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Bridging the state-of-the-art and the state-of-the-practice of SaaS pricing: A multivocal literature review Inf. Softw. Technol. (IF 2.726) Pub Date : 2021-01-13 Andrey Saltan; Kari Smolander
Context Pricing is an essential element of software business strategy and tactics. Informed pricing decision-making requires the involvement of different stakeholders and comprehensive data analysis. Achieving both appears to be challenging, and pricing remains one of the most under-managed processes in the software business. Simultaneously, a coherent SaaS pricing body of knowledge and verified solutions
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A survey of iris datasets Image Vis. Comput. (IF 3.103) Pub Date : 2021-01-23 Lubos Omelina; Jozef Goga; Jarmila Pavlovičová; Miloš Oravec; Bart Jansen
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Multi-information-based convolutional neural network with attention mechanism for pedestrian trajectory prediction Image Vis. Comput. (IF 3.103) Pub Date : 2021-01-23 Ruiping Wang; Yong Cui; Xiao Song; Kai Chen; Hong Fang
Predicting pedestrian trajectory is useful in many applications, such as autonomous driving and unmanned vehicles. However, it is a challenging task because of the complexity of the interactions among pedestrians and the environment. Most existing works employ long short-term memory networks to learn pedestrian behaviors, but their prediction accuracy is not good, and their computing speed is relatively
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Energy and Performance-Efficient Task Scheduling in Heterogeneous Virtualized Cloud Computing Sustain. Comput. Inform. Syst. (IF 2.798) Pub Date : 2021-01-24 Mehboob Hussain; Lian-Fu Wei; Abdullah Lakhan; Samad Wali; Soragga Ali; Abid Hussain
In virtualized cloud computing systems, energy reduction is a serious concern since it can offer many major advantages, such as reducing running costs, increasing system efficiency, and protecting the environment. At the same time, an energy-efficient task scheduling strategy is a viable way to meet these goals. Unfortunately, mapping cloud resources to user requests to achieve good performance by
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RBFNN versus GRNN Modeling Approach for Sub-Surface Evaporation Rate Prediction in Arid Region Sustain. Comput. Inform. Syst. (IF 2.798) Pub Date : 2021-01-23 Ammar Hatem Kamel; Haitham Abdulmohsin Afan; Mohsen Sherif; Ali Najah Ahmed; Ahmed El-Shafie
Evaporation from sub-surface reservoirs is a phenomenon that has drawn a considerable amount of attention, over recent years. An accurate prediction of the sub-surface evaporation rate is a vital step towards drawing better managing of the reservoir’ water system. In fact, the evaporation rate and more specifically from sub-surface is considered as highly stochastic and non-linear process that affected
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Analysis of Service-Oriented Architecture and Scrum Software Development Approach for IIoT Sci. Program. (IF 0.963) Pub Date : 2021-01-23 Yanqing Cui; Islam Zada; Sara Shahzad; Shah Nazir; Shafi Ullah Khan; Naveed Hussain; Muhammad Asshad
Flexibility and change adoption are key attributes for service-oriented architecture (SOA) and agile software development processes. Although the notion of agility is quite visible on both sides, still the integration of the two diverse concepts (architectural framework and development process) should be well thought of before employing them for a software development project. For this purpose, this
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Shear band static evolution by spatially mobilized plane criterion based Drucker-Prager model and numerical manifold method Comput. Geotech. (IF 3.818) Pub Date : 2021-01-22 Zibo Fan; Hong Zheng; Shan Lin
The shear band due to strain localization is deemed a strong discontinuous plane in this study, and simulated by the numerical manifold method (NMM). The SMP (Spatially Mobilized Plane) criterion is incorporated into the Drucker-Prager (DP) model by the transformed stress (TS) method. The constitutive integration of plasticity is carried out on the new yielding surface with the tensile part being cut
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Formulation, validation and application of a practice-oriented two-surface plasticity sand model Comput. Geotech. (IF 3.818) Pub Date : 2021-01-24 Zhao Cheng; Christine Detournay
Fully coupled fluid-mechanical numerical analyses using a nonlinear constitutive model to analyze soil deformation and liquefaction caused by monotonic or cyclic loading are challenging and in increasing demand. The constitutive model performance impacts the quality of the analysis and its practice-friendliness influences the calibration cost. The Dafalias-Manzari 2004 (DM04) two-surface model is a
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3D DEM insights into the effect of particle overall regularity on macro and micro mechanical behaviours of dense sands Comput. Geotech. (IF 3.818) Pub Date : 2021-01-24 Jia-Yan Nie; Zi-Jun Cao; Dian-Qing Li; Yi-Fei Cui
Particle shape affects the mechanical properties of sands, but the underlying micro-mechanisms are not yet explored, at least partially, due to difficulties in accessing the particle scale information in the laboratory. This study aims to fill this gap through DEM by proposing a general framework for DEM simulation considering realistic particle shape and grading characteristics. Within the proposed
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Two-phase SPH numerical study of pore-water pressure effect on debris flows mobility: Yu Tung debris flow Comput. Geotech. (IF 3.818) Pub Date : 2021-01-22 Saeid Moussavi Tayyebi; Manuel Pastor; Miguel Martin Stickle
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An elastoplastic solution to undrained expansion of a cylindrical cavity in SANICLAY under plane stress condition Comput. Geotech. (IF 3.818) Pub Date : 2021-01-23 Lin Li; Haohua Chen; Jingpei Li; De'an Sun
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Probabilistic simulation of entire process of rainfall-induced landslides using random finite element and material point methods with hydro-mechanical coupling Comput. Geotech. (IF 3.818) Pub Date : 2021-01-24 Xin Liu; Yu Wang
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An exact branch-and-price approach for the medical student scheduling problem Comput. Oper. Res. (IF 3.424) Pub Date : 2021-01-06 Babak Akbarzadeh; Broos Maenhout
In this paper, we consider the medical student scheduling problem, which is a tactical scheduling problem assigning medical students to specific disciplines and hospitals in order to ensure an appropriate training over a one-year scheduling horizon. These internship positions are offered by local hospitals that specify minimum and maximum staffing requirements. To some extent, students can customise
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Adaptive neighborhood simulated annealing for the heterogeneous fleet vehicle routing problem with multiple cross-docks Comput. Oper. Res. (IF 3.424) Pub Date : 2021-01-05 Vincent F. Yu; Parida Jewpanya; A.A.N. Perwira Redi; Yu-Chung Tsao
This paper introduces the heterogeneous fleet vehicle routing problem with multiple cross-docks, a variant of the vehicle routing problem with cross-docking, which considers the use of multiple cross-docks and a heterogeneous fleet of vehicles in a distribution system. A mixed integer linear program and an adaptive neighborhood simulated annealing algorithm are developed for the problem. The proposed
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A compact reformulation of the two-stage robust resource-constrained project scheduling problem Comput. Oper. Res. (IF 3.424) Pub Date : 2021-01-23 Matthew Bold; Marc Goerigk
This paper considers the resource-constrained project scheduling problem with uncertain activity durations. We assume that activity durations lie in a budgeted uncertainty set, and follow a robust two-stage approach, where a decision maker must resolve resource conflicts subject to the problem uncertainty, but can determine activity start times after the uncertain activity durations become known. We
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Accelerating the Calculation of Makespan Used in Scheduling Improvement Heuristics Comput. Oper. Res. (IF 3.424) Pub Date : 2021-01-23 Golshan Madraki; Robert P. Judd
The goal of this research is to accelerate improvement heuristics which use a graph to model the system and calculates the makespan, i.e., longest path in the graph, during each iteration. These heuristics iteratively perturb the graph and recalculate the makespan in each iteration until a satisfactory schedule is determined. We propose Improved Structural Perturbation Algorithm (ISPA) to accelerate the
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Selecting common projection direction in DEA directional distance function based on directional extensibility Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-13 Junfei Chu; Fangqing Wei; Jie Wu; Zhe Yuan
This paper develops a new approach to select a common projection direction for performance evaluation of decision-making units (DMUs) using the data envelopment analysis (DEA) directional distance function. First, we define the concept of directional extensibility of a specific projection direction with respect to a set of inefficient DMUs. The concept shows the projection direction’s ability in reducing
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A heuristic approach for a scheduling problem in additive manufacturing under technological constraints Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-12 Aymen Aloui; Khaled Hadj-Hamou
In the context of the future industry, companies have urged to innovate the manufactured products. Today, additive manufacturing makes it possible to respond to the needs of the market in terms of customized production. The recent advances in additive manufacturing technologies have caused a considerable increase in the number of products manufactured by additive processes in industries. In order to
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Dynamic pricing and lot sizing for a newsvendor problem with supplier selection, quantity discounts, and limited supply capacity Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-13 Omid Jadidi; Mohamad Y. Jaber; Saeed Zolfaghri; Roberto Pinto; Fatemeh Firouzi
This study considers the joint pricing and sourcing decision problem for a buyer purchasing a product from a set of suppliers who offer quantity discounts. The suppliers’ supply and/or the buyer’s warehouse capacities are bounded, causing the buyer to split its order over multiple suppliers and periods. This study assumes that demand is random over the planning horizon, divided into several periods
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Innovation beyond optimization: Application to cutting tool design Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-23 Hicham Chibane; Sébastien Dubois; Roland De Guio
During the development of a product, several steps and iterations are necessary for meeting specifications and optimizing performance criteria. This article address machining problem, that are faced to increasing constraints and performance criteria. A multi-objective optimization approach is a common approach for determining a solution that meets all these constraints. The Design of Experiments (DoE)
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A novel multi-attribute decision-making method based on fuzzy rough sets Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-23 Jin Ye; Jianming Zhan; Zeshui Xu
The purpose of this paper is to propose a novel decision-making method based on fuzzy rough sets (FRSs) to deal with the uncertainty and imprecision existed in various multi-attribute decision-making (MADM) problems. In view of the effectiveness of fuzzy neighborhood operators in handling uncertain numerical data and the deficiencies of existing fuzzy neighborhood operators, we first define a reflexive
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A classification proposal of digital twin applications in the safety domain Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-23 Giulio Paolo Agnusdei; Valerio Elia; Maria Grazia Gnoni
The increasing diffusion of digitalization in industry and society is forcing the adopting of tools based on new enabling technologies. This phenomenon is clearly observable in the manufacturing sector, where, due to the diffusion of Industry 4.0 paradigm, physical processes are integrating effectively with digital ones. One recent innovative technology is the Digital Twin (DT), where digital models
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Fast Analytical Motion Blur with Transparency Comput. Graph. (IF 1.351) Pub Date : 2021-01-23 Mads J.L. Rønnow; Ulf Assarsson; Marco Fratarcangeli
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SlidAR+: Gravity-Aware 3D Object Manipulation for Handheld Augmented Reality Comput. Graph. (IF 1.351) Pub Date : 2021-01-23 Varunyu Fuvattanasilp; Yuichiro Fujimoto; Alexander Plopski; Takafumi Taketomi; Christian Sandor; Masayuki Kanbara; Hirokazu Kato
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Automatic Portrait Image Pixelization Comput. Graph. (IF 1.351) Pub Date : 2021-01-23 Yunyi Shang; Hon-Cheng Wong
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Improving high-impact bug report prediction with combination of interactive machine learning and active learning Inf. Softw. Technol. (IF 2.726) Pub Date : 2021-01-20 Xiaoxue Wu; Wei Zheng; Xiang Chen; Yu Zhao; Tingting Yu; Dejun Mu
Context: Bug reports record issues found during software development and maintenance. A high-impact bug report (HBR) describes an issue that can cause severe damage once occurred after deployment. Identifying HBRs from the bug repository as early as possible is crucial for guaranteeing software quality. Objective: In recent years, many machine learning-based approaches have been proposed for HBR prediction
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Collaborative knowledge distillation for incomplete multi-view action prediction Image Vis. Comput. (IF 3.103) Pub Date : 2021-01-21 Deepak Kumar; Chetan Kumar; Ming Shao
Predicting future actions is a key in visual understanding, surveillance, and human behavior analysis. Current methods for video-based prediction are primarily using single-view data, while in the real world multiple cameras and produced videos are readily available, which may potentially benefit the action prediction tasks. However, it may bring up a new challenge: subjects in the videos are more
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Guidelines for Quality Assurance of Machine Learning-Based Artificial Intelligence Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Gaku Fujii; Koichi Hamada; Fuyuki Ishikawa; Satoshi Masuda; Mineo Matsuya; Tomoyuki Myojin; Yasuharu Nishi; Hideto Ogawa; Takahiro Toku; Susumu Tokumoto; Kazunori Tsuchiya; Yasuhiro Ujita
Significant effort is being put into developing industrial applications for artificial intelligence (AI), especially those using machine learning (ML) techniques. Despite the intensive support for building ML applications, there are still challenges when it comes to evaluating, assuring, and improving the quality or dependability. The difficulty stems from the unique nature of ML, namely, system behavior
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Analyzing the Stationarity Process in Software Effort Estimation Datasets Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Michael Franklin Bosu; Stephen G. MacDonell; Peter A. Whigham
Software effort estimation models are typically developed based on an underlying assumption that all data points are equally relevant to the prediction of effort for future projects. The dynamic nature of several aspects of the software engineering process could mean that this assumption does not hold in at least some cases. This study employs three kernel estimator functions to test the stationarity
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Enabling Reliability-Driven Optimization Selection with Gate Graph Attention Neural Network Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Jiang Wu; Jianjun Xu; Xiankai Meng; Haoyu Zhang; Zhuo Zhang
Modern compilers provide a huge number of optional compilation optimization options. It is necessary to select the appropriate compilation optimization options for different programs or applications. To mitigate this problem, machine learning is widely used as an efficient technology. How to ensure the integrity and effectiveness of program information is the key to problem mitigation. In addition
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Plagiarism Detection of Multi-threaded Programs Using Frequent Behavioral Pattern Mining Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Zhenzhou Tian; Qing Wang; Cong Gao; Lingwei Chen; Dinghao Wu
Software dynamic birthmark techniques construct birthmarks using the captured execution traces from running the programs, which serve as one of the most promising methods for obfuscation-resilient software plagiarism detection. However, due to the perturbation caused by non-deterministic thread scheduling in multi-threaded programs, such dynamic approaches optimized for sequential programs may suffer
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Prediction of Regional Commercial Activeness and Entity Condition Based on Online Reviews Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Dongjin Yu; Xinfeng Wang; Xiaoxiao Sun
The activeness of regional business entities, like restaurants, cinemas and shopping malls, represents the evolvement of their corresponding commercial districts, whose prediction helps practitioners grasp the trend of commercial development and provides support for urban layout. On the other hand, online social network services, such as Yelp, are generating massive online reviews toward business entities
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Automatic Voter Recommendation Method for Closing Questions in Stack Overflow Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Zhang Zhang; Xinjun Mao; Yao Lu; Jinyu Lu; Yue Yu; Zhixing Li
Stack Overflow is the most popular programming question and answer community that continuously receives a large number of questions every day. To ensure the quality of questions, the community grants privileges for the moderators and a group of experienced users to review the quality of questions and close the low-quality ones (e.g. duplicate or irrelevant questions). The review process is a typical
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Identifying Similar Users Based on Their Check-in Data: A Graph Embedding Approach Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Rui Song; Tong Li; Xin Dong; Zhiming Ding
In recent years, the amount of user check-in data has significantly increased on social network platforms. Such data is an ideal source for characterizing user behaviors and identifying similar users, contributing to many research areas (e.g. user-based collaborative filtering). However, existing trajectory-based user similarity analysis approaches do not distinguish the effects of geographical factors
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An Experimental Study of Spammer Detection on Chinese Microblogs Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Jialing Liang; Peiquan Jin; Lin Mu; Jie Zhao
With the development of Web 2.0, social media such as Twitter and Sina Weibo have become an essential platform for disseminating hot events. Simultaneously, due to the free policy of microblogging services, users can post user-generated content freely on microblogging platforms. Accordingly, more and more hot events on microblogging platforms have been labeled as spammers. Spammers will not only hurt
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Is Bug Severity in Line with Bug Fixing Change Complexity? Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Zengyang Li; Peng Liang; Dengwei Li; Ran Mo; Bing Li
Both complexity of code change for bug fixing and bug severity play an important role in release planning when considering which bugs should be fixed in a specific release under certain constraints. This work investigates whether there are significant differences between bugs of different severity levels regarding the complexity of code change for fixing the bugs. Code change complexity is measured
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Conversion-based Approach to Obtain an SNN Construction Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Ying Shang; Yongli Li; Feng You; RuiLian Zhao
Spiking Neuron Network (SNN) uses spike sequence for data processing, so it has an excellent characteristic of low power consumption. However, due to the immaturity of learning algorithm, the multiplayer network training has difficulty in convergence. Utilizing the mature learning algorithm and fast training speed of the back-propagation network, this paper proposes a method to converse the Convolutional
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Modeling and Selecting Frameworks in Terms of Patterns, Tactics and System Qualities Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Hind Milhem; Michael Weiss; Stephane S. Some
Selecting a framework and documenting the rationale for choosing it is an essential task for system architects. Different framework selection approaches have been proposed in the literature. However, none of these connect frameworks to qualities based on their implemented patterns and tactics. In this paper, we propose a way to semi-automatically compare the quality attributes of frameworks by extracting
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An Attribute-Based Cross-Domain Access Control Model for a Distributed Multiple Autonomous Network Int. J. Softw. Eng. Knowl. Eng. (IF 0.886) Pub Date : 2021-01-21 Yunpeng Zhang; Xin Liu
The distributed multiple autonomous network has become the main trend of modern information systems, such as Cloud, Service-Oriented Architecture (SOA) and Internet of Things (IoT). Access control in such a heterogeneous and dynamic system has become a major information security challenge, which hinders the sharing of resources and information. In this work, we present an Attribute-Based Access Control
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Active Learning for Inference and Regeneration of Applications that Access Databases ACM Trans. Program. Lang. Syst. (IF 0.765) Pub Date : 2021-01-22 Jiasi Shen; Martin C. Rinard
We present Konure, a new system that uses active learning to infer models of applications that retrieve data from relational databases. Konure comprises a domain-specific language (each model is a program in this language) and associated inference algorithm that infers models of applications whose behavior can be expressed in this language. The inference algorithm generates inputs and database contents
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Sustainable task scheduling strategy in cloudlets Sustain. Comput. Inform. Syst. (IF 2.798) Pub Date : 2021-01-18 Dhritiman Mukherjee; Sudarshan Nandy; Senthilkumar Mohan; Yasser D. Al-Otaibi; Waleed S. Alnumay
Cloudlet is an important part of providing cloud services in Mobile Edge Computing (MEC) with sustainability. As the number of mobile users grows rapidly in the current era, the load in the cloudlet becomes very high. The cloudlet is considered in the middle layer for providing cloud services with low latency and energy efficiency. Hence the task allocation and scheduling inside of the cloudlet is
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Machine intelligence approach: To solve load balancing problem with high quality of service performance for multi-controller based Software Defined Network Sustain. Comput. Inform. Syst. (IF 2.798) Pub Date : 2021-01-08 Vivek Srivastava; Ravi Shankar Pandey
In this paper, we have proposed a DRL based method to obtain the route based on an optimized load of SDN which is based on self-learning of human intelligence. In this proposal, the Bio-Inspired RBM is used for Bio-Inspired Deep Belief Architecture (BDBA) for implementing deep learning to obtain the optimized route. This Bio-Inspired RBM has two parts one is simple RBM and another part is inspired
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Plug-and-Play Synthetic Aperture Radar Image Formation Using Deep Priors IEEE Trans. Comput. Imaging (IF 4.015) Pub Date : 2020-12-25 Muhammed Burak Alver; Ammar Saleem; Müjdat Çetin
The reconstruction of synthetic aperture radar (SAR) images from phase history data is an ill-posed inverse problem which, in several lines of recent work, is solved by minimizing a cost function. Existing reconstruction methods use regularization to tackle the ill-posed nature of the imaging task. However, in general, these regularizers are either too simple to capture complex spatial patterns and
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Accurate and locking-free analysis of beams, plates and shells using solid elements Comput. Mech. (IF 3.459) Pub Date : 2021-01-22 Savvas Saloustros, Miguel Cervera, Sungchul Kim, Michele Chiumenti
This paper investigates the capacity of solid finite elements with independent interpolations for displacements and strains to address shear, membrane and volumetric locking in the analysis of beam, plate and shell structures. The performance of the proposed strain/displacement formulation is compared to the standard one through a set of eleven benchmark problems. In addition to the relative performance
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Enabling Large NNs on Tiny MCUs with Swapping arXiv.cs.AR Pub Date : 2021-01-14 Hongyu Miao; Felix Xiaozhu Lin
Running neural network (NN) on microcontroller unites (MCU) is becoming increasingly important, but is very difficult due to the tiny SRAM size of MCU. Prior work proposes many algorithm-level techniques to reduce NN memory footprints, but all at the cost of sacrificing accuracy and generality, which disqualifies MCUs for many important use cases. We investigate a system solution for MCUs to execute
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Cain: Automatic Code Generation for Simultaneous Convolutional Kernels on Focal-plane Sensor-processors arXiv.cs.AR Pub Date : 2021-01-21 Edward Stow; Riku Murai; Sajad Saeedi; Paul H. J. Kelly
Focal-plane Sensor-processors (FPSPs) are a camera technology that enable low power, high frame rate computation, making them suitable for edge computation. Unfortunately, these devices' limited instruction sets and registers make developing complex algorithms difficult. In this work, we present Cain - a compiler that targets SCAMP-5, a general-purpose FPSP - which generates code from multiple convolutional
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An Efficient Communication Protocol for FPGA IP Protection arXiv.cs.AR Pub Date : 2021-01-21 Farzane Khajuyi; Behnam Ghavami; Human Nikmehr
We introduce a protection-based IP security scheme to protect soft and firm IP cores which are used on FPGA devices. The scheme is based on Finite State Machin (FSM) obfuscation and exploits Physical Unclonable Function (PUF) for FPGA unique identification (ID) generation which help pay-per-device licensing. We introduce a communication protocol to protect the rights of parties in this market. On standard
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ItNet: iterative neural networks with tiny graphs for accurate and efficient anytime prediction arXiv.cs.AR Pub Date : 2021-01-21 Thomas Pfeil
Deep neural networks have usually to be compressed and accelerated for their usage in low-power, e.g. mobile, devices. Recently, massively-parallel hardware accelerators were developed that offer high throughput and low latency at low power by utilizing in-memory computation. However, to exploit these benefits the computational graph of a neural network has to fit into the in-computation memory of
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UNIT: Unifying Tensorized Instruction Compilation arXiv.cs.AR Pub Date : 2021-01-21 Jian Weng; Animesh Jain; Jie Wang; Leyuan Wang; Yida Wang; Tony Nowatzki
Because of the increasing demand for computation in DNN, researchers develope both hardware and software mechanisms to reduce the compute and memory burden. A widely adopted approach is to use mixed precision data types. However, it is hard to leverage mixed precision without hardware support because of the overhead of data casting. Hardware vendors offer tensorized instructions for mixed-precision
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Numerical study of the chemo-mechanical behavior of FEBEX bentonite in nuclear waste disposal based on the Barcelona expansive model Comput. Geotech. (IF 3.818) Pub Date : 2021-01-22 Hao Xu; Liange Zheng; Jonny Rutqvist; Jens Birkholzer
Experimental studies show that compacted bentonite used as a backfill material for nuclear waste repository experiences strong coupling between chemical and mechanical processes. In this paper, we use a dual-structure expansive soil model, referred to as the Barcelona Expansive Model (BExM), to predict the behavior of bentonite buffer in subsurface emplacement tunnels for high-level radioactive waste
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Simplified model of defective pile-soil interaction considering three-dimensional effect and application to integrity testing Comput. Geotech. (IF 3.818) Pub Date : 2021-01-22 Xin Liu; M. Hesham El Naggar; Kuihua Wang; Yuan Tu; Xinchen Qiu
A new simplified model for defective pile-soil interaction (DPSI) is developed to account for the three-dimensional (3D) effect in the pile integrity test (PIT) for large diameter piles. To account for the 3D effect, the defective pile is treated as linear continuum rather than the conventional 1D rod model. The surrounding soil is simulated employing the classical plane strain model and the soil resistance
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Geotechnical and Structural stochastic analysis of piled solar farm foundations Comput. Geotech. (IF 3.818) Pub Date : 2021-01-21 Richard Kelly; Jinsong Huang; Harry Poulos; Mark G. Stewart
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Optimal monitoring of Poisson data with known and unknown shifts Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-09 Junjie Wang; Zhi Lin Chong; Peihua Qiu
The number of event occurrences, called counts are prevalent in many fields such as manufacturing industry and public health. Control charts have been widely employed to monitor such count data for quality improvement of products or medical service by assuming the data follows the Poisson distribution. However, the shift information of Poisson mean has not been well considered in current design of
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Scheduling of field service resources in cloud manufacturing based on multi-population competitive-cooperative GWO Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-14 Bo Yang; Shilong Wang; Qingqing Cheng; Tianguo Jin
Cloud manufacturing (CMfg) is a new networked manufacturing mode based on the big data and the Internet of Thing technologies, which can dynamically and flexibly allocate the manufacturing resources on demand. All the current researches and applications on CMfg focused on the factory manufacturing schema, the field manufacturing schema has not been concerned. Field manufacturing refers to the geographically
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Lead management optimization using data mining: A case in the telecommunications sector Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-14 P. Espadinha-Cruz; A. Fernandes; A. Grilo
The growing competitiveness of the market has put pressure on companies to improve their customer relationship management strategies. In an era where mass marketing techniques are inadequate, lead management is at the forefront to provide a customized approach to customer acquisition. For this, lead management depends on the correct selection of leads and decision making on what type of approach to
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An optimal preventive maintenance policy for a two-stage competing-risk system with hidden failures Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-22 Yanjing Zhang; Jingyuan Shen; Yizhong Ma
In many complex industrial systems, failures are not always evident to the operating crew, thus inspections are used to identify such hidden failures and then make necessary maintenance actions. In this paper, we study a two-stage system that is subject to two competing risks of degradation and random shocks. Failures of this two-stage competing-risk system are hidden and could only be detected by
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A note on scheduling a rate modifying activity to minimize total late work Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-22 Gur Mosheiov; Daniel Oron
We study a single machine scheduling problem with a rate modifying activity. In most cases, performing such an activity (e.g., a maintenance procedure) improves the system performance, as reflected by shorter processing times of the jobs processed after it. The scheduling measure assumed is total late work: each job is considered as a collection of unit-time jobs, and the late work is defined as the
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A novel model and solution algorithm to improve crew scheduling in railway transportation: A real world case study Comput. Ind. Eng. (IF 4.135) Pub Date : 2021-01-21 Paweł Hanczar; Arash Zandi
This paper presents a novel mathematical formulation in railway crew scheduling, considering real challenges most European passenger railway companies face like roundtrip policy for crew members joining from different cities and stricter working time standards. To solve the problem in large scales of data (consistent with the real case size of the planning problems solved by rail transport companies)
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PIG-Net: Inception based deep learning architecture for 3D point cloud segmentation Comput. Graph. (IF 1.351) Pub Date : 2021-01-21 Sindhu Hegde; Shankar Gangisetty
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Case Study Research in Software Engineering—It is a Case, and it is a Study, but is it a Case Study? Inf. Softw. Technol. (IF 2.726) Pub Date : 2021-01-18 Claes Wohlin
Background: Case studies are regularly published in the software engineering literature, and guidelines for conducting case studies are available. Based on a perception that the label “case study” is assigned to studies that are not case studies, an investigation has been conducted. Objective: The aim was to investigate whether or not the label “case study” is correctly used in software engineering
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