User Acceptance Of Mobile Augmented Reality For Tourism By Adopting The UTAUT Model

Of recent times, Augmented Reality (AR) applications have been seen to be able to execute through numerous seamless channels through our smartphones. However, the problem statement identified in the research shows that Malaysia therefore being a country flooded with mobile devices, still have many users who are unaware of the possibilities of AR and making the technology being limited among the mobile users here. That is why the objectives of this research will be to investigate a user’s acceptance of AR technology using the Unified Theory of Acceptance and Use of Technology (UTAUT) model in Malaysia. From here, the research can identify relevant acceptance rate of AR technology, which can then be used to gather and analyse data for this research. The final objective will then be targeted to validate the analysed acceptance rate based on UTAUT. The research is targeted to develop and construct an AR application through a mobile phone which is able to merge 3D AR models of historical monuments. These historical monuments are then identified to be within UNESCO World Heritage Site of Malacca. Such mobile application will enable fellow tourists to be able to get multiple data and information via the monuments from the 3D object models which will be constructed and displayed via AR. The AR models are believed to be able to give tourists an alternative method to visit or view the actual monuments which can enable the prevention of overcrowding effect while at the mean time enforces heritage preservation. Using fellow tourists in Melaka as respondents, the researcher can determine user’s acceptance of the mobile applications in AR based on the methodologies of UTAUT. The main UTAUT methodology used here for the research contains constructs which has been finalized. These includes Performance Expectancy (PE), Effort Expectancy (EE), Facilitating Conditions (FC), and Perceived Playfulness (PP) which are then used as determinants of a user’s Behavioral Intention (BI). Through numerous testing and analysis, user’s acceptance for the AR application was tested and affirmed. Finally, it was found that the coefficient table confirms PE, FC and PP to have a positive significant effect to the model while EE was insignificant. This is due to the high ownership of smartphone device adoption of late therefore allowing users to have minimal effort to use the AR application

Induction of cell cycle arrest and apoptosis by copper complex Cu(SBCM)₂ towards oestrogen-receptor positive MCF-7 breast cancer cells

Copper complexes have the potential to be developed as targeted therapy for cancer because cancer cells take up larger amounts of copper than normal cells. Copper complex Cu(SBCM)2 has been reported to induce cell cycle arrest and apoptosis towards triple-negative breast cancer cells. Nevertheless, its effect towards other breast cancer subtypes has not been explored. Therefore, the present study was conducted to investigate the effect of Cu(SBCM)₂ towards oestrogen-receptor positive MCF-7 breast cancer cells. Growth inhibition of Cu(SBCM)₂ towards MCF-7 and human non-cancerous MCF-10A breast cells was determined by MTT assay. Morphological changes of Cu(SBCM)2-treated-MCF-7 cells were observed under an inverted microscope. Annexin V/PI apoptosis assay and cell cycle analysis were evaluated by flow cytometry. The expression of wild-type p53 protein was evaluated by Western blot analysis. The intracellular ROS levels of MCF-7 treated with Cu(SBCM)₂ were detected using DCFH-DA under a fluorescence microscope. The cells were then co-treated with Cu(SBCM)₂ and antioxidants to evaluate the involvement of ROS in the cytotoxicity of Cu(SBCM)2. Docking studies of Cu(SBCM)2 with DNA, DNA topoisomerase I, and human ribonucleotide reductase were also performed. The growth of MCF-7 cells was inhibited by Cu(SBCM)2 in a dose-dependent manner with less toxicity towards MCF-10A cells. It was found that Cu(SBCM)₂ induced G2/M cell cycle arrest and apoptosis in MCF-7 cells, possibly via a p53 pathway. Induction of intracellular ROS was not detected in MCF-7 cells. Interestingly, antioxidants enhance the cytotoxicity of Cu(SBCM)2 towards MCF-7 cells. DNA topoisomerase I may be the most likely target that accounts for the cytotoxicity of Cu(SBCM)₂

RCEA: Real-time, Continuous Emotion Annotation for collecting precise mobile video ground truth labels

Collecting accurate and precise emotion ground truth labels for mobile video watching is essential for ensuring meaningful predictions. However, video-based emotion annotation techniques either rely on post-stimulus discrete self-reports, or allow real-time, continuous emotion annotations (RCEA) only for desktop settings. Following a user-centric approach, we designed an RCEA technique for mobile video watching, and validated its usability and reliability in a controlled, indoor (N=12) and later outdoor (N=20) study. Drawing on physiological measures, interaction logs, and subjective workload reports, we show that (1) RCEA is perceived to be usable for annotating emotions while mobile video watching, without increasing users' mental workload (2) the resulting time-variant annotations are comparable with intended emotion attributes of the video stimuli (classification error for valence: 8.3%; arousal: 25%). We contribute a validated annotation technique and associated annotation fusion method, that is suitable for collecting fine-grained emotion annotations while users watch mobile videos

Performance of the CMS muon trigger system in proton-proton collisions at √s = 13 TeV

The muon trigger system of the CMS experiment uses a combination of hardware and software to identify events containing a muon. During Run 2 (covering 2015-2018) the LHC achieved instantaneous luminosities as high as 2 × 10 cm s while delivering proton-proton collisions at √s = 13 TeV. The challenge for the trigger system of the CMS experiment is to reduce the registered event rate from about 40 MHz to about 1 kHz. Significant improvements important for the success of the CMS physics program have been made to the muon trigger system via improved muon reconstruction and identification algorithms since the end of Run 1 and throughout the Run 2 data-taking period. The new algorithms maintain the acceptance of the muon triggers at the same or even lower rate throughout the data-taking period despite the increasing number of additional proton-proton interactions in each LHC bunch crossing. In this paper, the algorithms used in 2015 and 2016 and their improvements throughout 2017 and 2018 are described. Measurements of the CMS muon trigger performance for this data-taking period are presented, including efficiencies, transverse momentum resolution, trigger rates, and the purity of the selected muon sample. This paper focuses on the single- and double-muon triggers with the lowest sustainable transverse momentum thresholds used by CMS. The efficiency is measured in a transverse momentum range from 8 to several hundred GeV

Mobile augmented reality applications for heritage preservation in UNESCO world heritage sites through adopting the UTAUT model

Augmented reality (AR) technology has undergone enormous advancement and now AR applications can be seamlessly executed using modern-day smartphones. This study aims to develop a mobile AR application which consists of 3D AR models of historical monuments located within the UNESCO World Heritage Site in Melaka. The application allows tourists to obtain information of the monuments from the AR models, which provide an alternative way of visiting the actual monuments to prevent overcrowding effect and promote heritage preservation. Perceived Usefulness (PU), Perceived Ease of Use (PEU), Facilitating Conditions (FC), and Perceived Playfulness (PP) are proposed as the determinants of user’s Behavioural Intention to Use (BI) the application. Using 50 tourists in Melaka as respondents, a pilot study has been conducted to determine user’s acceptance of the AR mobile application based on the Unified Theory of Acceptance and Use of Technology (UTAUT). Cronbach’s Alpha test validated the internal consistency of the measures. Multiple Linear Regression analysis suggested that the proposed determinants explained 51.2% in user’s BI the application. PU was the strongest determinant followed by FC while PEU and PP were found to be insignificant

Performance aware tasking for environmentally powered sensor networks

The use of environmental energy is now emerging as a feasible energy source for embedded and wireless computing systems such as sensor networks where manual recharging or replacement of batteries is not practical. However, energy supply from environmental sources is highly variable with time. Further, for a distributed system, the energy available at its various locations will be different. These variations strongly influence the way in which environmental energy is used. We present a harvesting theory for determining performance in such systems. First we present a model for characterizing environmental sources. Second, we state and prove two harvesting theorems that help determine the sustainable performance level from a particular source. This theory leads to practical techniques for scheduling processes in energy harvesting systems. Third, we present our implementation of a real embedded system that runs on solar energy and uses our harvesting techniques. The system adjusts its performance level in response to available resources. Fourth, we propose a localized algorithm for increasing the performance of a distributed system by adapting the process scheduling to the spatio-temporal characteristics of the environmental energy in the distributed system. While our theoretical intuition is based on certain abstractions, all the scheduling methods we present are motivated solely from the experimental behavior and resource constraints of practical sensor networking systems