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نتیجه جستجو - TTS

تعداد مقالات یافته شده: 24
ردیف عنوان نوع
1 Extending Fitts’ law in three-dimensional virtual environments with current low-cost virtual reality technology
گسترش قانون Fitts در محیط های مجازی سه بعدی با فناوری واقعیت مجازی کم هزینه فعلی-2020
Virtual reality (VR) interfaces require users to perform three-dimensional reaching and pointing movements to interact with objects positioned within the users arms reach. However, there has been limited work that has evaluated the applicability of established models of human motor control to model performance of these tasks in 3D virtual reality environments using current low-cost technologies. In this study, a 3D discrete pointing task using the Oculus Rift system was used to explore potential influences on movement in VR and to account for these influences in a new formulation of Fitts’ law. Target size and distance from the starting point of movement were systematically varied to generate a broad range of index of difficulty (ID) values. Target locations were specified using a spherical coordinate system in which inclination angle corresponded to the pitch of the movement axis with respect to the starting point of movements and azimuth angle corresponded to the roll of the movement axis with respect to the horizontal plane. In line with previous work, we observed that target size, radial distance, and inclination angle had a significant effect on movement time. The effect of inclination angle varied with target size, which suggests that target size affected depth estimation. Significant target characteristics and interaction effects were used to develop an extended Fitts’ law model, which accounted for 64.5% of the variation in movement times. Comparisons to other Fitts’ law models revealed that models accounting for the effects of target depth improved predictive power relative to the traditional Fitts’ law formulation. Together, these findings support the value of extending Fitts’ law models to account for domain-specific constraints in VR environments. We discuss these results in the context of previous work examining HMD display deficiencies and discrete 3D pointing tasks, and suggest several directions for future work.
Keywords: Fitts’ law | Virtual reality | Oculus Rift | Depth perception | Stereoscopic display
مقاله انگلیسی
2 Engaging vulnerable populations in drug treatment court: Six month outcomes from a co-occurring disorder wraparound intervention
درگیر کردن جمعیت آسیب پذیر در دادگاه درمان مواد مخدر: نتایج شش ماهه از یک مداخله پیچیده اختلال همزمان-2020
Objective: Although drug treatment courts (DTCs) have demonstrated positive outcomes, participants with co- occurring mental health and substance use disorders (CODs) are a high-risk group that often struggle with treatment engagement not previously examined. This pilot study fills this gap by looking at six-month behavioral health and criminal justice outcomes among a hard to engage DTC COD participant sample in two Massachusetts DTCs receiving a wraparound-treatment (Maintaining Independence and Sobriety through Systems Integration, Outreach, and Networking-Criminal Justice - MISSION-CJ).Methods: Participants were evaluated at baseline and at six-month follow-up. Bivariate analyses examined baseline differences between clients with higher versus low engagement were examined. A mixed analysis of variance (ANOVA) for repeated measures with time as the within subject factor, and level of engagement as the between subject factor was performed for criminal justice (CJ) and behavioral health outcomes.Results: Participants were primarily male (86.6%), White (90.6%), living in unstable housing (86.2%), had an average of 18.94 years of criminal justice involvement, had an average of 15.49 years of regular illicit substance use, and mild mental health symptoms as measured by the BASIS-32 average total score (0.51), with no sta- tistically significant differences at baseline from bivariate analyses. Mixed ANOVA results demonstrated signif-icant effect time of time in MISSION-CJ on reducing nights in jail (p = 0.0266), opioid use (p = 0.0013), andmental health symptom (p = 0.0349). Additional improvements in nights in jail p = 0.0139), illicit substance use (p = 0.0358), and opioid use (p = 0.0013), were observed for clients that had high engagement in MISSION-CJ.Conclusions: Wraparound services, such as MISSION-CJ, alongside DTC programming for a chronic relapsing DTC population can improve engagement in treatment and CJ and behavioral health outcomes. Future research is needed with MISSION-CJ that includes a randomized trial and a larger sample.
Keywords: Specialty-courts | Relapse prevention | Engagement | Co-occurring disorders | Addiction | Substance use disorders | Mental health | Alternatives to incarceration
مقاله انگلیسی
3 Network properties of healthy and Alzheimer brains
خواص شبکه مغز سالم و آلزایمر-2020
The application of graph theory in diffusion weighted resonance magnetic images have allowed the description of the brain as a complex network, often called structural network. For many years, the small-world properties of brain networks have been studied and reported. However, few studies have gone beyond of clustering and characteristic path length. In this work, we compare the structural connection network of a healthy brain and a brain affected by Alzheimer’s disease with artificial small-world networks. Based on statistical analysis, we demonstrate how artificial networks can be constructed using Newman–Watts procedure. The network quantifiers of both structural matrices are identified inside a probabilistic valley. Despite of similarities between structural connection matrices and artificial small-world networks, increased assortativity can be found in the Alzheimer brain. Due to limited experimental data, we cannot define a direct link between Alzheimer’s disease and assortativity. Nevertheless, we intend to call attention for an important network quantifier that has been neglected. Our results indicate that network quantifiers can be helpful to identify abnormalities in real structural connections, for instance Alzheimer’s disease that disrupts the communication among neurons. One of our main results is to show that the network indicators of the Alzheimer brain are almost identical with the small-world network, except the assortativity.
Keywords: Network | Human brain | Alzheimer’s disease | Small-world
مقاله انگلیسی
4 The Integration of AI on Workforce Performance for a South African Banking Institution
ادغام هوش مصنوعی در عملکرد نیروی کار برای یک موسسه بانکی آفریقای جنوبی-2020
Artificial Intelligence advanced technologies are growing rapidly in th e banking sector. This research paper assesses the factors that contribute to a worker s Improved productivity and performance through tbe adoption and integration of artificial Intelligence to perform various activities in a South African banking Insututten. The different aspects of artificial intelligence toolset which include data, recognhlon, natural language processing, machine lear ning, robotics, planning, perceiving, problem-solving, and dectsfon making a re evaluated on how they influence the workforce performance which is measured through competencies, capabilities, satisfaction, motivation and so forth. Also, these aspects are evaluated in terms of their contributions towards productivity when integrated with the ana lytica l and organized stra tegies that advance the workforces performance. The ultimate purpose is to improve the workforces performance in the South African banking tnsutunon and ensure successful adaptation tn artificial intelligence. Descriptive statistics have been adopted with the use of frequ ency distribution tables to an alyze and present tbe information on the variables of interest. The outcomes evaluated with th e descriptive and tnrerenetst stattsetc s based on the variables hav e shown that artificial intelligence bas a relatively strong impact on workforce performance. Therefore, it is essential and recommended for tbe banking institution to adopt and integrate artificial intelligence witb wcrkrcrces because the next frontier for shared serv ices may be far more interesting, Incorporating greater computing power and a rt ificial intelligence into robotics, 50 that the differences between buman perception and intelligent automation become indistinct.
Keywords : artificial intelligence | robotics | banks | worllforces performance | machine learning
مقاله انگلیسی
5 Rehabilitation Intervention in an Ice Hockey Context: What Changes under the Helmet
مداخله توانبخشی در زمینه هاکی روی یخ: آنچه در زیر کلاه ایمنی تغییر می کند-2020
Most studies of sport-based interventions in rehabilitation settings with youth with disruptive behaviors look at their effects. To our knowledge, there are few studies of the processes by which these interventions allow participants to benefit from them. This article looks at the process of therapeutic change based on the subjective theories concept and is inspired by the significant events approach. The participants are five young people receiving services under the Youth Protection Act or the Youth Criminal Justice Act for adolescents who took part in a rehabilitative intervention in an ice hockey context. All of these young people have experienced early relational traumas. A semi-structured interview on the highlights of their participation was conducted at the end of the activity. A qualitative content analysis aimed at identifying psychological changes and an interpretative phenomenological analysis intended to explore their experience in the intervention revealed psychological changes and linked them to significant events. The results support the idea that psychological change is a singular process. In order to capture the clinical significance, the results were linked to Winnicotts theoretical elaboration of the parent-child relationship in the context of early relational trauma.
Keywords: sport-based interventions | rehabilitation | disruptive behaviors | therapeutic change | significant events
مقاله انگلیسی
6 End-to-end Conversion Speed Analysis of an FPT.AI-based Text-to-Speech Application
تجزیه و تحلیل سرعت تبدیل پایان به پایان یک برنامه متن به گفتار مبتنی بر FPT.AI-2020
In this paper, an FPT.AI-based text-to-speech (TTS) application is developed that converts Vietnamese text into spoken words. The application is developed based on Django for Python and in the form of an interactive web page which is connected to an FPT.AI server through its application programming interface (API). The application supports conversion of text to seven different Vietnamese speeches. Four out of seven voices can be used to convert up to 500 characters in a single transaction while the others support that of 400 characters. Based on the results obtained, the first conversion time takes up to 10 s to convert 400-character text into speech while the subsequent times, given same text, it takes under 1.8 s for the conversion. This is applicable to all voices.
Keywords: FPT.AI | TTS | performance | analysis | Vietnamese | voice
مقاله انگلیسی
7 Machine learning phase transition: An iterative proposal
فاز انتقال یادگیری ماشین: یک پیشنهاد تکرار شونده-2019
We propose an iterative proposal to estimate critical points for statistical models based on configurations by combing machine-learning tools. Firstly, phase scenarios and preliminary boundaries of phases are obtained by dimensionality-reduction techniques. Besides, this step not only provides labelled samples for the subsequent step but also is necessary for its application to novel statistical models. Secondly, making use of these samples as training set, neural networks are employed to assign labels to those samples between the phase boundaries in an iterative manner. Newly labelled samples would be put in the training set used in subsequent training and the phase boundaries would be updated as well. The average of the phase boundaries is expected to converge to the critical temperature in this proposal. In concrete examples, we implement this proposal to estimate the critical temperatures for two q-state Potts models with continuous and first order phase transitions. Linear and manifold dimensionality-reduction techniques are employed in the first step. Both a convolutional neural network and a bidirectional recurrent neural network with long short-term memory units perform well for two Potts models in the second step. The convergent behaviors of the estimations reflect the types of phase transitions. And the results indicate that our proposal may be used to explore phase transitions for new general statistical models.
مقاله انگلیسی
8 Evaluation of predictive capabilities of ordinary geostatistical interpolation, hybrid interpolation, and machine learning methods for estimating PM2:5 constituents over space
ارزیابی قابلیت های پیش بینی کننده یابی درون زمین آماری معمولی ، درون یابی ترکیبی و روش های یادگیری ماشین برای برآورد ترکیبات PM2:5 بر روی فضا-2019
Numerous modeling approaches to estimate concentrations of PM2.5 components have been developed to derive better exposures for health studies, including geostatistical interpolation approaches, land use regression models and, models based on remote sensing technology. Recently, there have been some efforts to develop models based on machine learning algorithms. Each one of these exposure assessment methods has inherent uncertainties resulting in varying levels of exposure misclassification. To date, only a few studies have attempted to systematically compare exposure estimates from different PM2.5 constituent models. Our research addresses this gap, by comparing the predictive capabilities of ordinary geostatistical interpolation (Ordinary Kriging – OK), hybrid interpolation (combination of Empirical Bayesian Kriging and land use regression), and machine learning techniques (forest-based regression) for estimating PM2.5 constituents in Eastern Massachusetts in the United States. We compared the estimates of 10 ambient PM2.5 components, which included Al, Cu, Fe, K, Ni, Pb, S, Ti, V, and Zn. The OK model performed poorest for all PM2.5 components, with an R2 under 0.30. The hybrid model presented a slight improvement, especially for Cu and Fe, for which the R2 value increased to 0.62 and 0.59, respectively. These elements presented the highest R2 value from the hybrid model. The forest model presented the best performance, with R2 values higher than 0.7 for most of the particle components, including Cu, Fe, Ni, Pb, Ti, and V. Same as observed with the hybrid model, the forest model for Cu and Fe explained the highest concentration variance, with a R2 value equal to 0.88 and 0.92, respectively. The forest model for K, S, and Zn performed poorest with an R2 value of 0.54, 0.37, and 0.44, respectively. The results presented here can be useful for the environmental health community to more accurately estimate PM2.5 constituents over space.
Keywords: Air pollution | PM2.5 components | Geostatistical interpolation | Machine learning
مقاله انگلیسی
9 Gender gap in entrepreneurship
شکاف جنسیتی در کارآفرینی-2019
Using data on the entire population of businesses registered in the states of California and Massachusetts between 1995 and 2011, we decompose the well-established gender gap in entrepreneurship. We show that femaleled ventures are 63 percentage points less likely than male-led ventures to obtain external funding (i.e., venture capital). The most significant portion of the gap (65 percent) stems from gender differences in initial startup orientation, with women being less likely to found ventures that signal growth potential to external investors. However, the residual gap is as much as 35 percent and much of this disparity likely reflects investors’ gendered preferences. Consistent with theories of statistical discrimination, the residual gap diminishes significantly when stronger signals of growth are available to investors for comparable female- and male-led ventures or when focal investors appear to be more sophisticated. Finally, conditional on the reception of external funds (i.e., venture capital), women and men are equally likely to achieve exit outcomes, through IPOs or acquisitions.
Keywords: Entrepreneurship | Gender | Venture capital | Discrimination
مقاله انگلیسی
10 Novel systematic mathematical computation based on the spiking frequency gate (SFG): Innovative organization of spiking computer
محاسبات ریاضی سیستماتیک رمان مبتنی بر دروازه فرکانس سنبله (SFG): سازمان نوآورانه رایانه های سنبله-2019
The idea that the brain is composed of logical gates similar to IP cores of today’s computers were provided by McCulloch and Pitts in 1943. In this paper, six structures for the inter- action of dynamic neurons have been proposed to create neural circuits with spike coding that operate similarly to Boolean gates. It was concluded that the network of the dynamic model of spiking neurons and synapses called spiking frequency gates (SFG) can emulate the operations of digital gates AND, OR, NOT, NOR, XOR, and NAND. Also, an attempt was made to construct complex spiking circuits like full-adder, multiplexer, and arithmetic- logic-unit using cascade connections of SFGs. Extending simple designs to more complex spiking circuits can continue in order to access sophisticated computing tools based on SFGs. SFGs are not limited to zero and one and respond to the continuous range of spike train frequencies. Therefore, the information coding of SFGs is more powerful than Boolean gates. This paper illustrates a novel Boolean computation platform in a neural-like manner, which can provide a potential and clear horizon for designing neural circuits with complex applications. We hope that our results will lead to a deeper comprehension of the brain’s functionalities and the development of new systematic methods based on the proposed spiking approach of Boolean logic gates.
Keywords: Spiking frequency gates | Boolean computation | Spiking circuit | Information coding | Pattern recognition
مقاله انگلیسی
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