A novel multilayer neural network model for TOA-based localization in wireless sensor networks

A novel multilayer neural network model, called artificial synaptic network, was designed and implemented for single sensor localization with time-of-arrival (TOA) measurements. In the TOA localization problem, the location of a source sensor is estimated based on its distance from a number of anchor sensors. The measured distance values are noisy and the estimator should be able to handle different amounts of noise. Three neural network models: the proposed artificial synaptic network, a multi-layer perceptron network, and a generalized radial basis functions network were applied to the TOA localization problem. The performance of the models was compared with one another. The efficiency of the models was calculated based on the memory cost. The study result shows that the proposed artificial synaptic network has the lowest RMS error and highest efficiency. The robustness of the artificial synaptic network was compared with that of the least square (LS) method and the weighted least square (WLS) method. The Cramer-Rao lower bound (CRLB) of TOA localization was used as a benchmark. The model's robustness in high noise is better than the WLS method and remarkably close to the CRLB

Infrared Thermography Enhancements for Concrete Bridge Evaluation

Infrared thermography is a well-recognized non-destructive testing technique for evaluating concrete bridge elements such as bridge decks and piers. However, overcoming some obstacles and limitations are necessary to be able to add this invaluable technique to the bridge inspector\u27s tool box. Infrared thermography is based on collecting radiant temperature and presenting the results as a thermal infrared image. Two methods considered in conducting an infrared thermography test include passive and active. The source of heat is the main difference between these two approaches of infrared thermography testing. Solar energy and ambient temperature change are the main heat sources in conducting a passive infrared thermography test, while active infrared thermography involves generating a temperature gradient using an external source of heat other than sun. Passive infrared thermography testing was conducted on three concrete bridge decks in Michigan. Ground truth information was gathered through coring several locations on each bridge deck to validate the results obtained from the passive infrared thermography test. Challenges associated with data collection and processing using passive infrared thermography are discussed and provide additional evidence to confirm that passive infrared thermography is a promising remote sensing tool for bridge inspections. To improve the capabilities of the infrared thermography technique for evaluation of the underside of bridge decks and bridge girders, an active infrared thermography technique using the surface heating method was developed in the laboratory on five concrete slabs with simulated delaminations. Results from this study demonstrated that active infrared thermography not only eliminates some limitations associated with passive infrared thermography, but also provides information regarding the depth of the delaminations. Active infrared thermography was conducted on a segment of an out-of-service prestressed box beam and cores were extracted from several locations on the beam to validate the results. This study confirms the feasibility of the application of active infrared thermography on concrete bridges and of estimating the size and depth of delaminations. From the results gathered in this dissertation, it was established that applying both passive and active thermography can provide transportation agencies with qualitative and quantitative measures for efficient maintenance and repair decision-making

Economic impact of climate change on Malaysian rice production

Climate change poses challenges for all sectors of an economy, particularly those dependent on natural resources such as agriculture. Studies have shown that overall agricultural productivity in low latitudes are likely to decline with the effect of climate change. This has implications for world food security, as most developing countries, including Malaysia, are located in lower latitude regions. This will subsequently affect farm income, self-sufficiency level and food security. Rice production in Malaysia, as in other parts of the world, is extremely vulnerable to weather changes and extreme conditions such as drought and flooding. Such situations forced Malaysia to start and maintain a protectionist regime with respect to its rice industry to better ensure food security for the country. This study attempts to investigate the economic impact of climate change on the Malaysian rice industry, a strategic crop that largely determines the Malaysian food security. The study involves estimating the potential impact of temperature and rainfall changes on rice yields in the major rice granary areas until 2030, and policy simulation under the present and alternative policy scenarios on the rice industry. This study employed a Crop Simulation Model (DSSAT) to predict the rice production in the eight granary areas until 2030, based on projected weather data. The DSSAT model can simulate growth, development, and yield of a crop growing on a uniform area of land under recommended or simulated management. It needs the minimum data sets including weather data, soil data, and crop management data. The projected climate change over Peninsular Malaysia showed an increasing trend for maximum, minimum temperatures and changes in rainfall pattern. Increase in temperature and variations in rainfall pattern over the growing period were found to affect the rice yield. Results show that during the main growing season, a yearly increase in temperature by 0.05°C and rainfall by 0.11mm can be expected to reduce the rice yield by 12% until the year 2030. During the off season, a yearly increase of maximum and minimum temperatures by 0.15°C and 0.08°C,respectively, and a reduction in rainfall by 0.19mm would reduce the rice yield by 31.3% over the next 18 years. These results indicated that rice yield would be more negatively affected by the climate change during off season rather than main season. The system dynamics simulation model then used to assess the effect of predicted yield on self sufficiency level and farmers’ gross income of the country until 2013. It is an approach for analysing and solving complex problems, and focuses mostly on policy analysis and design. Based on the system dynamics’ results, the reduction in rice yield was expected to reduce farmers’ gross income and the rice self sufficiency level of the country. The study suggested three different policy scenarios to overcome these adverse effects. Under Scenario 1, a doubling of the government’s fertilizer subsidy from the year 2013 to 2030 was able to increase the rice yield, SSL, and farmers’ gross income about 3‒4%, 0.3‒5.6%, and 8.3‒12.7%, respectively. Based on Scenario 2, if the government increases the price support by 10% during the 2013 to 2030 time period, the farmers’ income will also increase by 1.7% per year. Under Scenario 3, Malaysia may be able to sustain the 70% SSL target until 2020, if the government open about 51,565 ha of new land area for rice fields. Malaysia also can maintain this level of self sufficiency until 2030, if the area planted increase to 154,000 ha. The overall policy implication is that the Malaysian rice industry cannot be sustained if government takes no action to change its current policies

Online Social Networks’ Investigations of Individuals’ Healthy and Unhealthy Lifestyle Behaviors and Social Factors Influencing Them —Three Essays

More than half of U.S. adults suffer from one or more chronic diseases, which account for 86% of total U.S. healthcare costs. Major contributors to chronic diseases are unhealthy lifestyle behaviors, which include lack of physical activity, poor nutrition, tobacco use, and drinking too much alcohol. A reduction in the prevalence of health-risk behaviors could improve individuals’ longevity and quality of life and may halt the exponential growth of healthcare costs. Prior studies in the field have acknowledged that a comprehensive understanding of health behaviors requires the examination of individual’ behaviors in supra-dyadic social networks. In recent years, the growth of online social networks and popularity of location-based services have opened new research opportunities for observational studies on individuals’ healthy and unhealthy lifestyle behaviors. The goal of this three-essay dissertation is to examine the effect of various social factors, shared images, and communities of interest on healthy and unhealthy lifestyle behaviors of individuals. This dissertation makes novel contributions in terms of theoretical implications, data collection and analysis methods, and policy implications for promoting healthy lifestyle behaviors and inhibiting unhealthy behaviors. Essay 1 draws on a synthesis of social cognitive and social network theories to conceptualize a causal model for healthy and unhealthy behaviors. To test the conceptualized model, we developed a new method—dynamic sequential data extraction and integration—to collect and integrate data over time from Twitter and Foursquare. The captured dataset was then combined with relevant data from the U.S. Census Bureau. The final dataset has more than 32,000 individuals from all states in the United States. Using this dataset, we derived variables to measure healthy and unhealthy lifestyle behaviors and metrics for factors representing individuals’ social support, social influence, and homophily, as well as the socioeconomic status of the communities where they live. To capture the impacts of social factors, we collected individuals’ behaviors in two separate time periods. We used zero-inflated negative binomial regression method for data analysis. The results of this study uncover factors that have significant impacts on healthy and unhealthy lifestyle behaviors. Essay 2 focuses on embedded images in self-disclosed posts related to healthy and unhealthy lifestyle behaviors. While online photo-sharing has become widely popular, and neuroscience has reported the influence of images in brain activities, to our knowledge, there is no published research on the impacts of shared photos on health-related lifestyle behaviors. This study addresses this gap and examines the moderating role of shared images and the direct impacts of their contents. We relied on social learning and multimodality theories to argue that images can attract individuals’ attention and enhance the process of observational learning in online social networks. We developed a novel method for image analysis that involves the extraction, processing, dimensionality reduction, and categorization of images. The results show that the presence of photos in self-disclosed unhealthy lifestyle behaviors positively moderates friends’ social influence. Moreover, the results indicate that the contents of shared photos influence individuals’ health-related behaviors. Essay 3 focuses on the role of personal interests in individuals’ health-related lifestyle behaviors. Prior studies have demonstrated that health promotional programs can benefit from targeting individuals based on their interests. Specifically, prior studies have emphasized the role of interests as a factor influencing behaviors. However, current literature suffers from two major gaps. First, there is no systematic and comprehensive approach to capture individuals’ interests in online social networks. Second, to our knowledge, the role of interests in individuals’ healthy and unhealthy lifestyle behaviors as disclosed online has not been investigated. To address these gaps, we examine the role of individuals’ interests in their health-related behaviors. The theoretical foundation of this study is a synthesis of homophily and self-determination theories. We developed a novel method—the homophily-based interest detection method—that involves network simplification, network clustering, cluster labeling, and interest metrics. This method was applied to social networks of individuals in Essay 1 to measure individuals’ interests. The results show that health-related interests are associated with individuals’ healthy and unhealthy lifestyle behaviors. Our findings indicate that other forms of interest, such as music taste and political views, also play a role. Moreover, our results show that belonging to healthy (unhealthy) communities of interest has an inhibitive role that prevents postings of unhealthy (healthy) behaviors

Screen Time and Productivity: An Extension of Goal-setting Theory to Explain Optimum Smartphone Use

Over the past several years, much research has examined the negative consequences that can arise from smartphone use. To help reduce these consequences, companies have developed smartphone applications and features to enable self-monitoring behaviors. However, the mechanisms that have caused smartphone-enabled self-monitoring behaviors to emerge and the positive outcomes that might result from such behaviors have received limited scholarly attention. In this study, we ameliorate this gap by proposing a framework that highlights key antecedents and outcomes of screen- time self-monitoring success based on a smartphone-based self-monitoring intervention. Informed by a short-term longitudinal study, our results show how smartphone-based self-monitoring can enhance awareness of smartphone use and, consequently, lead to positive outcomes for users. Our findings reveal that how users perceive smartphone self- monitoring affordances, their outcome expectations, and their smartphone self-monitoring efficacy positively relate to the extent they engage in smartphone-based self-monitoring behavior. In turn, self-monitoring enhances user productivity and leads to an overall sense of contentment with achievement. Nevertheless, our findings suggest that self-monitoring fatigue negatively moderates these relationships. This study offers novel theoretical and practical insights to encourage users to use smartphones in a more regulated manner. More generally, this study contributes to the literature on self-monitoring and self-regulation in digitally enabled environments

Extraction of Regression Relations of Tidal Rivers by Artificial Neural Network Method

Source: ICHE Conference Archive - https://mdi-de.baw.de/icheArchiv

Evaluation of Different Methods for Considering Bar-Concrete Interaction in Nonlinear Dynamic Analysis of RC Frames by Using Layer Section Theory

In this paper, the bond-slip effect has been applied to the numerical equations in the process of nonlinear dynamic analysis of reinforced concrete frames. The formulation is similar to that of the layer sectiontheory, but the perfect bond assumption has been removed. The precision of the proposed method in considering the real nonlinear behavior of reinforced concrete frames has been compared to the precision of two other suggested methods for considering bond-slip effect in layer model. Among the capabilities of this method for seismic analysis are its ability of modeling the embedded lengths of bars within joints and nonlinear modeling of bond-slip. The precision of the analytical results were compared with the experimental ones achieved from a one bay two storeyframe under seismic loading on the shaking table. According to the numerical results, the presence or absence of bond effect in numerical modeling and analysis will bring about considerable different results, including results for deformation and forces. All the studied methods for inserting the bond-slip effect into the layer model can relativelyimprove the accuracy of analytical results compared to experimental ones. The proposed method of this study has proved to enjoy the highest accuracy with regard to time-history seismic analysis of reinforced concrete frames. Among the capabilities of the proposed method, we may refer to its ability to model beam-column and joint element’s nonlinear behavior separately

Aluminium Phosphide Poisoning: a Case Report

Background: Aluminum phosphide as pesticide commonly used to protect crops from pests. Despite the limited number of cases of poisoning with this substance, it is important due to the high risk of being fatal. The major cause of the poisoning is suicide attempt. Due to the lack of specific treatment in poisoning, taking more than 500 mg is fatal.Case Report: The patient was a 16-year-old woman who attempted suicide by consuming some 4.5gram aluminum phosphide tablets. Within half an hour after consumption she had vomiting and nausea then smoking cigar, followed closely by smoking in her mouth flames around his mouth is created which will burn (grade II). Subsequently she had argument with her husband and injured her right ear. During the admission she was alert, 2nd degree burn were observed on the upper lip and around the mouth and nose and ears areas. Physical examination was normal, when she arrived she had severe hypotension and her oxygen saturation was 69% with tachycardia. The patient was immediately intubated and received mechanical ventilation. After installing Nasogastric tube, gastric lavage was done with potassium permanganate and bicarbonate. At Arterial Blood Gas (ABG), severe metabolic acidosis (pH 6.9) and a chest X-ray, diffuse lung opacities was seen. Blood test showed that there was a leukocytosis (22,000). Treatment was given Saline, high dose inotrope drugs (norepinephrine and dopamine), bicarbonate, calcium gluconate, magnesium sulfate hydrocortisone. Burns around the mouth was dressing after admission. On the third day the patient was alert and complained of pain in the right ear and hearing loss. 9 days after admission, the patient was discharged well with complication of sensory neural hearing loss (unrelated to slap injury).Conclusion: Despite the extreme virulence of the Aluminum phosphide (rice tablets), especially in high doses, conventional therapeutic measures can sometimes unexpected ways leading to improved patient. The patient's well general condition was discharged with remained hearing loss in her right ear, despite the very poor prognosis. It is recommended that phosphine gas research on the possible impact of hearing loss further

A Perforated Duodenal Ulcer after Using of Methamphetamin and Methadone

Background: Acute poisonings with corrosive substances lead to serious peptic ulcer disease despite of the major improvements in both diagnostic and therapeutic strategies; perforated peptic ulcer is still the most common cause of gastrointestinal perforation and the second most common complication of the peptic ulcer. Duodenal ulcers tend to be the posterior penetrating and in pancreas can cause pancreatitis whereas gastric ulcers are penetrating to left liver’s lobe.Case Report: We report the case of a 23-year-old man with a history of chronic consumption of methamphetamin and methadone referred to emergency state with epigastric pain. He consumed methamphetamin following about 10cc methadone, then amount of methadone syrup yesterday. When he was admitted, he was awake, alert, agitated and restless; also he was feeling abdominal pain. In examination, we found out generalized abdominal pain with garding and rebound tenderness. Pain is continuously and referred to back and the testis. The pupils had mild mydriasis and reactive to light. Free subdiphragmatic air was seen in the right subphrenic area in upright chest x-Ray. It didn’t administrate to activated charcoal due to perforation detection and immediately he was transferred to the operating room for diagnosis an acute abdomen. Purulent discharge was seen between the left lobe of liver and gastric as well as adhesion of omentum. Then, post pyloric perforation was seen after release of adhesion that bile discharge excreted. We treated him with essential treatment.Conclusion: Here, we report a patient with a history of addiction to methamphetamin and methadone and perforated duodenal ulcer after took acute overdose of these substances. As a result of that perforation opened and postulated to the left lobe of liver, thus he was taken to the operating room. This patient had perforated duodenal ulcer after acute overdose of methamphetamin and also this ulcer opened atypically to the left lobe of liver. Furthermore, investigation on the effects of amphetamine and methamphetamine on peptic ulcer and its effect on the perforation is recommended

Can IT Hurt Productivity? An Investigation of IT Addiction

While IT is generally found to augment productivity, recent evidence indicates that excessive and compulsive usage of IT is likely to have some adverse consequences. Given the prevalence of IT addiction, it becomes increasingly important to study this phenomenon. We seek to investigate the adverse effects of IT addiction, especially on productivity, in work settings. We propose a model showing that two types of factors (related to individual differences and technology features) could have an impact on addictive IT use, which in turn will affect work productivity. A quantitative cross-sectional design will be used to test the model; as needed, survey instruments will be developed and/or validated. Our study will contribute to the IS discipline by proposing a model of IT addiction to identify and explain its significant antecedents and impacts. For managers, the findings will help understanding the formation of addictive IT behaviors and their effects