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2019 IEEE East-West Design and Test Symposium, EWDTS 2019

作者： Adamov, Alexander Carlsson, Anders Surmacz, Tomasz NioGuard Security Lab Kharkiv National University of Radio Electronics Kharkiv Ukraine Dep. of Computer Science Blekinge Institute of Technology Karlskrona Sweden Institute of Computer Engineering Control and Robotics Wroclaw University of Science and Technology Wroclaw Poland

ISBN: (纸本)9781728110035

This paper contains an analysis of the LockerGoga ransomware that was used in the range of targeted cyberattacks in the first half of 2019 against Norsk Hydra-A world top 5 aluminum manufacturer, as well as the US chemical enterprises Hexion, and Momentive-Those companies are only the tip of the iceberg that reported the attack to the public. The ransomware was executed by attackers from inside a corporate network to encrypt the data on enterprise servers and, thus, taking down the information control systems. The intruders asked for a ransom to release a master key and decryption tool that can be used to decrypt the affected files. The purpose of the analysis is to find out tactics and techniques used by the LockerGoga ransomware during the cryptolocker attack as well as an encryption model to answer the question if the encrypted files can be decrypted with or without paying a ransom. The scientific novelty of the paper lies in an analysis methodology that is based on various reverse engineering techniques such as multi-process debugging and using open source code of a cryptographic library to find out a ransomware encryption model. © 2019 IEEE.

关键词： Reverse engineering

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arXiv

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arXiv 2019年

作者： Zarei, Mohammad Reza Moosavi, Mohammad Reza Dep. of Computer Science and Engineering School of Electrical and Computer Engineering Shiraz University Shiraz Iran

The aim of the recommender systems is to provide relevant and potentially interesting information to each user. This is fulfilled by utilizing the already recorded tendencies of similar users or detecting items similar to interested items of the user. Challenges such as data sparsity and cold start problem are addressed in recent studies. Utilizing social information not only enhances the prediction accuracy but also tackles the data sparseness challenges. In this paper, we investigate the impact of using direct and indirect trust information in a memory-based collaborative filtering recommender system. An adaptive similarity measure is proposed and the contribution of social information is tuned using two learning schemes, greedy and gradient-based optimization. The results of the proposed method are compared with state-of-the-art memory-based and model-based CF approaches on two real-world datasets, Epinions and FilmTrust. The experiments show that our method is quite effective in designing an accurate and comprehensive recommender system. Copyright © 2019, The Authors. All rights reserved.

关键词： Recommender systems

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Prediction of Maize Grain Yield before Maturity Using Improved Temporal Height Estimates of Unmanned Aerial Systems

Plant Phenome Journal

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Plant Phenome Journal 2019年第1期2卷 1-15页

作者： Anderson, Steven L. Murray, Seth C. Malambo, Lonesome Ratcliff, Colby Popescu, Sorin Cope, Dale Chang, Anjin Jung, Jinha Thomasson, J. Alex Dep. of Biological and Agricultural Engineering Texas A&M Univ. College Station 77843 TX United States Dep. of Ecosystem Science and Management Texas A&M Univ. College Station 77843-2120 TX United States Dep. of Mechanical Engineering Texas A&M Univ. College Station 77843 TX United States Dep. of Soil and Crop Sciences Texas A&M Univ. College Station 77843-2474 TX United States School of Engineering and Computer Sciences Texas A&M Univ. Corpus Christi 78412 TX United States

Core Ideas UAS captured increased genetic variation compared with manual terminal height. There were small significant differences in ground filtering methods to extract plant structure. Higher resolution did not improve imagery informativeness with regard to plant height. Logistic function provides informative phenotypes for temporal maize growth. Correlation and prediction accuracy of grain yield increased by ∼20% with UAS heights. Weekly unmanned aerial system (UAS) imagery was collected over the College Station, TX, 2017 Genomes to Fields (G2F) hybrid trial, across three environmental stress treatments, using two UAS platforms. The high-altitude (120-m) fixed-wing platform increased the fraction of variation attributed to genetics and had highly repeatable (R > 60%) height estimates, increasing the genetic variance explained (10–40%) over traditional terminal plant height measurement (PHT_TRML ∼30%), as well as over the low-altitude rotary-wing UAS platform (10–20%). A logistic function reduced the dimensionality (>20 flights) of each UAS dataset to three parameters (inflection point, growth rate, and asymptote) and produced a more robust predictive model than indep.ndent flight dates, effectively summarizing (R² > 0.98) the UAS flight dates. The logistic model overcame the need to use specific flight dates when comparing different environments. The UAS height estimates (r = 0.36–0.48) doubled the correlations to grain yield in this G2F experiment compared with PHT_TRML (r = 0.23–0.28). Parameters of the logistical function achieved equivalent correlations (r = 0.30–0.46) to individual flight dates (r = 0.36–0.48), improving grain yield prediction by ∼400% (R² = 0.25–0.34) over PHT_TRML (R² = 0.06–0.08). Incorporating other UAS-derived parameters beyond plant height may allow yield to be accurately predicted before maturity, speeding breeding programs. A new public R function to generate ESRI shapefi

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Synthesis of a Single-Channel Device for Receiving and Primary Signal Processing under Conditions of Structural-Parametric A priori Uncertainty

Synthesis of a Single-Channel Device for Receiving and Prima...

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Ukrainian Microwave Week (UkrMW), IEEE

作者： Mykola Kaliuzhnyi Valerii Semenets Valerii Orlenko Serhii Galkin Qiang Guo Yu Zheng Problem research laboratory Kharkiv National University of Radio Electronics Kharkiv Ukraine Kharkiv National University of Radio Electronics Kharkiv Ukraine Ukrainian-Chineese Cooperation Dep. Kharkiv National University of Radio Electronics Kharkiv Ukraine Computer Science and Intellectual Department National Technical University «KhPI» Kharkiv Ukraine College of Information and Telecommunication Enginttring Harbin Engineering University) Harbin P.R. China Department Micro- and Nano-Electronics Qingdao University Qingdao P.R. China

ISBN: (纸本)9798350331530

The synthesis of a single-channel broadband device for receiving and primary processing of radio signals that employs the pulse compression technique is presented given the case where its input signals are received in conditions of their structural-parametric a priori uncertainty. The synthesis was carried out based on the mathematical apparatus of the theory of statistical decisions and on the discrete signal representation in the time-frequency domain. The results of prototyping and experimental studies concerning the receiver that was synthesized in accordance with the structural-functional diagram on the basis of spectrum analyzer with pulse compression technique (SAPCT) are briefly presented. An experiment is described that allowed us to verify the possibilities of obtaining the Fourier transform with regard to the elements of input signals, as well as possibilities of detecting and measuring the frequency-time parameters of these signals. These parameters allow us to figure out the structure and characteristics of input signal bursts [6].

关键词： Microwave measurement Time-frequency analysis Uncertainty Fourier transforms Receivers Microwave devices Signal processing

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High-Performance Computing (HPC) design to improve the quality of Introduction of Parallel Computing lectures 1

High-Performance Computing (HPC) design to improve the quali...

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1st International Conference on Advanced engineering and Technology, ICATECH 2018

作者： Alfianto, E. Sa'Diyah, A. Rusydi, F. Puspitasari, I. Dep. of Computer System Institut Teknologi Adhi Tama Surabaya Jl Arif Rachman Hakim 100 Surabaya60111 Indonesia Dep. of Marine Engineering Politeknik Perkapalan Negeri Surabaya Kampus ITS-Sukolilo Jl Jalan Teknik Kimia Surabaya60117 Indonesia Theoretical Physics Research Group Dep. of Physics Fac. of Science and Technology Airlangga University Jl. Mulyorejo Surabaya60115 Indonesia Dep. of the Information System Fac. of Science and Technology Airlangga University Jl. Mulyorejo Surabaya60115 Indonesia

High-Performance Computing (HPC) has been created to improve the quality of Pengantar Komputasi Parallel lectures. HPC consists of two PCs with AMD Ryzen 7 processor connected by high-speed LAN. HPC is used to solve problems that students can't practice Parallel Computing because the computer used is not adequate. So it takes a machine that can used together that has many processors, so the problems encountered are resolved. The results obtained, participants can use more than four processors to solve tree problems directly. © 2019 IOP Publishing Ltd. All rights reserved.

关键词： Parallel processing systems

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G-gene: A gene alignment method for online partial stroke gestures recognition

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Proceedings of the ACM on Human-computer Interaction 2018年第EICS期2卷 1–17页

作者： Carcangiu, Alessandro Spano, Lucio Davide Dep. of Electric and Electronic Engineering University of Cagliari Via Marengo 2 Cagliari09123 Italy Dep. of Mathematics and Computer Science University of Cagliari Via Ospedale 72 Cagliari09124 Italy

The large availability of touch-sensitive screens fostered the research in gesture recognition. The Machine Learning community focused mainly on accuracy and robustness to noise, creating classifiers that precisely recognize gestures after their performance. Instead, the User Interface engineering community developed compositional gesture descriptions that model gestures and their sub-parts. They are suitable for building guidance systems, but they lack a robust and accurate recognition support. In this paper, we establish a compromise between the accuracy and the provided information introducing G-Gene, a method for transforming compositional stroke gesture definitions into profile Hidden Markov Models (HMMs), able to provide both a good accuracy and information on gesture sub-parts. It supports online recognition without using any global feature, and it updates the information while receiving the input stream, with an accuracy useful for prototyping the interaction. We evaluated the approach in a user interface development task, showing that it requires less time and effort for creating guidance systems with respect to common gesture classification approaches. © 2018 Association for Computing Machinery.

关键词： Feedback

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Autonomous Detection of Plant Disease Symptoms Directly from Aerial Imagery

Plant Phenome Journal

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Plant Phenome Journal 2019年第1期2卷 1-9页

作者： Wu, Harvey Wiesner-Hanks, Tyr Stewart, Ethan L. DeChant, Chad Kaczmar, Nicholas Gore, Michael A. Nelson, Rebecca J. Lipson, Hod Dep. of Computer Science Columbia Univ. New York 10027 NY United States Dep. of Mechanical Engineering and Institute of Data Science Columbia Univ. New York 10027 NY United States Plant Breeding and Genetics Section School of Integrative Plant Science Cornell Univ. Ithaca 14853 NY United States Plant Pathology and Plant-Microbe Biology Section School of Integrative Plant Science Cornell Univ. Ithaca 14853 NY United States

Core Ideas A deep learning model identified plant disease in UAV images with 95% accuracy. Transfer learning allowed for faster model optimization. This method detected plant disease symptoms at a very fine spatial scale. The detection, diagnosis and quantification of plant diseases using digital technologies is an important research frontier. New and accurate methods would be an asset to growers, for whom early disease detection can mean the difference between successful intervention and massive losses, and plant breeders, who often must rely on time-consuming phenotyping by eye. We have developed such a method for detecting an important maize (Zea mays L.) disease. Northern leaf blight [NLB;causal agent Setosphaeria turcica (Luttrell) Leonard & Suggs] is a foliar disease of maize that causes significant yield losses. Accurately measuring NLB infection is necessary both for breeding more resistant maize lines and for guiding crop management decisions. Visual disease scoring in a large area is time-consuming and human evaluations are subjective and prone to error. In this work, we demonstrate an automated, high-throughput system for the detection of NLB in field images of maize plants. Through the use of an unmanned aerial vehicle (UAV) to acquire high resolution images, we trained a convolutional neural network (CNN) model on lower resolution sub-images, achieving 95.1% accuracy on a separate test set of sub-images. The CNN model was used to create interpretable heat maps of the original images, indicating the locations of putative lesions. Detecting lesions at a fine spatial scale allows for the potential of unprecedented high-resolution disease detection for plant breeding and crop management strategies. © 2019 The Authors.

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Sensing with magnetostriction by coupling geometrical effect to an embedded fiber Bragg grating

Sensing with magnetostriction by coupling geometrical effect...

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Optical Sensors, Sensors 2019

作者： Jiménez, Raúl E. Frailey, David M. Law, Chiu Tai Acuna, Rodrigo Escuela de Física Universidad Nacional de Colombia - Medellín Medellín20036 Colombia Dep. of Electrical Engineering and Computer Science University of Wisconsin MilwaukeeWI53211 United States

This paper discusses the geometrical effects on the performance of a fiber optic magnetic field sensor based on a magnetostrictive composites. Experimental results for the cases under study agree with the discussed th... 详细信息

ISBN: (纸本)9781943580613

关键词： Fiber Bragg gratings

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An Implementation of IoT-Based Weather Monitoring System

An Implementation of IoT-Based Weather Monitoring System

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IEEE International Symposium on Parallel and Distributed Processing with Applications and IEEE International Conference on Ubiquitous Computing and communications (ISPA/IUCC)

作者： Yung-Chung Tsao Yin Te Tsai Yaw-Wen Kuo Chaokung Hwang Dep.of Electrical Engineering National Chi Nan University Nantou Taiwan Dep. Of Computer Science & Communication Engineering Providence University TaiChung Taiwan Wu Tso Elementary School TaiChung Taiwan

ISBN: (纸本)9781728152103

The living environment monitoring is a critical issue today. Many related researches focused on developing the living environment monitoring systems by using the web-based technology, but such information systems would increase the difficulty of promotion and migration to others, because of needing well-trained engineers to achieve and maintain such information system. This research focuses on developing the weather monitoring system. The main goal of the research is to use the technology of message queuing telemetry transport (MQTT) as roles of the communication layer instead of direct-connecting database, which can isolate the system migration complexity from heterogeneous relational database management system (RDBMS) and construct a distributed information system easily. Finally the contributions are demonstrated as implementation of the IoT-based weather monitoring system. The prototyping of the weather monitoring system is implemented and dep.oyed at Wu-Tso elementary school for the students' learning of nature science and activity environment. In addition, the system is implemented using open sources and is easy to be dep.oyed and scalable.

关键词： geophysics computing Internet of Things relational databases weather forecasting geophysics computing weather forecasting Relational databases Internet of things weather monitoring computer based information systems Relational database systems

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Intercross: An Android app for plant breeding and genetics cross management

arXiv

引用

arXiv 2021年

作者： Rife, Trevor W. Courtney, Chaney Bauchet, Guillaume Neilsen, Mitchell Poland, Jesse A. Wheat Genetics Resource Center Dep. of Plant Pathology 4024 Throckmorton Plant Sciences Center Kansas State Univ 1712 Claflin Road ManhattanKS66506 United States Boyce Thompson Institute Cornell University 533 Tower Road IthacaNY14853 United States Terre de Lin 605 Route de la Vallée Saint-Pierre-le-Viger76740 France Dep. of Computer Science 2184 Engineering Hall Kansas State University 1701D Platt St. ManhattanKS66506 United States

Plant breeding is fundamentally comprised of three cyclic activities: 1) intermating lines to generate novel allelic combinations, 2) evaluation of new plant cultivars in distinct environments, and 3) selection of superior individuals to be used as parents in the next breeding cycle. While digital technologies and tools are commonly utilized for the latter two stages, many plant research programs still rely on manual annotation and paper tags to track the crosses that constitute the basis of a plant breeding program. This presence of analog data is a crack in the foundation of a digital breeding ecosystem and a significant occasion for errors to be introduced that will propagate through the entire breeding program. However, implementing digital cross tracking into breeding programs is difficult due to the non-standardized workflows that different breeders have adopted. Intercross, an open-source Android app, aims to provide scientists with a robust and simple solution for planning, tracking, and managing the crosses being made each season and aims to serve as the primary tool to digitize crossing data for breeding programs. The simplicity and flexibility of Intercross allows rapid and broad adoption by diverse breeding programs and will solidify the concepts of a digital breeding ecosystem. © 2021, CC BY-SA.

关键词： Android (operating system)

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