Miracle-dz/UniFAR-FTUs huggingface dataset:
Performance Prediction Method for UML Software Architecture and Its Automation

The requirement of software performance as an important part of the software quality requirements is very concerning.The traditional software development methods that focus on the software performance issues later in the development process will bring high risks and high costs.If the performance of software architecture can be predicted at the early phases of the development cycle,the performance bottlenecks can be found in advance,and the possible optimization also can be worked out.In this paper,a model-based UML software architectures performance prediction method is introduced.This method selects and uses case diagrams,activity diagrams and component diagrams,and extends them to UML SPT(schedulability,performance and time) model by introducing the stereotypes and tagged values.It then transforms these UML SPT models into queueing network model through an algorithm which can handle the activity diagram with both branch nodes and confluence nodes.At last,uses the analysis theory of frequency domain to solve queuing network model to derive the performance parameters and performance bottlenecks.At the same time,the design of an automatic performance analysis tool for UML software architecture is introduced,and an instance of performance prediction is given.
Malware Detection with Malware Images using Deep Learning Techniques

Driven by economic benefits, the number of malware attacks is increasing significantly on a daily basis. Malware Detection Systems (MDS) is the first line of defense against malicious attacks, thus it is important for malware detection systems to accurately and efficiently detect malware. Traditional MDS typically utilizes traditional machine learning algorithms that require feature selection and extraction, which are time-consuming and error-prone. Conventional deep learning based approaches typically use Recurrent Neural Network (RNN) which can be vulnerable to redundant API injection. Thus, we investigate the effectiveness of Convolutional Neural Networks (CNN) against redundant API injection. We designed a malware detection system that transforms malware files into image representations and classifies the image representation with CNN. The CNN is implemented with spatial pyramid pooling layers (SPP) to deal with varying size input. We evaluate the effectiveness of SPP and image color space (greyscale/RGB) by measuring the performance of our system on both unaltered data and adversarial data with redundant API injected. Results show that naive SPP implementation is impractical due to memory constraints and greyscale imaging is effective against redundant API injection.
Number : WUCSE-2014-53 2014 Inferring Memory Map Instructions

We describe the problem of inferring a set of memory map instructions from a reference trace, with the goal of minimizing the number of such instructions as well as the number of unreferenced but mapped storage locations. We prove the related decision problem NP-complete. We then present and compare the results of two heuristic approaches on some actual traces. Type of Report: MS Project Report Department of Computer Science & Engineering Washington University in St. Louis Campus Box 1045 St. Louis, MO 63130 ph: (314) 935-6160 Inferring Memory Map Instructions Paul T. Scheid, Ari J. Spilo, and Ron K. Cytron Washington University August 6, 2014
A Unique Case of Primary Hepatic CD30-Positive, CD15-Negative Classical Hodgkin’s Lymphoma Presenting as Fever of Unknown Origin and Acute Hepatic Failure

Hodgkin’s lymphoma is a B-cell lymphoproliferative neoplasm that commonly presents with lymphadenopathy and constitutional symptoms. Primary Hodgkin’s lymphoma of the liver without extrahepatic lymphadenopathy is rare, representing about 0.016% of all non-Hodgkin’s lymphoma and 0.4% of all extranodal lymphomas. Most primary hepatic lymphomas (PHL) are of the diffuse large B-cell histology. In a patient presenting with fever and acute hepatic failure in the absence of extrahepatic lymphadenopathy, the diagnosis of primary Hodgkin’s lymphoma should be entertained. To our knowledge, this is the first reported case of CD30-positive, CD15-negative primary hepatic classical Hodgkin’s
Calibration and Validation of the VISSIM Parameters-State of the Art Arlinda

As a stochastic, microscopic, time-step, behavior-based model with capabilities to provide application of programming interface (API) and simulation, VISSIM has become one of the most useful and reliable programs utilized by contemporary engineers and researchers in the processes of evaluation of control operations and strategies of transportation. In this paper are given 'state of the art' calibration and validation techniques of VISSIM parameters that derive from the need to accurately match the simulations results of the models with the observed field data. In this context, different practices of different traffic control operations that have been done so far in calibration and validation process are overviewed. For each one of them the aim of calibration, developed methodologies, manner in which are identified "best" parameters for calibration, calibration objective functions, criteria, optimization techniques, evaluation of modeling outputs are emphasized. Finally, a prescription of credibility and reliability of calibrated parameters to the related traffic conditions is given. Keywordstraffic, microscopic simulation, calibration, validation
German Works Councils Counter or Foster the Implementation of Digital Technologies ? First Evidence from the IAB-Establishment Panel

As works councils’ information, consultation and co-determination rights affect the decision process of the management, works councils play a key role in the implementation of digital technologies in establishments. However, previous research focuses on the potential of digital technologies to substitute for labor and its impact on labor market outcomes of workers. This paper adds the role of industrial relations to the existing literature by analyzing the impact of works councils on the implementation of digital technologies. Theoretically, the role of works councils in the digital transformation is ambiguous. Using establishment data from the IAB Establishment Survey of 2016 combined with individual employee data from the Federal Employment Agency and occupational level data about the physical job exposure, empirical evidence indicates an ambivalent position of works councils towards digital technologies. The sole existence of works councils is associated with statistically significant lower equipment levels with digital technologies. However, works councils seem to foster the equipment with digital technologies in those establishments, which employ a high share of workers who are conducting physical demanding job activities. Thus, this study highlights the importance of establishment-level workforce representation for the digital adoption process within Germany. *Corresponding author: Sabrina Genz, Institute for Employment Research, Nuremberg, Germany; and University of Erlangen-Nuremberg, Nuremberg, Germany, E-mail: sabrina.genz@iab.de Lutz Bellmann, Institute for Employment Research, Nuremberg, Germany; and University of Erlangen-Nuremberg, Nuremberg, Germany; and Institute of Labor Economics, Bonn, Germany, E-mail: lutz.bellmann@iab.de Britta Matthes, Institute for Employment Research, Nuremberg, Germany, E-mail: britta.matthes@iab.de Journal of Economics and Statistics 2019; 239(3): 523–564
A Controlled Environment Agriculture Greenhouse for the Caribbean Region

A prototype Controlled Environment Agriculture (CEA) greenhouse, designed to suit the climatic conditions of Trinidad and Tobago was constructed and tested alongside a non-controlled prototype greenhouse with natural ventilation. In the CEA greenhouse, fan and pad type evaporative cooling were used to reduce temperature; circulating air combined with natural ventilation to reduce the humidity and provide air movement. LED lights were used to extend day length and supplement photons delivered to the plants. The effect of these control measures, in the CEA greenhouse, was evaluated by measuring temperature and humidity variations. Plant growth parameters (plant height, stem diameter, and leaf surface area) were evaluated for the two greenhouses. The mean saturation effectiveness of the coconut fibre cooling pad material used in the evaporative cooler was found to be 25.3%. While, the temperature and relative humidity in the non-controlled greenhouse were higher; those in the CEA greenhouse were lower than the ambient temperature. The CEA greenhouse had significantly higher growth rates in all plant growth parameters (about two and a half times on the average) than the noncontrolled greenhouse. The combination of blue LED light, evaporative cooling, and air circulation fans coupled with natural ventilation resulted in a significant increase in plant growth rates in the CEA greenhouse compared to the greenhouse with only natural ventilation as the weather control measure.
Study on Water Body Information Extraction from High Resolution Remote Sensing Image Based on Object-Oriented Method

Based on the software of eCognition and using the WorldView-2 image data of the southern region in Kunshan,this paper realized water body information extraction with object-oriented technology through choosing suitable scale and combining the features of image texture,shape and spectrum to construct rule set. Using the measured results to check the consistency of shape and area,the degree of accuracy can reach 89. 14%and 92. 06% respectively,which indicates using object-oriented classification technology to extract water body information from high resolution remote sensing image is reliable and practical.
Twitter Based Information Extraction

In the modern world of social media dominance, the microblogs like Twitter and Facebook are probably the best source of up-to-date information. The amount of information available on these platforms is huge, although most of it is unstructured and redundant which makes our task of extracting information from it much more challenging. This automatic extraction of information from noisy sources has opened up new opportunities for querying and analyzing data. This paper is a review of the research that has been done on extracting information like event dates [1] and classification of information from social networking platforms like Twitter. We present a brief study of the work which shows that extracting useful information from Twitter and other social media platforms is indeed feasible. We provide brief study about the extraction techniques applied by the applications based on this subject like the extraction tasks and the input exploited for extraction, the types of methods of extraction used and the type of output produced.
Research and Implementation of Access-control Model of Military Information System

For the complexity of access control mechanism of military information system,the concepts of domain role,role time-limit control,role conditional inheritance,role level and role group were introduced into the role management based on the available access control model.And task classification,task fraction,task time-based control and task template in the task management were studied according to the access control tactics,thus improving the task-role-based access control model. "Task" and "role" are referred to the centre of access control tactics to embody the access control thought involved the combination of active and passive access-visit,and the coexistence of static and dynamic authorization.Then a task-role-based access control model(M-TRBAC) was build to meet the demand of military information system.The formalized definition and the static and dynamic model design of M-TRBAC were given.
IMAGE SMOOTHENING AND MORPHOLOGICAL OPERATORS BASED JPEG COMPRESSION

Over the past decades the magnitude of transmitted information through internet has amplified exponentially. The considerable way to compress an image is provided by image compression. JPEG is the core triumphant still image compression for band width conservation. So images can be accumulated and transmitted earlier. Mathematical morphology is an inventive mathematical theory which can be used to route and appraise the images. In this paper, we intend an innovative JPEG compression algorithm based on fundamental morphological operators dilation and erosion and the other morphological operations which are the amalgamation of the two basic operations. The planned JPEG algorithms shows improved results compared to standard JPEG compressed data in terms of image quality metrics like PSNR, MSE and encoded bits. The planned JPEG algorithms augments speed while lessen memory necessities by reducing the encoded bits. The reconstructed images after decompression are at par with the original image data.
Context dependent initial/final acoustic modeling for continuous Chinese speech recognition

Acoustic modeling is very important for continuous Chinese speech recognition. The extended Initial/Final (XIF) set chosen as the basic speech recognition unit set to analyze the Chinese language characteristics outperformed the standard IF set. Decision tree-based state tying technology was used to construct the context dependent Initial/Final acoustic model (Tri-XIF model), with an appropriate question set design based on Chinese linguistic knowledge. Methods were developed to optimize the Tri-XIF modeling, including transcription refinement, question set extension, and model size reduction. Tests show that the Tri-XIF modeling is much better than either Tri-phone modeling or syllable modeling, with the syllable error rate reduced by 24.53% relative to the Tri-phone model and 41.65% relative to syllable model. More than 20% model size reduction was obtained with little performance deterioration using the methods in the Tri-XIF model.
OpenFlow-based Routing Mechanism for Call Session State Migration in the IMS

Mobile broadband and the shift to All-IP network lead the integration of mobile network services and over-the-top (OTT) services. Increasing and unpredictable traffic caused by this trend make it important for the IMS (IP multimedia subsystem), which is the call control system, to be flexible and reliable. With that goal, the authors have focused on call session state migration, which allows the IMS to distribute call sessions so as to minimize the number of servers and/or restore call sessions dependent on a halted server. This paper proposes a mechanism to enable call session state migration without modifying the standard procedure in the IMS. The proposed mechanism maps a SIP URI (uniform resource identifier), which identifies communication resources such as the user, to a flow routed by OpenFlow switches. When the call session state migrates, this mechanism changes the mapping for proper SIP message routing. This paper implements the proposal and shows that the proposal routing mechanism has insignificant impact on call session establishment unless the large number of call session states are migrated. Key-Words: IMS, SIP, Call session state migration, and OpenFlow.
Module 8

Objectives of the station • Plan and develop measures to assess the nutritional status of populations displaced by disasters, and to ensure optimal nutritional status in such contexts. • Implement feeding programs adapted to cultural characteristics and to the nutritional status of displaced populations. • Identify the clinical symptoms of the different types of malnutrition. • Determine the severity of malnutrition. • Calculate the anthropometric indexes in infants and older children. • Identify the clinical symptoms of iron deficiency anemia. • Identify the clinical symptoms of micronutrient deficiencies. • Give appropriate treatments for the different types and levels of malnutrition. • Give appropriate management to prevent and treat micronutrient deficiencies. • Classify the nutritional status according to the variables included in the IMCI guidelines.
THE ESSENTIAL SELF-ADJOINTNESS OF SCHRÖDINGER OPERATORS WITH OSCILLATING POTENTIALS

Let Ω be a domain in Rm with non-empty boundary and let H = −∆ + V be a Schrödinger operator defined on C∞ 0 (Ω) where V = V1 + V2 ∈ Lloc ∞ (Ω) is a real valued potential, V2 ∈ L∞(Ω) and V1(x) ≥ 1− μ2(Ω) d(x)2 . (1) Here d(x) is the Euclidean distance to the boundary of the domain and μ2(Ω) is the non-negative variational constant associated to the L2-Hardy inequality. In [1] it was shown that H is essentially self-adjoint and that the condition described by equation (1) is optimal on certain geometrically simple domains. In this paper investigate the essential self-adjointness of Schrödinger operators with potentials that oscillate around the critical limit described by equation (1).
Using Service-Dominant logic to examine hotels ’ intellectual capital assets : Deriving a disclosure instrument

Although service-dominant (S-D) logic is increasingly debated in the service marketing literature, little empirical research has translated S-D logic principles into practical processes. Research into intellectual capital (IC) in the hotel industry is also limited despite the significance of IC to creating value within the tourism sector. The authors created an IC disclosure instrument (95 itemsacross five categories) and applied it to the voluntary IC disclosures of 30 Asian hotel companies. Our instrument provides a practical interpretation of Grönroos and Gummerus‟ (2014) platform of cocreation wherein the firm‟s resources and assets support customers in their value co-creating activities.
Impact of gene polymorphisms located near ADAM 17 and additional SNP-SNP interaction on ovarian cancer risk in Chinese women

Objectives: The aim of this study was to investigate the impact of single nucleotide polymorphisms (SNPs) located near A disintegrin and metalloproteinase 17 (ADAM17) and additional SNP-SNP interaction on ovarian cancer (OC) risk. Methods: Four SNPs were detected by Taqman fluorescence probe, and ABI Prism 7000 software and allelic discrimination procedure was used for genotyping. Generalized multifactor dimensionality reduction (GMDR) model and logistic regression model was used to examine the SNP-SNP interaction on OC risk, odds ratio (OR) and 95% confident interval (95% CI) were calculated. Results: OC risk was higher in carriers of the rs11684747-G allele than those with AA genotype (AG + GG versus AA), adjusted OR (95% CI)=1.63 (1.29-2.19), and higher in carriers of the rs12692386-G allele than those with AA genotype (AG + GG versus AA), adjusted OR (95% CI)=1.72 (1.46 2.08). However, we did not find any significant association between rs1524668 and rs11689958 and OC risk before or after covariates adjustment. GMDR analysis indicated a significant two-locus model (p=0.0107) involving rs11684747 and rs12692386. Subjects with rs11684747-AG or GG and rs12692386-AG or GG genotype have the highest OC risk, compared to subjects with rs11684747-AA and rs12692386-AA genotype, OR (95% CI)=2.78 (1.79 3.98). Conclusions: rs11684747 and rs12692386 and additional combined effect of rs11684747-rs12692386 interaction were associated with increased OC risk.
HIGH ANGULAR RESOLUTION PLANEWAVE EXPANSION

First-order ambisonics suffers from low angular resolution and a small sweet spot, and decoding to many loudspeakers does not help. Parametric decoding methods solve this problem, at the risk of introducing audible artifacts. A method for high angular resolution planewave expansion (HARPEX) is proposed, which combines the spatial sharpness of parametric methods with the physical correctness of linear decoding without introducing audible artifacts. In a formal listening test, a decoder using this method to decode first-order B-format signals scores much higher than max rE decoding of the same signals, and similarly to max rE decoding of third-order versions of the same signals.
Kalman Filter based Neutral Axis tracking under varying temperature conditions

Structural Health Monitoring (SHM) is no longer a luxury but a necessity. Thus the search for an SHM strategy that is suitable for low level damage detection, is low cost, and is insensitive to ambient loading condition and environmental conditions is still on going. The use of Neutral Axis (NA) location as a damage sensitive feature has been proposed by few researchers. This paper thus helps to establish the robustness of NA, through the study of the temperature effects on its estimation. The paper presents results from an experiment on a simple composite beam, and shows that through advance mathematical tools, the effect of the temperature changes can be easily compensated and the NA as a damage indicator is robust and stable. The paper also presents the stability of NA under varying temperatures on a Finite Element (FE) model of a validated Nordtank NTK 500/41 wind turbine under simulated real damage conditions.
ATHENA: ASTRODYNAMICS TOOLBOX FOR HIGH-FIDELITY ERROR AND NAVIGATION ANALYSIS

In this paper the main components and architecture of the ATHENA toolbox are illustrated along with a number of examples of applications. ATHENA (Astrodynamics Toolbox for High-Fidelity Error and Navigation Analysis) is a toolbox for uncertainty propagation, guidance, navigation and control of single and multiple spacecraft with distributed architecture. This toolbox combines high fidelity dynamical and measurement models to advanced state estimation and error filtering techniques. ATHENA allows for the analysis of the coupled orbital and attitude dynamics during close proximity operations and docking with cooperative and non cooperative targets.
Cluster ensemble method for databases with mixed numeric and categorical values

Real-world intelligent databases always have mixed numeric and categorical values which are difficult to cluster.An ensemble-based mixed attribute cluster model was developed for mixed numeric and categorical databases based on the cluster ensemble method.The objective function and the methodology are described in the paper.The method has excellent scalability.Experimental results on real datasets show that the clustering accuracy is better than existing mixed numeric and categorical data clustering algorithms.
Anti-diabetic medications and risk of macular edema in patients with type 2 diabetes : a systemic review and meta-analysis

Several kinds of anti-diabetic medications (ADMs) are recommended for treatment of type 2 diabetes mellitus (T2DM). Association between use of ADMs and risk of macular edema is currently unclear. We reviewed the literature to quantify the effect of ADMs on the incidence of macular edema. A comprehensive search was conducted in MEDLINE, EMBASE, and Web of Science up through May 2016. The data of AMDs use and incidence of macular edema were pooled in a meta-analysis. A total of 13 (8 cohort studies, 4 case-control studies, and 1 randomizedcontrolled trial) studies were included in this meta-analysis. Among all of the ADMs, insulin use increased macular edema risk (OR = 2.65; 95% CI = 1.70-4.14) whereas oral ADM intake was probably not associated with macular edema incidence (OR = 1.77; 95% CI = 0.93-3.37). The use of thiazolinedione (OR = 2.19; 95% CI = 1.49-3.21) and meglitinide (OR = 2.20; 95% CI = 1.15-4.20) were risk factors for macular edema and the use of sulfonylureas (OR = 0.83; 95% CI = 0.69-0.99) might be a protective factor while metformin (OR = 0.94; 95% CI = 0.79-1.13) demonstrated no significant effect. Use of rosiglitazone (OR = 3.12; 95% CI = 1.30-7.49) affected the incidence of macular edema. Our results show that insulin, meglitinide, and rosiglitazon will increase the risk of macular edema while sulfonylureas shows a prospective effect. A series of well-designed studies with large samples are required to confirm our existing conclusions.