Search results for: mobility features

Authors: Azita Ramezani, Ghazal Mashhadiagha, Bahareh Sanabakhsh

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This study researches the combination of Random. Forest classifiers with large language models (LLMs) and natural language processing (NLP) to improve diagnostic accuracy in chest X-ray analysis using the Indiana University dataset. Utilizing advanced NLP techniques, the research preprocesses textual data from radiological reports to extract key features, which are then merged with image-derived data. This improved dataset is analyzed with Random Forest classifiers to predict specific clinical results, focusing on the identification of health issues and the estimation of case urgency. The findings reveal that the combination of NLP, LLMs, and machine learning not only increases diagnostic precision but also reliability, especially in quickly identifying critical conditions. Achieving an accuracy of 99.35%, the model shows significant advancements over conventional diagnostic techniques. The results emphasize the large potential of machine learning in medical imaging, suggesting that these technologies could greatly enhance clinician judgment and patient outcomes by offering quicker and more precise diagnostic approximations.

Keywords: natural language processing (NLP), large language models (LLMs), random forest classifier, chest x-ray analysis, medical imaging, diagnostic accuracy, indiana university dataset, machine learning in healthcare, predictive modeling, clinical decision support systems

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Authors: Shimaa A. Higazy, Olfat E. El-Azabawy, Ahmed M. Al-Sabagh, Notaila M. Nasser, Eman A. Khamis

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In this work, two novel Schiff base polymers (PSB1 and PSB₂) with extra-high protective barrier features were facilely prepared via Polycondensation reactions. They were applied for the first time as effective corrosion inhibitors in the sour corrosive media of petroleum environments containing hydrogen sulfide (H₂S) gas. For studying the polymers' inhibitive action on the carbon steel, numerous corrosion testing methods including potentiodynamic polarization (PDP), open circuit potential, and electrochemical impedance spectroscopy (EIS) have been employed at various temperatures (298-328 K) in the oil wells formation water with H₂S concentrations of 100, 400, and 700 ppm as aggressive media. The activation energy (Ea) and other thermodynamic parameters were computed to describe the mechanism of adsorption. The corrosion morphological traits and steel samples' surfaces composition were analyzed by field emission scanning electron microscope and energy dispersive X-ray analysis. The PSB2 inhibited sour corrosion more effectively than PSB1 when subjected to electrochemical testing. The 100 ppm concentration of PSB2 exhibited 82.18 % and 81.14 % inhibition efficiencies at 298 K in PDP and EIS measurements, respectively. While at 328 K, the inhibition efficiencies were 61.85 % and 67.4 % at the same dosage and measurements. These poly Schiff bases exhibited fascinating performance as corrosion inhibitors in sour environment. They provide a great corrosion inhibition platform for the sustainable future environment.

Keywords: schiff base polymers, corrosion inhibitors, sour corrosive media, potentiodynamic polarization, H₂S concentrations

Procedia PDF Downloads 101

Authors: Jamie R. Chua, Christina Irene D. Mejia, Regina P. Berba

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Disseminated tuberculosis is an infectious disease caused by Mycobacterium tuberculosis involving two or more non-contiguous sites identified through bacteriologic confirmation or clinical diagnosis. Over the five year period included in the study, the UP-PGH TB DOTS clinic had total of 3,967 referrals, and the prevalence of disseminated tuberculosis is 1% (68/3967). The mean age was 33.9 years (range 19-64 years) with a male: female ratio of 1:1. 67% (52 patients) had no predisposing comorbid illness or immune disorder. The most common presenting symptoms were abdominal pain (19%), back pain (13%), abdominal enlargement (11%) and mass (10.2%). Anemia, leukocytosis, hypoalbuminemia, and high-normal serum calcium were common biochemical and hematologic findings. Around 36% (25) of patients were diagnosed clinically with disseminated tuberculosis despite lacking bacteriologic evidence of multi-organ involvement. The lungs (86%) is still the most commonly involved site, followed by intestinal (22%), vertebral/Pott’s (27%), and pelvic/genital (19%). The mean time from presentation to initiation of therapy was 22 days (SD 32.7). Only 18 patients (29.3%) were properly recorded to have been referred to local TB DOTs facilities. Of the 68 patients, only 16% (11 patients) continued follow-up at PGH, and all had documented treatment completion. Treatment outcomes of the remaining were unknown. Due to the variety of involved sites, a high index of suspicion is required. Knowledge on clinical features, common radiographic findings, and histopathologic characteristics of disseminated TB is important as bacteriologic evidence of infection is not always apparent.

Keywords: disseminated tuberculosis, Mycobacterium tuberculosis, miliary tuberculosis, tuberculosis

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Authors: Rajkumar Ghosh, Bhabani Prasad Mukhopadhay

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Groundwater contamination with fluoride has emerged as a global concern affecting millions of people, leading to the widespread occurrence of fluorosis. It affects bones and teeth, leading to dental and skeletal fluorosis. This study presents a comprehensive analysis of the relationship between groundwater contamination and fluorosis. It delves into the causes of fluoride contamination in groundwater, its spatial distribution, and adverse health impacts of fluorosis on affected communities. Fluoride contamination in groundwater can be attributed to both natural and anthropogenic sources. Geogenic sources involve the dissolution of fluoride-rich minerals present in the aquifer materials. On the other hand, anthropogenic activities such as industrial discharges, agricultural practices, and improper disposal of fluoride-containing waste contribute to the contamination of groundwater. The spatial distribution of fluoride contamination varies widely across different regions and geological formations. High fluoride levels are commonly observed in areas with fluorine-rich geological deposits. Additionally, agricultural and industrial centres often exhibit elevated fluoride concentrations due to anthropogenic contributions. Excessive fluoride ingestion during tooth development leads to dental fluorosis, characterized by enamel defects, discoloration, and dental caries. The severity of dental fluorosis varies based on fluoride exposure levels during tooth development. Long-term consumption of fluoride-contaminated water causes skeletal fluorosis, resulting in bone and joint pain, decreased joint mobility, and skeletal deformities. In severe cases, skeletal fluorosis can lead to disability and reduced quality of life. Various defluoridation techniques such as activated alumina, bone char, and reverse osmosis have been employed to reduce fluoride concentrations in drinking water. These methods effectively remove fluoride, but their implementation requires careful consideration of cost, maintenance, and sustainability. Diversifying water sources, such as rainwater harvesting and surface water supply, can reduce the reliance on fluoride-contaminated groundwater, especially in regions with high fluoride concentrations. Groundwater contamination with fluoride remains a significant public health challenge, leading to the widespread occurrence of fluorosis globally. This scientific report emphasizes the importance of understanding the relationship between groundwater contamination and fluorosis. Implementing effective mitigation strategies and preventive measures is crucial to combat fluorosis and ensure sustainable access to safe drinking water for communities worldwide. Collaborative efforts between government agencies, local communities, and scientific researchers are essential to address this issue and safeguard the health of vulnerable populations. Additionally, the report explores various mitigation strategies and preventive measures to address the issue and offers recommendations for sustainable management of groundwater resources to combat fluorosis effectively.

Keywords: fluorosis, fluoride contamination, groundwater contamination, groundwater resources

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Authors: Mi-Hyang Lee, Seung-Hoon Han

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Korean traditional residences have been built with deep design issues for various values such as social, cultural, and environmental influences to be started from a few thousand years ago, but its meaning is being vanished due to the different lifestyles these days. It is necessary, therefore, to grasp the meaning of the Korea traditional building called Hanok and to get Korean people understand its real advantages. The purpose of this study is to propose a standardization methodology for evaluating comfort features towards Korean traditional houses. This paper is also trying to build an official standard evaluation system and to integrate aesthetic and psychological values induced from Hanok. Its comfort performance values could be divided into two large categories that are physical and psychological, and fourteen methods have been defined as the Korean Standards (KS). For this research, field survey data from representative Hanok types were collected for each method. This study also contains a qualitative in-depth analysis of the Hanok comfort index by the professions using AHP (Analytical Hierarchy Process) and has examined the effect of the methods. As a result, this paper could define what methods can provide trustful outcomes and how to evaluate the own strengths in aspects of spatial comfort of Hanok using suggested procedures towards the spatial configuration of the traditional dwellings. This study has finally proposed an integrated development of a standardization methodology assessing the comfort performance for Korean traditional residences, and it is expected that they could evaluate inhabitants of the residents and interior environmental conditions especially structured by wood materials like Hanok.

Keywords: Hanok, comfort performance, human condition, analytical hierarchy process

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Authors: Ali Kuzu

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There are about 800 thousand chemicals in our environment and the number is increasing more than a thousand every year. While most of these chemicals are used as components in various consumer products, some are faced as industrial waste in the environment. Unfortunately, many of these chemicals are hazardous and affect humans. According to the “International Program on Chemical Safety” of World Health Organization; Among the chronic health effects of chemicals, cancer is of major concern. Many substances have found in recent years to be carcinogenic in one or more species of laboratory animals. Especially with respect to long-term effects, the response to a chemical may vary, quantitatively or qualitatively, in different groups of individuals depending on predisposing conditions, such as nutritional status, disease status, current infection, climatic extremes, and genetic features, sex and age of the individuals. Understanding the response of such specific risk groups is an important area of toxicology research. People with age 65+ is defined as “aged (or elderly)”. The elderly population in the world is about 600 million, which corresponds to ~8 percent of the world population. While every 1 of each 4 people is aged in Japan, the elderly population is quite close to 20 percent in many developed countries. And elderly population in these countries is growing more rapidly than the total population. The negative effects of chemicals on elderly take an important place in health-care related issues in last decades. The aged population is more susceptible to the harmful effects of environmental chemicals. According to the poor health of the organ systems in elderly, the ability of their body to eliminate the harmful effects and chemical substances from their body is also poor. With the increasing life expectancy, more and more people will face problems associated with chemical residues.

Keywords: elderly, chemicals’ effects, aged care, care need

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Authors: Nishant Rodrigues, Nicole Spanedda, Chilukuri K. Mohan, Arindam Chakraborty

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A crucial objective in quantum chemistry is the computation of the energy levels of chemical systems. This task requires electron-repulsion integrals as inputs, and the steep computational cost of evaluating these integrals poses a major numerical challenge in efficient implementation of quantum chemical software. This work presents a moment-based machine-learning approach for the efficient evaluation of electron-repulsion integrals. These integrals were approximated using linear combinations of a small number of moments. Machine learning algorithms were applied to estimate the coefficients in the linear combination. A random forest approach was used to identify promising features using a recursive feature elimination approach, which performed best for learning the sign of each coefficient but not the magnitude. A neural network with two hidden layers were then used to learn the coefficient magnitudes along with an iterative feature masking approach to perform input vector compression, identifying a small subset of orbitals whose coefficients are sufficient for the quantum state energy computation. Finally, a small ensemble of neural networks (with a median rule for decision fusion) was shown to improve results when compared to a single network.

Keywords: quantum energy calculations, atomic orbitals, electron-repulsion integrals, ensemble machine learning, random forests, neural networks, feature extraction

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Authors: Alamrew Eyayu

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Riverine ecosystems are highly exposed to different forms of human activities, and different water features can affect fish distribution in such habitats. Tributaries of the Abbay and Tekeze Basins are supporting all life-requesting activities in Ethiopia. Fisheries of these habitats are also the mainstay of livelihoods. However, brutal human activities are affecting these ecosystems and the fish therein. This study was thus undertaken to examine fish distribution and community structure in relation to water parameters in Ayima, Gelegu and Shinfa Rivers. 2719 fish specimens identified into 43 species were sampled using gillnets, cast nets and electro-fishing on a seasonal campaign. Based on frequency of occurrence (%FO), 5 species fell in the ‘euconstant occurrence’ category or their FO was ≥75%, while many species were in the ‘constant occurrence’ category. Among others, site depth, total phosphorus, dissolved oxygen, and river channel diameter were key environmental factors determining fish community structure. Similarity percentage produced an overall average Bray-Curtis dissimilarity of 60.8% between the fish communities of the three rivers. The final model accounted for 77.2% of the total variance in fish composition, and all canonical axes were significant (Monte Carlo test 499, p =0.002). Generally, this study was conducted in areas where no ecological studies are undertaken, and the results obtained from this study could be important for the sustainable utilization of Ethiopian fisheries.

Keywords: fish biology, fisheries socioeconomics, aquatic biodiversity, fisheries management

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Authors: Syed Amer Mahmood, Rao Mansor Ali Khan

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This study deals with the remote sensing analysis of tectonic deformation and its implications to understand the regional uplift conditions in the lower Jhelum and eastern Potwar. Identification and mapping of active structures is an important issue in order to assess seismic hazards and to understand the Quaternary deformation of the region. Digital elevation models (DEMs) provide an opportunity to quantify land surface geometry in terms of elevation and its derivatives. Tectonic movement along the faults is often reflected by characteristic geomorphological features such as elevation, stream offsets, slope breaks and the contributing drainage area. The river profile analysis in this region using SRTM digital elevation model gives information about the tectonic influence on the local drainage network. The steepness and concavity indices have been calculated by power law of scaling relations under steady state conditions. An uplift rate map is prepared after carefully analysing the local drainage network showing uplift rates in mm/year. The active faults in the region control local drainages and the deflection of stream channels is a further evidence of the recent fault activity. The results show variable relative uplift conditions along MBT and Riasi and represent a wonderful example of the recency of uplift, as well as the influence of active tectonics on the evolution of young orogens.

Keywords: quaternary deformation, SRTM DEM, geomorphometric indices, active tectonics and MBT

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Authors: Nikola Radovanovic, Petros Gkotsis, Mathieu Doussineau

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Aeronautics is regarded as a strategically important sector for European competitiveness. It was at the heart of European entrepreneurial development since the industry was born. Currently, the EU is the world leader in the production of civil aircraft, including helicopters, aircraft engines, parts, and components. It is recording a surplus in trade relating to aerospace products, which are exported all over the globe. Also, this industry shows above-average investments in research and development, as demonstrated in the patent activity in this area. The post-pandemic recovery of the industry will partly depend on the possibilities to streamline collaboration in further research and innovation activities. Aeronautics features as one of the often selected priority domains in smart specialisation, which represents the main regional and national approach in developing and implementing innovation policies in Europe. The basis for the selection of priority domains for smart specialisation lies in the mapping of innovative potential, with research and patent activities being among the key elements of this analysis. This research is aimed at identifying characteristics of the trends in research and patent activities in the regions and countries that base their competitiveness on the aeronautics sector. It is also aimed at determining the scope and patterns of collaborations in aeronautics between innovators from the European regions, focusing on revealing new technology areas that emerge from these collaborations. For this purpose, we developed a methodology based on desk research and the analysis of the PATSTAT patent database as well as the databases of R&I framework programmes.

Keywords: aeronautics, smart specialisation, innovation, research, regional policy

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Authors: Yang Yu, Jian Wang, Jiqiang Liu, Lei Han, Xudong He, Shaohua Lv

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As the increasing network attacks become more and more complex, network situation assessment based on log analysis cannot meet the requirements to ensure network security because of the low quality of logs and alerts. This paper addresses the lack of consideration of security attributes of hosts and attacks in the network. Identity and effectiveness of Distributed Denial of Service (DDoS) are hard to be proved in risk assessment based on alerts and flow matching. This paper proposes a multi-dimension threat situation assessment method based on network security attributes. First, the paper offers an improved Common Vulnerability Scoring System (CVSS) calculation, which includes confident risk, integrity risk, availability risk and a weighted risk. Second, the paper introduces deterioration rate of properties collected by sensors in hosts and network, which aimed at assessing the time and level of DDoS attacks. Third, the paper introduces distribution of asset value in security attributes considering features of attacks and network, which aimed at assessing and show the whole situation. Experiments demonstrate that the approach reflects effectiveness and level of DDoS attacks, and the result can show the primary threat in network and security requirement of network. Through comparison and analysis, the method reflects more in security requirement and security risk situation than traditional methods based on alert and flow analyzing.

Keywords: DDoS evaluation, improved CVSS, network security attribute, threat situation assessment

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Authors: Reza Mehrafarin, Nafiseh Mirshekari, Mahila Mehrafarin

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Sistan is one of the ancient regions of Iran, which is located in the east of this country. 1660 ancient sites were identified in the archeological field surveys that we did in this area. Of these, about 900 sites belong to the Bronze Age, which are located in an area of about 3000 square kilometers. The Bronze Age in Iran began at the end of the fourth millennium BC and ended at the beginning of the second millennium BC. During this period, many cities and villages were established in Sistan, that the burnt city (Shahr-e Sokhta) was its most important center, with an area of about 150 hectares and a population of 5,000. In this article, we have tried to identify and introduce the most important features of the Bronze Age of Sistan, especially the burnt city. Another goal of the article is to identify the factors that led to the emergence of the Bronze Age, especially urbanization in Sistan at the end of the fourth millennium BCand then we want to know what factors caused the destruction of Bronze Age civilization and urbanization in Sistan. Studying and evaluating these factors are the most important goals of this article. The research method of this article is field research. As we surveyed all of Sistan with a large number of archaeologists for two years in order to identify its ancient sites and understanding its geographical space. The result of this survey led to the identification of a large number of ancient sites which were formed in three major terraces in Sistan. The most important factor in the emergence of these civilizations, especially the Bronze Age in Sistan, was the Hirmand River. On the other hand, the most important factor in the destruction of the Bronze Age and its cities in Sistan was the Hirmand River.As it was destroyed by the movement of the Hirmand River bed or the long droughts of the Bronze Age of Sistan.

Keywords: archaeological survey, bronze age, sistan, urbanization

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Authors: Szymon Kugler, Krzysztof Kowalczyk, Tadeusz Spychaj

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An addition of carbon nanotubes (CNT) can simultaneously improve many features of epoxy coatings, i.e. electrical, mechanical, functional and thermal. Unfortunately, this nanofiller negatively affects visual properties of the coatings, such as transparency and gloss. The main reason for the low visual performance of CNT-modified epoxy coatings is the lack of compatibility between CNT and popular amine curing agents, although epoxy resins based on bisphenol A are indisputable good CNT dispersants. This is a serious obstacle in utilization of the coatings in advanced applications, demanding both high transparency and electrical conductivity. The aim of performed investigations was to find amine curing agents exhibiting affinity for CNT, and ensuring good performance of epoxy coatings with them. Commercially available CNT was dispersed in epoxy resin, as well as in different aliphatic, cycloaliphatic and aromatic amines, using one of two dispergation methods: ultrasonic or mechanical. The CNT dispersions were subsequently used in the preparation of epoxy coating compositions and coatings on a transparent substrate. It was found that amine derivative of bio-based cardanol, as well as modified o-tolylbiguanide exhibit significant CNT, dispersing properties, resulting in improved transparent/electroconductive performance of epoxy coatings. In one of prepared coating systems just 0.025 wt.% (250 ppm) of CNT was enough to obtain coatings with semi conductive properties, 83% of transparency as well as perfect chemical resistance to methyl-ethyl ketone and improved thermal stability. Additionally, a theory of the influence of amine chemical structure on CNT dispersing properties was proposed.

Keywords: bio-based cardanol, carbon nanotubes, epoxy coatings, tolylbiguanide

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Authors: Jie Ding, Yingying Pan, Shammy Raj, Lindy Schaffrick, Jolene Wong, Antoinette Nguyen, Sharada Manchikanti, Larry Unsworth, Peter Kwan, Edward E. Tredget

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Background: Exosomes (EXOs) have been considered a new target that is thought to be involved in and treat wound healing. More research is needed to fully understand the EXO characteristics and mechanisms of EXO-mediated wound healing, especially wound healing after burn injury. Methods: Total EXOs were isolated from 85 serum samples of 29 burn patients and 13 healthy individuals. We characterized the EXOs for morphology and density, serum concentration, protein level, marker expression, size distribution, and cytokine content. After confirmation of EXO uptake by dermal fibroblasts, we also explored functional regulation of primary human normal skin and hypertrophic scar fibroblast cell lines by the EXOs in vitro, including cell proliferation and apoptosis. Results: EXOs dynamically changed their morphology, density, size, and cytokine level during wound healing in burn patients, which were correlated with burn severity and the stages of wound healing. EXOs from both burn patients and healthy individuals stimulated dermal fibroblast proliferation and apoptosis. Conclusion: EXO features may be important signals that influence wound healing after burn injury; however, to understand the mechanisms by which EXOs regulated the fibroblasts in healing wounds, further studies will be required in the future.

Keywords: exosome, burn, wound healing, hypertrophic scarring, cytokines

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

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Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Neda Seyyedi, Reza Berangi

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Voice over IP (VOIP) network, also known as Internet telephony, is growing increasingly having occupied a large part of the communications market. With the growth of each technology, the related security issues become of particular importance. Taking advantage of this technology in different environments with numerous features put at our disposal, there arises an increasing need to address the security threats. Being IP-based and playing a signaling role in VOIP networks, Session Initiation Protocol (SIP) lets the invaders use weaknesses of the protocol to disable VOIP service. One of the most important threats is denial of service attack, a branch of which in this article we have discussed as flooding attacks. These attacks make server resources wasted and deprive it from delivering service to authorized users. Distributed denial of service attacks and attacks with a low rate can mislead many attack detection mechanisms. In this paper, we introduce a mechanism which not only detects distributed denial of service attacks and low rate attacks, but can also identify the attackers accurately. We detect and prevent flooding attacks in SIP protocol using Shannon (FDP-S), Renyi (FDP-R) and Tsallis (FDP-T) entropy. We conducted an experiment to compare the percentage of detection and rate of false alarm messages using any of the Shannon, Renyi and Tsallis entropy as a measure of disorder. Implementation results show that, according to the parametric nature of the Renyi and Tsallis entropy, by changing the parameters, different detection percentages and false alarm rates will be gained with the possibility to adjust the sensitivity of the detection mechanism.

Keywords: VOIP networks, flooding attacks, entropy, computer networks

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Authors: Pradeepa Teegala, Ramreddy Chetteti

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This work emphasizes the effects of heat generation/absorption and Joule heating on chemically reacting micropolar fluid flow over a truncated cone with convective boundary condition. For this complex fluid flow problem, the similarity solution does not exist and hence using non-similarity transformations, the governing fluid flow equations along with related boundary conditions are transformed into a set of non-dimensional partial differential equations. Several authors have applied the spectral quasi-linearization method to solve the ordinary differential equations, but here the resulting nonlinear partial differential equations are solved for non-similarity solution by using a recently developed method called the spectral quasi-linearization method (SQLM). Comparison with previously published work on special cases of the problem is performed and found to be in excellent agreement. The influence of pertinent parameters namely Biot number, Joule heating, heat generation/absorption, chemical reaction, micropolar and magnetic field on physical quantities of the flow are displayed through graphs and the salient features are explored in detail. Further, the results are analyzed by comparing with two special cases, namely, vertical plate and full cone wherever possible.

Keywords: chemical reaction, convective boundary condition, joule heating, micropolar fluid, spectral quasilinearization method

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Authors: Mohammed Sherzad

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The Sahara desert covers third of the total surface of Africa with a quarter of this area within the national boundaries of Algeria. Sand drift and deposition is considered one of the major factors of the desertification process in the area. It is estimated that a third of the world's hot arid lands are covered by aeolian sand deposits, forming extensive sand bedforms. The Gourrara region in the Grand Erg Occidental (west of Algerian Sahara) and the region of Souf in the Grand Erg Oriental (east of Algerian Sahara) have been chosen as case studies. These were significant cultural and trading centers for many centuries despite their remote location and their harsh desert environment particularly solar radiation and sand drift and deposition. The architecture of the sustained vernacular settlements in each of the two regions has unique design features for this environment. So do the irrigation systems used - palm groves and the foggara system for capturing and distributing groundwater. However, the ecological balance which enabled the Saharans to live with the desert has been upset. New buildings often use technology based on models imported or imposed from areas that climatically have little in common. These make the inhabitants live ‘in the desert’ rather than ‘with the desert’. This paper will describe the qualities of the vernacular architecture and demonstrate its effectiveness and adaptability to the region’s harsh desert environment in comparison with contemporary buildings. Developing design guides and approaches based on lessons from the traditional architecture is important to ensure sustained livelihoods of the inhabitants in these areas.

Keywords: vernacular architecture, desert architecture, hot climate, aeolian sand deposition

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

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In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Anna Perrone, Federico Martinelli

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Olive fruit is well-known for the high content in secondary metabolites with high interest at nutritional, nutraceutical, antioxidant, and healthy levels. The content of secondary metabolites in olive at harvest may be affected by different water regimes, with significant effects on olive oil composition and quality and, consequently, on its healthy and nutritional features. In this work, a summary of several research studies dealing with the biosynthesis of healthy and nutraceutical metabolites of the secondary metabolism in olive fruit will be reported. The phytochemical findings have been correlated with the expression of key genes involved in polyphenol, terpenoid, and carotenoid biosynthesis and metabolism in response to different development stages and water regimes. Flavonoids were highest in immature fruits, while anthocyanins increased at ripening. In epicarp tissue, this was clearly associated with an up-regulation of the UFGT gene. Olive fruits cultivated under different water regimes were analyzed by metabolomics. This method identified several hundred metabolites in the ripe mesocarp. Among them, 46 were differentially accumulated in the comparison between rain-fed and irrigated conditions. Well-known healthy metabolites were more abundant at a higher level of water regimes. Increased content of polyphenols was observed in the rain-fed fruit; particularly, anthocyanin concentration was higher at ripening. Several secondary metabolites were differentially accumulated between different irrigation conditions. These results showed that these metabolic approaches could be efficiently used to determine the effects of agronomic treatments on olive fruit physiology and, consequently, on nutritional and healthy properties of the obtained extra-virgin olive oil.

Keywords: olea europea, anthocyanins, polyphenols, water regimes

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Authors: H. G. C. P. Dinesh, G. Tharshini, M. P. B. Ekanayake, G. M. R. I. Godaliyadda

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This paper presents a new spatial feature extraction method based on principle component analysis (PCA) and Fisher Discernment Analysis (FDA) for facial expression recognition. It not only extracts reliable features for classification, but also reduces the feature space dimensions of pattern samples. In this method, first each gray scale image is considered in its entirety as the measurement matrix. Then, principle components (PCs) of row vectors of this matrix and variance of these row vectors along PCs are estimated. Therefore, this method would ensure the preservation of spatial information of the facial image. Afterwards, by incorporating the spectral information of the eigen-filters derived from the PCs, a feature vector was constructed, for a given image. Finally, FDA was used to define a set of basis in a reduced dimension subspace such that the optimal clustering is achieved. The method of FDA defines an inter-class scatter matrix and intra-class scatter matrix to enhance the compactness of each cluster while maximizing the distance between cluster marginal points. In order to matching the test image with the training set, a cosine similarity based Bayesian classification was used. The proposed method was tested on the Cohn-Kanade database and JAFFE database. It was observed that the proposed method which incorporates spatial information to construct an optimal feature space outperforms the standard PCA and FDA based methods.

Keywords: facial expression recognition, principle component analysis (PCA), fisher discernment analysis (FDA), eigen-filter, cosine similarity, bayesian classifier, f-measure

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Authors: Virender Singh, Mathew Rees, Simon Hampton, Sivaram Annadurai

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Plant identification is a challenging task that aims to identify the family, genus, and species according to plant morphological features. Automated deep learning-based computer vision algorithms are widely used for identifying plants and can help users narrow down the possibilities. However, numerous morphological similarities between and within species render correct classification difficult. In this paper, we tested custom convolution neural network (CNN) and vision transformer (ViT) based models using the PyTorch framework to classify plants. We used a large dataset of 88,000 provided by the Royal Horticultural Society (RHS) and a smaller dataset of 16,000 images from the PlantClef 2015 dataset for classifying plants at genus and species levels, respectively. Our results show that for classifying plants at the genus level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420 and other state-of-the-art CNN-based models suggested in previous studies on a similar dataset. ViT model achieved top accuracy of 83.3% for classifying plants at the genus level. For classifying plants at the species level, ViT models perform better compared to CNN-based models ResNet50 and ResNet-RS-420, with a top accuracy of 92.5%. We show that the correct set of augmentation techniques plays an important role in classification success. In conclusion, these results could help end users, professionals and the general public alike in identifying plants quicker and with improved accuracy.

Keywords: plant identification, CNN, image processing, vision transformer, classification

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Authors: Ali Momeni

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Visual media has had a significant impact on the mental structure and behaviors of humanity. One interactive platform that has played a major role in this is Instagram. In Islamic countries, particularly Iran, many Muslims have embraced this interactive media platform for various reasons. Instagram has also provided an opportunity for individuals to become famous and gain micro-celebrity status through its semi-algorithmic features. A notable group of Iranian women who have gained fame through Instagram are religious Muslim women who have transitioned into bloggers. These Iranian religious women bloggers (IRWB) have garnered a large following by showcasing different models of hijab and their private lives. This research aims to qualitatively study the representation of femininity and religiosity of these women. The main question addressed in this study is the acceptance of Instagram activity by IRWB among religious women. Drawing on concepts such as 'The Society of the Spectacle' and 'Celebrity Online', this study utilized the netnography method to analyze 14 pages of IRWB. Data was collected in two phases, with the first phase involving the analysis of religious women's comments on posts related to these themes. The second phase included interviews with religious women students who view or follow these pages. A total of 120 comments and 14 interviews were thematically analyzed. The results revealed that the reception of these pages by religious women fell into four main themes: the spectacle of femininity, the commercialization of religiosity, the distortion of Islam, and the construction of religiosity and femininity. Ultimately, religious women did not find these pages to be reflective of their own experiences of female and religious life.

Keywords: women, bloggers, instagram, IRWB, reception.

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Authors: Tuba Kizilirmak

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Distinct properties of porous metamaterials have been largely processed for biomedicine requiring a three-dimensional (3D) porous structure engaged with fine mechanical features, biodegradation ability, and biocompatibility. Applications of metamaterials are (i) porous orthopedic and dental implants; (ii) in vitro cell culture of metamaterials and bone regeneration of metamaterials in vivo; (iii) macro-, micro, and nano-level porous metamaterials for sensors, diagnosis, and drug delivery. There are some specific properties to design metamaterials for tissue engineering. These are surface to volume ratio, pore size, and interconnection degrees are selected to control cell behavior and bone ingrowth. In this study, additive manufacturing technique selective laser melting will be used to print the scaffolds. Selective Laser Melting prints the 3D components according to designed 3D CAD models and manufactured materials, adding layers progressively by layer. This study aims to design metamaterials with Ti6Al4V material, which gives benefit in respect of mechanical and biological properties. Ti6Al4V scaffolds will support cell attachment by conferring a suitable area for cell adhesion. This study will control the osteoblast cell attachment on Ti6Al4V scaffolds after the determination of optimum stiffness and other mechanical properties which are close to mechanical properties of bone. Before we produce the samples, we will use a modeling technique to simulate the mechanical behavior of samples. These samples include different lattice models with varying amounts of porosity and density.

Keywords: additive manufacturing, titanium lattices, metamaterials, porous metals

Procedia PDF Downloads 194

Authors: Mohamed F. Ahmed, Mabruka S. Elashheb, Fatma M. Ben Rabha

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This study aimed to determine the possible protective effects of L‐carnitine against gentamicin‐induced nephrotoxicity. Forty male albino rats were divided into 4 groups (10 rats each); Group 1: normal control, group 2: induced nephrotoxicity (gentamicin 50 mg/kg/day S.C; 8 days) , group 3: treated with L‐carnitine (40 mg/kg/d SC for 12 days) and group 4: treated with L‐carnitine 4 days before and for 8 days in concomitant with gentamicin. Gentamicin‐induced nephrotoxicity (group 2): caused significant increase in serum urea, creatinine, urinary N‐acetyl‐B‐D‐glucosaminidase (NAG), gamma glutamyl transpeptidase (GGT), urinary total protein and kidney tissue malondialdehyde (MDA) with significant decrease in serum superoxide dismutase (SOD), serum catalase and creatinine clearance and marked tubular necrosis in the proximal convoluted tubules with interruption in the basement membrane around the necrotic tubule compared to the normal control group. L‐carnitine 4 days before and for 8 days in concomitant with gentamicin (group 4) offered marked decrease in serum urea, serum creatinine, urinary NAG, urinary GGT, urinary proteins and kidney tissue MDA, with marked increase in serum SOD, serum catalase and creatinine clearance with marked improvement in the tubular damage compared to gentamicin‐induced nephrotoxicity group. L‐carnitine administered for 12 days produced no change in the above-mentioned parameters as compared to the normal control group. In conclusion: L‐carnitine could reduce most of the biochemical parameters and also improve the histopathological features of the kidney associated with gentamicin-induced nephrotoxicity.

Keywords: gentamicin, nephrotoxicity, L‐carnitine, kidney disease

Procedia PDF Downloads 357

Authors: Boon Yih Mah

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Web-based Cognitive Writing Instruction (WeCWI)’s contribution towards language development can be divided into linguistic and non-linguistic perspectives. In linguistic perspective, WeCWI focuses on the literacy and language discoveries, while the cognitive and psychological discoveries are the hubs in non-linguistic perspective. In linguistic perspective, WeCWI draws attention to free reading and enterprises, which are supported by the language acquisition theories. Besides, the adoption of process genre approach as a hybrid guided writing approach fosters literacy development. Literacy and language developments are interconnected in the communication process; hence, WeCWI encourages meaningful discussion based on the interactionist theory that involves input, negotiation, output, and interactional feedback. Rooted in the e-learning interaction-based model, WeCWI promotes online discussion via synchronous and asynchronous communications, which allows interactions happened among the learners, instructor, and digital content. In non-linguistic perspective, WeCWI highlights on the contribution of reading, discussion, and writing towards cognitive development. Based on the inquiry models, learners’ critical thinking is fostered during information exploration process through interaction and questioning. Lastly, to lower writing anxiety, WeCWI develops the instructional tool with supportive features to facilitate the writing process. To bring a positive user experience to the learner, WeCWI aims to create the instructional tool with different interface designs based on two different types of perceptual learning style.

Keywords: WeCWI, literacy discovery, language discovery, cognitive discovery, psychological discovery

Procedia PDF Downloads 561

Authors: Shubham Sharma, Swarna Jaiswal, Brendan Duffy, Amit Jaiswal

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The key features of any active packaging film are its biodegradability and antimicrobial properties. Biological macromolecules such as polyphenols (ferulic acid (FA) and tannic acids (TA)) are naturally found in plants such as grapes, berries, and tea. In this study, antimicrobial activity screening of several polyphenols was carried out by using minimal inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) against two strains of gram-negative bacteria - Salmonella typhimurium, Escherichia coli, and two-gram positive strains - Staphylococcus aureus and Listeria monocytogenes. FA and TA had shown strong antibacterial activity at the low concentration against both gram-positive and gram-negative bacteria. The selected polyphenols FA and TA were incorporated at various concentrations (1%, 5%, and 10% w/w) in the poly(lactide) – poly (butylene adipate-co-terephthalate) (PLA-PBAT) composite film by using the solvent casting method. The effect of TA and FA incorporation in the packaging was characterized based on morphological, optical, color, mechanical, thermal, and antimicrobial properties. The thickness of the FA composite film was increased by 1.5 – 7.2%, while for TA composite film, it increased by 0.018 – 1.6%. FA and TA (10 wt%) composite film had shown approximately 65% - 66% increase in the UV barrier property. As the FA and TA concentration increases from 1% - 10% (w/w), the TS value increases by 1.98 and 1.80 times, respectively. The water contact angle of the film was observed to decrease significantly with the increase in the FA and TA content in the composite film. FA has shown more significant increase in antimicrobial activity than TA in the composite film against Listeria monocytogenes and E. coli. The FA and TA composite film has the potential for its application as an active food packaging.

Keywords: active packaging, biodegradable film, polyphenols, UV barrier, tensile strength

Procedia PDF Downloads 152

Authors: Arnaldo G. de Oliveira, Jr, Matthieu Tubino

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The transesterification process of triglycerides with alcohols that occurs during the biodiesel synthesis causes continuous changes in several physical properties of the reaction mixture, such as refractive index, viscosity and density. Amongst them, density can be an useful parameter to monitor the reaction, in order to predict the composition of the reacting mixture and to verify the conversion of the oil into biodiesel. In this context, a system was constructed in order to continuously determine changes in the density of the reacting mixture containing soybean oil, methanol and sodium methoxide (30 % w/w solution in methanol), stirred at 620 rpm at room temperature (about 27 °C). A polyethylene pipe network connected to a peristaltic pump was used in order to collect the mixture and pump it through a coil fixed on the plate of an analytical balance. The collected mass values were used to trace a curve correlating the mass of the system to the reaction time. The density variation profile versus the time clearly shows three different steps: 1) the dispersion of methanol in oil causes a decrease in the system mass due to the lower alcohol density followed by stabilization; 2) the addition of the catalyst (sodium methoxide) causes a larger decrease in mass compared to the first step (dispersion of methanol in oil) because of the oil conversion into biodiesel; 3) the final stabilization, denoting the end of the reaction. This density variation profile provides information that was used to predict the composition of the mixture over the time and the reaction rate. The precise knowledge of the duration of the synthesis means saving time and resources on a scale production system. This kind of monitoring provides several interesting features such as continuous measurements without collecting aliquots.

Keywords: biodiesel, density measurements, online continuous monitoring, synthesis

Procedia PDF Downloads 575

Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

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Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

Procedia PDF Downloads 377

Authors: Nathaniel Carpenter

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Web-enabled systems for supporting youth mental health management in Australia are pioneering in their field; however, with their success, these systems are experiencing exponential growth in demand which is straining an already stretched service. Supporting youth mental is critical as the lack of support is associated with significant and lasting negative consequences. To meet this growing demand, and provide critical support, investigations are needed on evaluating and improving existing online support services. Improvements should focus on developing frameworks capable of augmenting and scaling service provisions. There are few investigations informing best-practice frameworks when implementing e-mental health support systems for youth mental health; there are fewer which implement machine learning or artificially intelligent systems to facilitate the delivering of services. This investigation will use a case study methodology to highlight the design features which are important for systems to enable young people to self-manage their mental health. The investigation will also highlight the current information system challenges, to include challenges associated with service quality, provisioning, and scaling. This work will propose methods of meeting these challenges through improved design, service augmentation and automation, service quality, and through artificially intelligent inspired solutions. The results of this study will inform a framework for supporting youth mental health with intelligent and scalable web-enabled technologies to support an ever-growing user base.

Keywords: artificial intelligence, information systems, machine learning, youth mental health

Procedia PDF Downloads 110