Search results for: continuous time domain estimation

Authors: Kamila Tišlerová

Abstract:

This contribution aims to outline some topics around the process of introduction of compulsory electronic exchange of documents (so called e-Boxes) in public administration. The research was conducted in order to gauge the difference between the expectation of those using internal email and their experience in reality. Both qualitative and quantitative research is employed to lead also to an estimation of the willingness and readiness of government bodies, business units and citizens to adopt new technologies. At the same time the most potent barriers to successful e-communication through the e-Boxes are identified.

Keywords: E-Box, e-Government, electronic document exchange, digitalisation, public administration.

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Authors: János Levendovszky, András Oláh

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In this paper, novel statistical sampling based equalization techniques and CNN based detection are proposed to increase the spectral efficiency of multiuser communication systems over fading channels. Multiuser communication combined with selective fading can result in interferences which severely deteriorate the quality of service in wireless data transmission (e.g. CDMA in mobile communication). The paper introduces new equalization methods to combat interferences by minimizing the Bit Error Rate (BER) as a function of the equalizer coefficients. This provides higher performance than the traditional Minimum Mean Square Error equalization. Since the calculation of BER as a function of the equalizer coefficients is of exponential complexity, statistical sampling methods are proposed to approximate the gradient which yields fast equalization and superior performance to the traditional algorithms. Efficient estimation of the gradient is achieved by using stratified sampling and the Li-Silvester bounds. A simple mechanism is derived to identify the dominant samples in real-time, for the sake of efficient estimation. The equalizer weights are adapted recursively by minimizing the estimated BER. The near-optimal performance of the new algorithms is also demonstrated by extensive simulations. The paper has also developed a (Cellular Neural Network) CNN based approach to detection. In this case fast quadratic optimization has been carried out by t, whereas the task of equalizer is to ensure the required template structure (sparseness) for the CNN. The performance of the method has also been analyzed by simulations.

Keywords: Cellular Neural Network, channel equalization, communication over fading channels, multiuser communication, spectral efficiency, statistical sampling.

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Authors: G. Gradinaru, S. Olteanu

Abstract:

The quality improvements of the environmental elements could increase the recreational opportunities in a certain area (destination). The technique of the need for recreation focuses on choosing certain destinations for recreational purposes. The basic exchange taken into consideration is the one between the satisfaction gained after staying in that area and the value expressed in money and time allocated. The number of tourists in the respective area, the duration of staying and the money spent including transportation provide information on how individuals rank the place or certain aspects of the area (such as the quality of the environmental elements). For the statistical analysis of the environmental benefits offered by an area through the need of recreation technique, the following stages are suggested: - characterization of the reference area based on the statistical variables considered; - estimation of the environmental benefit through comparing the reference area with other similar areas (having the same environmental characteristics), from the perspective of the statistical variables considered. The model compared in recreation technique faced with a series of difficulties which refers to the reference area and correct transformation of time in money.

Keywords: Comparison in recreation technique, the quality of the environmental elements, statistical analysis model.

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Authors: Ali Taee Zade, Siamak Rasulzadeh, Reza Torkashvan

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Although Model Driven Architecture has taken successful steps toward model-based software development, this approach still faces complex situations and ambiguous questions while applying to real world software systems. One of these questions - which has taken the most interest and focus - is how model transforms between different abstraction levels, MDA proposes. In this paper, we propose an approach based on Story Driven Modeling and Aspect Oriented Programming to ease these transformations. Service Oriented Architecture is taken as the target model to test the proposed mechanism in a functional system. Service Oriented Architecture and Model Driven Architecture [1] are both considered as the frontiers of their own domain in the software world. Following components - which was the greatest step after object oriented - SOA is introduced, focusing on more integrated and automated software solutions. On the other hand - and from the designers' point of view - MDA is just initiating another evolution. MDA is considered as the next big step after UML in designing domain.

Keywords: SOA, MDA, SDM, Model Transformation, Middleware Transparency, Aspects and Jini.

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Authors: Sepehr Aslani, Homayoun Mahdavi-Nasab

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Automated motion detection and tracking is a challenging task in traffic surveillance. In this paper, a system is developed to gather useful information from stationary cameras for detecting moving objects in digital videos. The moving detection and tracking system is developed based on optical flow estimation together with application and combination of various relevant computer vision and image processing techniques to enhance the process. To remove noises, median filter is used and the unwanted objects are removed by applying thresholding algorithms in morphological operations. Also the object type restrictions are set using blob analysis. The results show that the proposed system successfully detects and tracks moving objects in urban videos.

Keywords: Optical flow estimation, moving object detection, tracking, morphological operation, blob analysis.

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Authors: Yeongyu Choi, Ju H. Park, S. M. Lee, Ho-Youl Jung

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In this paper, an improved method for estimating fundamental matrix is proposed. The method is applied effectively to monocular camera based moving object detection. The method consists of corner points detection, moving object’s motion estimation and fundamental matrix calculation. The corner points are obtained by using Harris corner detector, motions of moving objects is calculated from pyramidal Lucas-Kanade optical flow algorithm. Through epipolar geometry analysis using RANSAC, the fundamental matrix is calculated. In this method, we have improved the performances of moving object detection by using two threshold values that determine inlier or outlier. Through the simulations, we compare the performances with varying the two threshold values.

Keywords: Corner detection, optical flow, epipolar geometry, RANSAC.

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Authors: Masoud Nasri, Ali Gholami, Ali Najafi

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In recent years, most of the regions in the world are exposed to degradation and erosion caused by increasing population and over use of land resources. The understanding of the most important factors on soil erosion and sediment yield are the main keys for decision making and planning. In this study, the sediment yield and soil erosion were estimated and the priority of different soil erosion factors used in the MPSIAC method of soil erosion estimation is evaluated in AliAbad watershed in southwest of Isfahan Province, Iran. Different information layers of the parameters were created using a GIS technique. Then, a multivariate procedure was applied to estimate sediment yield and to find the most important factors of soil erosion in the model. The results showed that land use, geology, land and soil cover are the most important factors describing the soil erosion estimated by MPSIAC model.

Keywords: land degradation, Soil erosion, Sediment yield, Aliabad, GIS technique, Land use.

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Authors: S. Anbu, N. Jaya

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Nonlinearity is the inherent characteristics of all the industrial processes. The Classical control approach used for a generation often fails to show better results particularly for non-linear systems and in the systems, whose parameters changes over a period of time for a variety of reasons. Alternatively, adaptive control strategies provide very good performance. The Model Reference Adaptive Control based on Lyapunov stability analysis and classical PI control strategies are designed and evaluated for Continuous Stirred Tank Reactor, which shows appreciable dynamic nonlinear characteristics.

Keywords: Adaptive Control, CSTR, Lyapunov stability, MRAS, PID.

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Authors: Hyeon-Cheol Lee

Abstract:

The adaptive power control of Code Division Multiple Access (CDMA) communications using Remote Radio Head (RRH) between multiple Unmanned Aerial Vehicles (UAVs) with a link-budget based Signal-to-Interference Ratio (SIR) estimate is applied to four inner loop power control algorithms. It is concluded that Base Station (BS) can calculate not only UAV distance using linearity between speed and Consecutive Transmit-Power-Control Ratio (CTR) of Adaptive Step-size Closed Loop Power Control (ASCLPC), Consecutive TPC Ratio Step-size Closed Loop Power Control (CS-CLPC), Fixed Step-size Power Control (FSPC), but also UAV position with Received Signal Strength Indicator (RSSI) ratio of RRHs.

Keywords: speed estimation, adaptive power control, link-budget, SIR, multi-bit quantizer, RRH

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Authors: A. Ameur, B. Mokhtari, N. Essounbouli, L. Mokrani

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This paper presents a speed sensorless direct torque control scheme using space vector modulation (DTC-SVM) for permanent magnet synchronous motor (PMSM) drive based a Model Reference Adaptive System (MRAS) algorithm and stator resistance estimator. The MRAS is utilized to estimate speed and stator resistance and compensate the effects of parameter variation on stator resistance, which makes flux and torque estimation more accurate and insensitive to parameter variation. In other hand the use of SVM method reduces the torque ripple while achieving a good dynamic response. Simulation results are presented and show the effectiveness of the proposed method.

Keywords: MRAS, PMSM, SVM, DTC, Speed and Resistance estimation, Sensorless drive

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Authors: Ng Yee Luon, Mohd Zamri Yusoff, Norshah Hafeez Shuaib

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Meshing is the process of discretizing problem domain into many sub domains before the numerical calculation can be performed. One of the most popular meshes among many types of meshes is tetrahedral mesh, due to their flexibility to fit into almost any domain shape. In both 2D and 3D domains, triangular and tetrahedral meshes can be generated by using Delaunay triangulation. The quality of mesh is an important factor in performing any Computational Fluid Dynamics (CFD) simulations as the results is highly affected by the mesh quality. Many efforts had been done in order to improve the quality of the mesh. The paper describes a mesh generation routine which has been developed capable of generating high quality tetrahedral cells in arbitrary complex geometry. A few test cases in CFD problems are used for testing the mesh generator. The result of the mesh is compared with the one generated by a commercial software. The results show that no sliver exists for the meshes generated, and the overall quality is acceptable since the percentage of the bad tetrahedral is relatively small. The boundary recovery was also successfully done where all the missing faces are rebuilt.

Keywords: Mesh generation, tetrahedral, CFD, Delaunay.

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Authors: S. K. Tomar, R. Prasad, S. Panda, C. Ardil

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Reduction of Single Input Single Output (SISO) discrete systems into lower order model, using a conventional and an evolutionary technique is presented in this paper. In the conventional technique, the mixed advantages of Modified Cauer Form (MCF) and differentiation are used. In this method the original discrete system is, first, converted into equivalent continuous system by applying bilinear transformation. The denominator of the equivalent continuous system and its reciprocal are differentiated successively, the reduced denominator of the desired order is obtained by combining the differentiated polynomials. The numerator is obtained by matching the quotients of MCF. The reduced continuous system is converted back into discrete system using inverse bilinear transformation. In the evolutionary technique method, Particle Swarm Optimization (PSO) is employed to reduce the higher order model. PSO method is based on the minimization of the Integral Squared Error (ISE) between the transient responses of original higher order model and the reduced order model pertaining to a unit step input. Both the methods are illustrated through numerical example.

Keywords: Discrete System, Single Input Single Output (SISO), Bilinear Transformation, Reduced Order Model, Modified CauerForm, Polynomial Differentiation, Particle Swarm Optimization, Integral Squared Error.

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Authors: M. Brahim, I. Bahri, Y. Bernard

Abstract:

Traveling Wave Ultrasonic Motor (TWUM) is a compact, precise, and silent actuator generating high torque at low speed without gears. Moreover, the TWUM has a high holding torque without supply, which makes this motor as an attractive solution for holding position of robotic arms. However, their nonlinear dynamics, and the presence of load-dependent dead zones often limit their use. Those issues can be overcome in closed loop with effective and precise controllers. In this paper, robust H-infinity (H∞) and discrete time RST position controllers are presented. The H∞ controller is designed in continuous time with additional weighting filters to ensure the robustness in the case of uncertain motor model and external disturbances. Robust RST controller based on the pole placement method is also designed and compared to the H∞. Simulink model of TWUM is used to validate the stability and the robustness of the two proposed controllers.

Keywords: Piezoelectric motors, position control, H∞, RST, stability criteria, robustness.

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Authors: Kazuo Komatsu, Hitoshi Takata

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The objective of this study is to propose an observer design for nonlinear systems by using an augmented linear system derived by application of a formal linearization method. A given nonlinear differential equation is linearized by the formal linearization method which is based on Taylor expansion considering up to the higher order terms, and a measurement equation is transformed into an augmented linear one. To this augmented dimensional linear system, a linear estimation theory is applied and a nonlinear observer is derived. As an application of this method, an estimation problem of transient state of electric power systems is studied, and its numerical experiments indicate that this observer design shows remarkable performances for nonlinear systems.

Keywords: nonlinear system, augmented linear system, nonlinear observer, formal linearization, electric power system.

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Authors: GangHeok Kim, SungHoon Seo, JooSeok Song

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Stream Control Transmission Protocol (SCTP) has been proposed to provide reliable transport of real-time communications. Due to its attractive features, such as multi-streaming and multihoming, the SCTP is often expected to be an alternative protocol for TCP and UDP. In the original SCTP standard, the secondary path is mainly regarded as a redundancy. Recently, most of researches have focused on extending the SCTP to enable a host to send its packets to a destination over multiple paths simultaneously. In order to transfer packets concurrently over the multiple paths, the SCTP should be well designed to avoid unnecessary fast retransmission and the mis-estimation of congestion window size through the paths. Therefore, we propose an Enhanced Cooperative ACK SCTP (ECASCTP) to improve the path recovery efficiency of multi-homed host which is under concurrent multiple transfer mode. We evaluated the performance of our proposed scheme using ns-2 simulation in terms of cwnd variation, path recovery time, and goodput. Our scheme provides better performance in lossy and path asymmetric networks.

Keywords: SCTP, Concurrent Multiple Transfer, CooperativeSack, Dynamic ack policy

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Authors: Ibrahim Shaker, Amr El Hossany, Moustafa Osman, Mohamed El Raey

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This paper will explore integration model between GIS–SCADA system and enclosure quantification model to approach the impact of failure-safe event. There are real demands to identify spatial objects and improve control system performance. Nevertheless, the employed methodology is predicting electro-mechanic operations and corresponding time to environmental incident variations. Open processing, as object systems technology, is presented for integration enclosure database with minimal memory size and computation time via connectivity drivers such as ODBC:JDBC during main stages of GIS–SCADA connection. The function of Geographic Information System is manipulating power distribution in contrast to developing issues. In other ward, GIS-SCADA systems integration will require numerical objects of process to enable system model calibration and estimation demands, determine of past events for analysis and prediction of emergency situations for response training.

Keywords: Air dispersion model, integration power system, SCADA systems, GIS system, environmental management.

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Authors: E. B. Jo, J. H. Lee, J. Y. Park, S. M. Kim

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In this study, we present an advanced detection technique for mass type breast cancer based on texture information of organs. The proposed method detects the cancer areas in three stages. In the first stage, the midpoints of mass area are determined based on AHE (Adaptive Histogram Equalization). In the second stage, we set the threshold coefficient of homogeneity by using MLE (Maximum Likelihood Estimation) to compute the uniformity of texture. Finally, mass type cancer tissues are extracted from the original image. As a result, it was observed that the proposed method shows an improved detection performance on dense breast tissues of Korean women compared with the existing methods. It is expected that the proposed method may provide additional diagnostic information for detection of mass-type breast cancer.

Keywords: Mass Type Breast Cancer, Mammography, Maximum Likelihood Estimation (MLE), Ranklets, SVM

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Authors: Hafizullah A. Hashim, Aniza. A

Abstract:

The Spiral development model has been used successfully in many commercial systems and in a good number of defense systems. This is due to the fact that cost-effective incremental commitment of funds, via an analogy of the spiral model to stud poker and also can be used to develop hardware or integrate software, hardware, and systems. To support adaptive, semantic collaboration between domain experts and knowledge engineers, a new knowledge engineering process, called Spiral_OWL is proposed. This model is based on the idea of iterative refinement, annotation and structuring of knowledge base. The Spiral_OWL model is generated base on spiral model and knowledge engineering methodology. A central paradigm for Spiral_OWL model is the concentration on risk-driven determination of knowledge engineering process. The collaboration aspect comes into play during knowledge acquisition and knowledge validation phase. Design rationales for the Spiral_OWL model are to be easy-to-implement, well-organized, and iterative development cycle as an expanding spiral.

Keywords: Domain Expert, Knowledge Base, Ontology, Software Process.

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Authors: Justinian Anatory, Nelson Theethayi

Abstract:

The paper compares different channel models used for modeling Broadband Power-Line Communication (BPLC) system. The models compared are Zimmermann and Dostert, Philipps, Anatory et al and Anatory et al generalized Transmission Line (TL) model. The validity of each model was compared in time domain with ATP-EMTP software which uses transmission line approach. It is found that for a power-line network with minimum number of branches all the models give similar signal/pulse time responses compared with ATP-EMTP software; however, Zimmermann and Dostert model indicates the same amplitude but different time delay. It is observed that when the numbers of branches are increased only generalized TL theory approach results are comparable with ATPEMTP results. Also the Multi-Carrier Spread Spectrum (MC-SS) system was applied to check the implication of such behavior on the modulation schemes. It is observed that using Philipps on the underground cable can predict the performance up to 25dB better than other channel models which can misread the actual performance of the system. Also modified Zimmermann and Dostert under multipath can predict a better performance of about 5dB better than the actual predicted by Generalized TL theory. It is therefore suggested for a realistic BPLC system design and analyses the model based on generalized TL theory be used.

Keywords: Broadband Power line Channel Models, loadimpedance, Branched network.

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Authors: Muna Tabuni

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The paper contains an investigation on basic problems about the zeros of analytic theta functions. A brief introduction to analytic representation of finite quantum systems is given. The zeros of this function and there evolution time are discussed. Two open problems are introduced. The first problem discusses the cases when the zeros follow the same path. As the basis change the quantum state |f transforms into different quantum state. The second problem is to define a map between two toruses where the domain and the range of this map are the analytic functions on toruses.

Keywords: open problems, constraint, change of basis.

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Authors: Nooshin Salari, Viliam Makis

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In this paper, we propose a condition-based maintenance policy for multi-unit systems considering the existence of economic dependency among units. We consider a system composed of N identical units, where each unit deteriorates independently. Deterioration process of each unit is modeled as a three-state continuous time homogeneous Markov chain with two working states and a failure state. The average production rate of units varies in different working states and demand rate of the system is constant. Units are inspected at equidistant time epochs, and decision regarding performing maintenance is determined by the number of units in the failure state. If the total number of units in the failure state exceeds a critical level, maintenance is initiated, where units in failed state are replaced correctively and deteriorated state units are maintained preventively. Our objective is to determine the optimal number of failed units to initiate maintenance minimizing the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A numerical example is developed to demonstrate the proposed policy and the comparison with the corrective maintenance policy is presented.

Keywords: Reliability, production, maintenance optimization, Semi-Markov Decision Process.

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Authors: Triloksingh G. Arora, Mohan V. Aware, Dhananjay R. Tutakne

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Thyristor based firing angle controlled voltage regulators are extensively used for speed control of single phase induction motors. This leads to power saving but the applied voltage and current waveforms become non-sinusoidal. These non-sinusoidal waveforms increase voltage and thermal stresses which result into accelerated insulation aging, thus reducing the motor life. Life models that allow predicting the capability of insulation under such multi-stress situations tend to be very complex and somewhat impractical. This paper presents the fuzzy logic application to investigate the synergic effect of voltage and thermal stresses on intrinsic aging of induction motor insulation. A fuzzy expert system is developed to estimate the life of induction motor insulation under multiple stresses. Three insulation degradation parameters, viz. peak modification factor, wave shape modification factor and thermal loss are experimentally obtained for different firing angles. Fuzzy expert system consists of fuzzyfication of the insulation degradation parameters, algorithms based on inverse power law to estimate the life and defuzzyficaton process to output the life. An electro-thermal life model is developed from the results of fuzzy expert system. This fuzzy logic based electro-thermal life model can be used for life estimation of induction motors operated with non-sinusoidal voltage and current waveforms.

Keywords: Aging, Dielectric losses, Insulation and Life Estimation.

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Authors: S. Gharbi, S. Labidi, M. Mars, M. Chelli, F. Ladeb

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The purpose of this study is to reduce radiation dose for chest CT examination by including Tube Current Modulation (TCM) to a standard CT protocol. A scan of an anthropomorphic male Alderson phantom was performed on a 128-slice scanner. The estimation of effective dose (ED) in both scans with and without mAs modulation was done via multiplication of Dose Length Product (DLP) to a conversion factor. Results were compared to those measured with a CT-Expo software. The size specific dose estimation (SSDE) values were obtained by multiplication of the volume CT dose index (CTDIvol) with a conversion size factor related to the phantom’s effective diameter. Objective assessment of image quality was performed with Signal to Noise Ratio (SNR) measurements in phantom. SPSS software was used for data analysis. Results showed including CARE Dose 4D; ED was lowered by 48.35% and 51.51% using DLP and CT-expo, respectively. In addition, ED ranges between 7.01 mSv and 6.6 mSv in case of standard protocol, while it ranges between 3.62 mSv and 3.2 mSv with TCM. Similar results are found for SSDE; dose was higher without TCM of 16.25 mGy and was lower by 48.8% including TCM. The SNR values calculated were significantly different (p=0.03<0.05). The highest one is measured on images acquired with TCM and reconstructed with Filtered back projection (FBP). In conclusion, this study proves the potential of TCM technique in SSDE and ED reduction and in conserving image quality with high diagnostic reference level for thoracic CT examinations.

Keywords: Anthropomorphic phantom, computed tomography, CT-expo, radiation dose.

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Authors: Jyothi Digge, B. U. Rindhe, S. K. Narayankhedkar

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A compact 1x3 power splitter based on Photonic Crystal Waveguides (PCW) with flexible power splitting ratio is presented in this paper. Multimode interference coupler (MMI) is integrated with PCW. The device size reduction compared with the conventional MMI power splitter is attributed to the large dispersion of the PCW. Band Solve tool is used to calculate the band structure of PCW. Finite Difference Time Domain (FDTD) method is adopted to simulate the relevant structure at 1550nm wavelength. The device is polarization insensitive and allows the control of output (o/p) powers within certain percentage points for both polarizations.

Keywords: Dispersion, MMI Coupler, Photonic Bandgap, Power Splitter.

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Authors: Yanchao Wang, Rajshekhar Sunderraman

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This paper presents an algebraic approach to optimize queries in domain-specific database management system for protein structure data. The approach involves the introduction of several protein structure specific algebraic operators to query the complex data stored in an object-oriented database system. The Protein Algebra provides an extensible set of high-level Genomic Data Types and Protein Data Types along with a comprehensive collection of appropriate genomic and protein functions. The paper also presents a query translator that converts high-level query specifications in algebra into low-level query specifications in Protein-QL, a query language designed to query protein structure data. The query transformation process uses a Protein Ontology that serves the purpose of a dictionary.

Keywords: Domain-Specific Data Management, Protein Algebra, Protein Ontology, Protein Structure Data.

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Authors: Thanida Sujarittham, Narumon Emarat, Jintawat Tanamatayarat, Kwan Arayathanitkul, Suchai Nopparatjamjomras

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Electric field is an important fundamental concept in electrostatics. In high-school, generally Thai students have already learned about definition of electric field, electric field due to a point charge, and superposition of electric fields due to multiple-point charges. Those are the prerequisite basic knowledge students holding before entrancing universities. In the first-year university level, students will be quickly revised those basic knowledge and will be then introduced to a more complicated topic—electric field due to continuous charged distributions. We initially found that our freshman students, who were from the Faculty of Science and enrolled in the introductory physic course (SCPY 158), often seriously struggled with the basic physics concepts—superposition of electric fields and inverse square law and mathematics being relevant to this topic. These also then resulted on students’ understanding of advanced topics within the course such as Gauss's law, electric potential difference, and capacitance. Therefore, it is very important to determine students' understanding of electric field due to continuous charged distributions. The open-ended question about sketching net electric field vectors from a uniformly charged insulating rod was administered to 260 freshman science students as pre- and post-tests. All of their responses were analyzed and classified into five levels of understandings. To get deep understanding of each level, 30 students were interviewed toward their individual responses. The pre-test result found was that about 90% of students had incorrect understanding. Even after completing the lectures, there were only 26.5% of them could provide correct responses. Up to 50% had confusions and irrelevant ideas. The result implies that teaching methods in Thai high schools may be problematic. In addition for our benefit, these students’ alternative conceptions identified could be used as a guideline for developing the instructional method currently used in the course especially for teaching electrostatics.

Keywords: Electrostatics Electric field due to continuous charged distributions, inverse square law, superposition principle, levels of student understandings.

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Authors: Carsten Röcker

Abstract:

This paper provides an introduction into the evolution of information and communication technology and illustrates its usage in the work domain. The paper is sub-divided into two parts. The first part gives an overview over the different phases of information processing in the work domain. It starts by charting the past and present usage of computers in work environments and shows current technological trends, which are likely to influence future business applications. The second part starts by briefly describing, how the usage of computers changed business processes in the past, and presents first Ambient Intelligence applications based on identification and localization information, which are already used in the production and retail sector. Based on current systems and prototype applications, the paper gives an outlook of how Ambient Intelligence technologies could change business processes in the future.

Keywords: Ambient Intelligence, Ubiquitous Computing, Business Applications, Radio Frequency Identification (RFID).

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Authors: Andy Handouyahia, Tony Haddad, Frank Eaton

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Recent quasi-experimental evaluation of the Canadian Active Labour Market Policies (ALMP) by Human Resources and Skills Development Canada (HRSDC) has provided an opportunity to examine alternative methods to estimating the incremental effects of Employment Benefits and Support Measures (EBSMs) on program participants. The focus of this paper is to assess the efficiency and robustness of inverse probability weighting (IPW) relative to kernel matching (KM) in the estimation of program effects. To accomplish this objective, the authors compare pairs of 1,080 estimates, along with their associated standard errors, to assess which type of estimate is generally more efficient and robust. In the interest of practicality, the authorsalso document the computationaltime it took to produce the IPW and KM estimates, respectively.

Keywords: Treatment effect, causal inference, observational studies, Propensity score based matching, Kernel Matching, Inverse Probability Weighting, Estimation methods for incremental effect.

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Authors: A. A. James, A. O. Adesanya, M. R. Odekunle, D. G. Yakubu

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This paper examines the development of one step, five hybrid point method for the solution of first order initial value problems. We adopted the method of collocation and interpolation of power series approximate solution to generate a continuous linear multistep method. The continuous linear multistep method was evaluated at selected grid points to give the discrete linear multistep method. The method was implemented using a constant order predictor of order seven over an overlapping interval. The basic properties of the derived corrector was investigated and found to be zero stable, consistent and convergent. The region of absolute stability was also investigated. The method was tested on some numerical experiments and found to compete favorably with the existing methods.

Keywords: Interpolation, Approximate Solution, Collocation, Differential system, Half step, Converges, Block method, Efficiency.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

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Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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