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

A Context-aware and Intelligent Framework for the Secure Mission Critical Systems

Recent technological advancements in pervasive systems have shown the poten-tial to address challenges in the military domain. Research developments in mili-tary-based mission-critical systems have refined a lot as in autopilot, sensing true target behavior, battle damage conditions, acquiring and manipulating command control information. However, the application of pervasive systems in the military domain is still evolving. In this paper, an intelligent framework has been pro-posed for mission-critical systems to incorporate advanced heterogeneous com-munication protocols; service-oriented layered structure and context-aware infor-mation manipulation. The proposed framework addresses the limitation of “time-space” constraints in Mission-critical systems that have been improved signifi-cantly. This improvement is courtesy to enhancing situation-aware tactical capa-bilities such as localization, decision significance, strategic span, strategic inten-tions, resource coordination and profiling concerning the situation. A comprehen-sive use case model has been presented for a typical battle-field scenario followed by a comparison of the proposed framework with existing techniques. It is evi-dent from experiments and analyses that the proposed framework provides more effective and seamless interaction with contextual resources to improve tactical capabilities. This is the peer reviewed version of the following article: A Context-aware and Intelligent Framework for the Secure Mission Critical Systems, which has been published in final form in Transactions on Emerging Telecommunications Technologies. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Version

Servicing Delay Sensitive Pervasive Communication Through Adaptable Width Channelization for Supporting Mobile Edge Computing

Over the last fifteen years, wireless local area networks (WLANs) have been populated by large variety of pervasive devices hosting heterogeneous applications. Pervasive Edge computing encouraged more distributed network applications for these devices, eliminating the round-trip to help in achieving zero latency dream. However, These applications require significantly variable data rates for effective functioning, especially in pervasive computing. The static bandwidth of frequency channelization in current WLANs strictly restricts the maximum achievable data rate by a network station. This static behavior spawns two major drawbacks: under-utilization of scarce spectrum resources and less support to delay sensitive applications such as voice and video.To this point, if the computing is moved to the edge of the network WLANs to reduce the frequency of communication, the pervasive devices can be provided with better services during the communication and networking. Thus, we aim to distribute spectrum resources among pervasive resources based upon delay sensitivity of applications while simultaneously maintaining the fair channel access semantics of medium access control (MAC) layer of WLANs. Henceforth, ultra-low latency, efficiency and reliability of spectrum resources can be assured. In this paper, two novel algorithms have been proposed for adaptive channelization to offer rational distribution of spectrum resources among pervasive Edge nodes based on their bandwidth requirement and assorted ambient conditions. The proposed algorithms have been implemented on a real test bed of commercially available universal software radio peripheral (USRP) devices. Thorough investigations have been carried out to enumerate the effect of dynamic bandwidth channelization on parameters such as medium utilization, achievable throughput, service delay, channel access fairness and bit error rates. The achieved empirical results demonstrate that we can optimally enhance the network-wide throughput by almost 30% using channels of adaptable bandwidths

Mitigating MAC Layer Performance Anomaly of Wi-Fi Networks through Adaptable Channelization

. 802.11 wireless local area networks (WLANs) can support multiple data rates at physical layer by using adaptive modulation and coding (AMC) scheme. However, this differential data rate capability introduces a serious performance anomaly in WLANs. In a network comprising of several nodes with varying transmission rates, nodes with lower data rate (slow nodes) degrade the throughput of nodes with higher transmission rates (fast nodes). The primary source of this anomaly is the channel access mechanism of WLANs which ensures long term equal channel access probability to all nodes irrespective of their transmission rates. In this work, we investigate the use of adaptable width channelization to minimize the effect of this absurdity in performance. It has been observed that surplus channel-width due to lower transmission rate of slow nodes can be assigned to fast nodes connected to other access points (APs), which can substantially increase the overall throughput of the whole network. We propose a medium access control (MAC) layer independent anomaly prevention (MIAP) algorithm that assigns channel-width to nodes connected with different APs based on their transmission rate. We have modeled the effect of adaptable channelization and provide lower and upper bounds for throughput in various network scenarios. Our empirical results indicate a possible increase in network throughput by more than 20% on employing the proposed MIAP algorith

Ontology Evolution for Personalized and Adaptive Activity Recognition

Ontology-based knowledge driven Activity Recognition (AR) models play a vital role in realm of Internet of Things (IoTs). However, these models suffer the shortcomings of static nature, inability of self-evolution and lack of adaptivity. Also, AR models cannot be made comprehensive enough to cater all the activities and smart home inhabitants may not be restricted to only those activities contained in AR model. So, AR models may not rightly recognize or infer new activities. In this paper, a framework has been proposed for dynamically capturing the new knowledge from activity patterns to evolve behavioural changes in AR model (i.e. ontology based model). This ontology based framework adapts by learning the specialized and extended activities from existing user-performed activity patterns. Moreover, it can identify new activity patterns previously unknown in AR model, adapt the new properties in existing activity models and enrich ontology model by capturing change representation to enrich ontology model. The proposed framework has been evaluated comprehensively over the metrics of accuracy, statistical heuristics and Kappa Coefficient. A well-known dataset named DAMSH has been used for having an empirical insight to the effectiveness of proposed framework that shows a significant level of accuracy for AR models This paper is a postprint of a paper submitted to and accepted for publication in IET Wireless Sensor Systems and is subject to Institution of Engineering and Technology Copyright. The copy of record is available at the IET Digital Librar

Patient-Reported Outcomes (PROs) in NRG Oncology RTOG 1010: Phase III Trial Evaluating the Addition of Trastuzumab to Trimodality Treatment of HER2 Overexpressing (HER2+) Esophageal Adenocarcinoma (EAC)

Purpose/Objective(s): NRG/RTOG 1010 evaluated the benefit of trastuzumab for patients (pts) with HER2+ localized EAC receiving trimodality therapy. Adding trastuzumab did not improve disease-free (primary endpoint) or overall survival, nor treatment toxicity (Lancet Oncology 2022). The primary PRO objective was improvement (impr) in the FACT-Esophageal Cancer Subscale (ECS) score with trastuzumab at restaging prior to surgery. A secondary objective was to assess if impr in ECS score is associated with pathologic complete response (pCR). Materials/Methods: Pts with HER2+ EAC (T1N1-2; T2-3N0-2) were stratified by presence of adenopathy & randomized 1:1 to weekly paclitaxel, carboplatin with 50.4 Gy radiation (CRT) followed by surgery ± trastuzumab (CRT+T), 4mg/kg week 1, 2mg/kg/weekly x 5 during CRT, 6 mg/kg x1 prior to surgery, and then 6mg/kg every 3 weeks (wks) x 13. The ECS, v4, was done at baseline, 6-8 wks post-CRT and at 1 & 2 years. Impr in ECS and its Swallowing Index (SI) & Eating Index (EI) were defined as increases of 5, 2 & 2 points, respectively, from baseline. PRO sample size provided ≥ 80% power with 1-sided 0.05 alpha & a chi-squared test to determine if the proportion of pts categorized as improved at 6-8 wks is ≥ 25% higher for the CRT+T arm. Correlation between pCR & impr in ECS score was evaluated via chi-squared test. Results: From 2010-2015, 203 HER2+ pts were randomized; 194 eligible. Of 171 PRO consenting pts, the ECS was completed by 162 (95%) at baseline, 108 (64%) 6-8 wks, 82 (49%) 1 year & 55 (33%) at 2 years. The main reason for FACT-E noncompliance was pt death. Patient & tumor characteristics were similar between arms. Median age was 63 years; 86% male; 96% white; 65% Zubrod 0, 80% cT3 & 71% cN1-2 (AJCC 7th ed). For ECS scores at 6-8 wks, the mean change (Δ) was higher (better) from baseline at 4.6 (95% CI: 1.3, 7.8) for the CRT+T arm vs 0.9 (95% CI: -2.7, 4.6) for the CRT arm; the proportion of pts with an impr in 6-8 wks ECS was higher on the CRT+T arm (46% vs 38% on the CRT arm) although not significantly different (p=0.39). Table 1 shows ECS, SI & EI scores for all timepoints. At 6-8 wks, 30% with a pCR had an impr in ECS vs 45% of nonpCR pts (p=0.18). There were no significant correlations between pCR and ECS, SI & EI impr at any time points. Conclusion: The addition of trastuzumab to trimodality therapy for localized HER2+ EAC did not significantly improve survival or PROs. ECS score improvement following therapy was not associated with a pCR. The higher proportion of pts with improved ECS at 6-8 weeks and 2 years in the CRT+T arm is interesting and suggests that HER2 may still be an important target to explore

Fabry disease: recent advances in pathology, diagnosis, treatment and monitoring

<p>Abstract</p> <p>Background</p> <p>In Fabry disease (α-galactosidase A deficiency) accumulation of Globotriaosylceramide (Gb3) leads to progressive organ failure and premature death. The introduction of enzyme replacement therapy (ERT) was the beginning of a new era in this disorder, and has prompted a broad range of research activities. This review aims to summarize recent developments and progress with high impact for Fabry disease.</p> <p>Methods</p> <p>A Pubmed analysis was performed using the search terms "Fabry disease", "Anderson-Fabry disease", "alpha-galactosidase A" and "Gb3". Of the given publications by 31st January 2009 only original articles recently published in peer reviewed journals were included for this review. Case reports were included only when they comprised a new aspect. In addition we included relevant conference abstracts when the results had not already been published as original articles.</p> <p>Results</p> <p>Apart from Gb3-accumulation cellular and organ specific damages may be related also to inflammatory and immunological consequences. It will be interesting whether this may lead to new therapeutic strategies in the treatment of Fabry disease. Since newborn screening is still difficult in Fabry disease, detection of patients in populations at risk is of great importance. Undiagnosed patients with Fabry disease may still be found in cohorts of subjects with renal diseases, cardiomyopathy and TIA or stroke. Efforts should be undertaken to identify these individuals and initialise ERT in order to hault disease progression. It has also been demonstrated that Gb3-accumulation leads to pre-clinical damages and it is believed that early treatment may be the only possibility so far to prevent irreversible organ damage.</p

Shared Hybrid ARQ with Incremental Redundancy (SHARQ-IR) in Overloaded MIMO Systems to support Energy-Efficient Transmissions

© 2020 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Multiple Input and Multiple Output (MIMO) is a technology through which data is transmitted over the channel through multiple antennas. However, during its deployment and implementation, some pragmatic issues arise such as interference, multipath fading and noise leading to potential packet losses and consume substantial energy. In order address such issues, Hybrid ARQ transmissions provide effective means for error correction, especially in a noisy wireless channel. More often few bits in packets are found to be in error and it is unnecessary to use the entire MIMO channel for retransmission to correct the remaining errors. So a novel approach has been proposed in this paper i.e. Shared Hybrid ARQ (SHARQ - IR) using piggyback technique in overloaded MIMO systems where the transmitting antennas (Nt) are more than the receiving antennas (Nr) and used the concept of simple retransmission method to transform an overloaded MIMO into the critically loaded system (Nt=Nr) or under loaded MIMO systems (Nt<Nr). Simulation results outperform the contemporary approaches through reduced BER and a 20% throughput gain is observed during the simulation analyses which will ultimately support energy-efficient transmissions to encourage for Green IoT Applications