Search results for: maximum input

Authors: S. Padmapriya, V. Lakshmi Prabha

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In this paper, an efficient reconfigurable fixed-point Least Mean Square Adaptive FIR filter is proposed. The proposed architecture has two methods of operation: one is area efficient design and the other is optimized power. Pipelining of the adder blocks and partial product generator are used to achieve low area and reversible logic is used to obtain low power design. Depending upon the input samples and filter coefficients, one of the techniques is chosen. Least-Mean-Square adaptation is performed to update the weights. The architecture is coded using Verilog and synthesized in cadence encounter 0.18μm technology. The synthesized results show that the area reduction ratio of the proposed when compared with conventional technique is about 1.2%.

Keywords: adaptive filter, carry select adder, least mean square algorithm, reversible logic

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Authors: Talha Ali Khan

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Discovering different energy resources to fulfill the world's growing demand is now one of the society’s bigger challenges for the next half-century. The main task is to convert the sun radiation into electricity via photovoltaic solar cells which is suddenly decreasing $/watt of delivered solar electricity. Therefore, in this context the sun trackers are those devices that can be used to ameliorate efficiency. In this paper, a variety of the sun tracking systems are evaluated and their merits and demerits are highlighted. The most adept and proficient sun-tracking devices are polar axis and azimuth-elevation types.

Keywords: dual axis, fixed axis, sun tracker, sun radiation

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Authors: Tauqir A. Moughal, Fusheng Yu, Abeer Mazher

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Land-cover and land-use change information are important because of their practical uses in various applications, including deforestation, damage assessment, disasters monitoring, urban expansion, planning, and land management. Therefore, developing change detection methods for remote sensing images is an important ongoing research agenda. However, detection of change through optical remote sensing images is not a trivial task due to many factors including the vagueness between the boundaries of changed and unchanged regions and spatial dependence of the pixels to its neighborhood. In this paper, we propose a binary change detection technique for bi-temporal optical remote sensing images. As in most of the optical remote sensing images, the transition between the two clusters (change and no change) is overlapping and the existing methods are incapable of providing the accurate cluster boundaries. In this regard, a methodology has been proposed which uses the fuzzy c-means clustering to tackle the problem of vagueness in the changed and unchanged class by formulating the soft boundaries between them. Furthermore, in order to exploit the neighborhood information of the pixels, the input patterns are generated corresponding to each pixel from bi-temporal images using 3×3, 5×5 and 7×7 window. The between images and within image spatial dependence of the pixels to its neighborhood is quantified by using Pearson product moment correlation and Moran’s I statistics, respectively. The proposed technique consists of two phases. At first, between images and within image spatial correlation is calculated to utilize the information that the pixels at different locations may not be independent. Second, fuzzy c-means technique is used to produce two clusters from input feature by not only taking care of vagueness between the changed and unchanged class but also by exploiting the spatial correlation of the pixels. To show the effectiveness of the proposed technique, experiments are conducted on multispectral and bi-temporal remote sensing images. A subset (2100×1212 pixels) of a pan-sharpened, bi-temporal Landsat 5 thematic mapper optical image of Los Angeles, California, is used in this study which shows a long period of the forest fire continued from July until October 2009. Early forest fire and later forest fire optical remote sensing images were acquired on July 5, 2009 and October 25, 2009, respectively. The proposed technique is used to detect the fire (which causes change on earth’s surface) and compared with the existing K-means clustering technique. Experimental results showed that proposed technique performs better than the already existing technique. The proposed technique can be easily extendable for optical hyperspectral images and is suitable for many practical applications.

Keywords: burned area, change detection, correlation, fuzzy clustering, optical remote sensing

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Authors: Saad Saeed Althiabi

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This paper discusses the corporate positioning and how it became popular as a way to systematize production because of the unique manner in which incorporation legalized organizers to secure financial capital through locking it in. The power to lock in capital comes from the fact that a corporate exists as a separate legal entity, whose survival and governance are separated from any of its participants. The law essentially creates a different legal person when a corporation is created. Although this idea has been played down in the legal learning of the last decades in favor of the view that a corporation is purely something through which natural persons interrelate, recent legal research has begun to reassess the importance of entity status. Entity status, under the law and the related separation of governance from input of financial capital through the configuration of a corporation, sanctioned corporate participants to do somewhat more than connect in a series of business transactions.

Keywords: corporate law, entity status, locking in capital, financial capital

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Authors: Ersan Aktas, Eren Turanoğuz

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In this study, the quad-electrical rotor driven unmanned aerial vehicle system is designed and modeled using fundamental dynamic equations. After that, mechanical, electronical and control system of the air vehicle are designed and implemented. Brushless motor speeds are altered via electronic speed controllers in order to achieve desired controllability. The vehicle's fundamental Euler angles (i.e., roll angle, pitch angle, and yaw angle) are obtained via AHRS sensor. These angles are provided as an input to the control algorithm that run on soft the processor on the electronic card. The vehicle control algorithm is implemented in the electronic card. Controller is designed and improved for each Euler angles. Finally, flight tests have been performed to observe and improve the flight characteristics.

Keywords: quadrotor, UAS applications, control architectures, PID

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Authors: Pramod Somvanshi, Manu Tomar, K. V. Venkatesh

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Insulin and glucagon are responsible for homeostasis of key plasma metabolites like glucose, amino acids and fatty acids in the blood plasma. These hormones act antagonistically to each other during the secretion and signaling stages. In the present work, we analyze the effect of macronutrients on the response from integrated insulin and glucagon signaling pathways. The insulin and glucagon pathways are connected by DAG (a calcium signaling component which is part of the glucagon signaling module) which activates PKC and inhibits IRS (insulin signaling component) constituting a crosstalk. AKT (insulin signaling component) inhibits cAMP (glucagon signaling component) through PDE3 forming the other crosstalk between the two signaling pathways. Physiological level of anabolism and catabolism is captured through a metric quantified by the activity levels of AKT and PKA in their phosphorylated states, which represent the insulin and glucagon signaling endpoints, respectively. Under resting and starving conditions, the phosphorylation metric represents homeostasis indicating a balance between the anabolic and catabolic activities in the tissues. The steady state analysis of the integrated network demonstrates the presence of a bistable response in the phosphorylation metric with respect to input plasma glucose levels. This indicates that two steady state conditions (one in the homeostatic zone and other in the anabolic zone) are possible for a given glucose concentration depending on the ON or OFF path. When glucose levels rise above normal, during post-meal conditions, the bistability is observed in the anabolic space denoting the dominance of the glycogenesis in liver. For glucose concentrations lower than the physiological levels, while exercising, metabolic response lies in the catabolic space denoting the prevalence of glycogenolysis in liver. The non-linear positive feedback of AKT on IRS in insulin signaling module of the network is the main cause of the bistable response. The span of bistability in the phosphorylation metric increases as plasma fatty acid and amino acid levels rise and eventually the response turns monostable and catabolic representing diabetic conditions. In the case of high fat or protein diet, fatty acids and amino acids have an inhibitory effect on the insulin signaling pathway by increasing the serine phosphorylation of IRS protein via the activation of PKC and S6K, respectively. Similar analysis was also performed with respect to input amino acid and fatty acid levels. This emergent property of bistability in the integrated network helps us understand why it becomes extremely difficult to treat obesity and diabetes when blood glucose level rises beyond a certain value.

Keywords: bistability, diabetes, feedback and crosstalk, obesity

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Authors: Ian A. Grout

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In this paper, the design and development of a system to provide hand motion and gesture control of laboratory test equipment is considered and discussed. The Leap Motion controller is used to provide an input to control a laboratory power supply as part of an electronic circuit experiment. By suitable hand motions and gestures, control of the power supply is provided remotely and without the need to physically touch the equipment used. As such, it provides an alternative manner in which to control electronic equipment via a PC and is considered here within the field of human computer interaction (HCI).

Keywords: control, hand gesture, human computer interaction, test equipment

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Authors: Muhammad Shafiq

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In accelerated life testing approaches life time data is obtained under various conditions which are considered more severe than usual condition. Classical techniques are based on obtained precise measurements, and used to model variation among the observations. In fact, there are two types of uncertainty in data: variation among the observations and the fuzziness. Analysis techniques, which do not consider fuzziness and are only based on precise life time observations, lead to pseudo results. This study was aimed to examine the behavior of empirical acceleration functions using fuzzy lifetimes data. The results showed an increased fuzziness in the transformed life times as compare to the input data.

Keywords: acceleration function, accelerated life testing, fuzzy number, non-precise data

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Authors: Bozena Dohnalkova

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This paper presents a part of the project solving which is dedicated to the identification of the hazardous waste with the most critical production within the Czech Republic with the aim to study and find the optimal composition of the cement matrix that will ensure maximum content disposal of chosen hazardous waste. In the first stage of project solving – which represents this paper – a specific hazardous waste was chosen, its properties were identified and suitable solidification agents were chosen. Consequently solidification formulas and testing methodology was proposed.

Keywords: cementation, solidification, waste, binder

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Authors: Priya Tomar, Pallavi Mittal

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As industrialization is inevitable and progress with rapid acceleration, the need for innovative ways to get rid of waste has increased. Recent advancement in bioresource technology paves novel ideas for recycling of factory waste that has been polluting the agro-industry, soil and water bodies. Paper industries in India are in a considerable number, where molasses and impure alcohol are still being used as raw materials for manufacturing of paper. Paper mills based on nonconventional agro residues are being encouraged due to increased demand of paper and acute shortage of forest-based raw materials. The colouring body present in the wastewater from pulp and paper mill is organic in nature and is comprised of wood extractives, tannin, resins, synthetic dyes, lignin and its degradation products formed by the action of chlorine on lignin which imparts an offensive colour to the water. These mills use different chemical process for paper manufacturing due to which lignified chemicals are released into the environment. Therefore, the chemical oxygen demand (COD) of the emanating stream is quite high. This paper presents some new techniques that were developed for the efficiency of bioremediation on paper industry. A short introduction to paper industry and a variety of presently available methods of bioremediation on paper industry and different strategies are also discussed here. For solving the above problem, two bacterial strains (Pseudomonas aeruginosa and Bacillus subtilis) and their consortia (Pseudomonas aeruginosa and Bacillus subtilis) were utilized for the pulp and paper mill effluent. Pseudomonas aeruginosa and Bacillus subtilis named as T–1, T–2, T–3, T–4, T–5, T–6, for the decolourisation of paper industry effluent. The results indicated that a maximum colour reduction is (60.5%) achieved by Pseudomonas aeruginosa and COD reduction is (88.8%) achieved by Bacillus subtilis, maximum pH changes is (4.23) achieved by Pseudomonas aeruginosa, TSS reduction is (2.09 %) achieved by Bacillus subtilis, and TDS reduction is (0.95 %) achieved by Bacillus subtilis. When the wastewater was supplemented with carbon (glucose) and nitrogen (yeast extract) source and data revealed the efficiency of Bacillus subtilis, having more with glucose than Pseudomonas aeruginosa.

Keywords: bioremediation, paper and pulp mill effluent, treated effluent, lignin

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Authors: M. Prasanth, V. Nithin, R. Keerthana, S.Kalyani

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In the current scenario, the steering system in automobiles is such that the motion from the steering wheel is transferred to driving wheel by mechanical linkages. In this paper, we propose a method to design a steering mechanism using servomotors to turn the wheels instead of linkages. In this method, a steering angle sensor senses the turn angle of the steering wheel and its output is processed by an electronical control module. Then the ECM compares the angle value to that of a standard value from a look-up database. Then it gives the appropriate input power and the turning duration to the motors. Correspondingly, the motors turn the wheels by means of bevel gears welded to both the motor output shafts and the wheel hubs. Thus, the wheels are turned without the complicated framework of linkages, reducing the driver’s effort and fatigue considerably.

Keywords: electronic control unit, linkage-less steering, servomotors, E-Mo Steer

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Authors: Manolo Dulva Hina, Clement Thierry, Assia Soukane, Amar Ramdane-Cherif

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In this paper, we presented our innovative way of determining the driving context for a driving assistance system. We invoke the fusion of all parameters that describe the context of the environment, the vehicle and the driver to obtain the driving context. We created a training set that stores driving situation patterns and from which the system consults to determine the driving situation. A machine-learning algorithm predicts the driving situation. The driving situation is an input to the fission process that yields the action that must be implemented when the driver needs to be informed or assisted from the given the driving situation. The action may be directed towards the driver, the vehicle or both. This is an ongoing work whose goal is to offer an alternative driving assistance system for safe driving, green driving and comfortable driving. Here, ontologies are used for knowledge representation.

Keywords: cognitive driving, intelligent transportation system, multimodal system, ontology, machine learning

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Authors: Monalisa Pradhan, Ajana Dutta, Irshad Kariyattuparamb Abbas, Boby Joseph, T. N. Guru Row, Diptikanta Swain, Gopal K. Pradhan

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Compounds with the Vanthoffite crystal structure having general formula Na6M(SO₄)₄ (M= Mg, Mn, Ni , Co, Fe, Cu and Zn) display a variety of intriguing physical properties intimately related to their structural arrangements. The compound Na6Mn(SO4)4 shows antiferromagnetic ordering at low temperature where the in-plane Mn-O•••O-Mn interactions facilitates antiferromagnetic ordering via a super-exchange interaction between the Mn atoms through the oxygen atoms . The inter-atomic bond distances and angles can easily be tuned by applying external pressure and can be probed using high resolution X-ray diffraction. Moreover, because the magnetic interaction among the Mn atoms are super-exchange type via Mn-O•••O-Mn path, the variation of the Mn-O•••O-Mn dihedral angle and Mn-O bond distances under high pressure inevitably affects the magnetic properties. Therefore, it is evident that high pressure studies on the magnetically ordered materials would shed light on the interplay between their structural properties and magnetic ordering. This will indeed confirm the role of buckling of the Mn-O polyhedral in understanding the origin of anti-ferromagnetism. In this context, we carried out the pressure dependent X-ray diffraction measurement in a diamond anvil cell (DAC) up to a maximum pressure of 17 GPa to study the phase transition and determine equation of state from the volume compression data. Upon increasing the pressure, we didn’t observe any new diffraction peaks or sudden discontinuity in the pressure dependences of the d values up to the maximum achieved pressure of ~17 GPa. However, it is noticed that beyond 12 GPa the a and b lattice parameters become identical while there is a discontinuity in the β value around the same pressure. This indicates a subtle transition to a pseudo-monoclinic phase. Using the third order Birch-Murnaghan equation of state (EOS) to fit the volume compression data for the entire range, we found the bulk modulus (B0) to be 44 GPa. If we consider the subtle transition at 12 GPa, we tried to fit another equation state for the volume beyond 12 GPa using the second order Birch-Murnaghan EOS. This gives a bulk modulus of ~ 34 GPa for this phase.

Keywords: mineral, structural phase transition, high pressure XRD, spectroscopy

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Authors: Fatima Akhmedova, Simon Liao

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One of the most critical decision points in the design of a face recognition system is the choice of an appropriate face representation. Effective feature descriptors are expected to convey sufficient, invariant and non-redundant facial information. In this work, we propose a set of Hahn moments as a new approach for feature description. Hahn moments have been widely used in image analysis due to their invariance, non-redundancy and the ability to extract features either globally and locally. To assess the applicability of Hahn moments to Face Recognition we conduct two experiments on the Olivetti Research Laboratory (ORL) database and University of Notre-Dame (UND) X1 biometric collection. Fusion of the global features along with the features from local facial regions are used as an input for the conventional k-NN classifier. The method reaches an accuracy of 93% of correctly recognized subjects for the ORL database and 94% for the UND database.

Keywords: face recognition, Hahn moments, recognition-by-parts, time-lapse

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Authors: Victor Manuel Alcántara Alza

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The way in which the application of the deep cryogenic treatment DCT(-196°C) affects, applied with subsequent aging, was investigated, regarding the mechanical properties of hardness, toughness and microstructure, applied to martensitic stainless steels, with the aim of establishing a different methodology compared to the traditional DCT cryogenic treatment with subsequent tempering. For this experimental study, a muffle furnace was used, first subjecting the specimens to deep cryogenization in a liquid Nitrogen bath/4h, after being previously austenitized at the following temperatures: 1020-1030-1040-1050 (°C) / 1 hour; and then tempered in oil. A first group of cryogenic samples were subjected to subsequent aging at 150°C, with immersion times: 2.5 -5- 10 - 20 - 50 – 100 (h). The next group was subjected to subsequent tempering at temperatures: 480-500-510-520-530-540 (°C)/ 2h. The hardness tests were carried out under standards, using a Universal Durometer, and the readings were made on the HRC scale. The Impact Resistance tests were carried out in a Charpy machine following the ASTM E 23 – 93ª standard. Measurements were taken in joules. Microscopy was performed at the optical level using a 1000X microscope. It was found: For the entire aging interval, the samples austenitized at 1050°C present greater hardness than austenitized at 1040°C, with the maximum peak aged being at 30h. In all cases, the aged samples exceed the hardness of the tempered samples, even in their minimum values. In post-tempered samples, the tempering temperature hardly have effect on the impact strength of material. In the Cryogenic Treatment: DCT + subsequent aging, the maximum hardness value (58.7 HRC) is linked to an impact toughness value (54J) obtained with aging time of 39h, which is considered an optimal condition. The higher hardness of steel after the DCT treatment is attributed to the transformation of retained austenite into martensite. The microstructure is composed mainly of lath martensite; and the original grain size of the austenite can be appreciated. The choice of the combination: Hardness-toughness, is subject to the required service conditions of steel.

Keywords: deep cryogenic treatment; aged precipitation; martensitic steels;, mechanical properties; martensitic steels, hardness, carbides precipitaion

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Authors: Vlad Andrei Raducanu, Mariana Lucia Angelescu, Ion Cinca, Vasile Danut Cojocaru, Doina Raducanu

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By using smart digital tools, such as generative design (GD) and digital fabrication (DF), problems of high actuality concerning resources optimization (materials, energy, time) can be solved and applications or products of free-form type can be created. In the new digital technology materials are active, designed in response to a set of performance requirements, which impose a total rethinking of old material practices. The article presents the design procedure key steps of a free-form architectural object - a column type one with connections to get an adaptive 3D surface, by using the parametric design methodology and by exploiting the properties of conventional metallic materials. In parametric design the form of the created object or space is shaped by varying the parameters values and relationships between the forms are described by mathematical equations. Digital parametric design is based on specific procedures, as shape grammars, Lindenmayer - systems, cellular automata, genetic algorithms or swarm intelligence, each of these procedures having limitations which make them applicable only in certain cases. In the paper the design process stages and the shape grammar type algorithm are presented. The generative design process relies on two basic principles: the modeling principle and the generative principle. The generative method is based on a form finding process, by creating many 3D spatial forms, using an algorithm conceived in order to apply its generating logic onto different input geometry. Once the algorithm is realized, it can be applied repeatedly to generate the geometry for a number of different input surfaces. The generated configurations are then analyzed through a technical or aesthetic selection criterion and finally the optimal solution is selected. Endless range of generative capacity of codes and algorithms used in digital design offers various conceptual possibilities and optimal solutions for both technical and environmental increasing demands of building industry and architecture. Constructions or spaces generated by parametric design can be specifically tuned, in order to meet certain technical or aesthetical requirements. The proposed approach has direct applicability in sustainable architecture, offering important potential economic advantages, a flexible design (which can be changed until the end of the design process) and unique geometric models of high performance.

Keywords: parametric design, algorithmic procedures, free-form architectural object, sustainable architecture

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Authors: S. Dhivya, M. Abirami, M. Farjana Parveen, M. Keerthiga

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The development of high-speed railway makes people’s lives more and more convenient; meanwhile, handover is the major problem on high-speed railway communication services. In order to overcome that drawback the architecture of Long-Term Evolution (LTE) femtocell networks is used to improve network performance, and the deployment of a femtocell is a key for bandwidth limitation and coverage issues in conventional mobile network system. To increase the handover performance this paper proposed a multiple input multiple output (MIMO) assisted handoff (MAHO) algorithm. It is a technique used in mobile telecom to transfer a mobile phone to a new radio channel with stronger signal strength and improved channel quality.

Keywords: flawless handover, high-speed train, home evolved Node B, LTE, mobile femtocell, RSS

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Authors: B. Petrović, L. Rutonjski, M. Baucal, M. Teodorović, O. Čudić, B. Basarić

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Radiotherapy treatment planning computers use CT data of the patient. For the computation of a treatment plan, treatment planning system must have an information on electron densities of tissues scanned by CT. This information is given by the conversion curve CT (CT number) to ED (electron density), or simply calibration curve. Every treatment planning system (TPS) has built in default CT to ED conversion curves, for the CTs of different manufacturers. However, it is always recommended to verify the CT to ED conversion curve before actual clinical use. Objective of this study was to check how the default curve already provided matches the curve actually measured on a specific CT, and how much it influences the calculation of a treatment planning computer. The examined CT scanners were from the same manufacturer, but four different scanners from three generations. The measurements of all calibration curves were done with the dedicated phantom CIRS 062M Electron Density Phantom. The phantom was scanned, and according to real HU values read at the CT console computer, CT to ED conversion curves were generated for different materials, for same tube voltage 140 kV. Another phantom, CIRS Thorax 002 LFC which represents an average human torso in proportion, density and two-dimensional structure, was used for verification. The treatment planning was done on CT slices of scanned CIRS LFC 002 phantom, for selected cases. Interest points were set in the lungs, and in the spinal cord, and doses recorded in TPS. The overall calculated treatment times for four scanners and default scanner did not differ more than 0.8%. Overall interest point dose in bone differed max 0.6% while for single fields was maximum 2.7% (lateral field). Overall interest point dose in lungs differed max 1.1% while for single fields was maximum 2.6% (lateral field). It is known that user should verify the CT to ED conversion curve, but often, developing countries are facing lack of QA equipment, and often use default data provided. We have concluded that the CT to ED curves obtained differ in certain points of a curve, generally in the region of higher densities. This influences the treatment planning result which is not significant, but definitely does make difference in the calculated dose.

Keywords: Computation of treatment plan, conversion curve, radiotherapy, electron density

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Authors: G. Bhushan, S. Dhingra, K. K. Dubey

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This paper presents the evaluation of performance (BSFC and BTE), combustion (P_max) and emission (CO, NO_x, HC and smoke opacity) parameters of karanja biodiesel in a single cylinder, four stroke, direct injection diesel engine by considering significant engine input parameters (blending ratio, compression ratio and load torque). Multi-objective optimization of performance, combustion and emission parameters is also carried out in a karanja biodiesel engine using hybrid RSM-NSGA-II technique. The pareto optimum solutions are predicted by running the hybrid RSM-NSGA-II technique. Each pareto optimal solution is having its own importance. Confirmation tests are also conducted at randomly selected few pareto solutions to check the authenticity of the results.

Keywords: genetic algorithm, rsm, biodiesel, karanja

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Authors: N. Sateesh, C. S. P. Rao, K. Satyanarayana, C. Rajashekar

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This paper proposes a development of a CAD/CAM system for complex profiles of various machine members using a synthetic curve i.e. B-spline. Conventional methods in designing and manufacturing of complex profiles are tedious and time consuming. Even programming those on a computer numerical control (CNC) machine can be a difficult job because of the complexity of the profiles. The system developed provides graphical and numerical representation B-spline profile for any given input. In this paper, the system is applicable to represent a cam profile with B-spline and attempt is made to improve the follower motion.

Keywords: plate-cams, cam profile, b-spline, computer numerical control (CNC), computer aided design and computer aided manufacturing (CAD/CAM), R-D-R-D (rise-dwell-return-dwell)

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Authors: Marzieh Zarei

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Well instability is one of the most fundamental challenges faced by the oil and gas industry. Well wall stability analysis is a gap to be filled in the oil industry. The collection of static data such as well logging leads to the construction of a geomechanical numerical model, which will help in assessing the probable risks in future drilling. In this paper, geomechanical model was designed, and mechanical properties of the rock was determined at all points of the model. It was found the safe mud window was determined and the minimum and maximum mud pressures were determined in the ranges of 70-60 MPa and 110-100 MPa, respectively.

Keywords: geomechanics, numerical model, well stability, in-situ stress, underbalanced drilling

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Authors: Barkaoui Asma

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In our article, we use the economic approach of measuring advertising effectiveness to show the margin of advertising spread gained through digital communication. For economists, profit maximization depends on determining the optimal advertising budget. For this, they use the theories of the marginalist current to determine when the maximum level of benefits is reached. Using the economic approach we show the significant return on investment for advertisers. We then discuss the risks of perception of advertising pressure by consumers.

Keywords: digital advertising, economic approach, effectiveness, pressure

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Authors: Michał Gęca, Konrad Pietrykowski, Grzegorz Barański

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The water pump in the compression-ignition internal combustion engine transports a hot coolant along a system of ducts from the engine block to the radiator where coolant temperature is lowered. This part needs to maintain a constant volumetric flow rate. Its power should be regulated to avoid a significant drop in pressure if a coolant flow decreases. The internal combustion engine cooling system uses centrifugal pumps for suction. The paper investigates 4 constructions of engine pumps. The pumps are from diesel engine of a maximum power of 75 kW. Each of them has a different rotor shape, diameter and width. The test stand was created and the geometry inside the all 4 engine blocks was mapped. For a given pump speed on the inverter of the electric engine motor, the valve position was changed and volumetric flow rate, pressure, and power were recorded. Pump speed was regulated from 1200 RPM to 7000 RPM every 300 RPM. The volumetric flow rates and pressure drops for the pump speeds and efficiencies were specified. Accordingly, the operations of each pump were mapped. Our research was to select a pump for the aircraft compression-ignition engine. There was calculated a pressure drop at a given flow on the block and radiator of the designed aircraft engine. The water pump should be lightweight and have a low power demand. This fact shall affect the shape of a rotor and bearings. The pump volumetric flow rate was assumed as 3 kg/s (previous AVL BOOST research model) where the temperature difference was 5°C between the inlet (90°C) and outlet (95°C). Increasing pump speed above the boundary flow power defined by pressure and volumetric flow rate does not increase it but pump efficiency decreases. The maximum total pump efficiency (PCC) is 45-50%. When the pump is driven by low speeds with a 90% closed valve, its overall efficiency drops to 15-20%. Acknowledgement: This work has been realized in the cooperation with The Construction Office of WSK "PZL-KALISZ" S.A." and is part of Grant Agreement No. POIR.01.02.00-00-0002/15 financed by the Polish National Centre for Research and Development.

Keywords: aircraft engine, diesel engine, flow, water pump

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Authors: Linta Rose, Prasad K. Bhaskaran

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Water-level information along the coast is very important for disaster management, navigation, planning shoreline management, coastal engineering and protection works, port and harbour activities, and for a better understanding of near-shore ocean dynamics. The water-level variation along a coast attributes from various factors like astronomical tides, meteorological and hydrological forcing. The study area is the Head Bay of Bengal which is highly vulnerable to flooding events caused by monsoons, cyclones and sea-level rise. The study aims to explore the extent to which wind and surface pressure can influence water-level elevation, in view of the low-lying topography of the coastal zones in the region. The ADCIRC hydrodynamic model has been customized for the Head Bay of Bengal, discretized using flexible finite elements and validated against tide gauge observations. Monthly mean climatological wind and mean sea level pressure fields of ERA Interim reanalysis data was used as input forcing to simulate water-level variation in the Head Bay of Bengal, in addition to tidal forcing. The output water-level was compared against that produced using tidal forcing alone, so as to quantify the contribution of meteorological forcing to water-level. The average contribution of meteorological fields to water-level in January is 5.5% at a deep-water location and 13.3% at a coastal location. During the month of July, when the monsoon winds are strongest in this region, this increases to 10.7% and 43.1% respectively at the deep-water and coastal locations. The model output was tested by varying the input conditions of the meteorological fields in an attempt to quantify the relative significance of wind speed and wind direction on water-level. Under uniform wind conditions, the results showed a higher contribution of meteorological fields for south-west winds than north-east winds, when the wind speed was higher. A comparison of the spectral characteristics of output water-level with that generated due to tidal forcing alone showed additional modes with seasonal and annual signatures. Moreover, non-linear monthly mode was found to be weaker than during tidal simulation, all of which point out that meteorological fields do not cause much effect on the water-level at periods less than a day and that it induces non-linear interactions between existing modes of oscillations. The study signifies the role of meteorological forcing under fair weather conditions and points out that a combination of multiple forcing fields including tides, wind, atmospheric pressure, waves, precipitation and river discharge is essential for efficient and effective forecast modelling, especially during extreme weather events.

Keywords: ADCIRC, head Bay of Bengal, mean sea level pressure, meteorological forcing, water-level, wind

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Authors: V. Prasannavenkadesan, A. Elango, S. Chockalingam

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During machining process, chatter is an unavoidable phenomenon. Boring bars possess the cantilever shape and due to this, it is subjected to chatter. The adverse effect of chatter includes the increase in temperature which will leads to excess tool wear. To overcome these problems, in this investigation, Cartridge brass (Cu – 70% and Zn – 30%) is passively fixed on the boring bar and also clearance is provided in order to reduce the displacement, tool wear and cutting temperature. A conventional all geared lathe is attached with vibrometer and pyrometer is used to measure the displacement and temperature. The influence of input parameters such as cutting speed, depth of cut and clearance on temperature, tool wear and displacement are investigated for various cutting conditions. From the result, the optimum conditions to obtain better damping in boring process for chatter reduction is identified.

Keywords: boring, chatter, mass damping, passive damping

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Authors: Hassan Almoslim

Abstract:

Background: The machine resistance training is an exercise that uses the equipment as loads to strengthen and condition the musculoskeletal system and improving muscle tone. The machine resistance training is easy to use, allow the individual to train with heavier weights without assistance, useful for beginners and elderly populations and specific muscle groups. Purpose: The purpose of this study was to examine the impact of nine weeks of machine resistance training on maximum strength among lean and normal weight male college students. Method: Thirty-six male college students aged between 19 and 21 years from King Fahd University of petroleum & minerals participated in the study. The subjects were divided into two an equal groups called Lean Group (LG, n = 18) and Normal Weight Group (NWG, n = 18). The subjects whose body mass index (BMI) is less than 18.5 kg / m2 is considered lean and who is between 18.5 to 24.9 kg / m2 is normal weight. Both groups performed machine resistance training nine weeks, twice per week for 40 min per training session. The strength measurements, chest press, leg press and abdomen exercises were performed before and after the training period. 1RM test was used to determine the maximum strength of all subjects. The training program consisted of several resistance machines such as leg press, abdomen, chest press, pulldown, seated row, calf raises, leg extension, leg curls and back extension. The data were analyzed using independent t-test (to compare mean differences) and paired t-test. The level of significance was set at 0.05. Results: No change was (P ˃ 0.05) observed in all body composition variables between groups after training. In chest press, the NWG recorded a significantly greater mean different value than the LG (19.33 ± 7.78 vs. 13.88 ± 5.77 kg, respectively, P ˂ 0.023). In leg press and abdomen exercises, both groups revealed similar mean different values (P ˃ 0.05). When the post-test was compared with the pre-test, the NWG showed significant increases in the chest press by 47% (from 41.16 ± 12.41 to 60.49 ± 11.58 kg, P ˂ 001), abdomen by 34% (from 45.46 ± 6.97 to 61.06 ± 6.45 kg, P ˂ 0.001) and leg press by 23.6% (from 85.27 ± 15.94 to 105.48 ± 21.59 kg, P ˂ 0.001). The LG also illustrated significant increases by 42.6% in the chest press (from 32.58 ± 7.36 to 46.47 ± 8.93 kg, P ˂ 0.001), the abdomen by 28.5% (from 38.50 ± 7.84 to 49.50 ± 7.88 kg, P ˂ 0.001) and the leg press by 30.8% (from 70.2 ± 20.57 to 92.01 ± 22.83 kg, P ˂ 0.001). Conclusion: It was concluded that the lean and the normal weight male college students can benefit from the machine resistance-training program remarkably.

Keywords: body composition, lean, machine resistance training, normal weight

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Authors: M. A. Ben Messaoud, A. Bouzid, N. Ellouze

Abstract:

Speech Segmentation is the measure of the change point detection for partitioning an input speech signal into regions each of which accords to only one speaker. In this paper, we apply two features based on multi-scale product (MP) of the clean speech, namely the spectral centroid of MP, and the zero crossings rate of MP. We focus on multi-scale product analysis as an important tool for segmentation extraction. The multi-scale product is based on making the product of the speech wavelet transform coefficients at three successive dyadic scales. We have evaluated our method on the Keele database. Experimental results show the effectiveness of our method presenting a good performance. It shows that the two simple features can find word boundaries, and extracted the segments of the clean speech.

Keywords: multiscale product, spectral centroid, speech segmentation, zero crossings rate

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Authors: Khuram Nawaz Sadozai, Rizwan Ahmad, Munawar Raza Kazmi, Awais Habib

Abstract:

Climate change and crop production are intrinsically associated with each other. Therefore, this research study is designed to assess the impact of climate change on pulses production in Southern districts of Khyber Pakhtunkhwa (KP) Province of Pakistan. Two pulses (i.e. chickpea and mung bean) were selected for this research study with respect to climate change. Climatic variables such as temperature, humidity and precipitation along with pulses production and area under cultivation of pulses were encompassed as the major variables of this study. Secondary data of climatic variables and crop variables for the period of thirty four years (1986-2020) were obtained from Pakistan Metrological Department and Agriculture Statistics of KP respectively. Panel data set of chickpea and mung bean crops was estimated separately. The analysis validate that both data sets were a balanced panel data. The Hausman specification test was run separately for both the panel data sets whose findings had suggested the fixed effect model can be deemed as an appropriate model for chickpea panel data, however random effect model was appropriate for estimation of the panel data of mung bean. Major findings confirm that maximum temperature is statistically significant for the chickpea yield. This implies if maximum temperature increases by 1 0C, it can enhance the chickpea yield by 0.0463 units. However, the impact of precipitation was reported insignificant. Furthermore, the humidity was statistically significant and has a positive association with chickpea yield. In case of mung bean the minimum temperature was significantly contributing in the yield of mung bean. This study concludes that temperature and humidity can significantly contribute to enhance the pulses yield. It is recommended that capacity building of pulses growers may be made to adapt the climate change strategies. Moreover, government may ensure the availability of climate change resistant varieties of pulses to encourage the pulses cultivation.

Keywords: climate change, pulses productivity, agriculture, Pakistan

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Authors: Varun Agarwal

Abstract:

Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

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Authors: P. Kooche Baghy, S. Eskandari, E.javanmard

Abstract:

Neural network has been used as a predictive means of cold rolling force in this dissertation. Thus, imposed average force on rollers as a mere input and five pertaining parameters to its as a outputs are regarded. According to our study, feed-forward multilayer perceptron network has been selected. Besides, Bayesian algorithm based on the feed-forward back propagation method has been selected due to noisy data. Further, 470 out of 585 all tests were used for network learning and others (115 tests) were considered as assessment criteria. Eventually, by 30 times running the MATLAB software, mean error was obtained 3.84 percent as a criteria of network learning. As a consequence, this the mentioned error on par with other approaches such as numerical and empirical methods is acceptable admittedly.

Keywords: artificial neural network, Bayesian, cold rolling, force evaluation

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