Search results for: automated investment systems

Authors: H. Nikzad, S. Yoshitomi

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This study investigates and develops the structural optimization method. The effect of size constraints on practical solution of reinforced concrete (RC) building structure with shear wall is proposed. Cross-sections of beam and column, and thickness of shear wall are considered as design variables. The objective function to be minimized is total cost of the structure by using a simple and efficient automated MATLAB platform structural optimization methodology. With modification of mathematical formulations, the result is compared with optimal solution without size constraints. The most suitable combination of section sizes is selected as for the final design application based on linear static analysis. The findings of this study show that defining higher value of upper bound of sectional sizes significantly affects optimal solution, and defining of size constraints play a vital role in finding of global and practical solution during optimization procedures. The result and effectiveness of proposed method confirm the ability and efficiency of optimal solutions for 3D RC shear wall-frame structure.

Keywords: structural optimization, linear static analysis, ETABS, MATLAB, RC shear wall-frame structures

Procedia PDF Downloads 369

Authors: Varun Singh, Mainak Bandyopadhyay, Maharana Pratap Singh

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The shortest path (SP) problem concerns with finding the shortest path from a specific origin to a specified destination in a given network while minimizing the total cost associated with the path. This problem has widespread applications. Important applications of the SP problem include vehicle routing in transportation systems particularly in the field of in-vehicle Route Guidance System (RGS) and traffic assignment problem (in transportation planning). Well known applications of evolutionary methods like Genetic Algorithms (GA), Ant Colony Optimization, Particle Swarm Optimization (PSO) have come up to solve complex optimization problems to overcome the shortcomings of existing shortest path analysis methods. It has been reported by various researchers that PSO performs better than other evolutionary optimization algorithms in terms of success rate and solution quality. Further Geographic Information Systems (GIS) have emerged as key information systems for geospatial data analysis and visualization. This research paper is focused towards the application of PSO for solving the shortest path problem between multiple points of interest (POI) based on spatial data of Allahabad City and traffic speed data collected using GPS. Geovisualization of results of analysis is carried out in GIS.

Keywords: particle swarm optimization, GIS, traffic data, outliers

Procedia PDF Downloads 470

Authors: Alicja Starczewska, Aleksander Nawrat, Krzysztof Daniec, Jarosław Homa, Kacper Hołda

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Border Gateway Protocol is the main routing protocol that enables routing establishment between all autonomous systems, which are the basic administrative units of the internet. Due to the poor protection of BGP, it is important to use additional BGP security systems. Many solutions to this problem have been proposed over the years, but none of them have been implemented on a global scale. This article describes a system capable of building images of real-time BGP network topology in order to detect BGP anomalies. Our proposal performs a detailed analysis of BGP messages that come into local network cards supplemented by information collected by remote collectors in different localizations.

Keywords: BGP, BGP hijacking, cybersecurity, detection

Procedia PDF Downloads 65

Authors: David Krejci, Tony Schönherr, Quirin Koch, Valentin Hugonnaud, Lou Grimaud, Alexander Reissner, Bernhard Seifert

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In 2018 the NANO thruster became the first Field Emission Electric Propulsion (FEEP) system ever to be verified in space in an In-Orbit Demonstration mission conducted together with Fotec. Since then, 160 additional ENPULSION NANO propulsion systems have been deployed in orbit on 73 different spacecraft across multiple customers and missions. These missions included a variety of different satellite bus sizes ranging from 3U Cubesats to >100kg buses, and different orbits in Low Earth Orbit and Geostationary Earth orbit, providing an abundance of on orbit data for statistical analysis. This large-scale industrialization and flight heritage allows for a holistic way of gathering data from testing, integration and operational phases, deriving lessons learnt over a variety of different mission types, operator approaches, use cases and environments. Based on these lessons learnt a new generation of propulsion systems is developed, addressing key findings from the large NANO heritage and adding new capabilities, including increased resilience, thrust vector steering and increased power and thrust level. Some of these successor products have already been validated in orbit, including the MICRO R3 and the NANO AR3. While the MICRO R3 features increased power and thrust level, the NANO AR3 is a successor of the heritage NANO thruster with added thrust vectoring capability. 5 NANO AR3 have been launched to date on two different spacecraft. This work presents flight telemetry data of ENPULSION NANO systems and onorbit statistical data of the ENPULSION NANO as well as lessons learnt during onorbit operations, customer assembly, integration and testing support and ground test campaigns conducted at different facilities. We discuss how transfer of lessons learnt and operational improvement across independent missions across customers has been accomplished. Building on these learnings and exhaustive heritage, we present the design of the new generation of propulsion systems that increase the power and thrust level of FEEP systems to address larger spacecraft buses.

Keywords: FEEP, field emission electric propulsion, electric propulsion, flight heritage

Procedia PDF Downloads 75

Authors: Jamie L. Stangel

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Increased popularity and visibility of college athletics have contributed to an environment in which institutions -most of which lack self-sufficient athletics department budgets- reallocate monies from the university general fund and seek additional funding sources to keep up with increasing levels of spending on athletics. Given the prevalence of debates on student debt levels, coach salaries, and athlete pay, empirical evidence on whether this spending yields an expected return on investment is necessary. This study considered the relationship between the independent variable of the winning percentage of the men’s basketball team at a mid-major university, moderated by NCAA tournament appearance, number of applicants, number of enrollments, average SAT score of students, and donor giving to the university general and athletic funds. The results indicate that, other than a small correlation between athletic success and number of applicants, only when NCAA tournament appearance is used as a moderating variable, these purported benefits are not supported, suggesting the need for a reevaluation of athletic department spending and perceptions on tangible and intangible benefits for universities.

Keywords: athletic success, enrollment, NCAA, private giving

Procedia PDF Downloads 117

Authors: Okoro Ikechukwu Ralph, Fuat Kara

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The discoveries of hydrocarbon reserves has clearly drifted offshore, and in deeper waters - areas where the industry still has limited knowledge; and that were hitherto, regarded as being out of reach. This shift presents significant and increased challenges in technology requirements needed to guarantee safety of personnel, environment and equipment; ensure high reliability of installed equipment; and provide high level of confidence in security of investment and company reputation. Nowhere are these challenges more apparent than on subsea well integrity and production performance. The past two decades has witnessed enormous rise in deep and ultra-deep water offshore field developments for the recovery of hydrocarbons. Subsea installed equipment at the seabed has been the technology of choice for these developments. This paper discusses the role of Subsea Control module (SCM) as a vital factor for deep-water well integrity and production performance. A case study for Deep-water well integrity and production performance is analysed.

Keywords: offshore reliability, production performance, subsea control module, well integrity

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Authors: Umesh Kumar Singh, Chanchala Joshi

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With increasing dependency on IT infrastructure, the main objective of a system administrator is to maintain a stable and secure network, with ensuring that the network is robust enough against malicious network users like attackers and intruders. Security risk management provides a way to manage the growing threats to infrastructures or system. This paper proposes a framework for risk level estimation which uses vulnerability database National Institute of Standards and Technology (NIST) National Vulnerability Database (NVD) and the Common Vulnerability Scoring System (CVSS). The proposed framework measures the frequency of vulnerability exploitation; converges this measured frequency with standard CVSS score and estimates the security risk level which helps in automated and reasonable security management. In this paper equation for the Temporal score calculation with respect to availability of remediation plan is derived and further, frequency of exploitation is calculated with determined temporal score. The frequency of exploitation along with CVSS score is used to calculate the security risk level of the system. The proposed framework uses the CVSS vectors for risk level estimation and measures the security level of specific network environment, which assists system administrator for assessment of security risks and making decision related to mitigation of security risks.

Keywords: CVSS score, risk level, security measurement, vulnerability category

Procedia PDF Downloads 316

Authors: Nabil A. Ahmed

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DC-DC converters are necessary to interface low-voltage fuel cell power generation systems to a higher voltage DC bus system. A system and method for generating a regulated output power from fuel cell power generation systems is proposed in this paper, this includes a soft-switching isolated DC-DC converter to reduce the idling and circulating currents. The system incorporates a high-frequency center tap transformer link DC-DC converter using secondary-side soft switching control. Snubber capacitors including the parasitic capacitance of the switching devices and the transformer leakage inductance are utilized to achieve zero-voltage switching (ZVS) in the primary side of the high-frequency transformer. Therefore, no extra resonant components are required for ZVS. The inherent soft-switching capability allows high power density, efficient power conversion, and compact packaging. A prototype rated at 6.5 kW is proposed and simulated. Simulation results confirmed a wide range of soft-switching operation and consequently high conversion efficiency will be achieved.

Keywords: secondary-side, phase-shift, high-frequency transformer, zero voltage, zero current, soft switching operation, switching losses

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Authors: R. R. Ramsheeja, R. Sreeraj

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For view the internal structures of the human body such as liver, brain, kidney etc have a wide range of different modalities for medical images are provided nowadays. Computer Tomography is one of the most significant medical image modalities. In this paper use CT liver images for study the use of automatic computer aided techniques to calculate the volume of the liver tumor. Segmentation method is used for the detection of tumor from the CT scan is proposed. Gaussian filter is used for denoising the liver image and Adaptive Thresholding algorithm is used for segmentation. Multiple Region Of Interest(ROI) based method that may help to characteristic the feature different. It provides a significant impact on classification performance. Due to the characteristic of liver tumor lesion, inherent difficulties appear selective. For a better performance, a novel proposed system is introduced. Multiple ROI based feature selection and classification are performed. In order to obtain of relevant features for Support Vector Machine(SVM) classifier is important for better generalization performance. The proposed system helps to improve the better classification performance, reason in which we can see a significant reduction of features is used. The diagnosis of liver cancer from the computer tomography images is very difficult in nature. Early detection of liver tumor is very helpful to save the human life.

Keywords: computed tomography (CT), multiple region of interest(ROI), feature values, segmentation, SVM classification

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Authors: A. Rong, P. B. Luh, R. Lahdelma

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High penetration of intermittent renewable energy sources (RES) such as solar power and wind power into the energy system has caused temporal and spatial imbalance between electric power supply and demand for some countries and regions. This brings about the critical need for coordinating power production and power exchange for different regions. As compared with the power-only systems, the combined heat and power (CHP) systems can provide additional flexibility of utilizing RES by exploiting the interdependence of power and heat production in the CHP plant. In the CHP system, power production can be influenced by adjusting heat production level and electric power can be used to satisfy heat demand by electric boiler or heat pump in conjunction with heat storage, which is much cheaper than electric storage. This paper addresses multi-site CHP systems without considering RES, which lay foundation for handling penetration of RES. The problem under study is the unit commitment (UC) of the transmission-constrained multi-site CHP systems. We solve the problem by combining linear relaxation of ON/OFF states and sequential dynamic programming (DP) techniques, where relaxed states are used to reduce the dimension of the UC problem and DP for improving the solution quality. Numerical results for daily scheduling with realistic models and data show that DP-based algorithm is from a few to a few hundred times faster than CPLEX (standard commercial optimization software) with good solution accuracy (less than 1% relative gap from the optimal solution on the average).

Keywords: dynamic programming, multi-site combined heat and power system, relaxed states, transmission-constrained generation unit commitment

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Authors: Alice Civera, Mattia Cattaneo, Michele Meoli, Stefano Paleari

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Despite the fact that more equal access to higher education has been an objective public policy for several decades, little is known about the effectiveness of alternative means for achieving such goal. Indeed, nowadays, high level of graduate population can be observed both in countries with the high and low level of fees, or high and low level of public expenditure in higher education. This paper surveys the extant literature providing some background on the economic concepts of the higher education market, and reviews key determinants of demand and supply. A theoretical model of aggregate demand and supply of higher education is derived, with the aim to facilitate the understanding of the challenges in today’s higher education systems, as well as the opportunities for development. The model is validated on some exemplary case studies describing the different relationship between the level of public investment and levels of graduate population and helps to derive general implications. In addition, using a two-stage least squares model, we build a macroeconomic model of supply and demand for European higher education. The model allows interpreting policies shifting either the supply or the demand for higher education, and allows taking into consideration contextual conditions with the aim of comparing divergent policies under a common framework. Results show that the same policy objective (i.e., increasing graduate population) can be obtained by shifting either the demand function (i.e., by strengthening student aid) or the supply function (i.e., by directly supporting higher education institutions). Under this theoretical perspective, the level of tuition fees is irrelevant, and empirically we can observe high levels of graduate population in both countries with high (i.e., the UK) or low (i.e., Germany) levels of tuition fees. In practice, this model provides a conceptual framework to help better understanding what are the external conditions that need to be considered, when planning a policy for increasing graduate population. Extrapolating a policy from results in different countries, under this perspective, is a poor solution when contingent factors are not addressed. The second implication of this conceptual framework is that policies addressing the supply or the demand function needs to address different contingencies. In other words, a government aiming at increasing graduate population needs to implement complementary policies, designing them according to the side of the market that is interested. For example, a ‘supply-driven’ intervention, through the direct financial support of higher education institutions, needs to address the issue of institutions’ moral hazard, by creating incentives to supply higher education services in efficient conditions. By contrast, a ‘demand-driven’ policy, providing student aids, need to tackle the students’ moral hazard, by creating an incentive to responsible behavior.

Keywords: graduates, higher education, higher education policies, tuition fees

Procedia PDF Downloads 153

Authors: Rashmi Malik, Videep Mishra

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The practice of generative design has become a transformative approach for an efficient way of generating multiple iterations for any design project. The conventional way of modeling the game elements is very time-consuming and requires skilled artists to design. A 3D modeling tool like 3D S Max, Blender, etc., is used traditionally to create the game library, which will take its stipulated time to model. The study is focused on using the generative design tool to increase the efficiency in game development at the stage of prop and environment generation. This will involve procedural level and customized regulated or randomized assets generation. The paper will present the system design approach using generative tools like Grasshopper (visual scripting) and other scripting tools to automate the process of game library modeling. The script will enable the generation of multiple products from the single script, thus creating a system that lets designers /artists customize props and environments. The main goal is to measure the efficacy of the automated system generated to create a wide variety of game elements, further reducing the need for manual content creation and integrating it into the workflow of AAA and Indie Games.

Keywords: iterative game design, generative design, gaming asset automation, generative game design

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Authors: Olufemi M. Alabi, Foluke A. Aderemi, Adebayo A. Adewumi, Banwo O. Alabi

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General well-being of animals is of paramount interest in some developed countries and of global importance hence the shift onto alternative housing systems for egg-type chickens as replacement for conventional battery cage system. However, there is paucity of information on the effect of this shift on physiological status of the hens to judge their health via the blood profile. Therefore, investigation was carried out on two strains of hen kept in three different housing systems in humid tropics to evaluate changes in their blood parameters. 108, 17-weeks old super black (SBL) hens and 108, 17-weeks old super brown (SBR) hens were randomly allotted to three different intensive systems Partitioned Conventional Cage (PCC), Extended Conventional Cage (ECC) and Deep Litter System (DLS) in a randomized complete block design with 36 hens per housing system, each with three replicates. The experiment lasted 37 weeks during which blood samples were collected at 18th week of age and bi-weekly thereafter for analyses. Parameters measured are packed cell volume (PCV), hemoglobin concentration (Hb), red blood counts (RBC), white blood counts (WBC) and serum metabolites such as total protein (TP), albumin (Alb), globulin (Glb), glucose, cholesterol, urea, bilirubin, serum cortisol while blood indices such as mean corpuscular hemoglobin (MCH), mean cell volume (MCV) and mean corpuscular hemoglobin concentration (MCHC) were calculated. The hematological values of the hens were not significantly (p>0.05) affected by the housing system and strain, so also the serum metabolites except for the serum cortisol which was significantly (p<0.05) affected by the housing system only. Hens housed on PCC had higher values (20.05 ng/ml for SBL and 20.55 ng/ml for SBR) followed by hens on ECC (18.15ng/ml for SBL and 18.38ng/ml for SBL) while hens on DLS had the lowest value (16.50ng/ml for SBL and 16.00ng/ml for SBR) thereby confirming indication of stress with conventionally caged birds. Alternative housing systems can also be adopted for egg-type chickens in the humid tropics from welfare point of view with the results of this work confirming stress among caged hens.

Keywords: blood, housing, humid-tropics, layers

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Authors: Maria Ahmadnezhad, Seyedgharani Ghoreishi ‎

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Electrohydraulic servo system have been used in industry in a wide ‎number of applications. Its ‎dynamics are highly nonlinear and also ‎have large extent of model uncertainties and external ‎disturbances. ‎In this thesis, a robust back-stepping control (RBSC) scheme is ‎proposed to overcome ‎the problem of disturbances and system ‎uncertainties effectively and to improve the set-point ‎performance ‎of EHS systems. In order to implement the proposed control ‎scheme, the system ‎uncertainties in EHS systems are considered as ‎total leakage coefficient and effective oil volume. In ‎addition, in ‎order to obtain the virtual controls for stabilizing system, the ‎update rule for the ‎system uncertainty term is induced by the ‎Lyapunov control function (LCF). To verify the ‎performance and ‎robustness of the proposed control system, computer simulation of ‎the ‎proposed control system using Matlab/Simulink Software is ‎executed. From the computer ‎simulation, it was found that the ‎RBSC system produces the desired set-point performance and ‎has ‎robustness to the disturbances and system uncertainties of ‎EHS systems.‎

Keywords: electro hydraulic servo system, back-stepping control, robust back-‎stepping control, Lyapunov redesign‎

Procedia PDF Downloads 988

Authors: Clare S. Sullivan

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The high desert of central Oregon, USA is a challenging growing environment: short growing season (70-100 days); average annual precipitation of 280 mm; drastic swings in diurnal temperatures; possibility of frost any time of year; and sandy soils low in organic matter. Despite strong demand, there is almost no fruit grown in central Oregon due to potential yield loss caused by early and late frosts. Elsewhere in the USA, protected culture (i.e., high tunnels) has been used to extend fruit production seasons and improve yields. In central Oregon, high tunnels are used to grow multiple high-value vegetable crops, and farmers are unlikely to plant a perennial crop in a high tunnel unless proven profitable. In May 2019, two berry trials were established on a farm in Alfalfa, OR, to evaluate raspberry and strawberry yield, season length, and fruit quality in protected (high tunnels) vs. unprotected culture (open field). The main objective was to determine whether high tunnel berry production is a viable enterprise for the region. Each trial was arranged using a split-plot design. The main factor was the production system (high tunnel vs. open field), and the replicated, subplot factor was berry variety. Four day-neutral strawberry varieties and four primocane-bearing raspberry varieties were planted for the study and were managed using organic practices. Berries were harvested once a week early in the season, and twice a week as production increased. Harvested berries were separated into ‘marketable’ and ‘unmarketable’ in order to calculate percent cull. First-year results revealed berry yield and quality differences between varieties and production systems. Strawberry marketable yield and berry fruit size increased significantly in the high tunnel compared to the field; percent yield increase ranged from 7-46% by variety. Evie 2 was the highest yielding strawberry, although berry quality was lower than other berries. Raspberry marketable yield and berry fruit size tended to increase in the high tunnel compared to the field, although variety had a more significant effect. Joan J was the highest yielding raspberry and out-yielded the other varieties by 250% outdoor and 350% indoor. Overall, strawberry and raspberry yields tended to improve in high tunnels as compared to the field, but data from a second year will help determine whether high tunnel investment is worthwhile. It is expected that the production system will have more of an effect on berry yield and season length for second-year plants in 2020.

Keywords: berries, high tunnel, local food, organic

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Authors: Andrey Kupriyanov

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In recent years, much attention has been paid to the problems of ionospheric disturbances and their influence on the signals of global navigation satellite systems (GNSS) around the world. This is due to the increase in solar activity, the expansion of the scope of GNSS, the emergence of new satellite systems, the introduction of new frequencies and many others. The influence of the Earth's ionosphere on the propagation of radio signals is an important factor in many applied fields of science and technology. The paper considers the application of the method of transionospheric sounding using measurements from signals from Global Navigation Satellite Systems to determine the TEC distribution and scintillations of the ionospheric layers. To calculate these parameters, the International Reference Ionosphere (IRI) model of the ionosphere, refined in the local area, is used. The organization of operational monitoring of ionospheric parameters is analyzed using several NovAtel GPStation6 base stations. It allows performing primary processing of GNSS measurement data, calculating TEC and fixing scintillation moments, modeling the ionosphere using the obtained data, storing data and performing ionospheric correction in measurements. As a result of the study, it was proved that the use of the transionospheric sounding method for reconstructing the altitude distribution of electron concentration in different altitude range and would provide operational information about the ionosphere, which is necessary for solving a number of practical problems in the field of many applications. Also, the use of multi-frequency multisystem GNSS equipment and special software will allow achieving the specified accuracy and volume of measurements.

Keywords: global navigation satellite systems (GNSS), GPstation6, international reference ionosphere (IRI), ionosphere, scintillations, total electron content (TEC)

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Authors: Kenny Onayemi

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In an era where academic institutions increasingly rely on information technology, the security of academic networks has emerged as a paramount concern. This comprehensive study delves into the effectiveness of security practices, including network mapping, vulnerability scanning, and penetration testing, within academic networks. Leveraging data from surveys administered to faculty, staff, IT professionals and IT students in the university, the study assesses their familiarity with these practices, perceived effectiveness, and frequency of implementation. The findings reveal that a significant portion of respondents exhibit a strong understanding of network mapping, vulnerability scanning, and penetration testing, highlighting the presence of knowledgeable professionals within academic institutions. Additionally, active scanning using network scanning tools and automated vulnerability scanning tools emerge as highly effective methods. However, concerns arise as the respondents show that the academic institutions conduct these practices rarely or never. Notably, many respondents have reported significant vulnerabilities or security incidents through these security measures within their institution. This study concludes with recommendations to enhance network security awareness and practices among faculty, staff, IT personnel, and students, ultimately fortifying the security posture of academic networks in the digital age.

Keywords: network security, academic networks, vulnerability scanning, penetration testing, information security

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Authors: Rong-Terng Juang

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Autonomous vehicles offer the possibility of significant benefits to social welfare. However, fully automated cars might not be going to happen in the near further. To speed the adoption of the self-driving technologies, many governments worldwide are passing laws requiring data recorders for the testing of autonomous vehicles. Currently, the self-driving vehicle, (e.g., shuttle bus) has to be monitored from a remote control center. When an autonomous vehicle encounters an unexpected driving environment, such as road construction or an obstruction, it should request assistance from a remote operator. Nevertheless, large amounts of data, including images, radar and lidar data, etc., have to be transmitted from the vehicle to the remote center. Therefore, this paper proposes a data compression method of in-vehicle networks for remote monitoring of autonomous vehicles. Firstly, the time-series data are rearranged into a multi-dimensional signal space. Upon the arrival, for controller area networks (CAN), the new data are mapped onto a time-data two-dimensional space associated with the specific CAN identity. Secondly, the data are sampled based on differential sampling. Finally, the whole set of data are encoded using existing algorithms such as Huffman, arithmetic and codebook encoding methods. To evaluate system performance, the proposed method was deployed on an in-house built autonomous vehicle. The testing results show that the amount of data can be reduced as much as 1/7 compared to the raw data.

Keywords: autonomous vehicle, data compression, remote monitoring, controller area networks (CAN), Lidar

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Authors: Bin Feng, Zhulin Zong

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Radar systems are critical in the modern military, aviation, and maritime operations, and their proper functioning is essential for the success of these operations. However, due to the complexity and sensitivity of radar systems, they are susceptible to various faults that can significantly affect their performance. Traditional radar fault diagnosis strategies rely on expert knowledge and rule-based approaches, which are often limited in effectiveness and require a lot of time and resources. Deep learning has recently emerged as a promising approach for fault diagnosis due to its ability to learn features and patterns from large amounts of data automatically. In this paper, we propose a radar fault diagnosis strategy based on deep learning that can accurately identify and classify faults in radar systems. Our approach uses convolutional neural networks (CNN) to extract features from radar signals and fault classify the features. The proposed strategy is trained and validated on a dataset of measured radar signals with various types of faults. The results show that it achieves high accuracy in fault diagnosis. To further evaluate the effectiveness of the proposed strategy, we compare it with traditional rule-based approaches and other machine learning-based methods, including decision trees, support vector machines (SVMs), and random forests. The results demonstrate that our deep learning-based approach outperforms the traditional approaches in terms of accuracy and efficiency. Finally, we discuss the potential applications and limitations of the proposed strategy, as well as future research directions. Our study highlights the importance and potential of deep learning for radar fault diagnosis. It suggests that it can be a valuable tool for improving the performance and reliability of radar systems. In summary, this paper presents a radar fault diagnosis strategy based on deep learning that achieves high accuracy and efficiency in identifying and classifying faults in radar systems. The proposed strategy has significant potential for practical applications and can pave the way for further research.

Keywords: radar system, fault diagnosis, deep learning, radar fault

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Authors: Shohreh Moshiri, Hossein Alimohammadi

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Building construction has a great impact on climate change. Adaptive design strategies were developed to provide new life and purpose to old buildings and create new environments with economic benefits to meet resident needs. The role of smart material systems is undeniable in providing adaptivity of the architectural environments and their effects on creating better adaptive building environments. In this research, a case study named Neuhoff site located near Cumberland River in the Germantown neighborhood in the city of Nashville, Tennessee, was considered. This building in the early 1920s was constructed as a meat-packing facility and then served as a mixed-use space; however, New City has partnered with world-class architects to reinvent this site to be changed to mixed-use waterfront development. The future office space will be designed with LEED certification as a goal. Environmentally friendly sensitive materials and designs will offer for all adaptive reuse of the building. The smart materials and their applications, especially in the field of building technology and architecture, were emphasized in providing a renovation plan for the site. The advantages and qualities of smart material systems were targeted to explore in this research on the field of architecture. Also, this research helps to understand better the effects of smart material systems on the construction and design processes, exploration of the way to make architecture with better adaptive characteristics, plus provide optimal environmental situations for the users, which reflect on the climatic, structural, and architectural performances.

Keywords: adaptive architecture, building technology, case study, smart material systems

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Authors: Abdul Musaweer Habib, Habibul Hasan Mazumder, Saiful Islam, Sohel Sikder, Omar Faruk Sikder

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The plethora of genome sequence information of bacteria in recent times has ushered in many novel strategies for antibacterial drug discovery and facilitated medical science to take up the challenge of the increasing resistance of pathogenic bacteria to current antibiotics. In this study, we adopted subtractive genomics approach to analyze the whole genome sequence of the Fusobacterium nucleatum, a human oral pathogen having association with colorectal cancer. Our study divulged 1499 proteins of Fusobacterium nucleatum, which has no homolog in human genome. These proteins were subjected to screening further by using the Database of Essential Genes (DEG) that resulted in the identification of 32 vitally important proteins for the bacterium. Subsequent analysis of the identified pivotal proteins, using the KEGG Automated Annotation Server (KAAS) resulted in sorting 3 key enzymes of F. nucleatum that may be good candidates as potential drug targets, since they are unique for the bacterium and absent in humans. In addition, we have demonstrated the 3-D structure of these three proteins. Finally, determination of ligand binding sites of the key proteins as well as screening for functional inhibitors that best fitted with the ligands sites were conducted to discover effective novel therapeutic compounds against Fusobacterium nucleatum.

Keywords: colorectal cancer, drug target, Fusobacterium nucleatum, homology modeling, ligands

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Authors: Nikita Koradia

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Hyundai Motor Company, which started off as a small fish in a big sea, paved its way out successfully and established itself as an independent group from the conglomerate. Hyundai, with its officious power across the globe and particularly in South Korea in the automobile industry, has one the most complex yet fascinating governance structure. Being the second largest contributor to the Gross Domestic Product of South Korea after Samsung and having a market share of 51.3% domestically in automobile industry, Hyundai has faced its part of criticism owing to its anti-labor union approach and owing to its internalization of supply chain management. The censure has been coming from across jurisdictions like China, India, Canada, the EU, etc. The paper focuses on the growth of Hyundai and its inward and outward investment structure. The paper questions the ability of Hyundai to become a mini-state in itself by focusing on its governance structure. The paper further elaborates on its compliance and disclosure regime in the field of Corporate social responsibility and explores how far the business structure adopted by Hyundai works in its favor to become one of the leading automobile contenders in the market.

Keywords: compliance regime, disclosure regime, Hyundai motor company, supply-chain management

Procedia PDF Downloads 114

Authors: Der Chyan Lin

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Since the early introduction by Ormondroyd and Den Hartog, vibration absorber (VA) has become one of the most commonly used vibration mitigation strategies. The strategy is most effective for a primary plant subjected to a single frequency excitation. For continuous systems, notable advances in vibration absorption in the multi-frequency system were made. However, the efficacy of the VA strategy for systems under multi-frequency excitation is not well understood. For example, for an N degrees-of-freedom (DOF) primary-absorber system, there are N 'peak' frequencies of large amplitude vibration per every new excitation frequency. In general, the usable range for vibration absorption can be greatly reduced as a result. Frequency modulated harmonic excitation is a commonly seen multi-frequency excitation example: f(t) = cos(ϖ(t)t) where ϖ(t)=ω(1+α sin⁡(δt)). It is known that f(t) has a series expansion given by the Bessel function of the first kind, which implies an infinity of forcing frequencies in the frequency modulated harmonic excitation. For an SDOF system of natural frequency ωₙ subjected to f(t), it can be shown that amplitude peaks emerge at ω₍ₚ,ₖ₎=(ωₙ ± 2kδ)/(α ∓ 1),k∈Z; i.e., there is an infinity of resonant frequencies ω₍ₚ,ₖ₎, k∈Z, making the use of VA strategy ineffective. In this work, we propose an absorber frequency placement strategy for SDOF vibration systems subjected to frequency-modulated excitation. An SDOF linear mass-spring system coupled to lateral absorber systems is used to demonstrate the ideas. Although the mechanical components are linear, the governing equations for the coupled system are nonlinear. We show using N identical absorbers, for N ≫ 1, that (a) there is a cluster of N+1 natural frequencies around every natural absorber frequency, and (b) the absorber frequencies can be moved away from the plant's resonance frequency (ω₀) as N increases. Moreover, we also show the bandwidth of the VA performance increases with N. The derivations of the clustering and bandwidth widening effect will be given, and the superiority of the proposed strategy will be demonstrated via numerical experiments.

Keywords: Bessel function, bandwidth, frequency modulated excitation, vibration absorber

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Authors: Kedar J. Mahadeshwar

Abstract:

Concept introduction: This paper talks about how an innovative cloud based analytics enabled solution that could address a major industry challenge that is approaching all of us globally faster than what one would think. The world of supply chain for drugs and devices is changing today at a rapid speed. In the US, the Drug Supply Chain Security Act (DSCSA) is a new law for Tracing, Verification and Serialization phasing in starting Jan 1, 2015 for manufacturers, repackagers, wholesalers and pharmacies / clinics. Similarly we are seeing pressures building up in Europe, China and many countries that would require an absolute traceability of every drug and device end to end. Companies (both manufacturers and distributors) can use this opportunity not only to be compliant but to differentiate themselves over competition. And moreover a country such as UAE can be the leader in coming up with a global solution that brings innovation in this industry. Problem definition and timing: The problem of counterfeit drug market, recognized by FDA, causes billions of dollars loss every year. Even in UAE, the concerns over prevalence of counterfeit drugs, which enter through ports such as Dubai remains a big concern, as per UAE pharma and healthcare report, Q1 2015. Distribution of drugs and devices involves multiple processes and systems that do not talk to each other. Consumer confidence is at risk due to this lack of traceability and any leading provider is at risk of losing its reputation. Globally there is an increasing pressure by government and regulatory bodies to trace serial numbers and lot numbers of every drug and medical devices throughout a supply chain. Though many of large corporations use some form of ERP (enterprise resource planning) software, it is far from having a capability to trace a lot and serial number beyond the enterprise and making this information easily available real time. Solution: The solution here talks about a service provider that allows all subscribers to take advantage of this service. The solution allows a service provider regardless of its physical location, to host this cloud based traceability and analytics solution of millions of distribution transactions that capture lots of each drug and device. The solution platform will capture a movement of every medical device and drug end to end from its manufacturer to a hospital or a doctor through a series of distributor or retail network. The platform also provides advanced analytics solution to do some intelligent reporting online. Why Dubai? Opportunity exists with huge investment done in Dubai healthcare city also with using technology and infrastructure to attract more FDI to provide such a service. UAE and countries similar will be facing this pressure from regulators globally in near future. But more interestingly, Dubai can attract such innovators/companies to run and host such a cloud based solution and become a hub of such traceability globally.

Keywords: cloud, pharmaceutical, supply chain, tracking

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Authors: Anna Carolina De Paula Sermarini, Rodrigo Flora Calili

Abstract:

Energy Efficiency (EE) needs investments, new technologies, greater awareness and management on the side of citizens and organizations, and more planning. However, this issue is usually remembered and discussed only in moments of energy crises, and opportunities are missed to take better advantage of the potential of EE in the various sectors of the economy. In addition, there is little concern about the subject among the less favored classes, especially in low-income communities. Accordingly, this article presents suggestions for public policies that aim to increase EE for low-income housing and communities based on international and national experiences. After reviewing the literature, eight policies were listed, and to evaluate them; a multicriteria decision model was developed using the AHP (Analytical Hierarchy Process) and TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution) methods, combined with fuzzy logic. Nine experts analyzed the policies according to 9 criteria: economic impact, social impact, environmental impact, previous experience, the difficulty of implementation, possibility/ease of monitoring and evaluating the policies, expected impact, political risks, and public governance and sustainability of the sector. The results found in order of preference are (i) Incentive program for equipment replacement; (ii) Community awareness program; (iii) EE Program with a greater focus on low income; (iv) Staggered and compulsory certification of social interest buildings; (v) Programs for the expansion of smart metering, energy monitoring and digitalization; (vi) Financing program for construction and retrofitting of houses with the emphasis on EE; (vii) Income tax deduction for investment in EE projects in low-income households made by companies; (viii) White certificates of energy for low-income. First, the policy of equipment substitution has been employed in Brazil and the world and has proven effective in promoting EE. For implementation, efforts are needed from the federal and state governments, which can encourage companies to reduce prices, and provide some type of aid for the purchase of such equipment. In second place is the community awareness program, promoting socio-educational actions on EE concepts and with energy conservation tips. This policy is simple to implement and has already been used by many distribution utilities in Brazil. It can be carried out through bids defined by the government in specific areas, being executed by third sector companies with public and private resources. Third on the list is the proposal to continue the Energy Efficiency Program (which obliges electric energy companies to allocate resources for research in the area) by suggesting the return of the mandatory investment of 60% of the resources in projects for low income. It is also relatively simple to implement, requiring efforts by the federal government to make it mandatory, and on the part of the distributors, compliance is needed. The success of the suggestions depends on changes in the established rules and efforts from the interested parties. For future work, we suggest the development of pilot projects in low-income communities in Brazil and the application of other multicriteria decision support methods to compare the results obtained in this study.

Keywords: energy efficiency, low-income community, public policy, multicriteria decision making

Procedia PDF Downloads 111

Authors: Wafa' Slaibi Alsharafat

Abstract:

Cloud computing is a modern approach in network environment. According to increased number of network users and online systems, there is a need to help these systems to be away from unauthorized resource access and detect any attempts for privacy contravention. For that purpose, Intrusion Detection System is an effective security mechanism to detect any attempts of attacks for cloud resources and their information. In this paper, Cloud Intrusion Detection System has been proposed in term of reducing or eliminating any attacks. This model concerns about achieving high detection rate after conducting a set of experiments using benchmarks dataset called KDD'99.

Keywords: IDS, cloud computing, anticipating classifier system, intrusion detection

Procedia PDF Downloads 463

Authors: M. Cortés, E. Vera, M. Avella

Abstract:

Corrosion is an imminent process in nature, which affects all types of materials. In sewerage systems, the corrosion process caused by microorganisms, also known as biogenic sulfuric acid attack, has been studied. This affects the structural integrity of the concrete drainage pipes and the sewage treatment plants. This article is a review of research which focuses on the study of how to reduce the production of hydrogen sulfide, how to improve the resistance of concrete through the use of additives and the implementation of antimicrobial techniques to reduce bacterial growth.

Keywords: bactericides, biogenic sulfuric acid, corrosion, concrete, hydrogen sulphide, nano materials, zeolites

Procedia PDF Downloads 432

Authors: Andreas Livera, Spyros Theocharides, Michalis Florides, Charalambos Anastassiou

Abstract:

A main challenge in the quest for ensuring quality of operation, especially for photovoltaic (PV) systems, is to safeguard the reliability and optimal performance by detecting and diagnosing potential failures and performance losses at early stages or before the occurrence through real-time monitoring, supervision, fault detection, and predictive maintenance. The purpose of this work is to present the functionalities and results related to the development and validation of a software platform for PV assets diagnosis and maintenance. The platform brings together proprietary hardware sensors and software algorithms to enable the early detection and prediction of the most common and critical faults in PV systems. It was validated using field measurements from operating PV systems. The results showed the effectiveness of the platform for detecting faults and losses (e.g., inverter failures, string disconnections, and potential induced degradation) at early stages, forecasting PV power production while also providing recommendations for maintenance actions. Increased PV energy yield production and revenue can be thus achieved while also minimizing operation and maintenance (O&M) costs.

Keywords: failure detection and prediction, operation and maintenance, performance monitoring, photovoltaic, platform, recommendations, predictive maintenance

Procedia PDF Downloads 38

Authors: M. Kastek, M. Kowalski, M. Szustakowski, H. Polakowski, T. Sosnowski

Abstract:

Development of highly efficient security systems is one of the most urgent topics for science and engineering. There are many kinds of threats and many methods of prevention. It is very important to detect a threat as early as possible in order to neutralize it. One of the very challenging problems is detection of dangerous objects hidden under human’s clothing. This problem is particularly important for safety of airport passengers. In order to develop methods and algorithms to detect hidden objects it is necessary to determine the thermal signatures of such objects of interest. The laboratory measurements were conducted to determine the thermal signatures of dangerous tools hidden under various clothes in different ambient conditions. Cameras used for measurements were working in spectral range 0.6-12.5 μm An infrared imaging Fourier transform spectroradiometer was also used, working in spectral range 7.7-11.7 μm. Analysis of registered thermograms and hyperspectral datacubes has yielded the thermal signatures for two types of guns, two types of knives and home-made explosive bombs. The determined thermal signatures will be used in the development of method and algorithms of image analysis implemented in proposed monitoring systems.

Keywords: hyperspectral detection, nultispectral detection, image processing, monitoring systems

Procedia PDF Downloads 339

Authors: Mohamed Ghorab

Abstract:

Local generated and distributed system for thermal and electrical energy is sighted in the near future to reduce transmission losses instead of the centralized system. Distributed Energy Resources (DER) is designed at different sizes (small and medium) and it is incorporated in energy distribution between the hubs. The energy generated from each technology at each hub should meet the local energy demands. Economic and environmental enhancement can be achieved when there are interaction and energy exchange between the hubs. Network energy system and CO₂ optimization between different six hubs presented Canadian community level are investigated in this study. Three different scenarios of technology systems are studied to meet both thermal and electrical demand loads for the six hubs. The conventional system is used as the first technology system and a reference case study. The conventional system includes boiler to provide the thermal energy, but the electrical energy is imported from the utility grid. The second technology system includes combined heat and power (CHP) system to meet the thermal demand loads and part of the electrical demand load. The third scenario has integration systems of CHP and Organic Rankine Cycle (ORC) where the thermal waste energy from the CHP system is used by ORC to generate electricity. General Algebraic Modeling System (GAMS) is used to model DER system optimization based on energy economics and CO₂ emission analyses. The results are compared with the conventional energy system. The results show that scenarios 2 and 3 provide an annual total cost saving of 21.3% and 32.3 %, respectively compared to the conventional system (scenario 1). Additionally, Scenario 3 (CHP & ORC systems) provides 32.5% saving in CO₂ emission compared to conventional system subsequent case 2 (CHP system) with a value of 9.3%.  

Keywords: distributed energy resources, network energy system, optimization, microgeneration system

Procedia PDF Downloads 186