Search results for: manufacturing optimization

Authors: Loveneet Kaur

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Introduction: Osteoarthritis (OA) is one of the leading causes of disability, and the knee is the most commonly affected joint in the body. The last resort for treatment of knee OA is Total Knee Replacement (TKR) surgery. Despite numerous advances in prosthetic design, patients do not reach normal function after surgery. Current surgical decisions are made on 2D radiographs and patient interviews. Aims: The aim of this study was to compare knee kinematics pre and post-TKR surgery using computer-animated images of patient-specific models under everyday conditions. Methods: 7 subjects were recruited for the study. Subjects underwent 3D gait analysis during 4 everyday activities and medical imaging of the knee joint pre- and one-month post-surgery. A 3D model was created from each of the scans, and the kinematic gait analysis data was used to animate the images. Results: Improvements were seen in a range of motion in all 4 activities 1-year post-surgery. The preoperative 3D images provide detailed information on the anatomy of the osteoarthritic knee. The postoperative images demonstrate potential future problems associated with the implant. Although not accurate enough to be of clinical use, the animated data can provide valuable insight into what conditions cause damage to both the osteoarthritic and prosthetic knee joints. As the animated data does not require specialist training to view, the images can be utilized across the fields of health professionals and manufacturing in the assessment and treatment of patients pre and post-knee replacement surgery. Future improvements in the collection and processing of data may yield clinically useful data. Conclusion: Although not yet of clinical use, the potential application of 3D animations of the knee joint pre and post-surgery is widespread.

Keywords: Orthoporosis, Ortharthritis, knee replacement, TKR

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Authors: N. Jirukkakul, J. Sodtipinta

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Tomatoes are widely consumed as fresh and processed products through the manufacturing industry. Therefore, tomato pomace is generated as a by-product accounting for about 5-13% of the whole tomato. Antioxidants still remain in tomato pomace and extraction of tomato oil may useful in edible film production. The edible film solution was prepared by mixing gelatin (2, 4 and 6%) with the distilled water and heating at 40oC for 30 min. Effect of tomato pomace oil was evaluated at 0, 0.5 and 1%. Film solution was poured in plate and dried overnight at 40oC before determining the physical properties, which are tensile strength, moisture content, color, solubility, and swelling power. The results showed that an increase gelatin concentration caused increasing of tensile strength, moisture content, solubility and swelling power. The edible film with tomato pomace oil extract appeared as the rough film with oil droplet dispersion. The addition of tomato pomace oil extract caused an increase in lightness, redness and yellowness, while tensile strength, moisture content, and solubility were decreased. Film with tomato pomace oil extract at 0.5 and 1% exhibited antioxidant properties but those properties were not significantly different (p<0.05) between film incorporated with tomato pomace oil extract 0.5 and 1%. The suitable condition for film production in this study, 4% of gelatin and 0.5% of tomato pomace oil extract, was selected for protecting oxidation of palm oil. At 15 days of the storage period, the palm oil which covered by gelatin film with tomato pomace oil extract had 22.45 milliequivalents/kg of peroxide value (PV), while, the palm oil which covered by polypropylene film and control had 24.79 and 26.67 milliequivalents/kg, respectively. Therefore, incorporation of tomato pomace oil extract in gelatin film was able to protect the oxidation of food products with high fat content.

Keywords: antioxidant, gelatin films, physical properties, tomato oil extract

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Authors: Walid Tawfik

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The interaction of high intensity ultrashort laser pulses with plasma generates many significant applications, including soft x-ray lasers, time-resolved laser induced plasma spectroscopy LIPS, and laser-driven accelerators. The development in producing of femtosecond down to ten femtosecond optical pulses has facilitates scientists with a vital tool in a variety of ultrashort phenomena, such as high field physics, femtochemistry and high harmonic generation HHG. In this research, we generate a two-octave-wide ultrashort supercontinuum pulses with an optical spectrum extending from 3.5 eV (ultraviolet) to 1.3 eV (near-infrared) using a capillary fiber filled with neon gas. These pulses are formed according to nonlinear self-phase modulation in the neon gas as a nonlinear medium. The investigations of the created pulses were made using spectral phase interferometry for direct electric-field reconstruction (SPIDER). A complete description of the output pulses was considered. The observed characterization of the produced pulses includes the beam profile, the pulse width, and the spectral bandwidth. After reaching optimization conditions, the intensity of the reconstructed pulse autocorrelation function was applied for the shorts pulse duration to achieve transform limited ultrashort pulses with durations below 6-fs energies up to 600μJ. Moreover, the effect of neon pressure variation on the pulse width was examined. The nonlinear self-phase modulation realized to be increased with the pressure of the neon gas. The observed results may lead to an advanced method to control and monitor ultrashort transit interaction in femtochemistry.

Keywords: supercontinuum, ultrafast, SPIDER, ultra-broadband

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Authors: Pia Wetzl

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The learning process of students can be optimized by combining online teaching with face-to-face sessions. So-called blended learning offers extensive flexibility as well as contact opportunities with fellow students and teachers. Furthermore, learning can be individualized and self-regulated. The aim of this article is to investigate which factors are necessary for blended learning to be successful. Semi-structured interviews were conducted with students (N = 60) and lecturers (N = 21) from different disciplines at two German universities. The questions focused on the perception of online, face-to-face and blended learning courses. In addition, questions focused on possible optimization potential and obstacles to practical implementation. The results show that on-site presence is very important for blended learning to be successful. If students do not get to know each other on-site, there is a risk of loneliness during the self-learning phases. This has a negative impact on motivation. From the perspective of the lecturers, the willingness of the students to participate in the sessions on-site is low. Especially when there is no obligation to attend, group work is difficult to implement because the number of students attending is too low. Lecturers would like to see more opportunities from the university and its administration to enforce attendance. In their view, this is the only way to ensure the success of blended learning. In addition, they see the conception of blended learning courses as requiring a great deal of time, which they are not always willing to invest. More incentives are necessary to keep the lecturers motivated to develop engaging teaching material. The study identifies factors that can help teachers conceptualize blended learning. It also provides specific implementation advice and identifies potential impacts. This catalogue has great value for the future-oriented development of courses at universities. Future studies could test its practical use.

Keywords: blended learning, higher education, teachers, student learning, qualitative research

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Authors: Didem Venus Yildiz, Murat Hocaoglu, Murat Dursun, Taner Akkan

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The shoulder joint is a more complex structure than the hip or knee joints. In addition to the overall complexity of the shoulder joint, two different factors influence the insufficient outcome of shoulder replacement: the shoulder prosthesis design is far from fully developed and it is difficult to place these shoulder prosthesis due to shoulder anatomy. The glenohumeral joint is the most complex joint of the human shoulder. There are various treatments for shoulder failures such as total shoulder arthroplasty, reverse total shoulder arthroplasty. Due to its reverse design than normal shoulder anatomy, reverse total shoulder arthroplasty has different physiological and biomechanical properties. Post-operative achievement of this arthroplasty is depend on improved design of reverse total shoulder prosthesis. Designation achievement can be increased by several biomechanical and computational analysis. In this study, data of human both shoulders with right side fracture was collected by 3D Computer Tomography (CT) machine in dicom format. This data transferred to 3D medical image processing software (Mimics Materilise, Leuven, Belgium) to reconstruct patient’s left and right shoulders’ bones geometry. Provided 3D geometry model of the fractured shoulder was used to constitute of reverse total shoulder prosthesis by 3-matic software. Finite element (FE) analysis was conducted for comparison of intact shoulder and prosthetic shoulder in terms of stress distribution and displacements. Body weight physiological reaction force of 800 N loads was applied. Resultant values of FE analysis was compared for both shoulders. The analysis of the performance of the reverse shoulder prosthesis could enhance the knowledge of the prosthetic design.

Keywords: reverse shoulder prosthesis, biomechanics, finite element analysis, 3D printing

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Authors: Luis Guiliana, Andrea Osorio

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The lack of comprehension of the reservoir geomechanics conditions may cause operational problems that cost to the industry billions of dollars per year. The drilling operations at the Ceuta Field, Area 2 South, Maracaibo Lake, have been very expensive due to problems associated with drilling. The principal objective of this investigation is to develop a 3D geomechanical model in this area, in order to optimize the future drillings in the field. For this purpose, a 1D geomechanical model was built at first instance, following the workflow of the MEM (Mechanical Earth Model), this consists of the following steps: 1) Data auditing, 2) Analysis of drilling events and structural model, 3) Mechanical stratigraphy, 4) Overburden stress, 5) Pore pressure, 6) Rock mechanical properties, 7) Horizontal stresses, 8) Direction of the horizontal stresses, 9) Wellbore stability. The 3D MEM was developed through the geostatistic model of the Eocene C-SUP VLG-3676 reservoir and the 1D MEM. With this data the geomechanical grid was embedded. The analysis of the results threw, that the problems occurred in the wells that were examined were mainly due to wellbore stability issues. It was determined that the stress field change as the stratigraphic column deepens, it is normal to strike-slip at the Middle Miocene and Lower Miocene, and strike-slipe to reverse at the Eocene. In agreement to this, at the level of the Eocene, the most advantageous direction to drill is parallel to the maximum horizontal stress (157º). The 3D MEM allowed having a tridimensional visualization of the rock mechanical properties, stresses and operational windows (mud weight and pressures) variations. This will facilitate the optimization of the future drillings in the area, including those zones without any geomechanics information.

Keywords: geomechanics, MEM, drilling, stress

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Authors: Pixiang Wang, Shaoyang Liu, Yucheng Peng

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Polypropylene (PP) is an essential material of numerous applications in different industrial sectors, including packaging, construction, and automotive. Because the application of homopolypropylene (HPP) is limited by its relatively low impact strength and high embrittlement temperature, various types of impact copolymer PP (ICPP) that incorporate elastomers/rubbers into HPP to increase impact strength have been successfully commercialized. Crystallization kinetics of an isotactic HPP, an ICPP, and their composites were studied in this work understand the composites’ behaviors better. The Avrami-Jeziorny model was used to describe the crystallization process. For most samples, the Avrami exponent, n, was greater than 3, indicating the crystal grew in three dimensions with spherical geometry. However, the n value could drop below 3 when the ICPP content was 80 wt.% or higher and the cooling rate was 7.5°C/min or lower, implying that the crystals could grow in two dimensions and some lamella structures could be formed under those conditions. The nucleation activity increased with the increase of the ICPP content, demonstrating that the rubber phase in the ICPP acted as a nucleation agent and facilitated the nucleation process. The decrease in crystallization rate after the ICPP content exceeded 60 wt.% might be caused by the excessive amount of crystal nuclei induced by the high ICPP content, which caused strong crystal-crystal interactions and limited the crystal growth space. The nucleation activity and the n value showed high correlations to the mechanical and thermal properties of the materials. The quantitative study of the kinetics of crystallization in this work could be a helpful reference for manufacturing ICPP and HPP/ICPP mixtures.

Keywords: polypropylene, crystallization kinetics, Avrami-Jeziorny model, crystallization activation energy, Nucleation activity

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Authors: Devendra Sillu, Shekhar Agnihotri

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The 'nano-biocatalyst' utilizes an ordered assembling of enzyme on to nanomaterial carriers to catalyze desirable biochemical kinetics and substrate selectivity. The current study describes an inter-disciplinary approach for converting agriculture waste, sugarcane bagasse into D-glucose exploiting halloysite nanotubes (HNTs) decorated cellulase enzyme as nano-biocatalytic system. Cellulase was successfully immobilized on HNTs employing polydopamine as an eco-friendly crosslinker while iron oxide nanoparticles were attached to facilitate magnetic recovery of material. The characterization studies (UV-Vis, TEM, SEM, and XRD) displayed the characteristic features of both cellulase and magnetic HNTs in the resulting nanocomposite. Various factors (i.e., working pH, temp., crosslinker conc., enzyme conc.) which may influence the activity of biocatalytic system were investigated. The experimental design was performed using Response Surface Methodology (RSM) for process optimization. Analyses data demonstrated that the nanobiocatalysts retained 80.30% activity even at elevated temperature (55°C) and excellent storage stabilities after 10 days. The repeated usage of system revealed a remarkable consistent relative activity over several cycles. The immobilized cellulase was employed to decompose agro-waste and the maximum decomposition rate of 67.2 % was achieved. Conclusively, magnetic HNTs can serve as a potential support for enzyme immobilization with long term usage, good efficacy, reusability and easy recovery from solution.

Keywords: halloysite nanotubes, enzyme immobilization, cellulase, response surface methodology, magnetic recovery

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Authors: Filip Buruiana, Alexander Hall, Reimar Hofmann, Thomas Hofmann, Silviu Ganceanu, Alexandru Tudorica

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In-memory column-stores make interactive analysis feasible for many big data scenarios. PowerDrill is a system used internally at Google for exploration in logs data. Even though it is a highly parallelized column-store and uses in memory caching, interactive response times cannot be achieved for all datasets (note that it is common to analyze data with 50 billion records in PowerDrill). In this paper, we investigate two orthogonal approaches to optimize performance at the expense of an acceptable loss of accuracy. Both approaches can be implemented as outer wrappers around existing database engines and so they should be easily applicable to other systems. For the first optimization we show that memory is the limiting factor in executing queries at speed and therefore explore possibilities to improve memory efficiency. We adapt some of the theory behind data sketches to reduce the size of particularly expensive fields in our largest tables by a factor of 4.5 when compared to a standard compression algorithm. This saves 37% of the overall memory in PowerDrill and introduces a 0.4% relative error in the 90th percentile for results of queries with the expensive fields. We additionally evaluate the effects of using sampling on accuracy and propose a simple heuristic for annotating individual result-values as accurate (or not). Based on measurements of user behavior in our real production system, we show that these estimates are essential for interpreting intermediate results before final results are available. For a large set of queries this effectively brings down the 95th latency percentile from 30 to 4 seconds.

Keywords: big data, in-memory column-store, high-performance SQL queries, approximate SQL queries

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Authors: Anil Bhandari, Imran Khan Pathan, Peeyush K. Sharma, Rakesh K. Patel, Suresh Purohit

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The purpose of this study was to prepare time and pH dependent release tablets of Ayurvedic Churna formulation and evaluate their advantages as colon targeted drug delivery system. The Vidangadi Churna was selected for this study which contains Embelin and Gallic acid. Embelin is used in Helminthiasis as therapeutic agent. Embelin is insoluble in water and unstable in gastric environment so it was formulated in time and pH dependent tablets coated with combination of two polymers Eudragit L100 and ethyl cellulose. The 150mg of core tablet of dried extract and lactose were prepared by wet granulation method. The compression coating was used in the polymer concentration of 150mg for both the layer as upper and lower coating tablet was investigated. The results showed that no release was found in 0.1 N HCl and pH 6.8 phosphate buffers for initial 5 hours and about 98.97% of the drug was released in pH 7.4 phosphate buffer in total 17 hours. The in vitro release profiles of drug from the formulation could be best expressed first order kinetics as highest linearity (r2= 0.9943). The results of the present study have demonstrated that the time and pH dependent tablets system is a promising vehicle for preventing rapid hydrolysis in gastric environment and improving oral bioavailability of Embelin and Gallic acid for treatment of Helminthiasis.

Keywords: embelin, gallic acid, Vidangadi Churna, colon targeted drug delivery

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Authors: Xi Liu, Fan Yuan

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In the evolving landscape of physics-based machine learning (PBML), particularly within fluid dynamics and its applications in electromechanical engineering, robot vision, and robot learning, achieving precision and alignment with researchers' specific needs presents a formidable challenge. In response, this work proposes a methodology that integrates neural transformation with a modified smoothed particle hydrodynamics model for generating transformed 3D fluid simulations. This approach is useful for nanoscale science, where the unique and complex behaviors of viscoelastic medium demand accurate neurally-transformed simulations for materials understanding and manipulation. In electromechanical engineering, the method enhances the design and functionality of fluid-operated systems, particularly microfluidic devices, contributing to advancements in nanomaterial design, drug delivery systems, and more. The proposed approach also aligns with the principles of PBML, offering advantages such as multi-fluid stylization and consistent particle attribute transfer. This capability is valuable in various fields where the interaction of multiple fluid components is significant. Moreover, the application of neurally-transformed hydrodynamical models extends to manufacturing processes, such as the production of microelectromechanical systems, enhancing efficiency and cost-effectiveness. The system's ability to perform neural transfer on 3D fluid scenes using a deep learning algorithm alongside physical models further adds a layer of flexibility, allowing researchers to tailor simulations to specific needs across scientific and engineering disciplines.

Keywords: physics-based machine learning, robot vision, robot learning, hydrodynamics

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Authors: S. J. Matlan, M. Mukhlisin, M. R. Taha

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Characterization of the engineering behavior of unsaturated soil is dependent on the soil-water characteristic curve (SWCC), a graphical representation of the relationship between water content or degree of saturation and soil suction. A reasonable description of the SWCC is thus important for the accurate prediction of unsaturated soil parameters. The measurement procedures for determining the SWCC, however, are difficult, expensive, and time-consuming. During the past few decades, researchers have laid a major focus on developing empirical equations for predicting the SWCC, with a large number of empirical models suggested. One of the most crucial questions is how precisely existing equations can represent the SWCC. As different models have different ranges of capability, it is essential to evaluate the precision of the SWCC models used for each particular soil type for better SWCC estimation. It is expected that better estimation of SWCC would be achieved via a thorough statistical analysis of its distribution within a particular soil class. With this in view, a statistical analysis was conducted in order to evaluate the reliability of the SWCC prediction models against laboratory measurement. Optimization techniques were used to obtain the best-fit of the model parameters in four forms of SWCC equation, using laboratory data for relatively coarse-textured (i.e., sandy) soil. The four most prominent SWCCs were evaluated and computed for each sample. The result shows that the Brooks and Corey model is the most consistent in describing the SWCC for sand soil type. The Brooks and Corey model prediction also exhibit compatibility with samples ranging from low to high soil water content in which subjected to the samples that evaluated in this study.

Keywords: soil-water characteristic curve (SWCC), statistical analysis, unsaturated soil, geotechnical engineering

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Authors: Manjitsingh Rajput

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Visual communication plays an important role in artificial intelligence (AI) because it enables machines to understand and interpret visual information, similar to how humans do. This abstract explores the importance of visual communication in AI and emphasizes the importance of various applications such as computer vision, object emphasis recognition, image classification and autonomous systems. In going deeper, with deep learning techniques and neural networks that modify visual understanding, In addition to AI programming, the abstract discusses challenges facing visual interfaces for AI, such as data scarcity, domain optimization, and interpretability. Visual communication and other approaches, such as natural language processing and speech recognition, have also been explored. Overall, this abstract highlights the critical role that visual communication plays in advancing AI capabilities and enabling machines to perceive and understand the world around them. The abstract also explores the integration of visual communication with other modalities like natural language processing and speech recognition, emphasizing the critical role of visual communication in AI capabilities. This methodology explores the importance of visual communication in AI development and implementation, highlighting its potential to enhance the effectiveness and accessibility of AI systems. It provides a comprehensive approach to integrating visual elements into AI systems, making them more user-friendly and efficient. In conclusion, Visual communication is crucial in AI systems for object recognition, facial analysis, and augmented reality, but challenges like data quality, interpretability, and ethics must be addressed. Visual communication enhances user experience, decision-making, accessibility, and collaboration. Developers can integrate visual elements for efficient and accessible AI systems.

Keywords: visual communication AI, computer vision, visual aid in communication, essence of visual communication.

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Authors: Zohreh Soleimani, Sally Salome Shahzad, Stamatis Zoras

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As a result of current energy and environmental issues, the human body is known as one of the promising candidate for converting wasted heat to electricity (Seebeck effect). Thermoelectric generator (TEG) is one of the most prevalent means of harvesting body heat and converting that to eco-friendly electrical power. However, the uneven distribution of the body heat and its curvature geometry restrict harvesting adequate amount of energy. To perfectly transform the heat radiated by the body into power, the most direct solution is conforming the thermoelectric generators (TEG) with the arbitrary surface of the body and increase the temperature difference across the thermoelectric legs. Due to this, a computational survey through COMSOL Multiphysics is presented in this paper with the main focus on the impact of integrating a flexible wearable TEG with a corrugated shaped heat sink on the module power output. To eliminate external parameters (temperature, air flow, humidity), the simulations are conducted within indoor thermal level and when the wearer is stationary. The full thermoelectric characterization of the proposed TEG fabricated by a wavy shape heat sink has been computed leading to a maximum power output of 25µW/cm2 at a temperature gradient nearly 13°C. It is noteworthy that for the flexibility of the proposed TEG and heat sink, the applicability and efficiency of the module stay high even on the curved surfaces of the body. As a consequence, the results demonstrate the superiority of such a TEG to the most state of the art counterparts fabricated with no heat sink and offer a new train of thought for the development of self-sustained and unobtrusive wearable power suppliers which generate energy from low grade dissipated heat from the body.

Keywords: device simulation, flexible thermoelectric module, heat sink, human body heat

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Authors: Rakesh Kumar, A. K. Ghosh

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The paper presents the modeling of linear and nonlinear longitudinal aerodynamics using real flight data of Hansa-3 aircraft gathered at low and high angles of attack. The Neural-Gauss-Newton (NGN) method has been applied to model the linear and nonlinear longitudinal dynamics and estimate parameters from flight data. Unsteady aerodynamics due to flow separation at high angles of attack near stall has been included in the aerodynamic model using Kirchhoff’s quasi-steady stall model. NGN method is an algorithm that utilizes Feed Forward Neural Network (FFNN) and Gauss-Newton optimization to estimate the parameters and it does not require any a priori postulation of mathematical model or solving of equations of motion. NGN method was validated on real flight data generated at moderate angles of attack before application to the data at high angles of attack. The estimates obtained from compatible flight data using NGN method were validated by comparing with wind tunnel values and the maximum likelihood estimates. Validation was also carried out by comparing the response of measured motion variables with the response generated by using estimates a different control input. Next, NGN method was applied to real flight data generated by executing a well-designed quasi-steady stall maneuver. The results obtained in terms of stall characteristics and aerodynamic parameters were encouraging and reasonably accurate to establish NGN as a method for modeling nonlinear aerodynamics from real flight data at high angles of attack.

Keywords: parameter estimation, NGN method, linear and nonlinear, aerodynamic modeling

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Authors: Komal Kumar, Sreedevi Upadhyayula

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In this study, a two-stage process was established for the synthesis of HMF esters using ionic liquid acid catalyst. Ionic liquid catalyst with different strength of the Bronsted acidity was prepared in the laboratory and characterized using 1H NMR, FT-IR, and 13C NMR spectroscopy. Solid acid catalyst from the ionic liquid catalyst was prepared using the immobilization method. The acidity of the synthesized acid catalyst was measured using Hammett function and titration method. Catalytic performance was evaluated for the biomass conversion to 5-hydroxymethylfurfural (5-HMF) and levulinic acid (LA) in methyl isobutyl ketone (MIBK)-water biphasic system. A good yield of 5-HMF and LA was found at the different composition of MIBK: Water. In the case of MIBK: Water ratio 10:1, good yield of 5-HMF was observed at ambient temperature 150˚C. Upgrading of 5-HMF into monoesters from the reaction of 5-HMF and reactants using biomass-derived monoacid were performed. Ionic liquid catalyst with -SO₃H functional group was found to be best efficient in comparative of a solid acid catalyst for the esterification reaction and biomass conversion. A good yield of 5-HMF esters with high 5-HMF conversion was found to be at 105˚C using the best active catalyst. In this process, process A was the hydrothermal conversion of cellulose and monomer into 5-HMF and LA using acid catalyst. And the process B was the esterification followed by using similar acid catalyst. All monoesters of 5-HMF synthesized here can be used in chemical, cross linker for adhesive or coatings and pharmaceutical industry. A theoretical density functional theory (DFT) study for the optimization of the ionic liquid structure was performed using the Gaussian 09 program to find out the minimum energy configuration of ionic liquid catalyst.

Keywords: biomass conversion, 5-HMF, Ionic liquid, HMF ester

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Authors: A. V. Chandewar, Sanjay Bais

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Backgound: In India, drugs of herbal origin have been used in traditional systems of medicines such as Unani and Ayurveda since ancient times. WHO limit for Escherichia coli is 101/gm cfu, for Staphylococus aureus 105/gm cfu, and for Pseudomonas aeruginosa 103/gm cfu and for Salmonella species nil cfu. WHO mentions maximum permissible limits in raw materials only for arsenic, cadmium, and lead, which amount to 1.0, 0.3, and 10 ppm, respectively. Aim: The main purpose of the investigation was to document evidence for the users, and practitioners of marketed haematinic herbal formulations. In the present study haematinic herbal formulations marketed in Yavatmal India were determined for the presence of microbial and heavy metal content. Method: The investigations were performed by using specific medias and atomic absorption spectrometry. Result: The present work indicates the presence of heavy metal contents in herbal formulations selected for study. It was found that arsenic content in formulations was below the permissible limit in all formulations. The cadmium and lead content in six formulations were above the permissible limits. Such formulations are injurious to health of patient if consumed regularly. The specific medias were used to determining the presence of Escherichia coli 4 samples, Staphylococcus aureus 3 samples, and P. aeruginosa 4 samples. The data indicated suggest that there is requirement of in process improvement to provide better quality for consumer health in order to be competitive in international markets. Summary/Conclusion: The presence of microbial and heavy metal content above WHO limits indicates that the GMP was not followed during manufacturing of herbal formulations marketed in India.

Keywords: toxicological standardization, heavy metals, microbial contamination, haematinic herbal formulations

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Authors: Bidzina Matsaberidze

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It is known that, in emergency situations, multi-attribute group decision-making (MAGDM) models are characterized by insufficient objective data and a lack of time to respond to the task. Evidence theory is an effective tool for describing such incomplete information in decision-making models when the expert and his knowledge are involved in the estimations of the MAGDM parameters. We consider an emergency decision-making model, where expert assessments on humanitarian aid from distribution centers (HADC) are represented in q-rung ortho-pair fuzzy numbers, and the data structure is described within the data body theory. Based on focal probability construction and experts’ evaluations, an objective function-distribution centers’ selection ranking index is constructed. Our approach for solving the constructed bicriteria partitioning problem consists of two phases. In the first phase, based on the covering’s matrix, we generate a matrix, the columns of which allow us to find all possible partitionings of the HADCs with the service centers. Some constraints are also taken into consideration while generating the matrix. In the second phase, based on the matrix and using our exact algorithm, we find the partitionings -allocations of the HADCs to the centers- which correspond to the Pareto-optimal solutions. For an illustration of the obtained results, a numerical example is given for the facility location-selection problem.

Keywords: emergency MAGDM, q-rung orthopair fuzzy sets, evidence theory, HADC, facility location problem, multi-objective combinatorial optimization problem, Pareto-optimal solutions

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Authors: Muhammad Zahid

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The mechanical process of smoothing and compressing a molten material by passing it through a number of pairs of heated rolls in order to produce a sheet of desired thickness is called calendering. The rolls that are in combination are called calenders, a term derived from kylindros the Greek word for the cylinder. It infects the finishing process used on cloth, paper, textiles, leather cloth, or plastic film and so on. It is a mechanism which is used to strengthen surface properties, minimize sheet thickness, and yield special effects such as a glaze or polish. It has a wide variety of applications in industries in the manufacturing of textile fabrics, coated fabrics, and plastic sheeting to provide the desired surface finish and texture. An analysis has been presented for the calendering of Pseudoplastic material. The lubrication approximation theory (LAT) has been used to simplify the equations of motion. For the investigation of the nature of the steady solutions that exist, we make use of the combination of exact solution and numerical methods. The expressions for the velocity profile, rate of volumetric flow and pressure gradient are found in the form of exact solutions. Furthermore, the quantities of interest by engineering point of view, such as pressure distribution, roll-separating force, and power transmitted to the fluid by the rolls are also computed. Some results are shown graphically while others are given in the tabulated form. It is found that the non-Newtonian parameter and Reynolds number serve as the controlling parameters for the calendering process.

Keywords: calendering, exact solutions, lubrication approximation theory, numerical solutions, pseudoplastic material

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Authors: K. G. Sorokozherdyev, E. A. Efimov

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The socio-economic development of regions and countries is an important research issue. Today, in the face of many negative events in the global and regional economies, it is especially important to identify those areas that can serve as sources of economic growth and the basis for the well-being of the population. This study aims to identify the most important sectors of the economy of the Arkhangelsk region that can contribute to the socio-economic development of the region as a whole. For research, the Arkhangelsk region was taken as one of the typical Russian regions that do not have significant reserves of hydrocarbons nor there are located any large industrial complexes. In this regard, the question of possible origins of economic growth seems especially relevant. The basis of this study constitutes the distributed lag regression model (ADL model) developed by the authors, which is based on quarterly data on the socio-economic development of the Arkhangelsk region for the period 2004-2016. As a result, we obtained three equations reflecting the dynamics of three indicators of the socio-economic development of the region -the average wage, the regional GRP, and the birth rate. The influencing factors are the shares in GRP of such sectors as agriculture, mining, manufacturing, construction, wholesale and retail trade, hotels and restaurants, as well as the financial sector. The study showed that the greatest influence on the socio-economic development of the region is exerted by such industries as wholesale and retail trade, construction, and industrial sectors. The study can be the basis for forecasting and modeling the socio-economic development of the Arkhangelsk region in the short and medium term. It also can be helpful while analyzing the effectiveness of measures aimed at stimulating those or other industries of the region. The model can be used in developing a regional development strategy.

Keywords: regional economic development, regional sectoral structure, ADL model, Arkhangelsk region

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Authors: Saurav S. Rath, Birendra K. David

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Generic pharmaceutical industry has to operate in strict timelines of product development and scale-up from lab to plant. Hence, detailed product & process understanding and implementation of appropriate mechanistic modelling and Quality-by-design (QbD) approaches are imperative in the product life cycle. This work provides example cases of such efforts in topical dosage products. Topical products are typically in the form of emulsions, gels, thick suspensions or even simple solutions. The efficacy of such products is determined by characteristics like rheology and morphology. Defining, and scaling up the right manufacturing process with a given set of ingredients, to achieve the right product characteristics presents as a challenge to the process engineer. For example, the non-Newtonian rheology varies not only with CPPs and CMAs but also is an implicit function of globule size (CQA). Hence, this calls for various mechanistic models, to help predict the product behaviour. This paper focusses on such models obtained from computational fluid dynamics (CFD) coupled with population balance modelling (PBM) and constitutive models (like shear, energy density). In a special case of the use of high shear homogenisers (HSHs) for the manufacture of thick emulsions/gels, this work presents some findings on (i) scale-up algorithm for HSH using shear strain, a novel scale-up parameter for estimating mixing parameters, (ii) non-linear relationship between viscosity and shear imparted into the system, (iii) effect of hold time on rheology of product. Specific examples of how this approach enabled scale-up across 1L, 10L, 200L, 500L and 1000L scales will be discussed.

Keywords: computational fluid dynamics, morphology, quality-by-design, rheology

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Authors: Svetlana Gudkova

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The Internet of Things experiences a rapid growth bringing inevitable changes into many spheres of human activities. As the Internet has changed the social and business landscape, IoT as its extension, can bring much more profound changes in economic value creation and competitiveness of the economies. It has been already recognized as the next industrial revolution. However, the development of IoT is in a great extent stimulated by the entrepreneurial activity. To expand and reach its full potential it requires proactive entrepreneurs, who explore the potential and create innovative ideas pushing the boundaries of IoT technologies' application further. The goal of the research is to analyze, how entrepreneurs utilize the opportunities created by IoT and how do they stimulate the development of IoT through discovering of new ways of generating economic value and creating opportunities, which attract other entrepreneurs. The qualitative research methods have been applied to prepare the case studies. Entrepreneurs are recognized as an engine of economic growth. They introduce innovative products and services into the market through the creation of a new combination of the existing resources and utilizing new knowledge. Entrepreneurs not only create economic value but what is more important, they challenge the existing business models and invent new ways of value creation. Through identification and exploitation of entrepreneurial opportunities, they create new opportunities for other entrepreneurs. It makes the industry more attractive to other profit/innovation-driven start-ups. IoT creates numerous opportunities for entrepreneurs in the different industries. Smart cities, healthcare, manufacturing, retail, agriculture, smart vehicles and smart buildings benefit a lot from IoT-based breakthrough innovations introduced by entrepreneurs. They reinvented successfully the business models and created new entrepreneurial opportunities for other start-ups to introduce next innovations.

Keywords: entrepreneurship, internet of things, breakthrough innovations, start-ups

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Authors: A. Rong, P. B. Luh, R. Lahdelma

Abstract:

High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

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Authors: Mukesh Khadka, Alexander Paz, Hanns de la Fuente-Mella

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Typically, pavement performance models are developed in two steps: (i) pavement segments with similar characteristics are grouped together to form a cluster, and (ii) the corresponding performance models are developed using statistical techniques. A challenge is to select the characteristics that define clusters and the segments associated with them. If inappropriate characteristics are used, clusters may include homogeneous segments with different performance behavior or heterogeneous segments with similar performance behavior. Prediction accuracy of performance models can be improved by grouping the pavement segments into more uniform clusters by including both characteristics and a performance measure. This grouping is not always possible due to limited information. It is impractical to include all the potential significant factors because some of them are potentially unobserved or difficult to measure. Historical performance of pavement segments could be used as a proxy to incorporate the effect of the missing potential significant factors in clustering process. The current state-of-the-art proposes Clusterwise Linear Regression (CLR) to determine the pavement clusters and the associated performance models simultaneously. CLR incorporates the effect of significant factors as well as a performance measure. In this study, a mathematical program was formulated for CLR models including multiple explanatory variables. Pavement data collected recently over the entire state of Nevada were used. International Roughness Index (IRI) was used as a pavement performance measure because it serves as a unified standard that is widely accepted for evaluating pavement performance, especially in terms of riding quality. Results illustrate the advantage of the using CLR. Previous studies have used CLR along with experimental data. This study uses actual field data collected across a variety of environmental, traffic, design, and construction and maintenance conditions.

Keywords: clusterwise regression, pavement management system, performance model, optimization

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Authors: Zhongnan Ye, Xiaoyi Liu, Shu-Chien Hsu

Abstract:

Rapid urbanization has led to a significant increase in construction and demolition waste (C&D waste), underscoring the need for sustainable waste management strategies in the construction industry. Aiming to enhance the sustainability of urban construction practices, this study develops an optimization model to effectively suggest the optimal recycling and reuse strategies for C&D waste, including concrete and steel. By employing Life Cycle Assessment (LCA), the model evaluates the environmental impacts of adopted construction materials throughout their lifecycle. The model optimizes the quantity of materials to recycle or reuse, the selection of specific recycling and reuse processes, and logistics decisions related to the transportation and storage of recycled materials with the objective of minimizing the overall environmental impact, quantified in terms of carbon emissions, energy consumption, and associated costs, while adhering to a range of constraints. These constraints include capacity limitations, quality standards for recycled materials, compliance with environmental regulations, budgetary limits, and temporal considerations such as project deadlines and material availability. The strategies are expected to be both cost-effective and environmentally beneficial, promoting a circular economy within the construction sector, aligning with global sustainability goals, and providing a scalable framework for managing construction waste in densely populated urban environments. The model is helpful in reducing the carbon footprint of construction projects, conserving valuable resources, and supporting the industry’s transition towards a more sustainable future.

Keywords: circular construction, construction and demolition waste, life cycle assessment, material recycling

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Authors: Mihai Caramihai, Dan Vasilescu

Abstract:

The main research objective of the experimental bioprocess analyzed in this paper was to obtain large biomass quantities. The bioprocess is performed in 100 L Bioengineering bioreactor with 42 L cultivation medium made of peptone, meat extract and sodium chloride. The reactor was equipped with pH, temperature, dissolved oxygen, and agitation controllers. The operating parameters were 37 oC, 1.2 atm, 250 rpm and air flow rate of 15 L/min. The main objective of this paper is to present a case study to demonstrate that intelligent control, describing the complexity of the biological process in a qualitative and subjective manner as perceived by human operator, is an efficient control strategy for this kind of bioprocesses. In order to simulate the bioprocess evolution, an intelligent control structure, based on fuzzy logic has been designed. The specific objective is to present a fuzzy control approach, based on human expert’ rules vs. a modeling approach of the cells growth based on bioprocess experimental data. The kinetic modeling may represent only a small number of bioprocesses for overall biosystem behavior while fuzzy control system (FCS) can manipulate incomplete and uncertain information about the process assuring high control performance and provides an alternative solution to non-linear control as it is closer to the real world. Due to the high degree of non-linearity and time variance of bioprocesses, the need of control mechanism arises. BIOSIM, an original developed software package, implements such a control structure. The simulation study has showed that the fuzzy technique is quite appropriate for this non-linear, time-varying system vs. the classical control method based on a priori model.

Keywords: intelligent, control, fuzzy model, bioprocess optimization

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Authors: Shweta Singh, Sudaman Katti

Abstract:

The most well-known sequence models make use of complex recurrent neural networks in an encoder-decoder configuration. The model used in this research makes use of a transformer, which is based purely on a self-attention mechanism, without relying on recurrence at all. More specifically, encoders and decoders which make use of self-attention and operate based on a memory, are used. In this research work, results for various 3D visual and non-visual reinforcement learning tasks designed in Unity software were obtained. Convolutional neural networks, more specifically, nature CNN architecture, are used for input processing in visual tasks, and comparison with standard long short-term memory (LSTM) architecture is performed for both visual tasks based on CNNs and non-visual tasks based on coordinate inputs. This research work combines the transformer architecture with the proximal policy optimization technique used popularly in reinforcement learning for stability and better policy updates while training, especially for continuous action spaces, which are used in this research work. Certain tasks in this paper are long horizon tasks that carry on for a longer duration and require extensive use of memory-based functionalities like storage of experiences and choosing appropriate actions based on recall. The transformer, which makes use of memory and self-attention mechanism in an encoder-decoder configuration proved to have better performance when compared to LSTM in terms of exploration and rewards achieved. Such memory based architectures can be used extensively in the field of cognitive robotics and reinforcement learning.

Keywords: convolutional neural networks, reinforcement learning, self-attention, transformers, unity

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Authors: Ju-Hong Lee, Yi-Lin Shieh

Abstract:

Two-dimensional (2-D) quadrature mirror filter (QMF) banks have been widely considered for high-quality coding of image and video data at low bit rates. Without implementing subband coding, a 2-D QMF bank is required to have an exactly linear-phase response without magnitude distortion, i.e., the perfect reconstruction (PR) characteristics. The design problem of 2-D QMF banks with the PR characteristics has been considered in the literature for many years. This paper presents a transformation approach for designing 2-D two-channel QMF banks. Under a suitable one-dimensional (1-D) to two-dimensional (2-D) transformation with a specified decimation/interpolation matrix, the analysis and synthesis filters of the QMF bank are composed of 1-D causal and stable digital allpass filters (DAFs) and possess the 2-D doubly complementary half-band (DC-HB) property. This facilitates the design problem of the two-channel QMF banks by finding the real coefficients of the 1-D recursive DAFs. The design problem is formulated based on the minimax phase approximation for the 1-D DAFs. A novel objective function is then derived to obtain an optimization for 1-D minimax phase approximation. As a result, the problem of minimizing the objective function can be simply solved by using the well-known weighted least-squares (WLS) algorithm in the minimax (L∞) optimal sense. The novelty of the proposed design method is that the design procedure is very simple and the designed 2-D QMF bank achieves perfect magnitude response and possesses satisfactory phase response. Simulation results show that the proposed design method provides much better design performance and much less design complexity as compared with the existing techniques.

Keywords: Quincunx QMF bank, doubly complementary filter, digital allpass filter, WLS algorithm

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Authors: K. Dhanalakshmi, N. Deepak, E. Manikandan, S. Kanagaraj, M. Sulthan Ariff Rahman, P. Chilambarasan C. Abhimanyu, C. A. Akaash Emmanuel Raj, V. R. Sanal Kumar

Abstract:

In this paper using a validated double precision, density-based implicit standard k-ε model, the detailed 2D and 3D numerical studies have been carried out to examine the external flow choking at wing-in-ground (WIG) effect craft. The CFD code is calibrated using the exact solution based on the Sanal flow choking condition for adiabatic flows. We observed that at the identical WIG effect conditions the numerically predicted 2D boundary layer blockage is significantly higher than the 3D case and as a result, the airfoil exhibited an early external flow choking than the corresponding wing, which is corroborated with the exact solution. We concluded that, in lieu of the conventional 2D numerical simulation, it is invariably beneficial to go for a realistic 3D simulation of the wing in ground effect, which is analogous and would have the aspects of a real-time parametric flow. We inferred that under the identical flying conditions the chances of external flow choking at WIG effect is higher for conventional aircraft than an aircraft facilitating a divergent channel effect at the bottom surface of the fuselage as proposed herein. We concluded that the fuselage and wings integrated geometry optimization can improve the overall aerodynamic performance of WIG craft. This study is a pointer to the designers and/or pilots for perceiving the zone of danger a priori due to the anticipated external flow choking at WIG effect craft for safe flying at the close proximity of the terrain and the dynamic surface of the marine.

Keywords: boundary layer blockage, chord dominated ground effect, external flow choking, WIG effect

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Authors: H. J. Liu, Y. A. Chan, C. K. Pai, K. C. Tseng, Y. H. Chen, Y. L. Chan, T. C. Kuo

Abstract:

To satisfy the mission requirement of the FORMOSAT-7 project, NSPO has initialized a self-reliant development on satellite propulsion technology. A trade-off study on different types of on-board propulsion system has been done. A green propellant, high-concentration hydrogen peroxide (H2O2 hereafter), is chosen in this research because it is ITAR-free, nontoxic and easy to produce. As the components designed for either cold gas or hydrazine propulsion system are not suitable for H2O2 propulsion system, the primary objective of the research is to develop the components compatible with H2O2. By cooperating with domestic research institutes and manufacturing vendors, several prototype components, including a diaphragm-type tank, pressure transducer, ball latching valve, and one-Newton thruster with catalyst bed, were manufactured, and the functional tests were performed successfully according to the mission requirements. The requisite environmental tests, including hot firing test, thermal vaccum test, vibration test and compatibility test, are prepared and will be to completed in the near future. To demonstrate the subsystem function, an Air-Bearing Thrust Stand (ABTS) and a real-time Data Acquisition & Control System (DACS) were implemented to assess the performance of the proposed H2O2 propulsion system. By measuring the distance that the thrust stand has traveled in a given time, the thrust force can be derived from the kinematics equation. To validate the feasibility of the approach, it is scheduled to assess the performance of a cold gas (N2) propulsion system prior to the H2O2 propulsion system.

Keywords: FORMOSAT-7, green propellant, Hydrogen peroxide, thruster

Procedia PDF Downloads 432