Search results for: random routing optimization technique

Authors: Ghizlane Barzi, Zineb Bamousse

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In an increasingly volatile global economic context characterized by recurring crises, the financial function of companies is called upon to play a strategic role not only in resource management but also in organizational resilience. The emergence of financial technologies (fintech) offers innovative tools capable of transforming this function by enhancing the efficiency of financial processes and increasing companies' ability to adapt and overcome economic shocks. However, despite the rapid rise of fintechs and their growing adoption by companies, there remain uncertainties regarding the real impact of these innovations on the financial resilience of organizations. Indeed, how do fintech-driven innovations transform the financial function, and to what extent does this transformation contribute to strengthening the financial resilience of companies in the face of contemporary crises? This research aims to explore these questions by examining the interrelationships between the financial function, fintech innovations, and corporate resilience, in order to identify optimization levers that could be adopted for better financial risk management.

Keywords: finance, financial function, fintech, resilience, innovation

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Authors: Arslan Murtaza

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Model Driven Architecture (MDA) is technique presented by OMG (Object Management Group) for software development in which different models are proposed and converted them into code. The main plan is to identify task by using PIM (Platform Independent Model) and transform it into PSM (Platform Specific Model) and then converted into code. In this review paper describes some challenges and issues that are faced in MDA, type and transformation of models (e.g. CIM, PIM and PSM), and evaluation of MDA-based methodologies.

Keywords: OMG, model driven rrchitecture (MDA), computation independent model (CIM), platform independent model (PIM), platform specific model(PSM), MDA-based methodologies

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Authors: Abdullahi Garba

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The study investigated the effects of practical activities on performance among biology students in Zaria education zone, Kaduna State, Nigeria. The population consists of 18 public schools in the Zaria Education Zone with a total number of 4,763 students. A random sample of 115 students was selected from the population in the study area. The study design was quasi-experimental, which adopted the pre-test, post-test experimental, and control group design. The experimental group was exposed to practical activities, while the control group was taught with the lecture method. A validated instrument, a biology performance test (BPT) with a reliability coefficient of 0.82, was used to gather data which were analyzed using a t-test and paired sample t-test. Two research questions and hypotheses guided the study. The hypotheses were tested at p≤0.05 level of significance. Findings revealed that: there was a significant difference in the academic performance of students exposed to practical activities compared to their counterparts; there was no significant difference in performance between male and female Biology students exposed to practical activities. The recommendation given was that practical activities should be encouraged in the teaching and learning of Biology for better understanding. The Federal and State Ministry of Education should sponsor biology teachers for training and retraining of teachers to improve the academic performance of students in the subject.

Keywords: biology, practical, activity, performance

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Authors: Ali Pour Yazdanpanah, Farideh Foroozandeh Shahraki, Emma Regentova

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The reconstruction from sparse-view projections is one of important problems in computed tomography (CT) limited by the availability or feasibility of obtaining of a large number of projections. Traditionally, convex regularizers have been exploited to improve the reconstruction quality in sparse-view CT, and the convex constraint in those problems leads to an easy optimization process. However, convex regularizers often result in a biased approximation and inaccurate reconstruction in CT problems. Here, we present a nonconvex, Lipschitz continuous and non-smooth regularization model. The CT reconstruction is formulated as a nonconvex constrained L1 − L2 minimization problem and solved through a difference of convex algorithm and alternating direction of multiplier method which generates a better result than L0 or L1 regularizers in the CT reconstruction. We compare our method with previously reported high performance methods which use convex regularizers such as TV, wavelet, curvelet, and curvelet+TV (CTV) on the test phantom images. The results show that there are benefits in using the nonconvex regularizer in the sparse-view CT reconstruction.

Keywords: computed tomography, non-convex, sparse-view reconstruction, L1-L2 minimization, difference of convex functions

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Authors: Anil Ranjitbhai Patel, Clement John Shaji, Peter Liggesmeyer

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Safety and security of autonomous vehicles (AVs) is a growing concern, first, due to the increased number of safety-critical functions taken over by automotive embedded systems; second, due to the increased exposure of the software-intensive systems to potential attackers; third, due to dynamic interaction in an uncertain and unknown environment at runtime which results in changed functional and non-functional properties of the system. Frequently occurring environmental uncertainties, random component failures, and compromise security of the AVs might result in hazardous events, sometimes even in an accident, if left undetected. Beyond these technical issues, we argue that the safety and security of AVs against accidental and deliberate faults are poorly understood and rarely implemented. One possible way to overcome this is through a well-known diversity approach. As an effective approach to increase safety and security, diversity has been widely used in the aviation, railway, and aerospace industries. Thus, the paper proposes fault-tolerance by diversity model takes into consideration the mitigation of accidental and deliberate faults by application of structure and variant redundancy. The model can be used to design the AVs with various types of diversity in hardware and software-based multi-version system. The paper evaluates the presented approach by employing an example from adaptive cruise control, followed by discussing the case study with initial findings.

Keywords: autonomous vehicles, diversity, fault-tolerance, adaptive cruise control, safety, security

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Authors: Fatemeh Khalili Varnamkhasti

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In recent times, there has been a notable shift in the application of Total Quality Management (TQM) from manufacturing to service organizations, prompting numerous studies on the subject. TQM has firmly established itself across various sectors, emerging as an approach to process improvement, waste reduction, business optimization, and quality performance. Many researchers and academics have recognized the relevance of TQM for sustainable competitive advantage, particularly in service organizations. In light of this, the purpose of this research study is to explore the applicability of TQM within the service framework. The study delves into existing literature on TQM in service organizations and examines the reasons for its occasional shortcomings. Ultimately, the paper provides systematic guidelines for the effective implementation of TQM in service organizations. The findings of this study offer a much-improved understanding of TQM and its practices, shedding light on the evolution of service organizations. Additionally, the study highlights key insights from recent research on TQM in service organizations and proposes a ten-step approach for the successful implementation of TQM in the service sector. This framework aims to provide service managers and professionals with a comprehensive understanding of TQM fundamentals and encourages a deeper exploration of TQM theory.

Keywords: quality, control, service, management, teamwork

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Authors: B. V. Feujofack Kemda, N. Barka, M. Jahazi, D. Osmani

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Automobile manufacturers are constantly seeking means to reduce the weight of car bodies. The usage of several steel grades in auto body assembling has been found to be a good technique to enlighten vehicles weight. This few years, the usage of dual phase (DP) steels, transformation induced plasticity (TRIP) steels and boron steels in some parts of the auto body have become a necessity because of their lightweight. However, these steels are martensitic, when they undergo a fast heat treatment, the resultant microstructure is essential, made of martensite. Resistance spot welding (RSW), one of the most used techniques in assembling auto bodies, becomes problematic in the case of these steels. RSW being indeed a process were steel is heated and cooled in a very short period of time, the resulting weld nugget is mostly fully martensitic, especially in the case of DP, TRIP and boron steels but that also holds for plain carbon steels as AISI 1010 grade which is extensively used in auto body inner parts. Martensite in its turn must be avoided as most as possible when welding steel because it is the principal source of brittleness and it weakens weld nugget. Thus, this work aims to find a mean to reduce martensite fraction in weld nugget when using RSW for assembling. The prediction of phase transformation kinetics during RSW has been done. That phase transformation kinetics prediction has been made possible through the modelling of the whole welding process, and a technique called post weld heat treatment (PWHT) have been applied in order to reduce martensite fraction in the weld nugget. Simulation has been performed for AISI 1010 grade, and results show that the application of PWHT leads to the formation of not only martensite but also ferrite, bainite and pearlite during the cooling of weld nugget. Welding experiments have been done in parallel and micrographic analyses show the presence of several phases in the weld nugget. Experimental weld geometry and phase proportions are in good agreement with simulation results, showing here the validity of the model.

Keywords: resistance spot welding, AISI 1010, modeling, post weld heat treatment, phase transformation, kinetics

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Authors: Jaden Lu, Olivia Lu

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Despite the remarkable advancement of solar cell technology, the challenge of optimizing total solar energy harvest efficiency persists, primarily due to significant heat loss. This excess heat not only diminishes solar panel output efficiency but also curtails its operational lifespan. A promising approach to address this issue is the conversion of surplus heat into electricity. In recent years, there is growing interest in the use of thermoelectric generators (TEG) as a potential solution. The integration of efficient TEG devices holds the promise of augmenting overall energy harvest efficiency while prolonging the longevity of solar panels. While certain research groups have proposed the integration of solar cells and TEG devices, a substantial gap between conceptualization and practical implementation remains, largely attributed to low thermal energy conversion efficiency of TEG devices. To bridge this gap and meet the requisites of practical application, a feasible strategy involves the incorporation of a substantial number of p-n junctions within a confined unit volume. However, the manufacturing of high-density TEG p-n junctions presents a formidable challenge. The prevalent solution often leads to large device sizes to accommodate enough p-n junctions, consequently complicating integration with solar cells. Recently, the adoption of 3D printing technology has emerged as a promising solution to address this challenge by fabricating high-density p-n arrays. Despite this, further developmental efforts are necessary. Presently, the primary focus is on the 3D printing of vertically layered TEG devices, wherein p-n junction density remains constrained by spatial limitations and the constraints of 3D printing techniques. This study proposes a novel device configuration featuring horizontally arrayed p-n junctions of Bi2Te3. The structural design of the device is subjected to simulation through the Finite Element Method (FEM) within COMSOL Multiphysics software. Various device configurations are simulated to identify optimal device structure. Based on the simulation results, a new TEG device is fabricated utilizing 3D Selective laser melting (SLM) printing technology. Fusion 360 facilitates the translation of the COMSOL device structure into a 3D print file. The horizontal design offers a unique advantage, enabling the fabrication of densely packed, three-dimensional p-n junction arrays. The fabrication process entails printing a singular row of horizontal p-n junctions using the 3D SLM printing technique in a single layer. Subsequently, successive rows of p-n junction arrays are printed within the same layer, interconnected by thermally conductive copper. This sequence is replicated across multiple layers, separated by thermal insulating glass. This integration created in a highly compact three-dimensional TEG device with high density p-n junctions. The fabricated TEG device is then attached to the bottom of the solar cell using thermal glue. The whole device is characterized, with output data closely matching with COMSOL simulation results. Future research endeavors will encompass the refinement of thermoelectric materials. This includes the advancement of high-resolution 3D printing techniques tailored to diverse thermoelectric materials, along with the optimization of material microstructures such as porosity and doping. The objective is to achieve an optimal and highly integrated PV-TEG device that can substantially increase the solar energy harvest efficiency.

Keywords: thermoelectric, finite element method, 3d print, energy conversion

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Authors: Nadia Belu, Laurenţiu Mihai Ionescu, Agnieszka Misztal

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The automotive industry is one of the most important industries in the world that concerns not only the economy, but also the world culture. In the present financial and economic context, this field faces new challenges posed by the current crisis, companies must maintain product quality, deliver on time and at a competitive price in order to achieve customer satisfaction. Two of the most recommended techniques of quality management by specific standards of the automotive industry, in the product development, are Failure Mode and Effects Analysis (FMEA) and Control Plan. FMEA is a methodology for risk management and quality improvement aimed at identifying potential causes of failure of products and processes, their quantification by risk assessment, ranking of the problems identified according to their importance, to the determination and implementation of corrective actions related. The companies use Control Plans realized using the results from FMEA to evaluate a process or product for strengths and weaknesses and to prevent problems before they occur. The Control Plans represent written descriptions of the systems used to control and minimize product and process variation. In addition Control Plans specify the process monitoring and control methods (for example Special Controls) used to control Special Characteristics. In this paper we propose a computer-aided solution with Genetic Algorithms in order to reduce the drafting of reports: FMEA analysis and Control Plan required in the manufacture of the product launch and improved knowledge development teams for future projects. The solution allows to the design team to introduce data entry required to FMEA. The actual analysis is performed using Genetic Algorithms to find optimum between RPN risk factor and cost of production. A feature of Genetic Algorithms is that they are used as a means of finding solutions for multi criteria optimization problems. In our case, along with three specific FMEA risk factors is considered and reduce production cost. Analysis tool will generate final reports for all FMEA processes. The data obtained in FMEA reports are automatically integrated with other entered parameters in Control Plan. Implementation of the solution is in the form of an application running in an intranet on two servers: one containing analysis and plan generation engine and the other containing the database where the initial parameters and results are stored. The results can then be used as starting solutions in the synthesis of other projects. The solution was applied to welding processes, laser cutting and bending to manufacture chassis for buses. Advantages of the solution are efficient elaboration of documents in the current project by automatically generating reports FMEA and Control Plan using multiple criteria optimization of production and build a solid knowledge base for future projects. The solution which we propose is a cheap alternative to other solutions on the market using Open Source tools in implementation.

Keywords: automotive industry, FMEA, control plan, automotive technology

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Authors: Rakan A. Ahmed, Raja S. Khan, Mohammed M. Qahtani

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This paper explores the transformative impact of laser cladding technology on the circular economy, emphasizing its role in reducing environmental impact compared to traditional welding methods. Laser cladding, an innovative manufacturing process, optimizes resource efficiency and sustainability by significantly decreasing power consumption and minimizing material waste. The study explores how laser cladding operates within the framework of the circular economy, promoting energy efficiency, waste reduction, and emissions control. Through a comparative analysis of energy and material consumption between laser cladding and conventional welding methods, the paper highlights the significant strides in environmental conservation and resource optimization made possible by laser cladding. The findings highlight the potential for this technology to revolutionize industrial practices and propel a more sustainable and eco-friendly manufacturing landscape.

Keywords: laser cladding, circular economy, carbon emission, energy

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Authors: M. A. Aleem, M. S. Awan

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Flat spiral coil for electromagnetic forming system has been modelled in FEMM 4.2 software. Copper strip was chosen as the material for designing the actuator coil. Relationship between height to width ratio (S-factor) of the copper strip and coil’s performance has been studied. Magnetic field intensities, eddy currents, and Lorentz force were calculated for the coils that were designed using six different 'S-factor' values (0.65, 0.75, 1.05, 1.25, 1.54 and 1.75), keeping the cross-sectional area of strip the same. Results obtained through simulation suggest that actuator coil with S-factor ~ 1 shows optimum forming performance as it exerts maximum Lorentz force (84 kN) on work piece. The same coils were fabricated and used for electromagnetic sheet forming experiments. Aluminum 6061 sheets of thickness 1.5 mm have been formed using different voltage levels of capacitor bank. Smooth forming profiles were obtained with dome heights 28, 35 and 40 mm in work piece at 800, 1150 and 1250 V respectively.

Keywords: FEM modelling, electromagnetic forming, spiral coil, Lorentz force

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Authors: Mohammad Arshad Ikram

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We report three cases of challenging fractures in children treated by intramedullary fixation using the Metaizeau method and achieved anatomical reduction with excellent clinical results. Jean-Paul Metaizeau described the centromedullary fixation for the radial neck in 1980 using K-wires Radial neck fractures are uncommon in children. Treatment of severely displaced fractures is always challenging. Closed reduction techniques are more popular as compared to open reduction due to the low risk of complications. Metaizeau technique of closed reduction with centromedullary pinning is a commonly preferred method of treatment. We present two cases with a severely displaced radial neck fracture, treated by this method and achieved sound union; anatomical position of the radial head and full function were observed two months after surgery. Proximal humerus fractures are another uncommon injury in children accounting for less than 5% of all pediatric fractures. Most of these injuries occur through the growth plate because of its relative weakness. Salter-Harris type I is commonly seen in the younger age group, whereas type II & III occurs in older children and adolescents. In contrast to adults, traumatic glenohumeral dislocation is an infrequently observed condition among children. A combination of proximal humerus fracture and glenohumeral dislocation is extremely rare and occurs in less than 2% of the pediatric population. The management of this injury is always challenging. Treatment ranged from closed reduction with and without internal fixation and open reduction with internal fixation. The children who had closed reduction with centromedullary fixation by the Metaizeau method showed excellent results with the return of full movements at the shoulder in a short time without any complication. We present the case of a child with anterior dislocation of the shoulder associated with a complete displaced proximal humerus metaphyseal fracture. The fracture was managed by closed reduction and then fixation by two centromedullary K-wires using the Metaizeau method, achieving the anatomical reduction of the fracture and dislocation. This method of treatment enables us to achieve excellent radiological and clinical results in a short time.

Keywords: glenohumeral, Metaizeau method, pediatric fractures, radial neck

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence

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Authors: Shrestha Sharma, Jasjeet K. Sahni, Javed Ali, Sanjula Baboota

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Introduction: Rutin is a naturally occurring strong antioxidant molecule belonging to bioflavonoid category. Due to its free radical scavenging properties, it has been found to be beneficial in the treatment of various diseases including inflammation, cancer, diabetes, allergy, cardiovascular disorders and various types of microbial infections. Despite its beneficial effects, it suffers from the problem of low aqueous solubility which is responsible for low oral bioavailability. The aim of our study was to optimize and characterize self-nanoemulsifying drug delivery system (SNEDDS) of rutin using Box-Behnken design (BBD) combined with a desirability function. Further various antioxidant, pharmacokinetic and pharmacodynamic studies were performed for the optimized rutin SNEDDS formulation. Methodologies: Selection of oil, surfactant and co-surfactant was done on the basis of solubility/miscibility studies. Sefsol+ Vitamin E, Solutol HS 15 and Transcutol P were selected as oil phase, surfactant and co-surfactant respectively. Optimization of SNEDDS formulations was done by a three-factor, three-level (33)BBD. The independent factors were Sefsol+ Vitamin E, Solutol HS15, and Transcutol P. The dependent variables were globule size, self emulsification time (SEF), % transmittance and cumulative percentage drug released. Various response surface graphs and contour plots were constructed to understand the effect of different factor, their levels and combinations on the responses. The optimized Rutin SNEDDS formulation was characterized for various parameters such as globule size, zeta potential, viscosity, refractive index , % Transmittance and in vitro drug release. Ex vivo permeation studies and pharmacokinetic studies were performed for optimized formulation. Antioxidant activity was determined by DPPH and reducing power assays. Anti-inflammatory activity was determined by using carrageenan induced rat paw oedema method. Permeation of rutin across small intestine was assessed using confocal laser scanning microscopy (CLSM). Major findings:The optimized SNEDDS formulation consisting of Sefsol+ Vitamin E - Solutol HS15 -Transcutol HP at proportions of 25:35:17.5 (w/w) was prepared and a comparison of the predicted values and experimental values were found to be in close agreement. The globule size and PDI of optimized SNEDDS formulation was found to be 16.08 ± 0.02 nm and 0.124±0.01 respectively. Significant (p˂0.05) increase in percentage drug release was achieved in the case of optimized SNEDDS formulation (98.8 %) as compared to rutin suspension. Furthermore, pharmacokinetic study showed a 2.3-fold increase in relative oral bioavailability compared with that of the suspension. Antioxidant assay results indicated better efficacy of the developed formulation than the pure drug and it was found to be comparable with ascorbic acid. The results of anti-inflammatory studies showed 72.93 % inhibition for the SNEDDS formulation which was significantly higher than the drug suspension 46.56%. The results of CLSM indicated that the absorption of SNEDDS formulation was considerably higher than that from rutin suspension. Conclusion: Rutin SNEDDS have been successfully prepared and they can serve as an effective tool in enhancing oral bioavailability and efficacy of Rutin.

Keywords: rutin, oral bioavilability, pharamacokinetics, pharmacodynamics

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Authors: Binbin Chen, Dennis Y. C. Leung

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Aluminium (Al) -air cell holds a high volumetric capacity density of 8.05 Ah cm-3, benefit from the trivalence of Al ions. Additional benefits of Al-air cell are low price and environmental friendliness. Furthermore, the Al energy conversion process is characterized of 100% recyclability in theory. Along with a large base of raw material reserve, Al attracts considerable attentions as a promising material to be integrated within the global energy system. However, despite the early successful applications in military services, several problems exist that prevent the Al-air cells from widely civilian use. The most serious issue is the parasitic corrosion of Al when contacts with electrolyte. To overcome this problem, super-pure Al alloyed with various traces of metal elements are used to increase the corrosion resistance. Nevertheless, high-purity Al alloys are costly and require high energy consumption during production process. An alternative approach is to add inexpensive inhibitors directly into the electrolyte. However, such additives would increase the internal ohmic resistance and hamper the cell performance. So far these methods have not provided satisfactory solutions for the problem within Al-air cells. For the operation of alkaline Al-air cell, there are still other minor problems. One of them is the formation of aluminium hydroxide in the electrolyte. This process decreases ionic conductivity of electrolyte. Another one is the carbonation process within the gas diffusion layer of cathode, blocking the porosity of gas diffusion. Both these would hinder the performance of cells. The present work optimizes the above problems by building an Al-air cell operation system, consisting of four components. A top electrolyte tank containing fresh electrolyte is located at a high level, so that it can drive the electrolyte flow by gravity force. A mechanical rechargeable Al-air cell is fabricated with low-cost materials including low grade Al, carbon paper, and PMMA plates. An electrolyte waste tank with elaborate channel is designed to separate the hydrogen generated from the corrosion, which would be collected by gas collection device. In the first section of the research work, we investigated the performance of the mechanical rechargeable Al-air cell with a constant flow rate of electrolyte, to ensure the repeatability experiments. Then the whole system was assembled together and the feasibility of operating was demonstrated. During experiment, pure hydrogen is collected by collection device, which holds potential for various applications. By collecting this by-product, high utilization efficiency of aluminum is achieved. Considering both electricity and hydrogen generated, an overall utilization efficiency of around 90 % or even higher under different working voltages are achieved. Fluidic electrolyte could remove aluminum hydroxide precipitate and solve the electrolyte deterioration problem. This operation system provides a low-cost strategy for harvesting energy from the abundant secondary Al. The system could also be applied into other metal-air cells and is suitable for emergency power supply, power plant and other applications. The low cost feature implies great potential for commercialization. Further optimization, such as scaling up and optimization of fabrication, will help to refine the technology into practical market offerings.

Keywords: aluminium-air cell, high efficiency, hydrogen, mechanical recharge

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Authors: Nitin Singh, Meng Ling, Talha Ahmed, Tianxia Zhao, Reinier van de Pol

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We propose the use of reinforcement learning (RL) as a viable alternative for optimizing supply chain management, particularly in scenarios with stochasticity in product demands. RL’s adaptability to changing conditions and its demonstrated success in diverse fields of sequential decision-making makes it a promising candidate for addressing supply chain problems. We investigate the impact of demand fluctuations in a multi-product supply chain system and develop RL agents with learned generalizable policies. We provide experimentation details for training RL agents and statistical analysis of the results. We study the generalization ability of RL agents for different demand uncertainty scenarios and observe superior performance compared to the agents trained with fixed demand curves. The proposed methodology has the potential to lead to cost reduction and increased profit for companies dealing with frequent inventory movement between supply and demand nodes.

Keywords: inventory management, reinforcement learning, supply chain optimization, uncertainty

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Authors: Muhammet Dursun Kaya, Hasan Asil

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In recent years, different methods have been proposed to optimize question processing in database. Although different methods have been proposed to optimize the query, but the problem which exists here is that most of these methods destroy the query execution plan after executing the query. This research attempts to solve the above problem by using a combination of methods of communicating with the database (the present questions in the programming code and using store procedures) and making query processing adaptive in database, and proposing a new approach for optimization of query processing by introducing the idea of dynamic store procedures. This research creates dynamic store procedures in the database according to the proposed algorithm. This method has been tested on applied software and results shows a significant improvement in reducing the query processing time and also reducing the workload of DBMS. Other advantages of this algorithm include: making the programming environment a single environment, eliminating the parametric limitations of the stored procedures in the database, making the stored procedures in the database dynamic, etc.

Keywords: relational database, agent, query processing, adaptable, communication with the database

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Authors: Revoti Prasad Bora, Nikita Katyal

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Promotion is a key element in the retail business. Thus, analysis of promotions to quantify their effectiveness in terms of Revenue and/or Margin is an essential activity in the retail industry. However, measuring the sales/revenue uplift is based on estimations, as the actual sales/revenue without the promotion is not present. Further, the presence of Halo and Cannibalization in a multiple parallel promotions’ scenario complicates the problem. Calculating Baseline by considering inter-brand/competitor items or using Halo and Cannibalization's impact on Revenue calculations by considering Baseline as an interpretation of items’ unit sales in neighboring nonpromotional weeks individually may not capture the overall Revenue uplift in the case of multiple parallel promotions. Hence, this paper proposes a Machine Learning based method for calculating the Revenue uplift by considering the Halo and Cannibalization impact on the Baseline and the Revenue. In the first section of the proposed methodology, Baseline of an item is calculated by incorporating the impact of the promotions on its related items. In the later section, the Revenue of an item is calculated by considering both Halo and Cannibalization impacts. Hence, this methodology enables correct calculation of the overall Revenue uplift due a given promotion.

Keywords: Halo, Cannibalization, promotion, Baseline, temporary price reduction, retail, elasticity, cross price elasticity, machine learning, random forest, linear regression

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Authors: Adel El-Hadidy

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For any industry, the production and quality management or wastages reductions have major impingement on overall factory economy. This work discusses the quality improvement of garment industry by applying Pareto analysis, cause and effect diagram and Taguchi experimental design. The main purpose of the work is to reduce the stitching defects, which will also minimize the rejection and reworks rate. Application of Pareto chart, fish bone diagram and Process Sigma Level/and or Performance Level tools helps solving those problems on priority basis. Among all, only sewing, defects are responsible form 69.3% to 97.3 % of total defects. Process Sigma level has been improved from 0.79 to 1.3 and performance rate improved, from F to D level. The results showed that the new set of sewing parameters was superior to the original one. It can be seen that fabric size has the largest effect on the sewing defects and that needle size has the smallest effect on the stitching defects.

Keywords: garment, sewing defects, cost of rework, DMAIC, sigma level, cause and effect diagram, Pareto analysis

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Authors: Sultan Ben Jaber

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Optical properties of molecules exhibit dramatic changes when adsorbed close to nano-structure metallic surfaces such as gold and silver nanomaterial. This phenomena opened a wide range of research to improve conventional spectroscopies efficiency. A well-known technique that has an intensive focus of study is surface-enhanced Raman spectroscopy (SERS), as since the first observation of SERS phenomena, researchers have published a great number of articles about the potential mechanisms behind this effect as well as developing materials to maximize the enhancement. Infrared and Raman spectroscopy are complementary techniques; thus, surface-enhanced infrared absorption (SEIRA) also shows a noticeable enhancement of molecules in the mid-IR excitation on nonmetallic structure substrates. In the SEIRA, vibrational modes that gave change in dipole moments perpendicular to the nano-metallic substrate enhanced 200 times greater than the free molecule’s modes. SEIRA spectroscopy is promising for the characterization and identification of adsorbed molecules on metallic surfaces, especially at trace levels. IR reflection-absorption spectroscopy (IRAS) is a well-known technique for measuring IR spectra of adsorbed molecules on metallic surfaces. However, SEIRA spectroscopy sensitivity is up to 50 times higher than IRAS. SEIRA enhancement has been observed for a wide range of molecules adsorbed on metallic substrates such as Au, Ag, Pd, Pt, Al, and Ni, but Au and Ag substrates exhibited the highest enhancement among the other mentioned substrates. In this work, trace levels of 3,4-methylenedioxymethamphetamine (MDMA) have been detected using gold nanoparticles (AuNPs) substrates with surface-enhanced infrared absorption (SEIRA). AuNPs were first prepared and washed, then mixed with different concentrations of MDMA samples. The process of fabricating the substrate prior SEIRA measurements included mixing of AuNPs and MDMA samples followed by vigorous stirring. The stirring step is particularly crucial, as stirring allows molecules to be robustly adsorbed on AuNPs. Thus, remarkable SEIRA was observed for MDMA samples even at trace levels, showing the rigidity of our approach to preparing SEIRA substrates.

Keywords: surface-enhanced infrared absorption (SEIRA), gold nanoparticles (AuNPs), amphetamines, methylene dioxy- methamphetamine (MDMA), enhancement factor

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Authors: Sifen Abreham

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Employees are resources in organizations; as such, they need to be trained and developed properly to achieve an organization's goals and expectations. The initial development of the human resource management concept is based on the effective utilization of people to treat them as resources, leading to the realization of business strategies and organizational objectives. The study aimed to assess the effect of training and development practices on employee performance. The researcher used an explanatory research design, which helps to explain, understand, and predict the relationship between variables. To collect the data from the respondents, the study used probability sampling. From the probability, the researcher used stratified random sampling, which can branch off the entire population into homogenous groups. The result was analyzed and presented by using the statistical package for the social science (SPSS) version 26. The major finding of the study was that the training has an impact on employees' job performance to achieve organizational objectives. The district has a policy and procedure for training and development, but it doesn’t apply actively, and it’s not suitable for district-advised reform this policy and procedure and applied actively; the district gives training for the majority of its employees, but most of the time, the training is theoretical the district advised to use practical training method to see positive change, the district gives evaluation after the employees take training and development, but the result is not encouraging the district advised to assess employees skill gap and feel that gap, the district has a budget, but it’s not adequate the district advised to strengthen its financial ground.

Keywords: training, development, employees, performance, policy

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Authors: Ibtisam Mahmoud Mohammed Sultan

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The present research aimed to identify the level of both emotional and emotional competence among students in Tikrit University aimed to know the assumptions in statistical significance for both variables as gender variables (m-f) and specialty (scientific-humanistic), as research to learn what Relationship between emotional safety and efficiency alanfaalet Tikrit University students. The researcher built emotional security measure (54) as built measure emotional competence (46), as the researcher extract full alsaykomtrih characteristics of both scales. The research sample consisted of (600) students selected by the random way and applying the scales on a basic search sample and processed statistical data using a variety of methods, including statistical test (test T.) and Pearson correlation coefficient, the researcher found a set of results. The following: 1. that the Tikrit University students possess a high level of emotional security. 2. to safely enjoy passionate males more than females. 3. that there is no difference between students of scientific and humanitarian specialization in variable emotional security. 4. that the Tikrit University students enjoy a high level of emotional competence. 5. the female-male outperforming in emotional competence level. 6. the humanitarian specialization students Excel in emotional competence for those of specialty. 7. the existence of a positive correlation between variables. Through search results, the researcher has developed a set of conclusions, proposals, and recommendations.

Keywords: relation, emotional security, students, efficiency

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Authors: Khin Fai Chen, Jee-Hou Ho, Eng Hwa Yap

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An acoustic micro-energy harvester (AMEH) is developed to convert wasted acoustical energy into useful electrical energy. AMEH is mathematically modeled using lumped element modelling (LEM) and Euler-Bernoulli beam (EBB) modelling. An experiment is designed to validate the mathematical model and assess the feasibility of AMEH. Comparison of theoretical and experimental data on critical parameter value such as Mm, Cms, dm and Ceb showed the variances are within 1% to 6%, which is reasonably acceptable. Hence, AMEH mathematical model is validated. Then, AMEH undergoes bandwidth tuning for performance optimization for further experimental work. The AMEH successfully produces 0.9 V⁄(m⁄s^2) and 1.79 μW⁄(m^2⁄s^4) at 60Hz and 400kΩ resistive load which only show variances about 7% compared to theoretical data. By integrating a capacitive load of 200µF, the discharge cycle time of AMEH is 1.8s and the usable energy bandwidth is available as low as 0.25g. At 1g and 60Hz resonance frequency, the averaged power output is about 2.2mW which fulfilled a range of wireless sensors and communication peripherals power requirements. Finally, the design for AMEH is assessed, validated and deemed as a feasible design.

Keywords: piezoelectric, acoustic, energy harvester

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Authors: Ahmed Abdulrahman, Jalal Foroozesh

Abstract:

CO₂ based enhanced oil recovery (EOR) techniques have gained massive attention from major oil firms since they resolve the industry's two main concerns of CO₂ contribution to the greenhouse effect and the declined oil production. Carbonated water injection (CWI) is a promising EOR technique that promotes safe and economic CO₂ storage; moreover, it mitigates the pitfalls of CO₂ injection, which include low sweep efficiency, early CO₂ breakthrough, and the risk of CO₂ leakage in fractured formations. One of the main challenges that hinder the wide adoption of this EOR technique is the complexity of accurate modeling of the kinetics of CO₂ mass transfer. The mechanisms of CO₂ mass transfer during CWI include the slow and gradual cross-phase CO₂ diffusion from carbonated water (CW) to the oil phase and the CO₂ dispersion (within phase diffusion and mechanical mixing), which affects the oil physical properties and the spatial spreading of CO₂ inside the reservoir. A 2D non-equilibrium compositional simulator has been developed using a fully implicit finite difference approximation. The material balance term (k) was added to the governing equation to account for the slow cross-phase diffusion of CO₂ from CW to the oil within the gird cell. Also, longitudinal and transverse dispersion coefficients have been added to account for CO₂ spatial distribution inside the oil phase. The CO₂-oil diffusion coefficient was calculated using the Sigmund correlation, while a scale-dependent dispersivity was used to calculate CO₂ mechanical mixing. It was found that the CO₂-oil diffusion mechanism has a minor impact on oil recovery, but it tends to increase the amount of CO₂ stored inside the formation and slightly alters the residual oil properties. On the other hand, the mechanical mixing mechanism has a huge impact on CO₂ spatial spreading (accurate prediction of CO₂ production) and the noticeable change in oil physical properties tends to increase the recovery factor. A sensitivity analysis has been done to investigate the effect of formation heterogeneity (porosity, permeability) and injection rate, it was found that the formation heterogeneity tends to increase CO₂ dispersion coefficients, and a low injection rate should be implemented during CWI.

Keywords: CO₂ mass transfer, carbonated water injection, CO₂ dispersion, CO₂ diffusion, cross phase CO₂ diffusion, within phase CO2 diffusion, CO₂ mechanical mixing, non-equilibrium simulation

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Authors: Kei Kamada, Rikito Murakami, Masahiko Ito, Mototaka Arakawa, Yasuhiro Shoji, Toshiyuki Ueno, Masao Yoshino, Akihiro Yamaji, Shunsuke Kurosawa, Yuui Yokota, Yuji Ohashi, Akira Yoshikawa

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Techniques of energy harvesting y have been widely developed in recent years, due to high demand on the power supply for ‘Internet of things’ devices such as wireless sensor nodes. In these applications, conversion technique of mechanical vibration energy into electrical energy using magnetostrictive materials n have been brought to attention. Among the magnetostrictive materials, Fe-Ga and Fe-Al alloys are attractive materials due to the figure of merits such price, mechanical strength, high magnetostrictive constant. Up to now, bulk crystals of these alloys are produced by the Bridgman–Stockbarger method or the Czochralski method. Using these method big bulk crystal up to 2~3 inch diameter can be grown. However, non-uniformity of chemical composition along to the crystal growth direction cannot be avoid, which results in non-uniformity of magnetostriction constant and reduction of the production yield. The micro-pulling down (μ-PD) method has been developed as a shaped crystal growth technique. Our group have reported shaped crystal growth of oxide, fluoride single crystals with different shape such rod, plate tube, thin fiber, etc. Advantages of this method is low segregation due to high growth rate and small diffusion of melt at the solid-liquid interface, and small kerf loss due to near net shape crystal. In this presentation, we report the shaped long plate crystal growth of Fe-Ga and Fe-Al alloys using the μ-PD method. Alloy crystals were grown by the μ-PD method using calcium oxide crucible and induction heating system under the nitrogen atmosphere. The bottom hole of crucibles was 5 x 1mm² size. A <100> oriented iron-based alloy was used as a seed crystal. 5 x 1 x 320 mm³ alloy crystal plates were successfully grown. The results of crystal growth, chemical composition analysis, magnetostrictive properties and a prototype vibration energy harvester are reported. Furthermore, continuous crystal growth using powder supply system will be reported to minimize the chemical composition non-uniformity along the growth direction.

Keywords: crystal growth, micro-pulling-down method, Fe-Ga, Fe-Al

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Authors: Chitaranjan Sharma

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The present paper deals with the analysis of a fuel supply system in an automobile engine of a four wheeler which is having both the option of fuel i.e. PETROL and CNG. Since CNG is cheaper than petrol so the priority is given to consume CNG as compared to petrol. An automatic switch is used to start petrol supply at the time of failure of CNG supply. Using regenerative point technique with Markov renewal process, the reliability characteristics which are useful to system designers are obtained.

Keywords: reliability, redundancy, repair time, transition, probability, regenerative points, markov renewal, process

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Authors: M. Jerold, V. Sivasubramanian

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In this study, nano zero valent iron Sargassum swartzii (nZVI-SS) biocomposite a marine algal based biosorbent was used for the removal of simulated crystal violet (CV) in batch and continuous fixed bed operation. The Box-Behnen design (BBD) experimental results revealed the biosoprtion was maximum at pH 7.5, biosorbent dosage 0.1 g/L and initial CV concentration of 100 mg/L. The effect of various column parameters like bed depth (3, 6 and 9 cm), flow rate (5, 10 and 15 mL/min) and influent CV concentration (5, 10 and 15 mg/L) were investigated. The exhaustion time increased with increase of bed depth, influent CV concentration and decrease of flow rate. Adam-Bohart, Thomas and Yoon-Nelson models were used to predict the breakthrough curve and to evaluate the model parameters. Out of these models, Thomas and Yoon-Nelson models well described the experimental data. Therefore, the result implies that nZVI-SS biocomposite is a cheap and most promising biosorbent for the removal of CV from wastewater.

Keywords: algae, biosorption, zero-valent, dye, wastewater

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Authors: Serdal Pamuk, Irem Cay

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Our model is based on the theory of reinforced random walks coupled with Michealis-Menten mechanisms which view endothelial cell receptors as the catalysts for transforming both tumor and macrophage derived tumor angiogenesis factor (TAF) into proteolytic enzyme which in turn degrade the basal lamina. The model consists of two main parts. First part has seven differential equations (DE’s) in one space dimension over the capillary, whereas the second part has the same number of DE’s in two space dimensions in the extra cellular matrix (ECM). We connect these two parts via some boundary conditions to move the cells into the ECM in order to initiate capillary formation. But, when does this movement begin? To address this question we estimate the thresholds that activate the transport equations in the capillary. We do this by using steady-state analysis of TAF equation under some assumptions. Once these equations are activated endothelial, pericyte and macrophage cells begin to move into the ECM for the initiation of angiogenesis. We do believe that our results play an important role for the mechanisms of cell migration which are crucial for tumor angiogenesis. Furthermore, we estimate the long time tendency of these three cells, and find that they tend to the transition probability functions as time evolves. We provide our numerical solutions which are in good agreement with our theoretical results.

Keywords: angiogenesis, capillary formation, mathematical analysis, steady-state, transition probability function

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Authors: Tahsien Mohamed Okasha

Abstract:

We hypothesized that Post cardiac arrest patients with Glasgow coma scale (GCS) score of less than (8) and who will be exposed to therapeutic hypothermia protocol will exhibit improvement in their neurological performance. Purposive sample of 17 patients who were fulfilling the inclusion criteria during one year collected. The study carried out using Quasi-experimental research design. Four Tools used for data collection of this study: Demographic and medical data sheet, Post cardiac arrest health assessment sheet, Bedside Shivering Assessment Scale (BSAS), and Glasgow Pittsburgh cerebral performance category scale (CPC). Result: the mean age was X̅ ± SD = 53 ± 8.122 years, 47.1% were arrested because of cardiac etiology. 35.3% with initial arrest rhythm ventricular tachycardia (VT), 23.5% with ventricular fibrillation (VF), and 29.4% with A-Systole. Favorable neurological outcome was seen among 70.6%. There was significant statistical difference in WBC, Platelets, blood gases value, random blood sugar. Also Initial arrest rhythm, etiology of cardiac arrest, and shivering status were significantly correlated with cerebral performance categories score. therapeutic hypothermia has positive effects on neurological performance among post cardiac arrest patients with GCS score of less than (8). replication of the study on larger probability sample, with randomized control trial design. Further study for suggesting nursing protocol for patients undergoing therapeutic hypothermia.

Keywords: therapeutic hypothermia, neurological performance, after resuscitation from cardiac arrest., resuscitation

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Authors: Adrian Priceputu, Elena Mihaela Stan

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Our research addresses a critical challenge in renewable energy: improving efficiency and reducing the costs associated with the installation of ground-mounted photovoltaic (PV) panels. The most commonly used foundation solution is metal piles - with various sections adapted to soil conditions and the structural model of the panels. However, direct foundation systems are also sometimes used, especially in brownfield sites. Although metal micropiles are generally the first design option, understanding and predicting their bearing capacity, particularly under varied soil conditions, remains an open research topic. CPT Method and Current Challenges: Metal piles are favored for PV panel foundations due to their adaptability, but existing design methods rely heavily on costly and time-consuming in situ tests. The Cone Penetration Test (CPT) offers a more efficient alternative by providing valuable data on soil strength, stratification, and other key characteristics with reduced resources. During the test, a cone-shaped probe is pushed into the ground at a constant rate. Sensors within the probe measure the resistance of the soil to penetration, divided into cone penetration resistance and shaft friction resistance. Despite some existing CPT-based design approaches for metal piles, these methods are often cumbersome and difficult to apply. They vary significantly due to soil type and foundation method, and traditional approaches like the LCPC method involve complex calculations and extensive empirical data. The method was developed by testing 197 piles on a wide range of ground conditions, but the tested piles were very different from the ones used for PV pile foundations, making the method less accurate and practical for steel micropiles. Project Objectives and Methodology: Our research aims to develop a calculation method for metal micropile foundations using CPT data, simplifying the complex relationships involved. The goal is to estimate the pullout bearing capacity of piles without additional laboratory tests, streamlining the design process. To achieve this, a case study was selected which will serve for the development of an 80ha solar power station. Four testing locations were chosen spread throughout the site. At each location, two types of steel profiles (H160 and C100) were embedded into the ground at various depths (1.5m and 2.0m). The piles were tested for pullout capacity under natural and inundated soil conditions. CPT tests conducted nearby served as calibration points. The results served for the development of a preliminary equation for estimating pullout capacity. Future Work: The next phase involves validating and refining the proposed equation on additional sites by comparing CPT-based forecasts with in situ pullout tests. This validation will enhance the accuracy and reliability of the method, potentially transforming the foundation design process for PV panels.

Keywords: cone penetration test, foundation optimization, solar power stations, steel pile foundations

Procedia PDF Downloads 45