Search results for: case citation network

Authors: Reza Dinarvand, Mahdi Sadeghian, Somaye Sadeghian

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Prediction of the ultimate bearing capacity of piles (Qu) is one of the basic issues in geotechnical engineering. So far, several methods have been used to estimate Qu, including the recently developed artificial intelligence methods. In recent years, optimization algorithms have been used to minimize artificial network errors, such as colony algorithms, genetic algorithms, imperialist competitive algorithms, and so on. In the present research, artificial neural networks based on colonial competition algorithm (ANN-ICA) were used, and their results were compared with other methods. The results of laboratory tests of short piles in clayey soils with parameters such as pile diameter, pile buried length, eccentricity of load and undrained shear resistance of soil were used for modeling and evaluation. The results showed that ICA-based artificial neural networks predicted lateral bearing capacity of short piles with a correlation coefficient of 0.9865 for training data and 0.975 for test data. Furthermore, the results of the model indicated the superiority of ICA-based artificial neural networks compared to back-propagation artificial neural networks as well as the Broms and Hansen methods.

Keywords: artificial neural network, clayey soil, imperialist competition algorithm, lateral bearing capacity, short pile

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Authors: Dativa Maria Aliddeki, Fred Monje, Godfrey Nsereko, Benon Kwesiga, Daniel Kadobera, Alex Riolexus Ario

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Background: Cholera is a severe gastrointestinal disease caused by Vibrio cholera. It has caused several pandemics. On 26 February 2018, a suspected cholera outbreak, with one death, occurred in School X in Hoima Municipality, western Uganda. We investigated to identify the scope and mode of transmission of the outbreak, and recommend evidence-based control measures. Methods: We defined a suspected case as onset of diarrhea, vomiting, or abdominal pain in a student or staff of School X or their family members during 14 February–10 March. A confirmed case was a suspected case with V. cholerae cultured from stool. We reviewed medical records at Hoima Hospital and searched for cases at School X. We conducted descriptive epidemiologic analysis and hypothesis-generating interviews of 15 case-patients. In a retrospective cohort study, we compared attack rates between exposed and unexposed persons. Results: We identified 15 cases among 75 students and staff of School X and their family members (attack rate=20%), with onset from 25-28 February. One patient died (case-fatality rate=6.6%). The epidemic curve indicated a point-source exposure. On 24 February, a student brought fried fish from her home in a fishing village, where a cholera outbreak was ongoing. Of the 21 persons who ate the fish, 57% developed cholera, compared with 5.6% of 54 persons who did not eat (RR=10; 95% CI=3.2-33). None of 4 persons who recooked the fish before eating, compared with 71% of 17 who did not recook it, developed cholera (RR=0.0, 95%CIFisher exact=0.0-0.95). Of 12 stool specimens cultured, 6 yielded V. cholerae. Conclusion: This cholera outbreak was caused by eating fried fish, which might have been contaminated with V. cholerae in a village with an ongoing outbreak. Lack of thorough cooking of the fish might have facilitated the outbreak. We recommended thoroughly cooking fish before consumption.

Keywords: cholera, disease outbreak, foodborne, global health security, Uganda

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Authors: Gauranga Das

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People in cities have prosperity but there is immense pollution, chaos in the mind, anxiety and turbulence. People in the villages experience pristine pure environment but they also experience poverty. There is a need to find out ways by which the cities and the villages can complement each other through their strengths and take care of each other’s weaknesses. In order to do this, the case study of Govardhan Ecovillage has been explored in this paper. All its environment, social and economic initiatives along with eco-tourism and wellness features are being analyzed. The analysis shows that Govardhan Ecovillage is successfully able to harmonize its different initiatives and provide a package which has created a win-win solution for the city people and also the villagers. Such kind of Eco-tourism initiatives should be supported and replicated in other places in the world to benefit everyone.

Keywords: sustainability, ecotourism, ecology, rural development, wellness, biodiversity

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Authors: J. O. Alvarez, L. Y. Rivera

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Physical activity can reduce symptomatology in children with autism spectrum disorder (ASD). The sport of soccer has been widely applied as a therapeutic method for ASD children. However, empirical results from soccer programs are not widely known. This paper presents the case study of Golitos, the only dedicated soccer program for children on the island of Puerto Rico, and analyzes its results in the reduction of ASD social and emotional symptoms. The paper shows evidence that suggests that program approach, content, and community-based elements can make a notable difference in the effectiveness of using soccer or sports as therapeutic methods for children with ASD.

Keywords: autism, soccer, program, community

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Authors: Shaode Yu, Jiajian Meng, Bing Zhu, Hang Yu, Qiurui Sun

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Speech emotion recognition (SER) is for recognizing human subjective emotions through audio data in-depth analysis. From speech audios, how to comprehensively extract emotional information and how to effectively fuse extracted features remain challenging. This paper presents a dual-stream SER framework that embraces both full training and transfer learning of different networks for thorough feature encoding. Besides, a plug-and-play cross-attention fusion (CAF) module is implemented for the valid integration of the dual-stream encoder output. The effectiveness of the proposed CAF module is compared to the other three fusion modules (feature summation, feature concatenation, and feature-wise linear modulation) on two databases (RAVDESS and IEMO-CAP) using different dual-stream encoders (full training network, DPCNN or TextRCNN; transfer learning network, HuBERT or Wav2Vec2). Experimental results suggest that the CAF module can effectively reconcile conflicts between features from different encoders and outperform the other three feature fusion modules on the SER task. In the future, the plug-and-play CAF module can be extended for multi-branch feature fusion, and the dual-stream SER framework can be widened for multi-stream data representation to improve the recognition performance and generalization capacity.

Keywords: speech emotion recognition, cross-attention fusion, dual-stream, pre-trained

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Authors: Adrian Sebastian, Chris Gillespie

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We describe a case of diffuse rectal involvement with cap polyposis, manifesting with a protein-losing colopathy and occurring in the setting of advanced mechanical pelvic floor dysfunction. A 59-year-old male with a 5-year history of persistent excessive flatulence, defecatory difficulties, and diarrhea. He had extensive cap polyposis of the entire rectum endoscopically. His symptoms progressed to severe fecal incontinence with mucus leakage, pelvic pain, weight loss, and hypoalbuminemia. Clinical examination exhibited severe perineal descent, a large rectocele, poor anal squeeze, and a poor defecatory technique. After a trial of nonoperative therapies addressing his defecatory dysfunction, and Helicobacter pylori eradication, surgical resection was offered due to severe symptoms with ongoing incontinence and protein loss with no other reasonable options. A robotic abdominoperineal resection with a permanent colostomy was performed, followed by an uncomplicated recovery. Our observation of coexisting mechanical pelvic floor changes in this patient lends weight to the concept of a prolapse-related phenomenon in the pathophysiology of this rare condition.

Keywords: cap polyposis, pelvic dysfunction, fecal incontinence, case report

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Authors: Aref Aasi, Sahar Ebrahimi Bajgani, Erfan Aasi

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Breast cancer (BC) continues to be the most frequent cancer in females and causes the highest number of cancer-related deaths in women worldwide. Inspired by recent advances in studying the relationship between different patient attributes and features and the disease, in this paper, we have tried to investigate the different classification methods for better diagnosis of BC in the early stages. In this regard, datasets from the University Hospital Centre of Coimbra were chosen, and different machine learning (ML)-based and neural network (NN) classifiers have been studied. For this purpose, we have selected favorable features among the nine provided attributes from the clinical dataset by using a random forest algorithm. This dataset consists of both healthy controls and BC patients, and it was noted that glucose, BMI, resistin, and age have the most importance, respectively. Moreover, we have analyzed these features with various ML-based classifier methods, including Decision Tree (DT), K-Nearest Neighbors (KNN), eXtreme Gradient Boosting (XGBoost), Logistic Regression (LR), Naive Bayes (NB), and Support Vector Machine (SVM) along with NN-based Multi-Layer Perceptron (MLP) classifier. The results revealed that among different techniques, the SVM and MLP classifiers have the most accuracy, with amounts of 96% and 92%, respectively. These results divulged that the adopted procedure could be used effectively for the classification of cancer cells, and also it encourages further experimental investigations with more collected data for other types of cancers.

Keywords: breast cancer, diagnosis, machine learning, biomarker classification, neural network

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Authors: Naghmeh Moradpoor Sheykhkanloo

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Structured Query Language Injection (SQLI) attack is a code injection technique in which malicious SQL statements are inserted into a given SQL database by simply using a web browser. Losing data, disclosing confidential information or even changing the value of data are the severe damages that SQLI attack can cause on a given database. SQLI attack has also been rated as the number-one attack among top ten web application threats on Open Web Application Security Project (OWASP). OWASP is an open community dedicated to enabling organisations to consider, develop, obtain, function, and preserve applications that can be trusted. In this paper, we propose an effective pattern recognition neural network model for detection and classification of SQLI attacks. The proposed model is built from three main elements of: a Uniform Resource Locator (URL) generator in order to generate thousands of malicious and benign URLs, a URL classifier in order to: 1) classify each generated URL to either a benign URL or a malicious URL and 2) classify the malicious URLs into different SQLI attack categories, and an NN model in order to: 1) detect either a given URL is a malicious URL or a benign URL and 2) identify the type of SQLI attack for each malicious URL. The model is first trained and then evaluated by employing thousands of benign and malicious URLs. The results of the experiments are presented in order to demonstrate the effectiveness of the proposed approach.

Keywords: neural networks, pattern recognition, SQL injection attacks, SQL injection attack classification, SQL injection attack detection

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Authors: Nigar Kantarci Carsibasi

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Coarse-grained elastic network models, namely Gaussian network model (GNM) and Anisotropic network model (ANM), are utilized in order to investigate the fluctuation dynamics of Murine Double Minute 2 (MDM2), which is the native inhibitor of p53. Conformational dynamics of MDM2 are elucidated in unbound, p53 bound, and non-peptide small molecule inhibitor bound forms. With this, it is aimed to gain insights about the alterations brought to global dynamics of MDM2 by native peptide inhibitor p53, and two small molecule inhibitors (HDM201 and NVP-CGM097) that are undergoing clinical stages in cancer studies. MDM2 undergoes significant conformational changes upon inhibitor binding, carrying pieces of evidence of induced-fit mechanism. Small molecule inhibitors examined in this work exhibit similar fluctuation dynamics and characteristic mode shapes with p53 when complexed with MDM2, which would shed light on the design of novel small molecule inhibitors for cancer therapy. The results showed that residues Phe 19, Trp 23, Leu 26 reside in the minima of slowest modes of p53, pointing to the accepted three-finger binding model. Pro 27 displays the most significant hinge present in p53 and comes out to be another functionally important residue. Three distinct regions are identified in MDM2, for which significant conformational changes are observed upon binding. Regions I (residues 50-77) and III (residues 90-105) correspond to the binding interface of MDM2, including (α2, L2, and α4), which are stabilized during complex formation. Region II (residues 77-90) exhibits a large amplitude motion, being highly flexible, both in the absence and presence of p53 or other inhibitors. MDM2 exhibits a scattered profile in the fastest modes of motion, while binding of p53 and inhibitors puts restraints on MDM2 domains, clearly distinguishing the kinetically hot regions. Mode shape analysis revealed that the α4 domain controls the size of the cleft by keeping the cleft narrow in unbound MDM2; and open in the bound states for proper penetration and binding of p53 and inhibitors, which points to the induced-fit mechanism of p53 binding. P53 interacts with α2 and α4 in a synchronized manner. Collective modes are shifted upon inhibitor binding, i.e., second mode characteristic motion in MDM2-p53 complex is observed in the first mode of apo MDM2; however, apo and bound MDM2 exhibits similar features in the softest modes pointing to pre-existing modes facilitating the ligand binding. Although much higher amplitude motions are attained in the presence of non-peptide small molecule inhibitor molecules as compared to p53, they demonstrate close similarity. Hence, NVP-CGM097 and HDM201 succeed in mimicking the p53 behavior well. Elucidating how drug candidates alter the MDM2 global and conformational dynamics would shed light on the rational design of novel anticancer drugs.

Keywords: cancer, drug design, elastic network model, MDM2

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Authors: P. S. Dhananjaya Swamy, B. Chinnappa, G. B. Ramesh, Naveen P. Kumar

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Kodagu district is one of the most densely forested districts in the India as around sixty five per cent of geographical areas under tree cover. Nearly 53 per cent of the flora of Kodagu is endemic. The district is also a hotspot of endemic orchids found mainly in the Thadiandamol. Shade grown, eco-friendly coffee farms are perhaps a selected few places on this planet where nature runs wild. The Kodagu accounts for more than 8.8 per cent of floral diversity of Karnataka state. Estimation of unit cost of cultivation plays a vital role in determining the governmental program their market intervention policies. On an average, planters incurred around Rs. 17041 per acre. The extent of production risk was highest among small category of planters (66 %) compared to other two exhibiting production instability. The result shows that, the coffee productivity in medium plantations was 1051.2 kg per acre as against 758.5 and 789.2 kg in the case of small and large plantations. An annual net return per acre was highest in the case of medium planters (Rs. 26109.3) as against Rs. 20566.7 and Rs. 18572.7 in the case of small and large planters. Cost of production was lowest in the case of small planters (Rs. 18.9 per kg of output) followed by medium planters (Rs. 21.2 per kg of output) and large planters (Rs. 22.5 per kg of output). The productivity of coffee is less whenever it is grown under high shade and native tree cover; it is around 6 quintals per acre when compared with low shade conditions, which is around 8.9 quintals per acre, without a significant difference in the amount invested for growing coffee. Net gain was lower by Rs. 15.5 per kg for the planters growing under high shade and native trees cover when compared with low shade and exotic trees cover.

Keywords: coffee, cultivation, economics, Kodagu

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Authors: Syed Jawad Hussain, Abir Touati, Farid Touati

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Free-Space Optics (FSO) is a wireless technology that enables the optical transmission of data though the air. FSO is emerging as a promising alternative or complementary technology to fiber optic and wireless radio-frequency (RF) links due to its high-bandwidth, robustness to EMI, and operation in unregulated spectrum. These systems are envisioned to be an essential part of future generation heterogeneous communication networks. Despite the vibrant advantages of FSO technology and the variety of its applications, its widespread adoption has been hampered by rather disappointing link reliability for long-range links due to atmospheric turbulence-induced fading and sensitivity to detrimental climate conditions. Qatar, with modest cloud coverage, high concentrations of airborne dust and high relative humidity particularly lies in virtually rainless sunny belt with a typical daily average solar radiation exceeding 6 kWh/m2 and 80-90% clear skies throughout the year. The specific objective of this work is to study for the first time in Qatar the effect of solar irradiation on the deliverability of the FSO Link. In order to analyze the transport media, we have ported Embedded Linux kernel on Field Programmable Gate Array (FPGA) and designed a network sniffer application that can run into FPGA. We installed new FSO terminals and configure and align them successively. In the reporting period, we carry out measurement and relate them to weather conditions.

Keywords: free space optics, solar irradiation, field programmable gate array, FSO outage

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Authors: Meital Amzalag, Sharon Hardof-Jaffe

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In the last few decades, children and youth have been immersed in digital technologies. Indeed, recent studies explored the implication of technology use in their leisure and learning activities. Educators face an essential need to utilize technology and implement them into the curriculum. To do that, educators need to understand how young people use digital technology. This study aims to explore K12 students' digital lives from their point of view, to reveal their digital activities, age and gender differences with respect to digital activities, and to present the students' attitudes towards technologies in learning. The study approach is quantitative and includes354 students ages 6-16 from three schools in Israel. The online questionnaire was based on self-reports and consists of four parts: Digital activities: leisure time activities (such as social networks, gaming types), search activities (information types and platforms), and digital application use (e.g., calendar, notes); Digital skills (requisite digital platform skills such as evaluation and creativity); Social and emotional aspects of digital use (conducting digital activities alone and with friends, feelings, and emotions during digital use such as happiness, bullying); Digital attitudes towards digital integration in learning. An academic ethics board approved the study. The main findings reveal the most popular K12digital activities: Navigating social network sites, watching TV, playing mobile games, seeking information on the internet, and playing computer games. In addition, the findings reveal age differences in digital activities, such as significant differences in the use of social network sites. Moreover, the finding raises gender differences as girls use more social network sites and boys use more digital games, which are characterized by high complexity and challenges. Additionally, we found positive attitudes towards technology integration in school. Students perceive technology as enhancing creativity, promoting active learning, encouraging self-learning, and helping students with learning difficulties. The presentation will provide an up-to-date, accurate picture of the use of various digital technologies by k12 students. In addition, it will discuss the learning potentials of such use and how to implement digital technologies in the curriculum. Acknowledgments: This study is a part of a broader study about K-12 digital life in Israel and is supported by Mofet-the Israel Institute for Teachers'Development.

Keywords: technology and learning, K-12, digital life, gender differences

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Authors: Dan Qu, Dezhi Sun, Benhang Li

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The removal of Nitenpyram from farmland runoff by an integrated eco-ditches and constructed wetland system was investigated in the case of different HRT. Experimental results show that the removal of COD, N and P was not influenced by the Nitenpyram. When the HRT was 2.5 d, 2 d, and 1 d, the Nitenpyram removal efficiency could reach 100%, 100% and 84%, respectively. The removal efficiency in the ecological ditches was about 38%-40% in the case of different HRT, while that in the constructed wetland was influenced by the HRT variation. The optimum HRT for Nitenpyram and pollutants removal was 2 d. The substrate zeolite with soil and hollow brick layer enabled higher Nitenpyram removal rates, probably due to the cooperative phenomenon of plant uptake and microbiological deterioration as well as the adsorption by the substrate.

Keywords: ecological ditch, vertical flow constructed wetland, hydraulic retention time, Nitenpyram

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Authors: Tianyi Qin

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Along with the acceleration of Chinese urbanization, the expansion, renovation and demolition of old buildings is on the stage together with the design and construction of new buildings every day in downtown of the old city area. The coordinative symbiosis between new and old buildings is an important problem which needs to be solved in the process of urban development. By studying and analyzing the case of Shanghai Citic Plaza and surroundings, this paper contributes to discussing the concept, value and problems to be solved of the coordination of new and old buildings, meanwhile, striking the balance between new and old buildings from the aspects of architectural form, space, function and local context. As a result, the strategy of the coordinative symbiosis between new and old buildings is summarized, which can offer some guiding principles to urban development from now on.

Keywords: coordinative symbiosis, new and old buildings, Shanghai Citic Plaza, strategy

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Authors: Steven Robinson, Adriana Dager, Param Patel

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Wandering spleen is a rare variant where there is abnormal development of the ligamentous peritoneal attachments of the spleen which normally anchor it in the left upper quadrant of the abdomen. Ligamentous abnormalities can be congenital, or acquired through pregnancy, injury, or iatrogenic causes. Absence or laxity of these ligaments allows migration of the spleen into ectopic portions of the abdomen, which is also associated with an elongated vascular pedicle. Incidence of wandering spleen is reported at less than 0.25% with a female to male ratio of approximately 6:1. The most common complication of a wandering spleen is torsion around its vascular pedicle which can lead to thrombosis and infarction. Torsion of a wandering spleen is a rare but important cause of an acute abdomen. Imaging, and specifically CT or ultrasound, is crucial in the diagnosis. We present a case of a torsed wandering spleen which was treated with splenectomy.

Keywords: Wandering Spleen, Torsion, Splenic Torsion, Spleen

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a new robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics and using the weighted sum-squared prediction error as the residual. The recursive orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. The several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control

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Authors: Mahdi Goharrokhi, Rasool Shiri, Eiraj Naser

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A depropanizer column of a particular refinery was redesigned in this work. That is, minimum reflux ratio, minimum number of trays, feed tray location and the hydraulic characteristics of the tower were calculated and compared with the actual values of the existing tower. To Design review of the tower, fundamental equations were used to develop software which its results were compared with two commercial software results. In each case PR EOS was used. Based on the total energy consumption in reboiler and condenser, feed tray location was also determined using case study definition for tower.

Keywords: column, hydraulic design, pressure drop, energy consumption

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Authors: Iqra Yaseen

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One of the well-known areas of computer science and engineering, image processing in the context of computer vision has been essential to automation. In remote sensing, medical science, and many other fields, it has made it easier to uncover previously undiscovered facts. Grading of diverse items is now possible because of neural network algorithms, categorization, and digital image processing. Its use in the classification of agricultural products, particularly in the grading of seeds or grains and their cultivars, is widely recognized. A grading and sorting system enables the preservation of time, consistency, and uniformity. Global population growth has led to an increase in demand for food staples, biofuel, and other agricultural products. To meet this demand, available resources must be used and managed more effectively. Image processing is rapidly growing in the field of agriculture. Many applications have been developed using this approach for crop identification and classification, land and disease detection and for measuring other parameters of crop. Vegetation localization is the base of performing these task. Vegetation helps to identify the area where the crop is present. The productivity of the agriculture industry can be increased via image processing that is based upon Unmanned Aerial Vehicle photography and satellite. In this paper we use the machine learning techniques like Convolutional Neural Network, deep learning, image processing, classification, You Only Live Once to UAV imaging dataset to divide the crop into distinct groups and choose the best way to use it.

Keywords: image processing, UAV, YOLO, CNN, deep learning, classification

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Authors: G. S. Thyagaraju, U. P. Kulkarni

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Context-aware computing refers to a general class of computing systems that can sense their physical environment, and adapt their behaviour accordingly. Context aware computing makes systems aware of situations of interest, enhances services to users, automates systems and personalizes applications. Context-aware services have been introduced into mobile devices, such as PDA and mobile phones. In this paper we are presenting a novel approaches used to realize the context aware mobile. The context aware mobile phone (CAMP) proposed in this paper senses the users situation automatically and provides user context required services. The proposed system is developed by using artificial intelligence techniques like Bayesian Network, fuzzy logic and rough sets theory based decision table. Bayesian Network to classify the incoming call (high priority call, low priority call and unknown calls), fuzzy linguistic variables and membership degrees to define the context situations, the decision table based rules for service recommendation. To exemplify and demonstrate the effectiveness of the proposed methods, the context aware mobile phone is tested for college campus scenario including different locations like library, class room, meeting room, administrative building and college canteen.

Keywords: context aware mobile, fuzzy logic, decision table, Bayesian probability

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Authors: Jamaiah H. Yahaya, Aziz Deraman, Abdul Razak Hamdan, Yusmadi Yah Jusoh

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One of the most essential issues in software products is to maintain it relevancy to the dynamics of the user’s requirements and expectation. Many studies have been carried out in quality aspect of software products to overcome these problems. Previous software quality assessment models and metrics have been introduced with strengths and limitations. In order to enhance the assurance and buoyancy of the software products, certification models have been introduced and developed. From our previous experiences in certification exercises and case studies collaborating with several agencies in Malaysia, the requirements for user based software certification approach is identified and demanded. The emergence of social network applications, the new development approach such as agile method and other varieties of software in the market have led to the domination of users over the software. As software become more accessible to the public through internet applications, users are becoming more critical in the quality of the services provided by the software. There are several categories of users in web-based systems with different interests and perspectives. The classifications and metrics are identified through brain storming approach with includes researchers, users and experts in this area. The new paradigm in software quality assessment is the main focus in our research. This paper discusses the classifications of users in web-based software system assessment and their associated factors and metrics for quality measurement. The quality model is derived based on IEEE structure and FCM model. The developments are beneficial and valuable to overcome the constraints and improve the application of software certification model in future.

Keywords: software certification model, user centric approach, software quality factors, metrics and measurements, web-based system

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Authors: Darma Putra Sitepu, Dewi Larasati, Yohanes Wolter Hendrik George

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Sepsis is a life-threatening medical emergency frequently observed in intensive care unit (ICU). Surviving Sepsis Campaign in 2018 has recommended the administration of early vasopressor in the first hour of sepsis or septic shock but has not yet included de-resuscitation protocol. De-resuscitation in acute management of septic shock is where patient received active removal of accumulated fluid. It has been proposed by some studies and ongoing clinical trials. Here we present a case with early vasopressor and de-resuscitation. Male, 27 years old presenting to the emergency room with shortness of breath, altered mental status, and widespread blisters on his body and lips started a few hours prior, after receiving non-steroidal anti-inflammatory drug through intravenous injection. Patient was hypotensive, tachycardic, and tachypneic at admission, diagnosed with Steven Johnson Syndrome with Septic Shock. Patient received fluid resuscitation, early vasopressor, and diuresis agent aimed to actively remove fluid after the initial phase of resuscitation. Patient was admitted to ICU and progressively recovering. At day-10, patient was stabilized and was transferred to general ward. Early vasopressor and de-resuscitation are beneficial for the patient.

Keywords: sepsis, shock, de-resuscitation, vasopressor, fluid, case report

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Authors: Pavel Adámek

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This study examines perception of environmental approach in small and medium-sized enterprises (SMEs) – the process by which firms integrate environmental concern into business. Based on a review of the literature, the paper synthesizes focus on environmental issues with the reflection in a case study in the Czech Republic. Two themes of corporate environmentalism are discussed – corporate environmental orientation and corporate stances toward environmental concerns. It provides theoretical material on greening organizational culture that is helpful in understanding the response of contemporary business to environmental problems. We integrate theoretical predictions with empirical findings confronted with reality. Scales to measure these themes are tested in a survey of managers in 229 Czech firms. We used the process of in-depth questioning. The research question was derived and answered in the context of the corresponding literature and conducted research. A case study showed us that environmental approach is variety different (depending on the size of the firm) in SMEs sector. The results of the empirical mapping demonstrate Czech company’s approach to environment and define the problem areas and pinpoint the main limitation in the expansion of environmental aspects. We contribute to the debate for recognition of the particular role of environmental issues in business reality.

Keywords: corporate environmentalism, Czech Republic, empirical mapping, environmental performance

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Authors: Zohreh Soltani, Seyedmohammadhossein Hosseinian

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Reduction of energy consumption in built infrastructure, through the installation of energy-efficient technologies, is a major approach to achieving sustainability. In practice, the viability of energy efficiency projects strongly depends on the cost reimbursement and profitability. These projects are subject to failure if the actual cost savings do not reimburse the project cost in a timely manner. In such cases, refinancing could be a solution to benefit from the long-term returns of the project if implemented wisely. However, very little is still known about the effect of refinancing options on financial performance of energy efficiency projects. To fill this gap, the present study investigates the financial behavior of energy efficiency projects with focus on refinancing options, such as Leveraged Loans. A System Dynamics (SD) model is introduced, and the model application is presented using an actual case-study data. The case study results indicate that while high-interest start-ups make using Leveraged Loan inevitable, refinancing can rescue the project and bring about profitability. This paper also presents some managerial implications of refinancing energy efficiency projects based on the case-study analysis. Results of this study help implementing financially viable energy efficiency projects, so the community could benefit from their environmental advantages widely.

Keywords: energy efficiency projects, leveraged loan, refinancing, sustainability

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Authors: M. Zafar, S. Rasheed, Imran Hashmi

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Very little is concerned about the bacterial contamination in drinking water biofilm which provide a potential source for bacteria to grow and increase rapidly. So as to understand the microbial density in DWDs, a three-month study was carried out. The aim of this study was to examine biofilm in three different pipe materials including PVC, PPR and GI. A set of all these pipe materials was installed in DWDs at nine different locations and assessed on monthly basis. Drinking water quality was evaluated by different parameters and characterization of biofilm. Among various parameters are Temperature, pH, turbidity, TDS, electrical conductivity, BOD, COD, total phosphates, total nitrates, total organic carbon (TOC) free chlorine and total chlorine, coliforms and spread plate counts (SPC) according to standard methods. Predominant species were Bacillus thuringiensis, Pseudomonas fluorescens , Staphylococcus haemolyticus, Bacillus safensis and significant increase in bacterial population was observed in PVC pipes while least in cement pipes. The quantity of DWDs bacteria was directly depended on biofilm bacteria and its increase was correlated with growth and detachment of bacteria from biofilms. Pipe material also affected the microbial community in drinking water distribution network biofilm while Similarity in bacterial species was observed between systems due to same disinfectant dose, time period and plumbing pipes.

Keywords: biofilm, DWDs, pipe material, bacterial population

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Authors: Wid Kattan, Rahaf Albarraq

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Background: Tokophobia is a pathological fear of pregnancy that can lead to the avoidance of childbirth. It is classified as primary or secondary. This report describes a patient with tokophobia, as well as her presentation, risk factors, comorbidities, and treatment. Case Presentation: A 43-year-old Saudi woman experienced tokophobia upon becoming pregnant for the fifth time. She was assessed in two clinical interviews by a consultant psychiatrist specializing in women’s mental health. In addition, she completed several questionnaires for assessment of different aspects of her mental health: overall depression, perinatal depression, generalized anxiety, maternal functioning, and fear of childbirth (FOC). Several risk factors and comorbidities that may have contributed to the development of tokophobia in this patient were discussed, including traumatic experiences in previous deliveries, the unplanned nature of the pregnancy, perinatal depression, and pronounced symptoms of anxiety. A collaborative decision to perform a C-section was made, in line with obstetric guidelines and good mental health practice. Full symptomatic recovery was achieved immediately after delivery. Conclusions: We hope to increase clinical awareness of the assessment and management of tokophobia, which is a relatively new concept and, as yet, understudied.

Keywords: tokophobia, fear of childbirth, mental health, anxiety, case report, depression, fear of delivery, psychiatry, cesarean section, perinatal depression

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Authors: W. S. Hsu, Y. Chiang, H. C. Chen, J. R. Wang, S. W. Chen, J. H. Yang, C. Shih

Abstract:

Not only radiation materials, but also the normal chemical material stored in the power plant can cause a risk to the residents. In this research, the ALOHA code was used to perform the concentration analysis under the CO₂ storage burst or leakage conditions for Kuosheng nuclear power plant (NPP). The Final Safety Analysis Report (FSAR) and data were used in this study. Additionally, the analysis results of ALOHA code were compared with the R.G. 1.78 failure criteria in order to confirm the control room habitability. The comparison results show that the ALOHA result for burst case was 0.923 g/m³ which was below the criteria. However, the ALOHA results for leakage case was 11.3 g/m³.

Keywords: BWR, ALOHA, habitability, Kuosheng

Procedia PDF Downloads 359

Authors: Farhat Sultana

Abstract:

Originality: TQM principles are considered the tools to enhance organizational performance for most organizations. The paper contributes to the literature on the social enterprise because social organizations are still far behind in implementing TQM as compared to other private, public, and nonprofit organizations. Study design: The study is based on the data and information provided by two case studies and one focus group of social enterprises. Purpose: The purpose of the study is to get a deep understating of TQM implementation and to recognize the enablers of TQM in social enterprises that enhance the organizational performance of social enterprises located in UAE. Findings: As per the findings of the study, key enablers of Total Quality management in the case enterprises are leadership support, strategic approach for quality, continuous improvement, process improvement, employee empowerment and customer focus practices, though some inhibitors for TQM implementation such as managerial structure for quality assurance and performance appraisal mechanism are also pointed out by the study. Research limitations: The study findings are only based on two case studies and one focus group, which is not enough to generalize the findings to all social organizations. Practical Implications: Identified TQM enablers can help management to implement TQM successfully in social enterprises. Social implications: The study provides enabling path for Social enterprises to implement TQM to seek quality output to build a better society.

Keywords: TQM, social enterprise, enablers of TQM, UAE

Procedia PDF Downloads 111

Authors: Syed Atif Hassan, Luv Mehta, Syed Asif Hassan

Abstract:

Hit song science is a field of investigation wherein machine learning techniques are applied to music tracks in order to extract such features from audio signals which can capture information that could explain the popularity of respective tracks. Record companies invest huge amounts of money into recruiting fresh talents and churning out new music each year. Gaining insight into the basis of why a song becomes popular will result in tremendous benefits for the music industry. This paper aims to extract basic musical and more advanced, acoustic features from songs while also taking into account external factors that play a role in making a particular song popular. We use a dataset derived from popular Spotify playlists divided by genre. We use ten genres (blues, classical, country, disco, hip-hop, jazz, metal, pop, reggae, rock), chosen on the basis of clear to ambiguous delineation in the typical sound of their genres. We feed these features into three different classifiers, namely, SVM with RBF kernel, a deep neural network, and a recurring neural network, to build separate predictive models and choosing the best performing model at the end. Predicting song popularity is particularly important for the music industry as it would allow record companies to produce better content for the masses resulting in a more competitive market.

Keywords: classifier, machine learning, music tracks, popularity, prediction

Procedia PDF Downloads 663

Authors: Bin Mu, Site Li, Shijin Yuan

Abstract:

Under the circumstance of environment deterioration, people are increasingly concerned about the quality of the environment, especially air quality. As a result, it is of great value to give accurate and timely forecast of AQI (air quality index). In order to simplify influencing factors of air quality in a city, and forecast the city’s AQI tomorrow, this study used MATLAB software and adopted the method of constructing a mathematic model of PCA-GABP to provide a solution. To be specific, this study firstly made principal component analysis (PCA) of influencing factors of AQI tomorrow including aspects of weather, industry waste gas and IAQI data today. Then, we used the back propagation neural network model (BP), which is optimized by genetic algorithm (GA), to give forecast of AQI tomorrow. In order to verify validity and accuracy of PCA-GABP model’s forecast capability. The study uses two statistical indices to evaluate AQI forecast results (normalized mean square error and fractional bias). Eventually, this study reduces mean square error by optimizing individual gene structure in genetic algorithm and adjusting the parameters of back propagation model. To conclude, the performance of the model to forecast AQI is comparatively convincing and the model is expected to take positive effect in AQI forecast in the future.

Keywords: AQI forecast, principal component analysis, genetic algorithm, back propagation neural network model

Procedia PDF Downloads 229

Authors: Olivia Rybak-Karkosz

Abstract:

This paper's purpose was to present a case study on a questioned Claude Monet's signature forensic handwriting analysis. It is an example taken from the author’s experience as a court handwriting expert. A comparative study was conducted to determine whether the signature resembles similarities (and if so, to what measure) with the features representing the writing patterns and their natural variability typical for Claude Monet. It was conducted to check whether all writing features are within the writer's normal range of variation. The paper emphasizes the difficulties and challenges encountered by the forensic handwriting expert while analysing the questioned signature.

Keywords: artist’s signatures, authenticity of an artwork, forensic handwriting analysis, graphic-comparative method

Procedia PDF Downloads 114