Prognose der Verkehrslage in der Region Hannover

Die primäre Anforderung der Verkehrsteilnehmer im Bereich des Straßenverkehrs ist die Kenntnis der aktuellen Verkehrslage. Diese basiert in der Regel auf der wirklich benötigten Reisezeit von sehr vielen Verkehrsteilnehmern, deren Daten häufig im Kontext von Routingdiensten abgegriffen werden.

Im Rahmen von Data4UrbanMobility wurden Werkzeuge entwickelt um eine ganglineinbasierte Prognose der Verkehrslage zu ermöglichen. Die folgende Abbildung zeigt eine Oberfläche auf der typische Ganglinienverläufe und Ausreißer visualisiert werden.

Die Prognose der Verkehrslage kann dann mittels einer Karte für den Endnutzer visualisert werden:

Erste Version der MIC-App bereitgestellt

Eine erste Version der MIC-App (Move in the City) konnte allen Partnerinnen und Partnern des Projekts und einer geschützten Nutzer*innengruppe der Öffentlichkeit zur Verfügung gestellt werden. Die mobile App MiC ist ein Instrument zur Datenerhebung.

Dabei verknüpft MiC – eine Entwicklung des Institute for Sustainable Urbanism ISU der TU Braunschweig und Projektionisten GmbH Hannover – das wachsende Bewusstsein und die Notwendigkeit für digitale Bürger*innenrechte mit den Potentialen mittels der Auswertung großer Datenmengen neue Formen der menschzentrierten Entwicklung von Stadt und Mobilität zu ermöglichen stellt eine Möglichkeit dar, sich aktiv als Bürgerwissenschaftlerin und Bürgerwissenschaftler an der Forschung und Entwicklung der Mobilität für alle in der Stadt der Zukunft zu beteiligen.

MiC erhebt – durch die Nutzerinnen und Nutzer gesteuert – Daten zu Strecken und Art der Fortbewegung. Diese Daten werden pseudonymisiert, so dass ein Rückschluss auf die jeweilige Person nicht mehr möglich ist. Wichtig ist die Vielzahl der Nutzerinnen und Nutzer – nicht die einzelne Bewegung. Die Stadt der Zukunft zeichnet sich aus durch den barrierearmen Zugang zu Mobilität und Erreichbarkeit für alle. Der holistische Ansatz der Forscherinnen und Forscher des Institute for Sustainable Urbanism ISU (TU Braunschweig) sowie der Projektbeteiligten betrachtet Stadt dabei auf verschiedenen Maßstabsebenen und bringt intelligente Planungen – wie z.B. die 5-Minuten Stadt –, Städtebau und innovative Technologien zusammen. Für ein umfassendes Verständnis individueller Mobilität und darauf aufbauende neue Methoden und Werkzeuge für integrierte Verkehrs- und Stadtplanung werden mittels der MiC-App uns umfangreiche und detaillierte Daten darüber geliefert, wie und auf welchem Wege wir uns in der Stadt fortbewegen.

Entwicklungsstand:

In der ersten Version ermöglicht das Stadtforschungstool MiC den Nutzer*innen durch eine einfach Handhabung das Starten und Beenden der „Tracking-Time“ (Bild 1). Wichtig ist, die Nutzer*innen entscheidet selber über den Zeitraum. Als erstes Ergebnis für die Nutzer*innen steht eine Zusammenfassung ihrer bisher aufgezeichneten Routen (Bild2). In den Einstellung (Bild 3) kann der Nutzer sich aktiv an Feedback beteiligen (Bild 4) sowie seinen Account und somit seiner zur Verfügung gestellten Daten löschen (Bild 5).

von links nach recht: Bild1-5 MIC App Interface – Attribution-NonCommercial-ShareAlike 4.0 International  (CC BY-NC-SA 4.0)

Die aktuelle Weiterentwicklung sieht eine Visualisierung der Routen für den jeweiligen Nutzer vor.

Um Teil der Testgruppe zu werden ist zur Zeit noch eine Anmeldung unter: www.mic-app.org notwendig. Die Anwendung ist nicht frei im App Store / GooglePlay Store zu erhalten.

Auf der Internetseite www.mic-app.org wird zusätzlich detailliert auf häufige Fragen (FAQ) zur Anwendung sowie über Entwicklungen und Neuheiten informiert

D4UM Plattform und Dashboard V2

Die neue Version der Plattform inklusive des Dashboards gibt noch detailliertere Auskünfte über die Verkehrssituation

Die farblich unterschiedlichen Label lassen eine schnelle Unterscheidung zwischen den verschiedenen Event typen zu. Durch das klicken auf eines der Events wird der typically affected subgraph angezeigt für diesen Eventtyp.

Beispiele: Visualisierungen eines Konzerts und eines Fußballspiels

Zusätzlich gibt der Graph in der oberen rechten Ecke Auskunft über die Verkehrssituation vor und nach dem Eventstart.

{API}
Es wurden die API Endpunkte mit zusätzlichen Information erweitert.
Diese werden mittels der als Teil der Forschung entwickelten Modellen erstellt.

Erste Version der D4UM-App bereitgestellt

Eine erste Version der D4UM-App konnte allen Partnern des Projekts zur Verfügung gestellt werden. Die App stellt eine Möglichkeit dar, sich Fahrtauskünfte mit dem öffentlichen Personennahverkehr in Niedersachsen und Bremen (Datengrundlage: EFA – elektronische Fahrplanauskunft für Niedersachsen und Bremen) ausgeben zu lassen. Im Fokus stand hierbei, dass der Nutzer schnell und einfach an die für ihn wichtigen Informationen gelangen kann, um so seine Reise möglichst simpel planen zu können.

Folgende Funktionen dienen dabei in der ersten Version der schnellen Auskunft:

Abfahrten und Verbindungen

Über die Funktion Abfahrten lassen sich Abfahrtszeiten an einer bestimmten oder an nahegelegenen Haltestellen ermitteln. Unter Verbindungen können hingegen Fahrtvorschläge von einem Startpunkt (Adresse oder Haltestelle) zu einem Zielpunkt gesucht werden. Zeiten stehen dabei auch in Echtzeit zur Verfügung, sodass auch Verspätungen direkt von dem Nutzer erkannt werden können.

Karte

Über die Karte sind alle Haltestellen zu finden, sodass sich der Nutzer einen Überblick über die nähere Umgebung oder auch den Weg zur Haltestelle oder einem Ziel verschaffen kann.

Wird auf der Karte auf ein Haltestellensymbol oder den zugehörigen Haltestellennamen geklickt, öffnet sich der Abfahrtsmonitor zu dieser Haltestelle. Die nächsten Abfahrten können somit auch über diesen Weg aufgerufen werden.

Darüber hinaus kann sich der Nutzer auch den Verlauf seiner Fahrt anzeigen lassen.

Menü/Einstellungen

Weitere Funktionen und Einstellungen finden sich ergänzend im Menü der App.

Der Nutzer bekommt hier zum einen die Möglichkeit, dass erweiterte Einstellungen zu den Suchanfragen bei Verbindungen oder Abfahrten vorgenommen werden können, und zum anderen, dass er weitere Features verwenden kann. Darunter befindet sich zum Beispiel das Feedbackformular. Hierüber kann unkompliziert Kontakt mit den Entwicklern der D4UM-App per Mail aufgenommen werden. Icons ermöglichen es, dass ein Eindruck zu der App übermittelt werden kann. Ein weiteres Feld für Freitext bietet zudem Platz für individuelle Kritik und einer Meinung zu der App. So kann in Zukunft kundennah an der App weiterentwickelt und einfach auf Wünsche und Meinungen reagiert werden.

Quantifizierungen und Vorhersage von Auswirkungen von Veranstaltungen

Neue Data4UrbanMobility-Forschungsergebnisse ermöglichen es, die räumlichen Auswirkungen von Veranstaltungen zu quantifizieren und vorherzusagen. Dazu werden zusammenhängende, betroffene Straßenabschnitte in der Nähe von Veranstaltungen identifiziert. Auf dieser Grundlage kann dann die räumliche Auswirkung quantifiziert werden. Das Verfahren ist in der folgenden Grafik dargestellt.

(Karte von https://www.openstreetmap.org)

Hier in Gelb markiert ist eine Veranstaltung, in Rot betroffene Straßenabschnitte und in Dunkelblau die gemessene Auswirkung. Weiterhin wurden Verfahren des Maschinellen Lernens angewandt, um diese Auswirkungen zu prognostizieren. Dabei konnte der Fehler gegenüber bestehenden state-of-the-art Ansätzen um bis zu 40% verringert werden.

D4UM – Plattform V1 fertiggestellt

Die erste Version der Data4UrbanMobility Plattform wurde fertiggestellt. Dazu wurde zunächst eine 3-Schichten Architektur der Plattform konzipiert und implementiert. Die Plattform bietet RESTfull Webservices für Mobilitätsapplikationen wie Dashboard-Anwendungen oder Apps an. Als erste Beispielanwendung wurde dazu eine interaktive Karte entwickelt, die die Auswirkungen von Veranstaltungen visualisiert. Ein Ausschnitt aus der Anwendung ist im folgenden Screenshot zu sehen.

Zu sehen sind 4 Veranstaltungen in Hannover. Die Farben entsprechen dabei unterschiedlichen Veranstaltungsarten (etwa Konzerte, Messen, Fußballspiele). Die Kreise visualisieren die räumlichen Auswirkungen, die diese Veranstaltungen auf den Verkehr hatten.

Umfangreicher Anforderungskatalog
Die Data4UrbanMobility Anforderungsanalyse umfasst die Erfassung der Anforderungen der Anwendungspartner Region Hannover (RH) und Wolfsburg AG (WAG), sowie der nicht-funktionalen Anforderungen. Aus den Anforderungen der AnwendungspartnerInnen (RH und WAG), die von MOMA erhoben wurden, sind von L3S Forschungsfragen für die Datenanalyse abgeleitet worden, die sich speziell auf die Informationsbedürfnisse der AnwenderInnen beziehen und im weiteren Projektverlauf adressiert werden.

Die aktuelle Forschungsfragen adressieren insbesondere:

1.  Automatische Verifikation von Verkehrswarnmeldungen und Prognose von deren Auswirkungen.
2.  Identifikation von Veranstaltungen und Prognose verkehrsrelevanter Auswirkungen.
3. Korrelation von IV-Reiseflussdaten, EFA-Querylogs, Warnmeldungen und Twitterfeeds.
4. Bestimmung von optimalen Reisezeitpunkte.

Wachsende Datensammlung

Das ISU hat einen umfassende Datenmatrix mit potentiellen Quellen für mobilitätsrelevante Daten  erstellt. Das von L3S entwickelte Data4UrbanMobility Datenmodell beschreibt alle projektrelevanten Daten und setzt diese in Verbindung um die Daten sowohl für die Analyse als auch für die Anwendungen und Apps einheitlich zur Verfügung zu stellen. Die ausgewählten Datenquellen sind von L3S in das Data4UrbanMobility Datenmodell überführt. Einige der Datenquellen wie EFA-logs, und IV-Daten sind dabei auf deren Qualität geprüft worden.

Um die Datenintegration zu ermöglichen sind Werkzeuge zur Extraktion der relevanten Daten aus Mobilitätsrelevanten Datenquellen entwickelt worden:

• Straßen- und Graphextraktion aus OpenStreetMap
• EFA-Anfragen Bulkloader für die Extraktion der ÖPNV Anfragen aus EFA Logs
• Integration von Daten aus dem Zentralen Haltestellen Verzeichnis (ZHV) inklusive Verknüpfung der Daten mit den EFA-Anfragen

Die aktuelle Datensammlung (Stand: 12 Dezember 2017) umfasst:

EFA-Logs: 17 Mio. Suchanfragen
IV-Daten: 174 Tsd. Straßen, alle 15 Minuten
GTFS-Daten: 90 Tsd. Haltestellen, 2,6 Tsd. Routen
Wetter: Radolan Regenraster
Twitter: 2,5 Mio. Tweets ab Juni 2017

OSM: 440 Tsd. Straßen
Events: 21 Tsd. Veranstaltungen (14.08.2016-17.07.2018)

Warnmeldungen: 13 Tsd. Warnmeldungen (ab 06.2017)

Visualisierungen der ÖPNV Informationen

Zur intuitiven Analyse von mobilitätsrelevanten Informationen, insbesondere von ÖPNV Informationen, wurde von den PROJEKTIONISTEN (PROJ) eine Dashboard-Webapplikation konzipiert. Erste Prototypen visualisieren Anfragen an das regionale Fahrplanauskunftsystem EFA (www.efa.de) und dienen als Ausgangsbasis für explorative Analysen und die Implementierung der produktiven Version des Dashboards. Im Folgenden ist eine im Dashboard integrierte Visualisierung der häufigsten Start- und Ziel-punkte zu sehen.

Analysen der EFA-Logs
Als erste Forschungsfrage wird aktuell die Analyse der Auswirkungen der Veranstaltungen auf dem ÖPNV mit Methoden des Maschinellen Lernens analysiert.  Hierzu wurden in explorativen Datenanalysen der Einfluss von großen Veranstaltungen wie z.B. Fussballspielen und mittelgroßen Veranstaltungen, etwa Konzerte, auf Anfragen an den ÖPNV betrachtet.  Als Grundlage für umfassende Analysen wurden mit Hilfe visueller Methoden exemplarisch Korrelation zwischen ÖPNV-Nachfrage und Veranstaltungszeiträumen detektiert.

Dabei zeichnen sich z.B. für Hannovers Innenstadt klare, sternförmige Muster ab, die zentrale Mobilitätsknoten identifizieren.

Das Bild stellt die Luftlinie zwischen Start- und Ziel-Ort der Anfragen dar. Dabei entsprechen dunklere Farben häufigeren Strecken. Hier werden deutlich Hannover Hauptbahnhof und Hannover Kröpcke (die zentrale U-Bahn Station) als Mobilitätsknoten identifiziert.

Analysen der Nachfrage für einzelne Stationen lassen wochentagspezifische Muster erkennen.

Hier dargestellt sind die durchschnittliche Anzahl der Anfragen mit der Ziel-Haltestelle “Hannover Stadionbrücke”. Zu erkennen sind vor allem Unterschiede zwischen Werktagen und dem Wochenende.

Auch der Einfluss von Veranstaltungen kann mit Hilfe der Anfragen visualisiert werden:

Dargestellt sind die Anzahl der Anfragen mit Ziel “Hannover Stadionbrücke” für Mittwoch, den 26.04.2017 (Orange) sowie die durchschnittlichen Anzahl von Anfragen, die mittwochs mit gleichem Ziel gestellt wird (Blau).
An diesem Tag fand in einer nahe gelegenen Konzerthalle ein Konzert statt, das um 20 Uhr begann. Die signifikante Abweichung zwischen 17 und 19 Uhr wurde sehr wahrscheinlich von den anreisenden Gästen verursacht wurde. Dies illustriert, dass Anfragen an den ÖPNV eine wertvolle Informationsquelle sein können, um Prognosen über die Auswirkung von Veranstaltungen auf Mobilität zu erstellen.

• Estimation of Cardiovascular Risk Using SCORE2, REGICOR and Vascular Age Scales in Spanish Healthcare Workers: A Retrospective Longitudinal Study. Marcos, Pedro Javier Tárraga; López, Pedro Juan Tárraga; López-González, Ángel Arturo; Rifá, Emilio Martínez-Almoyna; Oliveira, Hernán Paublini; Sánchez, Cristina Martorell; Ramírez-Manent, José Ignacio (2025). 13(4) 375-.

  Background/Objectives: Cardiovascular diseases (CVD) are one of the major public health concerns worldwide due to their high morbidity and mortality rates. This situation has necessitated the development of tools to assess cardiovascular risk (CVR) in order to prevent the onset of CVD. The aim of this study is to assess how sociodemographic variables and health habits are associated with the values of CVR scales, such as REGICOR, SCORE2, and vascular age. Methodology: This is a descriptive and cross-sectional study involving 44,939 Spanish healthcare workers, where the association between age, sex, type of work, smoking, physical activity, and Mediterranean diet with CVR scales such as REGICOR, SCORE2, and vascular age was evaluated. Results: All the variables analyzed showed an association with the occurrence of moderate-high values in all three CVR scales. Age was the variable that showed the highest odds ratio values: 13.446 (95% CI 11.16-14.77) for REGICOR, 13.90 (95% CI 12.01-15.81) for vascular age, and 14.12 (95% CI 12.01-16.23) for SCORE2. Conclusions: The profile of a healthcare worker with the highest risk of presenting moderate-high values on all three CVR scales would be a male over 60 years old, a nursing assistant or orderly, a smoker, sedentary, and with low adherence to the Mediterranean diet.
• Body Fat and Visceral Fat Values in Spanish Healthcare Workers: Associated Variables. Tárraga Marcos, Pedro Javier; López-González, Ángel Arturo; Martínez-Almoyna Rifá, Emilio; Paublini Oliveira, Hernán; Martorell Sánchez, Cristina; Tárraga López, Pedro Juan; Ramírez-Manent, José Ignacio (2025). 17(4) 649-.

  BACKGROUND/OBJECTIVES: Excessive body adiposity is a significant public health challenge on a global scale. This study aimed to investigate the association between various sociodemographic factors and healthy lifestyle habits and the presence or absence of elevated body adiposity levels. METHODOLOGY: Two studies were conducted, a retrospective longitudinal study and a cross-sectional descriptive study. The analysis included 44,939 healthcare workers, categorised into four professional groups, to explore the relationship between age, sex, smoking, physical activity, and adherence to the Mediterranean diet and body adiposity, assessed as elevated body fat (BF) and visceral fat (VF) levels. Descriptive statistics encompassed categorical and quantitative variables, analysed using frequencies, Student's t-tests, chi-square tests, and multinomial logistic regression models. Associations, concordances, and correlations were further examined using logistic regression and Cohen's and Pearson's kappa coefficients. RESULTS: Age, sex, and physical activity were the factors most strongly associated with elevated BF and VF levels. Odds ratios (ORs) indicated the following significant associations: individuals aged 60 years and older exhibited ORs of 6.71 (95% CI: 5.68-7.74) for BF and 12.18 (95% CI: 10.01-14.26) for VF; male sex was associated with ORs of 2.21 (95% CI: 2.06-2.36) for BF and 12.51 (95% CI: 11.29-13.74) for VF. Sedentary behaviour was linked to ORs of 3.69 (95% CI: 3.41-3.97) for BF and 4.20 (95% CI: 3.78-4.63) for VF. Among healthcare professionals, nursing assistants and orderlies demonstrated the highest levels of adipose tissue accumulation. CONCLUSIONS: Elevated BF and VF levels among healthcare personnel are significantly associated by lifestyle factors, sex, and age, with the most pronounced risk observed in nursing assistants and orderlies. Further research focusing on the causal relationships between lifestyle behaviours and adiposity in this population will provide valuable insights and support the design of targeted preventive strategies to mitigate its prevalence.
• Risk of Insulin Resistance in 44,939 Spanish Healthcare Workers: Association with Sociodemographic Variables and Healthy Habits. Tárraga Marcos, Pedro Javier; López-González, Ángel Arturo; Martínez-Almoyna Rifá, Emilio; Paublini Oliveira, Hernán; Martorell Sánchez, Cristina; Tárraga López, Pedro Juan; Ramírez-Manent, José Ignacio (2025). 13(2) 33-.

  Introduction: Insulin resistance (IR) is a highly prevalent pathophysiological entity implicated in the development of a wide variety of metabolic, cardiovascular, and endocrine disorders. The aim of this study is to assess the association between sociodemographic variables and healthy habits with IR risk scales. Methodology: This dual study, incorporating both longitudinal-retrospective and cross-sectional designs, analyzed healthcare workers across four professional categories (physicians, nurses, healthcare technicians, and auxiliary personnel). It examined the association of age, sex, professional category, smoking status, physical activity, and adherence to the Mediterranean diet with elevated scores on insulin resistance risk scales. Results: All the variables analyzed were associated with the presence of elevated values of the IR scales, with age, sex, and physical activity showing the strongest association (reflected in the odds ratio values). Conclusions: The profile of an individual with a higher risk of presenting elevated values of the IR risk scales would be an elderly male auxiliary health worker who is a smoker and is physically inactive, with a low adherence to the Mediterranean diet.
• Compartment model of strategy-dependent time delays in replicator dynamics. Fic, Małgorzata; Bastian, Frank; Miȩkisz, Jacek; Gokhale, Chaitanya S. (2025). 601 112044.

  Real-world processes often exhibit temporal separation between actions and reactions - a characteristic frequently ignored in many modelling frameworks. Adding temporal aspects, like time delays, introduces a higher complexity of problems and leads to models that are challenging to analyse and computationally expensive to solve. In this work, we propose an intermediate solution to resolve the issue in the framework of evolutionary game theory. Our compartment-based model includes time delays while remaining relatively simple and straightforward to analyse. We show that this model yields qualitatively comparable results with models incorporating explicit delays. Particularly, we focus on the case of delays between parents’ interaction and an offspring joining the population, with the magnitude of the delay depending on the parents’ strategy. We analyse Stag-Hunt, Snowdrift, and the Prisoner’s Dilemma game and show that strategy-dependent delays are detrimental to affected strategies. Additionally, we present how including delays may change the effective games played in the population, subsequently emphasising the importance of considering the studied systems’ temporal aspects to model them accurately.
• Self-Aligned InGaZnO Thin-Film Transistors and Circuits on Transparent Thin Glass and FEP Film. Corsino, Dianne C.; Catania, Federica; Garner, Sean; Cantarella, Giuseppe; Münzenrieder, Niko (2024). 3(11) 484–491.

  Thin-film electronics realized on flexible substrates opens up a new realm of innovative applications, such as wearable technologies that are unviable with conventional electronic systems on rigid carriers. The challenge, however, is to establish the fabrication of miniaturized devices with dimensions at the micrometer scale and to take into account the possibility of misalignment on thin, flexible, and, potentially, soft substrates. One efficient way to structure short channels is to employ self-alignment where the channel length is defined by the gate contact. Such an approach relies on the transparency of the substrate and is extremely time consuming, and if traditional, only partially transparent substrates are used. Here, we implement self-aligned InGaZnO (IGZO) thin-film transistors (TFTs) and circuits on novel flexible and highly transparent substrates, namely, 100- \($\mu $\) m thin glass and 50- \($\mu $\) m fluorinated ethylene propylene (FEP) film, resulting in self-aligned IGZO TFTs with channel lengths as short as 2.2 and \($4.5~\mu $\) m, respectively. The IGZO TFTs on the respective substrates exhibit on-off current ratios and effective mobilities of \($\approx 10^10$\) and 7.6 cm \($^2 \cdot $\) V \($^-1 \cdot $\) s−1, and \($\approx 10^2$\) and 11.5 cm \($^2 \cdot $\) V \($^-1 \cdot $\) s−1. The ac performance of the TFTs reaches a maximum oscillation frequency up to 147 MHz. The IGZO TFT further demonstrates mechanical stability by showing full functionality on thin glass even when bent to a radius of 25 mm. At the same time, inverters and common-source amplifiers based on self-aligned IGZO TFTs demonstrate operation at frequencies in the kilohertz range. This work presents a facile approach for realizing high-speed and flexible transistors and circuits based on self-alignment, leveraging the merit of transparent substrates.
• Generating High-Quality Symbolic Music Using Fine-Grained Discriminators. Zhang, Zhedong; Li, Liang; Zhang, Jiehua; Hu, Zhenghui; Wang, Hongkui; Yan, Chenggang; Yang, Jian; Qi, Yuankai in Lecture Notes in Computer Science, A. Antonacopoulos, S. Chaudhuri, R. Chellappa, C.-L. Liu, S. Bhattacharya, U. Pal (eds.) (2024). (Vol. 15320) 332–344.
• SM4Depth: Seamless Monocular Metric Depth Estimation across Multiple Cameras and Scenes by One Model. Liu, Yihao; Xue, Feng; Ming, Anlong; Zhao, Mingshuai; Ma, Huadong; Sebe, Nicu J. Cai, M. S. Kankanhalli, B. Prabhakaran, S. Boll, R. Subramanian, L. Zheng, V. K. Singh, P. César, L. Xie, D. Xu (eds.) (2024). 3469–3478.
• MedIE-Instruct: A Comprehensive Instruction Dataset for Medical Information Extraction. Xiang, Zhuoyi; Wang, Xinda; Yan, Xiaodong; Zhao, Deng; Ding, Keyan; Zhang, Qiang V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 420–427.
• Generating Multiple Choice Questions from Scientific Literature via Large Language Models. Luo, Shunyang; Tang, Yuqi; Jiang, Mingyuan; Feng, Kehua; Zhang, Qiang; Ding, Keyan V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 219–226.
• Instance-Level Neural Feature Selection Based on Disentanglement Enhancement. Liu, Zihao; Pan, Jun; Wang, Hao; Yu, Kui V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 211–218.
• Knowledge Graph Reasoning with Logics and Embeddings: Survey and Perspective. Zhang, Wen; Chen, Jiaoyan; Li, Juan; Xu, Zezhong; Pan, Jeff Z.; Chen, Huajun V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 492–499.
• Deep Learning for SLP-based ISAC Waveform Design. Jiang, Peng; Liu, Rang; Li, Ming; Xiao, Zichao; Liu, Qian (2024). 2270–2275.
• A Novel Dynamic Hybrid Beamforming Design for ELAA Systems. Liu, Mengzhen; Li, Ming; Liu, Rang; Liu, Qian (2024). 4494–4499.
• MuSc: Zero-Shot Industrial Anomaly Classification and Segmentation with Mutual Scoring of the Unlabeled Images. Li, Xurui; Huang, Ziming; Xue, Feng; Zhou, Yu (2024).
• Enhancing Risk Assessment in Transformers with Loss-at-Risk Functions. Zhang, Jinghan; Xie, Henry; Zhang, Xinhao; Liu, Kunpeng V. S. Sheng, C. Hicks, C. Ling, V. Raghavan, X. Wu (eds.) (2024). 477–484.
• Impacts and State-Dependence of AMOC Weakening in a Warming Climate. Bellomo, Katinka; Mehling, Oliver (2024). 51(10) e2023GL107624.

  Abstract All climate models project a weakening of the Atlantic Meridional Overturning Circulation (AMOC) strength in response to greenhouse gas forcing. However, the climate impacts of the AMOC decline alone cannot be isolated from other drivers of climate change using existing Coupled Model Intercomparison Project simulations. To address this issue, we conduct idealized experiments using the EC-Earth3 climate model. We compare an abrupt 4×CO2 simulation with the same experiment, except we artificially fix the AMOC strength at preindustrial levels. With this design, we can formally attribute differences in climate change impacts between these two experiments to the AMOC decline. In addition, we quantify the state-dependence of AMOC impacts by comparing the aforementioned experiments with a preindustrial simulation in which we artificially reduce the AMOC strength. Our findings demonstrate that AMOC decline impacts are state-dependent, thus understanding AMOC impacts on future climate change requires targeted model experiments.
• Catalysing cooperation: the power of collective beliefs in structured populations. Fic, Małgorzata; Gokhale, Chaitanya S. (2024). 1(1) 6.

  Abstract Collective beliefs can catalyse cooperation in a population of selfish individuals. We study this transformative power of collective beliefs, an effect that intriguingly persists even when beliefs lack moralising components. Besides the process itself, we consider the structure of human populations explicitly. We incorporate the intricate structure of human populations into our model, acknowledging the bias brought by social and cultural identities in interaction networks. Hence, we develop our model by assuming a heterogeneous group size and structured population. We recognise that beliefs, typically complex story systems, might not spontaneously emerge in society, resulting in different spreading rates for actions and beliefs within populations. As the degree of connectedness can vary among individuals perpetuating a belief, we examine the speed of trust build-up in networks with different connection densities. We then scrutinise the timing, speed and dynamics of trust and belief spread across specific network structures, including random Erdös-Rényi networks, scale-free Barabási-Albert networks, and small-world Newman-Watts-Strogatz networks. By comparing these characteristics across various network topologies, we disentangle the effects of structure, group size diversity, and evolutionary dynamics on the evolution of trust and belief.
• Effects of time spent in pregnancy or brooding on immunocompetence. Revathi Venkateswaran, Vandana; Gokhale, Chaitanya S.; Mangel, Marc; Eliassen, Sigrunn (2024). 14(1) e10764.

  Sexes of a species may show different characteristics beyond the differences in their sexual organs and such sexual dimorphism often occurs in the level of immune response when exposed to pathogens (immunocompetence). In general, females have increased longevity relative to males, which is associated with higher immunocompetence. However, males have higher immunocompetence in some species, such as pipefishes and seahorses. Experimental evidence suggests that this could be because males, rather than females, carry fertilized eggs to birth in these species. This observation suggests that an increase in immunocompetence may be related to the level of parental investment and not to a particular sex. We use state-dependent life-history theory to study optimal investment in offspring production relative to parent immunocompetence, varying the relative time that a parent spends in brooding or pregnancy within a breeding cycle. When offspring is dependent on a parent's survival for a large part of the breeding cycle, we predict higher investments in immunity and longer life expectancies.
• Terrain Classification Based on Wheel-terrain Interaction Measurements using Aside-Wheel Camera. Xue, Feng; Hu, Longteng; Yao, Chen; Wei, Jin; Li, Yunzhou; Wang, Peichen; Zhu, Zheng; Jia, Zhenzhong (2023). 1–6.
• Theoretical assessment of persistence and adaptation in weeds with complex life cycles. Lauenroth, Dana; Gokhale, Chaitanya S. (2023). 9(8) 1267–1279.

  Herbicide-resistant weeds pose a substantial threat to global food security. Perennial weed species are particularly troublesome. Such perennials as Sorghum halepense spread quickly and are difficult to manage due to their ability to reproduce sexually via seeds and asexually through rhizomes. Our theoretical study of S. halepense incorporates this complex life cycle with control measures of herbicide application and tillage. Rooted in the biology and experimental data of S. halepense, our population-based model predicts population dynamics and target-site resistance evolution in this perennial weed. We found that the resistance cost determines the standing genetic variation for herbicide resistance. The sexual phase of the life cycle, including self-pollination and seed bank dynamics, contributes substantially to the persistence and rapid adaptation of S. halepense. While self-pollination accelerates target-site resistance evolution, seed banks considerably increase the probability of escape from control strategies and maintain genetic variation. Combining tillage and herbicide application effectively reduces weed densities and the risk of control failure without delaying resistance adaptation. We also show how mixtures of different herbicide classes are superior to rotations and mono-treatment in controlling perennial weeds and resistance evolution. Thus, by integrating experimental data and agronomic views, our theoretical study synergistically contributes to understanding and tackling the global threat to food security from resistant weeds. The perennial weed, Johnsongrass, is a threat to global food security. Its two reproduction modes drive acquisition of herbicide resistance, but a well-strategized blend of tillage and diverse herbicides offers effective countermeasures.
• Uncertainty-Aware Image Captioning. Fei, Zhengcong; Fan, Mingyuan; Zhu, Li; Huang, Junshi; Wei, Xiaoming; Wei, Xiaolin B. Williams, Y. Chen, J. Neville (eds.) (2023). 614–622.
• Terrain Classification Using Inside-Wheel Cameras Based on Wheel-Terrain Interaction Characteristics. Hu, Longteng; Xue, Feng; Yao, Chen; Li, Yunzhou; Wei, Jin; Wang, Peichen; Zhu, Zheng; Jia, Zhenzhong (2023). 1–6.
• The Effect of Mating Complexity on Gene Drive Dynamics. Verma, Prateek; Reeves, R Guy; Simon, Samson; Otto, Mathias; Gokhale, Chaitanya S (2023). 201(1) E1-E22.

  AbstractGene drive technology promises to deliver on some of the global challenges humanity faces today in health care, agriculture, and conservation. However, there is a limited understanding of the consequences of releasing self-perpetuating transgenic organisms into wild populations under complex ecological conditions. In this study, we analyze the impact of three such complexities-mate choice, mating systems, and spatial mating network-on the population dynamics for two distinct classes of modification gene drive systems. All three factors had a high impact on the modeling outcome. First, we demonstrate that distortion-based gene drives appear to be more robust against mate choice than viability-based gene drives. Second, we find that gene drive spread is much faster for higher degrees of polygamy. Including a fitness cost, the drive is fastest for intermediate levels of polygamy. Finally, the spread of a gene drive is faster and more effective when the individuals have fewer connections in a spatial mating network. Our results highlight the need to include mating complexities when modeling the properties of gene drives, such as release thresholds, timescales, and population-level consequences. This inclusion will enable a more confident prediction of the dynamics of engineered gene drives and possibly even inform about the origin and evolution of natural gene drives.
• Optimizing crop rotations via Parrondo’s paradox for sustainable agriculture. Gokhale, Chaitanya S.; Sharma, Nikhil (2023). 10(5) 221401.

  Crop rotation, a sustainable agricultural technique, has been at humanity’s disposal since time immemorial and is practised globally. Switching between cover crops and cash crops helps avoid the adverse effects of intensive farming. Determining the optimum cash-cover rotation schedule for maximizing yield has been tackled on multiple fronts by agricultural scientists, economists, biologists and computer scientists, to name a few. However, considering the uncertainty due to diseases, pests, droughts, floods and impending effects of climate change is essential when designing rotation strategies. Analysing this time-tested technique of crop rotations with a new lens of Parrondo’s paradox allows us to optimally use the rotation technique in synchrony with uncertainty. While previous approaches are reactive to the diversity of crop types and environmental uncertainties, we make use of the said uncertainties to enhance crop rotation schedules. We calculate optimum switching probabilities in a randomized cropping sequence and suggest optimum deterministic sequences and judicious use of fertilizers. Our methods demonstrate strategies to enhance crop yield and the eventual profit margins for farmers. Conforming to translational biology, we extend Parrondo’s paradox, where two losing situations can be combined eventually into a winning scenario, to agriculture.
• Multimodal Counterfactual Learning Network for Multimedia-based Recommendation. Li, Shuaiyang; Guo, Dan; Liu, Kang; Hong, Richang; Xue, Feng H.-H. Chen, W.-J. (Edward) Duh, H.-H. Huang, M. P. Kato, J. Mothe, B. Poblete (eds.) (2023). 1539–1548.
• A Quantize-then-Estimate Protocol for CSI Acquisition in IRS-Aided Downlink Communication. Wang, Rui; Wang, Zhaorui; Liu, Liang; Zhang, Shuowen; Jin, Shi (2023). 6127–6132.
• Unknown Sniffer for Object Detection: Don’t Turn a Blind Eye to Unknown Objects. Liang, Wenteng; Xue, Feng; Liu, Yihao; Zhong, Guofeng; Ming, Anlong (2023). 3230–3239.
• Bias Reduced Semidefinite Relaxation Method for Multistatic Localization in the Absence of Transmitter Position And Its Synchronization. Pei, Jian; Wang, Gang; Ho, K. C.; Huang, Lei (2023). 1–5.
• Masked Auto-Encoders Meet Generative Adversarial Networks and Beyond. Fei, Zhengcong; Fan, Mingyuan; Zhu, Li; Huang, Junshi; Wei, Xiaoming; Wei, Xiaolin (2023). 24449–24459.
• Social engineering: how crowdmasters, phreaks, hackers, and trolls created a new form of manipulative communication Gehl, Robert W.; Lawson, Sean T. (2022). Cambridge, The MIT Press.

  Manipulative communication—from early twentieth-century propaganda to today's online con artistry—examined through the lens of social engineering. The United States is awash in manipulated information about everything from election results to the effectiveness of medical treatments. Corporate social media is an especially good channel for manipulative communication, with Facebook a particularly willing vehicle for it. In Social Engineering, Robert Gehl and Sean Lawson show that online misinformation has its roots in earlier techniques: mass social engineering of the early twentieth century and interpersonal hacker social engineering of the 1970s, converging today into what they call “masspersonal social engineering.” As Gehl and Lawson trace contemporary manipulative communication back to earlier forms of social engineering, possibilities for amelioration become clearer. The authors show how specific manipulative communication practices are a mixture of information gathering, deception, and truth-indifferent statements, all with the instrumental goal of getting people to take actions the social engineer wants them to. Yet the term “fake news,” they claim, reduces everything to a true/false binary that fails to encompass the complexity of manipulative communication or to map onto many of its practices. They pay special attention to concepts and terms used by hacker social engineers, including the hacker concept of “bullshitting,” which the authors describe as a truth-indifferent mix of deception, accuracy, and sociability. They conclude with recommendations for how society can undermine masspersonal social engineering and move toward healthier democratic deliberation.
• Fast Road Segmentation via Uncertainty-aware Symmetric Network. Chang, Yicong; Xue, Feng; Sheng, Fei; Liang, Wenteng; Ming, Anlong (2022). 11124–11130.
• Feature Selection and Extreme Learning Machine Tuning by Hybrid Sand Cat Optimization Algorithm for Diabetes Classification. Stankovic, Marko; Bacanin, Nebojsa; Zivkovic, Miodrag; Jovanovic, Dijana; Antonijevic, Milos; Bukmira, Milos; Strumberger, Ivana in Communications in Computer and Information Science, D. Simian, L. F. Stoica (eds.) (2022). (Vol. 1761) 188–203.
• Multivariate Time Series Anomaly Detection with Few Positive Samples. Xue, Feng; Yan, Weizhong (2022). 1–7.
• Monocular Depth Distribution Alignment with Low Computation. Sheng, Fei; Xue, Feng; Chang, Yicong; Liang, Wenteng; Ming, Anlong (2022). 6548–6555.
• Morphable Detector for Object Detection on Demand. Zhao, Xiangyun; Zou, Xu; Wu, Ying (2021). 4751–4760.
• Multi-stage Knowledge Propagation Network for Recommendation. Xue, Feng; Zhou, Wenjie; Hong, Zikun; Liu, Kang in Communications in Computer and Information Science, B. Qin, Z. Jin, H. Wang, J. Z. Pan, Y. Liu, B. An (eds.) (2021). (Vol. 1466) 253–264.
• Spatial-Temporal Super-Resolution of Satellite Imagery via Conditional Pixel Synthesis. He, Yutong; Wang, Dingjie; Lai, Nicholas; Zhang, William; Meng, Chenlin; Burke, Marshall; Lobell, David B.; Ermon, Stefano M. Ranzato, A. Beygelzimer, Y. N. Dauphin, P. Liang, J. W. Vaughan (eds.) (2021). 27903–27915.
• Graph Attention-Based Deep Neural Network for 3D Point Cloud Processing. Li, Xun; Xue, Feng; Chen, Chao; Yuan, Xiaohui; Lu, Qiang (2021). 1–6.
• Learning Associations between Features and Clusters: An Interpretable Deep Clustering Method. Huang, Hao; Xue, Feng; Yan, Weizhong; Wang, Tianyi; Yoo, Shinjae; Xu, Chenxiao (2021). 1–10.
• Intelligent Visualization System for Big Multi-source Medical Data Based on Data Lake. Ren, Peng; Mao, Ziyun; Li, Shuaibo; Xiao, Yang; Ke, Yating; Yao, Lanyu; Lan, Hao; Li, Xin; Sheng, Ming; Zhang, Yong in Lecture Notes in Computer Science, C. Xing, X. Fu, Y. Zhang, G. Zhang, C. Borjigin (eds.) (2021). (Vol. 12999) 706–717.
• MHDP: An Efficient Data Lake Platform for Medical Multi-source Heterogeneous Data. Ren, Peng; Li, Shuaibo; Hou, Wei; Zheng, Wenkui; Li, Zhen; Cui, Qin; Chang, Wang; Li, Xin; Zeng, Chun; Sheng, Ming; Zhang, Yong in Lecture Notes in Computer Science, C. Xing, X. Fu, Y. Zhang, G. Zhang, C. Borjigin (eds.) (2021). (Vol. 12999) 727–738.
• Science-utility and science-trust associations and how they relate to knowledge about how science works. Schoor, Cornelia; Schütz, Astrid (2021). 16(12) 1–21.

  Knowledge about how science works, trust in scientists, and the perceived utility of science currently appear to be eroding in these times in which “alternative facts” or personal experiences and opinions are used as arguments. Yet, in many situations, it would be beneficial for the individual and all of society if scientific findings were considered in decision-making. For this to happen, people have to trust in scientists and perceive science as useful. Still, in university contexts, it might not be desirable to report negative beliefs about science. In addition, science-utility and science-trust associations may differ from explicit beliefs because associations were learned through the co-occurrence of stimuli rather than being based on propositional reasoning. We developed two IATs to measure science-utility and science-trust associations in university students and tested the psychometric properties and predictive potential of these measures. In a study of 261 university students, the IATs were found to have good psychometric properties and small correlations with their corresponding self-report scales. Science-utility and science-trust associations predicted knowledge about how science works over and above self-reported beliefs. The results suggest that indirect measures are useful for assessing beliefs about science and can be used to predict outcome measures.
• Flight data anomaly detection and diagnosis with variable association change. He, Sijie; Huang, Hao; Yoo, Shinjae; Yan, Weizhong; Xue, Feng; Wang, Tianyi; Xu, Chenxiao C.-C. Hung, J. Hong, A. Bechini, E. Song (eds.) (2021). 346–354.
• Imbalanced Time Series Classification for Flight Data Analyzing with Nonlinear Granger Causality Learning. Huang, Hao; Xu, Chenxiao; Yoo, Shinjae; Yan, Weizhong; Wang, Tianyi; Xue, Feng M. d’Aquin, S. Dietze, C. Hauff, E. Curry, P. Cudré-Mauroux (eds.) (2020). 2533–2540.
• On The Degrees Of Freedom in Total Variation Minimization. Xue, Feng; Blu, Thierry (2020). 5690–5694.
• A Novel Multi-layer Framework for Tiny Obstacle Discovery. Xue, Feng; Ming, Anlong; Zhou, Menghan; Zhou, Yu (2019). 2939–2945.
• An Iterative Sure-Let Deconvolution Algorithm Based on BM3D Denoiser. Xue, Feng; Li, Jizhou; Blu, Thierry (2019). 1795–1799.
• Discriminative and Correlative Partial Multi-Label Learning. Wang, Haobo; Liu, Weiwei; Zhao, Yang; Zhang, Chen; Hu, Tianlei; Chen, Gang S. Kraus (ed.) (2019). 3691–3697.
• Mining Graphs and Networks: A 15-Year Journey. Pei, Jian in CEUR Workshop Proceedings, A. Bifet, M. Berlingerio, J. Gama, J. Read, A. R. Nogueira (eds.) (2019). (Vol. 2579)
• Occlusion-Shared and Feature-Separated Network for Occlusion Relationship Reasoning. Lu, Rui; Xue, Feng; Zhou, Menghan; Ming, Anlong; Zhou, Yu (2019). 10342–10351.
• Generative Creativity: Adversarial Learning for Bionic Design. Yu, Simiao; Dong, Hao; Wang, Pan; Wu, Chao; Guo, Yike in Lecture Notes in Computer Science, I. V. Tetko, V. Kurková, P. Karpov, F. J. Theis (eds.) (2019). (Vol. 11729) 525–536.
• Recursive Evaluation of Sure for Total Variation Denoising. Xue, Feng; Blu, Thierry; Liu, Jiaqi; Ai, Xia (2018). 1338–1342.
• Security-Driven Task Scheduling for Multiprocessor System-on-Chips with Performance Constraints. Wang, Nan; Yao, Manting; Jiang, Dongxu; Chen, Song; Zhu, Yu (2018). 545–550.
• Visual-SLIM: Integrated Sparse Linear Model with Visual Features for Personalized Recommendation. Chen, Siyang; Xue, Feng; Zhang, Haobo in Lecture Notes in Computer Science, R. Hong, W.-H. Cheng, T. Yamasaki, M. Wang, C.-W. Ngo (eds.) (2018). (Vol. 11164) 126–135.
• A Novel Gcv-Based Criterion for Parameter Selection In Image Deconvolution. Xue, Feng; Blu, Thierry; Liu, Jiaqi; Ai, Xia (2018). 1403–1407.
• How to Exploit Weaknesses in Biomedical Challenge Design and Organization. Reinke, Annika; Eisenmann, Matthias; Onogur, Sinan; Stankovic, Marko; Scholz, Patrick; Full, Peter M.; Bogunovic, Hrvoje; Landman, Bennett A.; Maier, Oskar; Menze, Bjoern H.; Sharp, Gregory C.; Sirinukunwattana, Korsuk; Speidel, Stefanie; van der Sommen, Fons; Zheng, Guoyan; Müller, Henning; Kozubek, Michal; Arbel, Tal; Bradley, Andrew P.; Jannin, Pierre; Kopp-Schneider, Annette; Maier-Hein, Lena in Lecture Notes in Computer Science, A. F. Frangi, J. A. Schnabel, C. Davatzikos, C. Alberola-López, G. Fichtinger (eds.) (2018). (Vol. 11073) 388–395.
• Gaussian blur estimation for photon-limited images. Li, Jizhou; Xue, Feng; Blu, Thierry (2017). 495–499.
• Same but different? Measurement invariance of the PIAAC motivation-to-learn scale across key socio-demographic groups. Gorges, Julia; Koch, Tobias; Maehler, Débora B.; Offerhaus, Judith (2017). 5(1)
• Abstract: Können wir Rankings vertrauen? Eine systematische Analyse biomedizinischer Challenges hinsichtlich Reporting und Design. Eisenmann, Matthias; Scholz, Patrick; Stankovic, Marko; Jannin, Pierre; Stock, Christian; Maier-Hein, Lena in Informatik Aktuell, K. H. Maier-Hein, T. M. Deserno, H. Handels, T. Tolxdorff (eds.) (2017). 49.
• An iterative sure-let approach to sparse reconstruction. Xue, Feng; Blu, Thierry; Du, Runle; Liu, Jiaqi (2016). 4493–4497.
• Modelling Sentence Pairs with Tree-structured Attentive Encoder. Zhou, Yao; Liu, Cong; Pan, Yan N. Calzolari, Y. Matsumoto, R. Prasad (eds.) (2016). 2912–2922.
• I Just Don’t Trust Them: The Development and Validation of an Assessment Instrument to Measure Trust in Science and Scientists. Nadelson, Louis; Jorcyk, Cheryl; Yang, Dazhi; Jarratt Smith, Mary; Matson, Sam; Cornell, Ken; Husting, Virginia (2014). 114(2) 76–86.
• A Localized Efficient Forwarding Algorithm in Large-Scale Delay Tolerant Networks. He, Yuxing; Liu, Cong; Pan, Yan; Zhang, Jun; Wu, Jie; Zhao, Yaxiong; Yang, Shuhui; Lu, Mingming (2014). 594–599.
• SURE-LET image deconvolution using multiple Wiener filters. Xue, Feng; Luisier, Florian; Blu, Thierry (2012). 3037–3040.
• Sure-based blind Gaussian deconvolution. Xue, Feng; Blu, Thierry (2012). 452–455.
• A compact integrated 100 GS/s sampling module for UWB see through wall radar with fast refresh rate for dynamic real time imaging. Liu, Quanhua; Wang, Yazhou; Fathy, Aly E. (2012). 59–62.
• Sonic Hedgehog Signaling Inhibition Provides Opportunities for Targeted Therapy by Sulforaphane in Regulating Pancreatic Cancer Stem Cell Self-Renewal. Rodova, Mariana; Fu, Junsheng; Watkins, Dara Nall; Srivastava, Rakesh K.; Shankar, Sharmila (2012). 7(9) 1–10.

  Dysregulation of the sonic hedgehog (Shh) signaling pathway has been associated with cancer stem cells (CSC) and implicated in the initiation of pancreatic cancer. Pancreatic CSCs are rare tumor cells characterized by their ability to self-renew, and are responsible for tumor recurrence accompanied by resistance to current therapies. The lethality of these incurable, aggressive and invasive pancreatic tumors remains a daunting clinical challenge. Thus, the objective of this study was to investigate the role of Shh pathway in pancreatic cancer and to examine the molecular mechanisms by which sulforaphane (SFN), an active compound in cruciferous vegetables, inhibits self-renewal capacity of human pancreatic CSCs. Interestingly, we demonstrate here that Shh pathway is highly activated in pancreatic CSCs and plays important role in maintaining stemness by regulating the expression of stemness genes. Given the requirement for Hedgehog in pancreatic cancer, we investigated whether hedgehog blockade by SFN could target the stem cell population in pancreatic cancer. In an in vitro model, human pancreatic CSCs derived spheres were significantly inhibited on treatment with SFN, suggesting the clonogenic depletion of the CSCs. Interestingly, SFN inhibited the components of Shh pathway and Gli transcriptional activity. Interference of Shh-Gli signaling significantly blocked SFN-induced inhibitory effects demonstrating the requirement of an active pathway for the growth of pancreatic CSCs. SFN also inhibited downstream targets of Gli transcription by suppressing the expression of pluripotency maintaining factors (Nanog and Oct-4) as well as PDGFRα and Cyclin D1. Furthermore, SFN induced apoptosis by inhibition of BCL-2 and activation of caspases. Our data reveal the essential role of Shh-Gli signaling in controlling the characteristics of pancreatic CSCs. We propose that pancreatic cancer preventative effects of SFN may result from inhibition of the Shh pathway. Thus Sulforaphane potentially represents an inexpensive, safe and effective alternative for the management of pancreatic cancer.
• Suggesting Topic-Based Query Terms as You Type. Fan, Ju; Wu, Hao; Li, Guoliang; Zhou, Lizhu W.-S. Han, D. Srivastava, G. Yu, H. Yu, Z. H. Huang (eds.) (2010). 61–67.
• Firefly: illuminating future network-on-chip with nanophotonics. Pan, Yan; Kumar, Prabhat; Kim, John; Memik, Gokhan; Zhang, Yu; Choudhary, Alok N. S. W. Keckler, L. A. Barroso (eds.) (2009). 429–440.
• Jet engine gas path fault diagnosis using dynamic fusion of multiple classifiers. Yan, Weizhong; Xue, Feng (2008). 1585–1591.
• Temperature Control in Precalcinator with Dual Heuristic Dynamic Programming. Lin, Xiaofeng; Zhang, Zhigang; Liu, Derong (2007). 344–349.
• Probabilistic Skylines on Uncertain Data. Pei, Jian; Jiang, Bin; Lin, Xuemin; Yuan, Yidong C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 15–26.
• Minimality Attack in Privacy Preserving Data Publishing. Wong, Raymond Chi-Wing; Fu, Ada Wai-Chee; Wang, Ke; Pei, Jian C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 543–554.
• Efficiently Answering Top-k Typicality Queries on Large Databases. Hua, Ming; Pei, Jian; Fu, Ada Wai-Chee; Lin, Xuemin; fung Leung, Ho C. Koch, J. Gehrke, M. N. Garofalakis, D. Srivastava, K. Aberer, A. Deshpande, D. Florescu, C. Y. Chan, V. Ganti, C.-C. Kanne, W. Klas, E. J. Neuhold (eds.) (2007). 890–901.
• Parametric model-based anomaly detection for locomotive subsystems. Xue, Feng; Yan, Weizhong (2007). 3074–3079.
• A Review of Two Industrial Deployments of Multi-criteria Decision-making Systems at General Electric. Subbu, Raj; Bonissone, Piero P.; Bollapragada, Srinivas; Chalermkraivuth, Kete Charles; Eklund, Neil H. W.; Iyer, Naresh; Shah, Rasik; Xue, Feng; Yan, Weizhong (2007). 136–145.
• Multi-Dimensional Analysis of Data Streams Using Stream Cubes. Han, Jiawei; Cai, Yandong; Chen, Yixin; Dong, Guozhu; Pei, Jian; Wah, Benjamin W.; Wang, Jianyong C. C. Aggarwal (ed.) (2007). (Vol. 31) 103–125.
• Minimum Description Length Principle: Generators Are Preferable to Closed Patterns. Li, Jinyan; Li, Haiquan; Wong, Limsoon; Pei, Jian; Dong, Guozhu (2006). 409–414.
• Achieving k-Anonymity by Clustering in Attribute Hierarchical Structures. Li, Jiuyong; Wong, Raymond Chi-Wing; Fu, Ada Wai-Chee; Pei, Jian in Lecture Notes in Computer Science, A. M. Tjoa, J. Trujillo (eds.) (2006). (Vol. 4081) 405–416.
• Catching the Best Views of Skyline: A Semantic Approach Based on Decisive Subspaces. Pei, Jian; Jin, Wen; Ester, Martin; Tao, Yufei K. Böhm, C. S. Jensen, L. M. Haas, M. L. Kersten, P.- Åke Larson, B. C. Ooi (eds.) (2005). 253–264.
• Mining Most General Multidimensional Summarization of Probably Groups in Data Warehouses. Yu, Hui; Pei, Jian; Tang, Shiwei; Yang, Dongqing J. Frew (ed.) (2005). 185–194.
• Efficiently Mining Frequent Closed Partial Orders. Pei, Jian; Liu, Jian; Wang, Haixun; Wang, Ke; Yu, Philip S.; Wang, Jianyong (2005). 753–756.
• GraphMiner: a structural pattern-mining system for large disk-based graph databases and its applications. Wang, Wei; Wang, Chen; Zhu, Yongtai; Shi, Baile; Pei, Jian; Yan, Xifeng; Han, Jiawei F. Özcan (ed.) (2005). 879–881.
• Preface to CoMWIM 2004. Yang, Dongqing; Tang, Shiwei; Pei, Jian; Wang, Tengjiao; Gao, Jun in Lecture Notes in Computer Science, S. Wang, D. Yang, K. Tanaka, F. Grandi, S. Zhou, E. E. Mangina, T. W. Ling, I.-Y. Song, J. Guan, H. C. Mayr (eds.) (2004). (Vol. 3289) 197.
• Data Mining: The Next Generation. Ramakrishnan, Raghu; Agrawal, Rakesh; Freytag, Johann-Christoph; Bollinger, Toni; Clifton, Christopher W.; Dzeroski, Saso; Hipp, Jochen; Keim, Daniel A.; Kramer, Stefan; Kriegel, Hans-Peter; Leser, Ulf; Liu, Bing; Mannila, Heikki; Meo, Rosa; Morishita, Shinichi; Ng, Raymond T.; Pei, Jian; Raghavan, Prabhakar; Spiliopoulou, Myra; Srivastava, Jaideep; Torra, Vicenç in Dagstuhl Seminar Proceedings, R. Agrawal, J.-C. Freytag, R. Ramakrishnan (eds.) (2004). (Vol. 04292)
• Data Mining for Intrusion Detection: Techniques, Applications and Systems. Pei, Jian; Upadhyaya, Shambhu J.; Farooq, Faisal; Govindaraju, Venugopal Z. M. Özsoyoglu, S. B. Zdonik (eds.) (2004). 877.
• A Fast Algorithm for Subspace Clustering by Pattern Similarity. Wang, Haixun; Chu, Fang; Fan, Wei; Yu, Philip S.; Pei, Jian (2004). 51–60.
• MaPle: A Fast Algorithm for Maximal Pattern-based Clustering. Pei, Jian; Zhang, Xiaoling; Cho, Moonjung; Wang, Haixun; Yu, Philip S. (2003). 259–266.
• SOCQET: Semantic OLAP with Compressed Cube and Summarization. Lakshmanan, Laks V. S.; Pei, Jian; Zhao, Yan A. Y. Halevy, Z. G. Ives, A. Doan (eds.) (2003). 658.
• Mining Confident Colocation Rules without A Support Threshold. Huang, Yan; Xiong, Hui; Shekhar, Shashi; Pei, Jian G. B. Lamont, H. Haddad, G. A. Papadopoulos, B. Panda (eds.) (2003). 497–501.
• QC-Trees: An Efficient Summary Structure for Semantic OLAP. Lakshmanan, Laks V. S.; Pei, Jian; Zhao, Yan A. Y. Halevy, Z. G. Ives, A. Doan (eds.) (2003). 64–75.
• ApproxMAP: Approximate Mining of Consensus Sequential Patterns. Kum, Hye-Chung; Pei, Jian; Wang, Wei; Duncan, Dean D. Barbará, C. Kamath (eds.) (2003). 311–315.
• On Computing Condensed Frequent Pattern Bases. Pei, Jian; Dong, Guozhu; Zou, Wei; Han, Jiawei (2002). 378–385.
• Quotient Cube: How to Summarize the Semantics of a Data Cube. Lakshmanan, Laks V. S.; Pei, Jian; Han, Jiawei (2002). 778–789.
• Online Analytical Processing Stream Data: Is It Feasible?. Chen, Yixin; Dong, Guozhu; Han, Jiawei; Pei, Jian; Wah, Benjamin W.; Wang, Jianyong (2002).
• PrefixSpan: Mining Sequential Patterns by Prefix-Projected Growth. Pei, Jian; Han, Jiawei; Mortazavi-Asl, Behzad; Pinto, Helen; Chen, Qiming; Dayal, Umeshwar; Hsu, Meichun D. Georgakopoulos, A. Buchmann (eds.) (2001). 215–224.
• Fault-Tolerant Frequent Pattern Mining: Problems and Challenges. Pei, Jian; Tung, Anthony K. H.; Han, Jiawei (2001).
• Multi-Dimensional Sequential Pattern Mining. Pinto, Helen; Han, Jiawei; Pei, Jian; Wang, Ke; Chen, Qiming; Dayal, Umeshwar (2001). 81–88.
• FreeSpan: frequent pattern-projected sequential pattern mining. Han, Jiawei; Pei, Jian; Mortazavi-Asl, Behzad; Chen, Qiming; Dayal, Umeshwar; Hsu, Meichun R. Ramakrishnan, S. J. Stolfo, R. J. Bayardo, I. Parsa (eds.) (2000). 355–359.
• Humanisme de l’Autre Homme Lévinas, Emmanuel (1972). LGF/Le Livre de Poche, [Montpellier].