Search results for: ground data

Authors: Mais Haj Qasem, Maen M. Al Assaf, Ali Rodan

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Parallel hybrid storage systems consist of a hierarchy of different storage devices that vary in terms of data reading speed performance. As we ascend in the hierarchy, data reading speed becomes faster. Thus, migrating the application’ important data that will be accessed in the near future to the uppermost level will reduce the application I/O waiting time; hence, reducing its execution elapsed time. In this research, we implement trace-driven two-levels parallel hybrid storage system prototype that consists of HDDs and SSDs. The prototype uses data mining techniques to classify application’ data in order to determine its near future data accesses in parallel with the its on-demand request. The important data (i.e. the data that the application will access in the near future) are continuously migrated to the uppermost level of the hierarchy. Our simulation results show that our data migration approach integrated with data mining techniques reduces the application execution elapsed time when using variety of traces in at least to 22%.

Keywords: hybrid storage system, data mining, recurrent neural network, support vector machine

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Authors: Kalpana Adhikari, Mandip Subedi, Keshab Sharma, Indra P. Acharya

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The Gorkha Nepal earthquake of moment magnitude (Mw) 7.8 struck the central region of Nepal on April 25, 2015 with the epicenter about 77 km northwest of Kathmandu Valley . Peak ground acceleration observed during the earthquake was 0.18g. This motion induced several geotechnical effects such as landslides, foundation failures liquefaction, lateral spreading and settlement, and local amplification. An aftershock of moment magnitude (Mw) 7.3 hit northeast of Kathmandu on May 12 after 17 days of main shock caused additional damages. Kathmandu is the largest city in Nepal, have a population over four million. As the Kathmandu Valley deposits are composed mainly of sand, silt and clay layers with a shallow ground water table, liquefaction is highly anticipated. Extensive liquefaction was also observed in Kathmandu Valley during the 1934 Nepal-Bihar earthquake. Field investigations were carried out in Kathmandu Valley immediately after Mw 7.8, April 25 main shock and Mw 7.3, May 12 aftershock. Geotechnical investigation of both liquefied and non-liquefied sites were conducted after the earthquake. This paper presents observations of liquefaction and liquefaction induced damage, and the liquefaction potential assessment based on Standard Penetration Tests (SPT) for liquefied and non-liquefied sites. SPT based semi-empirical approach has been used for evaluating liquefaction potential of the soil and Liquefaction Potential Index (LPI) has been used to determine liquefaction probability. Recorded ground motions from the event are presented. Geological aspect of Kathmandu Valley and local site effect on the occurrence of liquefaction is described briefly. Observed liquefaction case studies are described briefly. Typically, these are sand boils formed by freshly ejected sand forced out of over-pressurized sub-strata. At most site, sand was ejected to agricultural fields forming deposits that varied from millimetres to a few centimeters thick. Liquefaction-induced damage to structures in these areas was not significant except buildings on some places tilted slightly. Boiled soils at liquefied sites were collected and the particle size distributions of ejected soils were analyzed. SPT blow counts and the soil profiles at ten liquefied and non-liquefied sites were obtained. The factors of safety against liquefaction with depth and liquefaction potential index of the ten sites were estimated and compared with observed liquefaction after 2015 Gorkha earthquake. The liquefaction potential indices obtained from the analysis were found to be consistent with the field observation. The field observations along with results from liquefaction assessment were compared with the existing liquefaction hazard map. It was found that the existing hazard maps are unrepresentative and underestimate the liquefaction susceptibility in Kathmandu Valley. The lessons learned from the liquefaction during this earthquake are also summarized in this paper. Some recommendations are also made to the seismic liquefaction mitigation in the Kathmandu Valley.

Keywords: factor of safety, geotechnical investigation, liquefaction, Nepal earthquake

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Authors: Fulya Gokalp Yavuz, Mark Daniel Ward

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This study focuses on a contemporary and inevitable topic of Data Science and its exemplary application for early career building: Big Data and Leaving Learning Community (LLC). ‘Academia’ and ‘Industry’ have a common sense on the importance of Big Data. However, both of them are in a threat of missing the training on this interdisciplinary area. Some traditional teaching doctrines are far away being effective on Data Science. Practitioners needs some intuition and real-life examples how to apply new methods to data in size of terabytes. We simply explain the scope of Data Science training and exemplified its early stage application with LLC, which is a National Science Foundation (NSF) founded project under the supervision of Prof. Ward since 2014. Essentially, we aim to give some intuition for professors, researchers and practitioners to combine data science tools for comprehensive real-life examples with the guides of mentees’ feedback. As a result of discussing mentoring methods and computational challenges of Big Data, we intend to underline its potential with some more realization.

Keywords: Big Data, computation, mentoring, training

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Authors: Ricky Saputra, Rashmi Walvekar, Mohammad Khalid

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Landfills, water contamination, and toxic gas emission are a few impacts faced by the environment due to the increasing number of αof waste rubber tires (WRT). In spite of such concerning issue, only minimal efforts are taken to reclaim or recycle these wastes as their products are generally not-profitable for companies. Unlike the typical reclamation process, devulcanization is a method to selectively cleave sulfidic bonds within vulcanizates to avoid polymeric scissions that compromise elastomer’s mechanical and tensile properties. The process also produces devulcanizates that are re-processable similar to virgin rubber. Often, a devulcanizing agent is needed. In the current study, novel and sustainable ammonium chloride-based ternary deep eutectic solvents (TDES), with a different number of α-hydrogens, were utilised to devulcanize ground rubber tire (GRT) as an effort to implement green chemistry to tackle such issue. 40-mesh GRT were soaked for 1 day with different TDESs and sonicated at 37-80 kHz for 60-120 mins and heated at 100-140oC for 30-90 mins. Devulcanizates were then filtered, dried, and evaluated based on the percentage of by means of Flory-Rehner calculation and swelling index. The result shows that an increasing number of α-Hs increases the degree of devulcanization, and the value achieved was around eighty-percent, thirty percent higher than the typical industrial-autoclave method. Resulting bondages of devulcanizates were also analysed by Fourier transform infrared spectrometer (FTIR), Horikx fitting, and thermogravimetric analyser (TGA). The earlier two confirms only sulfidic scissions were experienced by GRT through the treatment, while the latter proves the absence or negligibility of carbon-chains scission.

Keywords: ammonium, sustainable, deep eutectic solvent, α-hydrogen, waste rubber tire

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Authors: Farnaz Nazem

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Iranian architects had creative ways for constructing the buildings in each climate. Some of these architectural elements were made under the ground. Shovadan is one of these underground spaces in hot- humid regions in Dezfoul and Shoushtar city that had special functions and characteristics. In this paper some subjects such as the history of Shovadan, its elements and effective factors in the formation of Shovadan in Dezfool city are discussed.

Keywords: architecture, dezfoul city, Shovadan, south west of Iran

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Authors: Larry V. Aceres, Jesryl B. Paulite, Emelie M. Pelicano, J. B. Anciano, J. A. Esteban

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Enhancing the population of beneficial arthropods under less diverse agroecosystem is the most sought by many researchers and plant growers. This strategy was done through the establishment of pintoi peanut, Arachis pintoi as live mulch or cover crop in pummelo orchard of the University of Southeastern Philippines (USeP), Mabini, Compostela Valley Province, Philippines. This study was conducted to compare and compute population dynamics and diversity of beneficial arthropods in pummelo in with and without Arachis pintoi cover crop. Data collections were done for the 12-month period (from June 2013 to May 2014) at the pummelo orchard of USeP Mabini Campus, COMVAL Province, Philippines and data were analyzed using the Independent Samples T-Test to compare the effect of the presence and absence of Arachis pintoi on beneficial arthropods incidence in pummelo orchard. Moreover, diversity and family richness analyses were computed using the Margalef’s diversity index for family richness; the Shannon index of general diversity and the evenness index; and the Simpson index of dominance. Results revealed numerically and statistically higher density of important beneficial arthropods such as microhymenopterans, macrohymenopterans, spiders, tachinid flies and ground beetles were recorded in pummelo orchard with Arachis pintoi than from without Arachis pintoi cover crop for the 12-month observation period. Further, the result of the study revealed the high family richness and diversity index with more or less even distribution of individuals within the family and low dominance index were documented in pummelo with Arachis pintoi cover crop than from pummelo without Arachis pintoi cover crop. The study revealed that planting A. pintoi in pummelo orchard could enhance natural enemy populations.

Keywords: Arachis pintoi, cover crop, beneficial arthropods, pummelo

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Authors: Mohamed Elkholy, Ahmed Elfatatry

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Cloud computing has emerged as a flexible computing paradigm that reshaped the Information Technology map. However, cloud computing brought about a number of security challenges as a result of the physical distribution of computational resources and the limited control that users have over the physical storage. This situation raises many security challenges for data integrity and confidentiality as well as authentication and access control. This work proposes a security mechanism for data integrity that allows a data owner to be aware of any modification that takes place to his data. The data integrity mechanism is integrated with an extended Kerberos authentication that ensures authorized access control. The proposed mechanism protects data confidentiality even if data are stored on an untrusted storage. The proposed mechanism has been evaluated against different types of attacks and proved its efficiency to protect cloud data storage from different malicious attacks.

Keywords: access control, data integrity, data confidentiality, Kerberos authentication, cloud security

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Authors: Simran Baweja, Bhavika Kalal, Surajit Maity

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Photoinduced tautomerization reactions have been the centre of attention among the scientific community over the past several decades because of their significance in various biological systems. 7-azaindole (7AI) is considered a model system for DNA base pairing and to understand the role of such tautomerization reactions in mutations. To the best of our knowledge, extensive studies have been carried out on 7-azaindole and its solvent clusters exhibiting proton/ hydrogen transfer in both solution as well as gas phases. Derivatives of the above molecule, like 2,7- and 2,6-diazaindoles are proposed to have even better photophysical properties due to the presence of -aza group on the 2nd position. However, there are studies in the solution phase that suggest the relevance of these molecules, but there are no experimental studies reported in the gas phase yet. In our current investigation, we present the first gas phase spectroscopic data of 2,7-diazaindole (2,7-DAI) and its solvent cluster (2,7-DAI-H2O). In this, we have employed state-of-the-art laser spectroscopic methods such as fluorescence excitation (LIF), dispersed fluorescence (DF), resonant two-photon ionization-time of flight mass spectrometry (2C-R2PI), photoionization efficiency spectroscopy (PIE), IR-UV double resonance spectroscopy, i.e., fluorescence-dip infrared spectroscopy (FDIR) and resonant ion-dip infrared spectroscopy (IDIR) to understand the electronic structure of the molecule. The origin band corresponding to the S1 ← S0 transition of the bare 2,7-DAI is found to be positioned at 33910 cm-1, whereas the origin band corresponding to S1 ← S0 transition of the 2,7-DAI-H2O is positioned at 33074 cm-1. The red-shifted transition in the case of solvent cluster suggests the enhanced feasibility of excited state hydrogen/ proton transfer. The ionization potential for the 2,7-DAI molecule is found to be 8.92 eV which is significantly higher than the previously reported 7AI (8.11 eV) molecule, making it a comparatively complex molecule to study. The ionization potential is reduced by 0.14 eV in the case of 2,7-DAI-H2O (8.78 eV) cluster compared to that of 2,7-DAI. Moreover, on comparison with the available literature values of 7AI, we found the origin band of 2,7-DAI and 2,7-DAI-H2O to be red-shifted by -729 and -280 cm-1 respectively. The ground and excited state N-H stretching frequencies of the 27DAI molecule were determined using fluorescence-dip infrared spectra (FDIR) and resonant ion dip infrared spectroscopy (IDIR), obtained at 3523 and 3467 cm-1, respectively. The lower value of vNH in the electronically excited state of 27DAI implies the higher acidity of the group compared to the ground state. Moreover, we have done extensive computational analysis, which suggests that the energy barrier in the excited state reduces significantly as we increase the number of catalytic solvent molecules (S= H2O, NH3) as well as the polarity of solvent molecules. We found that the ammonia molecule is a better candidate for hydrogen transfer compared to water because of its higher gas-phase basicity. Further studies are underway to understand the excited state dynamics and photochemistry of such N-rich chromophores.

Keywords: excited state hydrogen transfer, supersonic expansion, gas phase spectroscopy, IR-UV double resonance spectroscopy, laser induced fluorescence, photoionization efficiency spectroscopy

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Authors: Bourama Mane, Ibrahima Fall, Mamadou Samba Camara, Alassane Bah

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At the level of the National Statistical Institutes, there is a large volume of data which is generally in a format which conditions the method of publication of the information they contain. Each household or business data collection project includes a dissemination platform for its implementation. Thus, these dissemination methods previously used, do not promote rapid access to information and especially does not offer the option of being able to link data for in-depth processing. In this paper, we present an approach to modeling these data to publish them in a format intended for the Semantic Web. Our objective is to be able to publish all this data in a single platform and offer the option to link with other external data sources. An application of the approach will be made on data from major national surveys such as the one on employment, poverty, child labor and the general census of the population of Senegal.

Keywords: Semantic Web, linked open data, database, statistic

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Authors: Shadi Fathi, Moura Mehravar, Mujib Rahman

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The railwaytransportation network in the UK is over 100 years old and is known as one of the oldest mass transit systems in the world. This aged track network requires frequent closure for maintenance. One of the main reasons for closure is inadequate drainage due to the leakage in the buried drainage pipes. The leaking water can cause localised subgrade weakness, which subsequently can lead to major ground/substructure failure.Different condition assessment methods are available to assess the railway substructure. However, the existing condition assessment methods are not able to detect any local ground weakness/damageand provide details of the damage (e.g. size and location). To tackle this issue, a hybrid back-analysis technique based on artificial neural network (ANN) and genetic algorithm (GA) has been developed to predict the substructurelayers’ moduli and identify any soil weaknesses. At first, afinite element (FE) model of a railway track section under Falling Weight Deflection (FWD) testing was developed and validated against field trial. Then a drainage pipe and various scenarios of the local defect/ soil weakness around the buried pipe with various geometriesand physical properties were modelled. The impact of the soil local weaknesson the track surface deflection wasalso studied. The FE simulations results were used to generate a database for ANN training, and then a GA wasemployed as an optimisation tool to optimise and back-calculate layers’ moduli and soil weakness moduli (ANN’s input). The hybrid ANN-GA back-analysis technique is a computationally efficient method with no dependency on seed modulus values. The modelcan estimate substructures’ layer moduli and the presence of any localised foundation weakness.

Keywords: finite element (FE) model, drainage defect, falling weight deflectometer (FWD), hybrid ANN-GA

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Authors: Ch. Sridevi, S. P. Shailender Kumar, B. Gurudayal, A. Chalapathi Rao, K. Koteswara Rao, P. Srinivasulu

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System reliability and system availability evaluation plays a crucial role in ensuring the seamless operation of complex satellite data reception system with consistent performance for longer periods. This paper presents a novel approach for the same using a case study on one of the antenna systems at satellite data reception ground station in India. The methodology involves analyzing system's components, their failure rates, system's architecture, generation of logical reliability block diagram model and estimating the reliability of the system using the component level mean time between failures considering exponential distribution to derive a baseline estimate of the system's reliability. The model is then validated with collected system level field failure data from the operational satellite data reception systems that includes failure occurred, failure time, criticality of the failure and repair times by using statistical techniques like median rank, regression and Weibull analysis to extract meaningful insights regarding failure patterns and practical reliability of the system and to assess the accuracy of the developed reliability model. The study mainly focused on identification of critical units within the system, which are prone to failures and have a significant impact on overall performance and brought out a reliability model of the identified critical unit. This model takes into account the interdependencies among system components and their impact on overall system reliability and provides valuable insights into the performance of the system to understand the Improvement or degradation of the system over a period of time and will be the vital input to arrive at the optimized design for future development. It also provides a plug and play framework to understand the effect on performance of the system in case of any up gradations or new designs of the unit. It helps in effective planning and formulating contingency plans to address potential system failures, ensuring the continuity of operations. Furthermore, to instill confidence in system users, the duration for which the system can operate continuously with the desired level of 3 sigma reliability was estimated that turned out to be a vital input to maintenance plan. System availability and station availability was also assessed by considering scenarios of clash and non-clash to determine the overall system performance and potential bottlenecks. Overall, this paper establishes a comprehensive methodology for reliability and availability analysis of complex satellite data reception systems. The results derived from this approach facilitate effective planning contingency measures, and provide users with confidence in system performance and enables decision-makers to make informed choices about system maintenance, upgrades and replacements. It also aids in identifying critical units and assessing system availability in various scenarios and helps in minimizing downtime and optimizing resource allocation.

Keywords: exponential distribution, reliability modeling, reliability block diagram, satellite data reception system, system availability, weibull analysis

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Authors: Nazura Abdul Manap, Siti Nur Farah Atiqah Salleh

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For decades, the misuse of personal data has been a critical issue. Malaysia has accepted responsibility by implementing the Malaysian Personal Data Protection Act 2010 to secure personal data (PDPA 2010). After more than a decade, this legislation is set to be revised by the current PDPA 2023 Amendment Bill to align with the world's key personal data protection regulations, such as the European Union General Data Protection Regulations (GDPR). Among the other suggested adjustments is the Data User's appointment of a Data Protection Officer (DPO) to ensure the commercial entity's compliance with the PDPA 2010 criteria. The change is expected to be enacted in parliament fairly soon; nevertheless, based on the experience of the Personal Data Protection Department (PDPD) in implementing the Act, it is projected that there will be a slew of additional concerns associated with the DPO mandate. Consequently, the goal of this article is to highlight the issues that the DPO will encounter and how the Personal Data Protection Department should respond to this subject. The study result was produced using a qualitative technique based on an examination of the current literature. This research reveals that there are probable obstacles experienced by the DPO, and thus, there should be a definite, clear guideline in place to aid DPO in executing their tasks. It is argued that appointing a DPO is a wise measure in ensuring that the legal data security requirements are met.

Keywords: guideline, law, data protection officer, personal data

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Authors: Nouha Mhimdi, Wahiba Ben Abdessalem Karaa, Henda Ben Ghezala

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The methods identified in data collection are diverse: electronic media, focus group interviews and short-answer questionnaires [1]. The collection of poor-quality data resulting, for example, from poorly designed questionnaires, the absence of good translators or interpreters, and the incorrect recording of data allow conclusions to be drawn that are not supported by the data or to focus only on the average effect of the program or policy. There are several solutions to avoid or minimize the most frequent errors, including obtaining expert advice on the design or adaptation of data collection instruments; or use technologies allowing better "anonymity" in the responses [2]. In this context, we opted to collect good quality data by doing a sizeable questionnaire-based survey on hospital emergencies to improve emergency services and alleviate the problems encountered. At the level of this paper, we will present our study, and we will detail the steps followed to achieve the collection of relevant, consistent and practical data.

Keywords: data collection, survey, questionnaire, database, data analysis, hospital emergencies

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Authors: Ananya Gangavarapu

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Convolutional Neural Networks (CNN) based models are providing diagnostic capabilities on par with the medical specialists in many specialty areas. However, collecting the medical data for training purposes is very challenging because of the increased regulations around data collections and privacy concerns around personal health data. The gathering of the data becomes even more difficult if the capture devices are edge-based mobile devices (like smartphones) with feeble wireless connectivity in rural/remote areas. In this paper, I would like to highlight Federated Learning approach to mitigate data privacy and security issues.

Keywords: deep learning in healthcare, data privacy, federated learning, training in distributed environment

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Authors: Benmessaoud Hassen

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We propose in this study to address the impact of socio-economic and environmental impact on the physical environment, especially their spatiotemporal dynamics in semi-arid and arid eastern Aurès. Including 11 municipalities, the study area spreads out over a relatively large surface area of about 60.000 ha. The hindsight is quite important and is determined by 03 days of analysis of environmental variation spread over thirty years (between 1987 and 2007). The multi-source data acquired in this context are integrated into a geographic information system (GIS).This allows, among other indices to calculate areas and classes for each thematic layer of the 4 layers previously defined by a method inspired MEDALUS (Mediterranean Desertification and Land Use).The database created is composed of four layers of information (population, livestock, farming and land use). His analysis in space and time has been supplemented by a validation of the ground truth. Once the database has corrected it used to develop the comprehensive map with the calculation of the index of socio-economic and environmental (ISCE). The map supports and the resulting information does not consist only of figures on the present situation but could be used to forecast future trends.

Keywords: impact of socio-economic and environmental, spatiotemporal dynamics, semi-arid environments, GIS, Eastern Aurès

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Authors: Mohd Amran, Chan Yi Jing, Chong Chien Hwa

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Production of biogas from POME requires anaerobic digestion (AD), thus, anaerobic digester performance in biogas plants is crucial. As POME from different sources have varying characteristics due to different process flows in mills, there is no ideal treatment parameters for POME. Hence, different treatment plants alter different parameters in anaerobic digestion to achieve desired biogas production levels and to meet POME waste discharge limits. The objective of this study is to evaluate the performance of mesophilic anaerobic digestion in four different biogas plants in Malaysia. Aspects of POME pre-treatment efficiency, analysis of treated POME and AD’s bottom sludge characteristics, including several parameters like chemical oxygen demand (COD), biological oxygen demand (BOD), total solid (TS) removal in the effluent, pH and temperature changes, total biogas produced, the composition of biogas including methane (CH₄), carbon dioxide (CO₂), hydrogen sulfide (H₂S) and oxygen (O₂) were investigated. The effect of organic loading rate (OLR) and hydraulic retention time (HRT) on anaerobic digester performance is also evaluated. In pre-treatment, it is observed that BGP B has the lowest average outlet temperature of 40.41°C. All BGP shows a high-temperature fluctuation (36 to 49 0C) and good pH readings (minimum 6.7), leaving the pre-treatment facility before entering the AD.COD removal of POME is considered good, with an average of 78% and maximum removal of 85%. BGP C has the lowest average COD and TS content in treated POME, 13,313 mg/L, and 12,048 mg/L, respectively. However, it is observed that the treated POME leaving all ADs, still contains high-quality organic substances (COD between 12,000 to 19,000 mg/L) that might be able to digest further to produce more biogas. The biogas produced in all four BGPs varies due to different COD loads. BGP B has the highest amount of biogas produced, 378,874.7 Nm³/month, while BGP D has the lowest biogas production of 272,378.5 Nm³/month. Furthermore, the composition of biogas produced in all plants is well within literature values (CH4 between 55 to 65% and CO₂ between 32 to 36%).

Keywords: palm oil mill effluent, in-ground lagoon anaerobic digester, anaerobic digestion, biogas

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Authors: K. R. Sreenivas, Shaurya Kaushal

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After sunset, under calm & clear-sky nocturnal conditions, the air layer near the surface containing aerosols cools through radiative processes to the upper atmosphere. Due to this cooling, surface air-layer temperature can fall 2-6 degrees C lower than the ground-surface temperature. This unstable convection layer, on the top, is capped by a stable inversion-boundary layer. Radiative divergence, along with the convection within the surface layer, governs the vertical transport of heat and moisture. Micro-physics in this layer have implications for the occurrence and growth of the fog layer. This particular configuration, featuring a convective mixed layer beneath a stably stratified inversion layer, exemplifies a classic case of penetrative convection. In this study, we conduct numerical simulations of the penetrative convection phenomenon within the nocturnal atmospheric surface layer and elucidate its relevance to the dynamics of fog layers. We employ field and laboratory measurements of aerosol number density to model the strength of the radiative cooling. Our analysis encompasses horizontally averaged, vertical profiles of temperature, density, and heat flux. The energetic incursion of the air from the mixed layer into the stable inversion layer across the interface results in entrainment and the growth of the mixed layer, modeling of which is the key focus of our investigation. In our research, we ascertain the appropriate length scale to employ in the Richardson number correlation, which allows us to estimate the entrainment rate and model the growth of the mixed layer. Our analysis of the mixed layer and the entrainment zone reveals a close alignment with previously reported laboratory experiments on penetrative convection. Additionally, we demonstrate how aerosol number density influences the growth or decay of the mixed layer. Furthermore, our study suggests that the presence of fog near the ground surface can induce extensive vertical mixing, a phenomenon observed in field experiments.

Keywords: inversion layer, penetrative convection, radiative cooling, fog occurrence

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Authors: Daniel Brian Thompson, Subarmaniam Kannan

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The huge weightage of knowledge in this world and within the repository of organizations has already reached immense capacity and is constantly increasing as time goes by. To accommodate these constraints, Big Data implementation and algorithms are utilized to obtain new or enhanced knowledge for decision-making. With the transition from data to knowledge provides the transformational changes which will provide tangible benefits to the individual implementing these practices. Today, various organization would derive knowledge from observations and intuitions where this information or data will be translated into best practices for knowledge acquisition, generation and sharing. Through the widespread usage of Big Data, the main intention is to provide information that has been cleaned and analyzed to nurture tangible insights for an organization to apply to their knowledge-creation practices based on facts and figures. The translation of data into knowledge will generate value for an organization to make decisive decisions to proceed with the transition of best practices. Without a strong foundation of knowledge and Big Data, businesses are not able to grow and be enhanced within the competitive environment.

Keywords: big data, knowledge management, data driven, knowledge creation

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Authors: Gia Lam Le, Dennis T. Bergado, Thi Ngoc Truc Nguyen

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This study focuses on behaviors of improved soft clay using prefabricated vertical drain (PVD) combined with vacuum and electro-osmotic preloading. Large-scale consolidations of reconstituted soft Bangkok clay were conducted for PVD improvement with vacuum (vacuum-PVD), and vacuum combined with heat (vacuum-thermo-PVD). The research revealed that vacuum-thermo-PVD gives high efficiency of the consolidation rate compared to the vacuum-PVD. In addition, the magnitude of settlement of the specimen improved by the vacuum-thermo-PVD is higher than the vacuum-PVD because the assistance of heat causes the collapse of the clay structure. Particularly, to reach 90% degree of consolidation, the thermal-vacuum-PVD reduced about 58% consolidation time compared to the vacuum-PVD. The increase in consolidation rate is resulted from the increase in horizontal coefficient of consolidation, Ch, the reduction of the smear effect expressed by the ratio of the horizontal hydraulic conductivity in the undisturbed zone, kh, and the horizontal hydraulic conductivity in the smeared zone, ks. Furthermore, the shear strength, Su, increased about 100% when compared using the vacuum-thermal-PVD to the vacuum PVD. In addition, numerical simulations gave reasonable results compared to the laboratory data.

Keywords: PVD improvement, vacuum preloading, prefabricated vertical drain, thermal PVD

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Authors: Masese Chuma Benard, Martin Onsiro Ronald

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Businesses have been using cloud computing more frequently recently because they wish to take advantage of its advantages. However, employing cloud computing also introduces new security concerns, particularly with regard to data security, potential risks and weaknesses that could be exploited by attackers, and various tactics and strategies that could be used to lessen these risks. This study examines data security issues on cloud computing amongst sme’s in Nairobi county, Kenya. The study used the sample size of 48, the research approach was mixed methods, The findings show that data owner has no control over the cloud merchant's data management procedures, there is no way to ensure that data is handled legally. This implies that you will lose control over the data stored in the cloud. Data and information stored in the cloud may face a range of availability issues due to internet outages; this can represent a significant risk to data kept in shared clouds. Integrity, availability, and secrecy are all mentioned.

Keywords: data security, cloud computing, information, information security, small and medium-sized firms (SMEs)

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Authors: M. Strémy, P. Závacký, P. Cuninka, M. Juhás

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Main goal of this paper is to introduce our design of private cloud for storing large amount of data, especially pictures, and to provide good technological backend for data analysis based on parallel processing and business intelligence. We have tested hypervisors, cloud management tools, storage for storing all data and Hadoop to provide data analysis on unstructured data. Providing high availability, virtual network management, logical separation of projects and also rapid deployment of physical servers to our environment was also needed.

Keywords: cloud, glusterfs, hadoop, juju, kvm, maas, openstack, virtualization

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Authors: Amitha Puranik, V. S. Binu, Seena Biju

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Missing data is a common problem in spatial analysis especially at the aggregate level. Missing can either occur in covariate or in response variable or in both in a given location. Many missing data techniques are available to estimate the missing data values but not all of these methods can be applied on spatial data since the data are autocorrelated. Hence there is a need to develop a method that estimates the missing values in both response variable and covariates in spatial data by taking account of the spatial autocorrelation. The present study aims to develop a model to estimate the missing data points at the aggregate level in spatial data by accounting for (a) Spatial autocorrelation of the response variable (b) Spatial autocorrelation of covariates and (c) Correlation between covariates and the response variable. Estimating the missing values of spatial data requires a model that explicitly account for the spatial autocorrelation. The proposed model not only accounts for spatial autocorrelation but also utilizes the correlation that exists between covariates, within covariates and between a response variable and covariates. The precise estimation of the missing data points in spatial data will result in an increased precision of the estimated effects of independent variables on the response variable in spatial regression analysis.

Keywords: spatial regression, missing data estimation, spatial autocorrelation, simulation analysis

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Authors: Abdul-Razak Saeed

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Addressing the climate change crisis that this generation faces has evolved to include the consideration of a policy mechanism referred to as reduced emissions from deforestation and forest degradation with plus components of conservation, sustainable forest management and enhancement of forest carbon stocks (REDD+). REDD+ emerged from the International level of UNFCCC but its implementation is by developing countries. It challenges the development paradigm of nations that depend on the unsustainable clearing of forests and land use change for economic development whilst posing as an opportunity or risk for forest community livelihoods, institutions and their interaction with the forest resources. As a novel policy mechanism, it is imperative to gain global insight into local contexts of its implementation and to understand local level mobilization of their agency for institutional sustainability as reconfigured by new carbon economy initiatives like REDD+. Using a systematic review process, as the initial stages of this study, secondary data of REDD+ projects across the globe were evaluated to pick up gaps in research and that of on ground REDD+ implementation. Primary data was gathered from 30 actors in the government, NGO, private sector and traditional authorities using face-to-face semi structured interviews in Ghana; participation in meetings and workshops and policy and strategy document reviews. Preliminary findings of the study include REDD+ knowledge being a key determinant of power distribution and affects who shapes the process; in Ghana, informal relationships are playing key roles in advancing REDD+ unlike in traditional forestry and a subjectivity shift of local communities from an 'emotive-link' of environmental care to one of 'economic self-seeking and enriching' domain of thought.

Keywords: climate change, communities, forests, REDD+

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Authors: Jaypalsinh Parmar, Pintu Nakrani, Bhaumik Shah

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Digital Elevation Model (DEM) is elevation data of the virtual grid on the ground. DEM can be used in application in GIS such as hydrological modelling, flood forecasting, morphometrical analysis and surveying etc.. For morphometrical analysis the stream flow network plays a very important role. DEM lacks accuracy and cannot match field data as it should for accurate results of morphometrical analysis. The present study focuses on comparing the Agree method and the conventional Shortest path method for finding out morphometric parameters in the flat region of the Lower Tapi Basin which is located in the western India. For the present study, open source SRTM (Shuttle Radar Topography Mission with 1 arc resolution) and toposheets issued by Survey of India (SOI) were used to determine the morphometric linear aspect such as stream order, number of stream, stream length, bifurcation ratio, mean stream length, mean bifurcation ratio, stream length ratio, length of overland flow, constant of channel maintenance and aerial aspect such as drainage density, stream frequency, drainage texture, form factor, circularity ratio, elongation ratio, shape factor and relief aspect such as relief ratio, gradient ratio and basin relief for 53 catchments of Lower Tapi Basin. Stream network was digitized from the available toposheets. Agree DEM was created by using the SRTM and stream network from the toposheets. The results obtained were used to demonstrate a comparison between the two methods in the flat areas.

Keywords: agree method, morphometric analysis, lower Tapi basin, shortest path method

Procedia PDF Downloads 239

Authors: Eric Muñoz de la Torre, Julián González Trinidad, Efrén González Ramírez

Abstract:

Rain varies greatly in its duration, intensity, and spatial coverage, it is important to have sub-daily rainfall data for various applications, including risk prevention. However, the ground measurements are limited by the low and irregular density of rain gauges. An alternative to this problem are the Satellite Precipitation Products (SPPs) that use passive microwave and infrared sensors to estimate rainfall, as IMERG, however, these SPPs have to be validated before their application. The aim of this study is to evaluate the performance of the IMERG: Integrated Multi-satellitE Retrievals for Global Precipitation Measurament final run V06B SPP in a semi-arid region of Mexico, using 4 automatic rain gauges (pluviographs) sub-daily data of October 2019 and June to September 2021, using the Minimum inter-event Time (MIT) criterion to separate unique rain events with a dry period of 10 hrs. for the purpose of evaluating the rainfall properties (depth, duration and intensity). Point to pixel analysis, continuous, categorical, and volumetric statistical metrics were used. Results show that IMERG is capable to estimate the rainfall depth with a slight overestimation but is unable to identify the real duration and intensity of the rain events, showing large overestimations and underestimations, respectively. The study zone presented 80 to 85 % of convective rain events, the rest were stratiform rain events, classified by the depth magnitude variation of IMERG pixels and pluviographs. IMERG showed poorer performance at detecting the first ones but had a good performance at estimating stratiform rain events that are originated by Cold Fronts.

Keywords: IMERG, rainfall, rain gauge, remote sensing, statistical evaluation

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Authors: A. Rifa’i, Y. Takeshita, M. Komatsu

Abstract:

After Yogyakarta earthquake in 2006, the main problem that occurred in the first yard of Prambanan Temple is ponding area that occurred after rainfall. Soil characterization needs to be determined by conducting several processes, especially permeability coefficient (k) in both saturated and unsaturated conditions to solve this problem. More accurate and efficient field testing procedure is required to obtain permeability data that present the field condition. One of the field permeability test equipment is Constant Discharge procedure to determine the permeability coefficient. Necessary adjustments of the Constant Discharge procedure are needed to be determined especially the value of geometric factor (F) to improve the corresponding value of permeability coefficient. The value of k will be correlated with the value of volumetric water content (θ) of an unsaturated condition until saturated condition. The principle procedure of Constant Discharge model provides a constant flow in permeameter tube that flows into the ground until the water level in the tube becomes constant. Constant water level in the tube is highly dependent on the tube dimension. Every tube dimension has a shape factor called the geometric factor that affects the result of the test. Geometric factor value is defined as the characteristic of shape and radius of the tube. This research has modified the geometric factor parameters by using empty material tube method so that the geometric factor will change. Saturation level is monitored by using soil moisture sensor. The field test results were compared with the results of laboratory tests to validate the results of the test. Field and laboratory test results of empty tube material method have an average difference of 3.33 x 10^-4 cm/sec. The test results showed that modified geometric factor provides more accurate data. The improved methods of constant discharge procedure provide more relevant results.

Keywords: constant discharge, geometric factor, permeability coefficient, unsaturated soils

Procedia PDF Downloads 294

Authors: Chong Hu, Tiantian Wang, Zhe Li, Ourui Huang, Yichen Pan

Abstract:

When the train is running in a high geothermal tunnel, changes in the temperature field will cause disturbances in the propagation and superposition of pressure waves in the tunnel, which in turn have an effect on the aerodynamic resistance of the train. The aim of this paper is to investigate the effect of the changes in the lengths of the high-temperature zone of the tunnel on the aerodynamic resistance of the train, clarifying the evolution mechanism of aerodynamic resistance of trains in tunnels with high ground temperatures. Firstly, moving model tests of trains passing through wall-heated tunnels were conducted to verify the reliability of the numerical method in this paper. Subsequently, based on the three-dimensional unsteady compressible RANS method and the standard k-ε two-equation turbulence model, the change laws of the average aerodynamic resistance under different high-temperature zone lengths were analyzed, and the influence of frictional resistance and pressure difference resistance on total resistance at different times was discussed. The results show that as the length of the high-temperature zone LH increases, the average aerodynamic resistance of a train running in a tunnel gradually decreases; when LH = 330 m, the aerodynamic resistance can be reduced by 5.7%. At the moment of maximum resistance, the total resistance, differential pressure resistance, and friction resistance all decrease gradually with the increase of LH and then remain basically unchanged. At the moment of the minimum value of resistance, with the increase of LH, the total resistance first increases and then slowly decreases; the differential pressure resistance first increases and then remains unchanged, while the friction resistance first remains unchanged and then gradually decreases, and the ratio of the differential pressure resistance to the total resistance gradually increases with the increase of LH. The results of this paper can provide guidance for scholars who need to investigate the mechanism of aerodynamic resistance change of trains in high geothermal environments, as well as provide a new way of thinking for resistance reduction in non-high geothermal tunnels.

Keywords: high-speed trains, aerodynamic resistance, high-ground temperature, tunnel

Procedia PDF Downloads 67

Authors: Sarra Senhadji, Imene Benzeguimi, Zohra Yagoub

Abstract:

Big Data represents the recent technology of manipulating voluminous and unstructured data sets over multiple sources. Therefore, NOSQL appears to handle the problem of unstructured data. Association rules mining is one of the popular techniques of data mining to extract hidden relationship from transactional databases. The algorithm for finding association dependencies is well-solved with Map Reduce. The goal of our work is to reduce the time of generating of frequent itemsets by using Map Reduce and NOSQL database oriented document. A comparative study is given to evaluate the performances of our algorithm with the classical algorithm Apriori.

Keywords: Apriori, Association rules mining, Big Data, Data Mining, Hadoop, MapReduce, MongoDB, NoSQL

Procedia PDF Downloads 162

Authors: Melaku Tsehay

Abstract:

The Consortium of Christian Relief and Development Associations (CCRDA), and the CORE Group Polio Partners (CGPP) Secretariat have been working with Global Alliance for Vac-cines and Immunization (GAVI) to improve the immunization data quality in Afar and Somali Regional States. The main aim of this study was to compare the quality of immunization data before and after the above interventions in health facilities in the pastoralist communities in Ethiopia. To this end, a comparative-cross-sectional study was conducted on 51 health facilities. The baseline data was collected in May 2019, while the end line data in August 2021. The WHO data quality self-assessment tool (DQS) was used to collect data. A significant improvment was seen in the accuracy of the pentavalent vaccine (PT)1 (p = 0.012) data at the health posts (HP), while PT3 (p = 0.010), and Measles (p = 0.020) at the health centers (HC). Besides, a highly sig-nificant improvment was observed in the accuracy of tetanus toxoid (TT)2 data at HP (p < 0.001). The level of over- or under-reporting was found to be < 8%, at the HP, and < 10% at the HC for PT3. The data completeness was also increased from 72.09% to 88.89% at the HC. Nearly 74% of the health facilities timely reported their respective immunization data, which is much better than the baseline (7.1%) (p < 0.001). These findings may provide some hints for the policies and pro-grams targetting on improving immunization data qaulity in the pastoralist communities.

Keywords: data quality, immunization, verification factor, pastoralist region

Procedia PDF Downloads 124

Authors: Sofiane Grira, Hichem Eleuch

Abstract:

We explore the analytical soliton-pair solutions for unbalanced coupling between the two coherent lights and the atomic transitions in a dissipative three-level system in lambda configuration. The two allowed atomic transitions are interacting resonantly with two laser fields. For unbalanced coupling, it is possible to derive an explicit solution for non-linear differential equations describing the soliton-pair propagation in this three-level system with the same velocity. We suppose that the spontaneous emission rates from the excited state to both ground states are the same. In this work, we focus on such case where we consider the coupling between the transitions and the optical fields are unbalanced. The existence conditions for the soliton-pair propagations are determined. We will show that there are four possible configurations of the soliton-pair pulses. Two of them can be interpreted as a couple of solitons with same directions of polarization and the other two as soliton-pair with opposite directions of polarization. Due to the fact that solitons have stable shapes while propagating in the considered media, they are insensitive to noise and dispersion. Our results have potential applications in data transfer with the soliton-pair pulses, where a dissipative three-level medium could be a realistic model for the optical communication media.

Keywords: non-linear differential equations, solitons, wave propagations, optical fiber

Procedia PDF Downloads 137