An Object Detection and Identification System for a Mobile Robot Control

The one of the features of mobile robot control is to detect and to identify objects in workspace. Especially, autonomous systems must detect obstacles and then revise actual trajectories according to new conditions. Hence, many solutions and approaches can be found in literature. Different sensors and cameras are used to solve problem by many researchers. Different type sensors usage can affect not only system performance but also operational cost. In this study, single camera based obstacle detection and identification algorithm was developed to control omni-drive mobile robot systems. Objects and obstacles, which are in robot view, are detected and identified their coordinates by using developed algorithms dynamically. Developed algorithm was tested on Festo Robotino mobile robot. Proposed approach offers not only cost efficiency but also short process time

Short term effects of prescribed fire on soil microbial biomass of black pine forests

In this study, we were examined of changes microbial carbon (MBC) and microbial Nitrogen (MBN) after one month controlled fire. The study area consist of sloping and flat areas, high and low intensity of burnt areas and control areas (unburned) including (flat low intensity: FLI, flat high intensity: FHI, smooth low intensity: SLI, smooth high intensity: SHI and 0-5 cm and 5-10 cm depth soil). In terms of microbial carbon on the upper soil in the flat high intensity and upper and lower soil in the smooth high intensity, there was a significant differences between burning and unburning area. Also, microbial carbon has been reduced approximately 50 % in the burning area. İn terms of microbial nitrogen has been found a significant reduction between upper and lower soil in the smooth low intensity area. However, we found a significant increase in the lower soil on smooth high intensity area. With regard to microbial carbon were found a significant differences between the intensity of the effect of low and high fire in burning areas. There were a significant relationship between microbial carbon and microbial nitrogen and also organic matter. Microbial carbon was also found a positive correlation with Ph (?<0,05). As a result, in the short term of fire reducing of microbial biomass on the top soil (0-5 cm). In addition, microbial nitrogen was increased and microbial carbon was reduced after fire. Additionaly, after fire microbial nitrogen was increasing in the lower soil and microbial biomass may decrease the usability of the organic karbon

Forest fire influence on microbial biomass of forest soils: a review

Microbial biomass is one of the important companent of the C and N cycling in soil. It directly affects soil biological activity. Being a storage medium for C and N, microbial biomass, interacts many biotic and abiotic environmental factors. Forest fires affect soil microbial biomass as other soil properties do. In this study, a general evaluation was made on the effects of forest fire on soil microbial biomass. In general, the effect of forest fire on soil microbial biomass is negative. Both natural and prescribed fires affect soil microbial carbon but the magnitude of the effect is larger in natural fires. This effect could be negative or positive in short term, but in long term the effect is mainly negative. The fire effected upper soil is generally adversly affected while the deeper soil is affected positively. Fire effect on microbial biomass should be evaluated considering climate and the other ecosystem companents all together

Medical Image Segmentation Using Deep Neural Networks

Medikal görüntülerin otomatik bölütlenmesi, bu görüntüler kullanılarak çeşitli hastalıkların teşhis edilmesinde önemli bir rol oynamaktadır. Görüntü bölütleme, bir çok medikal görüntüye ayrı ayrı uygulanarak farklı analizlerin ve teşhislerin yapılması sağlanabilmektedir. Örneğin, bir hücre kültüründeki hücrelerin otomatik bölütlenmesi ile, hücrelerin miktarı, canlılığı, her bir hücrenin çapı veya şeklinin ayrı ayrı analiz edilmesi sağlanabilmektedir. Ayrıca bir dokudaki kan damarlarının otomatik bölütlenmesi ile, damarların uzunluğu, yoğunluğu, her damarın ayrı ayrı yarı çapı gibi analizler yapılabilmektedir. Bu sayede incelen görüntüden, bir hastalığın erken teşhisi, hastalığın türü gibi çıkarımlar gerçekleştirilir. Bu çalışmada çeşitli hücre görüntülerinden ve retina görüntülerinden olu¸san iki ayrı veri seti kullanılarak, bu veri setindeki görüntüler ayrı ayrı bölütlenmiştir. Otomatik bölütleme için, bir evrişimsel sinir ağı modeli olan U-Net kullanılmış ve gerçek referans değerler ile U-Net ağı ile bölütlenen çıktılar karşılaştırılmıştır. Her iki veri seti için elde edilen yüzdesel doğruluk değerleri sırası ile; retina veri seti için 95.2, hücre veri seti için 97.25 olarak hesaplanmıştır.Automatic segmentation of medical images plays an important role in diagnosing various diseases using these images. Image segmentation can be applied separately through many medical samples to make different analyses and diagnoses. For example, by auto-segmentation cells in a cell culture, the amount, vitality, diameter or shape of the cells in the cell culture can be analysed separately. In addition, by automatic segmentation of blood vessels in a tissue, analyses such as the length and density of the vessels, and the radius of each vessel can be made separately. In this way, inferences such as early diagnosis of a disease and the type of the disease can be made from the examined image. In this study, using two different data sets consisting of various cell images and retinal images, the images in this data set were segmented separately. For automatic segmentation, a convolutional neural network model U-Net is used. The existing ground truth images and the images segmented using the U-Net network were compared. Percentage accuracy values obtained for both data sets, respectively; 95.2 for retina data set and 97.25 for cell data set

Mikrodenetleyicileri Kullanarak Türkçe Sesli Komutlarla Beş Eksenli Manipülatör Kontrolü

The interaction between human beings and machines has been increasing in conjunction with the development of computer technology. Controlling a system with voice-based commands is one of the most popular applications in this area. In this study, the main goal is to build a system, which is able to control a robotic arm comprised of five controllable axes with certain voice commands. The robotic arm controlling process starts with the matching of sounds taken from the user. Then sounds processed in voice recognition card. After the command recognized by voice recognition card, then index number is sent to a microcontroller. Consequently, this operation provides a communication between voice recognition module and servo motor drive card. Finally, the microcontroller calculates the required angles by using the data provided by the previous process and sends this data to the servo motor drive card in order to realize the robotic arm action.Bilgisayar teknolojisi gelişimiyle birlikte, insanlar ile makineler arasındaki etkileşim artmaktadır. Ses tabanlı komutlarla bir sistemi kontrol etmek bu alandaki en popüler uygulamalardan biridir. Bu çalışmada ana hedef, belirli sesli komutlarla beş kontrol edilebilir eksenden oluşan robot kolunu kontrol edebilen bir sistem oluşturmaktır. Robot kolunu kontrol etme işlemi, kullanıcıdan alınan seslerin ve ses tanıma kartında işlenmiş ve ses tanıma kartı tarafından tanımlanan seslerin eşleştirilmesi ile başlar. Ardından pozitif bir eşleme varsa, sistem tarafından ses tanıma modülü ve servo motor sürücü kartı arasında bir iletişim sağlayan bir mikrodenetleyiciye veri gönderilir. Son olarak, mikrodenetleyici, önceki işlem tarafından sağlanan verileri kullanarak gerekli açıları hesaplar ve robotik kol hareketini gerçekleştirmek için bu verileri servo motor sürücü kartına gönderir

Change of soil respiration among different vegetations- results by the year of 2012

In this study, the influence of species type and sampling time on soil respiration in young and old oriental spruce (Picea orientalis (L.) Link.) stands without understory and with a Rhododendron ponticum L. understory and in adjacent grasslands were investigated in Kafkasör region, Artvin, Turkey. For this porpose, three sampling areas were choosen from each vegetation types. Soil respiration was measured at 12 trial courts approximately monthly from May’12 to November’12 using the soda-lime technique. Mean daily soil respiration across all sites ranged from 0,08 to 6,64 g C m-2 d-1. Generally mean soil respiration was higher than others at grasslands and was lower than the others at spruce with a Rhododendron ponticum L. understory. Changes in soil respiration were strongly related to soil temperature, soil moisture and sampling time changes. Overall, grasslands had significantly higher soil respiration rates than did adjacent old forests, indicating greater biological activity within the grasslands

Nitrogen mineralization in burned corsican pine stands

This study was carried out to determine the effects of fire on the nitrogen mineralization. The study was conducted in Vezirkopru Forest area of Samsun Province, Turkey. We made measurements of nitrogen mineralization in 80 to 100 years old Corsican pine(P. nigra) stands subjected to prescribed burning. Measurements were made between November, 2013 and October, 2014. There was no significant difference between burned and control areas in nitrogen mineralization except total N mineralization in 5-10 cm soil depth. The effect of sampling time on the amount of total N mineralization were found to be significant except NH4 mineralization in 5-10 cm depth (P <0.05). The effect of the fire intensity on N mineralization was not significant (P <0.05). We found significant slope factor effect in burned sites in N mineralization (P <0.05), but this effect was not significant in the control sites. N mineralization in the sites with 20-30% slope were lower than N min. in the flat areas in the burned sites, but this was opposite in the control sites. The mean total N mineralization in flat sites were 33,3 kg/ha in burned sites and 32,4 kg/ha in control sites. In the areas with slope, mean total N mineralization were 24,9 kg/ha in burned and 41,1 kg/ha in control sites

Low-cost VIS/NIR Range Hand-held and Portable Photospectrometer and Evaluation of Machine Learning Algorithms for Classification Performance

In this study, the electronic design of a low-cost and portable spectrophotometer device capable of analyzing in the visible-near infrared region was established. The design of C#.NET-based user-friendly device control software and the development of machine learning algorithms for data classification as well as the comparison of the results were presented. When the spectrophotometer design and implementation studies are reviewed in the literature, two groups of subjects become prominent: (i) a new device fabrication, (ii) solution approaches to current problems by combining commercial portable spectrometer systems and devices with artificial intelligence applications. This work encompasses both groups, and a supportive approach has been followed on how to transform the theoretical knowledge into practice in device development and supportive software with the help of machine learning approaches from design to production. Three commercial spectral sensors, each with six photodiode arrays, were adopted in the spectrophotometer. Thus, 18 features belonging to each sample were acquired in the optical spectral region in the 410 nm to 940 nm band range. The spectral analyses were conducted with 9 different food types of powder or flake structures. A Support Vector Machines (SVM) and Convolutional Neural Network (CNN) approaches were employed for data classification. As a result, SVM and CNN achieved 97% and 95% accuracies, respectively. Moreover, we provided the spectral measurement data, the electronic circuit designs, the API files containing the artificial intelligence algorithms and the graphical user interface (GUI)

The investigation of forest fire on soil respiration

We investigated the effect of forest fire disturbance on soil respiration. This study was conducted in Vezirkopru Forest area of Samsun Province, Turkey. We made measurements of soil respiration, soil moisture and soil temperature in the 80 to 100 years old larch stand by controlled burning. Measurements were made between November, 2013 and October, 2014. As a result of the measurement of soil respiration; was found statistically significant effect on soil moisture and soil temperature by time. There were not significant differences between fire and control area with regard to variables of fire intensity and slope (P> 0.05). In general, soil respiration had negative relationship with soil moisture and positive relationship with soil temperature (P <0.05). Soil respiration increases depending on the fire intensity. Soil respiration ranged from 2.63 to 0.94 g C m-2 gün-1

Evaluation of Artvin-Murgul black locust plantations in terms of biomass production, carbon storage, soil quality improvement and erosion control compared to adjacent grassland areas

Black locust plantations in Artvin-Murgul (established in 1996) were investigated for the purposes of: 1) wood production, 2) above- and belowground biomass, 3) carbon storage, 4) soil quality improvement, 5) erosion control and economic value. For these purposes, soil samples were taken from black locust plantation sites and adjacent grassland (control) sites, and soil respiration, soil infiltration, surface runoff, sediment removal, water holding capacity, soil organic matter, texture, pH, N, P, K, Ca, and Mg contents were determined in both areas. Sample trees were cut to determine aboveground biomass and carbon storage. Root samples were taken to determine root biomass and root carbon storage. Surface runoff and erosion were five-fold lower in black locust stands compared to controls (grasslands). Soil quality improvements in black locust areas were not significantly higher than in grasslands. Grasslands had higher soil respiration rates compared to black locust areas. Soil organic matter did not differ significantly between grasslands and black locust areas. Above- and belowground carbon storage were higher in black locust areas than in grassland