Half Gaussian-based wavelet transform for pooling layer for convolution neural network

Pooling methods are used to select most significant features to be aggregated to small region. In this paper, anew pooling method is proposed based on probability function. Depending on the fact that, most information is concentrated from mean of the signal to its maximum values, upper half of Gaussian function is used to determine weights of the basic signal statistics, which is used to determine the transform of the original signal into more concise formula, which can represent signal features, this method named half gaussian transform (HGT). Based on strategy of transform computation, Three methods are proposed, the first method (HGT1) is used basic statistics after normalized it as weights to be multiplied by original signal, second method (HGT2) is used determined statistics as features of the original signal and multiply it with constant weights based on half Gaussian, while the third method (HGT3) is worked in similar to (HGT1) except, it depend on entire signal. The proposed methods are applied on three databases, which are (MNIST, CIFAR10 and MIT-BIH ECG) database. The experimental results show that, our methods are achieved good improvement, which is outperformed standard pooling methods such as max pooling and average pooling

Microstructure Investigation of Activated Carbon Prepared from Potato Peel

This research investigates how activated carbon (AC) was synthesized from potato peel waste (PPW). Different ACs were synthesized under the atmosphere's conditions during carbonation via two activation methods: first, chemical activation, and second, carbon dioxide-physical activation. The influence of the drying period on the preparation of the precursor and the methods of activation were investigated. The specific surface area and pore volume of the activated carbon were estimated using the Brunauer–Emmett–Teller method. The AC produced using physical activation had a surface area as high as 1210 m2/g with a pore volume of 0.37 cm3/g, whereas the chemical activation had a surface area of 1210 m2/g with a pore volume of 0.34 cm3/g. The main aim of this research is to produce activated carbon from natural materials and to prepare and characterize the elemental analysis, surface area, and morphological properties of ACs from potato peel waste using potassium hydroxide (KOH) AC-PPK and Carbon dioxide (CO2) AC-PPC as activating agents. X-ray diffraction analysis showed the degree of crystallinity to be 35.03% in the case of AC-PPK, and AC-PPC showed a crystallinity of 35.46%. In both methods, the results showed that the crystallographic structure revealed that all the synthesized AC took on an amorphous state with low crystallinity. The atomic force microscopy (AFM) image of AC shows the presence of nanotips on the surface and shows that the maximum height was 1396 nm and 778 nm. The outer surfaces are full of cavities and highly irregular as a result of activation. The morphological analysis of the precursors was determined by scanning electron microscopy. The external surfaces are full of cavities and quite irregular as a result of activation. Also, activated carbon prepared from potato peel waste is a low-cost and effective adsorbent when compared with several activated carbon sources

Study the effect of polyphenols extracted from Iraqi grape seeds on glucose , MDA levels and GST activity in streptozotocin (STZ ) induced diabetic mice.

1-Objective:- Polyphenols are biochemical compounds with antioxidant activity against differences diseases related to Lipid peroxidation such as diabetes mellitus. Polyphenols distributed widely in medical plants, the aim of the study is to extract and analyze some polyphenolic compounds from grape seeds and examine their effects on (STZ) induced diabetic mice. 2-Methods:- In the present study , a group of polyphenols has been extracted from Iraqi grape seeds by ethanol and the extract has been analyzed by using High Performance Liquid Chromatography (HPLC) coupled to ultra violet (UV) detection. Five fractions were eluted from the column : procyanidin B1, gallic acid , quercetin , catechin and epicatechin. The detection was recorded at (280 nm). The reactive action of the above polyphenols on glucose, and malondialdehyde (MDA) levels and glutathione – S – transferase (GST) activity was tested in (30) streptozotocin (STZ) induced diabetic mice which treated with extracted grape seeds polyphenols to examine the antioxidant effect of these compounds . Grape seeds polyphenols action on the above parameters was determined before treatment and after (1 week), ( 2 weeks) and (3 weeks) of treatment with this reactive extract. 3-Results:- The data have shown that glucose levels were increased in (30) diabetic mice (after injection with streptozotocin) compared with control group (

Design and Implementation of an Embedded System for Software Defined Radio

In this paper, developing high performance software for demanding real-time embedded systems is proposed. This software-based design will enable the software engineers and system architects in emerging technology areas like 5G Wireless and Software Defined Networking (SDN) to build their algorithms. An ADSP-21364 floating point SHARC Digital Signal Processor (DSP) running at 333 MHz is adopted as a platform for an embedded system. To evaluate the proposed embedded system, an implementation of frame, symbol and carrier phase synchronization is presented as an application. Its performance is investigated with an on line Quadrature Phase Shift keying (QPSK) receiver. Obtained results show that the designed software is implemented successfully based on the SHARC DSP which can utilized efficiently for such algorithms. In addition, it is proven that the proposed embedded system is pragmatic and capable of dealing with the memory constraints and critical time issue due to a long length interleaved coded data utilized for channel coding

Isolation of sophorose during sophorolipid production and studies of its stability in aqueous alkali: epimerisation of sophorose to 2-O-β-d-glucopyranosyl-d-mannose

NMR and anion exchange chromatography analysis of the waste streams generated during the commercial production of sophorolipids by the yeast Candida bombicola identified the presence of small but significant quantities (1% w/v) of free sophorose. Sophorose, a valuable disaccharide, was isolated from the aqueous wastes using a simple extraction procedure and was purified by chromatography on a carbon celite column providing easy access to large quantities of the disaccharide. Experiments were undertaken to identify the origin of sophorose and it is likely that acetylated sophorose derivatives were produced by an enzyme catalysed hydrolysis of the glucosyl-lipid bond of sophorolipids; the acetylated sophorose derivatives then undergo hydrolysis to release the parent disaccharide. Treatment of sophorose with aqueous alkali at elevated temperatures (0.1M NaOH at 50 °C) resulted in C2-epimerisation of the terminal reducing sugar and its conversion to the corresponding 2-O-β-d-glucopyranosyl-d-mannose which was isolated and characterised. In aqueous alkaline solution β-(1,2)-linked glycosidic bonds do not undergo either hydrolysis or peeling reactions

Cartografiado de áreas arenosas y sus cambios mediante teledetección. Caso de estudio en el noreste de la provincia de Al-Muthanna, sur de Irak

[EN] Sandy areas are the main problem in regions of arid and semi-arid climate in the world that threaten urban life, buildings, agricultural, and even human health. Remote sensing is one of the technologies that can be used as an effective tool in dynamic features study of sandy areas and sand accumulations. In this study, two new indices were developed to separate the sandy areas from the non-sandy areas. The first one is called the Normalized Differential Sandy Areas Index (NDSAI) that has been based on the assumption that the sandy area has the lowest water content (moisture) than the other land cover classes. The second other is called the Sandy Areas Surface Temperature index (SASTI) which was built on the assumption that the surface temperature of sandy soil is the highest. The results of proposed indices have been compared with two indices that were previously proposed by other researchers, namely the Normalized Differential Sand Dune Index NDSI and the Eolain Mapping Index (EMI). The accuracy assessment of the sandy indices showed that the NDSAI provides very good performance with an overall accuracy of 89 %. The SASTI can isolate many sandy and non-sandy pixels with an overall accuracy about 86 %. The performance of the NDSI is low with an overall accuracy about 82 %. It fails to classify or isolate the vegetation area from the sandy area and might have better performance in desert environments. The performing of NDSAI that is calculated with the SWIR1 band of the Landsat satellite is better than the performing of NDSI that is calculated with the SWIR2 band of the same satellite. EMI performance is less robust than other methods as it is not useful for extracting sandy surfaces in area with different land covers. Change detection techniques were used by comparing the areas of the sandy lands for the periods from 1987 to 2017. The results showed an increase in sandy areas over four decades. The percentage of this increase was about 20 % to 30 % during 2002 and 2017 compared to 1987.[ES] Las áreas arenosas son el principal problema en las regiones de clima árido y semiárido del mundo que amenazan la vida urbana, los edificios, la agricultura e incluso la salud humana. La teledetección es una de las tecnologías que puede utilizarse como una herramienta eficaz en el estudio de características dinámicas de áreas arenosas y acumulaciones de arena. En este estudio, se desarrollaron dos nuevos índices para separar las áreas arenosas de las áreas no arenosas. El primero llamado Índice de áreas arenosas diferenciales normalizadas (NDSAI), que se ha basado en el supuesto de que el área arenosa tiene el contenido de agua (humedad) más bajo que las otras clases de cobertura del suelo. El segundo llamado índice de temperatura superficial de las áreas arenosas (SASTI), que se basa en el supuesto de que la temperatura superficial del suelo arenoso es la más alta. Estos nuevos índices se han comparado con dos índices propuestos previamente por otros investigadores, a saber, el Índice de dunas de arena diferencial normalizado NDSI y el Eolain Mapping Index (EMI). La evaluación de la precisión de los índices arenosos mostró que el índice NDSAI proporciona un buen desempeño con una precisión general del 89 %. El índice SASTI puede extraer muchos píxeles arenosos y no arenosos con una precisión general del 86 %. El rendimiento del índice NDSI es pobre, con una precisión general del 82 %, no puede clasificar o aislar el área de vegetación del área arenosa y tal vez funcione mejor en entornos desérticos. El índice NDSAI calculado con la banda SWIR1 del satélite Landsat generó resultados más precisos que el NDSI calculado con la banda SWIR2 del mismo satélite. El índice EMI utilizado fue menos robusto que los otros métodos ya que no ha logrado extraer áreas arenosas con una precisión aceptable en áreas con diversas coberturas terrestres. Se utilizaron técnicas de detección de cambios para analizar las áreas de las tierras arenosas para los períodos de 1987 a 2017. Los resultados marcaron un aumento en las áreas arenosas durante cuatro décadas. El porcentaje de este aumento fue de aproximadamente 20 % a 30 % durante 2002 y 2017 en comparación con 1987.Sahar, AA.; Rasheed, MJ.; Uaid, DAA.; Jasim, AA. (2021). Mapping Sandy Areas and their changes using remote sensing. A Case Study at North-East Al-Muthanna Province, South of Iraq. Revista de Teledetección. 0(58):39-52. https://doi.org/10.4995/raet.2021.13622OJS3952058Abbas, A. 2010. Desertification Study of Dalmaj Lake Area in Mesopotamian Plain by Using Remote Sensing Techniques. Baghdad University.Abdul-Ameer, E.A. 2012. 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Enhancing Rice Leaf Disease Classification: A Customized Convolutional Neural Network Approach

In modern agriculture, correctly identifying rice leaf diseases is crucial for maintaining crop health and promoting sustainable food production. This study presents a detailed methodology to enhance the accuracy of rice leaf disease classification. We achieve this by employing a Convolutional Neural Network (CNN) model specifically designed for rice leaf images. The proposed method achieved an accuracy of 0.914 during the final epoch, demonstrating highly competitive performance compared to other models, with low loss and minimal overfitting. A comparison was conducted with Transfer Learning Inception-v3 and Transfer Learning EfficientNet-B2 models, and the proposed method showed superior accuracy and performance. With the increasing demand for precision agriculture, models like the proposed one show great potential in accurately detecting and managing diseases, ultimately leading to improved crop yields and ecological sustainability

Application of GIS Technique to Assess the Habbaniya Lake Water for Human Consumption

Geographic Information System (GIS) technique was used in this study to produce a Water Quality Index (WQI) map to assess the water of Habbaniya Lake for drinking purposes. Sixteen samples of fresh surface water were collected and analyzed to verify the physiochemical parameters of the WQI. These parameters include Total Dissolved Solids, pH, Calcium, Magnesium, Sodium, Potassium, Chloride, Sulfate, and Nitrates. The result of these parameters has been transferred to the GIS platform to construct a water quality database and map of spatial distribution for each parameter using the inverse distance weight (IDW technique). The results of these parameters were also used to calculate irrigation water quality index values, and transferred to the GIS platform for the production of the water quality index map. The spatial distribution index of drinking water in Habbaniya Lake is depicted on this map. It shows that WQI for all water samples is within the second category (50-100) except (S 5 and S 8) below the second category (<50). The short-scope of WQI indicates that the water quality of Habbaniya Lake has been considered as convergent water quality that fluctuated from excellent water to good water for human drinking. It shows also that the northwestern part of Habbaniya Lake waters is more appropriate for drinking since the Al-Warar Canal drains in this part, which takes its water mainly from the Euphrates River

Impact of primary kidney disease on the effects of empagliflozin in patients with chronic kidney disease: secondary analyses of the EMPA-KIDNEY trial

Background: The EMPA KIDNEY trial showed that empagliflozin reduced the risk of the primary composite outcome of kidney disease progression or cardiovascular death in patients with chronic kidney disease mainly through slowing progression. We aimed to assess how effects of empagliflozin might differ by primary kidney disease across its broad population. Methods: EMPA-KIDNEY, a randomised, controlled, phase 3 trial, was conducted at 241 centres in eight countries (Canada, China, Germany, Italy, Japan, Malaysia, the UK, and the USA). Patients were eligible if their estimated glomerular filtration rate (eGFR) was 20 to less than 45 mL/min per 1·73 m2, or 45 to less than 90 mL/min per 1·73 m2 with a urinary albumin-to-creatinine ratio (uACR) of 200 mg/g or higher at screening. They were randomly assigned (1:1) to 10 mg oral empagliflozin once daily or matching placebo. Effects on kidney disease progression (defined as a sustained ≥40% eGFR decline from randomisation, end-stage kidney disease, a sustained eGFR below 10 mL/min per 1·73 m2, or death from kidney failure) were assessed using prespecified Cox models, and eGFR slope analyses used shared parameter models. Subgroup comparisons were performed by including relevant interaction terms in models. EMPA-KIDNEY is registered with ClinicalTrials.gov, NCT03594110. Findings: Between May 15, 2019, and April 16, 2021, 6609 participants were randomly assigned and followed up for a median of 2·0 years (IQR 1·5–2·4). Prespecified subgroupings by primary kidney disease included 2057 (31·1%) participants with diabetic kidney disease, 1669 (25·3%) with glomerular disease, 1445 (21·9%) with hypertensive or renovascular disease, and 1438 (21·8%) with other or unknown causes. Kidney disease progression occurred in 384 (11·6%) of 3304 patients in the empagliflozin group and 504 (15·2%) of 3305 patients in the placebo group (hazard ratio 0·71 [95% CI 0·62–0·81]), with no evidence that the relative effect size varied significantly by primary kidney disease (pheterogeneity=0·62). The between-group difference in chronic eGFR slopes (ie, from 2 months to final follow-up) was 1·37 mL/min per 1·73 m2 per year (95% CI 1·16–1·59), representing a 50% (42–58) reduction in the rate of chronic eGFR decline. This relative effect of empagliflozin on chronic eGFR slope was similar in analyses by different primary kidney diseases, including in explorations by type of glomerular disease and diabetes (p values for heterogeneity all &gt;0·1). Interpretation: In a broad range of patients with chronic kidney disease at risk of progression, including a wide range of non-diabetic causes of chronic kidney disease, empagliflozin reduced risk of kidney disease progression. Relative effect sizes were broadly similar irrespective of the cause of primary kidney disease, suggesting that SGLT2 inhibitors should be part of a standard of care to minimise risk of kidney failure in chronic kidney disease. Funding: Boehringer Ingelheim, Eli Lilly, and UK Medical Research Council