Search results for: stochastic subspace identification

Authors: M. Yakoubi, N. Belboukhari, A. Cheriti, K. Sekoum

Abstract:

Launaea nudicaulis (L.) Hook.f. is a desert, spontaneous plant and endemic to northem Sahara, which belongs to the Asteraceae family. This species exists in the region of Bechar (Local name; El-Rghamma). In our knowledge, no work has been founded, except studies showing the antimicrobial and antifungal activity of methalonic extract of this plant. The present paper describes the chemical composition of the essential oil from Launaea nudicaulis and qualification of isolation and identification of some pure products by column chromatography. The essential oil from the aerial parts of Launaea nudicaulis (Asteraceae) was obtained by hydroditillation in 0.4% yield, led to isolation of four several new products. The isolation is made by column chromatography and followed by GC-IK and GC-MS analysis.

Keywords: Launaea nudicaulis, asteraceae, essential oil, column chromatography, GC-FID, GC-MS

Procedia PDF Downloads 301

Authors: Jaime A. Palma-Mendoza

Abstract:

A supply chain consists of different processes and when conducting supply chain re-design is necessary to identify the relevant processes and select a target for re-design. A solution was developed which consists to identify first the relevant processes using the Supply Chain Operations Reference (SCOR) model, then to use Analytical Hierarchy Process (AHP) for target process selection. An application was conducted in an Airline MRO supply chain re-design project which shows this combination can clearly aid the identification of relevant supply chain processes and the selection of a target process for re-design.

Keywords: decision support systems, multiple criteria analysis, supply chain management

Procedia PDF Downloads 492

Authors: M. Mulumpwa, W. W. L. Jere, M. Lazaro, A. H. N. Mtethiwa

Abstract:

The study considered Seasonal Autoregressive Integrated Moving Average (SARIMA) processes to select an appropriate stochastic model to forecast the monthly data from the Lake Malawi water levels for the period 1986 through 2015. The appropriate model was chosen based on SARIMA (p, d, q) (P, D, Q)S. The Autocorrelation function (ACF), Partial autocorrelation (PACF), Akaike Information Criteria (AIC), Bayesian Information Criterion (BIC), Box–Ljung statistics, correlogram and distribution of residual errors were estimated. The SARIMA (1, 1, 0) (1, 1, 1)12 was selected to forecast the monthly data of the Lake Malawi water levels from August, 2015 to December, 2021. The plotted time series showed that the Lake Malawi water levels are decreasing since 2010 to date but not as much as was the case in 1995 through 1997. The future forecast of the Lake Malawi water levels until 2021 showed a mean of 474.47 m ranging from 473.93 to 475.02 meters with a confidence interval of 80% and 90% against registered mean of 473.398 m in 1997 and 475.475 m in 1989 which was the lowest and highest water levels in the lake respectively since 1986. The forecast also showed that the water levels of Lake Malawi will drop by 0.57 meters as compared to the mean water levels recorded in the previous years. These results suggest that the Lake Malawi water level may not likely go lower than that recorded in 1997. Therefore, utilisation and management of water-related activities and programs among others on the lake should provide room for such scenarios. The findings suggest a need to manage the Lake Malawi jointly and prudently with other stakeholders starting from the catchment area. This will reduce impacts of anthropogenic activities on the lake’s water quality, water level, aquatic and adjacent terrestrial ecosystems thereby ensuring its resilience to climate change impacts.

Keywords: forecasting, Lake Malawi, water levels, water level fluctuation, climate change, anthropogenic activities

Procedia PDF Downloads 230

Authors: Hongmin Deng, Qionghua Wang

Abstract:

A modified two dimensional (2D) logistic map based on cross feedback control is proposed. This 2D map exhibits more random chaotic dynamical properties than the classic one dimensional (1D) logistic map in the statistical characteristics analysis. So it is utilized as the pseudo-random (PN) sequence generator, where the obtained real-valued PN sequence is quantized at first, then applied to radio frequency identification (RFID) communication system in this paper. This system is experimentally validated on a cortex-M₀ development board, which shows the effectiveness in key generation, the size of key space and security. At last, further cryptanalysis is studied through the test suite in the National Institute of Standards and Technology (NIST).

Keywords: chaos encryption, logistic map, pseudo-random sequence, RFID

Procedia PDF Downloads 400

Authors: Lavanya Srinivasan

Abstract:

Biometric identification is to identify unique features in a person like fingerprints, iris, ear, and voice recognition that need the subject's permission and physical contact. Gait biometric is used to identify the unique gait of the person by extracting moving features. The main advantage of gait biometric to identify the gait of a person at a distance, without any physical contact. In this work, the gait biometric is used for person re-identification. The person walking naturally compared with the same person walking with bag, coat, and case recorded using longwave infrared, short wave infrared, medium wave infrared, and visible cameras. The videos are recorded in rural and in urban environments. The pre-processing technique includes human identified using YOLO, background subtraction, silhouettes extraction, and synthesis Gait Entropy Image by averaging the silhouettes. The moving features are extracted from the Gait Entropy Energy Image. The extracted features are dimensionality reduced by the principal component analysis and recognised using different classifiers. The comparative results with the different classifier show that linear discriminant analysis outperforms other classifiers with 95.8% for visible in the rural dataset and 94.8% for longwave infrared in the urban dataset.

Keywords: biometric, gait, silhouettes, YOLO

Procedia PDF Downloads 172

Authors: H. Imad, Y. Cheah, O. Aamera

Abstract:

The aims of this research are to study the mitochondrial non-coding region by using the Sanger sequencing technique and establish the degree of variation characteristics of a fragment. FTA® Technology (FTA™ paper DNA extraction) utilized to extract DNA. A portion of a non-coding region encompassing positions 37 to 340 amplified in accordance with the Anderson reference sequence. PCR products purified by EZ-10 spin column then sequenced and detected by using the ABI 3730xL DNA Analyzer. New polymorphic positions 57, 63, and 101 are described may in future be suitable sources for identification purpose. The data obtained can be used to identify variable nucleotide positions characterized by frequent occurrence most promising for identification variants.

Keywords: encompassing nucleotide positions 37 to 340, HVII, Iraq, mitochondrial DNA, polymorphism, frequency

Procedia PDF Downloads 761

Authors: S. Rozhkova, O. Rozhkova, A. Harlova, V. Lasukov

Abstract:

For optimal unbiased filter as mean-square and in the case of functioning anomalous noises in the observation memory channel, we have proved insensitivity of filter to inaccurate knowledge of the anomalous noise intensity matrix and its equivalence to truncated filter plotted only by non anomalous components of an observation vector.

Keywords: mathematical expectation, filtration, anomalous noise, memory

Procedia PDF Downloads 362

Authors: Olga Biedova, Victoria Steblovskaya, Kai Wallbaum

Abstract:

In the current capital market environment, investors constantly face the challenge of finding a successful and stable investment mechanism. Highly volatile equity markets and extremely low bond returns bring about the demand for sophisticated yet reliable risk management strategies. Investors are looking for risk management solutions to efficiently protect their investments. This study compares a classic Constant Proportion Portfolio Insurance (CPPI) strategy to a Volatility Target portfolio insurance (VTPI). VTPI is an extension of the well-known Option Based Portfolio Insurance (OBPI) to the case where an embedded option is linked not to a pure risky asset such as e.g., S&P 500, but to a Volatility Target (VolTarget) portfolio. VolTarget strategy is a recently emerged rule-based dynamic asset allocation mechanism where the portfolio’s volatility is kept under control. As a result, a typical VTPI strategy allows higher participation rates in the market due to reduced embedded option prices. In addition, controlled volatility levels eliminate the volatility spread in option pricing, one of the frequently cited reasons for OBPI strategy fall behind CPPI. The strategies are compared within the framework of the stochastic dominance theory based on numerical simulations, rather than on the restrictive assumption of the Black-Scholes type dynamics of the underlying asset. An extended comparative quantitative analysis of performances of the above investment strategies in various market scenarios and within a range of input parameter values is presented.

Keywords: CPPI, portfolio insurance, stochastic dominance, volatility target

Procedia PDF Downloads 167

Authors: Emmy Pratiwi, Ketut B. Artana, A. A. B. Dinariyana

Abstract:

Madura Strait is considered as one of the busiest shipping channels in Indonesia. High vessel traffic density in Madura Strait gives serious threat due to navigational safety in this area, i.e. ship collision. This study is necessary as an attempt to enhance the safety of marine traffic. Fuzzy inference system (FIS) is proposed to calculate risk collision of ships. Collision risk is evaluated based on ship domain, Distance to Closest Point of Approach (DCPA), and Time to Closest Point of Approach (TCPA). Data were collected by utilizing Automatic Identification System (AIS). This study considers several ships’ domain models to give the characteristic of marine traffic in the waterways. Each encounter in the ship domain is analyzed to obtain the level of collision risk. Risk level of ships, as the result in this study, can be used as guidance to avoid the accident, providing brief description about safety traffic in Madura Strait and improving the navigational safety in the area.

Keywords: automatic identification system, collision risk, DCPA, fuzzy inference system, TCPA

Procedia PDF Downloads 549

Authors: Cheng Zhang, James Marco, Walid Allafi, Truong Q. Dinh, W. D. Widanage

Abstract:

Equivalent circuit models (ECMs) are widely used in battery management systems in electric vehicles and other battery energy storage systems. The battery dynamics and the model parameters vary under different working conditions, such as different temperature and state of charge (SOC) levels, and therefore online parameter identification can improve the modelling accuracy. This paper presents a way of online ECM parameter identification using a continuous time (CT) estimation method. The CT estimation method has several advantages over discrete time (DT) estimation methods for ECM parameter identification due to the widely separated battery dynamic modes and fast sampling. The presented method can be used for online SOC estimation. Test data are collected using a lithium ion cell, and the experimental results show that the presented CT method achieves better modelling accuracy compared with the conventional DT recursive least square method. The effectiveness of the presented method for online SOC estimation is also verified on test data.

Keywords: electric circuit model, continuous time domain estimation, linear integral filter method, parameter and SOC estimation, recursive least square

Procedia PDF Downloads 383

Authors: Arun Prabhakar

Abstract:

Threat modeling is an important activity carried out in the initial stages of the development lifecycle that helps in building proactive security measures in the product. Though there are many techniques and tools available today, one of the common challenges with the traditional methods is the lack of a systematic approach in identifying security threats. The proposed solution describes an organized model by defining ontologies that help in building patterns to enumerate threats. The concepts of graph theory are applied to build the pattern for discovering threats for any given scenario. This graph-based solution also brings in other benefits, making it a customizable and scalable model.

Keywords: directed acyclic graph, ontology, patterns, threat identification, threat modeling

Procedia PDF Downloads 139

Authors: Svetlana Cojocaru, Mircea Petic, Inga Titchiev

Abstract:

Humanity faces more and more often with different social disasters, which in turn can generate new accidents and catastrophes. To mitigate their consequences, it is important to obtain early possible signals about the events which are or can occur and to prepare the corresponding scenarios that could be applied. Our research is focused on solving two problems in this domain: identifying signals related that an accident occurred or may occur and mitigation of some consequences of disasters. To solve the first problem, methods of selecting and processing texts from global network Internet are developed. Information in Romanian is of special interest for us. In order to obtain the mentioned tools, we should follow several steps, divided into preparatory stage and processing stage. Throughout the first stage, we manually collected over 724 news articles and classified them into 10 categories of social disasters. It constitutes more than 150 thousand words. Using this information, a controlled vocabulary of more than 300 keywords was elaborated, that will help in the process of classification and identification of the texts related to the field of social disasters. To solve the second problem, the formalism of Petri net has been used. We deal with the problem of inhabitants’ evacuation in useful time. The analysis methods such as reachability or coverability tree and invariants technique to determine dynamic properties of the modeled systems will be used. To perform a case study of properties of extended evacuation system by adding time, the analysis modules of PIPE such as Generalized Stochastic Petri Nets (GSPN) Analysis, Simulation, State Space Analysis, and Invariant Analysis have been used. These modules helped us to obtain the average number of persons situated in the rooms and the other quantitative properties and characteristics related to its dynamics.

Keywords: lexicon of disasters, modelling, Petri nets, text annotation, social disasters

Procedia PDF Downloads 197

Authors: Maciej Zaręba, Sławomir Lasota

Abstract:

Understanding the dependencies between the input signal, that controls the production system and signals, that capture its output, is of a great importance in intelligent systems. The method for identification of the relationship between signals in continuous monitoring of production systems is described in the paper. The method discovers the correlation between changes in the states derived from input signals and resulting changes in the states of output signals of the production system. The method is able to handle system inertia, which determines the time shift of the relationship between the input and output.

Keywords: manufacturing operation management, signal relationship, continuous monitoring, production systems

Procedia PDF Downloads 92

Authors: Ghasem Sharifi, Hamed Shahmohamadi Ousaloo, Milad Azimi, Mehran Mirshams

Abstract:

The ever-increasing use of satellites demands a search for increasingly accurate and reliable pointing systems. Reaction wheels are rotating devices used commonly for the attitude control of the spacecraft since provide a wide range of torque magnitude and high reliability. The numerical modeling of this device can significantly enhance the accuracy of the satellite control in space. Modeling the wheel rotation in the presence of the various frictions is one of the critical parts of this approach. This paper presents a Dynamic Model Control of a Reaction Wheel (DMCR) in the current control mode. In current-mode, the required current is delivered to the coils in order to achieve the desired torque. During this research, all the friction parameters as viscous and coulomb, motor coefficient, resistance and voltage constant are identified. In order to model identification of a reaction wheel, numerous varying current commands apply on the particular wheel to verify the estimated model. All the parameters of DMCR are identified by classical Levenberg-Marquardt (CLM) optimization method. The experimental results demonstrate that the developed model has an appropriate precise and can be used in the satellite control simulation.

Keywords: experimental modeling, friction parameters, model identification, reaction wheel

Procedia PDF Downloads 233

Authors: Tong He, Long Chen, Irag Mantegh, Wen-Fang Xie

Abstract:

This paper proposes an image-based obstacle avoidance and tracking target identification strategy in GPS-degraded or GPS-denied environment for an Unmanned Aerial Vehicle (UAV). The traditional force algorithm for obstacle avoidance could produce local minima area, in which UAV cannot get away obstacle effectively. In order to eliminate it, an artificial potential approach based on harmonic potential is proposed to guide the UAV to avoid the obstacle by using the vision system. And image-based visual servoing scheme (IBVS) has been adopted to implement the proposed obstacle avoidance approach. In IBVS, the pixel accuracy is a key factor to realize the obstacle avoidance. In this paper, the deep reinforcement learning framework has been applied by reducing pixel errors through constant interaction between the environment and the agent. In addition, the combination of OpenTLD and Tensorflow based on neural network is used to identify the type of tracking target. Numerical simulation in Matlab and ROS GAZEBO show the satisfactory result in target identification and obstacle avoidance.

Keywords: image-based visual servoing, obstacle avoidance, tracking target identification, deep reinforcement learning, artificial potential approach, neural network

Procedia PDF Downloads 143

Authors: Tugba Bayoglu

Abstract:

Aerodynamic parameter estimation is very crucial in missile design phase, since accurate high fidelity aerodynamic model is required for designing high performance and robust control system, developing high fidelity flight simulations and verification of computational and wind tunnel test results. However, in literature, there is not enough missile aerodynamic parameter identification study for three main reasons: (1) most air to air missiles cannot fly with constant speed, (2) missile flight test number and flight duration are much less than that of fixed wing aircraft, (3) variation of the missile aerodynamic parameters with respect to Mach number is higher than that of fixed wing aircraft. In addition to these challenges, identification of aerodynamic parameters for high wind angles by using classical estimation techniques brings another difficulty in the estimation process. The reason for this, most of the estimation techniques require employing polynomials or splines to model the behavior of the aerodynamics. However, for the missiles with a large variation of aerodynamic parameters with respect to flight variables, the order of the proposed model increases, which brings computational burden and complexity. Therefore, in this study, it is aimed to solve nonlinear aerodynamic parameter identification problem for a supersonic air to air missile by using Artificial Neural Networks. The method proposed will be tested by using simulated data which will be generated with a six degree of freedom missile model, involving a nonlinear aerodynamic database. The data will be corrupted by adding noise to the measurement model. Then, by using the flight variables and measurements, the parameters will be estimated. Finally, the prediction accuracy will be investigated.

Keywords: air to air missile, artificial neural networks, open loop simulation, parameter identification

Procedia PDF Downloads 279

Authors: Meet Shah, Ankita Aditya, Dhruv Bindra, V. S. Omkar, Aashruti Seervi

Abstract:

In today's world, we need documents everywhere for a smooth workflow in the identification process or any other security aspects. The current system and techniques which are used for identification need one thing, that is ‘proof of existence’, which involves valid documents, for example, educational, financial, etc. The main issue with the current identity access management system and digital identification process is that the system is centralized in their network, which makes it inefficient. The paper presents the system which resolves all these cited issues. It is based on ‘blockchain’ technology, which is a 'decentralized system'. It allows transactions in a decentralized and immutable manner. The primary notion of the model is to ‘have everything with nothing’. It involves inter-linking required documents of a person with a single identity card so that a person can go anywhere without having the required documents with him/her. The person just needs to be physically present at a place wherein documents are necessary, and using a fingerprint impression and an iris scan print, the rest of the verification will progress. Furthermore, some technical overheads and advancements are listed. This paper also aims to layout its far-vision scenario of blockchain and its impact on future trends.

Keywords: blockchain, decentralized system, fingerprint impression, identity management, iris scan

Procedia PDF Downloads 128

Authors: Abdelmalek Ouannou, Adil Brouri, Laila Kadi, Tarik

Abstract:

Switched reluctance motor (SRM) has a major interest in a large domain as in electric vehicle driving because of its wide range of speed operation, high performances, low cost, and robustness to run under degraded conditions. The purpose of the paper is to develop a new analytical approach for modeling SRM parameters. Then, an identification scheme is proposed to obtain the SRM parameters. Since the SRM is featured by a highly nonlinear behavior, modeling these devices is difficult. Then, it is convenient to develop an accurate model describing the SRM. Furthermore, it is always operated in the magnetically saturated mode to maximize the energy transfer. Accordingly, it is shown that the SRM can be accurately described by a generalized polynomial Hammerstein model, i.e., the parallel connection of several Hammerstein models having polynomial nonlinearity. Presently an analytical identification method is developed using a chirp excitation signal. Afterward, the parameters of the obtained model have been determined using Finite Element Method analysis. Finally, in order to show the effectiveness of the proposed method, a comparison between the true and estimate models has been performed. The obtained results show that the output responses are very close.

Keywords: switched reluctance motor, swept-sine signal, generalized Hammerstein model, nonlinear system

Procedia PDF Downloads 236

Authors: Dawood Al Chanti, Alice Caplier

Abstract:

Sparse representations of signals have received a great deal of attention in recent years. In this paper, the interest of using sparse representation as a mean for performing sparse discriminative analysis between spontaneous facial expressions is demonstrated. An automatic facial expressions recognition system is presented. It uses a KSVD-SVM approach which is made of three main stages: A pre-processing and feature extraction stage, which solves the problem of shared subspace distribution based on the random projection theory, to obtain low dimensional discriminative and reconstructive features; A dictionary learning and sparse coding stage, which uses the KSVD model to learn discriminative under or over dictionaries for sparse coding; Finally a classification stage, which uses a SVM classifier for facial expressions recognition. Our main concern is to be able to recognize non-basic affective states and non-acted expressions. Extensive experiments on the JAFFE static acted facial expressions database but also on the DynEmo dynamic spontaneous facial expressions database exhibit very good recognition rates.

Keywords: dictionary learning, random projection, pose and spontaneous facial expression, sparse representation

Procedia PDF Downloads 305

Authors: Christian A. Romero, Tanja Grkovic, John. R. J. French, D. İpek Kurtböke, Ronald J. Quinn

Abstract:

A high-throughput and automated 1H NMR metabolic fingerprinting dereplication approach was used to accelerate the discovery of unknown bioactive secondary metabolites. The applied dereplication strategy accelerated the discovery of natural products, provided rapid and competent identification and quantification of the known secondary metabolites and avoided time-consuming isolation procedures. The effectiveness of the technique was demonstrated by the isolation and elucidation of arglecins B (1), C (2) and actinofuranosin A (3) from a termite-gut associated Streptomyces sp. (USC 597) grown under solid state fermentation. The structures of these compounds were elucidated by extensive interpretation of 1H, 13C and 2D NMR spectroscopic data. These represent the first report of arglecin analogs isolated from a termite gut-associated Streptomyces species.

Keywords: actinomycetes, actinofuranosin, antibiotics, arglecins, NMR spectroscopy

Procedia PDF Downloads 61

Authors: Churamani Pokhrel, C. B. Jha, S. R. Niraula, P. R. Pokharel

Abstract:

Human identification is one of the most challenging subjects that man has confronted. The determination of adult sex and stature are two of the four key factors (sex, stature, age, and race) in identification of an individual. Craniofacial and odontometric parameters are important tools for forensic anthropologists when it is not possible to apply advanced techniques for identification purposes. The present study provides anthropometric correlation of the parameters with stature and gender and also devises regression formulae for reconstruction of stature. A total of 312 Nepalese students with equal distribution of sex i.e., 156 male and 156 female students of age 18-35 years were taken for the study. Total of 10 parameters were measured (age, sex, stature, head circumference, head length, head breadth, facial height, bi-zygomatic width, mesio-distal canine width and inter-canine distance of both maxilla and mandible). Co-relation and regression analysis was done to find the association between the parameters. All parameters were found to be greater in males than females and each was found to be statistically significant. Out of total 312 samples, the best regressor for the determination of stature was head circumference and mandibular inter-canine width and that for gender was head circumference and right mandibular teeth. The accuracy of prediction was 83%. Regression equations and analysis generated from craniofacial and odontometric parameters can be a supplementary approach for the estimation of stature and gender when extremities are not available.

Keywords: craniofacial, gender, odontometric, stature

Procedia PDF Downloads 191

Authors: S. Malarvizhi, S. Sadiq Basha, M. Santhosh Kumar, K. Saravanan, R. Sasikumar, R. Satheesh

Abstract:

This is a web based application which provides authorization for the vehicle identification and registration. It also provides mutual authentication between the police and users in order to avoid misusage. The QR code generation in this application overcomes the difficulty in the manual registration of the vehicle documents. This generated QR code is placed in the number plates of the vehicles. The QR code is scanned using the QR Reader installed in the smart devices. The police officials can check the vehicle details and file cases on accidents, theft and traffic rules violations using QR code. In addition to vehicle insurance payments and renewals, the renewal alert is sent to the vehicle owner about payment deadline. The non-permitted vehicles can be blocked in the next check-post by sending the alert messages.

Keywords: QR code, QR reader, registration, authentication, idenfication

Procedia PDF Downloads 494

Authors: Keiji Komatsu, Hayato Maruyama, Ariyuki Kato, Atsushi Nakamura, Shigeo Ohshio, Hiroki Akasaka, Hidetoshi Saitoh

Abstract:

Violet Sr–Al–O:Eu2+ phosphor particles were synthesized from a metal–ethylenediaminetetraacetic acid (EDTA) solution of Sr, Al, Eu, and particulate alumina via spray drying and sintering in a reducing atmosphere. The crystal structures and emission properties at 85–300 K were investigated. The composition of the violet Sr–Al–O:Eu2+ phosphor particles was determined from various Sr–Al–O:Eu2+ phosphors by their emission properties’ dependence on temperature. The highly crystalline SrAl12O19:Eu2+ emission phases were confirmed by their crystallite sizes and the activation energies for the 4f5d–8S7/2 transition of the Eu2+ ion. These results showed that the material identification for the violet Sr–Al–O:Eu2+ phosphor was accomplished by the low-temperature luminescence measurements.

Keywords: low temperature luminescence spectroscopy, material identification, strontium aluminates phosphor, emission properties

Procedia PDF Downloads 448

Authors: Kate Whitman, Zahra Murad, Joe Cox

Abstract:

Corporate social responsibility projects are suggested to motivate consumers to reciprocate good corporate deeds with their custom. When the projects benefit the ingroup vs the outgroup, such as locals rather than foreigners, the effect on reciprocity is suggested to be more powerful. This may be explained by group heuristics, a theory which indicates that favours to the ingroup (but not outgroup) are expected to be reciprocated, resulting in ingroup favouritism. The heuristic is theorised to explain prosocial behaviours towards the ingroup. The aim of this study is to test whether group heuristics similarly explain a reduction in antisocial behaviours towards the ingroup, measured by illegal consumption which harms a group that consumers identify with. In order to test corporate social responsibility messages, a population of interested consumers is required, so sport fans are recruited. A pre-registered experiment (N = 600) tests the influence of a focused “team” benefiting message vs a broader “sport” benefiting message on change in illegal intentions. The influence of group (team) identity and trait reciprocity on message efficacy are tested as measures of group heuristics. Results suggest that the “team” treatment significantly reduces illegal consumption intentions. The “sport” treatment interacted with the team identification measure, increasing illegal consumption intentions for low team identification individuals. The results suggest that corporate social responsibility may be effective in reducing illegal consumption, if the messages are delivered directly from brands to consumers with brand identification. Messages delivered on the behalf of an industry may have an undesirable effect.

Keywords: live sports, piracy, counterfeiting, corporate social responsibility, group heuristics, ingroup bias, team identification

Procedia PDF Downloads 84

Authors: M. T. Alodat

Abstract:

In this paper, we propose a mechanism for skewing any symmetric distribution. The new distribution is called the deflation-inflation distribution (DID). We discuss some statistical properties of the DID such moments, stochastic representation, log-concavity. Also we fit the distribution to real data and we compare it to normal distribution and Azzlaini's skew normal distribution. Numerical results show that the DID fits the the tree ring data better than the other two distributions.

Keywords: normal distribution, moments, Fisher information, symmetric distributions

Procedia PDF Downloads 656

Authors: Mary Gouva, Elena Dragioti, Evangelia Kotrsotsiou

Abstract:

Family identification has the potential to play a very decisive role in psychopathology. In this study we aimed to investigate the impact of family identifications on female psychopathology. A community sample of 101 women (mean age 20.81 years, SD = 0.91 ranged 20-25) participated to the present study. The girls completed a) the Symptom Check-List Revised (SCL-90) and b) questionnaire concerning socio-demographic information and questions for family identifications. The majority of women reported that they matched to the father in terms of identifications (47.1%). Age and birth order were not contributed on family identifications (F(5) =2.188, p=.062 and F(3)=1.244, p=.299 respectively). Multivariate analysis by using MANCOVA found statistical significant associations between family identifications and domains of psychopathology as provided by SCL-90 (P<05). Our results highlight the role of identifications especially on father and female psychopathology as well as replicate the Freudian perception about the female Oedipus complex.

Keywords: family identification, psychoanalysis, psychopathology, women

Procedia PDF Downloads 323

Authors: Ghazi Bouaziz, Abderrahim Derouiche, Damien Brulin, Hélène Pigot, Eric Campo

Abstract:

Automatic ADL classification is a crucial part of ambient assisted living technologies. It allows to monitor the daily life of the elderly and to detect any changes in their behavior that could be related to health problem. But detection of ADLs is a challenge, especially because each person has his/her own rhythm for performing them. Therefore, we used a correlation matrix to extract custom rules that enable to detect ADLs, including eating activity. Data collected from 3 different individuals between 35 and 105 days allows the extraction of personalized eating patterns. The comparison of the results of the process of eating activity extracted from the correlation matrices with the declarative data collected during the survey shows an accuracy of 90%.

Keywords: elderly monitoring, ADL identification, matrix correlation, meal-taking activity

Procedia PDF Downloads 93

Authors: Paul Rowley, Adam Thirkill, Nick Doylend, Philip Leicester, Becky Gough

Abstract:

The dynamic performance of all energy generation technologies is impacted to varying degrees by the stochastic properties of the wider system within which the generation technology is located. This stochasticity can include the varying nature of ambient renewable energy resources such as wind or solar radiation, or unpredicted changes in energy demand which impact upon the operational behaviour of thermal generation technologies. An understanding of these stochastic impacts are especially important in contexts such as highly distributed (or embedded) generation, where an understanding of issues affecting the individual or aggregated performance of high numbers of relatively small generators is especially important, such as in ESCO projects. Probabilistic evaluation of monitored or simulated performance data is one technique which can provide an insight into the dynamic performance characteristics of generating systems, both in a prognostic sense (such as the prediction of future performance at the project’s design stage) as well as in a diagnostic sense (such as in the real-time analysis of underperforming systems). In this work, we describe the development, application and outcomes of a new approach to the acquisition of datasets suitable for use in the subsequent performance and impact analysis (including the use of Bayesian approaches) for a number of distributed generation technologies. The application of the approach is illustrated using a number of case studies involving domestic and small commercial scale photovoltaic, solar thermal and natural gas boiler installations, and the results as presented show that the methodology offers significant advantages in terms of plant efficiency prediction or diagnosis, along with allied environmental and social impacts such as greenhouse gas emission reduction or fuel affordability.

Keywords: renewable energy, dynamic performance simulation, Bayesian analysis, distributed generation

Procedia PDF Downloads 495

Authors: Ladislav Ptacek, Jan Vanek, Jan Eisner, Alexandra Pruchova, Pavel Linhart, Ludek Muller, Dana Jirotkova

Abstract:

One of the essential steps of avian song processing is signal filtering. Currently, the standard methods of filtering are the Mel Bank Filter or linear filter distribution. In this article, a new type of bank filter called the Bird-Adapted Filter is introduced; whereby the signal filtering is modifiable, based upon a new mathematical description of audiograms for particular bird species or order, which was named the Avian Audiogram Unified Equation. According to the method, filters may be deliberately distributed by frequency. The filters are more concentrated in bands of higher sensitivity where there is expected to be more information transmitted and vice versa. Further, it is demonstrated a comparison of various filters for automatic individual recognition of chiffchaff (Phylloscopus collybita). The average Equal Error Rate (EER) value for Linear bank filter was 16.23%, for Mel Bank Filter 18.71%, the Bird-Adapted Filter gave 14.29%, and Bird-Adapted Filter with 1/3 modification was 12.95%. This approach would be useful for practical use in automatic systems for avian species and individual identification. Since the Bird-Adapted Filter filtration is based on the measured audiograms of particular species or orders, selecting the distribution according to the avian vocalization provides the most precise filter distribution to date.

Keywords: avian audiogram, bird individual identification, bird song processing, bird species recognition, filter bank

Procedia PDF Downloads 387

Authors: Meryem Saban Guler, Saniye Bilici

Abstract:

Malnutrition is a problem that significantly affects patients with cancer throughout the course of their illness, and it may be present from the moment of diagnosis until the end of treatment. We searched electronic databases using key terms such as ‘malnutrition in cancer patients’ or ‘nutritional status in cancer’ or ‘nutritional screening tools’ etc. Decline in nutritional status and continuing weight loss are associated with an increase in number and severity of complications, impaired quality of life and decreased survival rate. Nutrition is an important factor in the treatment and progression of cancer. Cancer patients are particularly susceptible to nutritional depletion due to the combined effects of the malignant disease and its treatment. With increasing incidence of cancer, identification and management of nutritional deficiencies are needed. Early identification of malnutrition, is substantial to minimize or prevent undesirable outcomes throughout clinical course. In determining the nutritional status; food consumption status, anthropometric methods, laboratory tests, clinical symptoms, psychosocial data are used. First-line strategies must include routine screening and identification of inpatients or outpatients at nutritional risk with the use of a simple and standardized screening tool. There is agreement among international nutrition organizations and accredited health care organizations that routine nutritional screening should be a standard procedure for every patient admitted to a hospital. There are f management of all cancer patients therefore routine nutritional screening with validated tools can identify cancer patients at risk.

Keywords: cancer, malnutrition, nutrition, nutritional screening

Procedia PDF Downloads 205