Search results for: intelligent transportation

Authors: S. Al-Fadala, J. Chakkamalayath, S. Al-Bahar, A. Al-Aibani, S. Ahmed

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Globally, the use of pozzolan in blended cement is gaining great interest due to the desirable effect of pozzolan from the environmental and energy conservation standpoint and the technical benefits they provide to the performance of cement. The deterioration of concrete structures in the marine environment and extreme climates demand the use of pozzolana cement in concrete construction in the Gulf region. Also, natural sources of cement clinker materials are limited in the Gulf region, and cement industry imports the raw materials for the production of Portland cement, resulting in an increase in the greenhouse gas effect due to the CO₂ emissions generated from transportation. Even though the Gulf region has vast deposits of natural pozzolana, it is not explored properly for the production of high performance concrete. Hence, an optimum use of regionally available natural pozzolana for the production of blended cement can result in sustainable construction. This paper investigates the effect of incorporating natural pozzolan sourced from the Gulf region on the performance of blended cement in terms of heat evolution and strength development. For this purpose, a locally produced Ordinary Portland Cement (OPC) and pozzolan-incorporated blended cements containing different amounts of natural pozzolan (volcanic ash) were prepared on laboratory scale. The strength development and heat evolution were measured and quantified. Promising results of strength development were obtained for blends with the percentages of Volcanic Ash (VA) replacement varying from 10 to 30%. Results showed that the heat of hydration decreased with increase in percentage of replacement of OPC with VA, indicating increased retardation in hydration due to the addition of VA. This property could be used in mass concreting in which a reduction in heat of hydration is required to reduce cracking in concrete, especially in hot weather concreting.

Keywords: blended cement, hot weather, hydration, volcanic ash

Procedia PDF Downloads 325

Authors: Huseyin A. Yavasoglu, Yusuf Ziya Tengiz, Ali Göksenli

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In this study, an automatic feeding machine for different type and class of bovine animals is designed. Daily nutrition of a bovine consists of grass, corn, straw, silage, oat, wheat and different vitamins and minerals. The amount and mixture amount of each of the nutrition depends on different parameters of the bovine. These parameters are; age, sex, weight and maternity of the bovine, also outside temperature. The problem in a farm is to constitute the correct mixture and amount of nutrition for each animal. Faulty nutrition will cause an insufficient feeding of the animal concluding in an unhealthy bovine. To solve this problem, a new automatic feeding machine is designed. Travelling of the machine is performed by four tires, which is pulled by a tractor. The carrier consists of eight bins, which each of them carries a nutrition type. Capacity of each unit is 250 kg. At the bottom of each chamber is a sensor measuring the weight of the food inside. A funnel is at the bottom of each chamber by which open/close function is controlled by a valve. Each animal will carry a RFID tag including ID on its ear. A receiver on the feeding machine will read this ID and by given previous information by the operator (veterinarian), the system will detect the amount of each nutrition unit which will be given to the selected animal for feeding. In the system, each bin will open its exit gate by the help of the valve under the control of PLC (Programmable Logic Controller). The amount of each nutrition type will be controlled by measuring the open/close time. The exit canals of the bins are collected in a reservoir. To achieve a homogenous nitration, the collected feed will be mixed by a worm gear. Further the mixture will be transported by a help of a funnel to the feeding unit of the animal. The feeding process can be performed in 100 seconds. After feeding of the animal, the tractor pulls the travelling machine to the next animal. By the help of this system animals can be feeded by right amount and mixture of nutrition

Keywords: bovine, feeding, nutrition, transportation, automatic

Procedia PDF Downloads 342

Authors: Adishirin Mammadov

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Polymers and polymer composites play vital roles in diverse industries, including food and beverage packaging, transportation innovations, and medical advancements. However, the advancements in polymer technology bring certain risks, particularly concerning water and soil pollution due to the presence of polymers. The creation of new polymers is a critical aspect of this field. While the primary focus is on improving their physical and chemical properties, ensuring their ecological compatibility is equally important. An advanced method for developing innovative polymer types involves integrating fillers with diverse characteristics, offering advantages such as cost reduction and improved quality indicators. In the conducted research, efforts were made to enhance environmental aspects by employing waste fillers. Specifically, low-density polyethylene (LDPE) was used as the polymer, and waste from cocoon factories was chosen as the filler. Following a process of cleaning, drying, and crushing the filler to specific dimensions, it was incorporated into polyethylene through a mechanical-chemical method under laboratory conditions. The varied rheological properties of the resulting polyethylene compositions examined at temperatures ranging from 145 to 165 degrees Celsius. These compositions demonstrated different rheological properties at various temperature intervals. Achieving homogeneity in the obtained compositions is crucial in the polymers mechanochemical process. Beyond rheological properties, swelling rates in different environments and percentages of mass loss at different temperatures learned using the differential thermal analysis method. The research revealed that, to a certain extent, the physico-chemical properties of polyethylene were not significantly affected by the polymer compositions. This suggests that incorporating cocoon waste enables cost reduction in composite production while positively impacting the environment.

Keywords: polyethylene, polymer, composites, filler, reology

Procedia PDF Downloads 56

Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Gulcin Yildiz, Gokcen Izli

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Drying (dehydration) is the process of removing water from food in order to preserve the food. Drying is one of the oldest methods known for the preservation of agricultural products such as fruits and vegetables. Drying of agricultural products enhances their storage life, minimizes losses during storage, and save shipping and transportation costs. Apples are considered excellent candidates for drying. The objective of this research was to investigate the effects of microwave and oven processing on the quality of selected apple products. Red delicious and golden delicious apples were washed, peeled, and sliced. Drying experiments were performed in an oven at 50, 75 and 100 °C and in a microwave at 140 W and 210 W. Quality attributes such as color, total phenolic content and antioxidant capacity of dried samples with different methods were compared with the fresh sample. A Minolta CR-300 Chroma Meter was used to examine color changes in the apples. Total phenolic content was determined using the Folin-Ciocalteu reagent. The free radical scavenging activity of the extract was determined using 1,1-diphenyl-2-picrylhydrazyl (DPPH). It was found that the phenolic contents and antioxidant capacities of dried samples under all drying conditions were decreased compared to the fresh samples. The phenolic contents of microwave dried samples at 140 W and 210 W for both red and golden delicious apples were higher than those of the oven drying at 50, 75 and 100 °C. Similarly, the antioxidant activities of microwave dried samples at 140 W and 210 W were higher than those of the oven drying at 50, 75 and 100 °C for both types of apples. All color parameters (L*, a*, b*) were changed significantly depending on the drying methods and temperatures. The closest color values to the fresh sample were found for the microwave dried samples at 140 W. Microwave drying was proven to be more effective than oven drying.

Keywords: antioxidant capacity, color, golden delicious, microwave, red delicious, total phenolic content

Procedia PDF Downloads 236

Authors: Tesfaye Mengistu

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Power cables play a crucial role in the transmission and distribution of electrical energy. As the electricity generation, transmission, distribution, and storage systems become smarter, there is a growing emphasis on incorporating intelligent approaches to ensure the reliability of power cables. Various types of electrical cables are employed for transmitting and distributing electrical energy, with cross-linked polyethylene (XLPE) cables being widely utilized due to their exceptional electrical and mechanical properties. However, insulation defects can occur in XLPE cables due to subpar manufacturing techniques during production and cable joint installation. To address this issue, experts have proposed different methods for monitoring XLPE cables. Some suggest the use of interdigital capacitive (IDC) technology for online monitoring, while others propose employing continuous wave (CW) terahertz (THz) imaging systems to detect internal defects in XLPE plates used for power cable insulation. In this study, we have developed models that employ a custom dataset collected locally to classify the physical safety status of individual power cables. Our models aim to replace physical inspections with computer vision and image processing techniques to classify defective power cables from non-defective ones. The implementation of our project utilized the Python programming language along with the TensorFlow package and a convolutional neural network (CNN). The CNN-based algorithm was specifically chosen for power cable defect classification. The results of our project demonstrate the effectiveness of CNNs in accurately classifying power cable defects. We recommend the utilization of similar or additional datasets to further enhance and refine our models. Additionally, we believe that our models could be used to develop methodologies for detecting power cable defects from live video feeds. We firmly believe that our work makes a significant contribution to the field of power cable inspection and maintenance. Our models offer a more efficient and cost-effective approach to detecting power cable defects, thereby improving the reliability and safety of power grids.

Keywords: artificial intelligence, computer vision, defect detection, convolutional neural net

Procedia PDF Downloads 112

Authors: Danying Gu, Xiaoyan Li, Yuanlei He

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As a knowledge-intensive industry, nuclear industry highly values the importance of safety and quality. The life cycle of a NPP (Nuclear Power Plant) can last 100 years from the initial research and design to its decommissioning. How to implement the high-quality knowledge management and how to contribute to a more safe, advanced and economic NPP (Nuclear Power Plant) is the most important issue and responsibility for knowledge management. As the lead of nuclear industry, nuclear research and design institute has competitive advantages of its advanced technology, knowledge and information, DKM (Design Knowledge Management) of nuclear research and design institute is the core of the knowledge management in the whole nuclear industry. In this paper, the study and practice on DKM and knowledge transfer across the life cycle of a new-built NPP in China is introduced. For this digital intelligent NPP, the whole design process is based on a digital design platform which includes NPP engineering and design dynamic analyzer, visualization engineering verification platform, digital operation maintenance support platform and digital equipment design, manufacture integrated collaborative platform. In order to make all the design data and information transfer across design, construction, commissioning and operation, the overall architecture of new-built digital NPP should become a modern knowledge management system. So a digital information transfer model across the NPP life cycle is proposed in this paper. The challenges related to design knowledge transfer is also discussed, such as digital information handover, data center and data sorting, unified data coding system. On the other hand, effective delivery of design information during the construction and operation phase will contribute to the comprehensive understanding of design ideas and components and systems for the construction contractor and operation unit, largely increasing the safety, quality and economic benefits during the life cycle. The operation and maintenance records generated from the NPP operation process have great significance for maintaining the operating state of NPP, especially the comprehensiveness, validity and traceability of the records. So the requirements of an online monitoring and smart diagnosis system of NPP is also proposed, to help utility-owners to improve the safety and efficiency.

Keywords: design knowledge management, digital nuclear power plant, knowledge transfer, life cycle

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Authors: Abisha Isaac Mohanlal

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Amidst all suspicions and cynicism raised by the legal fraternity, Artificial Intelligence has found its way into the legal system and has revolutionized the conventional forms of legal services delivery. Be it legal argumentation and research or resolution of complex legal disputes; artificial intelligence has crept into all legs of modern day legal services. Its impact has been largely felt by way of big data, legal expert systems, prediction tools, e-lawyering, automated mediation, etc., and lawyers around the world are forced to upgrade themselves and their firms to stay in line with the growth of technology in law. Researchers predict that the future of legal services would belong to artificial intelligence and that the age of human lawyers will soon rust. But as far as the Judiciary is concerned, even in the developed countries, the system has not fully drifted away from the orthodoxy of preferring Natural Intelligence over Artificial Intelligence. Since Judicial decision-making involves a lot of unstructured and rather unprecedented situations which have no single correct answer, and looming questions of legal interpretation arise in most of the cases, discretion and Emotional Intelligence play an unavoidable role. Added to that, there are several ethical, moral and policy issues to be confronted before permitting the intrusion of Artificial Intelligence into the judicial system. As of today, the human judge is the unrivalled master of most of the judicial systems around the globe. Yet, scientists of Artificial Intelligence claim that robot judges can replace human judges irrespective of how daunting the complexity of issues is and how sophisticated the cognitive competence required is. They go on to contend that even if the system is too rigid to allow robot judges to substitute human judges in the recent future, Artificial Intelligence may still aid in other judicial tasks such as drafting judicial documents, intelligent document assembly, case retrieval, etc., and also promote overall flexibility, efficiency, and accuracy in the disposal of cases. By deconstructing the major challenges that Artificial Intelligence has to overcome in order to successfully invade the human- dominated judicial sphere, and critically evaluating the potential differences it would make in the system of justice delivery, the author tries to argue that penetration of Artificial Intelligence into the Judiciary could surely be enhancive and reparative, if not fully transformative.

Keywords: artificial intelligence, judicial decision making, judicial systems, legal services delivery

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Authors: Arun Kumar Singh, Rupesh M. Das, Shailendra Saini

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The present work is an attempt to evaluate the sub-auroral ionospheric behavior under changing space weather conditions especially during high solar activity year 2014. In view of this, the GPS TEC along with Ionosonde data over Indian permanent scientific base 'Maitri', Antarctica (70°46′00″ S, 11°43′56″ E) has been utilized. The results suggested that the nature of ionospheric responses to the geomagnetic disturbances mainly depended upon the status of high latitudinal electro-dynamic processes along with the season of occurrence. Fortunately, in this study, both negative and positive ionospheric impact to the geomagnetic disturbances has been observed in a single year but in different seasons. The study reveals that the combination of equator-ward plasma transportation along with ionospheric compositional changes causes a negative ionospheric impact during summer and equinox seasons. However, the combination of pole-ward contraction of the oval region along with particle precipitation may lead to exhibiting positive ionospheric response during the winter season. Other than this, some Ionosonde based new experimental evidence also provided clear evidence of particle precipitation deep up to the low altitudinal ionospheric heights, i.e., up to E-layer by the sudden and strong appearance of E-layer at 100 km altitudes. The sudden appearance of E-layer along with a decrease in F-layer electron density suggested the dominance of NO⁺ over O⁺ at a considered region under geomagnetic disturbed condition. The strengthening of E-layer is responsible for modification of auroral electrojet and field-aligned current system. The present study provided a good scientific insight on sub-auroral ionospheric to the changing space weather condition.

Keywords: high latitude ionosphere, space weather, geomagnetic storms, sub-storm

Procedia PDF Downloads 169

Authors: Margarida Porfírio Tomás, Paula Pereira, José Palma Oliveira

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Robotic grasping is advancing rapidly, but transferring techniques from rigid to deformable objects remains a challenge. Deformable and flexible items, such as food containers, demand nuanced handling due to their changing shapes. Bridging this gap is crucial for applications in food processing, surgical robotics, and household assistance. AGILEHAND, a Horizon project, focuses on developing advanced technologies for sorting, handling, and packaging soft and deformable products autonomously. These technologies serve as strategic tools to enhance flexibility, agility, and reconfigurability within the production and logistics systems of European manufacturing companies. Key components include intelligent detection, self-adaptive handling, efficient sorting, and agile, rapid reconfiguration. The overarching goal is to optimize work environments and equipment, ensuring both efficiency and safety. As new technologies emerge in the food industry, there will be some implications, such as labour force, safety problems and acceptance of the new technologies. To overcome these implications, AGILEHAND emphasizes the integration of social sciences and humanities, for example, the application of the Technology Acceptance Model (TAM). The project aims to create a change management manual, that will outline strategies for developing digital skills and managing health and safety transitions. It will also provide best practices and models for organizational change. Additionally, AGILEHAND will design effective training programs to enhance employee skills and knowledge. This information will be obtained through a combination of case studies, structured interviews, questionnaires, and a comprehensive literature review. The project will explore how organizations adapt during periods of change and identify factors influencing employee motivation and job satisfaction. This project received funding from European Union’s Horizon 2020/Horizon Europe research and innovation program under grant agreement No101092043 (AGILEHAND).

Keywords: change management, technology acceptance model, organizational change, health and safety

Procedia PDF Downloads 45

Authors: Muhammad Shoaib, Hassan M. Al-Swaidan

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Air pollution has been a major challenge for the scientists today, due to the release of toxic emissions from various industries like power plants, desalination plants, industrial processes and transportation vehicles. Harmful emissions into the air represent an environmental pressure that reflects negatively on human health and productivity, thus leading to a real loss in the national economy. Variety of air pollutants in the form of carbon oxides, hydrocarbons, nitrogen oxides, sulfur oxides, suspended particulate material etc. are present in air due to the combustion of different types of fuels like crude oil, diesel oil and natural gas. Among various pollutants, NOx and SOx emissions are considered as highly toxic due to its carcinogenicity and its relation with various health disorders. In Kingdom of Saudi Arabia electricity is generated by burning of crude, diesel or natural gas in the turbines of electricity stations. Out of these three, crude oil is used extensively for electricity generation. Due to the burning of the crude oil there are heavy contents of gaseous pollutants like sulfur dioxides (SOx) and nitrogen oxides (NOx), gases which are ultimately discharged in to the environment and is a serious environmental threat. The breakthrough point in case of lab studies using 1 gm of sliced activated carbon adsorbant comes after 20 and 30 minutes for NOx and SOx, respectively, whereas in case of PP8 plant breakthrough point comes in seconds. The saturation point in case of lab studies comes after 100 and 120 minutes and for actual PP8 plant it comes after 60 and 90 minutes for NOx and SOx adsorption, respectively. Surface characterization of NOx and SOx adsorption on SAC confirms the presence of peaks in the FT-IR spectrum. CHNS study verifies that the SAC is suitable for NOx and SOx along with some other C and H containing compounds coming out from stack emission stream from the turbines of a power plant.

Keywords: activated carbon, flue gases, NOx and SOx adsorption, physical activation, power plants

Procedia PDF Downloads 347

Authors: Aidan Jacobsen, Morgan Motia, David Sam, Jonathan Mudge

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Background: The Centers for Disease Control (CDC) lists vaccine requirements for children under two years old to correlate with development markers. CDC lists the coverage by age 24 months to be at least 90% nationally and 84% for Rhode Island Blackstone Valley Community Health Center (BVCHC) in Central Falls, Rhode Island, currently has a completed vaccination rate of 51% for children by the age of 24 months. Current barriers to care for up to date well child vaccinations include lack of transportation, parental work, childcare, and other social stressors. Objective: Increase the vaccination rate of children under the age of 24 months at BVCHC. Conduct a literature review to identify the common barriers preventing children under 24 months from receiving vaccinations. Reduce the barriers to expand access to vaccination care for infants Methods: Setting: Blackstone Valley Community Health Center, Pawtucket, RI Participants: (n=41), Patients between the age of 20-24 months, not up to date with the CDC vaccination recommendations and without a future appointment. QI Intervention: Patients were contacted via phone and offered an appointment during extra Saturday clinic hours in order to receive up to date vaccine care. A Saturday vaccine clinic was established specifically for patients in need of vaccines and having identified barriers to care. Conclusions: Expanding clinic hours and targeting non vaccine up –to-date patients can increase the current standard of childhood immunizations at BVCHC. Overcoming barriers preventing childhood immunization can improve access to providing up to date vaccinations. Other barriers still deter from reaching the national standard of immunizations rates.

Keywords: vaccinations, well child care, barriers to care, social determinants of health

Procedia PDF Downloads 74

Authors: Adeyinka Adeniran, Omowunmi Bakare, Esther Oluwole, Florence Chieme, Temitope Durojaiye, Modupe Akinyinka, Omobola Ojo, Babatunde Olujobi, Marcus Ilesanmi, Akintunde Ogunsakin

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Introduction: Globally, COVID-19 has greatly impacted the human race physically, socially, mentally, and economically. However, healthcare workers seemed to bear the greatest impact. The study, therefore, sought to assess the impact of COVID-19 on the primary healthcare workers in Ekiti, South-west Nigeria. Methods: The study was a cross-sectional descriptive study using a quantitative data collection method of 716 primary healthcare workers in Ekiti state. Respondents were selected using an online convenience sampling method via their social media platforms. Data was collected, collated, and analyzed using SPSS version 25 software and presented as frequency tables, mean and standard deviation. Bivariate and multivariate analyses were conducted using a t-test, and the level of statistical significance was set at p<0.05. Results: Less than half (47.1%) of respondents were between 41-50 age group and a mean age of 44.4+6.4SD. A majority (89.4%) were female, and almost all (96.2%) were married. More than (90%) had ever heard of Coronavirus, and (85.8%) had to spend more money on activities of daily living such as transportation (90.1%), groceries (80.6%), assisting relations (95.8%) and sanitary measures (disinfection) at home (95.0%). COVID-19 had a huge negative impact on about (89.7%) of healthcare workers, with a mean score of 22+4.8. Conclusion: COVID-19 negatively impacted the daily living and professional duties of primary healthcare workers, which reflected their psychological, physical, social, and economic well-being. Disease outbreaks are unlikely to disappear in the near future. Hence, global proactive interventions and homegrown measures should be adopted to protect healthcare workers and save lives.

Keywords: Covid-19, health workforce, primary health care, health systems, depression

Procedia PDF Downloads 83

Authors: M. R. Ahmad, I. Musirin, M. M. Othman, N. A. Rahmat

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Plug-in Hybrid-Electric Vehicle (PHEV) has gained immense popularity in recent years. PHEV offers numerous advantages compared to the conventional internal-combustion engine (ICE) vehicle. Millions of PHEVs are estimated to be on the road in the USA by 2020. Uncoordinated PHEV charging is believed to cause severe impacts to the power grid; i.e. feeders, lines and transformers overload and voltage drop. Nevertheless, improper PHEV data model used in such studies may cause the findings of their works is in appropriated. Although smart charging is more attractive to researchers in recent years, its implementation is not yet attainable on the street due to its requirement for physical infrastructure readiness and technology advancement. As the first step, it is finest to study the impact of charging PHEV based on real vehicle travel data from National Household Travel Survey (NHTS) and at present charging rate. Due to the lack of charging station on the street at the moment, charging PHEV at home is the best option and has been considered in this work. This paper proposed a technique that comprehensively presents the impact of charging PHEV on power system networks considering huge numbers of PHEV samples with its traveling data pattern. Vehicles Charging Load Profile (VCLP) is developed and implemented in IEEE 30-bus test system that represents a portion of American Electric Power System (Midwestern US). Normalization technique is used to correspond to real time loads at all buses. Results from the study indicated that charging PHEV using opportunity charging will have significant impacts on power system networks, especially whereas bigger battery capacity (kWh) is used as well as for higher penetration level.

Keywords: plug-in hybrid electric vehicle, transportation electrification, impact of charging PHEV, electricity demand profile, load profile

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Authors: Chondrogianni Dimitra, Yorgos J. Stephanedes

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The impact of the economic crisis, coupled with the aging of the city's old core, is reflected in central Athens. Public and private users, residents, employees, visitors desire the quality upgrading of abandoned buildings and public spaces through environmental upgrading and sustainable mobility, and promotion of the international metropolitan character of the city. In the study, a strategy for reshaping the character and function of the historic Athenian triangle is proposed, aiming at its economic, environmental, and social sustainable development through feasible, meaningful, and non-landscaping solutions of low cost and high positive impact. Sustainable mobility is the main principle in re-planning the study area and transforming it into a “Low Pollution and Limited Vehicle Traffic Zone” is the main strategy. Τhe proposed measures include the development of pedestrian mobility networks by expanding the pedestrian roads and limited-traffic routes, of bicycle networks based on the approved Metropolitan Bicycle Route of Athens, of public transportation networks with new lines of electric mini-buses, and of new regulations for vehicle mobility in the historic triangle. In addition, complementary actions are proposed regarding the provision of Wi-Fi on fixed track media, development of applications that facilitate combined travel and provide real-time data, integration of micromobility (roller skates, Segway, Hoverboard), and its enhancement as a flexible means of personal mobility, and development of car-sharing, ride-sharing and dynamic carpooling initiatives.

Keywords: regeneration plans, sustainable mobility, environmental upgrading, athens historical triangle

Procedia PDF Downloads 167

Authors: Behzad Behnia, Noah LaRussa-Trott

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In recent years, fibers have been successfully used as an additive to reinforce asphalt concrete materials and to enhance the sustainability and resiliency of transportation infrastructure. Roads covered with fiber-reinforced asphalt concrete (FRAC) require less frequent maintenance and tend to have a longer lifespan. The present work investigates the application of sasobit-coated aramid fibers in asphalt pavements and employs machine learning to develop prediction models to evaluate the cracking performance of FRAC materials. For the experimental part of the study, the effects of several important parameters such as fiber content, fiber length, and testing temperature on fracture characteristics of FRAC mixtures were thoroughly investigated. Two mechanical performance tests, i.e., the disk-shaped compact tension [DC(T)] and indirect tensile [ID(T)] strength tests, as well as the non-destructive acoustic emission test, were utilized to experimentally measure the cracking behavior of the FRAC material in both macro and micro level, respectively. The experimental results were used to train the supervised machine learning approach in order to establish prediction models for fracture performance of the FRAC mixtures in the field. Experimental results demonstrated that adding fibers improved the overall fracture performance of asphalt concrete materials by increasing their fracture energy, tensile strength and lowering their 'embrittlement temperature'. FRAC mixtures containing long-size fibers exhibited better cracking performance than regular-size fiber mixtures. The developed prediction models of this study could be easily employed by pavement engineers in the assessment of the FRAC pavements.

Keywords: fiber reinforced asphalt concrete, machine learning, cracking performance tests, prediction model

Procedia PDF Downloads 141

Authors: Nadhia Maharany Siara, Muammal, Ilham Nurhakim, Rofifah Yusadi, M. Adie Putra Tanggara, I. Nyoman Suluh Wijaya

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Urbanization in urban areas has impact to the demand of land use for housing, and it began to occur development in the high-density area called Kampung Kota. Kampung Kota grows and develops without planning or organically. The existence of Kampung Kota, becoming identity of the city development in Indonesia, gives self-identity to the city planning in Indonesia, but the existence of Kampung Kota in the development of the city in Indonesia is often considered as a source of environment, health, and social problems. This cause negative perception about the sustainability of Kampung Kota. This research aims to identify morphology and sustainability level of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City. So far, there have not been many studies that define sustainability of Kampung Kota especially from the perspective of Kampung Kota morphology as a part of urban housing areas. This research took place in in Polehan Sub-District, Blimbing District, Malang City which is one of the oldest Kampung Kota in Malang City. Identification of the sustainability level in this research is done by defining the morphology of Kampung Kota in Polehan Sub-District, Blimbing District, Malang City with a descriptive approach to the observation case (Kampung Kota Polehan Sub-District). After that, definition of sustainability level is defined by quantifying the spatial structure by using the criteria from the new urbanism model which consist of buildings and populations density, compactness, diversity and mix land uses and sustainable transportation. In this case, the use of new urbanism model approach is very appropriate. New Urbanism is a design-driven strategy that is based on traditional forms to minimize urban sprawl in the suburbs. The result obtained from this study is the hometown of the level of sustainability in Polehan Sub-District, Blimbing District, Malang City of 3.2 and can be considered to have a good sustainability.

Keywords: Kampung Kota, new urbanism model, sustainability, urban morphology

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Authors: Oumaima Khlifati, Khadija Baba

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Pavement distress is the main factor responsible for the deterioration of road structure durability, damage vehicles, and driver comfort. Transportation agencies spend a high proportion of their funds on pavement monitoring and maintenance. The auscultation of pavement distress was based on the manual survey, which was extremely time consuming, labor intensive, and required domain expertise. Therefore, the automatic distress detection is needed to reduce the cost of manual inspection and avoid more serious damage by implementing the appropriate remediation actions at the right time. Inspired by recent deep learning applications, this paper proposes an algorithm for automatic road distress detection and classification using on the Deep Convolutional Neural Network (DCNN). In this study, the types of pavement distress are classified as transverse or longitudinal cracking, alligator, pothole, and intact pavement. The dataset used in this work is composed of public asphalt pavement images. In order to learn the structure of the different type of distress, the DCNN models are trained and tested as a multi-label classification task. In addition, to get the highest accuracy for our model, we adjust the structural optimization hyper parameters such as the number of convolutions and max pooling, filers, size of filters, loss functions, activation functions, and optimizer and fine-tuning hyper parameters that conclude batch size and learning rate. The optimization of the model is executed by checking all feasible combinations and selecting the best performing one. The model, after being optimized, performance metrics is calculated, which describe the training and validation accuracies, precision, recall, and F1 score.

Keywords: distress pavement, hyperparameters, automatic classification, deep learning

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Authors: Arda Bagus M, Yehezkiel Festian P, Budianto Santoso

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The Tourism Area of Southern Malang is administratively located in the Regency of Malang, East Java Province, Indonesia and geographically is in a position between 112o17' - 112o57' E dan 7o44' - 8o26' S. Southern Malang consists of several sub-districts that directly borders with the Indian Ocean, such as Donomulyo, Bantur, Gedangan, Sumbermanjing, Tirto Yudo, and Ampel Gading. This area has a high geotourism potential because of the existence of geodiversity such as beaches, waterfalls, caves, and karst area. However, to the best of the authors’ knowledge, there is still no systematic data that informs the geotourism potentials to the public. The aim of this research is to complete the lack of data and then arrange it systematically so it can be used for both tourism and research purposes. Research methods such as field observation, literature study, and depth interview to local people have been implemented. Aspects reviewed by visiting the field are accommodation, transportation, and the feasibility of a place to be geotourism object. The primary data was taken in Sumbermanjing, Gedangan, Bantur, and Donomulyo sub-district. A literature study is needed to determine the regional geology of Southern Malang and as a comparison to new data obtained in the field. The results of the literature study show that southern Malang consists of three formations: Wonosari Formation, Mandalaka Formation, and River-swamps Sediment Formation with the age range of Oligocene to Quaternary. Depth interviews have been conducted by involving local people with the aim of knowing cultural-history in the research area. From this research, the geotourism object distribution map has been made. The map also includes Geotrek and basic geological information of each object. The results of this research can support the development of geotourism in Southern Malang.

Keywords: geodiversity, geology, geotourism, geotrek, southern Malang

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Authors: Marina Petrova

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Language policy issues related to the preservation and development of the native languages of the Russian peoples and the state languages of the national republics are increasingly becoming the focus of recent attention of educators and parents, public and national figures. Is it legal to teach the national language or the mother tongue as the state language? Due to that dispute language phobia moods easily evolve into xenophobia among the population. However, a civilized, intelligent multicultural personality can only be formed if the country develops bilingualism and multilingualism, and languages as a political tool help to find ‘keys’ to sufficiently closed national communities both within a poly-ethnic state and in internal relations of multilingual countries. The purpose of this study is to design and theoretically substantiate an efficient model of language education in the innovatively developing Republic of Sakha. 800 participants from different educational institutions of Yakutia worked at developing a multilingual model of education. This investigation is of considerable practical importance because researchers could build a methodical system designed to create conditions for the formation of a cultural language personality and the development of the multilingual communicative competence of Yakut youth, necessary for communication in native, Russian and foreign languages. The selected methodology of humane-personal and competence approaches is reliable and valid. Researchers used a variety of sources of information, including access to related scientific fields (philosophy of education, sociology, humane and social pedagogy, psychology, effective psychotherapy, methods of teaching Russian, psycholinguistics, socio-cultural education, ethnoculturology, ethnopsychology). Of special note is the application of theoretical and empirical research methods, a combination of academic analysis of the problem and experienced training, positive results of experimental work, representative series, correct processing and statistical reliability of the obtained data. It ensures the validity of the investigation’s findings as well as their broad introduction into practice of life-long language education.

Keywords: intercultural communication, language policy, multilingual and multicultural education, the Sakha Republic of Yakutia

Procedia PDF Downloads 222

Authors: Ashley R. Logsdon, Becky F. Antle, Cynthia M. Kamer

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This study examines the cost and benefits of a family treatment drug court in an urban county in a southeastern state. Additionally, this cost analysis will provide a detailed description of the type and cost of activities to produce the services provided to child welfare families. This study utilized return-on-investment analysis, which uses child welfare practices, disaggregates them into separate activities and estimates costs for these activities including child-level placement data for total cost of care for the child. Direct and indirect costs were considered as well as saving calculations what costs would be associated with child welfare outcomes both short and long term. The costs included were general program costs (salaries, drug screens, transportation, childcare, parent education, program evaluation, visitation, incentives) or personnel costs for other team members (judges, court administrators, child welfare workers, child welfare supervisors, and community mental health provider). The savings that were used in the study were length of time in out of home care, Medicaid costs, substance exposed births, emergency room utilization and jail/probation costs. This study documents an overall savings of between $168,993.30 and $837,993.30. The total savings per family divided by the 40 families who have participated in the program was between $4,224.83 to $20,949.83 per family. The results of this cost benefit analysis are consistent with prior research documenting savings associated with out of home care and jail/probation; however, there are also unique contributions of this study to the literature on cost effectiveness of family treatment drug courts. We will present recommendations for further utilization of family treatment drug courts and how to expand the current model.

Keywords: child welfare, cost analysis, family drug court, family treatment drug court

Procedia PDF Downloads 184

Authors: Abdul Basit Kiani, Maryam Kiani

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Online developers now have the tools necessary to create online apps that are not only reliable but also highly interactive, thanks to the introduction of JavaScript frameworks and APIs. The objective is to give a broad overview of the recent advances in the area. The fusion of machine learning (ML) and artificial intelligence (AI) has expanded the possibilities for web development. Modern websites now include chatbots, clever recommendation systems, and customization algorithms built in. In the rapidly evolving landscape of modern websites, it has become increasingly apparent that user engagement and personalization are key factors for success. To meet these demands, websites now incorporate a range of innovative technologies. One such technology is chatbots, which provide users with instant assistance and support, enhancing their overall browsing experience. These intelligent bots are capable of understanding natural language and can answer frequently asked questions, offer product recommendations, and even help with troubleshooting. Moreover, clever recommendation systems have emerged as a powerful tool on modern websites. By analyzing user behavior, preferences, and historical data, these systems can intelligently suggest relevant products, articles, or services tailored to each user's unique interests. This not only saves users valuable time but also increases the chances of conversions and customer satisfaction. Additionally, customization algorithms have revolutionized the way websites interact with users. By leveraging user preferences, browsing history, and demographic information, these algorithms can dynamically adjust the website's layout, content, and functionalities to suit individual user needs. This level of personalization enhances user engagement, boosts conversion rates, and ultimately leads to a more satisfying online experience. In summary, the integration of chatbots, clever recommendation systems, and customization algorithms into modern websites is transforming the way users interact with online platforms. These advanced technologies not only streamline user experiences but also contribute to increased customer satisfaction, improved conversions, and overall website success.

Keywords: Javascript, machine learning, artificial intelligence, web development

Procedia PDF Downloads 80

Authors: Benjamin L. Freidman, Sally L. Gras, Ian Snape, Geoff W. Stevens, Kathryn A. Mumford

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Increasing transportation and storage of petroleum hydrocarbons in Antarctic and sub-Antarctic regions have resulted in frequent accidental spills. Migrating petroleum hydrocarbon spills can have a significant impact on terrestrial and marine ecosystems in cold regions, as harsh environmental conditions result in heightened sensitivity to pollution. This migration of contaminants has led to the development of Permeable Reactive Barriers (PRB) for application in cold regions. PRB’s are one of the most practical technologies for on-site or in-situ groundwater remediation in cold regions due to their minimal energy, monitoring and maintenance requirements. The Main Power House site has been used as a fuel storage and power generation area for the Macquarie Island research station since at least 1960. Soil analysis at the site has revealed Total Petroleum Hydrocarbon (TPH) (C9-C28) concentrations as high as 19,000 mg/kg soil. Groundwater TPH concentrations at this site can exceed 350 mg/L TPH. Ongoing migration of petroleum hydrocarbons into the neighbouring marine ecosystem resulted in the installation of a ‘funnel and gate’ PRB in November 2014. The ‘funnel and gate’ design successfully intercepted contaminated groundwater and analysis of TPH retention and biodegradation on PRB media are currently underway. Installation of the PRB facilitates research aimed at better understanding the contribution of particle attached biofilms to the remediation of groundwater systems. Bench-scale PRB system analysis at The University of Melbourne is currently examining the role biofilms play in petroleum hydrocarbon degradation, and how controlled release nutrient media can heighten the metabolic activity of biofilms in cold regions in the presence of low temperatures and low nutrient groundwater.

Keywords: groundwater, petroleum, Macquarie island, funnel and gate

Procedia PDF Downloads 358

Authors: Zhaocheng Shang

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In order to study the topic of cities crossing rivers, a Four-Dimensional Analysis Method consisting of timeline, X-axis, Y-axis, and Z-axis is proposed. Policies, plans, and their implications are summarized and researched along with the timeline. The X-axis is the direction which is parallel to the river. The research area was chosen because of its important connection function. It is proposed that more surface water network should be built because of the ecological orientation of the research area. And the analysis of groundwater makes it for sure that the proposal is feasible. After the blue water network is settled, the green landscape network which is surrounded by it could be planned. The direction which is transversal to the river (Y-axis) should run through the transportation axis so that the urban texture could stretch in an ecological way. Therefore, it is suggested that the work of the planning bureau and river bureau should be coordinated. The Z-axis research is on the section view of the river, especially on the Yellow River’s special feature of being a perched river. Based on water control safety demands, river parks could be constructed on the embankment buffer zone, whereas many kinds of ornamental trees could be used to build the buffer zone. City Crossing River is a typical case where we make use of landscaping to build a symbiotic relationship between the urban landscape architecture and the environment. The local environment should be respected in the process of city expansion. The planning order of "Benefit- Flood Control Safety" should be replaced by "Flood Control Safety - Landscape Architecture- People - Benefit".

Keywords: blue-green landscape network, city crossing river, four-dimensional analysis method, planning order

Procedia PDF Downloads 159

Authors: Mohammed Masum, Mohammad Omer Faruk Khan, Md. Nazwanul Haque, Anwar Sadat Md. Sayem, Md. Azhar Hossain

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The study area is the Hakaluki Haor which is the second largest wet land of Bangladesh. It spans over the districts of Moulvibazar and Sylhet in southeast Bangladesh. The study was focused in the exploration of peat reserve, reconstruction of the paleo-environment as well as the utilization of the peat resources. Peat is found randomly from 0.5 m to 7 m below the surface and 1 m to 11 m thickness at over 40 beels as well as small plain lands of 90 km2 area of Hakaluki Haor. The total reserve of peat is 282 million ton in wet condition and 112 million ton in dry condition. The peat deposits of Hakaluki Haor area is the largest peat reserves of the Bangladesh. Peat bearing Hakaluki Haor is a low-lying wet land which geological term is synclinal depression. It may be a syncline between two anticlines which was filled with sediments as well as various plant materials derived from the hilly region (anticline) on both sides (west and east) of the Haor. The transportation may be triggered by large natural disasters or any tectonic reason. On the other hand vegetation occurred in this depression as aquatic plants which might have been destroyed by large natural disasters or any tectonic reason. As environment dictates the characteristics and the source of sediments, various aspects of the sediment are indicators of the environment. Peat has mainly industrial importance as a fuel for power production, traditionally used for cooking, domestic heating and in brick fields, also used as insulator in many industries, agricultural purposes, retaining moisture in soil, raw material in horticulture and colour industries etc. Power plants of about 100 MW capacities may be established in this region based on peat of Hakaluki Haor which may be continued more than one hundred years.

Keywords: peat, pale environment, Hakaluki Haor, beel, syncline, anticline

Procedia PDF Downloads 421

Authors: Fatmah Almathkour

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Managing and controlling the construction supply chain (CSC) are very important components of effective construction project execution. The goals of managing the CSC are to reduce uncertainty and optimize the performance of a construction project by improving efficiency and reducing project costs. The heart of much SC activity is addressing risk, and the CSC is no different. The delivery and consumption of construction materials is highly variable due to the complexity of construction operations, rapidly changing demand for certain components, lead time variability from suppliers, transportation time variability, and disruptions at the job site. Current notions of managing and controlling CSC, involve focusing on one project at a time with a push-based material ordering system based on the initial construction schedule and, then, holding a tremendous amount of inventory. A two-stage methodology was proposed to coordinate the feed-forward control of advanced order placement with a supplier to a feedback local control in the form of adding the ability to transship materials between projects to improve efficiency and reduce costs. It focused on the single supplier integrated production and transshipment problem with multiple products. The methodology is used as a design tool for the CSC because it includes an external storage site not associated with one of the projects. The idea is to add this feature to a highly constrained environment to explore its effectiveness in buffering the impact of variability and maintaining project schedule at low cost. The methodology uses deterministic optimization models with objectives that minimizing the total cost of the CSC. To illustrate how this methodology can be used in practice and the types of information that can be gleaned, it is tested on a number of cases based on the real example of multiple construction projects in Kuwait.

Keywords: construction supply chain, inventory control supply chain, transshipment

Procedia PDF Downloads 122

Authors: Meron Okbandrias

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The South African formal economy is rule-based economy, unlike most African and Asian markets. It has a highly developed financial market. In such a market, foreign migrants have dominated the small or spaza shops that service the poor. They are highly competitive and capture significant market share in South Africa. This paper analyses the factors that assisted the foreign migrants in having a competitive age. It does that by interviewing Somali, Bangladesh, and Ethiopian shop owners in Cape Town analysing the data through a narrative analysis. The paper also analyses the 2019 South African consumer report. The three migrant nationalities mentioned above dominate the spaza shop business and have significant distribution networks. The findings of the paper indicate that family, ethnic, and nationality based network, in that order of importance, form bases for a relationship-based business network that has trust as its mainstay. Therefore, this network ensures the pooling of resources and abiding by certain principles outside the South African rule-based system. The research identified practises like bulk buying within a community of traders, sharing information, buying from a within community distribution business, community based transportation system and providing seed capital for people from the community to start a business is all based on that relationship-based system. The consequences of not abiding by the rules of these networks are social and economic exclusion. In addition, these networks have their own commercial and social conflict resolution mechanisms aside from the South African justice system. Network theory and relationship based systems theory form the theoretical foundations of this paper.

Keywords: migrant, spaza shops, relationship-based system, South Africa

Procedia PDF Downloads 127

Authors: Abdolreza Farhadian, Anh Phan, Zahra Taheri Rizi, Elaheh Sadeh

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The utilization of solidified gas technology based on hydrates exhibits considerable promise for carbon capture, storage, and natural gas transportation applications. The pivotal factor impeding the industrial implementation of hydrates lies in the need for efficient and non-foaming promoters. In this study, a biosurfactant with sulfonate, amide, and carboxyl groups (BS) was synthesized as a methane hydrate formation promoter, replicating the chemical characteristics of amino acids and sodium dodecyl sulfate (SDS). The synthesis of BS was achieved using an eco-friendly and three-step process. The first two steps were solvent-free, while a water-isopropanol mixture was utilized in the final step. High-pressure autoclave experiments demonstrated a significant enhancement in methane hydrate formation kinetics with low BS concentrations. 50 ppm of BS yielded a maximum water-to-hydrate conversion of 66.9%, equivalent to a storage capacity of 119.9 v/v in distilled water. With increasing BS concentration to 500 ppm, the conversion degree and storage capacity reached 97% and 162.6 v/v, respectively. Molecular dynamic simulation revealed that BS molecules acted as collectors for methane molecules, augmenting hydrate growth rate and increasing the number of hydrate cavities. Additionally, BS demonstrated a biodegradability exceeding 60% within 28 days. Toxicity assessments confirmed BS's biocompatibility, with cell viability above 70% for skin and lung cells at concentrations up to 160 and 80 µg/mL, respectively. BS showed significant potential as an environmentally friendly alternative to synthetic surfactants like SDS for methane storage. These findings suggest that the synthesis of effective, such as BS, holds promise for diverse applications, including seawater desalination, carbon capture, and gas storage.

Keywords: solidified methane, gas storage, gas hydrates, green surfactant, gas hydrate promoter, computational simulation, sustainability

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Authors: S. Thanabanjerdsin, F. Srisuriyachai, J. Chewaroungroj

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Drilling horizontal well is one of the most cost-effective method to exploit reservoir by increasing exposure area between well and formation. Together with horizontal well technology, intelligent completion is often co-utilized to increases petroleum production by monitoring/control downhole production. Combination of both technological results in an opportunity to lower water cresting phenomenon, a detrimental problem that does not lower only oil recovery but also cause environmental problem due to water disposal. Flow of reservoir fluid is a result from difference between reservoir and wellbore pressure. In horizontal well, reservoir fluid around the heel location enters wellbore at higher rate compared to the toe location. As a consequence, Oil-Water Contact (OWC) at the heel side of moves upward relatively faster compared to the toe side. This causes the well to encounter an early water encroachment problem. Installation of Inflow Control Valve (ICV) in particular sections of horizontal well can involve several parameters such as number of ICV, water cut constrain of each valve, length of each section. This study is mainly focused on optimization of ICV configuration to minimize water production and at the same time, to enhance oil production. A reservoir model consisting of high aspect ratio of oil bearing zone to underneath aquifer is drilled with horizontal well and completed with variation of ICV segments. Optimization of the horizontal well configuration is firstly performed by varying number of ICV, segment length, and individual preset water cut for each segment. Simulation results show that installing ICV can increase oil recovery factor up to 5% of Original Oil In Place (OOIP) and can reduce of produced water depending on ICV segment length as well as ICV parameters. For equally partitioned-ICV segment, more number of segment results in better oil recovery. However, number of segment exceeding 10 may not give a significant additional recovery. In first production period, deformation of OWC strongly depends on number of segment along the well. Higher number of segment results in smoother deformation of OWC. After water breakthrough at heel location segment, the second production period begins. Deformation of OWC is principally dominated by ICV parameters. In certain situations that OWC is unstable such as high production rate, high viscosity fluid above aquifer and strong aquifer, second production period may give wide enough window to ICV parameter to take the roll.

Keywords: horizontal well, water cresting, inflow control valve, reservoir simulation

Procedia PDF Downloads 418

Authors: Harneet Walia, Morteza Zihayat

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Customer acquisition has become one of the critical issues of any business in the 21st century; having a healthy customer base is the essential asset of the bank business. Term deposits act as a major source of cheap funds for the banks to invest and benefit from interest rate arbitrage. To attract customers, the marketing campaigns at most financial institutions consist of multiple outbound telephonic calls with more than one contact to a customer which is a very time-consuming process. Therefore, customized direct marketing has become more critical than ever for attracting new clients. As customer acquisition is becoming more difficult to archive, having an intelligent and redefined list is necessary to sell a product smartly. Our aim of this research is to increase the effectiveness of campaigns by predicting customers who will most likely subscribe to the fixed deposit and suggest the most suitable month to reach out to customers. We design a Time Aware Upsell Prediction Framework (TAUPF) using two different approaches, with an aim to find the best approach and technique to build the prediction model. TAUPF is implemented using Upsell Prediction Approach (UPA) and Clustered Upsell Prediction Approach (CUPA). We also address the data imbalance problem by examining and comparing different methods of sampling (Up-sampling and down-sampling). Our results have shown building such a model is quite feasible and profitable for the financial institutions. The Time Aware Upsell Prediction Framework (TAUPF) can be easily used in any industry such as telecom, automobile, tourism, etc. where the TAUPF (Clustered Upsell Prediction Approach (CUPA) or Upsell Prediction Approach (UPA)) holds valid. In our case, CUPA books more reliable. As proven in our research, one of the most important challenges is to define measures which have enough predictive power as the subscription to a fixed deposit depends on highly ambiguous situations and cannot be easily isolated. While we have shown the practicality of time-aware upsell prediction model where financial institutions can benefit from contacting the customers at the specified month, further research needs to be done to understand the specific time of the day. In addition, a further empirical/pilot study on real live customer needs to be conducted to prove the effectiveness of the model in the real world.

Keywords: customer acquisition, predictive analysis, targeted marketing, time-aware analysis

Procedia PDF Downloads 124