Application Specific Instrumentation Research Articles

CommSense: a communication infrastructure based sensing instrument for environment monitoring

The proposed work describes a novel way to use the existing communication infrastructure based sensing to monitor the change in the environment (CommSense). The key idea to this technology lies in focusing on already known information from received signal e.g. Pilot carriers in the communication signal frames. Comparing the received signal with the expected properties of the pilot, we can get an estimate of change in the environment based on change in channel properties. Existing Long Term Evolution telecommunication infrastructure is utilized for this environment sensing task. After the channel characteristics are estimated, those can be used to obtain phenomenological knowledge of the environment using Application Specific INstrumentation framework. This system was implemented using software defined radio platform and GNURadio software support.

LTE commsense for object detection in indoor environments

In this work, we describe a new method of using long-term evolution (LTE) telecommunication infrastructure to sense environmental changes. We call it LTE communication-based sensing (Com-mSense). It can be used in various environment-sensing tasks, e.g., sea level monitoring, security of large unmanned landscapes, snow avalanche monitoring, and activity detection inside forests. The main concept of this technology is to focus on the known signal embedded in the data frames. It compares the received signal with the expected reference signal to estimate the change in the environment. LTE telecommunication infrastructure is used for this environment-sensing task because of its wide coverage. In addition, LTE uses a two-dimensional (2D) frame structure of orthogonal frequency division multiplexing (OFDM) and multiple input and multiple output (MIMO), which may yield better performance compared to previous communication standards. This procedure of extracting channel characteristics using commensal radar principles does not affect the existing telecommunication system, because it is a receive-only system. After the channel characteristics are estimated, they can be used to obtain phenomenological knowledge of the environment using an application-specific instrumentation (ASIN) framework. The capability analysis of this scheme is presented in this article, first in simulation and then using field-collected data captured with the help of a software-defined radio (SDR) platform.

Mass spectrometry in freeze-drying: Motivations for using a bespoke PAT for laboratory and production environment

Mass Spectrometry has commonly been used in the semi-conductor industry where maintaining a clean environment with minimum contaminants under high vacuum is crucial for successful manufacturing. Since the technology’s early usage for pharmaceutical manufacturing in the 1980 s, particularly in the freeze-drying environment, much has changed. The focus of the current work is aimed at asking some key questions regarding the maturity of the technology, its challenges and importance of having an application-specific instrument for quantitative process analyses applied to freeze-drying. Furthermore, we compare the use of mass spectrometers in early installations from the '80s with recent experiences of the technology in the production and laboratory environments comparing data from different MS technologies. In addition, the manuscript covers broad application of the technology towards detection of and sensitivity for analytes including silicone oil and Helium. It also explores the option of using MS in detecting water vapor and nitrogen concentration not just in primary drying, but also in secondary drying. The technology, when purpose built, has the potential for use as a robust, multi-purpose PAT tool in the freeze-drying laboratory and production environments.

GSM-based commsense system to measure and estimate environmental changes

Facilitating the coexistence of radar systems with communication systems has been a major area of research in radar engineering. The current work presents a new way to sense the environment using the channel equalization block of existing communication systems. We have named this system CommSense. In the current paper we demonstrate the feasibility of the system using Global System for Mobile Communications (GSM) signals. The implementation has been done using open-source Software Defined Radio (SDR) environment. In the preliminary results obtained in our work we show that it is possible to distinguish environmental changes using the proposed system. The major advantage of the system is that it is inexpensive as channel estimation is an inherent block in any communication system and hence the added cost to make it work as an environment sensor is minimal. The major challenge, on which we are continuing our work, is how to characterize the features in the environmental changes. This is an acute challenge given the fact that the bandwidth available is narrow and the system is inherently a forward looking radar. However the initial results, as shown in this paper, are encouraging and we intend to use an application specific instrumentation (ASIN) scheme to distinguish the environmental changes.

ASIN-Based UWB Radar for Sludge Monitoring

In this paper, we propose an application specific instrument (ASIN)-based ultrawideband (UWB) radar system for sludge monitoring from scattering signatures from the bottom of industrial oil tanks. The method is validated by successful estimation of sludge volume in oil tanks using simulated and real data. First, as a demonstration of the conventional system, image reconstruction algorithms are used for tank-bottom sludge profile imaging for symmetrical and asymmetrical sludge profiles, where the setup is modeled in finite difference time domain method with reduced dimensions of the tank. A 3-D imaging algorithm is used for the 3-D simulation of real life targets. To get the volume of the sludge, ASIN-based UWB radar system is then applied and its effectiveness is demonstrated. In this framework, to get information about the sludge at the bottom of industrial tank, first, a scheme is proposed to differentiate between two sets of data which correspond to two different set of volumes. This method is validated using a commercial UWB kit, in which, practical experiments were performed. The data obtained is visualized using multidimensional scaling procedure and analyzed. Then, regression analysis using radial basis function artificial neuron network is performed, so that given a particular data, it can be predicted that, to which volume it best corresponds.

A sensor array optimization method for electronic noses with sub-arrays

Sensor array configuration needs to be optimized in developing an application-specific instrument of electronic noses. Currently, sensor array optimization is commonly done by feature selection techniques. These methods could solve how to optimize a sensor array. However, they could not figure out what are the unique functions that each sensor plays in the optimized sensor array. The method proposed in this paper could solve this problem by sensor clustering and dividing the whole sample classification mission into several small recognition tasks. A measurement with a six Taguchi Gas Sensors (TGS sensor hereinafter) sensors array to classify 11 gas sorts was used in the data validation. The sensor array was optimized to three sensors with the proposed method. Each sensor in the optimized array had unique functions to solve different recognition tasks. TGS2600 had the unique functions to discriminate butanone and acetaldehyde. TGS2602 had the unique functions to discriminate benzene and cyclohexane, methanol and ethanol. TGS813 had the unique functions to discriminate cyclohexane and pentane. The combination of TGS2600 and TGS2602 had the unique functions to discriminate acetone and butanone, acetone and acetaldehyde. The proposed method might be a new generation of sensor array optimization methods.

BorderPatrol

Causal request traces are valuable to developers of large concurrent and distributed applications, yet difficult to obtain. Traces show how a request is processed, and can be analyzed by tools to detect performance or correctness errors and anomalous behavior. We present BorderPatrol, which obtains precise request traces through suystems built from a litany of unmodified modules. Traced components include Apache, thttpd, PostgreSQL, TurboGears, BIND and notably Zeus, a closed-source event-driven web server. BorderPatrol obtains traces using active observation which carefully modifies the event stream observed by modules, simplifying precise observation. Protocol processors leverage knowledge about standard protocols, avoiding application-specific instrumentation. BorderPatrol obtains precise traces for black-box systems that cannot be traced by any other technique. We confirm the accuracy of BorderPatrol's traces by comparing to manual instrumentation, and compare the developer effort required for each kind of trace. BorderPatrol imposes limited overhead on real systems (approximately 10-15%) and it may be enabled or disabled in at run-time, making it a viable option for deployment in production environments.

A Confirmatory Factor Analysis of the End-User Computing Satisfaction Instrument

The dimensionality of the user satisfaction construct is an important theoretical issue that has received considerable attention. Focusing on end users who directly interact with application software, Doll and Torkzadeah (1988) develop a 12-item application specific instrument for providing an overall assessment of end-user computing satisfaction (EUCS). They also contend that EUCS is comprised of five component measures (content, accuracy, format, ease of use, timeliness) that explain the construct and permit more precision in formulating and testing research hypotheses. The acceptance of the EUCS as a standardized instrument requires confirmation that it explains and measures the user satisfaction construct.Based on a sample of 409 respondents from 18 organizations, this research uses confirmatory factor analysis (LISREL) to test alternative models of underlying factor structure and assess the reliability and validity of factors and items. Without respecifying the model, the results provide some support for Doll and Torkzadeh's proposed model of the five first-order factors and one second-order (higher-order) factor. Thus the evidence supports the use of: (1) the 12-item instrument as an overall measure of EUCS; and (2) the five component factors for explaining the EUCS construct.