Time-Series Models in Marketing

Marketing data appear in a variety of forms. An often-seen form is time-series data, like sales per month, prices over the last few years, market shares per week. Time-series data can be summarized in time-series models. In this chapter we review a few of these, focusing in particular on domains that have received considerable attention in the marketing literature. These are (1) the use of persistence modelling and (2) the use of state space models.Marketing;Persistence;State Space;Time Series

Polarization properties of specular and dense multipath components in a large industrial hall

This paper presents an analysis of the polarization characteristics of specular and dense multipath components (SMC & DMC) in a large industrial hall based on frequency-domain channel sounding experiments at 1.3 GHz with 22 MHz bandwidth. The RiMAX maximum-likelihood estimator is used to extract the full polarimetric SMC and DMC from the measurement data by taking into account the polarimetric radiating patterns of the dual-polarized antennas. Cross-polar discrimination (XPD) values are presented for the measured channels and for the SMC and DMC separately

An indoor localization technique based on ultra-wideband AoD/AoA/ToA estimation

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The protective effect of exercise on diabetic nephropathy : the role of histidine-containing dipeptides

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An indoor variance-based localization technique utilizing the UWB estimation of geometrical propagation parameters

A novel localization framework is presented based on ultra-wideband (UWB) channel sounding, employing a triangulation method using the geometrical properties of propagation paths, such as time delay of arrival, angle of departure, angle of arrival, and their estimated variances. In order to extract these parameters from the UWB sounding data, an extension to the high-resolution RiMAX algorithm was developed, facilitating the analysis of these frequency-dependent multipath parameters. This framework was then tested by performing indoor measurements with a vector network analyzer and virtual antenna arrays. The estimated means and variances of these geometrical parameters were utilized to generate multiple sample sets of input values for our localization framework. Next to that, we consider the existence of multiple possible target locations, which were subsequently clustered using a Kim-Parks algorithm, resulting in a more robust estimation of each target node. Measurements reveal that our newly proposed technique achieves an average accuracy of 0.26, 0.28, and 0.90 m in line-of-sight (LoS), obstructed-LoS, and non-LoS scenarios, respectively, and this with only one single beacon node. Moreover, utilizing the estimated variances of the multipath parameters proved to enhance the location estimation significantly compared to only utilizing their estimated mean values

Time-Series Models in Marketing

Marketing data appear in a variety of forms. An often-seen form is time-series data, like sales per month, prices over the last few years, market shares per week. Time-series data can be summarized in time-series models. In this chapter we review a few of these, focusing in particular on domains that have received considerable attention in the marketing literature. These are (1) the use of persistence modelling and (2) the use of state space models

Supramolecular hierarchy among halogen and hydrogen bond donors in light-induced surface patterning

Halogen bonding, a noncovalent interaction possessing several unique features compared to the more familiar hydrogen bonding, is emerging as a powerful tool in functional materials design. Herein, we unambiguously show that one of these characteristic features, namely high directionality, renders halogen bonding the interaction of choice when developing azobenzene-containing supramolecular polymers for light-induced surface patterning. The study is conducted by using an extensive library of azobenzene molecules that differ only in terms of the bond-donor unit. We introduce a new tetrafluorophenol-containing azobenzene photoswitch capable of forming strong hydrogen bonds, and show that an iodoethynyl-containing azobenzene comes out on top of the supramolecular hierarchy to provide unprecedented photoinduced surface patterning efficiency. Specifically, the iodoethynyl motif seems highly promising in future development of polymeric optical and photoactive materials driven by halogen bonding

Measurement-based analysis of dense multipath components in a large industrial warehouse

This work presents a measurement-based polarimetric analysis of the specular- and dense multipath components (SMCs and DMC) in a large industrial warehouse. MIMO channel sounding measurements were carried out in a flower auction warehouse, and were processed with the RiMAX multipath estimation framework. In the analysis, we investigate the behavior of the SMCs and the DMC power as a function of both the polarization and the transmitter-receiver distance for 1507 distinct positions of the receiver. The cross-polar discrimination of the transmitted V and H polarizations were analyzed statistically for this environment, as well as the relative power ratio of the DMC, and the DMC reverberation time

Factors associated with the local control of brain metastases:A systematic search and machine learning application

Background: Enhancing Local Control (LC) of brain metastases is pivotal for improving overall survival, which makes the prediction of local treatment failure a crucial aspect of treatment planning. Understanding the factors that influence LC of brain metastases is imperative for optimizing treatment strategies and subsequently extending overall survival. Machine learning algorithms may help to identify factors that predict outcomes. Methods: This paper systematically reviews these factors associated with LC to select candidate predictor features for a practical application of predictive modeling. A systematic literature search was conducted to identify studies in which the LC of brain metastases is assessed for adult patients. EMBASE, PubMed, Web-of-Science, and the Cochrane Database were searched up to December 24, 2020. All studies investigating the LC of brain metastases as one of the endpoints were included, regardless of primary tumor type or treatment type. We first grouped studies based on primary tumor types resulting in lung, breast, and melanoma groups. Studies that did not focus on a specific primary cancer type were grouped based on treatment types resulting in surgery, SRT, and whole-brain radiotherapy groups. For each group, significant factors associated with LC were identified and discussed.. As a second project, we assessed the practical importance of selected features in predicting LC after Stereotactic Radiotherapy (SRT) with a Random Forest machine learning model. Accuracy and Area Under the Curve (AUC) of the Random Forest model, trained with the list of factors that were found to be associated with LC for the SRT treatment group, were reported.Results: The systematic literature search identified 6270 unique records. After screening titles and abstracts, 410 full texts were considered, and ultimately 159 studies were included for review. Most of the studies focused on the LC of the brain metastases for a specific primary tumor type or after a specific treatment type. Higher SRT radiation dose was found to be associated with better LC in lung cancer, breast cancer, and melanoma groups. Also, a higher dose was associated with better LC in the SRT group, while higher tumor volume was associated with worse LC in this group. The Random Forest model predicted the LC of brain metastases with an accuracy of 80% and an AUC of 0.84. Conclusion: This paper thoroughly examines factors associated with LC in brain metastases and highlights the translational value of our findings for selecting variables to predict LC in a sample of patients who underwent SRT. The prediction model holds great promise for clinicians, offering a valuable tool to predict personalized treatment outcomes and foresee the impact of changes in treatment characteristics such as radiation dose.<br/