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In this paper, the influence of the stiffness and damping of real elastic shafts on the behavior of a multidrive system driving a tissue paper machine is investigated. The drive system consists of four dc motors, where two of them drive the Yankee drying cylinder and the other two drive the presses section. Six-pulse thyristor bridge power converters that are connected to the same power transformer supply the motors. The inertias of the motors and the driven machines, in conjunction with the shaft stiffness, form mechanical resonators. Thus, resonance phenomena may occur, which may lead to undesirable results. This particular case results to two three-mass and one five-mass systems. This paper presents an analysis of the resonance frequencies of two sections of the machine during startup and machine production, considering the shaft stiffness (shaft diameter, length, and thickness). The elastic shafts eliminate the ripple of the motor electromagnetic torque, which is transferred to the driven machine. The behavior of elastic shafts with different stiffness in the transmission system is studied. Moreover, the steady state and dynamic behavior of the system considering the influence of the elastic shafts and vibration analysis were investigated using simulation. A model algorithm for system simulation was developed using the MATLAB/SIMULINK software. Characteristic simulation results are presented and are expressed in terms of speed and torque response. Considering the resonance frequency analysis and simulation results, mechanical design guidelines can be given for the most significant drive components in order to avoid torsional oscillation resonance phenomena and minimize torsional oscillations of the drive system. [ABSTRACT FROM AUTHOR]

User interfaces to control networked household appliances are often inadequate. Either they are too simplistic or they are too complex and complicated relying on a PC-based interface. Therefore, a user interface that supports complex functionalities and is easy to use is required. In this article digital pen and paper are presented as a suitable interface. Digital pens are only marginally larger than their traditional counterparts, and digital paper is ordinary paper with an almost invisible unique pattern printed on it. Pen and paper are well known to users and thus an important barrier to the acceptance of networked appliances is removed. The approach is integrated with an Open Services Gateway Initiative (OSGi) gateway, thus allowing for flexibility with respect to the protocol used to communicate with the appliance. It is also shown how the approach can be applied to other appliances in and beyond the home. [ABSTRACT FROM AUTHOR]

The nine papers in this special section focus on new developments in agile software and reports on applications for its use. A key aspect for the extensive use of agile software is that it supports developers with coping with the growing uncertainty and turbulence in technological and market environments. Feedback and change are at the core of Agile for a dynamic, evolving, and organic, rather than static, predefined, and mechanistic development process advocated by waterfall management. To create timely, high-quality, cost-efficient, and innovative solutions, Agile developers organized in small, colocated, autonomous teams, build and test software in rapid iterative cycles, actively involving users to gather feedback, updating the project scope, and plan "on-the-fly," using face-to-face communication as opposed to documentation. These papers contribute to the state-of-the-art of agile research by offering a rich, up-todate account of the dynamics occurring when expanding Agile into "not-just-software" contexts of the key challenges and perils related to the scaling and of the possible solutions to them. [ABSTRACT FROM AUTHOR]

Focuses on optimal approach to fault tolerant software system design.

In this paper, a self-adaptive protection system is proposed for adjusting the time dial (TD) of reclosers found in electrical power distribution systems (EPDSs). The self-adjustment is carried out in both phase and ground protection. The methodology considers the fuses along the feeder to obtain the fuse-saving philosophy. This feature allows less interference on the protection system already implemented by the electrical power distribution utilities. This methodology also allows using other frameworks, such as the estimation of the fault distance. The software used for computer modeling and simulation was PSCAD™/EMTDC™. The flexibility provided by the method, which allows the incorporation of new logic and changes in decision-making, resulted in an adaptive method with a good performance against different locations, types, and fault impedance. It also resulted in better coordination between the protection devices (PDs). The results compared with well-coordinated conventional protection have shown significant performance gain with the adaptive system. [ABSTRACT FROM AUTHOR]

IPC (Inter-Process Communication) is a widely used operating system (OS) technique that allows one process to invoke the services of other processes. The IPC participants may share the same OS (internal IPC) or use a separate OS (external IPC). Even though a long line of researches has optimized the performance of IPC, it is still a major factor of the run-time overhead of IPC-intensive applications. Furthermore, there is no one-size-fits-all solution for both internal and external IPC. This paper presents SkyBridge, a general communication technique designed and optimized for both types of IPC. SkyBridge requires no involvement of the privileged software (the kernel or the hypervisor) and enables a process to directly switch to the virtual address space of the target process, regardless of whether they are running on the same OS or not. We have implemented SkyBridge on two microkernels (seL4 and Google Zircon) as well as an open-source serverless hypervisor (Firecracker). The evaluation results show that SkyBridge improves the latency of internal IPC and external IPC by up to 19.6x and 1265.7x, respectively. [ABSTRACT FROM AUTHOR]

The International Computer and Software Applications Conference has celebrated its tenth anniversary in 1986. The conference has been very successful in attracting excellent papers and panels from both academia and industry. It continued the tradition and attracted superb papers for the following tracks: software quality, software engineering, software requirements, development environments, software techniques and knowledge-based systems.

The article focuses on formal method for open object-based distributed systems (FMOODS). Object-based distributed computing is now a well-established technique for constructing large, heterogeneous computing and telecommunication systems. Standard bodies and consortia have defined distributed object-based frameworks as a foundation for open distributed computing. Its advent brings new challenge and opportunities for the use and development of formal methods. The FMOODS conference series has acted as a forum for presentation of research that addresses these challenges. It seeks to investigate how formal methods can be used to specify, develop and verify open object-based distributed systems. The objective of FMOODS is to represent work at the convergence of three important and related fields that is formal methods, distributed systems and object-based technology. The convergence represents some of the latest advances in the field of distributed systems and provides links between a number of important communities.

Thanks to relatively small public and secret keys, the Supersingular Isogeny Key Encapsulation (SIKE) protocol made it into the third evaluation round of the post-quantum standardization project of the National Institute of Standards and Technology (NIST). Even though a large body of research has been devoted to the efficient implementation of SIKE, its latency is still undesirably long for many real-world applications. Most existing implementations of the SIKE protocol use the Montgomery representation for the underlying field arithmetic since the corresponding reduction algorithm is considered the fastest method for performing multiple-precision modular reduction. In this paper, we propose a new data representation for supersingular isogeny-based Elliptic-Curve Cryptography (ECC), of which SIKE is a sub-class. This new representation enables significantly faster implementations of modular reduction than the Montgomery reduction, and also other finite-field arithmetic operations used in ECC can benefit from our data representation. We implemented all arithmetic operations in C using the proposed representation such that they have constant execution time and integrated them to the latest version of the SIKE software library. Using four different parameters sets, we benchmarked our design and the optimized generic implementation on a 2.6 GHz Intel Xeon E5-2690 processor. Our results show that, for the prime of SIKEp751, the proposed reduction algorithm is approximately 2.61 times faster than the currently best implementation of Montgomery reduction, and our representation also enables significantly better timings for other finite-field operations. Due to these improvements, we were able to achieve a speed-up by a factor of about 1.65, 2.03, 1.61, and 1.48 for SIKEp751, SIKEp610, SIKEp503, and SIKEp434, respectively, compared to state-of-the-art generic implementations. [ABSTRACT FROM AUTHOR]

Since modern cyber-physical power systems are vulnerable to coordinated wide-area cyber attacks, it is necessary to mitigate the potential risk as much as possible. At the planning stage, the defender can utilize software diversity, which is a common phenomenon that the cyber software of different substations comes from different competing vendors. Therefore, different kinds of software may not be exposed to the same zero-day security loophole, preventing the attacker from taking charge of multiple substations at the same time. In this paper, the optimal scheme of software deployment considering long-term risk mitigation is studied. Firstly, the framework of diversity-based cyber defense against malicious attacks is formulated. Secondly, the risk index based on representative attack patterns is constructed, which is the objective to be minimized. Thirdly, considering that the deployment scheme is long-term stable while the operating mode varies with time, we construct a multiobjective nonlinear stochastic programming to mitigate the average risk of operating modes. Then the optimization problem is solved by the multiobjective genetic algorithm. Lastly, results of the IEEE 39-node CPPS and and the Virtual European Grid demonstrate that the proposed method can considerably reduce the attack risk. [ABSTRACT FROM AUTHOR]

A steady increase in available processing power continues to drive advances in video compression technology. The recently completed Versatile Video Coding (VVC) standard aims to double the compression efficiency of HEVC and deliver a same quality of video at half the bitrate. To achieve this goal, VVC includes several new methods that improve coding efficiency at the cost of increased complexity. This paper provides a complexity analysis of VVC and its VTM reference software. Whereas VVC is more complex than HEVC, it remains readily implementable in software on current generation processors. Performance of practical decoders are reported, showing that real-time decoding of 8K content is feasible. An encoder is also presented, showing that most of the compression gains of VVC over HEVC can be obtained at a small fraction of the resources needed by the VTM encoder under common test conditions. [ABSTRACT FROM AUTHOR]

In the paper, “semQA: SPARQL with Idempotent Disjunction” [4], the authors study the RDF query language SPARQL. In particular, they claim that some of the results presented in [1] are not correct. In this note, we refute the claims made in [4], and actually show that some of the formal results of [4] are incorrect. [ABSTRACT FROM PUBLISHER]

This paper first reviews the Spectre and Meltdown processor security vulnerabilities that were revealed during January–October 2018 and that allow the extraction of protected information from billions of processors in large and small systems. It then discusses short-term mitigation actions and speculates on the longer term implications to computer software and hardware. This paper expands from a keynote/panel by the authors at IEEE Hot Chips 2018. [ABSTRACT FROM AUTHOR]

This paper presents a novel nonintrusive protection scheme for fault classification of power transmission networks in a wide-area measurement system using fault information for decision making. The protection scheme is a noncommunication without global positioning system as it depends completely on locally measured currents for the nonintrusive fault monitoring (NIFM) using the power-spectrum-based hyperbolic S-transform (PS-HST). In this work, the HST is used to extract the high-frequency components of the current signals generated by an electric fault. To effectively select the HST coefficients (HSTCs) representing fault transient signals with increasing performance, a power spectrum of the HSTCs in different scales calculated by Parseval's theorem is proposed in this paper. Finally, back-propagation artificial neural networks and PS-HST are used to identify fault classes in power transmission networks. The proposed method is tested for different breaker on/off conditions by simulations using electromagnetic transients program software. The results obtained have proved that the proposed method is promising and demonstrate a high success rates and reliability for considering different fault resistances and inception times in NIFM applications. [ABSTRACT FROM AUTHOR]

Grain is one of three hardware-oriented finalists of the eSTREAM Project. A nonlinear feedback shift register (NFSR) in Grain-like structure is a cascade connection of a linear feedback shift register (LFSR) into an NFSR, in which the characteristic polynomial of the LFSR is primitive and the feedback function of the NFSR is nonsingular. In 2011 Hu and Gong pointed out that the period of the sequence generated by an NFSR in Grain-like structure is a multiple of the period of the sequence generated by its LFSR if the initial state of the LFSR is nonzero. Meanwhile, they proposed an open problem: for fixed feedback functions of an NFSR and an LFSR, determine whether the sequences generated by the NFSR in Grain-like structure can achieve the minimum period, i.e., the period of the LFSR, when the initial state of the LFSR is nonzero, and if they can achieve, provide at least one pair of the initial states of the NFSR and LFSR. Clearly, from a security point of view, it is not preferable if the sequences generated by an NFSR in Grain-like structure achieve the minimum period. This paper converts the open problem into a problem of solving an integer equation with respect to two unknown integers that uniquely correspond to the initial states of the NFSR and LFSR, by viewing the NFSR as a Boolean control network. Based on the integer equation, this paper shows that for any given initial state of an $n$ -stage NFSR and any given nonzero initial state of an $m$ -stage LFSR, the probability that the sequence generated by the NFSR in Grain-like structure achieves the minimum period $2^{m}-1$ is at most $2^{-n}$. This implies that the probability of the cascade connection used in Grain achieving the minimum period is very small. [ABSTRACT FROM AUTHOR]

This paper examines the cloud computing for education (CCE) literature, and analyzes if the research is developing scientifically with adequate empirical validation. All aspects of empirical investigations covered in the literature are shown as weak, hence, the necessary scientific development of CCE requires extending its scope of interest, and involving scholars synergistically to create and maintain a “common research agenda.” Background: A need to develop research on CCE has been recognized, and considerable efforts made to create an accurate understanding of the development of its scope of interest, in terms of supporting pedagogical developments and processes for better quality of studies. Research Questions: This paper has three main aims: 1) to evaluate the scope of interest in the literature for CCE with specific reference to pedagogy and educational processes; 2) to analyze the characteristics of papers, specifically empirical studies, from the various points of view of the daily improvement activities of teachers and learners at all levels of education; and 3) to identify eventual research gaps to consider and stimulate new topics or further investigations. Methodology: This systematic mapping study review followed a rigorous, replicable process to collect and analyze representative studies of CCE. Findings: Differences are found across geographic areas in applying CCE infrastructure and technologies in educational institutions; few studies address CCE’s impact on pedagogic processes. The scope of interest in CCE is only partially covered; with empirical research being very shallow. Suggestions are made for more effective research on concerning the production and use of content. [ABSTRACT FROM AUTHOR]

Focuses on the advantages of an electronic system Manuscript Central, a state-of-the-art Internet-based reviewing process. Adoption of the service by the Institute of Electrical and Electronics Engineers; Capability of the system in enabling the entire peer-review process to take place online; Introduction of temc.manuscript central.com Web site.

Events of interest to Computer Society members. [ABSTRACT FROM AUTHOR]

IEEE Software editor-in-chief Forrest Shull discusses the software sustainability and his interview with Girish Seshagiri, the CEO of AIS, an organization that offers "firm fixed-price contracting with performance guarantees, including a lifetime warranty on software defects" in government contracts. In addition, he discusses the best paper award at the 21st Annual IEEE International Requirements Engineering Conference and the best research paper award at the Agile Conference. The first Web extra at http://youtu.be/L1XN0R4koRk is an audio interview highlighting IEEE Software editor in chief Forrest Shull's discussion with Girish Seshagiri, the CEO of AIS, about the organization's philosophy of offering "firm fixed-price contracting with performance guarantees, including a lifetime warranty on software defects" in government contracts. The second Web extra at http://youtu.be/iFsZlrhSM9E is the complete audio interview in which IEEE Software editor in chief Forrest Shull's speaks with Girish Seshagiri, the CEO of AIS, about the organization's philosophy of offering "firm fixed-price contracting with performance guarantees, including a lifetime warranty on software defects" in government contracts. [ABSTRACT FROM PUBLISHER]

The ever-increasing and unbalanced traffic load in cellular vehicle-to-everything (C-V2X) networks have increased the network congestion and led to user dissatisfaction. To relieve the network congestion and improve the traffic load balance, in this paper, we propose an intelligent software defined C-V2X network framework to enable flexible and low-complexity traffic offloading by decoupling the network data plane from the control plane. In the data plane, the cellular traffic offloading and the vehicle assisted traffic offloading are jointly performed. In the control plane, deep learning is deployed to reduce the software defined network (SDN) control complexity and improve the traffic offloading efficiency. Under the proposed framework, we investigate the traffic offloading problem, which can be formulated as a multi-objective optimization problem. Specifically, the first objective maximizes the cellular access point (AP) throughput with consideration of the load balance by associating the users with the APs. The second objective maximizes the vehicle throughput with consideration of the vehicle trajectory by associating the delay-insensitive users with the vehicles. The two objectives are coupled by the association between the cellular APs and the vehicles. A deep learning based online-offline approach is proposed to solve the multi-objective optimization problem. The online stage decouples the optimization problem into two sub-problems and utilizes the ‘Pareto optimal’ to find the solutions. The offline stage utilizes deep learning to learn from the historical optimization information of the online stage and helps predict the optimal solutions with reduced complexity. Numerical results are provided to validate the advantages of our proposed traffic offloading approach via deep learning in C-V2X networks. [ABSTRACT FROM AUTHOR]

This paper discusses the marginal line loss approximation in the dc optimal power flow (DCOPF) and proposes a new methodology that improves the accuracy of current practices. In practice, the DCOPF solution may have significant differences compared to the ac base point that determines marginal losses, and this paper provides the only published example that illustrates this problem to our knowledge. The proposed methodology updates the marginal losses without solving a new ac base point so that the optimal solution accurately reflects system losses. Previously proposed methodologies require nonlinear programming solvers, additional ac power flow solutions, or are less accurate compared to actual losses, and they only give results for one or two test networks. This paper provides results on nine different test networks. The key advantage of the proposed methodology is that it can be easily integrated into current market software. [ABSTRACT FROM AUTHOR]

One technique which may be employed in certain types of sensing application is the phase-sensitive or lock-in method. Since this method essentially trades off longer measurement time for a greater accuracy, it is sometimes necessary to capture samples over a long time period to ensure sufficient stability in the calculated parameter estimate. This may adversely affect safety-critical systems, and some method of determining the relative stability of the measured parameter is needed to permit this useful approach to be more widely employed. In this paper, we propose and evaluate a novel entropy-based method for ascertaining stability. The contributions of this paper are to first highlight the need for a convergence measure which is reliable, automatic, and easily computed; second, we propose one such measure, and place it on a theoretical footing; finally, we give results both with simulated Gaussian noise having a typical sensor power spectrum, as well as experimental results using the type of optical sensor which would benefit from the proposed method. It is demonstrated that this approach produces a reliable asymptotic figure for convergence, both under simulated noise conditions as well as with real measurements in the field. [ABSTRACT FROM PUBLISHER]

Embedded processors have been widely used for building up Internet of Things (IoT) platforms, in which the security issue is becoming critical. This paper studies efficient techniques of lattice-based cryptography on these processors and presents the first implementation of ring-LWE encryption on ARM NEON and MSP430 architectures. For ARM NEON architecture, we propose a vectorized version of Iterative Number Theoretic Transform (NTT) for high-speed computation of polynomial multiplication on ARM NEON platforms and a 32-bit variant of SAMS2 technique for fast reduction. For MSP430 architecture, we propose an optimized SWAMS2 reduction technique, which consists of five different basic operations, including Shifting, Swapping, Addition, and two Multiplication-Subtractions. Regarding of the sampling from the discrete Gaussian distribution, we adopt Knuth-Yao sampler, accompanied with optimized methods such as Look-Up Table (LUT) and byte-scanning. Subsequently, a full-fledged implementation of Ring-LWE is presented by both taking advantage of our proposed method and previous optimization techniques re-designed for desired platforms. Our ring-LWE implementation of encryption/decryption at a classical security level of 128 bits requires only $149.4k/32.8k$ 149. 4 k / 32. 8 k clock cycles on ARM NEON, and $2126.3k/244.5k$ 2126. 3 k / 244. 5 k clock cycles on MSP430. These results are roughly 7 times faster than the fastest ECC implementation on desired platforms with same security level. [ABSTRACT FROM AUTHOR]

Side-channel attacks are a concrete and practical threat to the security of computing systems, ranging from high performance platforms to embedded devices. In this paper, we will provide a brief systematization of the current existing approaches to analyze the side-channel vulnerability of an implementation, or automatically implement countermeasures, relying on methodologies typical of compiler systems. We will dedicate a spotlight to a significant progress in the countermeasures techniques which is represented by the application of dynamic compilation techniques to prevent a side-channel attacker from devising a model of the attacked application. We conclude the work highlighting promising research directions in this field. [ABSTRACT FROM AUTHOR]

As software may be used by multiple users, caching popular software at the wireless edge has been considered to save computation and communications resources for mobile edge computing (MEC). However, fetching uncached software from the core network and multicasting popular software to users have so far been ignored. Thus, existing design is incomplete and less practical. In this paper, we propose a joint caching, computation and communications mechanism which involves software fetching, caching and multicasting, as well as task input data uploading, task executing (with non-negligible time duration) and computation result downloading, and mathematically characterize it. Then, we optimize the joint caching, offloading and time allocation policy to minimize the weighted sum energy consumption subject to the caching and deadline constraints. The problem is a challenging two-timescale mixed integer nonlinear programming (MINLP) problem, and is NP-hard in general. We convert it into an equivalent convex MINLP problem by using some appropriate transformations and propose two low-complexity algorithms to obtain suboptimal solutions of the original non-convex MINLP problem. Specifically, the first suboptimal solution is obtained by solving a relaxed convex problem using the consensus alternating direction method of multipliers (ADMM), and then rounding its optimal solution properly. The second suboptimal solution is proposed by obtaining a stationary point of an equivalent difference of convex (DC) problem using the penalty convex-concave procedure (Penalty-CCP) and ADMM. Finally, by numerical results, we show that the proposed solutions outperform existing schemes and reveal their advantages in efficiently utilizing storage, computation and communications resources. [ABSTRACT FROM AUTHOR]

As the first provably capacity-achieving codes, polar codes have been selected as the coding scheme for 5G enhanced mobile broadband (eMBB) control channels. Furthermore, if the bottleneck in decoding complexity is addressed, polar codes are still promising for long code length scenarios in the future with superior error-correcting performance. Considering the demand of cloud radio access network (C-RAN) in 5G system, the low-latency software polar decoder is studied in this paper. Two novel algorithms are proposed to reduce the latency of the successive cancellation list (SCL) decoding, including the segmented list-pruning (SLP) algorithm and the modified distributed sorting (MDS) algorithm. Moreover, the proposed SLP algorithm improves the decoding performance compared to existing segmentation schemes. In terms of the software implementation, our decoder is nearly $20\%$ faster than the state-of-the-art flexible software polar list decoder. [ABSTRACT FROM AUTHOR]

In order to provide dynamic adaptation of the performance/energy tradeoff, systems today rely on heterogeneous multicore architectures (different micro-architectures on a chip). These systems are limited to single-ISA approaches to enable transparent migration between the different cores. To offer more tradeoff, we can integrate statically scheduled micro-architecture and use dynamic binary translation (DBT) for task migration. However, in a system where performance and energy consumption are a prime concern, the translation overhead has to be kept as low as possible. In this paper, we present Hybrid-DBT, an open-source, hardware accelerated DBT system targeting VLIW cores. Three different hardware accelerators have been designed to speed-up critical steps of the translation process. Experimental study shows that the accelerated steps are two orders of magnitude faster than their software equivalent. The impact on the total execution time of applications and the quality of generated binaries are also measured. [ABSTRACT FROM AUTHOR]

This paper exploits the torque–speed operating limits of a dual three-phase interior permanent magnet synchronous machine (ADT-IPMSM) during postfault operation for different neutral configurations. To achieve the maximum permissible torque–speed limits, the study proposes software and hardware modifications to the latest fault-tolerant techniques using: an offline optimization that takes into account simultaneously the voltage and current constraints during postfault operation and a simple hardware addition that modifies the neutral points configuration to either isolatede (1N) or connected (2N) based on the operating torque and/or speed. Compared to the literature, the proposed study considers the field-weakening operation, extending the permissible achievable speeds. A 2.5-kW ADT-IPMSM prototype validates the theoretical findings. [ABSTRACT FROM AUTHOR]

Since the development of computer science, our lives have become increasingly dependent on software. While we enjoy the benefits and convenience that software programs provide, we cannot ignore issues with software reliability, complexity, and security. Since the introduction of complex networks, people have been using software network to analyze software problems; however, traditional software network models are not currently capable of analyzing software with large scale and complex structures. In this paper, a new software network model is proposed, with which each node in the network can be assigned a set of coordinates that reflect its function-call information and make the disorder of the network graph more orderly. Additionally, characteristics and derivatives of the model are thoroughly examined and analyzed. A case study using the coordinate model combined with bug information is then conducted to analyze five different software programs. The results show that the proposed model can be used to analyze the relationship between nodes or defects distribution and software network parameters, as well as high-risk module excavation through a defect density analysis. Compared to traditional software network models, the model maintains the inner logic relationship of the software systems better, which makes it easier to analyze many aspects of software. [ABSTRACT FROM AUTHOR]

In this paper, a simple energy-efficient physical layer modulation scheme termed as random number modulation (RNM) is proposed. It is a class of new systems that harness the randomness of pseudo random number generators (RNGs) for efficient communication, and adds a new degree of freedom to digital communication systems. It is also highly adaptable to high-rate, low-latency, and low-rate, high-energy efficiency scenarios. This paper includes a detailed system model, preliminary performance analysis, and extended discussions. The performance of the proposed system is analyzed in terms of symbol and block error probabilities, energy efficiency, and latency. It is shown that there is a fundamental tradeoff between the energy efficiency and the latency of the proposed system, and they can be easily software programmable allowing devices to adapt to different circumstances and environments rapidly. Based upon the basic system model herein, it is anticipated that more sophisticated RNM systems can be developed. [ABSTRACT FROM PUBLISHER]

The annotation of significant events within soccer videos is a fundamental step in content-based soccer video retrieval. In this paper, we propose a soccer video annotation approach based on semantic matching with coarse time constraints, where video events and external text information (match reports) are synchronized using their semantic correspondence in the temporal sequence. Unlike the state-of-the-art soccer video analysis methods that assume that the time of an event’s occurrence is given precisely by the external text information, this paper considers the problem of annotating soccer videos using match reports with coarse-grained time information. The contributions of the proposed approach are: 1) we propose a more generalized approach that synchronizes video events with text descriptions using high-level semantics with coarse time constraints, rather than assuming that the timestamp is given exactly in the text description; 2) the detection of event boundaries is improved by attack–defense transition analysis (ADTA); 3) a robust and fast center circle detection algorithm is proposed for the classification of soccer field zones and ADTA; and 4) unlike conventional audio-based whistle detection, we propose a novel Hough-transform-based algorithm from the perspective of image processing. This allows the game start time to be detected, and further helps the synchronization of video and text events. The experimental results conducted on a large number of soccer videos validate the effectiveness of the proposed approach. [ABSTRACT FROM PUBLISHER]

Over the past ten years, human re-identification has received increased attention from the computer vision research community. However, for the most part, these research papers are divorced from the context of how such algorithms would be used in a real-world system. This paper describes the unique opportunity our group of academic researchers had to design and deploy a human re-identification system in a demanding real-world environment: a busy airport. The system had to be designed from the ground up, including robust modules for real-time human detection and tracking, a distributed, low-latency software architecture, and a front-end user interface designed for a specific scenario. None of these issues are typically addressed in re-identification research papers, but all are critical to an effective system that end users would actually be willing to adopt. We detail the challenges of the real-world airport environment, the computer vision algorithms underlying our human detection and re-identification algorithms, our robust software architecture, and the ground-truthing system required to provide the training and validation data for the algorithms. Our initial results show that despite the challenges and constraints of the airport environment, the proposed system achieves very good performance while operating in real time. [ABSTRACT FROM PUBLISHER]

Traditional standalone embedded system is limited in their functionality, flexibility, and scalability. Fog computing platform, characterized by pushing the cloud services to the network edge, is a promising solution to support and strengthen traditional embedded system. Resource management is always a critical issue to the system performance. In this paper, we consider a fog computing supported software-defined embedded system, where task images lay in the storage server while computations can be conducted on either embedded device or a computation server. It is significant to design an efficient task scheduling and resource management strategy with minimized task completion time for promoting the user experience. To this end, three issues are investigated in this paper: 1) how to balance the workload on a client device and computation servers, i.e., task scheduling, 2) how to place task images on storage servers, i.e., resource management, and 3) how to balance the I/O interrupt requests among the storage servers. They are jointly considered and formulated as a mixed-integer nonlinear programming problem. To deal with its high computation complexity, a computation-efficient solution is proposed based on our formulation and validated by extensive simulation based studies. [ABSTRACT FROM PUBLISHER]

Part-based models have demonstrated their merit in object detection. However, there is a key issue to be solved on how to integrate the inaccurate scores of part detectors when there are occlusions, abnormal deformations, appearances, or illuminations. To handle the imperfection of part detectors, this paper presents a probabilistic pedestrian detection framework. In this framework, a deformable part-based model is used to obtain the scores of part detectors and the visibilities of parts are modeled as hidden variables. Once the occluded parts are identified, their effects are properly removed from the final detection score. Unlike previous occlusion handling approaches that assumed independence among the visibility probabilities of parts or manually defined rules for the visibility relationship, a deep model is proposed in this paper for learning the visibility relationship among overlapping parts at multiple layers. The proposed approach can be viewed as a general postprocessing of part-detection results and can take detection scores of existing part-based models as input. The experimental results on three public datasets (Caltech, ETH, and Daimler) and a new CUHK occlusion dataset (http://www.ee.cuhk.edu.hk/~xgwang/CUHK_pedestrian.html), which is specially designed for the evaluation of occlusion handling approaches, show the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

Being the first codes achieving the capacity of symmetric binary-input discrete memoryless channels, polar codes have been favorable and standardized for enhanced mobile broadband (eMBB) control channels. In future mobile communications, the entire system is required to be flexible and adaptive to varying scenarios. Therefore, efficient software implementation of polar decoder is expected. Existing software successive cancellation list polar decoder can achieve good performance but with a good memory consumption. For short control channel codes, a more memory-efficient alternative is sphere decoder, but its latency gives rise to another issue. Equipped with a breadth-first search to keep a fixed complexity, list sphere decoder (LSD) is also considered. To improve the performance of LSD, a software LSD with synchronous determination is proposed in this paper. We precalculate the synchro sets to improve the decoding, which leads to a performance gain. Meanwhile, the decoding process is simplified due to the precalculation, which attains even lower complexity. Implemented with C++, the proposed decoder can achieve up to 2 dB performance gain compared with the existing LSD. [ABSTRACT FROM AUTHOR]

Smart TVs are coming to dominate the television market. This accompanied by an increase in the use of the smart TV applications (apps). Due to the increasing demand, developers need modeling techniques to analyze these apps and assess their comprehensiveness, completeness, and quality. In this paper, we present an automated strategy for generating models of smart TV apps based on a black-box reverse engineering. The strategy can be used to cumulatively construct a model for a given app by exploring the user interface in a manner consistent with the use of a remote control device and extracting the runtime information. The strategy is based on capturing the states of the user interface to create a model during runtime without any knowledge of the internal structure of the app. We have implemented our strategy in a tool called EvoCreeper. The evaluation results show that our strategy can automatically generate unique states and a comprehensive model that represents the real user interactions with an app using a remote control device. The models thus generated can be used to assess the quality and completeness of smart TV apps in various contexts, such as the control of other consumer electronics in smart houses. [ABSTRACT FROM AUTHOR]

This paper presents a traveling-wave-based fault location method for two terminal transmission lines using unsynchronized current measurements from intelligent electronic devices (IEDs) recorded at both ends. In the formulation, the method considers practical implementation issues such as IED hardware and software processing delays, and data synchronization error. In this method, two possible fault location solutions are determined using the first two traveling wave arrival time recorded at both terminals. Then, the correct fault location is identified between the two based on the faulted half-section information. Identification of faulted half-section is accomplished by comparing the rise time of the first traveling wave recorded at both terminals of the line. The proposed method does not require GPS synchronization and field experiments to calibrate the various asymmetrical delays and synchronization error. The method is tested on a 220 kV transmission line using data simulated in EMTDC/PSCAD tool with frequency-dependent phase models. The proposed method can locate faults using unsynchronized data with various asymmetrical delays, whereas classical methods work properly only for synchronized data with symmetrical delays. The performance of the proposed method is evaluated for different fault scenarios. The proposed method demonstrated high accuracy, noise immunity, robustness against fault inception angles, and high impedance faults. Test results are compared with classical two-terminal methods for a transmission line. [ABSTRACT FROM AUTHOR]

Embedded systems present stringent and often conflicting requirements. On the one side, the need for high performance within a tight energy budget favors inflexible Application Specific Integrated Circuit (ASIC) implementations; on the other side, a short time-to-market demands programmability. Hybrid architectures such as special-purpose customized processors represent an attractive solution, as they are programmable by software, but use dedicated hardware to accelerate parts of the computation. In such a scenario, the capability of automatically identifying the computation parts to be realized in hardware is highly desirable, in order to reduce design time and effort. This paper aims at advancing the state-of-the-art in this field. We recognize that subgraphs of control flow graphs having a single input control point and a single output control point, that we call regions, are good targets for the synthesis of application specific hardware accelerators. We therefore provide a method to identify them and an LLVM-based toolchain (named RegionSeeker) that, analyzing a software application, automatically selects its most profitable regions given an area constraint. Experimental evidence shows that the accelerators identified by RegionSeeker provide a speedup of up to $4.6\boldsymbol {\times }$ and, on average, approximately 30% higher speedup is achieved compared to state-of-the-art identification techniques. [ABSTRACT FROM AUTHOR]

As the size and complexity of high performance computing (HPC) systems grow in line with advancements in hardware and software technology, HPC systems increasingly suffer from performance variations due to shared resource contention as well as software- and hardware-related problems. Such performance variations can lead to failures and inefficiencies, which impact the cost and resilience of HPC systems. To minimize the impact of performance variations, one must quickly and accurately detect and diagnose the anomalies that cause the variations and take mitigating actions. However, it is difficult to identify anomalies based on the voluminous, high-dimensional, and noisy data collected by system monitoring infrastructures. This paper presents a novel machine learning based framework to automatically diagnose performance anomalies at runtime. Our framework leverages historical resource usage data to extract signatures of previously-observed anomalies. We first convert collected time series data into easy-to-compute statistical features. We then identify the features that are required to detect anomalies, and extract the signatures of these anomalies. At runtime, we use these signatures to diagnose anomalies with negligible overhead. We evaluate our framework using experiments on a real-world HPC supercomputer and demonstrate that our approach successfully identifies 98 percent of injected anomalies and consistently outperforms existing anomaly diagnosis techniques. [ABSTRACT FROM AUTHOR]

The increasing penetration of renewable energy resources, such as wind and solar, is changing AC grid dynamics. Potential dynamic stability issues such as small signal instability may occur when these resources are connected to a grid with low strength, i.e., a weak grid. In this paper, the relationships between small signal stability and grid strength measured with short circuit ratio (SCR), along with the relationships between the stability boundary and critical SCR (CSCR) are analytically studied in a single-infeed power electronic system (SIPES). On this basis, these relationships are extended to a multi-infeed power electronic system (MIPES) through eigenvalue decomposition techniques to define the so-called generalized short circuit ratio (gSCR) and critical gSCR (CgSCR) for small signal stability analysis. The defined gSCR and CgSCR are the generalized representation of SCR and CSCR for SIPESs in MIPESs. The gSCR can assess the grid strength of a MIPES in terms of its small signal stability while the CgSCR can characterize the stability boundary of a MIPES. In addition, the condition of CgSCR = CSCR is satisfied for a MIPES with homogeneous power electronic devices. This enables the proposed method based on the gSCR to simplify the complex stability analysis of MIPESs into the stability study of SIPESs. The efficacy of the proposed gSCR and CgSCR is validated with eigenvalue analysis and time-domain simulations. [ABSTRACT FROM AUTHOR]

The initiation of tracks for newly discovered objects presents unique challenges in space situational awareness. Recent work explores the use of admissible regions to initialize filters for space object tracking; however, these methods require follow-on measurements to refine the initial admissible region solution. This paper presents an approach to the joint search and track problem, designed to allow a single sensor to build and maintain a catalog of objects without requiring ana prioriestimate. [ABSTRACT FROM AUTHOR]

In recent years, misconfigurations have become one of the major causes of software system failures, resulting in numerous service outages. What is worse, misconfigurations are also costly to diagnose and troubleshoot. This remains a great challenge for sysadmins (system administrators) to detect, diagnose, or troubleshoot these misconfigurations. Unlike software bugs, misconfigurations are more vulnerable to sysadmins’ mistakes. Developers and researchers are attempting to improve system reactions to misconfigurations to ease the burden of sysadmins’ diagnoses. Such efforts would greatly benefit from the techniques that can comprehensively detect bad system reactions through injected misconfigurations. Unfortunately, few such studies have achieved the above goal in the past, primarily because they only relied on generic alterations and failed to find a way to systematically generate misconfigurations. In this paper, we study eight mature open-source and commercial software packages and summarize a fine-grained classification of option types. Based on this classification, we use Augmented Backus–Naur Form to summarize and extract syntactic and semantic constraints of each type. In order to generate comprehensive misconfigurations in the test systems, we propose misconfiguration generation methods for our constraints. We implement a tool named Configuration Vulnerability Detector (ConfVD) to conduct misconfiguration injection and further analyze the systems’ reaction abilities to various misconfigurations. We carried out comprehensive analyses upon Apache Httpd, MySQL, PostgreSQL, and Yum. The results of our analysis show that our option classification covers 96% of 1582 options from the above-mentioned systems. Our constraints are more fine grained than previous works and their accuracy was found to be 91% (ascertained by manual verification). Our technique could improve generic alteration approaches without constraints, and we found that ConfVD could find nearly three times the bad reactions that were found by ConfErr. In total, we found 65 bad reactions from the systems being tested and our fine-grained constraints contributed 27.7% more bad reactions than techniques only using coarse-grained constraints. [ABSTRACT FROM AUTHOR]

GPUs have been becoming an indispensable computing platform in data centers, and co-locating multiple applications on the same GPU is widely used to improve resource utilization. However, performance interference due to uncontrolled resource contention severely degrades the performance of co-locating applications and fails to deliver satisfactory user experience. In this paper, we present SMGuard, a software approach to flexibly manage the GPU resource usage of multiple applications under co-location. We also propose a capacity based GPU resource model CapSM, which provisions the GPU resources in a fine-grained granularity among co-locating applications. When co-locating latency-sensitive applications with batch applications, SMGuard can prevent batch applications from occupying resources without constraint using quota based mechanism, and guarantee the resource usage of latency-sensitive applications with reservation based mechanism. In addition, SMGuard supports dynamic resource adjustment through evicting the running thread blocks of batch applications to release the occupied resources and remapping the uncompleted thread blocks to the remaining resources, which avoids the relaunch of the preempted kernel. The SMGuard is a pure software solution that does not rely on special GPU hardware or programming model, which is easy to adopt on commodity GPUs in data centers. Our evaluation shows that SMGuard improves the average performance of latency-sensitive applications by 9.8× when co-located with batch applications. In the meanwhile, the GPU utilization can be improved by 35 percent on average. [ABSTRACT FROM AUTHOR]

Versatile video coding is the next generation video coding standard expected by the end of 2020. Several new contributions have been proposed to enhance the coding efficiency beyond the high efficiency video coding standard. One of these tools is the adaptive multiple transform (AMT) as a new approach of the transform core design. The AMT involves five discrete cosine transform/discrete sine transform types with larger and more flexible partitioning block sizes. However, the AMT coding efficiency comes with the cost of higher computational complexity, especially at the encoder side. In this paper, a efficient pipelined hardware implementation of the AMT including the five types of sizes $4\times 4$ , $8\times 8$ , $16\times 16$ and $32\times 32$ is proposed. The architecture design takes advantage of the internal software/hardware resources of the target field-programmable gate array device such as library of parametrized modules core intellectual properties and digital signal processing blocks. The proposed 1-D 32-point AMT design allows to process 4K video at 44 frames/s. A unified 2-D implementation of the 4, 8, 16, and 32-point AMT design is also presented.The implementation takes into account all the asymmetric 2-D block size combinations from 4 to 32. The 2-D architecture design is able to sustain 2K video coding at 50 frames/s with an operational frequency up to 147 MHz. [ABSTRACT FROM AUTHOR]

Islanded microgrids provide unique challenges due to the lack of transmission support, requiring local energy supply and grid regulation architecture. This paper presents a unified probabilistic assessment of wind reserves for demand response (DR) and frequency regulation in islanded microgrids. A multivariate nonparametric kernel density estimation algorithm is used to generate the probabilistic models of the wind resource, electrical demand, and predicted performance of wind generation. These models are numerically combined to evaluate the capability of wind generation to act as a dynamic reserve and predict its performance for DR, secondary generation, and frequency regulation in an islanded system. The probabilistic model captures multivariate cross-correlation, nonstationary environmental and load behavior, as well as multimodality in their underlying probability distributions. A case study is conducted to validate the proposed model, which predicts wind generation effectiveness for varying load profiles, wind profiles, and generation capacities. PLEXIM simulation software is used to implement a model microgrid to demonstrate the integration of wind generation and its regulatory capabilities. The proposed algorithm has applications in power system planning and operation, and it provides a method using probabilistic data set for long term energy management and optimization of islanded microgrids. [ABSTRACT FROM AUTHOR]

This paper presents a simple and accurate industrial tool that can be used to estimate the full-load efficiency of three-phase induction motors based on no-load tests. The objective of this research work is to eliminate the need for the expensive dynamometer test, which is available only in well-equipped laboratories and provide electric motor service centers in North America with a user-friendly tool that enables the centers to have their rewound, refurbished, or any existing motors evaluated for efficiency prior to delivery to customers. The proposed technique utilizes a test data of 129 motors, ranging from 1 to 500 hp, tested in Hydro-Québec Laboratory as per IEEE Std. 112B and CAN/CSA C390 standards procedures. The technique also utilizes a recently proposed stray-load loss formula. The algorithm is validated by recalculating the efficiency of the 195 motors by using the proposed technique. The results show an acceptable degree of accuracy. Error analysis study is conducted to examine the level of uncertainty within the accuracy of the proposed algorithm. The outcome of the study completely supports the algorithm. A spreadsheet-based software is designed to turn the algorithm into a practical user-friendly industrial tool. [ABSTRACT FROM AUTHOR]

Nonorthogonal multiple access (NOMA) has been considered as an essential multiple access technique for enhancing system capacity and spectral efficiency in future communication scenarios. However, the existing NOMA systems have a fundamental limit: high computational complexity and a sharply changing wireless channel make exploiting the characteristics of the channel and deriving the ideal allocation methods very difficult tasks. To break this fundamental limit, in this paper, we propose a novel and effective deep learning (DL)-aided NOMA system, in which several NOMA users with random deployment are served by one base station. Since DL is advantageous in that it allows training the input signals and detecting sharply changing channel conditions, we exploit it to address wireless NOMA channels in an end-to-end manner. Specifically, it is employed in the proposed NOMA system to learn a completely unknown channel environment. A long short-term memory (LSTM) network based on DL is incorporated into a typical NOMA system, enabling the proposed scheme to detect the channel characteristics automatically. In the proposed strategy, the LSTM is first trained by simulated data under different channel conditions via offline learning, and then the corresponding output data can be obtained based on the current input data used during the online learning process. In general, we build, train and test the proposed cooperative framework to realize automatic encoding, decoding and channel detection in an additive white Gaussian noise channel. Furthermore, we regard one conventional user activity and data detection scheme as an unknown nonlinear mapping operation and use LSTM to approximate it to evaluate the data detection capacity of DL based on NOMA. Simulation results demonstrate that the proposed scheme is robust and efficient compared with conventional approaches. In addition, the accuracy of the LSTM-aided NOMA scheme is studied by introducing the well-known tenfold cross-validation procedure. [ABSTRACT FROM AUTHOR]

This paper proposes a new data prefetching technique for Graphics Processing Units (GPUs) called Warp Aware Selective Prefetching (WASP). The main idea of WASP is to dynamically select warps whose progress is slower than that of the current warp as prefetching target warps. Under the in-order instruction execution model of GPUs, these prefetching target warps will certainly execute the same load as the current warp. Exploiting that, WASP prefetches the data for prefetching target warps, which allows the prefetched data to be accurately accessed. To simply verify the progress of the warps, WASP monitors the counts of the dynamic load executions for all warps. When a warp executes a load, WASP searches the warps with lower load execution counts than the current warp and generates the prefetch requests for them. In our evaluation, WASP achieves a 16.8 percent speedup compared to the baseline GPU. [ABSTRACT FROM AUTHOR]

Casper is a process-based asynchronous progress model for MPI one-sided communication on multi- and many-core architectures. The one-sided communication is not truly one-sided in most MPI implementations: the target process still relies on software progress to complete incoming operations. Casper allows the user to specify an arbitrary number of cores dedicated to background ghost processes and transparently redirects the RMA operations to ghost processes by utilizing the PMPI redirection and MPI-3 shared-memory technologies. Although Casper benefits applications that suffer from lack of asynchronous progress, the operation redirection design might not support complex multiphase applications effectively, which often involve dynamically changing communication density and computing workloads. In this paper, we present an adaptive mechanism in Casper to address the limitation of static asynchronous progress in multiphase applications. We exploit two adaptive strategies, a user-guided strategy and a fully transparent and automatic strategy based on self-profiling and prediction, to dynamically reconfigure the asynchronous progress in Casper according to real-time performance characteristics during multiphase execution. We evaluate the adaptive approaches in both microbenchmarks and a real quantum chemistry application suite, NWChem, on the Cray XC30 supercomputer and an Intel Omni-Path cluster. [ABSTRACT FROM AUTHOR]