Search results for: multimodal optimization

Authors: Jose Francisco Ferreira Ribeiro, Alexandre Bevilacqua Leoneti, Andre Lucirton Costa

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This paper presents a mathematical model in binary variables 0/1 to make the assignment of surgical procedures to the operating rooms in a hospital. The proposed mathematical model is based on the generalized assignment problem, which maximizes the sum of preferences for the use of the operating rooms by doctors, respecting the time available in each room. The corresponding program was written in Visual Basic of Microsoft Excel, and tested to schedule surgeries at St. Lydia Hospital in Ribeirao Preto, Brazil.

Keywords: generalized assignment problem, logistics, optimization, scheduling

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Authors: Suman Chaudhary, Rinku Dhanker, Tanvi, Sneh Goyal

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Sulphur oxidizing bacteria (SOB) have marked their significant role in perspectives of maintaining healthy environment as researchers from all over the world tested and apply these in waste water treatment plants, bioleaching of heavy metals, deterioration of bridge structures, concrete and for bioremediation purposes, etc. Also, these SOB are well adapted in all kinds of environment ranging from normal soil, water habitats to extreme natural sources like geothermal areas, volcanic eruptions, black shale and acid rock drainage (ARD). SOB have been isolated from low pH environment of anthropogenic origin like acid mine drainage (AMD) and bioleaching heaps, hence these can work efficiently in different environmental conditions. Besides having many applications in field of environment science, they may be proven to be very beneficial in area of agriculture as sulphur is the fourth major macronutrients required for the growth of plants. More amount of sulphur is needed by pulses and oilseed crops with respect to the cereal grains. Due to continuous use of land for overproduction of more demanding sulphur utilizing crops and without application of sulphur fertilizers, its concentration is decreasing day by day, and thus, sulphur deficiency is becoming a great problem as it affects the crop productivity and quality. Sulphur is generally found in soils in many forms which are unavailable for plants (cannot be use by plants) like elemental sulphur, thiosulphate which can be taken up by bacteria and converted into simpler forms usable by plants by undergoing a series of transformations. So, keeping the importance of sulphur in view for various soil types, oilseed crops and role of microorganisms in making them available to plants, we made an effort to isolate, optimize, and characterize SOB. Three potential strains of bacteria were isolated, namely SSF7, SSA21, and SSS6, showing sulphate production of concentration, i.e. 2.268, 3.102, and 2.785 mM, respectively. Also, these were optimized for various culture conditions like carbon, nitrogen source, pH, temperature, and incubation time, and characterization was also done.

Keywords: sulphur oxidizing bacteria, isolation, optimization, characterization, sulphate production

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Authors: Xiaoquan Huang, Congcong Li, Tingting Wei, Changcun Bai, Na Liu, Meng Tang

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Silver is often doped on nano-titanium dioxide photocatalysts (Ag-TiO₂) by photodeposition method to improve their utilization of visible-light while increasing the toxicity of TiO₂。 However, it is not known what factors influence this toxicity and how to reduce toxicity while maintaining the maximum catalytic activity. In this study, Ag-TiO₂ photocatalysts were synthesized by the photodeposition method with different silver content (AgC) and photodeposition time (PDT). Characterization and catalytic experiments demonstrated that silver was well assembled on TiO₂ with excellent visible-light catalytic activity, and the size of silver increased with PDT. In vitro, the cell viability of lung epithelial cells A549 and BEAS-2B showed that the higher content and smaller size of silver doping caused higher toxicity. In vivo, Ag-TiO₂ catalysts with lower AgC or larger silver particle size obviously caused less pulmonary pro-inflammatory and pro-fibrosis responses. However, the visible light catalytic activity decreased with the increase in silver size. Therefore, in order to optimize the Ag-TiO₂ photocatalyst with the lowest pulmonary toxicity and highest catalytic performance, response surface methodology (RSM) was further performed to optimize the two independent variables of AgC and PDT. Visible-light catalytic activity was evaluated by the degradation rate of Rhodamine B, the antibacterial property was evaluated by killing log value for Escherichia coli, and cytotoxicity was evaluated by IC50 to BEAS-2B cells. As a result, the RSM model showed that AgC and PDT exhibited an interaction effect on catalytic activity in the quadratic model. AgC was positively correlated with antibacterial activity. Cytotoxicity was proportional to AgC while inversely proportional to PDT. Finally, the optimization values were AgC 3.08 w/w% and PDT 28 min. Under this optimal condition, the relatively high silver proportion ensured the visible-light catalytic and antibacterial activity, while the longer PDT effectively reduced the cytotoxicity. This study is of significance for the safe and efficient application of silver-doped TiO₂ photocatalysts.

Keywords: Ag-doped TiO₂, cytotoxicity, inflammtion, fibrosis, response surface methodology

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Authors: Jiachen Wang, Dongxu Ji

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Geothermal power generation is a mature technology with zero carbon emission and stable power output, which could play a vital role as an optimum substitution of base load technology in China’s future decarbonization society. However, the development of geothermal power plants in China is stagnated for a decade due to the underestimation of geothermal energy and insufficient favoring policy. Lack of understanding of the potential value of base-load technology and environmental benefits is the critical reason for disappointed policy support. This paper proposed a different energy-economic model to uncover the potential benefit of developing a geothermal power plant in Puer, including the value of base-load power generation, and environmental and economic benefits. Optimization of the Organic Rankine Cycle (ORC) for maximum power output and minimum Levelized cost of electricity was first conducted. This process aimed at finding the optimum working fluid, turbine inlet pressure, pinch point temperature difference and superheat degrees. Then the optimal ORC model was sent to the energy-economic model to simulate the potential economic and environmental benefits. Impact of geothermal power plants based on the scenarios of implementing carbon trade market, the direct subsidy per electricity generation and nothing was tested. In addition, a requirement of geothermal reservoirs, including geothermal temperature and mass flow rate for a competitive power generation technology with other renewables, was listed. The result indicated that the ORC power plant has a significant economic and environmental benefit over other renewable power generation technologies when implementing carbon trading market and subsidy support. At the same time, developers must locate the geothermal reservoirs with minimum temperature and mass flow rate of 130 degrees and 50 m/s to guarantee a profitable project under nothing scenarios.

Keywords: geothermal power generation, optimization, energy model, thermodynamics

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Authors: Yasmeen Coaxum

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The year 2020 became synonymous with the words “Emergency Remote Teaching,” which was imposed upon educators during the COVID-19 pandemic. Consequently, teachers were compelled to find new and engaging ways to educate their students outside of the face-to-face classroom setting. Now online instruction has become more of the norm rather than a way to manage educational expectations during a crisis. Therefore, implementing a strategic way to create online environments for students to thrive, create, and fully engage in their learning process is essential. The Synchronous Online Flipped Learning Approach or SOFLA® is a distance learning model that most closely replicates actual classroom teaching. SOFLA® includes structured, interactive, multimodal activities in an eight-step learning cycle with both asynchronous and synchronous components that foster autonomous and interactive learning among today’s online learners. The results of a pilot study in an Intensive English Program at a university, using SOFLA® methodology to facilitate podcasting in an online learning environment will be shared. Previous findings on student-produced podcasting projects have shown that students felt they improved their pronunciation, vocabulary, and speaking skills. However, few if any studies have been conducted on using a structured online flipped learning approach to facilitate such projects. Therefore, the purpose of this study is to assess the effect of using the SOFLA® framework to enhance optimum engagement in the online environment while using podcasts as the primary tool of instruction. Through data from interviews, questionnaires, and the results of formative and summative assessments, this study also investigates the affective and academic impact this flipped learning method combined with podcasting has on the students in terms of speaking confidence and vocabulary retention, and production. The steps of SOFLA will be illustrated, a video demonstration of the Anchor podcasting app will be shown, and final student projects and questionnaire responses will be shared. The specific context is a 14-week advanced level conversation and listening class. Participants vary in age but are all adult language learners representing a diverse array of countries.

Keywords: mall online flipped learning, podcasting, productive vocabulary

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Authors: Y. El Kaissi, M. Allam, A. Koulou, M. Galai, M. Ebn Touhami

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The aim of our work is to develop an industrial bath of nickel alloy deposit on mild steel. The optimization of the operating parameters made it possible to obtain a stable Ni-P alloy deposition formulation. To understand the reaction mechanism of the deposition process, a kinetic study was performed by cyclic voltammetry and by electrochemical impedance spectroscopy (EIS). The coatings obtained have a very high corrosion resistance in a very aggressive acid medium which increases with the heat treatment.

Keywords: cyclic voltammetry, EIS, electroless Ni–P coating, heat treatment, potentiodynamic polarization

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Authors: Justas Dilys

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ThispaperaddressestheimplementationandoptimizationofanUnscentedKalmanFilter(UKF) for the Permanent Magnet Synchronous Motor (PMSM) sensorless control using an ARM Cortex- M3 microcontroller. A various optimization levels based on arithmetic calculation reduction was implemented in ARM Cortex-M3 microcontroller. The execution time of UKF estimator was up to 90µs without loss of accuracy. Moreover, simulation studies on the Unscented Kalman filters are carried out using Matlab to explore the usability of the UKF in a sensorless PMSMdrive.

Keywords: unscented kalman filter, ARM, PMSM, implementation

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Authors: David Muyise

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Mixed Integer Programming (MIP) is an approach that involves the optimization of a range of decision variables in order to minimize or maximize a particular objective function. The main objective of this study was to apply the MIP approach to optimize the deployment of waste plastic to fuel oil processing plants in Uganda. The processing plants are meant to reduce plastic pollution by pyrolyzing the waste plastic into a cleaner fuel that can be used to power diesel/paraffin engines, so as (1) to reduce the negative environmental impacts associated with plastic pollution and also (2) to curb down the energy gap by utilizing the fuel oil. A programming model was established and tested in two case study applications that are, small-scale applications in rural towns and large-scale deployment across major cities in the country. In order to design the supply chain, optimal decisions on the types of waste plastic to be processed, size, location and number of plants, and downstream fuel applications were concurrently made based on the payback period, investor requirements for capital cost and production cost of fuel and electricity. The model comprises qualitative data gathered from waste plastic pickers at landfills and potential investors, and quantitative data obtained from primary research. It was found out from the study that a distributed system is suitable for small rural towns, whereas a decentralized system is only suitable for big cities. Small towns of Kalagi, Mukono, Ishaka, and Jinja were found to be the ideal locations for the deployment of distributed processing systems, whereas Kampala, Mbarara, and Gulu cities were found to be the ideal locations initially utilize the decentralized pyrolysis technology system. We conclude that the model findings will be most important to investors, engineers, plant developers, and municipalities interested in waste plastic to fuel processing in Uganda and elsewhere in developing economy.

Keywords: mixed integer programming, fuel oil plants, optimisation of waste plastics, plastic pollution, pyrolyzing

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Authors: Arun Kumar R. K. Gothra, Hasan Alhakamy

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With increasing expectations and demands for warehousing and distribution, Warehouse Solution Incorporated in Victoria has been looking at ways to improve on its business processes to maintain the competitive edge. To maintain the provision of high quality service standards at competitive and affordable prices, improvements in the logistics management are necessary. One such avenue is to make efficient use of space available in the warehouse. This paper is based on a study of the collaboration of Warehouse Solution Inc with Dandenong Distribution Centre (DDC) to solve congestion problem and enhance efficiency of the whole warehouse activities.

Keywords: space optimization, optimal utilization, warehouse, DDC

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Authors: S. Gómez, G. Sánchez, J. Zarama, M. Castañeda Ramos, J. Escoto Alcántar, J. Torres, A. Núñez, S. Santana, F. Nájera, J. A. Lopez

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This paper shows in detail the mathematical model of direct and inverse kinematics for a robot manipulator (welding type) with four degrees of freedom. Using the D-H parameters, screw theory, numerical, geometric and interpolation methods, the theoretical and practical values of the position of robot were determined using an optimized algorithm for inverse kinematics obtaining the values of the particular joints in order to determine the virtual paths in a relatively short time.

Keywords: kinematics, degree of freedom, optimization, robot manipulator

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Authors: Mathuravech Thanaphon, Thephasit Nat

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The Electricity Generating Authority of Thailand (EGAT) is focusing on expanding its pumped storage hydropower (PSH) capacity to increase the reliability of the system during peak demand and allow for greater integration of renewables. To achieve this requirement, Thailand will have to double its current renewable electricity production. To address the challenges of balancing supply and demand in the grid with increasing levels of RE penetration, as well as rising peak demand, EGAT has already been studying the potential for additional PSH capacity for several years to enable an increased share of RE and replace existing fossil fuel-fired generation. In addition, the role that pumped-storage hydropower would play in fulfilling multiple grid functions and renewable integration. The proposed sites for new PSH would help increase the reliability of power generation in Thailand. However, most of the electricity generation will come from RE, chiefly wind and photovoltaic, and significant additional Energy Storage capacity will be needed. In this paper, the impact of integrating the PSH system on the adequacy of renewable rich power generating systems to reduce the thermal power generating units is investigated. The variations of system adequacy indices are analyzed for different PSH-renewables capacities and storage levels. Power Development Plan 2018 rev.1 (PDP2018 rev.1), which is modified by integrating a six-new PSH system and RE planning and development aftermath in 2030, is the very challenge. The system adequacy indices through power generation are obtained using Multi-Objective Genetic Algorithm (MOGA) Optimization. MOGA is a probabilistic heuristic and stochastic algorithm that is able to find the global minima, which have the advantage that the fitness function does not necessarily require the gradient. In this sense, the method is more flexible in solving reliability optimization problems for a composite power system. The optimization with hourly time step takes years of planning horizon much larger than the weekly horizon that usually sets the scheduling studies. The objective function is to be optimized to maximize RE energy generation, minimize energy imbalances, and minimize thermal power generation using MATLAB. The PDP2018 rev.1 was set to be simulated based on its planned capacity stepping into 2030 and 2050. Therefore, the four main scenario analyses are conducted as the target of renewables share: 1) Business-As-Usual (BAU), 2) National Targets (30% RE in 2030), 3) Carbon Neutrality Targets (50% RE in 2050), and 5) 100% RE or full-decarbonization. According to the results, the generating system adequacy is significantly affected by both PSH-RE and Thermal units. When a PSH is integrated, it can provide hourly capacity to the power system as well as better allocate renewable energy generation to reduce thermal generations and improve system reliability. These results show that a significant level of reliability improvement can be obtained by PSH, especially in renewable-rich power systems.

Keywords: pumped storage hydropower, renewable energy integration, system adequacy, power development planning, RE100, multi-objective genetic algorithm

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Authors: Angela Bargenda, Erhard Lick, Dhoha Trabelsi

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Research in retailing has identified the importance of atmospherics as an essential element in enhancing store image, store patronage intentions, and the overall shopping experience in a retail environment. However, in the area of atmospherics, store window design, which represents an essential component of external store atmospherics, remains a vastly underrepresented phenomenon in extant scholarship. This paper seeks to fill this gap by exploring the relevance of store window design as an atmospheric tool. In particular, empirical evidence of theme-based theatrical store front windows, which put emphasis on the use of verbo-visual design elements, was found in Paris and New York. The purpose of this study was to identify to what extent such multimodal window designs of high-end department stores in metropolitan cities have an impact on store entry decisions and attitudes towards the retailer’s image. As theoretical construct, the linguistic concept of multimodality and Mehrabian’s and Russell’s model in environmental psychology were applied. To answer the research question, two studies were conducted. For Study 1 a case study approach was selected to define three different types of store window designs based on different types of visual-verbal relations. Each of these types of store window design represented a different level of cognitive elaboration required for the decoding process. Study 2 consisted of an on-line survey carried out among more than 300 respondents to examine the influence of these three types of store window design on the consumer behavioral variables mentioned above. The results of this study show that the higher the cognitive elaboration needed to decode the message of the store window, the lower the store entry propensity. In contrast, the higher the cognitive elaboration, the higher the perceived image of the retailer’s image. One important conclusion is that in order to increase consumers’ propensity to enter stores with theme-based theatrical store front windows, retailers need to limit the cognitive elaboration required to decode their verbo-visual window design.

Keywords: consumer behavior, multimodality, store atmospherics, store window design

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Authors: Carolina Zambrana, Grover Zurita

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The food loss production that occurs in deficient agricultural production is one of the major problems worldwide. This puts the population's food security and the efficiency of farming investments at risk. It is to be expected that this food security will be achieved with the own and efficient production of each country. It will have an impact on the well-being of its population and, thus, also on food sovereignty. The production losses in quantity and quality occur due to the lack of efficient detection of diseases at an early stage. It is very difficult to solve the agriculture efficiency using traditional methods since it takes a long time to be carried out due to detection imprecision of the main diseases, especially when the production areas are extensive. Therefore, the main objective of this research study is to perform a systematic literature review, of the latest five years, of Precision Agriculture (PA) to be able to understand the state of the art of the set of new technologies, procedures, and optimization processes with Artificial Intelligence (AI). This study will focus on Corns, Potatoes, and Rice diagnostic diseases. The extensive literature review will be performed on Elsevier, Scopus, and IEEE databases. In addition, this research will focus on advanced digital imaging processing and the development of software and hardware for PA. The convolution neural network will be handling special attention due to its outstanding diagnostic results. Moreover, the studied data will be incorporated with artificial intelligence algorithms for the automatic diagnosis of crop quality. Finally, precision agriculture with technology applied to the agricultural sector allows the land to be exploited efficiently. This system requires sensors, drones, data acquisition cards, and global positioning systems. This research seeks to merge different areas of science, control engineering, electronics, digital image processing, and artificial intelligence for the development, in the near future, of a low-cost image measurement system that allows the optimization of crops with AI.

Keywords: precision agriculture, convolutional neural network, deep learning, artificial intelligence

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Authors: Migena Mana, Ahmed Khalid Syed, Abdul Malik, Nikhil Cherian

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In recent years, advancements in deep learning enabled researchers to tackle the problem of self-driving cars. Car companies use huge datasets to train their deep learning models to make autonomous cars a reality. However, this approach has certain drawbacks in that the state space of possible actions for a car is so huge that there cannot be a dataset for every possible road scenario. To overcome this problem, the concept of reinforcement learning (RL) is being investigated in this research. Since the problem of autonomous driving can be modeled in a simulation, it lends itself naturally to the domain of reinforcement learning. The advantage of this approach is that we can model different and complex road scenarios in a simulation without having to deploy in the real world. The autonomous agent can learn to drive by finding the optimal policy. This learned model can then be easily deployed in a real-world setting. In this project, we focus on three RL algorithms: Q-learning, Deep Deterministic Policy Gradient (DDPG), and Proximal Policy Optimization (PPO). To model the environment, we have used TORCS (The Open Racing Car Simulator), which provides us with a strong foundation to test our model. The inputs to the algorithms are the sensor data provided by the simulator such as velocity, distance from side pavement, etc. The outcome of this research project is a comparative analysis of these algorithms. Based on the comparison, the PPO algorithm gives the best results. When using PPO algorithm, the reward is greater, and the acceleration, steering angle and braking are more stable compared to the other algorithms, which means that the agent learns to drive in a better and more efficient way in this case. Additionally, we have come up with a dataset taken from the training of the agent with DDPG and PPO algorithms. It contains all the steps of the agent during one full training in the form: (all input values, acceleration, steering angle, break, loss, reward). This study can serve as a base for further complex road scenarios. Furthermore, it can be enlarged in the field of computer vision, using the images to find the best policy.

Keywords: autonomous driving, DDPG (deep deterministic policy gradient), PPO (proximal policy optimization), reinforcement learning

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Authors: Abdullah Alsheddy

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This paper presents the employment of Pareto optimality as a strategy to help (single-objective) local search escaping local optima. Instead of local search, Pareto local search is applied to solve the quadratic assignment problem which is multi-objectivized by adding a helper objective. The additional objective is defined as a function of the primary one with augmented penalties that are dynamically updated.

Keywords: Pareto optimization, multi-objectivization, quadratic assignment problem, local search

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

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

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

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Authors: Graziano Chesi

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The topological entropy plays a key role in linear dynamical systems, allowing one to establish the existence of stabilizing feedback controllers for linear systems in the presence of communications constraints. This paper addresses the determination of a robust value of the topological entropy in nonlinear dynamical systems, specifically the largest value of the topological entropy over all linearized models in a region of interest of the state space. It is shown that a sufficient condition for establishing upper bounds of the sought robust value of the topological entropy can be given in terms of a semidefinite program (SDP), which belongs to the class of convex optimization problems.

Keywords: non-linear system, communication constraint, topological entropy

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Authors: Jefferson S. Galanza, Jewel An Mischelle R.Camcam, Alyssa Karryl C. Co, Stephanie P. De Guzman, Jet Jet K. Dongui-is, Rodolfo Dane C. Frias, Ovelle C. Jueco, Harvey L. Matbagan, Victoria Luzette T. Rillon, Christelle Romyna H. Saruca, Jeanette Roma M. Villasper

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Background: Amidst numerous studies conducted on learning styles of students from a variety of courses, levels and school, a recent study recommended a great need for research on learning styles of student nurses. Moreover, related literatures have not been found exploring both the learning and teaching style of student nurses. Aims: The study aimed to determine the learning and teaching styles of student nurses and if there is an association between them. It also intended to discover whether student nurses are unimodal or multimodal in their styles and identified which faculty teaching style affords maximum outcome for student’s learning styles. Methods: Quantitative Descriptive-Correlational design was used. Participants were randomly selected 312 student nurses at School of Nursing X, Baguio City, Philippines. The questionnaire utilized a modified version of an adopted tool from Fleming’s VARK learning style version 7.2 (Visual, Auditory, Reader/Writer, Kinaesthetic) and Grasha’s teaching styles (Formal Authority, Demonstrator, Facilitator, Delegator). SPSS 19 was used for statistical treatment of data, where Chi square was used for the correlation of unimodal learning and teaching styles. Results/Finding: Majority of student nurses’ learning style is Kinesthetic and their teaching style is Demonstrator, which was also found to be significantly associated. Moreover, 8 out of 10 students are Unimodal in their learning and teaching modalities. In general, their preferred faculty teaching style is similar to their teaching style, which supports the concept, that teachers teach the way they learn. Conclusion: Study concludes that student nurses’ learning styles and teaching styles are varied, which exemplifies the uniqueness of every learner.This diversity in styles provided more evidence that a variety of mode of teaching and learning should be used by faculty and students to increase learning outcome and academic achievement. Recommendation: Future studies could be carried out in various schools of nursing utilizing faculty as respondents. Conduct assessment of learning style at the onset of classes/clinical placements so that faculty will become aware of the diversity of learners leading them to deliver diverse teaching methods.

Keywords: learning, learning styles, teaching styles, student nurses

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Authors: M. K. Benhaoua, A. K. Singh, A. E. H. Benyamina

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In this paper, we propose heuristic for dynamic communications mapping that considers the placement of communications in order to optimize the overall performance. The mapping technique uses a newly proposed Algorithm to place communications between the tasks. The placement we propose of the communications leads to a better optimization of several performance metrics (time and energy consumption). Experimental results show that the proposed mapping approach provides significant performance improvements when compared to those using static routing.

Keywords: Multi-Processor Systems-on-Chip (MPSoCs), Network-on-Chip (NoC), heterogeneous architectures, dynamic mapping heuristics

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Authors: Zhijie Ma, Qinglin Zhao, Hongning Dai, Huan Zhang

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This paper proposes an APPLE scheme that aims at providing absolute and proportional throughput guarantees, and maximizing system throughput simultaneously for wireless LANs with homogeneous and heterogenous traffic. We formulate our objectives as an optimization problem, present its exact and approximate solutions, and prove the existence and uniqueness of the approximate solution. Simulations validate that APPLE scheme is accurate, and the approximate solution can well achieve the desired objectives already.

Keywords: IEEE 802.11e, throughput guarantee, priority, WLANs

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Authors: M. S. Maglasang, S. O. Palacio, L. P. Ogdoc

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Business Process Outsourcing has been one of the fastest growing and emerging industry in the Philippines today. Unlike most of the contact service centers, more popularly known as "call centers", The BPO Industry’s primary outsourced service is performing audits of the global clients' logistics. As a service industry, manpower is considered as the most important yet the most expensive resource in the company. Because of this, there is a need to maximize the human resources so people are effectively and efficiently utilized. The main purpose of the study is to optimize the current manpower resources through effective distribution and assignment of different types of bills to the different skill-level of data entry operators. The assignment model parameters include the average observed time matrix gathered from through time study, which incorporates the learning curve concept. Subsequently, a simulation model was made to duplicate the arrival rate of demand which includes the different batches and types of bill per day. Next, a mathematical linear programming model was formulated. Its objective is to minimize direct labor cost per bill by allocating the different types of bills to the different skill-levels of operators. Finally, a hypothesis test was done to validate the model, comparing the actual and simulated results. The analysis of results revealed that the there’s low utilization of effective capacity because of its failure to determine the product-mix, skill-mix, and simulated demand as model parameters. Moreover, failure to consider the effects of learning curve leads to overestimation of labor needs. From 107 current number of operators, the proposed model gives a result of 79 operators. This results to an increase of utilization of effective capacity to 14.94%. It is recommended that the excess 28 operators would be reallocated to the other areas of the department. Finally, a manpower capacity planning model is also recommended in support to management’s decisions on what to do when the current capacity would reach its limit with the expected increasing demand.

Keywords: optimization modelling, linear programming, simulation, time and motion study, capacity planning

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Authors: Kourosh Modarresi

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The Netflix problem has brought the topic of “Recommendation Systems” into the mainstream of computer science, mathematics, and statistics. Though much progress has been made, the available algorithms do not obtain satisfactory results. The success of these algorithms is rarely above 5%. This work is based on the belief that the main challenge is to come up with “scalable personalization” models. This paper uses an adaptive regularization of inverse singular value decomposition (SVD) that applies adaptive penalization on the singular vectors. The results show far better matching for recommender systems when compared to the ones from the state of the art models in the industry.

Keywords: convex optimization, LASSO, regression, recommender systems, singular value decomposition, low rank approximation

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Authors: Atin Mukherjee, Amitabha Sinha, Debesh Choudhury

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Fast Fourier transform (FFT) of large-number of samples requires larger hardware resources of field programmable gate arrays and it asks for more area as well as power. In this paper, an area efficient architecture of FFT processor is proposed, that reuses the butterfly units more than once. The FFT processor is emulated and the results are validated on Virtex-6 FPGA. The proposed architecture outperforms the conventional architecture of a N-point FFT processor in terms of area which is reduced by a factor of log_N(2) with the negligible increase of processing time.

Keywords: FFT, FPGA, resource optimization, butterfly units

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Authors: Hidouri Sami, Aguili Taoufik

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We consider fast and accurate solutions of scattering problems by large perfectly conducting objects (PEC) formulated by an optimization of the Method of Auxiliary Sources (MAS). We present various techniques used to reduce the total computational cost of the scattering problem. The first technique is based on replacing the object by an array of finite number of small (PEC) object with the same shape. The second solution reduces the problem on considering only the half of the object.These two solutions are compared to results from the reference bibliography.

Keywords: method of auxiliary sources, scattering, large object, RCS, computational resources

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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: Katharina Kargel, Frederic Vobbe

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Sexualized violence against children and adolescents using digital media poses particular challenges for practitioners with a focus on crisis intervention (social work, psychotherapy, law enforcement). The technical delimitation of violence increases the burden on those affected and increases the complexity of interdisciplinary cooperation. Urgently needed recommendations for practical action do not yet exist in Germany. Funded by the Federal Ministry of Education and Research, these recommendations for action are being developed in the HUMAN project together with science and practice. The presentation introduces the participatory approach of the HUMAN project. We discuss the application-oriented, casuistic approach of the project and present its results using the example of concrete case-based recommendations for Action. The participants will be presented with concrete prototypical case studies from the project, which will be used to illustrate quality criteria for crisis intervention in cases of sexualized violence using digital media. On the basis of case analyses, focus group interviews and interviews with victims of violence, we present the six central challenges of sexualized violence with the use of digital media, namely: • Diffusion (Ambiguities regarding the extent and significance of violence) , • Transcendence (Space and time independence of the dynamics of violence, omnipresence), • omnipresent anxiety (considering diffusion and transcendence), • being haunted (repeated confrontation with digital memories of violence or the perpetrator), • disparity (conflicts of interpretative power between those affected and the social environment) • simultaneity (of all other factors). We point out generalizable principles with which these challenges can be dealt with professionally. Dealing professionally with sexualized violence using digital media requires a stronger networking of professional actors. A clear distinction must be made between their own mission and the mission of the network partners. Those affected by violence must be shown options for crisis intervention in the context of the aid networks. The different competencies and the professional mission of the offers of help are to be made transparent. The necessity of technical possibilities for deleting abuse images beyond criminal prosecution will be discussed. Those affected are stabilized by multimodal strategies such as a combination of rational emotive therapy, legal support and technical assistance.

Keywords: sexualized violence, intervention, digital media, children and youth

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Authors: Henry Lau, Dilupa Nakandala, Li Zhao

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All along the length of the supply chain, fresh food firms face the challenge of managing both product quality, due to the perishable nature of the products, and product cost. This paper develops a method to assist logistics managers upstream in the fresh food supply chain in making cost optimized decisions regarding transportation, with the objective of minimizing the total cost while maintaining the quality of food products above acceptable levels. Considering the case of multiple fresh food products collected from multiple farms being transported to a warehouse or a retailer, this study develops a total cost model that includes various costs incurred during transportation. The practical application of the model is illustrated by using several computational intelligence approaches including Genetic Algorithms (GA), Fuzzy Genetic Algorithms (FGA) as well as an improved Simulated Annealing (SA) procedure applied with a repair mechanism for efficiency benchmarking. We demonstrate the practical viability of these approaches by using a simulation study based on pertinent data and evaluate the simulation outcomes. The application of the proposed total cost model was demonstrated using three approaches of GA, FGA and SA with a repair mechanism. All three approaches are adoptable; however, based on the performance evaluation, it was evident that the FGA is more likely to produce a better performance than the other two approaches of GA and SA. This study provides a pragmatic approach for supporting logistics and supply chain practitioners in fresh food industry in making important decisions on the arrangements and procedures related to the transportation of multiple fresh food products to a warehouse from multiple farms in a cost-effective way without compromising product quality. This study extends the literature on cold supply chain management by investigating cost and quality optimization in a multi-product scenario from farms to a retailer and, minimizing cost by managing the quality above expected quality levels at delivery. The scalability of the proposed generic function enables the application to alternative situations in practice such as different storage environments and transportation conditions.

Keywords: cost optimization, food supply chain, fuzzy sets, genetic algorithms, product quality, transportation

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Authors: Amar Partap Singh Pharwaha, Shweta Rani

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To develop a reliable and cost effective communication platform for the telemedicine applications, novel antenna design has been presented using bacterial foraging optimization (BFO) technique. The proposed antenna geometry is achieved by etching a modified Koch curve fractal shape at the edges and a square shape slot at the center of the radiating element of a patch antenna. It has been found that the new antenna has achieved 43.79% size reduction and better resonating characteristic than the original patch. Representative results for both simulations and numerical validations are reported in order to assess the effectiveness of the developed methodology.

Keywords: BFO, electrical permittivity, fractals, Koch curve

Procedia PDF Downloads 489

Authors: Beloulou Mohamed Lamine, Fedili Benamar, Meliani Walid, Chaid Dalila, Lamara Abdelhak

Abstract:

Introduction: Post-surgical chronic pain (PSCP) is a pathological condition with a rather complex etiopathogenesis that extensively involves sensitization processes and neuronal damage. The neuropathic component of these pains is almost always present, with variable expression depending on the type of surgery. Objective: To assess the presumed beneficial effect of Regional Anesthesia-Analgesia Techniques (RAAT) on the development of post-surgical chronic neuropathic pain (PSCNP) in various surgical procedures. Patients and Methods: A comparative study involving 510 patients distributed across five surgical models (mastectomy, thoracotomy, hernioplasty, cholecystectomy, and major abdominal-pelvic surgery) and randomized into two groups: Group A (240) receiving conventional postoperative analgesia and Group B (270) receiving balanced analgesia, including the implementation of a Regional Anesthesia-Analgesia Technique (RAAT). These patients were longitudinally followed over a 6-month period, with postsurgical chronic neuropathic pain (PSCNP) defined by a Neuropathic Pain Score DN2≥ 3. Comparative measurements through univariate and multivariable analyses were performed to identify associations between the development of PSCNP and certain predictive factors, including the presumed preventive impact (protective effect) of RAAT. Results: At the 6th month post-surgery, 419 patients were analyzed (Group A= 196 and Group B= 223). The incidence of PSCNP was 32.2% (n=135). Among these patients with chronic pain, the prevalence of neuropathic pain was 37.8% (95% CI: [29.6; 46.5]), with n=51/135. It was significantly lower in Group B compared to Group A, with respective percentages of 31.4% vs. 48.8% (p-value = 0.035). The most significant differences were observed in breast and thoracopulmonary surgeries. In a multiple regression analysis, two predictors of PSCNP were identified: the presence of preoperative pain at the surgical site as a risk factor (OR: 3.198; 95% CI [1.326; 7.714]) and RAAT as a protective factor (OR: 0.408; 95% CI [0.173; 0.961]). Conclusion: The neuropathic component of PSCNP can be observed in different types of surgeries. Regional analgesia included in a multimodal approach to postoperative pain management has proven to be effective for acute pain and seems to have a preventive impact on the development of PSCNP and its neuropathic nature, particularly in surgeries that are more prone to chronicization.

Keywords: post-surgical chronic pain, post-surgical chronic neuropathic pain, regional anesthesia-analgesia techniques, neuropathic pain score DN2, preventive impact

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Authors: Sašo Pečnik, Borut Žalik

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This paper presents a real-time visualization technique and filtering of classified LiDAR point clouds. The visualization is capable of displaying filtered information organized in layers by the classification attribute saved within LiDAR data sets. We explain the used data structure and data management, which enables real-time presentation of layered LiDAR data. Real-time visualization is achieved with LOD optimization based on the distance from the observer without loss of quality. The filtering process is done in two steps and is entirely executed on the GPU and implemented using programmable shaders.

Keywords: filtering, graphics, level-of-details, LiDAR, real-time visualization

Procedia PDF Downloads 283