scholarly journals Implementasi Webiot Sistem Absensi Face Dalam Antisipasi Bencana Alam

2021 ◽  
Vol 1 (2) ◽  
pp. 56-61
Author(s):  
Ahmad Hunaepi ◽  
Ahmad Roihan ◽  
Mochamad Yusuf Romdoni

Natural disasters are unexpected natural events, have a major impact on every level of society, especially coastal areas such as power generation companies that use coal as a natural resource. Every company hopes to be able to anticipate early and quickly so that employees are maintained and safe. The face attendance system is a monitoring tool combined with a smart gate with a face recognition concept that can be monitored online. Faces that have been registered can be recognized so that the device will act as a trigger to open the door, and vice versa if the face is not recognized, the device will still record and act as a trigger for the door to remain closed. The implementation of the facial attendance system can be used as a data source to calculate the number of employees who are still in and out of the company when a natural disaster occurs.

2010 ◽  
Vol 69 (3) ◽  
pp. 161-167 ◽  
Author(s):  
Jisien Yang ◽  
Adrian Schwaninger

Configural processing has been considered the major contributor to the face inversion effect (FIE) in face recognition. However, most researchers have only obtained the FIE with one specific ratio of configural alteration. It remains unclear whether the ratio of configural alteration itself can mediate the occurrence of the FIE. We aimed to clarify this issue by manipulating the configural information parametrically using six different ratios, ranging from 4% to 24%. Participants were asked to judge whether a pair of faces were entirely identical or different. The paired faces that were to be compared were presented either simultaneously (Experiment 1) or sequentially (Experiment 2). Both experiments revealed that the FIE was observed only when the ratio of configural alteration was in the intermediate range. These results indicate that even though the FIE has been frequently adopted as an index to examine the underlying mechanism of face processing, the emergence of the FIE is not robust with any configural alteration but dependent on the ratio of configural alteration.


2013 ◽  
Vol 44 (4) ◽  
pp. 271-277 ◽  
Author(s):  
Simona Sacchi ◽  
Paolo Riva ◽  
Marco Brambilla

Anthropomorphization is the tendency to ascribe humanlike features and mental states, such as free will and consciousness, to nonhuman beings or inanimate agents. Two studies investigated the consequences of the anthropomorphization of nature on people’s willingness to help victims of natural disasters. Study 1 (N = 96) showed that the humanization of nature correlated negatively with willingness to help natural disaster victims. Study 2 (N = 52) tested for causality, showing that the anthropomorphization of nature reduced participants’ intentions to help the victims. Overall, our findings suggest that humanizing nature undermines the tendency to support victims of natural disasters.


Author(s):  
Reshma P ◽  
Muneer VK ◽  
Muhammed Ilyas P

Face recognition is a challenging task for the researches. It is very useful for personal verification and recognition and also it is very difficult to implement due to all different situation that a human face can be found. This system makes use of the face recognition approach for the computerized attendance marking of students or employees in the room environment without lectures intervention or the employee. This system is very efficient and requires very less maintenance compared to the traditional methods. Among existing methods PCA is the most efficient technique. In this project Holistic based approach is adapted. The system is implemented using MATLAB and provides high accuracy.


Face recognition plays a vital role in security purpose. In recent years, the researchers have focused on the pose illumination, face recognition, etc,. The traditional methods of face recognition focus on Open CV’s fisher faces which results in analyzing the face expressions and attributes. Deep learning method used in this proposed system is Convolutional Neural Network (CNN). Proposed work includes the following modules: [1] Face Detection [2] Gender Recognition [3] Age Prediction. Thus the results obtained from this work prove that real time age and gender detection using CNN provides better accuracy results compared to other existing approaches.


Author(s):  
Ki-Gab Park

The chapter argues that natural disasters are common concerns in the international community. At the same time, the current international cooperation mechanism, based on the principle of equal sovereignty, require prior consent by the state affected by a natural disaster. Unfortunately, this is not always an efficient tool for the protection of victims. The globalization of problems and the proliferation of humanitarian crises make the veritable solidarity of the international community increasingly necessary, and therefore another high value, namely international solidarity or community obligations, should create direct and immediate obligations for all members of the international community. The main object of this chapter is to discuss the future-oriented direction of the law on natural disasters. This means, first, to ascertain the lex lata, especially customary rules. The chapter further offers some suggestions on possible ways for the international community to provide more effective relief for victims of natural disasters.


Author(s):  
Yao Li ◽  
Haoyang Li ◽  
Jianqing Ruan

The natural environment is one of the most critical factors that profoundly influences human races. Natural disasters may have enormous effects on individual psychological characteristics. Using China’s long-term historical natural disaster dataset from 1470 to 2000 and data from a household survey in 2012, we explore whether long-term natural disasters affect social trust. We find that there is a statistically significant positive relationship between long-term natural disaster frequency and social trust. We further examine the impact of long-term natural disaster frequency on social trust in specific groups of people. Social trust in neighbors and doctors is stronger where long-term natural disasters are more frequent. Our results are robust after we considering the geographical difference. The effect of long-term natural disasters remains positively significant after we divide the samples based on geographical location. Interestingly, the impact of long-term flood frequency is only significant in the South and the impact of long-term drought frequency is only significant in the North.


2021 ◽  
pp. 1-11
Author(s):  
Suphawimon Phawinee ◽  
Jing-Fang Cai ◽  
Zhe-Yu Guo ◽  
Hao-Ze Zheng ◽  
Guan-Chen Chen

Internet of Things is considerably increasing the levels of convenience at homes. The smart door lock is an entry product for smart homes. This work used Raspberry Pi, because of its low cost, as the main control board to apply face recognition technology to a door lock. The installation of the control sensing module with the GPIO expansion function of Raspberry Pi also improved the antitheft mechanism of the door lock. For ease of use, a mobile application (hereafter, app) was developed for users to upload their face images for processing. The app sends the images to Firebase and then the program downloads the images and captures the face as a training set. The face detection system was designed on the basis of machine learning and equipped with a Haar built-in OpenCV graphics recognition program. The system used four training methods: convolutional neural network, VGG-16, VGG-19, and ResNet50. After the training process, the program could recognize the user’s face to open the door lock. A prototype was constructed that could control the door lock and the antitheft system and stream real-time images from the camera to the app.


2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Yunjun Nam ◽  
Takayuki Sato ◽  
Go Uchida ◽  
Ekaterina Malakhova ◽  
Shimon Ullman ◽  
...  

AbstractHumans recognize individual faces regardless of variation in the facial view. The view-tuned face neurons in the inferior temporal (IT) cortex are regarded as the neural substrate for view-invariant face recognition. This study approximated visual features encoded by these neurons as combinations of local orientations and colors, originated from natural image fragments. The resultant features reproduced the preference of these neurons to particular facial views. We also found that faces of one identity were separable from the faces of other identities in a space where each axis represented one of these features. These results suggested that view-invariant face representation was established by combining view sensitive visual features. The face representation with these features suggested that, with respect to view-invariant face representation, the seemingly complex and deeply layered ventral visual pathway can be approximated via a shallow network, comprised of layers of low-level processing for local orientations and colors (V1/V2-level) and the layers which detect particular sets of low-level elements derived from natural image fragments (IT-level).


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