Search results for: optimization intelligence strategy

Authors: Joshna Rani S., Ahmadi Banu

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Artificial Intelligence (AI) has a significant task to carry out in the medical care contributions of things to come. As AI, it is the essential capacity behind the advancement of accuracy medication, generally consented to be a painfully required development in care. Albeit early endeavors at giving analysis and treatment proposals have demonstrated testing, we anticipate that AI will at last dominate that area too. Given the quick propels in AI for imaging examination, it appears to be likely that most radiology, what's more, pathology pictures will be inspected eventually by a machine. Discourse and text acknowledgment are now utilized for assignments like patient correspondence and catch of clinical notes, and their utilization will increment. The best test to AI in these medical services areas isn't regardless of whether the innovations will be sufficiently skilled to be valuable, but instead guaranteeing their appropriation in day by day clinical practice. For far reaching selection to happen, AI frameworks should be affirmed by controllers, coordinated with EHR frameworks, normalized to an adequate degree that comparative items work likewise, instructed to clinicians, paid for by open or private payer associations, and refreshed over the long haul in the field. These difficulties will, at last, be survived, yet they will take any longer to do as such than it will take for the actual innovations to develop. Therefore, we hope to see restricted utilization of AI in clinical practice inside 5 years and more broad use inside 10 years. It likewise appears to be progressively evident that AI frameworks won't supplant human clinicians for a huge scope, yet rather will increase their endeavors to really focus on patients. Over the long haul, human clinicians may advance toward errands and work plans that draw on remarkably human abilities like sympathy, influence, and higher perspective mix. Maybe the lone medical services suppliers who will chance their professions over the long run might be the individuals who will not work close by AI

Keywords: artificial intellogence, health care, breast cancer, AI applications

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Authors: Hoora Beheshti Haradasht, Abooali Golzary

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Environmental education plays a pivotal role in shaping the future stewards of our planet. Leveraging the power of artificial intelligence (AI) in this endeavor presents an innovative approach to captivate and educate elementary school children about environmental sustainability. This paper explores the application of AI technologies in designing interactive and personalized learning experiences that foster curiosity, critical thinking, and a deep connection to nature. By harnessing AI-driven tools, virtual simulations, and personalized content delivery, educators can create engaging platforms that empower children to comprehend complex environmental concepts while nurturing a lifelong commitment to protecting the Earth. With the pressing challenges of climate change and biodiversity loss, cultivating an environmentally conscious generation is imperative. Integrating AI in environmental education revolutionizes traditional teaching methods by tailoring content, adapting to individual learning styles, and immersing students in interactive scenarios. This paper delves into the potential of AI technologies to enhance engagement, comprehension, and pro-environmental behaviors among elementary school children. Modern AI technologies, including natural language processing, machine learning, and virtual reality, offer unique tools to craft immersive learning experiences. Adaptive platforms can analyze individual learning patterns and preferences, enabling real-time adjustments in content delivery. Virtual simulations, powered by AI, transport students into dynamic ecosystems, fostering experiential learning that goes beyond textbooks. AI-driven educational platforms provide tailored content, ensuring that environmental lessons resonate with each child's interests and cognitive level. By recognizing patterns in students' interactions, AI algorithms curate customized learning pathways, enhancing comprehension and knowledge retention. Utilizing AI, educators can develop virtual field trips and interactive nature explorations. Children can navigate virtual ecosystems, analyze real-time data, and make informed decisions, cultivating an understanding of the delicate balance between human actions and the environment. While AI offers promising educational opportunities, ethical concerns must be addressed. Safeguarding children's data privacy, ensuring content accuracy, and avoiding biases in AI algorithms are paramount to building a trustworthy learning environment. By merging AI with environmental education, educators can empower children not only with knowledge but also with the tools to become advocates for sustainable practices. As children engage in AI-enhanced learning, they develop a sense of agency and responsibility to address environmental challenges. The application of artificial intelligence in elementary environmental education presents a groundbreaking avenue to cultivate environmentally conscious citizens. By embracing AI-driven tools, educators can create transformative learning experiences that empower children to grasp intricate ecological concepts, forge an intimate connection with nature, and develop a strong commitment to safeguarding our planet for generations to come.

Keywords: artificial intelligence, environmental education, elementary children, personalized learning, sustainability

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Authors: Nicolae Bold, Daniel Nijloveanu

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The idea of cropping-system is a method used by farmers. It is an environmentally-friendly method, protecting the natural resources (soil, water, air, nutritive substances) and increase the production at the same time, taking into account some crop particularities. The combination of this powerful method with the concepts of genetic algorithms results into a possibility of generating sequences of crops in order to form a rotation. The usage of this type of algorithms has been efficient in solving problems related to optimization and their polynomial complexity allows them to be used at solving more difficult and various problems. In our case, the optimization consists in finding the most profitable rotation of cultures. One of the expected results is to optimize the usage of the resources, in order to minimize the costs and maximize the profit. In order to achieve these goals, a genetic algorithm was designed. This algorithm ensures the finding of several optimized solutions of cropping-systems possibilities which have the highest profit and, thus, which minimize the costs. The algorithm uses genetic-based methods (mutation, crossover) and structures (genes, chromosomes). A cropping-system possibility will be considered a chromosome and a crop within the rotation is a gene within a chromosome. Results about the efficiency of this method will be presented in a special section. The implementation of this method would bring benefits into the activity of the farmers by giving them hints and helping them to use the resources efficiently.

Keywords: chromosomes, cropping, genetic algorithm, genes

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Authors: Wang Yichen, Haruka Yamashita

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In recent years, in the field of sports, decision making such as member in the game and strategy of the game based on then analysis of the accumulated sports data are widely attempted. In fact, in the NBA basketball league where the world's highest level players gather, to win the games, teams analyze the data using various statistical techniques. However, it is difficult to analyze the game data for each play such as the ball tracking or motion of the players in the game, because the situation of the game changes rapidly, and the structure of the data should be complicated. Therefore, it is considered that the analysis method for real time game play data is proposed. In this research, we propose an analytical model for "determining the optimal lineup composition" using the real time play data, which is considered to be difficult for all coaches. In this study, because replacing the entire lineup is too complicated, and the actual question for the replacement of players is "whether or not the lineup should be changed", and “whether or not Small Ball lineup is adopted”. Therefore, we propose an analytical model for the optimal player selection problem based on Small Ball lineups. In basketball, we can accumulate scoring data for each play, which indicates a player's contribution to the game, and the scoring data can be considered as a time series data. In order to compare the importance of players in different situations and lineups, we combine RNN (Recurrent Neural Network) model, which can analyze time series data, and NN (Neural Network) model, which can analyze the situation on the field, to build the prediction model of score. This model is capable to identify the current optimal lineup for different situations. In this research, we collected all the data of accumulated data of NBA from 2019-2020. Then we apply the method to the actual basketball play data to verify the reliability of the proposed model.

Keywords: recurrent neural network, players lineup, basketball data, decision making model

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Authors: Marcel Heimar Ribeiro Utiyama, Fernanda Caveiro Correia, Dario Henrique Alliprandini

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The importance of the correct allocation of improvement programs is of growing interest in recent years. Due to their limited resources, companies must ensure that their financial resources are directed to the correct workstations in order to be the most effective and survive facing the strong competition. However, to our best knowledge, the literature about allocation of improvement programs does not analyze in depth this problem when the flow shop process has two capacity constrained resources. This is a research gap which is deeply studied in this work. The purpose of this work is to identify the best strategy to allocate improvement programs in a flow shop with two capacity constrained resources. Data were collected from a flow shop process with seven workstations in an industrial control and automation company, which process 13.690 units on average per month. The data were used to conduct a simulation with the System Dynamics-Factory Physics model. The main variables considered, due to their importance on lead time reduction, were the mean time between failures and the mean time to repair. The lead time reduction was the output measure of the simulations. Ten different strategies were created: (i) focused time to repair improvement, (ii) focused time between failures improvement, (iii) distributed time to repair improvement, (iv) distributed time between failures improvement, (v) focused time to repair and time between failures improvement, (vi) distributed time to repair and between failures improvement, (vii) hybrid time to repair improvement, (viii) hybrid time between failures improvements, (ix) time to repair improvement strategy towards the two capacity constrained resources, (x) time between failures improvement strategy towards the two capacity constrained resources. The ten strategies tested are variations of the three main strategies for improvement programs named focused, distributed and hybrid. Several comparisons among the effect of the ten strategies in lead time reduction were performed. The results indicated that for the flow shop analyzed, the focused strategies delivered the best results. When it is not possible to perform a large investment on the capacity constrained resources, companies should use hybrid approaches. An important contribution to the academy is the hybrid approach, which proposes a new way to direct the efforts of improvements. In addition, the study in a flow shop with two strong capacity constrained resources (more than 95% of utilization) is an important contribution to the literature. Another important contribution is the problem of allocation with two CCRs and the possibility of having floating capacity constrained resources. The results provided the best improvement strategies considering the different strategies of allocation of improvement programs and different positions of the capacity constrained resources. Finally, it is possible to state that both strategies, hybrid time to repair improvement and hybrid time between failures improvement, delivered best results compared to the respective distributed strategies. The main limitations of this study are mainly regarding the flow shop analyzed. Future work can further investigate different flow shop configurations like a varying number of workstations, different number of products or even different positions of the two capacity constrained resources.

Keywords: allocation of improvement programs, capacity constrained resource, hybrid strategy, lead time, mean time to repair, mean time between failures

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Authors: Noreen Sajjad Ghulam Hussain

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Catalysts are prepared by simple physical mixing and thermal treatment of support and metal acetate precursors.The effect of metal ratio and metal loading to produce highly active catalyst for the oxidation of benzyl alcohol are studied.

Keywords: catalyst, acetates, benzyl alcohols

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Rabiatu Bonku, Faisal Alkaabneh

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Inspired by a food banks distribution operation for non-profit organization, we study a variant synchronized vehicle routing problem for equitable resource allocation. This research paper introduces a Mixed Integer Programming (MIP) model aimed at addressing the complex challenge of efficiently distributing vital resources, particularly for food banks serving vulnerable populations in urban areas. Our optimization approach places a strong emphasis on social equity, ensuring a fair allocation of food to partner agencies while minimizing wastage. The primary objective is to enhance operational efficiency while guaranteeing fair distribution and timely deliveries to prevent food spoilage. Furthermore, we assess four distinct models that consider various aspects of sustainability, including social and economic factors. We conduct a comprehensive numerical analysis using real-world data to gain insights into the trade-offs that arise, while also demonstrating the models’ performance in terms of fairness, effectiveness, and the percentage of food waste. This provides valuable managerial insights for food bank managers. We show that our proposed approach makes a significant contribution to the field of logistics optimization and social responsibility, offering valuable insights for improving the operations of food banks.

Keywords: food banks, humanitarian logistics, equitable resource allocation, synchronized vehicle routing

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Authors: Phichak Phutrakhul

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The purposes of this research were to study concepts and strategies of human resource development in the automotive manufacturers and to articulate the proposals against the government about the human resource development for automotive industry. In the present study, qualitative study was an in-depth interview in which the qualitative data were collected from the executive or the executive of human resource division from five automotive companies - Toyota Motor (Thailand) Co., Ltd., Nissan Motor (Thailand) Co., Ltd., Mitsubishi Motors (Thailand) Co., Ltd., Honda Automobile (Thailand) Co., Ltd., and Suzuki Motor (Thailand) Co., Ltd. Qualitative data analysis was performed by using inter-coder agreement technique. The research findings were as follows: The external factors included the current conditions of the automotive industry, government’s policy related to the automotive industry, technology, labor market and human resource development systems of the country. The internal factors included management, productive management, organizational strategies, leadership, organizational culture and philosophy of human resource development. These factors were affected to the different concept of human resources development -the traditional human resource development and the strategies of human resource development. The organization focuses on human resources as intellectual capital and uses the strategies of human resource development in all development processes. The strategies of human resource development will enhance the ability of human resources in the organization and the country.

Keywords: human resource development strategy, automotive industry, eco-cars, ASEAN

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Authors: Saeed Farivar, Mohsen Kahrom

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The purpose of this work is to develop a physical simulation model for the purpose of studying the effect of various design parameters on the performance of packaged-liquid chillers. This paper presents a steady-state model for predicting the performance of package-Liquid chiller over a wide range of operation condition. The model inputs are inlet conditions; geometry and output of model include system performance variable such as power consumption, coefficient of performance (COP) and states of refrigerant through the refrigeration cycle. A computer model that simulates the steady-state cyclic performance of a vapor compression chiller is developed for the purpose of performing detailed physical design analysis of actual industrial chillers. The model can be used for optimizing design and for detailed energy efficiency analysis of packaged liquid chillers. The simulation model takes into account presence of all chiller components such as compressor, shell-and-tube condenser and evaporator heat exchangers, thermostatic expansion valve and connection pipes and tubing’s by thermo-hydraulic modeling of heat transfer, fluids flow and thermodynamics processes in each one of the mentioned components. To verify the validity of the developed model, a 7.5 USRT packaged-liquid chiller is used and a laboratory test stand for bringing the chiller to its standard steady-state performance condition is build. Experimental results obtained from testing the chiller in various load and temperature conditions is shown to be in good agreement with those obtained from simulating the performance of the chiller using the computer prediction model. An entropy-minimization-based optimization analysis is performed based on the developed analytical performance model of the chiller. The variation of design parameters in construction of shell-and-tube condenser and evaporator heat exchangers are studied using the developed performance and optimization analysis and simulation model and a best-match condition between the physical design and construction of chiller heat exchangers and its compressor is found to exist. It is expected that manufacturers of chillers and research organizations interested in developing energy-efficient design and analysis of compression chillers can take advantage of the presented study and its results.

Keywords: optimization, packaged liquid chiller, performance, simulation

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Authors: Srinivas Vangari

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In the era of big data, ensuring the accuracy, consistency, and reliability of critical data assets is crucial for data-driven enterprises. Master Data Management (MDM) plays a crucial role in this endeavor. This paper investigates the role of Artificial Intelligence (AI) in enhancing MDM, focusing on how AI-driven solutions can automate and optimize various stages of the master data lifecycle. By integrating AI (Quantitative and Qualitative Analysis) into processes such as data creation, maintenance, enrichment, and usage, organizations can achieve significant improvements in data quality and operational efficiency. Quantitative analysis is employed to measure the impact of AI on key metrics, including data accuracy, processing speed, and error reduction. For instance, our study demonstrates an 18% improvement in data accuracy and a 75% reduction in duplicate records across multiple systems post-AI implementation. Furthermore, AI’s predictive maintenance capabilities reduced data obsolescence by 22%, as indicated by statistical analyses of data usage patterns over a 12-month period. Complementing this, a qualitative analysis delves into the specific AI-driven strategies that enhance MDM practices, such as automating data entry and validation, which resulted in a 28% decrease in manual errors. Insights from case studies highlight how AI-driven data cleansing processes reduced inconsistencies by 25% and how AI-powered enrichment strategies improved data relevance by 24%, thus boosting decision-making accuracy. The findings demonstrate that AI significantly enhances data quality and integrity, leading to improved enterprise performance through cost reduction, increased compliance, and more accurate, real-time decision-making. These insights underscore the value of AI as a critical tool in modern data management strategies, offering a competitive edge to organizations that leverage its capabilities.

Keywords: artificial intelligence, master data management, data governance, data quality

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Authors: Fuyuan Ma, Ying Wang, Xin Wang

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Social networks have become breeding grounds for the rapid spread of rumors and malicious information, posing threats to societal stability and causing significant public harm. Existing research focuses on simulating the spread of information and its impact on users through propagation dynamics and applies methods such as greedy approximation strategies to approximate the optimal control solution at the global scale. However, the greedy strategy at the global scale may fall into locally optimal solutions, and the approximate simulation of information spread may accumulate more errors. Therefore, we propose a multi-scale control model for network group behavior, introducing individual and group scales on top of the greedy strategy’s global scale. At the individual scale, we calculate the propagation influence of nodes based on their structural attributes to alleviate the issue of local optimality. At the group scale, we conduct precise propagation simulations to avoid introducing cumulative errors from approximate calculations without increasing computational costs. Experimental results on three real-world datasets demonstrate the effectiveness of our proposed multi-scale model in controlling network group behavior.

Keywords: influence blocking maximization, competitive linear threshold model, social networks, network group behavior

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Authors: Leila H. Khiabani, Mohammadreza Vafaee, Farshad Hashemzadeh

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Industrial waste management regulates different stages of production, storage, transfer, recycling and waste disposal. There are several common practices for industrial waste management. However, due to various local health, economic, social, environmental and aesthetic considerations, the most optimal principles and measures often vary at each specific industrial zone. In addition, waste management strategies are heavily impacted by local administrative, legal, and financial regulations. In this study, a hybrid qualitative and quantitative research methodology has been designed for waste management planning in an industrial city. Firstly, following a qualitative research methodology, the most relevant waste management strategies for the specific industrial city were identified through interviews with environmental planning and waste management experts. Forty experts participated in this study. Alborz industrial city in Iran, which hosts more than one thousand industrial units in nine hundred acres, was chosen as the sample industrial city in this study. The findings from the expert interviews at the first phase were then used to design a quantitative questionnaire for the second phase of the study. The aim of the questionnaire was to quantify the relative impact of different waste management strategies in the sample industrial city. Eight waste management strategies and three implementation policies were included in the questionnaire. The experts were asked to rank the relative effectiveness of each strategy for environmental planning of the sample industrial city. They were also asked to rank the relative effectiveness of each planning policy on each of the waste management strategies. In the end, the weighted average of all the responses was calculated to identify the most effective waste management strategy and planning policies for the sample industrial city. The results suggested that among the eight suggested waste management strategies, industrial composting is the most effective (31%) strategy based on the collective evaluation of the local expert. Additionally, the results suggested that the most effective policy (58%) in the city’s environmental planning is to reduce waste generation by prolonging the effective life of industrial products using higher quality and recyclable materials. These findings can provide useful expert guidelines for prioritization between different waste management strategies in the city’s overall environmental planning roadmap. The findings may also be applicable to similar industrial cities. In addition, a similar methodology can be utilized in the environmental planning of other industrial cities.

Keywords: environmental planning, industrial city, quantitative research, waste management

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Authors: Shola Haruna Adeosun, Ajoke F. Adebiyi

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Business organizations in Nigeria have failed to realize the role of a good corporate image policy in business dealings. This is probably because they do not understand the concept of corporate image and the necessary tools for promoting it. Corporate image goes beyond attractive products or rendering quality services, advertising and paying good salary. It pervades every aspect of business concern, from the least worker’s personality to the dealings within the organization and with the large society. In the face of the societal dynamics, especially in the business world, brought by technology, companies are faced with stiff competition that maintaining a competitive edge requires aggressive strategies. One of such strategies in effective corporate image management is promotion. This study investigates the strategies that could be deployed in order to build and promote the effective corporate image, as well as enhance profit margins of an organization, using Phinomar Nigeria Limited, Ngwo as case study. The study reveals that Phinomar Nigeria Limited has a laid down corporate image policy but not effectively managed; and that, strategies deployed to promote corporate image are limited; while responses to Phinomar products are fairly high. It, therefore, suggests profitable products but requires periodical improvement in the employee's welfare and work environment; as well as, the need to increase the scope of Phinomar’s social responsibility.

Keywords: corporate image, effective, enhancing, management, profitability, strategy

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Authors: Tomer Gans-Or, Shmulik Pinkert

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The determination of lateral pile capacity per unit length is a key aspect in geotechnical engineering. Traditional approaches for assessing piles lateral capacity in cohesive soils involve the application of upper-bound and lower-bound plasticity theorems. However, a comprehensive solution encompassing the entire spectrum of soil strength parameters, particularly in frictional soils with or without cohesion, is still lacking. This research introduces an innovative implementation of the slice method limit equilibrium solution for lateral capacity assessment. For any given numerical discretization of the soil's domain around the pile, the lateral capacity evaluation is based on mobilized strength concept. The critical failure geometry is then found by a unique optimization procedure which includes both factor of safety minimization and geometrical optimization. The robustness of this suggested methodology is that the solution is independent of any predefined assumptions. Validation of the solution is accomplished through a comparison with established plasticity solutions for cohesive soils. Furthermore, the study demonstrates the applicability of the limit equilibrium method to address unresolved cases related to frictional and cohesive-frictional soils. Beyond providing capacity values, the method enables the utilization of the mobilized strength concept to generate safety-factor distributions for scenarios representing pre-failure states.

Keywords: lateral pile capacity, slice method, limit equilibrium, mobilized strength

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Authors: Alaa Yehia, Ayatollah Yehia, Sherif Yehia

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There is a recurring issue of low enrollments across many civil engineering departments in postsecondary institutions. While there have been moments where enrollments begin to increase, civil engineering departments find themselves facing low enrollments at around 60% over the last five years across the Middle East. There are many reasons that could be attributed to this decline, such as low entry-level salaries, over-saturation of civil engineering graduates in the job market, and a lack of construction projects due to the impending or current recession. However, this recurring problem alludes to an intrinsic issue of the curriculum. The societal shift to the usage of high technology such as machine learning (ML) and artificial intelligence (AI) demands individuals who are proficient at utilizing it. Therefore, existing curriculums must adapt to this change in order to provide an education that is suitable for potential and current students. In this paper, In order to provide potential solutions for this issue, the analysis considers two possible implementations of high technology into the civil engineering curriculum. The first approach is to implement a course that introduces applications of high technology in Civil Engineering contexts. While the other approach is to intertwine applications of high technology throughout the degree. Both approaches, however, should meet requirements of accreditation agencies. In addition to the proposed improvement in civil engineering curriculum, a different pedagogical practice must be adapted as well. The passive learning approach might not be appropriate for Gen Z students; current students, now more than ever, need to be introduced to engineering topics and practice following different learning methods to ensure they will have the necessary skills for the job market. Different learning methods that incorporate high technology applications, like AI, must be integrated throughout the curriculum to make the civil engineering degree more attractive to prospective students. Moreover, the paper provides insight on the importance and approach of adapting the Civil Engineering curriculum to address the current low enrollment crisis that civil engineering departments globally, but specifically in the Middle East, are facing.

Keywords: artificial intelligence (AI), civil engineering curriculum, high technology, low enrollment, pedagogy

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Authors: A. J. Otjen

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Native American communities are struggling with unemployment and depressed economies. A major cause is a lack of business knowledge, education, and cultural desire. And yet, in the history of the American West, Native Americans were considered the best traders and negotiators for everything from furs to weapons to buffalo. To improve these economies, there has been an effort to reintroduce that heritage to todays and tomorrows generation of tribal members, such Crow, Cheyenne, and Blackfeet. Professors at the College of Business Montana State University-Billings (MSUB) teach tribal students in Montana to create business plans. These plans have won national small business plan competitions. The teaching and advising method used at MSUB is uniquely successful as theses business students are now five time national champions. This article reviews the environment and the method of learning to achieve a winning small business plan with Native American students. It discusses the five plans that became national champions. And it discusses the problems and solutions discovered in the process of achieving results. Students who participated in this endeavor have graduated and become CPAs, MBAs, and gainfully employed in their chosen professions. They have also worked to improve the economies of their native lands and homes. By educating members of these communities with business strategy and plan development, they are better able to impact their own economies.

Keywords: entrepreneurship, native American economies, small businesses, unemployment

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Authors: Shiva Kumar G.

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The present study is to know the level of noises emanated from vehicles in intersections located in urban areas using Sound Level Meter and the possibility of reducing noise levels through traffic flow optimization. The main objective is to study traffic noise level of the Intersections located at on-going metro construction activities and which are away from metro construction activities. To compare traffic noise level between stop phase, go phase and drive phase at the Intersections. To study the effect of traffic noise level of directional movement of traffic and variation in noise level during day and night times. The range of Noise level observed at intersections is between 60 to 105 decibel. The noise level of stop and drive phases were minimum and almost same where go phase had maximum noise level. By comparing noise level of directional movement of traffic, it has been noticed that Vijayanagar intersection has no significant difference in their noise level and all other intersection has a significant difference in their noise level. By comparing noise level of stop, go and drive phase it has been noticed that there was a significant difference in noise level during peak hours compared to off-peak hour. By comparing noise level between Metro and Non-Metro construction activity intersections it has been noticed that there was a significant difference in noise level. By comparing noise level during day and night times, significant differences in noise level were observed at all intersections.

Keywords: noise, metro and non-metro intersections, traffic flow optimization, stop-go and drive phase

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Authors: Gia Sirbiladze

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Route planning problems are among the activities that have the highest impact on logistical planning, transportation, and distribution because of their effects on efficiency in resource management, service levels, and client satisfaction. In extreme conditions, the difficulty of vehicle movement between different customers causes the imprecision of time of movement and the uncertainty of the feasibility of movement. A feasibility level of vehicle movement on the closed route of the disaster-streaking zone is defined for the construction of an objective function. Experts’ evaluations of the uncertain parameters in q-rung ortho-pair fuzzy numbers (q-ROFNs) are presented. A fuzzy bi-objective combinatorial optimization problem of fuzzy vehicle routine problem (FVRP) is constructed based on the technique of possibility theory. The FVRP is reduced to the bi-criteria partitioning problem for the so-called “promising” routes which were selected from the all-admissible closed routes. The convenient selection of the “promising” routes allows us to solve the reduced problem in real-time computing. For the numerical solution of the bi-criteria partitioning problem, the -constraint approach is used. The main results' support software is designed. The constructed model is illustrated with a numerical example.

Keywords: q-rung ortho-pair fuzzy sets, facility location selection problem, multi-objective combinatorial optimization problem, partitioning problem

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Authors: Tripta Dixit, Smita Sahu, William Selvamurthy, Sadhana Srivastava

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India is battling with the issues of accessibility, affordability and availability of quality health to the masses. Indian medical heritage which dated back to 3000 BC unveils the rich knowledge pool which has undergone a perceptible change over years, such as eradication of many communicable diseases, increasing individual awareness of quality health and import driven medical device market etc. Despite a slew of initiatives the holistic slogan of ‘health for all’ remains elusive and a concern for the nation. The 21st-century projects a myriad of challenges like cultural diversity, large population, demographic dividend and geographical segmentation leading to varied needs of people as per their regional conditions of climate, disease prevalence, nutrition and sanitation. But these challenges are also opportunities for the development of indigenous, low cost and accessible technologies to tackle them. This requires reinforcing the potential of indigenous technologies in coordination with prevailing health issues in various regions of country. This paper emphasis on the strategy for exploring the indigenous technologies with entrusted up-scaling to meet the diverse needs of the people. This review proposes to adopt technology transfer as a strategy to establish a vibrant ecosystem for identifying and up-scaling the indigenous medical technologies with diligent hand-holding for public health.

Keywords: health, indigenous, medical technology, technology transfer

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Authors: Priyakant Vaghela, Jagdish Prajapati

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Bending stress at the root of the gear tooth is the very important criteria in gear design and it should be kept the minimum. Minimization of bending stress at the root of the gear tooth is a recent demand from industry. This paper presents an innovative approach to obtain minimum bending stress at the root of a tooth by optimizing tooth root profile and drive side pressure angle. Circular-filleted at the root of the tooth is widely used in the design. Circular fillet creates discontinuity at the root of the tooth. So, at root stress concentration occurs. In order to minimize stress concentration, an important criterion is a G2 continuity at the blending of the gear tooth. A Bezier curve is used with G2 continuity at the root of asymmetric spur gear tooth. The comparison has been done between normal and modified tooth using ANSYS simulation. Tooth root profile and drive side pressure angle are optimized to minimize bending stress at the root of the tooth of the asymmetric involute spur gear. Von Mises stress of optimized profile is analyzed and compared with normal profile symmetric gear. Von Mises stress is reducing by 31.27% by optimization of drive side pressure angle and root profile. Stress concentration of modified gear was significantly reduced.

Keywords: asymmetric spur gear tooth, G2 continuity, pressure angle, stress concentration at the root of tooth, tooth root stress

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Authors: Aasheesh Raturi, Vimal Kothiyal, P. D. Semalty

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We studied mechanical properties of Eucalyptus tereticornis using FT-NIR spectroscopy. Firstly, spectra were pre-processed to eliminate useless information. Then, prediction model was constructed by partial least squares regression. To study the influence of pre-processing on prediction of mechanical properties for NIR analysis of wood samples, we applied various pretreatment methods like straight line subtraction, constant offset elimination, vector-normalization, min-max normalization, multiple scattering. Correction, first derivative, second derivatives and their combination with other treatment such as First derivative + straight line subtraction, First derivative+ vector normalization and First derivative+ multiplicative scattering correction. The data processing methods in combination of preprocessing with different NIR regions, RMSECV, RMSEP and optimum factors/rank were obtained by optimization process of model development. More than 350 combinations were obtained during optimization process. More than one pre-processing method gave good calibration/cross-validation and prediction/test models, but only the best calibration/cross-validation and prediction/test models are reported here. The results show that one can safely use NIR region between 4000 to 7500 cm-1 with straight line subtraction, constant offset elimination, first derivative and second derivative preprocessing method which were found to be most appropriate for models development.

Keywords: FT-NIR, mechanical properties, pre-processing, PLS

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Authors: Louay Safi

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The notion of secular society that evolved over the last two centuries was initially intended to free the public sphere from religious imposition, before it assumed the form a comprehensive ideology whose aim is to prevent any overt religious expression from the public space. The negative view of religious expression, and the desire by political elites to purge the public space from all forms of religious expressions were first experienced in the Middle East in the last decades of the twentieth century in relation to Islam, before it manifests itself in the twentieth century Europe. Arab regimes were encouraged by European democracies to marginalize all forms of religious expressions in the public as part of the secularization process that was deemed necessary for modernization and progress. The prohibition of Islamic symbols and outlawing the headscarf was first undertaken to Middle Eastern republics, such as Turkey in 1930s and Syria in 1970s, before it is implemented recently in France. Secularization has been perceived by European powers as the central aspect of social and political liberalization, and was given priority over democratization and human rights, so much so that European elites were willing to entrust the task of nurturing liberal democracy to Arab autocrats and dictators. Not only did the strategy of empowering autocratic regimes to effect liberal democratic culture failed, but it contributed to the rise of Islamist extremism and produced failed states in Syria and Iraq that undermine both national and global peace and stability. The paper adopts the distinction made by John Rawls between political and comprehensive liberalism to argue that the modernization via secularization in Muslim societies is counterproductive and has subverted early successful efforts at democratization and reform in the Middle East. Using case studies that illustrate the role of the secularization strategy in Syria, Iran, and Egypt in undermining democratic and reformist movements in those countries, the paper calls for adopting a different approach rooted in liberal and democratic values rather than cultural practices and lifestyle. The paper shows that Islamic values as articulated by reform movements support a democratic and pluralist political order, and emphasizes the need to legitimize and support social forces that advocate democracy and human rights. Such an alternative strategy allows for internal competition among social groups for popular support, and therefore enhances the chances that those with inclusive and forward-looking political principles and policies would create a democratic and pluralist political order more conducive to meaningful national and global cooperation, and respectful of human dignity.

Keywords: democracy, Islamic values, political liberalism, secularization

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Authors: Amer Rghei

Abstract:

The Sahara region potentially is one of the most attractive heritage areas in the world. Yet presently, the heritage of the Sahara is currently facing serious planning challenges of underdeveloped and neglected economic and physical potentials. Deterioration of heritage resources has been observed by the author during his several field tours for historic sites has discovered special heritage values such as in Ghadames which combines historic oasis, natural environment along with its exceptional urban fabric and architectural character. Despite the richness of Ghadames with historic significance, it is found that at the present time, Ghadames city, the UNESCO World Heritage site, is facing serious challenges including the abandonment by its tenants and inclusive negligence by its officials. The author believes that Ghadames can illustrate an excellent heritage example in North Africa with cultural pride and socio-economic opportunities that can contribute to overall economic development in the Sahara region. However, the paper deals with the case of Ghadames ‘The World Heritage Site’ in Libya and discusses the current challenges and possible planning for its heritage conservation strategy. The momentous resources in Ghadames with their historical, environmental, economic, social, cultural, and aesthetic values would benefit from a careful heritage planning and management program for its significant values. In this paper an attempt is made to investigate this issue seriously towards building a model of a strategy for heritage conservation planning for Ghadames is proposed.

Keywords: Ghadames, Oasis architecture, Sahara region, heritage environment

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Authors: Josif Figueroa, Kush Bubbar, Greg Young-Morris

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The reliability evaluation of composite generation and bulk transmission systems is crucial for ensuring a reliable supply of electrical energy to significant system load points. However, evaluating adequacy indices using probabilistic methods like sequential Monte Carlo Simulation can be computationally expensive. Despite this, it is necessary when time-varying and interdependent resources, such as renewables and energy storage systems, are involved. Recent advances in solving power network optimization problems and parallel computing have improved runtime performance while maintaining solution accuracy. This work introduces CompositeSystems, an open-source Composite System Reliability Evaluation tool developed in Julia™, to address the current deficiencies of commercial and non-commercial tools. This work introduces its design, validation, and effectiveness, which includes analyzing two different formulations of the Optimal Power Flow problem. The simulations demonstrate excellent agreement with existing published studies while improving replicability and reproducibility. Overall, the proposed tool can provide valuable insights into the performance of transmission systems, making it an important addition to the existing toolbox for power system planning.

Keywords: open-source software, composite system reliability, optimization methods, Monte Carlo methods, optimal power flow

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Authors: Ouahiba Taamallah, Tarek Litim

Abstract:

The study deals with the burnishing effect of AISI 52100 steel and parameters influence (Py, i and f on surface integrity. The results show that the optimal effects are closely related to the treatment parameters. With a 92% improvement in roughness, SB can be defined as a finishing operation within the machining range. Due to 85% gain in consolidation rate, this treatment constitutes an efficient process for work-hardening of material. In addition, a statistical study based on regression and Taguchi's design has made it possible to develop mathematical models to predict output responses according to the studied burnishing parameters. Response Surface Methodology RSM showed a simultaneous influence of the burnishing parameters and to observe the optimal parameters of the treatment. ANOVA Analysis of results led to validate the prediction model with a determination coefficient R2=94.60% and R2=93.41% for surface roughness and micro-hardness, respectively. Furthermore, a multi-objective optimization allowed to identify a regime characterized by P=20 Kgf, i=5 passes and f=0.08 mm.rev-1, which favors minimum surface roughness and a maximum of micro-hardness. The result was validated by a composite desirability D_i=1 for both surface roughness and microhardness, respectively. Applying optimal parameters, burnishing showed its beneficial effects in fatigue resistance, especially for imposed loading in the low cycle fatigue of the material where the lifespan increased by 90%.

Keywords: AISI 52100 steel, burnishing, Taguchi, fatigue

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Authors: Qing Zhang, Jiachen Nie, Yujia Wen, Guanyuan Kou, Peng Yu, Kun Xia, Qin Yang, Li Ding

Abstract:

BACKGROUND: A facility layout problem (FLP) is an NP-complete (non-deterministic polynomial) problem, which is hard to obtain an exact optimal solution. FLP has been widely studied in various limited spaces and workflows. For example, cafeterias with many types of equipment for troops cause chaotic processes when dining. OBJECTIVE: This article tried to optimize the layout of troops’ cafeteria and to improve the overall efficiency of the dining process. METHODS: First, the original cafeteria layout design scheme was analyzed from an ergonomic perspective and two new design schemes were generated. Next, three facility layout models were designed, and further simulation was applied to compare the total time and density of troops between each scheme. Last, an experiment of the dining process with video observation and analysis verified the simulation results. RESULTS: In a simulation, the dining time under the second new layout is shortened by 2.25% and 1.89% (p<0.0001, p=0.0001) compared with the other two layouts, while troops-flow density and interference both greatly reduced in the two new layouts. In the experiment, process completing time and the number of interference reduced as well, which verified corresponding simulation results. CONCLUSIONS: Our two new layout schemes are tested to be optimal by a series of simulation and space experiments. In future research, similar approaches could be applied when taking layout-design algorithm calculation into consideration.

Keywords: layout optimization, dining efficiency, troops’ cafeteria, anylogic simulation, field experiment

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Authors: Tingke Wu, Man Yuan

Abstract:

“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: driving forces, Hubei, optimizing strategies, spatial pattern, territory

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Authors: Shanshan Guo, Xiaoying Zhu, Dominik Jańczewski, Koon Gee Neoh

Abstract:

Surface charge and wettability are two prominent physical factors governing cell adhesion and have been extensively studied in the literature. However, a comparison between the two driving forces in terms of their independent and cooperative effects in affecting cell adhesion is rarely explored on a systematic and quantitative level. Herein, we formulate a protocol which allows two-dimensional and independent control over both surface charge and wettability. This protocol enables the unambiguous comparison of the effects of these two properties on cell adhesion. This strategy is implemented by controlling both the relative thickness of polyion layers in the layer-by-layer assembly and the polyion side chain chemical structures. The 2D property matrix spans surface isoelectric point ranging from 5 to 9 and water contact angle from 35º to 70º, with other interferential factors (e.g. roughness) eliminated. The interplay between these two surface variables influences 3T3 fibroblast cell adhesion. The results show that both surface charge and wettability have an effect on its adhesion. The combined effects of positive charge and hydrophilicity led to the highest cell adhesion whereas negative charge and hydrophobicity led to the lowest cell adhesion. Our design strategy can potentially form the basis for studying the distinct behaviors of electrostatic force or wettability driven interfacial phenomena and serving as a reference in future studies assessing cell adhesion to surfaces with known charge and wettability within the property range studied here.

Keywords: cell adhesion, layer-by-layer, surface charge, surface wettability

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Authors: Sisi Xia, Dezhuan Tao

Abstract:

Urban Double Reform is an effective means to improve the quality of ecological space, based on improving the living environment and urban functions and promoting the organic integration of the city and nature. This paper takes the design of Qinyang Wetland Park in Jiaozuo, Henan Province, as an example, attempting to closely link the ecological restoration of wetland with the urban culture and to extend the urban spirit of the ancient county of Qinyang while purifying the ecological water system. This design uses ecological technology to repair underwater forests and underwater turf, rapidly improving the quality of urban water without biological side effects. The ecological grass slope is used to create multiple bank forms, combining with a number of hydrophilic platforms to provide a good view of the public. Through the placement of ecological education bases, urban cultural exhibition halls, and other means, the cultural value of wetland parks will be enhanced, and the citizens will return to nature and experience the ecology and appreciate the charm of urban culture in the ecological space. Repair the ecosystem, sculpt the urban culture, let the public return to nature, experience the ecology, and experience the charm of urban culture in the ecological space.

Keywords: urban double reform, ecological space, improvement strategy, wetland park design

Procedia PDF Downloads 238