Search results for: 2d and 3d data conversion

Authors: Dino Carpentras, Paul J. Maher, Caoimhe O'Reilly, Michael Quayle

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Opinion dynamics is a sub-field of agent-based modeling that focuses on people’s opinions and their evolutions over time. Despite the rapid increase in the number of publications in this field, it is still not clear how to apply these models to real-world scenarios. Indeed, there is no agreement on how people update their opinion while interacting. Furthermore, it is not clear if different topics will show the same dynamics (e.g., more polarized topics may behave differently). These problems are mostly due to the lack of experimental validation of the models. Some previous studies started bridging this gap in the literature by directly measuring people’s opinions before and after the interaction. However, these experiments force people to express their opinion as a number instead of using natural language (and then, eventually, encoding it as numbers). This is not the way people normally interact, and it may strongly alter the measured dynamics. Another limitation of these studies is that they usually average all the topics together, without checking if different topics may show different dynamics. In our work, we collected data from 200 participants on 5 unpolarized topics. Participants expressed their opinions in natural language (“agree” or “disagree”). We also measured the certainty of their answer, expressed as a number between 1 and 10. However, this value was not shown to other participants to keep the interaction based on natural language. We then showed the opinion (and not the certainty) of another participant and, after a distraction task, we repeated the measurement. To make the data compatible with opinion dynamics models, we multiplied opinion and certainty to obtain a new parameter (here called “continuous opinion”) ranging from -10 to +10 (using agree=1 and disagree=-1). We firstly checked the 5 topics individually, finding that all of them behaved in a similar way despite having different initial opinions distributions. This suggested that the same model could be applied for different unpolarized topics. We also observed that people tend to maintain similar levels of certainty, even when they changed their opinion. This is a strong violation of what is suggested from common models, where people starting at, for example, +8, will first move towards 0 instead of directly jumping to -8. We also observed social influence, meaning that people exposed with “agree” were more likely to move to higher levels of continuous opinion, while people exposed with “disagree” were more likely to move to lower levels. However, we also observed that the effect of influence was smaller than the effect of random fluctuations. Also, this configuration is different from standard models, where noise, when present, is usually much smaller than the effect of social influence. Starting from this, we built an opinion dynamics model that explains more than 80% of data variance. This model was also able to show the natural conversion of polarization from unpolarized states. This experimental approach offers a new way to build models grounded on experimental data. Furthermore, the model offers new insight into the fundamental terms of opinion dynamics models.

Keywords: experimental validation, micro-dynamics rule, opinion dynamics, update rule

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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

Procedia PDF Downloads 437

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: 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

Procedia PDF Downloads 785

Authors: Jianwen Li, Hongfang Ma, Haitao Zhang, Qiwen Sun, Weiyong Ying

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Catalytic cracking of butene to propylene was carried out in a continuous-flow fixed-bed reactor over HZSM-5 catalysts modified by nickel and phosphorus. The structure and acidity of catalysts were measured by N2 adsorption, NH3-TPD and XPS. The results revealed that surface area and strong acid sites both decreased with increasing phosphorus loadings. The increment of phosphorus loadings reduced the butene conversion but enhanced the propylene selectivity and catalyst stability.

Keywords: butene, catalytic cracking, HZSM-5, modification

Procedia PDF Downloads 398

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: 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: 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: Mohammed Makha, Jakob Heier, Frank Nüesch, Roland Hany

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Organic solar cells (OSCs) have made rapid progress and currently achieve power conversion efficiencies (PCE) of over 10%. OSCs have several merits over other direct light-to-electricity generating cells and can be processed at low cost from solution on flexible substrates over large areas. Moreover, combining organic semiconductors with transparent and conductive electrodes allows for the fabrication of semitransparent OSCs (SM-OSCs). For SM-OSCs the challenge is to achieve a high average visible transmission (AVT) while maintaining a high short circuit current (Jsc). Typically, Jsc of SM-OSCs is smaller than when using an opaque metal top electrode. This is because the non-absorbed light during the first transit through the active layer and the transparent electrode is forward-transmitted out of the device. Recently, OSCs using a ternary blend of organic materials have received attention. This strategy was pursued to extend the light harvesting over the visible range. However, it is a general challenge to manipulate the performance of ternary OSCs in a predictable way, because many key factors affect the charge generation and extraction in ternary solar cells. Consequently, the device performance is affected by the compatibility between the blend components and the resulting film morphology, the energy levels and bandgaps, the concentration of the guest material and its location in the active layer. In this work, we report on a solvent-free lamination process for the fabrication of efficient and semitransparent ternary blend OSCs. The ternary blend was composed of PC70BM and the electron donors PBDTTT-C and an NIR cyanine absorbing dye (Cy7T). Using an opaque metal top electrode, a PCE of 6% was achieved for the optimized binary polymer: fullerene blend (AVT = 56%). However, the PCE dropped to ~2% when decreasing (to 30 nm) the active film thickness to increase the AVT value (75%). Therefore we resorted to the ternary blend and measured for non-transparent cells a PCE of 5.5% when using an active polymer: dye: fullerene (0.7: 0.3: 1.5 wt:wt:wt) film of 95 nm thickness (AVT = 65% when omitting the top electrode). In a second step, the optimized ternary blend was used of the fabrication of SM-OSCs. We used a plastic/metal substrate with a light transmission of over 90% as a transparent electrode that was applied via a lamination process. The interfacial layer between the active layer and the top electrode was optimized in order to improve the charge collection and the contact with the laminated top electrode. We demonstrated a PCE of 3% with AVT of 51%. The parameter space for ternary OSCs is large and it is difficult to find the best concentration ratios by trial and error. A rational approach for device optimization is the construction of a ternary blend phase diagram. We discuss our attempts to construct such a phase diagram for the PBDTTT-C: Cy7T: PC70BM system via a combination of using selective Cy7T selective solvents and atomic force microscopy. From the ternary diagram suitable morphologies for efficient light-to-current conversion can be identified. We compare experimental OSC data with these predictions.

Keywords: organic photovoltaics, ternary phase diagram, ternary organic solar cells, transparent solar cell, lamination

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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

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Authors: Daria Karasalihovic Sedlar, Lucija Jukic, Ivan Smajla, Marija Macenic

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This paper analyses possible geothermal energy production from a mature oil reservoir based on exploitation of underlying aquifer thermal energy for the purpose of heating public buildings. Research was conducted based on the case study of the City of Ivanic-Grad public buildings energy demand and Ivanic oil filed that is situated in the same area. Since the City of Ivanic is one of the few cities in the EU where hydrocarbon exploitation has been taking place for decades almost entirely in urban area, decommissioning of oil wells is inevitable; therefore, the research goal was to investigate how to extend the life-time of the reservoir by exploiting geothermal brine beneath the oil reservoir in an environmental friendly manner. This kind of a project is extremely complex in all segments, from documentation preparation, implementation of technological solutions, and providing ecological measures for environmentally acceptable geothermal energy production and utilization. New mining activities that will be needed for the development of geothermal project at the observed Hydrocarbon Exploitation Field Ivanic will be carried out in order to prepare wells for increasing geothermal brine production. These operations involve the conversion of existing wells (well completion for conversion of the observation wells to production ones) along with workover activities, installation of new heat exchangers, and pipelines. Since the wells are in the urban area of the City of Ivanic-Grad in high density populated area, the inhabitants will be exposed to the different environmental impacts during preparation phase of the project. For the purpose of performing workovers, it will be necessary to secure access to wellheads of existing wells. This paper gives guidelines for describing potential impacts on environment components that could occur during geothermal production preparation on existing mature oil filed, recommends possible protection measures to mitigate these impacts, and gives recommendations for environmental monitoring.

Keywords: geothermal energy production, mature oil filed, environmental impact assessment, underlying aquifer thermal energy

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Authors: Tawfig Alghbaili

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LP3D Field is located near the center of the Sirt Basin in the Marada Trough approximately 215 km south Marsa Al Braga City. The Marada Trough is bounded on the west by a major fault, which forms the edge of the Beda Platform, while on the east, a bounding fault marks the edge of the Zelten Platform. The main reservoir in the LP3D Field is Upper Paleocene Beda Formation. The Beda Formation is mainly limestone interbedded with shale. The reservoir average thickness is 117.5 feet. To develop a better understanding of the characterization and distribution of the Beda reservoir, quantitative seismic data interpretation has been done, and also, well logs data were analyzed. Six reflectors corresponding to the tops of the Beda, Hagfa Shale, Gir, Kheir Shale, Khalifa Shale, and Zelten Formations were picked and mapped. Special work was done on fault interpretation part because of the complexities of the faults at the structure area. Different attribute analyses were done to build up more understanding of structures lateral extension and to view a clear image of the fault blocks. Time to depth conversion was computed using velocity modeling generated from check shot and sonic data. The simplified stratigraphic cross-section was drawn through the wells A1, A2, A3, and A4-LP3D. The distribution and the thickness variations of the Beda reservoir along the study area had been demonstrating. Petrophysical analysis of wireline logging also was done and Cross plots of some petrophysical parameters are generated to evaluate the lithology of reservoir interval. Structure and Stratigraphic Framework was designed and run to generate different model like faults, facies, and petrophysical models and calculate the reservoir volumetric. This study concluded that the depth structure map of the Beda formation shows the main structure in the area of study, which is north to south faulted anticline. Based on the Beda reservoir models, volumetric for the base case has been calculated and it has STOIIP of 41MMSTB and Recoverable oil of 10MMSTB. Seismic attributes confirm the structure trend and build a better understanding of the fault system in the area.

Keywords: LP3D Field, Beda Formation, reservoir models, Seismic attributes

Procedia PDF Downloads 223

Authors: J-C. Leneveu, A. Chereau, L. Mansart, T. Mesbah, M. Wyka

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Extracting and interpreting information from Big Data represent a stake for years to come in several sectors such as finance. Currently, numerous methods are used (such as Technical Analysis) to try to understand and to anticipate market behavior, with mixed results because it still seems impossible to exactly predict a financial trend. The increase of available data on Internet and their diversity represent a great opportunity for the financial world. Indeed, it is possible, along with these standard financial data, to focus on exogenous data to take into account more macroeconomic factors. Coupling the interpretation of these data with standard methods could allow obtaining more precise trend predictions. In this paper, in order to observe the influence of exogenous data price independent of other usual effects occurring in classical markets, behaviors of Bitcoin users are introduced in a model reconstituting Bitcoin value, which is elaborated and tested for prediction purposes.

Keywords: big data, bitcoin, data mining, social network, financial trends, exogenous data, global economy, behavioral finance

Procedia PDF Downloads 358

Authors: Jeroen S. de Bruin, Karin Schindler, Christian Schuh

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With increasingly more mobile health applications appearing due to the popularity of smartphones, the possibility arises that these data can be used to improve the medical diagnostic process, as well as the overall quality of healthcare, while at the same time lowering costs. However, as of yet there have been no reports of a successful combination of patient-generated data from smartphones with data from clinical routine. In this paper, we describe how these two types of data can be combined in a secure way without modification to hospital information systems, and how they can together be used in a medical expert system for automatic nutritional classification and triage.

Keywords: mobile health, data integration, expert systems, disease-related malnutrition

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Authors: Sombol Mokhles

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This paper tries to show the prospects of utilising (big)data for enabling just the transition of diverse cities. Our key purpose is to offer a framework of applications and implications of utlising (big) data in comparing sustainability transitions across different cities. Relying on the cosmopolitan comparison, this paper explains the potential application of (big) data but also its limitations. The paper calls for adopting a data-driven and just perspective in including different cities around the world. Having a just and inclusive approach at the front and centre ensures a just transition with synergistic effects that leave nobody behind.

Keywords: big data, just sustainable transition, cosmopolitan city comparison, cities

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Authors: Marcin Dębowski, Marcin Zieliński, Mirosław Krzemieniewski

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As methane fermentation is a complex series of successive biochemical transformations, its subsequent stages are determined, to a various extent, by physical and chemical factors. A specific state of equilibrium is being settled in the functioning fermentation system between environmental conditions and the rate of biochemical reactions and products of successive transformations. In the case of physical factors that influence the effectiveness of methane fermentation transformations, the key significance is ascribed to temperature and intensity of biomass agitation. Among the chemical factors, significant are pH value, type, and availability of the culture medium (to put it simply: the C/N ratio) as well as the presence of toxic substances. One of the important elements which influence the effectiveness of methane fermentation is the pre-treatment of organic substrates and the mode in which the organic matter is made available to anaerobes. Out of all known and described methods for organic substrate pre-treatment before methane fermentation process, the ultrasound disintegration is one of the most interesting technologies. Investigations undertaken on the ultrasound field and the use of installations operating on the existing systems result principally from very wide and universal technological possibilities offered by the sonication process. This physical factor may induce deep physicochemical changes in ultrasonicated substrates that are highly beneficial from the viewpoint of methane fermentation processes. In this case, special role is ascribed to disintegration of biomass that is further subjected to methane fermentation. Once cell walls are damaged, cytoplasm and cellular enzymes are released. The released substances – either in dissolved or colloidal form – are immediately available to anaerobic bacteria for biodegradation. To ensure the maximal release of organic matter from dead biomass cells, disintegration processes are aimed to achieve particle size below 50 μm. It has been demonstrated in many research works and in systems operating in the technical scale that immediately after substrate supersonication the content of organic matter (characterized by COD, BOD5 and TOC indices) was increasing in the dissolved phase of sedimentation water. This phenomenon points to the immediate sonolysis of solid substances contained in the biomass and to the release of cell material, and consequently to the intensification of the hydrolytic phase of fermentation. It results in a significant reduction of fermentation time and increased effectiveness of production of gaseous metabolites of anaerobic bacteria. Because disintegration of Virginia fanpetals biomass via ultrasounds applied in order to intensify its conversion is a novel technique, it is often underestimated by exploiters of agri-biogas works. It has, however, many advantages that have a direct impact on its technological and economical superiority over thus far applied methods of biomass conversion. As for now, ultrasound disintegrators for biomass conversion are not produced on the mass-scale, but by specialized groups in scientific or R&D centers. Therefore, their quality and effectiveness are to a large extent determined by their manufacturers’ knowledge and skills in the fields of acoustics and electronic engineering.

Keywords: ultrasound disintegration, biomass, methane fermentation, biogas, Virginia fanpetals

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Authors: Modesta E. Ezema, Christopher C. Ezema, Christian C. Ugwu, Udoka F. Eze, Florence M. Babalola

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Some employees knowingly or unknowingly contribute to loss of data and also expose data to threat in the process of getting their jobs done. Many organizations today are faced with the challenges of how to secure their data as cyber criminals constantly devise new ways of attacking the organization’s secret data. However, this paper enlists the latest strategies that must be put in place in order to protect these important data from being attacked in a collaborative work place. It also introduces us to Advanced Persistent Threats (APTs) and how it works. The empirical study was conducted to collect data from the employee in data centers on how data could be protected from malicious codes and cyber criminals and their responses are highly considered to help checkmate the activities of malicious code and cyber criminals in our work places.

Keywords: data, employee, malware, work place

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Authors: Stefan Andersson, Balram Panjwani, Bernd Wittgens, Jan Erik Olsen

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Polycyclic Aromatic hydrocarbons are organic compounds consisting of only hydrogen and carbon aromatic rings. PAH are neutral, non-polar molecules that are produced due to incomplete combustion of organic matter. These compounds are carcinogenic and interact with biological nucleophiles to inhibit the normal metabolic functions of the cells. Norways, the most important sources of PAH pollution is considered to be aluminum plants, the metallurgical industry, offshore oil activity, transport, and wood burning. Stricter governmental regulations regarding emissions to the outer and internal environment combined with increased awareness of the potential health effects have motivated Norwegian metal industries to increase their efforts to reduce emissions considerably. One of the objective of the ongoing industry and Norwegian research council supported "SCORE" project is to reduce potential PAH emissions from an off gas stream of a ferroalloy furnace through controlled combustion. In a dedicated combustion chamber. The sizing and configuration of the combustion chamber depends on the combined properties of the bulk gas stream and the properties of the PAH itself. In order to achieve efficient and complete combustion the residence time and minimum temperature need to be optimized. For this design approach reliable kinetic data of the individual PAH-species and/or groups thereof are necessary. However, kinetic data on the combustion of PAH are difficult to obtain and there is only a limited number of studies. The paper presents an evaluation of the kinetic data for some of the PAH obtained from literature. In the present study, the oxidation is modelled for pure PAH and also for PAH mixed with process gas. Using a perfectly stirred reactor modelling approach the oxidation is modelled including advanced reaction kinetics to study influence of residence time and temperature on the conversion of PAH to CO2 and water. A Chemical Reactor Network (CRN) approach is developed to understand the oxidation of PAH inside the combustion chamber. Chemical reactor network modeling has been found to be a valuable tool in the evaluation of oxidation behavior of PAH under various conditions.

Keywords: PAH, PSR, energy recovery, ferro alloy furnace

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Authors: Jia Yi Yap, Angela S. H. Lee

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With the use of big data technologies, organization can get result that they are interested in. Big data technologies simply load all the data that is useful for the organizations and provide organizations a better way of analysing data. The purpose of this research is to get employees’ opinion from films in Malaysia to explore the use of big data technologies in their organization in order to provide how it may affect the perception of the employees on job performance. Therefore, in order to identify will accepting big data technologies in the organization affect the perception of the employee, questionnaire will be distributed to different employee from different Small and medium-sized enterprises (SME) organization listed in Malaysia. The conceptual model proposed will test with other variables in order to see the relationship between variables.

Keywords: big data technologies, employee, job performance, questionnaire

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Authors: Siyanda S. Biyela, Willie A. Cronje

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This paper presents a desktop study of comparing two different wave energy to electricity technologies (WECs) using a techno-economic approach. This techno-economic approach forms basis of a framework for rapid comparison of current and future technologies. The approach also seeks to assist in investment and strategic decision making expediting future deployment of wave energy harvesting in South Africa.

Keywords: cost of energy (COE) tool, sea state, wave energy converter (WEC), WEC-Sim

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Authors: Z. Khalifa, K. M. Hassan, M. Abdel Azzem

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Potential strategies for deriving useful forms of renewable high density energy from abundant energy stored in carbohydrates is direct conversion of glucose (GLU) to electrical power. A three novel versatile modified electrodes, synthesized by electrochemical polymerization of organic monomers on glassy carbon electrodes (GC), have been developed for biofuel cells results in stable and long-term power production. Electrocatalytic oxidation of glucose in alkaline solution on conducting polymers electrodes modified by incorporation of Ni nanoparticles (NiNPs) onto poly(1,5-aminonaphthalene) (1,5-PDAN), poly(1,8-diaminonaphthalene) (1,8-PDAN) and poly(1-amino-2-methyl-9,10-anthraquinone) (PAMAQ) was investigated. The electrocatalytic oxidation of glucose at NiNPs-modified 1,5-PDAN/GC, 1,8-PDAN/GC and PAMAQ/GC electrodes has been studied using voltammetry technique. The PDAN electrodes show a slight activity in the potential of interest. The prepared NiNPs/PAMAQ/GC catalyst showed a very interesting catalytic activity that was nicely comparable to the NiNPs/1,5-PDAN/GC, NiNPs/1,8-PDAN/GC modified electrodes. In advance, both shows a significant more catalytic activity compared to the reported data for electrodes for glucose electrocatalytic oxidation.

Keywords: biofuel cells, glucose oxidation, electrocatalysis, nanoparticles and modified electrodes

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Authors: Beulah Rani Inbanathan

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In the present era, it is vivid from the numerous outcomes that data privacy is being compromised in various ways. Machine learning is one technology that uses the centralized server, and then data is given as input which is being analyzed by the algorithms present on this mentioned server, and hence outputs are predicted. However, each time the data must be sent by the user as the algorithm will analyze the input data in order to predict the output, which is prone to threats. The solution to overcome this issue is federated learning, where the models alone get updated while the data resides on the local machine and does not get exchanged with the other local models. Nevertheless, even on these local models, there are chances of data poisoning, and it is crystal clear from various experiments done by many people. This paper delves into many ways where data poisoning occurs and the many methods through which it is prevalent that data poisoning still exists. It includes the poisoning attacks on IoT devices, Edge devices, Autoregressive model, and also, on Industrial IoT systems and also, few points on how these could be evadible in order to protect our data which is personal, or sensitive, or harmful when exposed.

Keywords: data poisoning, federated learning, Internet of Things, edge computing

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Authors: A. U. Adamu, Hamisu Abdu, A. A. Saidu

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The enzymatic synthesis of 3-O-β-D-glucopyranoside-betulinic acid using Novozyme-435 as a catalyst was studied. The effect of various parameters such as substrate molar ratio, reaction temperature, reaction time, re-used enzymes and amount of enzymes were investigated. The optimum rection conditions for the enzymatic glycosidation of betulinic acid in an organic solvent using Novozym-435 was found to be at 1:1.2 substrate molar ratio, 55oC, 24 h and 180 mg of enzymes with percentage conversion of 88.69 %.

Keywords: betulinic acid, glycosidation, novozyme-435, optimization

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Authors: Sunbul Jassim Hamodi, Muna Khalid Khudayer, Firas Muzahem Hussein

Abstract:

The experiment was conducted to study the effect of supplement sources of Phytase enzyme (bacterial, fungal, enzymes mixture) using levels (250, 500, 750) FTY/ kg feed to diets compared with control on the performance for one thousand fifty broiler chicks (Ross 308) from 1day old with initial weight 39.78 gm till 42 days. The study involved 10 treatments, three replicates per treatment (35 chicks/replicate). Treatments were as follows: T1: control diet (without any addition). T2: added bacterial phytase enzyme 250FTY/ kg feed. T3: added bacterial phytase enzyme 500FTY/ kg feed. T4: added bacterial phytase enzyme 750FTY/ kg feed. T5: added fungal phytase enzyme 250FTY/ kg feed. T6: added fungal phytase enzyme 500FTY/ kg feed. T7: added fungal phytase enzyme 750FTY/ kg feed. T8 added enzymes mixture 250U/ kg feed. T9: added enzymes mixture 500U/ kg feed. T10: added enzymes mixture 750U/ kg feed. The results revealed that supplementing 750 U from enzymes mixture to broiler diet increased significantly (p <0.05) body weight compared with (250 FTY bacterial phytase/Kgfeed), (750 FTY bacterial phytase/Kg feed), (750FTY fungal phytase/Kgfeed) at 6 weeks, also supplemented different sources and levels from phytase enzyme improved a cumulative weight gain for (500 FTY bacterial phytase/Kgfeed), (250FTY fungal phytase/Kgfeed), (500FTY fungal phytase/Kgfeed), (250 Uenzymes mixture/Kgfeed), (500 Uenzymes mixture/Kgfeed) and (750 U enzymes mixture/Kgfeed) treatments compared with (750 FTY fungal phytase/Kgfeed)treatment, about accumulative feed consumption (500 FTY fungal phytase/Kgfeed) and (250 Uenzymes mixture/Kgfeed) increased significantly compared with control group and (750FTY fungal phytase/Kgfeed) during 1-6 weeks. There were significantly improved in cumulative feed conversion for (500U enzymes mixture/Kgfeed) compared with the worse feed conversion ratio that recorded in (250 FTY bacterial phytase/Kgfeed). No significant differences between treatments in internal organs relative weights, carcass cuts, dressing percentage and production index. Mortality was increased in (750FTY fungal phytase/Kgfeed) compared with other treatments.

Keywords: phytase, phytic acid, broiler, productive performance

Procedia PDF Downloads 303

Authors: Selvamuthukumaran Thirunavukkarasu, Arivudainambi Sundararajan

Abstract:

The plant active molecules with their known mode of action are important leads to the development of newer insecticides. Lactone glycoside was identified earlier as the active principle in Cleistanthus collinus (Roxb.) Benth. (Fam: Euphorbiaceae). It possessed feeding deterrent, insecticidal and insect growth regulatory actions at varying concentrations. Deducing its mode of action opens a possibility of its further development. A no-choice leaf disc bioassay was carried out with lactone glycoside at different doses for different instars and Deterrence Indices were worked out. Using regression analysis concentrations imparting 10, 30 and 50 per cent deterrence (DI10, DI30 & DI50) were worked out. At these doses, effect on nutritional indices like Relative Consumption and Growth Rates (RCR & RGR), Efficiencies of Conversion of Ingested and Digested food (ECI & ECD) and Approximate Digestibility (AD) were worked out. The Relative Consumption and Growth Rate of control and lactone glycoside larva were compared by regression analysis. Regression analysis of deterrence indices revealed that the concentrations needed for imparting 50 per cent deterrence was 60.66, 68.47 and 71.10 ppm for third, fourth and fifth instars respectively. Relative consumption rate (RCR) and relative growth rate (RGR) were reduced. This confirmed the antifeedant action of the fraction. Approximate digestibility (AD) was found greater in treatments indicating reduced faeces because of poor digestibility and retention of food in the gut. Efficiency of conversion of both ingested and digested (ECI and ECD) food was also found to be greatly reduced. This indicated presence of toxic action. This was proved by comparing growth efficiencies of control and lactone glycoside treated larvae. Lactone glycoside was found to possess both feeding deterrent and toxic modes of action. Studies on molecular targets based on this preliminary site of action lead to new insecticide development.

Keywords: Spodoptera litura Fabricius, Cleistanthus collinus (Roxb.) Benth, feeding deterrence, mode of action

Procedia PDF Downloads 157

Authors: Shashank Tiwari

Abstract:

The most common method of drug delivery is the oral solid dosage form, of which tablets and capsules are predominant. The tablet is more widely accepted and used compared to capsules for a number of reasons, such as cost/price, tamper resistance, ease of handling and packaging, ease of identification, and manufacturing efficiency. Over the past several years, the issue of tamper resistance has resulted in the conversion of most over-the-counter (OTC) drugs from capsules to predominantly all tablets.

Keywords: capsule, drug delivery, dosages, solid, tablet

Procedia PDF Downloads 441

Authors: R. M. Kalayappan, N. Kathiravan

Abstract:

In automobile industries, Controller Area Network (CAN) is widely used to reduce the system complexity and inter-task communication. Therefore, this paper proposes the hardware implementation of data frame communication between one controller to other. The CAN data frames and protocols will be explained deeply, here. The data frames are transferred without any collision or corruption. The simulation is made in the KEIL vision software to display the data transfer between transmitter and receiver in CAN. ARM7 micro-controller is used to transfer data’s between the controllers in real time. Data transfer is verified using the CRO.

Keywords: control area network (CAN), automotive electronic control unit, CAN 2.0, industry

Procedia PDF Downloads 399