Miracle-dz/UniFAR-FTUs huggingface dataset:
APT Detection with Concolic Execution

Advanced persistent threat (APT) is sophisticated cyber-attack and has attracted lots of attention of security researchers in cybersecurity. Traditional defense measures based on signature matching such as antivirus products and IDS/IPS are insufficient to detect APT. Concolic(a portmanteau of CONCrete and SymbOLIC) execution is a hybrid software verification technique that performs symbolic execution which could be used for APT detection. In this paper, we proposed a framework of APT detection which includes network traffic redirection module, user agent, reconstruction module, dynamic analysis module and response module. With the help of concolic execution in dynamic analysis module, the framework could effectively and accurately detect APT attacks compared with current defense systems. We provide a detailed example to illustrate how the framework works against APT attacks especially passive attacks.
Analysis and Improvement of I/O Performance Degradation by Journaling in a Virtualized Environment

This paper analyzes the host cache effectiveness in full virtualization, particularly associated with journaling of guests. We observe that the journal access of guests degrades cache performance significantly due to the write-once access pattern and the frequent sync operations. To remedy this problem, we design and implement a novel caching policy, called PDC (Pollution Defensive Caching), that detects the journal accesses and prevents them from entering the host cache. The proposed PDC is implemented in QEMU-KVM 2.1 on Linux 4.14 and provides 3-32% performance improvement for various file and I/O benchmarks
A semantic model for axiomatic systems design

Design of large-scale engineering systems such as an automobile, satellite, or airplane is a process to satisfy requirements by making various decisions. Design axioms provide system designers with a theoretical background to make right decisions. However, the axiomatic systems design is still hard to be implemented in the real word due to its informal representation for both the human and machine, and few researches focus on formalizing concepts of this process. In order to define axiomatic systems design models to be both user-understandable and machine-readable, this paper combines axiomatic design process with the Semantic Web technology and proposes an axiomatic design semantic representation model, called axiomatic design ontology, which organizes customers’ requirements, functional requirements, design parameters, and design solutions. The class of concepts elements and their semantic relationships are defined by the Web Ontology Language (OWL2). Rules for identifying functional couplings (the Independence Axiom) and selecting the optimal design solution (the Information Axiom) are formally represented and encoded with the Semantic Web Rule Language, which enhances the reasoning capability of the axiomatic design ontology. A framework for capturing systems design semantic information based on the axiomatic design ontology, and aligning it with domain-specific ontologies according to the semantic mapping approach has been developed, by which elaborated design information is captured and shared. Finally, a case study of systems design of a satellite solar wing subsystem is given to demonstrate the proposed axiomatic design ontology-based systems design approach.
Guardians and Actions" Linguistic for Robust, Distributed Programs

An overview is presented of an integrated programming language and system designed to support the construction and maintenance of distributed programs: programs in which modules reside and execute at communicating, but geographically distinct, nodes. The language is intended to support a class of applications concerned with the manipulation and preservation of long-lived, on-line, distributed data. The language addresses the writing of robust programs that survive hardware failures without loss of distributed information and that provide highly concurrent access to that information while preserving its consistency. Several new linguistic constructs are provided; among them are atomic actions, and modules called guardians that survive node failures.
Reuse efficiency in urban microcellular networks

We study how efficiently radio channel resources can be reused in urban microcellular networks (rectilinear street environments). Compared with conventional cellular networks, this kind of microcellular system introduces a markedly different propagation environment, characterized by a mix of strong line-of-sight (LOS) propagation and much weaker non-LOS propagation. We propose guidelines for site layout and reuse planning in such microcellular networks, and present numerical results showing the influences of frequency, cell size, link quality requirements, and shadow fading statistics on the reuse efficiency. For 900 MHz systems, orthogonal multiple access schemes (e.g., time division), and a typical set of system parameters, we estimate that the reuse efficiency in urban microcellular networks could be up to 50% higher than that in conventional cellular networks with 3-sector antennas.
Touch screen technology in the first three years

Sara Baumgarten Touch Screen Technology in the First Three Years There has long been debate about the use of screen technology with young children, which has been renewed with the introduction of touch screen technologies like the iPad. The novelty of this technology means that there has thus far been limited research on the matter, especially in regard to how infants and toddlers may benefit or miss out by playing with these devices. The first part of this paper reviews the literature currently available, looking at previous research about television viewing as well as emerging research about touch screens. The second part takes observation of three toddlers, ages 20-26 months, using iPads as well as playing with traditional toys and analyzes the differences in play and the developmental skills demonstrated by each.
Bengali Diphone Duration Modeling for Bengali Text to Speech Synthesis System

This paper elaborates the analysis and implementation of a durational model of diphone for Bengali Text To Speech. Our analysis focused on duration of diphone according to several categories of consonant. Here we have proposed and implemented a durational model of diphone based on pronunciation place of consonant. This durational model is convenient to any diphone based Bengali Text to Speech Synthesizer. We have implemented our proposed durational model of diphone on Bengali Text To Speech synthesis software “Subachan”. Outcomes of this implementation is satisfactory. We have enhanced the overall performance of “Subachan” successfully with new diphone set.
A computer model of chess memory

Chess research provides rich data for testing computational models of human memory. This paper presents a model which shares several common concepts with an earlier attempt (Simon & Gilmartin, 1973), but features several new attributes: dynamic short-term memory, recursive chunking, more sophisticated perceptual mechanisms and use of a retrieval structure (Chase & Ericsson, 1982). Simulations of data from three experiments are presented: 1) differential recall of random and game positions; 2) recall of several boards presented in short succession; 3) recall of positions modified by mirror image reflection about various axes. The model fits the data reasonably well, although some empirical phenomena are not captured by it. At a theoretical level, the conceptualization of the internal representation and its relation with the retrieval structure needs further refinement.
Usage of Simplified Fuzzy ARTMAP for improvement of classification performances

This study presents a simplified fuzzy ARTMAP (SFAM) for different classification applications. The proposed SFAM model is synergy of fuzzy logic and adaptive resonance theory (ART) neural networks. SFAM is supervised network consisting of two layers (Fuzzy ART and Inter ART) that build constant classification groups in answer to series of input patterns. Fuzzy ART layer takes a series of input patterns and relate them to output classes. Inter ART layer functions in such a way that it raises the vigilance parameter of fuzzy ART layer. By combining this two layers, SFAM is capable to perform classification very efficiently and giving very high performances. Lastly, the SFAM model is applied to different simulations. The simulation results obtained for the three different datasets: Iris, Wisconsin breast cancer and wine dataset prove that SFAM model has better performance results than other models for these classification applications.
Discovering pulsars with machine learning

Pulsars are magnetized and rapidly rotating neutron stars that emit a periodic, pulsed signal most often observed in the radio domain. They enable investigations of fundamental physics in extreme conditions, and truly unique high precision tests of Gravity when found orbiting a companion star. The most efficient way to discover new pulsars is to survey wide areas of the Galactic plane or even the entire sky using a radio telescope and search the recorded time series data for periodic signals using a Fourier transform. This generates up to millions of candidates, sets of diagnostic values and graphical plots each describing the signal from a potential new source; the overwhelming majority of them are unfortunately the manifestation of terrestrial interference, and differentiating them reliably from genuine pulsars is a subtle task that traditionally relies on visual inspection by an expert. Due to the ever increasing data volumes acquired by pulsar surveys, this approach is already unsustainable and human intervention needs to be removed without sacrificing discovery potential. In this thesis we present a pulsar candidate classifier named SPINN that uses an artificial neural network, a type of Machine Learning (ML) algorithm. While the idea is not new, the accuracy reached by previous implementations has arguably been insufficient, either missing discoveries or still leaving an excessive amount of spurious candidates to be rejected by a human operator. Here we delve into the inner workings of ML algorithms, and from general principles governing their use on any data problem we proceed to tackle the specificities of pulsar candidate classification. We attach particular importance on how to properly represent pulsar candidates as vectors of real-valued inputs (or features) to the algorithm. A detailed understanding of the entire pulsar searching process is helpful, if not necessary to design optimal features. We also went one step back and entirely rewrote the software responsible for producing the candidate plots, as their quality significantly impacts the accuracy of the classifier that rates them. Our classification system is tested on a recent pulsar survey observed with the Parkes radio telescope, and shown to reduce the amount of non-pulsar candidates to inspect by a factor of 1,000 while correctly identifying almost every known pulsar observation. A single person can now extract the value from the outputs of an entire pulsar survey in a matter of hours instead of years. More importantly, we discovered 21 new pulsars with SPINN, more than half of them in archival data previously searched and left behind due to the use of more rudimentary candidate selection tools. Among the new discoveries are the fastest spinning pulsar (P = 1.49 ms) in the Galactic plane and a possible transitional
Quantitative Definitions of Collaborative Research Fields in Science and Engineering

Practical methodology for categorizing collaborative disciplines or research in a quantitative manner is presented by developing a Correlation Matrix of Major Disciplines (CMMD) using bibliometric data collected between 2009 and 2014. First, 21 major disciplines in science and engineering are defined based on journal publication frequency. Second, major disciplines using a comparing discipline correlation matrix is created and correlation score using CMMD is calculated based on an analyzer function that is given to the matrix elements. Third, a correlation between the major disciplines and 14 research fields using CMMD is calculated for validation. Collaborative researches are classified into three groups by partially accepting the definition of pluri-discipline from peer review manual, European Science Foundation, inner-discipline, inter-discipline and cross-discipline. Applying simple categorization criteria identifies three groups of collaborative research and also those results can be visualized. Overall, the proposed methodology supports the categorization for each research field.
Smart Collection and Storage Method for Network Traffic Data

Abstract : Captured network data enables an organization to perform routine tasks such as network situational awareness and incident response to security alerts. The process of capturing, storing, and evaluating network traffic as part of monitoring is an increasingly complex and critical problem. With high-speed networks and ever-increasing network traffic volumes, full-packet traffic capture solutions can require petabytes of storage for a single day. The capacity needed to store full-packet captures for a time frame that permits the needed analysis is unattainable for many organizations. A tiered network storage solution, which stores only the most critical or effective types of traffic in full-packet captures and the rest as summary data, can help organizations mitigate the storage issues while providing the detailed information they need. This report discusses considerations and decisions to be made when designing a tiered network data storage solution. It includes a method, based on a cost-effectiveness model, that can help organizations decide what types of network traffic to store at each storage tier. The report also uses real-world network measurements to show how storage requirements change based on what traffic is stored in which storage tier.
Equalization in coherent lightwave systems using a fractionally-spaced equalizer

The performance of a fractionally spaced analog trapped delay line equalizer that has the advantages of being adaptive, being capable of equalizing other linear distortions such as polarization dispersion and nonideal receiver response, and eliminating chromatic dispersion over any distance if a sufficient number of taps are used is discussed. It is shown how this equalizer can be implemented at intermediate frequencies (IF) and at baseband (for homodyne detection). Results show that an N-tap equalizer increases the maximum bit rate distance, B/sup 2/L, approximately (N-1)/2-fold (e.g., a threefold increase in distance with a seven-tap equalizer). <<ETX>>
Current sensing for built-in testing of CMOS circuits

Built-in current (BIC) testing involves the monitoring of power bus currents in a VLSI circuit, as a means of detecting processing defects in the circuit. The design and performance of a prototype BIC sensor for static CMOS are discussed. It has been demonstrated that a fully-operational BIC sensor can be designed using a standard CMOS process. The presented design met all basic requirements: it was small, it caused only a small degradation of the performance of the monitored module, and it provided sufficient current resolution. The main disadvantage of the described design, however, was a substrate current caused by the structure of the bipolar transistor. <<ETX>>
Research in Complex Event of Intelligent Logistics System’s Warehousing and Storage Activities

Complex event refers to many fields, such as finance, telecommunications, banking, automotive, and so on. Especially, it has an advantage of dealing with real-time data stream. However, as the gradually mature of IOT, there being a lot of real-time data stream problem that are difficult to be solved. The research we study is how to tackle these urgent and complicated problems with Complex Event application that oriented Intelligent logistics system and Networking Middleware.
A study on the detection of a pedestrian holding an umbrella with a Selective DPM

Abstract In recent years, pedestrian detection from an in-vehicle camera has been attracting interest. However, in the case of a raining situation, there is a problem that the detection accuracy decreases because the head of a pedestrian tends to be occluded by an umbrella. In this report, as a variation of the deformable part models (DPM) which is widely used in the field of object recognition, we propose “Selective DPM” which selectively chooses the original part filters and additional part filters trained independently. In the detection of a pedestrian holding an umbrella, the selection of head and umbrella parts will make pedestrian detection more robust to the occlusion. We conducted experiments to evaluate the performance of the proposed method. As a result, pedestrian detection with the Selective DPM achieved high detection accuracy in raining situations, compared with the detection by conventional DPM. Moreover, we confirmed that it does not affect the pedestrian detection accuracy in fine weather.
Mitigation of common-mode voltage in matrix converter

This paper presents a new modulation scheme for matrix converters. With the proposed method, the peak common mode voltage is reduced to 1/√3 of the input phase voltage amplitude; at least 2/3 reduction in the high order harmonics and 1/3 in RMS value are realised. Indirect space vector modulation is adopted and modified. Four active voltage vectors in the three-dimensional space are utilised to generate the desired output voltage, with reduced common mode voltage. The switching period is full filled and no zero states are implemented. Comparisons of different modulation techniques are made. Simulation results are provided to demonstrate the superior performance of the proposed scheme over conventional modulation techniques.
Android APK on-the-fly tampering

The Android operating system is widely deployed and relied upon by both providers and users of various applications. These applications get frequently downloaded from other sources than just Google Play. This makes Android and its application treatment a popular target for attackers. We first present an automated offline attack injecting a previously prepared code to a previously unseen Android application installation file (APK) in an automatic manner. Moreover, we present a novel transparent on-the-fly extension of our attack when a proxy server performs code injection during a new APK download.
Decoupled extended Kalman filter training of feedforward layered networks

Presents a training algorithm for feedforward layered networks based on a decoupled extended Kalman filter (DEKF). The authors present an artificial process noise extension to DEKF that increases its convergence rate and assists in the avoidance of local minima. Computationally efficient formulations for two particularly natural and useful cases of DEKF are given. Through a series of pattern classification and function approximation experiments, three members of DEKF are compared with one another and with standard backpropagation (SBP). These studies demonstrate that the judicious grouping of weights along with the use of artificial process noise in DEKF result in input-output mapping performance that is comparable to the global extended Kalman algorithm, and is often superior to SBP, while requiring significantly fewer presentations of training data than SBP and less overall training time than either of these procedures. <<ETX>>
Exploiting Higher-level Semantic Information for the Opinion-oriented Summarization of Blogs

Together with the growth of the Web 2.0, people have started more and more to communicate, share ideas and comment in blogs, social networks, forums and review sites. Within this context, new and suitable techniques must be developed for the automatic treatment of the large volume of subjective data, to appropriately summarize the arguments presented therein (e.g. as "in favor" and "against"). This article assesses the impact of exploiting higher-level semantic information such as named entities and IS-A relationships for the automatic summarization of positive and negative opinions in blog threads. We first run a sentiment analyzer (with and without topic detection) and subsequently a summarizer based on a framework drawing on Latent Semantic Analysis. Further on, we employ an annotated corpus and the standard ROUGE scorer to automatically evaluate our approach. We compare the results obtained using different system configurations and discuss the issues involved, proposing a suitable method for tackling this scenario.
An Energy-efficient Mobile Routing Algorithm in Wireless Sensor Network

In order to extend the lifetime of wireless sensor network and avoid network premature invalidation caused by local emergency, this paper proposes an energy-efficient mobile routing algorithm (MREEMRP). The network based on the MREEMRP is divided into several square virtual grids to reduce energy consumption, and the cluster head is selected according to the residual energy of nodes and the weighted sum of coordinate distance between a node and the cluster barycenter. The sink node receives data from the cluster head by controllable moving scheduling strategy, and relay nodes with unlimited energy are introduces to extend the network lifetime, and serve as information transmitting large area. On this basis, the simulation is carried out and the results are compared with the MSEERP algorithm without relay nodes. The analysis shows that the proposed algorithm is superior to the MSEERP algorithm from the aspects of total energy consumption of the network, active nodes number and data amount that the gathering node receives.
Cloud Computing Survey

Since the concept of cloud computing was proposed in 2006, cloud computing has been considered as the technology that probably drives the next-generation Internet revolution and rapidly becomes the hottest topic in the field of IT. The paper synthetically introduces cloud computing techniques, including the currently non-uniform definition and the characteristics of cloud computing; The paper also introduces the core techniques of cloud computing, such as data management techniques, data storage techniques, programming model and virtualization techniques. Then the 4-tie overall technique framework of general cloud computing is talked about. Finally, the paper talks about the obstacles and opportunities.
Block Scheduling in the Secondary Arena: Perceptions from the Inside.

Several studies have found that an inordinate amount of potential instructional time is lost in the American secondary school classroom. This paper briefly overviews the history and types of block scheduling in secondary schools and presents findings of a study that examined the perceptions of administrators and teachers in two large eastern Tennessee high scilools that implemented block scheduling. The schools changed from a traditional six-period school day to a four-block school day, in which students took four 90-minute classes daily for 90 days. Data were gathered by a survey of 238 teachers and 10 administrators, which yielded response rates of 86 and 60 percent, respectively. Interviews were also conducted with six teachers and four administrators. Most of the teachers and all of the administrators agreed that the staff was adequately prepared for the transition; the staff required more preparation time; and the staff used a wider variety of instructional delivery approaches. Administrators 'and teachers did not want to abandon the four-by-four block schedule and return to the traditional schedule. Two tables and a copy of the questionnaire are included. (Contains 13 references.) (LMI) *********************************************************************** Reproductions supplied by EDRS are te best that can be made from the original document. ***********************************************************************