Power Reduction Sleep Scheduling Technique for Cloud Integrated Green Social Sensor Network

The wireless sensor network is the maximum appropriate technology nowadays with such awesome applications and areas including Infrastructure tracking, environment tracking, health care tracking, etc. Cloud Computing has fantastic data collecting skills and effective data processing ability. Social Network is a group of People or organizations of human beings with similar intentions. Social Sensor Cloud is one type of expertise-sharing mechanism wherein similar types of human beings can connect. Energy Consumption is nowadays the largest challenge as far as the concern with green environment. Because the battery life of the sensor is so limited, the Social Sensor Cloud must be energy efficient. As a result, this article will concentrate on Energy-Efficient Techniques for the Social Sensor Cloud. According to our findings, findings, the majority of energy-saving measures will cope with not unusual place Parameters including Network Lifetime, Network Work rate, Throughput, Energy, Bandwidth, etc. We will Summarize current Technology and we Will Provide Our Architecture for Energy Reduction in Social Sensor Cloud

Location Based Power Reduction Cloud Integrated Social Sensor Network

It is great to hear about the advancements in wireless sensor networks and their applications, as well as the integration of cloud computing to enhance data analysis and storage capabilities. Indeed, these technologies have opened up numerous possibilities across various fields, including infrastructure tracking, environmental monitoring, healthcare, and more. The concept of a social sensor cloud, as you mentioned, brings an interesting dimension to this technology landscape by focusing on knowledge-sharing and connecting like-minded individuals or organizations. This could potentially lead to more collaborative and efficient solutions across a wide range of domains. Energy efficiency is a critical consideration in the design and operation of wireless sensor networks and the cloud infrastructure that supports them. The limited battery life of sensors necessitates careful management of energy consumption to ensure optimal functionality and longevity. Sleep scheduling methods are a common technique used to manage energy consumption in these networks. By coordinating when sensors are active and when they are in a low-power sleep mode, energy consumption can be significantly reduced without compromising the network's overall effectiveness. In the context of the Social Sensor Cloud, managing energy efficiency becomes even more crucial due to the shorter battery life of the sensors involved. This is particularly relevant given the growing concerns about environmental sustainability and the need to reduce energy consumption across technological systems. It's clear that your research paper addresses these challenges head-on, by exploring energy-efficient techniques for the Social Sensor Cloud. Sleep scheduling is just one of the many strategies that researchers and engineers are working on to strike a balance between functionality and energy consumption. Other methods might include optimizing data transfer protocols, developing energy-harvesting mechanisms, and enhancing sensor hardware efficiency. As technology continues to evolve, the integration of wireless sensor networks, cloud computing, and social networks will likely pave the way for innovative solutions and transformative applications. Addressing energy efficiency concerns will undoubtedly play a crucial role in ensuring the long-term viability and positive impact of these technologies

Design and Functional Validation of a Mechanism for Dual-Spinning CubeSats

The mission of the Micro-sized Microwave Atmospheric Satellite (MicroMAS) is to collect useful atmospheric images using a miniature passive microwave radiometer payload hosted on a low-cost CubeSat platform. In order to collect this data, the microwave radiometer payload must rotate to scan the ground-track perpendicular to the satellite's direction of travel. A custom motor assembly was developed to facilitate the rotation of the payload while allowing the spacecraft bus to remained fixed in the local-vertical, local-horizontal (LVLH) frame for increased pointing accuracy. This paper describes the mechanism used to enable this dual-spinning operation for CubeSats, and the lessons learned during the design, fabrication, integration, and testing phases of the mechanism's development lifecycle

Radiometer Calibration Using Colocated GPS Radio Occultation Measurements

We present a new high-fidelity method of calibrating a cross-track scanning microwave radiometer using Global Positioning System (GPS) radio occultation (GPSRO) measurements. The radiometer and GPSRO receiver periodically observe the same volume of atmosphere near the Earth's limb, and these overlapping measurements are used to calibrate the radiometer. Performance analyses show that absolute calibration accuracy better than 0.25 K is achievable for temperature sounding channels in the 50-60-GHz band for a total-power radiometer using a weakly coupled noise diode for frequent calibration and proximal GPSRO measurements for infrequent (approximately daily) calibration. The method requires GPSRO penetration depth only down to the stratosphere, thus permitting the use of a relatively small GPS antenna. Furthermore, only coarse spacecraft angular knowledge (approximately one degree rms) is required for the technique, as more precise angular knowledge can be retrieved directly from the combined radiometer and GPSRO data, assuming that the radiometer angular sampling is uniform. These features make the technique particularly well suited for implementation on a low-cost CubeSat hosting both radiometer and GPSRO receiver systems on the same spacecraft. We describe a validation platform for this calibration method, the Microwave Radiometer Technology Acceleration (MiRaTA) CubeSat, currently in development for the National Aeronautics and Space Administration (NASA) Earth Science Technology Office. MiRaTA will fly a multiband radiometer and the Compact TEC/Atmosphere GPS Sensor in 2015.United States. Dept. of Defense. Assistant Secretary of Defense for Research & Engineering (United States. Air Force Contract FA8721-05-C-0002

Tradespace Investigation of a Telescope Architecture for Next-generation Space Astronomy and Exploration

Humanity’s endeavor to further its scientific understanding of the celestial heavens has led to the creation and evolution of increasingly powerful and complex space telescopes. Space telescopes provide a view of the solar system, galaxy, and universe unobstructed by Earth’s atmosphere and have profoundly changed the way people view space. In an effort to further advance space telescope capability and achieve the accompanying scientific understanding, the Massachusetts Institute of Technology (MIT), specifically, course 16.89 Space Systems Engineering, explored the tradespace of architectural enumerations encompassed within the design of an ultraviolet-optical-infrared (UVOIR) space telescope located at Sun-Earth Lagrangian Point Two (SE-L2). SE-L2 presents several advantages as an operating location for a UVOIR telescope such as a thermally stable environment and an orbit that allows the telescope to maintain a constant orientation with respect to all of the primary sources of heat and light. The main disadvantages associated with SE-L2 are caused by its relatively large distance from Earth, which marginalizes the effectiveness of real-time telerobotics because of latency and increases the cost of communications, launch, and servicing. Course 16.89 believes that, for this UVOIR application, the strengths of this operating location outweigh its weaknesses and therefore decided to explore the family of opportunities associated with SE-L2. This course used appropriate performance and system metrics to quantify the effectiveness of the aforementioned architectures and create a Pareto front of viable architectures. Evaluating the designs along the Pareto front allowed the course to characterize and group architectures and present these group-types to stakeholders for the selection of an optimal space telescope according to stakeholder requirements and resources. This course also developed sensitivity analysis, which allowed for a greater understanding of how architectural decisions affect the performance of the satellite. Segmentation, modularity, assembly, autonomy, and servicing were key aspects of this multidimensional analysis given the 16.8-meter class size and location of the telescope. Within the respective operating environment and for a spacecraft of similar characteristics, this model will allow stakeholders to predict the long-term operational effectiveness of different space telescope architectures and capture the synergistic effects of combining various architectural decisions into a spacecraft design. The following sections step through the aforesaid analysis and design efforts conducted in 16.89 beginning with Section III, which explicitly performs the stakeholder analysis and articulates the requirements of the mission. Section IV gives an overview of past designs and expands upon the architecture enumerations pertinent to this project, while Section V presents the methods and metrics by which those architectures will be evaluated and the system metrics which will be balanced and optimized in the creation of this space telescope. Section VI will present the model validation of this project and Section VII will discuss the results and analyses of the project. Finally, Section VIII will explore the future work opportunities of this project, while Section IX will present the conclusions and recommendations drawn from this project.MIT Department of Aeronautics and Astronautic

Systemic effects of periodontitis treatment in patients with type 2 diabetes: a 12 month, single-centre, investigator-masked, randomised trial

BACKGROUND: Chronic inflammation is believed to be a major mechanism underlying the pathophysiology of type 2 diabetes. Periodontitis is a cause of systemic inflammation. We aimed to assess the effects of periodontal treatment on glycaemic control in people with type 2 diabetes. METHODS: In this 12 month, single-centre, parallel-group, investigator-masked, randomised trial, we recruited patients with type 2 diabetes, moderate-to-severe periodontitis, and at least 15 teeth from four local hospitals and 15 medical or dental practices in the UK. We randomly assigned patients (1:1) using a computer-generated table to receive intensive periodontal treatment (IPT; whole mouth subgingival scaling, surgical periodontal therapy [if the participants showed good oral hygiene practice; otherwise dental cleaning again], and supportive periodontal therapy every 3 months until completion of the study) or control periodontal treatment (CPT; supra-gingival scaling and polishing at the same timepoints as in the IPT group). Treatment allocation included a process of minimisation in terms of diabetes onset, smoking status, sex, and periodontitis severity. Allocation to treatment was concealed in an opaque envelope and revealed to the clinician on the day of first treatment. With the exception of dental staff who performed the treatment and clinical examinations, all study investigators were masked to group allocation. The primary outcome was between-group difference in HbA1c at 12 months in the intention-to-treat population. This study is registered with the ISRCTN registry, number ISRCTN83229304. FINDINGS: Between Oct 1, 2008, and Oct 31, 2012, we randomly assigned 264 patients to IPT (n=133) or CPT (n=131), all of whom were included in the intention-to-treat population. At baseline, mean HbA1c was 8·1% (SD 1·7) in both groups. After 12 months, unadjusted mean HbA1c was 8·3% (SE 0·2) in the CPT group and 7·8% (0·2) in the IPT group; with adjustment for baseline HbA1c, age, sex, ethnicity, smoking status, duration of diabetes, and BMI, HbA1c was 0·6% (95% CI 0·3-0·9; p<0·0001) lower in the IPT group than in the CPT group. At least one adverse event was reported in 30 (23%) of 133 patients in the IPT group and 23 (18%) of 131 patients in the CPT group. Serious adverse events were reported in 11 (8%) patients in the IPT group, including one (1%) death, and 11 (8%) patients in the CPT group, including three (2%) deaths. INTERPRETATION: Compared with CPT, IPT reduced HbA1c in patients with type 2 diabetes and moderate-to-severe periodontitis after 12 months. These results suggest that routine oral health assessment and treatment of periodontitis could be important for effective management of type 2 diabetes. FUNDING: Diabetes UK and UK National Institute for Health Research.Diabetes UK and UK National Institute for Health Researc

The development and validation of a scoring tool to predict the operative duration of elective laparoscopic cholecystectomy

Background: The ability to accurately predict operative duration has the potential to optimise theatre efficiency and utilisation, thus reducing costs and increasing staff and patient satisfaction. With laparoscopic cholecystectomy being one of the most commonly performed procedures worldwide, a tool to predict operative duration could be extremely beneficial to healthcare organisations. Methods: Data collected from the CholeS study on patients undergoing cholecystectomy in UK and Irish hospitals between 04/2014 and 05/2014 were used to study operative duration. A multivariable binary logistic regression model was produced in order to identify significant independent predictors of long (> 90 min) operations. The resulting model was converted to a risk score, which was subsequently validated on second cohort of patients using ROC curves. Results: After exclusions, data were available for 7227 patients in the derivation (CholeS) cohort. The median operative duration was 60 min (interquartile range 45–85), with 17.7% of operations lasting longer than 90 min. Ten factors were found to be significant independent predictors of operative durations > 90 min, including ASA, age, previous surgical admissions, BMI, gallbladder wall thickness and CBD diameter. A risk score was then produced from these factors, and applied to a cohort of 2405 patients from a tertiary centre for external validation. This returned an area under the ROC curve of 0.708 (SE = 0.013, p  90 min increasing more than eightfold from 5.1 to 41.8% in the extremes of the score. Conclusion: The scoring tool produced in this study was found to be significantly predictive of long operative durations on validation in an external cohort. As such, the tool may have the potential to enable organisations to better organise theatre lists and deliver greater efficiencies in care

Community-Driven Data Analysis Training for Biology

The primary problem with the explosion of biomedical datasets is not the data, not computational resources, and not the required storage space, but the general lack of trained and skilled researchers to manipulate and analyze these data. Eliminating this problem requires development of comprehensive educational resources. Here we present a community-driven framework that enables modern, interactive teaching of data analytics in life sciences and facilitates the development of training materials. The key feature of our system is that it is not a static but a continuously improved collection of tutorials. By coupling tutorials with a web-based analysis framework, biomedical researchers can learn by performing computation themselves through a web browser without the need to install software or search for example datasets. Our ultimate goal is to expand the breadth of training materials to include fundamental statistical and data science topics and to precipitate a complete re-engineering of undergraduate and graduate curricula in life sciences. This project is accessible at https://training.galaxyproject.org. We developed an infrastructure that facilitates data analysis training in life sciences. It is an interactive learning platform tuned for current types of data and research problems. Importantly, it provides a means for community-wide content creation and maintenance and, finally, enables trainers and trainees to use the tutorials in a variety of situations, such as those where reliable Internet access is unavailable

Ultralight vector dark matter search using data from the KAGRA O3GK run

Among the various candidates for dark matter (DM), ultralight vector DM can be probed by laser interferometric gravitational wave detectors through the measurement of oscillating length changes in the arm cavities. In this context, KAGRA has a unique feature due to differing compositions of its mirrors, enhancing the signal of vector DM in the length change in the auxiliary channels. Here we present the result of a search for U(1)B−L gauge boson DM using the KAGRA data from auxiliary length channels during the first joint observation run together with GEO600. By applying our search pipeline, which takes into account the stochastic nature of ultralight DM, upper bounds on the coupling strength between the U(1)B−L gauge boson and ordinary matter are obtained for a range of DM masses. While our constraints are less stringent than those derived from previous experiments, this study demonstrates the applicability of our method to the lower-mass vector DM search, which is made difficult in this measurement by the short observation time compared to the auto-correlation time scale of DM