614 research outputs found
Passive visible light positioning systems
No full textLocalization is one of the key applications of visible light communication (VLC) using which sub-centimeter level positioning
accuracy is possible. Many visible light-based positioning (VLP) systems have been designed by industry and the research community. Their commercial viability is hampered by the requirement of significantch anges in the deployed lighting infrastructure, resulting in a prohibitive increase in the cost and overhead of deployment. In this paper, we review passive VLP systems an emerging paradigm that offers hope to overcome this challenge and thus can catalyze commercial adoption of a new wave of VLP systems. Unlike active systems, passive ones provide unprecedented flexibility and can enable new potential applications and scenarios such as ability to track users not carrying photosensors. Both natural light sources e.g., sunlight and artificial man-made sources can be used to transmit location information. This paper provides a taxonomy of recently proposed passive VLP systems which is supported by several examples from the recent research literature. A comparative performance of these systems based on factors like accuracy and infrastructure changes is provided along with their limitations
The role of disciplinary, interdisciplinary, and transdisciplinary education in sustainability science : Experiences from my professional journey
No full textUnderstanding and addressing the complex societal sustainability challenges requires applying novel approaches, devising innovative assessment frameworks, and adopting methods and tools from other research fields. Dr Jagdeep Singh has been conducting inter- and trans-disciplinary research on these challenges impacting academia and society. He has pursued university degrees in Electrical Engineering (Bachelor of Technology), Energy Studies (Master of Technology), and Industrial Ecology (Licentiate and Doctor of Philosophy). Before beginning his research journey into the field of sustainability science, he also worked as a Maintenance Engineer in a manufacturing plant and as a university lecturer on subjects such as microprocessor 8085 and Electromagnetic Field Theory. However, he believes his previous education and job experiences have constantly enriched this journey, allowing metacognition and deep learning about societal sustainability challenges. In this chapter, he introduces his educational and research journey so far and highlights some of the critical moments and decisions undertaken that helped him in this journey
When BLE Meets Light: Multi-modal Fusion for Enhanced Indoor Localization
No full textDesigning a reliable and highly accurate indoor localization system is challenging due to the non-uniformity of indoor spaces, multipath fading, and satellite signal blockage. To address these issues, we propose a Deep Neural Network-based localization system that combines passive Visible Light Positioning (p-VLP) and Bluetooth Low Energy (BLE) technologies to achieve stable, energy-efficient, and accurate indoor localization. Our solution leverages incremental learning to fuse data from visible light and BLE, overcoming their individual limitations and achieving centimeter-level localization accuracy. We build a prototype using low-cost S9706 hue sensors for p-VLP and low-power nrf52830 BLE boards to collect data simultaneously from both technologies in a 25m2 testbed. Our approach demonstrates a significant localization accuracy improvement of approximately 47% and 64% compared to individual p-VLP and BLE technologies, respectively, achieving a mean localization error of 20 cm
HueSense: Featuring white LEDs through Hue Sensing
No full textVisible Light Positioning (VLP) has been prevalent in providing high-precision localization systems in the past decade. However, the commercial availability or usage is still limited primarily due to the requirement of changing the existing lighting infrastructure. In this paper, we propose HueSense, an alternative technique to develop a passive VLP system by extracting light-emission intrinsic features, such as dominant colours present in the white LED light. The method can eliminate the need to change lighting-infrastructure, and only uses cheaper and power-efficient off-the-shelf hue sensors. Our experiments demonstrate that HueSense can achieve a location-mapping accuracy of 80.14% with a moving robot in uncontrolled lighting environments
SOAP-Based Web Services vs. RESTful Web Services for Multimedia Conferencing Applications: A Case Study
Get PDFRESTful web services are now emerging as an alternative that may be more suitable than SOAP-based counterparts in some cases. In this paper, we contrast these two web programmatic interfaces for the development of multimedia conferencing applications, an important category of web applications. A RESTful web service that offers the same functionality as the standard Parlay-X multimedia SOAP-based web service is proposed. The two interfaces are prototyped in the same environment, and the same application is developed using both interfaces. The performance of each are compared and lessons learned are discussed.
Fatna Belqasmi, Jagdeep Singh, Suhib Bani melhem, Roch H. Glith
Potential Mechanisms of SGLT2 Inhibitors for the Treatment of Heart Failure With Preserved Ejection Fraction
Get PDFHeart failure with preserved ejection fraction (HFpEF) is an unsolved and growing concern in cardiovascular medicine. While no treatment options that improve prognosis in HFpEF patients has been established so far, SGLT2 inhibitors (SGLT2i) are currently being investigated for the treatment of HFpEF patients. SGLT2i have already been shown to mitigate comorbidities associated with HFpEF such as type 2 diabetes and chronic renal disease, however, more recently there has been evidence that they may also directly improve diastolic function. In this article, we discuss some potential beneficial mechanisms of SGLT2i in the pathophysiology of HFpEF with focus on contractile function
BmmW: A DNN-based Joint BLE and mmWave Radar System for Accurate 3D Localization
No full textBluetooth Low Energy (BLE) has emerged as one of the reference technologies for the development of indoor localization systems, due to its increasing ubiquity, low-cost hardware, and to the introduction of direction-finding enhancements improving its ranging performance. However, the intrinsic narrowband nature of BLE makes this technology susceptible to multipath and channel interference. As a result, it is still challenging to achieve decimetre-level localization accuracy, which is necessary when developing location-based services for smart factories and workspaces. To address this challenge, we present BmmW,an indoor localization system that augments the ranging estimates obtained with BLE 5.1's constant tone extension feature with mmWave radar measurements to provide real-time 3D localization of a mobile tag with decimetre-level accuracy. Specifically, BmmW embeds a deep neural network (DNN) that is jointly trained with both BLE and mmWave measurements, practically leveraging the strengths of both technologies. In fact, mmWave radars can locate objects and people with decimetre-level accuracy, but their effectiveness in monitoring stationary targets and multiple objects is limited, and they also suffer from a fast signal attenuation limiting the usable range to a few metres. We evaluate BmmW's performance experimentally, and show that its joint DNN training scheme allows to track mobile tags in real-time with a mean 3D localization accuracy of 10 cm when combining angle-of-arrival BLE measurements with mmWave radar data. We further evaluate a variant of BmmW, named BmmW-LITE, that is specifically designed for single-antenna BLE devices (i.e., that avoids the need of bulky and costly multi-antenna arrays). Our results show that Bmm W-Liteachieves a mean 3D localization accuracy of 36 cm, thus enabling accurate tracking of objects in indoor environments despite the use of inexpensive single-antenna BLE devices
Evaluating the sustainability impacts of the sharing economy using input-output analysis
No full textEvaluating the sustainability impacts of the sharing economy using input-output analysis’ by Andrius Plepys and Jagdeep Singh presents key challenges associated with a systematic sustainability evaluation of access-based consumption models. Starting with a causal loop diagram representing various reported and potential impacts of a generic sharing system, the authors provide a comprehensive picture of main direct and indirect social, economic and environmental implications of the sharing economy. They also discuss the limitations in sustainability evaluations of the sharing economy, including non-transparency about methods as well as unclear system boundaries and assumptions made. An overview of the strengths and weaknesses of different modelling approaches employed for analysing the effects of sharing economy is provided. Car sharing is used as an example for demonstrating an input-output-based sustainability assessment. Implications for modelling impacts from changes in consumption patterns and from changes in production sectors are discussed. Future research directions include suggestions for improving the existing national accounting frameworks to accommodate the specifics of the emerging sharing economy, better measurements of labour inputs and annual income in the sharing economy and improving resolution and geographical and sectoral coverage of the multiregional input–output tables
Management of mites with homemade neem fruit aqueous extract in capsicum under protected cultivation
No full textBhullar, Manmeet Brar, Kaur, Paramjit, Kumar, Sanjeev, Sharma, Rakesh Kumar, Kumar, Rajinder, Kumari, Suman, Singh, Vinay, Kaur, Arshdeep, Kaur, Jagdeep, Sharma, Urvi, Kaur, Jasjinder (2021): Management of mites with homemade neem fruit aqueous extract in capsicum under protected cultivation. Persian Journal of Acarology 10 (1): 85-94, DOI: 10.22073/pja.v10i1.61968, URL: https://www.mendeley.com/catalogue/f143dbd7-151b-317f-a54c-e05015597a71
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