Search results for: multiple query optimization

Authors: Amit Kumar, Himanshu Singal, Arnav Bhavsar

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In this modern era of automation, most of the academic exams and competitive exams are Multiple Choice Questions (MCQ). The responses of these MCQ based exams are recorded in the Optical Mark Reader (OMR) sheet. Evaluation of the OMR sheet requires separate specialized machines for scanning and marking. The sheets used by these machines are special and costs more than a normal sheet. Available process is non-economical and dependent on paper thickness, scanning quality, paper orientation, special hardware and customized software. This study tries to tackle the problem of evaluating the OMR sheet without any special hardware and making the whole process economical. We propose an image processing based algorithm which can be used to read and evaluate the scanned OMR sheets with no special hardware required. It will eliminate the use of special OMR sheet. Responses recorded in normal sheet is enough for evaluation. The proposed system takes care of color, brightness, rotation, little imperfections in the OMR sheet images.

Keywords: OMR, image processing, hough circle trans-form, interpolation, detection, binary thresholding

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Authors: Mateusz Paszko, Miroslaw Wendeker, Adam Majczak

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High temperature waste energy offers a number of management options. The most common energy recuperation systems, that are actually used to utilize energy from the high temperature sources are steam turbines working in a high pressure and temperature closed cycles. Due to the high costs of production of energy recuperation systems, especially rotary turbine discs equipped with blades, currently used solutions are limited in use with waste energy sources of temperature below 100 °C. This study presents the results of simulating the flow of the water vapor in various configurations of flow ducts in a reaction steam turbine based on Hero’s steam turbine. The simulation was performed using a numerical model and the ANSYS Fluent software. Simulation computations were conducted with use of the water vapor as an internal agent powering the turbine, which is fully safe for an environment in case of a device failure. The conclusions resulting from the conducted numerical computations should allow for optimization of the flow ducts geometries, in order to achieve the greatest possible efficiency of the turbine. It is expected that the obtained results should be useful for further works related to the development of the final version of a low drag steam turbine dedicated for low cost energy recuperation systems.

Keywords: energy recuperation, CFD analysis, waste energy, steam turbine

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Authors: Justin Woulfe

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Siloed logistics and supply chain management systems throughout the Department of Defense (DOD) has led to disparate approaches to modeling and simulation (M&S), a lack of understanding of how one system impacts the whole, and issues with “optimal” solutions that are good for one organization but have dramatic negative impacts on another. Many different systems have evolved to try to understand and account for uncertainty and try to reduce the consequences of the unknown. As the DoD undertakes expansive digital transformation initiatives, there is an opportunity to fuse and leverage traditionally disparate data into a centrally hosted source of truth. With a streamlined process incorporating machine learning (ML) and artificial intelligence (AI), advanced M&S will enable informed decisions guiding program success via optimized operational readiness and improved mission success. One of the current challenges is to leverage the terabytes of data generated by monitored systems to provide actionable information for all levels of users. The implementation of a cloud-based application analyzing data transactions, learning and predicting future states from current and past states in real-time, and communicating those anticipated states is an appropriate solution for the purposes of reduced latency and improved confidence in decisions. Decisions made from an ML and AI application combined with advanced optimization algorithms will improve the mission success and performance of systems, which will improve the overall cost and effectiveness of any program. The Systecon team constructs and employs model-based simulations, cutting across traditional silos of data, aggregating maintenance, and supply data, incorporating sensor information, and applying optimization and simulation methods to an as-maintained digital twin with the ability to aggregate results across a system’s lifecycle and across logical and operational groupings of systems. This coupling of data throughout the enterprise enables tactical, operational, and strategic decision support, detachable and deployable logistics services, and configuration-based automated distribution of digital technical and product data to enhance supply and logistics operations. As a complete solution, this approach significantly reduces program risk by allowing flexible configuration of data, data relationships, business process workflows, and early test and evaluation, especially budget trade-off analyses. A true capability to tie resources (dollars) to weapon system readiness in alignment with the real-world scenarios a warfighter may experience has been an objective yet to be realized to date. By developing and solidifying an organic capability to directly relate dollars to readiness and to inform the digital twin, the decision-maker is now empowered through valuable insight and traceability. This type of educated decision-making provides an advantage over the adversaries who struggle with maintaining system readiness at an affordable cost. The M&S capability developed allows program managers to independently evaluate system design and support decisions by quantifying their impact on operational availability and operations and support cost resulting in the ability to simultaneously optimize readiness and cost. This will allow the stakeholders to make data-driven decisions when trading cost and readiness throughout the life of the program. Finally, sponsors are available to validate product deliverables with efficiency and much higher accuracy than in previous years.

Keywords: artificial intelligence, digital transformation, machine learning, predictive analytics

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Authors: Akshaya P., Priyanjali Prabhkaran

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The paper examines the formulation of strategies to develop a comprehensive model of city level water utility management to addressing urban sanitation issues. The water is prime life sustaining natural resources and nature’s gifts to all living beings on the earth multiple urban sanitation issues are addressed in the supply of water in a city. Many of these urban sanitation issues are linked to population expansion and economic inequity. Increased usage of water and the development caused water scarcity. The lack of water supply results increases the chance of unhygienic situations in the cities. In this study, the urban sanitation issues are identified with respect to water supply and utility management. The study compared based on their best practices and initiatives. From this, best practices and initiatives identify suitable sustainable measures to address water supply issues in the city level. The paper concludes with the listed provision that should be considered suitable measures for water supply and utility management in city level to address the urban sanitation issues.

Keywords: water, benchmarking water supply, water supply networks, water supply management

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Authors: Fethi Soltani, Adel Almarashi, Idir Mechai

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Tikhonov regularization and reproducing kernels are the most popular approaches to solve ill-posed problems in computational mathematics and applications. And the Fourier multiplier operators are an essential tool to extend some known linear transforms in Euclidean Fourier analysis, as: Weierstrass transform, Poisson integral, Hilbert transform, Riesz transforms, Bochner-Riesz mean operators, partial Fourier integral, Riesz potential, Bessel potential, etc. Using the theory of reproducing kernels, we construct a simple and efficient representations for some class of Fourier multiplier operators Tm on the Paley-Wiener space Hh. In addition, we give an error estimate formula for the approximation and obtain some convergence results as the parameters and the independent variables approaches zero. Furthermore, using numerical quadrature integration rules to compute single and multiple integrals, we give numerical examples and we write explicitly the extremal function and the corresponding Fourier multiplier operators.

Keywords: fourier multiplier operators, Gauss-Kronrod method of integration, Paley-Wiener space, Tikhonov regularization

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Authors: A. Prajapati, K. L. Koo, F. Ghassemi, M. Mulimakwenda

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In the UK, as the volume of non-linear loads connected to transmission grid continues to rise steeply, the harmonic distortion levels on transmission network are becoming a serious concern for the network owners and system operators. This paper outlines the findings of the study conducted to verify the proposal that the harmonic mitigation could be optimized and can be managed economically and effectively at the transmission network level by the Transmission Owner (TO) instead of the individual polluter connected to the grid. Harmonic mitigation studies were conducted on selected regions of the transmission network in England for recently connected offshore wind power plants to strategize and optimize selected harmonic filter options. The results – filter volume and capacity – were then compared against the mitigation measures adopted by the individual connections. Estimation ratios were developed based on the actual installed and optimal proposed filters. These estimation ratios were then used to derive harmonic filter requirements for future contracted connections. The study has concluded that a saving of 37% in the filter volume/capacity could be achieved if the TO is to centrally manage the harmonic mitigation instead of individual polluter installing their own mitigation solution.

Keywords: C-type filter, harmonics, optimization, offshore wind farms, interconnectors, HVDC, renewable energy, transmission owner

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Authors: Luis Miguel Méndez Díaz

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In this article, a mathematics teaching-learning strategy will be presented, specifically differential calculus in one variable, in a fun and competitive space in which the action on the part of the student is manifested and not only the repetition of information on the part of the teacher. Said action refers to motivating, problematizing, summarizing, and coordinating a game of dominoes whose thematic cards are designed around the basic and main contents of differential calculus. The strategies for teaching this area are diverse and precisely the game of dominoes is one of the most used strategies in the practice of mathematics because it stimulates logical reasoning and mental abilities. The objective on this investigation is to identify the way in which the game of dominoes affects the learning and understanding of fundamentals concepts of differential calculus in one variable through experimentation carried out on students of the first semester of the School of Engineering and Sciences of the Technological Institute of Monterrey Campus Querétaro. Finally, the results of this study will be presented and the use of this strategy in other topics around mathematics will be recommended to facilitate logical and meaningful learning in students.

Keywords: collaborative learning, logical-mathematical intelligence, mathematical games, multiple intelligences

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Authors: Laila Montaser, Hala Gabr, Maha El-Bassuony, Gehan Tawfeek

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Orthotropic liver transplantation (OLT) is the final procedure of both end stage and metabolic liver diseases. Hepatocyte transplantation is an alternative for OLT, but the sources of hepatocytes are limited. Bone marrow mesenchymal stem cells (BM-MSCs) can differentiate into hepatocyte-like cells and are a potential alternative source for hepatocytes. The MSCs from bone marrow are a promising target population as they are capable of differentiating along multiple lineages and, at least in vitro, have significant expansion capability. MSCs from bone marrow may have the potential to differentiate in vitro and in vivo into hepatocytes. Our study examined whether mesenchymal stem cells (MSCs), which are stem cells originated from human bone marrow, are able to differentiate into functional hepatocyte-like cells in vitro. Our aim was to investigate the differentiation potential of BM-MSCs into hepatocyte-like cells. Adult stem cell therapy could solve the problem of degenerative disorders, including liver disease.

Keywords: bone marrow, differentiation, hepatocyte, stem cells

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Authors: Khon Natalya, Kim Alla, Mukhitdinova Tansulu

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The aim of the research was to reveal the link between mental variables, such as spatial abilities, memory, intellect and professional experience of drivers. Participants were allocated within 4 groups: no experience, inexperienced, skilled and professionals (total 85 participants). Level of ability for spatial navigation and indicator of nonverbal memory grow along the process of accumulation of driving experience. At high levels of driving experience this tendency is especially noticeable. The professionals having personal achievements in driving (racing) differ from skilled drivers in better feeling of direction which is specific for them not just in a short-term situation of an experimental task, but in life-size perspective. The level of ability of mental rotation does not grow with growth of driving experience which confirms the multiple intelligence theory according to which spatial abilities represent specific, other than logical intelligence type of intellect. The link between spatial abilities, memory, intellect, and professional experience of drivers seems to be different relating spatial navigation or mental rotation as different kinds of spatial abilities.

Keywords: memory, spatial ability, intellect, drivers

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Authors: Jiaoya Huang, Jianghong Liu

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This paper endeavors to comprehend and scrutinize the entrepreneurial development process within Chinese cultural and creative small and medium-sized enterprises (SMEs), as well as the factors that impinge on entrepreneurs' recognition and exploitation of entrepreneurial opportunities from the vantage point of institutional theory. The study is centered around three key research questions: namely, the drivers and impediments for entrepreneurs to identify opportunities within three prominent Chinese cultural and creative regions and the influence of institutional facets on the exploitation and recognition of opportunities within the cultural industry. Adopting a qualitative interpretivist research paradigm, a comparative multiple case study design is utilized. Semi-structured interviews will be carried out with founders and mid-level professionals of SMEs in Beijing, Shanghai, and Guangzhou, which are chosen in accordance with specific criteria. The data will be analyzed through an inductive thematic approach. Anticipatedly, this research will contribute to bridging the research gap in the nexus between institutional theory and entrepreneurial opportunities within the context of cultural and creative industries.

Keywords: entrepreneurial opportunities, cultural and creative industries, institutional theory, Chinese SMEs

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Authors: Amita Barik, Ranjit Prasad Bahadur

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We investigate the role of water molecules in 89 protein-RNA complexes taken from the Protein Data Bank. Those with tRNA and single-stranded RNA are less hydrated than with duplex or ribosomal proteins. Protein-RNA interfaces are hydrated less than protein-DNA interfaces, but more than protein-protein interfaces. Majority of the waters at protein-RNA interfaces makes multiple H-bonds; however, a fraction does not make any. Those making Hbonds have preferences for the polar groups of RNA than its partner protein. The spatial distribution of waters makes interfaces with ribosomal proteins and single-stranded RNA relatively ‘dry’ than interfaces with tRNA and duplex RNA. In contrast to protein-DNA interfaces, mainly due to the presence of the 2’OH, the ribose in protein-RNA interfaces is hydrated more than the phosphate or the bases. The minor groove in protein-RNA interfaces is hydrated more than the major groove, while in protein-DNA interfaces it is reverse. The strands make the highest number of water-mediated H-bonds per unit interface area followed by the helices and the non-regular structures. The preserved waters at protein-RNA interfaces make higher number of H-bonds than the other waters. Preserved waters contribute toward the affinity in protein-RNA recognition and should be carefully treated while engineering protein-RNA interfaces.

Keywords: h-bonds, minor-major grooves, preserved water, protein-RNA interfaces

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Authors: Payam Mousavi, Andrew L. Stewart, Huiwen You, Aryeh F. G. Fayerman

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We present a decision-support tool to assist an operator in the detection and tracking of a suspect vehicle traveling to an unknown target destination. Multiple data sources, such as traffic cameras, traffic information, weather, etc., are integrated and processed in real-time to infer a suspect’s intended destination chosen from a list of pre-determined high-value targets. Previously, we presented our work in the detection and tracking of vehicles using traffic and airborne cameras. Here, we focus on the fusion and processing of that information to predict a suspect’s behavior. The network of cameras is represented by a directional graph, where the edges correspond to direct road connections between the nodes and the edge weights are proportional to the average time it takes to travel from one node to another. For our experiments, we construct our graph based on the greater Los Angeles subset of the Caltrans’s “Performance Measurement System” (PeMS) dataset. We propose a Bayesian approach where a posterior probability for each target is continuously updated based on detections of the suspect in the live video feeds. Additionally, we introduce the concept of ‘soft interventions’, inspired by the field of Causal Inference. Soft interventions are herein defined as interventions that do not immediately interfere with the suspect’s movements; rather, a soft intervention may induce the suspect into making a new decision, ultimately making their intent more transparent. For example, a soft intervention could be temporarily closing a road a few blocks from the suspect’s current location, which may require the suspect to change their current course. The objective of these interventions is to gain the maximum amount of information about the suspect’s intent in the shortest possible time. Our system currently operates in a human-on-the-loop mode where at each step, a set of recommendations are presented to the operator to aid in decision-making. In principle, the system could operate autonomously, only prompting the operator for critical decisions, allowing the system to significantly scale up to larger areas and multiple suspects. Once the intended target is identified with sufficient confidence, the vehicle is reported to the authorities to take further action. Other recommendations include a selection of road closures, i.e., soft interventions, or to continue monitoring. We evaluate the performance of the proposed system using simulated scenarios where the suspect, starting at random locations, takes a noisy shortest path to their intended target. In all scenarios, the suspect’s intended target is unknown to our system. The decision thresholds are selected to maximize the chances of determining the suspect’s intended target in the minimum amount of time and with the smallest number of interventions. We conclude by discussing the limitations of our current approach to motivate a machine learning approach, based on reinforcement learning in order to relax some of the current limiting assumptions.

Keywords: autonomous surveillance, Bayesian reasoning, decision support, interventions, patterns of life, predictive analytics, predictive insights

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Authors: Abdellatif Amouri, Sami Boudabbous

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The current study provides insights on the importance of entrepreneurial coaching as a source of developing entrepreneurial intentions among entrepreneurs and a determinant factor of business creation process and growth. Coaching, which implies exchange of adequate information and a mutual understanding between entrepreneurs and their partners, requires a better mutual knowledge of the representations and the perceptions of ideas which are widely present in their dealings and transactions. Therefore, to analyze entrepreneurs’ perceptions of business creation, we addressed a survey questionnaire to a group of Tunisian entrepreneurs and experts in business creation to indicate their level of approval concerning the prominence of coaching. The factor analysis indicates that more than 60% of the respondents believe that each statement reflects an aspect of coaching, with no bias to its position in the entrepreneurial process. Therefore, the image drawn from our respondents’ perceptions is that an entrepreneur is rather "constructed" and "shaped" by multiple apprenticeships both before and during the entrepreneurial act, through an accompaniment process and within interactions with trainers, consultants or professionals in starting a business. Similarly, the results indicate that the poor support structures and lack of accompaniment procedures stand as an obstacle impeding the development of entrepreneurial intention among business creators.

Keywords: Entrepreneurial Behavior, Entrepreneurial Coaching, Entrepreneurial Intention, Perceptions, Venture Creation

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Authors: Maram Saleh

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Knowledge has become an essential resource in today’s economy and become the most important asset of maintaining competition advantage in organizations. The importance of knowledge has made organizations to manage their knowledge assets and resources through all multiple knowledge management stages such as: Knowledge Creation, knowledge storage, knowledge sharing and knowledge use. Researches on data mining are continues growing over recent years on both business and educational fields. Data mining is one of the most important steps of the knowledge discovery in databases process aiming to extract implicit, unknown but useful knowledge and it is considered as significant subfield in knowledge management. Data miming have the great potential to help organizations to focus on extracting the most important information on their data warehouses. Data mining tools and techniques can predict future trends and behaviors, allowing businesses to make proactive, knowledge-driven decisions. This review paper explores the applications of data mining techniques in supporting knowledge management process as an effective knowledge discovery technique. In this paper, we identify the relationship between data mining and knowledge management, and then focus on introducing some application of date mining techniques in knowledge management for some real life domains.

Keywords: Data Mining, Knowledge management, Knowledge discovery, Knowledge creation.

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Authors: A. K. M. Rezaul Karim, Abu Yusuf Mahmud, S. H. Mahmud

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The study aimed to investigate whether the affect (experience of feeling or emotion) of ethnic minority people can be predicted by gender and marital status. Toward this end, positive affect and negative affect of 103 adult indigenous persons were measured. Analysis of data in multiple regressions demonstrated that both gender and marital status are significantly associated with positive affect (Gender: β=.318, p < .001; Marital status: β=.201, p < .05), but not with negative affect. Results indicated that the indigenous males have 0.32 standard deviations increased positive affect as compared to the indigenous females and that married individuals have 0.20 standard deviations increased positive affect as compared to their unmarried counterparts. These findings advance our understanding that gender and marital status inequalities in the experience of emotion are not specific to the mainstream society; rather it is a generalized picture of all societies. In general, men possess more positive affect than females; married persons possess more positive affect than the unmarried persons.

Keywords: positive affect, negative affect, ethnic minority, gender, marital status

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Authors: J. Hidalgo de Quintana, I. Stoner, M. Tackett, G. Doran, C. Rafferty, A. Windemuth, J. Tytell, D. Pregibon

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We have developed the Multiplexed Circulating microRNA assay that allows the detection of up to 68 microRNA targets per sample. The assay combines particle­based multiplexing, using patented Firefly hydrogel particles, with single­ step RT-PCR signal. Thus, the Circulating microRNA assay leverages PCR sensitivity while eliminating the need for separate reverse transcription reactions and mitigating amplification biases introduced by target­-specific qPCR. Furthermore, the ability to multiplex targets in each well eliminates the need to split valuable samples into multiple reactions. Results from the Circulating microRNA assay are interpreted using Firefly Analysis Workbench, which allows visualization, normalization, and export of experimental data. To aid discovery and validation of biomarkers, we have generated fixed panels for Oncology, Cardiology, Neurology, Immunology, and Liver Toxicology. Here we present the data from several studies investigating circulating and tumor microRNA, showcasing the ability of the technology to sensitively and specifically detect microRNA biomarker signatures from fluid specimens.

Keywords: biomarkers, biofluids, miRNA, photolithography, flowcytometry

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Authors: J. Skibinski, P. Caban, T. Wejrzanowski, K. J. Kurzydlowski

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In the present study, numerical simulations of heat and mass transfer during gallium nitride growth process in Metal Organic Vapor Phase Epitaxy reactor AIX-200/4RF-S is addressed. Existing knowledge about phenomena occurring in the MOVPE process allows to produce high quality nitride based semiconductors. However, process parameters of MOVPE reactors can vary in certain ranges. Main goal of this study is optimization of the process and improvement of the quality of obtained crystal. In order to investigate this subject a series of computer simulations have been performed. Numerical simulations of heat and mass transfer in GaN epitaxial growth process have been performed to determine growth rate for various mass flow rates and pressures of reagents. According to the fact that it’s impossible to determine experimentally the exact distribution of heat and mass transfer inside the reactor during the process, modeling is the only solution to understand the process precisely. Main heat transfer mechanisms during MOVPE process are convection and radiation. Correlation of modeling results with the experiment allows to determine optimal process parameters for obtaining crystals of highest quality.

Keywords: Finite Volume Method, semiconductors, epitaxial growth, metalorganic vapor phase epitaxy, gallium nitride

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Authors: Pawit Tangviroon, Apichit Svang-Ariyaskul

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Rubber seed oil is an attractive alternative feedstock for biodiesel production because it is not related to food-chain plant. Rubber seed oil contains large amount of free fatty acids, which causes problem in biodiesel production. Free fatty acids can react with alkaline catalyst in biodiesel production. Acid esterification is used as pre-treatment to convert unwanted compound to desirable biodiesel. Phase separation of oil and methanol occurs at low ratio of methanol to oil and causes low reaction rate and conversion. Acid esterification requires large excess of methanol in order to increase the miscibility of methanol in oil and accordingly, it is a more expensive separation process. In this work, the kinetics of esterification of rubber seed oil with methanol is developed from available experimental results. Reactive distillation process was designed by using Aspen Plus program. The effects of operating parameters such as feed ratio, molar reflux ratio, feed temperature, and feed stage are investigated in order to find the optimum conditions. Results show that the reactive distillation process is proved to be better than conventional process. It consumes less feed methanol and less energy while yielding higher product purity than the conventional process. This work can be used as a guideline for further development to industrial scale of biodiesel production using reactive distillation.

Keywords: biodiesel, reactive distillation, rubber seed oil, transesterification

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Authors: Shibo Wei, Ting Jiang

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Convolutional-recurrent neural networks (CRN) have achieved much success recently in the speech enhancement field. The common processing method is to use the convolution layer to compress the feature space by multiple upsampling and then model the compressed features with the LSTM layer. At last, the enhanced speech is obtained by deconvolution operation to integrate the global information of the speech sequence. However, the feature space compression process may cause the loss of information, so we propose to model the upsampling result of each step with the residual LSTM layer, then join it with the output of the deconvolution layer and input them to the next deconvolution layer, by this way, we want to integrate the global information of speech sequence better. The experimental results show the network model (RES-CRN) we introduce can achieve better performance than LSTM without residual and overlaying LSTM simply in the original CRN in terms of scale-invariant signal-to-distortion ratio (SI-SNR), speech quality (PESQ), and intelligibility (STOI).

Keywords: convolutional-recurrent neural networks, speech enhancement, residual LSTM, SI-SNR

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Authors: Seyed Sadegh Naseralavi, Sadegh Balaghi, Ehsan Khojastehfar

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Time history dynamic analysis of structures is considered as an exact method while being computationally intensive. Filtration of earthquake strong ground motions applying wavelet transform is an approach towards reduction of computational efforts, particularly in optimization of structures against seismic effects. Wavelet transforms are categorized into continuum and discrete transforms. Since earthquake strong ground motion is a discrete function, the discrete wavelet transform is applied in the present paper. Wavelet transform reduces analysis time by filtration of non-effective frequencies of strong ground motion. Filtration process may be repeated several times while the approximation induces more errors. In this paper, strong ground motion of earthquake has been filtered once applying each wavelet. Strong ground motion of Northridge earthquake is filtered applying various wavelets and dynamic analysis of sampled shear and moment frames is implemented. The error, regarding application of each wavelet, is computed based on comparison of dynamic response of sampled structures with exact responses. Exact responses are computed by dynamic analysis of structures applying non-filtered strong ground motion.

Keywords: wavelet transform, computational error, computational duration, strong ground motion data

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Authors: Taher Eid Shaaban Ahmed Mousa

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Non-Alcoholic fatty liver disease (NAFLD) is a major cause of multiple liver disorders, which strongly linked to a poor lifestyle. This study aiming to elucidate the exercise program’s effectiveness on hepatic fat mobilization among nonalcoholic fatty liver patients. Subjects: A purposive sample of 150 adult male & female patients. Setting: National institute of liver out patient's clinics of Menoufia University. Tools: three tools I: An interviewing structured questionnaire, II: International Physical Activity Questionnaire, III: compliance assessment sheet. Results: There was statistically significant difference pre and post exercise program regarding total body weight, physical activity level and compliance that prevent new fat development with resolution of existing one. Conclusion: regular exercise is the best implemented approach as an initial step for the prevention, treatment and management of NAFLD. Recommendation: It is highly important to unravel the mechanism and dose by which each exercise specifically resolve various stages of liver diseases.

Keywords: exercise program, hebatic fat mobilization, nonalcoholic fatty liver patients, sport science

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Authors: Jayprakash Yadav, Nivedita Patra

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Polyhydroxybutyrate (PHB) is an interesting material in the field of medical science, pharmaceutical industries, and tissue engineering because of its properties such as biodegradability, biocompatibility, hydrophobicity, and elasticity. PHB is naturally accumulated by several microbes in their cytoplasm during the metabolic process as energy reserve material. PHB can be extracted from cell biomass using halogenated hydrocarbons, chemicals, and enzymes. In this study, a cheaper and non-toxic solvent, acetone, was used for the extraction process. The different parameters like acetone percentage, and solvent pH, process temperature, and incubation periods were optimized using the Response Surface Methodology (RSM). RSM was performed and the determination coefficient (R2) value was found to be 0.8833 from the quadratic regression model with no significant lack of fit. The designed RSM model results indicated that the fitness of the response variable was significant (P-value < 0.0006) and satisfactory to denote the relationship between the responses in terms of PHB recovery and purity with respect to the values of independent variables. Optimum conditions for the maximum PHB recovery and purity were found to be solvent pH 7, extraction temperature - 43 °C, incubation time - 70 minutes, and percentage acetone – 30 % from this study. The maximum predicted PHB recovery was found to be 0.845 g/g biomass dry cell weight and the purity was found to be 97.23 % using the optimized conditions.

Keywords: acetone, PHB, RSM, halogenated hydrocarbons, extraction, bacillus subtilis.

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Authors: Umar Albalawi, Sang C. Suh, Jinoh Kim

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As internet continues to expand its usage with an enormous number of applications, cyber-threats have significantly increased accordingly. Thus, accurate detection of malicious traffic in a timely manner is a critical concern in today’s Internet for security. One approach for intrusion detection is to use Machine Learning (ML) techniques. Several methods based on ML algorithms have been introduced over the past years, but they are largely limited in terms of detection accuracy and/or time and space complexity to run. In this work, we present a novel method for intrusion detection that incorporates a set of supervised learning algorithms. The proposed technique provides high accuracy and outperforms existing techniques that simply utilizes a single learning method. In addition, our technique relies on partial flow information (rather than full information) for detection, and thus, it is light-weight and desirable for online operations with the property of early identification. With the mid-Atlantic CCDC intrusion dataset publicly available, we show that our proposed technique yields a high degree of detection rate over 99% with a very low false alarm rate (0.4%).

Keywords: intrusion detection, supervised learning, traffic classification, computer networks

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Authors: Haitao Yang, Zhenjiang Ruan, Fei Xu, Lanting Xia

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Industry data centers often need to sync data changes reliably and instantly from a large-scale of heterogeneous autonomous relational databases accessed via the not-so-reliable Internet, for which a practical universal sync middle of low maintenance and operation costs is most wanted, but developing such a product and adapting it for various scenarios are a very sophisticated and continuous practice. The authors have been devising, applying, and optimizing a generic sync middleware system, named GSMS since 2006, holding the principles or advantages that the middleware must be SyncML-compliant and transparent to data application layer logic, need not refer to implementation details of databases synced, does not rely on host computer operating systems deployed, and its construction is light weighted and hence, of low cost. A series of ultimate experiments with GSMS sync performance were conducted for a persuasive example of a source relational database that underwent a broad range of write loads, say, from one thousand to one million intensive writes within a few minutes. The tests proved that GSMS has achieved an instant sync level of well below a fraction of millisecond per record sync, and GSMS’ smooth performances under ultimate write loads also showed it is feasible and competent.

Keywords: heterogeneous massive data, instantly sync intensive writes, Internet generic middleware design, optimization

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Authors: Mohammed Bala Banki

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This paper examines the relationship between employee satisfaction, customer satisfaction and loyalty in fast food restaurants in Nigeria and ascertains if prior job experience of employees before their present job moderate the relationship between customer satisfaction and loyalty. Data for this study were collected from matched pairs of employees and customers of fast restaurants in four Nigerian cities. A Structural Equation Modelling (SEM) was used for the analysis to test the proposed relationships and hierarchical multiple regression was performed in SPSS 22 to test moderating effect. Findings suggest that there is a direct positive and significant relationship between employee satisfaction and customer satisfaction and customer satisfaction and loyalty while the path between employee satisfaction and customer loyalty is insignificant. Results also reveal that employee’s prior job experience significantly moderate the relationship between customer satisfaction and loyalty. Further analysis indicates that employees with more years of experience provide more fulfilling services to restaurants customers. This paper provides some theoretical and managerial implications for academia and practitioners.

Keywords: employee’s satisfaction, customer’s satisfaction, loyalty, employee’s prior job experience, fast food industry

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Authors: Lei Ye, Min Liu, Yong-Li Gao, Jun Zhang

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Purpose: The aims of the study are to investigate the status of health-promoting lifestyle and to compare the healthy lifestyle of emergency nurses in different levels of hospitals in Sichuan province, China. The investigation is mainly about the health-promoting lifestyle, including spiritual growth, health responsibility, physical activity, nutrition, interpersonal relations, stress management. Then the factors were analyzed influencing the health-promoting lifestyle of emergency nurses in hospitals of Sichuan province in order to find the relevant models to provide reference evidence for intervention. Study Design: A cross-sectional research method was adopted. Stratified cluster sampling, based on geographical location, was used to select the health facilities of 1389 emergency nurses in 54 hospitals from Sichuan province in China. Method: The 52-item, six-factor structure Health-Promoting Lifestyle Profile II (HPLP- II) instrument was used to explore participants’ self-reported health-promoting behaviors and measure the dimensions of health responsibility, physical activity, nutrition, interpersonal relations, spiritual growth, and stress management. Demographic characteristics, education, work duration, emergency nursing work duration and self-rated health status were documented. Analysis: Data were analyzed through SPSS software ver. 17.0. Frequency, percentage, mean ± standard deviation were used to describe the general information, while the Nonparametric Test was used to compare the constituent ratio of general data of different hospitals. One-way ANOVA was used to compare the scores of health-promoting lifestyle in different levels hospital. A multiple linear regression model was established. P values which were less than 0.05 determined statistical significance in all analyses. Result: The survey showed that the total score of health-promoting lifestyle of nurses at emergency departments in Sichuan Province was 120.49 ± 21.280. The relevant dimensions are ranked by scores in descending order: interpersonal relations, nutrition, health responsibility, physical activity, stress management, spiritual growth. The total scores of the three-A hospital were the highest (121.63 ± 0.724), followed by the senior class hospital (119.7 ± 1.362) and three-B hospital (117.80 ± 1.255). The difference was statistically significant (P=0.024). The general data of nurses was used as the independent variable which includes age, gender, marital status, living conditions, nursing income, hospital level, Length of Service in nursing, Length of Service in emergency, Professional Title, education background, and the average number of night shifts. The total score of health-promoting lifestyle was used as dependent variable; Multiple linear regression analysis method was adopted to establish the regression model. The regression equation F = 20.728, R2 = 0.061, P < 0.05, the age, gender, nursing income, turnover intention and status of coping stress affect the health-promoting lifestyle of nurses in emergency department, the result was statistically significant (P < 0.05 ). Conclusion: The results of the investigation indicate that it will help to develop health promoting interventions for emergency nurses in all levels of hospital in Sichuan Province through further research. Managers need to pay more attention to emergency nurses’ exercise, stress management, self-realization, and conduct intervention in nurse training programs.

Keywords: emergency nurse, health-promoting lifestyle profile II, health behaviors, lifestyle

Procedia PDF Downloads 285

Authors: Réka Sárközi, Péter Iványi, Attila B. Széll

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The aim of this paper is to present the adaptation of the dome construction tool for formex algebra to the parametric design software Grasshopper. Formex algebra is a mathematical system, primarily used for planning structural systems such like truss-grid domes and vaults, together with the programming language Formian. The goal of the research is to allow architects to plan truss-grid structures easily with parametric design tools based on the versatile formex algebra mathematical system. To produce regular structures, coordinate system transformations are used and the dome structures are defined in spherical coordinate system. Owing to the abilities of the parametric design software, it is possible to apply further modifications on the structures and gain special forms. The paper covers the basic dome types, and also additional dome-based structures using special coordinate-system solutions based on spherical coordinate systems. It also contains additional structural possibilities like making double layer grids in all geometry forms. The adaptation of formex algebra and the parametric workflow of Grasshopper together give the possibility of quick and easy design and optimization of special truss-grid domes.

Keywords: parametric design, structural morphology, space structures, spherical coordinate system

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Authors: Gautam Kumar Saharia, Sagardeep Talukdar, Riki Dutta, Sudipta Nandy

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The physics-informed neural network (PINN) method opens up an approach for numerically solving nonlinear partial differential equations leveraging fast calculating speed and high precession of modern computing systems. We construct the PINN based on a strong universal approximation theorem and apply the initial-boundary value data and residual collocation points to weekly impose initial and boundary conditions to the neural network and choose the optimization algorithms adaptive moment estimation (ADAM) and Limited-memory Broyden-Fletcher-Golfard-Shanno (L-BFGS) algorithm to optimize learnable parameter of the neural network. Next, we improve the PINN with a weighted loss function to obtain both the bright and dark soliton solutions of the Fokas-Lenells equation (FLE). We find the proposed scheme of adjustable weight coefficients into PINN has a better convergence rate and generalizability than the basic PINN algorithm. We believe that the PINN approach to solve the partial differential equation appearing in nonlinear optics would be useful in studying various optical phenomena.

Keywords: deep learning, optical soliton, physics informed neural network, partial differential equation

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Authors: Robert D. Hanser, Gina M. Hanser

Abstract:

This paper provides an overview of Coordinated Community Response Teams (CCRT) to Intimate Partner Violence (IPV). The CCRT, as a partnership and collaborative effort between multiple agencies is highlighted. This paper is a legal analysis that showcases new legislation and legal requirements in the United States for investigating, processing, and reporting to acts of victimization have transformed the role of the university’s CCRT on campus, making its mission all the more important, both internal and external to the campus. As a specific example, discussion of the CCRT in Northeast Louisiana at the University of Louisiana at Monroe is provided as an example of involvement in this initiative, where federal grant funding has allowed a micro version of the region’s CCRT to be implemented on that campus. Simultaneously, university personnel also work with external agencies throughout the community in intimate partner violence response. Amidst this, the result is a genuine partnership between practitioners and researchers who work together to provide public awareness, prevention, first-responder, and intervention services in a comprehensive manner throughout Northeast Louisiana.

Keywords: interperaonal violence, sexual assault, dating violence, campus violence

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Authors: Shahzamani Kiana, Esmaeil Lashgarian Hamed, Merat Shahin

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HCV and GBV-C belong to the Flaviviridae family of viruses and GBV-C is the closest virus to HCV genetically. Accumulative research is in progress all over the world to clarify clinical aspects of GBV-C. Possibility of interaction between HCV and GBV-C and also its consequence with other liver diseases are the most important clinical aspects which encourage researchers to develop a technique for simultaneous detection of these viruses. In this study a SYBR Green multiplex real time RT-PCR technique as a new economical and sensitive method was optimized for simultaneous detection of HCV/GBV-C in HCV positive plasma samples. After designing and selection of two pairs of specific primers for HCV and GBV-C, SYBR Green Real time RT-PCR technique optimization was performed separately for each virus. Establishment of multiplex PCR was the next step. Finally our technique was performed on positive and negative plasma samples. 89 cirrhotic HCV positive plasma samples (29 of genotype 3 a and 27 of genotype 1a) were collected from patients before receiving treatment. 14% of genotype 3a and 17.1% of genotype 1a showed HCV/GBV-C co-infection. As a result, 13.48% of 89 samples had HCV/GBV-C co-infection that was compatible with other results from all over the world. Data showed no apparent influence of HGV co-infection on the either clinical or virological aspect of HCV infection. Furthermore, with application of multiplex Real time RT-PCR technique, more time and cost could be saved in clinical-research settings.

Keywords: HCV, GBV-C, cirrhotic patients, multiplex real time RT- PCR

Procedia PDF Downloads 296