Miracle-dz/UniFAR-FTUs huggingface dataset:
Sequence Feature Extraction for Malware Family Analysis via Graph Neural Network

Malicious software (malware) causes much harm to our devices and life. We are eager to understand the malware behavior and the threat it made. Most of the record files of malware are variable length and text-based files with time stamps, such as event log data and dynamic analysis profiles. Using the time stamps, we can sort such data into sequence-based data for the following analysis. However, dealing with the text-based sequences with variable lengths is difficult. In addition, unlike natural language text data, most sequential data in information security have specific properties and structure, such as loop, repeated call, noise, etc. To deeply analyze the API call sequences with their structure, we use graphs to represent the sequences, which can further investigate the information and structure, such as the Markov model. Therefore, we design and implement an Attention Aware Graph Neural Network (AWGCN) to analyze the API call sequences. Through AWGCN, we can obtain the sequence embeddings to analyze the behavior of the malware. Moreover, the classification experiment result shows that AWGCN outperforms other classifiers in the call-like datasets, and the embedding can further improve the classic model's performance.
Network Security Node-Edge Scoring System Using Attack Graph Based on Vulnerability Correlation

: As network technology has advanced, and as larger and larger quantities of data are being collected, networks are becoming increasingly complex. Various vulnerabilities are being identiﬁed in such networks, and related attacks are continuously occurring. To solve these problems and improve the overall quality of network security, a network risk scoring technique using attack graphs and vulnerability information must be used. This technology calculates the degree of risk by collecting information and related vulnerabilities in the nodes and the edges existing in the network-based attack graph, and then determining the degree of risk in a speciﬁc network location or the degree of risk occurring when a speciﬁc route is passed within the network. However, in most previous research, the risk of the entire route has been calculated and evaluated based on node information, rather than edge information. Since these methods do not include correlations between nodes, it is relatively difﬁcult to evaluate the risk. Therefore, in this paper, we propose a vulnerability Correlation and Attack Graph-based node-edge Scoring System (VCAG-SS) that can accurately measure the risk of a speciﬁc route. The proposed method uses the Common Vulnerability Scoring System (CVSS) along with node and edge information. Performing the previously proposed arithmetic evaluation of conﬁdentiality, integrity, and availability (CIA) and analyzing the correlation of vulnerabilities between each node make it possible to calculate the attack priority. In the experiment, the risk scores of nodes and edges and the risk of each attack route were calculated. Moreover, the most threatening attack route was found by comparing the attack route risk. This conﬁrmed that the proposed method calculated the risk of the network attack route and was able to effectively select the network route by providing the network route priority according to the risk score.
User Cold Start Problem in Recommendation Systems: A Systematic Review

The recommendation system makes recommendations based on the preferences of the users. These user preferences usually come from the user’s basic information, item rating, historical data, and so on. The “user cold start problem” happens when a new user cannot be appropriately suggested due to a lack of more detailed preference information. In many instances, the user cold start problem hinders the use of the recommendation system. Many researchers are currently trying to discover a solution to the user cold start problem. Unfortunately, there are two drawbacks in the current systematic reviews of how to deal with the user cold start problem. First, systematic reviews on how to deal with the user cold start problem are scarce or outdated. Second, existing reviews lack the distinction between the user cold start problem and the item cold start problem. Nevertheless, the solutions to the two problems differ. To address these problems, our study thorough review of all literature published by researchers from January 2016 to April 2023 about 8 years. Firstly, this study analyzes the literatures on approaches that addressed the user cold start problem during the past eight years and divides them into two categories: data-driven technology and approach-driven technology, and then describes and classifies each type of technology in detail. Secondly, this study also analyzes the main evaluation criteria currently used in these methods to provide a reference for researchers in related fields. Finally, this paper also points out the future research direction of this field.
Digital Signal Processing: A Computer-Based Approach

From the Publisher: "Digital Signal Processing: A Computer-Based Approach" is intended for a two-semester course on digital signal processing for seniors or first-year graduate students. Based on user feedback,a number of new topics have been added to the second edition,while some excess topics from the first edition have been removed. The author has taken great care to organize the chapters more logically by reordering the sections within chapters. More worked-out examples have also been included. The book contains more than 500 problems and 150 MATLAB exercises. New topics in the second edition include: finite-dimensional discrete-time systems,correlation of signals,inverse systems,system identification,matched filter,design of analog and IIR digital highpass,bandpass and bandstop filters,more on FIR filters,spectral analysis of random signals and sparse antenna array design.
Loyola eCommons Loyola eCommons

Alcohol misuse is a leading cause of premature death in the United States. Nearly a third of trauma patients are found to have elevated blood alcohol levels upon admission, and there is a high risk of relapse for patients with alcohol misuse. However, timely intervention has been shown to reduce this risk. It is thus important to be able to quickly screen patients to identify alcohol misuse. Many medical centers use standardized questionnaires such as the Alcohol Use Disorder Indicator Test to identify alcohol misuse, but since the test is not usually a part of routine care, there are many cases where it is not done. Also, some patients may under-report their scores, making misuse identification and subsequent intervention unfeasible. The data captured by care providers in clinical narrative is a potentially rich source of data for identifying patients with alcohol misuse which can be used to augment the screening process. In this study, large quantities of notes were processed with natural language processing and machine learning methods to identify important social and behavioral determinants for health. It resulted in the creation of a system, which uses NLP and ML, that provides good discrimination of patients with and without alcohol misuse.
Transmission of ST8-USA300 Latin American Variant Methicillin-Resistant Staphylococcus aureus on a Neonatal Intensive Care Unit: Recurrent Skin and Soft- Tissue Infections as a Marker for Epidemic Community-Associated-MRSA Colonization

Infectious Diseases Society of America. Clin Infect Dis 2010;50:133–164. 9. Lopez-Cerero L, Picon E, Morillo C, et al. Comparative assessment of inoculum effects on the antimicrobial activity of amoxycillinclavulanate and piperacillin-tazobactam with extended-spectrum β-lactamase-producing and extended-spectrum β -lactamase-nonproducing Escherichia coli isolates. Clin Microbiol Infect 2010;16:132–136. 10. Tamma PD, Girdwood SC, Gopaul R, et al. The use of cefepime for treating AmpC β -lactamase-producing Enterobacteriaceae. Clin Infect Dis 2013;57:781–788.
Overcoming Testing Challenges in Project Life Cycle using Risk Based Validation Approach

— According to James Whittake, Microsoft Testing Expert and Author, “There are a number of trends that testers are going to have to grapple with. The first is that software is getting better. The result of this is that bugs are going to become harder and harder to find and the weaker testers will be relegated to Darwinian insignificance. Keeping sharp, building skills and maintaining a cutting edge testing knowledge has never been more important”. The key drive for software testing is capturing defects. Testing is becoming a lot more complex. Most software products are not tested thoroughly, so both users and the organizations that write the software expect them to have bugs. There is more and more realization that testing becomes a bottleneck without upfront planning and projects need consider that in software development reducing defects is substantially important. When a project is low on funding or over budget, the first important task that is cut is ‘Testing’. But limiting testing of a solution will increase the chance of system failure or unknown bugs that can cripple your business. This paper focuses on the approaches that can be considered to reduce the number of defects captured in testing or later phase of testing.
Postural control and adaptation to threats to balance stability

Postural control is the ability to maintain equilibrium and orientation in a gravitational environment. It is dependent on feedback and feedforward mechanisms that generate appropriate corrective movement based on body-sway motion detected primarily by visual, vestibular, and proprioceptive sensory systems. Since information from the various senses is not always accurate (e.g. by disease) or available (e.g. with eyes closed), the postural control system must adapt to maintain stance. This thesis aimed to investigate postural control and adaptation to threats of balance. Effective approaches for the clinical measurement of postural control still remains to be developed. In the past, it has been common to investigate patients’ balance by having them stand upon compliant foam blocks with eyes open and closed since standing on foam is believed to affect the accuracy of information from cutaneous mechanoreceptors on the soles of the feet. However, when assessing balance on foam blocks with different compliances and mechanical properties, it was found that postural sway was larger on firmer compliant surfaces, which also increased the importance of visual information. Postural adaptation was also investigated by repeatedly perturbing balance using muscle vibrations. In healthy, young persons, a slow adaptive change was observed. This adaptation involved decreased costs of standing including decreased energy, body movement and muscle activity and changes to the relationship between muscle activity and movement. The characteristics of the adaptation also depended on the availability of visual information. The elderly had poor postural control with and without being perturbed but were able to adapt to improve their poor balance. However, decreased mechanoreceptive sensation in the elderly prevented them from adapting their balance to the level of younger test subjects. Sleep deprivation decreased attention and alertness and resulted in decreased postural control and adaptation. The findings in this thesis extend what is known about motor learning. The adaptive learning capability of the postural control system, and hence the accurate reconstruction of the kinematics and kinetics of movement, was dependant on ones own mechanoreceptive somatosensation and availability of visual information. Decreasing attention and alertness through sleep deprivation decreased adaptive capabilities, suggesting an important role for sleep in memory and consolidation of a new motor skill. (Less)
Faults' context matters

When choosing a testing technique, practitioners want to know which one will detect the faults that matter most to them in the programs that they plan to test. Do empirical evaluations of testing techniques provide this information? More often than not, they report how many faults in a carefully chosen "representative" sample the evaluated techniques detect. But the population of faults that such a sample would represent depends heavily on the faults' context or environment---as does the cost of failing to detect those faults. If empirical studies are to provide information that a practitioner can apply outside the context of the study, they must characterize the faults studied in a way that translates across contexts. A testing technique's fault-detecting abilities could then be interpreted relative to the fault characterization. In this paper, we present a list of criteria that a fault characterization must meet in order to be fit for this task, and we evaluate several well-known fault characterizations against the criteria. Two families of characterizations are found to satisfy the criteria: those based on graph models of programs and those based on faults' detection by testing techniques.
Motivic characteristic classes

Motivic characteristic classes of possibly singular alge braic varieties are ho- mology class versions of motivic characteristics, not clas ses in the so-called motivic (co) homology. This paper is a survey on them with more emphasis on capturing infinitude finitely and on the motivic nature, in other words, the scisso r relation or additivity. Characteristic classes are usually cohomological objects defined on real or complex vec- tor bundles, thus for any smooth manifold, characteristic classes of it are defined through its tangent bundle. For the real vector bundles, Stiefel-Whitney classes and Pontraygin classes are fundamental ones and in the complex vector bundles the Chern class is the fun- damental one. When it comes to a non-manifold space, such as a singular real or complex algebraic or analytic variety, one cannot talk about its coh omological characteristic class, unlike the smooth case, simply because one cannot define its t angent bundle, although one can define some reasonable substitutes, such as tangent cone , tangent star cone, which are not vector bundles, rather stratified vector bundles. In the 1960's people started to de- fine characteristic classes on algebraic varieties as homol ogical objects, not through some kind of vector bundles considered on them, but as higher analogues of some geometri- cally important invariants such as Euler-Poincare characteristic, signature, etc. I suppose that the theory of characteristic classes of singular space s start with Thom's L-class for oriented P L-manifolds (Thom), whereas Sullivan's Stiefel-Whitney cl asses and the so- called Deligne-Grothendieck conjecture about the existence of Chern homology classes started the whole story of capturing characteristic classes of singular spaces as nat ural transformations, more precisely as a natural transformation from a certain covariant func- tor to the homology functor. The Deligne-Grothendieck conjecture seems to be based on Grothendieck's idea or modifying his conjecture on a Riemann-Roch type formulacon- cerning the constructiblesheaves and Chow rings (cf. (Grot, Part II, note(871), p.361 ff. )) and made in the well-known form by P. Deligne later. R. MacPherson (M1) gave a positive answer to the Deligne-Grothendieck conjecture and, motivated by this solution, P. Baum, W. Fulton and R. MacPherson (BFM1) further established the singular Riemann- Roch Theorem, which is a singular version of Grothendieck-Riemann-Roch, which is a functorial extension of the celebrated Hirzebruch-Riemann-Roch (abbr. HRR) (Hi). HRR is the very origin of Atiyah-Singer Index Theorem.
Many Shades of Creativity

Creativity means constructive actions ending in innovation, art, breaking rules or thinking out of the box. Creativity is good, the new resource of the future. I would not like to query the importance or the benefits of creativity for individuals, organizations, and societies. Creativity is also beneficial at the individual level or organizational level. For instance, creativity helps us manage our daily lives or helps us to find creative and innovative solutions for both organizational and daily problems. At the same time, creativity might also produce negative effects by leading individuals to engage in unethical behavior and to skip or reason wrong ethical solutions. Greater creativity helps us solve difficult problems across many domains, but creative sparks may lead us to take unethical routes when searching for solutions to tasks. But I think not only creativity but moral creativity is highly relevant in this increasingly changing, innovative, and competitive world of the 21st century. This study aims to examine the relationship between creativity and morality. In this article I am going to summarize the literature of the „dark side of creativity” highlighting the economical part and I try to give an overall point into state of art. In the first chapter I will give an overall overview about the definition of creativity which based on the 4 Ps (personality, product, process, press) without going in the depths of psychopathology. This summarizing is followed by the definition of moral. Regarding the 4Ps of creativity I try to find some connections between the creative and ethical economical behavior. I focus on results of important literatures and try to translate those into some practical guidelines for the futures. This article is the first but important step to draw the readers’ attention to see creativity through the glasses of moral. This theoretical paper will not contain any empirical study but try to be dominantly a literature review which is mainly important for the business actors.
Efficient Current Mode Sense Amplifier for Low Power SRAM

Sense amplifiers are one of the most vital circuits in the margin of CMOS memories. Their performance influences both memory access time and overall memory power dissipa tion. The existing Current-Mode Sense Amplifier cou pled with a simplified read-cycle-only memory system has the ab ility to quickly amplify a small differential signa l on the Bit-Lines (BLs) and Data-Lines (DLs) to the full CMOS logic level w ithout requiring a large input voltage swing. The C urrent-Mode Sense Amplifier has two levels of sensing schemes. This h ierarchical two-level sensing scheme helps in reduc ing both power consumption and sensing delay imposed by the bit-li nes and the data-lines on high density SRAM designs . Thi type of CurrentMode Sense Amplifier improves the sensing speed and reliability of the previously published designs an d at the same time reduces the power consumption to a considerable ext ent. In order to further improve the performance of the existing currentmode sense amplifier, an efficient current-mode sen se amplifier is proposed in this research. The prop osed research work uses the clamped bit-line sense amplifier .
Efficient Triangular Surface Approximations Using Wavelets and Quadtree Data Structures

We present a method for adaptive surface meshing and triangulation which controls the local level of detail of the surface approximation by local spectral estimates. These estimates are determined by a wavelet representation of the surface data. The basic idea is to decompose the initial data set by means of an orthogonal or semi orthogonal tensor product wavelet transform (WT) and to analyze the resulting coefficients. In surface regions, where the partial energy of the resulting coefficients is low, the polygonal approximation of the surface can be performed with larger triangles without losing too much fine grain details. However, since the localization of the WT is bound by the Heisenberg principle, the meshing method has to be controlled by the detail signals rather than directly by the coefficients. The dyadic scaling of the WT stimulated us to build an hierarchical meshing algorithm which transforms the initially regular data grid into a quadtree representation by rejection of unimportant mesh vertices. The optimum triangulation of the resulting quadtree cells is carried out by selection from a look up table. The tree grows recursively as controlled by detail signals which are computed from a modified inverse WT. In order to control the local level of detail, we introduce a new class of wavelet space filters acting as "magnifying glasses" on the data. We show that our algorithm performs a low algorithmic complexity, so that surface meshing can be achieved at interactive rates, such as required by flight simulators, however, other applications are possible as well.
New Analysis Method Application in Metallographic Images through the Construction of Mosaics Via Speeded Up Robust Features and Scale Invariant Feature Transform

In many applications in metallography and analysis, many regions need to be considered and not only the current region. In cases where there are analyses with multiple images, the specialist should also evaluate neighboring areas. For example, in metallurgy, welding technology is derived from conventional testing and metallographic analysis. In welding, these tests allow us to know the features of the metal, especially in the Heat-Affected Zone (HAZ); the region most likely for natural metallurgical problems to occur in welding. The expanse of the Heat-Affected Zone exceeds the size of the area observed through a microscope and typically requires multiple images to be mounted on a larger picture surface to allow for the study of the entire heat affected zone. This image stitching process is performed manually and is subject to all the inherent flaws of the human being due to results of fatigue and distraction. The analyzing of grain growth is also necessary in the examination of multiple regions, although not necessarily neighboring regions, but this analysis would be a useful tool to aid a specialist. In areas such as microscopic metallography, which study metallurgical products with the aid of a microscope, the assembly of mosaics is done manually, which consumes a lot of time and is also subject to failures due to human limitations. The mosaic technique is used in the construct of environment or scenes with corresponding characteristics between themselves. Through several small images, and with corresponding characteristics between themselves, a new model is generated in a larger size. This article proposes the use of Digital Image Processing for the automatization of the construction of these mosaics in metallographic images. The use of this proposed method is meant to significantly reduce the time required to build the mosaic and reduce the possibility of failures in assembling the final image; therefore increasing efficiency in obtaining results and expediting the decision making process. Two different methods are proposed: One using the transformed Scale Invariant Feature Transform (SIFT), and the second using features extractor Speeded Up Robust Features (SURF). Although slower, the SIFT method is more stable and has a better performance than the SURF method and can be applied to real applications. The best results were obtained using SIFT with Peak Signal-to-Noise Ratio = 61.38, Mean squared error = 0.048 and mean-structural-similarity = 0.999, and processing time of 4.91 seconds for mosaic building. The methodology proposed shows be more promissory in aiding specialists during analysis of metallographic images.