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In this paper, a light-weight, low-power atmospheric multi-parameter sensor (AMPS), which could be mounted on small flying platforms such as a tethered balloon, a quad-rotor unmanned aerial vehicle (UAV), a UAV helicopter, etc., is implemented and integrated to sample vertical distribution of aerosols with integrated parameters of aerosol particle concentration, temperature, relative humidity and atmospheric pressure.

The AMPS integrates three kinds of probes in an embedded system. A synchronous method based on GPS is proposed to drive the laser aerosol particle sensor, the temperature and humidity probe and the pressure probe to sample four channels approximately simultaneously. Different kinds of housing are designed to accommodate various flying platforms, and the weight is controlled to adapt the payload of each platform.

A series of validation tests show that while the AMPS achieves high precision, its power consumption is less than 1.3 W, which is essential for light flying platforms. The AMPS was mounted on different flying platforms and the difference was evaluated. For three times every five days, vertical profiles of PM2.5 and PM10 concentrations were observed by the AMPS mounted on a quad-rotor UAV, which revealed the significant correlation between the aerosol particle concentration and atmospheric parameters.

A new light-weight and low-power AMPS for small flying platforms is designed and tested, which provides an effective way to explore the properties of aerosol vertical distribution, and to monitor pollutants flexibly.

An autonomous mobile robot requires efficient perception of the environment to perform various tasks in a challenging environment. The precise sensory information from the range sensors is required to accomplish prerequisites, such as SLAM, path planning and localization. But the accuracy and precision of the sensors become unreliable in harsh environmental conditions because of the effect of rain, dust, humidity, fog and smoke. The purpose of this paper is to generate robust mapping of the environment in harsh environmental conditions.

This paper presents a novel technique, averaging data with short range selection (ADWSRS), to reduce the effect of harsh environmental (rain, wind, humidity, etc.) conditions on sensory information (range) to generate reliable grid mapping. The sensory information on laser and sonar sensors in terms of probability values (occupied/unoccupied cell) in generating grid maps are fused after passing through two newly designed pre-processing filters: laser averaging filter and short range selection filter. This proposed approach relies on various aspects such as averaging laser data analogous to current pose of the sensor, selection of short range with respect to threshold value to remove the effect of specular reflection/crosstalk of sonar and a newly designed apparatus in which dirt cover (glass cover) and air blower are coupled to remove the influence of dirt, rain and humidity.

This proposed approach is tested in different environmental conditions, and to verify the consistency of the proposed approach, qualitative and quantitative analyses are carried out, which shows 42.5 per cent improvement in the probability value of occupied cells in the generated grid map.

The proposed ADWSRS approach reduced the effect of harsh environmental conditions such as fog, rain and smoke to generate efficient mapping of the environment, which may be implemented in diverse applications such as autonomous navigation, localization, path planning and mapping.

Examines the fourteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the fifteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the thirteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Examines the sixteenth published year of the ITCRR. Runs the whole gamut of textile innovation, research and testing, some of which investigates hitherto untouched aspects. Subjects discussed include cotton fabric processing, asbestos substitutes, textile adjuncts to cardiovascular surgery, wet textile processes, hand evaluation, nanotechnology, thermoplastic composites, robotic ironing, protective clothing (agricultural and industrial), ecological aspects of fibre properties – to name but a few! There would appear to be no limit to the future potential for textile applications.

Information technology (IT) systems are already ubiquitous, and their future growth is expected to drive the global economy for the next several decades. However, energy consumption by these systems is growing rapidly, and their sustained growth requires curbing the energy consumption, and the associated heat removal requirements. Currently, 20-50 percent of the incoming electrical power is used to meet the cooling demands of IT facilities. Careful co-optimization of electrical power and thermal management is essential for reducing energy consumption requirements of IT equipment. Such modeling based co-optimization is complicated by the presence of several decades of spatial and temporal scales. The purpose of this paper is to review recent approaches for handling these challenges.

In this paper, the authors illustrate the challenges and possible modeling approaches by considering three examples. The multi-scale modeling of chip level transient heating using a combination of Progressive Zoom-in, and proper orthogonal decomposition (POD) is an effective approach for chip level electrical/thermal co-design for mitigation of reliability concerns, such as Joule heating driven electromigration. In the second example, the authors will illustrate the optimal microfluidic thermal management of hot spots, and large background heat fluxes associated with future high-performance microprocessors. In the third example, data center facility level energy usage reduction through a transient measurements based POD modeling framework will be illustrated.

Through modeling based electrical/thermal co-design, dramatic savings in energy usage for cooling are possible.

The multi-scale nature of the thermal modeling of IT systems is an important challenge. This paper reviews some of the approaches employed to meet this challenge.