A Decision Support System for Market Segmentation - A Neural Networks Approach

Market segmentation refers to the subdividing of a market into distinct subsets of customers where any subset may conceivably be selected as a market target to be reached with a distinct marketing mix [Kotler 1980]. The reason for segmenting a market is that consumers are often numerous, geographically dispersed, and heterogeneous, and therefore seek varying benefits from the products they buy. Consumers within a segment are expected to have homogeneous buying preferences whereas those in different segments tend to behave differently. By properly identifying the benefit segment of a firm\u27s product, the marketing manager can target the sales effort at specific groups of consumers rather than at the total population. The identification of consumer segments is of critical importance for key strategic issues in marketing involving the assessment of a firm\u27s opportunities and threats. The marketing manager must evaluate the potential of the firm\u27s products in the target segment and ultimately select the most promising strategy for the segment. In thisresearch, we introduce a new approach, a neural networks based method, to discover market segments and configure them into meaningful structures. The particular type of neural networks, the Self-Organizing Map networks, can be used as a decision support tool for supporting strategic decisions involving identifying and targeting market segments. The Self-Organizing Map (SOM) network, a variation of neural computing networks, is a categorization network developed by Kohonen. The theory of the SOM network is motivated by the observation of the operation of the brain. This paper presents the technique of SOM and shows how it may be applied as a clustering tool to market segmentation. A computer program for implementing the SOM neural networks is developed and the results will be compared with other clustering approaches. The study demonstrates the potential of using the Self-Organizing Map as the clustering tool for market segmentation

Broadband energy-efficient optical modulation by hybrid integration of silicon nanophotonics and organic electro-optic polymer

Silicon-organic hybrid integrated devices have emerging applications ranging from high-speed optical interconnects to photonic electromagnetic-field sensors. Silicon slot photonic crystal waveguides (PCWs) filled with electro-optic (EO) polymers combine the slow-light effect in PCWs with the high polarizability of EO polymers, which promises the realization of high-performance optical modulators. In this paper, a broadband, power-efficient, low-dispersion, and compact optical modulator based on an EO polymer filled silicon slot PCW is presented. A small voltage-length product of V{\pi}*L=0.282Vmm is achieved, corresponding to an unprecedented record-high effective in-device EO coefficient (r33) of 1230pm/V. Assisted by a backside gate voltage, the modulation response up to 50GHz is observed, with a 3-dB bandwidth of 15GHz, and the estimated energy consumption is 94.4fJ/bit at 10Gbit/s. Furthermore, lattice-shifted PCWs are utilized to enhance the optical bandwidth by a factor of ~10X over other modulators based on non-band-engineered PCWs and ring-resonators.Comment: 12 pages, 4 figures, SPIE Photonics West Conference 201

Spin dynamics near a putative antiferromagnetic quantum critical point in Cu substituted BaFe2_2As2_2 and its relation to high-temperature superconductivity

We present the results of elastic and inelastic neutron scattering measurements on non-superconducting Ba(Fe${_{0.957}}$Cu${_{0.043}}$)${_2}$As${_2}$, a composition close to a quantum critical point between AFM ordered and paramagnetic phases. By comparing these results with the spin fluctuations in the low Cu composition as well as the parent compound BaFe$_2$As$_2$ and superconducting Ba(Fe$_{1-x}$Ni$_x$)$_2$As$_2$ compounds, we demonstrate that paramagnon-like spin fluctuations are evident in the antiferromagnetically ordered state of Ba(Fe$_{0.957}$Cu$_{0.043}$)$_2$As$_2$, which is distinct from the AFM-like spin fluctuations in the superconducting compounds. Our observations suggest that Cu substitution decouples the interaction between quasiparticles and the spin fluctuations. We also show that the spin-spin correlation length, ${\xi(T)}$, increases rapidly as the temperature is lowered and find ${\omega/T}$ scaling behavior, the hallmark of quantum criticality, at an antiferromagnetic quantum critical point.Comment: 10 pages, 7 figure

A quantitative approach for measuring the reservoir of latent HIV-1 proviruses.

A stable latent reservoir for HIV-1 in resting CD4+ T cells is the principal barrier to a cure1-3. Curative strategies that target the reservoir are being tested4,5 and require accurate, scalable reservoir assays. The reservoir was defined with quantitative viral outgrowth assays for cells that release infectious virus after one round of T cell activation1. However, these quantitative outgrowth assays and newer assays for cells that produce viral RNA after activation6 may underestimate the reservoir size because one round of activation does not induce all proviruses7. Many studies rely on simple assays based on polymerase chain reaction to detect proviral DNA regardless of transcriptional status, but the clinical relevance of these assays is unclear, as the vast majority of proviruses are defective7-9. Here we describe a more accurate method of measuring the HIV-1 reservoir that separately quantifies intact and defective proviruses. We show that the dynamics of cells that carry intact and defective proviruses are different in vitro and in vivo. These findings have implications for targeting the intact proviruses that are a barrier to curing HIV infection

Financial Toxicity in Cancer Patients and Subsequent Risk of Repeat Acute Care Utilization

BACKGROUND: Acute care (AC) visits by cancer patients are costly sources of healthcare resources and can exert a financial burden of oncology care both for individuals with cancer and healthcare systems. We sought to identify whether cancer patients who reported more severe initial financial toxicity (FT) burdens shouldered excess risks for acute care utilization. METHODS: In 225 adult patients who participated in the Economic Strain and Resilience in Cancer (ENRICh) survey study of individuals receiving ambulatory cancer care between March and September 2019, we measured the baseline FT (a multidimensional score of 0-10 indicating the least to most severe global, material, and coping FT burdens). All AC visits, including emergency department (ED) and unplanned hospital admissions, within 1-year follow-up were identified. The association between the severity of FT and the total number of AC visits was tested using Poisson regression models. RESULTS: A total of 18.6% ( CONCLUSION: In this prospective study of acute oncology care utilization outcomes among adult cancer patients, FT was a predictor of a higher burden of acute care visits. Patients with severely depleted material and also practical and social coping resources were at particular risk for repeated visits. Future studies are needed to identify whether early FT screening and intervention efforts may help to mitigate urgent acute care utilization burdens

The IMPROVEDD VTE risk score: Incorporation of D-dimer into the IMPROVE score to improve venous thromboembolism risk stratification

Background The IMPROVE score is a validated venous thromboembolism (VTE) assessment tool to risk stratify hospitalized, medically ill patients based on clinical variables. It was hypothesized that addition of D-dimer measurement to derive a new IMPROVEDD score would improve identification of at risk of VTE. Methods The association of the IMPROVE score and D-dimer ≥ 2 × the upper limit of normal (ULN) with the risk of symptomatic deep vein thrombosis, nonfatal pulmonary embolism, or VTE-related death was evaluated in 7,441 hospitalized, medically ill patients randomized in the APEX trial. Based on the Cox regression analysis, the IMPROVEDD score was derived by adding two points to the IMPROVE score if the D-dimer was ≥ 2 × ULN. Results Baseline D-dimer was independently associated with symptomatic VTE through 77 days (adjusted HR: 2.22 [95% CI: 1.38–1.58], p = 0.001). Incorporation of D-dimer into the IMPROVE score improved VTE risk discrimination (ΔAUC: 0.06 [95% CI: 0.02–0.09], p = 0.0006) and reclassification (continuous NRI: 0.34 [95% CI: 0.17–0.51], p = 0.001; categorical NRI: 0.13 [95% CI: 0.03–0.23], p = 0.0159). Patients with an IMPROVEDD score of ≥2 had a greater VTE risk compared with those with an IMPROVEDD score of 0 to 1 (HR: 2.73 [95% CI: 1.52–4.90], p = 0.0007). Conclusion Incorporation of D-dimer into the IMPROVE VTE risk assessment model further improves risk stratification in hospitalized, medically ill patients who received thromboprophylaxis. An IMPROVEDD score of ≥2 identifies hospitalized, medically ill patients with a heightened risk for VTE through 77 days.</jats:p