Comparison of CNNs and Vision Transformers-Based Hybrid Models Using Gradient Profile Loss for Classification of Oil Spills in SAR Images

Oil spillage over a sea or ocean surface is a threat to marine and coastal ecosystems. Spaceborne synthetic aperture radar (SAR) data have been used efficiently for the detection of oil spills due to their operational capability in all-day all-weather conditions. The problem is often modeled as a semantic segmentation task. The images need to be segmented into multiple regions of interest such as sea surface, oil spill, lookalikes, ships, and land. Training of a classifier for this task is particularly challenging since there is an inherent class imbalance. In this work, we train a convolutional neural network (CNN) with multiple feature extractors for pixel-wise classification and introduce a new loss function, namely, “gradient profile” (GP) loss, which is in fact the constituent of the more generic spatial profile loss proposed for image translation problems. For the purpose of training, testing, and performance evaluation, we use a publicly available dataset with selected oil spill events verified by the European Maritime Safety Agency (EMSA). The results obtained show that the proposed CNN trained with a combination of GP, Jaccard, and focal loss functions can detect oil spills with an intersection over union (IoU) value of 63.95%. The IoU value for sea surface, lookalikes, ships, and land class is 96.00%, 60.87%, 74.61%, and 96.80%, respectively. The mean intersection over union (mIoU) value for all the classes is 78.45%, which accounts for a 13% improvement over the state of the art for this dataset. Moreover, we provide extensive ablation on different convolutional neural networks (CNNs) and vision transformers (ViTs)-based hybrid models to demonstrate the effectiveness of adding GP loss as an additional loss function for training. Results show that GP loss significantly improves the mIoU and F$_1$ scores for CNNs as well as ViTs-based hybrid models. GP loss turns out to be a promising loss function in the context of deep learning with SAR images

Barriers for the Adoption of Professional Development Courses (PDCs) in Public Sector University Libraries

Objective: The purpose of the study was to explore the major problems of Library Professionals working in the academic libraries of public sector universities regarding participation in Professional Development Courses (PDCs). Methodology: Public sector Universities affiliated with Higher Education Commission (HEC) Pakistan, located in Lahore, Pakistan were the target population. The Census sampling technique was adopted to accomplish the objectives of the conducted study. 67 respondents participated in the study. A quantitative research technique was used in the study. A self-created questionnaire was used to collect the data. Key Findings: The findings of the study revealed that a good number of respondents were willing to participate in development activities. But, due to numerous hurdles included shortage of library staff, poor allocation of budget for development activities and non-interesting attitude of organizational administration towards the professional development of Library professionals were the major barriers towards professional development activities. Rationale and Significance: Past literature indicated that no study was conducted covering the objective of barriers in professional development. No researcher made the proper investigation in the local scenario. It was highly desired to explore the barriers in participating in professional development activities in the local context. Implication: This study would contribute to the professional literature. It will also assist policy makers to take initiatives for the capacity building of library professionals

Energy-aware scheduling for multiprocessor real-time systems

Les applications temps réel modernes deviennent plus exigeantes en termes de ressources et de débit amenant la conception d architectures multiprocesseurs. Ces systèmes, des équipements embarqués au calculateur haute performance, sont, pour des raisons d autonomie et de fiabilité, confrontés à des problèmes cruciaux de consommation d énergie. Pour ces raisons, cette thèse propose de nouvelles techniques d optimisation de la consommation d énergie dans l ordonnancement de systèmes multiprocesseur. La première contribution est un algorithme d ordonnancement hiérarchique à deux niveaux qui autorise la migration restreinte des tâches. Cet algorithme vise à réduire la sous-optimalité de l algorithme global EDF. La deuxième contribution de cette thèse est une technique de gestion dynamique de la consommation nommée Assertive Dynamic Power Management (AsDPM). Cette technique, qui régit le contrôle d admission des tâches, vise à exploiter de manière optimale les modes repos des processeurs dans le but de réduire le nombre de processeurs actifs. La troisième contribution propose une nouvelle technique, nommée Deterministic Strech-to-Fit (DSF), permettant d exploiter le DVFS des processeurs. Les gains énergétiques observés s approchent des solutions déjà existantes tout en offrant une complexité plus réduite. Ces techniques ont une efficacité variable selon les applications, amenant à définir une approche plus générique de gestion de la consommation appelée Hybrid Power Management (HyPowMan). Cette approche sélectionne, en cours d exécution, la technique qui répond le mieux aux exigences énergie / performance.Modern real-time applications have become more sophisticated and complex in their behaviour over the time. Contemporaneously, multiprocessor architectures have emerged. Multiprocessor systems, due to their autonomy and reliability, face critical problem of energy consumption. To address this issue in real-time systems, many software-based approaches have emerged. This thesis proposes new techniques for energy-efficient scheduling of multiprocessor systems. Our first contribution is a hierarchical scheduling algorithm that allows restricted migration of tasks. This algorithm aims at reducing the sub-optimality of global EDF algorithm. The second contribution of this thesis is a dynamic power management technique called Assertive Dynamic Power Management (AsDPM). This technique is an admission control technique for real-time tasks, which decides when exactly a ready task shall execute, thereby reducing the number of active processors. The third contribution of this dissertation is a DVFS technique, referred as Deterministic Strech-to-Fit (DSF) technique, which falls in the category of inter-task DVFS techniques. Both DPM and DVFS techniques are efficient for specific operating conditions. However, they often outperform each other when these conditions change. Our fourth and final contribution is a generic power / energy management scheme, called Hybrid Power Management (HyPowMan) scheme. This scheme, instead of designing new power / energy management techniques for specific operating conditions, takes a set of well-known existing policies. At runtime, the best-performing policy for given workload is adapted by HyPowMan scheme through machine-learning approach.NICE-BU Sciences (060882101) / SudocSudocFranceF

Architectures for Security: A comparative analysis of hardware security features in Intel SGX and ARM TrustZone

International audienceA variety of applications are executing on a large untrusted computing base, which includes the operating system, hypervisor, firmware, and hardware. This large computing base is becoming complex and unverifiable. This untrusted computing base problem opens a way for a malicious application to steal secrets of a security-critical application by compromising the untrusted computing base. To resolve the untrusted computing base problem, computer architectures have introduced a concept of the trusted execution environment, which aim to ensure the sensitive data to be stored and processed in an isolated environment. Existing popular trusted execution environments are relying on hardware to isolate the environments without or minimum relying on system software. However, existing hardware assisted trusted execution environments are still vulnerable to sophisticated attacks. This paper analyses popular trusted execution environments that are Intel SGX and ARM TrustZone in order to provide better insights about the intended scope of the protection. This paper illustrates the functionality, implementation and security analysis

Method for scheduling with deadline constraints, in particular in linux, carried out in user space

A method for scheduling tasks with deadline constraints, based on a model of independent periodic tasks and carried out in the user space by means of API POSIX. http://patentscope.wipo.int/search/en/WO201407290

Comparison of direct and switch-based inter-fpga routing interconnect for multi-fpga systems

Prototyping using multi-FPGA systems offers significant advantages over simulation and emulation based pre-silicon verification techniques in terms of performance and real world testing experience. Inter-FPGA routing interconnect and the quality of associated tool play a very important role in the performance of final prototyped design. In this work, we present a detailed comparison between four inter-FPGA interconnect routing topologies. We present a generic inter-FPA routing tool and for each topology, ten large benchmarks are prototyped on four different FPGA boards. Experimental results show that interconnect topology using a hybrid combination of two and multipoint tracks gives best results for smaller FPGA boards while topology using hybrid combination of switch-based and direct multi point tracks gives best frequency results for large FPGA boards and this frequency gain increases with increase in the number of FPGAs on board. We also perform execution time comparison between four interconnect topologies and the topology using direct two point connections only gives the best overall execution results. This topology, on average, requires 12%, 82%, and 70% less execution time as compared to other interconnect topologies under consideration

The Kingsguard OS-level mitigation against cache side-channel attacks using runtime detection

International audienceMost of the mitigation techniques against access-driven cache side-channel attacks (CSCAs) are not very effective. This is mainly because most mitigation techniques usually protect against any given specific vulnerability of the system and do not take a system-wide approach. Moreover, they either completely remove or greatly reduce the performance benefits. Therefore, to find a security vs performance trade-off, we argue in favor of need-based protection in this paper, which will allow the operating system to apply mitigation only after successful detection of CSCAs. Thus, detection can serve as a first line of defense against such attacks. In this work, we propose a novel OS-level runtime detection-based mitigation mechanism, called the Kingsguard, against CSCAs in general-purpose operating systems. The proposed mechanism enhances the security and privacy capabilities of Linux as a proof of concept, and it can be widely used in commodity systems without any hardware modifications. We provide experimental validation by mitigating three state-of-the-art CSCAs on two different cryptosystems running under Linux. We have also provided results by analyzing the effect of the combination of multiple attacks running concurrently under variable system noise. Our results show that the Kingsguard can detect and mitigate known CSCAs with an accuracy of more than 99% and 95%, respectively

Biodiesel Production from Waste Plant Oil over a Novel Nano-Catalyst of Li-TiO2/Feldspar

A novel Li-impregnated TiO2 catalyst loaded on feldspar mineral (Li-TiO2/feldspar) was synthesized via a wet impregnation method and was characterized using X-ray diffraction (XRD), scanning electron microscopy (SEM), and Fourier transform infrared (FTIR) analysis. Using these techniques, it was possible to confirm the catalyst’s structural organization with a high crystallinity. This catalyst was used in the transesterification of five waste plant oils of Citrullus colocynthis (bitter apple), Pongamia pinnata (karanja), Sinapis arvensis (wild mustard), Ricinus communis (castor) and Carthamus oxyacantha (wild safflower). The catalytic tests were performed at temperatures ranging from 40 to 80 °C, employing a variable methanol/ester molar ratio (5:1, 10:1, 15:1, 20:1 and 25:1) and different catalyst concentrations (0.5%, 1%, 1.5%, 2% and 2.5%) relative to the total reactants mass. Conversion of 98.4% of fatty acid methyl esters (FAMEs) was achieved for Pongamia pinnata (karanja). The main fatty acids present in bitter apple, karanja, wild mustard, castor and wild safflower oils were linoleic acid (70.71%), oleic acid (51.92%), erucic acid (41.43%), ricinoleic acid (80.54%) and linoleic acid (75.17%), respectively. Li-TiO2/feldspar produced more than 96% for all the feedstocks. Fuel properties such as iodine value (AV), cetane number (CN), cloud point (CP), iodine value (IV), pour point (PP) and density were within the ranges specified in ASTM D6751