Subnational institutions and open innovation: evidence from China

Purpose: The purpose of this paper is to examine how subnational institutions within a country explain the performance consequences of open innovation (OI) in emerging market enterprises (EMEs). Design/methodology/approach: The paper conducts a regression analysis by using a novel panel data set comprising of 438 innovative Chinese firms over the period of 2008-2011. Findings: The authors show that although on average openness to external actors improves innovation performance this effect is pronounced for EMEs that operate in subnational regions with a higher level of intellectual property rights (IPR) enforcement and of factor market development. The findings point to the context-dependent nature of OI strategy and the complementary effect of institutional parameters in emerging markets and help to reconcile the contrasting findings regarding the effect of OI in the prior literature. Originality/value: This paper extends the literature on OI by suggesting that the analysis of the performance consequences of OI strategy should go beyond the nexus between OI and firm performance, and instead, focus on subnational-specific institutions, such as region-specific IPR enforcement, factor market development and intermediation market development, that may facilitate or constrain the effect of OI model

Fake Alignment: Are LLMs Really Aligned Well?

The growing awareness of safety concerns in large language models (LLMs) has sparked considerable interest in the evaluation of safety within current research endeavors. This study investigates an interesting issue pertaining to the evaluation of LLMs, namely the substantial discrepancy in performance between multiple-choice questions and open-ended questions. Inspired by research on jailbreak attack patterns, we argue this is caused by mismatched generalization. That is, the LLM does not have a comprehensive understanding of the complex concept of safety. Instead, it only remembers what to answer for open-ended safety questions, which makes it unable to solve other forms of safety tests. We refer to this phenomenon as fake alignment and construct a comparative benchmark to empirically verify its existence in LLMs. Such fake alignment renders previous evaluation protocols unreliable. To address this, we introduce the Fake alIgNment Evaluation (FINE) framework and two novel metrics--Consistency Score (CS) and Consistent Safety Score (CSS), which jointly assess two complementary forms of evaluation to quantify fake alignment and obtain corrected performance estimates. Applying FINE to 14 widely-used LLMs reveals several models with purported safety are poorly aligned in practice. Our work highlights potential limitations in prevailing alignment methodologies

The IPIN 2019 Indoor Localisation Competition—Description and Results

IPIN 2019 Competition, sixth in a series of IPIN competitions, was held at the CNR Research Area of Pisa (IT), integrated into the program of the IPIN 2019 Conference. It included two on-site real-time Tracks and three off-site Tracks. The four Tracks presented in this paper were set in the same environment, made of two buildings close together for a total usable area of 1000 m 2 outdoors and and 6000 m 2 indoors over three floors, with a total path length exceeding 500 m. IPIN competitions, based on the EvAAL framework, have aimed at comparing the accuracy performance of personal positioning systems in fair and realistic conditions: past editions of the competition were carried in big conference settings, university campuses and a shopping mall. Positioning accuracy is computed while the person carrying the system under test walks at normal walking speed, uses lifts and goes up and down stairs or briefly stops at given points. Results presented here are a showcase of state-of-the-art systems tested side by side in real-world settings as part of the on-site real-time competition Tracks. Results for off-site Tracks allow a detailed and reproducible comparison of the most recent positioning and tracking algorithms in the same environment as the on-site Tracks

Off-line evaluation of indoor positioning systems in different scenarios: the experiences from IPIN 2020 competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001

Off-Line Evaluation of Indoor Positioning Systems in Different Scenarios: The Experiences From IPIN 2020 Competition

Every year, for ten years now, the IPIN competition has aimed at evaluating real-world indoor localisation systems by testing them in a realistic environment, with realistic movement, using the EvAAL framework. The competition provided a unique overview of the state-of-the-art of systems, technologies, and methods for indoor positioning and navigation purposes. Through fair comparison of the performance achieved by each system, the competition was able to identify the most promising approaches and to pinpoint the most critical working conditions. In 2020, the competition included 5 diverse off-site off-site Tracks, each resembling real use cases and challenges for indoor positioning. The results in terms of participation and accuracy of the proposed systems have been encouraging. The best performing competitors obtained a third quartile of error of 1 m for the Smartphone Track and 0.5 m for the Foot-mounted IMU Track. While not running on physical systems, but only as algorithms, these results represent impressive achievements.Track 3 organizers were supported by the European Union’s Horizon 2020 Research and Innovation programme under the Marie Skłodowska Curie Grant 813278 (A-WEAR: A network for dynamic WEarable Applications with pRivacy constraints), MICROCEBUS (MICINN, ref. RTI2018-095168-B-C55, MCIU/AEI/FEDER UE), INSIGNIA (MICINN ref. PTQ2018-009981), and REPNIN+ (MICINN, ref. TEC2017-90808-REDT). We would like to thanks the UJI’s Library managers and employees for their support while collecting the required datasets for Track 3. Track 5 organizers were supported by JST-OPERA Program, Japan, under Grant JPMJOP1612. Track 7 organizers were supported by the Bavarian Ministry for Economic Affairs, Infrastructure, Transport and Technology through the Center for Analytics-Data-Applications (ADA-Center) within the framework of “BAYERN DIGITAL II. ” Team UMinho (Track 3) was supported by FCT—Fundação para a Ciência e Tecnologia within the R&D Units Project Scope under Grant UIDB/00319/2020, and the Ph.D. Fellowship under Grant PD/BD/137401/2018. Team YAI (Track 3) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 109-2221-E-197-026. Team Indora (Track 3) was supported in part by the Slovak Grant Agency, Ministry of Education and Academy of Science, Slovakia, under Grant 1/0177/21, and in part by the Slovak Research and Development Agency under Contract APVV-15-0091. Team TJU (Track 3) was supported in part by the National Natural Science Foundation of China under Grant 61771338 and in part by the Tianjin Research Funding under Grant 18ZXRHSY00190. Team Next-Newbie Reckoners (Track 3) were supported by the Singapore Government through the Industry Alignment Fund—Industry Collaboration Projects Grant. This research was conducted at Singtel Cognitive and Artificial Intelligence Lab for Enterprises (SCALE@NTU), which is a collaboration between Singapore Telecommunications Limited (Singtel) and Nanyang Technological University (NTU). Team KawaguchiLab (Track 5) was supported by JSPS KAKENHI under Grant JP17H01762. Team WHU&AutoNavi (Track 6) was supported by the National Key Research and Development Program of China under Grant 2016YFB0502202. Team YAI (Tracks 6 and 7) was supported by the Ministry of Science and Technology (MOST) of Taiwan under Grant MOST 110-2634-F-155-001.Peer reviewe

Origami Mönster Tube för Vehicle Crash Box

With an increasing number of traffic accidents, more and more people are injuring or even dying during the collision. One of the main reasons is frontal collisions. Therefore, the safety system is a very important part of the vehicle. In order to ensure the passengers’ safety, the common way to minimize mortality and property damage in a collision is to install energy absorption device in the vehicle structure called crash box. We propose to implement the principle of the origami pattern to improve the traditional bumper system, let the bumper have folding property. Origami properties make it useful to apply in a variety of engineering fields. The thin-walled tube and beam will undergo elastic deformation to decrease the impact force and absorb more kinetic energy. We use Autodesk Inventor 2012 to model the seamless origami pattern tube, and do the simulation by ABAQUS to analyze the displacement of axial compression and the impact force. The numerical results show that origami patterns perform well. Then we can obtain the plot with relationship between force and displacement in the elastic behavior and in the elastic-ideal plastic behavior. As for manufacturing field, we analyze existing manufacturing methods include stamping and tube hydroforming, compare them to find their features. Meanwhile we try to explore a new way to improve the accuracy and efficiency of manufacturing origami pattern tube.Med ett ökande antal trafikolyckor, fler och fler människor att skada eller till och med dö under kollisionen. Ett av de viktigaste skälen är frontalkollisioner. Därför är säkerhetssystemet en mycket viktig del av fordonet. För att garantera passagerarnas säkerhet, är det vanligaste sättet att minimera dödlighet och skador på egendom vid en kollision för att installera enheten energiupptagning i fordonets struktur som kallas crash box. Vi föreslår att genomföra principen om origami mönstret att förbättra traditionella stötfångaren systemet, låt stötfångaren har fällbara egendom. Origami egenskaper gör det användbart att tillämpa i en mängd olika tekniska områden. Den tunnväggigt rör och strålen kommer att genomgå elastisk deformation för att minska stötkraften och absorbera mer kinetisk energi. Vi använder Autodesk Inventor 2012 att modellera sömlösa rör origami mönster, och göra simuleringen av ABAQUS att analysera förskjutning av axiell kompression och slagstyrka. De numeriska resultaten visar att origami mönster prestera bra. Då kan vi få tomten med förhållandet mellan kraft och förskjutning i den elastiska beteendet och i det elastiska-ideala plast beteende. När det gäller tillverkning område, vi analyserar befintliga tillverkningsmetoder inkluderar stämpling och rör hydroformning, jämföra dem att hitta sina funktioner. Samtidigt försöker vi att utforska ett nytt sätt att förbättra noggrannheten och effektiviteten i tillverkningen origami mönster röret

Origami Mönster Tube för Vehicle Crash Box

With an increasing number of traffic accidents, more and more people are injuring or even dying during the collision. One of the main reasons is frontal collisions. Therefore, the safety system is a very important part of the vehicle. In order to ensure the passengers’ safety, the common way to minimize mortality and property damage in a collision is to install energy absorption device in the vehicle structure called crash box. We propose to implement the principle of the origami pattern to improve the traditional bumper system, let the bumper have folding property. Origami properties make it useful to apply in a variety of engineering fields. The thin-walled tube and beam will undergo elastic deformation to decrease the impact force and absorb more kinetic energy. We use Autodesk Inventor 2012 to model the seamless origami pattern tube, and do the simulation by ABAQUS to analyze the displacement of axial compression and the impact force. The numerical results show that origami patterns perform well. Then we can obtain the plot with relationship between force and displacement in the elastic behavior and in the elastic-ideal plastic behavior. As for manufacturing field, we analyze existing manufacturing methods include stamping and tube hydroforming, compare them to find their features. Meanwhile we try to explore a new way to improve the accuracy and efficiency of manufacturing origami pattern tube.Med ett ökande antal trafikolyckor, fler och fler människor att skada eller till och med dö under kollisionen. Ett av de viktigaste skälen är frontalkollisioner. Därför är säkerhetssystemet en mycket viktig del av fordonet. För att garantera passagerarnas säkerhet, är det vanligaste sättet att minimera dödlighet och skador på egendom vid en kollision för att installera enheten energiupptagning i fordonets struktur som kallas crash box. Vi föreslår att genomföra principen om origami mönstret att förbättra traditionella stötfångaren systemet, låt stötfångaren har fällbara egendom. Origami egenskaper gör det användbart att tillämpa i en mängd olika tekniska områden. Den tunnväggigt rör och strålen kommer att genomgå elastisk deformation för att minska stötkraften och absorbera mer kinetisk energi. Vi använder Autodesk Inventor 2012 att modellera sömlösa rör origami mönster, och göra simuleringen av ABAQUS att analysera förskjutning av axiell kompression och slagstyrka. De numeriska resultaten visar att origami mönster prestera bra. Då kan vi få tomten med förhållandet mellan kraft och förskjutning i den elastiska beteendet och i det elastiska-ideala plast beteende. När det gäller tillverkning område, vi analyserar befintliga tillverkningsmetoder inkluderar stämpling och rör hydroformning, jämföra dem att hitta sina funktioner. Samtidigt försöker vi att utforska ett nytt sätt att förbättra noggrannheten och effektiviteten i tillverkningen origami mönster röret

On the Convergence of Clustered Federated Learning

Knowledge sharing and model personalization are essential components to tackle the non-IID challenge in federated learning (FL). Most existing FL methods focus on two extremes: 1) to learn a shared model to serve all clients with non-IID data, and 2) to learn personalized models for each client, namely personalized FL. There is a trade-off solution, namely clustered FL or cluster-wise personalized FL, which aims to cluster similar clients into one cluster, and then learn a shared model for all clients within a cluster. This paper is to revisit the research of clustered FL by formulating them into a bi-level optimization framework that could unify existing methods. We propose a new theoretical analysis framework to prove the convergence by considering the clusterability among clients. In addition, we embody this framework in an algorithm, named Weighted Clustered Federated Learning (WeCFL). Empirical analysis verifies the theoretical results and demonstrates the effectiveness of the proposed WeCFL under the proposed cluster-wise non-IID settings.Comment: draf