Compressively Sensed Image Recognition

Compressive Sensing (CS) theory asserts that sparse signal reconstruction is possible from a small number of linear measurements. Although CS enables low-cost linear sampling, it requires non-linear and costly reconstruction. Recent literature works show that compressive image classification is possible in CS domain without reconstruction of the signal. In this work, we introduce a DCT base method that extracts binary discriminative features directly from CS measurements. These CS measurements can be obtained by using (i) a random or a pseudo-random measurement matrix, or (ii) a measurement matrix whose elements are learned from the training data to optimize the given classification task. We further introduce feature fusion by concatenating Bag of Words (BoW) representation of our binary features with one of the two state-of-the-art CNN-based feature vectors. We show that our fused feature outperforms the state-of-the-art in both cases.Comment: 6 pages, submitted/accepted, EUVIP 201

The Structural Behavior of Composite Beams With Prefabricated Reinforced Concrete Plate (Connection with Bolt) In Negative Moment Zone

Composite beam are made up by R.C shell and structural steel, and bolts are used forshear connector. Additionally several plates are placed on the bottom face of composite beamfor each test. Therefore composite behaviour, comparison of experimental and numericalresults, shell detachment, the impact of several displacement and shapes of bolts and plates tothe structural behaviour, the crack formation are investigated.300X80X12 cm R.C shell and 300 cm HEB 120 are joined by the help of bolts andplates, and samples are tested. These samples are 3 sets (total of 6 quantities) are made ofcomposite beams.Simple span beams are set for easily rotatable at the supports. At the middle of thespan P point load is applied. Ultimate load of bearing capacity is determined when the minorcrack is occurred.Load - deformation, load - extension, moment - curvature diagrams are drawn and comparisons are made at the end of the tests. Eventually compatibility of plastic calculation method, the impact of situation of uprising shell to the bearing capacity, using of plate reducethe deformation and increase the crack load are investigated and bolts as a well shear connector is proved

MAMAF-Net: Motion-Aware and Multi-Attention Fusion Network for Stroke Diagnosis

Stroke is a major cause of mortality and disability worldwide from which one in four people are in danger of incurring in their lifetime. The pre-hospital stroke assessment plays a vital role in identifying stroke patients accurately to accelerate further examination and treatment in hospitals. Accordingly, the National Institutes of Health Stroke Scale (NIHSS), Cincinnati Pre-hospital Stroke Scale (CPSS) and Face Arm Speed Time (F.A.S.T.) are globally known tests for stroke assessment. However, the validity of these tests is skeptical in the absence of neurologists. Therefore, in this study, we propose a motion-aware and multi-attention fusion network (MAMAF-Net) that can detect stroke from multimodal examination videos. Contrary to other studies on stroke detection from video analysis, our study for the first time proposes an end-to-end solution from multiple video recordings of each subject with a dataset encapsulating stroke, transient ischemic attack (TIA), and healthy controls. The proposed MAMAF-Net consists of motion-aware modules to sense the mobility of patients, attention modules to fuse the multi-input video data, and 3D convolutional layers to perform diagnosis from the attention-based extracted features. Experimental results over the collected StrokeDATA dataset show that the proposed MAMAF-Net achieves a successful detection of stroke with 93.62% sensitivity and 95.33% AUC score

Evaluation from Rural to Urban Scale for the Effect of NDVI-NDBI Indices on Land Surface Temperature, in Samsun, Türkiye

In this study, in order to evaluate the change of LST from rural to urban scale in 20 years, a zoonal statistical analysis was performed by separating the urban and rural districts located on the coastline. Algorithms were applied to the raw data of Landsat 8 and Landsat 7 satellite images, using the Arc Gis 10.2 and Q Gis 3.16 utilities. In this way, NDVI, NDBI and LST data were compared and evaluated in terms of rural and urban districts. The correlation coefficient between the parameters was calculated. In the study, the land change between the years 2000-2020 was also determined to reveal the land change. As a result of the analyzes made, the amount of green areas decreased by 14.1% between 2000 and 2020 in the study area, which includes the central districts of Samsun, İlkadım and Atakum, and in the rural areas, Bafra and Ondokuz Mayıs. It has been observed that this rate is shared as 7.1% in built up areas and 7.33% in bare soil areas. Considering the effect of the decrease in green areas on the LST value, in 2000, max. While LST is 41.75 C, in 2020 max. It is seen that LST has increased to 43.44 C. When the districts were analyzed separately, it was seen that LST established a strong correlation with NDBI (positive) and NDVI (negative) for all four districts. However, the correlation was stronger in rural districts. It was observed that the correlation strength weakened in urban districts due to heterogeneous land surface cover

Three-Year Evaluation of Nosocomial Infection Rates of the ICU

AbstractBackground and objectivesEvaluating the incidence of nosocomial and invasive device-related infections enables the comparison of the health care associated infection (HAI) between the intensive care units of different hospitals and different units in the same hospital.Material and methodsA retrospective surveillance study was performed to identify nosocomial infections, device-related infections rates, and causal agents from January 2007 through December 2010 in the Anesthesiology Intensive care unit (ICU). HAI were defined according to the CDC (Centers for Disease Control and Prevention) criteria, and invasive device-related infections were defined according to National Nosocomial Infection Surveillance System (NNIS) criteria.ResultsDuring a two-year period, 939 patients were analyzed throughout a total of 7,892 patientdays. The rates of HAI were 53% in 2007, 29.15% in 2008, 28.85% in 2009 while 16.62% in 2010. Most common HAI was blood stream infection. The rate of soft tissue and skin infection was the second most common. Overall, the most common agents were Gram(−) 56.68%, Gram(+) 31.02% and Candida spp 12.3% among patients with nosocomial infections.ConclusionsThe incidence of HAI in the ICU of our hospital was high, compared to the Turkish overall rates obtained at the Refik Saydam Center in 2007. When the rates of device-related infections between 2007 and 2008 were compared, they were higher in 2007. The rates of devicerelated infections were diminished in 2008 to below-national mean rates by infection control measures. Since the rate of urinary catheter-related infections are still high, we should exert continuous efforts for infection control

Assessment of the energy and exergy efficiencies of farm to fork grain cultivation and bread making processes in Turkey and Germany

Energy and exergy efficiencies of the wheat and rye bread and hamburger bunmaking processes are assessed based on data from Turkey and Germany. Amount of the land required to produce the same amount of wheat in Turkey is 3.34 times of that required in Germany; this ratio is 2.30 for the rye grain. These results show that the efficiency of the conversion of the solar energy into the grain mass is low in Turkey. Cumulative degree of perfection (CDP) for the wheat and the rye grain production is 3.73 and 4.96 in Turkey, and 11.26 and 10.46 in Germany. Specific energy utilization for rye bread production is almost the same in Turkey and Germany; but it is 12 % higher in Turkey for wheat bread and hamburger bun making. Hamburger bun production requires the maximum energy utilization due to the higher weight loss in baking. The rye bread production process requires the minimum energy utilization due to the lower energy input in the agriculture and higher efficiency in the flour production. The maximum exergy destructions occur during the milling and the baking steps

Using the Remote Sensing Method to Simulate the Land Change in the Year 2030

This is study is based with the support of RS-GIS technology on the land use of Samsun Center, as well as the coastal districts of Ilkadım,Atakum,Bafra Plain, through the processing and interpretation of satellite images in the summer months of 2000,2010,2020. Spatial and temporal variability properties of LU/LC were determined using MLC algorithm, controlled classification approach. The predictive values of the LU/LC change that will occur in 2030, calculated with the MLP‑ANN model based on Machine Learning algorithms and mapped with the QGIS 3.16 program. To determine the accuracy coefficient of the model, 2020 LU/LC simulation performed using the transition potential matrix of 2000 and 2010 LU/LC data. The results of simulation were compared the data of land use land cover with the 2020 to evaluate the accuracy of the simulation model. The model of MLP‑ANN provided an accuracy of 72% based on the kappa fit index. According to MLP‑ANN model 2030 results were an increase of 73.33 km² in built up areas, an increase of 56.89 km² in bare areas, and a decrease of 129.66 km² in green areas. It provided a reference basis for future Samsun urban to rural coastline LU planning and management and LU structure optimization

SAM: A new GHz sampling ASIC for the H.E.S.S.-II front-end electronics

The H.E.S.S.-II front-end electronics, with its 20 GeV energy threshold, will require a much higher acquisition rate capability and a larger dynamic range than was relevant for H.E.S.S.-I. These constraints led to the development of a new ASIC, called SAM for Swift Analogue Memory, to replace the ARS used for H.E.S.S.-I. The SAM chip features 2 channels for the low and high gain outputs of a PMT, each channel having a depth of 256 analogue memory cells. The sampling frequency is adjustable from 0.7 up to 2 GS/s and the read-out time for one event is decreased from 275 down to 2.3 μs. The SAM input bandwidth and dynamic range are increased up to 300 MHz and more than 11 bits, respectively

Pixel Detectors for Charged Particles

Pixel Detectors, as the current technology of choice for the innermost vertex detection, have reached a stage at which large detectors have been built for the LHC experiments and a new era of developments, both for hybrid and for monolithic or semi-monolithic pixel detectors is in full swing. This is largely driven by the requirements of the upgrade programme for the superLHC and by other collider experiments which plan to use monolithic pixel detectors for the first time. A review on current pixel detector developments for particle tracking and vertexing is given, comprising hybrid pixel detectors for superLHC with its own challenges in radiation and rate, as well as on monolithic, so-called active pixel detectors, including MAPS and DEPFET pixels for RHIC and superBelle.Comment: 19 pages, 23 drawings in 14 figure