Miracle-dz/UniFAR-FTUs huggingface dataset:
A rigorous and efficient run-time security monitor for real-time critical embedded system applications

We introduce a run-time security monitor for embedded system applications that detects both known and unknown computational cyber-attacks. Our security monitor is rigorous (i.e. sound and complete), eliminating false alarms, as well as efficient, supporting real-time detection. In contrast, conventional run-time security monitors for application software either produce (high rates of) false alarms (e.g. intrusion detection systems) or limit application performance (e.g. run-time verification systems). Such monitors are typically non-adaptive against constantly changing attacks of variable extent. Our run-time monitor detects attacks by checking the consistency between the application run-time behavior and its specified (expected) behavior model. Our specification language is based on monadic second order logic and event calculus interpreted over algebraic data structures; the application implementation can be in any programming language. Based on our defined denotational semantics of the specification language, we prove that the security monitor is sound and complete, i.e. it produces an alarm iff it detects an inconsistency between the application execution and the specified behavior. Importantly, the monitor detects not only cyber-attacks but all behavioral deviations from specification, e.g. bugs, and so, is readily applicable to the security of legacy systems. Through an application of our prototype monitor to a PID controller for a feedwater tank, we demonstrate that rigorous run-time monitors employing verification techniques are effective, efficient and readily applicable to demanding real-time critical systems, without scalability limitations.
Combining Classifiers in Multimodal Affect Detection

Affect detection where users' mental states are automatically recognized from facial expressions, speech, physiology and other modalities, requires accurate machine learning and classification techniques. This paper investigates how combined classifiers, and their base classifiers, can be used in affect detection using features from facial video and multichannel physiology. The base classifiers evaluated include function, lazy and decision trees; and the combined where implemented as vote classifiers. Results indicate that the accuracy of affect detection can be improved using the combined classifiers especially by fusing the multimodal features. The base classifiers that are more useful for certain modalities have been identified. Vote classifiers also performed best for most of the individuals compared to the base classifiers.
A Maximum-Throughput Call Admission Control Policy for CDMA Beamforming Systems

A throughput-maximization call admission control (CAC) policy is proposed for CDMA beamforming systems in which the QoS requirements in both physical and network layers can be guaranteed. While the existing cross-layer CAC policies rely on a separate reduced-outage-probability (ROP) algorithm to guarantee the physical layer QoS requirement, which adds to system complexity and reduces spectral efficiency, the proposed CAC policy can maintain arbitrary outage probability constraints as well as all the other QoS requirements without the aid of any ROP algorithm. The optimal CAC policy, obtained by formulating a constrained semi-Markov decision process (SMDP), is able to optimize the overall system throughput across different layers. Numerical examples demonstrate that the proposed policy is capable of achieving a significant performance gain, in terms of lowered blocking and outage probabilities as well as increased system throughput.
Activity recognition based on accelerometer sensor using combinational classifiers

In recent years, people nowadays easily to contact each other by using smartphone. Most of the smartphone now embedded with inertial sensors such accelerometer, gyroscope, magnetic sensors, GPS and vision sensors. Furthermore, various researchers now dealing with this kind of sensors to recognize human activities incorporate with machine learning algorithm not only in the field of medical diagnosis, forecasting, security and for better live being as well. Activity recognition using various smartphone sensors can be considered as a one of the crucial tasks that needs to be studied. In this paper, we proposed various combination classifiers models consists of J48, Multi-layer Perceptron and Logistic Regression to capture the smoothest activity with higher frequency of the result using vote algorithmn. The aim of this study is to evaluate the performance of recognition the six activities using ensemble approach. Publicly accelerometer dataset obtained from Wireless Sensor Data Mining (WISDM) lab has been used in this study. The result of classification was validated using 10-fold cross validation algorithm in order to make sure all the experiments perform well.
Limited growth of severed CNS axons after treatment of adult rat brain with hyaluronidase

Many chondroitin sulfate proteoglycans (CSPGs) have been shown to influence CNS axon growth in vitro and in vivo. These interactions can be mediated through the core protein or through the chondroitin sulfate (CS) glycosaminoglycan (GAG) side chains. We have shown previously that degrading CS GAG side chains using chondroitinase ABC enhances dopaminergic nigrostriatal axon regeneration in vivo. We test the hypothesis that interfering with complete CSPGs also limit axon growth in vivo. Neurocan, versican, aggrecan, and brevican CSPGs may be anchored within extracellular matrix through binding to hyaluronan glycosaminoglycan. We examine whether degradation of hyaluronan using hyaluronidase might release these inhibitory CSPGs from the extracellular matrix and thereby enhance regeneration of cut nigrostriatal axons. Anesthetized adult rats were given knife cut lesions of the right hemisphere nigrostriatal tract and cannulae were secured transcranially thereby allowing repeated perilesional infusion of saline or saline containing hyaluronidase once daily for 10 days post‐axotomy. Eleven days post‐transection brains from animals under terminal anesthesia were recovered for histological evaluation. Effective delivery of substance was inferred from the observed reduction in perilesional immunoreactivity for neurocan and versican after treatment with hyaluronidase (relative to saline). Immunolabeling using antibodies against tyrosine hydroxylase was used to examine the response of cut dopaminergic nigral neurons. After transection and treatment with saline, dopaminergic nigral neurons sprouted in a region lacking astrocytes, neurocan and versican. Axons did not regenerate into the lesion surround that contained astrocytes and abundant neurocan and versican. After transection and treatment with hyaluronidase, there was a significant increase in the number of cut dopaminergic nigral axons growing up to 800 μm anterior to the site of transection. However, cut dopaminergic nigral axons still did not regenerate into the lesion surround that contained reduced (albeit residual) neurocan and versican immunoreactivity. Thus, partial degradation of hyaluronan and chondroitin sulfate and depletion of hyaluronan‐binding CSPGs enhances local sprouting of cut CNS axons, but long‐distance regeneration fails in regions containing residual hyaluronan‐binding CSPGs. Hyaluronan, chondroitin sulfate and hyaluronan‐binding CSPGs therefore likely contribute toward the failure of spontaneous axon regeneration in the injured adult mammalian brain and spinal cord. © 2002 Wiley‐Liss, Inc.
Computer vision signal processing on graphics processing units

This paper shows speedups attained by using computer graphics hardware for implementation of computer vision algorithms by efficiently mapping mathematical operations of computer vision onto modem computer graphics architecture. As an example computer vision algorithm, we implement a real-time projective camera motion tracking routine on modern, GeForce FX class GPUs (graphics processing units). Algorithms are implemented using OpenGL and the nVIDIA Cg fragment shaders. Trade-offs between computer vision requirements and GPU resources are discussed. Algorithm implementation is examined closely, and hardware bottlenecks are addressed to examine the performance of GPU architecture for computer vision. It is shown that significant speedups can be achieved, while leaving the CPU free for other signal processing tasks. Applications of our work include wearable, computer mediated reality systems that use both computer vision and computer graphics, and require realtime processing with low-latency and high throughput provided by modem GPUs.
Non-interleaved deferred shading of interleaved sample patterns

This paper presents a novel and fast technique to combine interleaved sampling and deferred shading on a GPU. The core idea of this paper is quite simple. Interleaved sample patterns are computed in a non-interleaved deferred shading process. The geometric buffer (G-buffer) which contains all of the pixel information is actually split into several separate and distinct sub-buffers. To achieve such a result in a fast way, a massive two-pass swizzling copy is used to convert between these two buffer organizations. Once split, the sub-buffers can then be accessed to perform any fragment operation as it is done with a standard deferred shading rendering pipeline. By combining interleaved sampling and deferred shading, real time rendering of global illumination effects can be therefore easily achieved. Instead of evaluating each light contribution on the whole geometric buffer, each shading computation is coherently restricted to a smaller subset a fragments using the sub-buffers. Therefore, each screen pixel in a regular n X m pattern will have its own small set of light contributions. Doing so, the consumed fillrate is considerably decreased and the provided rendering quality remains close to the quality obtained with a non-interleaved approach. The implementation of this rendering pipeline is finally straightforward and it can be easily integrated in any existing real-time rendering package already using deferred shading.
Public confidence and cardiac surgical outcome

The General Medical Council has recently been grappling with the problem of measuring and comparing surgical outcomes after complex surgery in a heterogeneous patient population with differing severities of illness.1 Cardiothoracic surgery, with its immediate, and sometimes catastrophic outcomes, is the first surgical specialty to come under such scrutiny. Inevitably the media coverage has dented public confidence in the ability of the medical profession to police itself, and in particular this has been focused on cardiothoracic surgery.1 Yet, the irony is that in the United Kingdom cardiothoracic surgery has better data and is more subject to internal scrutiny than perhaps any other specialty. The Society of Cardiothoracic Surgeons has a long history of audit. In 1977 Sir Terence English established the United Kingdom cardiac surgical register,2 which collects activity and mortality data on all cardiac surgical procedures performed in each NHS cardiac surgical unit, amounting to 35 000 procedures a year. Although apparently simple in concept, the process represented the first attempt in Britain by any specialty to collect national activity and outcome data. All data are anonymised, since this was a prerequisite for encouraging voluntary data submission from all units. Similarly the United Kingdom heart valve registry has collected national valve surgery data since 1986. Linkage of this registry to the Office for National Statistics means we now have unique 10 year survival data following heart valve replacements in the NHS. 3 18 Both registries return aggregated data to each member of the society as an annual report containing national activity and mortality data for a wide range of cardiac operations. Since inception the presumption has been that access to national information would draw each surgeon's attention to his or her own performance and encourage …
Decision Aid Influences on Factors Associated with Patient Empowerment prior to Cancer Treatment Decision Making

Background. Despite progress, models that incorporate antecedent and mediating factors associated with shared decision making (SDM)–related outcomes remain limited. An experimental study tests patient decision aid (DA) effects on a network of antecedents and mediators associated with patient empowerment prior to a medical decision-making consultation regarding cancer treatment. Methods. A pilot study initially evaluated measurement scales, model fit, and the overall effect of the DA experience. The pilot compared matched treatment and control group samples of US adult online panel members exposed to a vignette about meeting their dermatologist to decide on skin cancer treatment. The treatment group also experienced a skin cancer DA with treatment options and value clarification activity, while the control group did not. The main study employed a randomized experimental design to formally test hypothesized path coefficients across the groups. Results. The pilot study suggested an overall enhanced DA effect on self-empowerment. In the experimental study, the DA experience strengthened the direct path from desire for medical information to self-empowerment and the indirect path from comprehension/participation confidence to self-empowerment through cancer attitude. The DA had no strengthening effect on the direct path from life satisfaction to self-empowerment, but in the DA condition, the factor appeared to play a role by contributing to the enhanced association between confidence and cancer attitude. Conclusion. Evidence from this research indicates that experiencing a DA prior to treatment decision making affects patient empowerment through a network that includes desire for information, life satisfaction, and multiple mediators. The studies also demonstrate the role that theory-based, multigroup structural equation modeling (SEM) can play in increasing understanding of DA effects. Such understanding is critical to improving SDM between patients and their physicians.
Plasma Sterilization: What are the Conditions to Meet this Claim?

Plasma-based processes to inactivate micro-organisms are usually called 'plasma sterilization'. Based on the debatable assumption of exponential first-order micro-organism inactivation kinetics, sterilization process validation is realizable by a combination of experimental tests and data extrapolation. In this article, an alternative concept for a solid and reproducible process qualification is proposed to guarantee reliable microbiological safety on a sufficient level for products that must be sterilized by alternative procedures like plasma processes. A proof of antimicrobial efficacy on the highest experimentally accessible level under experimentally realizable, reproducible, and statistically evaluable conditions is demanded.
Thermal performance evaluation of SiC power devices packaging

The development of power components based on silicon carbide (SiC) allows high power densities, size reduction and elevated operating temperatures (above 200 or 300°C). In this study, we present solutions for SiC device packaging base on 3D finite element simulation and experimental approach. Various test vehicles were assembled with different die attach and substrate. New materials like copper carbide (CuC) and copper diamond (Cu-diamond) were selected for base plate. Their thermal performances were evaluated through the measurement of the thermal resistance and 3D finite elements simulations.
An energy balanced topology construction protocol for Wireless Sensor Networks

Energy efficiency in Wireless Sensor Networks (WSNs) is an important area of research for practical WSN deployment for extended periods of time. Appropriate topology control (TC), consisting of topology construction and maintenance, facilitates an energy aware and load balanced network while ensuring connectivity and coverage. In this research, the authors propose a novel load balanced TC protocol for connectivity - EAST (Energy Aware Spanning Tree). The EAST protocol's goal is to balance the load while reducing energy utilization for the network. The EAST protocol builds upon the Minimal Spanning Tree (MST) construction method. A Connected Dominating Set (CDS) is constructed while taking into account the energy level of each parent branch to form the communication backbone. The aim of this EAST protocol is to place as many nodes into sleep mode while maintaining the communication backbone of active nodes as determined based on an energy metric. Dynamic Global Topology Recreation (DGTRec) was implemented as the topology maintenance protocol which periodically builds a new communication backbone. The proposed EAST algorithm was simulated and compared with Simple Tree, Random Nearest Neighbor Tree (Random NNT) and Euclidian Minimal Spanning Tree (Euclidian MST). The simulation results demonstrate that the EAST algorithm improves load balancing and event coverage as compared to the other tested algorithms.
A geometrical origin for the covariant entropy bound

Causal diamond-shaped subsets of spacetime are naturally associated with operator algebras in quantum field theory, and they are also related to the Bousso covariant entropy bound. In this work we argue that the net of these causal sets to which are assigned the local operator algebras of quantum theories should be taken to be non-orthomodular if there is some lowest scale for the description of spacetime as a manifold. This geometry can be related to a reduction in the degrees of freedom of the holographic type under certain natural conditions for the local algebras. A non-orthomodular net of causal sets that implements the cutoff in a covariant manner is constructed. It gives an explanation, in a simple example, of the non-positive expansion condition for lightsheet selection in the covariant entropy bound. It also suggests a different covariant formulation of the entropy bound.
Question-answering in webtalk: an evaluation study

WebTalk is an intelligent agent that automatically mines company websites to create interactive spoken and chat-based dialog systems. In this paper, we briefly describe the technologies that WebTalk utilizes for extracting task knowledge from websites and answering questions specified in natural language. We elaborate on an evaluation of the question answering component of WebTalk. In particular, we compare this component with a deployed hand-crafted question answering agent. A detailed evaluation analysis is presented.
Gene Network Disruptions and Neurogenesis Defects in the Adult Ts1Cje Mouse Model of Down Syndrome

Background Down syndrome (DS) individuals suffer mental retardation with further cognitive decline and early onset Alzheimer's disease. Methodology/Principal Findings To understand how trisomy 21 causes these neurological abnormalities we investigated changes in gene expression networks combined with a systematic cell lineage analysis of adult neurogenesis using the Ts1Cje mouse model of DS. We demonstrated down regulation of a number of key genes involved in proliferation and cell cycle progression including Mcm7, Brca2, Prim1, Cenpo and Aurka in trisomic neurospheres. We found that trisomy did not affect the number of adult neural stem cells but resulted in reduced numbers of neural progenitors and neuroblasts. Analysis of differentiating adult Ts1Cje neural progenitors showed a severe reduction in numbers of neurons produced with a tendency for less elaborate neurites, whilst the numbers of astrocytes was increased. Conclusions/Significance We have shown that trisomy affects a number of elements of adult neurogenesis likely to result in a progressive pathogenesis and consequently providing the potential for the development of therapies to slow progression of, or even ameliorate the neuronal deficits suffered by DS individuals.
Fast macroblock intra and inter modes selection for H.264/AVC

The major complexity source in H.264 is the rate distortion (R-D) optimization. This work proposes a method to reduce the complexity of R-D analysis, paying a little video degradation, by estimating the encoding modes that are more likely used by the encoder. Since the encoding modes depend mainly on the typology of the video and on the quantization parameter used to encode each block, the work proposes to group the modes into subsets that depend on the quantizer level and the characteristics of the video. In particular, the motion compensability of each frame modulates the intra modes, while texture difficulty addresses the inter modes. The R-D algorithm evaluates only the modes included into the resulting subset. The usage of subset modes reduces the complexity of the encoding process (40-70%) with respect to the original R-D optimized encoder, with a slight PSNR reduction (0-0,30 dB).
Molecular dynamics simulation of carbon nanotubes under elevated temperatures

The mechanical characteristics of high‐strength materials or nanodevices made with carbon nanotubes (CNTs) depend on the intrinsic properties of the CNT building blocks. In this paper, the dynamics of the CNT structure and its stability under heat loading has been studied through molecular dynamic (MD) simulations. The ultimate goal was to observe the variations in the overall structure of the CNT and study the quality of the changes occurring in the bond lengths and bond angles in the original hexagonal structure building up the CNT. We have used a Lennard‐Jones pair potential to characterize the interactions between non‐bonded atoms and harmonic potentials for bond stretching and bond angle vibrations. Results of the MD simulations indicate that the overall shape of the CNT and its hexagonal structure are affected by the heat loading under the considered temperatures and the structural orientation of the hexagonal building blocks are highly affected by temperature variations.
Blood autotransfusion outcomes compared with Ringer lactate infusion in dogs with hemorrhagic shock induced by controlled bleeding

BACKGROUND: The most common cause of shock in the surgical or trauma patient is hemorrhage. Crystalloid solutions and blood transfusion are the mainstays of treatment of hemorrhagic shock. Considering the disadvantages of allogeneic blood transfusion, such as risk of transmission of infectious diseases, and access and maintenance limitations, treatment of shock with autologous blood seems to be a decent solution. Autologous blood accumulated in body cavities in traumatic bleeding (such hemothorax), and bloodshed in operation field during open heart or vascular surgeries, and similar situations, can be utilized again. In this study, autotransfusion effects compared with crystalloid fluid in the treatment of hemorrhagic shock was investigated. METHODS: After induction of hemorrhagic shock in dogs by Wiggers type controlled bleeding, treating them in a group with autologous blood and another group with Ringer lactate were performed, and the results of treatment were studied. RESULTS: There was no mortality in both treatment approaches. Immediately after treatment, crystalloid positive effects such as renormalized vital signs and appropriate consciousness were more noticeable than autotransfusion, while twenty-four hours after, the desired effects of autologous blood were more pronounced like decreased metabolic acidosis and improvement of diuresis. CONCLUSIONS: Crystalloid during the first hours after treatment of hemorrhagic shock may be better than autologous blood as preferred treatment, while autotransfusion showed its benefits some hours after. This finding can be used to develop better strategies for treatment of hemorrhagic shock.