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

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

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

Personality Predictors of IT Addiction

Prior research on addiction has extensively looked at the personality traits of individuals and their interactions in explaining various types of substance and non-substance addictions. Recent studies have also shown the importance of neuroticism, conscientiousness, and agreeableness on IT addiction. Nevertheless, little is known in IS research regarding the moderated effects of personality traits on the development of IT addiction. Given the increasing attention to the dark side of IT, in this study, we build on Five-Factor personality model to propose a theoretical model that shows the direct and moderated effects of neuroticism, conscientiousness, and agreeableness on addiction to social networking sites (SNS). We empirically test our research model using data collected from 275 SNS users and covariance-based structural equation modeling technique. Furthermore, we shed light on the moderation effects of these factors on SNS addiction via two post-hoc analyses. The implications for theory and practice are discussed