Data-driven nonparametric Li-ion battery ageing model aiming at learning from real operation data – Part A : storage operation

Conventional Li-ion battery ageing models, such as electrochemical, semi-empirical and empirical models, require a significant amount of time and experimental resources to provide accurate predictions under realistic operating conditions. At the same time, there is significant interest from industry in the introduction of new data collection telemetry technology. This implies the forthcoming availability of a significant amount of real-world battery operation data. In this context, the development of ageing models able to learn from in-field battery operation data is an interesting solution to mitigate the need for exhaustive laboratory testing

Efñcient Test Generation Guided by Field Coverage Gritería

Field-exhaustive testing is a testing criterion that requires suites to contain enough test inputs to cover all feasible valúes for fields within a certain input-size bound. While previous work shows that field- exhaustive suites can be automatically generated, the generation tech- nique requires a formal specification of the inputs that can be subject to SAT-based analysis. Moreover, this constraint together with the resfrie- tion of producing all feasible valúes for input fields makes test generation costly, and field-exhaustive testing difficult to generalize to further testing domains. In this paper, we deal with field. coverage as testing criteria that measure the degree to which a program is tested by examining to what extent the valúes of inputs’ fields are covered. We show that this notion generalizes field-exhaustive testing, withdrawing the need for a SAT-analyzable formal specification, and thus can be combined with any test generation technique to produce smaller test suites, reducing testing time. In particular, we consider field coverage: (i) in combination with test generation based on symbolic execution, to produce underapproximations of all testing sequences; (ii) as a relaxation of bounded-exhaustive testing, producing smaller suites using the Korat tool; and (iii) in combination with random testing, producing smaller test suites and even serving as a termination criterion for generation. As we show, in all these cases field coverage helps producing significantly smaller suites, thus contributing to testing time, while retaining the effectiveness of the corresponding original techniques, in terms of test suite quality.Sociedad Argentina de Informática e Investigación Operativ

Study of Different Aspects of Software Testing and Problem Analysis in Security Issues in Project Development

Software is a term, which referred information or program which is used by a computer. There is a rapidly growth in the software field so the software testing is becoming an important part in the field of software industry. Software testing is an important part in the software field, which is an ancient term used in this field. Software testing is used in the software field for determining the quality of the software. Automatic methods are used for ensuring the software correctness range from static techniques to dynamic technique. In static technique model checking or static analysis is used for checking the software. In these technique there has some strengths & some weaknesses like, model checking is automatic & exhaustive but has scalability issues. Static technique scales to very large program but gives to many false warnings

Fair comparison of skin detection approaches on publicly available datasets

Skin detection is the process of discriminating skin and non-skin regions in a digital image and it is widely used in several applications ranging from hand gesture analysis to track body parts and face detection. Skin detection is a challenging problem which has drawn extensive attention from the research community, nevertheless a fair comparison among approaches is very difficult due to the lack of a common benchmark and a unified testing protocol. In this work, we investigate the most recent researches in this field and we propose a fair comparison among approaches using several different datasets. The major contributions of this work are an exhaustive literature review of skin color detection approaches, a framework to evaluate and combine different skin detector approaches, whose source code is made freely available for future research, and an extensive experimental comparison among several recent methods which have also been used to define an ensemble that works well in many different problems. Experiments are carried out in 10 different datasets including more than 10000 labelled images: experimental results confirm that the best method here proposed obtains a very good performance with respect to other stand-alone approaches, without requiring ad hoc parameter tuning. A MATLAB version of the framework for testing and of the methods proposed in this paper will be freely available from https://github.com/LorisNann

An investigation into wayside hot-box detector efficacy and optimization

Wayside hot-box detectors (HBDs) are devices used to assess the health of railcar components including bearings, axles, and brakes by monitoring their temperatures. HBDs use infrared (IR) sensors to record the temperatures of railroad bearings. Bearings that trigger an alarm or exhibit warm trending are removed and sent for inspection. In many cases, no discernable defects were found in the flagged bearings. Motivated by this finding, an investigation was conducted which included performing a controlled field test as well as exhaustive laboratory testing utilizing an HBD simulator. Data acquired from field and laboratory testing was used to evaluate the accuracy and efficacy of wayside HBDs. The results suggest that the scanning location on the bearing cup significantly affects the temperature measurement. Different calibrations for the field- and laboratory-acquired data were also explored. An optimized calibration technique along with proper IR sensor alignment can markedly improve the accuracy of HBD measurements

Iso-duration determination of D´ and CS under laboratory and field conditions

Whilst Critical Speed (CS) has been successfully translated from the laboratory into the field, this translation is still outstanding for the related maximum running distance (D´). Using iso-duration exhaustive laboratory and field runs, this study investigated the potential interchangeable use of both parameters, D´ and CS. After an incremental exercise test, ten male participants (age: 24.9±2.1 yrs; height: 180.8±5.8 cm; body mass: 75.3±8.6 kg; V ̇O2peak 52.9±3.1 mL∙min-1∙kg-1) performed three time-to-exhaustion runs on a treadmill followed by three exhaustive time-trial runs on a 400 m athletics outdoor track. Field time-trial durations were matched to their respective laboratory time-to-exhaustion runs. D´ and CS were calculated using the inverse-time model (speed=D´/t+CS). Laboratory and field values of D´ and CS were not significantly different (221±7 m vs. 225±72 m; P = 0.73 and 3.75±0.36 m∙s-1 vs. 3.77±0.35 m∙s-1, P = 0.68), and they were significantly correlated (r = 0.86 and 0.94). The 95% LoA were ±75.5m and ±0.24 m∙s-1 for D´ and CS, respectively. Applying iso-durations provides non-significant differences for D´ and CS and a significant correlation between conditions. This novel translation testing method can consequently be recommended to coaches and practitioners, however a questionable level of agreement indicates to use D´ with caution

Consistent SDNs through Network State Fuzzing

The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Nevertheless, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part. Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to continuously test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly

Consistent SDNs through Network State Fuzzing

The conventional wisdom is that a software-defined network (SDN) operates under the premise that the logically centralized control plane has an accurate representation of the actual data plane state. Unfortunately, bugs, misconfigurations, faults or attacks can introduce inconsistencies that undermine correct operation. Previous work in this area, however, lacks a holistic methodology to tackle this problem and thus, addresses only certain parts of the problem. Yet, the consistency of the overall system is only as good as its least consistent part. Motivated by an analogy of network consistency checking with program testing, we propose to add active probe-based network state fuzzing to our consistency check repertoire. Hereby, our system, PAZZ, combines production traffic with active probes to periodically test if the actual forwarding path and decision elements (on the data plane) correspond to the expected ones (on the control plane). Our insight is that active traffic covers the inconsistency cases beyond the ones identified by passive traffic. PAZZ prototype was built and evaluated on topologies of varying scale and complexity. Our results show that PAZZ requires minimal network resources to detect persistent data plane faults through fuzzing and localize them quickly while outperforming baseline approaches.Comment: Added three extra relevant references, the arXiv later was accepted in IEEE Transactions of Network and Service Management (TNSM), 2019 with the title "Towards Consistent SDNs: A Case for Network State Fuzzing

Fast Quantum Algorithm for Solving Multivariate Quadratic Equations

In August 2015 the cryptographic world was shaken by a sudden and surprising announcement by the US National Security Agency NSA concerning plans to transition to post-quantum algorithms. Since this announcement post-quantum cryptography has become a topic of primary interest for several standardization bodies. The transition from the currently deployed public-key algorithms to post-quantum algorithms has been found to be challenging in many aspects. In particular the problem of evaluating the quantum-bit security of such post-quantum cryptosystems remains vastly open. Of course this question is of primarily concern in the process of standardizing the post-quantum cryptosystems. In this paper we consider the quantum security of the problem of solving a system of {\it $m$ Boolean multivariate quadratic equations in $n$ variables} (\MQb); a central problem in post-quantum cryptography. When $n=m$, under a natural algebraic assumption, we present a Las-Vegas quantum algorithm solving \MQb{} that requires the evaluation of, on average, $O(2^{0.462n})$ quantum gates. To our knowledge this is the fastest algorithm for solving \MQb{}