Search results for: water quality model.

Authors: Dinesh Acharya U., N. V. Subba Reddy, Krishnamoorthi Makkithaya

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The recognition of handwritten numeral is an important area of research for its applications in post office, banks and other organizations. This paper presents automatic recognition of handwritten Kannada numerals based on structural features. Five different types of features, namely, profile based 10-segment string, water reservoir; vertical and horizontal strokes, end points and average boundary length from the minimal bounding box are used in the recognition of numeral. The effect of each feature and their combination in the numeral classification is analyzed using nearest neighbor classifiers. It is common to combine multiple categories of features into a single feature vector for the classification. Instead, separate classifiers can be used to classify based on each visual feature individually and the final classification can be obtained based on the combination of separate base classification results. One popular approach is to combine the classifier results into a feature vector and leaving the decision to next level classifier. This method is extended to extract a better information, possibility distribution, from the base classifiers in resolving the conflicts among the classification results. Here, we use fuzzy k Nearest Neighbor (fuzzy k-NN) as base classifier for individual feature sets, the results of which together forms the feature vector for the final k Nearest Neighbor (k-NN) classifier. Testing is done, using different features, individually and in combination, on a database containing 1600 samples of different numerals and the results are compared with the results of different existing methods.

Keywords: Fuzzy k Nearest Neighbor, Multiple Classifiers, Numeral Recognition, Structural features.

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Authors: Kee-Young Kwahk

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Cognizant of the fact that enterprise systems involve organizational change and their implementation is over shadowed by a high failure rate, it is argued that there is the need to focus attention on employees- perceptions of such organizational change when explaining adoption behavior of enterprise systems. For this purpose, the research incorporates a conceptual constructo fattitude toward change that captures views about the need for organizational change. Centered on this conceptual construct, the research model includes beliefs regarding the system and behavioral intention as its consequences, and the personal characteristics of organizational commitment and perceived personal competence as its antecedents. Structural equation analysis using LISREL provides significant support for the proposed relationships. Theoretical and practical implications are discussed along with limitations.

Keywords: Sociotechnical changes, organizational change, attitude toward change, enterprise information systems.

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Authors: Amit Kumar Gautam, Sudipta Majumdar

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This paper presents parameter estimation of a single-phase rectifier using extended Kalman filter (EKF). The state space model has been obtained using Kirchhoff’s current law (KCL) and Kirchhoff’s voltage law (KVL). The capacitor voltage and diode current of the circuit have been estimated using EKF. Simulation results validate the better accuracy of the proposed method as compared to the least mean square method (LMS). Further, EKF has the advantage that it can be used for nonlinear systems.

Keywords: Extended Kalman filter, parameter estimation, single phase rectifier, state space modelling.

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Authors: Max Ti-Kuang Hou, Hui-Mei Shen, Chiang-Ni Lu, I-Jen Hsu

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We present design, fabrication, and characterization of a small (12 mm × 12 mm × 8 mm) movable railway vehicle for sensor carrying. The miniature railway vehicle (MRV) was mainly composed of a vibrational structure and three legs. A railway was designed and fabricated to power and guide the MRV. It also transmits the sensed data from the MRV to the signal processing unit. The MRV with legs on the railway was moving due to its high-frequency vibration. A model was derived to describe the motion. Besides, FEM simulations were performed to design the legs. Then, the MRV and the railway were fabricated by precision machining. Finally, an infrared sensor was carried and tested. The result shows that the MRV without loading was moving along the railway and its maximum speed was 12.2 mm/s. Moreover, the testing signal was sensed by the MRV.

Keywords: Locomotion, Micro-Robot, Miniature Railway Vehicle, Stick-Slip.

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Authors: Nagalingam Arun Prasanth, Ahmed Syed Adnan, S. H. Yeo

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Surface topography plays a significant role in the functional performance of engineered parts. It is important to have a control on the surface geometry and understanding on the surface details to get the desired performance. Hence, in the current research contribution, a non-contact micro-texturing technique has been explored and developed. The technique involves ultrasonic excitation of a tool as a prime source of surface texturing for aluminum alloy workpieces. The specimen surface is polished first and is then immersed in a liquid bath containing 10% weight concentration of Ti6Al4V grade 5 spherical powders. A submerged slurry jet is used to recirculate the spherical powders under the ultrasonic horn which is excited at an ultrasonic frequency and amplitude of 40 kHz and 70 µm respectively. The distance between the horn and workpiece surface was remained fixed at 200 µm using a precision control stage. Texturing effects were investigated for different process timings of 1, 3 and 5 s. Thereafter, the specimens were cleaned in an ultrasonic bath for 5 mins to remove loose debris on the surface. The developed surfaces are characterized by optical and contact surface profiler. The optical microscopic images show a texture of circular spots on the workpiece surface indented by titanium spherical balls. Waviness patterns obtained from contact surface profiler supports the texturing effect produced from the proposed technique. Furthermore, water droplet tests were performed to show the efficacy of the proposed technique to develop hydrophilic surfaces and to quantify the texturing effect produced.

Keywords: Surface texturing, surface modification, topography, ultrasonic.

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Authors: Nabil Sultan

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A great deal has been written on Massive Open Online Courses (MOOCs) since 2012 (considered by some as the year of the MOOCs). The emergence of MOOCs caused a great deal of interest amongst academics and technology experts as well as ordinary people. Some of the authors who wrote on MOOCs perceived it as the next big thing that will disrupt education. Other authors saw it as another fad that will go away once it ran its course (as most fads often do). But MOOCs did not turn out to be a fad and it is still around. Most importantly, they evolved into something that is beginning to look like a viable business model. This paper explores this phenomenon within the theoretical frameworks of disruptive innovations and jobs to be done as developed by Clayton Christensen and his colleagues and its implications for the future of higher education (HE).

Keywords: MOOCs, disruptive innovations, higher education, jobs theory.

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Authors: Hui-Ling Huang, Yue-Yang Chen, Ming-Chi Tsai, Cheng-Jiun Lee

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Recently, a great number of theoretical frameworks have been proposed to develop the linkages between knowledge management (KM) and organizational strategies. However, while there has been much theorizing and case study in the area, validated research models integrating KM and information technology strategies for empirical testing of these theories have been scarce. In this research, we try to develop a research model for explaining the relationship between KM strategy and IT strategy and their effects on performance. Finally, meaningful propositions and conclusions are derived, and suggestions for future research are proposed and discussed.

Keywords: Knowledge management strategy, information technology strategy, knowledge management performance, information technology performance

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Authors: A. Schuchter, M. Promegger

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The outbreak of the COVID-19 pandemic has shown us that online education is so much more than just a cool feature for teachers – it is an essential part of modern teaching. In online math teaching, it is common to use tools to share screens, compute and calculate mathematical examples, while the students can watch the process. On the other hand, flipped classroom models are on the rise, with their focus on how students can gather knowledge by watching videos and on the teacher’s use of technological tools for information transfer. This paper proposes a co-educational teaching approach for coding and engineering subjects with the help of drone-building to spark interest in technology and create a platform for knowledge transfer. The project combines aspects from mathematics (matrices, vectors, shaders, trigonometry), physics (force, pressure and rotation) and coding (computational thinking, block-based programming, JavaScript and Python) and makes use of collaborative-shared 3D Modeling with clara.io, where students create mathematics knowhow. The instructor follows a problem-based learning approach and encourages their students to find solutions in their own time and in their own way, which will help them develop new skills intuitively and boost logically structured thinking. The collaborative aspect of working in groups will help the students develop communication skills as well as structural and computational thinking. Students are not just listeners as in traditional classroom settings, but play an active part in creating content together by compiling a Handbook of Knowledge (called “open book”) with examples and solutions. Before students start calculating, they have to write down all their ideas and working steps in full sentences so other students can easily follow their train of thought. Therefore, students will learn to formulate goals, solve problems, and create a ready-to use product with the help of “reverse engineering”, cross-referencing and creative thinking. The work on drones gives the students the opportunity to create a real-life application with a practical purpose, while going through all stages of product development.

Keywords: Flipped classroom, co-creational education, coding, making, drones, co-education, ARCS-model, problem-based learning.

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Authors: Jae Young Park, Seung Wook Lee, Jong Tae Kim

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OpenMP is an API for parallel programming model of shared memory multiprocessors. Novice OpenMP programmers often produce the code that compiler cannot find human errors. It was investigated how compiler coped with the common mistakes that can occur in OpenMP code. The latest version(4.4.3) of GCC is used for this research. It was found that GCC compiled the codes without any errors or warnings. In this paper the programming aid tool is presented for OpenMP programs. It can check 12 common mistakes that novice programmer can commit during the programming of OpenMP. It was demonstrated that the programming aid tool can detect the various common mistakes that GCC failed to detect.

Keywords: Parallel programming, OpenMP, programming aid.

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Authors: Violina R. Angelova, Vanja I. Akova, Stefan V. Krustev, Krasimir I. Ivanov

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A field study was conducted to evaluate the efficacy of safflower plant for phytoremediation of contaminated soils. The experiment was performed on an agricultural fields contaminated by the Non-Ferrous-Metal Works near Plovdiv, Bulgaria. Field experiments with randomized complete block design with five treatments (control, compost amendments added at 20 and 40 t/daa, and vermicompost amendments added at 20 and 40 t/daa) were carried out. The quality of safflower seeds and oil (heavy metals and fatty acid composition) were determined. Tested organic amendments significantly influenced the chemical composition of safflower seeds and oil. The compost and vermicompost treatments significantly reduced heavy metals concentration in safflower seeds and oils, but the effect differed among them. Addition of vermicompost and compost leads to an increase in the content of palmitic acid and linoleic acid, and a decrease in the stearic and oleic acids compared with the control. A significant increase in the quantity of saturated acids was observed in the variants with 20 t/daa of compost and 20 t/daa of vermicompost (9.1 and 8.9% relative to the control). Safflower is a plant which is tolerant to heavy metals and can be successfully used in the phytoremediation of heavy metal contaminated soils. The processing of seeds to oil and using the obtained oil for nutritional purposes will greatly reduce the cost of phytoremediation.

Keywords: Heavy metals, organic amendments, phytoremediation, safflower.

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Authors: Adel Bettayeb, Robert Kaczmarek, Jean-Claude Vannier

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In this paper, we analyze the rotor eddy currents losses provoqued by the stator slot harmonics developed in the permanent magnets or pole pieces of synchronous machines. An analytical approach is presented to evaluate the effect of slot ripples on rotor field and losses calculation. This analysis is then tested on a model by 2D/3D finite element (FE) calculation. The results show a good agreement on loss calculations when skin effect is negligible and the magnet is considered.

Keywords: Analytical modeling, Eddy-currents, Finite-elementmethods, Power losses, Slot harmonics effect.

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Authors: Ibrahim M. Buamod, Muattaz Elaneizi

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Mobile Ad hoc Network (MANET) is a wireless ad hoc self-configuring network of mobile routers (and associated hosts) connected by wireless links, the union of which forms an arbitrary topology, cause of the random mobility of the nodes. In this paper, an attempt has been made to compare these three protocols DSDV, AODV and DSR on the performance basis under different traffic protocols namely CBR and TCP in a large network. The simulation tool is NS2, the scenarios are made to see the effect of pause times. The results presented in this paper clearly indicate that the different protocols behave differently under different pause times. Also, the results show the main characteristics of different traffic protocols operating on MANETs and thus select the best protocol on each scenario.

Keywords: Awk, CBR, Random waypoint model, TCP.

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Authors: Wen-Hsiang Lai

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Except for the internal aspects of entrepreneurship (i.e.motivation, opportunity perspective and alertness), there are external aspects that affecting entrepreneurship (i.e. the industrial cluster). By comparing the machinery companies located inside and outside the industrial district, this study aims to explore the cluster effects on the entrepreneurship of companies in Taiwan machinery clusters (TMC). In this study, three factors affecting the entrepreneurship in TMC are conducted as “competition”, “embedded-ness” and “specialized knowledge”. The “competition” in the industrial cluster is defined as the competitive advantages that companies gain in form of demand effects and diversified strategies; the “embedded-ness” refers to the quality of company relations (relational embedded-ness) and ranges (structural embedded-ness) with the industry components (universities, customers and complementary) that affecting knowledge transfer and knowledge generations; the “specialized knowledge” shares theinternal knowledge within industrial clusters. This study finds that when comparing to the companieswhich are outside the cluster, the industrial cluster has positive influence on the entrepreneurship. Additionally, the factor of “relational embedded-ness” has significant impact on the entrepreneurship and affects the adaptation ability of companies in TMC. Finally, the factor of “competition” reveals partial influence on the entrepreneurship.

Keywords: Entrepreneurship, Industrial Cluster, Industrial District, Economies of Agglomerations, Taiwan Machinery Cluster (TMC).

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Authors: Irena Markovska, Dimitar Rusev, Nikolai Zaicev, Bogdan Bogdanov, Dimitar Georgiev, Yancho Hristov

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A prototype model of an emulsion separator was designed and manufactured. Generally, it is a cylinder filled with different fractal modules. The emulsion was fed into the reactor by a peristaltic pump through an inlet placed at the boundary between the two phases. For hydrodynamic design and sizing of the reactor the assumptions of the theory of filtration were used and methods to describe the separation process were developed. Based on this methodology and using numerical methods and software of Autodesk the process is simulated in different operating modes. The basic hydrodynamic characteristics - speed and performance for different types of fractal systems and decisions to optimize the design of the reactor were also defined.

Keywords: fractal systems, reactor, separation, emulsions

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Authors: Khalid Ali, Manar Jammal

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In order to meet the stringent latency and reliability requirements of the upcoming 5G networks, Open Radio Access Networks (O-RAN) have been proposed. The virtualization of O-RAN has allowed it to be treated as a Network Function Virtualization (NFV) architecture, while its components are considered Virtualized Network Functions (VNFs). Hence, intelligent Machine Learning (ML) based solutions can be utilized to apply different resource management and allocation techniques on O-RAN. However, intelligently allocating resources for O-RAN VNFs can prove challenging due to the dynamicity of traffic in mobile networks. Network providers need to dynamically scale the allocated resources in response to the incoming traffic. Elastically allocating resources can provide a higher level of flexibility in the network in addition to reducing the OPerational EXpenditure (OPEX) and increasing the resources utilization. Most of the existing elastic solutions are reactive in nature, despite the fact that proactive approaches are more agile since they scale instances ahead of time by predicting the incoming traffic. In this work, we propose and evaluate traffic forecasting models based on the ML algorithm. The algorithms aim at predicting future O-RAN traffic by using previous traffic data. Detailed analysis of the traffic data was carried out to validate the quality and applicability of the traffic dataset. Hence, two ML models were proposed and evaluated based on their prediction capabilities.

Keywords: O-RAN, traffic forecasting, NFV, ARIMA, LSTM, elasticity.

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Authors: Ujjwala Bhand, Mridula Goel

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Global Competitiveness Index (GCI) prepared by World Economic Forum has become a benchmark in studying the competitiveness of countries and for understanding the factors that enable competitiveness. Innovation is a key pillar in competitiveness and has the unique property of enabling exponential economic growth. This paper attempts to analyze how the pillars comprising the Global Competitiveness Index affect innovation and whether GDP growth can directly affect innovation outcomes for a country. The key objective of the study is to identify areas on which governments of developing countries can focus policies and programs to improve their country’s innovativeness. We have compiled a panel data set for top innovating countries and large emerging economies called BRICS from 2007-08 to 2014-15 in order to find the significant factors that affect innovation. The results of the regression analysis suggest that government should make policies to improve labor market efficiency, establish sophisticated business networks, provide basic health and primary education to its people and strengthen the quality of higher education and training services in the economy. The achievements of smaller economies on innovation suggest that concerted efforts by governments can counter any size related disadvantage, and in fact can provide greater flexibility and speed in encouraging innovation.

Keywords: Innovation, Global Competitiveness Index, BRICS, economic growth.

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Authors: Zixian Zhang, Shanliang Yao, Zile Huang, Zhaodong Wu, Xiaohui Zhu, Yong Yue, Jieming Ma

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Unmanned Surface Vehicles (USVs) hold significant value for their capacity to undertake hazardous and labor-intensive operations over aquatic environments. Object detection tasks are significant in these applications. Nonetheless, the efficacy of USVs in object detection is impeded by several intrinsic challenges, including the intricate dispersal of obstacles, reflections emanating from coastal structures, and the presence of fog over water surfaces, among others. To address these problems, this paper provides a fusion method for USVs to effectively detect objects in the inland surface environment, utilizing vision sensors and 3+1D Millimeter-wave radar. The MMW radar is a complementary tool to vision sensors, offering reliable environmental data. This approach involves the conversion of the radar’s 3D point cloud into a 2D radar pseudo-image, thereby standardizing the format for radar and vision data by leveraging a point transformer. Furthermore, this paper proposes the development of a multi-source object detection network, named RV-YOLOX, which leverages radar-vision integration specifically tailored for inland waterway environments. The performance is evaluated on our self-recording waterways dataset. Compared with the YOLOX network, our fusion network significantly improves detection accuracy, especially for objects with bad light conditions.

Keywords: Inland waterways, object detection, YOLO, sensor fusion, self-attention, deep learning.

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Authors: Ilya Popov, Steven Hulshoff

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A numerical investigation of the effects of nanosecond barrier discharge on the stability of a two-dimensional free shear layer is performed. The computations are carried out using a compressible Navier-Stokes algorithm coupled with a thermodynamic model of the discharge. The results show that significant increases in the shear layer-s momentum thickness and Reynolds stresses occur due to actuation. Dependence on both frequency and amplitude of actuation are considered, and a comparison is made of the computed growth rates with those predicted by linear stability theory. Amplitude and frequency ranges for the efficient promotion of shear-layer instabilities are identified.

Keywords: NS-DBD, plasma, actuator, flow control, instability, shear layer

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Authors: W. Fethallah, L. Chraibi, N. Sefiani

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The present paper is concerned with a statistical approach involving latent and manifest variables applied in order to assess the organization's social responsibility performance. The main idea is to develop an assessment tool and a measurement of the Social Responsibility Performance, enabling the company to characterize her performance regarding to the ISO 26000 standard's seven core subjects. For this, we conceptualize a structural equation modeling (SEM) which describes various causal connections between the Social Responsibility’s components. The SEM’s resolution is based on the Partial Least squares (PLS) method and the implementation is running in the XLSTAT software.

Keywords: Corporate social responsibility, latent and manifest variable, partial least squares, structural equation model.

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Authors: F. D. Konstandakopoulou, G. A. Papagiannopoulos, N. G. Pnevmatikos, G. D. Hatzigeorgiou

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This paper examines the effects of pile-soil-structure interaction on the dynamic response of offshore platforms under the action of near-fault earthquakes. Two offshore platforms models are investigated, one with completely fixed supports and one with piles which are clamped into deformable layered soil. The soil deformability for the second model is simulated using non-linear springs. These platform models are subjected to near-fault seismic ground motions. The role of fault mechanism on platforms’ response is additionally investigated, while the study also examines the effects of different angles of incidence of seismic records on the maximum response of each platform.

Keywords: Hazard analysis, offshore platforms, earthquakes, safety.

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Authors: Jieun Kim, Haejin Cho, Yongtae Park, Yoonjo Kim, Jeonghwan Jeon

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As creative economy is important theme for national policy, many countries have been raising investments through national R&D programs. Since not all of programs are aligned with the ultimate vision and R&D investment is one of the most decisive elements, the strategic fit of national R&D programs should be evaluated for effective resource allocation. This study aims at identifying the factors of strategic fit of national R&D program on the creative economy policy. For this purpose, the balanced scorecard (BSC) model for R&D is utilized to translate national strategic objectives into a set of coherent performance factors.

Keywords: Balanced scorecard, Creative economy, National R&D program, Strategic fit.

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Authors: Lida Haghnegahdar, Ezzatollah Asgharizadeh

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Value engineering is an efficacious contraption for administrators to make up their minds. Value perusals proffer the gaffers a suitable instrument to decrease the expenditures of the life span, quality amelioration, structural improvement, curtailment of the construction schedule, longevity prolongation or a merging of the aforementioned cases. Subjecting organizers to pressures on one hand and their accountability towards their pertinent fields together with inherent risks and ambiguities of other options on the other hand set some comptrollers in a dilemma utilization of risk management and the value engineering in projects manipulation with regard to complexities of implementing projects can be wielded as a contraption to identify and efface each item which wreaks unnecessary expenses and time squandering sans inflicting any damages upon the essential project applications. Of course It should be noted that implementation of risk management and value engineering with regard to the betterment of efficiency and functions may lead to the project implementation timing elongation. Here time revamping does not refer to time diminishing in the whole cases. his article deals with risk and value engineering conceptualizations at first. The germane reverberations effectuated due to its execution in Iran Khodro Corporation are regarded together with the joint features and amalgamation of the aforesaid entia; hence the proposed blueprint is submitted to be taken advantage of in engineering and industrial projects including Iran Khodro Corporation.

Keywords: Management, risk engineering, value engineering, project manipulation, Iran Khodro.

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Authors: Mohamed Belaid, Edison Muzenda, Getrude Mitilene, Mansoor Mollagee

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A feasibility study for the design and construction of a pilot plant for the extraction of castor oil in South Africa was conducted. The study emphasized the four critical aspects of project feasibility analysis, namely technical, financial, market and managerial aspects. The technical aspect involved research on existing oil extraction technologies, namely: mechanical pressing and solvent extraction, as well as assessment of the proposed production site for both short and long term viability of the project. The site is on the outskirts of Nkomazi village in the Mpumalanga province, where connections for water and electricity are currently underway, potential raw material supply proves to be reliable since the province is known for its commercial farming. The managerial aspect was evaluated based on the fact that the current producer of castor oil will be fully involved in the project while receiving training and technical assistance from Sasol Technology, the TSC and SEDA. Market and financial aspects were evaluated and the project was considered financially viable with a Net Present Value (NPV) of R2 731 687 and an Internal Rate of Return (IRR) of 18% at an annual interest rate of 10.5%. The payback time is 6years for analysis over the first 10 years with a net income of R1 971 000 in the first year. The project was thus found to be feasible with high chance of success while contributing to socio-economic development. It was recommended for lab tests to be conducted to establish process kinetics that would be used in the initial design of the plant.

Keywords: Mechanical pressing, Net Present Value, Oilextraction, Project feasibility, Solvent extraction

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. To approach this problem, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Ghada Abo-Zaid

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Objectives: The main objective of this study was to examine the association between the elevated level of C-reactive protein (CRP) and incidence of hypertension before and after adjustments for age, BMI, gender, SES, smoking, diabetes, cholesterol LDL and cholesterol HDL, and to determine whether the association differs by race. Method: Cross sectional data for participants from aged 17 years to 74 years, included in The National Health and Nutrition Examination Survey (NHANES) from 1999 to 2010 were analyzed. The CRP level was classified into three categories (> 3 mg/L, between 1 mg/L and 3 mg/L, and < 3 mg/L). Blood pressure categorization was done using JNC 7 indicator. Hypertension is defined as either systolic blood pressure (SBP) of 140 mmHg or more and diastolic blood pressure (DBP) of 90 mmHg or more, otherwise a self-reported prior diagnosis by a physician. Pre-hypertension was defined as 139 ≥ SBP > 120 or 89 ≥ DBP >80. Multinominal regression model was undertaken to measure the association between CRP level and hypertension. Results: In univariable models, CRP concentrations > 3 mg/L were associated with a 73% greater risk of incident hypertension compared with CRP concentrations < 1 mg/L (Hypertension: odds ratio [OR] = 1.73; 95% confidence interval [CI], 1.50-1.99). Ethnic comparisons showed that American Mexicans had the highest risk of incident hypertension (OR = 2.39; 95% CI, 2.21-2.58). This risk was statistically insignificant after controlling by other variables (Hypertension: OR = 0.75; 95% CI, 0.52-1.08), or categorized by race [American Mexican: OR= 1.58; 95% CI, 0.58-4.26, Other Hispanic: OR = 0.87; 95% CI, 0.19-4.42, Non-Hispanic white: OR = 0.90; 95% CI, 0.50-1.59, Non-Hispanic Black: OR = 0.44; 95% CI, 0.22-0.87. The same results were found for pre-hypertension, and the Non-Hispanic black segment showed the highest significant risk for Pre-Hypertension (OR = 1.60; 95% CI, 1.26-2.03). When CRP concentrations were between 1.0 and 3.0 mg/L in unadjusted models, prehypertension was associated with higher likelihood of elevated CRP (OR = 1.37; 95% CI, 1.15-1.62). The same relationship was maintained in Non-Hispanic white, Non-Hispanic black, and other race (Non-Hispanic white: OR = 1.24; 95% CI, 1.03-1.48, Non-Hispanic black: OR = 1.60; 95% CI, 1.27-2.03, other race: OR = 2.50; 95% CI, 1.32-4.74) while the association was insignificant with American Mexican and other Hispanic. In the adjusted model, the relationship between CRP and prehypertension were no longer available. Contrary, hypertension was not independently associated with elevated CRP, and the results were the same after being grouped by race or adjustments for the possible confounder variables. The same results were obtained when SBP or DBP were on a continuous measure. Conclusions: This study confirmed the existence of an association between hypertension, prehypertension and elevated level of CRP, however this association was no longer available after adjusting by other variables. Ethic group differences were statistically significant at the univariable models, while it disappeared after controlling by other variables. 

Keywords: CRP, hypertension, ethnicity, NHANES, blood pressure.

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Authors: Ashwani Kumar, Jitender Kumar

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In this paper, an optimal power flow based approach has been applied for multi-transactions deregulated environment for ATC determination with SVC and STATCOM. The main contribution of the paper is (i) OPF based approach for evaluation of ATC with multi-transactions, (ii) ATC enhancement with FACTS devices viz. SVC and STATCOM for intact and line contingency cases, (iii) Impact of ZIP load on ATC determination and comparison of ATC obtained with SVC and STATCOM. The results have been determined for intact and line contingency cases taking simultaneous as well as single transaction cases for IEEE 24 bus RTS.

Keywords: Available transfer capability, FACTS devices, line contingency, multi-transactions, ZIP load model.

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Authors: S. Srikiran, Dharmala Venkata Padmaja, P. N. L. Pavani, R. Pola Rao, K. Ramji

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Technological advancements in the development of cutting tools and coolant/lubricant chemistry have enhanced the machining capabilities of hard materials under higher machining conditions. Generation of high temperatures at the cutting zone during machining is one of the most important and pertinent problems which adversely affect the tool life and surface finish of the machined components. Generally, cutting fluids and solid lubricants are used to overcome the problem of heat generation, which is not effectively addressing the problems. With technological advancements in the field of tribology, nano-level particulate solid lubricants are being used nowadays in machining operations, especially in the areas of turning and grinding. The present investigation analyses the effect of using nano-particulate graphite powder as lubricant in the turning of AISI 1040 steel under variable machining conditions and to study its effect on cutting forces, tool temperature and surface roughness of the machined component. Experiments revealed that the increase in cutting forces and tool temperature resulting in the decrease of surface quality with the decrease in the size of nano-particulate graphite powder as lubricant.

Keywords: Solid lubricant, graphite, minimum quantity lubrication, nanoparticles.

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Authors: Zdravka Aljinović, Snježana Pivac, Boško Šego

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According to the interaction of inflation and unemployment, expectation of the rate of inflation in Croatia is estimated. The interaction between inflation and unemployment is shown by model based on three first-order differential i.e. difference equations: Phillips relation, adaptive expectations equation and monetary-policy equation. The resulting equation is second order differential i.e. difference equation which describes the time path of inflation. The data of the rate of inflation and the rate of unemployment are used for parameters estimation. On the basis of the estimated time paths, the stability and convergence analysis is done for the rate of inflation.

Keywords: Differencing, inflation, time path, unemployment.

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Authors: B. Abbad, A. Lounis, Tassalit Djilali

Abstract:

The effects of equilibrium time, solution pH, and sorption temperature of cationic methylene blue (MB) adsorption on nanoporous metallosilicoaluminophosphate ZnAPSO-34 was studied using a batch equilibration method. UV–VIS spectroscopy was used to obtain the adsorption isotherms at 20° C. The optimum period for adsorption was 300 min. However, MB removal increased from 81,82 % to 94,81 %. The equilibrium adsorption data was analyzed by using Langmuir, Freundlich and Temkin isotherm models. Langmuir isotherm was found to be the better-fitting model and the process followed pseudo second–order kinetics. The results showed that ZnAPSO-34 could be employed as an effective material and could be an attractive alternative for the removal of dyes and colors from aqueous solutions.

Keywords: Adsorption, Dye, Metallosilicoaluminophosphate, Methylene Blue.

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Authors: Karunakar A K, Manohara Pai M M

Abstract:

In 3D-wavelet video coding framework temporal filtering is done along the trajectory of motion using Motion Compensated Temporal Filtering (MCTF). Hence computationally efficient motion estimation technique is the need of MCTF. In this paper a predictive technique is proposed in order to reduce the computational complexity of the MCTF framework, by exploiting the high correlation among the frames in a Group Of Picture (GOP). The proposed technique applies coarse and fine searches of any fast block based motion estimation, only to the first pair of frames in a GOP. The generated motion vectors are supplied to the next consecutive frames, even to subsequent temporal levels and only fine search is carried out around those predicted motion vectors. Hence coarse search is skipped for all the motion estimation in a GOP except for the first pair of frames. The technique has been tested for different fast block based motion estimation algorithms over different standard test sequences using MC-EZBC, a state-of-the-art scalable video coder. The simulation result reveals substantial reduction (i.e. 20.75% to 38.24%) in the number of search points during motion estimation, without compromising the quality of the reconstructed video compared to non-predictive techniques. Since the motion vectors of all the pair of frames in a GOP except the first pair will have value ±1 around the motion vectors of the previous pair of frames, the number of bits required for motion vectors is also reduced by 50%.

Keywords: Motion Compensated Temporal Filtering, predictivemotion estimation, lifted wavelet transform, motion vector

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