Simulation analysis of security performance of DPSKOCDMA network via virtual user scheme

A novel technique to enhance the security of an optical code division multipleaccess (OCDMA) system against eavesdropping is proposed. It has been observed that whena single user is active in the network, an eavesdropper can easily sift the data beingtransmitted without decoding. To increase the security, a virtual user scheme is proposed andsimulated on a differential phase shift keying (DPSK) OCDMA system. By using the virtualuser scheme, the security of the DPSK-OCDMA system can be effectively improved and themultiple access interference, which is generally considered to be a limitation of the OCDMAsystem, is used to increase the confidentiality of the system

SPECTRUM OF CT FINDINGS IN CLINICALLY SUSPECTED CASES OF MUCORMYCOSIS – A STUDY AT TERTIARY HEALTH-CARE CENTER (RAJINDRA HOSPITAL PATIALA) DURING SECOND WAVE OF COVID PANDEMIC

Objective: Rhinocereberal mucormycosis is an acute, fulminant, and often lethal opportunistic infection typically affecting diabetic or immunocompromised patients. Early diagnosis is vital in these infections because delay in initiation of the treatment can be life-threatening. Computed tomography (CT) with axial and coronal sections is a highly accurate and non-invasive modality to accurately image sinonasal mycosis. The aim of the study was to describe the imaging findings in suspected cases of mucormycosis on CT. Methods: This study was conducted in Radiodiagnosis Department of Rajindra Hospital, Patiala. The data of 22 patients who were referred for CT with a clinical suspicion of mucormycosis were collected and all these patients were followed up to know about the prognosis of the disease. Results: In our study, there were 54.60% females and 45.40% males. Maximum number of patients (45.45%) belonged to 40–49 year age group. Diabetes mellitus was found to be the most commonly (90.90%) found comorbidity followed by hypertension (36.36%). In our study, involvement of unilateral nasal cavity was observed in 36.36% cases. Among the paranasal sinuses, maxillary and ethmoid sinuses were the most commonly involved in 95.45% and 77.27% cases. Conclusion: Prompt diagnosis and treatment of rhino-orbital mucormycosis are the sine qua non as antifungal drugs and surgical debridement can successfully control the infection and thus reduce the high mortality and morbidity associated with mucormycosis

The role of inflammatory markers in COVID-19 associated rhino-orbital-cerebral mucormycosis patients

Background: India has experienced an unprecedented heave of mucormycosis (MCR) cases during second wave of COVID-19. Possible mechanisms may involve immune and inflammatory processes. The aim of the study is to estimate the role of inflammatory markers for triaging patients of COVID-19 associated rhino-orbital-cerebral mucormycosis (CAROCM) at tertiary care hospital in north India. Methods: A retrospective observational study was conducted between September 2021 to December 2021, at Government medical college and hospital, Patiala (Pb), 83 CAROCM patients admitted in ENT department were evaluated for serum ferritin, D-dimer and PCT. Results: The median age of the patients was 50 years. The number of male patients were 45 and female patients were 38. Based upon the medical history and associated comorbidities involved, 83 CAROCM patients were divided into three groups. 43 diabetic patients in group I, 33 patients with multiple risk factors in group II and 7 patients with no comorbidity in group III. The mean D-dimer levels were 702 ng/ml in group 1, 831ng/ml in group II and 399 ng/ml in group III, and ferritin levels were 522 ng/ml, 711 ng/ml and 426 ng/ml in group I, II and III respectively. Mean PCT levels in group I were 0.27 ng/ml, 1.32 ng/ml in group II and 0.42 ng/ml in group III. Conclusions: Our study concluded that a significant association was observed between levels of inflammatory markers and susceptibility factors. Serum ferritin, D-dimer and procalcitonin, can be used for assessing the severity of infection and decreases the mortality and morbidity in CAROCM patients.

ScOSA system software: the reliable and scalable middleware for a heterogeneous and distributed on-board computer architecture

Designing on-board computers (OBC) for future space missions is determined by the trade-off between reliability and performance. Space applications with higher computational demands are not supported by currently available, state-of-the-art, space-qualified computing hardware, since their requirements exceed the capabilities of these components. Such space applications include Earth observation with high-resolution cameras, on-orbit real-time servicing, as well as autonomous spacecraft and rover missions on distant celestial bodies. An alternative to state-of-the-art space-qualified computing hardware is the use of commercial-off-the-shelf (COTS) components for the OBC. Not only are these components cheap and widely available, but they also achieve high performance. Unfortunately, they are also significantly more vulnerable to errors induced by radiation than space-qualified components. The ScOSA (Scalable On-board Computing for Space Avionics) Flight Experiment project aims to develop an OBC architecture which avoids this trade-off by combining space-qualified radiation-hardened components (the reliable computing nodes, RCNs) together with COTS components (the high performance nodes, HPNs) into a single distributed system. To abstract this heterogeneous architecture for the application developers, we are developing a middleware for the aforementioned OBC architecture. Besides providing an monolithic abstraction of the distributed system, the middleware shall also enhance the architecture by providing additional reliability and fault tolerance. In this paper, we present the individual components comprising the middleware, alongside the features the middleware offers. Since the ScOSA Flight Experiment project is a successor of the OBC-NG and the ScOSA projects, its middleware is also a further development of the existing middleware. Therefore, we will present and discuss our contributions and plans for enhancement of the middleware in the course of the current project. Finally, we will present first results for the scalability of the middleware, which we obtained by conducting software-in-the-loop experiments of different sized scenarios

Model Checking Message Delivery Times in SpaceWire Networks

This paper presents a model checking framework in Uppaal for finding worst-case message delivery times for periodic and event-driven message flows in a SpaceWire network with wormhole switching. In particular, we focus on segmentation of large messages into smaller packets. We present a collection of timed automata for SpaceWire links and network messages, that capture message segmentation and wormhole blocking. We evaluate our approach on a realistic example network with 4 routers and 16 message flows, two of which are large messages that need to be segmented. Our model can be used to determine the bounds on the possible segment size, and how this size affects the worst-case message delivery times. Model checking time for these experiments ranges from several minutes to several hours, and we further investigate how it depends on the number of flows, the segmentation size, and the message periods

Community Based Assessment of Biochemical Risk Factors for Cardiovascular Diseases in Rural and Tribal Area of Himalayan Region, India

Context. Evident change in nutrition and lifestyle among individuals of urban and rural areas raises suspicion for similar change in tribal area population of India. Aim. To study the biochemical risk factor for CVDs in rural and tribal population of Sub-Himalayan state of India. Settings and Design. Cross-sectional study in rural (low altitude) and tribal (high altitude) area of Himachal Pradesh, India. Methodology. Blood lipid profile using standard laboratory methods. Statistical Analysis. Chi-square test and multiple linear regression analysis. Results. Total of 900 individuals were studied in both areas. As per Asian criteria, obesity (BMI 27.5–30.0 kg/m2) was observed to be significantly high (P=0.00) as 13.7% in tribal area as compared to 5.5% in rural area. Normal level of TC (<200 mg/dL) and LDL (<130 mg/dL) was observed in the majority of the population of both areas, whereas, at risk level of HDL (<40 mg/dL) was present in half of the population of both rural and tribal areas. The prevalence of borderline to high level of TGs was observed to be 60.2% and 55.2% in rural and tribal (P=0.10) area, respectively. Conclusion. Prevalent abnormal lipid profile in tribal area demands establishment of an effective surveillance system for development of chronic diseases

Parallelizing On-Board Data Analysis Applications for a Distributed Processing Architecture

Satellite-based applications produce ever-increasing quantities of data, challenging the capabilities of existing telemetry and on-board processing systems, especially when results must be transmitted quickly to ground. The Scalable On-Board Computing for Space Avionics (ScOSA) platform contributes the processing capability necessary to perform such computationally intensive analysis on-board. This platform offers a high-performance on-board computer by combining multiple commercial off-the-shelf processors and space-grade processors into a distributed computer. Middleware ensures reliability by detecting and mitigating faults, while allowing applications to effectively use multiple, distributed processors. The current work aims to demonstrate the use and advantages of utilizing the data-flow programming paradigm supported by the ScOSA platform to provide high-throughput on-board analysis. This enables rapid analysis even for applications requiring high frame rates, high resolutions, multi-spectral imaging or in-depth processing. The On-Board Data Analysis and Real-Time Information System (ODARIS) is used to demonstrate this method. ODARIS is a system for providing low-latency access to satellite-based observations, even when large quantities of sensor data are involved. By performing on-board processing of the data from the satellite-borne instruments, the amount of data which must be sent to ground is drastically reduced. This allows the use of low-latency telecommunication-satellite constellations for communicating with ground to achieve query-response times of only a few minutes. The current application combines an Earth-observation camera with AI-based image processing to provide real-time object detection. In the data-flow driven implementation of ODARIS on the ScOSA platform, images are captured by a camera and sent to any of several processors for the computationally intensive image processing. This allows multiple images to be processed in parallel by as many processors as are available, while avoiding the need to divide each image across several processors. The results are transferred to an on-board database from which queries can be served asynchronously. The system will be tested in configurations with one, two and three processors and the resulting image throughput presented. Testing is performed on a ground-based prototype system using pre-recorded images. This paper presents the necessary details of the underlying ScOSA and ODARIS systems as well as the implementation of the objection-detection algorithm using a parallelized, data-flow model. The results of executing the system using a variable number of processors are presented to demonstrate the improvement in image throughput and its potential application to other computationally-intensive tasks

Human-computer interaction based joint attention cues: implications on functional and physiological measures for children with autism spectrum disorder

One of the important facets of effective social communication is Joint Attention (JA). However, children with Autism Spectrum Disorder (ASD) are often characterized by JA-related deficits, adversely affecting their social communication. In conventional interventions, therapists use different types of JA cues depending on one's capability to pick up the delivered cue. Though effective, conventional approaches suffer from restricted healthcare resources, cost, etc. With an increase in computational power, investigators are exploring alternative robot-based and computer-based techniques for JA skill training while delivering different types of JA cues. However, robot-assisted techniques are powerful but suffer from limitations such as high cost, restricted flexibility, etc. Thus, researchers are exploring the use of computer-based techniques for JA skill training since it can be controllable, flexible, cost-effective, more accessible, etc. With the advent of rich graphics, researchers are augmenting computer-based interfaces with Virtual Reality (VR) while designing Human-Computer Interaction (HCI)-based JA tasks. Given the importance of VR-enabled HCI-based JA training platform, studying the comparative potential of different types of JA cues (having varying information content) implemented using a VR-enabled HCI-based task platform is important. In this research work, we presented a VR-enabled HCI-based JA task platform that can deliver avatar-mediated and environment-triggered JA cues of varying information content. Results of a preliminary study with twenty typically developing and twenty age-matched children with ASD indicate differentiated implications of JA cues of varying information content on one's functional and physiological measures.by Vishav Jyoti and Uttama Lahir

Virtual Reality based Joint Attention Task Platform for Children with Autism

Children with Autism Spectrum Disorder (ASD) are characterized by deficits in social communication. Social communication is facilitated by ability to pick up cues from social partner using Joint Attention (JA) skill, which gets established in early stages of development. However, children with ASD possess deficits in JA skill. These deficits manifest as delay in language acquisition and cognitive skills development at later stages. Therapist-mediated interventions addressing these JA related deficits are labor-intensive and unaffordable. Alternatively, robots and computers can be used. Robot-facilitated skill training suffers from high cost, specialized knowledge to operate, etc. In contrast, Computer-based JA skill training platforms are affordable, offers flexibility to designer, but having limited interactivity coupled with lack of individualization and mostly operate as standalone applications. Individualization is critical for effective skill training. To bridge this gap, we have developed Virtual Reality based Joint Attention Task platform. This system (adaptive to individual's performance) was augmented with Hierarchical Prompt Protocol that autonomously increased level of prompting on demand. Results of a preliminary study with 20 pairs of age-matched ASD and Typically Developing (TD) participants indicates potential of our VR-based system to identify the JA skill deficits of children with ASD vis-a-vis their Typically Developed counterpart.by Vishav Jyoti and Uttama Lahir