Off-line Setting Research Articles

Current-state opacity verification in discrete event systems using an observer net

Due to the proliferation of contemporary computer-integrated systems and communication networks, there is more concern than ever regarding privacy, given the potential for sensitive data exploitation. A recent cyber-security research trend is to focus on security principles and develop the foundations for designing safety-critical systems. In this work, we investigated the problem of verifying current-state opacity in discrete event systems using labeled Petri nets. A system is current-state opaque provided that the current-state estimate cannot be revealed as a subset of secret states. We introduced a new sub-model of the system, named an observer net. The observer net have the same structure as the plant, but it is distinguished by the use of colored markers as well as simultaneous and recursive transition enabling and firing, which offer an efficient state estimation. We considered two settings of the proposed approach: an on-line setting, in which a current-state opacity algorithm is proposed. The algorithm waits for the occurrence of an observable event and determines if the current observation of a plant reveals the secret behaviour, as well as, an off-line setting, where the verification problem is solved based on a state estimator called a colored estimator. In this context, necessary and sufficient conditions for verifying opacity are developed with illustrative examples to demonstrate the presented approach.

On-line sound event localization and detection for real-time recognition of surrounding environment

Sound Event Localization and Detection (SELD) is a task of simultaneously identifying sound events and their locations. The existing methods perform SELD in the off-line setting using deep neural networks (DNNs) including bi-directional recurrent neural network (BiRNN). Although their effectiveness has been shown in the literature, they cannot be directly applied to real-time applications which requires on-line execution of SELD, i.e., the input signals must be successively processed with small latency. In this paper, we propose on-line extension of the off-line SELD systems and discuss about the essential latency of an on-line SELD system. The relationship between the system latency and accuracy of SELD was investigated by experiments. From the experimental results, we confirmed that on-line extension of the SELD system maintains or improves the performance of localization, while event detection performance is degraded in low-latency.

A dissimilarity-based approach to automatic classification of biosignal modalities

Over the last years, pervasive wearable technology has spread to people’s daily lives, unobtrusively acquiring large amounts of data. Such devices contain biomedical sensors, prone to contribute for the improvement of the user’s quality of life through artificial intelligence algorithms (e.g. health monitoring and emotion recognition). Physiological signals are the basis of such applications, and critical problems are data (un)labeling and incorrect metadata about the source. We propose a framework for the automatic identification of the type of physiological data source, namely Respiration, Electrocardiography, Electrodermal Activity, and Blood Volume Pulse data through the application of Supervised Learning on different representation spaces (feature-based and dissimilarity-based), in both an Online and Offline setting. We build our model through a comprehensive study of (1) Supervised Learning classifiers; (2) Similarity metrics; (3) Data representation; and lastly, (4) Sample aggregation techniques for the creation of the prototypes that will translate the data into the dissimilarity-based space. We explore the aforementioned techniques on two unexplored databases. The experimental results led to accuracies superior to 92% for the online setting, and 96% for the offline setting, attaining competitive results with the current state of the art. Our work paves the way to the development of systems capable of automatically identifying sensor types and subsequently applying the most appropriate data processing, analysis and classification workflows.

The Power of Subsampling in Submodular Maximization

We propose subsampling as a unified algorithmic technique for submodular maximization in centralized and online settings. The idea is simple: independently sample elements from the ground set and use simple combinatorial techniques (such as greedy or local search) on these sampled elements. We show that this approach leads to optimal/state-of-the-art results despite being much simpler than existing methods. In the usual off-line setting, we present SampleGreedy, which obtains a [Formula: see text]-approximation for maximizing a submodular function subject to a p-extendible system using [Formula: see text] evaluation and feasibility queries, where k is the size of the largest feasible set. The approximation ratio improves to p + 1 and p for monotone submodular and linear objectives, respectively. In the streaming setting, we present Sample-Streaming, which obtains a [Formula: see text]-approximation for maximizing a submodular function subject to a p-matchoid using O(k) memory and [Formula: see text] evaluation and feasibility queries per element, and m is the number of matroids defining the p-matchoid. The approximation ratio improves to 4p for monotone submodular objectives. We empirically demonstrate the effectiveness of our algorithms on video summarization, location summarization, and movie recommendation tasks.

The Teachers' Pedagogic Competence in Teaching English through Online and Offline Setting

Nowadays, a new trend in the teaching and learning process emerges along with the development of technology. This study aims at exploring the pedagogical competence of English teachers at SMPN 8 Satap Maiwa. It also aims at finding out the students' perceptions of their teachers' pedagogical competence. There were three kinds of instruments in this study. They were observation, interview, and a questionnaire. Based on the interviews, the results showed that the teachers enjoyed teaching in the classroom, and they were interested in conducting online instruction even sometimes found problems in doing the process. Based on the questionnaire, the researcher found students perceived their teachers as quite good instructors in the classroom. Finally, the researchers suggested to the teachers that they should always intend to improve their competence by applying some new methods to make students better understand the materials.

Energy Optimal Wireless Data Transmission for Wearable Devices: A Compression Approach

Wearable devices are designed to have a small size and be lightweight. Consequently, the battery life is constrained and becomes a crucial limitation. In this paper, we use both data compression and wireless transmission speed control to minimize the energy consumption of wearable devices for data transmission, subject to a deadline constraint. We consider both an off-line setting where future channel gains are known ahead of time and a stochastic setting where channel gains change stochastically according to a Markov process. For the first case, we present an efficient $(1+\epsilon)$ approximation algorithm for an arbitrarily small $\epsilon$ , while in the latter case we give a stochastic algorithm to minimize the total expected energy use. We also conduct experimental studies on the proposed algorithms and show that the stochastic algorithm, despite not knowing future channel gains, closely approximates the performance of the nearly optimal off-line solution with less than 0.1% difference in energy consumption on an average. We also compared the stochastic algorithm with several other practical algorithms and showed that our algorithm achieves significant improvements in the overall energy use.

A pilot-based distance protection scheme for meshed distribution systems with distributed generation

This paper proposes a pilot-based distance protection scheme for meshed distribution systems with a high penetration of distributed generation. The proposed scheme assumes distance relays installed at the opponent ends of each main line segment. A forward distance element is enabled in each relay to protect the main line segment, while, a reverse distance element is enabled in each relay for protecting adjacent buses and laterals. The relays protecting a main line segment or a bus/lateral communicate in a permissive logic, ensuring protection sensitivity and security at the same time. The scheme provides efficient primary and backup protection against faults of any type, even with a considerable fault resistance, and under weak-infeed conditions. It is also appropriate for both the grid-connected and the islanded mode of system operation. Coordination of the distance protection scheme with the lateral protection means is also addressed. Existing numerical distance relay technology is considered, to enhance the applicability of the proposed scheme. Offline setting of the distance relays is required, which has to be performed once. Only one setting group is ultimately extracted for each relay, suitable for different fault/system conditions, avoiding the need for adaptive protection techniques. The proposed scheme is applied to a test meshed distribution system and conclusions are drawn. Comparison with directional overcurrent and differential protection shows the advantages of the designed distance-based protection scheme.

The Embedded Lesson Approach to Social Media Research: Researching Online Phenomena in an Authentic Offline Setting

For American teenagers, social media participation has become a routine feature of everyday life, with ready access to their online networks via smartphones, tablets, and computers. Despite questions and concerns about its effects, relatively few educational researchers have qualitatively explored how students use social media. Complexities such as parental consent, unintended access to non-consented peers, and privacy rights may be deterrents to this research. In this paper, we describe our embedded lesson approach to studying teenagers’ social media use in a high school setting. We designed and delivered three consecutive lessons about social media to two classes. Embedded within these lessons were opportunities to collect data via surveys, focus groups, and observations, along with member checking as a form of quality assurance. This approach rapidly yielded a rich data set, while also giving students the opportunity to articulate and reflect on their social media activities and experiences.

On controlling prioritized discrete event systems with real-time constraints

We study a class of prioritized Discrete Event Systems (DESs) that involve the control of resources allocated to tasks under real-time constraints. Our work is motivated by applications in communication systems, computing systems, and manufacturing systems where the objective is to minimize energy consumption while guaranteeing that task deadlines are always met. In the off-line setting, we discover several structural properties of the optimal sample path of such DESs. Using the structural properties, we also propose a greedy algorithm which is shown numerically near optimal. For on-line control, we design a Receding Horizon (RH) controller. Using worst-case estimation, the RH control is able to guarantee feasibility (when the off-line problem is feasible) and achieve good performance.

Off-line digital cash schemes providing untraceability, anonymity and change

Several ecash systems have been proposed in the last twenty years or so, each offering features similar to real cash. One feature which to date has not been provided is that of a payee giving change to a payer for an e-coin in an off-line setting. In this paper, we indicate how an off-line ecash system can solve the change-giving problem. In addition, our protocol offers the usual expected features of anonymity and unlinkability of the payer, but can reveal the identity of an individual who illegally tries to spend ecash twice.

Quantifying Pharmaceutical Film Coating with Optical Coherence Tomography and Terahertz Pulsed Imaging: An Evaluation

Spectral domain optical coherence tomography (OCT) has recently attracted a lot of interest in the pharmaceutical industry as a fast and non-destructive modality for quantification of thin film coatings that cannot easily be resolved with other techniques. Because of the relative infancy of this technique, much of the research to date has focused on developing the in-line measurement technique for assessing film coating thickness. To better assess OCT for pharmaceutical coating quantification, this paper evaluates tablets with a range of film coating thickness measured using OCT and terahertz pulsed imaging (TPI) in an off-line setting. In order to facilitate automated coating quantification for film coating thickness in the range of 30–200 μm, an algorithm that uses wavelet denoising and a tailored peak finding method is proposed to analyse each of the acquired A-scan. Results obtained from running the algorithm reveal an increasing disparity between the TPI and OCT measured intra-tablet variability when film coating thickness exceeds 100 μm. The finding further confirms that OCT is a suitable modality for characterising pharmaceutical dosage forms with thin film coatings, whereas TPI is well suited for thick coatings. © 2015 The Authors. Journal of Pharmaceutical Sciences published by Wiley Periodicals, Inc. and the American Pharmacists Association J Pharm Sci 104:3377–3385, 2015

Future Mobility

Abstract This article presents an automotive control approach for information-rich future mobility. It integrates in-vehicle networked controls with cloud computing accessible through a wireless network to elevate current on-board controls to a new level for additional benefits and performance. Outsourcing computation-intensive tasks to a cloud-computing server is an extension of the current server-based concierge/infotainment type features. While in-vehicle controls remain essential for safety critical and real-time functionality, the cloud-computing paradigm offers another degree of freedom for control system design. In future vehicle controls, the cloud can be used for very demanding computations that otherwise cannot be accomplished by on-board electronic control units (ECUs), especially for information-intensive tasks. The so-called local-simple-remote-complex vehicle control strategies are likely to unlock the potential of implementing methods and tools that are presently used only in an off-line setting. The cloud can also be used as a storage place to record current and historic vehicle data that can be used for predictive diagnosis and prognostics of the vehicle health.

Research on Short-Delay Adaptive Current Protection Scheme for Shipboard Electrical Power Systems

For specific mission and unique configure of Shipboard Electrical Power Systems (SEPS), their relay protection schemes are different from Terrestrial Electrical Power Systems (TEPS). With development of system capacity and network topology, the traditional three-step current protection method can not meet protection demands, which has the feature of off-line setting. Based on the characteristic and requirement of SEPS, a new short-delay adaptive current protection scheme is proposed, which can automatically adjust current settings of short-delay protection on-line according to the system operation state. Simulation results of typical instance verify the feasibility and validity to improve protection performance.

On-line secret sharing

In an on-line secret sharing scheme the dealer assigns shares in the order the participants show up, knowing only those qualified subsets whose all members she has seen. We assume that the overall access structure is known and only the order of the participants is unknown. On-line secret sharing is a useful primitive when the set of participants grows in time, and redistributing the secret is too expensive. In this paper we start the investigation of unconditionally secure on-line secret sharing schemes. The complexity of a secret sharing scheme is the size of the largest share a single participant can receive over the size of the secret. The infimum of this amount in the on-line or off-line setting is the on-line or off-line complexity of the access structure, respectively. For paths on at most five vertices and cycles on at most six vertices the on-line and offline complexities are equal, while for other paths and cycles these values differ. We show that the gap between these values can be arbitrarily large even for graph based access structures. We present a general on-line secret sharing scheme that we call first-fit. Its complexity is the maximal degree of the access structure. We show, however, that this on-line scheme is never optimal: the on-line complexity is always strictly less than the maximal degree. On the other hand, we give examples where the first-fit scheme is almost optimal, namely, the on-line complexity can be arbitrarily close to the maximal degree. The performance ratio is the ratio of the on-line and off-line complexities of the same access structure. We show that for graphs the performance ratio is smaller than the number of vertices, and for an infinite family of graphs the performance ratio is at least constant times the square root of the number of vertices.

Comparative Experimental Research on Product Evaluations and Approach Behaviors of Utilitarian and Hedonic Clothing in On-line and Off-line Settings

This study explores the differences in product evaluation and approach behaviors as well as the effects of product evaluation on approach behaviors of utilitarian and hedonic products in on-line and off-line settings. A total of 332 subjects participated in the experiments to assess product evaluation and approach behaviors for utilitarian and hedonic clothing products in on-line and off-line settings. The results show that even though the same stimulus was presented, consumers` product evaluation of utilitarian clothing (i.e., t-shirts) was higher in the off-line setting than in the on-line setting while the approach behavior of hedonic clothing was better in the on-line setting than in the off-line setting. In addition, color was a crucial factor generating positive approach behaviors for utilitarian clothing while style and quality were core factors influencing the approach behaviors of hedonic products in an on-line setting. There was no consistency in the results of the important factors affecting approach behaviors of utilitarian and hedonic clothing in an off-line setting. The conclusion suggests implications for marketing based upon the results of this study.

Effect of Color Sensibility Evaluation of Clothing Product on Attitude toward Product in On-line and Off-line-Focusing on White T-Shirt-

Purpose of this study is to explore: 1) the difference in color sensibility evaluation, color attractiveness, and attitude toward the product, 2) the difference in the effect of color sensibility evaluation on color attractiveness, and 3) the difference in the effect of color sensibility evaluation on attitude toward the product between the identical clothing product presented in on-line and off-line settings. Experimental method was applied with 230 male and female university students using stimuli of an on-line site as well as an off-line window display presenting the same white t-shirts. Color sensibility factors of white t-shirt were hedonic, stimulating, active, and spatial senses. These color sensibility factors of the clothing product affected product color attractiveness as well as attitude toward the product. Although there were not differences in color sensibility evaluation, product attractiveness, and attitude toward the product between items presented in on-line and off-line settings, difference was found in the effect of color sensibility on the color attractiveness and attitude toward the product. The effect of color sensibility on color attractiveness and attitude toward the product was stronger in on-line than in off-line setting. Hedonic sense was the most important factor influencing attractiveness of product color and attitude toward the product. In addition, spatial sense affected attractiveness of product color in on-line setting; and stimulating sense impacted attitude toward the product in off-line setting. Based on the results implications were generated.

SCHEDULING TO MINIMIZE MAX FLOW TIME: OFF-LINE AND ON-LINE ALGORITHMS

We investigate the max flow time scheduling problem in the off-line and on-line setting. We prove positive and negative theoretical results. In the off-line setting, we address the unrelated parallel machines model and present the first known fully polynomial time approximation scheme, when the number of machines is fixed. In the on-line setting and when the machines are identical, we analyze the First In First Out (FIFO) heuristic when preemption is allowed. We show that FIFO is an on-line algorithm with a (3-2/m)-competitive ratio. Finally, we present two lower bounds on the competitive ratio of deterministic on-line algorithms.