Miracle-dz/UniFAR-FTUs huggingface dataset:
Research on Intrusion Detection Method Based on Hierarchical Self-convergence PCA-OCSVM Algorithm

At present, traditional intrusion detection methods have some shortcomings, such as long detection time, low detection accuracy and poor classification effect. This paper will combine PCA and OCSVM algorithm to build a multi-level intrusion detection model, using attack feature analysis method to preprocess data, while data cleaning and data feature selection of training set. It highlights the characteristics of abnormal data and normal data, and weakens the influence of irrelevant features on training model. PCA algorithm is used to process data to improve detection rate and reduce noise. Different models are trained by different data features to detect four attack types, namely Probe, DDOS, R2L and U2R. The optimal dimension of PCA is automatically obtained by calculating the contribution rate M of feature, which improves the traditional method that requires frequent input of K value. The model is trained by using OCSVM algorithm based on RBF core, and the disadvantage of poor classification effect of OCSVM algorithm is eliminated through improved multi-layer detection mechanism. Finally, the KDDCUP99 data set is used for experimental verification. The results show that the proposed method has more advantages than the traditional detection method.
FrameNet-assisted Noun Compound Interpretation

Given a noun compound (NC), we address the problem of predicting the appropriate semantic label linking the constituents of the NC. This problem is called Noun Compound Interpretation (NCI) . We use FrameNet as a semantic label repository. For example, given the noun compound ( board approval ), we predict the frame ( D ENY OR GRANT PERMISSION , as per FrameNet) as appropriate and the semantic role of the modiﬁer word ( A UTHORITY ) as the semantic label linking board and approval ; the resulting label is D ENY OR GRANT PERMISSION : A UTHORITY . Our semantic label repository is very large ( ≈ 11k labels) compared to the NC data available for training (approx 1900). Thus, learning in this case, especially for unseen semantic labels, is hard. We propose to solve this problem by predicting semantic labels in a continuous label embedding space , which is novel. This embedding space is created by learning label embeddings using the FrameNet data. The embeddings are then used to train two separate models – one for predicting Frames and the other for FEs. As the label embedding space captures the semantics of the labels, using these embeddings enables generalizing well on unseen labels, thus achieving zero-shot learning. Our preliminary investigations show that the proposed approach performs well for unseen labels, achieving 5% and 2% points improvements over baselines for the frame and FE prediction, respectively. The study shows the promise of the use of continuous space embeddings for noun compound interpretation and points to the need for further investigation.
DeepReflect: Discovering Malicious Functionality through Binary Reconstruction

Deep learning has continued to show promising results for malware classiﬁcation. However, to identify key malicious behaviors, malware analysts are still tasked with reverse engineering unknown malware binaries using static analysis tools, which can take hours. Although machine learning can be used to help identify important parts of a binary, supervised approaches are impractical due to the expense of acquiring a sufﬁciently large labeled dataset. To increase the productivity of static (or manual) reverse engineering, we propose D EEP R EFLECT : a tool for localizing and identifying malware components within a malicious binary. To localize malware components, we use an unsupervised deep neural network in a novel way, and classify the components through a semi-supervised cluster analysis, where analysts incrementally provide labels during their daily work ﬂow. The tool is practical since it requires no data labeling to train the localization model, and minimal/noninvasive labeling to train the classiﬁer incrementally. In our evaluation with ﬁve malware analysts on over 26k malware samples, we found that D EEP R EFLECT reduces the numberoffunctionsthatananalystneedstoreverseengineerby85%onaverage.Ourapproachalsodetects80%ofthemalware componentscomparedto43%whenusingasignature-based tool(CAPA). Furthermore,D EEP R EFLECT performs better with our proposed autoencoder than SHAP (an AI explanation tool). This is signiﬁcant because SHAP, a state-of-the-art method, requires a labeled dataset and autoencoders do not.
Conservative Management of Traumatic Brown-Séquard Syndrome: A Case Report

Patient: Male, 33-year-old Final Diagnosis: Traumatic Brown-Séquard syndrome Symptoms: Bilateral lower limb weakness • contralateral (right) hypoesthesia from the level of the nipple below • knee and ankle jerks both were 2 on the right side and 0 on the left Medication: — Clinical Procedure: Magnetic resonance imaging (MRI) of the cervical and thoracic spine • whole-body computed tomography (CT) Specialty: Surgery Objective: Unusual clinical course Background: Traumatic spinal cord injuries are quite common; however, a rare form of incomplete spinal cord injury is Brown-Séquard syndrome. Brown-Séquard syndrome is defined by the National Institute of Neurological Disorders and Strokes as “a rare neurological condition characterized by a lesion in the spinal cord which results in weakness or paralysis (hemiparaplegia) on one side of the body and a loss of sensation (hemianesthesia) on the opposite side. ” Case Report: A 33-year-old man was brought to the Emergency Department by Saudi Red Crescent with multiple stab wounds on the left upper thoracic and lower cervical regions. He was tachycardic, but otherwise vitally stable. His Glasgow Coma Scale score was 15. The patient presented with bilateral lower limb weakness, more on the ipsilateral (left) side, and contralateral (right) hypoesthesia from the level of the nipple below. Cervical and thoracic magnetic resonance imaging revealed ligamentous injury defect at the posterior dura and indicating a dural tear with minor cerebrospinal fluid leak. Focal hyperintense signal intensity was noted on the left side of the spinal cord, representing contusion. The patient was managed conservatively with daily physical therapy. Strength had improved substantially by the time of discharge and sensation was improving. Conclusions: Brown-Séquard syndrome is associated with good prognosis. These patients require a multidisciplinary approach because it provides the best chance of recovery to pre-injury status. These injuries may cause disastrous neurological deficits; therefore, preventive strategies should be designated to decrease the incidence of such injuries.
A Systematic Review of API Evolution Literature

Recent software advances have led to an expansion of the development and usage of application programming interfaces (APIs). From millions of Android packages (APKs) available on Google Store to millions of open-source packages available in Maven, PyPI, and npm, APIs have become an integral part of software development. Like any software artifact, software APIs evolve and suffer from this evolution. Prior research has uncovered many challenges to the development, usage, and evolution of APIs. While some challenges have been studied and solved, many remain. These challenges are scattered in the literature, which hides advances and cloaks the remaining challenges. In this systematic literature review on APIs and API evolution, we uncover and describe publication trends and trending topics. We compile common research goals, evaluation methods, metrics, and subjects. We summarize the current state-of-the-art and outline known existing challenges as well as new challenges uncovered during this review. We conclude that the main remaining challenges related to APIs and API evolution are (1) automatically identifying and leveraging factors that drive API changes, (2) creating and using uniform benchmarks for research evaluation, and (3) understanding the impact of API evolution on API developers and users with respect to various programming languages.
ORIENTATION AND SENSING BASED DRIVERS TO ENHANCE MARKETING PERFORMANCE OF INDONESIAN PHARMACEUTICAL SMES: MEDIATING ROLE OF MARKET PIONEERING

In the shadow of increased number of pharmaceutical small and medium sized enterprise in Indonesia, which has given rise to immense competition, management must constantly provide greater value in order to preserve a competitive position and market share. This study discovers how two noticeable market strategies such as market orientation and market pioneering influence a pharmaceutical SME marketing performance. Specifically, it was scrutinized how market pioneering mediates the interaction between market-oriented dimension and market performance. A questionnaire survey in a purposive sample of 423 top managers from pharmaceutical small and medium sized enterprises, data was analyzed by operating structural equation modeling, statistical analysis showed that proactive market orientation, responsive market orientation and market sensing capability are significantly related to marketing performance and are crucial to maintain firm performance. This study also spells out that market pioneering mediates orientation drivers (responsive, proactive orientation, sensing capability) and marketing performance. This paper is added in existing literature that provides delivers new insights for market orientation by exploring the inter connection of market performance and market pioneering. It provides broader understanding of market responsive proactivity. It facilitates managers in devising market-oriented strategies.
Increasing Health Insurance Coverage for Same-Sex Couples: The Roles of the ACA and Same-Sex Marriage

This paper examines the roles of the Affordable Care Act (ACA) and employer spousal coverage made possible by same-sex marriage in increasing health insurance coverage for same-sex couples in the United States. I use data from the American Community Survey in a difference-in-differences model on same-sex couples in ACA Medicaid expansion states to determine if people who did not have access to legal same-sex marriage at the time of the ACA had larger gains in insurance coverage postACA than those who already had access to marriage. I find a 1.8pp larger increase in Medicaid coverage and a 3.5pp larger increase in overall coverage for states that had not passed same-sex marriage before the main ACA implementation. These differences are the combined effects of the initial differential response to the ACA and the subsequent direct response to same-sex marriage passage in the post period. When I directly control for same-sex marriage passage, I find a 2.8pp larger increase in Medicaid and suggestive evidence for increased crowd-out of employer coverage in states without access to same-sex marriage at the time of the public insurance expansion. ∗University of California, San Diego. cswete@ucsd.edu. I would like to thank Kate Antonovics, Jeffrey Clemens, Julie Cullen, Itzik Fadlon, and the UCSD Applied Micro Seminar participants for excellent comments and feedback.
DEVELOPING COMMUNITY-BASED DRINKING WATER AND SANITATION MANAGEMENT MODULE IN PADANG PARIAMAN REGENCY – INDONESIA

One of the reasons for the low skills of the community-based water and Sanitation management group in Padang Pariaman Regency is the absence of an adequate training module to train the management groups concerned. This research aims at developing a community-based drinking water and sanitation facility management module in Padang Pariaman Regency using the methods of Analysis, Design, Develop, Implement, and Evaluate (ADDIE) model. It was found that 1) The module currently used does not have an instruction component for the facilitator, a worksheet key, an evaluation sheet, and an evaluation sheet key; 2) The development result module is valid with values 0.86 (very high); 3) Module development results are practical with a value of K = 0.87 (very high); and 4) Module development results are proven to significantly increase the knowledge of the management group with a sig value of 0.00 <0, 05. It is concluded that the developed module has fulfilled valid, practical, and effective criteria. The implications of the research results are: 1) The module can be used as a source and independent learning media for the management groups; 2) The use of module by the facilitator in mentoring and conducting training for the management group can be more effective; and 3) the management groups can improve their knowledge in carrying out their functions and roles related to the management of existing facilities. It is recommended that the central and provincial work units socialize the use of the module to facilitators throughout Indonesia, and the use of the module must follow the instructions and stages as presented in the module. Keyword—Developing, community, drinking water, sanitation, management module.
Learning rigid body dynamics for legged robots

Implementing torque controllers on legged robots exposes the fact that current models often do not fully capture the real dynamics. As a consequence, high feedback gains are required, performance suffers, and in the worst case, instabilities occur. Improving the accuracy of the equations of motion would increase the effectiveness of model-based controllers, state estimators, and dynamic motion planners.
THE EFFECT OF FIRING TEMPERATURE AND MOLARITY ON THE STRUCTURAL AND ELECTRICAL PROPERTIES OF NANO PARTICLES OFNICKEL- COBALT OXIDE

Nano particles of Nickel-Cobalt Oxide were prepared by chemical co-precipitation method by decomposition of their respective metal chlorides, sodium carbonate and Ethylene Diamene Tetra acetic Acid (EDTA). The metal chlorides were taken in different molar ratios but the total molarity remains the same as 0.5M. The influences of molarity on the formation of nano particles of NickelCobalt oxide were analyzed. The heat treatment of the ground precursor powders at their respective decomposition temperatures and beyond, resulted in the evolution of heat from the combustion of the residual carbonaceous material. This facilitated the reaction among the constituent metal ions and the formation of the desired oxide phase at low temperature. The average particle size was determined from X-ray diffraction line broadening and the diffractogram was compared with JCPDS data to identify the crystallographic phase of the particles. The shift in the d-value due to the nano nature was also analyzed. The effect of sintering on the particle size was also analyzed. The low temperature DC conductivity studies of the samples were carried out and it was seen that for Spinel structure, the activation energy was found to be 0.14552eV for the temperature range 100K-250K and 0.09030eV for the temperature range 250K-350K and for the cubic structure, it was found to be 0.5145eV for the temperature range 100K-245K and 0.5836eV for the range 245K-350K. The conductivity in the temperature range 250K-350K was much larger than in the range 100K-250K.
Female Directors and Corporate Social Performance of Listed Deposit Money Banks in Nigeria

The board objective of any company is the center force that determines its overall performance and the basis for evaluation of the strength and weakness of the company. The efficacy of a board depends largely on the traits and qualities of the personalities of the directors in the boards. This paper, therefore, examines the influence of female directors on corporate social performance of listed deposit money banks (DMBs) in Nigeria. The study comprises 14 banks listed on the Nigerian Stock Exchange at 31st December 2018. A sample size of 10 banks was selected using the Purposive Sampling Technique. Data were obtained from published annual reports of the selected banks for the period of 2010 to 2018. Descriptive statistics and Feasible Generalized Least Square regression (FGLS) were used to analyse data collected. The findings revealed that female board composition, female board expertise and female board independence had a statistically significant positive effect on corporate social responsibility expenditure. The implication of these findings is that the quality of female directors in companies’ boards has the potential to influence the corporate social expenditures of the firms. It also implies that the focus on female representation in the boards alone is inadequate; the quality of women selected must be also considered, to promote a better social performance.
Cognitive-inspired Perceptual Model for Driving Automation

—This paper proposes a neural network model for visual perception in the context of autonomous driving inspired by the human cognition. Despite the growing research aimed at implementing self-driving cars, no artiﬁcial system can claim to have reached the driving performance of humans, yet. We believe that the theories about the human mind and its neural organization may reveal precious insights on how to design a more reﬁned perceptual system for driving automation
Design and simulation of mechanical ventilator with self-inflating bag

The COVID-19 pandemic has resulted in serious shortages of ventilators around the world. A manual ventilator is a simple type of ventilator that is operated manually and uses a bag and mask to open the airway and generate significant ventilation. Bag-Mask Ventilation (BMV) is an essential part of manual ventilation, so it improves both airflow and respiration. In this work, a simplified mechanism of a mechanical ventilator with a BMV is proposed and designed for ventilation. The bag is operated by DC motor-driven rack and pinion mechanism. According to a control signal, the rack and pinion simultaneously compresses and decompress the bag. The computational fluid dynamics (CFD) is used to investigate the response of BMV for ventilation. The proposed design was simulated by using MATLAB for the tidal volume, it is similar to the manual ventilator of the BMV. It can be used for immediate medication with risk avoidance.
Survivalism: Systematic Analysis of Windows Malware Living-Off-The-Land

As malware detection algorithms and methods become more sophisticated, malware authors adopt equally sophisticated evasion mechanisms to defeat them. Anecdotal evidence claims Living-Off-The-Land (LotL) techniques are one of the major evasion techniques used in many malware attacks. These techniques leverage binaries already present in the system to conduct malicious actions. We present the first large-scale systematic investigation of the use of these techniques by malware on Windows systems.In this paper, we analyse how common the use of these native system binaries is across several malware datasets, containing a total of 31,805,549 samples. We identify an average 9.41% prevalence. Our results show that the use of LotL techniques is prolific, particularly in Advanced Persistent Threat (APT) malware samples where the prevalence is 26.26%, over twice that of commodity malware.To illustrate the evasive potential of LotL techniques, we test the usage of LotL techniques against several fully patched Windows systems in a local sandboxed environment and show that there is a generalised detection gap in 10 of the most popular anti-virus products.
SENTIMENT ANALYSIS ALGORITHMS AND ITS DIVERSE APPLICATIONS: A SURVEY

In recent years, the field of sentiment analysis, which collects, analyses, and aggregates sentiment from text, has received a lot of interest. As this topic grew, it spawned a slew of other subfields, each targeting a different degree of inquiry.This article focuses on an overview of the most recent developments in this sector. In sentiment analysis, classic machine learning methods are employed to handle categorization problems successfully.Deep learning has been employed in various disciplines to get successful outcomes as a result of its rapid expansion. This review summarizes a number of deep learning models that have been employed in sentiment analysis applications.This assessment includes looks at recently developed techniques and various semantic analysis applications.
Iron Isotope Fractionation during Skarn Cu-Fe Mineralization

Fe isotopes have been applied to the petrogenesis of ore deposits. However, the behavior of iron isotopes in the mineralization of porphyry-skarn deposits is still poorly understood. In this study, we report the Fe isotopes of ore mineral separations (magnetite, pyrite, chalcopyrite and pyrrhotite) from two different skarn deposits, i.e., the Tonglvshan Cu-Fe skarn deposit developed in an oxidized hydrothermal system and the Anqing Cu skarn deposit developed in a reduced hydrothermal system. In both deposits, the Fe isotopes of calculated equilibrium fluids are lighter than those of the intrusions responsible for the skarn and porphyry mineralization, corroborating the “light-Fe fluid” hypothesis. Interestingly, chalcopyrite in the oxidized-Tonglvshan skarn deposit has lighter Fe than chalcopyrite in the reduced-Anqing skarn deposit, which is best understood as the result of the prior precipitation of magnetite (heavy Fe) from the ore fluid in the oxidized-Tonglvshan systems and the prior precipitation of pyrrhotite (light Fe) from the ore fluid in the reduced-Anqing system. The δ56Fe for pyrite shows an inverse correlation with δ56Fe of magnetite in the Tonglvshan. In both deposits, the Fe isotope fractionation between chalcopyrite and pyrite is offset from the equilibrium line at 350 °C and lies between the FeS-chalcopyrite equilibrium line and pyrite-chalcopyrite equilibrium line at 350 °C. These observations are consistent with the FeS pathway towards pyrite formation. That is, Fe isotopes fractionation during pyrite formation depends on a path from the initial FeS-fluid equilibrium towards the pyrite-fluid equilibrium due to the increasing extent of Fe isotopic exchange with fluids. This finding, together with the data from other deposits, allows us to propose that the pathway effect of pyrite formation in the Porphyry-skarn deposit mineralization is the dominant mechanism that controls Fe isotope characteristics.
Is There a Va Advantage? Evidence from Dually Eligible Veterans

We study public versus private provision of health care for veterans aged 65 and older who may receive care provided by the US Department of Veterans Affairs (VA) and in private hospitals financed by Medicare. Utilizing the ambulance design of Doyle et al. (2015), we find that the VA reduces 28-day mortality by 46 percent (4.5 per centage points) and that these survival gains are persistent. The VA also reduces 28-day spending by 21 percent and delivers strikingly different reported services relative to private hospitals. We find suggestive evidence of complementarities between continuity of care, health IT, and integrated care. (JEL H51, I11, I12, I18, J14)