Miracle-dz/UniFAR-FTUs huggingface dataset:
Towards end-to-end Continuous Monitoring of Compliance Status Across Multiple Requirements

Monitoring compliance status by an organization has been historically difficult due to the growing number of compliance requirements being imposed by various standards, frameworks, and regulatory requirements. Existing practices by organizations even with the assistance of security tools and appliances is mostly manual in nature as there is still a need for a human expert to interpret and map the reports generated by various solutions to actual requirements as stated in various compliance documents. As the number of requirements increases, this process is becoming either too costly or impractical to manage by the organization. Aside from the numerous requirements, multiple of these documents actually overlap in terms of domains and actual requirements. However, since current tools do not directly map and highlight overlaps as well as generate detailed gap reports, an organization would perform compliance activities redundantly across multiple requirements thereby increasing cost as well. In this paper, we present an approach that attempts to provide an end-to-end solution from compliance document requirements to actual verification and validation of implementation for audit purposes with the intention of automating compliance status monitoring as well as providing the ability to have continuous compliance monitoring as well as reducing the redundant efforts that an organization embarks on for multiple compliance requirements. This research thru enhancing existing security ontologies to model compliance documents and applying information extraction practices would allow for overlapping requirements to be identified and gaps to be clearly explained to the organization. Thru the use of secure systems development lifecycle, and heuristics the research also provide a mechanism to automate the technical validation of compliance statuses thereby allowing for continuous monitoring as well as mapping to the enhanced ontology to allow reusability via conceptual mapping of multiple standards and requirements. Practices such as unit testing and continuous integration from secure systems development life cycle are incorporated to allow for flexibility of the automation process while at the same time using it to support the mapping between compliance requirements.
Nature grasping by a cable-driven under-actuated anthropomorphic robotic hand

Human hand is the best sample for humanoid robotic hand and a nature grasping is the final target that most robotic hands are pursuing. Many prior researches had been done in virtual and real for simulation the human grasping. Unfortunately, there is no perfect solution to duplicate the nature grasping of human. The main difficulty comes from three points. 1. How to 3D modelling and fabricate the real hand. 2. How actuated the robotic hand as real hand. 3. How to grasp objects in different shapes like human hand. To deal with these three problems and further to provide a partial solution for duplicate human grasping, this paper introduces our method to solve these problems from robotic hand design, fabrication, actuation and grasping plan. Our modelling progress takes only around 12 minutes that include 10 minutes of 3D scanning of a real human hand and two minutes for changing the scanned model to an articulated model by running our algorithm. Our grasping plan is based on the sampled trajectory and easy to implement for grasping different objects. Followed these steps, a seven DOF robotic hand is created and tested in the experiments.
Management of Gallstone-Induced Acute Pancreatitis in Pregnancy: A Tertiary-Center Experience

Objectives: Gallbladder stones are the most frequently reported etiology of acute pancreatitis in pregnancy and are often diagnosed in the third trimester. This condition is associated with both mother and infant morbidity and mortality, and its treatment remains controversial. Methods: Relevant patient data between September 2010 and April 2017 from the Kanuni Sultan Suleyman Training and Research Hospital were analyzed regarding etiology (of gallstone pancreatitis), trimester of pregnancy, diagnostic tools, pancreatitis stage, clinical status, medical treatment, surgical interventions, and pregnancy status. Results: We included 68 patients recorded with acute pancreatitis due to biliary gallstones. Pancreatitis symptoms developed in most (n=38) (55.8%) patients during the third trimester. Of 24 patients who had their first episode of pancreatitis in the first trimester of pregnancy, 12 (50%) were readmitted due to recurrence. Seven (11.3%) patients whose Ranson scale score was 3 underwent computed tomography evaluation. The number of patients with acute cholecystitis with pancreatitis was 5 (7.3%), whereas the number of patients with choledocholithiasis was 4 (5.8%). Sphincterotomy with endoscopic retrograde cholangiopancreatography was performed in 2 (2.9%) patients. Laparoscopic cholecystectomy was performed in 9 (13.2%) patients during pregnancy. No fetal and maternal morbidity and mortality was found in all periods. Conclusion: Developments in supportive care, wide-spread use of imaging methods, and a multidisciplinary approach with better antenatal care of pregnant patients with acute pancreatitis can help prevent fetal and maternal morbidity and mortality in such cases. Early laparoscopic cholecystectomy should be considered especially in pregnant patients with acute pancreatitis due to gallstones in the first trimester.
Approximate simulation model for analysis and optimization in engineering system design

Computational support of the engineering design process routinely requires mathematical models of behavior to inform designers of the system response to external stimuli. However, designers also need to know the effect of the changes in design variable values on the system behavior. For large engineering systems, the conventional way of evaluating these effects by repetitive simulation of behavior for perturbed variables is impractical because of excessive cost and inadequate accuracy. An alternative is described based on recently developed system sensitivity analysis that is combined with extrapolation to form a model of design. This design model is complementary to the model of behavior and capable of direct simulation of the effects of design variable changes.
SISTEM DETEKSI MALICIOUS SOFTWARE BERBASIS SYSTEM CALL UNTUK KLASIFIKASI BARANG BUKTI DIGITAL MENGGUNAKAN METODE SUPPORT VECTOR MACHINE

Saat ini pertumbuhan sistem operasi android di perangkat smartphone berkembang dengan pesat. Dengan demikian platform android menjadi peluang target tindak kejahatan terhadap ancaman keamanan pengguna seperti Malicious Software atau Malware. Forensika Digital merupakan disiplin ilmu yang menerapkan investigasi dan identifikasi dalam menindak kejahatan digital. Salah satu tahapan utama dalam menginvestigasi tindak kejahatan yaitu mengumpulkan barang bukti digital. Menemukan barang bukti digital berupa malware pada sistem operasi android, dibutuhkan sebuah filter yang mendeteksi aktifitas malware yang terjadi dalam sistem. Namun yang menjadi masalah adalah berkembangnya kemampuan malware yang terus meningkat menimbulkan pendeteksian yang komplek. Umumnya solusi yang digunakan untuk mengatasi permasalahan ini yaitu dengan metode berbasis Signature. Namun hal ini dapat dengan mudah dimanfaatkan oleh malware yang mempunyai kemampuan polimorfik. Oleh Karena itu dibutuhkan pendeteksian malware secara dinamis untuk mengatasi masalah tersebut, salah satunya dengan cara mengamati penggunaan System Call. Namun, hal ini akan menjadi tidak efisien apabila pencarian malware diperiksa satu per satu dari banyaknya list aktifitas yang telah terekam. Oleh sebab itu metode Support Vector Machine (SVM) diterapkan untuk mengatasi permasalahan klasifikasi penentuan malware dan non malware. Berdasarkan permasalahan tersebut penelitian ini bertujuan untuk membuktikan bahwa system call dapat mendeteksi tingkah laku malware dan dapat mengklasifikasikan antar aplikasi malware dan non malware menggunakan metode Support Vector Machine pada platform sistem operasi Android.
Do plot studies generate “directionally” correct assessments of field-level phosphorus losses?

The National Phosphorus Research Project coordinated a tremendous amount of research at the plot scale to assess the influence of nutrient management on phosphorus (P) transport at the fields scale. The objective of this research was to determine if plot-scale rainfall simulations could be used to assess P transport from two fields that were managed using no-tillage or rotational tillage. Plots were constructed within the management zone but adjacent to monitored fields. Phosphorus transport at the field scale from throughout the growing season was compared to confidence limits established by the rainfall simulations, and a secondary analysis compared values from individual storms to the rainfall simulations. Soluble phosphorus (SP) loads from the no-tillage AS1 field (75 g ha−1 [0.066 lb ac−1]) were greater than from the rotationally tilled AS2 field (11g ha−1 [0.010 lb ac−1]) in 2004. Stratification of P in the uppermost portion of the soil profile is a known contributor to SP loading in long-term no-tillage fields. This trend was reversed in 2006 though, as SP loads were 16 g ha−1 (0.014 lb ac−1) from the AS1 field and 55 g ha−1 (0.049 lb ac−1) from the AS2 field. The greater loads from the AS2 field were due to greater discharge and a greater P application rate, compared to the AS1 field. Soluble P and total P loads were generally directionally correct, but the values obtained from plots were not necessarily similar to those observed at the field scale. Precipitation normalized loads for SP and total P were the most similar metric when comparing values from the plot to the field scale (i.e., more field scale values fell within the 95% confidence limits set by the plot data than the other metrics). Using cumulative field-scale data from each year or the mean values from storms by year did not appear to change the results of this study. This study would appear to confirm that the management decisions based on the National Phosphorus Research Project are likely to be sound and will probably lead to improved quality of runoff water from fields. Precipitation normalized loads appear to be a metric that may provide additional insight into P transport at various scales.
A Comparative Study of Sentiment-Based Graphs of Text Summaries

Sentiment included in a sentence can indicate whether a sentence may have positive, negative or neutral polarity. Polarity of the sentences is deemed important in text summarization, especially when summarizing narrative texts. This paper proposes to discover the patterns and sentiment scores of the summaries generated by established summarization methods: Luhn, Latent Semantic Analysis (LSA) and LexRank. This is done by conducting a study and comparison on the generated sentiment-based graphs of the summaries. A comparative study is conducted on the sentiment-based graph of the generated summaries with two different sentiment lexicons, namely SentiWordNet and VADER. The analysis is conducted by comparing the patterns of the sentiment-based graph and their sentiment scores as well. In the experiments conducted, there is an obvious pattern for the two sentiment lexicons. This implies that sentiment-based graph’s pattern and score are helpful in generating a compact summary. The analysis will alleviate future research on sentiment-based summarization and motivates a new method which can be considered as a graph-based summarization to extract a summary based on its sentiment score.
Juvenile growth response of European beech (Fagus sylvatica L.) to sudden change of climatic environment in SE European trials

Abstract: The aim of the study was to analyse provenance tests of beech situated close to the south-eastern continental limits of the species, in order to develop a response model of adaptation and plasticity of populations on evolutionary-ecological basis, following sudden climatic changes, as a result of transplanting. Modelling of juvenile height was performed with the help of ecodistance variables. The concept of transfer analysis and ecodistance is based on the hypothesis that phenotypic response to macroclimatic changes depends on the inherited adaptive potential of the population and on the magnitude and direction of experienced environmental change. In common garden experiments, the transfer to the planting site is interpreted as simulation of environmental change. The application of ecodistance of transfer for evaluating common garden experiments provides much needed quantitative information about response of tree populations to predicted climatic changes. The analysis of three field experiments of European beech in SE Europe indicates that macroclimatic adaptation patterns exist in juvenile growth and justify restrictions of use of reproductive material on the basis of evolutionary ecology. The presented model illustrates that response to climatic change is regionally divergent, depending on testing conditions and on hereditary traits. In particular, climatic warming in the central-northern part of the range may lead to production increase. However, under the stressful and uncertain conditions at the lower (xeric) limit of the species, growth depression and vitality loss are predicted. The deviating behaviour of higher elevation provenances support their separate treatment. The results may be utilised in climate change adaptation and mitigation policy in forestry and nature conservation, to revise rules for use of reproductive material and also for validating evolutionary and ecological hypotheses related to climate change effects.
Temperature and Fast Voltage On-Chip Monitoring using Low-Cost Digital Sensors

Power efficiency of embedded systems is nowadays a challenge to reach the increasing performance requirements while limiting the power consumption. Adaptive architecture allows to adapt the operating point of each power domain of a MultiProcessor System-on-Chip using independent Dynamic Voltage and Frequency Scaling techniques. Furthermore the optimal operating point of each power domain is dependent on the current variability state, thus it appears essential to monitor locally and on-line the environmental variability. To limit the power consumption and hardware overhead the monitoring system must have the lowest cost and the best possible efficiency. This paper presents a monitoring system based on two complementary methods to estimate dynamically the local conditions using low-cost digital sensors. A fast voltage drop monitoring method is performed every 0. 66μs and a low-cost calibration method is also proposed based on the Voltage-Temperature state of the platform at startup.
Simplifying virtual machine introspection using LibVMI.

Ensuring the security of a computer system requires the careful integration of many components. Key among these is security monitoring. Recent research trends show an increasing acceptance of external host-based monitoring techniques such as virtual machine introspection (VMI), a technique for viewing the runtime state of a virtual machine (VM). VMI’s primary drawbacks include performance and the semantic gap problem (i.e., understanding the low-level information available through VMI). This report describes work performed under an Early Career Laboratory Directed Research and Development (LDRD) project that aimed to address these two key challenges. Our results are promising, with significant performance improvements and a much more usable VMI programming environment. This work resulted in the creation and release of LibVMI, an open source software project based on the author’s previous work with the XenAccess library.
Current progress in searching for clinically useful biomarkers of blood–brain barrier damage following cerebral ischemia

Ischemic stroke is a leading cause of death and disability. Fear of intracranial hemorrhage (ICH) has been the primary reason for withholding tissue plasminogen activator (tPA) and thrombectomy, the only two widely accepted treatments for ischemic stroke. Thrombolysis treatment is only allowed in a very narrow time window (within 4.5–6 h). However, so far, other than the time window guideline, there is no reliable indicator available in the clinic to predict ICH before thrombolysis treatment. Recently, extensive research efforts have been devoted to the development of reliable indicators to predict ICH and safely guide the thrombolysis treatment. Accumulating evidence suggests that ischemic brain regions with a compromised blood–brain barrier (BBB) before tPA treatment develop ICH at the later time during thrombolytic reperfusion. Assessing BBB damage before thrombolysis could potentially help predict the risk of ICH after thrombolysis. This article reviews the literature reports on BBB damage biomarkers that have been developed in recent years, including biochemical markers such as BBB structural proteins, circulating brain microvascular endothelial cells, plasma albumin, and brain parenchyma proteins, as well as image markers such as magnetic resonance imaging assessment for BBB damage.
Performance of Artificial Neural Network and Particle Swarm Optimization Technique based Maximum Power Point Tracking for Photovoltaic System Under Different Environmental Conditions

Photovoltaic (PV) array may receive different levels of solar irradiance and temperature under different environmental conditions, such as partially shaded by clouds or nearby building. However, all PV systems have two major drawbacks: the efficiency of PV power generation is very low and the output power of a PV system is nonlinear, which depends closely on weather conditions, such as ambient temperature and the solar irradiance. Hence, tracking the maximum power of the PV arrays at real time is very important to increase the whole system performance. Multiple peak power points occur when PV module is under partially shaded conditions, which would significantly reduce the energy produced by PV without proper control. Therefore, a Maximum Power Point Tracking (MPPT) algorithm is used to extract maximum available PV power from the PV array. However, most of the conventional MPPT algorithms are incapable to detect global peak (GP) power point with the presence of several local peaks (LP). A hybrid Artificial Neural Network and Particle Swarm Optimization (ANN-PSO) algorithm is proposed in this report to detect the global peak power. A PV system which consists of PV array, DC-DC boost converter, a hybrid ANN-PSO Algorithm, and a resistive load, is simulated using MATLAB/Simulink. The simulation results are carried out, compared and discussed. The proposed algorithm should perform well to detect the Global Peak of the PV array under different environmental conditions.
Research on Massive MIMO Key Technology in 5G

The fifth generation mobile communication network (5G) has received extensive attention and a lot of research from global enterprises, research institutes and universities. massive MIMO technology is considered as an important technology in future 5G, mainly used to improve the spectrum utilization and channel capacity of communication system. This paper analyses in detail the standardization process of MIMO technology and the technical advantages of massive MIMO. It mainly applies scenarios, and then introduces from the perspective of channel measurement and channel modelling. It analyses the channel estimation technology, pre-coding technology and signal detection technology in massive MIMO system and makes a summary finally.
33 ans de synthèse de la parole à partir du texte : une promenade sonore (1968-2001)

Cet article presente un disque compact de 69 exemples sonores de synthese de parole. Des exemples de 25 systemes de synthese automatique a partir du texte, principalement en francais, sont decrits, avec 54 voix differentes. Dans une premiere partie, l'article presente des systemes anciens (de 1968 a 1992). La deuxieme partie contient des exemples lies aux articles de ce numero. La troisieme partie contient des exemples d'autres systemes contemporains. Ensuite, des parcours d'ecoute sont proposes au lecteur/auditeur, afin d'apprecier divers aspects de la synthese de parole: par types de synthetiseurs, sur le calcul de la prosodie, par type d'unites de synthese. Enfin, un texte commun a ete prononce par 20 voix de synthese differentes.
Music Therapists’ Experience with Resistance in an Inpatient Psychiatric Setting

This phenomenological research study examined music therapists’ experiences with resistance as it occurred with patients in the context of inpatient psychiatric care in the New York City area. While there are many definitions of resistance in the previously published literature on the subject, participants were asked to recount their experiences of resistance without reference to a specific definition: their responses are based on an individual interpretation of the phenomenon. While there are notable studies on music therapy and resistance, there have been few studies on resistance in the context of inpatient psychiatric care. The following research questions were addressed in this study: When music therapists encounter resistance in the inpatient psychiatric setting, what is it like for them? How do music therapists manage and utilize resistance in an inpatient psychiatric setting (musically and otherwise)? The method that was employed to examine the therapists’ experience consisted of four in-depth interviews conducted in person by the researcher. All interviews were audio-recorded, and transcribed to text. The resulting transcriptions were then subjected to editing and cross-case analysis, in which the researcher coded the data and identified 23 emerging themes. An essential description of the phenomenon was drawn. Some examples of the findings were the therapists’ descriptions of encountering resistance, the MUSIC THERAPISTS’ EXPERIENCE WITH RESISTANCE ii ways that they worked with their resistant patients, and the outcomes that they attributed to their strategies. The implications for the findings of this study may 1) provide students, music therapists, and clinicians in related fields with additional resources and insight into a process for effective music therapy practice, 2) inform students in these disciplines respective to clinical training, and 3) improve the quality of services to the clients who are served by music therapy and its related disciplines. MUSIC THERAPISTS’ EXPERIENCE WITH RESISTANCE iv MUSIC THERAPISTS’ EXPERIENCE WITH RESISTANCE in an INPATIENT PSYCHIATRIC SETTING
Semantic Knowledge Base in Support of Activity Recognition in Smart Home Environments

Activity recognition plays a major role in smart home technologies in providing services to users. One of the approaches to identify activity is through the use of knowledge-driven reasoning. This paper presents a framework of semantic activity recognition, which is used to support smart home systems to identify users’ activities based on the existing context. The framework consists of two main components: a semantic knowledge base and an activity recognition module. The knowledge base is represented using ontology and it is used to provide a semantic understanding of the environment in order to classify users’ patterns of activities. Experimental results show that the proposed approach can support the classification process and accurately infer users’ activities with the accuracy of 90.9%.