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

Consideration of future consequences (CFC) serves as a buffer against aggression related to psychopathy.

Psychopathy is the most notorious trait in the Dark Triad, and it is strongly linked to many kinds of aggressive behaviors. However, not every individual who is characterized by psychopathy engages in aggression, which suggests that certain factors may attenuate the intensity of the relations between psychopathy and aggression. The purpose of the current study was to explore the protective roles of the consideration of future consequences (CFC) (high CFC-Future and low CFC- Immediate) in attenuating aggression related to psychopathy using proactive aggression (Study 1) and cyber-aggression (Study 2) behavior indexes. College students (Study 1; N = 1,058) and adults (Study 2; N = 350) voluntarily participated in this study. The results demonstrated that the relationship between psychopathy and aggressive behaviors was moderated by CFC-Future and CFC-Immediate. Individuals with high psychopathy scores who also had high CFC-Future scores or low CFC-Immediate scores exhibited less proactive aggression (Study 1) and left fewer aggressive online comments on news websites (Study 2). The results of the present study suggested that CFC serves as a buffer against aggression related to psychopathy and may extend the knowledge of the relationship between psychopathy and aggression

SCSS: An Intelligent Security System to Guard City Public Safe

Traditional security surveillance detection relies on post-event forensics or is hosted on a backend server, making it impossible to identify behaviors filmed in the field online. This paper proposes the Smart City Security System (SCSS) for detecting anomalous activity in public locations online. SCSS combines the DeepSORT and YOLOv4 algorithms to generate the DS-YOLO aberrant behavior detection algorithm, which compares and matches the target detected in the previous picture frame with the target detected in the following frame to achieve detection and tracking. SCSS is equipped with GPS, WIFI, and Uninterruptible Power Supply (UPS). When a risky behavior is detected, the system will upload the abnormal event as well as the latitude and longitude that occurred to the cloud via the WIFI and notify the user. The recognition accuracy of three deviant behaviors, including Fight, Car Accident, and Fall, was examined using diverse situations, and the results were 89%, 90%, and 90.33% respectively. The findings demonstrate that SCSS has successfully made the transition from passive monitoring to active identification, offsetting the flaws of conventional security systems that can only post-mordem forensics, and bridging the gap of the construction of national smart cities

Left-Behind Children’s Subtypes of Antisocial Behavior: A Qualitative Study in China

As a result of the recent decades of urbanization and industrialization, millions of people have migrated to cities in search of better work opportunities in China. Meanwhile, their children have often been left behind in the care of other family members. To classify the subtypes of antisocial behavior of the left-behind children, this qualitative study interviewed a total of 71 participants, including five groups: left-behind children, parents, teachers, principals and community workers. The findings showed that left-behind children’s antisocial behavior is manifested as the type of limited adolescent antisocial behavior, and the three subtypes of left-behind children’s antisocial behavior were rule-breaking behavior, delinquent behavior and criminal behavior. In addition, the development of children’s antisocial behavior could range from general violations to delinquent behaviors and even to criminal behaviors

Design of remote wireless monitoring system for coal mine main ventilator

The main ventilator room of coal mine is remote and difficultly covered by wired network, so as to cause main ventilator monitoring system falling into information island. For above problem, a design scheme of remote wireless monitoring system for coal mine main ventilator based on mobile platform was put forward. The system uses a GPRS DTU to communicate with PLC for collecting field monitoring data, and the data is uploaded to a cloud data sever through GPRS network. On the other hand, mobile client based on Android system accesses the cloud data sever by use of socket communication mode through 3G, 4G or WiFi wireless network, so that users can remotely monitor operation status of coal mine main ventilator anytime and anywhere. The test results verify feasibility of the system

Can Treating Oneself Kindly Inspire Trust? The Role of Interpersonal Responsibility

Self-compassion, as a personal psychological resource, has been proved to play an important role in coping with suffering. Based on self-determination theory, the present study attempts to establish that self-compassion can promote trust, and the sense of interpersonal responsibility mediates this relationship. Study 1 used cross-sectional data in a community sample of 322 adults to reveal that self-compassion was positively related to trust, and the mediating effects of the sense of interpersonal responsibility were significant. Study 2 used the latent cross-lagged panel model among 1304 college students at three-time points set at six-month intervals to replicate the results and proved the longitudinal mediating effects across groups. Finally, a casual chain design was used to test the mediation effect in Studies 3 and 4. The results indicated that self-compassion induced by writing task resulted in a sense of responsibility in Study 3 (N = 145), and the manipulated sense of responsibility promoted both trust behaviors and beliefs in Study 4 (N = 125). Through four studies, this study highlights a novel but unexpected viewpoint that treating oneself in a self-compassionate way can not only help individuals cope with various challenges but also motivate them to obtain interpersonal benefits. These findings can help motivate community workers and mental health researchers to increase social capital by focusing on self-compassion and interpersonal responsibility