The results are valuable in developing the framework for communication ethics of doctors.

Keywords: communication elements, doctor-patient interaction, hierarchy, Rasch measurement model

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Authors: Mosab kh. A. A. Bashir, E. Mohamed-Ahmed

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The aim of the study is to compare the results of the external exposure and the range of the dose spread by the patients, hospitalized in two different groups of 3-5 d receiving radioiodine therapy because of thyroid cancer, and one of group were giving the local diuretic plant (barley) as local juice. The control group was 28 patients they were isolated as international precautions after taken I-131 capsule 100 mCi, and their external exposure was recorded day by day after first 24 hrs. and the distance for external measurement was 1 m at the abdominal level. The mean of external exposure values of patients at fourth day were 30.24±12.92 µSv h−1. The second group after taking I-131 capsule 100 mCi we were given barley juice (250 mL) after every meal three times on day and their external exposure was recorded day by day after first 24 hrs. The mean of external exposure values of patients of this group at third day was 26.92±9.89 (14-55) µSv h−1. It was observed that the external exposure from the second group clearly decreased to low levels which contributed to the decrease in patient dose and also to the decrease in the exposure from the patient to his/her family.

Keywords: local diuretic juice, therapy, radiation medicine, diuretic plant

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Authors: D. S. Palimkar

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Random fixed point theory has received much attention in recent years, and it is needed for the study of various classes of random equations. The study of random fixed point theorems was initiated by the Prague school of probabilistic in the 1950s. The existence and uniqueness of fixed points for the self-maps of a metric space by altering distances between the points with the use of a control function is an interesting aspect in the classical fixed point theory. In a new category of fixed point problems for a single self-map with the help of a control function that alters the distance between two points in a metric space which they called an altering distance function. In this paper, we prove the results of existence of random common fixed point and its uniqueness for a pair of random mappings under weakly contractive condition for generalizing alter distance function in polish spaces using Random Common Fixed Point Theorem for Generalized Weakly Contractions.

Keywords: Polish space, random common fixed point theorem, weakly contractive mapping, altering function

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Authors: Ren Moses

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The process of classifying vehicles on a highway is hereby viewed as a pattern recognition problem in which connectionist techniques such as artificial neural networks (ANN) can be used to assign vehicles to their correct classes and hence to establish optimum axle spacing thresholds. In the United States, vehicles are typically classified into 13 classes using a methodology commonly referred to as “Scheme F”. In this research, the ANN model was developed, trained, and applied to field data of vehicles. The data comprised of three vehicular features—axle spacing, number of axles per vehicle, and overall vehicle weight. The ANN reduced the classification error rate from 9.5 percent to 6.2 percent when compared to an existing classification algorithm that is not ANN-based and which uses two vehicular features for classification, that is, axle spacing and number of axles. The inclusion of overall vehicle weight as a third classification variable further reduced the error rate from 6.2 percent to only 3.0 percent. The promising results from the neural networks were used to set up new thresholds that reduce classification error rate.

Keywords: artificial neural networks, vehicle classification, traffic flow, traffic analysis, and highway opera-tions

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Authors: Yawen Wang, Hongchang Chen, Shaomei Li, Chao Gao, Jiangpeng Zhang

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As the main challenge for target tracking is accounting for target scale change and real-time, we combine Mean-Shift and PCA-SIFT algorithm together to solve the problem. We introduce similarity comparison method to determine how the target scale changes, and taking different strategies according to different situation. For target scale getting larger will cause location error, we employ backward tracking to reduce the error. Mean-Shift algorithm has poor performance when tracking scale-changing target due to the fixed bandwidth of its kernel function. In order to overcome this problem, we introduce PCA-SIFT matching. Through key point matching between target and template, that adjusting the scale of tracking window adaptively can be achieved. Because this algorithm is sensitive to wrong match, we introduce RANSAC to reduce mismatch as far as possible. Furthermore target relocating will trigger when number of match is too small. In addition we take comprehensive consideration about target deformation and error accumulation to put forward a new template update method. Experiments on five image sequences and comparison with 6 kinds of other algorithm demonstrate favorable performance of the proposed tracking algorithm.

Keywords: target tracking, PCA-SIFT, mean-shift, scale-adaptive

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Authors: Jaouadi Ikram, Machhout Mohsen

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The development of a quantum key distribution (QKD) system on a field-programmable gate array (FPGA) platform is the subject of this paper. A quantum cryptographic protocol is designed based on the properties of quantum information and the characteristics of FPGAs. The proposed protocol performs key extraction, reconciliation, error correction, and privacy amplification tasks to generate a perfectly secret final key. We modeled the presence of the spy in our system with a strategy to reveal some of the exchanged information without being noticed. Using an FPGA card with a 100 MHz clock frequency, we have demonstrated the evolution of the error rate as well as the amounts of mutual information (between the two interlocutors and that of the spy) passing from one step to another in the key generation process.

Keywords: QKD, BB84, protocol, cryptography, FPGA, key, security, communication

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Authors: Maryum Nawaz

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Purpose: To determine the frequency of refractive errors in squinting eyes of children from 4 to 16 years presenting at tertiary care hospital. Study Design: A descriptive cross-sectional study was done. Place and Duration: The study was conducted in Pediatric Ophthalmology, Hayatabad Medical Complex, Peshawar. Materials and Methods: The sample size was 146 keeping 41.45%5 proportion of refractive errors in children with squinting eyes, 95% confidence interval and 8% margin of error under WHO sample size calculations. Non-probability consecutive sampling was done. Result: Mean age was 8.57±2.66 years. Male were 89 (61.0%) and female were 57 (39.0%). Refractive error was present in 56 (38.4%) and was not present in 90 (61.6%) of patients. There was no association of gender, age, parent refractive errors, or early usage of electric equipment with the refractive errors. Conclusion: There is a high prevalence of refractive errors in a patient with strabismus. There is no association of age, gender, parent refractive errors, or early usage of electric equipment in the occurrence of refractive errors. Further studies are recommended for confirmation of these.

Keywords: strabismus, refractive error, myopia, hypermetropia, astigmatism

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Authors: Ahmed Abdelghany, Bernard Uguen, Christophe Moy, Dominique Lemur

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The Internet of Things (IoT) is developed to ensure monitoring and connectivity within different applications. Thus, it is critical to study the channel propagation characteristics in Low Power Wide Area Network (LPWAN), especially Long Range Wide Area Network (LoRaWAN). In this paper, an in-depth investigation of the reciprocity between the uplink and downlink Channel State Information (CSI) is done by performing an outdoor measurement campaign in the area of Campus Beaulieu in Rennes. At each different location, the CSI reciprocity is quantified using the Pearson Correlation Coefficient (PCC) which shows a very high linear correlation between the uplink and downlink CSI. This reciprocity feature could be utilized for the physical layer security between the node and the gateway. On the other hand, most of the CSI shapes from different locations are highly uncorrelated from each other. Hence, it can be anticipated that this could achieve significant localization gain by utilizing the frequency hopping in the LoRa systems by getting access to a wider band.

Keywords: IoT, LPWAN, LoRa, effective signal power, onsite measurement

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Authors: Buse T. Aydın, Enver Ozdemir

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In this study, a double layer authentication scheme between the aircraft and the Air Traffic Control (ATC) tower is designed to prevent any unauthorized aircraft from introducing themselves as friends. The method is a combination of classical cryptographic methods and new generation physical layers. The first layer has employed the embedded key of the aircraft. The embedded key is assumed to installed during the construction of the utility. The other layer is a physical attribute (flight path, distance, etc.) between the aircraft and the ATC tower. We create a mathematical model so that two layers’ information is employed and an aircraft is authenticated as a friend or foe according to the accuracy of the results of the model. The results of the aircraft are compared with the results of the ATC tower and if the values found by the aircraft and ATC tower match within a certain error margin, we mark the aircraft as a friend. In this method, even if embedded key is captured by the enemy aircraft, without the information of the second layer, the enemy can easily be determined. Overall, in this work, we present a more reliable system by adding a physical layer in the authentication process.

Keywords: ADS-B, communication with physical layer security, cryptography, identification friend or foe

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Authors: Maha Almumaiz, Harry Evdorides

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Change in land value typically occurs when a new interurban road construction causes an increase in accessibility; this change in the adjacent lands values differs according to land characteristics such as geographic location, land use type, land area and sale time (appraisal time). A multiple regression model is obtained to predict the percent change in land value (CLV) based on four independent variables namely land distance from the constructed road, area of land, nature of land use and time from the works completion of the road. The random values of percent change in land value were generated using Microsoft Excel with a range of up to 35%. The trend of change in land value with the four independent variables was determined from the literature references. The statistical analysis and model building process has been made by using the IBM SPSS V23 software. The Regression model suggests, for lands that are located within 3 miles as the straight distance from the road, the percent CLV is between (0-35%) which is depending on many factors including distance from the constructed road, land use, land area and time from works completion of the new road.

Keywords: interurban road, land use types, new road construction, percent CLV, regression model

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Authors: Faishal Muhammad, Erlinda Muslim, Nadia Faradilla, Sayidul Fikri

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To deal with the increase of mass transportation needs problem, PT. Kereta Commuter Jabodetabek (KCJ) implements Commuter Vending Machine (C-VIM) as the solution. For that background, C-VIM is implemented as a substitute to the conventional ticket windows with the purposes to make transaction process more efficient and to introduce self-service technology to the commuter line user. However, this implementation causing problems and long queues when the user is not accustomed to using the machine. The objective of this research is to evaluate user experience after using the commuter vending machine. The goal is to analyze the existing user experience problem and to achieve a better user experience design. The evaluation method is done by giving task scenario according to the features offered by the machine. The features are daily insured ticket sales, ticket refund, and multi-trip card top up. There 20 peoples that separated into two groups of respondents involved in this research, which consist of 5 males and 5 females each group. The experienced and inexperienced user to prove that there is a significant difference between both groups in the measurement. The user experience is measured by both quantitative and qualitative measurement. The quantitative measurement includes the user performance metrics such as task success, time on task, error, efficiency, and learnability. The qualitative measurement includes system usability scale questionnaire (SUS), questionnaire for user interface satisfaction (QUIS), and retrospective think aloud (RTA). Usability performance metrics shows that 4 out of 5 indicators are significantly different in both group. This shows that the inexperienced group is having a problem when using the C-VIM. Conventional ticket windows also show a better usability performance metrics compared to the C-VIM. From the data processing, the experienced group give the SUS score of 62 with the acceptability scale of 'marginal low', grade scale of “D”, and the adjective ratings of 'good' while the inexperienced group gives the SUS score of 51 with the acceptability scale of 'marginal low', grade scale of 'F', and the adjective ratings of 'ok'. This shows that both groups give a low score on the system usability scale. The QUIS score of the experienced group is 69,18 and the inexperienced group is 64,20. This shows the average QUIS score below 70 which indicate a problem with the user interface. RTA was done to obtain user experience issue when using C-VIM through interview protocols. The issue obtained then sorted using pareto concept and diagram. The solution of this research is interface redesign using activity relationship chart. This method resulted in a better interface with an average SUS score of 72,25, with the acceptable scale of 'acceptable', grade scale of 'B', and the adjective ratings of 'excellent'. From the time on task indicator of performance metrics also shows a significant better time by using the new interface design. Result in this study shows that C-VIM not yet have a good performance and user experience.

Keywords: activity relationship chart, commuter line vending machine, system usability scale, usability performance metrics, user experience evaluation

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Authors: Indrajit Ghosh, Jaydip Roy

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Literacy rate is an important indicator for measurement of human development. But this is not a good one to capture the qualitative dimension of educational attainment of an individual or a society. The overall educational level of an area is an important issue beyond the literacy rate. The overall educational level can be thought of as an outcome of the educational levels of individuals. But there is no well-defined algorithm and mathematical model available to measure the overall educational level of an area. A heuristic approach based on accumulated experience of experts is effective one. It is evident that fuzzy logic offers a natural and convenient framework in modeling various concepts in social science domain. This work suggests the implementation of fuzzy logic to develop a mathematical model for measurement of educational attainment of an area in terms of Education Index. The contribution of the study is two folds: conceptualization of “Education Profile” and proposing a new mathematical model to measure educational attainment in terms of “Education Index”.

Keywords: education index, education profile, fuzzy logic, literacy

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Authors: Uswah Khairuddin, Rubiyah Yusof, Nenny Ruthfalydia Rosli

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This paper presents a comparative study between k-Nearest Neighbour (k-NN) and Multi-Layer Perceptron Neural Network (MLP-NN) classifier using Genetic Algorithm (GA) as feature selector for wood recognition system. The features have been extracted from the images using Grey Level Co-Occurrence Matrix (GLCM). The use of GA based feature selection is mainly to ensure that the database used for training the features for the wood species pattern classifier consists of only optimized features. The feature selection process is aimed at selecting only the most discriminating features of the wood species to reduce the confusion for the pattern classifier. This feature selection approach maintains the ‘good’ features that minimizes the inter-class distance and maximizes the intra-class distance. Wrapper GA is used with k-NN classifier as fitness evaluator (GA-kNN). The results shows that k-NN is the best choice of classifier because it uses a very simple distance calculation algorithm and classification tasks can be done in a short time with good classification accuracy.

Keywords: feature selection, genetic algorithm, optimization, wood recognition system

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Authors: Jularat Chumnaul

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In forensic science, corpses from various homicides are different; there are both complete and incomplete, depending on causes of death or forms of homicide. For example, some corpses are cut into pieces, some are camouflaged by dumping into the river, some are buried, some are burned to destroy the evidence, and others. If the corpses are incomplete, it can lead to the difficulty of personally identifying because some tissues and bones are destroyed. To specify gender of the corpses from skeletal remains, the most precise method is DNA identification. However, this method is costly and takes longer so that other identification techniques are used instead. The first technique that is widely used is considering the features of bones. In general, an evidence from the corpses such as some pieces of bones, especially the skull and pelvis can be used to identify their gender. To use this technique, forensic scientists are required observation skills in order to classify the difference between male and female bones. Although this technique is uncomplicated, saving time and cost, and the forensic scientists can fairly accurately determine gender by using this technique (apparently an accuracy rate of 90% or more), the crucial disadvantage is there are only some positions of skeleton that can be used to specify gender such as supraorbital ridge, nuchal crest, temporal lobe, mandible, and chin. Therefore, the skeletal remains that will be used have to be complete. The other technique that is widely used for gender specifying in forensic science and archeology is skeletal measurements. The advantage of this method is it can be used in several positions in one piece of bones, and it can be used even if the bones are not complete. In this study, the classification and cluster analysis are applied to this technique, including the Kth Nearest Neighbor Classification, Classification Tree, Ward Linkage Cluster, K-mean Cluster, and Two Step Cluster. The data contains 507 particular individuals and 9 skeletal measurements (diameter measurements), and the performance of five methods are investigated by considering the apparent error rate (APER). The results from this study indicate that the Two Step Cluster and Kth Nearest Neighbor method seem to be suitable to specify gender from human skeletal remains because both yield small apparent error rate of 0.20% and 4.14%, respectively. On the other hand, the Classification Tree, Ward Linkage Cluster, and K-mean Cluster method are not appropriate since they yield large apparent error rate of 10.65%, 10.65%, and 16.37%, respectively. However, there are other ways to evaluate the performance of classification such as an estimate of the error rate using the holdout procedure or misclassification costs, and the difference methods can make the different conclusions.

Keywords: skeletal measurements, classification, cluster, apparent error rate

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Authors: Qinyi Mei, Li-Ping Wang

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MDS matrices are of great significance in the design of block ciphers and hash functions. In the present paper, we investigate the problem of constructing MDS matrices which are both lightweight and low-latency. We propose a new method of constructing lightweight MDS matrices using circulant matrices which can be implemented efficiently in hardware. Furthermore, we provide circulant MDS matrices with as few bit XOR operations as possible for the classical dimensions 4 × 4, 8 × 8 over the space of linear transformations over finite field F42 . In contrast to previous constructions of MDS matrices, our constructions have achieved fewer XORs.

Keywords: linear diffusion layer, circulant matrix, lightweight, maximum distance separable (MDS) matrix

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Authors: Photjanat Phimnom, Haruetai Lohasiriwat

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In today’s world, the LED display has been used for presenting visual information under various circumstances. Such information is an important intermediary in the human information processing. Researchers have been investigated diverse factors that influence this process effectiveness. The letter size is undoubtedly one major factor that has been tested and recommended by many standards and guidelines. However, viewing information on the display from direct perpendicular position is a typical assumption whereas many actual events are required viewing from the angles. This current research aims to study the effect of oblique viewing angle and viewing distance on ability to recognize alphabet, number, and English word. The total of ten participants was volunteered to our 3 x 4 x 4 within subject study. Independent variables include three distance levels (2, 6, and 12 m), four oblique angle (0, 45, 60, 75 degree), and four target types (alphabet, number, short words, and long words). Following the method of constant stimuli we found that the larger oblique angle, ranging from 0 to 75 degree from the line of sight, results in significant higher legibility threshold or larger font size required (p-value < 0.05). Viewing distance factor also shows to have significant effect on the threshold (p-value < 0.05). However, the effect from distance factor is expected to be confounded by the quality of the screen we used in our experiment. Lastly, our results show that single alphabet as well as single number are recognized at significant lower threshold (smaller font size) as compared to both short and long words (p-value < 0.05). Therefore, it is recommended that when designs information to be presented on LED display, understanding of all possible ranges of oblique angle should be taken into account in order to specify the preferred letter size. Additionally, the recommendation of letter size for 100 % readability in our tested conditions is provided in the paper.

Keywords: letter size, oblique angle, viewing distance, legibility threshold

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Authors: Derjew Ayele Ejigu, Houde Song, Xiaojing Liu

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This work presents the particle swarm optimization trained neural network (PSO-NN) supervisory proportional integral derivative (PID) control method to monitor the pressurized water reactor (PWR) core power for safe operation. The proposed control approach is implemented on the transfer function of the PWR core, which is computed from the state-space model. The PWR core state-space model is designed from the neutronics, thermal-hydraulics, and reactivity models using perturbation around the equilibrium value. The proposed control approach computes the control rod speed to maneuver the core power to track the reference in a closed-loop scheme. The particle swarm optimization (PSO) algorithm is used to train the neural network (NN) and to tune the PID simultaneously. The controller performance is examined using integral absolute error, integral time absolute error, integral square error, and integral time square error functions, and the stability of the system is analyzed by using the Bode diagram. The simulation results indicated that the controller shows satisfactory performance to control and track the load power effectively and smoothly as compared to the PSO-PID control technique. This study will give benefit to design a supervisory controller for nuclear engineering research fields for control application.

Keywords: machine learning, neural network, pressurized water reactor, supervisory controller

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Authors: S. Dorbani, M. Badaoui, D. Benouar

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The aim of this paper is to investigate the effect of the building fundamental period of reinforced concrete buildings of (6, 9, and 12-storey), with different floor plans: Symmetric, mono-symmetric, and unsymmetric. These structures are erected at different epicentral distances. Using the Boumerdes, Algeria (2003) earthquake data, we focused primarily on the establishment of the deterministic formulation linking the base shear force to two parameters: The first one is the fundamental period that represents the numerical fingerprint of the structure, and the second one is the epicentral distance used to represent the impact of the earthquake on this force. In a second step, with a view to highlight the effect of uncertainty in these parameters on the analyzed response, these parameters are modeled as random variables with a log-normal distribution. The variability of the coefficients of variation of the chosen uncertain parameters, on the statistics on the seismic base shear force, showed that the effect of uncertainty on fundamental period on this force statistics is low compared to the epicentral distance uncertainty influence.

Keywords: base shear force, fundamental period, epicentral distance, uncertainty, lognormal variables, statistics

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Authors: Ignatio Madanhire, Charles Mbohwa

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This study looks at the best model of aggregate planning activity in an industrial entity and uses the trial and error method on spreadsheets to solve aggregate production planning problems. Also linear programming model is introduced to optimize the aggregate production planning problem. Application of the models in a furniture production firm is evaluated to demonstrate that practical and beneficial solutions can be obtained from the models. Finally some benchmarking of other furniture manufacturing industries was undertaken to assess relevance and level of use in other furniture firms

Keywords: aggregate production planning, trial and error, linear programming, furniture industry

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Authors: Yassine Bouzouita, Oumaima Belghith, Cyrine Zitoun, Charles Bonneau

Abstract:

Performance measurement framework (PMF) is an essential tool in any organization to assess the performance of its processes. It guides businesses to stay on track with their objectives and benchmark themselves from the market. With the growing trend of the digital transformation of business processes, led by innovations in artificial intelligence (AI) & Big Data applications, developing a mature system capable of capturing the impact of digital solutions across different industries became a necessity. Based on the conducted research, no such system has been developed in academia nor the industry. In this context, this paper covers a variety of methodologies on performance measurement, overviews the major AI and big data applications in the banking sector, and covers an exhaustive list of relevant metrics. Consequently, this paper is of interest to both researchers and practitioners. From an academic perspective, it offers a comparative analysis of the reviewed performance measurement frameworks. From an industry perspective, it offers exhaustive research, from market leaders, of the major applications of AI and Big Data technologies, across the different departments of an organization. Moreover, it suggests a standardized classification model with a well-defined structure of intelligent digital solutions. The aforementioned classification is mapped to a centralized library that contains an indexed collection of potential metrics for each application. This library is arranged in a manner that facilitates the rapid search and retrieval of relevant metrics. This proposed framework is meant to guide professionals in identifying the most appropriate AI and big data applications that should be adopted. Furthermore, it will help them meet their business objectives through understanding the potential impact of such solutions on the entire organization.

Keywords: AI and Big Data applications, impact assessment, metrics, performance measurement

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Authors: Geeta Kasana, Kulbir Singh, Satvinder Singh

Abstract:

In this paper, a steganographic scheme for digital images using Integer Wavelet Transform (IWT) is proposed. The cover image is decomposed into wavelet sub bands using IWT. Each of the subband is divided into blocks of equal size and secret data is embedded into the largest and smallest pixel values of each block of the subband. Visual quality of stego images is acceptable as PSNR between cover image and stego is above 40 dB, imperceptibility is maintained. Experimental results show better tradeoff between capacity and visual perceptivity compared to the existing algorithms. Maximum possible error analysis is evaluated for each of the wavelet subbands of an image.

Keywords: DWT, IWT, MSE, PSNR

Procedia PDF Downloads 504