Search results for: robust statistic

Authors: Thanom Kaeniam

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ST-Elevation Myocardial Infarction (STEMI) is a state of sudden death of the heart muscle due to sudden blockage of the artery. STEMI patients are usually in critical condition and with a potential opportunity for sudden death. Therefore, management guidelines for safety in caring and referring STEMI patients are needed. The objective of this developmental research was to assess the effectiveness of using the guidelines for caring and referring STEMI patients at the Accident and Emergency Department of Songkhla Hospital. The subjects of the study were 22 nurses in the emergency room, and doctors on duty in the accident and emergency room selected using purposive sampling with inclusion criteria. The research instruments were the guidelines for caring and referring STEMI patients, and record forms for the effectiveness of using the guidelines for caring and referring STEMI patients (a general record form for STEMI patients, a record form for SK administering, a referring record form for PCI, and a record form for dead patient in the accident and emergency room and during referring). The instruments were tested for content validity by three experts, and the reliability was tested using Kuder-Richardson 20 (KR20). The descriptive statistic employed was the percentage. The outcomes of using the guidelines for caring and referring ST Elevation Myocardial Infarction (STEMI) Patients at the Accident and Emergency Department revealed that before using the guidelines in 2009, 2010, and 2011, there were 84, 73, and 138 STEMI patients receiving services at the accident and emergency room, of which, only 9, 32, and 48 patients were referred for PCI/SK medications, or 10.74; 43.84; and 34.78 percent, and the death rates were 10.71; 10.95; and 11.59 percent, respectively. However, after the use of the guidelines in 2012, 2013, and 2014, there were 97, 77, and 57 patients, of which, the increases to 77, 72, and 55 patients were referred for PCI /SK medications or 79.37; 93.51; and 96.49 percent, and the death rates were reduced to 10.30; 6.49; and 1.76 percent, respectively. The results of the study revealed that the use of the guidelines for caring and referring STEMI patients at the Accident and Emergency Department increased the effectiveness and quality of nursing, especially in terms of SK medication, caring and referring patients for PCI to reduce the death rate.

Keywords: outcomes, guidelines for caring, referring, myocardial infarction, STEMI

Procedia PDF Downloads 386

Authors: Bello, A., Muhammed Ibrahim Abba., Abdullahi, M., Dauda, Sabo, & Shittu, A. T.

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This study investigated the Predictors of Lecturers Knowledge Sharing Acceptance on Open Educational Resources (OER) in North-East Nigerian in Universities. The study population comprised of 632 lecturers of Federal Universities in North-east Nigeria. The study sample covered 338 lecturers who were selected purposively from Adamawa, Bauchi and Borno State Federal Universities in Nigeria. The study adopted a prediction correlational research design. The instruments used for data collection was the questionnaire. Experts in the field of educational technology validated the instrument and tested it for reliability checks using Cronbach’s alpha. The constructs on lecturers’ acceptance to share OER yielded a reliability coefficient of; α = .956 for Performance Expectancy, α = .925; for Effort Expectancy, α = .955; for Social Influence, α = .879; for Facilitating Conditions and α = .948 for acceptance to share OER. the researchers contacted the Deanery of faculties of education and enlisted local coordinators to facilitate the data collection process at each university. The data was analysed using multiple sequential regression statistic at a significance level of 0.05 using SPSS version 23.0. The findings of the study revealed that performance expectancy (β = 0.658; t = 16.001; p = 0.000), effort expectancy (β = 0.194; t = 3.802; p = 0.000), social influence (β = 0.306; t = 5.246; p = 0.000), collectively indicated that the variables have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. However, the finding revealed that facilitating conditions (β = .053; t = .899; p = 0.369), does not have a predictive capacity to stimulate lecturer’s acceptance to share their resources on OER repository. Based on these findings, the study recommends among others that the university management should consider adjusting OER policy to be centered around actualizing lecturers career progression.

Keywords: acceptance, lecturers, open educational resources, knowledge sharing

Procedia PDF Downloads 53

Authors: Arshia Aflaki, Hadis Karimipour, Anik Islam

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Generative Adversarial Attacks (GAAs) threaten critical sectors, ranging from fingerprint recognition to industrial control systems. Existing Deep Learning (DL) algorithms are not robust enough against this kind of cyber-attack. As one of the most critical industries in the world, the power grid is not an exception. In this study, a Deep Reinforcement Learning-based (DRL) framework assisting the DL model to improve the robustness of the model against generative adversarial attacks is proposed. Real-world smart grid stability data, as an IIoT dataset, test our method and improves the classification accuracy of a deep learning model from around 57 percent to 96 percent.

Keywords: generative adversarial attack, deep reinforcement learning, deep learning, IIoT, generative adversarial networks, power system

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Authors: Samir Zeghlache, Abderrahmen Bouguerra, Kamel Kara, Djamel Saigaa

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The control of the trirotor helicopter includes nonlinearities, uncertainties and external perturbations that should be considered in the design of control laws. This paper presents a control strategy for an underactuated six degrees of freedom (6 DOF) trirotor helicopter, based on the coupling of the fuzzy logic control and sliding mode control (SMC). The main purpose of this work is to eliminate the chattering phenomenon. To achieve our purpose we have used a fuzzy logic control to generate the hitting control signal, also the non linear observer is then synthesized in order to estimate the unmeasured states. Finally simulation results are included to indicate the trirotor UAV with the proposed controller can greatly alleviate the chattering effect and remain robust to the external disturbances.

Keywords: fuzzy sliding mode control, trirotor helicopter, dynamic modelling, underactuated systems

Procedia PDF Downloads 524

Authors: K. Brince Paul, Nagendra Pratap Singh, Shiv Govind Singh, Siva Rama Krishna Vanjari

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In this paper, we report optimized procedure for synthesizing highly oriented, horizontally aligned, Zinc oxide (ZnO) nanowires targeted towards developing highly sensitive piezoelectric transduction elements. The synthesis was carried out using Electrospinning technique, a facile, robust, low cost technique for producing nanowires. The as-synthesized ZnO nanowires were characterized by X-ray powder diffraction (XRD), Field Emission scanning electron microscopy (FESEM) and Energy-dispersive X-ray spectroscopy (EDX).The Piezoelectric behavior of these nanowires was characterized using Peizoelectric Force microscopy (PFM). A very high d33 coefficient of 23.1 pm/V obtained through the PFM measurements is an indicative of its potential application towards developing miniaturized piezoelectric transduction elements for nanoscale devices.

Keywords: electrospinning, piezoelectric, technique, zinc oxide

Procedia PDF Downloads 394

Authors: Sadiq J. Abou-Loukh, Hanan M. Habbi

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This paper presents a steganography to hide the transmitted information without excite suspicious and also illustrates the level of secrecy that can be increased by using cryptography techniques. The proposed system has been implemented firstly by encrypted image file one time pad key and secondly encrypted message that hidden to perform encryption followed by image embedding. Then the new image file will be created from the original image by using four triangles operation, the new image is processed by one of two image processing techniques. The proposed two processing techniques are thresholding and differential predictive coding (DPC). Afterwards, encryption or decryption keys are generated by functional key generator. The generator key is used one time only. Encrypted text will be hidden in the places that are not used for image processing and key generation system has high embedding rate (0.1875 character/pixel) for true color image (24 bit depth).

Keywords: encryption, thresholding, differential predictive coding, four triangles operation

Procedia PDF Downloads 483

Authors: Radwan Hussien Alkebsee

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Under the argument that reputational costs deter firms from engaging in tax avoidance activities, this paper investigates the relationship between tax avoidance and forced CEO turnover. This study is based on a broad sample of Chinese listed companies spanning the period 2011 to 2018. The findings reveal that tax avoidance is positively associated with forced CEO turnover. This suggests that firms that engage in tax avoidance experience a high rate of leadership replacement. The findings also reveal that the positive association between tax avoidance and forced CEO turnover is pronounced for state-owned firms, firms with no political connections, and firms located in “more developed” regions with extensive tax enforcement action, while it is not for private firms, firms with political connections, and firms located in “less developed” regions with weak tax enforcement actions. The baseline results remain consistent and robust for endogeneity concerns.

Keywords: tax avoidance, CEO turnover, political connections, regional tax enforcement, China

Procedia PDF Downloads 144

Authors: Magy Atef Awad Attia

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The objective of this study was to study the effect of social stories on social interaction of students with autism. The sample was at level 5 student with autism, Another University Demonstration School student, who was diagnosed by the Physician as High Functioning Autism since he was able to read, write, calculate and was studying in inclusive classroom. However, he still had disability in social interaction to participate in social activity group and communication. He could not learn how to develop friendship or create relationship. He had inappropriate behavior in social context. He did not understand complex social situations. In addition, he did seemed to not know time and place. He was not able to understand feeling of oneself as well as the others. Consequently, he could not express his emotion appropriately. He did not understand or express his non-verbal language for communicating with friends. He lacked of common interest or emotion with nearby persons. He greeted inappropriately or was not interested in greeting. In addition, he did not have eye contact. He used inadequate language etc. He was elected by Purposive Sampling. His parents were willing to allow them to participate in this study. The research instruments were the lesson plan of social stories, and the picture book of social stories. The instruments used for data collection, were the social interaction evaluation of autistic students. This research was Experimental Research as One Group Pre-test, Post-test Design. For the Pre-test, the experiment was conducted by social stories. Then, the Post-test was implemented. The statistic used for data analysis. The research results were shown by scale. The results revealed that the autistic students taught by social stories indicated better social reaction after being taught by social stories.

Keywords: autism, autistic behavior, stability, harsh environments, techniques, thermal, properties, materials, applications, brittleness, fragility, disadvantages, bank, branches, profitability, setting prediction, effective target, measurement, evaluation, performance, commercial, business, sustainability, financial, system.

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Authors: Precious Roselyn Obuobi

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Background: In Ghana, water-borne diseases remain a public health concern due to its impact. While marine pollution has been linked to outbreak of diseases especially in communities along the coast, associated risks such as oil spillage, marine debris, erosion, improper waste disposal and management practices persist. Objective: The study seeks to investigate sanitation practices that contribute to marine pollution in Prampram and the prevalence of selected water-borne diseases (diarrhea and typhoid fever). Method: This study used a descriptive cross-sectional design, employing the mix-method (qualitative and quantitative) approach. Twenty-two (22) participants were selected and semistructured questionnaire were administered to them. Additionally, interviews were conducted to collect more information. Further, an observation check-list was used to aid the data collection process. Secondary data comprising information on water-borne diseases in the district was acquired from the district health directorate to determine the prevalence of selected water-borne diseases in the community. Data Analysis: The qualitative data was analyzed using NVIVO® software by adapting the six steps thematic analysis by Braun and Clarke whiles STATA® version 16 was used to analyze the secondary data collected from the district health directorate. A descriptive statistic employed using mean, standard deviation, frequencies and proportions were used to summarize the results. Results: The results showed that open defecation and indiscriminate waste disposal were the main practices contributing to marine pollution in Prampram and its effect on public health. Conclusion: These findings have implications on public health and the environment, thus effort needs to be stepped up in educating the community on best sanitation practices.

Keywords: environment, sanitation, marine pollution, water-borne diseases

Procedia PDF Downloads 63

Authors: Sam Ng, Lewis Leighton, Sam Atkinson, Carson Yan, Landan Hu, Leslie Cheung, Brian Yap, Kent Lung, Ketat Sarakune

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This paper introduces a method for verifying cryptocurrency reserves that balances the need for both transparency and data confidentiality. Our methodology employs cryptographic techniques, including Merkle Trees, Bulletproof, and zkSnark, to verify that total assets equal or exceed total liabilities, represented by customer funds. Importantly, this verification is achieved without disclosing sensitive information such as the total asset value, customer count, or cold wallet addresses. We delve into the construction and implementation of this methodology. While the system is robust and scalable, we also identify areas for potential enhancements to improve its efficiency and versatility. As the digital asset landscape continues to evolve, our approach provides a solid foundation for ensuring continued trust and security in digital asset platforms.

Keywords: cryptocurrency, crypto-currency, proof-of-reserve, por, zero-knowledge, ZKP

Procedia PDF Downloads 64

Authors: Saeeda Nadir Ali, Najma Sultana, Muhammad Saeed Arayne, Amtul Qayoom

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Present study describes a simple and a fast liquid chromatographic method using ultraviolet detector for simultaneous determination of anxiety relief medicine alprazolam with ACE inhibitors i.e; lisinopril, captopril and enalapril employing purospher star C18 (25 cm, 0.46 cm, 5 µm). Separation was achieved within 5 min at ambient temperature via methanol: water (8:2 v/v) with pH adjusted to 2.9, monitoring the detector response at 220 nm. Optimum parameters were set up as per ICH (2006) guidelines. Calibration range was found out to be 0.312-10 µg mL-1 for alprazolam and 0.625-20 µg mL-1 for all the ACE inhibitors with correlation coefficients > 0.998 and detection limits 85, 37, 68 and 32 ng mL-1 for lisinopril, captopril, enalapril and alprazolam respectively. Intra-day, inter-day precision and accuracy of the assay were in acceptable range of 0.05-1.62% RSD and 98.85-100.76% recovery. Method was determined to be robust and effectively useful for the estimation of studied drugs in dosage formulations and human serum without obstruction of excipients or serum components.

Keywords: alprazolam, ACE inhibitors, RP HPLC, serum

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Authors: İsmail Karaca, Ömer Söner

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The use of advanced methods has been increasing day by day in the maritime sector, which is one of the sectors least affected by the COVID-19 pandemic. It is aimed to minimize accidents, especially by using advanced methods in the investigation of marine accidents. This research aimed to conduct an exploratory statistical analysis of particular ship accidents in the Transport Safety Investigation Center of Turkey database. 46 ship accidents, which occurred between 2010-2018, have been selected from the database. In addition to the availability of a reliable and comprehensive database, taking advantage of the robust statistical models for investigation is critical to improving the safety of ships. Thus, descriptive analysis has been used in the research to identify causes and conditional factors related to different types of ship accidents. The research outcomes underline the fact that environmental factors and day and night ratio have great influence on ship safety.

Keywords: descriptive analysis, maritime industry, maritime safety, ship accident statistics

Procedia PDF Downloads 129

Authors: Happy Zulu

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Neuropsychological examination is an important way of formally assessing brain function. While there is so much documentation about the influence that some factors, such as age and education, have on neuropsychological tests (NP), not so much has been done to assess the influence that residency (rural/urban) may have. The specific objectives of this study were to establish if there is a significant difference in mean test scores on NP tests between rural and urban participants and to assess which tests on the Zambia Neurobehavioural Test Battery (ZNTB) are more affected by the participants‘ residency (rural/urban) and to determine the extent to which education, gender, and age predict test performance on NP tests for rural and urban participants. The participants (324) were drawn from both urban and rural areas of Zambia (Rural = 152 and Urban = 172). However, only 234 participants (Rural = 152 and Urban 82) were used for all the analyses in this particular study. The 234 participants were used as the actual proportion of the rural vs urban population in Zambia was 65% : 35%, respectively (CSO, 2003). The rural-urban ratio for the participants that were captured during the data collection process was 152 : 172, respectively. Thus, all the rural participants (152) were included and 90 of the 172 urban participants were randomly excluded so that the rural/urban ratio reached the desired 65% : 35 % which was the required ideal statistic for appropriate representation of the actual population in Zambia. Data on NP tests were analyzed from 234 participants, rural (N=152) reflecting 65% and urban (N=82) reflecting 35%. T-tests indicated that urban participants had superior performances in all the seven NP test domains, and all the mean differences in all these domains were found to be statistically significant. Residency had a large or moderate effect in five domains, while its effect size was small only in two of the domains. A standard multiple regression revealed that education, age and residency as predictor variables made a significant contribution to variance in performance on various domains of the ZNTB. However, the gender of participants was not a major factor in determining one‘s performance on neuropsychological tests. This particular report is part of an ongoing, larger, cutting-edge study aimed at formulating the normative data for Zambia with regard to performance on neuropsychological tests. This is necessary for appropriate, effective, and efficient assessment or diagnosis of various neurocognitive and neurobehavioural deficits that a number of people may currently be suffering from. It has been shown in this study that it is vital to make careful analyses of the variables that may be associated with one‘s performance on neuropsychological tests.

Keywords: neuropsychology, neurobehavioural, residency, Zambia

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Authors: Florin Leon, Silvia Curteanu

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The Bacterial Foraging Optimization (BFO) algorithm is inspired by the behavior of bacteria such as Escherichia coli or Myxococcus xanthus when searching for food, more precisely the chemotaxis behavior. Bacteria perceive chemical gradients in the environment, such as nutrients, and also other individual bacteria, and move toward or in the opposite direction to those signals. The application example considered as a case study consists in establishing the dependency between the reaction yield of hydrogels based on polyacrylamide and the working conditions such as time, temperature, monomer, initiator, crosslinking agent and inclusion polymer concentrations, as well as type of the polymer added. This process is modeled with a neural network which is included in an optimization procedure based on BFO. An experimental study of BFO parameters is performed. The results show that the algorithm is quite robust and can obtain good results for diverse combinations of parameter values.

Keywords: bacterial foraging, hydrogels, modeling and optimization, neural networks

Procedia PDF Downloads 139

Authors: Masomeh Jamshid Nejad

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Nowadays, statistical literacy is no longer a necessary skill but an essential skill with broad applications across diverse fields, especially in operational decision areas such as business management, finance, and economics. As such, learning and deep understanding of statistical concepts are essential in the context of business studies. One of the crucial topics in statistical theory and its application is the normal distribution, often called a bell-shaped curve. To interpret data and conduct hypothesis tests, comprehending the properties of normal distribution (the mean and standard deviation) is essential for business students. This requires undergraduate students in the field of economics and business management to visualize and work with data following a normal distribution. Since technology is interconnected with education these days, it is important to teach statistics topics in the context of Python, R-studio, and Microsoft Excel to undergraduate students. This research endeavours to shed light on the effect of Excel-based instruction on learners’ knowledge of statistics, specifically the central concept of normal distribution. As such, two groups of undergraduate students (from the Business Management program) were compared in this research study. One group underwent Excel-based instruction and another group relied only on traditional teaching methods. We analyzed experiential data and BBA participants’ responses to statistic-related questions focusing on the normal distribution, including its key attributes, such as the mean and standard deviation. The results of our study indicate that exposing students to Excel-based learning supports learners in comprehending statistical concepts more effectively compared with the other group of learners (teaching with the traditional method). In addition, students in the context of Excel-based instruction showed ability in picturing and interpreting data concentrated on normal distribution.

Keywords: statistics, excel-based instruction, data visualization, pedagogy

Procedia PDF Downloads 46

Authors: Purevdolgor Luvsantseren, Ajnai Luvsan-Ish, Oyuntsetseg Sandag, Javzmaa Tsend, Akhit Tileubai, Baasandorj Chilhaasuren, Jargalbat Puntsagdash, Galbadrakh Chuluunbaatar

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One of the indicators of the quality of university services is student satisfaction. Aim: We aimed to study the level of satisfaction of students in the first year of premedical courses in the course of Medical Physics using the cluster method. Materials and Methods: In the framework of this goal, a questionnaire was collected from a total of 324 students who studied the medical physics course of the 1st course of the premedical course at the Mongolian National University of Medical Sciences. When determining the level of satisfaction, the answers were obtained on five levels of satisfaction: "excellent", "good", "medium", "bad" and "very bad". A total of 39 questionnaires were collected from students: 8 for course evaluation, 19 for teacher evaluation, and 12 for student evaluation. From the research, a database with 39 fields and 324 records was created. Results: In this database, cluster analysis was performed in MATLAB and R programs using the k-means method of data mining. Calculated the Hopkins statistic in the created database, the values are 0.88, 0.87, and 0.97. This shows that cluster analysis methods can be used. The course evaluation sub-fund is divided into three clusters. Among them, cluster I has 150 objects with a "good" rating of 46.2%, cluster II has 119 objects with a "medium" rating of 36.7%, and Cluster III has 54 objects with a "good" rating of 16.6%. The teacher evaluation sub-base into three clusters, there are 179 objects with a "good" rating of 55.2% in cluster II, 108 objects with an "average" rating of 33.3% in cluster III, and 36 objects with an "excellent" rating in cluster I of 11.1%. The sub-base of student evaluations is divided into two clusters: cluster II has 215 objects with an "excellent" rating of 66.3%, and cluster I has 108 objects with an "excellent" rating of 33.3%. Evaluating the resulting clusters with the Silhouette coefficient, 0.32 for the course evaluation cluster, 0.31 for the teacher evaluation cluster, and 0.30 for student evaluation show statistical significance. Conclusion: Finally, to conclude, cluster analysis in the model of the medical physics lesson “good” - 46.2%, “middle” - 36.7%, “bad” - 16.6%; 55.2% - “good”, 33.3% - “middle”, 11.1% - “bad” in the teacher evaluation model; 66.3% - “good” and 33.3% of “bad” in the student evaluation model.

Keywords: questionnaire, data mining, k-means method, silhouette coefficient

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Authors: Sunsoo Kim, Niladri Das, Raktim Bhattacharya

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This paper addresses modeling and control of a six-degree-of-freedom unmanned aerial vehicle capable of vertical take-off and landing in the presence of wind disturbances. We design a hybrid vehicle that combines the benefits of both the fixed-wing and the rotary-wing UAVs. A non-linear model for the hybrid vehicle is rapidly built, combining rigid body dynamics, aerodynamics of wing, and dynamics of the motor and propeller. Further, we design a H₂ optimal controller to make the UAV robust to wind disturbances. We compare its results against that of proportional-integral-derivative and linear-quadratic regulator based control. Our proposed controller results in better performance in terms of root mean squared errors and time responses during two scenarios: hover and level- flight.

Keywords: hybrid UAVs, VTOL, aircraft modeling, H2 optimal control, wind disturbances

Procedia PDF Downloads 142

Authors: W. Hasan, H. Farhat, A. Alhilo, L. Tamimi

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Oil in water (O/W) emulsions are utilized extensively for cooling and lubricating cutting tools during parts machining. A robust Lattice Boltzmann (LBM) thermal-surfactants model, which provides a useful platform for exploring complex emulsions’ characteristics under variety of flow conditions, is used here for the study of the fluid behavior during conventional tools cooling. The transient thermal capabilities of the model are employed for simulating the effects of the flow conditions of O/W emulsions on the cooling of cutting tools. The model results show that the temperature outcome is slightly affected by reversing the direction of upper plate (workpiece). On the other hand, an important increase in effective viscosity is seen which supports better lubrication during the work.

Keywords: hybrid lattice Boltzmann method, Gunstensen model, thermal, surfactant-covered droplet, Marangoni stress

Procedia PDF Downloads 294

Authors: Tarun Chand, Michael Jurczyk

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With the increasing need and popularity of IoT devices and how integrated they are becoming in our daily lives and industries, these devices make for a very lucrative target for malicious actors. And since these devices have such limited resources, the implementation of robust security features is a tradeoff to be made for the actual functionality the device was intended for. This makes them an easy target with high returns. Several frameworks for the secure firmware update of these devices have been recently proposed in the literature. They focus on methods such as blockchains and distributed file systems to secure firmware updates, but do not go into the details of the actual implementation of these frameworks and the lower-level interactions among these methods used. This work integrates some of these security measures into one overall framework and details the actual lower-level implementation of this framework in a virtual dockerized testbed running on AWS.

Keywords: blockchain, Ethereum, Geth, IPFS, secure IoT-firmware update, virtual testbed development

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Authors: Sarah Odofin, Zhiwei Gao, Sun Kai

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Operations, maintenance and reliability of wind turbines have received much attention over the years due to rapid expansion of wind farms. This paper explores early fault diagnosis scale technique based on a unique scheme of a 5MW wind turbine system that is optimized by genetic algorithm to be very sensitive to faults and resilient to disturbances. A quantitative model based analysis is pragmatic for primary fault diagnosis monitoring assessment to minimize downtime mostly caused by components breakdown and exploit productivity consistency. Simulation results are computed validating the wind turbine model which demonstrates system performance in a practical application of fault type examples. The results show the satisfactory effectiveness of the applied performance investigated in a Matlab/Simulink/Gatool environment.

Keywords: disturbance robustness, fault monitoring and detection, genetic algorithm, observer technique

Procedia PDF Downloads 369

Authors: Kyu Chul Lee, Sung Hyun Yoo, Choon Ki Ahn, Myo Taeg Lim

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Recent experimental evidences have shown that because of a fast convergence and a nice accuracy, neural networks training via extended Kalman filter (EKF) method is widely applied. However, as to an uncertainty of the system dynamics or modeling error, the performance of the method is unreliable. In order to overcome this problem in this paper, a new finite impulse response (FIR) filter based learning algorithm is proposed to train radial basis function neural networks (RBFN) for nonlinear function approximation. Compared to the EKF training method, the proposed FIR filter training method is more robust to those environmental conditions. Furthermore, the number of centers will be considered since it affects the performance of approximation.

Keywords: extended Kalman filter, classification problem, radial basis function networks (RBFN), finite impulse response (FIR) filter

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Authors: Leila Khosravi

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A major part of the drinking water in North West of Iran is supplied from Mahabad reservoir 80 km northwest of Mahabad. This reservoir collects water from 750 km-catchment which is undergoing accelerated changes due to deforestation and urbanization. The main objective of this study is to develop a catchment modeling platform which translates ongoing land-use changes, soil data, precipitation and evaporation into surface runoff of the river discharging into the reservoir: Soil and Water Assessment Tool, SWAT, model along with hydro -meteorological records of 1997–2011. A variety of statistical indices were used to evaluate the simulation results for both calibration and validation periods; among them, the robust Nash–Sutcliffe coefficients were found to be 0.52 and 0.62 in the calibration and validation periods, respectively. This project has developed a reliable modeling platform with the benchmark land physical conditions of the Mahabad dam basin.

Keywords: simulation, surface runoff, Mahabad dam, SWAT model

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Authors: Hugo d’Albert, Udo Lindemann

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The number of automotive electronic systems that allow realizing new functions, like driver assistance systems, has been increasing extremely in the last decade. Although they bring several benefits, their malfunctions can lead to severe consequences, such as personal injury of road users. Functional safety is an approach to identify these critical malfunctions and arrange technical systems that include only tolerable risk. This approach is– in comparison with other technical areas– relatively new in the automotive sector. For a long time, the automotive systems have based on mechanical components and approved principles, like robust design. With a growing number of electric and electronic components in the modern cars and realizing by software of the system functions, the need for new standards and methods to assure the functional safety has arisen. This paper described the current state of engineering for safety in automotive sector and discusses new directions to meet the challenges of the future.

Keywords: automotive systems, functional safety, quality engineering, quality management

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Authors: Carlos Gonzalez-Flores, Ernesto Liñan-García

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A simple and robust approach for developing secure software. A Four Phase methodology consists in developing the non-secure software in phase one, and for the next three phases, one phase for each of the secure developing types (i.e. self-protected software, secure code transformation, and the secure shield). Our methodology requires first the determination and understanding of the type of security level needed for the software. The methodology proposes the use of several teams to accomplish this task. One Software Engineering Developing Team, a Compiler Team, a Specification and Requirements Testing Team, and for each of the secure software developing types: three teams of Secure Software Developing, three teams of Code Breakers, and three teams of Intrusion Analysis. These teams will interact among each other and make decisions to provide a secure software code protected against a required level of intruder.

Keywords: secure software, four phases methodology, software engineering, code breakers, intrusion analysis

Procedia PDF Downloads 386

Authors: Mengke Zhan, Cheng-Gang Xie, Jian-Jun Shu

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A venturi flowmeter is a common device used in multiphase flow rate measurement in the upstream oil and gas industry. Having a robust computational model for multiphase flow in a venturi is desirable for understanding the gas-liquid and fluid-pipe interactions and predicting pressure and phase distributions under various flow conditions. A steady Eulerian-Eulerian framework is used to simulate upward gas-liquid flow in a vertical venturi. The simulation results are compared with experimental measurements of venturi differential pressure and chord-averaged gas holdup in the venturi throat section. The choice of turbulence model is nontrivial in the multiphase flow modelling in a venturi. The performance cross-comparison of the k-ϵ model, Reynolds stress model (RSM) and shear-stress transport (SST) k-ω turbulence model is made in the study. In terms of accuracy and computational cost, the SST k-ω turbulence model is observed to be the most efficient.

Keywords: computational fluid dynamics (CFD), gas-liquid flow, turbulence modelling, venturi

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Authors: Paul W. Murray, Marco Barajas

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Recent changes in supply chains, especially globalization and collaboration, have created new risks for enterprises of all sizes. A variety of complex frameworks, often based on enterprise risk management strategies have been presented under the heading of Supply Chain Risk Management (SCRM). The literature on promotes the benefits of a robust SCRM strategy; however, implementing SCRM is difficult and resource demanding for Large Enterprises (LEs), and essentially out of reach for Small and Medium Enterprises (SMEs). This research debunks the idea that SCRM is necessary for all enterprises and instead proposes a simple and effective Vendor Selection Template (VST). Empirical testing and a survey of supply chain practitioners provide a measure of validation to the VST. The resulting VSTis a valuable contribution because is easy to use, provides practical results, and is sufficiently flexible to be universally applied to SMEs.

Keywords: multiple regression analysis, supply chain management, risk assessment, vendor selection

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Authors: Hyun-Woo Cho

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The detection and identification of multivariate manufacturing processes are quite important in order to maintain good product quality. Unusual behaviors or events encountered during its operation can have a serious impact on the process and product quality. Thus they should be detected and identified as soon as possible. This paper focused on the efficient representation of process measurement data in detecting and identifying abnormalities. This qualitative method is effective in representing fault patterns of process data. In addition, it is quite sensitive to measurement noise so that reliable outcomes can be obtained. To evaluate its performance a simulation process was utilized, and the effect of adopting linear and nonlinear methods in the detection and identification was tested with different simulation data. It has shown that the use of a nonlinear technique produced more satisfactory and more robust results for the simulation data sets. This monitoring framework can help operating personnel to detect the occurrence of process abnormalities and identify their assignable causes in an on-line or real-time basis.

Keywords: detection, monitoring, identification, measurement data, multivariate techniques

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Authors: Pasala Gopi, P. Linga Reddy

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The response of the load frequency control problem in an multi-area interconnected electrical power system is much more complex with increasing size, changing structure and increasing load. This paper deals with Load Frequency Control of three area interconnected Power system incorporating Reheat, Non-reheat and Reheat turbines in all areas respectively. The response of the load frequency control problem in an multi-area interconnected power system is improved by designing PID controller using different tuning techniques and proved that the PID controller which was designed by Simulink Design Optimization (SDO) Software gives the superior performance than other controllers for step perturbations. Finally the robustness of controller was checked against system parameter variations

Keywords: load frequency control, pid controller tuning, step load perturbations, inter connected power system

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Authors: Eman I. Raslan, Haitham S. Hamza, Reda A. El-Khoribi

Abstract:

Fiber-Wireless (FiWi) networks are a promising candidate for future broadband access networks. These networks combine the optical network as the back end where different passive optical network (PON) technologies are realized and the wireless network as the front end where different wireless technologies are adopted, e.g. LTE, WiMAX, Wi-Fi, and Wireless Mesh Networks (WMNs). The convergence of both optical and wireless technologies requires designing architectures with robust efficient and effective bandwidth allocation schemes. Different bandwidth allocation algorithms have been proposed in FiWi networks aiming to enhance the different segments of FiWi networks including wireless and optical subnetworks. In this survey, we focus on the differentiating between the different bandwidth allocation algorithms according to their enhancement segment of FiWi networks. We classify these techniques into wireless, optical and Hybrid bandwidth allocation techniques.

Keywords: fiber-wireless (FiWi), dynamic bandwidth allocation (DBA), passive optical networks (PON), media access control (MAC)

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Authors: Sourita Ghosh, Falguni Pati, Suhanya Duraiswamy

Abstract:

Spheroid, a simple three-dimensional cellular aggregate, allows us to simulate the in-vivo complexity of cellular signaling and interactions in greater detail than traditional 2D cell culture. It can be used as an in-vitro model for drug toxicity testing, tumor modeling and many other such applications specifically for cancer. Our work is focused on the development of an affordable, user-friendly, robust, reproducible, high throughput microfluidic device for water in oil droplet production, which can, in turn, be used for spheroids manufacturing. Here, we have investigated the droplet breakup between two non-Newtonian fluids, viz. silicone oil and decellularized liver matrix, which acts as our extra cellular matrix (ECM) for spheroids formation. We performed some biochemical assays to characterize the liver ECM, as well as rheological studies on our two fluids and observed a critical dependence of capillary number (Ca) on droplet breakup and homogeneous drop formation

Keywords: chip less, droplets, extracellular matrix, liver spheroid

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