Third generation wireless signal profiling

This paper is about third generation, PCS and other cellular signal profiling in a built-up area such as Melbourne CBD. The purpose of this investigation is to determine the variation of the signal strength between a transmitter, 1218-BV lockable oscillator 900-2000MHz general radio, mounted on top of a RMIT University building and a portable receiver, Protek 3201, covering the streets below the transmitter. It is divided into sectors and the points of data collection are marked in steps of 10 meter. The transmission paths between the transmitter and receiver can be varied from direct line-of-sight to those fully blocked by a tree or a building. 3G systems require site-specific propagation modeling due to the high speed signal such as video-conferencing and video streaming. They require reliable and continuous service. Signal profiting is essential for service reliability.

ABSTRACTThe current study examines the temporal stability of the tripartite model of reminiscence functions in which eight separate reminiscence functions map onto three second-order factors which contribute significantly to measurement of an overarching reminiscence latent construct. We collected online responses from 411 adults 50+ years of age. Confirmatory factor analytic models were computed at three points of data collection over 16 months. Invariance analyses were next undertaken to simultaneously compare the measurement properties to assess within-person stability of reminiscence functions over time. The tripartite structure of reminiscence functions was replicated at each point of data collection. As hypothesised, self-positive and self-negative functions are consistent across points of data collection, whereas prosocial functions vary over time. The temporal stability of the self functions may be attributed to enduring characteristics of the individual such as personality traits and life attitudes, as well as their solitary nature. Previous research indicates that consistency of self-positive reminiscence functions has ensuing benefits for physical health and psychological well-being; the opposite is true for self-negative functions. The temporal variation of prosocial functions may be due to the varying availability of others to share memories and their responsiveness to the emotional context.

Recent research shows that significant energy saving can be achieved in wireless sensor networks by using mobile elements (MEs) capable of carrying data mechanically. Though ME can reduce the energy consumption at each sensor node, it increases the latency from the time the data is generated at a node to the time the base station receives it. To address this issue, we proposed a collection-based approach in which a subset of nodes served as the data collection points (CPs) that buffer data originated from sources and transfer to ME when it arrives. CPs shorten the trajectory of ME which can gather a large volume of data at a time, however, they also increase energy consumption of nodes to transmit data to them. There is a trade-off between the energy consumption of network and the length of trajectory of ME which is determined by the number of CPs. In this paper, we introduce a Probabilistic Path Selection (PPS) algorithm to reduce the data collection delay for stochastic event detection scenario. Furthermore, we develop a heuristic algorithm and extend to the more general case of combined ME and CPs selection to enable a flexible trade-off between energy consumption and data delivery latency. Our implementation and simulation results show nearly monotonic decrease of data delivery latency for greater limits on the energy consumption, and which is same on the contrary.

Radio Frequency Identification (RFID) technology is being widely applied within logistical supply chains to keep track of items and their containers from the point of manufacture all the way to the point of item use. The systems that provide this tracking capability consist of inexpensive electronic tags which are affixed to the items and containers, readers which extract data from these tags as they pass along the supply chain, data collection points where the data that has been read is aggregated, a communications system that connects the readers to the collection points and the collection points to each other, and a data base with accompanying software that can provide useful interpretations of the data that is being collected by the system. There are several applications of this technology with potential for enhancing military operations. For example, consider the preparation of a small unit of action about to embark on a mission that requires a collection of specialized equipment to be distributed among the unit individuals. Each item in the collection could be tagged before each individual is equipped. At the mission jumping-off point, each individual could be scanned by a reader to verify that they have the required equipment for the mission. In addition, the leader of the mission could periodically scan his individual soldiers to determine their equipment complement at any time during the mission.

Unnamed aerial vehicle (UAV) can be employed to collect sensed data from sensor nodes (SNs) in wireless sensor networks, thanks to its high mobility and great maneuverability. However, it is very challenging for one single UAV with limited energy storage to complete the data collection task while guaranteeing the information freshness of the SNs. In this work, we investigate the AoI-optimal data collection problem in multi-UAV-aided wireless sensor networks, where the SNs may be densely located and multiple UAVs with limited energy supply perform data collection collaboratively. In a dense network, the communication ranges of the SNs might overlap with each other, and there is no need for the UAVs to fly over the SNs one by one and collect their sensing data sequentially. Instead, some points can be selected as data collection points (CPs) at which the UAVs collect data from multiple SNs simultaneously. Accordingly, the multi-UAV-aided data collection problem can be decomposed into three parts. Firstly, the positions of the CPs are determined and the SN-CP association is established based on graph theory. Secondly, the CPs are clustered based on the kernel K-means method with each cluster of CPs being visited by one UAV. Thirdly, the optimal flight trajectory of each UAV is found to minimize the the SNs' maximal age of information (AoI) subject to the limited energy capacity. Simulation results validate the effectiveness of our proposed data collection scheme.

Objectives: In old age, the will-to-live (WTL) is one of the most important indicators of subjective well-being (SWB). However, few studies to date have focused on WTL. In these studies, WTL has mainly been evaluated via indirect questions concerning factors that may influence peoples’ WTL, or by measures directed to patients with specific diseases. The current study describes the development and psychometric properties of a new WTL scale.Method: The five-item WTL scale was developed on the basis of previous qualitative and quantitative research, and was evaluated in a longitudinal study of a random sample of 868 adults, aged 75+.Results: Confirmatory factor analytic (CFA) models were computed showing that each of the five items contributed significantly to measurement of a single WTL latent factor. Goodness-of-fit statistics were in ideal parameters for these CFA models at each point of data collection. Moreover, temporal analyses indicated that the relative contribution to measurement for each item was equivalent across time, attesting to reliability of measurement and the construct validity of WTL measurement. Concurrent validity was supported by significant positive correlations between WTL and life satisfaction, happiness, self-rated health, morale, self-rated aging, and, as expected, by inverse associations of WTL with depression and loneliness.Conclusion: The results of these analyses indicate that the WTL scale is a valid and reliable instrument. Considering the importance of the WTL concept in late life, and the psychometric properties of the WTL scale, we recommend it for use in research and practice related to older adults’ SWB and end-of-life care.

User responses to a smart charging system in Germany: Battery electric vehicle driver motivation, attitudes and acceptance

In UK hospitals, traditional ward pharmacy services involve pharmacists visiting their wards once or twice a day each weekday. However, to provide a more patient orientated ward pharmacy service, we developed the Imperial Model of Ward Pharmacy. This is based on pharmacists seeing every drug chart every other day, allowing increased focus towards patients' needs on other days. To assess the impact of the Imperial Model of Ward Pharmacy on the prevalence of new medication orders that have not been screened by pharmacists, and doses omitted due to medication being unavailable. We conducted an uncontrolled before-and-after study on eight medical wards. In each phase, we collected data on the number and prevalence of active medication orders that had not been screened by a pharmacist at the point of data collection, and the number and prevalence of regular doses documented as being omitted due to drug unavailability, or for which the administration record was left blank. The prevalence of unscreened medication orders reduced from 7.6 % of 1,433 orders to 4.1 % of 1,495 orders (p = 0.0002; Chi square test). There was no change in the prevalence of dose omissions (1.4 % in each phase of the study). This is a practical way to move to a more patient-focused service without affecting the safety of the service provided.

ObjectivesWe will investigate the effectiveness of high dose Interferon Beta 1a, compared to low dose Interferon Beta 1a (the base therapeutic regimen) in COVID-19 Confirmed Cases (Either RT-PCR or CT Scan Confirmed) with moderate to severe diseaseTrial DesignThis is a single center, open label, randomized, controlled, 2-arm parallel group (1:1 ratio), clinical trial.ParticipantsThe eligibility criteria in this study is: age ≥ 18 years, oxygen saturation (SPO2) ≤ 93% or respiratory rate ≥ 24, at least one of the following manifestation: radiation contactless body temperature ≥37.8, Cough, shortness of breath, nasal congestion/ discharge, myalgia/arthralgia, diarrhea/vomiting, headache or fatigue on admission. The onset of the symptoms should be acute (≤ 14 days). The exclusion criteria include refusal to participate, using drugs with potential interaction with lopinavir/ritonavir or interferon-β 1a, blood ALT/AST levels > 5 times the upper limit of normal on laboratory results, pregnant or lactating women, history of alcohol or drug addiction in the past 5 years, the patients who be intubated less than one hours after admission to hospital.This study will be undertaken at the Loghman Hakim Hospital, Shahid Beheshti University of Medical Sciences.Intervention and ComparatorCOVID- 19 confirmed patients (using the RT-PCR test or CT scan) will be randomly assigned to one of two groups. The intervention group (Arms1) will be treated with lopinavir / ritonavir (Kaletra) + high dose Interferon-β 1a (Recigen) and the control group will be treated with lopinavir / ritonavir (Kaletra) + low dose Interferon-β 1a (Recigen) (the base therapeutic regimen). Both groups will receive standard care consisting of the necessary oxygen support, non-invasive, or invasive mechanical ventilation.Main outcomesPrimary outcome: Time to clinical improvement is our primary outcome measure. This is an improvement of two points on a seven-category ordinal scale (recommended by the World Health Organization: Coronavirus disease (COVID-2019) R&D. Geneva: World Health Organization) or discharge from the hospital, whichever comes first.Secondary outcomes: mortality from the date of randomization until the last day of the study which will be the day all of the patients have had at least one of the following outcomes: 1) Improvement of two points on a seven-category ordinal scale. 2) Discharge from the hospital 3) Death. Improvement of SPO2 during the hospitalization, duration of hospitalization from date of randomization until the date of hospital discharge or death, whichever comes first. The incidence of new mechanical ventilation uses from the date of randomization until the last day of the study and the duration of it will be extracted. Please note that we are trying to add further secondary outcomes and this section of the protocol is still evolving.RandomizationEligible patients with confirmed SARS-Cov-2 infections will be randomly assigned in a 1:1 ratio to two therapeutic arms using permuted, block-randomization to balance the number of patients allocated to each group. The permuted block (three or six patients per block) randomization sequence will be generated, using Package ‘randomizeR’ in R software version 3.6.1. and placed in individual sealed and opaque envelopes by the statistician. The investigator will enroll the patients and only then open envelopes to assign patients to the different treatment groups. This method of allocation concealment will result in minimum selection and confounding biases.Blinding (Masking)The present research is open-label (no masking) of patients and health care professionals who are undertaking outcome assessment of the primary outcome - time to clinical improvement.Numbers to be randomised (sample size)Of the 100 patients randomised, 50 patients will be assigned to receive high dose Interferon beta-1a plus lopinavir/ritonavir (Kaletra), 50 patients will be assigned to receive low dose Interferon beta 1a plus lopinavir/ritonavir (Kaletra).Trial StatusProtocol version 1.2.1. Recruitment is finished, the start date of recruitment was on August 20th 2020, and the end date was on September 4th 2020. Last point of data collection will be the last day on which all of the 100 participants have had an outcome of clinical improvement or death, up to 14th days after hospitalization.Trial registrationThis study was registered with National Institutes of Health Clinical trials (www.clinicaltrials.gov; identification number NCT04521400, https://clinicaltrials.gov/ct2/show/NCT04521400, registered August 18, 2020 and first available online August 20, 2020).Full protocolThe full protocol is attached as an additional file, accessible from the Trials website (Additional file 1). In the interest in expediting dissemination of this material, the familiar formatting has been eliminated; this Letter serves as a summary of the key elements of the full protocol.

Digital devices, the data they collect, and the algorithms that process this data have transformed government, business and everyday life. In this chapter I offer a brief introduction to privacy in the context of American jurisprudence. I then identify major risks to personal privacy that occur at three stages of the “lifecycle” of data: infrastructural asymmetry at the point of data collection, distortion at the point of data analysis, and discrimination at the point of deployment of the insights of data analysis. Having identified these risks, I then introduce a framework consisting of four categories of responses that can be adopted to mitigate them. These categories of responses apply at the level of the individual and of society at large, and in both instrumental and epistemological senses. I conclude by arguing that this framework should serve as a basis for future research into the effects of ICTs on privacy.

The present study aims to examine the relationship between workplace support and job satisfaction among academic staff in five Malaysian public research universities. The population of this study is 12,994 academic staff, and the sample size was 325. The sample was obtained using convenience sampling technique, in which information was gathered from elements of the population who are conveniently available at the point of data collection. The workplace support construct is made up of four elements: Perceived organizational support (POS), supervisor support, co-worker support, and mentoring. The findings of Pearson correlation analysis indicate that workplace supports (POS, supervisor support, co-worker support, and mentoring) have positive correlation on job satisfaction. Meanwhile, the result of multiple regressions shows only POS and mentoring positively effect on employee job satisfaction. Thus, the greater the extent to which employees perceived that the organization is giving them support and support from mentor to junior employee, the more they feel a moral obligation to keep working for that organization. Still, efforts should be made to improve the existing workplace support in public research universities as it can lead to higher job satisfaction and higher productivity level among the academics staffs.

Advanced care planning (ACP) can empower patients to make decisions about their care according to their values and preferences. To improve the rate of advance care planning referral amongst inpatients...

e-Healthcare promises to be the next big wave in healthcare. It offers all the advantages and benefits imaginable by both the patient and the user. However, current e-Healthcare systems are not yet fully developed and mature, and thus lack the degree of confidentiality, integrity, privacy, and user trust necessary to be widely implemented. Two primary aspects of any operational healthcare enterprise are the quality of healthcare services and patient trust over the healthcare enterprise. Trust is intertwined with issues like confidentiality, integrity, accountability, authenticity, identity, and data management, to name a few. Privacy remains one of the biggest obstacles to ensuring the success of e-Healthcare solutions in winning patient trust as it indirectly covers most security concerns. Addressing privacy concerns requires addressing security issues like access control, authentication, non-repudiation, and accountability, without which end-to-end privacy cannot be ensured. Achieving privacy from the point of data collection in wireless sensor networks, to incorporating the Internet of Things, to communication links, and to data storage and access, is a huge undertaking and requires extensive work. Privacy requirements are further compounded by the fact that the data handled in an enterprise are of an extremely personal and private nature, and its mismanagement, either intentionally or unintentionally, could seriously hurt both the patient and future prospects of an e-Healthcare enterprise. Research carried out in order to address privacy concerns is not homogenous in nature. It focuses on the failure of certain parts of the e-Healthcare enterprise to fully address all aspects of privacy. In the middle of this ongoing research and implementation, a gradual shift has occurred, moving e-Healthcare enterprise controls away from an organizational level toward the level of patients. This is intended to give patients more control and authority over decision making regarding their protected health information/electronic health record. A lot of works and efforts are necessary in order to better assess the feasibility of this major shift in e-Healthcare enterprises. Existing research can be naturally divided on the basis of techniques used. These include data anonymization/pseudonymization and access control mechanisms primarily for stored data privacy. This, however, results in giving a back seat to certain privacy requirements (accountability, integrity, non-repudiation, and identity management). This paper reviews research carried out in this regard and explores whether this research offers any possible solutions to either patient privacy requirements for e-Healthcare or possibilities for addressing the (technical as well as psychological) privacy concerns of the users.

This study was conducted with the aim of knowing changes in temperature in the urban forest green open space (RTH) area and in non-green open space areas in the Megamas Manado complex. This study uses a descriptive analytical design. In this study, there are microclimate variables and the determination of the sample using purposive sampling method. This study aims to test the hypothesis whether it is true that the temperature in the green open space area is lower than the temperature in the non green open space area. There are three data collection points, namely in the urban forest area, the Mega Mall area, and the Marina-2 Manado area. Based on the average temperature value, it shows that the temperature in the green open space is lower than the temperature in the non green open area. The statistical test results also state that there is a significant (significant) difference between the temperature in the green open space and the temperature in the non green open space. Therefore, this research concludes that the Green Open Space Area (RTH) can reduce solar energy, so that the temperature in the green open space area is lower than the temperature in the non-RTH area.

Although class attendance is linked to academic performance, questions remain about what determines students' decisions to attend or miss class. In addition to the constructs of a common decision-making model, the theory of planned behaviour, the present study examined the influence of student role identity and university student (in-group) identification for predicting both the initiation and maintenance of students' attendance at voluntary peer-assisted study sessions in a statistics subject. University students enrolled in a statistics subject were invited to complete a questionnaire at two time points across the academic semester. A total of 79 university students completed questionnaires at the first data collection point, with 46 students completing the questionnaire at the second data collection point. Twice during the semester, students' attitudes, subjective norm, perceived behavioural control, student role identity, in-group identification, and intention to attend study sessions were assessed via on-line questionnaires. Objective measures of class attendance records for each half-semester (or 'term') were obtained. Across both terms, students' attitudes predicted their attendance intentions, with intentions predicting class attendance. Earlier in the semester, in addition to perceived behavioural control, both student role identity and in-group identification predicted students' attendance intentions, with only role identity influencing intentions later in the semester. These findings highlight the possible chronology that different identity influences have in determining students' initial and maintained attendance at voluntary sessions designed to facilitate their learning.