Search results for: artificial intelligence based optimization

Authors: Marda Vidrianto, Tania Surya Utami

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Electrical Submersible Pump (ESP) is an artificial lift of choice to produce oil on Offshore Java Sea. It is selected based on the production rate capacity and running life expectation. ESP performance in a mature field is highly affected by oil well conditions. The presence of sand, scale, gas, and low influx will create unstable ESP operation hence lowering the run life expectation and system efficiency. This paper reviews the current energy usage and efficiency on every part of the ESP system. The hydraulic and electrical losses, as well as system efficiency for each well, are calculated to identify energy losses and the possibility for improvement. It is shown that high back pressure on the system and low-efficiency pump are the major contributors to energy losses. It was found that optimized production rate and the use of advanced technology on pump and motor unit could improve energy efficiency.

Keywords: advance technology, energy efficiency, ESP, mature field, production rate

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Authors: Yunxiang Fang

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With the aging trend continuing to accelerate, open space is important for the daily life of the elderly, and its old-age friendliness is worthy of attention. Based on behavioral observation and literature research, this paper studies the behavior of the elderly in urban open space. Through the investigation, classification and quantitative analysis of the activity types, time characteristics and spatial behavior order of the elderly in Xicheng Square in Hangzhou, it summarizes the square space suitable for the psychological needs, physiology and activity needs of the elderly, combined with the basis of literature research. Finally, the suggestions for the improvement of the old-age friendship of Xicheng Square are put forward, from the aspects of microclimate, safety and accessibility, space richness and service facility quality.

Keywords: behavior characteristics, old-age friendliness, open space, square

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Authors: Fei Peng, Hai Xiao, Rajendra K. Bordia, Jianhua Tong, Dongsheng Li

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the report high-throughput, ultra-fast laser sintering of alumina sample array and characterization of sample units’ microstructure and hardness, as a fast exploration of laser processing parameters, microstructure, and property. These experimental data were used to train machine-learning (ML) models. Accurate ML predictions were demonstrated for the processing-microstructure-property relationship, specifically in (1) prediction of the microstructure of alumina under arbitrary laser power and (2) prediction of the expected microstructure from the desired hardness. An independent neural network was developed and showed that ML-predicted microstructure had less than 10% error from real ones, in terms of projected hardness. To monitor the microstructure during laser sintering, we demonstrated an ML model that can instantaneously predict ceramic’s microstructure at the laser spot, based on the laser spot brightness. The ML model can generate more than 10 predictions per second, and the error in average grain size was less than 5% from the experimental observations.

Keywords: machine learning, additive manufacturing, ceramics, microstructure, hardness

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Authors: Zhenyu Zhang, Hsi-Hsien Wei

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Highway networks play a vital role in post-disaster recovery for disaster-damaged areas. Damaged bridges in such networks can disrupt the recovery activities by impeding the transportation of people, cargo, and reconstruction resources. Therefore, rapid restoration of damaged bridges is of paramount importance to long-term disaster recovery. In the post-disaster recovery phase, the key to restoration scheduling for a highway network is prioritization of bridge-repair tasks. Resilience is widely used as a measure of the ability to recover with which a network can return to its pre-disaster level of functionality. In practice, highways will be temporarily blocked during the downtime of bridge restoration, leading to the decrease of highway-network functionality. The failure to take downtime effects into account can lead to overestimation of network resilience. Additionally, post-disaster recovery of highway networks is generally divided into emergency bridge repair (EBR) in the response phase and long-term bridge repair (LBR) in the recovery phase, and both of EBR and LBR are different in terms of restoration objectives, restoration duration, budget, etc. Distinguish these two phases are important to precisely quantify highway network resilience and generate suitable restoration schedules for highway networks in the recovery phase. To address the above issues, this study proposes a novel resilience quantification method for the optimization of long-term bridge repair schedules (LBRS) taking into account the impact of EBR activities and restoration downtime on a highway network’s functionality. A time-dependent integer program with recursive functions is formulated for optimally scheduling LBR activities. Moreover, since uncertainty always exists in the LBRS problem, this paper extends the optimization model from the deterministic case to the stochastic case. A hybrid genetic algorithm that integrates a heuristic approach into a traditional genetic algorithm to accelerate the evolution process is developed. The proposed methods are tested using data from the 2008 Wenchuan earthquake, based on a regional highway network in Sichuan, China, consisting of 168 highway bridges on 36 highways connecting 25 cities/towns. The results show that, in this case, neglecting the bridge restoration downtime can lead to approximately 15% overestimation of highway network resilience. Moreover, accounting for the impact of EBR on network functionality can help to generate a more specific and reasonable LBRS. The theoretical and practical values are as follows. First, the proposed network recovery curve contributes to comprehensive quantification of highway network resilience by accounting for the impact of both restoration downtime and EBR activities on the recovery curves. Moreover, this study can improve the highway network resilience from the organizational dimension by providing bridge managers with optimal LBR strategies.

Keywords: disaster management, highway network, long-term bridge repair schedule, resilience, restoration downtime

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Authors: Mohammad Khoshini, Arman Khoshghalb, Meghdad Payan, Nasser Khalili

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Most of the Earth’s crust surface rocks are technically categorized as weak rocks or weakly bonded geomaterials. Deeply weathered, weakly cemented, friable and easily erodible, they demonstrate complex material behaviour and understanding the overlooked mechanical behaviour of such materials is of particular importance in geotechnical engineering practice. Weakly bonded geomaterials are so susceptible to surface shear and moisture that conventional methods of core drilling fail to extract high-quality undisturbed samples out of them. Moreover, most of these geomaterials are of high heterogeneity rendering less reliable and feasible material characterization. In order to compensate for the unpredictability of the material response, either numerous experiments are needed to be conducted or large factors of safety must be implemented in the design process. However, none of these approaches is sustainable. In this study, a method for dry core drilling of such materials is introduced to take high-quality undisturbed core samples. By freezing the material at certain moisture content, a secondary structure is developed throughout the material which helps the whole structure to remain intact during the core drilling process. Moreover, to address the heterogeneity issue, the natural material was reconstructed artificially to obtain a homogeneous material with very high similarity to the natural one in both micro and macro-mechanical perspectives. The method is verified for both micro and macro scale. In terms of micro-scale analysis, using Scanning Electron Microscopy (SEM), pore spaces and inter-particle bonds were investigated and compared between natural and artificial materials. X-Ray Diffraction, XRD, analyses are also performed to control the chemical composition. At the macro scale, several uniaxial compressive strength tests, as well as triaxial tests, were performed to verify the similar mechanical response of the materials. A high level of agreement is observed between micro and macro results of natural and artificially bonded geomaterials. The proposed methods can play an important role to cut down the costs of experimental programs for material characterization and also to promote the accuracy of the numerical modellings based on the experimental results.

Keywords: Artificial geomaterial, core drilling, macro-mechanical behavior, micro-scale, sample preparation, SEM photography, weakly bonded geomaterials

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Authors: M. H. Shwehdi, S. Raja Mohammad

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Recently energy savings have become more pronounced as a result of the world financial crises as well the unstable oil prices. Certainly all entities needs to adapt Energy Conservation and Management Strategies due to high monthly consumption of their spread locations and advancements of its telecom systems. These system improvements necessitate the establishment of more exchange centers as well provide energy savings. This paper investigates the impact of HVAC System Characteristics, Operational Strategies, the impact of Envelope Thermal Characteristics, and energy conservation measures. These are classified under three types of measures i.e. Zero-Investment; Low-Investment and High-Investment Energy Conservation Measures. The study shows that the Energy Conservation Measures (ECMs) pertaining to the HVAC system characteristics and operation represent the highest potential for energy reduction, attention should be given to window thermal and solar radiation characteristics when large window areas are used. The type of glazing system needs to be carefully considered in the early design phase of future buildings. Paper will present the thermal optimization of different size centers in the two hot-dry and hot-humid Saudi Arabian city of Al Khobar, East province.

Keywords: energy conservation, optimization, thermal design, intermittent operation, exchange centers, hot-humid climate, Saudi Arabia

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Authors: Michele Catalano, Jacopo Di Domenico, Luca Riccetti, Andrea Teglio

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We develop a data-driven agent based model (ABM) for the Italian economy. We calibrate the model for the initial condition and parameters. As a preliminary step, we replicate the Monte-Carlo simulation for the Austrian economy. Then, we evaluate the dynamic properties of the model: the long-run equilibrium and the allocative efficiency in terms of disequilibrium patterns arising in the search and matching process for final goods, capital, intermediate goods, and credit markets. In this perspective, we use a randomized initial condition approach. We perform a robustness analysis perturbing the system for different parameter setups. We explore the empirical properties of the model using a rolling window forecast exercise from 2010 to 2022 to observe the model’s forecasting ability in the wake of the COVID-19 pandemic. We perform an analysis of the properties of the model with a different number of agents, that is, with different scales of the model compared to the real economy. The model generally displays transient dynamics that properly fit macroeconomic data regarding forecasting ability. We stress the model with a large set of shocks, namely interest policy, fiscal policy, and exogenous factors, such as external foreign demand for export. In this way, we can explore the most exposed sectors of the economy. Finally, we modify the technology mix of the various sectors and, consequently, the underlying input-output sectoral interdependence to stress the economy and observe the long-run projections. In this way, we can include in the model the generation of endogenous crisis due to the implied structural change, technological unemployment, and potential lack of aggregate demand creating the condition for cyclical endogenous crises reproduced in this artificial economy.

Keywords: agent-based models, behavioral macro, macroeconomic forecasting, micro data

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Authors: Mohsin Talib Mohammed, Zahid A. Khan, Arshad N. Siddiquee

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Biometallic materials are the most important materials for use in biomedical applications especially in manufacturing a variety of biological artificial replacements in a modern worlds, e.g. hip, knee or shoulder joints, due to their advanced characteristics. Titanium (Ti) and its alloys are used extensively in biomedical applications based on their high specific strength and excellent corrosion resistance. Beta-Ti alloys containing completely biocompatible elements are exceptionally prospective materials for manufacturing of bioimplants. They have superior mechanical, chemical and electrochemical properties for use as biomaterials. These biomaterials have the ability to introduce the most important property of biochemical compatibility which is low elastic modulus. This review examines current information on the recent developments in alloying elements leading to improvements of beta Ti alloys for use as biomaterials. Moreover, this paper focuses mainly on the evolution, evaluation and development of the modulus of elasticity as an effective factor on the performance of beta alloys.

Keywords: beta alloys, biomedical applications, titanium alloys, Young's modulus

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Authors: Tamar Trop, Ido Izhaki

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Small natural freshwater bodies (SNFWBs), which are vital for many waterbird species, are considered endangered habitats due to their progressive loss and extensive degradation. While SNFWBs are becoming extinct, studies have indicated that many waterbird species may greatly benefit from various types of small artificial waterbodies (SAWBs), such as floodwater and treated water reservoirs. If designed and managed with care, SAWBs hold significant potential to serve as alternative or complementary habitats for birds, and thus mitigate the adverse effects of SNFWBs loss. Currently, most reservoirs are built as infrastructural facilities and designed according to engineering best practices and site-specific considerations, which do not include catering for waterbirds' needs. Furthermore, as things stand, there is still a lack of clear and comprehensive knowledge regarding the additional factors that should be considered in tackling the challenge of attracting waterbirds' to reservoirs, without compromising on the reservoirs' original functions. This study attempts to narrow this knowledge gap by performing a systematic review of the various factors (e.g., bird attributes; physical, structural, spatial, climatic, chemical, and biological characteristics of the waterbody; and anthropogenic activities) affecting the occurrence, abundance, richness, and diversity of waterbirds in SNFWBs. The methodical review provides a concise and relatively unbiased synthesis of the knowledge in the field, which can inform decision-making and practice regarding the planning, design, and management of reservoirs with birds in mind. Such knowledge is especially beneficial for arid and semiarid areas, where natural water sources are deteriorating and becoming extinct even faster due to climate change.

Keywords: artificial waterbodies, reservoirs, small waterbodies, waterbirds

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Authors: Mohammad Jalali Varnamkhasti

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The genetic algorithms have been very successful in handling difficult optimization problems. The fundamental problem in genetic algorithms is premature convergence. This paper, present a new fuzzy genetic algorithm based on chaotic values instead of the random values in genetic algorithm processes. In this algorithm, for initial population is used chaotic sequences and then a new sexual selection proposed for selection mechanism. In this technique, the population is divided such that the male and female would be selected in an alternate way. The layout of the male and female chromosomes in each generation is different. A female chromosome is selected by tournament selection size from the female group. Then, the male chromosome is selected, in order of preference based on the maximum Hamming distance between the male chromosome and the female chromosome or The highest fitness value of male chromosome (if more than one male chromosome is having the maximum Hamming distance existed), or Random selection. The selections of crossover and mutation operators are achieved by running the fuzzy logic controllers, the crossover and mutation probabilities are varied on the basis of the phenotype and genotype characteristics of the chromosome population. Computational experiments are conducted on the proposed techniques and the results are compared with some other operators, heuristic and local search algorithms commonly used for solving p-median problems published in the literature.

Keywords: genetic algorithm, fuzzy system, chaos, sexual selection

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Authors: Swati Bajpai, S. P. K Jena

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Background: There is dramatic increase in the prevalence and severity of overweight in adolescents, raising concerns about their psychosocial and cognitive consequences, thereby indicating the immediate need to understand the effects of increased weight on scholastic performance. Although the body of research is currently limited, available results have identified an inverse relationship between obesity and cognition in adolescents. Aim: to examine the association between increased Body Mass Index in adolescents and their neurocognitive functioning. Methods: A case –control study of 28 subjects in the age group of 11-17 years (14 Males and 14 females) was taken on the basis of main inclusion criteria (Body Mass Index). All of them were randomized to (experimental group: overweight) and (control group: normal weighted). A complete neurocognitive assessment was carried out using validated psychological scales namely, Color Progressive Matrices (to assess intelligence); Bender Visual Motor Gestalt Test (Perceptual motor functioning); PGI-Memory Scale for Children (memory functioning) and Malin’s Intelligence Scale Indian Children (verbal and performance ability). Results: statistical analysis of the results depicted that 57% of the experimental group lack in cognitive abilities, especially in general knowledge (99.1±12.0 vs. 102.8±6.7), working memory (91.5±8.4 vs. 93.1±8.7), concrete ability (82.3±11.5 vs. 92.6±1.7) and perceptual motor functioning (1.5±1.0 vs. 0.3±0.9) as compared to control group. Conclusion: Our investigations suggest that weight gain results, at least in part, from a neurological predisposition characterized by reduced executive function, and in turn obesity itself has a compounding negative impact on the brain. Though, larger sample is needed to make more affirmative claims.

Keywords: adolescents, body mass index, neurocognition, obesity

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Authors: Erwanda Nuryahya, Aas Nurasyiah, Sri Yayu Ninglasari

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Indonesia is the fourth most populous country that still has many troubles in its development. One of the problems which is very important and unresolved is poverty. Limited job opportunity is one unresolved cause of it until today. The purpose of making this scientific paper is to know benefits of E-Money Paytren Application to enhance its partners’ income, owned by company Veritra Sentosa International. The methodology used here is the quantitative and qualitative descriptive method by case study approach. The data used are primary and secondary data. The primary data is obtained from interviews and observation to company Veritra Sentosa International and the distribution of 400 questionnaires to Paytren partner. Secondary data is obtained from the literature study and documentary. The result is that the Paytren with a system direct sales tiered syariah proven able to enhance its partners’ income. Therefore, the Optimization Financial Technology through E-Money Paytren Application should be utilized by Indonesians because it is proven that it is able to increase the income of the partners. Therefore, Paytren Application is very useful for the government, the sharia financial industry, and society in reducing poverty in Indonesia.

Keywords: e-money PayTren application, financial technology, poverty, direct sales tiered Sharia

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Authors: Daohong Yang, Xiang Zhang, Lei Li, Wanting Zhou

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Visual Simultaneous Localization and Mapping (VSLAM) is a technology that obtains information in the environment for self-positioning and mapping. It is widely used in computer vision, robotics and other fields. Many visual SLAM systems, such as OBSLAM3, employ a constant-speed motion model that provides the initial pose of the current frame to improve the speed and accuracy of feature matching. However, in actual situations, the constant velocity motion model is often difficult to be satisfied, which may lead to a large deviation between the obtained initial pose and the real value, and may lead to errors in nonlinear optimization results. Therefore, this paper proposed a motion model based on acceleration, which can be applied on most SLAM systems. In order to better describe the acceleration of the camera pose, we decoupled the pose transformation matrix, and calculated the rotation matrix and the translation vector respectively, where the rotation matrix is represented by rotation vector. We assume that, in a short period of time, the changes of rotating angular velocity and translation vector remain the same. Based on this assumption, the initial pose of the current frame is estimated. In addition, the error of constant velocity model was analyzed theoretically. Finally, we applied our proposed approach to the ORBSLAM3 system and evaluated two sets of sequences on the TUM dataset. The results showed that our proposed method had a more accurate initial pose estimation and the accuracy of ORBSLAM3 system is improved by 6.61% and 6.46% respectively on the two test sequences.

Keywords: error estimation, constant acceleration motion model, pose estimation, visual SLAM

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Authors: Renata De Toledo Cintra, Bruno Ramos, Douglas Gouvêa

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There is a huge global concern due to the emission of greenhouse gases, consequent environmental problems, and the increase in the average temperature of the planet, caused mainly by fossil fuels, petroleum derivatives represent a big part. One of the main greenhouse gases, in terms of volume, is CO₂. Recovering a part of this product through chemical reactions that use sunlight as an energy source and even producing renewable fuel (such as ethane, methane, ethanol, among others) is a great opportunity. The process of artificial photosynthesis, through the conversion of CO₂ and H₂O into organic products and oxygen using a metallic oxide catalyst, and incidence of sunlight, is one of the promising solutions. Therefore, this research is of great relevance. To this reaction take place efficiently, an optimized reactor was developed through simulation and prior analysis so that the geometry of the internal channel is an efficient route and allows the reaction to happen, in a controlled and optimized way, in flow continuously and offering the least possible resistance. The design of this reactor prototype can be made in different materials, such as polymers, ceramics and metals, and made through different processes, such as additive manufacturing (3D printer), CNC, among others. To carry out the photocatalysis in the reactors, different types of catalysts will be used, such as ZnO deposited by spray pyrolysis in the lighting window, probably modified ZnO, TiO₂ and modified TiO₂, among others, aiming to increase the production of organic molecules, with the lowest possible energy.

Keywords: artificial photosynthesis, CO₂ reduction, photocatalysis, photoreactor design, 3D printed reactors, solar fuels

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Authors: Nooshin Salari, Viliam Makis

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In this paper, we propose a condition-based maintenance policy for multi-unit systems considering the existence of economic dependency among units. We consider a system composed of N identical units, where each unit deteriorates independently. Deterioration process of each unit is modeled as a three-state continuous time homogeneous Markov chain with two working states and a failure state. The average production rate of units varies in different working states and demand rate of the system is constant. Units are inspected at equidistant time epochs, and decision regarding performing maintenance is determined by the number of units in the failure state. If the total number of units in the failure state exceeds a critical level, maintenance is initiated, where units in failed state are replaced correctively and deteriorated state units are maintained preventively. Our objective is to determine the optimal number of failed units to initiate maintenance minimizing the long run expected average cost per unit time. The problem is formulated and solved in the semi-Markov decision process (SMDP) framework. A numerical example is developed to demonstrate the proposed policy and the comparison with the corrective maintenance policy is presented.

Keywords: reliability, maintenance optimization, semi-Markov decision process, production

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Authors: Mateusz Paszko, Miroslaw Wendeker, Adam Majczak

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High temperature waste energy offers a number of management options. The most common energy recuperation systems, that are actually used to utilize energy from the high temperature sources are steam turbines working in a high pressure and temperature closed cycles. Due to the high costs of production of energy recuperation systems, especially rotary turbine discs equipped with blades, currently used solutions are limited in use with waste energy sources of temperature below 100 °C. This study presents the results of simulating the flow of the water vapor in various configurations of flow ducts in a reaction steam turbine based on Hero’s steam turbine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted with use of the water vapor as an internal agent powering the turbine, which is fully safe for an environment in case of a device failure. The conclusions resulting from the conducted numerical computations should allow for optimization of the flow ducts geometries, in order to achieve the greatest possible efficiency of the turbine. It is expected that the obtained results should be useful for further works related to the development of the final version of a low drag steam turbine dedicated for low cost energy recuperation systems.

Keywords: energy recuperation, CFD analysis, waste energy, steam turbine

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Authors: Maria Antonieta Erna Castillo Holly

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During the last decade, data analysis, strategic decision making, and the use of artificial intelligence (AI) tools in Latin American agriculture have been a challenge. In some countries, the availability, quality, and reliability of historical data, in addition to the current data recording methodology in the field, makes it difficult to use information systems, complete data analysis, and their support for making the right strategic decisions. This is something essential in Agriculture 4.0. where the increase in the global demand for fresh agricultural products of tropical origin, during all the seasons of the year requires a change in the production model and greater agility in the responses to the consumer market demands of quality, quantity, traceability, and sustainability –that means extensive data-. Having quality information available and updated in real-time on what, how much, how, when, where, at what cost, and the compliance with production quality standards represents the greatest challenge for sustainable and profitable agriculture in the region. The objective of this work is to present a methodological proposal for the collection of georeferenced data from the protected agriculture sector, specifically in production units (UP) with tall structures (Greenhouses), initially for Venezuela, taking the state of Mérida as the geographical framework, and horticultural products as target crops. The document presents some background information and explains the methodology and tools used in the 3 phases of the work: diagnosis, data collection, and analysis. As a result, an evaluation of the process is carried out, relevant data and dashboards are displayed, and the first satellite maps integrated with layers of information in a geographic information system are presented. Finally, some improvement proposals and tentatively recommended applications are added to the process, understanding that their objective is to provide better qualified and traceable georeferenced data for subsequent analysis of the information and more agile and accurate strategic decision making. One of the main points of this study is the lack of quality data treatment in the Latin America area and especially in the Caribbean basin, being one of the most important points how to manage the lack of complete official data. The methodology has been tested with horticultural products, but it can be extended to other tropical crops.

Keywords: greenhouses, protected agriculture, data analysis, geographic information systems, Venezuela

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Authors: Jyotsna Gupta, S. Ghosh, S. Aravindan

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The requirement of artificial prostheses (such as hip and knee joints) has increased with time. Many researchers are working to develop new implants with improved properties such as excellent biocompatibility with no tissue reactions, corrosion resistance in body fluid, high yield strength and low elastic modulus. Further, the morphological properties of the artificial implants should also match with that of the human bone so that cell adhesion, proliferation and transportation of the minerals and nutrition through body fluid can be obtained. Present study attempts to make porous Ti6Al15Mo alloys through powder metallurgy route using space holder technique. The alloy consists of 6wt% of Al which was taken as α phase stabilizer and 15wt% Mo was taken as β phase stabilizer with theoretical density 4.708. Ammonium hydrogen carbonate is used as a space holder in order to generate the porosity. The porosity of these fabricated porous alloys was controlled by adding the 0, 50, 70 vol.% of the space holder content. Three phases were found in the microstructure: α, α_2 and β phase of titanium. Kirkendall pores are observed to be decreased with increase of holding time during sintering and parallelly compressive strength and elastic modulus value increased slightly. Compressive strength and elastic modulus of porous Ti-6Al-15Mo alloy (1.17 g/cm3 density) is found to be suitable for cancellous bone. Released ions from Ti-6Al-15Mo alloy are far below from the permissible limits in human body.

Keywords: bone implant, powder metallurgy, sintering time, Ti-6Al-15Mo

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Authors: Nasser Al-Azmi, Al-Sabea Salem, Abu-Eida Abdullah, Milan Patra, Mohamed Elyas, Daniel Freile, Larisa Tagarieva

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Well intervention was done along with Production Logging Tools (PLT) to detect sources of water, and to check well integrity for two West Kuwait oil wells started to produce 100 % water. For the first well, to detect the source of water, PLT was performed to check the perforations, no production observed from the bottom two perforation intervals, and an intake of water was observed from the top most perforation. Then a decision was taken to extend the PLT survey from tag depth to the Y-tool. For the second well, the aim was to detect the source of water and if there was a leak in the 7’’liner in front of the upper zones. Data could not be recorded in flowing conditions due to the casing deformation at almost 8300 ft. For the first well from the interpretation of PLT and well integrity data, there was a hole in the 9 5/8'' casing from 8468 ft to 8494 ft producing almost the majority of water, which is 2478 bbl/d. The upper perforation from 10812 ft to 10854 ft was taking 534 stb/d. For the second well, there was a hole in the 7’’liner from 8303 ft MD to 8324 ft MD producing 8334.0 stb/d of water with an intake zone from10322.9-10380.8 ft MD taking the whole fluid. To restore the oil production, W/O rig was mobilized to prevent dump flooding, and during the W/O, the leaking interval was confirmed for both wells. The leakage was cement squeezed and tested at 900-psi positive pressure and 500-psi drawdown pressure. The cement squeeze job was successful. After W/O, the wells kept producing for cleaning, and eventually, the WC reduced to 0%. Regular PLT and well integrity logs are required to study well performance, and well integrity issues, proper cement behind casing is essential to well longevity and well integrity, and the presence of the Y-tool is essential as monitoring of well parameters and ESP to facilitate well intervention tasks. Cost and time optimization in oil and gas and especially during rig operations is crucial. PLT data quality and the accuracy of the interpretations contributed a lot to identify the leakage interval accurately and, in turn, saved a lot of time and reduced the repair cost with almost 35 to 45 %. The added value here was more related to the cost reduction and effective and quick proper decision making based on the economic environment.

Keywords: leak, water shut-off, cement, water leak

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Authors: Min-Hao Wang, Shih-Chih Chen

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Recently, the merits such as simple structure, low power consumption, and compatibility with complementary metal oxide semiconductor (CMOS) process give an advantage of resistive random access memory (RRAM) as a promising candidate for the next generation memory， hafnium dioxide (HfO2) has been widely studied as an oxide layer material, but the use of copper (Cu) as both top and bottom electrodes has rarely been studied. In this study, radio frequency sputtering was used to deposit the intermediate layer HfO₂, and electron beam evaporation was used. For the upper and lower electrodes (cu), using different AR: O ratios, we found that the control of the metal filament will make the filament widely distributed, causing the current to rise to the limit current during Reset. However, if the flow ratio is controlled well, the ON/OFF ratio can reach 104, and the set voltage is controlled below 3v.

Keywords: RRAM, metal filament, HfO₂, Cu electrode

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Authors: Patrick May Mukonki

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KOV pit (Kamoto Oliveira Virgule) is located 10 km from Kolwezi town, one of the mineral rich town in the Lualaba province of the Democratic Republic of Congo. The KOV pit is currently operating under the Katanga Mining Limited (KML), a Glencore-Gecamines (a State Owned Company) join venture. Recently, the mine optimization process provided a life of mine of approximately 10 years withnice pushbacks using the Datamine NPV Scheduler software. In previous KOV pit studies, we recently outlined the impact of the accuracy of the geological information on a long-term mine plan for a big copper mine such as KOV pit. The approach taken, discussed three main scenarios and outlined some weaknesses on the geological information side, and now, in this paper that we are going to develop here, we are going to highlight, as an overview, those weaknesses, strengths and opportunities, in a global SWOT analysis. The approach we are taking here is essentially descriptive in terms of steps taken to optimize KOV pit and, at every step, we categorized the challenges we faced to have a better tradeoff between what we called strengths and what we called weaknesses. The same logic is applied in terms of the opportunities and threats. The SWOT analysis conducted in this paper demonstrates that, despite a general poor ore body definition, and very rude ground water conditions, there is room for improvement for such high grade ore body.

Keywords: mine planning, mine optimization, mine scheduling, SWOT analysis

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Authors: Faisal Zaman, Ya Ping Wong, Boon Yian Ng

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Point cloud source data for surface reconstruction is usually contaminated with noise and outliers. To overcome this, we present a novel approach using modified kernel density estimation (KDE) technique with bilateral filtering to remove noisy points and outliers. First we present a method for estimating optimal bandwidth of multivariate KDE using particle swarm optimization technique which ensures the robust performance of density estimation. Then we use mean-shift algorithm to find the local maxima of the density estimation which gives the centroid of the clusters. Then we compute the distance of a certain point from the centroid. Points belong to outliers then removed by automatic thresholding scheme which yields an accurate and economical point surface. The experimental results show that our approach comparably robust and efficient.

Keywords: point preprocessing, outlier removal, surface reconstruction, kernel density estimation

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Authors: Qi Wang

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In the classroom, teachers have been trained to complete the target task within the limited lecture time, meanwhile learners need to receive a lot of new knowledge, however, most of the time the learners come without the proper pre-class preparation to efficiently take in the contents taught in class. Under this circumstance, teachers do have no time to check whether the learners fully understand the content or not, how the learners communicate in the different contexts, until teachers see the results when the learners are tested. In the past decade, the teaching of Chinese has taken a trend. Teaching focuses less on the use of proper grammatical terms/punctuation and is now placing a heavier focus on the materials from real life contexts. As a result, it has become a greater challenge to teachers, as this requires teachers to fully understand/prepare what they teach and explain the content with simple and understandable words to learners. On the other hand, the same challenge also applies to the learners, who come from different countries. As they have to use what they learnt, based on their personal understanding of the material to effectively communicate with others in the classroom, even in the contexts of a day to day communication. To reach this win-win stage, Feynman’s Technique plays a very important role. This practical report presents you how the Feynman’s Technique is applied into Chinese courses, both writing & oral, to motivate the learners to practice more on writing, reading and speaking in the past few years. Part 1, analysis of different teaching styles and different types of learners, to find the most efficient way to both teachers and learners. Part 2, based on the theory of Feynman’s Technique, how to let learners build the knowledge from knowing the name of something to knowing something, via different designed target tasks. Part 3. The outcomes show that Feynman’s Technique is the interaction of learning style and teaching style, the double-edged sword of Teaching & Learning Chinese as a Second Language.

Keywords: Chinese, Feynman’s technique, learners, teachers

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Authors: Tayfun Çay, Yasar İnceyol, Abdurrahman Özbeyaz

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Land reallocation is one of the most important steps in land consolidation projects. Many different models were proposed for land reallocation in the literature such as Fuzzy Logic, block priority based land reallocation and Spatial Decision Support Systems. A model including four parts is considered for automatic block reallocation with genetic algorithm method in land consolidation projects. These stages are preparing data tables for a project land, determining conditions and constraints of land reallocation, designing command steps and logical flow chart of reallocation algorithm and finally writing program codes of Genetic Algorithm respectively. In this study, we designed the first three steps of the considered model comprising four steps.

Keywords: land consolidation, landholding, land reallocation, optimization, genetic algorithm

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Authors: Anjian Chen, Joseph C. Chen

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This paper studies a case where the targeted surface roughness of fused deposition modeling (FDM) additive manufacturing process is improved. The process is designing to reduce or eliminate the defects and improve the process capability index Cp and Cpk for an FDM additive manufacturing process. The baseline Cp is 0.274 and Cpk is 0.654. This research utilizes the Taguchi methodology, to eliminate defects and improve the process. The Taguchi method is used to optimize the additive manufacturing process and printing parameters that affect the targeted surface roughness of FDM additive manufacturing. The Taguchi L9 orthogonal array is used to organize the parameters' (four controllable parameters and one non-controllable parameter) effectiveness on the FDM additive manufacturing process. The four controllable parameters are nozzle temperature [°C], layer thickness [mm], nozzle speed [mm/s], and extruder speed [%]. The non-controllable parameter is the environmental temperature [°C]. After the optimization of the parameters, a confirmation print was printed to prove that the results can reduce the amount of defects and improve the process capability index Cp from 0.274 to 1.605 and the Cpk from 0.654 to 1.233 for the FDM additive manufacturing process. The final results confirmed that the Taguchi methodology is sufficient to improve the surface roughness of FDM additive manufacturing process.

Keywords: additive manufacturing, fused deposition modeling, surface roughness, six-sigma, Taguchi method, 3D printing

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Authors: Tsang K. L. V., Lewis L. A., Griffith S., Tucker P.

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Background:  Many children with high incidence disabilities, such as autism spectrum disorder (ASD), struggle to participate in the community in a socially acceptable manner. There are limitations for clinical settings to provide natural, real-life scenarios for them to practice the life skills needed to meet their real-life challenges. Virtual reality (VR) offers potential solutions to resolve the existing limitations faced by clinicians to create simulated natural environments for their clients to generalize the facilitated skills. Research design: The research aimed to develop a prototype of an interactive VR system to provide realistic and immersive environments for clients to practice skills. The descriptive qualitative methodology is employed to design and develop the Artificial Interactive Reality Unified System (AIRUS) prototype, which provided insights on how to use advanced VR technology to create simulated real-life social scenarios and enable users to interact with the objects and people inside the virtual environment using natural eye-gazes, hand and body movements. The eye tracking (e.g., selective or joint attention), hand- or body-tracking (e.g., repetitive stimming or fidgeting), and facial tracking (e.g., emotion recognition) functions allowed behavioral data to be captured and managed in the AIRUS architecture. Impact of project: Instead of using external controllers or sensors, hand tracking software enabled the users to interact naturally with the simulated environment using daily life behavior such as handshaking and waving to control and interact with the virtual objects and people. The AIRUS protocol offers opportunities for breakthroughs in future VR-based psychosocial assessment and intervention in occupational therapy. Implications for future projects: AI technology can allow more efficient data capturing and interpretation of object identification and human facial emotion recognition at any given moment. The data points captured can be used to pinpoint our users’ focus and where their interests lie. AI can further help advance the data interpretation system.

Keywords: occupational therapy, psychosocial assessment and intervention, simulated interactive environment, virtual reality

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Authors: Mirzet SeHo, Alaa Alaabed, Mansur Masih

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In theory, risk-sharing-based financing (RSF) is considered a corner stone of Islamic finance. It is argued to render Islamic banks more resilient to shocks. In practice, however, this feature of Islamic financial products is almost negligible. Instead, debt-based instruments, with conventional like features, have overwhelmed the nascent industry. In addition, the framework of present-day economic, regulatory and financial reality inevitably exposes Islamic banks in dual banking systems to problems of conventional banks. This includes, but is not limited to, interest rate risk. Empirical evidence has, thus far, confirmed such exposures, despite Islamic banks’ interest-free operations. This study applies system GMM in modeling the determinants of RSF, and finds that RSF is insensitive to changes in interest rates. Hence, our results provide support to the “stability” view of risk-sharing-based financing. This suggests RSF as the way forward for risk management at Islamic banks, in the absence of widely acceptable Shariah compliant hedging instruments. Further support to the stability view is given by evidence of counter-cyclicality. Unlike debt-based lending that inflates artificial asset bubbles through credit expansion during the upswing of business cycles, RSF is negatively related to GDP growth. Our results also imply a significantly strong relationship between risk-sharing deposits and RSF. However, the pass-through of these deposits to RSF is economically low. Only about 40% of risk-sharing deposits are channeled to risk-sharing financing. This raises questions on the validity of the industry’s claim that depositors accustomed to conventional banking shun away from risk sharing and signals potential for better balance sheet management at Islamic banks. Overall, our findings suggest that, on the one hand, Islamic banks can gain ‘independence’ from conventional banks and interest rates through risk-sharing products, the potential for which is enormous. On the other hand, RSF could enable policy makers to improve systemic stability and restrain excessive credit expansion through its countercyclical features.

Keywords: Islamic banks, risk-sharing, financing, interest rate, dynamic system GMM

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Authors: Ahmed S. Fayed, Umima M. Mansour

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Three polyvinyl chloride membrane sensors were developed for the electrochemical evaluation of ferrous, manganese and zinc ions. The sensors were used for assaying metal ions in cervical mucus (CM) of Egyptian river buffalo-cows (Bubalus bubalis) as their levels vary dependent on cyclical hormone variation during different phases of estrus cycle. The presented sensors are based on using ionophores, β-cyclodextrin (β-CD), hydroxypropyl β-cyclodextrin (HP-β-CD) and sulfocalix-4-arene (SCAL) for sensors 1, 2 and 3 for Fe²⁺, Mn²⁺ and Zn²⁺, respectively. Dioctyl phthalate (DOP) was used as the plasticizer in a polymeric matrix of polyvinylchloride (PVC). For increasing the selectivity and sensitivity of the sensors, each sensor was enriched with a suitable complexing agent, which enhanced the sensor’s response. For sensor 1, β-CD was mixed with bathophenanthroline; for sensor 2, porphyrin was incorporated with HP-β-CD; while for sensor 3, oxine was the used complexing agent with SCAL. Linear responses of 10^-7-10^-2 M with cationic slopes of 53.46, 45.01 and 50.96 over pH range 4-8 were obtained using coated graphite sensors for ferrous, manganese and zinc ionic solutions, respectively. The three sensors were validated, according to the IUPAC guidelines. The obtained results by the presented potentiometric procedures were statistically analyzed and compared with those obtained by atomic absorption spectrophotometric method (AAS). No significant differences for either accuracy or precision were observed between the two techniques. Successful application for the determination of the three studied cations in CM, for the purpose to determine the proper time for artificial insemination (AI) was achieved. The results were compared with those obtained upon analyzing the samples by AAS. Proper detection of estrus and correct time of AI was necessary to maximize the production of buffaloes. In this experiment, 30 multi-parous buffalo-cows were in second to third lactation and weighting 415-530 kg, and were synchronized with OVSynch protocol. Samples were taken in three times around ovulation, on day 8 of OVSynch protocol, on day 9 (20 h before AI) and on day 10 (1 h before AI). Beside analysis of trace elements (Fe²⁺, Mn²⁺ and Zn²⁺) in CM using the three sensors, the samples were analyzed for the three cations and also Cu²⁺ by AAS in the CM samples and blood samples. The results obtained were correlated with hormonal analysis of serum samples and ultrasonography for the purpose of determining of the optimum time of AI. The results showed significant differences and powerful correlation with Zn²⁺ composition of CM during heat phase and the ovulation time, indicating that the parameter could be used as a tool to decide optimal time of AI in buffalo-cows.

Keywords: PVC Sensors, buffalo-cows, cyclodextrins, atomic absorption spectrophotometry, artificial insemination, OVSynch protocol

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Authors: Ava Salmanpour, Hanieh Saeedi, Payam Rouhi, Elahe Hamzeil, Shima Alimohammadi, Siamak Hossein Khalaj, Mohammad Asadian

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Software-defined network (SDN) is a network architecture designed to control network using software application in a central manner. This ability enables remote control of the whole network regardless of the network technology. In fact, in this architecture network intelligence is separated from physical infrastructure, it means that required network components can be implemented virtually using software applications. Today, power networks are characterized by a high range of complexity with a large number of intelligent devices, processing both huge amounts of data and important information. Therefore, reliable and secure communication networks are required. SDNs are the best choice to meet this issue. In this paper, SDN networks capabilities and characteristics will be reviewed and different basic controllers will be compared. The importance of using SDNs to escalate efficiency and reliability in utility power networks is going to be discussed and the comparison between the SDN-based power networks and traditional networks will be explained.

Keywords: software-defined network, SDNs, utility network, open flow, communication, gas and electricity, controller

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Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

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Researchers in the fields of AI and Robotics frequently encounter ethical dilemmas throughout their research endeavors. Various ethical challenges have been pinpointed in the existing literature, including biases and discriminatory outcomes, diffusion of responsibility, and a deficit in transparency within AI operations. This research aims to pinpoint these ethical quandaries faced by researchers and shed light on the mechanisms behind ethical decision-making in the research process. By synthesizing insights from existing literature and acknowledging prevalent shortcomings, such as overlooking the heterogeneous nature of decision-making, non-accumulative results, and a lack of consensus on numerous factors due to limited empirical research, the objective is to conceptualize and validate a model. This model will incorporate influences from individual perspectives and situational contexts, considering potential moderating factors in the ethical decision-making process. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focusing on collaborative robotics for several months. Subsequently, semi-structured interviews with 16 team members were conducted. The entire process took place during the first semester of 2023. Observations were analyzed using an analysis grid, and the interviews underwent thematic analysis using Nvivo software. An initial finding involves identifying the ethical challenges that AI/robotics researchers confront, underlining a disparity between practical applications and theoretical considerations regarding ethical dilemmas in the realm of AI. Notably, researchers in AI prioritize the publication and recognition of their work, sparking the genesis of these ethical inquiries. Furthermore, this article illustrated that researchers tend to embrace a consequentialist ethical framework concerning safety (for humans engaging with robots/AI), worker autonomy in relation to robots, and the societal implications of labor (can robots displace jobs?). A second significant contribution entails proposing a model for ethical decision-making within the AI/Robotics research sphere. The model proposed adopts a process-oriented approach, delineating various research stages (topic proposal, hypothesis formulation, experimentation, conclusion, and valorization). Across these stages and the ethical queries, they entail, a comprehensive four-point comprehension of ethical decision-making is presented: recognition of the moral quandary; moral judgment, signifying the decision-maker's aptitude to discern the morally righteous course of action; moral intention, reflecting the ability to prioritize moral values above others; and moral behavior, denoting the application of moral intention to the situation. Variables such as political inclinations ((anti)-capitalism, environmentalism, veganism) seem to wield significant influence. Moreover, age emerges as a noteworthy moderating factor. AI and robotics researchers are continually confronted with ethical dilemmas during their research endeavors, necessitating thoughtful decision-making. The contribution involves introducing a contextually tailored model, derived from meticulous observations and insightful interviews, enabling the identification of factors that shape ethical decision-making at different stages of the research process.

Keywords: ethical decision making, artificial intelligence, robotics, research

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