Search results for: target product profile

Authors: Jiexiu Chen

Abstract:

This research aims to examine several vital issues relating to the foreign scholars’ cross-cultural adaptation in China, including how they perceive about the adaptation process, what the affecting factors are in the adaptation, and which strategies they will apply to deal with perceived cultural differences. The target population of this research is academics regularly working or long-term visiting in these joint colleges, and semi-structured interviews are used in data collection. Moreover, the theoretical perspectives mainly include Ward’s sociocultural and psychological adaptation theory, Berry’s adaptation strategies and Black and his colleague’s expatriate’s adjustment model. This research offers an in-depth profile as well as theory-based analysis about this unique group, and the results of this research are profound in offering directory suggestions for foreign scholars to facilitate their adaptation in China better and for the Chinese universities to eliminate intercultural obstacles, and optimize the international cooperation programs in China.

Keywords: cross-cultural adaptation, foreign scholars, expatriates

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Authors: N. Dahbi, D. E. Arafah

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Cd1−xZnxS thins films have been fabricated from ZnS/CdS/ZnS multilayer thin film systems, by using the vacuum deposition method; the Rutherford back-scattering (RBS) technique have been applied in order to determine the: structure, composition, depth profile, and stoichiometric of these films. The influence of the chemical and heat treatments on the produced films also have been investigated; the RBS spectra of the films showed that homogenous Cd1−xZnxS can be synthesized with x=0.45.

Keywords: Cd1−xZnxS, chemical treatment, depth profile, heat treatment, RBS, RUMP simulation, thin film, vacuum deposition, ZnS/CdS/ZnS

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Authors: S. Mawlood, L. Denanny, N. Watson, B. Pickard

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DNA analysis has been widely accepted as providing valuable evidence concerning the identity of the source of biological traces. Our work has showed that DNA samples can survive on cartridges even after firing. The study also raised the possibility of determining other information such as the age of the donor. Such information may be invaluable in certain cases where spent cartridges from automatic weapons are left behind at the scene of a crime. In spite of the nature of touch evidence and exposure to high chamber temperatures during shooting, we were still capable to retrieve enough DNA for profile typing. In order to estimate age of contributor, DNA methylation levels were analyzed using EpiTect system for retrieved DNA. However, results were not conclusive, due to low amount of input DNA.

Keywords: DNA profile, DNA Methylation, fired cartridge, touch sample

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Authors: Munu Fritz-Austin Ndam

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Although the Cameroonian system of farming is considered as the first generation, the primary actors here involved have not yet understood the meaning of adding value to the product or produce they produce. The challenge here is for everyone who practices agriculture as an income generating activity in Cameroon to be able to understand the concept of value-added products and to know how to go about it. Recent studies have shown that these farmers who depend on agriculture as their main income generation activity make a great loss out of it because they don’t have the means to either transport their produce to the appropriate market, they don’t the knowledge on how to transform it, or they don’t have a means of conserving the product for a longer duration. It is important to note that after a thorough evaluation of the activity carried out, the final added value product sold is of great benefit not only to the producer but the buyer and the population at large. In my proposed prestation, I will discuss how the transformation activity will have a positive impact on the lives of farmers and the buyers and, most importantly, describe the methodology and procedure which is followed before the tubers (banana, Plantain, potato)is transformed into the finished or semi-finished product.

Keywords: transformation, sustainability, development, consumption

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Authors: Jagannath Singh, Durga Prasad Mohapatra

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Software refactoring is very essential for maintaining the software quality. It is an usual practice that we first design the software and then go for coding. But after coding is completed, if the requirement changes slightly or our expected output is not achieved, then we change the codes. For each small code change, we cannot change the design. In course of time, due to these small changes made to the code, the software design decays. Software refactoring is used to restructure the code in order to improve the design and quality of the software. In this paper, we propose an approach for performing code refactoring. We use slice-based cohesion metrics to identify the target methods which requires refactoring. After identifying the target methods, we use program slicing to divide the target method into two parts. Finally, we have used the concepts of Aspects to adjust the code structure so that the external behaviour of the original module does not change.

Keywords: software refactoring, program slicing, AOP, cohesion metrics, code restructure, AspectJ

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Authors: Luis N. Pereira, Marco P. Carrasco

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Dynamic pricing is a revenue management strategy in which hotel suppliers define, over time, flexible and different prices for their services for different potential customers, considering the profile of e-consumers and the demand and market supply. This means that the fundamentals of dynamic pricing are based on economic theory (price elasticity of demand) and market segmentation. This study aims to define a dynamic pricing strategy and a contextualized offer to the e-consumers profile in order to improve the number of reservations of an online distribution channel. Segmentation methods (hierarchical and non-hierarchical) were used to identify and validate an optimal number of market segments. A profile of the market segments was studied, considering the characteristics of the e-consumers and the probability of reservation a room. In addition, the price elasticity of demand was estimated for each segment using econometric models. Finally, predictive models were used to define rules for classifying new e-consumers into pre-defined segments. The empirical study illustrates how it is possible to improve the intelligence of an online distribution channel system through an optimal dynamic pricing strategy and a contextualized offer to the profile of each new e-consumer. A database of 11 million e-consumers of an online distribution channel was used in this study. The results suggest that an appropriate policy of market segmentation in using of online reservation systems is benefit for the service suppliers because it brings high probability of reservation and generates more profit than fixed pricing.

Keywords: dynamic pricing, e-consumers segmentation, online reservation systems, predictive analytics

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Authors: Kai-Yao Huang, Tzong-Yi Lee, Pin-Hao Ho, Tzu-Hao Chang, Cheng-Wei Chang

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Background: Human cytomegalovirus (HCMV) infects much people around the world, and there were many researches mention that many diseases were caused by HCMV. To understand the mechanism of HCMV lead to diseases during infection. We observe a microRNA (miRNA) – miRNA interaction between HCMV and host during infection. We found HCMV miRNA sequence component complementary with host miRNA precursors, and we also found that the host miRNA abundances were decrease in HCMV infection. Hence, we focus on the host miRNA which may target by the other HCMV miRNA to find theirs target mRNAs expression and analysis these mRNAs affect what kind of signaling pathway. Interestingly, we found the affected mRNA play an important role in some diseases related pathways, and these diseases had been annotated by HCMV infection. Results: From our analysis procedure, we found 464 human miRNAs might be targeted by 26 HCMV miRNAs and there were 291 human miRNAs shows the concordant decrease trend during HCMV infection. For case study, we found hcmv-miR-US22-5p may regulate hsa-mir-877 and we analysis the KEGG pathway which built by hsa-mir-877 validate target mRNA. Additionally, through survey KEGG Disease database found that these mRNA co-regulate some disease related pathway for instance cancer, nerve disease. However, there were studies annotated that HCMV infection casuse cancer and Alzheimer. Conclusions: This work supply a different scenario of miRNA target interactions(MTIs). In previous study assume miRNA only target to other mRNA. Here we wonder there is possibility that miRNAs might regulate non-mRNA targets, like other miRNAs. In this study, we not only consider the sequence similarity with HCMV miRNAs and human miRNA precursors but also the expression trend of these miRNAs. Then we analysis the human miRNAs validate target mRNAs and its associated KEGG pathway. Finally, we survey related works to validate our investigation.

Keywords: human cytomegalovirus, HCMV, microRNA, miRNA

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Authors: Anne Theresa Eidhoff, Sarah E. Stief, Markus Voeth, Sarah Gundlach

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With digitalization increasingly changing the rules of competition, firms face the need to adapt and assimilate digital technologies in order to remain competitive. Firms can choose from various possibilities to integrate digital technologies including the option to embed digital technologies aiming to innovate products or to develop digital products. However, the question of which specific factors influence a firm’s decision to pursue digital product innovation remains unanswered in research. By adopting the Technology-Organization-Environment (TOE)-framework we have designed a qualitative exploratory study including eleven German practitioners to investigate relevant contingency factors. Our results indicate that the most critical factors for a company’s decision to pursue digital product innovation can be found in the technological and environmental dimensions, namely customers, competitive pressure, technological change, as well as digitalization fit. 

Keywords: digital innovation, digitalization, product innovation, TOE-framework

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Authors: Hao Yuan, Yongjian Shen, Xiangjun He, Yuheng Li, Zhouzhou Zhang, Pengyu Zhang, Minkang Cai

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Remote sensing data can provide support for decision-making in disaster assessment or disaster relief. The traditional processing methods of sensitive targets in remote sensing mapping are mainly based on manual retrieval and image editing tools, which are inefficient. Methods based on deep learning for sensitive target hiding are faster and more flexible. But these methods have disadvantages in training time and cost of calculation. This paper proposed a target hiding model Self Attention (SA) Deepfill, which used self-attention modules to replace part of gated convolution layers in image inpainting. By this operation, the calculation amount of the model becomes smaller, and the performance is improved. And this paper adds free-form masks to the model’s training to enhance the model’s universal. The experiment on an open remote sensing dataset proved the efficiency of our method. Moreover, through experimental comparison, the proposed method can train for a longer time without over-fitting. Finally, compared with the existing methods, the proposed model has lower computational weight and better performance.

Keywords: remote sensing mapping, image inpainting, self-attention mechanism, target hiding

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Authors: Vitor Carneiro, Augusto Barata Da Rocha, Barbara Rangel, Jorge Lino Alves

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In the European Union countries, Small and Medium-Sized Enterprises (SME’s) have an important contribution to economic activity and to the Gross Domestic Product (GDP). The implementation of design practices in SME’s is often a difficult task due to resources limitations. Unlike large companies, their product development and innovation processes frequentlylack adequate planning and systematic procedures. Design management interest has grown exponentially in recent years, but as it is a recent topic there is an absence of systematic methodologies to implement design management in SME’s with little or no design experience. This work presents a contribution to improve and optimize the process of design integration and management in SME’s. A review analysis is presented to select relevant articles on the subject, review and classify the main published contributions. Based on the selected articles content it was possible to identify five main themes related to the subject under analysis: Design Function Organization, Design Management Integration, Design Management Capabilities, Managing Design Projects, and Tools and Methods. Design management is discussed from different perspectives depending on the focus on which it is placed, whether in a design or management perspective, leading to different visions and definitions: from a more upstream strand at the intersection of design and the organization's strategic management (strategic design management) to a more downstream strand related to project management and design process (design management operational). The review analysis of the selected articles allowed the identification of a high level of complexity of connections and parameters in the design management during the product development process in the context of SME’s. Within each group of the five main themes, several sub-themes, directly or indirectly related, should be considered.Sub-connections also occur between sub-themes of different themes creating a complex and intricate web of connections. This complexity of connections is often the main obstacle to conduct design management and product development efficiently. This work proposes a formulation of a systematic methodological approach to optimize the integrated project and the management and control of the product development process among SME's. The implementation of this formulation will improve the integration of design management in the product development and innovation process in SME’s.

Keywords: design management, product development, product innovation, SME’s.

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Authors: Pimploi Tirastittam, Phutthiwat Waiyawuththanapoom, Manop Tirastittam

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Traceability system is one of the tools which can ensure the product’s confident of the consumer as it can trace the product back to its origin and can reduce the operation cost of recall. Nowadays, there are so many technologies which can be applied to the traceability system and also able to increase the efficiency of the system such as QR Code, barcode, GS1 and GTIN. As the result, this research is aimed to study and design the information technology pattern that suits for the traceability of Thailand’s orchid because Thailand’s orchid is the popular export product for Japan, USA, China, Netherlands and Italy. This study will enhance the value of Thailand’s orchid and able to prevent the unexpected event of the defects or damaged product. The traceability pattern was received IOC test from 12 experts from 4 fields of study which are traceability field, information technology field, information communication technology field and orchid export field. The result of the in-depth interview and questionnaire showed that the technology which most compatibility with the traceability system is the QR code. The mean of the score was 4.25 and the standard deviation was 0.5 as the QR code is the new technology and user-friendly. The traceability system should start from the farm to the consumer in the consuming country as the traceability system will enhance the quality level of the product and increase the value of its as well. The other outcome from this research is the supply chain model of Thailand’s Orchid along with the system architecture and working system diagram.

Keywords: exporting, information technology pattern, orchid, traceability

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Authors: Koirala Abarodh, Maghaiya Ujjwal, Guragain Phani Raj

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This analysis focuses on defining the spectrum evaluation model for telecom operators in terms of total cost of ownership (TCO). A quantitative approach for specific case analysis research methodology was used for identifying the results. Specific input parameters like target User experience, year on year traffic growth, capacity site limit per year, target additional spectrum type, bandwidth, spectrum efficiency, UE penetration have been used for the spectrum evaluation process and desired outputs in terms of the number of sites, capex in USD and required spectrum bandwidth have been calculated. Furthermore, this study gives a comparison of capex investment for target growth with and without addition spectrum. As a result, the combination of additional spectrum bands of 700 and 2600 MHz has a better evaluation in terms of TCO and performance. It is our recommendation to use these bands for expansion rather than expansion in the current 1800 and 2100 bands.

Keywords: spectrum, capex planning, case study methodology, TCO

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Authors: Jean Berger, Nassirou Lo, Martin Noel

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Perfectly suited for natural or man-made emergency and disaster management situations such as flood, earthquakes, tornadoes, or tsunami, multi-target search path planning for a team of rescue agents is known to be computationally hard, and most techniques developed so far come short to successfully estimate optimality gap. A novel mixed-integer linear programming (MIP) formulation is proposed to optimally solve the multi-target multi-agent discrete search and rescue (SAR) path planning problem. Aimed at maximizing cumulative probability of successful target detection, it captures anticipated feedback information associated with possible observation outcomes resulting from projected path execution, while modeling agent discrete actions over all possible moving directions. Problem modeling further takes advantage of network representation to encompass decision variables, expedite compact constraint specification, and lead to substantial problem-solving speed-up. The proposed MIP approach uses CPLEX optimization machinery, efficiently computing near-optimal solutions for practical size problems, while giving a robust upper bound obtained from Lagrangean integrality constraint relaxation. Should eventually a target be positively detected during plan execution, a new problem instance would simply be reformulated from the current state, and then solved over the next decision cycle. A computational experiment shows the feasibility and the value of the proposed approach.

Keywords: search path planning, search and rescue, multi-agent, mixed-integer linear programming, optimization

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Authors: Nessa-Amie T. Peñaflor, Antonio Cinto

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This is a descriptive research on the level of math anxiety and mathematics misconceptions in algebra. This research is composed of four parts: (1) analysis of the level of anxiety of the respondents; (2) analysis of the common mathematical misconceptions in algebra; (3) relationship of socio-demographic profile in math anxiety and mathematical misconceptions and (4) analysis of the relationship of math anxiety and misconceptions in algebra. Through the demographic profile questionnaire it was found out that most of the respondents were female. Majority had ages that ranged from 13-15. Most of them had parents who finished secondary education. The biggest portion of Grade Seven students where from families with annual family income ranging from PhP 100, 000 to PhP 299, 999. Most of them came from public school. Mathematics Anxiety Scale for Secondary and Senior Secondary School Students (MAS) and set of 10 open-ended algebraic expressions and polynomials were also administered to determine the anxiety level and the common misconceptions in algebra. Data analysis revealed that respondents had high anxiety in mathematics. Likewise, the common mathematical misconceptions of the Grade Seven students were: combining unlike terms; multiplying the base and exponents; regarding the variable x as 0; squaring the first and second terms only in product of two binomials; wrong meaning attached to brackets; writing the terms next to each other but not simplifying in using the FOIL Method; writing the literal coefficient even if the numerical coefficient is 0; and dividing the denominator by the numerator when the numerical coefficient in the numerator is smaller than the numerical coefficient of the denominator. Results of the study show that the socio-demographic characteristics were not related to mathematics anxiety and misconceptions. Furthermore, students from higher section had high anxiety than those students on the lower section. Thus, belonging to higher or lower section may affect the mathematical misconceptions of the respondents.

Keywords: algebra, grade 7 math, math anxiety, math misconceptions

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Authors: K. Eshwara Prasad, R. Raman Goud, Swadesh Kumar Singh, N. Sateesh

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In the present work forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretchforming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening COEFFICIENT (n) and normal anisotropy (r−).Mechanical properties of EDD steel from room temperature to 4500C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy(r-) and strength coefficient of the material. Also the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, microhardness, strain distribution profile, stretch forming

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Authors: Giorgio Visentin, Inna S. Kalinina, Alexei A. Buchachenko

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In the ambit of intermolecular interactions, a combination rule is defined as a relation linking a potential parameter for the interaction of two unlike species with the same parameters for interaction pairs of like species. Some of their most exemplificative applications cover the construction of molecular dynamics force fields and dispersion-corrected density functionals. Here, an extended combination rule is proposed, relating the dipole-dipole dispersion coefficients for the interaction of like target species to the same coefficients for the interaction of the target and a set of partner species. The rule can be devised in two different ways, either by uniform discretization of the Casimir-Polder integral on a Gauss-Legendre quadrature or by relating the dynamic polarizabilities of the target and the partner species. Both methods return the same system of linear equations, which requires the knowledge of the dispersion coefficients for interaction between the partner species to be solved. The test examples show a high accuracy for dispersion coefficients (better than 1% in the pristine test for the interaction of Yb atom with rare gases and alkaline-earth metal atoms). In contrast, the rule does not ensure correct monotonic behavior of the dynamic polarizability of the target species. Acknowledgment: The work is supported by Russian Science Foundation grant # 17-13-01466.

Keywords: combination rule, dipole-dipole dispersion coefficient, Casimir-Polder integral, Gauss-Legendre quadrature

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Authors: Eshwara Prasad Koorapati, R. Raman Goud, Swadesh Kumar Singh

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In the present work forming limit diagrams and strain distribution profile diagrams for extra deep drawing steel at room and elevated temperatures have been determined experimentally by conducting stretch forming experiments by using designed and fabricated warm stretch forming tooling setup. With the help of forming Limit Diagrams (FLDs) and strain distribution profile diagrams the formability of Extra Deep Drawing steel has been analyzed and co-related with mechanical properties like strain hardening coefficient (n) and normal anisotropy (r−).Mechanical properties of EDD steel from room temperature to 4500 C were determined and discussed the impact of temperature on the properties like work hardening exponent (n) anisotropy (r-) and strength coefficient of the material. Also, the fractured surfaces after stretching have undergone the some metallurgical investigations and attempt has been made to co-relate with the formability of EDD steel sheets. They are co-related and good agreement with FLDs at various temperatures.

Keywords: FLD, micro hardness, strain distribution profile, stretch forming

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Authors: Parth Shah

Abstract:

The author examines the recent trend where business organizations are significantly reducing their developmental cycle times to stay competitive in today’s global marketspace. The author proposes a rapid systems engineering framework to address late design changes and allow for flexibility (i.e. to react to unexpected or late changes and its impacts) during the product development cycle using a Systems Engineering approach. A System Engineering approach is crucial in today’s product development to deliver complex products into the marketplace. Design changes can occur due to shortened timelines and also based on initial consumer feedback once a product or service is in the marketplace. The ability to react to change and address customer expectations in a responsive and cost-efficient manner is crucial for any organization to succeed. Past literature, research, and methods such as concurrent development, simultaneous engineering, knowledge management, component sharing, rapid product integration, tailored systems engineering processes, and studies on reducing product development cycles all suggest a research gap exist in specifically addressing late design changes due to the shortening of life cycle environments in increasingly competitive markets. The author’s research suggests that 1) product development cycles time scales are now measured in months instead of years, 2) more and more products have interdepended systems and environments that are fast-paced and resource critical, 3) product obsolesce is higher and more organizations are releasing products and services frequently, and 4) increasingly competitive markets are leading to customization based on consumer feedback. The author will quantify effectiveness with respect to success factors such as time-to-market, return-of-investment, life cycle time and flexibility in late design changes by complexity of product or service, number of late changes and ability to react and reduce late design changes.

Keywords: product development, rapid systems engineering, scalability, systems engineering, systems integration, systems life cycle

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Authors: M. Khajezadeh, M. Saied Fallah Niasar, S. Ali Asli, D. Davani Davari, M. Godarzi, Y. Asgari

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This study aims to explore the joint application of both Boston and Ansoff matrices in the operational development of the product. We conduct deep analysis, by utilizing the Artificial Neural Network, to predict the position of the product in the market while the company is interested in increasing its share. The data are gathered from two industries, called hygiene and detergent. In doing so, the effort is being made by investigating the behavior of top player companies and, recommend strategic orientations. In conclusion, this combination analysis is appropriate for operational development; as well, it plays an important role in providing the position of the product in the market for both hygiene and detergent industries. More importantly, it will elaborate on the company’s strategies to increase its market share related to a combination of the Boston Consulting Group (BCG) Matrix and Ansoff Matrix.

Keywords: artificial neural network, portfolio analysis, BCG matrix, Ansoff matrix

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Authors: Ziyu Diao, Yanyan Zhang, Zhentao Liu, Ruidong Yan

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The update frequency of wear profile in main bearing wear prognosis of internal combustion engine plays an important role in the calculation efficiency and accuracy. In order to investigate the appropriate cycle index of the simplified working condition of wear simulation, the main bearing-crankshaft journal friction pair of a diesel engine in service was studied in this paper. The method of multi-body dynamics simulation was used, and the wear prognosis model of the main bearing was established. Several groups of cycle indexes were set up for the wear calculation, and the maximum wear depth and wear profile were compared and analyzed. The results showed that when the cycle index reaches 3, the maximum deviation rate of the maximum wear depth is about 2.8%, and the maximum deviation rate comes to 1.6% when the cycle index reaches 5. This study provides guidance and suggestions for the optimization of wear prognosis by selecting appropriate value of cycle index according to the requirement of calculation cost and accuracy of the simulation work.

Keywords: cycle index, deviation rate, wear calculation, wear profile

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Authors: Leveque Benjamin, Rabaud Suzanne, Anest Hugo, Catalan Caroline, Neveux Guillaume

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Human products consumption is one of the main drivers of biodiversity loss. However, few pertinent ecological indicators regarding product life cycle impact on species and ecosystems have been built. Life cycle assessment (LCA) methodologies are well under way to conceive standardized methods to assess this impact, by taking already partially into account three of the Millennium Ecosystem Assessment pressures (land use, pollutions, climate change). Coupling LCA and ecological data and methods is an emerging challenge to develop a product biodiversity footprint. This approach was tested on three case studies from food processing, textile, and cosmetic industries. It allowed first to improve the environmental relevance of the Potential Disappeared Fraction of species, end-point indicator typically used in life cycle analysis methods, and second to introduce new indicators on overexploitation and invasive species. This type of footprint is a major step in helping companies to identify their impacts on biodiversity and to propose potential improvements.

Keywords: biodiversity, companies, footprint, life cycle assessment, products

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Authors: Michael Ayomoh, Adriaan Roux, Oyindamola Omotuyi

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This paper presents an efficient robot navigation model in a multi-target domain amidst static and dynamic workspace obstacles. The problem is that of developing an optimal algorithm to minimize the total travel time of a robot as it visits all target points within its task domain amidst unknown workspace obstacles and finally return to its initial position. In solving this problem, a classical algorithm was first developed to compute the optimal number of paths to be travelled by the robot amidst the network of paths. The principle of shortest distance between robot and targets was used to compute the target point visitation order amidst workspace obstacles. Algorithm premised on the standard polar coordinate system was developed to determine the length of obstacles encountered by the robot hence giving room for a geometrical estimation of the total surface area occupied by the obstacle especially when classified as a relevant obstacle i.e. obstacle that lies in between a robot and its potential visitation point. A stochastic model was developed and used to estimate the likelihood of a dynamic obstacle bumping into the robot’s navigation path and finally, the navigation/obstacle avoidance algorithm was hinged on the hybrid virtual force field (HVFF) method. Significant modelling constraints herein include the choice of navigation path to selected target points, the possible presence of static obstacles along a desired navigation path and the likelihood of encountering a dynamic obstacle along the robot’s path and the chances of it remaining at this position as a static obstacle hence resulting in a case of re-routing after routing. The proposed algorithm demonstrated a high potential for optimal solution in terms of efficiency and effectiveness.

Keywords: multi-target, mobile robot, optimal path, static obstacles, dynamic obstacles

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Authors: Anika Chebrolu

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Mono-targeted drugs can be of limited efficacy against complex diseases. Recently, multi-target drug design has been approached as a promising tool to fight against these challenging diseases. However, the scope of current computational approaches for multi-target drug design is limited. DeepLig presents a de-novo drug discovery platform that uses reinforcement learning to generate and optimize novel, potent, and multitargeted drug candidates against protein targets. DeepLig’s model consists of two networks in interplay: a generative network and a predictive network. The generative network, a Stack- Augmented Recurrent Neural Network, utilizes a stack memory unit to remember and recognize molecular patterns when generating novel ligands from scratch. The generative network passes each newly created ligand to the predictive network, which then uses multiple Graph Attention Networks simultaneously to forecast the average binding affinity of the generated ligand towards multiple target proteins. With each iteration, given feedback from the predictive network, the generative network learns to optimize itself to create molecules with a higher average binding affinity towards multiple proteins. DeepLig was evaluated based on its ability to generate multi-target ligands against two distinct proteins, multi-target ligands against three distinct proteins, and multi-target ligands against two distinct binding pockets on the same protein. With each test case, DeepLig was able to create a library of valid, synthetically accessible, and novel molecules with optimal and equipotent binding energies. We propose that DeepLig provides an effective approach to design multi-targeted drug therapies that can potentially show higher success rates during in-vitro trials.

Keywords: drug design, multitargeticity, de-novo, reinforcement learning

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Authors: Kaoutar Ben Azzou, Hanaa Talei

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Human resources is an important department in each organization as it manages the life cycle of employees from recruitment training to retirement or termination of contracts. The recruitment process starts with a job opening, followed by a selection of the best-fit candidates from all applicants. Matching the best profile for a job position requires a manual way of looking at many CVs, which requires hours of work that can sometimes lead to choosing not the best profile. The work presented in this paper aims at reducing the workload of HR personnel by automating the preliminary stages of the candidate screening process, thereby fostering a more streamlined recruitment workflow. This tool introduces an automated system designed to help with the recruitment process by scanning candidates' CVs, extracting pertinent features, and employing machine learning algorithms to decide the most fitting job profile for each candidate. Our work employs natural language processing (NLP) techniques to identify and extract key features from unstructured text extracted from a CV, such as education, work experience, and skills. Subsequently, the system utilizes these features to match candidates with job profiles, leveraging the power of classification algorithms.

Keywords: automated recruitment, candidate screening, machine learning, human resources management

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Authors: Rudi Hartono, Bambang Purwanto

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The translation quality of food and drink labels from Indonesian into English is poor because the translation is not accurate, less natural, and difficult to read. The label translation can be found in some cans packages of food and drink products produced and marketed by several companies in Indonesia. If this problem is left unchecked, it will lead to a misunderstanding on the translation results and make consumers confused. This study was conducted to analyze the translation errors on food and drink products labels and formulate the solution for the better translation quality. The research design was the evaluation research with a holistic criticism approach. The data used were words, phrases, and sentences translated from Indonesian to English language printed on food and drink product labels. The data were processed by using Interactive Model Analysis that carried out three main steps: collecting, classifying, and verifying data. Furthermore, the data were analyzed by using content analysis to view the accuracy, naturalness, and readability of translation. The results showed that the translation quality of food and drink product labels from Indonesian to English has the level of accuracy (60%), level of naturalness (50%), and level readability (60%). This fact needs a help to create an effective strategy for translating food and drink product labels later.

Keywords: translation quality, food and drink product labels, a holistic criticism approach, interactive model, content analysis

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Authors: Dávid Csercsik, Péter Kádár

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In the case of the proposed method, the problem is parallelized by considering multiple possible mode of operation profiles, which determine the range in which the generators operate in each period. For each of these profiles, the optimization is carried out independently, and the best resulting dispatch is chosen. For each such profile, the resulting problem is a quadratic programming (QP) problem with a potentially negative definite Q quadratic term, and constraints depending on the actual operation profile. In this paper we analyze the performance of available MATLAB optimization methods and solvers for the corresponding QP.

Keywords: optimization, MATLAB, quadratic programming, economic dispatch

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Authors: Rutuja Upadhyay, Anurag Mehra

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Solid food foams/cellular foods are colloidal systems which impart structure, texture and mouthfeel to many food products such as bread, cakes, ice-cream, meringues, etc. Their heterogeneous morphology makes the quantification of structure/mechanical relationships complex. The porous structure of solid food foams is highly influenced by the processing conditions, ingredient composition, and their interactions. Sensory perceptions of food foams are dependent on bubble size, shape, orientation, quantity and distribution and determines the texture of foamed foods. The state and structure of the solid matrix control the deformation behavior of the food, such as elasticity/plasticity or fracture, which in turn has an effect on the force-deformation curves. The obvious step in obtaining the relationship between the mechanical properties and the porous structure is to quantify them simultaneously. Here, we attempt to research food foams such as bread dough, baked bread and steamed rice cakes to determine the link between ingredients and the corresponding effect of each of them on the rheology, microstructure, bubble size and texture of the final product. Dynamic rheometry (SAOS), confocal laser scanning microscopy, flatbed scanning, image analysis and texture profile analysis (TPA) has been used to characterize the foods studied. In all the above systems, there was a common observation that when the mean bubble diameter is smaller, the product becomes harder as evidenced by the increase in storage and loss modulus (G′, G″), whereas when the mean bubble diameter is large the product is softer with decrease in moduli values (G′, G″). Also, the bubble size distribution affects texture of foods. It was found that bread doughs with hydrocolloids (xanthan gum, alginate) aid a more uniform bubble size distribution. Bread baking experiments were done to study the rheological changes and mechanisms involved in the structural transition of dough to crumb. Steamed rice cakes with xanthan gum (XG) addition at 0.1% concentration resulted in lower hardness with a narrower pore size distribution and larger mean pore diameter. Thus, control of bubble size could be an important parameter defining final food texture.

Keywords: food foams, rheology, microstructure, texture

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Authors: Ashi Gautam, Isha Shukla, Akhil Seghal

Abstract:

Biosensors are analytical devices that use a biological sensing element to detect and measure a specific chemical substance or biomolecule in a sample. These devices are widely used in various fields, including medical diagnostics, environmental monitoring, and food analysis, due to their high specificity, sensitivity, and selectivity. In this research paper, a machine learning model is proposed for predicting the suitability of skin care products based on biosensor readings. The proposed model takes in features extracted from biosensor readings, such as biomarker concentration, skin hydration level, inflammation presence, sensitivity, and free radicals, and outputs the most appropriate skin care product for an individual. This model is trained on a dataset of biosensor readings and corresponding skin care product information. The model's performance is evaluated using several metrics, including accuracy, precision, recall, and F1 score. The aim of this research is to develop a personalised skin care product recommendation system using biosensor data. By leveraging the power of machine learning, the proposed model can accurately predict the most suitable skin care product for an individual based on their biosensor readings. This is particularly useful in the skin care industry, where personalised recommendations can lead to better outcomes for consumers. The developed model is based on supervised learning, which means that it is trained on a labeled dataset of biosensor readings and corresponding skin care product information. The model uses these labeled data to learn patterns and relationships between the biosensor readings and skin care products. Once trained, the model can predict the most suitable skin care product for an individual based on their biosensor readings. The results of this study show that the proposed machine learning model can accurately predict the most appropriate skin care product for an individual based on their biosensor readings. The evaluation metrics used in this study demonstrate the effectiveness of the model in predicting skin care products. This model has significant potential for practical use in the skin care industry for personalised skin care product recommendations. The proposed machine learning model for predicting the suitability of skin care products based on biosensor readings is a promising development in the skin care industry. The model's ability to accurately predict the most appropriate skin care product for an individual based on their biosensor readings can lead to better outcomes for consumers. Further research can be done to improve the model's accuracy and effectiveness.

Keywords: biosensors, data model, machine learning, skin care

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Authors: Lucia Steenkamp, Chris V. D. Westhuyzen, Kgama Mathiba

Abstract:

Ambergris, and more specifically its oxidation product (–)-ambrafuran, is a scarce, valuable, and sought-after perfumery ingredient. The material is used as a fixative agent to stabilise perfumes in formulations by reducing the evaporation rate of volatile substances. Ambergris is a metabolic product of the sperm whale (Physeter macrocephatus L.), resulting from intestinal irritation. Chemically, (–)-ambrafuran is produced from the natural product sclareol in eight synthetic steps – in the process using harsh and often toxic chemicals to do so. An overall yield of no more than 76% can be achieved in some routes, but generally, this is lower. A new 'green' route has been developed in our laboratory in which sclareol, extracted from the Clary sage plant, is converted to (–)-ambrafuran in two steps with an overall yield in excess of 80%. The first step uses a microorganism, Hyphozyma roseoniger, to bioconvert sclareol to an intermediate diol using substrate concentrations up to 50g/L. The yield varies between 90 and 67% depending on the substrate concentration used. The purity of the diol product is 95%, and the diol is used without further purification in the next step. The intermediate diol is then cyclodehydrated to the final product (–)-ambrafuran using a zeolite, which is not harmful to the environment and is readily recycled. The yield of the product is 96%, and following a single recrystallization, the purity of the product is > 99.5%. A preliminary LC-MS study of the bioconversion identified several intermediates produced in the fermentation broth under oxygen-restricted conditions. Initially, a short-lived ketone is produced in equilibrium with a more stable pyranol, a key intermediate in the process. The latter is oxidised under Norrish type I cleavage conditions to yield an acetate, which is hydrolysed either chemically or under lipase action to afford the primary fermentation product, an intermediate diol. All the intermediates identified point to the likely CYP450 action as the key enzyme(s) in the mechanism. This invention is an exceptional example of how the power of biocatalysis, combined with a mild, benign chemical step, can be deployed to replace a total chemical synthesis of a specific chiral antipode of a commercially relevant material.

Keywords: ambrafuran, biocatalysis, fragrance, microorganism

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Authors: Thidaya Thitiapichart

Abstract:

The effect of additional magnesium oxide (MgO) was investigated by using the tungsten oxide supported on silica catalyst (WOx/SiO2) physically mixed with MgO in a weight ratio 1:1. The both fresh and spent catalysts were characterized by FT-Raman spectrometer, UV-Vis spectrometer, X-Ray diffraction (XRD), and temperature programmed oxidation (TPO). The results indicated that the additional MgO could enhance the conversion of trans-2-butene due to isomerization reaction. However, adding MgO would increase the amount of coke deposit on the WOx/SiO2 catalyst. The TPO profile presents two peaks when the WOx/SiO2 catalyst was physically mixed with MgO. The further peak was suggested to be coming from the coke precursor that could be produced by isomerization reaction of the undesired product. Then, the occurred coke precursor could deposit and form coke on the acid catalyst.

Keywords: coke formation, metathesis, magnesium oxide, physically mix

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