Search results for: innovative business model

Authors: Jean-Pierre Dubois, Jihad S. Daba, H. Karam, J. Abdallah

Abstract:

Tsunami early detection and warning systems have proved to be of ultimate importance, especially after the destructive tsunami that hit Japan in March 2012. Such systems are crucial to inform the authorities of any risk of a tsunami and of the degree of its danger in order to make the right decision and notify the public of the actions they need to take to save their lives. The purpose of this research is to enhance existing tsunami detection and warning systems. We first propose an automated and miniaturized model of an early tsunami detection and warning system. The model for the operation of a tsunami warning system is simulated using the data acquisition toolbox of Matlab and measurements acquired from specified internet pages due to the lack of the required real-life sensors, both seismic and hydrologic, and building a graphical user interface for the system. In the second phase of this work, we implement various satellite image filtering schemes to enhance the acquired synthetic aperture radar images of the tsunami affected region that are masked by speckle noise. This enables us to conduct a post-tsunami damage extent study and calculate the percentage damage. We conclude by proposing improvements to the existing telecommunication infrastructure of existing warning tsunami systems using a migration to IP-based networks and fiber optics links.

Keywords: detection, GIS, GSN, GTS, GPS, speckle noise, synthetic aperture radar, tsunami, wiener filter

Procedia PDF Downloads 392

Authors: Akiko Kondo, Akio Kondo

Abstract:

We are facing serious problems related to a long-term depopulation and an aging society with a falling birth rate in Japan. In this situation, we are suffering from a shortfall in human resources as well as a shortage of workforce in rural regions. In addition, we are struggling with a protracted economic slump and excess concentration of population in the Tokyo Metropolitan area. It is an urgent national issue to consider how to live in this country and what kind of structure of society and administration policy is needed. It is necessary to clarify people’s desire for their way of living and social assistance to be provided. The aim of this study is to clarify the characteristics of regional issues and the degree of their seriousness in local municipalities of Japan. We conducted a questionnaire survey about regional agenda in all local municipalities in Japan. We obtained responses concerning the degree of seriousness of regional issues and degree of importance of policies. Based on the data gathered from the survey, it is apparent that many local municipalities are facing an aging population and declining population. We constructed a model to analyze factors for declining population. Using the model, it was clarified that a population’s age structure, job opportunities, and income level affect the decline of population. In addition, we showed the way of the evaluation of the state of a local municipality.

Keywords: evaluation, local municipality, regional analysis, regional issue

Procedia PDF Downloads 288

Authors: Joseph M. Njoroge

Abstract:

The need for urgent adaptation have triggered tourism stakeholders and research community to develop generic adaptation framework(s) for national, regional and or local tourism desti-nations. Such frameworks have been proposed to guide the tourism industry in the adaptation process with an aim of reducing tourism industry’s vulnerability and to enhance their ability to cope to climate associated externalities. However research show that current approaches are far from sustainability since the adaptation options sought are usually closely associated with development needs-‘business as usual’-where the implication of adaptation to social justice and environmental integrity are often neglected. Based on this view there is a need to look at adaptation beyond addressing vulnerability and resilience to include the need for adaptation to enhance social justice and environmental integrity. This paper reviews the existing adaptation frameworks/models and evaluates their suitability in enhancing sustainable adaptation for regional tourist destinations. It is noted that existing frameworks contradicts the basic ‘principles of sustainable adaptation’. Further attempts are made to propose a Sustainable Regional Tourism Adaptation Framework (SRTAF) to assist regional tourism stakeholders in the achieving sustainable adaptation.

Keywords: sustainable adaptation, sustainability principles, sustainability portfolio, Regional Tourism

Procedia PDF Downloads 396

Authors: Jayprakash Yadav, Nivedita Patra

Abstract:

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.

Procedia PDF Downloads 440

Authors: Kimberly Samaha

Abstract:

In order to attract new types of investors into the emerging Bio-Economy, new methodologies to analyze investment risk are needed. The Bio-Hub Ecosystem model was developed to address a critical area of concern within the global energy market regarding the use of biomass as a feedstock for power plants. This study looked at repurposing existing biomass-energy plants into Circular Zero-Waste Bio-Hub Ecosystems. A Bio-Hub model that first targets a ‘whole-tree’ approach and then looks at the circular economics of co-hosting diverse industries (wood processing, aquaculture, agriculture) in the vicinity of the Biomass Power Plants facilities. This study modeled the economics and risk strategies of cradle-to-cradle linkages to incorporate the value-chain effects on capital/operational expenditures and investment risk reductions using a proprietary techno-economic model that incorporates investment risk scenarios utilizing the Monte Carlo methodology. The study calculated the sequential increases in profitability for each additional co-host on an operating forestry-based biomass energy plant in West Enfield, Maine. Phase I starts with the base-line of forestry biomass to electricity only and was built up in stages to include co-hosts of a greenhouse and a land-based shrimp farm. Phase I incorporates CO2 and heat waste streams from the operating power plant in an analysis of lowering and stabilizing the operating costs of the agriculture and aquaculture co-hosts. Phase II analysis incorporated a jet-fuel biorefinery and its secondary slip-stream of biochar which would be developed into two additional bio-products: 1) A soil amendment compost for agriculture and 2) A biochar effluent filter for the aquaculture. The second part of the study applied the Monte Carlo risk methodology to illustrate how co-location derisks investment in an integrated Bio-Hub versus individual investments in stand-alone projects of energy, agriculture or aquaculture. The analyzed scenarios compared reductions in both Capital and Operating Expenditures, which stabilizes profits and reduces the investment risk associated with projects in energy, agriculture, and aquaculture. The major findings of this techno-economic modeling using the Monte Carlo technique resulted in the masterplan for the first Bio-Hub to be built in West Enfield, Maine. In 2018, the site was designated as an economic opportunity zone as part of a Federal Program, which allows for Capital Gains tax benefits for investments on the site. Bioenergy facilities are currently at a critical juncture where they have an opportunity to be repurposed into efficient, profitable and socially responsible investments, or be idled and scrapped. The Bio-hub Ecosystems techno-economic analysis model is a critical model to expedite new standards for investments in circular zero-waste projects. Profitable projects will expedite adoption and advance the critical transition from the current ‘take-make-dispose’ paradigm inherent in the energy, forestry and food industries to a more sustainable Bio-Economy paradigm that supports local and rural communities.

Keywords: bio-economy, investment risk, circular design, economic modelling

Procedia PDF Downloads 101

Authors: Malo Pocheau-Lesteven, Olivier Le Maître

Abstract:

Engineering and optimisation of complex systems is often achieved through multi-disciplinary analysis of the system, where each subsystem is modeled and interacts with other subsystems to model the complete system. The coherence of the output of the different sub-systems is achieved through the use of compatibility constraints, which enforce the coupling between the different subsystems. Due to the complexity of some sub-systems and the computational cost of evaluating their respective models, it is often necessary to build surrogate models of these subsystems to allow repeated evaluation these subsystems at a relatively low computational cost. In this paper, gaussian processes are used, as their probabilistic nature is leveraged to evaluate the likelihood of satisfying the compatibility constraints. This paper presents infilling strategies to build accurate surrogate models of the subsystems in areas where they are likely to meet the compatibility constraint. It is shown that these infilling strategies can reduce the computational cost of building surrogate models for a given level of accuracy. An application of these methods to velocity prediction programs used in offshore racing naval architecture further demonstrates these method's applicability in a real engineering context. Also, some examples of the application of uncertainty quantification to field of naval architecture are presented.

Keywords: infilling strategy, gaussian process, multi disciplinary analysis, velocity prediction program

Procedia PDF Downloads 157

Authors: Rudi Hartono, Bambang Purwanto

Abstract:

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

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

Procedia PDF Downloads 374

Authors: Valeria Aman

Abstract:

The presented study examines the impact of international mobility on knowledge production among mobile scientists and within the sending and receiving research groups. Scientists are relevant to the dynamics of knowledge production because scientific knowledge is mainly characterized by embeddedness and tacitness. International mobility enables the dissemination of scientific knowledge to other places and encourages new combinations of knowledge. It can also increase the interdisciplinarity of research by forming synergetic combinations of knowledge. Particularly innovative ideas can have their roots in related research domains and are sometimes transferred only through the physical mobility of scientists. Diversity among scientists with respect to their knowledge base can act as an engine for the creation of knowledge. It is therefore relevant to study how knowledge acquired through international mobility affects the knowledge production process. In certain research domains, international mobility may be essential to contextualize knowledge and to gain access to knowledge located at distant places. The knowledge production process contingent on the type of international mobility and the epistemic culture of a research field is examined. The production of scientific knowledge is a multi-faceted process, the output of which is mainly published in scholarly journals. Therefore, the study builds upon publication and citation data covered in Elsevier’s Scopus database for the period of 1996 to 2015. To analyse these data, bibliometric and social network analysis techniques are used. A basic analysis of scientific output using publication data, citation data and data on co-authored publications is combined with a content map analysis. Abstracts of publications indicate whether a research stay abroad makes an original contribution methodologically, theoretically or empirically. Moreover, co-citations are analysed to map linkages among scientists and emerging research domains. Finally, acknowledgements are studied that can function as channels of formal and informal communication between the actors involved in the process of knowledge production. The results provide better understanding of how the international mobility of scientists contributes to the production of knowledge, by contrasting the knowledge production dynamics of internationally mobile scientists with those being nationally mobile or immobile. Findings also allow indicating whether international mobility accelerates the production of knowledge and the emergence of new research fields.

Keywords: bibliometrics, diversity, interdisciplinarity, international mobility, knowledge production

Procedia PDF Downloads 293

Authors: Joseph Daniel Lumain

Abstract:

The Philippine business sector has witnessed the emergence of a new category that distinguishes itself from the common framework that most enterprises utilize as this new emerging player incorporates social needs as part of its mission and goals. Various literature has manifested the relevance of social enterprises as an instrument towards poverty alleviation, as it concretely increases the capabilities of individuals. This study aims to identify whether or not social enterprises creates an impact towards their employees by positively influencing their respective perceptions on their capabilities on income, health and education. Utilizing Amartya Sen’s Capabilities Framework, this study is grounded on the relationships between social enterprises and increased capabilities, and increased capabilities and developing towards living a life they truly desire. The data gathered was analyzed quantitatively, supplemented by qualitative interviews with one to two employees from the social enterprise itself. Focusing on three social enterprises found within GKonomics, or the platform of Gawad Kalinga for social enterprise development, this purposive study was able to show that employees’ perceptions on their employment positively influenced their perceptions on their capabilities, and that this result affected their improvement towards living a life they desire.

Keywords: social enterprise, Amartya Sen, capabilities framework, Gawad Kalinga

Procedia PDF Downloads 443

Authors: Tatiana V. Melnikova, Lyudmila P. Polyakova, Alla A. Oudalova

Abstract:

As a result of environmental pollution, the production of agriculture and foodstuffs inevitably contain residual amounts of Persistent Organic Pollutants (POP). The special attention must be given to organic pollutants, including various organochlorinated pesticides (OCP). Among priorities, OCP is DDT (and its metabolite DDE), alfa-HCH, gamma-HCH (lindane). The control of these substances spends proceeding from requirements of sanitary norms and rules. During too time often is lost sight of that the primary product can pass technological processing (in particular irradiation treatment) as a result of which transformation of physicochemical forms of initial polluting substances is possible. The goal of the present work was to study the OCP radiation degradation at a various gamma-radiation dosimetric characteristics. The problems posed for goal achievement: to evaluate the content of the priority of OCPs in food; study the character the degradation of OCP in model solutions (with micro concentrations commensurate with the real content of their agricultural and food products) depending upon dosimetric characteristics of gamma-radiation. Qualitative and quantitative analysis of OCP in food and model solutions by gas chromatograph Varian 3400 (Varian, Inc. (USA)); chromatography-mass spectrometer Varian Saturn 4D (Varian, Inc. (USA)) was carried out. The solutions of DDT, DDE, alpha- and gamma- isomer HCH (0.01, 0.1, 1 ppm) were irradiated on "Issledovatel" (60Co) and "Luch - 1" (60Co) installations at a dose 10 kGy with a variation of dose rate from 0.0083 up to 2.33 kGy/sec. It was established experimentally that OCP residual concentration in individual samples of food products (fish, milk, cereal crops, meat, butter) are evaluated as 10-1-10-4 mg/kg, the value of which depends on the factor-sensations territory and natural migration processes. The results were used in the preparation of model solutions OCP. The dependence of a degradation extent of OCP from a dose rate gamma-irradiation has complex nature. According to our data at a dose 10 kGy, the degradation extent of OCP at first increase passes through a maximum (over the range 0.23 – 0.43 Gy/sec), and then decrease with the magnification of a dose rate. The character of the dependence of a degradation extent of OCP from a dose rate is kept for various OCP, in polar and nonpolar solvents and does not vary at the change of concentration of the initial substance. Also in work conditions of the maximal radiochemical yield of OCP which were observed at having been certain: influence of gamma radiation with a dose 10 kGy, in a range of doses rate 0.23 – 0.43 Gy/sec; concentration initial OCP 1 ppm; use of solvent - 2-propanol after preliminary removal of oxygen. Based on, that at studying model solutions of OCP has been established that the degradation extent of pesticides and qualitative structure of OCP radiolysis products depend on a dose rate, has been decided to continue researches radiochemical transformations OCP into foodstuffs at various of doses rate.

Keywords: degradation extent, dosimetric characteristics, gamma-radiation, organochlorinated pesticides, persistent organic pollutants

Procedia PDF Downloads 249

Authors: Behnam Zahednejad, Saeed Kosari

Abstract:

Widespread deployment of Internet of Things (IoT) has raised security and privacy issues in this environment. Designing a secure two-factor authentication scheme between the user and server is still a challenging task. In this paper, we focus on Cancelable Biometric (CB) as an authentication factor in IoT. We show that previous CB-based scheme fail to provide real two-factor security, Perfect Forward Secrecy (PFS) and suffer database attacks and traceability of the user. Then we propose our improved scheme based on CB and Physically Unclonable Functions (PUF), which can provide real two-factor security, PFS, user’s unlinkability, and resistance to database attack. In addition, Key Compromise Impersonation (KCI) resilience is achieved in our scheme. We also prove the security of our proposed scheme formally using both Real-Or-Random (RoR) model and the ProVerif analysis tool. For the usability of our scheme, we conducted a performance analysis and showed that our scheme has the least communication cost compared to the previous CB-based scheme. The computational cost of our scheme is also acceptable for the IoT environment.

Keywords: IoT, two-factor security, cancelable biometric, key compromise impersonation resilience, perfect forward secrecy, database attack, real-or-random model, ProVerif

Procedia PDF Downloads 102

Authors: Chi C. Lin, Chih. H. Hsieh, Chi H. Lin

Abstract:

The present study attempted to develop and test a self-determination theory dual-process model among teachers’ need supportive teaching, need thwarting teaching, and students’ need satisfaction, need frustration, and motivation regulation on vocational high school learners. This study adopted a survey questionnaire method. Participants were 736 (472 males, 264 females) vocational high school students in Taiwan. The instrument included five sets: the Teachers’ Need Supportive Teaching Scale, the Teachers’ Need Thwart Teaching Scale, the Need Satisfaction Scale, the Need Frustration Scale, and the Motivational Regulation Scale. A Structural equation modeling was used for the data analyses, results indicated that (1) teachers’ need supportive teaching had direct effects on students’ need satisfaction; (2) teachers’ thwarting teaching also had a direct effect on students’ need frustration; (3) teachers’ need supportive teaching had a negative direct effect on students’ need frustration; (4) students’ need satisfaction had direct effects on their autonomous motivation and control motivation, respectively; (5) students’ need frustration also had direct effects on their control motivation and motivation, respectively; (6) the model proposed in this study fit mostly with the empirical data.

Keywords: motivational regulation, need satisfaction, need frustration, supportive teaching, thwart teaching, vocational high school students

Procedia PDF Downloads 134

Authors: M. Irannezhad, E. H. N. Gashti, S. Mohammadighavam, M. Zarrini, B. Kløve

Abstract:

Climate warming would increase rainfall by shifting precipitation falling form from snow to rain, and would accelerate snow cover disappearing by increasing snowpack. Using temperature and precipitation data in the temperature-index snowmelt model, we evaluated variability of snowfall and continuous snow cover duration(CSCD) during 1944-2010 over Pelso, central Finland. MannKendall non-parametric test determined that annual precipitation increased by 2.69 (mm/year, p<0.05) during the study period, but no clear trend in annual temperature. Both annual rainfall and snowfall increased by 1.67 and 0.78 (mm/year, p<0.05), respectively. CSCD was generally about 205 days from 14 October to 6 May. No clear trend was found in CSCD over Pelso. Spearman’s rank correlation showed most significant relationships of annual snowfall with the East Atlantic (EA) pattern, and CSCD with the East Atlantic/West Russia (EA/WR) pattern. Increased precipitation with no warming temperature caused the rainfall and snowfall to increase, while no effects on CSCD.

Keywords: variations, snowfall, snow cover duration, temperature-index snowmelt model, teleconnection patterns

Procedia PDF Downloads 223

Authors: Egoitz Aldanondo, Ekaitz Arruti, Amaia Iturrioz, Ivan Huarte, Fidel Zubiri

Abstract:

Manufacturing aeronautic structures joining extruded profiles or stringers to sheets or skins of aluminium is a typical manufacturing procedure in aeronautic structures. Although riveting is the conventional manufacturing technology to produce such joints, the Friction Stir Welding (FSW) and Laser Beam Welding (LBW) technologies have also demonstrated their potential for this kind of applications. Therefore, FSW and LBW technologies have the potential to continue their development as manufacturing processes for aeronautic structures showing benefits such as time-saving, light-weighting and overall cost reduction. In addition to that, new aluminium-lithium based alloy developments represent great opportunities for advanced aeronautic structure manufacturing with potential benefits such as lightweight construction or improved corrosion resistance. This work presents the main approaches by FSW and LBW to develop those technologies to produce stiffened panel structures such as fuselage by stringer-skin joints and using innovative aluminium-lithium alloys. Initial welding tests were performed in AA2198-T3S aluminium alloys for LBW technology and with AA2198-T851 for FSW. Later tests for both FSW and LBW have been carried out using AA2099-T83 alloy extrusions as stringers and AA2060-T8E30 as skin materials. The weld quality and properties have been examined by metallographic analysis and mechanical testing, including shear tensile tests and pull-out tests. The analysis of the results have shown the relationships between processing conditions, micro-macrostructural properties and the mechanical strength of the welded joints. The effects produced in the different alloys investigated have been observed and particular weld formation mechanics have been studied for each material and welding technology. Therefore, relationships between welding conditions and the obtained weld properties for each material combination and welding technology will be discussed in this presentation.

Keywords: AA2060-T8E30, AA2099-T83, AA2198-T3S, AA2198-T851, friction stir welding, laser beam welding

Procedia PDF Downloads 200

Authors: Sara Khamseh, Kambiz Javanruee, Hamid Khorsand

Abstract:

Plenty of metallic materials are used for biomedical applications like hip joints and screws. Besides, it is reported that metal platforms such as stainless steel show significant deterioration because of wear and friction. The surface of metal substrates has been coated with a variety of multicomponent coatings to prevail these problems. The carbon-based multicomponent coatings such as metal-added amorphous carbon and diamond coatings are crucially important because of their remarkable tribological performance and chemical stability. In the current study, H-D contained Nb: (a-C) multicomponent coatings (H-D: hexagonal diamond, a-C: amorphous carbon) coated on A 304 steel substrates using an unbalanced magnetron (UBM) sputtering system. The effects of Nb and H-D content and ID/IG ratio on microstructure, mechanical and tribological characteristics of (Nb: H-D: a-C) composite coatings were investigated. The results of Raman spectroscopy represented that a-C phase with a Graphite-like structure (GLC with high value of sp2 carbon bonding) is formed, and its domain size increased with increasing Nb content of the coatings. Moreover, the Nb played a catalyst for the formation of the H-D phase. The nanoindentation hardness value of the coatings ranged between ~17 to ~35 GPa and (Nb: H-D: a-C) composite coatings with more H-D content represented higher hardness and plasticity index. It seems that the existence of extra-hard H-D particles straightly increased hardness. The tribological performance of the coatings was evaluated using the pin-on-disc method under the wet environment of SBF (Simulated Body Fluid). The COF value of the (Nb: H-D: a-C) coatings decreased with an increasing ID/IG ratio. The lower coefficient of friction is a result of the lamelliform array of graphitic domains. Also, the wear rate of the coatings decreased with increasing H-D content of the coatings. Based on the literature, a-C coatings with high hardness and H3/E2 ratio represent lower wear rates and better tribological performance. According to the nanoindentation analysis, hardness and H3/E2 ratio of (Nb: H-D: a-C) multicomponent coatings increased with increasing H-D content, which in turn decreased the wear rate of the coatings. The mechanical and tribological potency of (Nb: H-D: a-C) composite coatings on A 304 steel substrates paved the way for the development of innovative advanced coatings to ameliorate the performance of A 304 steel for biomedical applications.

Keywords: COF, mechanical properties, (Nb: H-D: a-C) coatings, wear rate

Procedia PDF Downloads 103

Authors: Mohamed Haffar, Muhammad Abdul Aziz, Ahmad Ghoneim

Abstract:

The importance of having a good organizational culture that supports employee job satisfaction has fascinated both the business and academic world because of a tantalizing promise: culture can be fundamental to the enhancement of financial performance. This promise has led to growing interest for both researchers and practitioners in attempting to understand the influence of organizational culture on employees’ satisfaction and organizational performance. Even though the relationship between organizational culture and employee job satisfaction have gained attention in the literature, the majority of studies have been conducted within manufacturing organizations and tend to oversee the impact of culture on employee job satisfaction in a service-based environment. Thus, the main driving force of this study was to explore the role of organizational culture types in facilitating employee job satisfaction at Emerald Publishing Group. Interviews qualitative data analysis indicated that Emerald’s culture dominated by adhocracy and clan culture values. In addition, the findings provided evidence, which demonstrated that group and adhocracy organizational culture types play key roles in facilitating employee job satisfaction in a service-based environment.

Keywords: employee satisfaction, organizational culture, performance, service based environment

Procedia PDF Downloads 439

Authors: Arpit Kumar Shrivastava, Subrat Kumar, Rajani Kanta Mohapatra, Priyadarshi Soumyaranjan Sahu

Abstract:

Computational approaches to predict structure, function and other biological characteristics of proteins are becoming more common in comparison to the traditional methods in drug discovery. Cryptosporidiosis is a major zoonotic diarrheal disease particularly in children, which is caused primarily by Cryptosporidium hominis and Cryptosporidium parvum. Currently, there are no vaccines for cryptosporidiosis and recommended drugs are not effective. With the availability of complete genome sequence of C. hominis, new targets have been recognized for the development of effective and better drugs and/or vaccines. We identified a unique hypothetical epitopic protein in C. hominis genome through BLASTP analysis. A 3D model of the hypothetical protein was generated using I-Tasser server through threading methodology. The quality of the model was validated through Ramachandran plot by PROCHECK server. The functional annotation of the hypothetical protein through DALI server revealed structural similarity with human Transportin 3. Phylogenetic analysis for this hypothetical protein also showed C. hominis hypothetical protein (CUV04613) was the closely related to human transportin 3 protein. The 3D protein model is further subjected to virtual screening study with inhibitors from the Zinc Database by using Dock Blaster software. Docking study reported N-(3-chlorobenzyl) ethane-1,2-diamine as the best inhibitor in terms of docking score. Docking analysis elucidated that Leu 525, Ile 526, Glu 528, Glu 529 are critical residues for ligand–receptor interactions. The molecular dynamic simulation was done to access the reliability of the binding pose of inhibitor and protein complex using GROMACS software at 10ns time point. Trajectories were analyzed at each 2.5 ns time interval, among which, H-bond with LEU-525 and GLY- 530 are significantly present in MD trajectories. Furthermore, antigenic determinants of the protein were determined with the help of DNA Star software. Our study findings showed a great potential in order to provide insights in the development of new drug(s) or vaccine(s) for control as well as prevention of cryptosporidiosis among humans and animals.

Keywords: cryptosporidium hominis, hypothetical protein, molecular docking, molecular dynamics simulation

Procedia PDF Downloads 365

Authors: Delphine Ribes Lemay, Valentine Bernasconi, André Andrade, Lara DéFayes, Mathieu Salzmann, FréDéRic Kaplan, Nicolas Henchoz

Abstract:

Digitization and preservation of large heritage induce high maintenance costs to keep up with the technical standards and ensure sustainable access. Creating impactful usage is instrumental to justify the resources for long-term preservation. The Museum für Gestaltung of Zurich holds one of the biggest poster collections of the world from which 52’000 were digitised. In the process of building a digital installation to valorize the collection, one objective was to develop an algorithm capable of predicting the next poster to show according to the ones already displayed. The work presented here describes the steps to build an algorithm able to automatically create sequences of posters reflecting associations performed by curator and professional designers. The exposed challenge finds similarities with the domain of song playlist algorithms. Recently, artificial intelligence techniques and more specifically, deep-learning algorithms have been used to facilitate their generations. Promising results were found thanks to Recurrent Neural Networks (RNN) trained on manually generated playlist and paired with clusters of extracted features from songs. We used the same principles to create the proposed algorithm but applied to a challenging medium, posters. First, a convolutional autoencoder was trained to extract features of the posters. The 52’000 digital posters were used as a training set. Poster features were then clustered. Next, an RNN learned to predict the next cluster according to the previous ones. RNN training set was composed of poster sequences extracted from a collection of books from the Gestaltung Museum of Zurich dedicated to displaying posters. Finally, within the predicted cluster, the poster with the best proximity compared to the previous poster is selected. The mean square distance between features of posters was used to compute the proximity. To validate the predictive model, we compared sequences of 15 posters produced by our model to randomly and manually generated sequences. Manual sequences were created by a professional graphic designer. We asked 21 participants working as professional graphic designers to sort the sequences from the one with the strongest graphic line to the one with the weakest and to motivate their answer with a short description. The sequences produced by the designer were ranked first 60%, second 25% and third 15% of the time. The sequences produced by our predictive model were ranked first 25%, second 45% and third 30% of the time. The sequences produced randomly were ranked first 15%, second 29%, and third 55% of the time. Compared to designer sequences, and as reported by participants, model and random sequences lacked thematic continuity. According to the results, the proposed model is able to generate better poster sequencing compared to random sampling. Eventually, our algorithm is sometimes able to outperform a professional designer. As a next step, the proposed algorithm should include a possibility to create sequences according to a selected theme. To conclude, this work shows the potentiality of artificial intelligence techniques to learn from existing content and provide a tool to curate large sets of data, with a permanent renewal of the presented content.

Keywords: Artificial Intelligence, Digital Humanities, serendipity, design research

Procedia PDF Downloads 184

Authors: Ceren Sevimli, Sedat İnan

Abstract:

The Silurian Dadaş Formation within the Diyarbakir Basin in SE Türkiye, like other Silurian shales in North Africa and Middle East, represents a significant prospect for conventional and unconventional hydrocarbon exploration. The Diyarbakır Basin remains relatively underexplored, presenting untapped potential that warrants further investigation. This study focuses on the thermal maturity and hydrocarbon generation histories of the Silurian Dadaş shales, utilizing basin modeling approach. The Dadaş shales are organic-rich and contain mainly Type II kerogen, especially the basal layer contains up to 10 wt. %TOC and thus it is named as “hot shale”. The research integrates geological, geochemical, and basin modeling data to elucidate the unconventional hydrocarbon potential of this formation, which is crucial given the global demand for energy and the need for new resources. The data obtained from previous studies were used to calibrate basin model that has been established by using PetroMod software (Schlumberger). The calibrated model results suggest that Dadaş shales are in oil generation window and that the major episode for thermal maturation and hydrocarbon generation took place prior rot Alpine orogeny (uplift and erosion) The modeling results elucidate the burial history, maturity history, and hydrocarbon production history of the Silurian-aged Dadaş shales, as well as its hydrocarbon content in the area.

Keywords: dadaş formation, diyarbakır basin, silurian hot shale, unconventional hydrocarbon

Procedia PDF Downloads 33

Authors: Diogo Ferreira Lima Filho, José Roberto Amazonas

Abstract:

Nanotechnology opens the door to new paradigms that introduces a variety of novel tools enabling a plethora of potential applications in the biomedical, industrial, environmental, and military fields. This work proposes an integrated node model by applying the same concepts of TCNet to networks of nanodevices where the nodes are cooperatively interconnected with a low-complexity Mealy Machine (MM) topology integrating in the same electronic system the modules necessary for independent operation in wireless sensor networks (WSNs), consisting of Rectennas (RF to DC power converters), Code Generators based on Finite State Machine (FSM) & Trellis Decoder and On-chip Transmit/Receive with autonomy in terms of energy sources applying the Energy Harvesting technique. This approach considers the use of a Graphene Composite Substrate (GCS) for the integrated electronic circuits meeting the following characteristics: mechanical flexibility, miniaturization, and optical transparency, besides being ecological. In addition, graphene consists of a layer of carbon atoms with the configuration of a honeycomb crystal lattice, which has attracted the attention of the scientific community due to its unique Electrical Characteristics.

Keywords: composite substrate, energy harvesting, finite state machine, graphene, nanotechnology, rectennas, wireless sensor networks

Procedia PDF Downloads 106

Authors: Mathias B. Michael, Esther T. Akinlabi, Tien-Chien Jen

Abstract:

Thermal energy consumption in palm oil production plant comprises mainly of steam, hot water and hot air. In most efficient plants, hot water and air are generated from the steam supply system. Research has shown that thermal energy utilize in palm oil production plants is about 70 percent of the total energy consumption of the plant. In order to manage the plants’ energy efficiently, the energy systems are modelled and optimized. This paper aimed to present the model of steam supply systems of a typical palm oil production plant in Ghana. The models include exergy and energy models of steam boiler, steam turbine and the palm oil mill. The paper further simulates the virtual plant model to obtain the thermal energy performance of the plant under study. The simulation results show that, under normal operating condition, the boiler energy performance is considerably below the expected level as a result of several factors including intermittent biomass fuel supply, significant moisture content of the biomass fuel and significant heat losses. The total thermal energy performance of the virtual plant is set as a baseline. The study finally recommends number of energy efficiency measures to improve the plant’s energy performance.

Keywords: palm biomass, steam supply, exergy and energy models, energy performance benchmark

Procedia PDF Downloads 350

Authors: Aragorn Joaquin Pineda Dela Cruz

Abstract:

Road traffic congestion is continually deteriorating in Hong Kong. The largest contributing factor is the increase in vehicle fleet size, resulting in higher competition over the utilisation of road space. This study proposes a project that can process closed-circuit television images and videos to provide real-time traffic detection and prediction capabilities. Specifically, a deep-learning model involving computer vision techniques for video and image-based vehicle counting, then a separate model to detect and predict traffic congestion levels based on said data. State-of-the-art object detection models such as You Only Look Once and Faster Region-based Convolutional Neural Networks are tested and compared on closed-circuit television data from various major roads in Hong Kong. It is then used for training in long short-term memory networks to be able to predict traffic conditions in the near future, in an effort to provide more precise and quicker overviews of current and future traffic conditions relative to current solutions such as navigation apps.

Keywords: intelligent transportation system, vehicle detection, traffic analysis, deep learning, machine learning, computer vision, traffic prediction

Procedia PDF Downloads 102

Authors: S. Behnia, S. Fathizadeh, A. Akhshani

Abstract:

In the recent decades, DNA has increasingly interested in the potential technological applications that not directly related to the coding for functional proteins that is the expressed in form of genetic information. One of the most interesting applications of DNA is related to the construction of nanostructures of high complexity, design of functional nanostructures in nanoelectronical devices, nanosensors and nanocercuits. In this field, DNA is of fundamental interest to the development of DNA-based molecular technologies, as it possesses ideal structural and molecular recognition properties for use in self-assembling nanodevices with a definite molecular architecture. Also, the robust, one-dimensional flexible structure of DNA can be used to design electronic devices, serving as a wire, transistor switch, or rectifier depending on its electronic properties. In order to understand the mechanism of the charge transport along DNA sequences, numerous studies have been carried out. In this regard, conductivity properties of DNA molecule could be investigated in a simple, but chemically specific approach that is intimately related to the Su-Schrieffer-Heeger (SSH) model. In SSH model, the non-diagonal matrix element dependence on intersite displacements is considered. In this approach, the coupling between the charge and lattice deformation is along the helix. This model is a tight-binding linear nanoscale chain established to describe conductivity phenomena in doped polyethylene. It is based on the assumption of a classical harmonic interaction between sites, which is linearly coupled to a tight-binding Hamiltonian. In this work, the Hamiltonian and corresponding motion equations are nonlinear and have high sensitivity to initial conditions. Then, we have tried to move toward the nonlinear dynamics and phase space analysis. Nonlinear dynamics and chaos theory, regardless of any approximation, could open new horizons to understand the conductivity mechanism in DNA. For a detailed study, we have tried to study the current flowing in DNA and investigated the characteristic I-V diagram. As a result, It is shown that there are the (quasi-) ohmic areas in I-V diagram. On the other hand, the regions with a negative differential resistance (NDR) are detectable in diagram.

Keywords: DNA conductivity, Landauer resistance, negative dierential resistance, Chaos theory, mean Lyapunov exponent

Procedia PDF Downloads 425

Authors: Qamar Ul Haq, Talat Hussain, Mufti Fahad Ahmed Qureshi

Abstract:

From the Islamic perspective, managing human resource meets various challenges, especially in the modern organizations. The adoption of Western practices in various aspects of management have caused gaps in justice, trustworthy, responsibility and other values of workers in Muslim countries. Thus, the interference of Islamic principles in human resource management (HRM) can be considered as a great solution for treating employees fairly and justly. This research aims to examine the level of Islamic practices in HRM, in which includes recruitment and selection, training and development, career development, performance management and rewards. The paper will analyze the relationships between HRM practices and organizational justice which focus on three elements, which are distributive justice, procedure justice and interactional justice. The data will be collected from selected Malaysian Government-Linked Company (GLC). Convenience sampling will be used to select the respondents for completing questionnaires. This conceptual paper essentially provides organizations with effective ways of understanding and implementing HRM by using Islamic principles. It also can be used as guidance for decision-making and day-today HR activities and will help organization to face uncertainties in the business world as well.

Keywords: human resource management, organizational justice, Islam, Islamic banking

Procedia PDF Downloads 440

Authors: Eleonora Carloni, Michela Arnaboldi

Abstract:

In academia, the investigation of the relationship between cultural heritage and corporations is ubiquitous in several fields of studies. In practice corporations are more and more integrating arts and cultural heritage in their strategies for disparate benefits, such as: to foster customer’s purchase intention with authentic and aesthetic experiences, to improve their reputation towards local communities, and to motivate employees with creative thinking. There are diverse forms under which corporations set these artistic interventions, from sponsorships to arts-based training centers for employees, but scholars agree that the maximum expression of this cultural trend are corporate museums, growing in number and relevance. Corporate museums are museum-like settings, hosting artworks of corporations’ history and interests. In academia they have been ascribed as strategic asset and they have been associated with diverse uses for corporations’ benefits, from place for preservation of cultural heritage, to tools for public relations and cultural flagship stores. Previous studies have thus extensively but fragmentally studied the diverse benefits of corporate museum opening to corporations, with a lack of comprehensive approach and a digression on how to evaluate and report corporate museum’s performances. Stepping forward, the present study aims to investigate: 1) what are the key performance measures corporate museums need to report to the associated corporations; 2) how are the key performance measures reported to the concerned corporations. This direction of study is not only suggested as future direction in academia but it has solid basis in practice, aiming to answer to the need of corporate museums’ directors to account for corporate museum’s activities to the concerned corporation. Coherently, at an empirical level the study relies on action research method, whose distinctive feature is to develop practical knowledge through a participatory process. This paper indeed relies on the experience of a collaborative project between the researchers and a set of corporate museums in Italy, aimed at co-developing a performance measurement system. The project involved two steps: a first step, in which researchers derived the potential performance measures from literature along with exploratory interviews; a second step, in which researchers supported the pool of corporate museums’ directors in co-developing a set of key performance indicators for reporting. Preliminary empirical findings show that while scholars insist on corporate museums’ capability to develop networking relations, directors insist on the role of museums as internal supplier of knowledge for innovation goals. Moreover, directors stress museums’ cultural mission and outcomes as potential benefits for corporation, by remarking to include both cultural and business measures in the final tool. In addition, they give relevant attention to the wording used in humanistic terms while struggling to express all measures in economic terms. The paper aims to contribute to corporate museums’ and more broadly to arts-based initiatives’ literature in two directions. Firstly, it elaborates key performance measures with related indicators to report on cultural initiatives for corporations. Secondly, it provides evidence of challenges and practices to handle reporting on these initiatives, because of tensions arising from the co-existence of diverse perspectives, namely arts and business worlds.

Keywords: arts-based initiative, corporate museum, hybrid organization, performance measurement

Procedia PDF Downloads 176

Authors: V. S. Manivasagam, R. Nagarajan

Abstract:

Modeling the soil, water and crop growth interactions are attaining major importance, considering the future climate change and water availability for agriculture to meet the growing food demand. Progress in understanding the crop growth response during water stress period through crop modeling approach provides an opportunity for improving and sustaining the future agriculture water use efficiency. An attempt has been made to evaluate the potential use of crop modeling approach for assessing the minimal supplementary irrigation requirement for crop growth during water limited condition and its practical significance in sustainable improvement of crop yield and water productivity. Among the numerous crop models, water driven-AquaCrop model has been chosen for the present study considering the modeling approach and water stress impact on yield simulation. The study has been evaluated in rainfed maize grown area of semi-arid Shanmuganadi watershed (a tributary of the Cauvery river system) located in southern India during the rabi cropping season (October-February). In addition to actual rainfed maize growth simulation, irrigated maize scenarios were simulated for assessing the supplementary irrigation requirement during water shortage condition for the period 2012-2015. The simulation results for rainfed maize have shown that the average maize yield of 0.5-2 t ha-1 was observed during deficit monsoon season (<350 mm) whereas 5.3 t ha-1 was noticed during sufficient monsoonal period (>350 mm). Scenario results for irrigated maize simulation during deficit monsoonal period has revealed that 150-200 mm of supplementary irrigation has ensured the 5.8 t ha-1 of irrigated maize yield. Thus, study results clearly portrayed that minimal application of supplementary irrigation during the critical growth period along with the deficit rainfall has increased the crop water productivity from 1.07 to 2.59 kg m-3 for major soil types. Overall, AquaCrop is found to be very effective for the sustainable irrigation assessment considering the model simplicity and minimal inputs requirement.

Keywords: AquaCrop, crop modeling, rainfed maize, water stress

Procedia PDF Downloads 269

Authors: Hannah Rosenqvist, Fanny Guay

Abstract:

Critical infrastructure protection has been an important topic for several years. Programmes such as the European Programme for Critical Infrastructure Protection (EPCIP), Critical Infrastructure Warning Information Network (CIWIN) and the European Reference Network for Critical Infrastructure Protection (ENR-CIP) have been the pillars to the work done since 2006. However, measuring critical infrastructure resilience has not been an easy task. This has to do with the fact that the concept of resilience has several definitions and is applied in different domains such as engineering and social sciences. Since June 2015, the EU project IMPROVER has been focusing on developing a methodology for implementing a combination of societal, organizational and technological resilience concepts, in the hope to increase critical infrastructure resilience. For this paper, we performed research on how to include societal resilience as a form of measurement of the context of critical infrastructure resilience. Because one of the main purposes of critical infrastructure (CI) is to deliver services to the society, we believe that societal resilience is an important factor that should be considered when assessing the overall CI resilience. We found that existing methods for CI resilience assessment focus mainly on technical aspects and therefore that is was necessary to develop a resilience model that take social factors into account. The model developed within the project IMPROVER aims to include the community’s expectations of infrastructure operators as well as information sharing with the public and planning processes. By considering such aspects, the IMPROVER framework not only helps operators to increase the resilience of their infrastructures on the technical or organizational side, but aims to strengthen community resilience as a whole. This will further be achieved by taking interdependencies between critical infrastructures into consideration. The knowledge gained during this project will enrich current European policies and practices for improved disaster risk management. The framework for societal resilience analysis is based on three dimensions for societal resilience; coping capacity, adaptive capacity and transformative capacity which are capacities that have been recognized throughout a widespread literature review in the field. A set of indicators have been defined that describe a community’s maturity within these resilience dimensions. Further, the indicators are categorized into six community assets that need to be accessible and utilized in such a way that they allow responding to changes and unforeseen circumstances. We conclude that the societal resilience model developed within the project IMPROVER can give a good indication of the level of societal resilience to critical infrastructure operators.

Keywords: community resilience, critical infrastructure protection, critical infrastructure resilience, societal resilience

Procedia PDF Downloads 230

Authors: Anukriti Kumar, Tanmay Singh, Dinesh Kumar Vishwakarma

Abstract:

Traffic control has been one of the most common and irritating problems since the time automobiles have hit the roads. Problems like traffic congestion have led to a significant time burden around the world and one significant solution to these problems can be the proper implementation of the Intelligent Transport System (ITS). It involves the integration of various tools like smart sensors, artificial intelligence, position technologies and mobile data services to manage traffic flow, reduce congestion and enhance driver's ability to avoid accidents during adverse weather. Road and traffic signs’ recognition is an emerging field of research in ITS. Classification problem of traffic signs needs to be solved as it is a major step in our journey towards building semi-autonomous/autonomous driving systems. The purpose of this work focuses on implementing an approach to solve the problem of traffic sign classification by developing a Convolutional Neural Network (CNN) classifier using the GTSRB (German Traffic Sign Recognition Benchmark) dataset. Rather than using hand-crafted features, our model addresses the concern of exploding huge parameters and data method augmentations. Our model achieved an accuracy of around 97.6% which is comparable to various state-of-the-art architectures.

Keywords: multiclass classification, convolution neural network, OpenCV

Procedia PDF Downloads 176

Authors: Ghita Benayad

Abstract:

Asset allocation, which affects the long-term profitability of portfolios by distributing assets to fulfill a range of investment objectives, is the cornerstone of investment management in the dynamic and complicated world of financial markets. This paper offers a technique for optimizing strategic asset allocation with the goal of improving portfolio performance by addressing the inherent complexity and uncertainty of the market through the use of Principal Component Analysis (PCA) in a multi-objective modeling framework. The study's first section starts with a critical evaluation of conventional asset allocation techniques, highlighting how poorly they are able to capture the intricate relationships between assets and the volatile nature of the market. In order to overcome these challenges, the project suggests a PCA-driven methodology that isolates important characteristics influencing asset returns by decreasing the dimensionality of the investment universe. This decrease provides a stronger basis for asset allocation decisions by facilitating a clearer understanding of market structures and behaviors. Using a multi-objective optimization model, the project builds on this foundation by taking into account a number of performance metrics at once, including risk minimization, return maximization, and the accomplishment of predetermined investment goals like regulatory compliance or sustainability standards. This model provides a more comprehensive understanding of investor preferences and portfolio performance in comparison to conventional single-objective optimization techniques. While applying the PCA-driven multi-objective optimization model to historical market data, aiming to construct portfolios better under different market situations. As compared to portfolios produced from conventional asset allocation methodologies, the results show that portfolios optimized using the proposed method display improved risk-adjusted returns, more resilience to market downturns, and better alignment with specified investment objectives. The study also looks at the implications of this PCA technique for portfolio management, including the prospect that it might give investors a more advanced framework for navigating financial markets. The findings suggest that by combining PCA with multi-objective optimization, investors may obtain a more strategic and informed asset allocation that is responsive to both market conditions and individual investment preferences. In conclusion, this capstone project improves the field of financial engineering by creating a sophisticated asset allocation optimization model that integrates PCA with multi-objective optimization. In addition to raising concerns about the condition of asset allocation today, the proposed method of portfolio management opens up new avenues for research and application in the area of investment techniques.

Keywords: asset allocation, portfolio optimization, principle component analysis, multi-objective modelling, financial market

Procedia PDF Downloads 47

Authors: Farzaneh Khorram

Abstract:

This paper endeavors to construct a block model to assess grinding energy consumption (CCE) and pinpoint blocks with the highest potential for energy usage during the grinding process within a specified region. Leveraging geostatistical techniques, particularly joint estimation, or simulation, based on geometallurgical data from various mineral processing stages, our objective is to forecast CCE across the study area. The dataset encompasses variables obtained from 2754 drill samples and a block model comprising 4680 blocks. The initial analysis encompassed exploratory data examination, variography, multivariate analysis, and the delineation of geological and structural units. Subsequent analysis involved the assessment of contacts between these units and the estimation of CCE via cokriging, considering its correlation with SPI. The selection of blocks exhibiting maximum CCE holds paramount importance for cost estimation, production planning, and risk mitigation. The study conducted exploratory data analysis on lithology, rock type, and failure variables, revealing seamless boundaries between geometallurgical units. Simulation methods, such as Plurigaussian and Turning band, demonstrated more realistic outcomes compared to cokriging, owing to the inherent characteristics of geometallurgical data and the limitations of kriging methods.

Keywords: geometallurgy, multivariate analysis, plurigaussian, turning band method, cokriging

Procedia PDF Downloads 70