Search results for: Management Information Systems (MIS)

Authors: Tatjana Jurić, Bojana Blagojević, Denis Uka, Ružica Ždero Pavlović, Boris M. Popović

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Natural deep eutectic solvents (NADES) represent a class of modern systems that have been developed as a green alternative to toxic organic solvents, which are commonly used as extraction media. It has been considered that hydrogen bonding is the main interaction leading to the formation of NADES. The aim of this study was phytochemical characterization and determination of the antioxidant and antibacterial activity of Mentha piperita leaf extracts obtained by six choline chloride-based NADES. NADES were prepared by mixing choline chloride with different hydrogen bond donors in 1:1 molar ratio following the addition of 30% (w/w) water. The mixtures were then heated (60 °C) and stirred (650 rpm) until the clear homogenous liquids were obtained. The Mentha piperita extracts were prepared by mixing 75 mg of peppermint leaves with 1 mL of NADES following by the heating and stirring (60 °C, 650 rpm) within 30 min. The content of six phenolics in extracts was determined using HPLC-PDA. The dominant compounds presented in peppermint leaves - rosmarinic acid and luteolin 7-O-glucoside, were extracted by NADES at a similar level as 70% ethanol. The microdilution method was applied to test the antibacterial activity of extracts. Compared with 70% ethanol, all NADES systems showed higher antibacterial activity towards Pseudomonas aeruginosa (Gram -), Staphylococcus aureus (Gram +), Escherichia coli (Gram -), and Salmonella enterica (Gram -), especially NADES containing organic acids. The majority of NADES extracts showed a better ability to neutralize DPPH radical than conventional solvent and similar ability to reduce Fe3+ to Fe2+ ions in FRAP assay. The obtained results introduce NADES systems as the novel, sustainable, and low-cost solvents with a variety of applications.

Keywords: antibacterial activity, antioxidant activity, green extraction, natural deep eutectic solvents, polyphenols

Procedia PDF Downloads 169

Authors: Dennis Infante

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This paper examined the reflections of teachers on curriculum reforms, the implementation of the K-12 Basic Education Program in the Philippines. The results revealed that problems and concerns raised by teachers could be classified into curriculum materials and design; competence, readiness and motivation of the teachers; the learning environment, and support systems; readiness, competence and motivation of students; and other relevant factors. The best features of the K-12 curriculum reforms included (1) the components, curriculum materials; (2) the design, structure and delivery of the lessons; (3) the framework and theoretical approach; (3) the qualities of the teaching-learning activities; (4) and other relevant features. With the demanding task of implementing the new curriculum, the teachers expressed their needs which included (1) making the curriculum materials available to achieve the goals of the curriculum reforms; (2) enrichment of the learning environments; (3) motivating and encouraging the teachers to embrace change; (4) providing appropriate support systems; (5) re-tooling, and empowering teachers to implement the curriculum reforms; and (6) other relevant factors. The research concluded with a synthesis that provided a paradigm for implementing curriculum reforms which recognizes the needs of the teachers and the features of the new curriculum.

Keywords: curriculum reforms, K-12, teachers' reflections, implementing curriculum change

Procedia PDF Downloads 263

Authors: Mustapha Kamel Mihoubi, Reda Madi

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The problem of natural disasters in general and flooding in particular is a topic which marks a memorable action in the world and specifically in cities and large urban areas. Torrential floods and faster flows pose a major problem in urban area. Indeed, a better management of risks of floods becomes a growing necessity that must mobilize technical and scientific means to curb the adverse consequences of this phenomenon, especially in the Saharan cities in arid climate. The aim of this study is to deploy a basic calculation approach based on a hydrologic and hydraulic quantification for locating the black spots in urban areas generated by the flooding and to locate the areas that are vulnerable to flooding. The principle of flooding method is applied to the city of Ghardaia to identify vulnerable areas to inundation and to establish maps management and prevention against the risks of flooding.

Keywords: Alea, Beni Mzab, cartography, HEC-RAS, inundation, torrential, vulnerability, wadi

Procedia PDF Downloads 288

Authors: Imene Atek, Abed M. Affoune, Hubert Girault, Pekka Peljo

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Due to the need for a rigorous mathematical model that can help to estimate kinetic properties for soluble-insoluble systems, through voltammetric experiments, a Nicholson Semi Analytical Approach was used in this work for modeling and prediction of theoretical linear sweep voltammetry responses for reversible, quasi reversible or irreversible electron transfer reactions. The redox system of interest is a one-step metal electrodeposition process. A rigorous analysis of simulated linear scan voltammetric responses following variation of dimensionless factors, the rate constant and charge transfer coefficients in a broad range was studied and presented in the form of the so called kinetic zones diagrams. These kinetic diagrams were divided into three kinetics zones. Interpreting these zones leads to empirical mathematical models which can allow the experimenter to determine electrodeposition reactions kinetics whatever the degree of reversibility. The validity of the obtained results was tested and an excellent experiment–theory agreement has been showed.

Keywords: electrodeposition, kinetics diagrams, modeling, voltammetry

Procedia PDF Downloads 127

Authors: Hiroaki Nasu, Ryota Miyamoto, Yuta Kodera, Yasuyuki Nogami

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To promote Industry 4.0 and Society 5.0 and so on, it is important to connect and share data so that every member can trust it. Blockchain (BC) technology is currently attracting attention as the most advanced tool and has been used in the financial field and so on. However, the data collaboration using BC has not progressed sufficiently among companies on the supply chain of manufacturing industry that handle sensitive data such as product quality, manufacturing conditions, etc. There are two main reasons why data utilization is not sufficiently advanced in the industrial supply chain. The first reason is that manufacturing information is top secret and a source for companies to generate profits. It is difficult to disclose data even between companies with transactions in the supply chain. In the blockchain mechanism such as Bitcoin using PKI (Public Key Infrastructure), in order to confirm the identity of the company that has sent the data, the plaintext must be shared between the companies. Another reason is that the merits (scenarios) of collaboration data between companies are not specifically specified in the industrial supply chain. For these problems this paper proposes a Business to Business (B2B) collaboration system using homomorphic encryption and BC technique. Using the proposed system, each company on the supply chain can exchange confidential information on encrypted data and utilize the data for their own business. In addition, this paper considers a scenario focusing on quality data, which was difficult to collaborate because it is a top secret. In this scenario, we show a implementation scheme and a benefit of concrete data collaboration by proposing a comparison protocol that can grasp the change in quality while hiding the numerical value of quality data.

Keywords: business to business data collaboration, industrial supply chain, blockchain, homomorphic encryption

Procedia PDF Downloads 115

Authors: Timothy E. Frank, Josh R. Aldred, Sophie B. Boulware, Michelle K. Cabonce, Justin H. White

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Materials degrade at different rates in different environments depending on factors such as temperature, aridity, salinity, and solar radiation. Therefore, predicting asset longevity depends, in part, on the environmental conditions to which the asset is exposed. Heating, ventilation, and air conditioning (HVAC) systems are critical to building operations yet are responsible for a significant proportion of their energy consumption. HVAC energy use increases substantially with slight operational inefficiencies. Understanding the environmental influences on HVAC degradation in detail will inform maintenance schedules and capital investment, reduce energy use, and increase lifecycle management efficiency. HVAC inspection records spanning 14 years from 21 locations across the United States were compiled and associated with the climate conditions to which they were exposed. Three environmental features were explored in this study: average high temperature, average low temperature, and annual precipitation, as well as four non-environmental features. Initial insights showed no correlations between individual features and the rate of HVAC component degradation. Using neighborhood component analysis, however, the most critical features related to degradation were identified. Two models were considered, and results varied between them. However, longitude and latitude emerged as potentially the best predictors of average HVAC component degradation. Further research is needed to evaluate additional environmental features, increase the resolution of the environmental data, and develop more robust models to achieve more conclusive results.

Keywords: climate, degradation, HVAC, neighborhood component analysis

Procedia PDF Downloads 411

Authors: Khaled Halimi, Hassina Seridi-Bouchelaghem

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The purpose of this paper is to describe how learning analytics approaches based on social semantic web techniques can be applied to enhance the lifelong learning experiences in a connectivist perspective. For this reason, a prototype of a system called SoLearn (Social Learning Environment) that supports this approach. We observed and studied literature related to lifelong learning systems, social semantic web and ontologies, connectivism theory, learning analytics approaches and reviewed implemented systems based on these fields to extract and draw conclusions about necessary features for enhancing the lifelong learning process. The semantic analytics of learning can be used for viewing, studying and analysing the massive data generated by learners, which helps them to understand through recommendations, charts and figures their learning and behaviour, and to detect where they have weaknesses or limitations. This paper emphasises that implementing a learning analytics approach based on social semantic web representations can enhance the learning process. From one hand, the analysis process leverages the meaning expressed by semantics presented in the ontology (relationships between concepts). From the other hand, the analysis process exploits the discovery of new knowledge by means of inferring mechanism of the semantic web.

Keywords: connectivism, learning analytics, lifelong learning, social semantic web

Procedia PDF Downloads 196

Authors: Rana Alaa El-Deen Ahmed, M. Elemam Shehab, Shereen Morsy, Nermeen Mekawie

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With the growing popularity and acceptance of e-commerce platforms, users face an ever increasing burden in actually choosing the right product from the large number of online offers. Thus, techniques for personalization and shopping guides are needed by users. For a pleasant and successful shopping experience, users need to know easily which products to buy with high confidence. Since selling a wide variety of products has become easier due to the popularity of online stores, online retailers are able to sell more products than a physical store. The disadvantage is that the customers might not find products they need. In this research the customer will be able to find the products he is searching for, because recommender systems are used in some ecommerce web sites. Recommender system learns from the information about customers and products and provides appropriate personalized recommendations to customers to find the needed product. In this paper eleven classification algorithms are comparatively tested to find the best classifier fit for consumer online shopping attitudes and behavior in the experimented dataset. The WEKA knowledge analysis tool, which is an open source data mining workbench software used in comparing conventional classifiers to get the best classifier was used in this research. In this research by using the data mining tool (WEKA) with the experimented classifiers the results show that decision table and filtered classifier gives the highest accuracy and the lowest accuracy classification via clustering and simple cart.

Keywords: classification, data mining, machine learning, online shopping, WEKA

Procedia PDF Downloads 340

Authors: André Augusto Ceballos Melo

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Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

Procedia PDF Downloads 88

Authors: Zicheng Zhang, Linli Zhang

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As China's biggest social media platform, Weibo has taken on essential health communication responsibilities during the pandemic. This research takes 105 posters in 15 health-related official Weibo accounts as the analysis objects to explore COVID19 health information communication and visualisation. First, the interaction between the audiences and Weibo, including forwarding, comments, and likes, is statistically analysed. The comments about the information design are extracted manually, and then the sentiment analysis is carried out to verdict audiences' views about the poster's design. The forwarding and comments are quantified as the attention index for a reference to the degree of likes. In addition, this study also designed an evaluation scale based on the standards of Health Literacy Resource by the Centers for Medicare& Medicaid Services (US). Then designers scored all selected posters one by one. Finally, combining the data of the two parts, concluded that: 1. To a certain extent, people think that the posters do not deliver substantive and practical information; 2. Non-knowledge posters(i.e., cartoon posters) gained more Forwarding and Likes, such as Go, Wuhan poster; 3. The analysis of COVID posters is still mainly picture-oriented, mainly about encouraging people to overcome difficulties; 4. Posters for pandemic prevention usually contain more text and fewer illustrations and do not clearly show cultural differences. In conclusion, health communication usually involves a lot of professional knowledge, so visualising that knowledge in an accessible way for the general public is challenging. The relevant posters still have the problems of lack of effective communication, superficial design, and insufficient content accessibility.

Keywords: weibo, visualisation, covid posters, poster design

Procedia PDF Downloads 112

Authors: Kolawole Taiwo Olabode

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This is a comparative study of ICTs adoption and use in selected manufacturing industries in for development. This study was carried out 2004 and was repeated 2013 (nine years after) using the same selected manufacturing industries to assess the level, improvement and extent ICT facilities used in these companies. The theory of modernization was explored to explain some developmental issues in this study. The same semi-structured questionnaire and IDI were used to elicit data on the subject matter. About 24.9% of the total workers (1,247) were sampled for this study using quota sampling technique. SPSS was used to analysis the quantitative data. The qualitative data was used to buttress the quantitative data. Findings indicated that Seven-Up Bottling Company and Frigoglass Glass Industry still remained Intensive ICT Users while only Niger Match Nigeria Limited still remained Non-Intensive ICT User while unfortunately, Askar Paint Nigeria Limited has gone liquidated. It is also important to discover that only the Intensive ICT users improved on relevant ICT facilities. The existing problems of ICT adoption and used in these companies remained the same in Niger Match Limited. The study concluded that for a society to be developed, management and government at all levels must do all things necessary to ensure that all existing organisations must be ICT compliance for workers and organisational performance and to enhance nation’s development in order to compete with other companies for global standard or recognition.

Keywords: ICT, intensive ICT-users, entrepreneurial, manufacturing industries, industries and development

Procedia PDF Downloads 285

Authors: S. Homrossukon, S. Sansureerungsigun

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This work aims to introduce an efficient and to standardize the measuring system analyses for automotive industrial. The study started by literature reviewing about the management and analyses measurement system. The approach of measuring system management, then, was constructed. Such approach was validated by collecting the current measuring system data using the equipments of interest including vernier caliper and micrometer. Their accuracy and precision of measurements were analyzed. Finally, the measuring system was improved and evaluated. The study showed that vernier did not meet its measuring characteristics based on the linearity whereas all equipment were lacking of the measuring precision characteristics. Consequently, the causes of measuring variation via the equipment of interest were declared. After the improvement, it was found that their measuring performance could be accepted as the standard required. Finally, the standardized approach for analyzing the measuring system of automotive was concluded.

Keywords: automotive part manufacturing measurement, measuring accuracy, measuring precision, measurement system analyses

Procedia PDF Downloads 298

Authors: Ilaria Lucrezia Amerise

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The statistical modelling of precipitation data for a given portion of territory is fundamental for the monitoring of climatic conditions and for Hydrogeological Management Plans (HMP). This modelling is rendered particularly complex by the changes taking place in the frequency and intensity of precipitation, presumably to be attributed to the global climate change. This paper applies the Wakeby distribution (with 5 parameters) as a theoretical reference model. The number and the quality of the parameters indicate that this distribution may be the appropriate choice for the interpolations of the hydrological variables and, moreover, the Wakeby is particularly suitable for describing phenomena producing heavy tails. The proposed estimation methods for determining the value of the Wakeby parameters are the same as those used for density functions with heavy tails. The commonly used procedure is the classic method of moments weighed with probabilities (probability weighted moments, PWM) although this has often shown difficulty of convergence, or rather, convergence to a configuration of inappropriate parameters. In this paper, we analyze the problem of the likelihood estimation of a random variable expressed through its quantile function. The method of maximum likelihood, in this case, is more demanding than in the situations of more usual estimation. The reasons for this lie, in the sampling and asymptotic properties of the estimators of maximum likelihood which improve the estimates obtained with indications of their variability and, therefore, their accuracy and reliability. These features are highly appreciated in contexts where poor decisions, attributable to an inefficient or incomplete information base, can cause serious damages.

Keywords: generalized extreme values, likelihood estimation, precipitation data, Wakeby distribution

Procedia PDF Downloads 127

Authors: Thomas Ousterhout

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The purpose of this study was to investigate if incorporating meaningful pictures of gestures and facial expressions in short sentences of text could supplement the text with enough semantic information to produce and N400 effect when probe words incongruent to the picture were subsequently presented. Event-related potentials (ERPs) were recorded from a 14-channel commercial grade EEG headset while subjects performed congruent/incongruent reaction time discrimination tasks. Since pictures of meaningful gestures have been shown to be semantically processed in the brain in a similar manner as words are, it is believed that pictures will add supplementary information to text just as the inclusion of their equivalent synonymous word would. The hypothesis is that when subjects read the text/picture mixed sentences, they will process the images and words just like in face-to-face communication and therefore probe words incongruent to the image will produce an N400.

Keywords: EEG, ERP, N400, semantics, congruency, facilitation, Emotiv

Procedia PDF Downloads 247

Authors: Diptimayee Nayak, V. Upadhyay

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This paper posits the attempt of conservation and the idea of protected areas from the Marxian primitive accumulation to the politics of sustainability. Using field survey data and secondary literature, this paper analyses an Indian wildlife sanctuary, the Bhitarkanika, Odisha and finds how the hegemony of power among different management regimes attempted for conservation and the present protected area management regime attempted to imbibe the policy of ecotourism for achieving sustainability. The paper contends that the current policy of ecotourism in protected areas acts as a veil for the local deprived people, to avoid many legal conflicts like property rights, livelihood, and man-wildlife issues. Moreover, opening the scope to accumulate on the part of tour operators, the policy of ecotourism establishes a nexus between the profit holders/tour operators (the capitalists) and the power hegemony on the part of management authorities. The sustainability attempt of ecotourism may lead to private benefits maximising the profit accumulation and can expand and continue, showing the bulk of employment generation of local people at petty odd jobs, grabbing a lion share! Positing ecotourism as a capitalist project as against the general assumption of one of the drivers of sustainable development, the paper shows that ecotourism in practice may end up ruining the very social-environmental set up, leading to unsustainability related to waste management, equality, culture, relationship and above all polarised private accumulators in absence of sound mechanism. The paper ends with the caveat that while shopping for neoliberal conservation, the conservators found ecotourism as a product without finalising the hallmark of mechanism/ institutions with appropriate modus operandii to check/guard the quality assurance/standard of ecotourism for sustainability. The paper proposes sound structural and institutional mechanism of ecotourism to be developed to harness sustainability in the local economy as well as in conservation.

Keywords: conservation, ecotourism, Marxian capitalism, protected areas, sustainability

Procedia PDF Downloads 153

Authors: Abhimanyu Pati, Prabir K. Bandyopadhyay

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The paper intends to highlight the significance of Digital Manufacturing (DM) strategy in support and achievement of business strategy and goals of any manufacturing organization. Towards this end, DM initiatives have been given a process perspective, while not undermining its technological significance, with a view to link its benefits directly with fulfilment of customer needs and expectations in a responsive and cost-effective manner. A digital process model has been proposed to categorize digitally enabled organizational processes with a view to create synergistic groups, which adopt and use digital tools having similar characteristics and functionalities. This will throw future opportunities for researchers and developers to create a unified technology environment for integration and orchestration of processes. Secondly, an effort has been made to apply “what” and “how” features of Quality Function Deployment (QFD) framework to establish the relationship between customers’ needs – both for external and internal customers, and the features of various digital processes, which support for the achievement of these customer expectations. The paper finally concludes that in the present highly competitive environment, business organizations cannot thrive to sustain unless they understand the significance of digital strategy and integrate it with their business strategy with a clearly defined implementation roadmap. A process-oriented approach to DM strategy will help business executives and leaders to appreciate its value propositions and its direct link to organization’s competitiveness.

Keywords: knowledge management, cloud computing, knowledge management approaches, cloud-based knowledge management

Procedia PDF Downloads 300

Authors: Nushrat Khan, Mike Thelwall, Kayvan Kousha

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Making research data openly accessible has been mandated by most funders over the last 5 years as it promotes reproducibility in science and reduces duplication of effort to collect the same data. There are evidence that articles that publicly share research data have higher citation rates in biological and social sciences. However, how and whether shared data is being reused is not always intuitive as such information is not easily accessible from the majority of research data repositories. This study aims to understand the practice of data citation and how data is being reused over the years focusing on biodiversity since research data is frequently reused in this field. Metadata of 38,878 datasets including citation counts were collected through the Global Biodiversity Information Facility (GBIF) API for this purpose. GBIF was used as a data source since it provides citation count for datasets, not a commonly available feature for most repositories. Analysis of dataset types, citation counts, creation and update time of datasets suggests that citation rate varies for different types of datasets, where occurrence datasets that have more granular information have higher citation rates than checklist and metadata-only datasets. Another finding is that biodiversity datasets on GBIF are frequently updated, which is unique to this field. Majority of the datasets from the earliest year of 2007 were updated after 11 years, with no dataset that was not updated since creation. For each year between 2007 and 2017, we compared the correlations between update time and citation rate of four different types of datasets. While recent datasets do not show any correlations, 3 to 4 years old datasets show weak correlation where datasets that were updated more recently received high citations. The results are suggestive that it takes several years to cumulate citations for research datasets. However, this investigation found that when searched on Google Scholar or Scopus databases for the same datasets, the number of citations is often not the same as GBIF. Hence future aim is to further explore the citation count system adopted by GBIF to evaluate its reliability and whether it can be applicable to other fields of studies as well.

Keywords: data citation, data reuse, research data sharing, webometrics

Procedia PDF Downloads 164

Authors: Mahmoud Owais

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Public Transit (P.T) is very important means to reduce traffic congestion, to improve urban environmental conditions and consequently affects people social lives. Planning, designing and management of P.T are the key issues for offering a competitive mode that can compete with the private transportation. These transportation planning, designing and management issues are addressed in the Transit Network Design Problem (TNDP). It deals with a complete hierarchy of decision making process. It includes strategic, tactical and operational decisions. The main body of TNDP is two stages, namely; route design stage and frequency setting. The TNDP is extensively studied in the last five decades; however the research gate is still widely open due to its many practical and modeling challenges. In this paper, a comprehensive background is given to illustrate the issues and challenges related to the TNDP to help in directing the incoming researches towards the untouched areas of the problem.

Keywords: frequency setting, network design, transit planning, urban planning

Procedia PDF Downloads 365

Authors: Justin Reverdi, Sixin Zhang, Saïd Aoues, Fabrice Gamboa, Serge Gratton, Thomas Pellegrini

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In vapor cycle systems, the mass flow sensor plays a key role for different monitoring and control purposes. However, physical sensors can be inaccurate, heavy, cumbersome, expensive, or highly sensitive to vibrations, which is especially problematic when embedded into an aircraft. The conception of a virtual sensor, based on other standard sensors, is a good alternative. This paper has two main objectives. Firstly, a data-driven model using a convolutional neural network is proposed to estimate the mass flow of the compressor. We show that it significantly outperforms the standard polynomial regression model (thermodynamic maps) in terms of the standard MSE metric and engineer performance metrics. Secondly, a semi-automatic segmentation method is proposed to compute the engineer performance metrics for real datasets, as the standard MSE metric may pose risks in analyzing the dynamic behavior of vapor cycle systems.

Keywords: deep learning, convolutional neural network, vapor cycle system, virtual sensor

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Authors: Ibrahim Alsendid, Rob Sturman, Benjamin Sharp

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In this paper, we consider a family of 2-dimensional nonlinear area-preserving transformations on the torus. A single parameter η varies between 0 and 1, taking the transformation from a hyperbolic toral automorphism to the “Cerbelli-Giona” map, a system known to exhibit multifractal properties. Here we study the multifractal properties of the family of maps. We apply a box-counting method by defining a grid of boxes Bi(δ), where i is the index and δ is the size of the boxes, to quantify the distribution of stable and unstable manifolds of the map. When the parameter is in the range 0.51< η <0.58 and 0.68< η <1 the map is ergodic; i.e., the unstable and stable manifolds eventually cover the whole torus, although not in a uniform distribution. For accurate numerical results, we require correspondingly accurate construction of the stable and unstable manifolds. Here we use the piecewise linearity of the map to achieve this, by computing the endpoints of line segments that define the global stable and unstable manifolds. This allows the generalized fractal dimension Dq, and spectrum of dimensions f(α), to be computed with accuracy. Finally, the intersection of the unstable and stable manifold of the map will be investigated and compared with the distribution of periodic points of the system.

Keywords: Discrete-time dynamical systems, Fractal geometry, Multifractal behaviour of the Perturbed map, Multifractal of Dynamical systems

Procedia PDF Downloads 199

Authors: Mojtaba Molaahmadi, Morteza Raei Dehaghi, Abdolrahim Arghavan

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The present study aims to explore the effect of computerization on marketing performance in Snowa Company. In other words, this study intends to respond to this question that whether or not there is a relationship between utilization of computerization in marketing activities and marketing performance. The statistical population included 60 marketing managers of Snowa Company. In order to test the research hypotheses, Pearson correlation coefficient was employed. The reliability was equal to 96.8%. In this study, computerization was the independent variable and marketing performance was the dependent variable with characteristics of market share, improving the competitive position, and sales volume. The results of testing the hypotheses revealed that there is a significant relationship between utilization of computerization and market share, sales volume and improving the competitive position

Keywords: computerization, e-marketing information, information technology, marketing performance

Procedia PDF Downloads 317

Authors: Eric Morettin

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Cybersecurity and digital literacy are pressing issues among Canadian citizens, yet formal education does not provide today’s students with the necessary knowledge and skills needed to adapt to these challenging issues within the physical and digital labor-market. Canada’s current education systems do not highlight the importance of these respective fields, aside from using technology for learning management systems and alternative methods of assignment completion. Educators are not properly trained to integrate technology into the compulsory courses within public education, to better prepare their learners in these topics and Canada’s digital economy. ICTC addresses these gaps in education and training through cross-Canadian educational programming in digital literacy and competency, cybersecurity and coding which is bridged with Canada’s provincially regulated K-12 curriculum guidelines. After analyzing Canada’s provincial education, it is apparent that there are gaps in learning related to technology, as well as inconsistent educational outcomes that do not adequately represent the current Canadian and global economies. Presently only New Brunswick, Nova Scotia, Ontario, and British Columbia offer curriculum guidelines for cybersecurity, computer programming, and digital literacy. The remaining provinces do not address these skills in their curriculum guidelines. Moreover, certain courses across some provinces not being updated since the 1990’s. The three territories respectfully take curriculum strands from other provinces and use them as their foundation in education. Yukon uses all British Columbia curriculum. Northwest Territories and Nunavut respectfully use a hybrid of Alberta and Saskatchewan curriculum as their foundation of learning. Education that is provincially regulated does not allow for consistency across the country’s educational outcomes and what Canada’s students will achieve – especially when curriculum outcomes have not been updated to reflect present day society. Through this, ICTC has aligned Canada’s provincially regulated curriculum and created opportunities for focused education in the realm of technology to better serve Canada’s present learners and teachers; while addressing inequalities and applicability within curriculum strands and outcomes across the country. As a result, lessons, units, and formal assessment strategies, have been created to benefit students and teachers in this interdisciplinary, cross-curricular, practice - as well as meeting their compulsory education requirements and developing skills and literacy in cyber education. Teachers can access these lessons and units through ICTC’s website, as well as receive professional development regarding the assessment and implementation of these offerings from ICTC’s education coordinators, whose combines experience exceeds 50 years of teaching in public, private, international, and Indigenous schools. We encourage you to take this opportunity that will benefit students and educators, and will bridge the learning and curriculum gaps in Canadian education to better reflect the ever-changing public, social, and career landscape that all citizens are a part of. Students are the future, and we at ICTC strive to ensure their futures are bright and prosperous.

Keywords: cybersecurity, education, curriculum, teachers

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Authors: Serhat Tuzun, Tufan Demirel

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Multi-Criteria Decision Making (MCDM) is the modelling of real-life to solve problems we encounter. It is a discipline that aids decision makers who are faced with conflicting alternatives to make an optimal decision. MCDM problems can be classified into two main categories: Multi-Attribute Decision Making (MADM) and Multi-Objective Decision Making (MODM), based on the different purposes and different data types. Although various MADM techniques were developed for the problems encountered, their methodology is limited in modelling real-life. Moreover, objective results are hard to obtain, and the findings are generally derived from subjective data. Although, new and modified techniques are developed by presenting new approaches such as fuzzy logic; comprehensive techniques, even though they are better in modelling real-life, could not find a place in real world applications for being hard to apply due to its complex structure. These constraints restrict the development of MADM. This study aims to conduct a comprehensive analysis of preference methods in MADM and propose an approach based on information. For this purpose, a detailed literature review has been conducted, current approaches with their advantages and disadvantages have been analyzed. Then, the approach has been introduced. In this approach, performance values of the criteria are calculated in two steps: first by determining the distribution of each attribute and standardizing them, then calculating the information of each attribute as informational energy.

Keywords: literature review, multi-attribute decision making, operations research, preference method, informational energy

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Authors: Matteo Rossini, Alberto Portioli Staudacher

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The market competition is moving from the single firm to the whole supply chain one because of increasing competition and growing need for operational efficiencies and customer orientation. Supply chain management allows companies to look beyond their organizational boundaries to develop and leverage resources and capabilities of their supply chain partners. This leads to create competitive advantages in the marketplace and because of this SCM has acquired strategic importance. Lean Approach is a management strategy that focuses on reducing every type of waste present in an organization. This approach is becoming more and more popular among supply chain managers. The supply chain application of lean approach is low diffused. It is not well studied which are the impacts of lean approach principles in a supply chain context. In literature there are only few studies simulating the lean approach performance in single products supply chain. This research work studies the impacts of lean principles implementation along a supply chain. To achieve this, a simulation model of a three-echelon multiproduct product supply chain has been built. Kanban system (and several priority policies) and setup time reduction degrees are implemented in the lean-configured supply chain to apply pull and lot-sizing decrease principles respectively. To evaluate the benefits of lean approach, lean supply chain is compared with an EOQ-configured supply chain. The simulation results show that Kanban system and setup-time reduction improve inventory stock level. They also show that logistics efforts are affected to lean implementation degree. The paper concludes describing performances of lean supply chain in different contexts.

Keywords: inventory policy, Kanban, lean supply chain, simulation study, supply chain management, planning

Procedia PDF Downloads 345

Authors: Jeong-Won Kang

Abstract:

Graphene, a single-atom sheet, has been considered as the most promising material for making future nanoelectromechanical systems as well as purely electrical switching with graphene transistors. Graphene-based devices have advantages in scaled-up device fabrication due to the recent progress in large area graphene growth and lithographic patterning of graphene nanostructures. Here we investigated its mechanical responses of circular graphene nanoflake under the nanoindentation using classical molecular dynamics simulations. A correlation between the load and the indentation depth was constructed. The nanoindented force in this work was applied to the center point of the circular graphene nanoflake and then, the resonance frequency could be tuned by a nanoindented depth. We found the hardening or the softening of the graphene nanoflake during its nanoindented-deflections, and such properties were recognized by the shift of the resonance frequency. The calculated mechanical parameters in the force vs deflection plot were in good agreement with previous experimental and theoretical works. This proposed schematics can detect the pressure via the deflection change or/and the resonance frequency shift, and also have great potential for versatile applications in nanoelectromechanical systems.

Keywords: graphene, pressure sensor, circular graphene nanoflake, molecular dynamics

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Authors: Anju Batta Sehgal

Abstract:

Climate change is a major challenge in terms of agriculture, food security and rural livelihood for thousands of people especially the poor in Himachal, which falls in North-Western Himalayas. Agriculture contributes over 45 per cent to net state domestic product. It is the main source of income and employment. Over 93 per cent of population is dependent on agriculture which provides direct employment to 71 percent of its people. Area of operation holding is about 9,79 lakh hectares owned by 9.14 lakh farmers. About 80 per cent area is rain-fed and farmers depend on weather gods for rains. Region is a home of diverse ethnic communities having enormous socio-economic and cultural diversities, gifted with range of farming systems and rich resource wealth, including biodiversity, hot spots and ecosystems sustaining millions of people living in the region. But growing demands of ecosystem goods and services are posing threats to natural resources. Climate change is already making adverse impact on the indigenous people. The rural populace is directly dependent for all its food, shelter and other needs on the climate. Our aim should be to shift the focus to indigenous people as primary actors in terms of global climate change monitoring, adaptations and innovations. Objective of this paper is to identify the climate change related threats and vulnerabilities associated with agriculture as a sector and agriculture as people’s livelihood. Broadly it analyses the connections between the nature and rural consumers the ethnic groups.

Keywords: climate change, agriculture, indigenous people, Himachal Pradesh

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Authors: Jia Li, Xing Wei, Yuchen Hong, Yang Lu

Abstract:

Detecting vehicle behavior has always been the focus of intelligent transportation, but with the explosive growth of the number of vehicles and the complexity of the road environment, the vehicle behavior videos captured by traditional surveillance have been unable to satisfy the study of vehicle behavior. The traditional method of manually labeling vehicle behavior is too time-consuming and labor-intensive, but the existing object detection and tracking algorithms have poor practicability and low behavioral location detection rate. This paper proposes a vehicle behavior detection algorithm based on the dual-stream convolution network and the multi-dimensional video dynamic detection network. In the videos, the straight-line behavior of the vehicle will default to the background behavior. The Changing lanes, turning and turning around are set as target behaviors. The purpose of this model is to automatically mark the target behavior of the vehicle from the untrimmed videos. First, the target behavior proposals in the long video are extracted through the dual-stream convolution network. The model uses a dual-stream convolutional network to generate a one-dimensional action score waveform, and then extract segments with scores above a given threshold M into preliminary vehicle behavior proposals. Second, the preliminary proposals are pruned and identified using the multi-dimensional video dynamic detection network. Referring to the hierarchical reinforcement learning, the multi-dimensional network includes a Timer module and a Spacer module, where the Timer module mines time information in the video stream and the Spacer module extracts spatial information in the video frame. The Timer and Spacer module are implemented by Long Short-Term Memory (LSTM) and start from an all-zero hidden state. The Timer module uses the Transformer mechanism to extract timing information from the video stream and extract features by linear mapping and other methods. Finally, the model fuses time information and spatial information and obtains the location and category of the behavior through the softmax layer. This paper uses recall and precision to measure the performance of the model. Extensive experiments show that based on the dataset of this paper, the proposed model has obvious advantages compared with the existing state-of-the-art behavior detection algorithms. When the Time Intersection over Union (TIoU) threshold is 0.5, the Average-Precision (MP) reaches 36.3% (the MP of baselines is 21.5%). In summary, this paper proposes a vehicle behavior detection model based on multi-dimensional dynamic detection network. This paper introduces spatial information and temporal information to extract vehicle behaviors in long videos. Experiments show that the proposed algorithm is advanced and accurate in-vehicle timing behavior detection. In the future, the focus will be on simultaneously detecting the timing behavior of multiple vehicles in complex traffic scenes (such as a busy street) while ensuring accuracy.

Keywords: vehicle behavior detection, convolutional neural network, long short-term memory, deep learning

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Authors: Mahmoud Jumah

Abstract:

This paper presents the circumstances and decision making in case of change management in any industrial processes, and the effective strategic planning ensured to provide with the on time completion of projects. In this specific case, the Front End Engineering Design and the awarded Lump Sum Turn Key Contract had provided for full control and ownership of all Liquid Metering Skids by Controlling Team. The demarcation and location were changed, and the Ownership and Control of the Liquid Metering Skids inside the boundaries of the Asset Owner were transferred from Controlling Team to Asset Owner after the award of the LSTK Contract. The requested changes resulted in Adjustment Order and the relevant scope of work is an essential part of the original Contract. The majority of equipment and materials (i.e. liquid metering skids, valves, piping, etc.) has already been in process.

Keywords: critical path, project change management, stakeholders problem solving, strategic planning

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Authors: Nosheen Fatima Warraich

Abstract:

One of the most often used models in information system (IS) research is the technology acceptance model (TAM). This meta-analysis aims to measure the relationship between TAM variables, Perceived Ease of Use (PEOU), and Perceived Usefulness (PU) with users’ attitudes and behavioral intention (BI) in mobile and digital libraries context. It also examines the relationship of external variables (information quality and system quality) with TAM variables (PEOU and PU) in digital libraries settings. This meta-analysis was performed through PRISMA-P guidelines. Four databases (Google Scholar, Web of Science, Scopus, and LISTA) were utilized for searching, and the search was conducted according to defined criteria. The findings of this study revealed a large effect size of PU and PEOU with BI. There was also a large effect size of PU and PEOU with attitude. A medium effect size was found between SysQ -> PU, InfoQ-> PU, and SysQ -> PEOU. However, there was a small effect size between InfoQ and PEOU. It fills the literature gap and also confirms that TAM is a valid model for the acceptance and use of technology in mobile and digital libraries context. Thus, its findings would be helpful for developers and designers in designing and developing mobile library apps. It will also be beneficial for library authorities and system librarians in designing and developing digital libraries in academic settings.

Keywords: technology acceptance model (tam), perceived ease of use, perceived usefulness, information quality, system quality, meta-analysis, systematic review, digital libraries, and mobile library apps.

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Authors: Harish Krishnamurthy, Anna Lafontant, Ren Yi

Abstract:

Unidentified Flying Objects (UFOs) have been an interesting topic for most enthusiasts and hence people all over the United States report such findings online at the National UFO Report Center (NUFORC). Some of these reports are a hoax and among those that seem legitimate, our task is not to establish that these events confirm that they indeed are events related to flying objects from aliens in outer space. Rather, we intend to identify if the report was a hoax as was identified by the UFO database team with their existing curation criterion. However, the database provides a wealth of information that can be exploited to provide various analyses and insights such as social reporting, identifying real-time spatial events and much more. We perform analysis to localize these time-series geospatial events and correlate with known real-time events. This paper does not confirm any legitimacy of alien activity, but rather attempts to gather information from likely legitimate reports of UFOs by studying the online reports. These events happen in geospatial clusters and also are time-based. We look at cluster density and data visualization to search the space of various cluster realizations to decide best probable clusters that provide us information about the proximity of such activity. A random forest classifier is also presented that is used to identify true events and hoax events, using the best possible features available such as region, week, time-period and duration. Lastly, we show the performance of the scheme on various days and correlate with real-time events where one of the UFO reports strongly correlates to a missile test conducted in the United States.

Keywords: time-series clustering, feature extraction, hoax prediction, geospatial events

Procedia PDF Downloads 361