Search results for: events detection

Authors: J. Jasmee, I. Roslina, A. Mohammed Yaziz & A.H Juazer Rizal

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The need of an effective building information collection method is vital to support a diversity of land development activities. At present, advances in remote sensing such as airborne LiDAR (Light Detection and Ranging) is an established technology for building information collection, location, and elevation of the reflecting laser points towards the construction of 3D building models. In this study, LiDAR datasets and terrestrial photographic images of buildings towards the construction of 3D building models is explored. It is found that, the quantitative accuracy of the constructed 3D building model, namely in the horizontal and vertical components were ± 0.31m (RMSEx,y) and ± 0.145m (RMSEz) respectively. The accuracies were computed based on sixty nine (69) horizontal and twenty (20) vertical surveyed points. As for the qualitative assessment, it is shown that the appearance of the 3D building model is adequate to support the requirements of LOD3 presentation based on the OGC (Open Geospatial Consortium) standard CityGML.

Keywords: LiDAR datasets, DSM, DTM, 3D building models

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Authors: Islam Abou El-Magd, Elham Ali, Ali Amasha

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Earthquakes strike without warning and cause widespread damage to social and economic infrastructures and creating life losses. These can neither be predicted nor prevented in terms of their magnitude, place, and time of occurrence. It is a global phenomenon that creates nearly 18% of life losses and nearly 35% of economic damage. The coastal zone of Egypt is considered low to medium risk, however, there is a record of high magnitude earthquakes that created Tsunami in the past. The northern coastal zone of Egypt is under the force of tension shear zones of African and European plates that have considerable earthquakes with variable degrees. This research studied the earthquakes in the last 65 years in the Mediterranean Basin in relation to the geotectonic shear zones. 85% of these earthquakes are in the marine that might create Tsunami. Aegean and Anatolia shear zones are the highest contributors of the earthquakes with nearly 37% and 36% respectively. However the least one is the Arabia zone with 1%, and Africa is about 26%. The research proposed three scenarios for the socioeconomic hazards, earthquakes with Tsunami that will destroy one fifth of the economic infrastructures with unpredictable life losses. The estimated cost of recovery of such losses is nearly 400B USD. The second scenario is earthquake without Tsunami that will impact the major urban and infrastructures. The last scenario is tidal gauges events that threaten the low-lying areas particularly the eastern side which has major land subsidence.

Keywords: natural hazards, earthquakes, tusnami, Nile delta, Egypt

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Authors: Yao-Hong Tsai

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This paper presents an efficient fusion algorithm for iris images to generate stable feature for recognition in unconstrained environment. Recently, iris recognition systems are focused on real scenarios in our daily life without the subject’s cooperation. Under large variation in the environment, the objective of this paper is to combine information from multiple images of the same iris. The result of image fusion is a new image which is more stable for further iris recognition than each original noise iris image. A wavelet-based approach for multi-resolution image fusion is applied in the fusion process. The detection of the iris image is based on Adaboost algorithm and then local binary pattern (LBP) histogram is then applied to texture classification with the weighting scheme. Experiment showed that the generated features from the proposed fusion algorithm can improve the performance for verification system through iris recognition.

Keywords: image fusion, iris recognition, local binary pattern, wavelet

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Authors: Sadia Nasrin Tisha, Mushfika Sharmin Rahman, Javier Orduz

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Machine learning is applied in a variety of fields throughout the world. The healthcare sector has benefited enormously from it. One of the most effective approaches for predicting human heart diseases is to use machine learning applications to classify data and predict the outcome as a classification. However, with the rapid advancement of quantum technology, quantum computing has emerged as a potential game-changer for many applications. Quantum algorithms have the potential to execute substantially faster than their classical equivalents, which can lead to significant improvements in computational performance and efficiency. In this study, we applied quantum machine learning concepts to predict coronary heart diseases from text data. We experimented thrice with three different features; and three feature sets. The data set consisted of 100 data points. We pursue to do a comparative analysis of the two approaches, highlighting the potential benefits of quantum machine learning for predicting heart diseases.

Keywords: quantum machine learning, SVM, QSVM, matrix product state

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Authors: Gaurav Malik, Satyendra Mourya, Jyoti Jaiswal, Ramesh Chandra

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The attractive and multifunctional properties of ZnO make it a promising material for the fabrication of highly sensitive and selective efficient gas sensors at room temperature. This presented article focuses on the development of highly selective and sensitive H₂ gas sensor based on the Pd-Pt decorated ZnO framework and its sensing mechanisms. The gas sensing performance of sputter made Pd-Pt/ZnO electrode on anodized porous silicon (PSi) substrate toward H₂ gas is studied under low detection limit (2–500 ppm) of H₂ in the air. The chemiresistive sensor demonstrated sublimate selectivity, good sensing response, and fast response/recovery time with excellent stability towards H₂ at low temperature operation under ambient environment. The elaborate selective measurement of Pd-Pt/ZnO/PSi structure was performed towards different oxidizing and reducing gases. This structure exhibited advance and reversible response to H₂ gas, which revealed that the acquired architecture with ZnO framework is a promising candidate for H₂ gas sensor.

Keywords: sputtering, porous silicon, ZnO framework, XPS spectra, gas sensor

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Authors: Vignesh Ratnaraj, Daniel Marascia, Kelly Ruecker

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Purpose: Pulmonary embolism (PE) is a major cause of morbidity and mortality in trauma patients. Data suggests PE is occurring earlier in trauma patients, with attention being turned to possible de novo events. Here, we examine the incidence of early PE at a level 1 trauma center and examine the relationship with a chest injury. Method: A retrospective analysis was performed from a prospective trauma registry at a level 1 trauma center. All patients admitted from 1 January 2010 to 30 June 2019 diagnosed with PE following trauma were included. Early PE was considered a diagnosis within 72 hours of admission. The severity of the chest injury was determined by the Abbreviated Injury Score (AIS). Analysis of severe chest injury and incidence of early PE was performed using chi-square analysis. Sub-analysis on the timing of PE and PE location was also performed using chi-square analysis. Results: Chest injury was present in 125 of 184 patients diagnosed with PE. Early PE occurred in 28% (n=35) of patients with a chest injury, including 24.39% (n=10) with a severe chest injury. Neither chest injury nor severe chest injury determined the presence of early PE (p= > 0.05). Sub-analysis showed a trend toward central clots in early PE (37.14%, n=13) compared to late (27.78%, n=25); however, this was not found to be significant (p= > 0.05). Conclusion: PE occurs early in trauma patients, with almost one-third being diagnosed before 72 hours. This analysis does not support the paradigm that chest injury, nor severe chest injury, results in statistically significant higher rates of early PE. Interestingly, a trend toward early central PE was noted in those suffering chest trauma.

Keywords: trauma, PE, chest injury, anticoagulation

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Authors: Sakshi Yadav, Sushila Shekhawat

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This study addresses different types of points of view as seen in nature documentary films with the help of three eco documentaries, and it would be significant in understanding the role of the narrative point of view as a tool for showing and telling in documentaries. Narrative analysis of a film forms an essential aspect of the discourse of scholarship in film studies. Narration is the chain of events occurring in time and space. The notion of narrative provides the idea of coherence and wholeness to the story. There are various components that the narration carries, one of which is the perspective or point of view. The narrator plays the role of a mediator between the film and the audience; thus, his perspective influences the way the audience interprets the film. Feature films have been analyzed through narrative points of view; however, this research intends to conduct it from the angle of a nature documentary film. The study will examine narrative viewpoints unique to nature documentary films using three ecological documentary films-The Cove (2009), Tale of a forest (2012), and Before the flood (2016). This research will apply the framework of narrative theory and will investigate the impact of the different types of narrative points of view, as each portrays the human-nature relationship from a different standpoint, and it will also study the effect that the narrative point of view has on the mode of these eco documentaries.

Keywords: ecodocumentary, narrative, human-nature relationship, point of view

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Authors: Aaron J. Small, Craig A. Fletcher

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This study investigates the effect of closed circuit television (CCTV) image patch layout on performance of a simulated train-platform departure task. The within-subjects experimental design measures target detection rate and response latency during a CCTV visual search task conducted as part of the procedure for safe train dispatch. Three interface designs were developed by manipulating CCTV image patch layout. Eye movements, perceived workload and system usability were measured across experimental conditions. Task performance was compared to identify significant differences between conditions. The results of this study have not been determined.

Keywords: rail human factors, workload, closed circuit television, platform departure, attention, information processing, interface design

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Authors: Jihad S. Daba, J. P. Dubois

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Understanding the statistics of non-isotropic scattering multipath channels that fade randomly with respect to time, frequency, and space in a mobile environment is very crucial for the accurate detection of received signals in wireless and cellular communication systems. In this paper, we derive stochastic models for the probability density function (PDF) of the shift in the carrier frequency caused by the Doppler Effect on the received illuminating signal in the presence of a dominant line of sight. Our derivation is based on a generalized Clarke’s and a two-wave partially developed scattering models, where the statistical distribution of the frequency shift is shown to be consistent with the power spectral density of the Doppler shifted signal.

Keywords: Doppler shift, filtered Poisson process, generalized Clark’s model, non-isotropic scattering, partially developed scattering, Rician distribution

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Authors: Jiwan Kumar, Pooja, Sandeep Negi, Anjum Rouf, Amit Kumar, Naveen Lakra

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In modern times where, health issues are increasing day by day, breast cancer is also one of them, which is very crucial and really important to find in the early stages. Doctors can use this model in order to tell their patients whether a cancer is not harmful (benign) or harmful (malignant). We have used the knowledge of machine learning in order to produce the model. we have used algorithms like Logistic Regression, Random forest, support Vector Classifier, Bayesian Network and Radial Basis Function. We tried to use the data of crucial parts and show them the results in pictures in order to make it easier for doctors. By doing this, we're making ML better at finding breast cancer, which can lead to saving more lives and better health care.

Keywords: Bayesian network, radial basis function, ensemble learning, understandable, data making better, random forest, logistic regression, breast cancer

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Authors: Bing Li, Tong Lu, Lei Qiang

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Stoneley waves are interface waves that propagate at the interface between two solid media. In this study, the dispersion characteristics and wave structures of Stoneley waves in elastic multilayered plates are displayed and investigated. With a perspective of bulk wave, a reasonable assumption of the potential function forms of the expansion wave and shear wave in nth layer medium is adopted, and the characteristic equation of Stoneley waves in a three-layered plate is given in a determinant form. The dispersion curves and wave structures are solved and presented in both numerical and simulation results. It is observed that two Stoneley wave modes exist in a three-layered plate, that conspicuous dispersion occurs on low frequency band, that the velocity of each Stoneley wave mode approaches the corresponding Stoneley wave velocity at interface between two half infinite spaces. The wave structures reveal that the in-plane displacement of Stoneley waves are relatively high at interfaces, which shows great potential for interface defects detection.

Keywords: characteristic equation, interface waves, potential function, Stoneley waves, wave structure

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Authors: Abderrhamane Jarou, Dominique Sauter, Christophe Aubrun

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Over the past decade, the growing demand for energy efficiency in buildings has attracted the attention of the control community. Failures in HVAC (heating, ventilation and air conditioning) systems in buildings can have a significant impact on the desired and expected energy performance of buildings and on the user's comfort as well. FTC is a recent technology area that studies the adaptation of control algorithms to faulty operating conditions of a system. The application of Fault-Tolerant Control (FTC) in HVAC systems has gained attention in the last two decades. The objective is to maintain the variations in system performance due to faults within an acceptable range with respect to the desired nominal behavior. This paper considers the so-called active approach, which is based on fault and identification scheme combined with a control reconfiguration algorithm that consists in determining a new set of control parameters so that the reconfigured performance is "as close as possible, "in some sense, to the nominal performance. Thermal models of buildings and their HVAC systems are described by non-linear (usually bi-linear) equations. Most of the works carried out so far in FDI (fault diagnosis and isolation) or FTC consider a linearized model of the studied system. However, this model is only valid in a reduced range of variation. This study presents a new fault diagnosis (FD) algorithm based on a bilinear observer for the detection and accurate estimation of the magnitude of the HVAC system failure. The main contribution of the proposed FD algorithm is that instead of using specific linearized models, the algorithm inherits the structure of the actual bilinear model of the building thermal dynamics. As an immediate consequence, the algorithm is applicable to a wide range of unpredictable operating conditions, i.e., weather dynamics, outdoor air temperature, zone occupancy profile. A bilinear fault detection observer is proposed for a bilinear system with unknown inputs. The residual vector in the observer design is decoupled from the unknown inputs and, under certain conditions, is made sensitive to all faults. Sufficient conditions are given for the existence of the observer and results are given for the explicit computation of observer design matrices. Dedicated observer schemes (DOS) are considered for sensor FDI while unknown input bilinear observers are considered for actuator or system components FDI. The proposed strategy for FTC works as follows: At a first level, FDI algorithms are implemented, making it also possible to estimate the magnitude of the fault. Once the fault is detected, the fault estimation is then used to feed the second level and reconfigure the control low so that that expected performances are recovered. This paper is organized as follows. A general structure for fault-tolerant control of buildings is first presented and the building model under consideration is introduced. Then, the observer-based design for Fault Diagnosis of bilinear systems is studied. The FTC approach is developed in Section IV. Finally, a simulation example is given in Section V to illustrate the proposed method.

Keywords: bilinear systems, fault diagnosis, fault-tolerant control, multi-zones building

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Authors: Francesco Morgan Bono, Simone Cinquemani

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This research aims to enhance bridge monitoring by employing innovative techniques that incorporate exogenous factors into the modeling of sensor signals, thereby improving long-term predictability beyond traditional static methods. Using real datasets from two different bridges equipped with Linear Variable Displacement Transducer (LVDT) sensors, the study investigates the fundamental principles governing sensor behavior for more precise long-term forecasts. Additionally, the research evaluates performance on noisy and synthetically damaged data, proposing a residual-based alarm system to detect anomalies in the bridge. In summary, this novel approach combines advanced modeling, exogenous factors, and anomaly detection to extend prediction horizons and improve preemptive damage recognition, significantly advancing structural health monitoring practices.

Keywords: structural health monitoring, dynamic models, sindy, railway bridges

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Authors: Saad Alkentar, Abdulkareem Assalem

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Recognizing small targets has always posed a significant challenge in image analysis. Over long distances, the image signal-to-noise ratio tends to be low, limiting the amount of useful information available to detection systems. Consequently, visual target recognition becomes an intricate task to tackle. In this study, we introduce a Track Before Detect (TBD) approach that leverages target trajectory information (coordinates) to effectively distinguish between noise and potential targets. By reframing the problem as a multivariate time series classification, we have achieved remarkable results. Specifically, our TBD method achieves an impressive 97% accuracy in separating target signals from noise within a mere half-second time span (consisting of 10 data points). Furthermore, when classifying the identified targets into our predefined categories—airplane, drone, and bird—we achieve an outstanding classification accuracy of 96% over a more extended period of 1.5 seconds (comprising 30 data points).

Keywords: small targets, drones, trajectory information, TBD, multivariate time series

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Authors: Sang Hun Park, Chul Gyu Song

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Artery and vein occlusion changes observed in patients and experimental animals are unexplainable symptoms. As the fat accumulated in cardiovascular ruptures, it causes vascular blocking. Likewise, early detection of cardiovascular disease can be useful for treatment. In this study, we used the mouse femoral occlusion model to observe the arterial and venous occlusion changes without darkroom. We observed the femoral arterial flow pattern changes by proposed fluorescent imaging system using an animal model of thrombosis. We adjusted the near-infrared light source current in order to control the intensity of the fluorescent substance light. We got the clear fluorescent images and femoral artery flow pattern were measured by a 5-minute interval. The result showed that the fluorescent substance flowing in the femoral arteries were accumulated in thrombus as time passed, and the fluorescence of other vessels gradually decreased.

Keywords: thrombus, fluorescence, femoral, arteries

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Authors: Steven D. P. Moore

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An electrical discharge in the air induces an electromagnetic (EM) wave capable of wireless transfer, reception, and conversion back into electrical discharge at a distant location. Following Norton’s ground wave principles, EM wave radiation (EMR) runs parallel to the Earth’s surface. Energy in an EMR wave can move through the air and be focused to create a spark at a distant location, focused by a receiver to generate a local electrical discharge. This local discharge can be amplified and stored but also has the propensity to initiate another EMR wave. In addition to typical EM waves, lightning is also associated with atmospheric events, trans-ionospheric pulse pairs, the most powerful natural EMR signal on the planet. With each lightning strike, regardless of global position, it generates naturally occurring pulse-pairs that are emitted towards space within a narrow cone. An EMR wave can self-propagate, travel at the speed of light, and, if polarized, contain vector properties. If this reflective pulse could be directed by design through structures that have increased probabilities for lighting strikes, it could theoretically travel near the surface of the Earth at light speed towards a selected receiver for local transformation into electrical energy. Through research, there are several influencing parameters that could be modified to model, test, and increase the potential for adopting this technology towards the goal of developing a global grid that utilizes natural sources of energy.

Keywords: electricity, sparkgap, wireless, electromagnetic

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Authors: Ivana Loncarevic, Biljana Pajin, Ivana Vasiljevic, Milana Lazovic, Danica Mrkajic, Aleksandar Fises, Strahinja Kovacevic

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Biscuits belong to a group of flour-confectionery products that are considerably consumed worldwide. The basic raw material for their production is wheat flour or integral flour as a nutritionally highly valuable component. However, this raw material is also a potential source of contamination since it may contain the residues of biochemical compounds originating from plant and soil protection agents. Therefore, it is necessary to examine the health safety of both raw materials and final products. The aim of this research was to examine the content of undesirable residues of pesticides (mostly organochlorine pesticides, organophosphorus pesticides, carbamate pesticides, triazine pesticides, and pyrethroid pesticides) in 30 different biscuit samples of domestic origin present on the Vojvodina market using Gas Chromatograph Thermo ISQ/Trace 1300. The results showed that all tested samples had the limit of detection of pesticide content below 0.01 mg/kg, indicating that this type of confectionary products is not contaminated with pesticides.

Keywords: biscuits, pesticides, contamination, quality

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Authors: Maamar Ali Saud Al Tobi, Geraint Bevan, K. P. Ramachandran, Peter Wallace, David Harrison

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Centrifugal pumps are complex machines which can experience different types of fault. Condition monitoring can be used in centrifugal pump fault detection through vibration analysis for mechanical and hydraulic forces. Vibration analysis methods have the potential to be combined with artificial intelligence systems where an automatic diagnostic method can be approached. An automatic fault diagnosis approach could be a good option to minimize human error and to provide a precise machine fault classification. This work aims to introduce an approach to centrifugal pump fault diagnosis based on artificial intelligence and genetic algorithm systems. An overview of the future works, research methodology and proposed experimental setup is presented and discussed. The expected results and outcomes based on the experimental work are illustrated.

Keywords: centrifugal pump setup, vibration analysis, artificial intelligence, genetic algorithm

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Authors: Xiaohui Wang, Zhichuan Guan, Roman Shor, Chuanbin Xu

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Early monitoring and real-time quantitative description of gas intrusion under the premise of ensuring the integrity of the drilling fluid circulation system will greatly improve the accuracy and effectiveness of deepwater gas-kick monitoring. Therefore, in order to study the propagation characteristics of ultrasonic waves in the gas-liquid two-phase flow within the marine riser, in this paper, a numerical simulation method of ultrasonic propagation in the annulus of the riser was established, and the credibility of the numerical analysis was verified by the experimental results of the established gas intrusion monitoring simulation experimental device. The numerical simulation can solve the sound field in the gas-liquid two-phase flow according to different physical models, and it is easier to realize the single factor control. The influence of each parameter on the received signal can be quantitatively investigated, and the law with practical guiding significance can be obtained.

Keywords: gas-kick detection, ultrasonic, void fraction, coda wave velocity

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Authors: Ankur P. Sati, Manju Mohan

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The hazardous combination of smoke and pollutant gases, smog, is harmful for health. There are strong evidences that the Agricultural waste burning (AWB) in the Northern India leads to adverse air quality in Delhi and its surrounding regions. A severe smog episode was observed over Delhi, India during November 2012 which resulted in very low visibility and various respiratory problems. Very high values of pollutants (PM10 as high as 989 µg m-3, PM2.5 as high as 585 µg m-3 an NO2 as high as 540 µg m-3) were measured all over Delhi during the smog episode. Ultra Violet Aerosol Index (UVAI) from Aura satellite and Aerosol Optical Depth (AOD) are used in the present study along with the output trajectories from HYSPLIT model and the in-situ data. Satellite data also reveal that AOD, UVAI are always at its highest during the farmfires duration in Punjab region of India and the extent of these farmfires may be increasing. It is observed that during the smog episode all the AOD, UVAI, PM2.5 and PM10 values surpassed those of the Diwali period (one of the most polluted events in the city) by a considerable amount at all stations across Delhi. The parameters used from the remote sensing data and the ground based observations at various stations across Delhi are very well in agreement about the intensity of Smog episode. The analysis clearly shows that regional pollution can have greater contributions in deteriorating the air quality than the local under adverse meteorological conditions.

Keywords: smog, farmfires, AOD, remote sensing

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Authors: Hailyie Tekleselase

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Deep learning is increasingly used as a building block of security systems. However, neural networks are hard to interpret and typically solid to the practitioner. This paper presents a detail survey of computing methods in cyber security, and analyzes the prospects of enhancing the cyber security capabilities by suggests that of accelerating the intelligence of the security systems. There are many AI-based applications used in industrial scenarios such as Internet of Things (IoT), smart grids, and edge computing. Machine learning technologies require a training process which introduces the protection problems in the training data and algorithms. We present machine learning techniques currently applied to the detection of intrusion, malware, and spam. Our conclusions are based on an extensive review of the literature as well as on experiments performed on real enterprise systems and network traffic. We conclude that problems can be solved successfully only when methods of artificial intelligence are being used besides human experts or operators.

Keywords: artificial intelligence, machine learning, deep learning, cyber security, big data

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Authors: José Eugenio Ortiz, Pierre Plaza, Josefa Herrero, Iván Cabria, José Luis Blanco, Javier Gavilanes, José Ignacio Escavy, Ignacio López-Cilla, Virginia Yagüe, César Pérez, Silvia Rodríguez, Jorge Rico, Cecilia Serrano, Jesús Bernat

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The development of Artificial Intelligence services in mining processes, specifically in aggregate quarries, is facilitating automation and improving numerous aspects of operations. Ultimately, AI is transforming the mining industry by improving efficiency, safety and sustainability. With the ability to analyze large amounts of data and make autonomous decisions, AI offers great opportunities to optimize mining operations and maximize the economic and social benefits of this vital industry. Within the framework of the European DIGIECOQUARRY project, various services were developed for the identification of material quality, production estimation, detection of anomalies and prediction of consumption and production automatically with good results.

Keywords: aggregates, artificial intelligence, automatization, mining operations

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Authors: Athdath Waduge Susantha Janaka Kumara, Xiefei Zhi, Zin Mie Mie Sein

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Understanding the air temperature variability is crucially important for disaster risk reduction and management. In this study, we used 15 synoptic meteorological stations to assess the spatiotemporal variability of air temperature over Sri Lanka during 1972–2021. The empirical orthogonal function (EOF), Principal component analysis (PCA), Mann-Kendall test, power spectrum analysis and correlation coefficient analysis were used to investigate the long-term trends of air temperature and their possible relation to sea surface temperature (SST) over the region. The results indicate that an increasing trend in air temperature was observed with the abrupt climate change noted in the year 1994. The spatial distribution of EOF1 (63.5%) shows the positive and negative loading dipole patterns from south to northeast, while EOF2 (23.4%) explains warmer (colder) in some parts of central (south and east) areas. The power spectrum of PC1 (PC2) indicates that there is a significant period of 3-4 years (quasi-2 years). Moreover, Indian Ocean Dipole (IOD) provides a strong positive correlation with the air temperature of Sri Lanka, while the EL Nino Southern Oscillation (ENSO) presents a weak negative correlation. Therefore, IOD events led to higher temperatures in the region. This study’s findings can help disaster risk reduction and management in the country.

Keywords: air temperature, interannaul variability, ENSO, IOD

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Authors: Ripon Sarkar, Kabita Chaterjee, Ananya Barui

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Smoking is one of the leading causes of oral cancer. Cigarette smoke affects various cellular parameters and alters molecular metabolism of cells. Epithelial cells losses their cytoskeleton structure, membrane integrity, cellular polarity that subsequently initiates the process of epithelial cells to mesenchymal transition due to long exposure of cigarette smoking. It changes the normal cellular metabolic activity which induces oxidative stress and enhances the reactive oxygen spices (ROS) formation. Excessive ROS and associated oxidative stress are considered to be a driving force in alteration in cellular phenotypes, polarity distribution and mitochondrial metabolism. Noninvasive assessment of such parameters plays essential role in development of routine screening system for early diagnosis of oral cancer. Electrical cell-substrate impedance sensing (ECIS) is one of such method applied for detection of cellular membrane impedance which can be correlated to cell membrane integrity. Present study intends to explore the alteration in cellular impedance along with the expression of cellular polarity molecules and cytoskeleton distributions in oral epithelial cells of habitual smokers and to correlate the outcome to that of clinically diagnosed oral leukoplakia and oral squamous cell carcinoma patients. Total 80 subjects were categorized into four study groups: nonsmoker (NS), cigarette smoker (CS), oral leukoplakia (OLPK) and oral squamous cell carcinoma (OSCC). Cytoskeleton distribution was analyzed by staining of actin filament and generation of ROS was measured using assay kit using standard protocol. Cell impedance was measured through ECIS method at different frequencies. Expression of E-cadherin and protease-activated receptor (PAR) proteins were observed through immune-fluorescence method. Distribution of actin filament is well organized in NS group however; distribution pattern was grossly varied in CS, OLPK and OSCC. Generation of ROS was low in NS which subsequently increased towards OSCC. Expressions of E-cadherin and change in cellular electrical impedance in different study groups indicated the hallmark of cancer progression from NS to OSCC. Expressions of E-cadherin, PAR protein, and cell impedance were decreased from NS to CS and farther OSCC. Generally, the oral epithelial cells exhibit apico-basal polarity however with cancer progression these cells lose their characteristic polarity distribution. In this study expression of polarity molecule and ECIS observation indicates such altered pattern of polarity among smoker group. Overall the present study monitored the alterations in intracellular ROS generation and cell metabolic function, membrane integrity in oral epithelial cells in cigarette smokers. Present study thus has clinical significance, and it may help in developing a noninvasive technique for early diagnosis of oral cancer amongst susceptible individuals.

Keywords: cigarette smoking, early oral cancer detection, electric cell-substrate impedance sensing, noninvasive screening

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Authors: Syed Mahbubuz Zaman, A. B. M. Abrar Haque, Mehedi Hassan Nayeem, Misbah Uddin Sagor

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Everyday e-mails are being used by millions of people as an effective form of communication over the Internet. Although e-mails allow high-speed communication, there is a constant threat known as spam. Spam e-mail is often called junk e-mails which are unsolicited and sent in bulk. These unsolicited emails cause security concerns among internet users because they are being exposed to inappropriate content. There is no guaranteed way to stop spammers who use static filters as they are bypassed very easily. In this paper, a smart system is proposed that will be using neural networks to approach spam in a different way, and meanwhile, this will also detect the most relevant features that will help to design the spam filter. Also, a comparison of different parameters for different neural network models has been shown to determine which model works best within suitable parameters.

Keywords: long short-term memory, bidirectional long short-term memory, gated recurrent unit, natural language processing, natural language processing

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Authors: R. Gadea, J. M. Monzó, F. J. Puertas, M. Castro, A. Tebar, P. J. Fito, R. J. Colom

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There exists a wide array of ailments impacting the structural soundness of the esophageal walls, predominantly linked to digestive issues. Presently, the techniques employed for identifying esophageal tract complications are excessively invasive and discomforting, subjecting patients to prolonged discomfort in order to achieve an accurate diagnosis. This study proposes the creation of a sensor with profound measuring capabilities designed to detect fluids coursing through the esophageal tract. The multi-sensor detection system relies on radiofrequency photospectrometry. During experimentation, individuals representing diverse demographics in terms of gender and age were utilized, positioning the sensors amidst the trachea and diaphragm and assessing measurements in vacuum conditions, water, orange juice, and saline solutions. The findings garnered enabled the identification of various liquid mediums within the esophagus, segregating them based on their ionic composition.

Keywords: radiofrequency spectrophotometry, medical device, gastroesophageal disease, photonics

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Authors: Musarat Ishaq, Tara Karnezis, Ramin Shayan

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Lipedema, a poorly understood chronic disease of adipose hyper-deposition, is often mistaken for obesity and causes significant impairment to mobility and quality-of-life. To identify molecular mechanisms underpinning lipedema, we employed comprehensive omics-based comparative analyses of whole tissue, adipocyte precursors (adipose-derived stem cells (ADSCs)), and adipocytes from patients with or without lipedema. Transcriptional profiling revealed significant differences in lipedema tissue, adipocytes, and ADSCs, with altered levels of mRNAs involved inproliferation and cell adhesion. One highly up-regulated gene in lipedema adipose tissue, adipocytes and ADSCs, ZIC4, encodes Zinc Finger Protein ZIC 4, a class of transcription factor which may be involved in regulating metabolism and adipogenesis. ZIC4 inhibition impaired the adipogenesis of ADSCs into mature adipocytes. Epigenetic regulation study revealed overexpression of ZIC4 is involved in decreased promoter DNA methylation and subsequent decrease in adipogenesis. These epigenetic modifications can alter adipocytes microenvironment and adipocytes differentiation. Our study show that epigenetic events regulate the ability of ADSCs to commit and differentiate into mature adipocytes by modulating ZIC4.

Keywords: lipedema, adipose-derived stem cells, adipose tisue, adipocytes, zinc finger protein, epigenetic

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Authors: Faouzi Ameur, Atef Belhaj Ali

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Located in the South-west of Saudi Arabia, Jeddah is more than a harbor. It is a big city of the Red Sea and the second town of Saudi Arabia, after Riyadh the capital. Jeddah profits from several economic assets due especially to its transit position towards the high sacred places of Islam like Mecca and Medina. During summer, this metropolis is transformed into a political capital and a tourist resort for foreigners and Saudis alike. The city of Jeddah was affected by serious sudden floods; two great ones took place in 2009, and in 2011. The human and material tools were considerable, since these events caused the death to hundreds of people, damaged thousands of buildings built on basins slopes, which, however had the authorizations necessary. To cope with these natural disasters, several urban hydraulic measures were undertaken like building dams and canals to collect surface waters. These urban measures aimed at the protection of inhabitants and belongings against the risks of floods as well as the interception and the drainage of streams. Although these protection measures are important, expensive, and effective, they are no longer enough or effective to cope with the evolution of the natural disasters that the city of Jeddah is constantly exposed to. These protective hydraulic measures did not make it possible to reach risk zero situations. They transferred the damages towards other zones. This paper purports to study the protection network systems in Jeddah and to understand their various impacts during floods on the city and on its inhabitants.

Keywords: Jeddah, Saudi Arabia, urbanization, hydraulic protection

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Authors: Balachandra Kumaraswamy, P. G. Poonacha

Abstract:

Automatic Music Information Retrieval has been one of the challenging topics of research for a few decades now with several interesting approaches reported in the literature. In this paper we have developed a pitch extraction method based on a finite Fourier series approximation to the given window of samples. We then estimate pitch as the fundamental period of the finite Fourier series approximation to the given window of samples. This method uses analysis of the strength of harmonics present in the signal to reduce octave as well as harmonic errors. The performance of our method is compared with three best known methods for pitch extraction, namely, Yin, Windowed Special Normalization of the Auto-Correlation Function and Harmonic Product Spectrum methods of pitch extraction. Our study with artificially created signals as well as music files show that Fourier Approximation method gives much better estimate of pitch with less octave and harmonic errors.

Keywords: pitch, fourier series, yin, normalization of the auto- correlation function, harmonic product, mean square error

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Authors: Kathryn Norgang, Sarah Howrath, Auni Idi Muhire, Pacifique Umubyeyi

Abstract:

Description : A group of nurses address the shortage of trained staff to respond to critical patients at Rwanda Military Hospital (RMH) by developing a training program and a resuscitation response team. Members of the group who received the training when it first launched are now trainer of trainers; all components of the training program are organized and delivered by RMH staff-the clinical mentor only provides adjunct support. This two day training is held quarterly at RMH; basic life support and exposure to interventions for advanced care are included in the test and skills sign off. Seventy staff members have received the training this year alone. An increased number of admission/transfer to ICU due to successful resuscitation attempts is noted. Lessons learned: -Number of staff trained 2012-2014 (to be verified). -Staff who train together practice with greater collaboration during actual resuscitation events. -Staff more likely to initiate BLS if peer support is present-more staff trained equals more support. -More access to Advanced Cardiac Life Support training is necessary now that the cadre of BLS trained staff is growing. Conclusions: Increased access to training, peer support, and collaborative practice are effective strategies to strengthening resuscitation capacity within a hospital.

Keywords: resuscitation, basic life support, capacity building, resuscitation response teams, nurse trainer of trainers

Procedia PDF Downloads 284