Supersymmetric backgrounds from 5d N=1 supergravity

We construct curved backgrounds with Euclidean signature admitting rigid supersymmetry by using a 5d N=1 off-shell Poincare supergravity. We solve the conditions for the background Weyl multiplet and vector multiplets that preserve at least one supersymmetry parameterized by a symplectic Majorana spinor, and represent the solution in terms of several independent fields. We also show that the partition function does not depends on the local degrees of freedom of the background fields. Namely, as far as we focus on a single coordinate patch, we can freely change the independent fields by combining Q-exact deformations and gauge transformations. We also discuss realization of several known examples of supersymmetric theories in curved backgrounds by using the supergravity.Comment: 31 pages, no figures; v2: references adde

On local likelihood asymptotics for Gaussian mixed-effects model with system noise

The Gaussian mixed-effects model driven by a stationary integrated Ornstein-Uhlenbeck process has been used for analyzing longitudinal data having an explicit and simple serial-correlation structure in each individual. However, the theoretical aspect of its asymptotic inference is yet to be elucidated. We prove the local asymptotics for the associated log-likelihood function, which in particular guarantees the asymptotic optimality of the suitably chosen maximum-likelihood estimator. We illustrate the obtained asymptotic normality result through some simulations for both balanced and unbalanced datasets.Comment: 11 pages, 3 figure

Design of facial recognition system implemented in an unmanned aerial vehicle for citizen security in Latin America

In the new technological era, facial recognition has become a central issue for a great number of engineers. Currently, there are a great number of techniques for facial recognition, but in this research, we focus on the use of deep learning. The problems with current facial recognition convection systems are that they are developed in non-mobile devices. This research intends to develop a Facial Recognition System implemented in an unmanned aerial vehicle of the quadcopter type. While it is true, there are quadcopters capable of detecting faces and/or shapes and following them, but most are for fun and entertainment. This research focuses on the facial recognition of people with criminal records, for which a neural network is trained. The Caffe framework is used for the training of a convolutional neural network. The system is developed on the NVIDIA Jetson TX2 motherboard. The design and construction of the quadcopter are done from scratch because we need the UAV for adapt to our requirements. This research aims to reduce violence and crime in Latin America

Developing a novel haptic device for non-rigid computer graphic objects utilizing unmanned aerial vehicles

In this paper, we propose a novel haptic device consisting of a Parrot quadcopter AR Drone 2.0 that delivers force-feedback to users when they press on the surface of the drone in the vertical direction. This drone haptic device will free users from any cumbersome devices which were utilized in previous haptics systems and allow them to sense kinesthetic feedback coming from the drone which in turn renders computer graphic objects, for example, a virtual box. Specifically, this system performs damped harmonic oscillation force motion on users’ hands and fingers. The oscillation function is implemented on the drone whenever users nudge the drone down. Overall, we evaluated the system with ten subjects, and results show the effectiveness of using damping oscillation motion to provide force-feedback delivered from the drone

Speech Recognition and Speech Synthesis Models for Micro Devices

With the advent and breakthrough of interaction between humans and electronic devices using speech in communication, we have seen a lot of applications using speech recognition and speech synthesis technology. There are some limitations we have identified to these applications. Availability of a lot of resources and internet connectivity have made it possible in making case but with limited resources it is quite difficult to achieve this feat. As a result, it limits the application of the technology into micro devices and deploying them into areas where there are no internet connectivity. In this article, we developed a smaller Deep Neural Network models for Automatic Speech Recognition (ASR) and Text-to-Speech (TTS) for communication on micro devices such as Raspberry Pi. We tested and evaluated the models of the system. The accuracy and the performance of the models to be implemented on micro devices shows that they are good for application development in micro devices

Recognition for Objects by Relationships Between Attributes

Object recognition methods based on attributes have been studied. Conventional methods recognize objects by the presence or absence of attributes. However, the conventional methods have two problems. Firstly, the conventional methods are not able to recognize a target object of which a part of attributes is occluded. Secondly, the conventional methods miss-recognize a target object, which has irrelevant attributes. Therefore, to solve these two problems, we propose the object recognition by relationships between attributes. In this paper, we focus on the face as the recognition object. The proposed method uses relationships as constraints for object recognition using attributes. The proposed method applies two major type constraints. The first constraint is a local constraint, which is applied to a part of attributes. To achieve robust face recognition against occlusion scenes, the proposed method uses the local constraint. And then, the second constraint is a global constraint, which is applied to all attributes. To achieve robust face recognition against irrelevant attributes, the proposed method uses the global constraint. In this paper, to evaluate the effectiveness of the proposed method, we compared the proposed method with a conventional method. We experimented in normal face, occlusion and irrelevant attributes. We used 2580 images of a face which are changed in scale and rotation. Experimental results showed that the recognition ratio of the proposed method is equal to or more than that of the conventional method in normal face, occlusion, and irrelevant attributes

A CG Generation Method of Wash Drawing

The opportunity of process the image increases, the research on generating the image like the painting became on important in recent years. Generally individual image blog shape contents open to the public chance is increase. In the painting, the drawing in ink and wash has the feature with a framing of the outline of the Iras key of G and an especially light color. Generally, it is a technique for coloring in the watercolor with a high transparency after it sketches with the pencil etc. and the brush. The outline of the image is extracted to reproduce this technique, and the stroke of the brush is reproduced. Coloring segments the area according to the inclination, and smoothes the inside.2009 International Conference on Complex, Intelligent and Software Intensive Systems (CISIS) : Fukuoka, Japan, 2009.03.16-2009.03.1

Clinical and genetic aspects of mild hypophosphatasia in Japanese patients

Background: Hypophosphatasia (HPP) is a rare inborn error of metabolism that results from a dysfunctional tissue non-specific alkaline phosphatase enzyme (TNSALP). Although genotype-phenotype correlations have been described in HPP patients, only sparse information is currently available on the genetics of mild type HPP. Methods: We investigated 5 Japanese patients from 3 families with mild HPP (patients 1 and 2 are siblings; patient 4 is a daughter of patient 5) who were referred to Fujita Health University due to the premature loss of deciduous teeth. Physical and dental examinations, and blood, urine and bone density tests were conducted. Genetic analysis of the ALPL gene was performed in all patients with their informed consent. Results: After a detailed interview and examination, we found characteristic symptoms of HPP in some of the study cases. Mobile teeth or the loss of permanent teeth were observed in 2 patients, and 3 out of 5 patients had a history of asthma. The serum ALP levels of all patients were 30% below the lower limit of the age equivalent normal range. ALPL gene analysis revealed compound heterozygous mutations, including Ile395Val and Leu520Argfs in family 1, Val95Met and Gly491Arg in family 2, and a dominant missense mutation (Gly456Arg) in family 3. The 3D-modeling of human TNSALP revealed three mutations (Val95Met, Ile395Val and Gly456Arg) at the homodimer interface. Severe collisions between the side chains were predicted for the Gly456Arg variant. Discussion: One of the characteristic findings of this present study was a high prevalence of coexisting asthma and a high level serum IgE level. These characteristics may account for the fragility of tracheal tissues and a predisposition to asthma in patients with mild HPP. The genotypes of the five mild HPP patients in our present study series included 1) compound heterozygous for severe and hypomorphic mutations, and 2) dominant-negative mutations. All of these mutations were at the homodimer interface, but only the dominant-negative mutation was predicted to cause a severe collision effect between the side chains. This may account for varying mechanisms leading to different effects on TNSALP function