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This article is from BMC Bioinformatics , volume 12 . Abstract Background: Tokenization is an important component of language processing yet there is no widely accepted tokenization method for English texts, including biomedical texts. Other than rule based techniques, tokenization in the biomedical domain has been regarded as a classification task. Biomedical classifier-based tokenizers either split or join textual objects through classification to form tokens. The idiosyncratic nature of each biomedical tokenizer’s output complicates adoption and reuse. Furthermore, biomedical tokenizers generally lack guidance on how to apply an existing tokenizer to a new domain (subdomain). We identify and complete a novel tokenizer design pattern and suggest a systematic approach to tokenizer creation. We implement a tokenizer based on our design pattern that combines regular expressions and machine learning. Our machine learning approach differs from the previous split-join classification approaches. We evaluate our approach against three other tokenizers on the task of tokenizing biomedical text. Results: Medpost and our adapted Viterbi tokenizer performed best with a 92.9% and 92.4% accuracy respectively. Conclusions: Our evaluation of our design pattern and guidelines supports our claim that the design pattern and guidelines are a viable approach to tokenizer construction (producing tokenizers matching leading custom-built tokenizers in a particular domain). Our evaluation also demonstrates that ambiguous tokenizations can be disambiguated through POS tagging. In doing so, POS tag sequences and training data have a significant impact on proper text tokenization.

Many intellectual property (IP) modules are present in contemporary system on chips (SoCs). This could provide an issue with interconnection among different IP modules, which would limit the system's ability to scale. Traditional bus-based SoC architectures have a connectivity bottleneck, and network on chip (NoC) has evolved as an embedded switching network to address this issue. The interconnections between various cores or IP modules on a chip have a significant impact on communication and chip performance in terms of power, area latency and throughput. Also, designing a reliable fault tolerant NoC became a significant concern. In fault tolerant NoC it becomes critical to identify faulty node and dynamically reroute the packets keeping minimum latency. This study provides an insight into a domain of NoC, with intention of understanding fault tolerant approach based on the XY routing algorithm for 4×4 mesh architecture. The fault tolerant NoC design is synthesized on field programmable gate array (FPGA).

The objective of this research paper is to design a control system to optimize the operating works of the gantry crane system. The dynamic model of the gantry crane system is derived in terms of trolley position and payload oscillation, which is highly nonlinear. The crane system should have the capability to transfer the material to destination end with desired speed along with reducing the load oscillation, obtain expected trolley position and preserving the safety. Proposed controlling method is based on the proportional-integral-derivative (PID) controller with a series differential compensator to control the swinging of the payload and the system trolley movement in order to perform the optimum utilization of the gantry crane. Standard sine cosine optimization algorithm is one of the most-recent optimization techniques based on a stochastic algorithm was presented to tune the PID controller with a series differential compensator. Furthermore, the considered optimization algorithm is modified in order to overcome the inherent drawbacks and solve complex benchmark test functions and to find the optimal design's parameters of the proposed controller. The simulation results show that the modified sine cosine optimization algorithm has better global search performance and exhibits good computational robustness based on test functions. Moreover, the results of testing the gantry crane model reveal that the proposed controller with standard and modified algorithms is effective, feasible and robust in achieving the desired requirements.

This paper proposes a design of a complete system to identify weak grip strength that is caused by multiple factors like ageing, diseases, or accidents. This paper presents a grip measurement system that comprises of force sensing resistor and flex sensor to evaluate the condition of the hand. The system is tested by gripping a pencil and a cylindrical object using the glove, to determine the condition of the hand. Force sensitive resistor (FSR) evaluates the force applied by the different parts of the palm on the object being grasped. Flex sensor evaluates the bending of the fingers and thumb. The data from the sensors is then compared with existing data to evaluate the state of the hand. The data from the sensors is stored on the personal computer (PC) through serial communication. A model is trained using the data from the sensors, which determine if the grip strength of the user is weak or strong. The model is also trained to differentiate between two modes that are pen mode and object mode. The model achieved an accuracy of 90.8 percent using support vector machine (SVM) algorithm. This glove can be deployed in medical centers to assist in grip strength measurement.

This report presents the results of an investigation to determine the feasibility of producing trial design algorithms for building components. This work is part of a project to develop an automated, integrated cost and scheduling system. Two functional building systems were investigated: the reinforced concrete framing system and the sprinkler system. The components of each of these systems were studied, designers were interviewed, and trial design rules were elicited and analyzed. Results showed that designers use a general algorithm if they are required to design an element at the early feasibility stage of a project, especially when information about the project is lacking. This general algorithm was illustrated and analyzed, and when it was tested on an existing facility the results were satisfactory. Keywords: Construction; Cost estimates; Scheduling; Algorithms; Sprinklers; Reinforced concrete.

A classic method used to solve for the electric (E) and magnetic (H) fields produced by a radiating source involves first solving for the vector potential (A) through the evaluation of the radiation integral. This study was undertaken to define a numerical algorithm that solves for A, so that a reduction in computation time can be realized through VLSI design implementation. Fast Fourier Transforms, Newton-Cotes numerical integration, and variable parameterization, were applied to the problem with unsuccessful results. A numerical summation approximation proved to have all the desired qualities for the algorithm. These qualities are, ability to handle arbitrary antennas, accurate results, and all digital mathematics algorithms exist. Verification of the numerical solution was accomplished by comparing the results it produced for a dipole antenna with a triangular shaped current density against the far-field approximation, and an incomplete cylindrical functions solution developed by Lee. Solution for E and H involves taking derivatives of A. Complications that arise from numerical techniques dictate that numerical differentiation should be performed before numerical integration. Follow on work on this topic will therefore have to focus on this detail before the actual VLSI chip architecture definition stage can be addressed.

This paper presents the active suspension system (ASS) control method using the adaptive cascade control scheme. The control scheme is implemented by two control loops, the inner control loop and outer control loop are designed respectively. The inner control loop uses the pole assignment method in order to move the poles of the original system to desired poles respect to the required performance of the suspension system. To design the controller in the inner loop, the model without the noise caused by the road profile and velocity of the car is used. The outer control loop then designed with an adaptive mechanism calculates the active control force to compensate for the vibrations caused by the road profile and velocity of the car. The control force is determined by the error between states of the reference model and states of suspension systems, the reference model is the model of closed loop with inner control loop without the noise. The simulation results implemented by using the practice date of the road profile show that the capability of oscillation decrease for ASS is quite efficient.

Artificial intelligence is not smart enough. This is why we are looking for complementary algorithms in order to increase the performance of machine learning and neural networks (NN). We have innovated an algorithm called learning focal point (LFP). This algorithm will help us increase the intelligence of machine learning and the NN. In this article, we will present the algorithm in detail, starting with the mathematical and theoretical principles, passing through the development and deployment in cloud docker containers, and ending with the security of its application programming interface (API). Finally, we are going to do a test in which we apply it in the case of using tin cans.

As part of the AFOSR Fast Algorithms Initiative, the project focused on the design of parallel algorithms and the related software design problems associated with multiprocessor systems. The research work was divided into two phases. The primary emphasis of the first phase was to study new algorithm ideas for solving the large numerical linear algebra problems associated with two and three dimensional elliptic P.D.E. problems. The work in the second phase of the research was directed toward understanding the software mechanisms needed to map these algorithms to existing parallel computers. In the following paragraphs we detail our work in both areas.

The U.S. Department of Defense has identified midair mishaps as a leading cause of loss of life, lost combat capability, and financial cost in fighter/attack aircraft operations. In the past, losses from midair mishaps were mitigated through training and ineffective warning systems. Now, an Automatic Air Collision Avoidance System (Auto ACAS) has been identified as a technology that could significantly reduce midair accidents. The Air Force Research Laboratory (AFRL) and Lockheed Martin are developing Auto ACAS for fighter aircraft operating in an air combat training environment. In this environment, emphasis is placed on providing protection for aircraft performing air combat maneuvers while eliminating nuisance. Auto ACAS is not a pilot advisory system or a de-confliction system; rather, Auto ACAS performs an automatic, aggressive maneuver to avoid collisions with other aircraft and returns control to the pilot as soon as the collision is prevented. The system coordinates maneuver trajectories between aircraft, determines which combination of maneuvers provides the best separation, and initiates maneuvers when a collision is imminent. The maneuvers incorporate pilot preferences and rules of the road where applicable and possible. Most maneuvers last only two to three seconds and occur well within the reaction time of an alert pilot.

The quasi-static antenna-design algorithm uses multipole basis function to model the general thick top load. A sequence of solutions converge in shape and Q. The absolute minimum Q-factor, 1.825, is obtained for a thick disk top load enclosed by a sphere. This is significantly smaller than the thin disk top load Q-factor 2.349 and previously derived thick-disk Q-factor 2.078. An analytic potential is derived for each multipole basis function. The capacitance and effective height is calculated from the potentials on the enclosing sphere. The impedance is computed with Computer Simulation Technology (CST) Microwave Studio. The impedance data is numerically fit to a dipole eigenmode equivalent circuit. The radiation resistance does not fit the expected omega2 frequency dependence (effective height). The error is an omega4 term that is explained by a capacitor approximated for the octupole eigenmode equivalent circuit. The quasistatic antenna design algorithm predicts the DC capacitance and the dipole eigenmode effective height. The octupole eigenmode increases the radiation resistance. The Q-factor, 1.77, is lower than expected. These results are compared to the spherical cap top load. The existence of an omega4 limits the accuracy of the theoretical limits in the Q values for antennas.

The quasi-static antenna-design algorithm uses multipole basis function to model the general thick top load. A sequence of solutions converge in shape and Q. The absolute minimum Q-factor, 1.825, is obtained for a thick disk top load enclosed by a sphere. This is significantly smaller than the thin disk top load Q-factor 2.349 and previously derived thick-disk Q-factor 2.078. An analytic potential is derived for each multipole basis function. The capacitance and effective height is calculated from the potentials on the enclosing sphere. The impedance is computed with Computer Simulation Technology (CST) Microwave Studio. The impedance data is numerically fit to a dipole eigenmode equivalent circuit. The radiation resistance does not fit the expected omega 2 frequency dependence (effective height). The error is an omega 4 term that is explained by a capacitor approximated for the octupole eigenmode equivalent circuit. The quasistatic antenna design algorithm predicts the DC capacitance and the dipole eigenmode effective height. The octupole eigenmode increases the radiation resistance. The Q-factor, 1.77, is lower than expected. These results are compared to the spherical cap top load. The existence of an omega 4 limits the accuracy of the theoretical limits in the Q values for antennas.

Parametric Design and Simulation Analysis of Electronic Equipment Structural Parts under the Background of Game Testing Algorithm

Information Platform Design and IOS Software Implementation of Sino-Japanese Cultural Exchange Based on the Hierarchical Fusion Algorithm of Internet Information

Intelligent Innovation Platform Design of Chinese Film and Television Music Based on Multi-Dimensional Information Fusion Algorithm

The Poisson equation occurs in many areas of science and engineering. Here we focus on its numerical solution for an equation in d dimensions. In particular we present a quantum algorithm and a scalable quantum circuit design which approximates the solution of the Poisson equation on a grid with error \varepsilon. We assume we are given a supersposition of function evaluations of the right hand side of the Poisson equation. The algorithm produces a quantum state encoding the solution. The number of quantum operations and the number of qubits used by the circuit is almost linear in d and polylog in \varepsilon^{-1}. We present quantum circuit modules together with performance guarantees which can be also used for other problems.

We propose a decentralized control synthesis procedure for stabilizing voltage and frequency in AC Islanded microGrids (ImGs), i.e. electrical networks composed of interconnected Distributed Generation Units (DGUs), power lines and loads. The presented approach enables Plug-and-Play (PnP) operations, meaning that DGUs can be arbitrarily added or removed without compromising the overall ImG stability. The main feature of our approach is that, differently from [Riverso et al., 2015], the proposed PnP design algorithm is line-independent. This implies that (i) the synthesis of each local controller does not require anymore the model of power lines connecting neighboring DGUs, and (ii) whenever a new DGU is plugged-in, DGUs physically connected to it do not have to retune their regulators. Theoretical results are validated by simulating in PSCAD the behavior of a 10-DGUs ImG.

Design and implementation of a cryptographic algorithm based on the AES advanced encryption standard for UHF RFID systems

Companion Website http://www.cs.princeton.edu/~wayne/kleinberg-tardos/ Algorithm Design introduces algorithms by looking at the real-world problems that motivate them. The book teaches students a range of design and analysis techniques for problems that arise in computing applications. The text encourages an understanding of the algorithm design process and an appreciation of the role of algorithms in the broader field of computer science. Chapter 1 Introduction: Some Representative Problems Chapter 2 Basics of Algorithm Analysis Chapter 3 Graphs Chapter 4 Greedy Algorithms Chapter 5 Divide and Conquer Chapter 6 Dynamic Programming Chapter 7 Network Flow Chapter 8 NP and Computational Intractability Chapter 9 PSPACE: A Class of Problems beyond NP Chapter 10 Extending the Limits of Tractability Chapter 11 Approximation Algorithms Chapter 12 Local Search Chapter 13 Randomized Algorithms

Book Source: Digital Library of India Item 2015.194589 dc.contributor.author: Ajeet Kumar dc.date.accessioned: 2015-07-08T04:44:25Z dc.date.available: 2015-07-08T04:44:25Z dc.date.digitalpublicationdate: 2005-09-27 dc.identifier.barcode: 1990010093373 dc.identifier.origpath: /rawdataupload/upload/0093/373 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/194589 dc.description.scannerno: 14 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 146 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Indian Institute Of Technology Kanpur dc.rights: Out_of_copyright dc.source.library: Indian Institute Of Technology Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Civil Engineering dc.title: Development Of A Standard Design Algorithm For Intze Tank

This is a novel research paper provides an optimal solution for object tracking using visual servoing control system with programmable gate array technology to realize the visual controller. The controller takes in account the robot dynamics to generate the joint torques directly for performing the tasks related to object tracking using visual servoing. Also, the notion of dynamic perceptibility provides the capability of the designed system to track desired objects employing direct visual servoing technique. This idea is assimilated in the suggested controller and realized in the programmable gate array. Additionally, this paper grants an ideal control framework for direct visual servoing robots that incorporates dynamic perceptibility features. With the aim of evaluating the proposed FPGA based architecture, the control algorithm is applied to Hardware-in-the-loop simulation (HIL) set up of three degrees of freedom rigid robotic manipulator with three links. Furthermore, different investigations are performed to demonstrate the behavior of the proposed system when a trajectory adjacent to a singularity is attained.

Line plotting is the one of the basic operations in the scan conversion. Bresenham’s line drawing algorithm is an efficient and high popular algorithm utilized for this purpose. This algorithm starts from one end-point of the line to the other end-point by calculating one point at each step. As a result, the calculation time for all the points depends on the length of the line thereby the number of the total points presented. In this paper, we developed an approach to speed up the Bresenham algorithm by partitioning each line into number of segments, find the points belong to those segments and drawing them simultaneously to formulate the main line. As a result, the higher number of segments generated, the faster the points are calculated. By employing 32 cores in the Field Programmable Gate Array, a line of length 992 points is formulated in 0.31μs only. The complete system is implemented using Zybo board that contains the Xilinx Zynq-7000 chip (Z-7010).  

Line plotting is the one of the basic operations in the scan conversion. Bresenham’s line drawing algorithm is an efficient and high popular algorithm utilized for this purpose. This algorithm starts from one end-point of the line to the other end-point by calculating one point at each step. As a result, the calculation time for all the points depends on the length of the line thereby the number of the total points presented. In this paper, we developed an approach to speed up the Bresenham algorithm by partitioning each line into number of segments, find the points belong to those segments and drawing them simultaneously to formulate the main line. As a result, the higher number of segments generated, the faster the points are calculated. By employing 32 cores in the Field Programmable Gate Array, a line of length 992 points is formulated in 0.31μs only. The complete system is implemented using Zybo board that contains the Xilinx Zynq-7000 chip (Z-7010).  

Line plotting is the one of the basic operations in the scan conversion. Bresenham’s line drawing algorithm is an efficient and high popular algorithm utilized for this purpose. This algorithm starts from one end-point of the line to the other end-point by calculating one point at each step. As a result, the calculation time for all the points depends on the length of the line thereby the number of the total points presented. In this paper, we developed an approach to speed up the Bresenham algorithm by partitioning each line into number of segments, find the points belong to those segments and drawing them simultaneously to formulate the main line. As a result, the higher number of segments generated, the faster the points are calculated. By employing 32 cores in the Field Programmable Gate Array, a line of length 992 points is formulated in 0.31μs only. The complete system is implemented using Zybo board that contains the Xilinx Zynq-7000 chip (Z-7010).  

Book Source: Digital Library of India Item 2015.192825 dc.contributor.author: Vikas Saxena dc.date.accessioned: 2015-07-08T01:41:34Z dc.date.available: 2015-07-08T01:41:34Z dc.date.digitalpublicationdate: 2005-08-20 dc.identifier.barcode: 1990010091216 dc.identifier.origpath: /rawdataupload/upload/0091/216 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/192825 dc.description.scannerno: 14 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 105 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Indian Institute Of Technology Kanpur dc.rights: Out_of_copyright dc.source.library: Indian Institute Of Technology Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Optimal Design Of Car Suspension System Using Genetic Algorithm

Motivated by the recently launched mobile data trading markets (e.g., China Mobile Hong Kong's 2nd exChange Market), in this paper we study the mobile data trading problem under the future data demand uncertainty. We introduce a brokerage-based market, where sellers and buyers propose their selling and buying quantities, respectively, to the trading platform that matches the market supply and demand. To understand the users' realistic trading behaviors, a prospect theory (PT) model from behavioral economics is proposed, which includes the widely adopted expected utility theory (EUT) as a special case. Although the PT modeling leads to a challenging non-convex optimization problem, the optimal solution can be characterized by exploiting the unimodal structure of the objective function. Building upon our analysis, we design an algorithm to help estimate the user's risk preference and provide trading recommendations dynamically, considering the latest market and usage information. It is shown in our simulation that the risk preferences have a significant impact on the user's decision and outcome: a risk-averse dominant user can guarantee a higher minimum profit in the trading, while a risk-seeking dominant user can achieve a higher maximum profit. By comparing with the EUT benchmark, it is shown that a PT user with a low reference point is more willing to buy mobile data. Moreover, when the probability of high future data demand is low, a PT user is more willing to buy mobile data due to the probability distortion comparing with an EUT user.

Motivated by the recently launched mobile data trading markets (e.g., China Mobile Hong Kong's 2nd exChange Market), in this paper we study the mobile data trading problem under the future data demand uncertainty. We introduce a brokerage-based market, where sellers and buyers propose their selling and buying quantities, respectively, to the trading platform that matches the market supply and demand. To understand the users' realistic trading behaviors, a prospect theory (PT) model from behavioral economics is proposed, which includes the widely adopted expected utility theory (EUT) as a special case. Although the PT modeling leads to a challenging non-convex optimization problem, the optimal solution can be characterized by exploiting the unimodal structure of the objective function. Building upon our analysis, we design an algorithm to help estimate the user's risk preference and provide trading recommendations dynamically, considering the latest market and usage information. It is shown in our simulation that the risk preferences have a significant impact on the user's decision and outcome: a risk-averse dominant user can guarantee a higher minimum profit in the trading, while a risk-seeking dominant user can achieve a higher maximum profit. By comparing with the EUT benchmark, it is shown that a PT user with a low reference point is more willing to buy mobile data. Moreover, when the probability of high future data demand is low, a PT user is more willing to buy mobile data due to the probability distortion comparing with an EUT user.

In this paper a pipelined architecture of a high speed network security processor (NSP) for SSL,TLS protocol is implemented on a system on chip (SOC) where hardware information of all encryption, hashing and key exchange algorithms are stored in flash memory in terms of bit files, in contrary to related works where all are actually implemented in hardware. The NSP finds applications in e-commerce, virtual private network (VPN) and in other fields that require data confidentiality. The motivation of the present work is to dynamically execute applications with stipulated throughput within budgeted hardware resource and power. A preferential algorithm choosing an appropriate cipher suite is proposed, which is based on Efficient System Index (ESI) budget comprising of power, throughput and resource given by the user. The bit files of the chosen security algorithms are downloaded from the flash memory to the partial region of field programmable gate array (FPGA). The proposed SOC controls data communication between an application running in a system through a PCI and the Ethernet interface of a network. Partial configuration feature is used in ISE14.4 suite with ZYNQ 7z020-clg484 FPGA platform. The performances

The uncapacitated facility location has always been an important problem due to its connection to operational research and infrastructure planning. Byrka obtained an algorithm that is parametrized by $\gamma$ and proved that it is optimal when $\gamma>1.6774$. He also proved that the algorithm achieved an approximation ratio of 1.50. A later work by Shi Li achieved an approximation factor of 1.488. In this research, we studied these algorithms and several related works. Although we didn't improve upon the algorithm of Shi Li, our work did provide some insight into the problem. We also reframed the problem as a vector game, which provided a framework to design balanced algorithms for this problem.

This paper presents the development of a new algorithm for Gaussian based color image enhancement system. The algorithm has been designed into architecture suitable for FPGA/ASIC implementation. The color image enhancement is achieved by first convolving an original image with a Gaussian kernel since Gaussian distribution is a point spread function which smoothen the image. Further, logarithm-domain processing and gain/offset corrections are employed in order to enhance and translate pixels into the display range of 0 to 255. The proposed algorithm not only provides better dynamic range compression and color rendition effect but also achieves color constancy in an image. The design exploits high degrees of pipelining and parallel processing to achieve real time performance. The design has been realized by RTL compliant Verilog coding and fits into a single FPGA with a gate count utilization of 321,804. The proposed method is implemented using Xilinx Virtex-II Pro XC2VP40-7FF1148 FPGA device and is capable of processing high resolution color motion pictures of sizes of up to 1600x1200 pixels at the real time video rate of 116 frames per second. This shows that the proposed design would work for not only still images but also for high resolution video sequences.

The Thalmann Exponential-Linear Decompression Algorithm (EL-DCA) was developed with the VVal-18 and HVal-21 parameter sets at Navy Experimental Diving Unit (NEDU) to produce 0.7 atmospheres absolute (ata) constant PO2-in-N2 and 0.7 ata constant PO2-in-He decompression tables. The original EL-DCA was extensively modified at NEDU to develop MK 16 MOD 1 N2-O2 and He-O2 decompression tables and Submarine Rescue and Diving Recompression System Operator/Tender decompression tables. The EL-DCA was further modified and used with a modified VVal-18 parameter set, designated VVal-18M, to produce an integrated set of air diving decompression tables for Revision 6 of the U.S. Navy Diving Manual. This report describes the design of the EL-DCA software that was used to produce the integrated air decompression tables and documents the software modifications made since publication of Thalmann's original reports.

The Thalmann Exponential-Linear Decompression Algorithm (EL-DCA) was developed with the VVal-18 and HVal-21 parameter sets at Navy Experimental Diving Unit (NEDU) to produce 0.7 atmospheres absolute (ata) constant PO2-in-N2 and 0.7 ata constant PO2-in-He decompression tables. The original EL-DCA was extensively modified at NEDU to develop MK 16 MOD 1 N2-O2 and He-O2 decompression tables and Submarine Rescue and Diving Recompression System Operator/Tender decompression tables. The EL-DCA was further modified and used with a modified VVal-18 parameter set, designated VVal-18M, to produce an integrated set of air diving decompression tables for Revision 6 of the U.S. Navy Diving Manual. This report describes the design of the EL-DCA software that was used to produce the integrated air decompression tables and documents the software modifications made since publication of Thalmann's original reports.

Book Source: Digital Library of India Item 2015.191771 dc.contributor.author: Vikas Saxena dc.date.accessioned: 2015-07-08T01:10:08Z dc.date.available: 2015-07-08T01:10:08Z dc.date.digitalpublicationdate: 2005-08-20 dc.identifier.barcode: 1990010090258 dc.identifier.origpath: /rawdataupload/upload/0090/258 dc.identifier.copyno: 1 dc.identifier.uri: http://www.new.dli.ernet.in/handle/2015/191771 dc.description.scannerno: 14 dc.description.scanningcentre: IIIT, Allahabad dc.description.main: 1 dc.description.tagged: 0 dc.description.totalpages: 104 dc.format.mimetype: application/pdf dc.language.iso: English dc.publisher: Indian Institute Of Technology Kanpur dc.rights: Out_of_copyright dc.source.library: Indian Institute Of Technology Kanpur dc.subject.classification: Technology dc.subject.classification: Engineering. Technology In General dc.subject.classification: Mechanical Engineering In General. Nuclear Technology. Electrical Engineering. Machinery dc.title: Optimal Design Of Car Suspension System Using Genetic Algorithm

The United States Air Force (USAF) continues to have a need for assured access to space. In addition to flexible and responsive spacelift, a reduction in the cost per launch of space launch vehicles is also desirable. For this purpose, an investigation of the design optimization of space launch vehicles has been conducted. Using a suite of custom codes, the performance aspects of an entire space launch vehicle were analyzed. A genetic algorithm (GA) was employed to optimize the design of the space launch vehicle. A cost model was incorporated into the optimization process with the goal of minimizing the overall vehicle cost. The other goals of the design optimization included obtaining the proper altitude and velocity to achieve a low-Earth orbit. Specific mission parameters that are particular to USAF space endeavors were specified at the start of the design optimization process. Solid propellant motors, liquid fueled rockets, and air-launched systems in various configurations provided the propulsion systems for two, three and four-stage launch vehicles. Mass properties models, an aerodynamics model, and a six-degree-of-freedom (6DOF) flight dynamics simulator were all used to model the system. The results show the feasibility of this method in designing launch vehicles that meet mission requirements. Comparisons to existing real world systems provide the validation for the physical system models. However, the ability to obtain a truly minimized cost was elusive. The cost model uses an industry standard approach, however, validation of this portion of the model was challenging due to the proprietary nature of cost figures and due to the dependence of many existing systems on surplus hardware.

In a previous paper, the author described a technique for designing an observer test in an iterative manner. In field tests to compare the observability of combat vehicles, the test designer must select the optimum number of observation opportunities to balance collecting enough data to draw valid conclusions against the high cost of supporting vehicles and personnel at a test site. The test designer can select the number of observations, N, so that a given experimental difference in detectability will be statistically significant at a given confidence level. Alternatively, the test designer can select N so that the probability of rejecting a given underlying difference in detectability is less than a given amount. The test designer, however, generally lacks key parameters for the efficient design of the test. Namely, the designer lacks the detection probabilities of the vehicles at each range. The standard deviation of the difference in detection probability depends upon the detection probability itself. Therefore, the test designer must select the number of observations for each range based upon the conservative assumption that the probabilities are near 50%, the probability for the maximum standard deviation. In the previous paper, an iterative technique of test design was described. In this technique, the test designer modifies the test matrix as the test progresses. Early test results yield estimates of the probability of detection for each vehicle at each range. Based on these estimates, the test designer reallocates the number of observations among the ranges, improving the efficiency of the test. In this paper, the author presents an algorithm to implement this iterative technique.

The general goal of this project is the application of concepts from topology and sheaf theory to better explain and systematize some of the intricate aspects of algorithms. The basic technique is the adoption of a topological view of data structures, in contrast to the normal algebraic view. In this project, this approach was extended to parsing algorithms for context- free grammars. This extension also yielded more insight into what a topological view of data structures entails, e.g., a connection to the object-oriented view of datatypes.

The super-lift technique is an exceptional contribution to DC–DC conversion technology. A replacement approach of symmetrical super-lift multilevel inverter (SLMLI) DC/AC technology is proposed with a reduced number of elements compared with the traditional multilevel inverter. In this method, the firefly algorithm conveys a leading task for the SLMLI topology for solar-photovoltaic applications. It generates low distortion output and consumes the harmonic band of the fast Fourier transform framework by the employment of the proposed algorithm. The simulation circuit for 15 levels output uses single switch super-lift inverter feed with different kinds of load (R, RL and RLE) conditions. The power quality is improved in SLMLI with minimized harmonics underneath the various modulation indices while varied from 0.1 up to 0.8. The circuit is designed in a field programmable gate array, which includes the firefly rule to help the multilevel output, to reduce the lower order harmonics and to find the best switching angle. As a result, the minimum total harmonic distortion from the simulation and hardware circuit is achieved. Due to the absence of bulky switches, inductor and filter elements expose the effectiveness of the proposed system.

Multidisciplinary design, analysis, and optimization using a genetic algorithm is being developed at the National Aeronautics and Space Administration Dryden Flight Research Center (Edwards, California) to automate analysis and design process by leveraging existing tools to enable true multidisciplinary optimization in the preliminary design stage of subsonic, transonic, supersonic, and hypersonic aircraft. This is a promising technology, but faces many challenges in large-scale, real-world application. This report describes current approaches, recent results, and challenges for multidisciplinary design, analysis, and optimization as demonstrated by experience with the Ikhana fire pod design.!

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This article is from SpringerPlus , volume 3 . Abstract This paper proposes designing of Static Synchronous Series Compensator (SSSC) based damping controller to enhance the stability of a Single Machine Infinite Bus (SMIB) system by means of Invasive Weed Optimization (IWO) technique. Conventional PI controller is used as the SSSC damping controller which takes rotor speed deviation as the input. The damping controller parameters are tuned based on time integral of absolute error based cost function using IWO. Performance of IWO based controller is compared to that of Particle Swarm Optimization (PSO) based controller. Time domain based simulation results are presented and performance of the controllers under different loading conditions and fault scenarios is studied in order to illustrate the effectiveness of the IWO based design approach.

This article is from Bioinformatics , volume 30 . Abstract Motivation: Structure-based computational protein design (SCPR) is an important topic in protein engineering. Under the assumption of a rigid backbone and a finite set of discrete conformations of side-chains, various methods have been proposed to address this problem. A popular method is to combine the dead-end elimination (DEE) and A* tree search algorithms, which provably finds the global minimum energy conformation (GMEC) solution.Results: In this article, we improve the efficiency of computing A* heuristic functions for protein design and propose a variant of A* algorithm in which the search process can be performed on a single GPU in a massively parallel fashion. In addition, we make some efforts to address the memory exceeding problem in A* search. As a result, our enhancements can achieve a significant speedup of the A*-based protein design algorithm by four orders of magnitude on large-scale test data through pre-computation and parallelization, while still maintaining an acceptable memory overhead. We also show that our parallel A* search algorithm could be successfully combined with iMinDEE, a state-of-the-art DEE criterion, for rotamer pruning to further improve SCPR with the consideration of continuous side-chain flexibility.Availability: Our software is available and distributed open-source under the GNU Lesser General License Version 2.1 (GNU, February 1999). The source code can be downloaded from http://www.cs.duke.edu/donaldlab/osprey.php or http://iiis.tsinghua.edu.cn/∼compbio/software.html.Contact:[email protected] .cnSupplementary information:Supplementary data are available at Bioinformatics online.

A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed where the maximum load shifting weightage was set up to 30% to reflect the consumers’ effort towards energy efficiency (EE) program. The previously proposed TOU design was identified to be a suitable structure that can promote balancing of EE and demand response (DR) program effort in most consumers' houses category in Malaysia.

A price-based program through a time of use tariff (TOU) program is one of the initiatives to offer sufficient benefit for both consumers and generations sides. However, without any strategy for implementing optimal load management, a new tariff design structure will lead to the miss perception by electricity consumers. Therefore, this study offers an investigation toward appropriate TOU tariff design to reflect load profiles. Concurrently, the ant colony optimization (ACO) algorithm was proposed to deal with the load shifting strategy to determine the best load profiles and reducing the consumers’ electricity cost. The sample load profiles data is obtained from various residential houses, such as single-story, double-story, semi-D, apartment, and bungalow houses. The significant comparison between baseline flat tariffs to several TOU tariffs has shown an improvement in the percentage of cost saving for approximately 7 to 40%. Furthermore, the identified load management was observed where the maximum load shifting weightage was set up to 30% to reflect the consumers’ effort towards energy efficiency (EE) program. The previously proposed TOU design was identified to be a suitable structure that can promote balancing of EE and demand response (DR) program effort in most consumers' houses category in Malaysia.

In x-ray coherent scatter tomography, tomographic measurements of the forward scatter distribution are used to infer scatter densities within a volume. A radiopaque 2D pattern placed between the object and the detector array enables the disambiguation between different scatter events. The use of a fan beam source illumination to speed up data acquisition relative to a pencil beam presents computational challenges. To facilitate the use of iterative algorithms based on a penalized Poisson log-likelihood function, efficient computational implementation of the forward and backward models are needed. Our proposed implementation exploits physical symmetries and structural properties of the system and suggests a joint system-algorithm design, where the system design choices are influenced by computational considerations, and in turn lead to reduced reconstruction time. Computational-time speedups of approximately 146 and 32 are achieved in the computation of the forward and backward models, respectively. Results validating the forward model and reconstruction algorithm are presented on simulated analytic and Monte Carlo data.

In x-ray coherent scatter tomography, tomographic measurements of the forward scatter distribution are used to infer scatter densities within a volume. A radiopaque 2D pattern placed between the object and the detector array enables the disambiguation between different scatter events. The use of a fan beam source illumination to speed up data acquisition relative to a pencil beam presents computational challenges. To facilitate the use of iterative algorithms based on a penalized Poisson log-likelihood function, efficient computational implementation of the forward and backward models are needed. Our proposed implementation exploits physical symmetries and structural properties of the system and suggests a joint system-algorithm design, where the system design choices are influenced by computational considerations, and in turn lead to reduced reconstruction time. Computational-time speedups of approximately 146 and 32 are achieved in the computation of the forward and backward models, respectively. Results validating the forward model and reconstruction algorithm are presented on simulated analytic and Monte Carlo data.

In this paper we study the problem of designing a distributed graph visualization algorithm for large graphs. The algorithm must be simple to implement and the computing infrastructure must not require major hardware or software investments. We design, implement, and experiment a force-directed algorithm in Giraph, a popular open source framework for distributed computing, based on a vertex-centric design paradigm. The algorithm is tested both on real and artificial graphs with up to million edges, by using a rather inexpensive PaaS (Platform as a Service) infrastructure of Amazon. The experiments show the scalability and effectiveness of our technique when compared to a centralized implementation of the same force-directed model. We show that graphs with about one million edges can be drawn in less than 8 minutes, by spending about 1\$ per drawing in the cloud computing infrastructure.

This paper presents the impact of introducing a two-controller on the linearized autonomous underwater vehicle (AUV) for vertical motion control. These controllers are presented to overcome the sensor noise of the AUV control model that effect on the tolerance and stability of the depth motion control. Linear quadratic Gaussian (LQG) controller is cascaded with AUV model to adapt the tolerance and the stability of the system and compared with FOPID established by the improved whale optimization algorithm (IWOA) to identify which controlling method can make the system more harmonize and tolerable. The developed algorithm is based on improving the original WOA by reshaping a specific detail on WOA to earn a warranty that the new IWOA will have values for the update position lower than the identified lower-bound (LB), and upper-bound (UB). Furthermore, the algorithm is examined by a set of test functions that include (unimodal, multimodal and fixed dimension multimodal functions). The privileges of applying IWOA are reducing the executing time and obtaining the semi-optimal objective function as compared with the original WOA algorithm and other popular swarm-intelligence optimization algorithms.

Presentation given at DWeb Camp 2024, in Navarro, California. What does the right-to-repair movement have to do with AI and algorithms? What would it look like if we could “repair” trust relationships in the context of the way we interact with algorithms? What does meaningful voice and responsibility mean in the context of AI innovation?  What do algorithmic reparation and algorithmic justice have to do with AI governance and innovation? This panel session will engage with these questions through short remarks and an interactive discussion. In fact, effective July 1, 2024, CA law requires manufacturers of some electronic or appliance products to make available sufficient service literature and functional parts to affect the repair of a product for at least three years after the date a product model or type was manufactured. Building on this effort we’ll explore why might everyday people want to “repair” physical or digital products that leverage AI algorithms and what are key considerations for the safety and evaluations of AI products. We’ll engage with the audience in an interactive discussion about the relationship between the right-to-repair movement, rebuilding trust, transparency, and democratic design.  The conversation will include: Welcome and introductions Icebreaker activity Motivation Panel Discussion, Remarks, and Q&A Reflections and next steps

Presentation given at DWeb Camp 2024, in Navarro, California. What does the right-to-repair movement have to do with AI and algorithms? What would it look like if we could “repair” trust relationships in the context of the way we interact with algorithms? What does meaningful voice and responsibility mean in the context of AI innovation?  What do algorithmic reparation and algorithmic justice have to do with AI governance and innovation? This panel session will engage with these questions through short remarks and an interactive discussion. In fact, effective July 1, 2024, CA law requires manufacturers of some electronic or appliance products to make available sufficient service literature and functional parts to affect the repair of a product for at least three years after the date a product model or type was manufactured. Building on this effort we’ll explore why might everyday people want to “repair” physical or digital products that leverage AI algorithms and what are key considerations for the safety and evaluations of AI products. We’ll engage with the audience in an interactive discussion about the relationship between the right-to-repair movement, rebuilding trust, transparency, and democratic design.  The conversation will include: Welcome and introductions Icebreaker activity Motivation Panel Discussion, Remarks, and Q&A Reflections and next steps

Presentation given at DWeb Camp 2024, in Navarro, California. What does the right-to-repair movement have to do with AI and algorithms? What would it look like if we could “repair” trust relationships in the context of the way we interact with algorithms? What does meaningful voice and responsibility mean in the context of AI innovation?  What do algorithmic reparation and algorithmic justice have to do with AI governance and innovation? This panel session will engage with these questions through short remarks and an interactive discussion. In fact, effective July 1, 2024, CA law requires manufacturers of some electronic or appliance products to make available sufficient service literature and functional parts to affect the repair of a product for at least three years after the date a product model or type was manufactured. Building on this effort we’ll explore why might everyday people want to “repair” physical or digital products that leverage AI algorithms and what are key considerations for the safety and evaluations of AI products. We’ll engage with the audience in an interactive discussion about the relationship between the right-to-repair movement, rebuilding trust, transparency, and democratic design.  The conversation will include: Welcome and introductions Icebreaker activity Motivation Panel Discussion, Remarks, and Q&A Reflections and next steps