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نتیجه جستجو - Naturalistic

تعداد مقالات یافته شده: 7
ردیف عنوان نوع
1 Cuneate spiking neural network learning to classify naturalistic texture stimuli under varying sensing conditions
یادگیری شبکه عصبی اسپایک کانیت برای طبقه بندی محرکهای بافت طبیعی در شرایط مختلف سنجش-2020
We implemented a functional neuronal network that was able to learn and discriminate haptic features from biomimetic tactile sensor inputs using a two-layer spiking neuron model and homeostatic synaptic learning mechanism. The first order neuron model was used to emulate biological tactile afferents and the second order neuron model was used to emulate biological cuneate neurons. We have evaluated 10 naturalistic textures using a passive touch protocol, under varying sensing conditions. Tactile sensor data acquired with five textures under five sensing conditions were used for a synaptic learning process, to tune the synaptic weights between tactile afferents and cuneate neurons. Using post-learning synaptic weights, we evaluated the individual and population cuneate neuron responses by decoding across 10 stimuli, under varying sensing conditions. This resulted in a high decoding performance. We further validated the decoding performance across stimuli, irrespective of sensing velocities using a set of 25 cuneate neuron responses. This resulted in a median decoding performance of 96% across the set of cuneate neurons. Being able to learn and perform generalized discrimination across tactile stimuli, makes this functional spiking tactile system effective and suitable for further robotic applications.
Keywords: Spiking neural network | Neurorobotics | Cuneate neurons | Primary afferents | Tactile sensing | Synaptic weight learning
مقاله انگلیسی
2 Sites of Circadian Clock Neuron Plasticity Mediate Sensory Integration and Entrainment
سایت های زمانی نورون شبانه روزی انعطاف پذیر یکپارچه سازی و دغام حسی-2020
Networks of circadian timekeeping in the brain display marked daily changes in neuronal morphology. In Drosophila melanogaster, the striking daily structural remodeling of the dorsal medial termini of the small ventral lateral neurons has long been hypothesized to mediate endogenous circadian timekeeping. To test this model, we have specifically abrogated these sites of daily neuronal remodeling through the reprogramming of neural development and assessed the effects on circadian timekeeping and clock outputs. Remarkably, the loss of these sites has no measurable effects on endogenous circadian timekeeping or on any of the major output functions of the small ventral lateral neurons. Rather, their loss reduces sites of glutamatergic sensory neurotransmission that normally encodes naturalistic time cues from the environment. These results support an alternative model: structural plasticity in critical clock neurons is the basis for proper integration of light and temperature and gates sensory inputs into circadian clock neuron networks.
Keywords: circadian | entrainment | plasticity | temperature | Drosophila | Glutamate
مقاله انگلیسی
3 Using trajectory-level SHRP2 naturalistic driving data for investigating driver lane-keeping ability in fog: An association rules mining approach
استفاده از داده های رانندگی در سطح طبیعی SHRP2 مسیر رانندگی برای بررسی توانایی نگه داشتن خط راننده در مه: یک رویکرد کاوش قوانین انجمنی-2019
The presence of fog has a significant adverse impact on driving. Reduced visibility due to fog obscures the driving environment and greatly affects driver behavior and performance. Lane-keeping ability is a lateral driver behavior that can be very crucial in run-off-road crashes under reduced visibility conditions. A number of data mining techniques have been adopted in previous studies to examine driver behavior including lane-keeping ability. This study adopted an association rules mining method, a promising data mining technique, to investigate driver lane-keeping ability in foggy weather conditions using big trajectory-level SHRP2 Naturalistic Driving Study (NDS) datasets. A total of 124 trips in fog with their corresponding 248 trips in clear weather (i.e., 2 clear trips: 1 foggy weather trip) were considered for the study. The results indicated that affected visibility was associated with poor lane-keeping performance in several rules. Furthermore, additional factors including male drivers, a higher number of lanes, the presence of horizontal curves, etc. were found to be significant factors for having a higher proportion of poor lane-keeping performance. Moreover, drivers with more miles driven last year were found to have better lane-keeping performance. The findings of this study could help transportation practitioners to select effective countermeasures for mitigating run-off-road crashes under limited visibility conditions.
Keywords: Foggy weather conditions | Data mining techniques | Association rules mining | Lane-keeping | Naturalistic driving study | SHRP2 | Limited visibility
مقاله انگلیسی
4 Theorizing animal–computer interaction as machinations
تئوری تعامل حیوان و کامپیوتر به عنوان مکانیسم-2017
The increased involvement of animals in digital technology and user-computer research opens up for new possibilities and forms of interaction. It also suggests that the emerging field of Animal–Computer Interaction (ACI) needs to reconsider what should be counted as interaction. The most common already established forms of interaction are direct and dyadic, and limited to domesticated animals such as working dogs and pets. Drawing on an ethnography of the use of mobile proximity sensor cameras in ordinary wild boar hunting we emphasize a more complex, diffuse, and not directly observable form of interaction, which involves wild animals in a technological and naturalistic setting. Investigating human and boar activities related to the use of these cameras in the light of Actor-Network Theory (ANT) and Goffmans notion of strategic interaction reveals a gamelike interaction that is prolonged, networked and heterogeneous, in which members of each species is opposed the other in a mutual assessment acted out through a set of strategies and counter-strategies. We stress the role of theory for the field of ACI and how conceptualizations of interaction can be used to excite the imagination and be generative for design. Seeing interaction as strategies and acknowledging the existence of complex interdependencies could potentially inspire the design of more indirect and non-dyadic interactions where a priori simplifications of design challenges as either human or animal can be avoided.& 2016 Elsevier Ltd. All rights reserved.
Keywords:Animal–computer interaction | Actor-networktheory | Strategic interaction | Ontological symmetry | Ethnography
مقاله انگلیسی
5 تجزیه و تحلیل خوشه¬ای در مورد آغاز زودهنگام اختلال اضطراب رایج
سال انتشار: 2016 - تعداد صفحات فایل pdf انگلیسی: 8 - تعداد صفحات فایل doc فارسی: 24
آغاز زودهنگام ،یکی از ویژگی های مهم اختلال اضطراب، در ارتباط با مراتب شدید آن است. با این حال، با تغییر معنی شروع زودهنگام، یافته های اخیر از هم فاصله گرفته و بی اساس شده اند. ما با استفاده از داده های جمع آوری شده در جمعیت کلی و با استفاده از آنالیز خوشه ای، شروع زودهنگام را به صورت عینی در فوبیای اجتماعی، اختلال هراس ، ترس از مکان های شلوغ (انزواطلبی)، و اختلال هراس کلی تعریف کردیم. سن-های قطع حاصل برای شروع زودهنگام به این صورت است ≤ 22 (فوبیای اجتماعی)، ≤ 31 (اختلال هراس)، ≤ 21 (ترس از مکان های شلوغ)، و ≤ 27 (اختلال اضطراب کلی). مقایسه ی همبستگی (همبودی ) روانپزشکی و سلامت عمومی بین افراد مورد آزمایش از کل جمعیت در شروع زودهنگام و دیرهنگام و یک بستر سرپایی، نشان داد که در بین بیماران سرپایی همبودی اضطراب در شروع زودهنگام ترس از مکان شلوغ رایج تر بوده، اما اضطراب و همبودی خلق و خو در شروع دیرهنگام فوبیای اجتماعی رایج تر بوده اند. محدودیت اصلی در ارزیابی بالقوه شروع بود. نتایج ما مطالعات آینده را به همبستگی شروع زودهنگام اختلالات روانی تشویق می کند.
کلمات کلیدی: اختلالات اضطرابی | سرپایی | جمعیت عمومی | طبیعت گرایانه | سن شروع | آنالیز خوشه ای
مقاله ترجمه شده
6 The Potential Utility of Eye Movements in the Detection and Characterization of Everyday Functional Difficulties in Mild Cognitive Impairment
ابزار بالقوه از حرکات چشم در شناسایی و تعیین خصوصیات مشکلات کاربردی روزمره در اختلال خفیف شناختی-2015
Mild cognitive impairment (MCI) refers to the in- termediate period between the typical cognitive decline of normal aging and more severe decline associated with demen- tia, and it is associated with greater risk for progression to dementia. Research has suggested that functional abilities are compromised in MCI, but the degree of impairment and underlying mechanisms remain poorly understood. The devel- opment of sensitive measures to assess subtle functional de- cline poses a major challenge for characterizing functional limitations in MCI. Eye-tracking methodology has been used to describe visual processes in everyday, naturalistic action among healthy older adults as well as several case studies of severely impaired individuals, and it has successfully differ- entiated healthy older adults from those with MCI on specific visual tasks. These studies highlight the promise of eye- tracking technology as a method to characterize subtle func- tional decline in MCI. However, to date no studies have ex- amined visual behaviors during completion of naturalistic tasks in MCI. This review describes the current understanding of functional ability in MCI, summarizes findings of eye- tracking studies in healthy individuals, severe impairment, and MCI, and presents future research directions to aid with early identification and prevention of functional decline in disorders of aging. Keywords: Mild cognitive impairment | Everyday function | Naturalistic action | Activities of daily living | Eye tracking
مقاله انگلیسی
7 Driving risk assessment using near-crash database through data mining of tree-based model
ارزیابی ریسک با استفاده از پایگاه داده نزدیک به تصادف از طریق داده کاوی مدل مبتنی بر درخت-2015
Article history:Received 5 November 2014Received in revised form 11 May 2015 Accepted 3 July 2015Available online 27 August 2015Keywords:Naturalistic driving study Driving riskNear-crashClassification and regression tree (CART) K-mean clusterThis paper considers a comprehensive naturalistic driving experiment to collect driving data under poten- tial threats on actual Chinese roads. Using acquired real-world naturalistic driving data, a near-crash database is built, which contains vehicle status, potential crash objects, driving environment and road types, weather condition, and driver information and actions. The aims of this study are summarized into two aspects: (1) to cluster different driving-risk levels involved in near-crashes, and (2) to unveil the factors that greatly influence the driving-risk level. A novel method to quantify the driving-risk level of a near-crash scenario is proposed by clustering the braking process characteristics, namely maximum deceleration, average deceleration, and percentage reduction in vehicle kinetic energy. A classification and regression tree (CART) is employed to unveil the relationship among driving risk, driver/vehicle char- acteristics, and road environment. The results indicate that the velocity when braking, triggering factors, potential object type, and potential crash type exerted the greatest influence on the driving-risk levels in near-crashes.© 2015 Elsevier Ltd. All rights reserved.
Keywords: Naturalistic driving study | Driving risk | Near-crash | Classification and regression tree (CART) | K-mean cluster
مقاله انگلیسی
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