Search results for: clutter

Authors: Murray Anderson, Galina Freed, Karli Jahn

Abstract:

Trauma is increasingly recognized as an important construct that has health implications for those who struggle with various mental health issues. For those individuals who meet the criteria for a diagnosis of hoarding disorder (HD), many have experienced some form of trauma. Further, some of the therapeutic interventions for those with HD can further perpetuate or magnify the experience of trauma. Therefore, the aim of this scoping review is to identify and document the nature and extent of research evidence related to trauma as it connects with HD. This review was guided by the questions, ‘How can our understanding of the trauma cycle help us to better appreciate the experiences of individuals who hoard, and how will a trauma informed lens inform the interventions for hoarding disorder? A comprehensive literature search was performed to identify original studies that contained the words “hoarding” and “trauma.” PsychINFO”,''EBSCO host,” “CINAHL” and “PubMed” were searched between January 2005 and April 2021. Articles were screened by three reviewers. Data extracted included publication date, demographics, study design, type of analysis, and noted connections between hoarding and trauma. Of the 329 articles, all duplicates, articles on hoardings of animals, articles not in English, and those without full-text availability were removed. Five categories were found in the remaining 45 articles, including (a) traumatic and stressful life events; (b) the link between posttraumatic stress disorder, trauma, and hoarding; (c) the relationships between different comorbidities, trauma, and hoarding; (d) the lack of early emotional expression and other forms of parental deprivation; and (e) the role of attachment. Lastly, the literature explains how the links between hoarding and trauma are difficult to study due to the highly stigmatized identities with this population. The review provided strong support for the connections between the experience of trauma and HD. What is missing from the literature is the use of a trauma-informed lens to better account for the ways in which hoarding disorder is understood. Other missing pieces in the literature are the potential uses of a trauma-informed lens to enhance the therapeutic process, to understand and reduce treatment attrition, and to improve treatment outcomes. The application of a trauma informed lens could improve our understanding of effective interactions among clients, families, and communities and improve the education around hoarding-related matters. Exploring the connections between trauma and HD can improve therapeutic delivery and destigmatize the experience of dealing with clutter and hoarding concerns. This awareness can also provide health care professionals with both the language and skills to liberate them from a reductionist view on HD.

Keywords: hoarding, attachment, parental deprivation, trauma

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Authors: Pragati Sirohi, Vivek Singh Rana

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Brand is a name, term, sign, symbol or design or a combination of all these which is intended to identify the goods or services of one seller or a group of sellers and to differentiate them from those of the competitors and perception influences purchase decisions here and so building that perception is critical. The FMCG industry is a low margin business. Volumes hold the key to success in this industry. Therefore, the industry has a strong emphasis on marketing. Creating strong brands is important for FMCG companies and they devote considerable money and effort in developing brands. Brand loyalty is fickle. Companies know this and that is why they relentlessly work towards brand building. The purpose of the study is a comparison between Indian and Multinational companies with regard to FMCG sector in India. It has been hypothesized that after liberalization the Indian companies has taken up the challenge of globalization and some of these are giving a stiff competition to MNCs. There is an existence of strong brand image of MNCs compared to Indian companies. Advertisement expenditures of MNCs are proportionately higher compared to Indian counterparts. The operational area of the study is the country as a whole. Continuous time series data is available from 1996-2014 for the selected 8 companies. The selection of these companies is done on the basis of their large market share, brand equity and prominence in the market. Research methodology focuses on finding trend growth rates of market capitalization, net worth, and brand values through regression analysis by the usage of secondary data from prowess database developed by CMIE (Centre for monitoring Indian Economy). Estimation of brand values of selected FMCG companies is being attempted, which can be taken to be the excess of market capitalization over the net worth of a company. Brand value indices are calculated. Correlation between brand values and advertising expenditure is also measured to assess the effect of advertising on branding. Major results indicate that although MNCs enjoy stronger brand image but few Indian companies like ITC is the outstanding leader in terms of its market capitalization and brand values. Dabur and Tata Global Beverages Ltd are competing equally well on these values. Advertisement expenditures are the highest for HUL followed by ITC, Colgate and Dabur which shows that Indian companies are not behind in the race. Although advertisement expenditures are playing a role in brand building process there are many other factors which affect the process. Also, brand values are decreasing over the years for FMCG companies in India which show that competition is intense with aggressive price wars and brand clutter. Implications for Indian companies are that they have to consistently put in proactive and relentless efforts in their brand building process. Brands need focus and consistency. Brand longevity without innovation leads to brand respect but does not create brand value.

Keywords: brand value, FMCG, market capitalization, net worth

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Authors: Olga Hernán-Vega, Patricia López-Rodríguez, David Escot-Bocanegra, Raúl Fernández-Recio, Ignacio Bravo

Abstract:

Non-Cooperative Target Identification has become a key research domain in the Defense industry since it provides the ability to recognize targets at long distance and under any weather condition. High Resolution Range Profiles, one-dimensional radar images where the reflectivity of a target is projected onto the radar line of sight, are widely used for identification of flying targets. According to that, to face this problem, an approach to Non-Cooperative Target Identification based on the exploitation of Singular Value Decomposition to a matrix of range profiles is presented. Target Identification based on one-dimensional radar images compares a collection of profiles of a given target, namely test set, with the profiles included in a pre-loaded database, namely training set. The classification is improved by using Singular Value Decomposition since it allows to model each aircraft as a subspace and to accomplish recognition in a transformed domain where the main features are easier to extract hence, reducing unwanted information such as noise. Singular Value Decomposition permits to define a signal subspace which contain the highest percentage of the energy, and a noise subspace which will be discarded. This way, only the valuable information of each target is used in the recognition process. The identification algorithm is based on finding the target that minimizes the angle between subspaces and takes place in a transformed domain. Two metrics, F1 and F2, based on Singular Value Decomposition are accomplished in the identification process. In the case of F2, the angle is weighted, since the top vectors set the importance in the contribution to the formation of a target signal, on the contrary F1 simply shows the evolution of the unweighted angle. In order to have a wide database or radar signatures and evaluate the performance, range profiles are obtained through numerical simulation of seven civil aircraft at defined trajectories taken from an actual measurement. Taking into account the nature of the datasets, the main drawback of using simulated profiles instead of actual measured profiles is that the former implies an ideal identification scenario, since measured profiles suffer from noise, clutter and other unwanted information and simulated profiles don't. In this case, the test and training samples have similar nature and usually a similar high signal-to-noise ratio, so as to assess the feasibility of the approach, the addition of noise has been considered before the creation of the test set. The identification results applying the unweighted and weighted metrics are analysed for demonstrating which algorithm provides the best robustness against noise in an actual possible scenario. So as to confirm the validity of the methodology, identification experiments of profiles coming from electromagnetic simulations are conducted, revealing promising results. Considering the dissimilarities between the test and training sets when noise is added, the recognition performance has been improved when weighting is applied. Future experiments with larger sets are expected to be conducted with the aim of finally using actual profiles as test sets in a real hostile situation.

Keywords: HRRP, NCTI, simulated/synthetic database, SVD

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Authors: Asma Omri, Iheb Sifaoui, Sofiane Sayahi, Hichem Besbes

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Future vehicle systems demand advanced capabilities, notably in-cabin life detection and driver monitoring systems, with a particular emphasis on drowsiness detection. To meet these requirements, several techniques employ artificial intelligence methods based on real-time vital sign measurements. In parallel, Frequency-Modulated Continuous-Wave (FMCW) radar technology has garnered considerable attention in the domains of healthcare and biomedical engineering for non-invasive vital sign monitoring. FMCW radar offers a multitude of advantages, including its non-intrusive nature, continuous monitoring capacity, and its ability to penetrate through clothing. In this paper, we propose a system utilizing the AWR6843AOP radar from Texas Instruments (TI) to extract precise vital sign information. The radar allows us to estimate Ballistocardiogram (BCG) signals, which capture the mechanical movements of the body, particularly the ballistic forces generated by heartbeats and respiration. These signals are rich sources of information about the cardiac cycle, rendering them suitable for heart rate estimation. The process begins with real-time subject positioning, followed by clutter removal, computation of Doppler phase differences, and the use of various filtering methods to accurately capture subtle physiological movements. To address the challenges associated with FMCW radar-based vital sign monitoring, including motion artifacts due to subjects' movement or radar micro-vibrations, Long Short-Term Memory (LSTM) networks are implemented. LSTM's adaptability to different heart rate patterns and ability to handle real-time data make it suitable for continuous monitoring applications. Several crucial steps were taken, including feature extraction (involving amplitude, time intervals, and signal morphology), sequence modeling, heart rate estimation through the analysis of detected cardiac cycles and their temporal relationships, and performance evaluation using metrics such as Root Mean Square Error (RMSE) and correlation with reference heart rate measurements. For dataset construction and LSTM training, a comprehensive data collection system was established, integrating the AWR6843AOP radar, a Heart Rate Belt, and a smart watch for ground truth measurements. Rigorous synchronization of these devices ensured data accuracy. Twenty participants engaged in various scenarios, encompassing indoor and real-world conditions within a moving vehicle equipped with the radar system. Static and dynamic subject’s conditions were considered. The heart rate estimation through LSTM outperforms traditional signal processing techniques that rely on filtering, Fast Fourier Transform (FFT), and thresholding. It delivers an average accuracy of approximately 91% with an RMSE of 1.01 beat per minute (bpm). In conclusion, this paper underscores the promising potential of FMCW radar technology integrated with artificial intelligence algorithms in the context of automotive applications. This innovation not only enhances road safety but also paves the way for its integration into the automotive ecosystem to improve driver well-being and overall vehicular safety.

Keywords: ballistocardiogram, FMCW Radar, vital sign monitoring, LSTM

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