Search results for: bearing degradation data

Authors: Syed Zameer, Mohamed Haneef

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Hip joint plays very important role in human beings as it takes up the whole body forces generated due to various activities. These loads are repetitive and fluctuating depending on the activities such as standing, sitting, jogging, stair casing, climbing, etc. which may lead to failure of Hip joint. Hip joint modification and replacement are common in old aged persons as well as younger persons. In this research study static and Fatigue analysis of Hip joint model was carried out using finite element software ANSYS. Stress distribution obtained from result of static analysis, material properties and S-N curve data of fabricated Ultra High molecular weight polyethylene / 50 wt% short E glass fibres + 40 wt% TiO2 Polymer matrix composites specimens were used to estimate fatigue life of Hip joint using stiffness Degradation model for polymer matrix composites. The stress distribution obtained from static analysis was found to be within the acceptable range.The factor of safety calculated from linear Palmgren linear damage rule is less than one, which indicates the component is safe under the design.

Keywords: hip joint, polymer matrix composite, static analysis, fatigue analysis, stress life approach

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Authors: Lakshmi Prayaga, Chandra Prayaga. Aaron Wade, Gopi Shankar Mallu, Harsha Satya Pola

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Synthetic data generated by Generative Adversarial Networks and Autoencoders is becoming more common to combat the problem of insufficient data for research purposes. However, generating synthetic data is a tedious task requiring extensive mathematical and programming background. Open-source platforms such as the Synthetic Data Vault (SDV) and Mostly AI have offered a platform that is user-friendly and accessible to non-technical professionals to generate synthetic data to augment existing data for further analysis. The SDV also provides for additions to the generic GAN, such as the Gaussian copula. We present the results from two synthetic data sets (CTGAN data and CTGAN with Gaussian Copula) generated by the SDV and report the findings. The results indicate that the ROC and AUC curves for the data generated by adding the layer of Gaussian copula are much higher than the data generated by the CTGAN.

Keywords: synthetic data generation, generative adversarial networks, conditional tabular GAN, Gaussian copula

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Authors: Tobias Schramm, Günther Prokop

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In Germany, the number of road fatalities has been falling since 2010 at a more moderate rate than before. At the same time, the average age of all registered passenger cars in Germany is rising continuously. Studies show that there is a correlation between the age and mileage of passenger cars and the degradation of their chassis components. Various studies show that degraded shock absorbers increase the braking distance of passenger cars and have a negative impact on driving stability. The exact effect of degraded vehicle shock absorbers on road safety is still the subject of research. A shock absorber examination as part of the periodic technical inspection is only mandatory in very few countries. In Germany, there is as yet no requirement for such a shock absorber examination. More comprehensive findings on the effect of degraded shock absorbers on the safety-critical driving dynamics of passenger cars can provide further arguments for the introduction of mandatory shock absorber testing as part of the periodic technical inspection. The specific effect chains of untripped rollover accidents are also still the subject of research. However, current research results show that the high proportion of sport utility vehicles in the vehicle field significantly increases the probability of untripped rollover accidents. The aim of this work is to estimate the effect of degraded twin-tube shock absorbers on the safety-critical tipping and rolling behaviour of passenger cars, which can lead to untripped rollover accidents. A characteristic curve-based five-mass full vehicle model and a semi-physical phenomenological shock absorber model were set up, parameterized and validated. The shock absorber model is able to reproduce the damping characteristics of vehicle twin-tube shock absorbers with oil and gas loss for various excitations. The full vehicle model was validated with steering wheel angle sinus sweep driving maneuvers. The model was then used to simulate steering wheel angle sine and fishhook maneuvers, which investigate the safety-critical tipping and rolling behavior of passenger cars. The simulations were carried out in a realistic parameter space in order to demonstrate the effect of various vehicle characteristics on the effect of degraded shock absorbers. As a result, it was shown that degraded shock absorbers have a negative effect on the tipping and rolling behavior of all passenger cars. Shock absorber degradation leads to a significant increase in the observed roll angles, particularly in the range of the roll natural frequency. This superelevation has a negative effect on the wheel load distribution during the driving maneuvers investigated. In particular, the height of the vehicle's center of gravity and the stabilizer stiffness of the vehicles has a major influence on the effect of degraded shock absorbers on the overturning and rolling behaviour of passenger cars.

Keywords: numerical simulation, safety-critical driving dynamics, suspension degradation, tipping and rolling behavior of passenger cars, vehicle shock absorber

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Authors: Desere Kokt

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Hospitality establishments worldwide are bearing the brunt of the effects of Covid-19. As the hospitality industry is looking to recover, emphasis is placed on rejuvenating the industry. This is especially pertinent for economic development in areas of high unemployment, such as the Free State province of South Africa. The province is not a main tourist area and thus depends on the influx of tourists. The province has great scenic beauty with many accommodation establishments that provide job opportunities to the local population. The two main economic hubs of the Free State province namely Bloemfontein and Clarens, were the focus of the investigation. The emphasis was on graded accommodation establishments as they must adhere to the quality principles of the Tourism Grading Council of South Africa (TGCSA) to obtain star grading. The hospitality industry is known for being labour intensive, and employees need to be available to cater for the needs of paying customers. This is referred to as ‘emotional labour’ and implies that employees need to manage their feelings and emotions as part of performing their jobs. The focus of this study was thus on psychological factors related to working in the hospitality industry – specifically psychological contract and psychological capital and its impact on the commitment of employees in graded accommodation establishments. Employee commitment can be explained as a psychological state that binds the individual to the organisation and involves a set of psychological relationships that include affective (emotions), normative (perceived obligation) and continuance (staying with the organisation) dimensions. Psychological contract refers to the reciprocal beliefs and expectations between the employer and the employee and consists of transactional and rational contracts. Transactional contracts are associated with the economic exchange, and contractional issues related to the employment contract and rational contracts relate to the social exchange between the employee and the organisation. Psychological capital refers to an individual’s positive psychology state of development that is characterised by self-efficiency (having confidence in doing one’s job), optimism (being positive and persevering towards achieving one’s goals), hope (expectations for goals to succeed) and resilience (bouncing back to attain success when beset by problems and adversity). The study employed a quantitative research approach, and a structured questionnaire was used to gather data from respondents. The study was conducted during the Covid-19 pandemic, which hampered the data gathering efforts of the researchers. Many accommodation establishments were either closed or temporarily closed, which meant that data gathering was an intensive and laborious process. The main researcher travelled to the various establishments to collect the data. Nine hospitality establishments participated in the study, and around 150 employees were targeted for data collection. Ninety-two (92) questionnaires were completed, which represents a response rate of 61%. Data were analysed using descriptive and inferential statistics, and partial least squares structural equation modelling (PLS-SEM) was applied to examine the relationship between the variables.

Keywords: employee commitment, hospitality industry, psychological contract, psychological capital

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Authors: Matej Buzgo, Erico Himawan, Ksenija JašIna, Aiva Simaite

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Electrospinning is a versatile and efficient technology for producing nanofibers for biomedical applications. One of the most common polymers used for the preparation of nanofibers for regenerative medicine and drug delivery applications is polycaprolactone (PCL). PCL is a biocompatible and bioabsorbable material that can be used to stimulate the regeneration of various tissues. It is also a common material used for the development of drug delivery systems by blending the polymer with small active molecules. However, for many drug delivery applications, e.g. cancer immunotherapy, PCL biodegradation rate that may exceed 9 months is too long, and faster nanofiber dissolution is needed. In this paper, we investigate the dissolution and small molecule release rates of PCL blends with two hydrophilic polymers: polyethylene oxide (PEO) or polyvinylpyrrolidone (PVP). We show that adding hydrophilic polymer to the PCL reduces the water contact angle, increases the dissolution rate, and strengthens the interactions between the hydrophilic drug and polymer matrix that further sustain its release. Finally using this method, we were also able to increase the nanofiber degradation rate when PCL-PEO and PCL-PVP were used as a shell in the electrospun core-shell nanofibers and spread up the release of active proteins from their core. Electrospinning can be used for the preparation of the core-shell nanofibers, where active ingredients are encapsulated in the core and their release rate is regulated by the shell. However, such fibers are usually prepared by coaxial electrospinning that is an extremely low-throughput technique. An alternative is emulsion electrospinning that could be upscaled using needleless blades. In this work, we investigate the possibility of using emulsion electrospinning for encapsulation and sustained release of the growth factors for the development of the organotypic skin models. The core-shell nanofibers were prepared using the optimized formulation and the release rate of proteins from the fibers was investigated for 2 weeks – typical cell culture conditions.

Keywords: electrospinning, polycaprolactone (PCL), polyethylene oxide (PEO), polyvinylpyrrolidone (PVP)

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Authors: Feng Tao, Ma Jing, Guo Xian, Wang Jing

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Named Data Networking (NDN) replaces IP address of traditional network with data name, and adopts dynamic cache mechanism. In the existing mechanism, however, only one-to-one search can be achieved because every data has a unique name corresponding to it. There is a certain mapping relationship between data content and data name, so if the data name is intercepted by an adversary, the privacy of the data content and user’s interest can hardly be guaranteed. In order to solve this problem, this paper proposes a one-to-many fuzzy search scheme based on order-preserving encryption to reduce the query overhead by optimizing the caching strategy. In this scheme, we use hash value to ensure the user’s query safe from each node in the process of search, so does the privacy of the requiring data content.

Keywords: NDN, order-preserving encryption, fuzzy search, privacy

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Authors: Dila Ram Bhandari

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Throughout the 20th century, new governments were created where identities such as ethnic, religious, linguistic, caste, communal, tribal, and others played a part in the development of constitutions and the legal system of victim and criminal justice. Acute issues with extremism, poverty, environmental degradation, cybercrimes, human rights violations, crime against, and victimization of both individuals and groups have recently plagued South Asian nations. Everyday massive number of crimes are steadfast, these frequent crimes have made the lives of common citizens restless. Crimes are one of the major threats to society and also for civilization. Crime is a bone of contention that can create a societal disturbance. The old-style crime solving practices are unable to live up to the requirement of existing crime situations. Crime analysis is one of the most important activities of the majority of intelligent and law enforcement organizations all over the world. The South Asia region lacks such a regional coordination mechanism, unlike central Asia of Asia Pacific regions, to facilitate criminal intelligence sharing and operational coordination related to organized crime, including illicit drug trafficking and money laundering. There have been numerous conversations in recent years about using data mining technology to combat crime and terrorism. The Data Detective program from Sentient as a software company, uses data mining techniques to support the police (Sentient, 2017). The goals of this internship are to test out several predictive model solutions and choose the most effective and promising one. First, extensive literature reviews on data mining, crime analysis, and crime data mining were conducted. Sentient offered a 7-year archive of crime statistics that were daily aggregated to produce a univariate dataset. Moreover, a daily incidence type aggregation was performed to produce a multivariate dataset. Each solution's forecast period lasted seven days. Statistical models and neural network models were the two main groups into which the experiments were split. For the crime data, neural networks fared better than statistical models. This study gives a general review of the applied statistics and neural network models. A detailed image of each model's performance on the available data and generalizability is provided by a comparative analysis of all the models on a comparable dataset. Obviously, the studies demonstrated that, in comparison to other models, Gated Recurrent Units (GRU) produced greater prediction. The crime records of 2005-2019 which was collected from Nepal Police headquarter and analysed by R programming. In conclusion, gated recurrent unit implementation could give benefit to police in predicting crime. Hence, time series analysis using GRU could be a prospective additional feature in Data Detective.

Keywords: time series analysis, forecasting, ARIMA, machine learning

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Authors: Anik Barua, Rabiul Hossain, Labonno Barua, Rashadul Hossain, Nurul Absar

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Background: Globally, the burden of cancer is increasing consistently. Modern cancer therapies include lots of toxicity in the non-targeted organs reducing the life expectancy of the patients. Hence, scientists are trying to seek noble compounds from natural sources to treat cancer. Objectives: The objectives of the present study are to evaluate the phytochemicals, in vitro antioxidants, and in vivo and in silico anticancer study of various solvent fractions of Tinospora cordifolia (Willd.). Methodology: In this experiment, standard quantitative and qualitative assay methods were used to analyze the phytochemicals. The antioxidant activity was measured using the DPPH and ABTS scavenging methods. The in vivo antitumor activity is evaluated against Ehrlich ascites carcinoma (EAC) cell bearing in Swiss albino mice. In-silico ADME/T and molecular docking study were performed to assess the potential of stated phytochemicals against Transcription Factor STAT3b/DNA Complex of adenocarcinoma. Findings: Phytochemical screening confirmed the presence of flavonoids, alkaloids, glycosides, tannins, and carbohydrates. A significant amount of phenolic (20.19±0.3 mg/g GAE) and flavonoids (9.46±0.18 mg/g GAE) were found in methanolic extract in quantitative screening. Tinospora cordifolia methanolic extract showed promising DPPH and ABTS scavenging activity with the IC50 value of 1222.99 µg/mL and 1534.34 µg/mL, respectively, which was concentration dependent. In vivo anticancer activity in EAC cell-bearing mice showed significant (P < 0.05) percent inhibition of cell growth (60.12±1.22) was found at the highest dose compared with standard drug 5-Fluorouracil (81.18±1.28). Forty-two phytochemicals exhibit notable pharmacokinetics properties and passed drug-likeness screening tests in silico. In molecular docking study, (25S)-3Beta-acetoxy-5-alpha-22-beta-spirost-9(11)-en-12-beta-ol showed docking score (-8.5 kJ/mol) with significant non-bonding interactions with target enzyme. Conclusions: The results were found to be significant and confirmed that the methanolic extract of Tinospora cordifolia has remarkable antitumor activity with antioxidant potential. The Tinospora cordifolia methanolic extract may be considered a potent anticancer agent for advanced research.

Keywords: anticancer, antioxidant, Tinospora cordifolia, EAC cell

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Authors: Chellammal Surianarayanan

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Healthcare industry is generating large amounts of data driven by various needs such as record keeping, physician’s prescription, medical imaging, sensor data, Electronic Patient Record(EPR), laboratory, pharmacy, etc. Healthcare data is so big and complex that they cannot be managed by conventional hardware and software. The complexity of healthcare big data arises from large volume of data, the velocity with which the data is accumulated and different varieties such as structured, semi-structured and unstructured nature of data. Despite the complexity of big data, if the trends and patterns that exist within the big data are uncovered and analyzed, higher quality healthcare at lower cost can be provided. Hadoop is an open source software framework for distributed processing of large data sets across clusters of commodity hardware using a simple programming model. The core components of Hadoop include Hadoop Distributed File System which offers way to store large amount of data across multiple machines and MapReduce which offers way to process large data sets with a parallel, distributed algorithm on a cluster. Hadoop ecosystem also includes various other tools such as Hive (a SQL-like query language), Pig (a higher level query language for MapReduce), Hbase(a columnar data store), etc. In this paper an analysis has been done as how healthcare big data can be processed and analyzed using Hadoop ecosystem.

Keywords: big data analytics, Hadoop, healthcare data, towards quality healthcare

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Authors: Yanné Etienne

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The current climatic conditions necessarily impose the development and use of construction materials with low or no carbon footprint. The Far North Region of Cameroon has huge deposits of termite mounds. Various tests in this work have been carried out on these soils with the aim of using them as construction materials. They are mainly geotechnical tests, physical and mechanical tests. The different tests gave the following values: uniformity coefficient (4.95), curvature coefficient (1.80), plasticity index (12.85%), optimum moisture content (6.70%), maximum dry density (2.05 g.cm-³), friction angles (14.07°), and cohesion of 100.29 kN.m2. The results obtained show that termite mound soils, which are ecological materials, are plastic and water-stable can be used for the production of load-bearing elements in construction.

Keywords: termite mound soil, ecological materials, building materials, geotechnical tests, physical and mechanical tests

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Authors: Teodrose Atnafu Abegaze, P. K. Sharma

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In this study, an attempt has been made to study the behavior of breakthrough curves in both layered and mixed heterogeneous soil by conducting experiments in long soil columns. Sodium chloride has been used as a conservative tracer in the experiment. Advective dispersive transport equations, including equilibrium sorption and first-order degradation coefficients, are used for solute transport through mobile-immobile porous media. In order to do the governing equation for solute transport, there are explicit and implicit schemes for our condition; we use an implicit scheme to numerically model the solute concentration. Results of experimental breakthrough curves indicate that the behavior of observed breakthrough curves is approximately similar in both cases of layered and mixed soil, while earlier arrival of solute concentration is obtained in the case of mixed soil. It means that the types of heterogeneity of the soil media affect the behavior of solute concentration. Finally, it is also shown that the asymptotic dispersion model simulates the experimental data better than the constant and linear distance-dependent dispersion models.

Keywords: numerical method, distance dependant dispersion, reactive transport, experiment

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Authors: Zakieh Piri, Shahla Damanabi, Peyman Rezaii Hachesoo

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Introduction: Healthcare organizations like other organizations suffer from a number of disorders such as Business Sponsor Disorder, Business Acceptance Disorder, Cultural/Political Disorder, Data Disorder, etc. As quality in healthcare care mostly depends on the quality of data, we aimed to identify data disorders and its symptoms in two teaching hospitals. Methods: Using a self-constructed questionnaire, we asked 20 questions in related to quality and usability of patient data stored in patient records. Research population consisted of 150 managers, physicians, nurses, medical record staff who were working at the time of study. We also asked their views about the symptoms and treatments for any data disorders they mentioned in the questionnaire. Using qualitative methods we analyzed the answers. Results: After classifying the answers, we found six main data disorders: incomplete data, missed data, late data, blurred data, manipulated data, illegible data. The majority of participants believed in their important roles in treatment of data disorders while others believed in health system problems. Discussion: As clinicians have important roles in producing of data, they can easily identify symptoms and disorders of patient data. Health information managers can also play important roles in early detection of data disorders by proactively monitoring and periodic check-ups of data.

Keywords: data disorders, quality, healthcare, treatment

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Authors: Byron Joseph A. Hallar, Annjeannette Alain D. Galang, Maria Visitacion N. Gumabay

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One of the unique challenges provided by the twenty-first century to Philippine higher education is the utilization of Big Data. The higher education system in the Philippines is generating burgeoning amounts of data that contains relevant data that can be used to generate the information and knowledge needed for accurate data-driven decision making. This study examines the status, relevance and future of Big Data and Analytics in Philippine higher education. The insights gained from the study may be relevant to other developing nations similarly situated as the Philippines.

Keywords: big data, data analytics, higher education, republic of the philippines, assessment

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Authors: Paolo Boscaro, Vasile Hulea, François Fajula, Francis Luck, Anne Galarneau

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TiO2 based monoliths with hierarchical macropores and mesopores have been synthesized following a novel one pot sol-gel synthesis method. Taking advantage of spinodal separation that occurs between titanium isopropoxide and an acidic solution in presence of polyethylene oxide polymer, monoliths with homogeneous interconnected macropres of 3 μm in diameter and mesopores of ca. 6 nm (surface area 150 m2/g) are obtained. Furthermore, these monoliths present some carbon and nitrogen (as shown by XPS and elemental analysis), which considerably reduce titanium oxide energy gap and enable light to be absorbed up to 700 nm wavelength. XRD shows that anatase is the dominant phase with a small amount of brookite. Enhanced light absorption and high porosity of the monoliths are responsible for a remarkable photocatalytic activity. Wastewater treatment has been performed in closed reactor under sunlight using orange G dye as target molecule. Glass reactors guarantee that most of UV radiations (to almost 300 nm) of solar spectrum are excluded. TiO2 nanoparticles P25 (usually used in photocatalysis under UV) and un-doped TiO2 monoliths with similar porosity were used as comparison. C,N-doped TiO2 monolith allowed a complete colorant degradation in less than 1 hour, whereas 10 h are necessary for 40% colorant degradation with P25 and un-doped monolith. Experiment performed in the dark shows that only 3% of molecules have been adsorbed in the C,N-doped TiO2 monolith within 1 hour. The much higher efficiency of C,N-doped TiO2 monolith in comparison to P25 and un-doped monolith, proves that doping TiO2 is an essential issue and that nitrogen and carbon are effective dopants. Monoliths offer multiples advantages in respect to nanometric powders: sample can be easily removed from batch (no needs to filter or to centrifuge). Moreover flow reactions can be set up with cylindrical or flat monoliths by simple sheathing or by locking them with O-rings.

Keywords: C-N doped, sunlight photocatalytic activity, TiO2 monolith, visible absorbance

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Authors: G. Julius P. Roy, Prateek Saxena, Sanjeev Singh

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Power distribution utilities two decades ago would collect data from its customers not later than a period of at least one month. The origin of SmartGrid and AMI has subsequently increased the sampling frequency leading to 1000 to 10000 fold increase in data quantity. This increase is notable and this steered to coin the tern Big Data in utilities. Power distribution industry is one of the largest to handle huge and complex data for keeping history and also to turn the data in to significance. Majority of the utilities around the globe are adopting SmartGrid technologies as a mass implementation and are primarily focusing on strategic interdependence and synergies of the big data coming from new information sources like AMI and intelligent SCADA, there is a rising need for new models of data management and resurrected focus on analytics to dissect data into descriptive, predictive and dictatorial subsets. The goal of this paper is to is to bring load disaggregation into smart energy toolkit for commercial usage.

Keywords: data management, analytics, energy data analytics, smart grid, smart utilities

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Authors: Ramon F. B. da Silva, Mateus Batistella, Emilio Moran

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Although the existence of two Forest Transition (FT) pathways, the economic development and the forest scarcity, there are many contexts that shape the model of FT observed in each particular region. This means that local conditions, such as relief, soil quality, historic land use/cover, public policies, the engagement of society in compliance with legal regulations, and the action of enforcement agencies, represent dimensions which combined, creates contexts that enable forest regeneration. From this perspective we can understand the regeneration process of native vegetation cover in the Paraíba Valley (Forest Atlantic biome), ongoing since the 1960s. This research analyzed public information, land use/cover maps, environmental public policies, and interviewed 17 stakeholders from the Federal and State agencies, municipal environmental and agricultural departments, civil society, farmers, aiming comprehend the contexts behind the forest regeneration in the Paraíba Valley, Sao Paulo State, Brazil. The first policy to protect forest vegetation was the Forest Code n0 4771 of 1965, but this legislation did not promote the increase of forest, just the control of deforestation, not enough to the Atlantic Forest biome that reached its highest pick of degradation in 1985 (8% of Atlantic Forest remnants). We concluded that the Brazilian environmental legislation acted in a strategic way to promote the increase of forest cover (102% of regeneration between 1985 and 2011) from 1993 when the Federal Decree n0 750 declared the initial and advanced stages of secondary succession protected against any kind of exploitation or degradation ensuring the forest regeneration process. The strategic policy formulation was also observed in the Sao Paulo State law n0 6171 of 1988 that prohibited the use of fire to manage agricultural landscape, triggering a process of forest regeneration in formerly pasture areas.

Keywords: forest transition, land abandonment, law enforcement, rural economic crisis

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Authors: P. Srinivasa Rao, K. Venkatesh Sharma, G. Sadhya Devi, V. Nagesh

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Privacy Preserving Data Publication is the main concern in present days because the data being published through the internet has been increasing day by day. This huge amount of data was named as Big Data by its size. This project deals the privacy preservation in the context of Big Data using a data warehousing solution called hive. We implemented Nearest Similarity Based Clustering (NSB) with Bottom-up generalization to achieve (v,l)-anonymity. (v,l)-Anonymity deals with the sensitivity vulnerabilities and ensures the individual privacy. We also calculate the sensitivity levels by simple comparison method using the index values, by classifying the different levels of sensitivity. The experiments were carried out on the hive environment to verify the efficiency of algorithms with Big Data. This framework also supports the execution of existing algorithms without any changes. The model in the paper outperforms than existing models.

Keywords: sensitivity, sensitive level, clustering, Privacy Preserving Data Publication (PPDP), bottom-up generalization, Big Data

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Authors: Elena K. Schneider, Johnny X. Huang, Vincenzo Carbone, Mark Baker, Mohammad A. K. Azad, Matthew A. Cooper, Jian Li, Tony Velkov

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Ivacaftor is a novel CF trans-membrane conductance regulator (CFTR) potentiator that improves the pulmonary function for cystic fibrosis patients bearing a G551D CFTR-protein mutation. Because ivacaftor is highly bound (>97%) to plasma proteins, there is the strong possibility that co-administered CF drugs that compete for the same plasma protein binding sites and impact the free drug concentration. This in turn could lead to drastic changes in the in vivo efficacy of ivacaftor and therapeutic outcomes. This study compares the binding affinity of ivacaftor and co-administered CF drugs for human serum albumin (HSA) and α1-acid glycoprotein (AGP) using surface plasmon resonance and fluorimetric binding assays that measure the displacement of site selective probes. Due to their high plasma protein binding affinities, drug-drug interactions between ivacaftor are to be expected with ducosate, montelukast, ibuprofen, dicloxacillin, omeprazole and loratadine. The significance of these drug-drug interactions is interpreted in terms of the pharmacodynamic/pharmacokinetic parameters and molecular docking simulations. The translational outcomes of the data are presented as recommendations for a staggered treatment regimen for future clinical trials which aims to maximize the effective free drug concentration and clinical efficacy of ivacaftor.

Keywords: human α-1-acid glycoprotein, binding affinity, human serum albumin, ivacaftor, cystic fibrosis

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Authors: Rabah Younes

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The reduction of available land resources and the increased cout associated with the use of high quality materials have led to the need for local soils to be used in geotechnical construction, however; poor engineering properties of these soils pose difficulties for constructions project and need to be stabilized to improve their properties in other works unsuitable soils with low bearing capacity , high plasticity coupled with high instability are frequently encountered hence, there is a need to improve the physical and mechanical characteristics of these soils to make theme more suitable for construction this can be done by using different mechanical and chemical methods clayey soil stabilization has been practiced for sometime but mixing additives, such us cement, lime and fly ash to the soil to increase its strength.

Keywords: clay, soil stabilization, naturaln pozzolana, atterberg limits, compaction, compressive strength shear strength, curing

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Authors: Behnam Tavakkol

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Uncertain data mining algorithms use different ways to consider uncertainty in data such as by representing a data object as a sample of points or a probability distribution. Fuzzy methods have long been used for clustering traditional (certain) data objects. They are used to produce non-crisp cluster labels. For uncertain data, however, besides some uncertain fuzzy k-medoids algorithms, not many other fuzzy clustering methods have been developed. In this work, we develop a fuzzy kernel k-medoids algorithm for clustering uncertain data objects. The developed fuzzy kernel k-medoids algorithm is superior to existing fuzzy k-medoids algorithms in clustering data sets with non-linearly separable clusters.

Keywords: clustering algorithm, fuzzy methods, kernel k-medoids, uncertain data

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Authors: H. M. Wilhelm, P. O. Fernandes, L. P. Dill, C. Steffens, K. G. Moscon, S. M. Peres, V. Bender, T. Marchesan, J. B. Ferreira Neto

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Deterioration of insulating oil is a natural process that occurs during transformers operation. However, this process can be accelerated by some factors, such as oxygen, high temperatures, metals and, moisture, which rapidly reduce oil insulating capacity and favor transformer faults. Parts of building materials of a transformer can be degraded and yield soluble compounds and insoluble particles that shorten the equipment life. Physicochemical tests, dissolved gas analysis (including propane, propylene and, butane), volatile and furanic compounds determination, besides quantitative and morphological analyses of particulate are proposed in this study in order to correlate transformers building materials degradation with insulating oil characteristics. The present investigation involves tests of medium temperature overheating simulation by means of an electric resistance wrapped with the following materials immersed in mineral insulating oil: test I) copper, tin, lead and, paper (heated at 350-400 °C for 8 h); test II) only copper (at 250 °C for 11 h); and test III) only paper (at 250 °C for 8 h and at 350 °C for 8 h). A different experiment is the simulation of electric arc involving copper, using an electric welding machine at two distinct energy sets (low and high). Analysis results showed that dielectric loss was higher in the sample of test I, higher neutralization index and higher values of hydrogen and hydrocarbons, including propane and butane, were also observed. Test III oil presented higher particle count, in addition, ferrographic analysis revealed contamination with fibers and carbonized paper. However, these particles had little influence on the oil physicochemical parameters (dielectric loss and neutralization index) and on the gas production, which was very low. Test II oil showed high levels of methane, ethane, and propylene, indicating the effect of metal on oil degradation. CO₂ and CO gases were formed in the highest concentration in test III, as expected. Regarding volatile compounds, in test I acetone, benzene and toluene were detected, which are oil oxidation products. Regarding test III, methanol was identified due to cellulose degradation, as expected. Electric arc simulation test showed the highest oil oxidation in presence of copper and at high temperature, since these samples had huge concentration of hydrogen, ethylene, and acetylene. Particle count was also very high, showing the highest release of copper in such conditions. When comparing high and low energy, the first presented more hydrogen, ethylene, and acetylene. This sample had more similar results to test I, pointing out that the generation of different particles can be the cause for faults such as electric arc. Ferrography showed more evident copper and exfoliation particles than in other samples. Therefore, in this study, by using different combined analytical techniques, it was possible to correlate insulating oil characteristics with possible contaminants, which can lead to transformers failure.

Keywords: Ferrography, gas analysis, insulating mineral oil, particle contamination, transformer failures

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Authors: Xiangming Ge, Bing Pan, Wei He, Hao Chen, Yong Zhou, Jiayao Wu, Weijiang Chu

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How the extraction and penetration of spudcan affect the performance of the adjacent pile foundation supporting the jacket platform was studied in the program FLAC3D depending on a wind farm project in Bohai sea. The simulations were conducted at the end of the spudcan penetration, which induced a pockmark in the seabed. The effects of the distance between the pile foundation and the pockmark were studied. The displacement at the mudline arose when the pockmark was closer. The bearing capacity of this jacket platform with deep pile foundations has been less influenced by the process of spudcan penetration, which can induce severe stresses on the pile foundation. The induced rotation was also satisfied with the rotation-controlling criteria.

Keywords: offshore foundation, pile-soil interaction, spudcan penetration, FLAC3D

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Authors: Nirmala Gopal, Sheetal Bhoola, Audecious Mugwagwa

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This paper discusses the continued infringement and exploitation of data by non-state actors for destructive purposes, emphasizing radical terrorist organizations. It will discuss how terrorist organizations access and use data to foster their nefarious agendas. It further examines how cybersecurity, designed as a tool to curb data exploitation, is ineffective in raising global citizens' concerns about how their data can be kept safe and used for its acquired purpose. The study interrogates several policies and data protection instruments, such as the Data Protection Act, Cyber Security Policies, Protection of Personal Information(PPI) and General Data Protection Regulations (GDPR), to understand data use and storage in democratic states. The study outcomes point to the fact that international cybersecurity and cybercrime legislation, policies, and conventions have not curbed violations of data access and use by radical terrorist groups. The study recommends ways to enhance cybersecurity and reduce cyber risks using democratic principles.

Keywords: cybersecurity, data exploitation, terrorist organizations, data democracy

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Authors: Eugenia Jilinguirian

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In the healthcare industry, data mining is essential since it transforms the field by collecting useful data from large datasets. Data mining is the process of applying advanced analytical methods to large patient records and medical histories in order to identify patterns, correlations, and trends. Healthcare professionals can improve diagnosis accuracy, uncover hidden linkages, and predict disease outcomes by carefully examining these statistics. Additionally, data mining supports personalized medicine by personalizing treatment according to the unique attributes of each patient. This proactive strategy helps allocate resources more efficiently, enhances patient care, and streamlines operations. However, to effectively apply data mining, however, and ensure the use of private healthcare information, issues like data privacy and security must be carefully considered. Data mining continues to be vital for searching for more effective, efficient, and individualized healthcare solutions as technology evolves.

Keywords: data mining, healthcare, big data, individualised healthcare, healthcare solutions, database

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Authors: Yunus Doğan, Ahmet Durap

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Coastal regions are the one of the most commonly used places by the natural balance and the growing population. In coastal engineering, the most valuable data is wave behaviors. The amount of this data becomes very big because of observations that take place for periods of hours, days and months. In this study, some statistical methods such as the wave spectrum analysis methods and the standard statistical methods have been used. The goal of this study is the discovery profiles of the different coast areas by using these statistical methods, and thus, obtaining an instance based data set from the big data to analysis by using data mining algorithms. In the experimental studies, the six sample data sets about the wave behaviors obtained by 20 minutes of observations from Mersin Bay in Turkey and converted to an instance based form, while different clustering techniques in data mining algorithms were used to discover similar coastal places. Moreover, this study discusses that this summarization approach can be used in other branches collecting big data such as medicine.

Keywords: clustering algorithms, coastal engineering, data mining, data summarization, statistical methods

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Authors: Seyed-Ahmad Shahidi, Salemeh Kazemzadeh, Mehdi Sharifi Soltani, Azade Ghorbani-HasanSaraei

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The kinetics of colour changes of American Pokeweed extract, due to concentration by various heating methods was studied. Three different heating/evaporation processes were employed for production of American Pokeweed extract concentrate. The American Pokeweed extract was concentrated to a final 40 °Brix from an initial °Brix of 4 by microwave heating, rotary vacuum evaporator and evaporating at atmospheric pressure. The final American Pokeweed extract concentration of 40 °Brix was achieved in 188, 216 and 320 min by using microwave, rotary vacuum and atmospheric heating processes, respectively. The colour change during concentration processes was investigated. Total colour differences, Hunter L, a and b parameters were used to estimate the extent of colour loss. All Hunter colour parameters decreased with time. The zero-order, first-order and a combined kinetics model were applied to the changes in colour parameters. All models were found to describe the L, a and b-data adequately. Results indicated that variation in TCD followed both first-order and combined kinetics models. This model implied that the colour formation and pigment destruction occurred during concentration processes of American Pokeweed extract.

Keywords: American pokeweed, colour, concentration, kinetics

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Authors: Marian Emmanuel Okon

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Introduction: The Niger Delta region of Nigeria has a vast reserve of oil and gas, which has globally positioned the nation as the sixth largest exporter of crude oil. Production rapidly rose following oil discovery. In most oil producing nations of the world, the wealth generated from oil production and export has propelled economic advancement, enabling the development of industries and other relevant infrastructures. Therefore, it can be assumed that majority of the oil resource such as Nigeria’s, has the potential to improve the health of the population via job creation and derived revenues. However, the health benefits of this economic development might be offset by the environmental consequences of oil exploitation and production. Objective: This research aims to evaluate the balance between the health benefits of oil-led economic development and harmful environmental consequences of crude oil exploitation in Nigeria. Study Design: A pathway has been designed to guide data search and this study. The model created will assess the relationship between oil-led economic development and population health development via job creation, improvement of education, development of infrastructure and other forms of development as well as through harmful environmental consequences from oil activities. Data/Emerging Findings: Diverse potentially suitable datasets which are at different geographical scales have been identified, obtained or applied for and the dataset from the World Bank has been the most thoroughly explored. This large dataset contains information that would enable the longitudinal assessment of both the health benefits and harms from oil exploitation in Nigeria as well as identify the disparities that exist between the communities, states and regions. However, these data do not extend far back enough in time to capture the start of crude oil production. Thus, it is possible that the maximum economic benefits and health harms could be missed. To deal with this shortcoming, the potential for a comparative study with countries like United Kingdom, Morocco and Cote D’ivoire has also been taken into consideration, so as to evaluate the differences between these countries as well as identify the areas of improvement in Nigeria’s environmental and health policies. Notwithstanding, these data have shown some differences in each country’s economic, environmental and health state over time as well as a corresponding summary statistics. Conclusion: In theory, the beneficial effects of oil exploitation to the health of the population may be substantial as large swaths of the ‘wider determinants’ of population heath are influenced by the wealth of a nation. However, if uncontrolled, the consequences from environmental pollution and degradation may outweigh these benefits. Thus, there is a need to address this, in order to improve environmental and population health in Nigeria.

Keywords: environmental pollution, health benefits, oil-led economic development, petroleum exploitation

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Authors: Ahmed H. Elkholy

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Aircraft gas turbine engines are subject to damage by airborne foreign objects such as birds and garbage dumps. In order to assess their effect on engine performance, a complete foreign object damage (FOD) test was carried out and a component failure analysis was used to verify airworthiness standards (AWS) requirements for engine certification as set by international regulations. Ingestion damage due to 1.8 Kg (4 lb.) bird strike on an engine is presented in some detail. Based on the observed damage, improvements to the engine design were suggested in two different locations: the front bearing housing and the low compressor shaft. When these improvements were implemented, the engine showed an acceptable containment capability that meets AWS requirements.

Keywords: aircraft engine, airworthiness standards, bird ingestion, foreign object damage

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Authors: Anny Retnowati, Elisabeth Sundari

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This research aims to elaborate the meaning of personal data protection principles on patient access to health data in medical records in Indonesia and its implications. The method uses normative legal research by examining health law in Indonesia regarding the patient's right to access their health data in medical records. The data will be analysed qualitatively using the interpretation method to elaborate on the limitation of the meaning of personal data protection principles on patients' access to their data in medical records. The results show that patients only have the right to obtain copies of their health data in medical records. There is no right to inspect directly at any time. Indonesian health law limits the principle of patients' right to broad access to their health data in medical records. This restriction has implications for the reduction of personal data protection as part of human rights. This research contribute to show that a limitaion of personal data protection may abuse the human rights.

Keywords: access, health data, medical records, personal data, protection

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Authors: Martin Böhmer, Agatha Dabrowski, Boris Otto

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The trend of digitization significantly changes the role of data for enterprises. Data turn from an enabler to an intangible organizational asset that requires management and qualifies as a tradeable good. The idea of a networked economy has gained momentum in the data domain as collaborative approaches for data management emerge. Traditional organizational knowledge consequently needs to be extended by comprehensive knowledge about data. The knowledge about data is vital for organizations to ensure that data quality requirements are met and data can be effectively utilized and sovereignly governed. As this specific knowledge has been paid little attention to so far by academics, the aim of the research presented in this paper is to conceptualize it by proposing a “data knowledge model”. Relevant model entities have been identified based on a design science research (DSR) approach that iteratively integrates insights of various industry case studies and literature research.

Keywords: data management, digitization, industry 4.0, knowledge engineering, metamodel

Procedia PDF Downloads 355