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检索条件"主题词=Software Algorithms"

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Examining the Potential of Machine Learning in Reducing Prescription Drug Costs

Examining the Potential of Machine Learning in Reducing Pres...

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International Conference on Computing and Networking Technology (ICCNT)

作者： Sachin C. Patil Sairam Madasu Krishna J Rolla Ketan Gupta N. Yuvaraj Senior Software Engineer USA Senior Cloud Software Engineer Microsoft Charlotte North Carolina USA Department of Information Technology University of The Cumberlands Williamsburg KY USA Computer Science and Engineering Sri Shakthi Institute of Engineering and Technology Coimbatore Tamil Nadu India

ISBN: (数字)9798350370249

ISBN: (纸本)9798350370270

The ability of the system to gain knowledge for lowering prescription drug prices has been increasingly studied in recent years. Gadget-gaining knowledge is a branch of synthetic intelligence that enables machines and PC systems to enhance their overall performance on specific obligations by means of mastering beyond facts. Within the context of prescription drug costs, gadget learning may be used to find patterns and developments in drug pricing and usage, decide disparities in getting admission to and usage, and have a look at pricing strategies hired by pharmaceutical businesses. The use of gadgets to gain knowledge can help to discover elements using prescription drug costs, inclusive of the pricing and utilization of individual capsules or the relationships among drug costs and effects. Moreover, AI-primarily based algorithms may be used to use massive datasets in an effort to apprehend the role that healthcare vendors, insurers, and pharmaceutical organizations have on prescription drug ***, AI-based total fashions can also be used to become aware of and degree cost elements associated with specific drug combinations. Sooner or later, machine studying may be leveraged to examine the effects of policy changes and healthcare reforms on prescription drug costs and to become aware of goal populations with high prescription drug prices. By combining gadget studying with conventional healthcare price analysis gear, researchers can gain insights into the drivers of prescription drug charges and make public coverage decisions. In sum, a device gaining knowledge can be a powerful tool.

关键词： Drugs Costs Accuracy Machine learning algorithms software algorithms Pricing Medical services Organizations Machine learning software

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Nonlinear Cross-Systems of Numerical Simulation of Diffusion Processes

Nonlinear Cross-Systems of Numerical Simulation of Diffusion...

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International Conference on Information Science and Communications Technologies (ICISCT)

作者： Beknazarova Saida Safibullaevna Abdurakhmanov Kaxar Patahovich Sadullaeva Shahlo Azimbayevna Beknazarov Kamoliddin Tursunnulatovich Tashkent Uzbekistan doctor of physical -mathematics science professor of Physic of Tashkent University of Information Technologies named after Muhammad Al-Khwarizrni Tashkent Uzbekistan doctor of physical - mathematics science vice rector of Tashkent University of Information Technologies named after Muhammad Al-Khwarizmi Tashkent Uzbekistan Journalism and Mass Communications University of Journalism and Mass Communications of the Republic of Uzbekistan Tashkent Uzbekistan

ISBN: (数字)9781728199696

ISBN: (纸本)9781728199702

In the article describes the methods of numerical simulation of mutual reaction-diffusion systems with double nonlinearity in multicomponent media, development of software packages. To obtain estimates of the free boundary for systems of reaction-diffusion with double nonlinearity. Development of numerical schemes of algorithms and software complexes for these problems in the multidimensional case. To investigate the properties of the finite velocity of perturbation propagation and spatial localization for a nonlinear model of polytropic filtration with double nonlinearity. To investigate the asymptotics of self-similar polytropic filtration systems in two-component media with a source. The object of research is the qualitative properties of solutions of polytropical filtration systems in a two-component medium with non-local boundary conditions. In the article uses the nonlinear splitting algorithm, the method of reference equations, the method of comparing solutions, iterative numerical methods, methods of variable directions and runs.

关键词： Filtration software packages Perturbation methods software algorithms Media Numerical simulation Boundary conditions

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Mining Association Rules in R Using the Package RKEEL

Mining Association Rules in R Using the Package RKEEL

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IEEE International Conference on Fuzzy Systems

作者： Oliver Sánchez Jose M. Moyano Luciano Sánchez Jesús Alcalá-Fdez Dpt. of Computer Science and A.I. University of Granada 18071 Granada Spain Dpt. of Computer Science and N. A. University of Cordoba 14071 Cordoba Spain Dpt. of Computer Science University of Oviedo 33204 Gijon Spain Dpt. of Computer Science and A.I. University of Granada 18071 Granada Spain

ISBN: (纸本)9781509060351

The discovery of fuzzy associations comprises a collection of data mining methods used to extract knowledge from large data sets. Although there is an extensive catalog of specialized algorithms that cover different aspects of the problem, the most recent approaches are not yet packaged in mainstream software environments. This makes it difficult to incorporate novel association rules methods to the data mining workflow. In this paper an extension of the RKEEL package is described that allows calling from the programming language R to those association rules methods contained in KEEL, which is one of the most comprehensive open source software suites. The potential of the proposed tool is illustrated through a case study comprising seven real-world datasets.

关键词： Data mining Computer science Electronic mail Measurement software algorithms Open source software Tools

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Exploring the Impact of Grouping Strategies on Cooperative Co-evolutionary algorithms for Solving the Advertising Budget Allocation Problem

Exploring the Impact of Grouping Strategies on Cooperative C...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Yongfeng Gu Yuxuan Zhou Hao Ding Fan Jia Shiping Wang Ant Group Hangzhou Zhejiang China

The large-scale optimization problem (LSOP), which evolves high-dimensional decision variables, exists in many industrial situations. With the increasing number of decision variables, the performance of traditional evolutionary algorithms deteriorates obviously due to the huge search space and sophisticated optimal hyperplane. To solve the LSOP, many improved cooperative co-evolutionary algorithms are proposed, whose main idea is to group the decision variables into sub-components and evolve each component alternately to obtain the global optimal solution. The grouping strategy plays a core role in these algorithms, however, most of the comparative studies are conducted in experimental environments and a rare of them are conducted in real-world applications. In this paper, to explore the performance of different strategies, we compare four popular grouping strategies in a real-world problem, i.e., the Advertising Budget Allocation Problem. Experiments show that the grouping strategies indeed improve the performance of evolutionary algorithms and Differential Grouping performs effectively and efficiently in our experiment.

关键词： software algorithms Evolutionary computation software quality software reliability Resource management Security Advertising

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Mining Library Migration Graphs

Mining Library Migration Graphs

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Working Conference on Reverse Engineering

作者： Cédric Teyton Jean-Rémy Falleri Xavier Blanc LaBRI UMR 5800 University of Bordeaux Talence France

software systems intensively depend on external libraries, chosen at conception time. However, relevance of any library irremediably changes during projects and/or library life cycle. As a consequence, projects developers must periodically reconsider the libraries they depend on, and must think about library migration. When they want to migrate their libraries, they then have to identify candidate libraries that offer similar facilities and thus can substitute to each other. They also have to compare candidates to choose the one that best fits their needs. Finding a relevant library replacement is a well known tedious and time-consuming task. In this paper, we propose an approach that identifies sets of similar libraries and that produces what we call library migration graphs that show how existing projects have performed migrations among them. These graphs, constructed from the observation of a large number of software projects, ease the discovery and selection of library replacements.

关键词： Libraries software Google Manuals Data mining software algorithms Search engines

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A Lightweight Decision-Tree Algorithm for detecting DDoS flooding attacks

A Lightweight Decision-Tree Algorithm for detecting DDoS flo...

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IEEE International Conference on software Quality, Reliability and Security Companion (QRS-C)

作者： Godswill Lucky Fred Jjunju Alan Marshall University of Liverpool Liverpool United Kingdom

ISBN: (数字)9781728189154

ISBN: (纸本)9781728189161

The development of an accurate, efficient and lightweight distributed solution for the detection and prevention of DDoS attacks provides network designers with new options to monitor and secure networks according to their strategic needs. Here we present, a lightweight architecture that distinguishes attack network flows from normal traffic flows with a detection accuracy of over 99.9%. The architecture presented is optimised for deployment in low-cost environments for efficient, rapid detection and prevention of DDoS attacks. To achieve a computationally efficiency architecture, the system was trained with a minimal number of features using a robust features selection approach and validated against the CIC 2017 and 2019 datasets. Analysis of the design is presented and results shows that the new architecture uses just 7% processing power of the detection system and provides no additional overhead to the monitored network.

关键词： software algorithms Computer architecture software quality Denial-of-service attack software reliability Computer crime Monitoring

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A recursive method for traffic management through a complex path network

A recursive method for traffic management through a complex ...

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Simulation Winter Conference

作者： M. Norman Brooks-PRI Automation Planning and Logistics Solutions Salt Lake UT USA

Many simulation models contain one or more transport systems where some type of vehicle, perhaps an AGV, a fork truck, a shuttle, or a human being, travel along predefined paths. Locations along the paths may specify where loads carried by the vehicle transfer to or from it, where some activity takes place requiring the vehicle's presence, or where vehicle routing logic executes. This paper focuses on the last topic, the routing of vehicles along a path system where alternate paths exist and path selection is determined at so called "routing nodes" based on a dynamic analysis of traffic congestion along each possible route towards some destination. Other routing nodes further along each path present more combinations of possible interim paths. A recursive search algorithm is presented to iteratively evaluate each possible route when a vehicle encounters a routing node. The vehicle is directed along a path with the least overall congestion towards its destination. A sample model demonstrating this algorithm implemented in the AutoMod software is used for illustration. Other simulation products may have the features to support this type of vehicle routing control algorithm.

关键词： Telecommunication traffic Routing Automatic control Space vehicles software algorithms Space exploration Round robin Traffic control Automation Path planning

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Towards a Mobile Robot Localization Benchmark with Challenging Sensordata in an Industrial Environment

Towards a Mobile Robot Localization Benchmark with Challengi...

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International Conference on Advanced Robotics (ICAR)

作者： Florian Spieß Jonas Friesslich Daniel Bluemm Fabio Mast Dmitrij Vinokour Samuel Kounev Tobias Kaupp Norbert Strobel University of Applied Sciences Wuerzburg-Schweinfurt Friedrich-Alexander-Universit&#x00E4 t Erlangen-N&#x00FC rnberg Faculty of Mathematics and Computer Science Julius-Maximilians-University of Wuerzburg Institute Digital Engineering (IDEE) University of Applied Sciences Wuerzburg-Schweinfurt Institute of Medical Engineering University of Applied Sciences Wuerzburg-Schweinfurt

ISBN: (数字)9781665436847

ISBN: (纸本)9781665436854

To arrive at a realistic assessment of localization methods in terms of their performance in an industrial environment under various challenging conditions, we provide a benchmark to evaluate algorithms both for individual components as well as multi-sensor systems. For several sensor types, including wheel odometry, RGB cameras, RGB-D cameras, and LIDAR, potential issues were identified. The accuracy of wheel odometry, for example, when there are bumps on the track. For each sensor type, we explicitly chose a track for the benchmark dataset containing situations where the sensor fails to provide adequate measurements. Based on the acquired sensor data, localization can be achieved either using a single sensor information or sensor fusion. To help evaluate the output of associated localization algorithms, we provide a software to evaluate a set of metrics as part of the paper. An example application of the benchmark with state-of-the-art algorithms for each sensor is also provided.

关键词： Location awareness Service robots software algorithms Wheels Benchmark testing Sensor fusion Robot sensing systems

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A Safe Vehicle Routing System based on Road Characteristics from Telematics Data

A Safe Vehicle Routing System based on Road Characteristics ...

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IEEE Annual International Computer software and Applications Conference (COMPSAC)

作者： Hiroshi Tei Tomoya Kawakami Yoshimi Kawamoto Graduate School of Engineering University of Fukui Fukui Japan

ISBN: (数字)9798350376968

ISBN: (纸本)9798350376975

In recent years, the rapid growth of the logistics and delivery industry has increased the demand for safe and efficient delivery planning. However, conventional navigation services do not take road and driver characteristics into account and recommend the same delivery route to every delivery person under the same settings. In this paper, the authors propose a safe and efficient delivery plan based on road characteristics by considering the risk and distance of each road segment estimated using telematics data. First, the proposed method uses clustering to determine the destinations to be handled by delivery personnel, and then uses a genetic algorithm to determine the route and order of delivery. The proposed method was simulated on two different road networks to evaluate its usefulness. The simulation results show that the proposed method can develop a delivery plan that satisfies the specific conditions and needs of delivery personnel and considers both safety and efficiency.

关键词： Roads Simulation Vehicle routing software algorithms Telematics software Safety

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Subjective Answer Grader using Semantic Similarity and Keyword Matching

Subjective Answer Grader using Semantic Similarity and Keywo...

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International Conference for Convergence of Technology (I2CT)

作者： Sanchit Kripalani Tejas Lipare Dipali Kadam Department of Computer Engineering Pune Institute of Computer Technology Pune India

ISBN: (数字)9798350394474

ISBN: (纸本)9798350394481

Subjective exams and tests have been a staple metric of student evaluation. These tests require students to give brief theoretical responses to the questions. Evaluation of subjective responses is based on the presence of certain facts, keywords, phrases that need to be mentioned. Traditional assessment of these tests requires an examiner to affirm the understanding of concepts by students through their answers. The human-dependant evaluation, however, is tedious, time consuming and is rarely impartial. The time constraints often mean that the examiner is unable to provide a detailed feedback to each and every student. This calls for the need to develop an objective automated grader system, which can investigate and analyze the student performances by considering different facets of learning based on semantic similarity. The enhanced BERT model, which has been fine-tuned, is utilized to capture the semantic characteristics found in the student’s response. In order to achieve this, the model compares the student’s response with the model answer and generates a model score based on the comparison. This model score is boosted through a keyword matching algorithm, which emphasizes the factual information contained within the student’s response. These final similarity scores are employed to offer comprehensive feedback that illuminates the specific areas in which the student’s comprehension may be lacking. Finally, the proposed approach is compared to other renowned algorithms like Cosine Similarity, Word Mover’s Distance, Paraphrase-mpnet, and Multi-qa-mpnet. The proposed system yields an experimental Mean Absolute Error (MAE) of 2.11, which is significantly better as compared to other algorithms.

关键词： Measurement Flowcharts software algorithms Semantics Taxonomy Prediction algorithms software

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