Search results for: early identification

Authors: Hend S.H. Hassan, Essam M. Shehab, Joe Peppard

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E-government projects have potential for greater efficiency and effectiveness of government operations. For this reason, many developing countries governments have invested heavily in this agenda and an increasing number of e-government projects are being implemented. However, there is a lack of clear case material, which describes the potentialities and consequence experienced by organizations trying to manage with this change. The Ministry of State for Administrative Development (MSAD) is the organization responsible for the e-Government program in Egypt since early 2004. This paper presents a case study of the process of admission to public universities and institutions in Egypt which is led by MSAD. Underlining the key benefits resulting from the initiative, explaining the strategies and the development steps used to implement it, and highlighting the main obstacles encountered and how they were overcome will help repeat the experience in other useful e-government projects.

Keywords: Case studies, Egypt, Electronic government, Electronic services, University enrolment.

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Authors: A. S. Kipcak, P. Gurses, K. Kunt, E. Moroydor Derun, S. Piskin

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There are many kinds of metal borates found not only in nature but also synthesized in the laboratory such as magnesium borates. Due to its excellent properties, as remarkable ceramic materials, they have also application areas in anti-wear and friction reducing additives as well as electro-conductive treating agents. The synthesis of magnesium borate powders can be fulfilled simply with two different methods, hydrothermal and thermal synthesis. Microwave assisted method, also another way of producing magnesium borate, can be classified into thermal synthesis because of using the principles of solid state synthesis. It also contributes producing particles with small size and high purity in nano-size material synthesize. In this study the production of magnesium borates, are aimed using MgCl2.6H2O and H3BO3. The identification of both starting materials and products were made by the equipments of, X-Ray Diffraction (XRD) and Fourier Transform Infrared Spectroscopy (FT-IR). After several synthesis steps magnesium borates were synthesized and characterized by XRD and FT-IR, as well.

Keywords: FT-IR, magnesium borates, microwave method, XRD.

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Authors: T. Hacib, M. R. Mekideche, N. Ferkha

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This paper presents an approach which is based on the use of supervised feed forward neural network, namely multilayer perceptron (MLP) neural network and finite element method (FEM) to solve the inverse problem of parameters identification. The approach is used to identify unknown parameters of ferromagnetic materials. The methodology used in this study consists in the simulation of a large number of parameters in a material under test, using the finite element method (FEM). Both variations in relative magnetic permeability and electrical conductivity of the material under test are considered. Then, the obtained results are used to generate a set of vectors for the training of MLP neural network. Finally, the obtained neural network is used to evaluate a group of new materials, simulated by the FEM, but not belonging to the original dataset. Noisy data, added to the probe measurements is used to enhance the robustness of the method. The reached results demonstrate the efficiency of the proposed approach, and encourage future works on this subject.

Keywords: Inverse problem, MLP neural network, parametersidentification, FEM.

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Authors: Wararat Rungworawut, Twittie Senivongse

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Business process model describes process flow of a business and can be seen as the requirement for developing a software application. This paper discusses a BPM2CD guideline which complements the Model Driven Architecture concept by suggesting how to create a platform-independent software model in the form of a UML class diagram from a business process model. An important step is the identification of UML classes from the business process model. A technique for object-oriented analysis called domain analysis is borrowed and key concepts in the business process model will be discovered and proposed as candidate classes for the class diagram. The paper enhances this step by using ontology search to help identify important classes for the business domain. As ontology is a source of knowledge for a particular domain which itself can link to ontologies of related domains, the search can give a refined set of candidate classes for the resulting class diagram.

Keywords: Business Process Model, Model DrivenArchitecture, Ontology, UML Class Diagram.

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Authors: S. Chhabra, C. Tickoo, P. Kalra

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Background: Bleeding during first half of pregnancy mostly originates from placenta, some abort, others are at risk of complications. Objective: Study was done to know perinatal outcome with bleeding up to 20 weeks in singleton pregnancy. Material Methods: Subjects were 1020, equal controls managed over 2 years, 435 had viable pregnancy at admission, 135 excluded, 300 followed for perinatal outcome, 99 (19.52% up to 10 weeks), 201 (39.18% of 11-20 weeks). Results: Hypertensive disorders occurred in 24% cases of bleeding within 10 weeks, 22% 11-20 weeks 14.79% controls, placenta previa 4% in 10 weeks, 0.9% 11-20 weeks, 0.97% controls, prelabor rupture of membranes in 16%, 7.45% controls. 20% up to 10 weeks, 35% 11-20 weeks, 18% controls had fetal growth restriction, 34.34% up to 10 weeks 30.35% of 11-20 weeks 17.17% controls had preterm births, perinatal mortality rate in study was 118.62, in controls 68.16 (Uneventful pregnancy in 13.52% study, 46.11% controls). Conclusion: Once bleeding occurs, one third continue pregnancy, maternal neonatal outcome gets affected with variations in cases of bleeding within first 10 weeks & 11-20 weeks.

Keywords: First, Second trimester, bleeding, Disorders, Perinatal Outcome.

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Authors: Pearl Goswell, Jun Jo

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Creating3D environments, including characters and cities, is a significantly time consuming process due to a large amount of workinvolved in designing and modelling.There have been a number of attempts to automatically generate 3D objects employing shape grammars. However it is still too early to apply the mechanism to real problems such as real-time computer games.The purpose of this research is to introduce a time efficient and cost effective method to automatically generatevarious 3D objects for real-time 3D games. This Shape grammar-based real-time City Generation (RCG) model is a conceptual model for generating 3Denvironments in real-time and can be applied to 3D gamesoranimations. The RCG system can generate even a large cityby applying fundamental principles of shape grammars to building elementsin various levels of detailin real-time.

Keywords: real-time city generation, shape grammars, 3D games, 3D modelling.

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Authors: N. Seladji-Hassaine, L. Merad, S.M. Meriah, F.T. Bendimerad

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UWB is a very attractive technology for many applications. It provides many advantages such as fine resolution and high power efficiency. Our interest in the current study is the use of UWB radar technique in microwave medical imaging systems, especially for early breast cancer detection. The Federal Communications Commission FCC allowed frequency bandwidth of 3.1 to 10.6 GHz for this purpose. In this paper we suggest an UWB Bowtie slot antenna with enhanced bandwidth. Effects of varying the geometry of the antenna on its performance and bandwidth are studied. The proposed antenna is simulated in CST Microwave Studio. Details of antenna design and simulation results such as return loss and radiation patterns are discussed in this paper. The final antenna structure exhibits good UWB characteristics and has surpassed the bandwidth requirements.

Keywords: Ultra Wide Band (UWB), microwave imaging system, Bowtie antenna, return loss, impedance bandwidth enhancement.

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Authors: Zarita Zainuddin, Ong Pauline

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Wavelet neural networks (WNNs) have emerged as a vital alternative to the vastly studied multilayer perceptrons (MLPs) since its first implementation. In this paper, we applied various clustering algorithms, namely, K-means (KM), Fuzzy C-means (FCM), symmetry-based K-means (SBKM), symmetry-based Fuzzy C-means (SBFCM) and modified point symmetry-based K-means (MPKM) clustering algorithms in choosing the translation parameter of a WNN. These modified WNNs are further applied to the heterogeneous cancer classification using benchmark microarray data and were compared against the conventional WNN with random initialization method. Experimental results showed that a WNN classifier with the MPKM algorithm is more precise than the conventional WNN as well as the WNNs with other clustering algorithms.

Keywords: Clustering, microarray, symmetry, wavelet neural networks.

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Authors: Sylvain Devie, Pierre-Philippe Robet, Yannick Aoustin, Maxime Gautier

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The aim of this paper is to show that the observation of the external effort and the sensor-less control of a system is limited by the mechanical system. First, the model of a one-joint robot with a prismatic joint is presented. Based on this model, two different procedures were performed in order to identify the mechanical parameters of the system and observe the external effort applied on it. Experiments have proven that the accuracy of the force observer, based on the DC motor current, is limited by the mechanics of the robot. The sensor-less control will be limited by the accuracy in estimation of the mechanical parameters and by the maximum static friction force, that is the minimum force which can be observed in this case. The consequence of this limitation is that industrial robots without specific design are not well adapted to perform sensor-less precision tasks. Finally, an efficient control law is presented for high effort applications.

Keywords: Control, Identification, Robot, Co-manipulation, Sensor-less.

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Authors: Narges Razeghi

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In studies on psychological health and children-s personality development and in researches on emotional distresses, children-s behavioral disorders associated with mother deprivation, are known as the major cause of mental disorders. Therefore, for identification of children-s attachment styles in nursery-s children are of significant importance. For this purpose, to compare the attachment styles between children of nursery with those provided care by their families, the Separation Anxiety Test (SAT) of Slough and et al was administered on 72 children (36 in nursery and 36 family-cared). The results indicated, almost half of children in both groups have insecure attachment styles. Tendency ratio of both groups of children towards Secure and Ambivalent Insecure styles are almost the same. However the avoidant style of attachment in children of nursery is more than those provided care by their families. The children under family care compared to the children of nursery, in the situations of separation from their mothers in the first day of school and sleeping in their room, have shown more self reliance.

Keywords: Attachment style, Separation Anxiety Test (SAT), Children, Nursery, Emotional and Behavioral Disorders

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Authors: John Florescu

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A challenged control problem is when the performance is pushed to the limit. The state-derivative feedback control strategy directly uses acceleration information for feedback and state estimation. The derivative part is concerned with the rateof- change of the error with time. If the measured variable approaches the set point rapidly, then the actuator is backed off early to allow it to coast to the required level. Derivative action makes a control system behave much more intelligently. A sensor measures the variable to be controlled and the measured in formation is fed back to the controller to influence the controlled variable. A high gain problem can be also formulated for proportional plus derivative feedback transformation. Using MATLAB Simulink dynamic simulation tool this paper examines a system with a proportional plus derivative feedback and presents an automatic implementation of finding an acceptable controlled system. Using feedback transformations the system is transformed into another system.

Keywords: Feedback, PD, state-space, derivative.

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Authors: Elnura Assyltayeva, Zhanar Aldubasheva, Zhengisbek Tolen

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An attempt has been made several times to identify and discuss the U.S. experience on the formation of political nation in political science. The purpose of this research paper is to identify the main aspects of the formation of civic identity in the United States and Kazakhstan, through the identification of similarities and differences that can get practical application in making decisions of national policy issues in the context of globalization, as well as to answer the questions “What should unite the citizens of Kazakhstan to the nation?" and “What should be the dominant identity: civil or ethnic (national) one?" Can Kazakhstan being multiethnic country like America, adopt its experience in the formation of a civic nation? Since it is believed that the “multi-ethnic state of the population is a characteristic feature of most modern countries in the world," it states that “inter-ethnic integration is one of the most important aspects of the problem of forming a new social community (metaetnic - Kazakh people, Kazakh nation" [1].

Keywords: nation, civic identity, nation building, globalization, interethnic relations, patriotism

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Authors: Bubaker M. F. Bushofa, Abdel Hafez A. Azab

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This article is based on the technique which is called Discrete Parameter Tracking (DPT). First introduced by A. A. Azab [8] which is applicable for less order reference model. The order of the reference model is (n-l) and n is the number of the adjustable parameters in the physical plant. The technique utilizes a modified gradient method [9] where the knowledge of the exact order of the nonadaptive system is not required, so, as to eliminate the identification problem. The applicability of the mentioned technique (DPT) was examined through the solution of several problems. This article introduces the solution of a third order system with three adjustable parameters, controlled according to second order reference model. The adjustable parameters have great initial error which represent condition. Computer simulations for the solution and analysis are provided to demonstrate the simplicity and feasibility of the technique.

Keywords: Adaptive Control System, Discrete Parameter Tracking, Discrete Time Model.

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Authors: Uchenna Bella Onu

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Traditional art is one of Nigerian cultural heritage. It is an excellent instrument for documentation and identification. Antiquities are priceless and irreplaceable. They are basically preserved for future generations. Sadly, preserving these highly prized cultural heritage is becoming a serious challenge. This paper examines the extent modernization has affected the preservation of traditional art in Nigeria. Particularly hit is the antiquities and traditional murals of eastern part of Nigeria. Participatory visual methods were used for this study. Efforts were made to reach the few surviving and aged mural artists. Oral information was collected from them as well as first hand drawings and some photographs of their works. Findings indicate that modernization has seriously affected the preservation of Nigerian artistic heritage. Further findings show that traditional mural artists are gradually dwindling and dangerously going into extinct. Antiquities are indiscriminately destroyed due to sheer ignorance and the blind quest to fit into the so called modern world.  

Keywords: Antiquities, artistic heritage, cultural preservation, drawings, modernization, murals.

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Authors: N. A. Ibrahim, A. Kudus, I. Daud, M. R. Abu Bakar

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Competing risks survival data that comprises of more than one type of event has been used in many applications, and one of these is in clinical study (e.g. in breast cancer study). The decision tree method can be extended to competing risks survival data by modifying the split function so as to accommodate two or more risks which might be dependent on each other. Recently, researchers have constructed some decision trees for recurrent survival time data using frailty and marginal modelling. We further extended the method for the case of competing risks. In this paper, we developed the decision tree method for competing risks survival time data based on proportional hazards for subdistribution of competing risks. In particular, we grow a tree by using deviance statistic. The application of breast cancer data is presented. Finally, to investigate the performance of the proposed method, simulation studies on identification of true group of observations were executed.

Keywords: Competing risks, Decision tree, Simulation, Subdistribution Proportional Hazard.

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Authors: V. I. Thajudin Ahamed, P. Dhanasekaran, A. Naseem, N. G. Karthick, T. K. Abdul Jaleel, Paul K.Joseph

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It is established that the instantaneous heart rate (HR) of healthy humans keeps on changing. Analysis of heart rate variability (HRV) has become a popular non invasive tool for assessing the activities of autonomic nervous system. Depressed HRV has been found in several disorders, like diabetes mellitus (DM) and coronary artery disease, characterised by autonomic nervous dysfunction. A new technique, which searches for pattern repeatability in a time series, is proposed specifically for the analysis of heart rate data. These set of indices, which are termed as pattern repeatability measure and pattern repeatability ratio are compared with approximate entropy and sample entropy. In our analysis, based on the method developed, it is observed that heart rate variability is significantly different for DM patients, particularly for patients with diabetic foot ulcer.

Keywords: Autonomic nervous system, diabetes mellitus, heart rate variability, pattern identification, sample entropy

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Authors: A. Sopharak, B. Uyyanonvara, S. Barman

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Microaneurysm is a key indicator of diabetic retinopathy that can potentially cause damage to retina. Early detection and automatic quantification are the keys to prevent further damage. In this paper, which focuses on automatic microaneurysm detection in images acquired through non-dilated pupils, we present a series of experiments on feature selection and automatic microaneurysm pixel classification. We found that the best feature set is a combination of 10 features: the pixel-s intensity of shade corrected image, the pixel hue, the standard deviation of shade corrected image, DoG4, the area of the candidate MA, the perimeter of the candidate MA, the eccentricity of the candidate MA, the circularity of the candidate MA, the mean intensity of the candidate MA on shade corrected image and the ratio of the major axis length and minor length of the candidate MA. The overall sensitivity, specificity, precision, and accuracy are 84.82%, 99.99%, 89.01%, and 99.99%, respectively.

Keywords: Diabetic retinopathy, microaneurysm, naive Bayes classifier

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Authors: Siti Khairunniza-Bejo, Yusnida Yusoff, Nik Salwani Nik Yusoff, Idris Abu Seman, Mohamad Izzuddin Anuar

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Most of the oil palm plantations have been threatened by Basal Stem Rot (BSR) disease which causes serious economic impact. This study was conducted to identify the healthy and BSRinfected oil palm tree using thirteen color indices. Multispectral and thermal camera was used to capture 216 images of the leaves taken from frond number 1, 9 and 17. Indices of normalized difference vegetation index (NDVI), red (R), green (G), blue (B), near infrared (NIR), green – blue (GB), green/blue (G/B), green – red (GR), green/red (G/R), hue (H), saturation (S), intensity (I) and thermal index (T) were used. From this study, it can be concluded that G index taken from frond number 9 is the best index to differentiate between the healthy and BSR-infected oil palm trees. It not only gave high value of correlation coefficient (R=-0.962), but also high value of separation between healthy and BSR-infected oil palm tree. Furthermore, power and S model developed using G index gave the highest R2 value which is 0.985.

Keywords: Oil palm, image processing, disease, leaves.

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Authors: Chunling Cong, Chris.P.Tsokos

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The objective of the present research manuscript is to perform parametric, nonparametric, and decision tree analysis to evaluate two treatments that are being used for breast cancer patients. Our study is based on utilizing real data which was initially used in “Tamoxifen with or without breast irradiation in women of 50 years of age or older with early breast cancer" [1], and the data is supplied to us by N.A. Ibrahim “Decision tree for competing risks survival probability in breast cancer study" [2]. We agree upon certain aspects of our findings with the published results. However, in this manuscript, we focus on relapse time of breast cancer patients instead of survival time and parametric analysis instead of semi-parametric decision tree analysis is applied to provide more precise recommendations of effectiveness of the two treatments with respect to reoccurrence of breast cancer.

Keywords: decision tree, breast cancer treatments, parametricanalysis, non-parametric analysis

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Authors: Ahmed Amin Mousa, M. Abd El Salam

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The current study presents a proposed program for acquisition the skills and techniques needed to produce concept cartoon. The proposed program has been prepared for non-specialist students who have never used neither graphics nor animating software. It was presented to postgraduates in Faculty of Education for Early Childhood, Cairo University, during the spring term of the 2014-2015 academic year. The program works in three different aspects: Drawing and images editing, sound manipulation, and creating animation. In addition, the researchers have prepared a questionnaire for measuring the quality of the concept cartoons produced by the students. The questionnaire was used as a pre-test and post-test, and at the end of the study, a significant difference was determined in favour of post-test results.

Keywords: Cartoon, concept cartoon, kindergarten, animation.

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Authors: Muhammad Kamil Abdullah, Khazaimatol S Subari, Justin Leo Cheang Loong, Nurul Nadia Ahmad

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This paper discusses the effectiveness of the EEG signal for human identification using four or less of channels of two different types of EEG recordings. Studies have shown that the EEG signal has biometric potential because signal varies from person to person and impossible to replicate and steal. Data were collected from 10 male subjects while resting with eyes open and eyes closed in 5 separate sessions conducted over a course of two weeks. Features were extracted using the wavelet packet decomposition and analyzed to obtain the feature vectors. Subsequently, the neural networks algorithm was used to classify the feature vectors. Results show that, whether or not the subjects- eyes were open are insignificant for a 4– channel biometrics system with a classification rate of 81%. However, for a 2–channel system, the P4 channel should not be included if data is acquired with the subjects- eyes open. It was observed that for 2– channel system using only the C3 and C4 channels, a classification rate of 71% was achieved.

Keywords: Biometric, EEG, Wavelet Packet Decomposition, NeuralNetworks

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Authors: Ahsan Bin Tufail, Ali Abidi, Adil Masood Siddiqui, Muhammad Shahzad Younis

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An early and accurate detection of Alzheimer's disease (AD) is an important stage in the treatment of individuals suffering from AD. We present an approach based on the use of structural magnetic resonance imaging (sMRI) phase images to distinguish between normal controls (NC), mild cognitive impairment (MCI) and AD patients with clinical dementia rating (CDR) of 1. Independent component analysis (ICA) technique is used for extracting useful features which form the inputs to the support vector machines (SVM), K nearest neighbour (kNN) and multilayer artificial neural network (ANN) classifiers to discriminate between the three classes. The obtained results are encouraging in terms of classification accuracy and effectively ascertain the usefulness of phase images for the classification of different stages of Alzheimer-s disease.

Keywords: Biomedical image processing, classification algorithms, feature extraction, statistical learning.

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Authors: Abderrahmane Diaf, Kamel Benabdellaziz

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Remote arid areas of the vast expanses of the African deserts hold huge subterranean reserves of brackish water resources waiting for economic development. This work presents design guidelines as well as initial performance data of new autonomous solar desalination equipment which could help local communities produce their own fresh water using solar energy only and, why not, contribute to transforming desert lands into lush gardens. The output of solar distillation equipments are typically low and in the range of 3 l/m2/day on the average. This new design with an integrated, water based, environmentally-friendly solar heat storage system produced 5 l/m2/day in early spring weather. Equipment output during summer exceeded 9 liters per m2 per day.

Keywords: Multiple trough distillation, solar desalination, solar distillation with heat storage, water based heat storage system.

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Authors: M. Naresh Kumar, Abhijit Mitra, C. Ardil

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A fast adaptive Tomlinson Harashima (T-H) precoder structure is presented for indoor wireless communications, where the channel may vary due to rotation and small movement of the mobile terminal. A frequency-selective slow fading channel which is time-invariant over a frame is assumed. In this adaptive T-H precoder, feedback coefficients are updated at the end of every uplink frame by using system identification technique for channel estimation in contrary with the conventional T-H precoding concept where the channel is estimated during the starting of the uplink frame via Wiener solution. In conventional T-H precoder it is assumed the channel is time-invariant in both uplink and downlink frames. However assuming the channel is time-invariant over only one frame instead of two, the proposed adaptive T-H precoder yields better performance than conventional T-H precoder if the channel is varied in uplink after receiving the training sequence.

Keywords: Tomlinson-Harashima precoder, Adaptive channel estimation, Indoor wireless communication, Bit error rate.

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Authors: Yetti Marlida , Rina Delfita , Neni Gusmanizar, Gita Ciptaan

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Phytases are acid phosphatase enzymes, which efficiently cleave phosphate moieties from phytic acid, thereby generating myo-inositol and inorganic phosphate. Thirty four isolates of endophytic fungi to produce of phytases were isolated from leaf, stem and root fragments of soybean. Screening of 34 isolates of endophytic fungi identified the phytases produced by Rhizoctonia sp. and Fusarium verticillioides . The phytase production were the best induced by phytic acid and rice bran compared the others inducer in submerged fermentation medium used. The phytase produced by both Rhizoctonia sp. and F. verticillioides have pH optimum at 4.0 and 5.0 respectively. The characterization of phytase from Fusarium verticillioides showed that temperature optimum was 500C and stability until 600C, the pH optimum 5.0 and pH stability was 2.5 – 6.0, and substrate specificity were rice bran>soybean meal>corn> coconut cake, respectively.

Keywords: endophytic fungus, phytase, soybean, Rhizoctoniasp., Fusarium verticillioides,

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Authors: S. W. Hong, Y. S. Choi, T. H. Chung, J. H. Song, H. S. Kim

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Bio-electrical responses obtained from freshwater sediments by employing microbial fuel cell (MFC) technology were investigated in this experimental study. During the electricity generation, organic matter in the sediment was microbially oxidized under anaerobic conditions with an electrode serving as a terminal electron acceptor. It was found that the sediment organic matter (SOM) associated with electrochemically-active electrodes became more humified, aromatic, and polydispersed, and had a higher average molecular weight, together with the decrease in the quantity of SOM. The alteration of characteristics of the SOM was analogous to that commonly observed in the early stage of SOM diagenetic process (i.e., humification). These findings including an elevation of the sediment redox potential present a possibility of the MFC technology as a new soil/sediment remediation technique based on its potential benefits: non-destructive electricity generation and bioremediation.

Keywords: Anaerobic oxidation, microbial fuel cell, remediation, sediment.

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Authors: Micheal Olaolu Arowolo, Muhammad Azam, Fei He, Mihail Popescu, Dong Xu

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As the quantity of biological articles rises, so does the number of biological route figures. Each route figure shows gene names and relationships. Manually annotating pathway diagrams is time-consuming. Advanced image understanding models could speed up curation, but they must be more precise. There is rich information in biological pathway figures. The first step to performing image understanding of these figures is to recognize gene names automatically. Classical optical character recognition methods have been employed for gene name recognition, but they are not optimized for literature mining data. This study devised a method to recognize an image bounding box of gene name as a photo using deep Siamese neural network models to outperform the existing methods using ResNet, DenseNet and Inception architectures, the results obtained about 84% accuracy.

Keywords: Biological pathway, gene identification, object detection, Siamese network, ResNet.

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Authors: Dawei Cai

Abstract:

This paper describes a design of earphone style wearable device that may provide an automatic guidance service for visitors. With both position information and orientation information obtained from NFC and terrestrial magnetism sensor, a high level automatic guide service may be realized. To realize the service, a algorithm for position detection using the packet from NFC tags, and developed an algorithm to calculate the device orientation based on the data from acceleration and terrestrial magnetism sensors called as MEMS. If visitors want to know some explanation about an exhibit in front of him, what he has to do is only move to the object and stands for a moment. The identification program will automatically recognize the status based on the information from NFC and MEMS, and start playing explanation content about the exhibit. This service should be useful for improving the understanding of the exhibition items and bring more satisfactory visiting experience without less burden.

Keywords: Wearable device, MEMS sensor, NFC, ubiquitous computing, guide system.

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Authors: A. Appe, B. Poluparthi, L. Kasivajjula, U. Mv, S. Bagadi, P. Modi, A. Singh, H. Gunupudi, S. Troiano, J. Paul, J. Stovall, J. Yamamoto

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The necessity of data-driven decisions in healthcare strategy formulation is rapidly increasing. A reliable framework which helps identify factors impacting a healthcare provider facility or a hospital (from here on termed as facility) market share is of key importance. This pilot study aims at developing a data-driven machine learning-regression framework which aids strategists in formulating key decisions to improve the facility’s market share which in turn impacts in improving the quality of healthcare services. The US (United States) healthcare business is chosen for the study, and the data spanning 60 key facilities in Washington State and about 3 years of historical data are considered. In the current analysis, market share is termed as the ratio of the facility’s encounters to the total encounters among the group of potential competitor facilities. The current study proposes a two-pronged approach of competitor identification and regression approach to evaluate and predict market share, respectively. Leveraged model agnostic technique, SHAP (SHapley Additive exPlanations), to quantify the relative importance of features impacting the market share. Typical techniques in literature to quantify the degree of competitiveness among facilities use an empirical method to calculate a competitive factor to interpret the severity of competition. The proposed method identifies a pool of competitors, develops Directed Acyclic Graphs (DAGs) and feature level word vectors, and evaluates the key connected components at the facility level. This technique is robust since it is data-driven, which minimizes the bias from empirical techniques. The DAGs factor in partial correlations at various segregations and key demographics of facilities along with a placeholder to factor in various business rules (for e.g., quantifying the patient exchanges, provider references, and sister facilities). Identified are the multiple groups of competitors among facilities. Leveraging the competitors' identified developed and fine-tuned Random Forest Regression model to predict the market share. To identify key drivers of market share at an overall level, permutation feature importance of the attributes was calculated. For relative quantification of features at a facility level, incorporated SHAP, a model agnostic explainer. This helped to identify and rank the attributes at each facility which impacts the market share. This approach proposes an amalgamation of the two popular and efficient modeling practices, viz., machine learning with graphs and tree-based regression techniques to reduce the bias. With these, we helped to drive strategic business decisions.

Keywords: Competition, DAGs, hospital, healthcare, machine learning, market share, random forest, SHAP.

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Authors: Togzhan D. Mukasheva, Anel A. Omirbekova, Raikhan S. Sydykbekova, Ramza Zh. Berzhanova, Lyudmila V. Ignatova

Abstract:

Following plants-barley (Hordeum sativum), alfalfa (Medicago sativa), grass mixture (red fescue-75%, long-term ryegrass - 20% Kentucky bluegrass - 10%), oilseed rape (Brassica napus biennis), resistant to growth in the contaminated soil with oil content of 15.8 g / kg 25.9 g / kg soil were used. Analysis of the population showed that the oil pollution reduces the number of bacteria in the rhizosphere and rhizoplane of plants and enhances the amount of spore-forming bacteria and saprotrophic micromycetes. It was shown that regardless of the plant, dominance of Pseudomonas and Bacillus genera bacteria was typical for the rhizosphere and rhizoplane of plants. The frequency of bacteria of these genera was more than 60%. Oil pollution changes the ratio of occurrence of various types of bacteria in the rhizosphere and rhizoplane of plants. Besides the Pseudomonas and Bacillus genera, in the presence of hydrocarbons in the root zone of plants dominant and most typical were the representatives of the Mycobacterium and Rhodococcus genera. Together the number was between 62% to 72%.

Keywords: Identification, micromycetes, pollution, root system.

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