Automatic test case generation from Simulink/Stateflow models using model checking

Model‐based test generation techniques based on random input generation and guided simulation do not satisfy the demands of high test coverage and completeness guarantees as required by safety‐critical applications. Recently, test generation techniques based on model checking have been reported to bridge this gap. To evaluate the effectiveness of these techniques, an in‐house tool suite, AutoMOTGen, has been developed for Simulink/Stateflow and applied on real‐life case studies at General Motors. This paper outlines the test generation methodology of AutoMOTGen and gives a comparative study with a commercial, primarily random input‐based, test generation tool on the same set of examples. The results indicate that in terms of coverage, model checking‐based techniques complement the random input‐based techniques. In addition, they provide proofs for unreachability that can aid in debugging the models. Therefore, it is recommended that model checking‐based tools be utilized to complement and enhance the effectiveness of model‐based testing methods in safety‐critical systems engineering. Copyright © 2013 John Wiley & Sons, Ltd.     

Comparative study on linearized robot models

For representing the input—output behaviour of a robot manipulator by a linear time-invariant model, four direct linearization schemes are: (i) state linearization, (ii) linearization based on an identification method, (iii) linearization based on neglecting velocity-dependent and gravity terms and (iv) linearization based on neglecting the velocity-dependent term only (rate linearization). In order to make an appropriate choice of linear model for the development of real-time control, these schemes are extensively studied in this paper. It is shown that the rate linearization method leads to a satisfactory tradeoff between computation, accuracy, and stability. In the case of high velocity motions, a combination of state linearization and rate linearization is proposed.     

Defect Oriented Testing of Analog Circuits Using Wavelet Analysis of Dynamic Supply Current

In recent years, Defect Oriented Testing (DOT) has been investigated as an alternative testing method for analog circuits. In this paper, we propose a wavelet transform based dynamic supply current (IDD) analysis technique for detecting catastrophic and parametric faults in analog circuits. Wavelet transform has the property of resolving events in both time and frequency domain simultaneously unlike Fourier transform which decomposes a signal in frequency components only. Simulation results on benchmark circuits show that wavelet transform has higher fault detection sensitivity than Fourier or time-domain methods and hence, can be considered very promising for defect oriented testing of analog circuits. Effectiveness of wavelet transform based DOT amidst process variation and measurement noise is studied.This research is supported in part by MARCO GSRC under contract number SA3273JB.A paper based on this work was presented at the Fourth IEEE Latin American Test Workshop, Natal, Brazil, February 2003.Swarup Bhunia received the undergraduate degree from Jadavpur University, Calcutta, India, and the Masters degree from the Indian Institute of Technology (IIT), Kharagpur. He is currently working toward the Ph.D. degree in the Department of Electrical Engineering, Purdue University, West Lafayette, IN.He has worked in the EDA industry on RTL synthesis and verification since 2000. His research interest includes defect-based testing, diagnosis, noise analysis, and noise-aware design.Arijit Raychowdhury received the B.E. degree in 2001 in electronics and telecommunication engineering from Jadavpur University, India. He is currently pursuing the Ph.D. degree in electrical and computer engineering in Purdue University, West Lafayette, IN.He has worked as an analog circuit designer in Texas Instruments India. His research interests include device/circuit design for scaled silicon and nonsilicon devices. He has received academic excellence awards in 1997, 2000, and 2001 and Messner Fellowship from Purdue University in 2002. Mr. Raychowdhury has been awarded the Best Student Paper Award in the IEEE Nanotechnology Conference, 2003.Kaushik Roy received the B.Tech. degree in electronics and electrical communications engineering from the Indian Institute of Technology, Kharagpur, India, and the Ph.D. degree from the Electrical and Computer Engineering Department, University of Illinois, Urbana, in 1990. He was with the Semiconductor Process and Design Center of Texas Instruments, Dallas, TX, where he worked on FPGA architecture development and low-power circuit design. He joined the electrical and computer engineering faculty, Purdue University, West Lafayette, IN, in 1993, where he is currently a Professor. His research interests include VLSI design/CAD with particular emphasis in low-power electronics for portable computing and wireless communications, VLSI testing and verification, and reconfigurable computing. He has published more than 250 papers in refereed journals and conferences, holds six patents, and is Co-Author of a book on Low Power CMOS VLSI Design (New York: Wiley). He was Guest Editor for a Special Issue on Low-Power VLSI in IEE Proceedings—Computers and Digital Techniques (July 2002). Dr. Roy received the National Science Foundation Career Development Award in 1995, the IBM Faculty Partnership Award, AT&T/Lucent Foundation Award, Best Paper Awards at the 1997 International Test Conference and 2000 International Symposium on Quality of IC Design, 2003 IEEE Latin American Test Workshop, and 2003 IEEE Nano. He is on the Editorial Board of IEEE Design and Test, IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS, and IEEE TRANSACTIONS ON VLSI SYSTEMS. He was Guest Editor for a Special Issue on Low-Power VLSI in IEEE DESIGN AND TEST (1994), and for the IEEE TRANSACTIONS ON VLSI SYSTEMS (June 2000).     

Industrial fluorosis in cattle and buffalo around Udaipur, India

Signs of dental discolouration, difficulty in mastication, bony lesions, lameness, debility and mortality in domesticated animals, reared around superphosphate fertiliser plants located approximately 15 km north of Udaipur, Rajasthan prompted us to investigate for the occurrence of fluorosis. Out of 166 animals clinically examined, the prevalence rate was 17.4% (4/23) in calves below 1 year of age, 37.2% (16/43) in cattle between 1 and 3 years, 61.3% (46/75) in cattle above 3 years and 72% (18/25) in buffalo above 1 year. Dental fluorosis was common in buffalo compared to cattle of all the age groups. Fluoride levels in fodder and water, consumed by the animals were much higher than the recommended permissible limit. Mean fluoride concentrations in serum and urine were 1.53 +/- 1.27 and 26.4 +/- 6.17 mg l(-1) in calves below 1 year of age, 0.56 +/- 0.17 and 26.2 +/- 3.86 mg l(-1) in cattle of 1-3 years, 0.49 +/- 1.13 and 27.5 +/- 4.63 mg l(-1) in cattle above 3 years and 0.60 +/- 0.07 and 28.6 +/- 4.73 mg l(-1) in buffalo over 1 year, respectively. The values were significantly (P < 0.01) higher than those of control animals kept over a 15-km distance from the factories. Fluoride concentrations in the environmental sample collected from the affected locality were 534.4 +/- 74.9 mg kg(-1) in fodder, 1.19 +/- 0.29 mg l(-1) in pond water and 0.479 +/- 0.351 mg l(-1) in tube well water. It was concluded that the consumption of fodder and water contaminated by the fumes and dusts emitting from superphosphate fertiliser plants resulted in the development of chronic fluorotic lesions in cattle and buffalo.     

Multiagent based differential evolution approach to optimal power flow

This paper proposes a new differential evolution approach named as multiagent based differential evolution (MADE) based on multiagent systems, for solving optimal power flow problem with non-smooth and non-convex generator fuel cost curves. This method integrates multiagent systems (MAS) and differential evolution (DE) algorithm. An agent in MADE represents an individual to DE and a candidate solution to the optimization problem. All agents live in a lattice like environment, with each agent fixed on a lattice point. In order to obtain optimal solution quickly, each agent competes and cooperates with its neighbors and it can also use knowledge. Making use of these agent-agent interaction and DE mechanism, MADE realizes the purpose of minimizing the value of objective function. MADE applied to optimal power flow is evaluated on 6 bus system and IEEE 30 bus system with different generator characteristics. Simulation results show that the proposed method converges to better solutions much faster than earlier reported approaches.     

An attention-based deep learning model for credibility assessment of online health information

With the surge of searching and reading online health-based articles, maintaining the quality and credibility of online health-based articles has become crucial. The circulation of deceptive health information on numerous social media sites can mislead people and can potentially cause adverse effects on people's health. To address these problems, this work uses deep learning approaches to automate the assessment and scoring of online health-related articles' credibility. The paper proposed an Attention-based Recurrent Multichannel Convolutional Neural Network (ARMCNN) model. The proposed model incorporates a BiLSTM layer, a multichannel CNN layer, and an attention layer and predicts the credibility of online health information. To perform a reliable evaluation of the presented model, we utilize the health articles reviewed by the experts, compiled in a labeled dataset termed “Pubhealth,” which consists of thousands of health articles. The results are evaluated using five performance measures, accuracy, precision, recall, f1-score, and area under the ROC curve (AUC). Furthermore, we extensively compared the proposed model with different deep learning and machine learning models such as Long short-term memory (LSTM), Bidirectional LSTM, CNN (Convolutional neural network), and RNN-CNN. The experimental results showed that the proposed model produced state-of-the-art performance on the used dataset by achieving an accuracy of 0.88, precision of 0.92, recall of 0.87, f1-score of 0.90, and AUC of 0.94. Further, the proposed model yielded better performance than other benchmarked techniques for the credibility assessment of online health articles.     

Particle swarm optimization based K-means clustering approach for security assessment in power systems

Security assessment is a major concern in planning and operation studies of a power system. Conventional method of security evaluation performed by simulation involves long computer time and generates voluminous results. This paper presents a K-means clustering approach for classifying power system states as secure/insecure under a given operating condition and contingency. This paper demonstrates how the traditional K-means clustering algorithm can be profitably modified to be used as a classifier algorithm. The proposed algorithm combines particle swarm optimization (PSO) with the traditional K-means algorithm to satisfy the requirements of a classifier. The proposed PSO based K-means clustering technique is implemented in IEEE 30 Bus, 57 Bus, 118 Bus and 300 Bus standard test systems for static security and transient security evaluation. The simulation results of the proposed algorithm are compared with unsupervised K-means clustering, which uses different methods for cluster center initialization.     

Golden-Free Hardware Trojan Detection with High Sensitivity Under Process Noise

Malicious modification of integrated circuits in untrusted design house or foundry has emerged as a major security threat. Such modifications, popularly referred to as Hardware Trojans, are difficult to detect during manufacturing test. Sequential hardware Trojans, usually triggered by a sequence of rare events, represent a common and deadly form of Trojans that can be extremely hard to detect using logic testing approaches. Side-channel analysis has emerged as an effective approach for detection of hardware Trojans. However, existing side-channel approaches suffer from increasing process variations, which largely reduce the detection sensitivity and sets a lower limit of the sizes of Trojans detectable. In this paper, we present TeSR, a Temporal Self-Referencing approach that compares the current signature of a chip at two different time windows to isolate the Trojan effect. Since it uses a chip as a reference to itself, the method completely eliminates the effect of process noise and other design marginalities (e.g. capacitive coupling), thus providing high detection sensitivity for Trojans of varying size. Furthermore, unlike most of the existing approaches, TeSR does not require a golden reference chip instance, which may impose a major limitation. Associated test generation, test application, and signature comparison approaches aimed at maximizing Trojan detection sensitivity are also presented. Simulation results for three complex sequential designs and three representative sequential Trojan circuits demonstrate the effectiveness of the approach under large inter- and intra-die process variations. The approach is also validated with current measurement results from several Xilinx Virtex-II FPGA chips.     

Structural and Thermal Validations of Y<Subscript>3</Subscript>Ba<Subscript>5</Subscript>Cu<Subscript>8</Subscript>O<Subscript>18</Subscript> Composites Synthesized via Citrate Sol-Gel Spontaneous Combustion Method

The fabrication of single-phase superconductors enabled promising advancements in a wide range of technological applications. Numerous parameters including processing temperature, thermal cycle, chemical composition, doping, and atmosphere will be carefully addressed and optimized. This paper investigates phase stability and compound formation of Y₃Ba₅Cu₈O_y (Y-358) preform powders which were sintered at different temperatures. The precursor powder synthesized via chemical route and employing spontaneous combustion technique, respectively. The presence of Y-358 and YBa₂Cu₃O_7-δ (Y-123) phases in composites sintered at different temperatures with varied phase fractions were further confirmed through Rietveld refinement. The formation of Y-123 phase is dominant in all samples and composite was sintered at 900 °C, which was exhibited higher as compared to Y-358 phase content. The decomposition of different phases present in the composites and reaction temperatures were investigated with simultaneous differential thermal and thermogravimetry analysis.     

Milk trace elements in lactating cows environmentally exposed to higher level of lead and cadmium around different industrial units

The present investigation was carried out to assess the trace mineral profile of milk from lactating cows reared around different industrial units and to examine the effect of blood and milk concentration of lead and cadmium on copper, cobalt, zinc and iron levels in milk. Respective blood and milk samples were collected from a total of 201 apparently healthy lactating cows above 3 years of age including 52 cows reared in areas supposed to be free from pollution. The highest milk lead (0.85 ± 0.11 µg/ml) and cadmium (0.23 ± 0.02 µg/ml) levels were recorded in lactating cows reared around lead–zinc smelter and steel manufacturing plant, respectively. Significantly (P < 0.05) higher concentration of milk copper, cobalt, zinc and iron compared to control animals was recorded in cows around closed lead cum operational zinc smelter. Analysis of correlation between lead and other trace elements in milk from lactating cows with the blood lead level > 0.20 µg/ml (n = 79) revealed a significant negative correlations between milk iron and milk lead (r = − 0.273, P = 0.015). However, such trend was not recorded with blood lead level < 0.20 µg/ml (n = 122). The milk cobalt concentration was significantly correlated (r = 0.365, P < 0.001) with cadmium level in milk and the highest milk cadmium (> 0.10 to 0.39 µg/ml) group had significantly (P < 0.05) increased milk cobalt. It is concluded that increased blood and milk lead or cadmium level as a result of natural exposure of lactating cows to these environmental toxicants significantly influences trace minerals composition of milk and such alterations affect the milk quality and nutritional values.