Search results for: indicator estimation

Authors: Linyu Wang, Jiahui Ma, Jianhong Xiang, Hanyu Jiang

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For the pilot design of the sparse channel estimation model in Multiple Input Multiple Output Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems, the observation matrix constructed according to the matrix cross-correlation criterion, total correlation criterion and other optimization criteria are not optimal, resulting in inaccurate channel estimation and high bit error rate at the receiver. This paper proposes a pilot design method combining high-power sum and high-power variance criteria, which can more accurately estimate the channel. First, the pilot insertion position is designed according to the high-power variance criterion under the condition of equal power. Then, according to the high power sum criterion, the pilot power allocation is converted into a cone programming problem, and the power allocation is carried out. Finally, the optimal pilot is determined by calculating the weighted sum of the high power sum and the high power variance. Compared with the traditional pilot frequency, under the same conditions, the constructed MIMO-OFDM system uses the optimal pilot frequency for channel estimation, and the communication bit error rate performance obtains a gain of 6~7dB.

Keywords: MIMO-OFDM, pilot optimization, compressed sensing, channel estimation

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Authors: Amira Mabrouk, Chokri Abdennadher

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The reduction of road congestion which is inherent to the use of vehicles is an obvious priority to public authority. Therefore, assessing the willingness to pay of an individual in order to save trip-time is akin to estimating the change in price which was the result of setting up a new transport policy to increase the networks fluidity and improving the level of social welfare. This study holds an innovative perspective. In fact, it initiates an economic calculation that has the objective of giving an estimation of the monetized time value during the trips made in Sfax. This research is founded on a double-objective approach. The aim of this study is to i) give an estimation of the monetized value of time; an hour dedicated to trips, ii) determine whether or not the consumer considers the environmental variables to be significant, iii) analyze the impact of applying a public management of the congestion via imposing taxation of city tolls on urban dwellers. This article is built upon a rich field survey led in the city of Sfax. With the use of the contingent valuation method, we analyze the “declared time preferences” of 450 drivers during rush hours. Based on the fond consideration of attributed bias of the applied method, we bring to light the delicacy of this approach with regards to the revelation mode and the interrogative techniques by following the NOAA panel recommendations bearing the exception of the valorization point and other similar studies about the estimation of transportation externality.

Keywords: willingness to pay, contingent valuation, time value, city toll

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Authors: Khaled M. EL-Naggar

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Synchronizing and damping torque coefficients of a synchronous machine can give a quite clear picture for machine behavior during transients. These coefficients are used as a power system transient stability measurement. In this paper, a crow search optimization algorithm is presented and implemented to study the power system stability during transients. The algorithm makes use of the machine responses to perform the stability study in time domain. The problem is formulated as a dynamic estimation problem. An objective function that minimizes the error square in the estimated coefficients is designed. The method is tested using practical system with different study cases. Results are reported and a thorough discussion is presented. The study illustrates that the proposed method can estimate the stability coefficients for the critical stable cases where other methods may fail. The tests proved that the proposed tool is an accurate and reliable tool for estimating the machine coefficients for assessment of power system stability.

Keywords: optimization, estimation, synchronous, machine, crow search

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Authors: M. Cizmesija, N. Erjavec, V. Bahovec

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While the European Union (EU) harmonized methodology is a benchmark of worldwide used business survey (BS) methodology, the choice of variables that are components of the confidence indicators, as the leading indicators, is not strictly determined and unique. Therefore, the aim of this paper is to investigate and to quantify the relationship between all business survey variables in manufacturing industry and industrial production as a reference macroeconomic series in Croatia. The assumption is that there are variables in the business survey, that are not components of Industrial Confidence Indicator (ICI) and which can accurately (and sometimes better then ICI) predict changes in Croatian industrial production. Empirical analyses are conducted using quarterly data of BS variables in manufacturing industry and Croatian industrial production over the period from the first quarter 2005 to the first quarter 2013. Research results confirmed the assumption: three BS variables which is not components of ICI (competitive position, demand and liquidity) are the best leading indicator then ICI, in forecasting changes in Croatian industrial production instantaneously, with one, two or three quarter ahead.

Keywords: balance, business survey, confidence indicators, industrial production, forecasting

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Authors: M. Peña Aguilar Juan, Valencia Luis, Pastrana Alberto, Nava Estefany, A. Martinez, M. Vivanco, A. Castañeda

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This paper seeks to compare the innovation of Mexico from an economic and human perspective, with the seven most innovative countries according to the Global Innovation Index 2013, done by the World Intellectual Property Organization (WIPO). The above analysis suggests nine dimensions: Expenditure on R & D, intellectual property, appropriate environment to conduct business, economic stability, and triple helix for R & D, ICT Infrastructure, education, human resources and quality of life. Each dimension is represented by an indicator which is later used to construct a radial graph that compares the innovative capacity of the countries analysed. As a result, it is proposed a new indicator of innovation called The Area of Innovation. Observations are made from the results, and finally as a conclusion, those items or dimensions in which Mexico suffers lag in innovation are identify.

Keywords: dimension, measure, innovation level, economy, radar chart

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Authors: Aliya K. Salahova

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Scientific thinking is a fundamental cognitive skill that plays a crucial role in preparing young minds for an increasingly complex world. This study explores the connection between scientific thinking and the ability to ask questions in children aged 5-9. The research aims to identify and assess how questioning ability serves as an indicator of scientific thinking development in this age group. A longitudinal investigation was conducted over a span of 240 weeks, involving 72 children from diverse backgrounds. The participants were divided into an experimental group, engaging in weekly STEM activities, and a control group with no STEM involvement. The development of scientific thinking was evaluated through a comprehensive assessment of questioning skills, hypothesis formulation, logical reasoning, and problem-solving abilities. The findings reveal a significant correlation between the ability to ask questions and the level of scientific thinking in children aged 5-9. Participants in the experimental group exhibited a remarkable improvement in their questioning ability, which positively influenced their scientific thinking growth. In contrast, the control group, devoid of STEM activities, showed minimal progress in questioning skills and subsequent scientific thinking development. This study highlights the pivotal role of questioning ability as a key indicator of scientific thinking in young children. The results provide valuable insights for educators and researchers, emphasizing the importance of fostering and nurturing questioning skills to enhance scientific thinking capabilities from an early age. The implications of these findings are crucial for designing effective educational interventions to promote scientific curiosity and critical thinking in the next generation of scientific minds.

Keywords: scientific thinking, education, STEM, intervention, psychology, pedagogy, collaborative learning, longitudinal study

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Authors: Malika Fekih, Abdenour Bourabaa, Rafika Hariti, Mohamed Saighi

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In Algeria the global solar radiation and its components is not available for all locations due to which there is a requirement of using different models for the estimation of global solar radiation that use climatological parameters of the locations. Empirical constants for these models have been estimated and the results obtained have been tested statistically. The results show encouraging agreement between estimated and measured values.

Keywords: global solar radiation, empirical model, semi arid areas, climatological parameters

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Authors: Desta Brhanu Gebrehiwot

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The study aims to investigate the impact of land tenure arrangements on fertilizer use per hectare in Northern Ethiopia. Household and Plot level data are used for analysis. Land tenure contracts such as sharecropping and fixed rent arrangements have endogeneity. Different unobservable characteristics may affect renting-out decisions. Thus, the appropriate method of analysis was the instrumental variable estimation technic. Therefore, the family of instrumental variable estimation methods two-stage least-squares regression (2SLS, the generalized method of moments (GMM), Limited information maximum likelihood (LIML), and instrumental variable Tobit (IV-Tobit) was used. Besides, a method to handle a binary endogenous variable is applied, which uses a two-step estimation. In the first step probit model includes instruments, and in the second step, maximum likelihood estimation (MLE) (“etregress” command in Stata 14) was used. There was lower fertilizer use per hectare on sharecropped and fixed rented plots relative to owner-operated. The result supports the Marshallian inefficiency principle in sharecropping. The difference in fertilizer use per hectare could be explained by a lack of incentivized detailed contract forms, such as giving more proportion of the output to the tenant under sharecropping contracts, which motivates to use of more fertilizer in rented plots to maximize the production because most sharecropping arrangements share output equally between tenants and landlords.

Keywords: tenure-contracts, endogeneity, plot-level data, Ethiopia, fertilizer

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Authors: F. Esfandyari Darabad, Z. Samadi

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The volume of runoff caused by rainfall in the river basin has enticed the researchers in the fields of the water management resources. In this study, first of the hydrological data such as the rainfall and discharge of the Khiyav river basin of Meshkin city in the northwest of Iran collected and then the process of analyzing and reconstructing has been completed. The soil conservation service (scs) has developed a method for calculating the runoff, in which is based on the curve number specification (CN). This research implemented the following model in the Khiyav river basin of Meshkin city by the GIS techniques and concluded the following fact in which represents the usage of weight model in calculating the curve numbers that provides the possibility for the all efficient factors which is contributing to the runoff creation such as; the geometric characteristics of the basin, the basin soil characteristics, vegetation, geology, climate and human factors to be considered, so an accurate estimation of runoff from precipitation to be achieved as the result. The findings also exposed the accident-prone areas in the output of the Khiyav river basin so it was revealed that the Khiyav river basin embodies a high potential for the flood creation.

Keywords: curve number, khiyav river basin, runoff estimation, SCS

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Authors: Redvan Ghasemlounia, Elham Ansari, Hikmet Kerem Cigizoglu

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Hydrological modeling in arid and semi-arid regions is very important. Iran has many regions with these climate conditions such as Chaharmahal and Bakhtiari province that needs lots of attention with an appropriate management. Forecasting of hydrological parameters and estimation of hydrological events of catchments, provide important information that used for design, management and operation of water resources such as river systems, and dams, widely. Discharge in rivers is one of these parameters. This study presents the application and comparison of some estimation methods such as Feed-Forward Back Propagation Neural Network (FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) to predict the daily flow discharge of the Soolegan River, located at Chaharmahal and Bakhtiari province, in Iran. In this study, Soolegan, station was considered. This Station is located in Soolegan River at 51° 14՜ Latitude 31° 38՜ longitude at North Karoon basin. The Soolegan station is 2086 meters higher than sea level. The data used in this study are daily discharge and daily precipitation of Soolegan station. Feed Forward Back Propagation Neural Network(FFBPNN), Multi Linear Regression (MLR), Gene Expression Programming (GEP) and Bayesian Network (BN) models were developed using the same input parameters for Soolegan's daily discharge estimation. The results of estimation models were compared with observed discharge values to evaluate performance of the developed models. Results of all methods were compared and shown in tables and charts.

Keywords: ANN, multi linear regression, Bayesian network, forecasting, discharge, gene expression programming

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Authors: Arcady Ponosov

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A novel mathematical approach is suggested, which facilitates a compressed representation and efficient validation of parameter-rich ordinary differential equation models describing the dynamics of complex, especially biology-related, systems and which is based on identification of the system's latent variables. In particular, an efficient parameter estimation method for the compressed non-linear dynamical systems is developed. The method is applied to the so-called 'power-law systems' being non-linear differential equations typically used in Biochemical System Theory.

Keywords: generalized law of mass action, metamodels, principal components, synergetic systems

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Authors: Balaji Sankar, Sadanand Kulkarni

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Compliant foil gas lubricated bearings are used for the support of light loads in the order of few kilograms at high speeds, in the order of 50,000 RPM. The stiffness of the foil bearings depends both on the stiffness of the compliant foil and on the lubricating gas film. The stiffness of the bearings plays a crucial role in the stable operation of the supported rotor over a range of speeds. This paper describes a numerical approach to estimate the stiffness of the bearings using pseudo spectral scheme. Methodology to obtain the stiffness of the foil bearing as a function of weight of the shaft is given and the results are presented.

Keywords: foil bearing, simulation, numerical, stiffness estimation

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Authors: Marcos Valdez Alexander Junior, Igor Aguilar-Alonso

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Malnutrition is the root of different diseases that universally affect everyone, diseases such as obesity and malnutrition. The objective of this research is to predict the calories of the food to be eaten, developing a smart mobile application to show the user if a meal is balanced. Due to the large percentage of obesity and malnutrition in Peru, the present work is carried out. The development of the intelligent application is proposed with a three-layer architecture, and for the prediction of the nutritional value of the food, the use of pre-trained models based on convolutional neural networks is proposed.

Keywords: volume estimation, calorie estimation, artificial vision, food nutrition

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Authors: Seyedeh Belin Tavakoly Sany, H. Rosli, R. Majid, S. Aishah

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In this study, water monitoring was performed from Nov. 2012 to Oct. 2013 to assess water quality and evaluate the spatial and temporal distribution of physicochemical and biological variables in water. Water samples were collected from 10 coastal water stations of West Port. In the case of water-quality assessment, multi-metric indices and operational indicators have been proposed to classify the trophic status at different stations. The trophic level of West Port coastal water ranges from eutrophic to hypertrophic. Chl-a concentration was used to estimate the biological response of phytoplankton biomass and indicated eutrophic conditions in West Port and mesotrophic conditions at the control site. During the study period, no eutrophication events or secondary symptoms occurred, which may be related to hydrodynamic turbulence and water exchange, which prevent the development of eutrophic conditions in the West Port.

Keywords: water quality, multi-metric indices, operational indicator, Malaysia, West Port

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Authors: Chulsang Yoo, Gildo Kim

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Dual polarization radar provides comprehensive information about rainfall by measuring multiple parameters. In Korea, for the rainfall estimation, JPOLE and CSU-HIDRO algorithms are generally used. This study evaluated the local applicability of JPOLE and CSU-HIDRO algorithms in Korea by using the observed rainfall data collected on August, 2014 by the Biseulsan dual polarization radar data and KMA AWS. A total of 11,372 pairs of radar-ground rain rate data were classified according to thresholds of synthetic algorithms into suitable and unsuitable data. Then, evaluation criteria were derived by comparing radar rain rate and ground rain rate, respectively, for entire, suitable, unsuitable data. The results are as follows: (1) The radar rain rate equation including KDP, was found better in the rainfall estimation than the other equations for both JPOLE and CSU-HIDRO algorithms. The thresholds were found to be adequately applied for both algorithms including specific differential phase. (2) The radar rain rate equation including horizontal reflectivity and differential reflectivity were found poor compared to the others. The result was not improved even when only the suitable data were applied. Acknowledgments: This work was supported by the Basic Science Research Program through the National Research Foundation of Korea, funded by the Ministry of Education (NRF-2013R1A1A2011012).

Keywords: CSU-HIDRO algorithm, dual polarization radar, JPOLE algorithm, radar rainfall estimation algorithm

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Authors: R. Niranchana, K. Meena Alias Jeyanthi

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As a result of the present climate change dilemma, the energy balancing strategy is to construct a sustainable environment has become a top concern for researchers worldwide. The environment itself has always been a solution from the earliest days of human evolution. Carbon capture begins with its accurate estimation and monitoring credit inventories, and its efficient use. Sustainable urban planning with deliverables of re-use energy models might benefit from assessment methods like biomass carbon credit ranking. The term "biomass energy" refers to the various ways in which living organisms can potentially be converted into a source of energy. The approaches that can be applied to biomass and an algorithm for evaluating carbon credits are presented in this paper. The micro-climate evaluation using Computational Fluid dynamics was carried out across the location (1 km x1 km) at Dindigul, India (10°24'58.68" North, 77°54.1.80 East). Sustainable Urban design must be carried out considering environmental and physiological convection, conduction, radiation and evaporative heat exchange due to proceeding solar access and wind intensities.

Keywords: biomass, climate assessment, urban planning, multi-regression, carbon estimation algorithm

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Authors: Nada Slimane, Foued Theljani, Faouzi Bouani

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The paper addresses the problem of fault diagnosis for systems operating in several modes (normal or faulty) based on states assessment. We use, for this purpose, a methodology consisting of three main processes: 1) sequential data clustering, 2) linear model regression and 3) state filtering. Typically, Kalman Filter (KF) is an algorithm that provides estimation of unknown states using a sequence of I/O measurements. Inevitably, although it is an efficient technique for state estimation, it presents two main weaknesses. First, it merely predicts states without being able to isolate/classify them according to their different operating modes, whether normal or faulty modes. To deal with this dilemma, the KF is endowed with an extra clustering step based fully on sequential version of the k-means algorithm. Second, to provide state estimation, KF requires state space models, which can be unknown. A linear regularized regression is used to identify the required models. To prove its effectiveness, the proposed approach is assessed on a simulated benchmark.

Keywords: clustering, diagnosis, Kalman Filtering, k-means, regularized regression

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Authors: Mahdy ‎Esmailian, Mahdi ‎Doostparast, Ahmad ‎Parsian

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‎In this article‎, ‎sequential order statistics (SOS) censoring type II samples coming from the generalized Pareto distribution are considered‎. ‎Maximum likelihood (ML) estimators of the unknown parameters are derived on the basis of the available multiple SOS data‎. ‎Necessary conditions for existence and uniqueness of the derived ML estimates are given‎. Due to complexity in the proposed likelihood function‎, ‎a useful re-parametrization is suggested‎. ‎For illustrative purposes‎, ‎a Monte Carlo simulation study is conducted and an illustrative example is analysed‎.

Keywords: bayesian estimation‎, generalized pareto distribution‎, ‎maximum likelihood estimation‎, sequential order statistics

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Authors: Hanna Lu, Sandra S. M. Chan, Linda C. W. Lam

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Objectives: Intra-individual variability (IIV) has been considered as a biomarker of healthy ageing. However, the composite role of IIV in attention, as an impending indicator for neurocognitive disorders warrants further exploration. This study aims to investigate the IIV, as well as their relationships with attention network functions in adults with neurocognitive disorders (NCD). Methods: 36adults with NCD due to Alzheimer’s disease(NCD-AD), 31adults with NCD due to vascular disease (NCD-vascular), and 137 healthy controls were recruited. Intraindividual standard deviations (iSD) and intraindividual coefficient of variation of reaction time (ICV-RT) were used to evaluate the IIV. Results: NCD groups showed greater IIV (iSD: F= 11.803, p < 0.001; ICV-RT:F= 9.07, p < 0.001). In ROC analyses, the indices of IIV could differentiateNCD-AD (iSD: AUC value = 0.687, p= 0.001; ICV-RT: AUC value = 0.677, p= 0.001) and NCD-vascular (iSD: AUC value = 0.631, p= 0.023;ICV-RT: AUC value = 0.615, p= 0.045) from healthy controls. Moreover, the processing speed could distinguish NCD-AD from NCD-vascular (AUC value = 0.647, p= 0.040). Discussion: Intra-individual variability in attention provides a stable measure of cognitive performance, and seems to help distinguish the senior adults with different cognitive status.

Keywords: intra-individual variability, attention network, neurocognitive disorders, ageing

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Authors: E. Younsi, H. Andriamboavonjy, A. David, S. Dokou, B. Lemrabet

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Software and time optimization are very important factors in financial markets, which are competitive fields, and emergence of new computer tools further stresses the challenge. In this context, any improvement of technical indicators which generate a buy or sell signal is a major issue. Thus, many tools have been created to make them more effective. This worry about efficiency has been leading in present paper to seek best (and most innovative) way giving largest improvement in these indicators. The approach consists in attaching a signature to frequent market configurations by application of frequent patterns extraction method which is here most appropriate to optimize investment strategies. The goal of proposed trading algorithm is to find most accurate signatures using back testing procedure applied to technical indicators for improving their performance. The problem is then to determine the signatures which, combined with an indicator, outperform this indicator alone. To do this, the FP-Tree algorithm has been preferred, as it appears to be the most efficient algorithm to perform this task.

Keywords: quantitative analysis, back-testing, computational models, apriori algorithm, pattern recognition, data mining, FP-tree

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Authors: Sherly M. A., Varsha Vijaykumar, Subhankar Karmakar, Terence Chan, Christian Rau

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This study aims at proposing an indicator-based framework for assessing social vulnerability of any coastal megacity to floods. The final set of indicators of social vulnerability are chosen from a set of feasible and available indicators which are prepared using a Geographic Information System (GIS) framework on a smaller scale considering 1-km grid cell to provide an insight into the spatial variability of vulnerability. The optimal weight for each individual indicator is assigned using data envelopment analysis (DEA) as it avoids subjective weights and improves the confidence on the results obtained. In order to de-correlate and reduce the dimension of multivariate data, principal component analysis (PCA) has been applied. The proposed methodology is demonstrated on twenty four wards of Mumbai under the jurisdiction of Municipal Corporation of Greater Mumbai (MCGM). This framework of vulnerability assessment is not limited to the present study area, and may be applied to other urban damage centers.

Keywords: urban floods, vulnerability, data envelopment analysis, principal component analysis

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Authors: Balimu Mwiya, Mundia Muya, Chabota Kaliba, Peter Mukalula

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Factors affecting construction unit cost vary depending on a country’s political, economic, social and technological inclinations. Factors affecting construction costs have been studied from various perspectives. Analysis of cost factors requires an appreciation of a country’s practices. Identified cost factors provide an indication of a country’s construction economic strata. The purpose of this paper is to identify the essential factors that affect unit cost estimation and their breakdown using artificial neural networks. Twenty-five (25) identified cost factors in road construction were subjected to a questionnaire survey and employing SPSS factor analysis the factors were reduced to eight. The 8 factors were analysed using the neural network (NN) to determine the proportionate breakdown of the cost factors in a given construction unit rate. NN predicted that political environment accounted 44% of the unit rate followed by contractor capacity at 22% and financial delays, project feasibility, overhead and profit each at 11%. Project location, material availability and corruption perception index had minimal impact on the unit cost from the training data provided. Quantified cost factors can be incorporated in unit cost estimation models (UCEM) to produce more accurate estimates. This can create improvements in the cost estimation of infrastructure projects and establish a benchmark standard to assist the process of alignment of work practises and training of new staff, permitting the on-going development of best practises in cost estimation to become more effective.

Keywords: construction cost factors, neural networks, roadworks, Zambian construction industry

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Authors: Shalini Rankawat, Mansi Rankawat, Rahul Dubey, Mazad Zaveri

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Physiological signals such as electrocardiogram (ECG) and arterial blood pressure (ABP) in the intensive care unit (ICU) are often seriously corrupted by noise, artifacts, and missing data, which lead to errors in the estimation of heart rate (HR) and incidences of false alarm from ICU monitors. Clinical support in ICU requires most reliable heart rate estimation. Cardiac activity, because of its relatively high electrical energy, may introduce artifacts in Electroencephalogram (EEG), Electrooculogram (EOG), and Electromyogram (EMG) recordings. This paper presents a robust heart rate estimation method by detection of R-peaks of ECG artifacts in EEG, EMG & EOG signals, using energy-based function and a novel Signal Quality Index (SQI) assessment technique. SQIs of physiological signals (EEG, EMG, & EOG) were obtained by correlation of nonlinear energy operator (teager energy) of these signals with either ECG or ABP signal. HR is estimated from ECG, ABP, EEG, EMG, and EOG signals from separate Kalman filter based upon individual SQIs. Data fusion of each HR estimate was then performed by weighing each estimate by the Kalman filters’ SQI modified innovations. The fused signal HR estimate is more accurate and robust than any of the individual HR estimate. This method was evaluated on MIMIC II data base of PhysioNet from bedside monitors of ICU patients. The method provides an accurate HR estimate even in the presence of noise and artifacts.

Keywords: ECG, ABP, EEG, EMG, EOG, ECG artifacts, Teager-Kaiser energy, heart rate, signal quality index, Kalman filter, data fusion

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Authors: Liang Qin, Hanan M. D. Habbi

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A robust sensorless speed for permanent magnet synchronous motor (PMSM) has been presented for estimation of stator flux components and rotor speed based on The Extended Kalman Filter (EKF). The model of PMSM and its EKF models are modeled in Matlab /Sirnulink environment. The proposed EKF speed estimation method is also proved insensitive to the PMSM parameter variations. Simulation results demonstrate a good performance and robustness.

Keywords: DTC, Extended Kalman Filter (EKF), PMSM, sensorless control, anti-windup PI

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Authors: Niharika Verma, Sandeep Santosh

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DOA technique is a localization technique used in the communication field. Various algorithms have been developed for direction of arrival estimation like MUSIC, ROOT MUSIC, etc. These algorithms depend on various parameters like antenna array elements, number of snapshots and various others. Basically the MUSIC spectrum is evaluated and peaks obtained are considered as the angle of arrivals. The angles evaluated using this process depends on the scanning interval chosen. The accuracy of the results obtained depends on the coarseness of the interval chosen. In this paper, golden section search is applied to the MUSIC algorithm and therefore, more accurate results are achieved. Initially the coarse DOA estimations is done using the MUSIC algorithm in the range -90 to 90 degree at the interval of 10 degree. After the peaks obtained then fine DOA estimation is done using golden section search. Also, the partitioning method is applied to estimate the number of signals incident on the antenna array. Dependency of the algorithm on the number of snapshots is also being explained. Hence, the accurate results are being determined using this algorithm.

Keywords: Direction of Arrival (DOA), golden section search, MUSIC, number of snapshots

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Authors: Günther Schuh, Christina König, Toni Drescher

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One of the key factors for the competitiveness and market success of technology-driven companies is the timely provision of information about emerging technologies, changes in existing technologies, as well as relevant related changes in the market's structures and participants. Therefore, many companies conduct technology intelligence (TI) activities to ensure an early identification of appropriate technologies and other (weak) signals. One base activity of TI is technology monitoring, which is defined as the systematic tracking of developments within a specified topic of interest as well as related trends over a long period of time. Due to the very large number of dynamically changing parameters within the technological and the market environment of a company as well as their possible interdependencies, it is necessary to focus technology monitoring on specific indicators or other criteria, which are able to point out technological developments and market changes. In addition to the execution of a literature review on existing approaches, which mainly propose patent-based indicators, it is examined in this paper whether indicator systems from other branches such as risk management or economic research could be transferred to technology monitoring in order to enable an efficient and focused technology monitoring for companies.

Keywords: technology forecasting, technology indicator, technology intelligence, technology management, technology monitoring

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Authors: Abd El Hady N. Ebraheim

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This paper introduces a new generalization of the two parameter Weibull distribution. To this end, the quadratic rank transmutation map has been used. This new distribution is named exponentiated transmuted Weibull (ETW) distribution. The ETW distribution has the advantage of being capable of modeling various shapes of aging and failure criteria. Furthermore, eleven lifetime distributions such as the Weibull, exponentiated Weibull, Rayleigh and exponential distributions, among others follow as special cases. The properties of the new model are discussed and the maximum likelihood estimation is used to estimate the parameters. Explicit expressions are derived for the quantiles. The moments of the distribution are derived, and the order statistics are examined.

Keywords: exponentiated, inversion method, maximum likelihood estimation, transmutation map

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Authors: María Victoria Alvarez Magañini, Lautaro Nahuel Rubbi

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According to different theories, the hegemonic war between the United States and the People's Republic of China seems to be imminent. However, nowadays, it is clear that China's conventional military capacity is inferior to that of the United States. Nevertheless, the conditions that in the past were considered to be an indicator of validity in asymmetrical warfare, at present, in a possible asymmetric war scenario, are no longer considered to be taken as such. The military capacity is not the only concept that represents the main indicator of victory. The organisation and the use of forces are also an essential part of it. The present paper aims to analyze the Chinese Defense Strategy in relation to the concept of asymmetric warfare in the face of a possible war with the United States. The starting point will be developed on the basis of application of the theory which corresponds to the concept aforementioned making focus on recent developments of the People’s Republic of China in the field of non-conventional defense. A comparative analysis of the conventional forces of both powers/countries will also be carried out.

Keywords: asymmetric warfare, China, United States, hegemonic warfare

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Authors: Ting (Grace) Lin, Jianhong (Cecilia) Xia, Todd Robinson

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Accessibility analysis, examining people’s ability to access facilities and destinations, is a fundamental assessment for transport planning, policy making, and social exclusion research. Dynamic accessibility which measures accessibility in real-time traffic environment has been an advanced accessibility indicator in transport research. It is also a useful indicator to help travelers to understand travel time daily variability, assists traffic engineers to monitor traffic congestions, and finally develop effective strategies in order to mitigate traffic congestions. This research involved real-time traffic information by collecting travel time data with 15-minute interval via the TomTom^® API. A framework for measuring dynamic accessibility was then developed based on the gravity theory and accessibility dichotomy theory through space and time interpolation. Finally, the dynamic accessibility can be derived at any given time and location under dynamic accessibility spatial analysis framework.

Keywords: dynamic accessibility, hot spot, transport research, TomTom® API

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Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

Procedia PDF Downloads 447