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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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)

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