Indoor localisation by using wireless sensor nodes

This study is devoted to investigating and developing WSN based localisation approaches with high position accuracies indoors. The study initially summarises the design and implementation of localisation systems and WSN architecture together with the characteristics of LQI and RSSI values. A fingerprint localisation approach is utilised for indoor positioning applications. A k-nearest neighbourhood algorithm (k-NN) is deployed, using Euclidean distances between the fingerprint database and the object fingerprints, to estimate unknown object positions. Weighted LQI and RSSI values are calculated and the k-NN algorithm with different weights is utilised to improve the position detection accuracy. Different weight functions are investigated with the fingerprint localisation technique. A novel weight function which produced the maximum position accuracy is determined and employed in calculations. The study covered designing and developing the centroid localisation (CL) and weighted centroid localisation (WCL) approaches by using LQI values. A reference node localisation approach is proposed. A star topology of reference nodes are to be utilized and a 3-NN algorithm is employed to determine the nearest reference nodes to the object location. The closest reference nodes are employed to each nearest reference nodes and the object locations are calculated by using the differences between the closest and nearest reference nodes. A neighbourhood weighted localisation approach is proposed between the nearest reference nodes in star topology. Weights between nearest reference nodes are calculated by using Euclidean and physical distances. The physical distances between the object and the nearest reference nodes are calculated and the trigonometric techniques are employed to derive the object coordinates. An environmentally adaptive centroid localisation approach is proposed.Weighted standard deviation (STD) techniques are employed adaptively to estimate the unknown object positions. WSNs with minimum RSSI mean values are considered as reference nodes across the sensing area. The object localisation is carried out in two phases with respect to these reference nodes. Calculated object coordinates are later translated into the universal coordinate system to determine the actual object coordinates. Virtual fingerprint localisation technique is introduced to determine the object locations by using virtual fingerprint database. A physical fingerprint database is organised in the form of virtual database by using LQI distribution functions. Virtual database elements are generated among the physical database elements with linear and exponential distribution functions between the fingerprint points. Localisation procedures are repeated with virtual database and localisation accuracies are improved compared to the basic fingerprint approach. In order to reduce the computation time and effort, segmentation of the sensing area is introduced. Static and dynamic segmentation techniques are deployed. Segments are defined by RSS ranges and the unknown object is localised in one of these segments. Fingerprint techniques are applied only in the relevant segment to find the object location. Finally, graphical user interfaces (GUI) are utilised with application program interfaces (API), in all calculations to visualise unknown object locations indoors

A Comparative Study of Handwritten Character Recognition by using Image Processing and Neural Network Techniques

This study aims to analyze the effects of noise, image filtering, and edge detection techniques in the preprocessing phase of character recognition by using a large set of character images exported from MNIST database trained with various sizes of neural networks. Canny edge detection algorithm was deployed to smooth the edges of the images while the Sobel edge detection algorithm was used to detect the edges of the images. Skeletonization algorithm was applied to re-shape the structural shapes. In the context of the image filtering, the Laplacian filter was utilized to enhance the images and High pass filtering was used to highlight the fine details in blurred images. Gaussian noise, image noise with Gaussian intensity, function in Matlab with the probability density function P was deployed on character images of MINST. Pattern recognition neural networks are widely used in optical character recognition. Feedforward neural networks are deployed in this study. A comprehensive analysis of the above-mentioned image processing techniques is included during character recognition. Improved accuracy is observed with character recognition during the prediction phase of the neural networks. A sample of unknown characters is tested with the application of High pass filtering + feedforward neural network and 89%, the highest, average output prediction accuracy was obtained. Other prediction accuracies were also tabulated for the reader’s attention

Indoor Localization by using Particle Filtering Approach with Wireless Sensor Nodes

Jennic type wireless sensor nodes are utilized together with a novel particle filtering technique for indoor localization. Target objects are localized with an accuracy of around 0.25 meters. The proposed technique introduces a new particle generation and distribution technique to improve current estimation of object positions. Particles are randomly distributed around the object in the sensing area within a circular strip of 2 STD of object distance measurements. Particle locations are related to object locations by using Gaussian weight distribution methods. Object distances from the transmitters are determined by using received RSSI values and ITU-R indoor propagation model. Measured object distances are used together with the particle distances from the transmitters to predict the object locations

Family history in stone disease: how important is it for the onset of the disease and the incidence of recurrence?

The aim of this study was to evaluate the possible effect of a positive family history on the age at the onset of urinary stone disease and the frequency of subsequent symptomatic episodes relating to the disease. Between March 2006 and April 2009, patients with either a newly diagnosed or a previously documented stone disease were included in the study program. They were required to fill in a questionnaire and divided into two groups according to the positive family history of stone disease; group I comprised patients with a family history for urinary calculi and group II those without. Depending on the data obtained from questionnaires, all patients were evaluated in detail with respect to the age at the onset of the stone disease, stone passage and interventions over time, time to first recurrence (time interval between the onset of the disease and the first recurrence), number of total stone episodes and recurrence intervals. 1,595 patients suffering from urolithiasis with the mean age of 41.7 (14–69 years) were evaluated with respect to their past history of the disease. There were 437 patients in group I and 1,158 in group II. There was no statistically significant difference between the mean age value of two groups (P = 0.09). When both genders in group I were analyzed separately, female patients tended to have higher rate of family history positivity than males. Comparative evaluation of the age at the onset of the disease between the two groups did reveal that stone formation occured at younger ages in patients with positive family history [P = 0.01 (males), P = 0.01 (females)] and the mean age of onset of the disease was lower in males than females in group I (P = 0.01). Patients in group I had relatively more stone episodes from the onset of the disease [P < 0.01 (2–4 episodes), P < 0.01 (≥5 episodes)]. Male patients were associated with higher number of stone episodes (P = 0.01). Mean time interval between recurrences was noted to be significantly shorter in group I patients when compared with patients in group II [P < 0.01 (males), P = 0.02 (females)]. In conclusion, our results showed that urinary stone formation may occur at younger ages and that the frequency of symptom episodes may be higher in patients with a positive family history. We believe that the positive family history for urinary stone disease could give us valuable information concerning the onset as well as the severity of the disease

Parental psychological distress associated with COVID-19 outbreak: A large-scale multicenter survey from Turkey

Aims: Pandemics can cause substantial psychological distress; however, we do not know the impact of the COVID-19 related lockdown and mental health burden on the parents of school age children. We aimed to comparatively examine the COVID-19 related the stress and psychological burden of the parents with different occupational, locational, and mental health status related backgrounds. Methods: A large-scale multicenter online survey was completed by the parents (n = 3,278) of children aged 6 to 18 years, parents with different occupational (health care workers—HCW [18.2%] vs. others), geographical (İstanbul [38.2%] vs. others), and psychiatric (child with a mental disorder [37.8%]) backgrounds. Results: Multivariable logistic regression analysis showed that being a HCW parent (odds ratio 1.79, p <.001), a mother (odds ratio 1.67, p <.001), and a younger parent (odds ratio 0.98, p =.012); living with an adult with a chronic physical illness (odds ratio 1.38, p <.001), having an acquaintance diagnosed with COVID-19 (odds ratio 1.22, p =.043), positive psychiatric history (odds ratio 1.29, p <.001), and living with a child with moderate or high emotional distress (odds ratio 1.29, p <.001; vs. odds ratio 2.61, p <.001) were independently associated with significant parental distress. Conclusions: Parents report significant psychological distress associated with COVID-19 pandemic and further research is needed to investigate its wider impact including on the whole family unit. © The Author(s) 2020

Predictors of Enhancing Human Physical Attractiveness: Data from 93 Countries

People across the world and throughout history have gone to great lengths to enhance their physical appearance. Evolutionary psychologists and ethologists have largely attempted to explain this phenomenon via mating preferences and strategies. Here, we test one of the most popular evolutionary hypotheses for beauty-enhancing behaviors, drawn from mating market and parasite stress perspectives, in a large cross-cultural sample. We also test hypotheses drawn from other influential and non-mutually exclusive theoretical frameworks, from biosocial role theory to a cultural media perspective. Survey data from 93,158 human participants across 93 countries provide evidence that behaviors such as applying makeup or using other cosmetics, hair grooming, clothing style, caring for body hygiene, and exercising or following a specific diet for the specific purpose of improving ones physical attractiveness, are universal. Indeed, 99% of participants reported spending \u3e10 min a day performing beauty-enhancing behaviors. The results largely support evolutionary hypotheses: more time was spent enhancing beauty by women (almost 4 h a day, on average) than by men (3.6 h a day), by the youngest participants (and contrary to predictions, also the oldest), by those with a relatively more severe history of infectious diseases, and by participants currently dating compared to those in established relationships. The strongest predictor of attractiveness-enhancing behaviors was social media usage. Other predictors, in order of effect size, included adhering to traditional gender roles, residing in countries with less gender equality, considering oneself as highly attractive or, conversely, highly unattractive, TV watching time, higher socioeconomic status, right-wing political beliefs, a lower level of education, and personal individualistic attitudes. This study provides novel insight into universal beauty-enhancing behaviors by unifying evolutionary theory with several other complementary perspectives

Sumatra kaynaklı tsunamilerin uzak alan ilerlemesi ve Maldiv adalarına etkisi.

In recent years the negative effects of tsunamis in the Indian Ocean dramatically increased. Although, this subject became very popular lately, the far-field activities of tsunamis are needed to be evaluated in Indian Ocean. In this thesis, Maldives and Sumatra islands were emphasized to analyze the effects of the transoceanic propagation of tsunamis in Indian Ocean. At first, using GIS Based softwares, the geographical data of the region were extracted and organized for analyzing. Secondly, a worst earthquake scenario was initiated at Sumatra which is located at a long distance from Maldives Islands. Then, corresponding effects of transoceanic tsunami were analyzed and accordingly coastal amplifications near Maldivian Islands were computed by NAMI DANCE. As a final step, an evaluation study was carried out to understand the transoceanic propagation behavior of tsunamis in Indian Ocean and results were discussed.M.S. - Master of Scienc

Crowdsensing Route Reconstruction using Portable Bluetooth Beacon-based two-way network

[[abstract]]There have been plenty of R&D efforts to achieve precise indoor positioning of users. With weak or no GPS signals, Wifi / Bluetooth and other approaches such as ultrasonic and accelerometers has been used for indoor positioning. In this demo we focus on reconstructing visitors route using the combination of Bluetooth proximity tags and custom made Bluetooth Beacons. Bluetooth Beacons are usually used to emitting simple identification information for retrieval by a mobile app, which will in turn use this information to get own position from a mobile network. Our custom Bluetooth beacons has the capability to form a two-way network between Bluetooth Beacons, making it highly portable and very easy for deployment. We'll show how to setup the system and how to identify and reconstruct route information of visitors. The information can be used to improve user experience.[[notice]]補正完