Multi Layered Multi Task Marker Based Interaction in Information Rich Virtual Environments

Simple and cheap interaction has a key role in the operation and exploration of any Virtual Environment (VE). In this paper, we propose an interaction technique that provides two different ways of interaction (information and control) on complex objects in a simple and computationally cheap way. The interaction is based on the use of multiple embedded markers in a specialized manner. The proposed marker like an interaction peripheral works just like a touch paid which can perform any type of interaction in a 3D VE. The proposed marker is not only used for interaction with Augmented Reality (AR), but also with Mixed Reality. A biological virtual learning application is developed which is used for evaluation and experimentation. We conducted our experiments in two phases. First, we compared a simple VE with the proposed layered VE. Second, a comparative study is conducted between the proposed marker, a simple layered marker, and multiple single markers. We found the proposed marker with improved learning, easiness in interaction, and comparatively less task execution time. The results gave improved learning for layered VE as compared to simple VE

Synthesis and characterization of CoFe2O4/MWCNTs nanocomposites and high-frequency analysis of their dielectric properties.

Nanoparticles of CoFe2O4 were synthesized by chemical co-precipitation method. The CoFe2O4/MWCNT nanocomposites were synthesized with increasing contents of MWCNTs, i.e., 0.0, 2.0, 3.0, and 5.0% by weight via ultrasonication method in a dispersive medium using ortho-xylene. The synthesized cobalt ferrite nanoparticles and their nanocomposites were characterized by impedance analyzer, Fourier-transform infrared spectroscopy (FTIR), scanning electron microscope (SEM), and x-ray diffraction (XRD) techniques. The XRD indexed patterns confirmed the face-centered cubic structure of CoFe2O4/MWCNT nanocomposites. The average crystallite size in all the samples was in the range of 15 to 35 nm. The decorations of CoFe2O4 on MWCNTs were confirmed by SEM images. The FTIR results showed two vibrational bands. With the increasing contents of multi-walled carbon nanotubes in the cobalt ferrite/MWCNT nanocomposites, the dielectric properties were also enhanced. At 1 MHz, dielectric constant, dielectric loss, and tangent loss factor were increased from 26, 15.1, and 0.580 for pure cobalt ferrite to 47, 28.9, and 0.614 for loading of 5% MWCNTs, respectively. At 1 GHz, dielectric constant, dielectric loss, and tangent loss factor were increased from 11.6, 0.33, and 0.028 for pure cobalt ferrite to 19.4, 0.61, and 0.031 for loading of 5% MWCNTs, respectively. Such a huge increase in the dielectric properties of cobalt ferrite and multi-walled carbon nanocomposites exploited their applications at high frequency

New Inflation in Waterfall Region

We introduce a class of new inflation models within the waterfall region of a generalized hybrid inflation framework. The initial conditions are generated in the valley of hybrid preinflation. Both single-field and multi-field inflationary scenarios have been identified within this context. A supersymmetric realization of this scenario can successfully be achieved within the tribrid inflation framework. To assess the model's viability, we calculate the predictions of inflationary observables using the $\delta N$ formalism, demonstrating excellent agreement with the most recent Planck data. Furthermore, this model facilitates successful reheating and nonthermal leptogenesis, with the matter-field component of the inflaton identified as a sneutrino.Comment: 15 pages, 9 figure

Exploring Association of Economic Ties and Social Interaction Between Minorities and Muslims in Pakistan

Financial The socio-political adjustment and economic well-being of minority groups has been reported as one of the important issues in the recent time in Pakistan. The study was conducted to know the adjustment issues of Christians and Sikhs minorities in District Peshawar and Swat of Khyber Pakhtunkhwa of Pakistan. More specifically, the aim of this study was to explore how Sikhs and Christian minorities in Pakistan are adjusted in the social fabric of Muslim majority areas and to what extent their economic ties with Muslims are strengthening their overall social interaction in the area. A total of 372 respondents from the targeted locales were selected through proportional allocation through Sekaran table and data was collected based on five-point Likert scale. The economic activities of the minorities were selected as independent variables while the level of social interaction was obtained as dependent variables. The collected data was analysed at uni-variate level through frequency distribution and Chi square test was performed at bi-variate level. It was found that minorities are fully enjoying participation in the economic activities which results in strong social ties and interaction in their daily lives with Muslim majority in the study area. However, it was also found that the minorities are still underprivileged in the area of economic and business activities in Pakistan

Betalogger: Smartphone Sensor-based Side-channel Attack Detection and Text Inference Using Language Modeling and Dense MultiLayer Neural Network

With the recent advancement of smartphone technology in the past few years, smartphone usage has increased on a tremendous scale due to its portability and ability to perform many daily life tasks. As a result, smartphones have become one of the most valuable targets for hackers to perform cyberattacks, since the smartphone can contain individuals' sensitive data. Smartphones are embedded with highly accurate sensors. This article proposes BetaLogger, an Android-based application that highlights the issue of leaking smartphone users' privacy using smartphone hardware sensors (accelerometer, magnetometer, and gyroscope). BetaLogger efficiently infers the typed text (long or short) on a smartphone keyboard using Language Modeling and a Dense Multi-layer Neural Network (DMNN). BetaLogger is composed of two major phases: In the first phase, Text Inference Vector is given as input to the DMNN model to predict the target labels comprising the alphabet, and in the second phase, sequence generator module generate the output sequence in the shape of a continuous sentence. The outcomes demonstrate that BetaLogger generates highly accurate short and long sentences, and it effectively enhances the inference rate in comparison with conventional machine learning algorithms and state-of-the-art studies

Digital-Twins-Based Internet of Robotic Things for Remote Health Monitoring of COVID-19 Patients

The deadly coronavirus disease (COVID-19) has highlighted the importance of remote health monitoring (RHM). The digital-twins (DTs) paradigm enables RHM by creating a virtual replica that receives data from the physical asset, representing its real-world behavior. However, DTs use passive Internet of Things (IoT) sensors, which limit their potential to a specific location or entity. This problem can be addressed by using the Internet of Robotic Things (IoRT), which combines robotics and IoT, allowing the robotic things (RTs) to navigate in a particular environment and connect to IoT devices in the vicinity. Implementing DTs in IoRT, creates a virtual replica [virtual twin (VT)] that receives real-time data from the physical RT [physical twin (PT)] to mirror its status. However, DTs require a user interface for real-time interaction and visualization. Virtual reality (VR) can be used as an interface due to its natural ability to visualize and interact with DTs. This research proposes a real-time system for RHM of COVID-19 patients using the DTs-based IoRT and VR-based user interface. It also presents and evaluates robot navigation performance, which is vital for remote monitoring. The VT operates the PT in the real environment (RE), which collects data from the patient-mounted sensors and transmits it to the control service to visualize in VR for medical examination. The system prevents direct interaction of medical staff with contaminated patients, protecting them from infection and stress. The experimental results verify the monitoring data quality (accuracy, completeness, and timeliness) and high accuracy of PT's navigation.- Qatar National Library - Qatar University Internal Gran

2-(Phenyl­sulfan­yl)pyridine-3-carboxylic acid

The title compound, C12H9NO2S, belongs to the nitro­gen-containing group of heterocyclic organic compounds and crystallized with two mol­ecules per asymmetric unit. In the crystal, both molecules form inversion dimers linked by pairs of O—H—O hydrogen bonds. Weak symmetry-related C—H—O inter­actions link the carboxyl dimers along b axis. The dihedral angle between the two aromatic rings in the two mol­ecules are 55.75 (14) and 58.33 (13)°

Production of Indigenous and Enriched Khyber Pakhtunkhwa Coal Briquettes: Combustion and Disintegration Strength Analysis

Khyber Pakhtun Khwa province of Pakistan has considerable amounts of low ranked coal. However, due to the absence of any centrally administered power generation system there is a need to explore indigenous methods for effectively using this valuable energy resource. In the present study an indigenous coal briquetting technology has been developed and evaluated in terms of combustion characteristics such as moisture content, volatile matter, ash, fixed carbon and calorific value of the resulting coal briquette and disintegration strength using polyvinyl acetate (PVA) in combination with calcium carbonate (sample no 3 with highest disintegration strength value of 2059N). Comparison of test samples with the commercially available coal briquettes revealed improved combustion characteristics for the PVA bonded (sample no 1 and 5) coal briquettes having higher fixed carbon content and calorific value, lower ash contents as well as lower initial ignition time