That’s Not Who I Am! Investigating the Role of Uniqueness and Belongingness for Designing Successful Personalized Recommendations

Although many firms rely on personalization to enhance the user experience of their digital service, their efforts might backfire if users feel misunderstood by the personalized offerings. So far, the psychological processes underlying the phenomenon of feeling misunderstood by personalization systems and potential means to alleviate this perception remain largely uninvestigated. Building on the psychological concepts of uniqueness and belongingness, we propose a framework to investigate how transparency impacts users’ feeling of being misunderstood by personalization systems. To test our research model, we conduct an online experiment using Spotify’s “Discover Weekly” playlist. The results show that considering not only users’ uniqueness but especially their belongingness is decisive to avoid misunderstanding. Further, we find that transparent explanations of the system’s inner workings elicit a feeling of control among users, which fosters the perception that both users’ uniqueness and belongingness are considered, resulting in less misunderstanding and continued usage

Modellierung und Analyse individuellen Konsumentenverhaltens mit probabilistischen Holonen

Der Schwerpunkt dieser Arbeit liegt in der Entwicklung eines agentenbasierten, probabilistischen Konsumentenverhaltensmodells zur Repräsentation und Analyse individuellen Kaufverhaltens. Das Modell dient zur Entscheidungsunterstützung im Handel und speziell im Customer Relationship Management (CRM). Als Modellgrundlage wird eine Klasse probabilistischer Agenten eingeführt, die sich zu Holonen zusammenschließen können und deren Wissensbasen erweiterte Bayes';sche Netze (Verhaltensnetze) sind. Mit Hilfe probabilistischer Holone werden Kundenagenten entwickelt, die einzelne reale Kundenmodellieren. Dazu werden kundenindividuelle Verhaltensmuster unter Berücksichtigung von Domänenwissen aus historischen Kundendaten extrahiert und als nichtlineare Abhängigkeiten zwischen Einflussfaktoren und artikelbezogenen Kundenreaktionen in Verhaltensnetzen repräsentiert. Ein Kundenagent ist dabei ein Holon aus mehreren so genannten Feature-Agenten, die jeweils einzelne Kundeneigenschaften repräsentieren, entsprechende Feature-Verhaltensnetze verwalten und durch Interaktion das Gesamtverhalten des Kunden bestimmen. Die Simulation des Verhaltens besteht aus der Ermittlung von Kundenreaktionen auf vorgegebene Einkaufsszenarien mit Hilfe quantifizierbarer probabilistischer Schlussfolgerungen. Kundenagenten können sich durch Holonisierung zu Kundengruppenagenten zusammenschließen, die unterschiedliche Aggregationen des Kaufverhaltens der Gruppenmitglieder repräsentieren. Zur Bestimmung gleichartiger Kunden werden auf Basis der Verhaltensnetze mehrere Ähnlichkeitsanalyseverfahren sowie verhaltensbezogene Ähnlichkeitsmaße zum Vergleich des dynamischen Kaufverhaltens entwickelt. Bestehende Klassifikations- und Clusteringverfahren werden anschließend so erweitert, dass sie neben klassischen Attributvektoren verhaltensnetzbasierte Repräsentationen als Vergleichsgrundlage verwenden können. Darüber hinaus werden Verfahren zur Zuordnung anonymer Kassenbons zu vorgegebenen Kundengruppen entwickelt, um Ergebnisse von Kundensimulationen auf die Gesamtheit der anonymen Kunden eines Unternehmens übertragen zu können. Nutzen und Qualität der entwickelten Modelle, Verfahren und Maße werden mit Hilfe einer umfangreichen Software-Implementierung anhand mehrerer Anwendungsbeispiele aus der Praxis demonstriert und in einigen Fallstudien evaluiert — basierend auf realen Daten eines deutschen Einzelhandelsunternehmens.The focus of this work is the development of an agent-based, probabilistic model for representing and analysing individual consumer behaviour. The model provides a basis for decision making in marketing and especially in customer relationship management (CRM). As foundation of the model, a class of probabilistic agents is introduced. These agents can be merged to holonic agents (holons) and have probabilistic knowledge bases adapted from Bayesian networks (behaviour networks). An individual customer is modelled as a customer agent which is a probabilistic holon consisting of several feature agents. A feature agent represents a particular property (feature) of the customer';s behaviour and encapsulates appropriate feature-related behaviour networks. The total behaviour of a customer agent is determined by interaction of its feature agents. Individual behaviour patterns of a customer are extracted from real data — in consideration of given domain knowledge — and are represented within behaviour networks as non-linear dependencies between influencing factors and the customer';s product-related reactions. Behaviour simulation is realised by evaluation of expected reactions of customers on given shopping scenarios based on quantifiable, probabilistic reasoning. Customer agents are able to join to customer group agents which represent different behaviour aggregations of their members. Based on behaviour networks, several behaviour-related methods of analysis as well as distance measures are developed to identify homogeneous customers on the basis of their dynamic shopping behaviour. Subsequently, existing vector-based methods of classification and clustering are extended by these behaviour-related methods and measures. In addition, methods are developed to assign anonymous receipts to given customer groups in order to extent customer-related simulation results to anonymous customers of a company. Benefits and quality of the developed models, methods and measures, which are implemented within a complex software system, are shown by practical examples and evaluated in several case studies — based on real data from a German retailer

Enhanced Transmission in Rolled-up Hyperlenses utilizing Fabry-Pe\'rot Resonances

We experimentally demonstrate that the transmission though rolled-up metal/semiconductor hyperlenses can be enhanced at desired frequencies utilizing Fabry-P\'erot resonances. By means of finite difference time domain simulations we prove that hyperlensing occurs at frequencies of high transmission.Comment: 3 pages, 3 figure

Use of Nuclear Magnetic Resonance Imaging Angiography to Follow-Up Arterial Remodeling in an Animal Model

Appropriately sized arteries in small animals may be possible models for studying the remodeling process as occurs after arterial balloon injury in humans. Magnetic resonance imaging (MRI) is able to noninvasively image tissue in vivo. To date, small animal angiog raphy models have mostly used research-dedicated instruments and resolution, which are not universally available.Experiments were carried out on a rat aorta model of remodeling in vivo (n=40). Arteries were injured by oversized balloon dilation; control arteries were uninjured. Angiography imaging was performed immediately before sacrifice with an unmodified clinical MRI unit, a 1.5 Tesla MR tomograph with a 20-cm-diameter coil. Longitudinal MRI pictures of the aorta and morphometry of tissue sections to measure luminal and arterial wall areas were analyzed with use of computer-assisted techniques.Comparison of dimensions demonstrated correlation between MRI and histology measurements of the lumen. MRI and morphometry showed a gradual increase in mean luminal area over 6 weeks following injury. The lumen increase correlated with total arterial area and thickness.In this rat aorta model, remodeling documented at histology was followed-up in vivo. The use of such clinical MRI scanners has potential to reduce animal numbers needed to follow-up the remodeling process after therapeutic intervention

Gain in Three-Dimensional Metamaterials utilizing Semiconductor Quantum Structures

We demonstrate gain in a three-dimensional metal/semiconductor metamaterial by the integration of optically active semiconductor quantum structures. The rolling-up of a metallic structure on top of strained semiconductor layers containing a quantum well allows us to achieve a three-dimensional superlattice consisting of alternating layers of lossy metallic and amplifying gain material. We show that the transmission through the superlattice can be enhanced by exciting the quantum well optically under both pulsed or continuous wave excitation. This points out that our structures can be used as a starting point for arbitrary three-dimensional metamaterials including gain

Diagnostic Value of Contrast-Enhanced Magnetic Resonance Imaging and Single-Photon Emission Computed Tomography for Detection of Myocardial Necrosis Early After Acute Myocardial Infarction

ObjectivesThis study sought to evaluate the diagnostic value of contrast-enhanced magnetic resonance imaging (CMR) and single-photon emission computed tomography (SPECT) for detection of myocardial necrosis after acute myocardial infarction (AMI).BackgroundSingle-photon emission computed tomography is widely accepted in the clinical setting for detection and estimation of myocardial infarction. Contrast-enhanced magnetic resonance imaging offers technical advantages and is therefore a promising new method for identification of infarcted tissue.MethodsSeventy-eight patients with AMI were examined by CMR and SPECT 7 days after percutaneous coronary intervention. Contrast-enhanced magnetic resonance imaging and SPECT images were scored for presence and location of infarction using a 17-segment model. Results were compared with the peak troponin T level, electrocardiographic, and angiographic findings.ResultsAcute myocardial infarction was detected significantly more often by CMR than SPECT (overall sensitivity: 97% vs. 87%; p = 0.008). Sensitivity of CMR was superior to SPECT in detecting small infarction as assessed by the peak troponin T level <3.0 ng/ml (92 vs. 69%; p = 0.03), and infarction in non-anterior location (98% vs. 84%; p = 0.03). Non–Q-wave infarctions were more likely to be detected by CMR (sensitivity 85% vs. 46%; p = 0.06). While CMR offered high sensitivity for detection of AMI irrespective of the infarct-related artery, SPECT was less sensitive, particularly within the left circumflex artery territory.ConclusionsContrast-enhanced magnetic resonance imaging is superior to SPECT in detecting myocardial necrosis after reperfused AMI because CMR detects small infarcts that were missed by SPECT independent of the infarct location. Thus, CMR is attractive for accurate detection and assessment of the myocardial infarct region in patients early after AMI

Direct comparison of activation maps during galvanic vestibular stimulation: A hybrid H-2[(15) O] PET-BOLD MRI activation study

Previous unimodal PET and fMRI studies in humans revealed a reproducible vestibular brain activation pattern, but with variations in its weighting and expansiveness. Hybrid studies minimizing methodological variations at baseline conditions are rare and still lacking for task-based designs. Thus, we applied for the first time hybrid 3T PET-MRI scanning (Siemens mMR) in healthy volunteers using galvanic vestibular stimulation (GVS) in healthy volunteers in order to directly compare (H2O)-O-15-PET and BOLD MRI responses. List mode PET acquisition started with the injection of 750 MBq (H2O)-O-15 simultaneously to MRI EPI sequences. Group-level statistical parametric maps were generated for GVS vs. rest contrasts of PET, MR-onset (event-related), and MR-block. All contrasts showed a similar bilateral vestibular activation pattern with remarkable proximity of activation foci. Both BOLD contrasts gave more bilateral wide-spread activation clusters than PET;no area showed contradictory signal responses. PET still confirmed the right-hemispheric lateralization of the vestibular system, whereas BOLD-onset revealed only a tendency. The reciprocal inhibitory visual-vestibular interaction concept was confirmed by PET signal decreases in primary and secondary visual cortices, and BOLD-block decreases in secondary visual areas. In conclusion, MRI activation maps contained a mixture of CBF measured using (H2O)-O-15-PET and additional non-CBF effects, and the activation-deactivation pattern of the BOLD-block appears to be more similar to the (H2O)-O-15-PET than the BOLD-onset

Bio-inspired micro-to-nanoporous polymers with tunable stiffness

Background: Inspired by structural hierarchies and the related excellent mechanical properties of biological materials, we created a smoothly graded micro- to nanoporous structure from a thermoplastic polymer. Results: The viscoelastic properties for the different pore sizes were investigated in the glassy regime by dynamic flat-punch indentation. Interestingly, the storage modulus was observed to increase with increasing pore-area fraction. Conclusion: This outcome appears counterintuitive at first sight, but can be rationalized by an increase of the pore wall thickness as determined by our quantitative analysis of the pore structure. Therefore, our approach represents a non-chemical way to tune the elastic properties and their local variation for a broad range of polymers by adjusting the pore size gradient