Probabilistic movement modeling for intention inference in human-robot interaction.

Intention inference can be an essential step toward efficient humanrobot interaction. For this purpose, we propose the Intention-Driven Dynamics Model (IDDM) to probabilistically model the generative process of movements that are directed by the intention. The IDDM allows to infer the intention from observed movements using Bayes ’ theorem. The IDDM simultaneously finds a latent state representation of noisy and highdimensional observations, and models the intention-driven dynamics in the latent states. As most robotics applications are subject to real-time constraints, we develop an efficient online algorithm that allows for real-time intention inference. Two human-robot interaction scenarios, i.e., target prediction for robot table tennis and action recognition for interactive humanoid robots, are used to evaluate the performance of our inference algorithm. In both intention inference tasks, the proposed algorithm achieves substantial improvements over support vector machines and Gaussian processes.

FuSSI-Net: Fusion of Spatio-temporal Skeletons for Intention Prediction Network

Pedestrian intention recognition is very important to develop robust and safe autonomous driving (AD) and advanced driver assistance systems (ADAS) functionalities for urban driving. In this work, we develop an end-to-end pedestrian intention framework that performs well on day- and night- time scenarios. Our framework relies on objection detection bounding boxes combined with skeletal features of human pose. We study early, late, and combined (early and late) fusion mechanisms to exploit the skeletal features and reduce false positives as well to improve the intention prediction performance. The early fusion mechanism results in AP of 0.89 and precision/recall of 0.79/0.89 for pedestrian intention classification. Furthermore, we propose three new metrics to properly evaluate the pedestrian intention systems. Under these new evaluation metrics for the intention prediction, the proposed end-to-end network offers accurate pedestrian intention up to half a second ahead of the actual risky maneuver.Comment: 5 pages, 6 figures, 5 tables, IEEE Asilomar SS

PENGARUH JOB SATISFACTION DAN JOB INSECURITY TERHADAP TURNOVER INTENTION PADA COFFEE SHOP KOTA MALANG

This research aims to determine the influence of job satisfaction and job insecurity on turnover intention at Coffee Shops in Malang City. The sample in this study consisted of 55 employees using a purposive sampling technique. This type of research is explanatory research with a quantitative approach. The data collection technique in this research uses a questionnaire. The data analysis techniqueuses a range of scales and multiple linear regression with the SPSS version 27 software. The research results show that job satisfaction has a significant effect on turnover intention, job insecurity has a significant effect on turnover intention, job satisfaction and job insecurity have a significant effect on turnover intention, and job insecurity is the variable that has the most influence on turnover intention

Metaphor, indeterminacy, and intention

David Cooper has argued that it is a constraint on any acceptable theory of metaphor that it account for the 'indeterminacy' of metaphorical content, that is, the sense that many metaphors admit of more than one acceptable interpretation, none of which can be uniquely demonstrated to be correct. He further argues that the 'speaker's meaning' model of metaphorical content proposed by Searle and others cannot meet this constraint, and thus must be disregarded as a prospective account of such content. In this paper I argue firstly that Cooper's characterisation of the proposed constraint is misguided, and that we should be careful to distinguish the role that intention plays in determining metaphorical content from the question of whether we can have satisfying interpretations of metaphors that do not take speaker intention into account. I then give my own characterisation of the problem, relating it to a more general tension between the intuition that first person ascriptions of intentions carry a certain authority, and the fact that it seems to misrepresent the phenomenology of metaphor production to ascribe to the speaker a pre-existing and precise cognitive content which his metaphorical utterance is intended to convey. I go on to argue that we can resolve this tension by following Crispin Wright in viewing self ascriptions of intention as essentially response dependent; with our best judgements constituting rather than tracking the facts about what we intend. I conclude that while such an account must be refined in order to distinguish intentions related to specifically metaphorical content from the literal case, the general shape of the account is sufficient to remove the intuitions that Cooper's objection trades on

Anticipating Daily Intention using On-Wrist Motion Triggered Sensing

Anticipating human intention by observing one's actions has many applications. For instance, picking up a cellphone, then a charger (actions) implies that one wants to charge the cellphone (intention). By anticipating the intention, an intelligent system can guide the user to the closest power outlet. We propose an on-wrist motion triggered sensing system for anticipating daily intentions, where the on-wrist sensors help us to persistently observe one's actions. The core of the system is a novel Recurrent Neural Network (RNN) and Policy Network (PN), where the RNN encodes visual and motion observation to anticipate intention, and the PN parsimoniously triggers the process of visual observation to reduce computation requirement. We jointly trained the whole network using policy gradient and cross-entropy loss. To evaluate, we collect the first daily "intention" dataset consisting of 2379 videos with 34 intentions and 164 unique action sequences. Our method achieves 92.68%, 90.85%, 97.56% accuracy on three users while processing only 29% of the visual observation on average

PENGARUH IKLIM ORGANISASI TERHADAP INTENTION TO STAY PADA PT MUSLA TRANS UTAMA DENGAN EMPLOYE ENGANGEMENT SEBAGAI VARIABEL INTERVENING

Penelitian bertujuan untuk mengetahui serta menganalisis pengaruh iklim organisasi terhadap intention to stay pada PT Musla Trans Utama dengan employee engangement sebagai variabel intervening. Teknik pengambilan sampel pada penelitian ini dengan menggunakan teknik proportionate random sampling dengan jumlah sampe sebanyak 98 karyawan. Teknik pengumpulan data menggunakan kuesioner. Teknik analisis data menggunakan analisis jalur dengan program Smart-PLS. Hasil penelitian ini menunjukkan bahwa iklim organisasi tidak berpengaruh terhadap intention to stay, iklim organisasi berpenagruh positif dan signifikan terhadap employee engangement, employe engangement berpengaruh positif dan signifikan terhadap intention to stay, iklim organisasi berpengaruh secara positif fan signifikan terhadap intention to stay dengan employee engangement sebagai variabel intervening

Fuzzy logic based intention recognition in STS processes

This paper represents a fuzzy logic based classifier that is able to recognise human users' intention of standing up from their behaviours in terms of the force they apply to the ground. The research reported focused on the selection of meaningful input data to the classifier and on the determination of fuzzy sets that best represent the intention information hidden in the force data. The classifier is a component of a robot chair which provides the users with assistance to stand up based on the recognised intention by the classifier

Comparing the Job Satisfaction and Intention to Leave of Different Categories of Health Workers in Tanzania, Malawi, and South Africa.

Job satisfaction is an important determinant of health worker motivation, retention, and performance, all of which are critical to improving the functioning of health systems in low- and middle-income countries. A number of small-scale surveys have measured the job satisfaction and intention to leave of individual health worker cadres in different settings, but there are few multi-country and multi-cadre comparative studies. The objective of this study was to compare the job satisfaction and intention to leave of different categories of health workers in Tanzania, Malawi, and South Africa. We undertook a cross-sectional survey of a stratified cluster sample of 2,220 health workers, 564 from Tanzania, 939 from Malawi, and 717 from South Africa. Participants completed a self-administered questionnaire, which included demographic information, a 10-item job satisfaction scale, and one question on intention to leave. Multiple regression was used to identify significant predictors of job satisfaction and intention to leave. There were statistically significant differences in job satisfaction and intention to leave between the three countries. Approximately 52.1% of health workers in South Africa were satisfied with their jobs compared to 71% from Malawi and 82.6% from Tanzania (χ2=140.3, p<0.001). 18.8% of health workers in Tanzania and 26.5% in Malawi indicated that they were actively seeking employment elsewhere, compared to 41.4% in South Africa (χ2=83.5, p<0.001). The country differences were confirmed by multiple regression. The study also confirmed that job satisfaction is statistically related to intention to leave. We have shown differences in the levels of job satisfaction and intention to leave between different groups of health workers from Tanzania, Malawi, and South Africa. Our results caution against generalising about the effectiveness of interventions in different contexts and highlight the need for less standardised and more targeted HRH strategies than has been practised to date

Intention to create legal relations and the reform of contract law: A conservative approach in the modern global era

This paper is partially to refute the submissions by Gulati’s article recently published on Beijing Law Review which proposes abandoning the requirement of proving intention to create legal relations for the formation of an enforceable contract. After a critical analysis of the abandonists’ arguments, this paper argues that intention to create legal relations is the “marrow of contractual relationships” and the arguments for abandoning such a requirement because of the existence of consideration and/or offer and acceptance as test(s) of contractual enforceability is untenable and unconvincing. Consideration and/or offer and acceptance may be evidence of serious intention to be bound somehow but unnecessary intention to be bound legally. For a number of reasons, the doctrine of consideration is very unlikely to work any better than the intention to create legal relations test. If a test of contractual enforceability must be abandoned, that should be the doctrine of consideration rather than the intention to create legal relations. This paper compares the current positions of some common law jurisdictions, upholds the needs of stability, consistency, and the harmonisation of contract law in the modern global era, and proposes a conservative approach of contract law reform regarding the intention requirement and the related presumptions, that is, all common law jurisdictions should “go back” to the orthodox English position

Detection of intention level in response to task difficulty from EEG signals

We present an approach that enables detecting intention levels of subjects in response to task difficulty utilizing an electroencephalogram (EEG) based brain-computer interface (BCI). In particular, we use linear discriminant analysis (LDA) to classify event-related synchronization (ERS) and desynchronization (ERD) patterns associated with right elbow flexion and extension movements, while lifting different weights. We observe that it is possible to classify tasks of varying difficulty based on EEG signals. Additionally, we also present a correlation analysis between intention levels detected from EEG and surface electromyogram (sEMG) signals. Our experimental results suggest that it is possible to extract the intention level information from EEG signals in response to task difficulty and indicate some level of correlation between EEG and EMG. With a view towards detecting patients' intention levels during rehabilitation therapies, the proposed approach has the potential to ensure active involvement of patients throughout exercise routines and increase the efficacy of robot assisted therapies