Search results for: data mining techniques
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 29848

Search results for: data mining techniques

26518 Reliability Analysis of Computer Centre at Yobe State University Using LRU Algorithm

Authors: V. V. Singh, Yusuf Ibrahim Gwanda, Rajesh Prasad

Abstract:

In this paper, we focus on the reliability and performance analysis of Computer Centre (CC) at Yobe State University, Damaturu, Nigeria. The CC consists of three servers: one database mail server, one redundant and one for sharing with the client computers in the CC (called as a local server). Observing the different possibilities of the functioning of the CC, the analysis has been done to evaluate the various popular measures of reliability such as availability, reliability, mean time to failure (MTTF), profit analysis due to the operation of the system. The system can ultimately fail due to the failure of router, redundant server before repairing the mail server and switch failure. The system can also partially fail when a local server fails. The failed devices have restored according to Least Recently Used (LRU) techniques. The system can also fail entirely due to a cooling failure of the server, electricity failure or some natural calamity like earthquake, fire tsunami, etc. All the failure rates are assumed to be constant and follow exponential time distribution, while the repair follows two types of distributions: i.e. general and Gumbel-Hougaard family copula distribution.

Keywords: reliability, availability Gumbel-Hougaard family copula, MTTF, internet data centre

Procedia PDF Downloads 531
26517 Controlling Cocoa Pod Borer, Conopomorpha cramerella (Snell.) and Cost Analysis Production at Cacao Plantation

Authors: Alam Anshary, Flora Pasaru, Shahabuddin

Abstract:

The Cocoa Pod Borer (CPB), Conopomorpha cramerella (Snell.) is present on most of the larger cocoa producing islands in Indonesia. Various control measures CPB has been carried out by the farmers, but the results have not been effective. This study aims to determine the effect of application of Beauveria bassiana treatments and pruning technique to the control of CPB in the cocoa plantation people. Research using completely randomized design with 4 treatments and 3 replications, treatment consists of B.bassiana, Pruning, B. bassiana+pruning (Bb + Pr), as well as the control. The results showed that the percentage of PBK attack on cocoa pods in treatment (Bb + Pr) 3.50% the lowest compared to other treatments. CPB attack percentage in treatment B.bassiana 6.15%; pruning 8.75%, and 15.20% control. Results of the analysis of production estimates, the known treatments (Bb + Pr) have the highest production (1.95 tonnes / ha). The model results estimated production is Y= 0,20999 + 0,53968X1 + 0,34298X2+ 0,31410X3 + 0,35629X4 + 0,08345X5 + 0,29732X6. Farm production costs consist of fixed costs and variable costs, fixed costs are costs incurred by the farmer that the size does not affect the results, such as taxes and depreciation of production equipment. Variable costs are costs incurred by farmers who used up in one year cocoa farming activities. The cost of production in farming cocoa without integrated techniques control of CPB is Rp. 9.205.550 million/ha, while the cost of production with integrated techniques control is Rp. 6.666.050 million/ha.

Keywords: cacao, cocoa pod borer, pruning, Beauveria bassiana, production costs

Procedia PDF Downloads 285
26516 Surface Elevation Dynamics Assessment Using Digital Elevation Models, Light Detection and Ranging, GPS and Geospatial Information Science Analysis: Ecosystem Modelling Approach

Authors: Ali K. M. Al-Nasrawi, Uday A. Al-Hamdany, Sarah M. Hamylton, Brian G. Jones, Yasir M. Alyazichi

Abstract:

Surface elevation dynamics have always responded to disturbance regimes. Creating Digital Elevation Models (DEMs) to detect surface dynamics has led to the development of several methods, devices and data clouds. DEMs can provide accurate and quick results with cost efficiency, in comparison to the inherited geomatics survey techniques. Nowadays, remote sensing datasets have become a primary source to create DEMs, including LiDAR point clouds with GIS analytic tools. However, these data need to be tested for error detection and correction. This paper evaluates various DEMs from different data sources over time for Apple Orchard Island, a coastal site in southeastern Australia, in order to detect surface dynamics. Subsequently, 30 chosen locations were examined in the field to test the error of the DEMs surface detection using high resolution global positioning systems (GPSs). Results show significant surface elevation changes on Apple Orchard Island. Accretion occurred on most of the island while surface elevation loss due to erosion is limited to the northern and southern parts. Concurrently, the projected differential correction and validation method aimed to identify errors in the dataset. The resultant DEMs demonstrated a small error ratio (≤ 3%) from the gathered datasets when compared with the fieldwork survey using RTK-GPS. As modern modelling approaches need to become more effective and accurate, applying several tools to create different DEMs on a multi-temporal scale would allow easy predictions in time-cost-frames with more comprehensive coverage and greater accuracy. With a DEM technique for the eco-geomorphic context, such insights about the ecosystem dynamic detection, at such a coastal intertidal system, would be valuable to assess the accuracy of the predicted eco-geomorphic risk for the conservation management sustainability. Demonstrating this framework to evaluate the historical and current anthropogenic and environmental stressors on coastal surface elevation dynamism could be profitably applied worldwide.

Keywords: DEMs, eco-geomorphic-dynamic processes, geospatial Information Science, remote sensing, surface elevation changes,

Procedia PDF Downloads 267
26515 Cyberfraud Schemes: Modus Operandi, Tools and Techniques and the Role of European Legislation as a Defense Strategy

Authors: Papathanasiou Anastasios, Liontos George, Liagkou Vasiliki, Glavas Euripides

Abstract:

The purpose of this paper is to describe the growing problem of various cyber fraud schemes that exist on the internet and are currently among the most prevalent. The main focus of this paper is to provide a detailed description of the modus operandi, tools, and techniques utilized in four basic typologies of cyber frauds: Business Email Compromise (BEC) attacks, investment fraud, romance scams, and online sales fraud. The paper aims to shed light on the methods employed by cybercriminals in perpetrating these types of fraud, as well as the strategies they use to deceive and victimize individuals and businesses on the internet. Furthermore, this study outlines defense strategies intended to tackle the issue head-on, with a particular emphasis on the crucial role played by European Legislation. European legislation has proactively adapted to the evolving landscape of cyber fraud, striving to enhance cybersecurity awareness, bolster user education, and implement advanced technical controls to mitigate associated risks. The paper evaluates the advantages and innovations brought about by the European Legislation while also acknowledging potential flaws that cybercriminals might exploit. As a result, recommendations for refining the legislation are offered in this study in order to better address this pressing issue.

Keywords: business email compromise, cybercrime, European legislation, investment fraud, NIS, online sales fraud, romance scams

Procedia PDF Downloads 98
26514 Public Wi-Fi Security Threat Evil Twin Attack Detection Based on Signal Variant and Hop Count

Authors: Said Abdul Ahad Ahadi, Elyas Baray, Nitin Rakesh, Sudeep Varshney

Abstract:

Wi-Fi is a widely used internet source that is used to provide internet access in many areas such as Stores, Cafes, University campuses, Restaurants and so on. This technology brought more facilities in communication and networking. On the other hand, due to the transmission of data over the air, which makes the network vulnerable, so it becomes prone to various threats such as Evil Twin and etc. The Evil Twin is a kind of adversary which impersonates a legitimate access point (LAP) as it can happen by spoofing the name (SSID) and MAC address (BSSID) of a legitimate access point (LAP). And this attack can cause many threats such as MITM, Service Interruption, Access point service blocking. Various Evil Twin Attack Detection Techniques are proposed, but they require additional hardware, or they require protocol modification. In this paper, we proposed a new technique based on Access Point’s two fingerprints, Received Signal Strength Indicator (RSSI) and Hop Count, that is hard to copy by an adversary. And we implemented the technique in a system called “ETDetector,” which can detect and prevent the attack.

Keywords: evil twin, LAP, SSID, Wi-Fi security, signal variation, ETAD, kali linux, scapy, python

Procedia PDF Downloads 143
26513 Vulnerability of Groundwater to Pollution in Akwa Ibom State, Southern Nigeria, using the DRASTIC Model and Geographic Information System (GIS)

Authors: Aniedi A. Udo, Magnus U. Igboekwe, Rasaaq Bello, Francis D. Eyenaka, Michael C. Ohakwere-Eze

Abstract:

Groundwater vulnerability to pollution was assessed in Akwa Ibom State, Southern Nigeria, with the aim of locating areas with high potentials for resource contamination, especially due to anthropogenic influence. The electrical resistivity method was utilized in the collection of the initial field data. Additional data input, which included depth to static water level, drilled well log data, aquifer recharge data, percentage slope, as well as soil information, were sourced from secondary sources. The initial field data were interpreted both manually and with computer modeling to provide information on the geoelectric properties of the subsurface. Interpreted results together with the secondary data were used to develop the DRASTIC thematic maps. A vulnerability assessment was performed using the DRASTIC model in a GIS environment and areas with high vulnerability which needed immediate attention was clearly mapped out and presented using an aquifer vulnerability map. The model was subjected to validation and the rate of validity was 73% within the area of study.

Keywords: groundwater, vulnerability, DRASTIC model, pollution

Procedia PDF Downloads 207
26512 Outcomes of Pain Management for Patients in Srinagarind Hospital: Acute Pain Indicator

Authors: Chalermsri Sorasit, Siriporn Mongkhonthawornchai, Darawan Augsornwan, Sudthanom Kamollirt

Abstract:

Background: Although knowledge of pain and pain management is improving, they are still inadequate to patients. The Nursing Division of Srinagarind Hospital is responsible for setting the pain management system, including work instruction development and pain management indicators. We have developed an information technology program for monitoring pain quality indicators, which was implemented to all nursing departments in April 2013. Objective: To study outcomes of acute pain management in process and outcome indicators. Method: This is a retrospective descriptive study. The sample population was patients who had acute pain 24-48 hours after receiving a procedure, while admitted to Srinagarind Hospital in 2014. Data were collected from the information technology program. 2709 patients with acute pain from 10 Nursing Departments were recruited in the study. The research tools in this study were 1) the demographic questionnaire 2) the pain management questionnaire for process indicators, and 3) the pain management questionnaire for outcome indicators. Data were analyzed and presented by percentages and means. Results: The process indicators show that nurses used pain assessment tool and recorded 99.19%. The pain reassessment after the intervention was 96.09%. The 80.15% of the patients received opioid for pain medication and the most frequency of non-pharmacological intervention used was positioning (76.72%). For the outcome indicators, nearly half of them (49.90%) had moderate–severe pain, mean scores of worst pain was 6.48 and overall pain was 4.08. Patient satisfaction level with pain management was good (49.17%) and very good (46.62%). Conclusion: Nurses used pain assessment tools and pain documents which met the goal of the pain management process. Patient satisfaction with pain management was at high level. However the patients had still moderate to severe pain. Nurses should adhere more strictly to the guidelines of pain management, by using acute pain guidelines especially when pain intensity is particularly moderate-high. Nurses should also develop and practice a non-pharmacological pain management program to continually improve the quality of pain management. The information technology program should have more details about non-pharmacological pain techniques.

Keywords: outcome, pain management, acute pain, Srinagarind Hospital

Procedia PDF Downloads 232
26511 Dynamic Conformal Arc versus Intensity Modulated Radiotherapy for Image Guided Stereotactic Radiotherapy of Cranial Lesion

Authors: Chor Yi Ng, Christine Kong, Loretta Teo, Stephen Yau, FC Cheung, TL Poon, Francis Lee

Abstract:

Purpose: Dynamic conformal arc (DCA) and intensity modulated radiotherapy (IMRT) are two treatment techniques commonly used for stereotactic radiosurgery/radiotherapy of cranial lesions. IMRT plans usually give better dose conformity while DCA plans have better dose fall off. Rapid dose fall off is preferred for radiotherapy of cranial lesions, but dose conformity is also important. For certain lesions, DCA plans have good conformity, while for some lesions, the conformity is just unacceptable with DCA plans, and IMRT has to be used. The choice between the two may not be apparent until each plan is prepared and dose indices compared. We described a deviation index (DI) which is a measurement of the deviation of the target shape from a sphere, and test its functionality to choose between the two techniques. Method and Materials: From May 2015 to May 2017, our institute has performed stereotactic radiotherapy for 105 patients treating a total of 115 lesions (64 DCA plans and 51 IMRT plans). Patients were treated with the Varian Clinac iX with HDMLC. Brainlab Exactrac system was used for patient setup. Treatment planning was done with Brainlab iPlan RT Dose (Version 4.5.4). DCA plans were found to give better dose fall off in terms of R50% (R50% (DCA) = 4.75 Vs R50% (IMRT) = 5.242) while IMRT plans have better conformity in terms of treatment volume ratio (TVR) (TVR(DCA) = 1.273 Vs TVR(IMRT) = 1.222). Deviation Index (DI) is proposed to better facilitate the choice between the two techniques. DI is the ratio of the volume of a 1 mm shell of the PTV and the volume of a 1 mm shell of a sphere of identical volume. DI will be close to 1 for a near spherical PTV while a large DI will imply a more irregular PTV. To study the functionality of DI, 23 cases were chosen with PTV volume ranged from 1.149 cc to 29.83 cc, and DI ranged from 1.059 to 3.202. For each case, we did a nine field IMRT plan with one pass optimization and a five arc DCA plan. Then the TVR and R50% of each case were compared and correlated with the DI. Results: For the 23 cases, TVRs and R50% of the DCA and IMRT plans were examined. The conformity for IMRT plans are better than DCA plans, with majority of the TVR(DCA)/TVR(IMRT) ratios > 1, values ranging from 0.877 to1.538. While the dose fall off is better for DCA plans, with majority of the R50%(DCA)/ R50%(IMRT) ratios < 1. Their correlations with DI were also studied. A strong positive correlation was found between the ratio of TVRs and DI (correlation coefficient = 0.839), while the correlation between the ratio of R50%s and DI was insignificant (correlation coefficient = -0.190). Conclusion: The results suggest DI can be used as a guide for choosing the planning technique. For DI greater than a certain value, we can expect the conformity for DCA plans to become unacceptably great, and IMRT will be the technique of choice.

Keywords: cranial lesions, dynamic conformal arc, IMRT, image guided radiotherapy, stereotactic radiotherapy

Procedia PDF Downloads 241
26510 The Dynamic of Decentralization of Education Policy in Post-Reform Indonesia: Local Perspectives

Authors: Mudiyati Rahmatunnisa

Abstract:

This study is about the implementation of decentralization of education policy in today’s Indonesia’s reform era. The policy has made education as one of the basic public services that must be performed by the local governments. After more than a decade of implementing the policy, what have been achieved? Has the implementation of educational affairs in the region been able to improve the quality of education services in the region? What obstacles or challenges faced by the region in the implementation of the educational affairs? How does region overcome obstacles or challenges? In answering those strategic questions, this study will particularly investigate the implementation of educational affairs in the city and District of Cirebon, the two district level of governments in West Java Province. The two loci of study provide interesting insight, given the range of previous studies did not specifically investigate using a local perspective (city and district level). This study employs a qualitative research method through case studies. Operationally, this study is sustained by several data collection techniques, i.e. interviews, documentary method, and systematic observation. Needless to say, there have been many factors distorting the ideal construction of decentralization of education policy.

Keywords: decentralization, decentralization of education, policy implementation, public service

Procedia PDF Downloads 378
26509 A Review Paper on Data Security in Precision Agriculture Using Internet of Things

Authors: Tonderai Muchenje, Xolani Mkhwanazi

Abstract:

Precision agriculture uses a number of technologies, devices, protocols, and computing paradigms to optimize agricultural processes. Big data, artificial intelligence, cloud computing, and edge computing are all used to handle the huge amounts of data generated by precision agriculture. However, precision agriculture is still emerging and has a low level of security features. Furthermore, future solutions will demand data availability and accuracy as key points to help farmers, and security is important to build robust and efficient systems. Since precision agriculture comprises a wide variety and quantity of resources, security addresses issues such as compatibility, constrained resources, and massive data. Moreover, conventional protection schemes used in the traditional internet may not be useful for agricultural systems, creating extra demands and opportunities. Therefore, this paper aims at reviewing state of the art of precision agriculture security, particularly in open field agriculture, discussing its architecture, describing security issues, and presenting the major challenges and future directions.

Keywords: precision agriculture, security, IoT, EIDE

Procedia PDF Downloads 90
26508 Hydrofracturing for Low Temperature Waxy Reservoirs: Problems and Solutions

Authors: Megh Patel, Arjun Chauhan, Jay Thakkar

Abstract:

Hydrofracturing is the most prominent but at the same time expensive, highly skilled and time consuming well stimulation technique. Due to high cost and skilled labor involved, it is generally carried out as the consummate solution among other well stimulation techniques. Considering today’s global petroleum market, no gaffe or complications could be entertained during fracturing, as it would further hamper the current dwindling economy. The literature would be dealing with the challenges encountered during fracturing low temperature waxy reservoirs and the prominent solutions to overcome such teething troubles. During fracturing treatment for, shallow and high freezing point waxy oil reservoirs, the first line problems are to overcome uncompleted breakdown, uncompleted cleanup of fracturing fluids and cold damages to the formations by injecting cold fluid (fluid at ambient conditions). Injecting fracturing fluids at ambient conditions have the tendency to decrease the near wellbore reservoir temperature below the freezing point of oil reservoir and hence leading to wax deposition around the wellbore thereby hampering the fluid production as well as fracture propagation. To overcome such problems, solutions such as hot fracturing fluid injection, encapsulated heat generating hydraulic fracturing fluid system, and injection of wax inhibitor techniques would be discussed. The paper would also be throwing light on changes in rheological properties occurred during heating fracturing fluids and solutions to deal with it taking economic considerations into account.

Keywords: hydrofracturing, waxy reservoirs, low temperature, viscosity, crosslinkers

Procedia PDF Downloads 258
26507 Commercial Automobile Insurance: A Practical Approach of the Generalized Additive Model

Authors: Nicolas Plamondon, Stuart Atkinson, Shuzi Zhou

Abstract:

The insurance industry is usually not the first topic one has in mind when thinking about applications of data science. However, the use of data science in the finance and insurance industry is growing quickly for several reasons, including an abundance of reliable customer data, ferocious competition requiring more accurate pricing, etc. Among the top use cases of data science, we find pricing optimization, customer segmentation, customer risk assessment, fraud detection, marketing, and triage analytics. The objective of this paper is to present an application of the generalized additive model (GAM) on a commercial automobile insurance product: an individually rated commercial automobile. These are vehicles used for commercial purposes, but for which there is not enough volume to apply pricing to several vehicles at the same time. The GAM model was selected as an improvement over GLM for its ease of use and its wide range of applications. The model was trained using the largest split of the data to determine model parameters. The remaining part of the data was used as testing data to verify the quality of the modeling activity. We used the Gini coefficient to evaluate the performance of the model. For long-term monitoring, commonly used metrics such as RMSE and MAE will be used. Another topic of interest in the insurance industry is to process of producing the model. We will discuss at a high level the interactions between the different teams with an insurance company that needs to work together to produce a model and then monitor the performance of the model over time. Moreover, we will discuss the regulations in place in the insurance industry. Finally, we will discuss the maintenance of the model and the fact that new data does not come constantly and that some metrics can take a long time to become meaningful.

Keywords: insurance, data science, modeling, monitoring, regulation, processes

Procedia PDF Downloads 76
26506 Investigation of Lead and Zinc Oxide Deposits Using Geological and Geophysical Techniques at Oshiri Province in Onicha Local Government Area of Ebonyi State Located Within Southeastern Part of Nigeria, West Africa

Authors: Amaechi O. Azi, Uche D. Aluge, Lim H. San, Godwin A. Agbo

Abstract:

This paper is centered on the investigation of mineral deposits in selected locations in Oshiri province in Ebonyi State. Mineral deposits contribute immensely to the economic growth of a society. In researching lead and zinc oxide-bearing sites at Oshiri, geological and geophysical research technique was employed. Petrozenith, Earth Resistivity Meter, and Schlumberger setup were selected to examine the electrical characteristics of the subsurface. To determine the apparent resistivity of the subsurface, five soundings were taken, and the field data were processed using WinResist software. The mudstone, lead-shale, shale-granite, and lateritic topsoil were the four geoelectric strata that were found. The third layer, which corresponds to the shale-lead lithology, has a resistivity value between 211.9 m to 807.7 m at a depth of 25 m. Due to its resistivity levels and geological trend, this layer makes an excellent signature for lead-zinc occurrence. This zone is expected to house deposits of lead and zinc oxide in commercial quantity.

Keywords: Schlumberger, current, resistivity, lithology

Procedia PDF Downloads 76
26505 Modeling Pan Evaporation Using Intelligent Methods of ANN, LSSVM and Tree Model M5 (Case Study: Shahroud and Mayamey Stations)

Authors: Hamidreza Ghazvinian, Khosro Ghazvinian, Touba Khodaiean

Abstract:

The importance of evaporation estimation in water resources and agricultural studies is undeniable. Pan evaporation are used as an indicator to determine the evaporation of lakes and reservoirs around the world due to the ease of interpreting its data. In this research, intelligent models were investigated in estimating pan evaporation on a daily basis. Shahroud and Mayamey were considered as the studied cities. These two cities are located in Semnan province in Iran. The mentioned cities have dry weather conditions that are susceptible to high evaporation potential. Meteorological data of 11 years of synoptic stations of Shahrood and Mayamey cities were used. The intelligent models used in this study are Artificial Neural Network (ANN), Least Squares Support Vector Machine (LSSVM), and M5 tree models. Meteorological parameters of minimum and maximum air temperature (Tmax, Tmin), wind speed (WS), sunshine hours (SH), air pressure (PA), relative humidity (RH) as selected input data and evaporation data from pan (EP) to The output data was considered. 70% of data is used at the education level, and 30 % of the data is used at the test level. Models used with explanation coefficient evaluation (R2) Root of Mean Squares Error (RMSE) and Mean Absolute Error (MAE). The results for the two Shahroud and Mayamey stations showed that the above three models' operations are rather appropriate.

Keywords: pan evaporation, intelligent methods, shahroud, mayamey

Procedia PDF Downloads 74
26504 Recent Advances in Pulse Width Modulation Techniques and Multilevel Inverters

Authors: Satish Kumar Peddapelli

Abstract:

This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have become popular and considerable interest by researcher are given on them. A fast Space-Vector Pulse Width Modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analysed.

Keywords: five-level inverter, space vector pulse wide modulation, diode clamped inverter, electrical engineering

Procedia PDF Downloads 388
26503 Technical and Economic Environment in the Polish Power System as the Basis for Distributed Generation and Renewable Energy Sources Development

Authors: Pawel Sowa, Joachim Bargiel, Bogdan Mol, Katarzyna Luszcz

Abstract:

The article raises the issue of the development of local renewable energy sources and the production of distributed energy in context of improving the reliability of the Polish Power System and the beneficial impact on local and national energy security. The paper refers to the current problems of local governments in the process of investment in the area of distributed energy projects, and discusses the issues of the future role and cooperation within the local power plants and distributed energy. Attention is paid to the local communities the chance to raise their own resources and management of energy fuels (biomass, wind, gas mining) and improving the local energy balance. The material presented takes the issue of the development of the energy potential of municipalities and future cooperation with professional energy. As an example, practical solutions used in one of the communes in Silesia.

Keywords: distributed generation, mini centers energy, renewable energy sources, reliability of supply of rural commune

Procedia PDF Downloads 600
26502 Synthesis and Characterisation of Bio-Based Acetals Derived from Eucalyptus Oil

Authors: Kirstin Burger, Paul Watts, Nicole Vorster

Abstract:

Green chemistry focuses on synthesis which has a low negative impact on the environment. This research focuses on synthesizing novel compounds from an all-natural Eucalyptus citriodora oil. Eight novel plasticizer compounds are synthesized and optimized using flow chemistry technology. A precursor to one novel compound can be synthesized from the lauric acid present in coconut oil. Key parameters, such as catalyst screening and loading, reaction time, temperature, residence time using flow chemistry techniques is investigated. The compounds are characterised using GC-MS, FT-IR, 1H and 13C-NMR techniques, X-ray crystallography. The efficiency of the compounds is compared to two commercial plasticizers, i.e. Dibutyl phthalate and Eastman 168. Several PVC-plasticized film formulations are produced using the bio-based novel compounds. Tensile strength, stress at fracture and percentage elongation are tested. The property of having increasing plasticizer percentage in the film formulations is investigated, ranging from 3, 6, 9 and 12%. The diastereoisomers of each compound are separated and formulated into PVC films, and differences in tensile strength are measured. Leaching tests, flexibility, and change in glass transition temperatures for PVC-plasticized films is recorded. Research objective includes using these novel compounds as a green bio-plasticizer alternative in plastic products for infants. The inhibitory effect of the compounds on six pathogens effecting infants are studied, namely; Escherichia coli, Staphylococcus aureus, Shigella sonnei, Pseudomonas putida, Salmonella choleraesuis and Klebsiella oxytoca.

Keywords: bio-based compounds, plasticizer, tensile strength, microbiological inhibition , synthesis

Procedia PDF Downloads 186
26501 Integration of Gravity and Seismic Methods in the Geometric Characterization of a Dune Reservoir: Case of the Zouaraa Basin, NW Tunisia

Authors: Marwa Djebbi, Hakim Gabtni

Abstract:

Gravity is a continuously advancing method that has become a mature technology for geological studies. Increasingly, it has been used to complement and constrain traditional seismic data and even used as the only tool to get information of the sub-surface. In fact, in some regions the seismic data, if available, are of poor quality and hard to be interpreted. Such is the case for the current study area. The Nefza zone is part of the Tellian fold and thrust belt domain in the north west of Tunisia. It is essentially made of a pile of allochthonous units resulting from a major Neogene tectonic event. Its tectonic and stratigraphic developments have always been subject of controversies. Considering the geological and hydrogeological importance of this area, a detailed interdisciplinary study has been conducted integrating geology, seismic and gravity techniques. The interpretation of Gravity data allowed the delimitation of the dune reservoir and the identification of the regional lineaments contouring the area. It revealed the presence of three gravity lows that correspond to the dune of Zouara and Ouchtata separated along with a positive gravity axis espousing the Ain Allega_Aroub Er Roumane axe. The Bouguer gravity map illustrated the compartmentalization of the Zouara dune into two depressions separated by a NW-SE anomaly trend. This constitution was confirmed by the vertical derivative map which showed the individualization of two depressions with slightly different anomaly values. The horizontal gravity gradient magnitude was performed in order to determine the different geological features present in the studied area. The latest indicated the presence of NE-SW parallel folds according to the major Atlasic direction. Also, NW-SE and EW trends were identified. The maxima tracing confirmed this direction by the presence of NE-SW faults, mainly the Ghardimaou_Cap Serrat accident. The quality of the available seismic sections and the absence of borehole data in the region, except few hydraulic wells that been drilled and showing the heterogeneity of the substratum of the dune, required the process of gravity modeling of this challenging area that necessitates to be modeled for the geometrical characterization of the dune reservoir and determine the different stratigraphic series underneath these deposits. For more detailed and accurate results, the scale of study will be reduced in coming research. A more concise method will be elaborated; the 4D microgravity survey. This approach is considered as an expansion of gravity method and its fourth dimension is time. It will allow a continuous and repeated monitoring of fluid movement in the subsurface according to the micro gal (μgall) scale. The gravity effect is a result of a monthly variation of the dynamic groundwater level which correlates with rainfall during different periods.

Keywords: 3D gravity modeling, dune reservoir, heterogeneous substratum, seismic interpretation

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26500 Review of K0-Factors and Related Nuclear Data of the Selected Radionuclides for Use in K0-NAA

Authors: Manh-Dung Ho, Van-Giap Pham, Van-Doanh Ho, Quang-Thien Tran, Tuan-Anh Tran

Abstract:

The k0-factors and related nuclear data, i.e. the Q0-factors and effective resonance energies (Ēr) of the selected radionuclides which are used in the k0-based neutron activation analysis (k0-NAA), were critically reviewed to be integrated in the “k0-DALAT” software. The k0- and Q0-factors of some short-lived radionuclides: 46mSc, 110Ag, 116m2In, 165mDy, and 183mW, were experimentally determined at the Dalat research reactor. The other radionuclides selected are: 20F, 36S, 49Ca, 60mCo, 60Co, 75Se, 77mSe, 86mRb, 115Cd, 115mIn, 131Ba, 134mCs, 134Cs, 153Gd, 153Sm, 159Gd, 170Tm, 177mYb, 192Ir, 197mHg, 239U and 239Np. The reviewed data as compared with the literature data were biased within 5.6-7.3% in which the experimental re-determined factors were within 6.1 and 7.3%. The NIST standard reference materials: Oyster Tissue (1566b), Montana II Soil (2711a) and Coal Fly Ash (1633b) were used to validate the new reviewed data showing that the new data gave an improved k0-NAA using the “k0-DALAT” software with a factor of 4.5-6.8% for the investigated radionuclides.

Keywords: neutron activation analysis, k0-based method, k0 factor, Q0 factor, effective resonance energy

Procedia PDF Downloads 126
26499 Optimizing Electric Vehicle Charging with Charging Data Analytics

Authors: Tayyibah Khanam, Mohammad Saad Alam, Sanchari Deb, Yasser Rafat

Abstract:

Electric vehicles are considered as viable replacements to gasoline cars since they help in reducing harmful emissions and stimulate power generation through renewable energy sources, hence contributing to sustainability. However, one of the significant obstacles in the mass deployment of electric vehicles is the charging time anxiety among users and, thus, the subsequent large waiting times for available chargers at charging stations. Data analytics, on the other hand, has revolutionized the decision-making tasks of management and operating systems since its arrival. In this paper, we attempt to optimize the choice of EV charging stations for users in their vicinity by minimizing the time taken to reach the charging stations and the waiting times for available chargers. Time taken to travel to the charging station is calculated by the Google Maps API and the waiting times are predicted by polynomial regression of the historical data stored. The proposed framework utilizes real-time data and historical data from all operating charging stations in the city and assists the user in finding the best suitable charging station for their current situation and can be implemented in a mobile phone application. The algorithm successfully predicts the most optimal choice of a charging station and the minimum required time for various sample data sets.

Keywords: charging data, electric vehicles, machine learning, waiting times

Procedia PDF Downloads 195
26498 Finding Data Envelopment Analysis Targets Using Multi-Objective Programming in DEA-R with Stochastic Data

Authors: R. Shamsi, F. Sharifi

Abstract:

In this paper, we obtain the projection of inefficient units in data envelopment analysis (DEA) in the case of stochastic inputs and outputs using the multi-objective programming (MOP) structure. In some problems, the inputs might be stochastic while the outputs are deterministic, and vice versa. In such cases, we propose a multi-objective DEA-R model because in some cases (e.g., when unnecessary and irrational weights by the BCC model reduce the efficiency score), an efficient decision-making unit (DMU) is introduced as inefficient by the BCC model, whereas the DMU is considered efficient by the DEA-R model. In some other cases, only the ratio of stochastic data may be available (e.g., the ratio of stochastic inputs to stochastic outputs). Thus, we provide a multi-objective DEA model without explicit outputs and prove that the input-oriented MOP DEA-R model in the invariable return to scale case can be replaced by the MOP-DEA model without explicit outputs in the variable return to scale and vice versa. Using the interactive methods for solving the proposed model yields a projection corresponding to the viewpoint of the DM and the analyst, which is nearer to reality and more practical. Finally, an application is provided.

Keywords: DEA-R, multi-objective programming, stochastic data, data envelopment analysis

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26497 The Nubian Ibex’s Distribution, Population, Habitat, and Conservation Status in Sudan’s Red Sea State Over the Past Decade

Authors: Lubna M. A. Hassan, Nasir Brema, Abdallah Mamy, Insaf Yahya, Tanzil A. G., Ahmed M. M. Hasoba, Omer A. Suliman

Abstract:

The Nubian ibex species has been categorized as vulnerable by the International Union for Conservation of Nature (IUCN) due to a lack of population data in specific regions within their habitat. This species faces numerous challenges, including habitat loss caused by agricultural practices, livestock rearing, mining activity, and infrastructure development. Additionally, competition with non-native species and hunting pose significant threats to their survival. Unfortunately, studies on the distribution, conservation status, ecology, and health of the ibex are limited and primarily descriptive in nature. In order to bridge this knowledge gap, recent surveys were conducted in the Red Sea State of Sudan during specific periods in 2015, 2016, 2019, and 2021. These surveys have provided valuable insights into the distribution, habitats, and conservation status of the Nubian ibex in the Red Sea State. The findings indicate that the Capra nubiana ibex can be found across more than 17 mountains in the Red Sea State. However, the total population estimate from recent years suggests that there are fewer than 250 individuals remaining. The study has also identified the highest altitude at which the Nubian ibex habitats existed in Sudan's Red Sea State, measuring 1675 m. This area harbors a diverse array of Nubian ibex habitats, encompassing a total of 21 wild plant species from 10 distinct families. The region experiences an average annual temperature ranging from 20.64°C in January to 33.30°C in August. Precipitation occurs in November and December, although it is characterized by unreliability and erratic patterns. It is important to note that these population estimates were obtained through surveys conducted in collaboration with rangers and local communities, and adjustments to survey methods are necessary to accommodate the challenging mountainous terrain, such as utilizing aerial surveys. To effectively address these threats, it is imperative to establish comprehensive long-term monitoring programs.

Keywords: Nubian ibex, distribution, population, habitats

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26496 Artificial Intelligence in the Design of High-Strength Recycled Concrete

Authors: Hadi Rouhi Belvirdi, Davoud Beheshtizadeh

Abstract:

The increasing demand for sustainable construction materials has led to a growing interest in high-strength recycled concrete (HSRC). Utilizing recycled materials not only reduces waste but also minimizes the depletion of natural resources. This study explores the application of artificial intelligence (AI) techniques to model and predict the properties of HSRC. In the past two decades, the production levels in various industries and, consequently, the amount of waste have increased significantly. Continuing this trend will undoubtedly cause irreparable damage to the environment. For this reason, engineers have been constantly seeking practical solutions for recycling industrial waste in recent years. This research utilized the results of the compressive strength of 90-day high-strength recycled concrete. The method for creating recycled concrete involved replacing sand with crushed glass and using glass powder instead of cement. Subsequently, a feedforward artificial neural network was employed to model the compressive strength results for 90 days. The regression and error values obtained indicate that this network is suitable for modeling the compressive strength data.

Keywords: high-strength recycled concrete, feedforward artificial neural network, regression, construction materials

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26495 Tectonic Complexity: Out-of-Sequence Thrusting in the Higher Himalaya of Jhakri-Sarahan region, Himachal Pradesh, India

Authors: Rajkumar Ghosh

Abstract:

The study focuses on the tectonics of out-of-sequence thrusting (OOST) in the NW region of the Himalaya, particularly in Himachal Pradesh. The research aims to identify the features and nature of OOST in the field and the associated rock types and lithological boundaries in the field of NW Himalaya, Himachal Pradesh, India. The research employs fieldwork and micro-structure observations, correlations, and analyses to identify and analyze the OOST features and associated rock types. The study reveals the presence of three OOSTs, namely Jhakri Thrust (JT), Sarahan Thrust (ST), and Chaura Thrust (CT), which consist of several branches, some of which are still active. The thrust system exhibits varying internal geometry, including box folds, boudins, scar folds, crenulation cleavages, kink folds, and tension gashes. The CT, which is concealed beneath Jutogh Thrust sheet, represents a steepened downward thrust, while the JT has a western dip and is south-westward verging. The research provides crucial information on the tectonics of OOST in the NW region of the Himalaya, particularly in Himachal Pradesh, which is crucial in understanding the regional geological evolution and associated hazards. The data were collected through fieldwork and micro-structure observations, correlations, and analyses of rock samples. The data were analyzed using tectonic and geochronological techniques to identify the nature and characteristics of OOST. The research addressed the question of identifying Higher Himalayan OOST in the field of NW Himalaya, Himachal Pradesh, India, and the associated rock types and lithological boundaries. The study concludes that there is minimal documentation and a lack of suitable exposure of rocks to generalize the features of OOST in the field in NW Higher Himalaya, Himachal Pradesh. The study recommends more extensive mapping and fieldwork to improve understanding of OOST in the region.

Keywords: out-of-sequence thrust (OOST), main central thrust (MCT), jhakri thrust (JT), sarahan thrust (ST), chaura thrust (CT), higher himalaya (HH)

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26494 Integrated Model for Enhancing Data Security Processing Time in Cloud Computing

Authors: Amani A. Saad, Ahmed A. El-Farag, El-Sayed A. Helali

Abstract:

Cloud computing is an important and promising field in the recent decade. Cloud computing allows sharing resources, services and information among the people of the whole world. Although the advantages of using clouds are great, but there are many risks in a cloud. The data security is the most important and critical problem of cloud computing. In this research a new security model for cloud computing is proposed for ensuring secure communication system, hiding information from other users and saving the user's times. In this proposed model Blowfish encryption algorithm is used for exchanging information or data, and SHA-2 cryptographic hash algorithm is used for data integrity. For user authentication process a simple user-name and password is used, the password uses SHA-2 for one way encryption. The proposed system shows an improvement of the processing time of uploading and downloading files on the cloud in secure form.

Keywords: cloud computing, data security, SAAS, PAAS, IAAS, Blowfish

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26493 Rock Thickness Measurement by Using Self-Excited Acoustical System

Authors: Janusz Kwaśniewski, Ireneusz Dominik, Krzysztof Lalik

Abstract:

The knowledge about rock layers thickness, especially above drilled mining pavements are crucial for workers safety. The measuring systems used nowadays are generally imperfect and there is a strong demand for improvement. The application of a new type of a measurement system called Self-Excited Acoustical System is presented in the paper. The system was applied until now to monitor stress changes in metal and concrete constructions. The change in measurement methodology resulted in possibility of measuring the thickness of the rocks above the tunnels as well as thickness of a singular rock layer. The idea is to find two resonance frequencies of the self-exited system, which consists of a vibration exciter and vibration receiver placed at a distance, which are coupled with a proper power amplifier, and which operate in a closed loop with a positive feedback. The resonance with the higher amplitude determines thickness of the whole rock, whereas the lower amplitude resonance indicates thickness of a singular layer. The results of the laboratory tests conducted on a group of different rock materials are also presented.

Keywords: auto-oscillator, non-destructive testing, rock thickness measurement, geotechnic

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26492 Comparison of Statistical Methods for Estimating Missing Precipitation Data in the River Subbasin Lenguazaque, Colombia

Authors: Miguel Cañon, Darwin Mena, Ivan Cabeza

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In this work was compared and evaluated the applicability of statistical methods for the estimation of missing precipitations data in the basin of the river Lenguazaque located in the departments of Cundinamarca and Boyacá, Colombia. The methods used were the method of simple linear regression, distance rate, local averages, mean rates, correlation with nearly stations and multiple regression method. The analysis used to determine the effectiveness of the methods is performed by using three statistical tools, the correlation coefficient (r2), standard error of estimation and the test of agreement of Bland and Altmant. The analysis was performed using real rainfall values removed randomly in each of the seasons and then estimated using the methodologies mentioned to complete the missing data values. So it was determined that the methods with the highest performance and accuracy in the estimation of data according to conditions that were counted are the method of multiple regressions with three nearby stations and a random application scheme supported in the precipitation behavior of related data sets.

Keywords: statistical comparison, precipitation data, river subbasin, Bland and Altmant

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26491 A phytochemical and Biological Study of Viscum schemperi Engl. Growing in Saudi Arabia

Authors: Manea A. I. Alqrad, Alaa Sirwi, Sabrin R. M. Ibrahim, Hossam M. Abdallah, Gamal A. Mohamed

Abstract:

Phytochemical study of the methanolic extract of the air dried powdered of the parts of Viscum schemperi Engl. (Family: Viscaceae) using different chromatographic techniques led to the isolation of five compounds: -amyrenone (1), betulinic acid (2), (3β)-olean-12-ene-3,23-diol (3), -oleanolic acid (4), and α-oleanolic acid (5). Their structures were established based on physical, chemical, and spectral data. Anti-inflammatory and anti-apoptotic activities of oleanolic acid in a mouse model of acute hepatorenal damage were assessed. This study showed the efficacy of oleanolic acid to counteract thioacetamide-induced hepatic and kidney injury in mice through the reduction of hepatocyte oxidative damage, suppression of inflammation, and apoptosis. More importantly, oleanolic acid suppressed thioacetamide-induced hepatic and kidney injury by inhibiting NF-κB/TNF-α-mediated inflammation/apoptosis and enhancing SIRT1/Nrf2/Heme-oxygenase signalling pathway. These promising pharmacological activities suggest the potential use of oleanolic acid against hepatorenal damage.

Keywords: oleanolic acid, viscum schimperi, thioacetamide, SIRT1/Nrf2/NF-κB, hepatorenal damage

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26490 Hyperspectral Data Classification Algorithm Based on the Deep Belief and Self-Organizing Neural Network

Authors: Li Qingjian, Li Ke, He Chun, Huang Yong

Abstract:

In this paper, the method of combining the Pohl Seidman's deep belief network with the self-organizing neural network is proposed to classify the target. This method is mainly aimed at the high nonlinearity of the hyperspectral image, the high sample dimension and the difficulty in designing the classifier. The main feature of original data is extracted by deep belief network. In the process of extracting features, adding known labels samples to fine tune the network, enriching the main characteristics. Then, the extracted feature vectors are classified into the self-organizing neural network. This method can effectively reduce the dimensions of data in the spectrum dimension in the preservation of large amounts of raw data information, to solve the traditional clustering and the long training time when labeled samples less deep learning algorithm for training problems, improve the classification accuracy and robustness. Through the data simulation, the results show that the proposed network structure can get a higher classification precision in the case of a small number of known label samples.

Keywords: DBN, SOM, pattern classification, hyperspectral, data compression

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26489 Adaptive Anchor Weighting for Improved Localization with Levenberg-Marquardt Optimization

Authors: Basak Can

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This paper introduces an iterative and weighted localization method that utilizes a unique cost function formulation to significantly enhance the performance of positioning systems. The system employs locators, such as Gateways (GWs), to estimate and track the position of an End Node (EN). Performance is evaluated relative to the number of locators, with known locations determined through calibration. Performance evaluation is presented utilizing low cost single-antenna Bluetooth Low Energy (BLE) devices. The proposed approach can be applied to alternative Internet of Things (IoT) modulation schemes, as well as Ultra WideBand (UWB) or millimeter-wave (mmWave) based devices. In non-line-of-sight (NLOS) scenarios, using four or eight locators yields a 95th percentile localization performance of 2.2 meters and 1.5 meters, respectively, in a 4,305 square feet indoor area with BLE 5.1 devices. This method outperforms conventional RSSI-based techniques, achieving a 51% improvement with four locators and a 52 % improvement with eight locators. Future work involves modeling interference impact and implementing data curation across multiple channels to mitigate such effects.

Keywords: lateration, least squares, Levenberg-Marquardt algorithm, localization, path-loss, RMS error, RSSI, sensors, shadow fading, weighted localization

Procedia PDF Downloads 25