Design and implementation of domain-specific cognitive system based on question similarity algorithm

The cognitive system is an artificial intelligence product that integrates natural language processing techniques. The biggest d on logical reasoning, which can help users improve exploration and accelerate discovery. On the basis of natural language processing and logical reasoning, the paper adopts similarity algorithm bas difference between big data analysis systems and cognitive systems is that cognitive systems can directly deal with the problems raised by natural language forms and provide predictions baseded on question sentences, designs a cognitive system for specific domains, and finally realizes it on the NAO robot platform.     

Bioinspired decision-making for a socially interactive robot

Nowadays, robots and humans coexist in real settings where robots need to interact autonomously making their own decisions. Many applications require that robots adapt their behavior to different users and remember each user’s preferences to engage them in the interaction. To this end, we propose a decision making system for social robots that drives their actions taking into account the user and the robot’s state. This system is based on bio-inspired concepts, such as motivations, drives and wellbeing, that facilitate the rise of natural behaviors to ease the acceptance of the robot by the users. The system has been designed to promote the human-robot interaction by using drives and motivations related with social aspects, such as the users’ satisfaction or the need of social interaction. Furthermore, the changes of state produced by the users’ exogenous actions have been modeled as transitional states that are considered when the next robot’s action has to be selected. Our system has been evaluated considering two different user profiles. In the proposed system, user’s preferences are considered and alter the homeostatic process that controls the decision making system. As a result, using reinforcement learning algorithms and considering the robot’s wellbeing as the reward function, the social robot Mini has learned from scratch two different policies of action, one for each user, that fit the users’ preferences. The robot learned behaviors that maximize its wellbeing as well as keep the users engaged in the interactions.     

Examining multiple feature evaluation and classification methods for improving the diagnosis of Parkinson’s disease

An accurate diagnosis of Parkinson’s disease by specialists involves many neurological, psychological and physical examinations. The specialists investigate a number of symptoms and signs when examining the nervous system conditions of a person. The diagnosis involves reviewing the medical history and genetic factor of the person. The recent diagnosis methodology to Parkinson’s disease relies on voice disorders analysis. This methodology entails extracting feature sets of a recorded person’s voice then utilizing a machine learning technique to identify the healthy and Parkinson’s cases from the voice. This paper attempts to improve the diagnoses of Parkinson’s disease by testing multiple feature evaluation and classification machine learning methods based on the voice disorders analysis. The aim of this paper is to find the optimal solution to the problem by (i) proposing a new Multiple Feature Evaluation Approach (MFEA) of a multi-agent system (ii) implementing five independent classification schemas which are Decision Tree, Naïve Bayes, Neural Network, Random Forests, and Support Vector Machine on the Parkinson’s diagnosis before and after applying the MFEA, and (iii) evaluating the diagnosis accuracy of the results. The methodology of the tests encompasses 10-fold cross-validation to evaluate the learning of methods and track variation in their performance. The test results show that the MFEA of the multi-agent system finds the best set of features and improves the performance of the classifiers. The average rate of improvement in the diagnostic accuracy of the classifiers are Decision Tree 10.51%, Naïve Bayes 15.22%, Neural Network 9.19%, Random Forests 12.75%, and Support Vector Machine 9.13%. These results show that the MFEA makes a significant improvement to the classifiers’ diagnosis results.     

Measuring driving workload of heavy vehicles at roundabouts

Correctly designed roundabouts proved to have positive safety and functional performances. However, they are also affected by peculiar disadvantages. In particular, they are difficult to manoeuvre, especially for heavy vehicle drivers. Despite these concerns, there are currently no driving workload metrics devoted to roundabouts.A novel methodological approach is proposed for trying to quantify workload impinging on heavy vehicle drivers when manoeuvring through complex at-grade intersections. Proper acquisition of input data constitutes the starting point for future research about ascertainment of workload for these particular road scenarios. The described procedure enables recording steering wheel angles performed by a driver when manoeuvring an articulated lorry through a complex at-grade intersection. A field trial was carried out for verifying the practical feasibility of proposed method in capturing driver’s steering behaviour. Dynamic data acquired via global navigation satellite system instrumentation were related to actual driver’s steering wheel behaviour captured by camera frames. As a complement to the experiment, selected steering behaviour metrics were calculated. Steering Entropy attributed a high difficulty level to the manoeuvres performed through the roundabout, whereas High Frequency Component and Steering Reversal Rate showed intensity and occurrences of driver’s corrections needed for controlling position of the semitrailer at the ring. It appears that even a single roundabout may represent an arduous task for drivers. The study concludes with recommendations for further research about workload imposed by roundabouts to heavy vehicle drivers, with special attention to successions of closely spaced roundabouts.     

School-Based Mental Health Services: Definitions and Models of Effective Practice

ABSTRACT

School-based mental health services are those delivered by school-employed and community-employed providers in school buildings. With the implementation of provisions of the Patient Protection and Affordable Care Act (2010) that funds school-based health centers, school-based mental health services could become more broadly available in communities throughout the United States. Playing a pivotal role in promoting models for school-based services that maximize benefits to children and adolescents while making efficient use of communities' mental health resources are school psychologists. School psychologists, who recognize and respect the separated development of school and community mental health professions, can foster school–agency partnerships to coordinate children's mental health services that are comprehensive, child centered, family focused, and culturally competent. In this article, we provide three case examples using the Participatory Culture-Specific Intervention Model (B. K. Nastasi, R. B. Moore, & K. M. Varjas, 2004 Nastasi, B. K., Moore, R. B., & Varjas, K. M. (2004). School-based mental health services: Creating comprehensive and culturally specific programs. Washington, DC: American Psychological Association. [Google Scholar]) as exemplars for the implementation of community partnerships providing comprehensive culturally and contextually relevant school-based mental health services.     

虚拟场景中不同客体朝向条件对内在参照系建立的影响

通过眼动记录和部分场景再认两种方法,探讨了虚拟建筑物对称场景中物体朝向统一、凸显两种条件对内在参照系建立的影响。结果发现:(1)场景中均为有朝向建筑物且朝向统一时,被试选择物体朝向与对称轴建立内在参照系的可能性没有差异;(2)场景中只有一个有朝向建筑物,其余均为无朝向物体时,即朝向凸显条件下,被试倾向于选择对称轴来建立内在参照系。物体朝向对内在参照系建立的影响作用具有局限性和不稳定性。     

Negotiating Ethical Paradoxes in Conducting a Randomized Controlled Trial: Aligning Intervention Science with Participatory Values

In this article, we describe ethical tensions we have faced in the context of our work as intervention scientists, where we aim to promote social justice and change systems that impact girls involved in the juvenile legal system. These ethical tensions are, at their core, about resisting collusion with systems of control while simultaneously collaborating with them. Over the course of designing and implementing a randomized controlled trial (RCT) of an ecological advocacy intervention for girls, called ROSES, ethical paradoxes crystalized and prompted us to engage in critical reflection and action toward the aim of moving away from conducting research on legal‐system‐involved girls and moving toward a more democratic, participatory process of inquiry with girls. Our experience revealed two intertwined paradoxes that ultimately served generative purposes. First, in collaborating with legal system stakeholders, we observed a single story of girls’ pathology narrated for girls, without girls, and ultimately internalized by girls. Second, in reflecting critically on the ethical implications of our study design, it became clear that the design was grounded in a medical model of inquiry although the intervention we sought to evaluate was based, in part, on resistance to the medical model. We describe emergent ethical tensions and the solutions we sought, which center on creating counternarratives and counterspaces that leverage, extend, and disrupt our existing RCT. We detail these solutions, focusing on how we restructured our research team to enhance structural competence, shifted the subject of inquiry to include the systems in which youth are embedded, and created new opportunities for former research participants to become co‐researchers through formal roles on an advisory board.     

Accountability,Collaboration, and Social Change: Ethical Tensions in an Action Research Project to Address Untested Sexual Assault Kits (SAKs)

We conducted a collaborative action research project with stakeholders in Detroit, Michigan, to develop long‐term policy strategies to resolve ~11,000 untested rape kits that were discovered in a police storage facility in August 2009. In our research, we uncovered overwhelming evidence of victim‐blaming behaviors and fundamental disrespect of rape survivors by the police, which directly contributed to their decisions not to submit kits for forensic testing. We had an ethical responsibility to report these negative findings accurately and completely, and in doing so, we were concerned that police stakeholders might disengage from the action research project and hamper our other ethical responsibilities to promote general and public welfare. In this article, we examine the ethical challenges of balancing accountability, collaboration, and social change.     

Comparison of the trunk-pelvis and lower extremities sagittal plane inter-segmental coordination and variability during walking in persons with and without chronic low back pain

Inter-segmental coordination can be influenced by chronic low back pain (CLBP). The sagittal plane lower extremities inter-segmental coordination pattern and variability, in conjunction with the pelvis and trunk, were assessed in subjects with and without non-specific CLBP during free-speed walking. Kinematic data were collected from 10 non-specific CLBP and 10 non-CLBP control volunteers while the subjects were walking at their preferred speed. Sagittal plane time-normalized segmental angles and velocities were used to calculate continuous relative phase for each data point. Mean absolute relative phase (MARP) and deviation phase (DP) were derived to quantify the trunk-pelvis and bilateral pelvis-thigh, thigh-shank and shank-foot coordination pattern and variability over the stance and swing phases of gait. Mann-Whitney U test was employed to compare the means of DP and MARP values between two groups (same side comparison). Statistical analysis revealed more in-phase/less variable trunk-pelvis coordination in the CLBP group (P < 0.05). CLBP group demonstrated less variable right or left pelvis-thigh coordination pattern (P < 0.05). Moreover, the left thigh-shank and left shank-foot MARP values in the CLBP group, were more in-phase than left MARP values in the non-CLBP control group during the swing phase (P < 0.05). In conclusion, the sagittal plane lower extremities, pelvis and trunk coordination pattern and variability could be generally affected by CLBP during walking. These changes can be possible compensatory strategies of the motor control system which can be considered in the CLBP subjects.     

运动技能水平与躯体感觉输入对运动表象的影响

运动表象质量与运动技能水平有关,运动表象质量随着运动技能水平的提高而上升。器械使用可使人脑产生可塑性改变,使用者会将器械纳入身体图式。然而,两者影响运动表象的神经心理机制还不清楚。本研究采用功能性磁共振成像探析篮球运动员与新手在不同持球条件下表象投篮时脑功能活动的差异。结果表明运动员表象质量较好,镜像神经系统激活高于新手;持球条件下运动员表象质量显著高于不持球条件下,镜像神经系统激活程度显著低于不持球条件下。研究说明持器械可以显著提高运动员的表象质量,器械使用带来镜像神经系统的可塑性变化。