OpenCarrier: Breaking the User Limit for Uplink MU-MIMO Transmissions With Coordinated APs

2022 ◽  
Vol 18 (2) ◽  
pp. 1-21
Author(s):  
Yubo Yan ◽  
Panlong Yang ◽  
Jie Xiong ◽  
Xiang-Yang Li
Keyword(s):  
Real Life ◽  
Wearable Devices ◽  
Node Degree ◽  
Transmission Rates ◽  
Current State ◽  
The Arts ◽  
Mimo Networks ◽  
Massive Number ◽  
Iot Devices ◽  
Very High

The global IoT market is experiencing a fast growth with a massive number of IoT/wearable devices deployed around us and even on our bodies. This trend incorporates more users to upload data frequently and timely to the APs. Previous work mainly focus on improving the up-link throughput. However, incorporating more users to transmit concurrently is actually more important than improving the throughout for each individual user, as the IoT devices may not require very high transmission rates but the number of devices is usually large. In the current state-of-the-arts (up-link MU-MIMO), the number of transmissions is either confined to no more than the number of antennas (node-degree-of-freedom, node-DoF) at an AP or clock synchronized with cables between APs to support more concurrent transmissions. However, synchronized APs still incur a very high collaboration overhead, prohibiting its real-life adoption. We thus propose novel schemes to remove the cable-synchronization constraint while still being able to support more concurrent users than the node-DoF limit, and at the same time minimize the collaboration overhead. In this paper, we design, implement, and experimentally evaluate OpenCarrier, the first distributed system to break the user limitation for up-link MU-MIMO networks with coordinated APs. Our experiments demonstrate that OpenCarrier is able to support up to five up-link high-throughput transmissions for MU-MIMO network with 2-antenna APs.

scholarly journals Decentralized spectrum learning for radio collision mitigation in ultra-dense IoT networks: LoRaWAN case study and experiments

2020 ◽  
Vol 75 (11-12) ◽  
pp. 711-727
Author(s):  
Christophe Moy ◽  
Lilian Besson ◽  
Guillaume Delbarre ◽  
Laurent Toutain
Keyword(s):  
Learning Algorithms ◽  
Real Life ◽  
Software Radio ◽  
Battery Life ◽  
Radio Signals ◽  
Massive Number ◽  
Collision Mitigation ◽  
Unlicensed Bands ◽  
Iot Devices ◽  
Network Capability

AbstractThis paper describes the theoretical principles and experimental results of reinforcement learning algorithms embedded into IoT devices (Internet of Things), in order to tackle the problem of radio collision mitigation in ISM unlicensed bands. Multi-armed bandit (MAB) learning algorithms are used here to improve both the IoT network capability to support the expected massive number of objects and the energetic autonomy of the IoT devices. We first illustrate the efficiency of the proposed approach in a proof-of-concept, based on USRP software radio platforms operating on real radio signals. It shows how collisions with other RF signals are diminished for IoT devices that use MAB learning. Then we describe the first implementation of such algorithms on LoRa devices operating in a real LoRaWAN network at 868 MHz. We named this solution IoTligent. IoTligent does not add neither processing overhead, so it can be run into the IoT devices, nor network overhead, so that it requires no change to LoRaWAN protocol. Real-life experiments done in a real LoRa network show that IoTligent devices’ battery life can be extended by a factor of 2, in the scenarios we faced during our experiment. Finally we submit IoTligent devices to very constrained conditions that are expected in the future with the growing number of IoT devices, by generating an artificial IoT massive radio traffic in anechoic chamber. We show that IoTligent devices can cope with spectrum scarcity that will occur at that time in unlicensed bands.

Natural Language Processing and Futures Studies

2019 ◽  
Vol 12 (2) ◽  
pp. 181-197 ◽  
Author(s):  
Walter Kehl ◽  
Mike Jackson ◽  
Alessandro Fergnani
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
Real Life ◽  
Software System ◽  
Futures Studies ◽  
Current State ◽  
Technological Improvements ◽  
High Degree ◽  
Very High

Because the input for Futures Studies is to a very high degree formulated as written words and texts, methods which automate the processing of texts can substantially help Futures Studies. At Shaping Tomorrow, we have developed a software system using Natural Language Processing (NLP), a subfield of Artificial Intelligence, which automatically analyzes publicly available texts and extracts future-relevant data from theses texts. This process can be used to study the futures. This article discusses this software system, explains how it works with a detailed example, and shows real-life applications and visualizations of the resulting data. The current state of this method is just the first step; a number of technological improvements and their possible benefits are explained. The implications of using this software system for the field of Futures Studies are mostly positive, but there are also a number of caveats.

scholarly journals The Device–Object Pairing Problem: Matching IoT Devices with Video Objects in a Multi-Camera Environment

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5518
Author(s):  
Kit-Lun Tong ◽  
Kun-Ru Wu ◽  
Yu-Chee Tseng
Keyword(s):  
Internet Of Things ◽  
Real Life ◽  
External World ◽  
Wearable Devices ◽  
Physiological Signals ◽  
Sensor Data ◽  
Visual Objects ◽  
Video Objects ◽  
Pairing Problem ◽  
Iot Devices

IoT technologies enable millions of devices to transmit their sensor data to the external world. The device–object pairing problem arises when a group of Internet of Things is concurrently tracked by cameras and sensors. While cameras view these things as visual “objects”, these things which are equipped with “sensing devices” also continuously report their status. The challenge is that when visualizing these things on videos, their status needs to be placed properly on the screen. This requires correctly pairing visual objects with their sensing devices. There are many real-life examples. Recognizing a vehicle in videos does not imply that we can read its pedometer and fuel meter inside. Recognizing a pet on screen does not mean that we can correctly read its necklace data. In more critical ICU environments, visualizing all patients and showing their physiological signals on screen would greatly relieve nurses’ burdens. The barrier behind this is that the camera may see an object but not be able to see its carried device, not to mention its sensor readings. This paper addresses the device–object pairing problem and presents a multi-camera, multi-IoT device system that enables visualizing a group of people together with their wearable devices’ data and demonstrating the ability to recover the missing bounding box.

Electron Microscopy in Molecular Biology

1967 ◽  
Vol 25 ◽  
pp. 2-3
Author(s):  
Cecil E. Hall
Keyword(s):  
Electron Microscopy ◽  
Molecular Biology ◽  
Noise Level ◽  
Molecular Structures ◽  
Material Structure ◽  
The Arts ◽  
Shadow Casting ◽  
Electron Image ◽  
High Degree ◽  
Very High

The visualization of organic macromolecules such as proteins, nucleic acids, viruses and virus components has reached its high degree of effectiveness owing to refinements and reliability of instruments and to the invention of methods for enhancing the structure of these materials within the electron image. The latter techniques have been most important because what can be seen depends upon the molecular and atomic character of the object as modified which is rarely evident in the pristine material. Structure may thus be displayed by the arts of positive and negative staining, shadow casting, replication and other techniques. Enhancement of contrast, which delineates bounds of isolated macromolecules has been effected progressively over the years as illustrated in Figs. 1, 2, 3 and 4 by these methods. We now look to the future wondering what other visions are waiting to be seen. The instrument designers will need to exact from the arts of fabrication the performance that theory has prescribed as well as methods for phase and interference contrast with explorations of the potentialities of very high and very low voltages. Chemistry must play an increasingly important part in future progress by providing specific stain molecules of high visibility, substrates of vanishing “noise” level and means for preservation of molecular structures that usually exist in a solvated condition.

Novel Therapeutic Approaches and Targets for Treatment of Chronic Urticaria: New Insights and Promising Targets for a Challenging Disease

2020 ◽  
Vol 22 (1) ◽  
pp. 32-45
Author(s):  
Emanuela Martina ◽  
Federico Diotallevi ◽  
Tommaso Bianchelli ◽  
Matteo Paolinelli ◽  
Annamaria Offidani
Keyword(s):  
English Language ◽  
Life Experience ◽  
Case Reports ◽  
Immunosuppressive Agents ◽  
Real Life ◽  
Chronic Spontaneous Urticaria ◽  
New Targets ◽  
Current State ◽  
Pubmed Database ◽  
Novel Drugs

Background: Chronic Spontaneous Urticaria (CSU) is a disease characterized by the onset of wheals and/or angioedema over 6 weeks. The pathophysiology for CSU is very complex, involving mast cells and basophils with a multitude of inflammatory mediators. For many years the treatment of CSU has been based on the use of antihistamines, steroids and immunosuppressive agents with inconstant and frustrating results. The introduction of omalizumab, the only licensed biologic for antihistamine- refractory CSU, has changed the management of the disease. Objective: The aim of this article is to review the current state of the art of CSU, the real-life experience with omalizumab and the promising drugs that are under development. Methods:: An electronic search was performed to identify studies, case reports, guidelines and reviews focused on the new targets for the treatment of chronic spontaneous urticaria, both approved or under investigation. The search was limited to articles published in peer-reviewed journals in the English Language in the PubMed database and trials registered in Clinicaltrials.gov. Results:: Since the advent of omalizumab, the search for new therapies for chronic spontaneous urticaria has had a new impulse. Anti-IgE drugs will probably still be the cornerstone of therapy, but new targets may prove effective in syndromic urticaria or refractory cases. Conclusion:: Although omalizumab has been a breakthrough in the treatment of CSU, many patients do not completely get benefit and even require more effective treatments. Novel drugs are under investigation with promising results.

Conclusion

2017 ◽  
Author(s):  
Andrea Harris
Keyword(s):  
New York ◽  
Twentieth Century ◽  
New York City ◽  
Driving Force ◽  
George Balanchine ◽  
Current State ◽  
The Arts ◽  
History Of ◽  
Lincoln Center

The Conclusion briefly examines the current state of the New York City Ballet under the auspices of industrial billionaire David H. Koch at Lincoln Center. In so doing, it to introduces a series of questions, warranting still more exploration, about the rapid and profound evolution of the structure, funding, and role of the arts in America through the course of the twentieth century. It revisits the historiographical problem that drives Making Ballet American: the narrative that George Balanchine was the sole creative genius who finally created an “American” ballet. In contrast to that hagiography, the Conclusion reiterates the book’s major contribution: illuminating the historical construction of our received idea of American neoclassical ballet within a specific set of social, political, and cultural circumstances. The Conclusion stresses that the history of American neoclassicism must be seen as a complex narrative involving several authors and discourses and crossing national and disciplinary borders: a history in which Balanchine was not the driving force, but rather the outcome.

The Influence of Assessment on Learning and Teaching

2019 ◽  
pp. 166-185
Author(s):  
Susan Hallam
Keyword(s):  
Communities Of Practice ◽  
Teaching And Learning ◽  
Formal Education ◽  
Peer Assessment ◽  
Real Life ◽  
Summative Assessment ◽  
Learning And Teaching ◽  
The Arts ◽  
Assessment Procedures ◽  
Assessment Research

It is debatable whether it is appropriate to assess performance in the arts. However, formal education institutions and the systems within which they operate continue to require summative assessment to take place in order to award qualifications. This chapter considers the extent to which such summative assessment systems in music determine not only what is taught but also what learners learn. The evidence suggests that any learning outcome in formal education that is not assessed is unlikely to be given priority by either learners or teachers. To optimize learning, the aims and the processes of learning, including formative, self-, and peer assessment procedures, should be aligned with summative assessment. Research addressing the roles, methods, and value of formative, self-, and peer assessment in enhancing learning is considered. A proposal is made that the most appropriate way of enhancing learning is to ensure that summative assessment procedures are authentic and have real-life relevance supporting the teaching and learning process, to ensure that learners are motivated and see the relevance of what they are learning. This might take many forms depending on musical genre, communities of practice, and the wider cultural environment.

scholarly journals Practical Cross-Layer Radio Frequency-Based Authentication Scheme for Internet of Things

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4034
Author(s):  
Arie Haenel ◽  
Yoram Haddad ◽  
Maryline Laurent ◽  
Zonghua Zhang
Keyword(s):  
Internet Of Things ◽  
Radio Frequency ◽  
Real Life ◽  
Computation Time ◽  
Cost Effective ◽  
Battery Life ◽  
Cross Layer ◽  
Security Level ◽  
Cost Of Energy ◽  
Iot Devices

The Internet of Things world is in need of practical solutions for its security. Existing security mechanisms for IoT are mostly not implemented due to complexity, budget, and energy-saving issues. This is especially true for IoT devices that are battery powered, and they should be cost effective to be deployed extensively in the field. In this work, we propose a new cross-layer approach combining existing authentication protocols and existing Physical Layer Radio Frequency Fingerprinting technologies to provide hybrid authentication mechanisms that are practically proved efficient in the field. Even though several Radio Frequency Fingerprinting methods have been proposed so far, as a support for multi-factor authentication or even on their own, practical solutions are still a challenge. The accuracy results achieved with even the best systems using expensive equipment are still not sufficient on real-life systems. Our approach proposes a hybrid protocol that can save energy and computation time on the IoT devices side, proportionally to the accuracy of the Radio Frequency Fingerprinting used, which has a measurable benefit while keeping an acceptable security level. We implemented a full system operating in real time and achieved an accuracy of 99.8% for the additional cost of energy, leading to a decrease of only ~20% in battery life.

scholarly journals A Multi-Objective Optimization Method for Hospital Admission Problem—A Case Study on Covid-19 Patients

Algorithms ◽  
2021 ◽  
Vol 14 (2) ◽  
pp. 38
Author(s):  
Amr Mohamed AbdelAziz ◽  
Louai Alarabi ◽  
Saleh Basalamah ◽  
Abdeltawab Hendawi
Keyword(s):  
Medical Care ◽  
Real Life ◽  
Optimization Method ◽  
Multi Objective Optimization ◽  
Admission Process ◽  
Multi Objective ◽  
Admission Time ◽  
King Faisal Specialist Hospital ◽  
Number Of Patients ◽  
Massive Number

The wide spread of Covid-19 has led to infecting a huge number of patients, simultaneously. This resulted in a massive number of requests for medical care, at the same time. During the first wave of Covid-19, many people were not able to get admitted to appropriate hospitals because of the immense number of patients. Admitting patients to suitable hospitals can decrease the in-bed time of patients, which can lead to saving many lives. Also, optimizing the admission process can minimize the waiting time for medical care, which can save the lives of severe cases. The admission process needs to consider two main criteria: the admission time and the readiness of the hospital that will accept the patients. These two objectives convert the admission problem into a Multi-Objective Problem (MOP). Pareto Optimization (PO) is a common multi-objective optimization method that has been applied to different MOPs and showed its ability to solve them. In this paper, a PO-based algorithm is proposed to deal with admitting Covid-19 patients to hospitals. The method uses PO to vary among hospitals to choose the most suitable hospital for the patient with the least admission time. The method also considers patients with severe cases by admitting them to hospitals with the least admission time regardless of their readiness. The method has been tested over a real-life dataset that consisted of 254 patients obtained from King Faisal specialist hospital in Saudi Arabia. The method was compared with the lexicographic multi-objective optimization method regarding admission time and accuracy. The proposed method showed its superiority over the lexicographic method regarding the two criteria, which makes it a good candidate for real-life admission systems.

Puzzles Unpuzzled

2021 ◽  
Vol 5 (CHI PLAY) ◽  
pp. 1-24
Author(s):  
Andrey Krekhov ◽  
Katharina Emmerich ◽  
Ronja Rotthaler ◽  
Jens Krueger
Keyword(s):  
Virtual Reality ◽  
Real Life ◽  
Basic Structure ◽  
Design Framework ◽  
Emotional Challenges ◽  
Related Research ◽  
Board Games ◽  
Current State ◽  
Prior Literature ◽  
High Level

Escape rooms exist in various forms, including real-life facilities, board games, and digital implementations. The underlying idea is always the same: players have to solve many diverse puzzles to (virtually) escape from a locked room. Within the last decade, we witnessed a rapidly increasing popularity of such games, which also amplified the amount of related research. However, the respective academic landscape is mostly fragmented in its current state, lacking a common model and vocabulary that would withstand these games' variety. This manuscript aims to establish such a foundation for the analysis and construction of escape rooms. In a first step, we derive a high-level design framework from prior literature. Then, as our main contribution, we establish an atomic puzzle taxonomy that closes the gap between the analog and digital domains. The taxonomy is developed in multiple steps: we compose a basic structure based on previous literature and systematically refine it by analyzing 39 analog and digital escape room games, including recent virtual reality representatives. The final taxonomy consists of mental, physical, and emotional challenges, thereby providing a robust and approachable basis for future works across all application domains that deal with escape rooms or puzzles in general.

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