Search results for: portfolio optimization task

Authors: Wang Yichen, Haruka Yamashita

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

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

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Authors: Julie Ramain, Christine Mohr, Ahmad Abu-Akel

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Divergent thinking—a cognitive component of creativity—and particularly the ability to generate unique and novel ideas, has been linked to both autistic and schizotypal traits. However, to our knowledge, the concurrent effect of these trait dimensions on divergent thinking has not been investigated. Moreover, it has been suggested that creativity is associated with different types of attention and cognitive control, and consequently how information is processed in a given context. Intriguingly, consistent with the diametric model, autistic and schizotypal traits have been associated with contrasting attentional and cognitive control styles. Positive schizotypal traits have been associated with reactive cognitive control and attentional flexibility, while autistic traits have been associated with proactive cognitive control and the increased focus of attention. The current study investigated the relationship between divergent thinking, autistic and schizotypal traits and cognitive control in a non-clinical sample of 83 individuals (Males = 42%; Mean age = 22.37, SD = 2.93), sufficient to detect a medium effect size. Divergent thinking was evaluated in an adapted version of-of the Figural Torrance Test of Creative Thinking. Crucially, since we were interested in testing divergent thinking productivity across contexts, participants were asked to generate items from basic shapes in four different contexts. The variance of the proportion of unique to total responses across contexts represented a measure of context adaptability, with lower variance indicating increased context adaptability. Cognitive control was estimated with the Behavioral Proactive Index of the AX-CPT task, with higher scores representing the ability to actively maintain goal-relevant information in a sustained/anticipatory manner. Autistic and schizotypal traits were assessed with the Autism Quotient (AQ) and the Community Assessment of Psychic Experiences (CAPE-42). Generalized linear models revealed a 3-way interaction of autistic and positive schizotypal traits, and proactive cognitive control, associated with increased context adaptability. Specifically, the concurrent effect of autistic and positive schizotypal traits on increased context adaptability was moderated by the level of proactive control and was only significant when proactive cognitive control was high. Our study reveals that autistic and positive schizotypal traits interactively facilitate the capacity to generate unique ideas across various contexts. However, this effect depends on cognitive control mechanisms indicative of the ability to proactively maintain attention when needed. The current results point to a unique profile of divergent thinkers who have the ability to respectively tap both systematic and flexible processing modes within and across contexts. This is particularly intriguing as such combination of phenotypes has been proposed to explain the genius of Beethoven, Nash, and Newton.

Keywords: autism, schizotypy, creativity, cognitive control

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Authors: Martin Cai, Khadijah B. Hashim, Leng Leo, Edmund F. Tian

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Analysis of traditional Chinese medicinal (TCM) supplements has always been a laborious task, particularly in the case of multi‐ingredient formulations. Traditionally, herbal extracts are analysed using one or few markers compounds. In the recent years, however, pharmaceutical companies are introducing health supplements of TCM active ingredients to cater to the needs of consumers in the fast-paced society in this age. As such, new problems arise in the aspects of composition identification as well as quality analysis. In most cases of products or supplements formulated with multiple TCM herbs, the chemical composition, and nature of each raw material differs greatly from the others in the formulation. This results in a requirement for individual analytical processes in order to identify the marker compounds in the various botanicals. Thin-layer Chromatography (TLC) is a simple, cost effective, yet well-regarded method for the analysis of natural products, both as a Pharmacopeia-approved method for identification and authentication of herbs, and a great analytical tool for the discovery of chemical compositions in herbal extracts. Recent technical advances introduced High-Performance TLC (HPTLC) where, with the help of automated equipment and improvements on the chromatographic materials, both the quality and reproducibility are greatly improved, allowing for highly standardised analysis with greater details. Here we report an industrial consultancy project with ONI Global Pte Ltd for the analysis of LAC Liver Protector, a TCM formulation aimed at improving liver health. The aim of this study was to identify 4 key components of the supplement using HPTLC, following protocols derived from Chinese Pharmacopeia standards. By comparing the TLC profiles of the supplement to the extracts of the herbs reported in the label, this project proposes a simple and cost-effective analysis of the presence of the 4 marker compounds in the multi‐ingredient formulation by using 4 different HPTLC methods. With the increasing trend of small and medium-sized enterprises (SMEs) bringing natural products and health supplements into the market, it is crucial that the qualities of both raw materials and end products be well-assured for the protection of consumers. With the technology of HPTLC, science can be incorporated to help SMEs with their quality control, thereby ensuring product quality.

Keywords: traditional Chinese medicine supplement, high performance thin layer chromatography, active ingredients, product quality

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Authors: Matjaž Šraml, Marko Renčelj, Tomaž Tollazzi, Chiara Gruden

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Road safety is a worldwide issue with numerous and heterogeneous factors influencing it. On the side, driver state – comprising distraction/inattention, fatigue, drowsiness, extreme emotions, and socio-cultural factors highly affect road safety. On the other side, the vehicle state has an important role in mitigating (or not) the road risk. Finally, the road environment is still one of the main determinants of road safety, defining driving task complexity. At the same time, thanks to technological development, a lot of detailed data is easily available, creating opportunities for the detection of driver state, vehicle characteristics and road conditions and, consequently, for the design of ad hoc interventions aimed at improving driver performance, increase awareness and mitigate road risks. This is the challenge faced by the i-DREAMS project. i-DREAMS, which stands for a smart Driver and Road Environment Assessment and Monitoring System, is a 3-year project funded by the European Union’s Horizon 2020 research and innovation program. It aims to set up a platform to define, develop, test and validate a ‘Safety Tolerance Zone’ to prevent drivers from getting too close to the boundaries of unsafe operation by mitigating risks in real-time and after the trip. After the definition and development of the Safety Tolerance Zone concept and the concretization of the same in an Advanced driver-assistance system (ADAS) platform, the system was tested firstly for 2 months in a driving simulator environment in 5 different countries. After that, naturalistic driving studies started for a 10-month period (comprising a 1-month pilot study, 3-month baseline study and 6 months study implementing interventions). Currently, the project team has approved a common evaluation approach, and it is developing the assessment of the usage and outcomes of the i-DREAMS system, which is turning positive insights. The i-DREAMS consortium consists of 13 partners, 7 engineering universities and research groups, 4 industry partners and 2 partners (European Transport Safety Council - ETSC - and POLIS cities and regions for transport innovation) closely linked to transport safety stakeholders, covering 8 different countries altogether.

Keywords: advanced driver assistant systems, driving simulator, safety tolerance zone, traffic safety

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Authors: Said Benaissa, David Plets, Emmeric Tanghe, Jens Trogh, Luc Martens, Leen Vandaele, Annelies Van Nuffel, Frank A. M. Tuyttens, Bart Sonck, Wout Joseph

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The herd monitoring and managing - in particular the detection of ‘attention animals’ that require care, treatment or assistance is crucial for effective reproduction status, health, and overall well-being of dairy cows. In large sized farms, traditional methods based on direct observation or analysis of video recordings become labour-intensive and time-consuming. Thus, automatic monitoring systems using sensors have become increasingly important to continuously and accurately track the health status of dairy cows. Wireless sensor networks (WSNs) and internet-of-things (IoT) can be effectively used in health tracking of dairy cows to facilitate herd management and enhance the cow welfare. Since on-cow measuring devices are energy-constrained, a proper characterization of the off-body wireless channel between the on-cow sensor nodes and the back-end base station is required for a power-optimized deployment of these networks in barns. The aim of this study was to characterize the off-body wireless channel in indoor (barns) environment at 868 MHz using LoRa nodes. LoRa is an emerging wireless technology mainly targeted at WSNs and IoT networks. Both large scale fading (i.e., path loss) and temporal fading were investigated. The obtained path loss values as a function of the transmitter-receiver separation were well fitted by a lognormal path loss model. The path loss showed an additional increase of 4 dB when the wireless node was actually worn by the cow. The temporal fading due to movement of other cows was well described by Rician distributions with a K-factor of 8.5 dB. Based on this characterization, network planning and energy consumption optimization of the on-body wireless nodes could be performed, which enables the deployment of reliable dairy cow monitoring systems.

Keywords: channel, channel modelling, cow monitoring, dairy cows, health monitoring, IoT, LoRa, off-body propagation, PLF, propagation

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Authors: Soledad Carinelli, Iñigo Fernández, José Luis González-Mora, Pedro A. Salazar-Carballo

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Mastitis is the most relevant inflammatory disease in cattle, affecting the animal health and causing important economic losses on dairy farms. This disease takes place in the mammary gland or udder when some opportunistic microorganisms, such as Staphylococcus aureus, Streptococcus agalactiae, Corynebacterium bovis, etc., invade the teat canal. According to the severity of the inflammation, mastitis can be classified as sub-clinical, clinical and chronic. Standard methods for mastitis detection include counts of somatic cells, cell culture, electrical conductivity of the milk, and California test (evaluation of “gel-like” matrix consistency after cell lysed with detergents). However, these assays present some limitations for accurate detection of subclinical mastitis. Currently, haptoglobin, an acute phase protein, has been proposed as novel and effective biomarker for mastitis detection. In this work, an electrochemical biosensor based on polydopamine-modified magnetic nanoparticles (MNPs@pDA) for haptoglobin detection is reported. Thus, MNPs@pDA has been synthesized by our group and functionalized with hemoglobin due to its high affinity to haptoglobin protein. The protein was labeled with specific antibodies modified with alkaline phosphatase enzyme for its electrochemical detection using an electroactive substrate (1-naphthyl phosphate) by differential pulse voltammetry. After the optimization of assay parameters, the haptoglobin determination was evaluated in milk. The strategy presented in this work shows a wide range of detection, achieving a limit of detection of 43 ng/mL. The accuracy of the strategy was determined by recovery assays, being of 84 and 94.5% for two Hp levels around the cut off value. Milk real samples were tested and the prediction capacity of the electrochemical biosensor was compared with a Haptoglobin commercial ELISA kit. The performance of the assay has demonstrated this strategy is an excellent and real alternative as screen method for sub-clinical bovine mastitis detection.

Keywords: bovine mastitis, haptoglobin, electrochemistry, magnetic nanoparticles, polydopamine

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Authors: Christian Ihwiwhu, Nnamdi Obioha, Udeme John, Edward Bobade, Oghenerunor Bekibele, Adedeji Awujoola, Ibi-Ada Itotoi

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Understanding the complexity in the distribution of hydrocarbon in a simple structure with flow baffles and connectivity issues is critical in targeting and developing the remaining pay in a mature asset. Subtle facies changes (heterogeneity) can have a drastic impact on reservoir fluids movement, and this can be crucial to identifying sweet spots in mature fields. This study aims to evaluate selected reservoirs in Ovhor Field, Niger Delta, Nigeria, with the objective of optimising production from the field by targeting undeveloped oil reserves, bypassed pay, and gaining an improved understanding of the selected reservoirs to increase the company’s reservoir limits. The task at the Ovhor field is complicated by poor stratigraphic seismic resolution over the field. 3-D geological (sedimentology and stratigraphy) interpretation, use of results from quantitative interpretation, and proper understanding of production data have been used in recognizing flow baffles and undeveloped compartments in the field. The full field 3-D model has been constructed in such a way as to capture heterogeneities and the various compartments in the field to aid the proper simulation of fluid flow in the field for future production prediction, proper history matching and design of good trajectories to adequately target undeveloped oil in the field. Reservoir property models (porosity, permeability, and net-to-gross) have been constructed by biasing log interpreted properties to a defined environment of deposition model whose interpretation captures the heterogeneities expected in the studied reservoirs. At least, two scenarios have been modelled for most of the studied reservoirs to capture the range of uncertainties we are dealing with. The total original oil in-place volume for the four reservoirs studied is 157 MMstb. The cumulative oil and gas production from the selected reservoirs are 67.64 MMstb and 9.76 Bscf respectively, with current production rate of about 7035 bopd and 4.38 MMscf/d (as at 31/08/2019). Dynamic simulation and production forecast on the 4 reservoirs gave an undeveloped reserve of about 3.82 MMstb from two (2) identified oil restoration activities. These activities include side-tracking and re-perforation of existing wells. This integrated approach led to the identification of bypassed oil in some areas of the selected reservoirs and an improved understanding of the studied reservoirs. New wells have/are being drilled now to test the results of our studies, and the results are very confirmatory and satisfying.

Keywords: facies, flow baffle, bypassed pay, heterogeneities, history matching, reservoir limit

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Authors: Tengku Sepora Tengku Mahadi

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Where the speed of book writing lags behind the high need for such material for tertiary studies, translation offers a way to enhance the equilibrium in this demand-supply equation. Nevertheless, translation is confronted by obstacles that threaten its effectiveness. The primary challenge to the production of efficient translations may well be related to the text-type and in terms of its complexity. A text that is intricately written with unique rhetorical devices, subject-matter foundation and cultural references will undoubtedly challenge the translator. Longer time and greater effort would be the consequence. To understand these text-related challenges, the present paper set out to analyze a lawbook entitled Learning the Law by David Melinkoff. The book is chosen because it has often been used as a textbook or for reference in many law courses in the United Kingdom and has seen over thirteen editions; therefore, it can be said to be a worthy book for studies in law. Another reason is the existence of a ready translation in Malay. Reference to this translation enables confirmation to some extent of the potential problems that might occur in its translation. Understanding the organization and the language of the book will help translators to prepare themselves better for the task. They can anticipate the research and time that may be needed to produce an effective translation. Another premise here is that this text-type implies certain ways of writing and organization. Accordingly, it seems practicable to adopt the functional theory of language as suggested by Michael Halliday as its theoretical framework. Concepts of the context of culture, the context of situation and measures of the field, tenor and mode form the instruments for analysis. Additional examples from similar materials can also be used to validate the findings. Some interesting findings include the presence of several other text-types or sub-text-types in the book and the dependence on literary discourse and devices to capture the meanings better or add color to the dry field of law. In addition, many elements of culture can be seen, for example, the use of familiar alternatives, allusions, and even terminology and references that date back to various periods of time and languages. Also found are parts which discuss origins of words and terms that may be relevant to readers within the United Kingdom but make little sense to readers of the book in other languages. In conclusion, the textual analysis in terms of its functions and the linguistic and textual devices used to achieve them can then be applied as a guide to determine the effectiveness of the translation that is produced.

Keywords: functional theory of language, lawbook text-type, rhetorical devices, culture

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Authors: Sujing Wang, Song Wang, Jian Zhang, Qiang Xu

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Flaring emissions during abnormal operating conditions such as plant start-ups, shut-downs, and upsets in chemical process industries (CPI) are usually significant. Flare minimization can help to save raw material and energy for CPI plants, and to improve local environmental sustainability. In this paper, a systematic methodology based on plant-wide dynamic simulation is presented for CPI plant flare minimizations under abnormal operating conditions. Since off-specification emission sources are inevitable during abnormal operating conditions, to significantly reduce flaring emission in a CPI plant, they must be either recycled to the upstream process for online reuse, or stored somewhere temporarily for future reprocessing, when the CPI plant manufacturing returns to stable operation. Thus, the off-spec products could be reused instead of being flared. This can be achieved through the identification of viable design and operational strategies during normal and abnormal operations through plant-wide dynamic scheduling, simulation, and optimization. The proposed study includes three stages of simulation works: (i) developing and validating a steady-state model of a CPI plant; (ii) transiting the obtained steady-state plant model to the dynamic modeling environment; and refining and validating the plant dynamic model; and (iii) developing flare minimization strategies for abnormal operating conditions of a CPI plant via a validated plant-wide dynamic model. This cost-effective methodology has two main merits: (i) employing large-scale dynamic modeling and simulations for industrial flare minimization, which involves various unit models for modeling hundreds of CPI plant facilities; (ii) dealing with critical abnormal operating conditions of CPI plants such as plant start-up and shut-down. Two virtual case studies on flare minimizations for start-up operation (over 50% of emission savings) and shut-down operation (over 70% of emission savings) of an ethylene plant have been employed to demonstrate the efficacy of the proposed study.

Keywords: flare minimization, large-scale modeling and simulation, plant shut-down, plant start-up

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Authors: Badrane Nohayla, Bamousse Zineb

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Financial crises, exchange rate volatility, fluctuations in commodity prices, increased competitive pressures, and environmental issues are all threats that businesses face. In light of these diverse challenges, proactive, agile, and innovative cash management becomes an indispensable financial shield, allowing companies to thrive despite the adverse conditions of the global environment. In the same spirit, uncertainty, turbulence, volatility, and competitiveness continue to disrupt economic environments, compelling companies to swiftly master innovative breakthroughs that provide added value. In such a context, innovation emerges as a catalytic vector for performance, aiming to reduce costs, strengthen growth, and ultimately ensure the sustainability of Moroccan companies in the national arena. Moreover, innovation in treasury management promises to be one of the key pillars of financial stability, enabling companies to navigate the tumultuous waters of a globalized environment. Therefore, the objective of this study is to better understand the impact of innovative treasury management on cost optimization and, by extension, performance improvement. To elucidate this relationship, we conducted an exploratory qualitative study with 20 large Moroccan companies operating in the Casablanca-Settat region. The results highlight that innovation at the heart of treasury management is a guarantee of sustainability against the risks of failure and stands as a true pivot of the performance of Moroccan companies, an important parameter of their financial balance and a catalytic vector of their growth in the national economic landscape. In this regard, this study aims to provide answers to the following question: To what extent does innovation at the core of the treasury function prove to be the indispensable shield to boost performance while optimizing costs for large Moroccan companies?

Keywords: innovative cash management, artificial intelligence (ai), financial performance, risk management, cost savings

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Authors: Shivdayal Patel, Suhail Ahmad

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Safety assurance and failure prediction of composite material component of an offshore structure due to low velocity impact is essential for associated risk assessment. It is important to incorporate uncertainties associated with material properties and load due to an impact. Likelihood of this hazard causing a chain of failure events plays an important role in risk assessment. The material properties of composites mostly exhibit a scatter due to their in-homogeneity and anisotropic characteristics, brittleness of the matrix and fiber and manufacturing defects. In fact, the probability of occurrence of such a scenario is due to large uncertainties arising in the system. Probabilistic finite element analysis of composite plates due to low-velocity impact is carried out considering uncertainties of material properties and initial impact velocity. Impact-induced damage of composite plate is a probabilistic phenomenon due to a wide range of uncertainties arising in material and loading behavior. A typical failure crack initiates and propagates further into the interface causing de-lamination between dissimilar plies. Since individual crack in the ply is difficult to track. The progressive damage model is implemented in the FE code by a user-defined material subroutine (VUMAT) to overcome these problems. The limit state function is accordingly established while the stresses in the lamina are such that the limit state function (g(x)>0). The Gaussian process response surface method is presently adopted to determine the probability of failure. A comparative study is also carried out for different combination of impactor masses and velocities. The sensitivity based probabilistic design optimization procedure is investigated to achieve better strength and lighter weight of composite structures. Chain of failure events due to different modes of failure is considered to estimate the consequences of failure scenario. Frequencies of occurrence of specific impact hazards yield the expected risk due to economic loss.

Keywords: composites, damage propagation, low velocity impact, probability of failure, uncertainty modeling

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Authors: Bogale Tadesse, Krutik Parikh, Ndagha Mkandawire, Boris Albijanic, Nimal Subasinghe

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It is well established that the floatability and selectivity of mineral particles are highly dependent on the particle size. Generally, a particle size of 10 micron is considered as the critical size below which both flotation selectivity and recovery decline sharply. It is widely accepted that the majority of ultrafine particles, including highly liberated valuable minerals, will be lost in tailings during a conventional flotation process. This is highly undesirable particularly in the processing of finely disseminated complex and refractory ores where there is a requirement for fine grinding in order to liberate the valuable minerals. In addition, the continuing decline in ore grade worldwide necessitates intensive processing of low grade mineral deposits. Recent advances in comminution allow the economic grinding of particles down to 10 micron sizes to enhance the probability of liberating locked minerals from low grade ores. Thus, it is timely that the flotation of fine and ultrafine particles is improved in order to reduce the amount of valuable minerals lost as slimes. It is believed that the use of fine bubbles in flotation increases the bubble-particle collision efficiency and hence the flotation performance. Electroflotation, where bubbles are generated by the electrolytic breakdown of water to produce oxygen and hydrogen gases, leads to the formation of extremely finely dispersed gas bubbles with dimensions varying from 5 to 95 micron. The sizes of bubbles generated by this method are significantly smaller than those found in conventional flotation (> 600 micron). In this study, microbubbles generated by electrolysis of water were injected into a bench top flotation cell to assess the performance electroflotation in enhancing the flotation of fine and ultrafine pyrite particles of sizes ranging from 5 to 53 micron. The design of the cell and the results from optimization of the process variables such as current density, pH, percent solid and particle size will be presented at this conference.

Keywords: electroflotation, fine bubbles, pyrite, ultrafine particles

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Authors: S. H. J. Liu

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This paper aims to explore the role of peer Corrective Feedback (CF) in improving written productions by English-as-a- foreign-language (EFL) learners who work together via Wikispaces. It attempted to determine the effect of peer CF on form accuracy in English, such as grammar and lexis. Thirty-four EFL learners at the tertiary level were randomly assigned into the experimental (with peer feedback) or the control (without peer feedback) group; each group was subdivided into small groups of two or three. This resulted in six and seven small groups in the experimental and control groups, respectively. In the experimental group, each learner played a role as an assessor (providing feedback to others), as well as an assessee (receiving feedback from others). Each participant was asked to compose his/her written work and revise it based on the feedback. In the control group, on the other hand, learners neither provided nor received feedback but composed and revised their written work on their own. Data collected from learners’ compositions and post-task interviews were analyzed and reported in this study. Following the completeness of three writing tasks, 10 participants were selected and interviewed individually regarding their perception of collaborative learning in the Computer-Mediated Communication (CMC) environment. Language aspects to be analyzed included lexis (e.g., appropriate use of words), verb tenses (e.g., present and past simple), prepositions (e.g., in, on, and between), nouns, and articles (e.g., a/an). Feedback types consisted of CF, affective, suggestive, and didactic. Frequencies of feedback types and the accuracy of the language aspects were calculated. The results first suggested that accurate items were found more in the experimental group than in the control group. Such results entail that those who worked collaboratively outperformed those who worked non-collaboratively on the accuracy of linguistic aspects. Furthermore, the first type of CF (e.g., corrections directly related to linguistic errors) was found to be the most frequently employed type, whereas affective and didactic were the least used by the experimental group. The results further indicated that most participants perceived that peer CF was helpful in improving the language accuracy, and they demonstrated a favorable attitude toward working with others in the CMC environment. Moreover, some participants stated that when they provided feedback to their peers, they tended to pay attention to linguistic errors in their peers’ work but overlook their own errors (e.g., past simple tense) when writing. Finally, L2 or FL teachers or practitioners are encouraged to employ CMC technologies to train their students to give each other feedback in writing to improve the accuracy of the language and to motivate them to attend to the language system.

Keywords: peer corrective feedback, computer-mediated communication (CMC), second or foreign language (L2 or FL) learning, Wikispaces

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Authors: Priyanka Bharti

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Decades ago designs were based on common sense and tradition, but after an enhancement in visualization technology and research, we are now able to comprehend the cognitive ability involved in the decoding of the visual information. However, many fields in visuals need intense research to deliver an efficient explanation for the events. Visuals are an information representation mode through images, symbols and graphics. It plays an impactful role in decision making by facilitating quick recognition, comprehension, and analysis of a situation. They enhance problem-solving capabilities by enabling the processing of more data without overloading the decision maker. As research proves that, visuals offer an improved learning environment by a factor of 400 compared to textual information. Visual information engages learners at a cognitive level and triggers the imagination, which enables the user to process the information faster (visuals are processed 60,000 times faster in the brain than text). Appropriate information, visualization, and its presentation are known to aid and intensify the decision-making process for the users. However, most literature discusses the role of visual aids in comprehension and decision making during normal conditions alone. Unlike emergencies, in a normal situation (e.g. our day to day life) users are neither exposed to stringent time constraints nor face the anxiety of survival and have sufficient time to evaluate various alternatives before making any decision. An emergency is an unexpected probably fatal real-life situation which may inflict serious ramifications on both human life and material possessions unless corrective measures are taken instantly. The situation demands the exposed user to negotiate in a dynamic and unstable scenario in the absence or lack of any preparation, but still, take swift and appropriate decisions to save life/lives or possessions. But the resulting stress and anxiety restricts cue sampling, decreases vigilance, reduces the capacity of working memory, causes premature closure in evaluating alternative options, and results in task shedding. Limited time, uncertainty, high stakes and vague goals negatively affect cognitive abilities to take appropriate decisions. More so, theory of natural decision making by experts has been understood with far more depth than that of an ordinary user. Therefore, in this study, the author aims to understand the role of visual aids in supporting rapid comprehension to take appropriate decisions during an emergency situation.

Keywords: cognition, visual, decision making, graphics, recognition

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Authors: Burcu Doymus, Fatma N. Kok, Sakip Onder

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Titanium and titanium-based materials are commonly used to replace or regenerate the injured or lost tissues because of accidents or illnesses. Hospital infections and strong bond formation at the implant-tissue interface are directly affecting the success of the implantation as weak bonding with the native tissue and hospital infections lead to revision surgery. The purpose of the presented study is to modify the surface of the titanium substrates with nano/microspheres for local drug delivery and to prevent hospital infections. Firstly, titanium surfaces were silanized with APTES (3-Triethoxysilylpropylamine) following the negatively charged oxide layer formation. Then characterization studies using Scanning Electron Microscopy (SEM) and Fourier transform infrared spectroscopy (FTIR) were done on the modified surfaces. Secondly, microspheres/nanospheres were prepared with chitosan that is a natural polymer and having valuable properties such as non-toxicity, high biocompatibility, low allergen city and biodegradability for biomedical applications. Antibiotic (ciprofloxacin) loaded micro/nanospheres have been fabricated using emulsion cross-linking method and have been immobilized onto the titanium surfaces with different immobilization techniques such as covalent bond and entrapment. Optimization studies on size and drug loading capacities of micro/nanospheres were conducted before the immobilization process. Light microscopy and SEM were used to visualize and measure the size of the produced micro/nanospheres. Loaded and released drug amounts were determined by using UV- spectrophotometer at 278 nm. Finally, SEM analysis and drug release studies on the micro/nanospheres coated Ti surfaces were done. As a conclusion, it was shown that micro/nanospheres were immobilized onto the surfaces successfully and drug release from these surfaces was in a controlled manner. Moreover, the density of the micro/nanospheres after the drug release studies was higher on the surfaces where the entrapment technique was used for immobilization. Acknowledgement: This work is financially supported by The Scientific and Technological Research Council Of Turkey (Project # 217M220)

Keywords: chitosan, controlled drug release, nanosphere, nosocomial infections, titanium

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Authors: Raphael M. Rettig, Tessa C. Flatten

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This empirical study answer calls for research on Absorptive Capacity and Process Innovation. Due to the fourth industrial revolution, manufacturing companies face the biggest disruption of their production processes since the rise of advanced manufacturing technologies in the last century. Therefore, process innovation will become a critical task to master in the future for many manufacturing firms around the world. The general ability of organizations to acquire, assimilate, transform, and exploit external knowledge, known as Absorptive Capacity, was proven to positively influence product innovation and is already conceptually associated with process innovation. The presented research provides empirical evidence for this influence. The findings are based on an empirical analysis of 732 companies from seven leading and emerging countries: Brazil, China, France, Germany, India, Japan, and the United States of America. The answers to the survey were collected in February and March 2018 and addressed senior- and top-level management with a focus on operations departments. The statistical analysis reveals the positive influence of potential and Realized Absorptive Capacity on successful process innovation taking the implementation of new digital manufacturing processes as an example. Potential Absorptive Capacity covering the acquisition and assimilation capabilities of an organization showed a significant positive influence (β = .304, p < .05) on digital manufacturing implementation success and therefore on process innovation. Realized Absorptive Capacity proved to have significant positive influence on process innovation as well (β = .461, p < .01). The presented study builds on prior conceptual work in the field of Absorptive Capacity and process innovation and contributes theoretically to ongoing research in two dimensions. First, the already conceptually associated influence of Absorptive Capacity on process innovation is backed by empirical evidence in a broad international context. Second, since Absorptive Capacity was measured with a focus on new product development, prior empirical research on Absorptive Capacity was tailored to the research and development departments of organizations. The results of this study highlight the importance of Absorptive Capacity as a capability in mechanical engineering and operations departments of organizations. The findings give managers an indication of the importance of implementing new innovative processes into their production system and fostering the right mindset of employees to identify new external knowledge. Through the ability to transform and exploit external knowledge, own production processes can be innovated successfully and therefore have a positive influence on firm performance and the competitive position of their organizations.

Keywords: absorptive capacity, digital manufacturing, dynamic capabilities, process innovation

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Authors: M. Jerold, V. Sivasubramanian, A. George, B.S. Ashik, S. S. Kumar

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Bioethanol is a sustainable biofuel that can be used alternative to fossil fuels. Today, third generation (3G) biofuel is gaining more attention than first and second-generation biofuel. The more lignin content in the lignocellulosic biomass is the major drawback of second generation biofuels. Algae are the renewable feedstock used in the third generation biofuel production. Algae contain a large number of carbohydrates, therefore it can be used for the fermentation by hydrolysis process. There are two groups of Algae, such as micro and macroalgae. In the present investigation, Macroalgae was chosen as raw material for the production of bioethanol. Two marine algae viz. Ulva Lactuca and Sargassum swartzii were used for the experimental studies. The algal biomass was characterized using various analytical techniques like Elemental Analysis, Scanning Electron Microscopy Analysis and Fourier Transform Infrared Spectroscopy to understand the physio-Chemical characteristics. The batch experiment was done to study the hydrolysis and operation parameters such as pH, agitation, fermentation time, inoculum size. The saccharification was done with acid and alkali treatment. The experimental results showed that NaOH treatment was shown to enhance the bioethanol. From the hydrolysis study, it was found that 0.5 M Alkali treatment would serve as optimum concentration for the saccharification of polysaccharide sugar to monomeric sugar. The maximum yield of bioethanol was attained at a fermentation time of 9 days. The inoculum volume of 1mL was found to be lowest for the ethanol fermentation. The agitation studies show that the fermentation was higher during the process. The percentage yield of bioethanol was found to be 22.752% and 14.23 %. The elemental analysis showed that S. swartzii contains a higher carbon source. The results confirmed hydrolysis was not completed to recover the sugar from biomass. The specific gravity of ethanol was found to 0.8047 and 0.808 for Ulva Lactuca and Sargassum swartzii, respectively. The purity of bioethanol also studied and found to be 92.55 %. Therefore, marine algae can be used as a most promising renewable feedstock for the production of bioethanol.

Keywords: algae, biomass, bioethaol, biofuel, pretreatment

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Authors: Muhammad Awais Kiani, Maryam Kiani

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This abstract explores the confluence of these two domains and highlights the key factors driving success in sales marketing for electronics. The abstract begins by digging into the ever-evolving landscape of consumer electronics, emphasizing how technological advancements and the growth of smart devices have revolutionized the way people interact with electronics. This paradigm shift has created tremendous opportunities for sales and marketing professionals to engage with consumers on various platforms and channels. Next, the abstract discusses the pivotal role of effective sales marketing strategies in the electronics industry. It highlights the importance of understanding consumer behavior, market trends, and competitive landscapes and how this knowledge enables businesses to tailor their marketing efforts to specific target audiences. Furthermore, the abstract explores the significance of leveraging digital marketing techniques, such as social media advertising, search engine optimization, and influencer partnerships, to establish brand identity and drive sales in the electronics market. It emphasizes the power of storytelling and creating captivating content to engage with tech-savvy consumers. Additionally, the abstract emphasizes the role of customer relationship management (CRM) systems and data analytics in optimizing sales marketing efforts. It highlights the importance of leveraging customer insights and analyzing data to personalize marketing campaigns, enhance customer experience, and ultimately drive sales growth. Lastly, the abstract concludes by underlining the importance of adapting to the ever-changing landscape of the electronics industry. It encourages businesses to embrace innovation, stay informed about emerging technologies, and continuously evolve their sales marketing strategies to meet the evolving needs and expectations of consumers. Overall, this abstract sheds light on the captivating realm of sales marketing in the electronics industry, emphasizing the need for creativity, adaptability, and a deep understanding of consumers to succeed in this rapidly evolving market.

Keywords: marketing industry, electronics, sales impact, e-commerce

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Authors: Zahid Ullah, Atlas Khan

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In today's data-driven world, the role of mathematics in bridging the gap between theory and applications is becoming increasingly vital. This abstract highlights the significance of mathematics as a powerful tool for analyzing, interpreting, and extracting meaningful insights from vast amounts of data. By integrating mathematical principles with real-world applications, researchers can unlock the full potential of data-driven decision-making processes. This abstract delves into the various ways mathematics acts as a bridge connecting theoretical frameworks to practical applications. It explores the utilization of mathematical models, algorithms, and statistical techniques to uncover hidden patterns, trends, and correlations within complex datasets. Furthermore, it investigates the role of mathematics in enhancing predictive modeling, optimization, and risk assessment methodologies for improved decision-making in diverse fields such as finance, healthcare, engineering, and social sciences. The abstract also emphasizes the need for interdisciplinary collaboration between mathematicians, statisticians, computer scientists, and domain experts to tackle the challenges posed by the data-driven landscape. By fostering synergies between these disciplines, novel approaches can be developed to address complex problems and make data-driven insights accessible and actionable. Moreover, this abstract underscores the importance of robust mathematical foundations for ensuring the reliability and validity of data analysis. Rigorous mathematical frameworks not only provide a solid basis for understanding and interpreting results but also contribute to the development of innovative methodologies and techniques. In summary, this abstract advocates for the pivotal role of mathematics in bridging theory and applications in a data-driven world. By harnessing mathematical principles, researchers can unlock the transformative potential of data analysis, paving the way for evidence-based decision-making, optimized processes, and innovative solutions to the challenges of our rapidly evolving society.

Keywords: mathematics, bridging theory and applications, data-driven world, mathematical models

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Authors: Gabriel Montague, Max Vilgalys, Catherine H. Crawford, Jorge Ortiz, Dava Newman

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There has never been so much publicly accessible atmospheric and environmental data. The possibilities of these data are exciting, but the sheer volume of available datasets represents a new challenge for researchers. The task of identifying and working with a new dataset has become more difficult with the amount and variety of available data. Datasets are often documented in ways that differ substantially from the common English used to describe the same topics. This presents a barrier not only for new scientists, but for researchers looking to find comparisons across multiple datasets or specialists from other disciplines hoping to collaborate. This paper proposes a method for addressing this obstacle: creating a knowledge graph to bridge the gap between everyday English language and the technical language surrounding these datasets. Knowledge graph generation is already a well-established field, although there are some unique challenges posed by working with Earth data. One is the sheer size of the databases – it would be infeasible to replicate or analyze all the data stored by an organization like The National Aeronautics and Space Administration (NASA) or the European Space Agency. Instead, this approach identifies topics from metadata available for datasets in NASA’s Earthdata database, which can then be used to directly request and access the raw data from NASA. By starting with a single metadata standard, this paper establishes an approach that can be generalized to different databases, but leaves the challenge of metadata harmonization for future work. Topics generated from the metadata are then linked to topics from a collection of English queries through a variety of standard and custom natural language processing (NLP) methods. The results from this method are then compared to a baseline of elastic search applied to the metadata. This comparison shows the benefits of the proposed knowledge graph system over existing methods, particularly in interpreting natural language queries and interpreting topics in metadata. For the research community, this work introduces an application of NLP to the ecological and environmental sciences, expanding the possibilities of how machine learning can be applied in this discipline. But perhaps more importantly, it establishes the foundation for a platform that can enable common English to access knowledge that previously required considerable effort and experience. By making this public data accessible to the full public, this work has the potential to transform environmental understanding, engagement, and action.

Keywords: earth metadata, knowledge graphs, natural language processing, question-answer systems

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Authors: Tingke Wu, Man Yuan

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

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

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Authors: Hung-Chun Lin, Tzu-Yuan Chao

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As the population aging has become an inevitable trend globally, issues of improving the well-being of elderly people in urban areas have been a challenging task for urban planners. Recent studies of ageing trend have also expended to explore the relationship between the built environment and mental condition of elderly people. These studies have proved that even though the built environment may not necessarily play the decisive role in affecting mental health, it can have positive impacts on individual mental health by promoting social linkages and social networks among older adults. There has been a great amount of relevant research examined the impact of the built environment attributes on depression in the elderly; however, most were conducted in the Western countries. Little attention has been paid in Asian cities with contrarily high density and mix-use urban contexts such as Taiwan regarding how the built environment attributes related to depression in elderly people. Hence, more empirical cross-principle studies are needed to explore the possible impacts of Asia urban characteristics on older residents’ mental condition. This paper intends to focus on Tainan city, the fourth biggest metropolis in Taiwan. We first analyze with data from National Health Insurance Research Database to pinpoint the empirical study area where residing most elderly patients, aged over 65, with depressive disorders. Secondly, we explore the relationship between specific attributes of the built environment collected from previous studies and elderly individuals who suffer from depression, under different socio-cultural and networking circumstances. To achieve the results, the research methods adopted in this study include questionnaire and database analysis, and the results will be proceeded by correlation analysis. In addition, through literature review, by generalizing the built environment factors that have been used in Western research to evaluate the relationship between built environment and older individuals with depressive disorders, a set of local evaluative indicators of the built environment for future studies will be proposed as well. In order to move closer to develop age-friendly cities and improve the well-being for the elderly in Taiwan, the findings of this paper can provide empirical results to grab planners’ attention for how built environment makes the elderly feel and to reconsider the relationship between them. Furthermore, with an interdisciplinary topic, the research results are expected to make suggestions for amending the procedures of drawing up an urban plan or a city plan from a different point of view.

Keywords: built environment, depression, elderly, Tainan

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Authors: Yogeeta O. Agrawal, Hitendra S. Mahajan, Sanjay J. Surana

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Methotrexate is effective in controlling recalcitrant psoriasis when administered by the oral or parenteral route long-term. However, the systematic use of this drug may provoke any of a number of side effects, notably hepatotoxic effects. To reduce these effects, clinical studies have been done with topical MTx. It is useful in treating a number of cutaneous conditions, including psoriasis. A major problem in topical administration of MTx currently available in market is that the drug is hydrosoluble and is mostly in the dissociated form at physiological pH. Its capacity for passive diffusion is thus limited. Localization of MTx in effected layers of skin is likely to improve the role of topical dosage form of the drug as a supplementary to oral therapy for treatment of psoriasis. One of the possibilities for increasing the penetration of drugs through the skin is the use of Nanostructured lipid Carriers. The objective of the present study was to formulate and characterize Methotrexate loaded Nanostructured Lipid Carriers (MtxNLCs), to understand in vitro drug release and evaluate the role of the developed gel in the topical treatment of psoriasis. MtxNLCs were prepared by solvent diffusion technique using 3(2) full factorial design.The mean diameter and surface morphology of MtxNLC was evaluated. MtxNLCs were lyophilized and crystallinity of NLC was characterized by Differential Scanning Calorimtery (DSC) and powder X-Ray Diffraction (XRD). The NLCs were incorporated in 1% w/w Carbopol 934 P gel base and in vitro skin deposition studies in Human Cadaver Skin were conducted. The optimized MtxNLCs were spherical in shape, with average particle size of 253(±9.92)nm, zeta potential of -30.4 (±0.86) mV and EE of 53.12(±1.54)%. DSC and XRD data confirmed the formation of NLCs. Significantly higher deposition of Methotrexate was found in human cadaver skin from MtxNLC gel (71.52 ±1.23%) as compared to Mtx plain gel (54.28±1.02%). Findings of the studies suggest that there is significant improvement in therapeutic index in treatment of psoriasis by MTx-NLCs incorporated gel base developed in this investigation over plain drug gel currently available in the market.

Keywords: methotrexate, psoriasis, NLCs, hepatotoxic effects

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Authors: Emma Avoyan

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The safety standards for flood protection in the Netherlands have been revised recently. It is expected that all major flood-protection structures will have to be reinforced to meet the new standards. The Dutch Flood Protection Programme aims at accomplishing this task through innovative integrated projects such as construction of multi-functional flood defenses. In these projects, flood safety purposes will be combined with spatial planning, nature development, emergency management or other sectoral objectives. Therefore, implementation of dike reinforcement projects requires early involvement and collaboration between public and private sectors, different governmental actors and agencies. The development and implementation of such integrated projects has been an issue in Dutch flood risk management since long. Therefore, this article analyses how cross-sector collaboration within flood risk governance in the Netherlands has evolved over time, and how this development can be explained. The integrative framework for collaborative governance is applied as an analytical tool to map external factors framing possibilities as well as constraints for cross-sector collaboration in Dutch flood risk domain. Supported by an extensive document and literature analysis, the paper offers insights on how the system context and different drivers changing over time either promoted or hindered cross-sector collaboration between flood protection sector, urban development, nature conservation or any other sector involved in flood risk governance. The system context refers to the multi-layered and interrelated suite of conditions that influence the formation and performance of complex governance systems, such as collaborative governance regimes, whereas the drivers initiate and enable the overall process of collaboration. In addition, by applying a method of process tracing we identify a causal and chronological chain of events shaping cross-sectoral interaction in Dutch flood risk management. Our results indicate that in order to evaluate the performance of complex governance systems, it is important to firstly study the system context that shapes it. Clear understanding of the system conditions and drivers for collaboration gives insight into the possibilities of and constraints for effective performance of complex governance systems. The performance of the governance system is affected by the system conditions, while at the same time the governance system can also change the system conditions. Our results show that the sequence of changes within the system conditions and drivers over time affect how cross-sector interaction in Dutch flood risk governance system happens now. Moreover, we have traced the potential of this governance system to shape and change the system context.

Keywords: collaborative governance, cross-sector interaction, flood risk management, the Netherlands

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Authors: Eva Nolan, Timothy Mcnichols

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Gamers spend over 3 billion hours collectively playing video games a week, which is arguably not nearly enough time to indulge in the many benefits gaming has to offer. Much of the previous research on video gaming is centered on the effects of playing violent video games and the negative impacts they have on the individual. However, there is a dearth of research in the area of non-violent video games, specifically the emotional and cognitive benefits playing non-violent games can offer individuals. Current research in the area of video game play suggests there are many benefits to playing for an individual, such as decreasing symptoms of depression, decreasing stress, increasing positive emotions, inducing relaxation, decreasing anxiety, and particularly improving mood. One suggestion as to why video games may offer such benefits is that they possess ideal characteristics to create and maintain flow experiences, which in turn, is the subjective experience where an individual obtains a heightened and improved state of mind while they are engaged in a task where a balance of challenge and skill is found. Many video games offer a platform for collaborative gameplay, which can enhance the emotional experience of gaming through the feeling of social support and social inclusion. The present study was designed to examine the effects of collaborative gameplay and flow experience on participants’ perceived mood. To investigate this phenomenon, an in-between subjects design involving forty participants were randomly divided into two groups where they engaged in solo or collaborative gameplay. Each group represented an even number of frequent gamers and non-frequent gamers. Each participant played ‘The Lego Movie Videogame’ on the Playstation 4 console. The participant’s levels of flow experience and perceived mood were measured by the Flow State Scale (FSS) and the Positive and Negative Affect Schedule (PANAS). The following research hypotheses were investigated: (i.) participants in the collaborative gameplay condition will experience higher levels of flow experience and higher levels of mood than those in the solo gameplay condition; (ii.) participants who are frequent gamers will experience higher levels of flow experience and higher levels of mood than non-frequent gamers; and (iii.) there will be a significant positive relationship between flow experience and mood. If the estimated findings are supported, this suggests that engaging in collaborative gameplay can be beneficial for an individual’s mood and that experiencing a state of flow can also enhance an individual’s mood. Hence, collaborative gaming can be beneficial to promote positive emotions (higher levels of mood) through engaging an individual’s flow state.

Keywords: collaborative gameplay, flow experience, mood, games, positive emotions

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Authors: Jelena Vucicevic

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Reliability analysis represents a very important task in different areas of work. In any industry, this is crucial for maintenance, efficiency, safety and monetary costs. There are ways to calculate reliability, unreliability, failure density and failure rate. This paper will try to introduce another way of calculating reliability by using R statistical software. R is a free software environment for statistical computing and graphics. It compiles and runs on a wide variety of UNIX platforms, Windows and MacOS. The R programming environment is a widely used open source system for statistical analysis and statistical programming. It includes thousands of functions for the implementation of both standard and new statistical methods. R does not limit user only to operation related only to these functions. This program has many benefits over other similar programs: it is free and, as an open source, constantly updated; it has built-in help system; the R language is easy to extend with user-written functions. The significance of the work is calculation of time to failure or reliability in a new way, using statistic. Another advantage of this calculation is that there is no need for technical details and it can be implemented in any part for which we need to know time to fail in order to have appropriate maintenance, but also to maximize usage and minimize costs. In this case, calculations have been made on diesel generator fans but the same principle can be applied to any other part. The data for this paper came from a field engineering study of the time to failure of diesel generator fans. The ultimate goal was to decide whether or not to replace the working fans with a higher quality fan to prevent future failures. Seventy generators were studied. For each one, the number of hours of running time from its first being put into service until fan failure or until the end of the study (whichever came first) was recorded. Dataset consists of two variables: hours and status. Hours show the time of each fan working and status shows the event: 1- failed, 0- censored data. Censored data represent cases when we cannot track the specific case, so it could fail or success. Gaining the result by using R was easy and quick. The program will take into consideration censored data and include this into the results. This is not so easy in hand calculation. For the purpose of the paper results from R program have been compared to hand calculations in two different cases: censored data taken as a failure and censored data taken as a success. In all three cases, results are significantly different. If user decides to use the R for further calculations, it will give more precise results with work on censored data than the hand calculation.

Keywords: censored data, R statistical software, reliability analysis, time to failure

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Authors: Dewi Retno Sari Saputro, Purnami Widyaningsih, Hendrika Handayani

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Extreme data on an observation can occur due to unusual circumstances in the observation. The data can provide important information that can’t be provided by other data so that its existence needs to be further investigated. The method for obtaining extreme data is one of them using maxima block method. The distribution of extreme data sets taken with the maxima block method is called the distribution of extreme values. Distribution of extreme values is Gumbel distribution with two parameters. The parameter estimation of Gumbel distribution with maximum likelihood method (ML) is difficult to determine its exact value so that it is necessary to solve the approach. The purpose of this study was to determine the parameter estimation of Gumbel distribution with quasi-Newton BFGS method. The quasi-Newton BFGS method is a numerical method used for nonlinear function optimization without constraint so that the method can be used for parameter estimation from Gumbel distribution whose distribution function is in the form of exponential doubel function. The quasi-New BFGS method is a development of the Newton method. The Newton method uses the second derivative to calculate the parameter value changes on each iteration. Newton's method is then modified with the addition of a step length to provide a guarantee of convergence when the second derivative requires complex calculations. In the quasi-Newton BFGS method, Newton's method is modified by updating both derivatives on each iteration. The parameter estimation of the Gumbel distribution by a numerical approach using the quasi-Newton BFGS method is done by calculating the parameter values that make the distribution function maximum. In this method, we need gradient vector and hessian matrix. This research is a theory research and application by studying several journals and textbooks. The results of this study obtained the quasi-Newton BFGS algorithm and estimation of Gumbel distribution parameters. The estimation method is then applied to daily rainfall data in Purworejo District to estimate the distribution parameters. This indicates that the high rainfall that occurred in Purworejo District decreased its intensity and the range of rainfall that occurred decreased.

Keywords: parameter estimation, Gumbel distribution, maximum likelihood, broyden fletcher goldfarb shanno (BFGS)quasi newton

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Authors: Yenny Paola Morales Cortés, Fabián Rico Rodríguez, Juan Carlos Serrato Bermúdez, Carlos Arturo Martínez Riascos

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Numerous benefits of galactooligosaccharides (GOS) as prebiotics have motivated the study of enzymatic processes for their production. These processes have special complexities due to several factors that make difficult high productivity, such as enzyme type, reaction medium pH, substrate concentrations and presence of inhibitors, among others. In the present work the production of galactooligosaccharides (with different degrees of polymerization: two, three and four) from lactose was studied. The study considers the formulation of a mathematical model that predicts the production of GOS from lactose using the enzyme β-galactosidase. The effect of pH in the reaction was studied. For that, phosphate buffer was used and with this was evaluated three pH values (6.0.6.5 and 7.0). Thus it was observed that at pH 6.0 the enzymatic activity insignificant. On the other hand, at pH 7.0 the enzymatic activity was approximately 27 times greater than at 6.5. The last result differs from previously reported results. Therefore, pH 7.0 was chosen as working pH. Additionally, the enzyme concentration was analyzed, which allowed observing that the effect of the concentration depends on the pH and the concentration was set for the following studies in 0.272 mM. Afterwards, experiments were performed varying the lactose concentration to evaluate its effects on the process and to generate the data for the adjustment of the mathematical model parameters. The mathematical model considers the reactions of lactose hydrolysis and transgalactosylation for the production of disaccharides and trisaccharides, with their inverse reactions. The production of tetrasaccharides was negligible and, because of that, it was not included in the model. The reaction was monitored by HPLC and for the quantitative analysis of the experimental data the Matlab programming language was used, including solvers for differential equations systems integration (ode15s) and nonlinear problems optimization (fminunc). The results confirm that the transgalactosylation and hydrolysis reactions are reversible, additionally inhibition by glucose and galactose is observed on the production of GOS. In relation to the production process of galactooligosaccharides, the results show that it is necessary to have high initial concentrations of lactose considering that favors the transgalactosylation reaction, while low concentrations favor hydrolysis reactions.

Keywords: β-galactosidase, galactooligosaccharides, inhibition, lactose, Matlab, modeling

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Authors: Zhenzhen Xu, Chunfu Shao, Shengyou Wang, Chunjiao Dong

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To improve the satisfaction of residents' travel, this paper analyzes the characteristics and influencing factors of urban residents' travel behavior. First, a Multinominal Logit Model (MNL) model is built to analyze the characteristics of residents' travel behavior, reveal the influence of individual attributes, family attributes and travel characteristics on the choice of travel mode, and identify the significant factors. Then put forward suggestions for policy improvement. Finally, Support Vector Machine (SVM) and Multi-Layer Perceptron (MLP) models are introduced to evaluate the policy effect. This paper selects Futian Street in Futian District, Shenzhen City for investigation and research. The results show that gender, age, education, income, number of cars owned, travel purpose, departure time, journey time, travel distance and times all have a significant influence on residents' choice of travel mode. Based on the above results, two policy improvement suggestions are put forward from reducing public transportation and non-motor vehicle travel time, and the policy effect is evaluated. Before the evaluation, the prediction effect of MNL, SVM and MLP models was evaluated. After parameter optimization, it was found that the prediction accuracy of the three models was 72.80%, 71.42%, and 76.42%, respectively. The MLP model with the highest prediction accuracy was selected to evaluate the effect of policy improvement. The results showed that after the implementation of the policy, the proportion of public transportation in plan 1 and plan 2 increased by 14.04% and 9.86%, respectively, while the proportion of private cars decreased by 3.47% and 2.54%, respectively. The proportion of car trips decreased obviously, while the proportion of public transport trips increased. It can be considered that the measures have a positive effect on promoting green trips and improving the satisfaction of urban residents, and can provide a reference for relevant departments to formulate transportation policies.

Keywords: neural network, travel characteristics analysis, transportation choice, travel sharing rate, traffic resource allocation

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Authors: Inayat Ur Rahman Arshad

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Stevia rebaudiana B. is a shrubby perennial herb of Asteraceae family that possesses the unique ability of accumulative non caloric sweet Steviol Glycosides (SGs). The purpose of the study is to optimize sugar concentration, pH level and inoculum size for inducing the callus with optimum growth and efficient antibacterial potential. Three different experiments were conducted in which Callus explant from three-months-old already established callus of Stevia reabudiana of four different sizes were inoculated on Murashige and Skoog (MS) basal medium supplemented with five different sucrose concentration and pH adjusted at four different levels. Maximum callus induction 100, 87.5 and 85.33% was resulted in the medium supplemented with 30g/l sucrose, pH maintained at 5.5 and inoculated with 1.25g inoculum respectively. Similarly, the highest fresh weight 65.00, 75.50 and 50.53g/l were noted in medium fortified with 40g/l sucrose, inoculated 1.25g inoculum and 6.0 pH level respectively. However, the callus developed in medium containing 50g/l sucrose found highly antibacterial potent with 27.3 and 26.5mm inhibition zone against P. vulgaris and B. subtilize respectively. Similarly, the callus grown on medium inoculated with 1.00g inoculum resulted in maximum antibacterial potential against S. aureus and P. vulgaris with 25 and 23.72mm inhibition zones respectively. However, in the case of pH levels the medium maintained at 6.5pH showed maximum antibacterial activity against P. vulgaris, B.subtilis and E.coli with 27.9, 25 and 23.72mm respectively. The ethyl acetate extract of Stevia callus and leaves did not show antibacterial potential against Xanthomonas campestris and Clavebactor michiganensis. In the entire experiment the standard antibacterial agent Streptomycin showed the highest inhibition zones from the rest of the callus extract, however the pure DMSO (Dimethyl Sulfoxide) caused no inhibitory zone against any bacteria. From these findings it is concluded that among various levels sucrose at the rate of 40g L-1, pH 6.0 and inoculums 0.75g was found best for most of the growth and quality attributes including fresh weight, dry weight and antibacterial activities and therefore can be recommended for callus proliferation and antibacterial potential of Stevia rebaudiana

Keywords: Steviol Glycosides, Skoog, Murashige, Clavebactor michiganensis

Procedia PDF Downloads 73