213 research outputs found
EFFECT OF GREEN FACADE ON THE URBAN MICROCLIMATE WITH DIFFERENT STREET CANYON
No full textUsing simulation tools, this study investigates the effect of green walls (GWs) on the urban heat island (UHI) phenomenon within different street sizes. It can be planted without taking up more area and could enhance the microclimate environment, which is why it has a wide range of use potential in urban areas. Because Mina City has a threat of UHI, it was chosen for this study. The temperature within various street sizes in the research region was evaluated using only software called ENVI-met that simulates climate, and three common scenarios were chosen. In the first experiment, green walls extending over an area of 50 m in the south facades of the street building, including a 3m Street width, are simulated to show the effect of GWs on UHI. In the second experiment, the Street width changed to 6 m, and the GWs are placed in the same condition. The last experiment is the same with a 9m street width. Temperature decreases from each green wall were contrasted with the street canyon situation as it was at the time of evaluation 1\u27s highest heat. In comparison to evaluation 1, the temperature decreases achieved by evaluation alternatives 2, 3, 4, and 5 were 2.17 °C, 1.97 °C, 1.78 °C, and 0.90 °C, accordingly. Conclusion: A well-planned urban green wall can significantly improve UHI in tropical Lebanon
Recognizing Driving Behavior and Road Anomaly using Smartphone Sensors
No full textRoad traffic accidents are caused 1.25 million deaths per year worldwide. To improve road safety and reducing road accidents, a recognition method for driving events is introduced in this paper. The proposed method detected and classified both driving behaviors and road anomalies patterns based on smartphone sensors (accelerometer and gyroscope). k-Nearest Neighbor and Dynamic Time Warping algorithms were utilized for method evaluation. Experiments were conducted to evaluate k-nearest neighbor and dynamic time warping algorithms accuracy for road anomalies and driving behaviors detection, moreover, driving behaviors classification. Evaluation results showed that k-nearest neighbor algorithm detected road anomalies and driving behaviors with total accuracy 98.67%. Dynamic time warping algorithm classified (normal and abnormal) driving behaviors with total accuracy 96.75%.</jats:p
Low Intensity Laser Irradiation Influence Proliferation of Mesenchymal Stem Cells: Comparison of Experimental Data to Intelligent Agent-Based Model Predictions
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Robust waveform design for MIMO radar from information theoretic and machine learning principles
No full textDie Radartechnologie ist für viele zivile Anwendungen von entscheidender Bedeutung geworden, doch viele alte Probleme stellen nach wie vor eine Herausforderung dar. Um diese Herausforderungen zu bewältigen, werden innovative und robuste Signalverarbeitungstechniken benötigt. In dieser Arbeit werden neue Lösungen aus Sicht der Informationstheorie und des maschinellen Lernens vorgeschlagen. Im ersten Hauptteil der Arbeit schlagen wir vor, die potenziellen Auswirkungen der unerwünschten Umgebungseinflüsse durch die Gestaltung der Signalform zu überwinden. Dazu schlagen wir verschiedene Strategien vor, die auf der Betriebsart des Radars und den verfügbaren Vorabinformationen basieren. Im zweiten Hauptteil gehen wir mit datengesteuerten Ansätzen auf allgemeine Probleme der DOA-Algorithmen ein, wobei wir beweisen, dass neuronale Netze die eingehenden Signale entrauschen und die schlechte Auflösung kleiner Arrays überwinden können.Radar technology has become key for many civilian applications but a lot of inherited problems remain a challenge. To address these challenges, innovative and robust signal processing techniques are needed. This thesis proposes novel solutions from information theory and machine learning perspectives. In the first main part of the thesis, we propose to overcome the potential effects of the environmental undesired returns through waveform design. Thus, we propose different strategies to tackle this problem based on the radar operation mode and the priori information available. In the second main part, armed with data driven approaches, we address DOA algorithms common problems, where we prove that neural networks can denoise the incoming signals and can overcome the poor resolution of small arrays
Robust Reinforcement Learning-based Wald-type Detector for Massive MIMO Radar
No full textInternational audienceThe two basic performance indices characterizing the multi-target detection task in a radar system are the probability of false alarm (PF A) and the probability of detection PD. It is well-known that, when the disturbance model (i.e., clutter and noise) is perfectly known, the Neyman-Pearson (NP) detector provides the best decision strategy, i.e., the detector that maximizes the PD, while keeping a constant PF A. However, in practical scenarios, the a priori knowledge of the statistical model of the disturbance is rarely available. In this paper we investigate the robustness of a reinforcement learning (RL) based Wald-type test to guarantee reliable detection performance even without knowledge of the disturbance distribution. Specifically, the constant false alarm Rate (CFAR) property is obtained by applying tools from misspecified asymptotic statistics, while the PD is maximized by exploiting an RL-based scheme
A Survey on AI Techniques for Thoracic Diseases Diagnosis Using Medical Images
No full textThoracic diseases refer to disorders that affect the lungs, heart, and other parts of the rib cage, such as pneumonia, novel coronavirus disease (COVID-19), tuberculosis, cardiomegaly, and fracture. Millions of people die every year from thoracic diseases. Therefore, early detection of these diseases is essential and can save many lives. Earlier, only highly experienced radiologists examined thoracic diseases, but recent developments in image processing and deep learning techniques are opening the door for the automated detection of these diseases. In this paper, we present a comprehensive review including: types of thoracic diseases; examination types of thoracic images; image pre-processing; models of deep learning applied to the detection of thoracic diseases (e.g., pneumonia, COVID-19, edema, fibrosis, tuberculosis, chronic obstructive pulmonary disease (COPD), and lung cancer); transfer learning background knowledge; ensemble learning; and future initiatives for improving the efficacy of deep learning models in applications that detect thoracic diseases. Through this survey paper, researchers may be able to gain an overall and systematic knowledge of deep learning applications in medical thoracic images. The review investigates a performance comparison of various models and a comparison of various datasets
Assessment of thyroid gland functions and hypogonadism among male patients with COPD
No full textAbstractChronic obstructive pulmonary disease (COPD) is no longer considered to affect only the lungs and airways but also the rest of the body. The systemic manifestations of COPD include a number of endocrine disorders, such as those involving the pituitary, the thyroid, the gonads, the adrenals and the pancreas.Aim of the workThe aim of this work was to assess thyroid gland functions and hypogonadism among male patients with COPD and its relation to diseases severity.Patients and methodsThe study included 60 male patients diagnosed as COPD were selected and classified according to the Egyptian society for chest diseases and tuberculosis (ESCT) into three groups (mild, moderate and sever COPD) where cases and their age matched controls were evaluated as regard thyroid, gonadotrophins and androgen levels (TSH, FT3, FT4, FSH, LH, DHEAS-S, testosterone total and free were measured).ResultsWhen we made comparison between patients with different grades of COPD as regard thyroid, gonadotrophins and androgen levels we found statistical difference between mild versus moderate and mild versus severe COPD as regard FT3 and mild versus moderate and severe COPD as regard DAHEAS-S and testosterone. And, the study showed that’s there were statistical difference as regard free testosterone among patients with COPD, but there was high statistical significant difference as regard DHEAS-S and testosterone.ConclusionAfter assessment of thyroid gland functions and hypogonadism among male patients with COPD, we found hypogonadism increases with age and the degree of severity of COPD
Table1_Inhibition of Brain GTP Cyclohydrolase I Attenuates 3-Nitropropionic Acid-Induced Striatal Toxicity: Involvement of Mas Receptor/PI3k/Akt/CREB/ BDNF Axis.DOCX
No full textGTP cyclohydrolase I (GTPCH I) is the rate-limiting enzyme for tetrahydrobiopterin (BH4) biosynthesis; the latter is an essential factor for iNOS activation that contributes neuronal loss in Huntington’s disease (HD). The aim of the study was to investigate the neuroprotective effect of 2,4-diamino-6-hydroxypyrimidine (DAHP), GTPCH I enzyme inhibitor, against neuronal loss in 3-nitropropinic acid (3-NP)-induced HD in rats and to reveal the possible involved mechanisms mediated through PI3K/Akt axis and its correlation to Mas receptor (MasR). Rats received 3-NP (10 mg/kg/day; i.p.) with or without administration of DAHP (0.5 g/kg/day; i.p.) or wortmannin (WM), a PI3K inhibitor, (15 μg/kg/day; i.v.) for 14 days. DAHP improved cognitive, memory, and motor abnormalities induced by 3-NP, as confirmed by striatal histopathological specimens and immunohistochemical examination of GFAP. Moreover, DAHP treatment inhibited GTPCH I activity, resulting in decreased BH4 levels and iNOS activation. Also, DAHP upregulated the protein expression of survival protein; p85/p55 (pY458/199)-PI3K and pS473-Akt that, in turn, boosted the activation of striatal neurotrophic factors and receptor, pS133-CREB, BDNF and pY515-TrKB, which positively affect MasR protein expression and improve mitochondrial dysfunction, as indicated by enhancing both SDH and PGC-1α levels. Indeed, DAHP attenuates oxidative stress by increasing SOD activity and Nrf2 expression in addition to reducing neuro-inflammatory status by inhibiting NF-κB p65 and TNF-α expression. Interestingly, all the previous effects were blocked by co-administration of WM with DAHP. In conclusion, DAHP exerts neuroprotective effect against neuronal loss induced by 3-NP administration via inhibition of GTPCH I and iNOS activity and activation of MasR/PI3K/Akt/CREB/BDNF/TrKB axis besides its antioxidant and anti-inflammatory effect.</p
Table2_Inhibition of Brain GTP Cyclohydrolase I Attenuates 3-Nitropropionic Acid-Induced Striatal Toxicity: Involvement of Mas Receptor/PI3k/Akt/CREB/ BDNF Axis.DOCX
No full textGTP cyclohydrolase I (GTPCH I) is the rate-limiting enzyme for tetrahydrobiopterin (BH4) biosynthesis; the latter is an essential factor for iNOS activation that contributes neuronal loss in Huntington’s disease (HD). The aim of the study was to investigate the neuroprotective effect of 2,4-diamino-6-hydroxypyrimidine (DAHP), GTPCH I enzyme inhibitor, against neuronal loss in 3-nitropropinic acid (3-NP)-induced HD in rats and to reveal the possible involved mechanisms mediated through PI3K/Akt axis and its correlation to Mas receptor (MasR). Rats received 3-NP (10 mg/kg/day; i.p.) with or without administration of DAHP (0.5 g/kg/day; i.p.) or wortmannin (WM), a PI3K inhibitor, (15 μg/kg/day; i.v.) for 14 days. DAHP improved cognitive, memory, and motor abnormalities induced by 3-NP, as confirmed by striatal histopathological specimens and immunohistochemical examination of GFAP. Moreover, DAHP treatment inhibited GTPCH I activity, resulting in decreased BH4 levels and iNOS activation. Also, DAHP upregulated the protein expression of survival protein; p85/p55 (pY458/199)-PI3K and pS473-Akt that, in turn, boosted the activation of striatal neurotrophic factors and receptor, pS133-CREB, BDNF and pY515-TrKB, which positively affect MasR protein expression and improve mitochondrial dysfunction, as indicated by enhancing both SDH and PGC-1α levels. Indeed, DAHP attenuates oxidative stress by increasing SOD activity and Nrf2 expression in addition to reducing neuro-inflammatory status by inhibiting NF-κB p65 and TNF-α expression. Interestingly, all the previous effects were blocked by co-administration of WM with DAHP. In conclusion, DAHP exerts neuroprotective effect against neuronal loss induced by 3-NP administration via inhibition of GTPCH I and iNOS activity and activation of MasR/PI3K/Akt/CREB/BDNF/TrKB axis besides its antioxidant and anti-inflammatory effect.</p
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