US2RO: Union of Superpoints to Recognize Objects

The creation of interactive virtual reality (VR) applications from 3D scanned content usually includes a lot of manual and repetitive work. Our research aim is to develop agents that recognize objects to enhance the creation of interactive VR applications. We trained partition agents in our superpoint growing environment that we extended with an expert function. This expert function solves the sparse reward signal problem of the previous approaches and enables to use a variant of imitation learning and deep reinforcement learning with dense feedback. Additionally, the function allows to calculate a performance metric for the degree of imitation for different partitions. Furthermore, we introduce an environment to optimize the superpoint generation. We trained our agents with 1182 scenes of the ScanNet data set. More specifically, we trained different neural network architectures with 1170 scenes and tested their performance with 12 scenes. Our intermediate results are promising such that our partition system might be able to assist the VR application development from 3D scanned content in near future.

Infrared thermal imaging monitoring on hands when performing repetitive tasks: An experimental study

The monitoring of infrared thermal images is reported to analyze changes in skin temperature in the hand fingers when repetitive work is performed to know which finger has a greater risk of injury, besides, the recovery time is analyzed regarding the initial temperature and its relationship with age, sex, weight, height if practice sports, and Body Mass Index (BMI) per individual. For the above, an experimental test was carried out for 10 minutes on a repetitive operation that takes place in the telecommunications industry and 39 subjects participated in which an infrared thermal image of the dorsal and palmar part of both hands was taken in periods of 5 minutes after the 10-minute test has elapsed. The results show that none of the participants recovered their initial temperature after 10 minutes of the experimental test. In addition, it was found that there is a relationship between skin temperature and sex, and that age influences the recovery of temperature. On the other hand, the thumb, index, and middle fingers have a higher risk of injury in the analyzed task. It is concluded that performing repetitive work with all the fingers of the hand does not show that all they have the same risk of injury, besides that, not all the variables studied affect the recovery of temperature and its behavior.

Algorithmic Agency and Autonomy in Archaeological Practice

A key development in archaeology is the increasing agency of the digital tools brought to bear on archaeological practice. Roles and tasks that were previously thought to be uncomputable are beginning to be digitalized, and the presumption that computerization is best suited to well-defined and restricted tasks is starting to break down. Many of these digital devices seek to reduce routinized and repetitive work in the office environment and in the field. Others incorporate data-driven methods to represent, store, and manipulate information in order to undertake tasks previously thought to be incapable of being automated. Still others substitute the human component in environments which would be otherwise be inaccessible or dangerous. Whichever applies, separately or in combination, such technologies are typically seen as black-boxing practice with often little or no human intervention beyond the allocation of their inputs and subsequent incorporation of their outputs in analyses. This paper addresses the implications of this shift to algorithmic automated practices for archaeology and asks whether there are limits to algorithmic agency within archaeology. In doing so, it highlights several challenges related to the relationship between archaeologists and their digital devices.

Design of web vulnerability scanner based on go language

The vulnerability scanner designed in this paper completed the collection of information and scanning of vulnerability, including six parts: input assets, asset collection, vulnerability profile, plug-in upload, single case detection and report display. The framework of vue realized the front end that included six pages, and the framework of gin realized the back end. The interface completed the separation of the front and back end. The database using MySQL designed seven tables. This scanner can avoid tedious and repetitive work, it can realize automatic scanning and testing of network vulnerabilities.

Analysis of Minimax Algorithm Using Tic-Tac-Toe

The game industry has been on exponential growth, has different businesses of varying size, ethos, scope and beyond. Success of these video-games comes from a lot of labor-intensive work by developers. Every little nuance of each character, the objects within a character’s environment must be hand-coded. Repetitive work takes up a significant part of development time, which leads to an increase in glitches and logical flaws. Artificial intelligence has been used to simulate human players in software games, provides an opportunity for game developers to create unique experiences and different outcomes for each player. Computer chess players are well-known examples, wherein modern chess programs are trained to defeat best human players. AI based algorithms that can be implemented for games, but a need for optimal solutions is on a rise. We require a comparative analysis of multiple algorithms for understanding the most efficient and ideal one. In our work, through use of a game Tic-Tac-Toe various algorithms will be carried out with its prototype compared in terms of effective rate and optimality.

FACTORS ASSOCIATED WITH LOWER BACK PAIN AMONG WORKERS IN A CHEMICAL FERTILIZER FACTORY

Most available data on the prevalence and characteristics of low back pain (LBP) are reported in developed countries. The aim of this study was to investigate the prevalence of LBP and potential risk factors among a group of workers in Malaysia. A cross-sectional study was conducted among 170 workers in a fertilizer company in Malaysia. The sample comprised both blue- and white-collar workers. A set of questionnaires consisting of sociodemographic items, the NORDIC musculoskeletal questionnaire and the Dutch Musculoskeletal Questionnaire was used for this study. The main analysis conducted was a multivariate logistic regression. Results showed that a total of 40% of workers experienced LBP. Compared to workers younger than 30 years of age, the risk of LBP was 8 times higher among those over 50 years of age. In addition, workers who were moderately stressed at work had a risk of LBP that was almost five times higher, and workers who did not have awkward posture for a long period of time had an 80% lower risk of LBP. In a multivariate logistic regression, after adjusting for sociodemographic variables, it was found that less repetitive work, shorter sustained positions and less frequent lifting of heavy objects prevented LBP. After the final adjustment including all other variables, only engaging in repetitive work was associated with LBP. In conclusion, each workplace should ensure that older workers, especially those who are working in stressful environments, are prevented from engaging in repetitive work, sustaining prolonged awkward postures and lifting heavy objects.