Miracle-dz/UniFAR-FTUs huggingface dataset:
Lutz Towards Revealing Attackers ’ Intent by Automatically Decrypting Network Traffic

Researchers and commercial security companies are constantly improving their techniques to detect and prevent malicious software (malware) proliferation. Unfortunately, at the same time malware authors continuously improve their techniques to evade detection. One recent development in this arms race is the use of encrypted network communication by malware authors to prevent the analysis of malware capabilities and hide malicious activities. To date, researchers have manually analyzed malware binaries to reverse engineer their decryption algorithms. Manual malware analysis, however, is very labor intensive and does not scale as the number of malware binaries that use encryption increases. To address these shortcomings of manual analysis we present a generic and automatic tool for the decryption of encrypted communication received by a binary. Our tool does not break cryptography but leverages the fact that the binary decrypts the encrypted input it receives during its execution. We use a dynamic binary analysis approach to run the binary and identify where and when the decrypted input is located in the system’s memory. We provide evidence that our tool effectively locates decrypted input for various linux cryptographic libraries. We also present a case study of the ability of our tool to decrypt the network communication of a real malware bot sample. We argue that our approach can be used as a tool for revealing the intent of attackers that try to masquerade their activities using encrypted communication.
Indium Antimonide (InSb) based planar terahertz plasmonic waveguide

We demonstrate experimental and theoretical studies on the transmission characteristics of Terahertz (THz) Semiconductor-Insulator-Semiconductor (SIS) Planar Plasmonic waveguide made up of Indium Antimonide (InSb). We report tunability of the waveguide characteristics by changing the device geometrical dimensions. The results are of critical importance for optimizing and determining the resonance characteristics of the device.
Techniques to Enhance Lifetime of Wireless Sensor Networks: A Survey

Increasing lifetime in wireless sensor networks is a major challenge because the nodes are equipped with low power battery. For increasing the lifetime of the sensor nodes energy efficient routing is one solution which minimizes maintenance cost and maximizes the overall performance of the nodes. In this paper, different energy efficient routing techniques are discussed. Here, photovoltaic cell for efficient power management in wireless sensor networks is also discussed which are developed to increase the lifetime of the nodes. Efficient battery usage techniques and discharge characteristics are then described which enhance the operational battery lifetime.
Fault detection of a seven level modular multilevel inverter via voltage histogram and Neural Network

The multilevel inverters (MLIs) utilization has been increased in recent years due to their lots of advantages. The MLI has many switches that increase the probability of fault events. In this paper a fault diagnosis method for a cascade H-bridge 7-level inverter is proposed. The output phase voltage is used to detect fault type and their locations. The histogram analysis is used for feature extraction and these features have been used as input to the Neural Networks (NNs). The multilayer perceptron NNs have been used for fault diagnosis. Simulation results are given for a cascade 7-level inverter at different modulation indices and show that this method is accurate for detection of faults and their locations. This method works correctly under noisy condition and the classification performance for the noise with variance up to 1500 is 100%. The proposed method is faster and less complicated because of using histogram analysis instead of using sophisticated methods such as FFT or wavelet
Kinect Handwritten Digit Recognition Based on Dynamic Time Warping and Support Vector Machine

Handwriting in-space from Kinect depth and color information is a challenging task due to the high variability of signature characteristics for different individuals. In this paper, a user-friendly human computer interaction system is proposed and implemented based on Kinect handwriting. The fingertip is firstly tracked by our detection method in every depth frame to generate 3D trajectory of handwriting, and then normalization and smoothing are performed before feature extraction. On this basis, the time sequence feature of 3D signature can be captured as an online character recognition method, and a joint recognition framework is proposed based on DTW and SVM for input vectors of different lengths. The evaluation on a handwriting in-space dataset of digits from 0 to 9 shows that the proposed recognition scheme can offer a high recognition accuracy and a satisfying robustness to noisy data in digit recognition test even with small training number. Therefore, the method can be successfully applied in many Human Computer Interaction applications in real world.
An Algorithm for Detection of Calibration Points for Photogrammetric Camera Calibrations Independent of Illumination Variations

Getting 3D information from 2D images depends on the appropriate camera calibration of the internal and external CCD (Charge Couple Device) camera parameters. The photogrammetric camera calibration technique needs a set of world coordinates and their corresponding calibration object image coordinates as an input. During this work we developed an algorithm to detect the image coordinates of a calibration object for different illumination conditions with subpixel accuracy. In other words, the proposed algorithm allows that any photogrammetric camera calibration technique that needs image coordinates of the calibration object will not be sensitive to illumination changes within a 200 to 6000 lux interval. The algorithm was tested in a vision system composed by a P.C. , a robotic arm and a CCD camera. The system automatically controls the position of the camera within the work space and it captures and processes the images using Matlab®. Key-Words: Machine Vision, Image Processing and Applications.
Soft Coherence : Preliminary Experiments with Error-Tolerant Cache Coherence in Numerical Applications

As we scale into the multi-core era, we face severe challenges in the scalability and performance of on-chip cache-coherent shared memory mechanisms. We explore application error-tolerance as an extra degree of freedom to meet these challenges. Iterative numerical algorithms, in particular, can cope with the occasional stale value with little or no effect on accuracy or convergence time. We explore analysis methods to distinguish between critical and non-critical data in such algorithms. We exploit this distinction to design soft coherence protocols that provide strong guarantees for critical data and weak guarantees for non-critical data. Our preliminary results use a conjugate gradient solver as an example, with experiments on five sparse matrices showing 6.9%12.6% performance improvement, with little loss in precision.
Fracture propagation and prediction in heterogeneous materials

Aalto University, P.O. Box 11000, FI-00076 Aalto www.aalto. fi Author Juha Koivisto Name of the doctoral dissertation Fracture propagation and prediction in heterogeneous materials Publisher School of Science Unit Department of Applied Physics Series Aalto University publication series DOCTORAL DISSERTATIONS 122/2013 Field of research Engineering Physics Manuscript submitted 31 May 2013 Date of the defence 4 September 2013 Permission to publish granted (date) 19 August 2013 Language English Monograph Article dissertation (summary + original articles) Abstract The topic of this thesis is fracture and damage. It is discussed with an experimental point of view in multiple geometries.The topic of this thesis is fracture and damage. It is discussed with an experimental point of view in multiple geometries. In Publications I and II a 1D fracture line is driven through elastic medium that is paper. The fracture line propagates with jerky motion producing audible avalanches. These acoustic emission events obey Gutenberg-Richter statistics for energy and Omori law for waiting times. In Publications III and IV digital image correlation technique is used to measure local strains in paper creep experiments. The significance of local fluctuations increases during the experiment as the fluctuations decay slower than the average strain rate. The global strain rate is found to have a Monkman-Grant relation. In Publication V the global and local strains are used to predict the failure in the paper fatique experiment. The system is compared to a standard fiberbundle model with viscous components. Chapter 4 relates to unpublished work of two interacting cracks. Here, it is shown that curved cracks follow the local symmetry path where the shear stress intensity factor KII = 0.
Single sperm tracking using Intersect Cortical Model-Mean Shift Method

Single sperm detection and tracking has received increasing attentions since In Vitro Fertilization (IVF) and Intracytoplasmic Sperm Injection (ICSI) techniques were introduced. In this paper, we proposed an automated system to extract and track single sperm movement. Intersect Cortical Model (ICM) which is derived from Pulse Coupled Neural Network (PCNN) is employed to extract region coordinates and the centroid of the sperm head region. By using the extracted region and centroid as an automated initialization in the proposed method, mean shift based tracking algorithm is then used to track the sperm for the entire video. As a comparison, the proposed method Intersect Cortical Model-Mean shift (ICMMS) has been evaluated with conventional mean shift based tracking method. From the results, the proposed ICMMS method remedies the drawback of mean shift based tracking algorithm by providing more accurate and robust tracking results. After testing with 100 sperm images, less misdetection of sperm has been observed from the results produced by the proposed ICMMS method. In future, the proposed method is expected to be implemented in analyzing male infertility.
The Algorithm Research of Detection Base on Machine Vision

Based on the analysis of the surface characteristics of solar cells, solar cells surface defects detection scheme based on machine vision is proposed. It is compared between the pefect solar cell and the battery to be detected, and then surface defects is analyzed. The first, the contours tracking is realised, and the defects of the cells, such as holes, fragments and breakage are determined. Secondly, In order to identification of the edge breakage, the affine transformation method is used, And then the presence or absence of the edge breakage of the cell sheet is determined by a differential comparison with the binary image of the standard template.
Agriculture and Science Integration: A Pre-service Prescription for Contextual Learning.

The purpose of the study was to determine if the delivery of an integrated agriculture and science curriculum to Agricultural Education MAT (Master of Arts in Teaching) pre-service teachers increased their desire and ability to integrate their own curriculum and collaborate with other teachers once they started teaching, and to identify social and cultural barriers in existence between secondary teachers in agriculture and science. The population for the treatment group consisted of all graduate students enrolled in the 1996-97 MAT Agricultural Education cohort at a west coast university. The control group consisted of the prev ious J i ve Agricultural Education cohorts at the same school. The research combined a series of personal interviews with the treatment group in addition to the written questionnaire administered to the treatment and control groups. The questionnaire served as the comparison for the groups. Data were analyzed using descriptive statistics. Evidence indicated that the treatment group was positive about integrating science into the agriculture curriculum and they were more willing to attend workshops about the integration of science than were members of the control group. Furthermore, the treatment group felt that preparation time was the greatest barrier in working with the science teacher in their school.
Probability based dynamic-alternate routing algorithm in all-optical WDM networks

This paper proposes a new dynamic-alternate routing algorithm for all-optical WDM networks without wavelength conversion in order to reduce the connection blocking probability. The main idea in the proposed dynamic-alternate routing algorithm is to try to route the traffics according to a predefined optimal probability distribution. The problem for finding the optimal probability distribution has been shown as a convex optimization problem. The problem can be solved by flow deviation method or other standard optimization techniques. The simulation results show that the proposed routing algorithm yields lower connection blocking probabilities than the previous works as well as the proposed routing algorithm produces similar traffic pattern as the optimal traffic pattern. The similarity between the traffic pattern produced by the proposed dynamic-alternate routing algorithm and the optimal traffic pattern can be further used for solving other network designing problems.
Another probabilistic method proposed to distinguish between fixations and saccades are Kalman filters

Common computational methods for automated eye movement detection – i.e. the task of detecting different types of eye movement in a continuous stream of gaze data – are limited in that they either involve thresholding on hand-crafted signal features, require individual detectors each only detecting a single movement, or require pre-segmented data. We propose a novel approach for eye movement detection that only involves learning a single detector end-to-end, i.e. directly from the continuous gaze data stream and simultaneously for different eye movements without any manual feature crafting or segmentation. Our method is based on convolutional neural networks (CNN) that recently demonstrated superior performance in a variety of tasks in computer vision, signal processing, and machine learning. We further introduce a novel multi-participant dataset that contains scripted and free-viewing sequences of ground-truth annotated saccades, fixations, and smooth pursuits. We show that our CNN-based method outperforms state-of-the-art baselines by a large margin on this challenging dataset, thereby underlining the significant potential of this approach for holistic, robust, and accurate eye movement protocol analysis.
Emerging reliability challenges in electronic packaging

The trend for microelectronic devices has historically been, and will continue to be, towards smaller feature size, faster speeds, more complexity, higher power and lower cost. The motivating force behind these advances has traditionally been microprocessors. With the tremendous growth of wireless telecommunication, RF applications are beginning to drive many areas of microelectronics traditionally led by the development of the microprocessor. An increasingly dominant factor in RF microelectronics is electronic packaging and the reliability of the package and the materials that comprise the package and, in particular, the solder interconnects. The need for Pb-free assembly and the application to hand-held electronics has challenged the reliability of electronic packages. This paper discusses packaging reliability of solder interconnects for hand-held wireless and RF applications and describe the tests used to evaluate reliability. The specific reliability issues discussed will be thermomechanical stress (fatigue), solder joint electromigration (DC and RF) and high speed impact stresses (drop test performance).
Heterogeneous Attitudes of Tourists toward Lionfish in the Mexican Caribbean: Implications for Invasive Species Management

Indo-Pacific lionfish (Pterois volitans and P. miles) are invasive predators established throughout the Wider Caribbean. They have already caused significant ecological impacts and have the potential to affect local economies that depend on coral reefs. Snorkeling and scuba diving are important activities that rely on aesthetically pleasant reefs. We asked whether lionfish-invaded reefs have lower aesthetic value and whether fees to help control the invasion might be acceptable to recreational divers and snorkelers in the Mexican Caribbean. To do so, we conducted a choice experiment in which tourists were asked to indicate their preferences for coral reef images with varying attributes that can be affected by lionfish. We specified a priori two classes of respondents, i.e. snorkelers and divers, but two latent classes of recreational divers (casual vs. committed) emerged on the basis of their preferences. Tourist age, commitment to snorkeling /diving, and lionfish awareness explained class membership. Casual divers and snorkelers preferred reefs with lionfish and accepted their impacts on the reefs. In contrast, committed divers disliked lionfish and associated impacts, and would elect to dive elsewhere if such impacts were high. Casual divers and snorkelers preferred options with low lionfish control fees, while committed divers were willing to pay high fees. Our results indicate potential economic impacts of the lionfish invasion in regions that depend on reef-related tourism, and that lionfish control fees might be acceptable to some but not all recreational users. However, because all tourists favored to a greater extent reef features that can be affected detrimentally by lionfish than they favored lionfish themselves, we predict that managing the lionfish invasion should be beneficial to the local reef tourism industry.
BALL SAW DEVICE FOR HYDROGEN GAS SENSOR

Surface acoustic waves (SAW) are used to coherently excite nanofabricated free standing beam resonators. Typical resonator sizes are L = 3.5 μm, w = 300nm, and h = 200nm, resulting in mechanical eigenfrequencies of the order of 100 MHz. Depending on the ratio between the resonator eigenfrequency and the frequency of the driving SAW, and depending on the SAW amplitude, we observe a complex interaction spectrum like mode locking or parametric oscillations of the NEMS beam. We give a detailled desription of our experimental findings in terms of a theoretical model. Moreover, we demonstrate that our unique experiment can even yield insight into the microscopic distribution of lattice defects and their dynamics in a nanometer size mechanical single crystal resonator. Acknowledgement: We gratefully acknowledge financial support by the Deutsche Forschungsgemeinschaft DFG.
AUSERA: Large-Scale Automated Security Risk Assessment of Global Mobile Banking Apps

Contemporary financial technology (FinTech) that enables cashless mobile payment has been widely adopted by financial institutions, such as banks, due to its convenience and efficiency. However, FinTech has also made massive and dynamic transactions susceptible to security risks. Given large financial losses caused by such vulnerabilities, regulatory technology (RegTech) has been developed, but more comprehensive security risk assessment is specifically desired to develop robust, scalable, and efficient financial activities. In this paper, we undertake the first automated security risk assessment and focus on global banking apps to examine FinTech. First, we analyze a large number of banking apps and propose a comprehensive set of security weaknesses widely existent in these apps. Second, we design a three-phase automated security risk assessment system (Ausera), which combines natural language processing and static analysis of data and control flows, to efficiently identify security weaknesses of banking apps. We performed experiments on 693 real-world banking apps across over 80 countries and unveiled 2,157 weaknesses. To date, 21 banks have acknowledged the weaknesses that we reported. We find that outdated version of banking apps, pollution from third-party libraries, and weak hash functions are all likely to be exploited by attackers. We also show that banking apps of different provenance exhibit various types of security weaknesses, mainly due to economies and regulations that take shape. Given the drastic change in the nature of intermediation, it behooves the RegTech companies and all stakeholders to understand the characteristics and consequences of security risks brought by contemporary FinTech.
Chinese Medicine History and Contemporary Practice in the West

In the health care professions today, research guides best clinical practice. Yet, the methodological constraints required by the two main branches of research into Chinese medicine—bio-scientific and socio-historical—rarely assist Chinese medicine students, practitioners, or clinical researchers with treatment and practice issues. A great deal of bio-scientific research assumes that it must be possible to utilise and test Chinese medicine from within a biomedical framework. However, by isolating therapeutic techniques and substances and standardising treatment protocols, bio-scientific research removes Chinese medicine's inbuilt flexibility and responsiveness to clinical instances and changes. While researchers in the historical and social sciences can reveal the sophisticated discourses built around Chinese medicine's distinctive approach to knowing the world and the body-person, they normally do not discuss the implications of their work for contemporary clinical practice. The paper advocates a synthetic approach using multidisciplinary sources within and adjacent to the field of Chinese medicine. Multidisciplinary researchers contest the simplified and biomedicalised version of Chinese medicine generally available in English speaking countries today. They can assist English speakers to approach Chinese medicine's traditional perspectives, demonstrate their relevance for contemporary clinical practice and help restore the traditional connectedness between Chinese medicine's theoretical concepts and its treatment methods.
Mathematical modeling of high-octane gasoline blending

The authors described a new approach to calculation of gasoline blending process taking into account the reaction interaction of blend components. The mathematical models of gasoline compounding process was developed taking into account the intensity of intermolecular interactions of mixture components and the interaction mechanism of antiknock additives with hydrocarbons. The computer simulation system for optimization of finished gasoline preparation process was designed on the basis of the developed models.
Gain Compression and Above-Threshold Linewidth Enhancement Factor in 1.3-$\mu\hbox{m}$  InAs–GaAs Quantum-Dot Lasers

Quantum-dot (QD) lasers exhibit many useful properties such as low threshold current, temperature and feedback insensitivity, chirpless behavior, and low linewidth enhancement factor (alphaH-factor). Although many breakthroughs have been demonstrated, the maximum modulation bandwidth remains limited in QD devices, and a strong damping of the modulation response is usually observed pointing out the role of gain compression. This paper investigates the influence of the gain compression in a 1.3-mum InAs-GaAs QD laser and its consequences on the above-threshold alphaH-factor. A model is used to explain the dependence of the alphaH-factor with the injected current and is compared with AM/FM experiments. Finally, it is shown that the higher the maximum gain, the lower the effects of gain compression and the lower the alphaH-factor. This analysis can be useful for designing chirpless QD lasers with improved modulation bandwidth as well as for isolator-free transmission under direct modulation.