Dvali-Gabadadze-Porrati Cosmology in Bianchi I brane

The dynamics of Dvali-Gabadadze-Porrati Cosmology (DGP) braneworld with an anisotropic brane is studied. The Friedmann equations and their solutions are obtained for two branches of anisotropic DGP model. The late time behavior in DGP cosmology is examined in the presence of anisotropy which shows that universe enters a self-accelerating phase much later compared to the isotropic case. The acceleration conditions and slow-roll conditions for inflation are obtained

A Study of Affordable Roofing Systems with Composite Slab

Affordable housing is a term used to describe dwelling units whose total housing cost are deemed affordable to a group of people within a specified income range. Structural roofing system contribute substantially to cost of construction of housing unit in normal situation, hence any savings attained in roofing system will reduce the cost of construction of housing unit. In the study undertaken, the roofing system consists of primary beams and secondary beams perpendicular to each other. The infill proposed is a composite slab panel consisting of decking sheets, galvanized iron(G.I) sheets of trapezoidal and corrugated cross section at bottom with a layer of concrete above it. The rectangular composite panelsconsidered in the study have a least width of 0.5m and 0.75m with an aspect ratio varying from 1.00 to 2.00. The rectangular composite panels are designed using M20 grade concrete and reinforcing steel of yield strength 415 N/mm2. The cost analysis is made for the roofing system and the proposed roofing system indicates a cost reduction 40% when compared to a conventional reinforced concrete (RCC) slab of same size. The weight of the beam systems and the panels are found to be relatively less and can handled easily by two to five masons thus reducing the labour cost. The beam systems and panels are precasted and can be easily placed thus eliminating need of shuttering, leading to faster construction of slab. The proposed roofing system is cost effective with a greater speed of construction compared to conventional roofing system

Computational intelligent sensor-rank consolidation approach for Industrial Internet of Things (IIoT).

Continues field monitoring and searching sensor data remains an imminent element emphasizes the influence of the Internet of Things (IoT). Most of the existing systems are concede spatial coordinates or semantic keywords to retrieve the entail data, which are not comprehensive constraints because of sensor cohesion, unique localization haphazardness. To address this issue, we propose deep-learning-inspired sensor-rank consolidation (DLi-SRC) system that enables 3-set of algorithms. First, sensor cohesion algorithm based on Lyapunov approach to accelerate sensor stability. Second, sensor unique localization algorithm based on rank-inferior measurement index to avoid redundancy data and data loss. Third, a heuristic directive algorithm to improve entail data search efficiency, which returns appropriate ranked sensor results as per searching specifications. We examined thorough simulations to describe the DLi-SRC effectiveness. The outcomes reveal that our approach has significant performance gain, such as search efficiency, service quality, sensor existence rate enhancement by 91%, and sensor energy gain by 49% than benchmark standard approaches

Management and Complications of Arnold Chiari Hydrocephalus at Tertiary Health Care Center

Objective: to investigate the role of CT and MRI in diagnosis of Arnold chiari malformation of hydrocephalus and its treatment with VP shunt along with complications. Study Design: Prospective study Place and duration: Department of Neurosurgery, DG Khan Medical College from May 4, 2018 to May 4, 2019. Methodology: Fifty patients of congenital hydrocephalus who were not treated previously were selected. Detailed history about disease and clinical examination of patients was performed. Follow ups were done at neurosurgery OPD. SPSS software for data analysis was used and mean ± SD, frequency and percentages were calculated for variables. P value ≤0.05 was considered as significant. Results: Treatment in case of congenital hydrocephalus as VP shunt, intra-aneurysmal coiling, excision of meningomyelocele with VP shunt and suboccipital craniectomy + upper cervical laminectomy (scucl) were observed as 10%, 6%, 8% and 8% respectively.  Twelve percent of patients were not treated. Conclusion: CT and MRI are the main diagnostic tools for diagnosis of Arnold chiari malformation and VP shunt is the treatment of choice. Among complications of VP shunt infection of shunt and shunt block are the main complications

An Adaptive Software Fault Tolerant Framework for Ubiquitous Vehicular Technologies

Probability for the occurrence of faults increases manifolds when program Lines of Code (LoC) exceeds a few thousand in ubiquitous applications. Faults mitigation in ubiquitous applications, such as those of autonomous Vehicular Technologies (VTs), has not been effective even with the use of formal methods. Faults in such applications require exhaustive testing for a timely fix, that seems infeasible computationally. This emphasizes the imperative role of Software Fault Tolerance (SFT) for autonomous applications. Several SFT techniques have been proposed but failures revealed in VT applications imply that existing SFT techniques need to be fine-tuned. In this paper, current replication-based SFT techniques have been analyzed and classified with respect to their diversity, adjudication, and adaptivity. Essential parameters (such as Reliability, Time, Variance, etc) for adjudication, diversity, and adaptiveness were recorded. The identified parameters were mapped to different techniques (such as AFTRC, SCOP, VFT, etc) for observing their shortcomings. Consequently, a generic framework named ”Diverse Parallel Adjudication for Software Fault Tolerance (DPA-SFT)” has been proposed. DPA-SFT addresses the shortcomings of existing SFT techniques for VTs with the added value of parallel and diverse adjudication. A prototype implementation of the proposed framework has been developed for assessing the viability of DPA-SFT over modules of VT. An empirical comparison of the proposed framework was performed with prevalent techniques (AFTRC, SCOP, VFT, etc). A thorough evaluation suggests that DPA-SFT performs better than contemporary SFT techniques in VTs due to its parallel and diverse adjudication

An Exploratory Framework for Intelligent Labelling of Fault Datasets

Software fault prediction (SFP) has become a pivotal aspect in realm of software quality. Nevertheless, discipline of software quality suffers the starvation of fault datasets. Most of the research endeavors are focused on type of dataset, its granularity, metrics used and metrics extractors. However, sporadic attention has been exerted on development of fault datasets and their associated challenges. There are very few publicly available datasets limiting the possibilities of comprehensive experiments on way to improvising the quality of software. Current research targets to address the challenges pertinent to fault dataset collection and development if one is not available publicly. It also considers dynamic identification of available resources such as public dataset, open-source software archieves, metrics parsers and intelligent labeling techniques. A framework for dataset collection and development process has been furnished along with evaluation procedure for the identified resources

A Novel Energy-Efficient Reservation System for Edge Computing in 6G Vehicular Ad Hoc Network

The roadside unit (RSU) is one of the fundamental components in a vehicular ad hoc network (VANET), where a vehicle communicates in infrastructure mode. The RSU has multiple functions, including the sharing of emergency messages and the updating of vehicles about the traffic situation. Deploying and managing a static RSU (sRSU) requires considerable capital and operating expenditures (CAPEX and OPEX), leading to RSUs that are sparsely distributed, continuous handovers amongst RSUs, and, more importantly, frequent RSU interruptions. At present, researchers remain focused on multiple parameters in the sRSU to improve the vehicle-to-infrastructure (V2I) communication; however, in this research, the mobile RSU (mRSU), an emerging concept for sixth-generation (6G) edge computing vehicular ad hoc networks (VANETs), is proposed to improve the connectivity and efficiency of communication among V2I. In addition to this, the mRSU can serve as a computing resource for edge computing applications. This paper proposes a novel energy-efficient reservation technique for edge computing in 6G VANETs that provides an energy-efficient, reservation-based, cost-effective solution by introducing the concept of the mRSU. The simulation outcomes demonstrate that the mRSU exhibits superior performance compared to the sRSU in multiple aspects. The mRSU surpasses the sRSU with a packet delivery ratio improvement of 7.7%, a throughput increase of 5.1%, a reduction in end-to-end delay by 4.4%, and a decrease in hop count by 8.7%. The results are generated across diverse propagation models, employing realistic urban scenarios with varying packet sizes and numbers of vehicles. However, it is important to note that the enhanced performance parameters and improved connectivity with more nodes lead to a significant increase in energy consumption by 2%