A high performance hardware architecture for one bit transform based motion estimation

Motion Estimation (ME) is the most computationally intensive part of video compression and video enhancement systems. One bit transform (IBT) based ME algorithms have low computational complexity. Therefore, in this paper, we propose a high performance systolic hardware architecture for IBT based ME. The proposed hardware performs full search ME for 4 Macroblocks in parallel and it is the fastest IBT based ME hardware reported in the literature. In addition, it uses less on-chip memory than the previous IBT based ME hardware by using a novel data reuse scheme and memory organization. The proposed hardware is implemented in Verilog HDL. It consumes %34 of the slices in a Xilinx XC2VP30-7 FPGA. It works at 115 MHz in the same FPGA and is capable of processing 50 1920x1080 full High Definition frames per second. Therefore, it can be used in consumer electronics products that require real-time video processing or compression

CINet: A Learning Based Approach to Incremental Context Modeling in Robots

There have been several attempts at modeling context in robots. However, either these attempts assume a fixed number of contexts or use a rule-based approach to determine when to increment the number of contexts. In this paper, we pose the task of when to increment as a learning problem, which we solve using a Recurrent Neural Network. We show that the network successfully (with 98\% testing accuracy) learns to predict when to increment, and demonstrate, in a scene modeling problem (where the correct number of contexts is not known), that the robot increments the number of contexts in an expected manner (i.e., the entropy of the system is reduced). We also present how the incremental model can be used for various scene reasoning tasks.Comment: The first two authors have contributed equally, 6 pages, 8 figures, International Conference on Intelligent Robots (IROS 2018

Mineral element distribution of cotton (Gossypium hirsutum L.) seedlings under different salinity levels

Cotton (Gossypium hirsutum L.) is the world's leading natural fiber and second largest oilseed crop. In addition to textile manufacturing, cotton and cotton-by products are the sources of wealth of consumer based products, livestock feed, fertilizer, foodstuff and paper. High concentrations of NaCl in soils account for large decreases in the yield of a wide variety of crops all over the world. The present study was conducted to evaluate NaCl stress on mineral nutrient composition of cotton due to its economic importance. Cotton seeds were germinated in Magenta vessels containing Murshige and Skoog (MS) media for 15 days and then transferred in sterile jars containing MS exposed to different levels of NaCl (50, 100, 200 and 400 mM) treatments for 1 month. Uptake of some mineral nutrients (B, Ca, Fe, K, Mg, Mn, Na and Zn) by the plants was examined in roots and leaves by using an Inductively Coupled Plasma Optical Emission Spectrometer (ICP-OES). The data proved that plant growth and uptake and accumulation of microelements are altered extensively in cotton grown with NaCl. Excess NaCl reduces the uptake pattern of certain elements and increases that of others, the patterns depending on the element and the plant part being compared to the control.Marmara University, Commission of Scientific Research Project under grant FEN-A-030108-001

SÜRÜ ZEKASI YÖNTEMLERİYLE AŞIRI ÖĞRENME MAKİNESİ’NİN ÖĞRENME PARAMETRELERİ OPTİMİZASYONU

SÜRÜ ZEKASI YÖNTEMLERİYLE AŞIRI ÖĞRENME MAKİNESİ’NİN ÖĞRENME PARAMETRELERİ OPTİMİZASYONUÖzetSinir ağları algoritmalarından olan Aşırı Öğrenme Makinesi (AÖM)’de giriş ağırlığı ve gizli eşik değeri parametrelerinin rastgele seçilmekte ve çıktı katman ağırlıkları analitik olarak hesaplanmaktadır. Bundan dolayı ağın öğrenme işlemi hızlı bir şekilde gerçekleşmektedir. Ayrıca AÖM’nin gradyan temelli algoritmalara göre gizli katmanda ihtiyaç duyduğu nöron sayısı daha fazla olmaktadır. Bu nedenle giriş ağırlıkları ve gizli nöron eşik değerlerinin optimum değerlerinin bulunması AÖM'nin performansına etki etmektedir. Bu çalışmada bu optimum değerlerin belirlenmesinde sürü zekası algoritmalarından Parçacık Sürü Optimizasyonu (PSO) ve Rekabetçi Sürü İyileştirici (RSİ) kullanılmıştır. Optimum giriş ağırlıkları ve gizli eşik değerlerinin belirlenerek çıkış ağırlıkları Moore-Penrose genelleştirilmiş tersiyle analitik olarak hesaplanmıştır. AÖM, RSİ-AÖM ve PSO-AÖM modellerinin çok sınıflı tiroit veri setine uyarlanarak öğrenme parametrelerinin optimizasyonu ile en iyi doğruluk oranları sırasıyla %94.74, %94.86, %95.42 olarak elde edilmiştir. Optimizasyon metotlarının AÖM modellerinin sınıflandırma performansını artırdığı görülmüştür.Anahtar Kelimeler: Aşırı Öğrenme Makinesi (AÖM), Metasezgisel, Parçacık Sürü Optimizasyonu (PSO), Rekabetçi Sürü İyileştirici (RSİ)OPTIMIZATION OF LEARNING PARAMETERS OF EXTREME LEARNING MACHINE WITH SWARM INTELLIGENCE METHODSAbstractIn the Extreme Learning Machine (ELM), which is one of the neural networks algorithms, the input weight and hidden bias value parameters are randomly selected and the output layer weights are calculated analytically. Therefore, the learning process of the network takes place quickly. In addition, the number of neurons needed by the hidden layer is higher than the gradient-based algorithms. Finding optimum values of entry weights and hidden neuron bias values affects the performance of the ELM. In this study, Particle Swarm Optimization (PSO) and Competitive Swarm Optimizer (CSO) were used to determine these optimum values. By determining the optimum input weights and hidden bias values, the output weights were analytically calculated by Moore-Penrose generalized inverse. By adapting the multi-class thyroid data set of ELM, CSO-ELM and PSO-ELM models, the best accuracy rates were obtained as 94.74%, 94.86%, 95.42% respectively. It has been seen that optimization methods increase the classification performance of the ELM models.Keywords: Extreme Learning Machine (ELM), Metaheuristic, Particle Swarm Optimization (PSO), Competitive Swarm Optimizer (CSO

Salinity induced changes in cotton (Gossypium hirsutum L.)

Cotton (Gossypium hirsutum L.) is susceptible to abiotic stresses. High salinity is a common abiotic stress condition that adversely affects plant growth. Altered ion and water homeostasis changes due to NaCI stress, lead to molecular damage, growth arrest and even death. As a consequence of salt stress effects, secondary stresses such as oxidative damage by reactive oxygen species may occur. Reactive oxygen species can alter cellular metabolism through oxidative damage of lipids, proteins and nucleic acids causing lipid peroxidation, protein denaturing and DNA mutation. In recent years, several selective and sensitive assays have been developed to evaluate the effects of environmental stress on vegetal organisms. RAPD is one of them and developed for DNA analysis. In this study, cotton seedlings were used as bioindicator of salinity stress in the range of 50-400 mM. Effects of salinity stress were determined by comparing RAPD profiles of normal and treated cotton seedlings include variations in band intensities as well as gains or losses of band numbers. The DNA polymorphisms detected by RAPD analysis could be used as an investigation tool and useful biomarker assay for observing environmental stresses such as high salinity on vegetal organisms.Marmara University, Commission of Scientific Research Project under grant FEN-A-030108-001

Competitiveness of forest products industry sector in Turkey: Revealed comparative advantage index

This study, aimed to determine the competitive advantage position of the forest products industry sector in Turkey between 2001-2017 by using the revealed comparative advantage approach. One of the three sub-production structures (wood and articles of wood; wood charcoal-21 sub-product group) of the forest products industry were examined at the level of their sub-product groups. As a result of the study, "the wood and articles of wood;wood charcoal" sector was far from the desired position in terms of competition. When "the wood and articles of wood;wood charcoal" sector was analyzed on sub-group basis, especially the products of 4411, 4413 and 4415 had competitive position. Moreover, it was found that the trend in Turkey's imports of wood and articles of wood sector was not high. However, imports carried out under specified product groups were carried above the level of imports in Turkey

Determination of some heavy metals and mineral nutrients of bay tree (Laurus nobilis L.) in Bartin city, Turkey

Concentrations of Al, Cd, Cu, Ni, and Pb in Laurus nobilis L. were examined for assessment of the impact of heavy metal exposure during winter periods, since these metals have the highest toxic potential. In this study, leaf (washed and unwashed), bark and branch samples of L. nobilis and soil samples were collected from 13 different localities, belonged to three stations. In conjunction with analyzing impact of the heavy metal exposure on the city using L. nobilis as a biomonitoring tool, the uptake and composition of mineral nutrients of L. nobilis were also investigated for determining the effects of heavy metals on mineral nutrition metabolism of the plant. The heavy metal and mineral nutrient concentrations of the collected samples were measured by using ICP-OES. The obtained data was analyzed with SPSS statistics program. As a result of measurements, the lowest and highest heavy metal accumulations and the amount of mineral nutrients measured in plants were as follows; Al (14.69-122.44 mg/kg d. wt), Cd (0.23-0.89 mg/kg d. wt), Cu (1.64-14.25 mg/kg d. wt.), Ni (0.001-0.45 mg/kg d. wt.), Pb (2.06-5.28 mg/kg d. wt.) and B (1.04- 6.67 mg/kg d. wt.), Ca (1195.34-4919.03 mg/kg d. wt.), Fe (17.13-203.25 mg/kg d. wt.), K (538.99-3778.37 mg/kg d. wt.), Mg(48.1-268.5 mg/kg d. wt.), Na (24.91-77.43 mg/kg d. wt.) and Zn (4.75-15.74 mg/kg d. wt.). According to the experimental data, the volume of the air pollution was analyzed and found significant in the city. Also, it was noticed that the metabolism of mineral nutrients of L. nobilis was altered by heavy metals. Finally, it was proved that L. nobilis is a suitable organism to be used as a biomonitoring tool for conducting research on heavy metal pollution

Autekologi dan Fisiologi Percambahan Centaurea kilaea Boiss. dari Turki

In this study germination requirements, plant-soil interactions and population biology of Centaurea kilaea was studied. The plant and soil samples were collected from Sofular Village (Sile District) and shore of Çatalca District (Istanbul) in Turkey by using standard methods. Methods like Scheibler, Wetdigestion, Kjeldahl and Olsen were employed for measurement of soil texture, structure and other physical and chemical characteristics (pH, total protein and electrical conductivity) using spectrophotometer, flame photometer, calcimeter and ICP. The results showed that ranges of different elements in the soil were 0.007-0.2% for N, 0.0007-0.001% for P, 0.001-0.01% for K, 0.0001-0.0002 % for Na. N, P, K and Na values in the plants were 2.17, 0.005, 0.1 and 0.006%, respectively. The data revealed that germination success of the seeds was influenced by the environmental factors such as pH, germination season and temperature.Dalam kajian ini keperluan percambahan, saling tindakan tumbuhan-tanih dan biologi populasi Centaurea kilaea telah dilakukan. Sampel tumbuhan dan tanih telah dikumpul dari Kampung Sofular (Daerah Şile) dan pantai Daerah Çatalca (Istanbul) di Turki dengan menggunakan kaedah piawai. Kaedah seperti Scheibler, Wetdigestion, Kjeldahl dan Olsen telah digunakan bagi pengukuran tekstur tanih, struktur dan sifat fizikal dan kimia lain (pH, jumlah protein dan kekonduksian elektrik) menggunakan spektrofotometer, fotometer api, kalsimeter dan ICP. Hasil menunjukkan bahawa julat unsur berbeza dalam tanih ialah 0.007-0.2% bagi N, 0.0007-0.001% bagi P, 0.001-0.01% bagi K, 0.0001-0.0002% bagi Na. N, P, K dan nilai Na dalam tumbuhan ialah masing-masing 2.17, 0.005, 0.1 dan 0.006%. Data menunjukkan kejayaan percambahan bagi biji benih telah dipengaruhi faktor persekitaran seperti pH, musim percambahan dan suhu

Mineral element uptake status of endemic Isoetes anatolica Prada & Rolleri populations from Bolu-Turkey

Isoetes genus is commonly known as the "quillworts" and considered to be "fern allies". There are about 200-250 species, with a cosmopolitan distribution but often scarce to rare. Isoetes genus members often grow in extremely sensitive aquatic environments such as temporary ponds, streams and lakes. They are therefore good indicators of environmental quality. Isoetes anatolica Prada & Rolleri is an endemic plant grows on calcareous sediment/soil on the edges of seasonal ponds located in a mountainous area near the southern coast of the Black Sea at 1400 m above sea level at Bolu, Turkey. In this study, mineral element uptake statuses of I. anatolica populations were studied on the background of plant-sediment/soil-water interactions. The study materials were collected from the place where this narrow endemic species only lives in the world (Abant Region, Bolu/Turkey) by using standard methods and plant and sediment/soil mineral element measurements (Al, B, Ca, Cu, Fe, K, Mg, Mn, Na, Ni and Zn) were done. ICP-OES was employed for the measurements during the study. Interrelations between mineral element contents in the sediment/soil, water and plant were discussed. The data revealed that I. anatolica is capable of accumulating considerable amounts of certain mineral elements (B, Ca, Mn and Na).Marmara University, Commission of Scientific Research Project (FEN-D-040712-0291