Query: An adaptive threshold deep learning method for fire and smoke detection

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Flame detection in video using hidden Markov models <=SEP=> This paper proposes a novel method to detect flames in video by processing the data generated by an ordinary camera monitoring a scene. In addition to ordinary motion and color clues, flame flicker process is also detected by using a hidden Markov model. Markov models representing the flame and flame colored ordinary moving objects are used to distinguish flame flicker process from motion of flame colored moving objects. Spatial color variations in flame are also evaluated by the same Markov models, as well. These clues are combined to reach a final decision. False alarms due to ordinary motion of flame colored moving objects are greatly reduced when compared to the existing video based fire detection systems.

An early fire-detection method based on image processing <=SEP=> The paper presents an early fire-alarm raising method based on video processing. The basic idea of the proposed of fire-detection is to adopt a RGB (red, green, blue) model based chromatic and disorder measurement for extracting fire-pixels and smoke-pixels. The decision function of fire-pixels is mainly deduced by the intensity and saturation of R component. The extracted fire-pixels will be verified if it is a real fire by both dynamics of growth and disorder, and further smoke. Based on iterative checking on the growing ratio of flames, a fire-alarm is given when the alarm-raising condition is met. Experimental results show that the developed technique can achieve fully automatic surveillance of fire accident with a lower false alarm rate and thus is very attractive for the important military, social security, commercial applications, and so on, at a general cost.

A Fire-Alarming Method Based on Video Processing <=SEP=> This paper presents a fire-alarming method based on video processing. We propose a system that uses color and motion information extracted from video sequences to detect fire. Flame can be recognized according to its color which is a primary element of fire images. Thus choosing a suitable color model is the key to detect flames from fire images. An effective fire detection criterion based on color model is proposed in this paper by intensive experiments and trainings. The detection criterion is used to make a raw localization of fire regions first. However, color alone is not enough for fire detection. To identify a real burning fire, in addition to chromatic features, dynamic features are usually adopted to distinguish other fire aliases. In this paper, both the growth of fire region and the invariability of flame are utilized to further detect the fire regions as a complement of the detection criterion. The effectiveness of the proposed fire-alarming method is demonstrated by the experiments implemented on a large number of scenes.

A System for Video Surveillance and Monitoring <=SEP=> The Robotics Institute at Carnegie Mellon University (CMU) and the Sarnoff Corporation are developing a system for autonomous Video Surveillance and Monitoring. The technical objective is to use multiple, cooperative video sensors to provide continuous coverage of people and vehicles in cluttered environments. This paper presents an overview of the system and significant results achieved to date.

Adaptive Background Mixture Models for Real-Time Tracking <=SEP=> A common method for real-time segmentation of moving regions in image sequences involves “background subtraction,” or thresholding the error between an estimate of the image without moving objects and the current image. The numerous approaches to this problem differ in the type of background model used and the procedure used to update the model. This paper discusses modeling each pixel as a mixture of Gaussians and using an on-line approximation to update the model. The Gaussian distributions of the adaptive mixture model are then evaluated to determine which are most likely to result from a background process. Each pixel is classified based on whether the Gaussian distribution which represents it most effectively is considered part of the background model. This results in a stable, real-time outdoor tracker which reliably deals with lighting changes, repetitive motions from clutter, and long-term scene changes. This system has been run almost continuously for 16 months, 24 hours a day, through rain and snow.

Antenna in package design for WLAN using MCM-D manufacturing technology <=SEP=> This paper introduces an antenna design based on MCM-D manufacturing technology to realize an antenna-integrated package for IEEE 802.11b/g application. Co-design guidelines are employed to include the parasitic effects caused by the integration of the antenna and the RF module. The loop antenna is located on the second layer of the MCM-D substrate. The antenna incorporates the capacitively feed strip which is fed by the coplanar waveguide (CPW). By the coupling feed technique, the size of the proposed antenna is only 3.8 mm × 4.7 mm over the WLAN band (2.4–2.484 GHz). Furthermore, the resonant frequency can be adjusted by tuning the length of the coupling strip. The results show that the coupling-fed loop antenna achieved a gain of 1.6 dBi and radiation efficiency of 85 % at 2.45 GHz in a very compact size (0.03 λ0 × 0.04 λ0). In addition, the occupied area of the antenna is very small (4.4%) compared to the overall area of the package; therefore, the proposed method is very useful for package antenna design. The detailed parameters studies are presented, which demonstrate the feasibility of the proposed method.

A study to evaluate the safety, tolerability, and efficacy of brodalumab in subjects with rheumatoid arthritis and an inadequate response to methotrexate. <=SEP=> OBJECTIVE
To evaluate the efficacy and safety of brodalumab, a human monoclonal antibody inhibitor of the interleukin 17 receptor, in subjects with rheumatoid arthritis (RA).


METHODS
Patients (n = 252) with inadequate response to methotrexate (MTX) were randomized to receive subcutaneous injections of brodalumab (70 mg, 140 mg, or 210 mg) or placebo. The primary endpoint was the American College of Rheumatology 50% response (ACR50) at Week 12.


RESULTS
Demographics and baseline characteristics were generally balanced among treatment groups. At Week 12, ACR50 occurred in 16% (70 mg), 16% (140 mg), 10% (210 mg), and 13% (placebo; all nonsignificant vs placebo) of subjects. No significant treatment effects were observed for the secondary endpoints, including ACR20, ACR70, and Disease Activity Score in 28 joints. Incidences of all adverse events (AE), including serious AE (SAE), were similar across treatment groups. A total of 7 subjects reported SAE during the study (2 in the placebo group and 5 in the brodalumab groups), none of which was treatment related. There was 1 death (cardiopulmonary failure) ∼1 week after the last dose in the 140 mg group.


CONCLUSION
Our study failed to find evidence of meaningful clinical efficacy with brodalumab treatment in subjects with RA who had an inadequate response to MTX. These preliminary results do not support further evaluation of brodalumab as a treatment for RA. Clinicaltrials.gov number: NCT00950989.

Relationship between procrastination and academic performance among a group of undergraduate dental students in India. <=SEP=> Procrastination, generally defined as a voluntary, irrational delay of behavior, is a prevalent phenomenon among college students throughout the world and occurs at alarmingly high rates. For this study, a survey was conducted of 209 second-, third-, and fourth-year undergraduate dental students of Bapuji Dental College and Hospital, Davangere, India, to identify the relationship between their level of procrastination and academic performance. A sixteen-item questionnaire was used to assess the level of procrastination among these students. Data related to their academic performance were also collected. Spearman's correlation coefficient test was used to assess the relationship between procrastination and academic performance. It showed a negative correlation of -0.63 with a significance level of p<0.01 (two-tailed test), indicating that students who showed high procrastination scores performed below average in their academics. In addition, analysis with the Mann-Whitney U test found a significant difference in procrastination scores between the two gender groups (p<0.05). Hence, among the Indian undergraduate dental students evaluated in this study, it appeared that individuals with above average and average academic performance had lower scores of procrastination and vice versa.

Detecting cyberbullying: query terms and techniques <=SEP=> In this paper we describe a close analysis of the language used in cyberbullying. We take as our corpus a collection of posts from Formspring.me. Formspring.me is a social networking site where users can ask questions of other users. It appeals primarily to teens and young adults and the cyberbullying content on the site is dense; between 7% and 14% of the posts we have analyzed contain cyberbullying content.
 The results presented in this article are two-fold. Our first experiments were designed to develop an understanding of both the specific words that are used by cyberbullies, and the context surrounding these words. We have identified the most commonly used cyberbullying terms, and have developed queries that can be used to detect cyberbullying content. Five of our queries achieve an average precision of 91.25% at rank 100.
 In our second set of experiments we extended this work by using a supervised machine learning approach for detecting cyberbullying. The machine learning experiments identify additional terms that are consistent with cyberbullying content, and identified an additional querying technique that was able to accurately assign scores to posts from Formspring.me. The posts with the highest scores are shown to have a high density of cyberbullying content.

The Magma Algebra System I: The User Language <=SEP=> Magma is a new software system for computational algebra, the design of which is based on the twin concepts of algebraic structure and morphism. The design is intended to provide a mathematically rigorous environment for computing with algebraic structures (groups, rings, fields, modules and algebras), geometric structures (varieties, special curves) and combinatorial structures (graphs, designs and codes). The philosophy underlying the design of Magma is based on concepts from Universal Algebra and Category Theory. Key ideas from these two areas provide the basis for a general scheme for the specification and representation of mathematical structures. The user language includes three important groups of constructors that realize the philosophy in syntactic terms: structure constructors, map constructors and set constructors. The utility of Magma as a mathematical tool derives from the combination of its language with an extensive kernel of highly efficient C implementations of the fundamental algorithms for most branches of computational algebra. In this paper we outline the philosophy of the Magma design and show how it may be used to develop an algebraic programming paradigm for language design. In a second paper we will show how our design philosophy allows us to realize natural computational “environments” for different branches of algebra. An early discussion of the design of Magma may be found in Butler and Cannon (1989, 1990). A terse overview of the language together with a discussion of some of the implementation issues may be found in Bosma et al. (1994).

Quadcopter control system <=SEP=> The paper presents two different types of approach for mathematical modeling of quadcopter kinematics and dynamics. The first one is based on the equations of classical mechanics and the other one is derived from Denavit-Hartenberg formalism and Lagrangian mechanics. The obtained models were used to design the control of the quadcopter motion on one rotation axis. The paper also offers some details of the physical and software implementation of the system on which tests have been made.

Recognition of Information Leakage of Computer via Conducted Emanations on the Power Line <=SEP=> The security problem of screen image leakage from a display unit has become serious with the rapid speed of signal transmission technology. This paper presents a novel investigation on the characteristics of the power line compromising channel. Moreover, a measurement system has been actually developed for the leakage signal analyzing and image reconstruction. In order to overcome the degradation of reconstructed motion images and enhance the reconstructed image quality, a multi-image blind deconvolution method was proposed and test experiments were carried out to verify the effectiveness of the multi-image blind deconvolution algorithm based on the conducted signal from the power line.

Out-of-domain FrameNet Semantic Role Labeling <=SEP=> Domain dependence of NLP systems is one of the major obstacles to their application in large-scale text analysis, also restricting the applicability of FrameNet semantic role labeling (SRL) systems. Yet, current FrameNet SRL systems are still only evaluated on a single in-domain test set. For the first time, we study the domain dependence of FrameNet SRL on a wide range of benchmark sets. We create a novel test set for FrameNet SRL based on user-generated web text and find that the major bottleneck for out-of-domain FrameNet SRL is the frame identification step. To address this problem, we develop a simple, yet efficient system based on distributed word representations. Our system closely approaches the state-of-the-art in-domain while outperforming the best available frame identification system out-of-domain. We publish our system and test data for research purposes.1

Marginal structural models for estimating effect modification. <=SEP=> PURPOSE
The use of marginal structural models (MSMs) to adjust for measured confounding factors is becoming increasingly common in observational studies. Here, we propose MSMs for estimating effect modification in observational cohort and case-control studies.


METHODS
MSMs for estimating effect modification were derived by the use of the potential outcome model. The proposed methods were applied to a cohort study and a case-control study.


RESULTS
In cohort studies, effect modification can be estimated by the application of a logistic MSM to individuals who experienced the event in question. In case-control studies, effect modification can be estimated by the ratio between the estimate from the model applied to case data and that applied to control data. The application of the model to real data from a cohort study indicated that the estimate from the proposed method was close to that from standard regression analysis. In a case-control study, the estimate from the proposed method may be biased.


CONCLUSIONS
Epidemiological researchers can use MSMs to estimate effect modification. In case-control studies, it should be determined whether the estimated effect modification is biased by applying a logistic MSM of control data.

S-Match: an algorithm and an implementation of semantic matching <=SEP=> We think of Match as an operator which takes two graph-like structures (e.g., conceptual hierarchies or ontologies) and produces a mapping between those nodes of the two graphs that correspond semantically to each other. Semantic matching is a novel approach where semantic correspondences are discovered by computing, and returning as a result, the semantic information implicitly or explicitly codified in the labels of nodes and arcs. In this paper we present an algorithm implementing semantic matching, and we discuss its implementation within the S-Match system. We also test S-Match against three state of the art matching systems. The results, though preliminary, look promising, in particular for what concerns precision and recall.

Behavioral Experiments for Assessing the Abstract Argumentation Semantics of Reinstatement <=SEP=> Argumentation is a very fertile area of research in Artificial Intelligence, and various semantics have been developed to predict when an argument can be accepted, depending on the abstract structure of its defeaters and defenders. When these semantics make conflicting predictions, theoretical arbitration typically relies on ad hoc examples and normative intuition about what prediction ought to be the correct one. We advocate a complementary, descriptive-experimental method, based on the collection of behavioral data about the way human reasoners handle these critical cases. We report two studies applying this method to the case of reinstatement (both in its simple and floating forms). Results speak for the cognitive plausibility of reinstatement and yet show that it does not yield the full expected recovery of the attacked argument. Furthermore, results show that floating reinstatement yields comparable effects to that of simple reinstatement, thus arguing in favor of preferred argumentation semantics, rather than grounded argumentation semantics. Besides their theoretical value for validating and inspiring argumentation semantics, these results have applied value for developing artificial agents meant to argue with human users.

An integrated framework for human activity recognition <=SEP=> This poster presents an integrated framework to enable using standard non-sequential machine learning tools for accurate multi-modal activity recognition. Our framework contains simple pre- and post-classification strategies such as class-imbalance correction on the learning data using structure preserving oversampling, leveraging the sequential nature of sensory data using smoothing of the predicted label sequence and classifier fusion, respectively, for improved performance. Through evaluation on recent publicly-available OPPORTUNITY activity datasets comprising of a large amount of multi-dimensional, continuous-valued sensory data, we show that our proposed strategies are effective in improving the performance over common techniques such as One Nearest Neighbor (1NN) and Support Vector Machines (SVM). Our framework also shows better performance over sequential probabilistic models, such as Conditional Random Field (CRF) and Hidden Markov Models (HMM) and when these models are used as meta-learners.

Honeypots : The Need of Network Security <=SEP=> Network forensics is basically used to detect attackers activity and to analyze their behavior. Data collection is the major task of network forensics and honeypots are used in network forensics to collect useful data. Honeypot is an exciting new technology with enormous potential for security communities. This review paper is based upon the introduction to honeypots, their importance in network security, types of honeypots, their advantages disadvantages and legal issues related with them. Research Paper also discuss about the shortcomings of intrusion detection system in a network security and how honeypots improve the security architecture of the organizational network. Furthermore, paper reveals about the different kind of honeypots their level of interaction and risks associated with them. Keywords—honeyd; honeypots; nmap; network forensics

Observations on periorbital and midface aging. <=SEP=> BACKGROUND
Many of the anatomical changes of facial aging are still poorly understood. This study looked at the aging process in individuals linearly over time, focusing on aspects of periorbital aging and the upper midface.


METHODS
The author compared photographs of patients' friends and relatives taken 10 to 50 years before with closely matched recent follow-up pictures. The best-matching old and recent pictures were equally sized and superimposed in the computer. The images were then assembled into GIF animations, which automate the fading of one image into the other and back again indefinitely.


RESULTS
The following findings were new to the author: (1) the border of the pigmented lid skin and thicker cheek skin (the lid-cheek junction) is remarkably stable in position over time, becoming more visible by contrast, not by vertical descent as is commonly assumed. (2) Orbicularis wrinkles on the cheek and moles and other markers on the upper midface were also stable over decades. (3) With aging, there can be a distinct change in the shape of the upper eyelid. The young upper lid frequently has a medially biased peak. The upper lid peak becomes more central in the older lid. This article addresses these three issues. No evidence was seen here for descent of the globe in the orbit.


CONCLUSIONS
There seems to be very little ptosis (inferior descent) of the lid-cheek junction or of the upper midface. These findings suggest that vertical descent of skin, and by association, subcutaneous tissue, is not necessarily a major component of aging in those areas. In addition, the arc of the upper lid changes shape in a characteristic way in some patients. Other known changes of the periorbital area are visualized.

The five-factor model of personality and managerial performance: validity gains through the use of 360 degree performance ratings. <=SEP=> This study investigated the usefulness of the five-factor model (FFM) of personality in predicting two aspects of managerial performance (task vs. contextual) assessed by utilizing the 360 degree performance rating system. The authors speculated that one reason for the low validity of the FFM might be the failure of single-source (e.g., supervisor) ratings to comprehensively capture the construct of managerial performance. The operational validity of personality was found to increase substantially (50%-74%) across all of the FFM personality traits when both peer and subordinate ratings were added to supervisor ratings according to the multitrait-multimethod approach. Furthermore, the authors responded to the recent calls to validate tests via a multivariate (e.g., multitrait-multimethod) approach by decomposing overall managerial performance into task and contextual performance criteria and by using multiple rating perspectives (sources). Overall, this study contributes to the evidence that personality may be even more useful in predicting managerial performance if the performance criteria are less deficient.

Towards a global participatory platform : democratising open data , complexity science and collective intelligence <=SEP=> The FuturICT project seeks to use the power of big data, analytic models grounded in complexity science, and the collective intelligence they yield for societal benefit. Accordingly, this paper argues that these new tools should not remain the preserve of restricted 110 The European Physical Journal Special Topics government, scientific or corporate élites, but be opened up for societal engagement and critique. To democratise such assets as a public good, requires a sustainable ecosystem enabling different kinds of stakeholder in society, including but not limited to, citizens and advocacy groups, school and university students, policy analysts, scientists, software developers, journalists and politicians. Our working name for envisioning a sociotechnical infrastructure capable of engaging such a wide constituency is the Global Participatory Platform (GPP). We consider what it means to develop a GPP at the different levels of data, models and deliberation, motivating a framework for different stakeholders to find their ecological niches at different levels within the system, serving the functions of (i) sensing the environment in order to pool data, (ii) mining the resulting data for patterns in order to model the past/present/future, and (iii) sharing and contesting possible interpretations of what those models might mean, and in a policy context, possible decisions. A research objective is also to apply the concepts and tools of complexity science and social science to the project’s own work. We therefore conceive the global participatory platform as a resilient, epistemic ecosystem, whose design will make it capable of selforganization and adaptation to a dynamic environment, and whose structure and contributions are themselves networks of stakeholders, challenges, issues, ideas and arguments whose structure and dynamics can be modelled and analysed.

Image Alignment and Stitching : A Tutorial 1 <=SEP=> This tutorial reviews image alignment and image stitching algorithms. Image alignment algorithms can discover the correspondence relationships among images with varying degrees of overlap. They are ideally suited for applications such as video stabilization, summarization, and the creation of panoramic mosaics. Image stitching algorithms take the alignment estimates produced by such registration algorithms and blend the images in a seamless manner, taking care to deal with potential problems such as blurring or ghosting caused by parallax and scene movement as well as varying image exposures. This tutorial reviews the basic motion models underlying alignment and stitching algorithms, describes effective direct (pixel-based) and feature-based alignment algorithms, and describes blending algorithms used to produce seamless mosaics. It closes with a discussion of open research problems in the area.

Neural Joint Model for Transition-based Chinese Syntactic Analysis <=SEP=> We present neural network-based joint models for Chinese word segmentation, POS tagging and dependency parsing. Our models are the first neural approaches for fully joint Chinese analysis that is known to prevent the error propagation problem of pipeline models. Although word embeddings play a key role in dependency parsing, they cannot be applied directly to the joint task in the previous work. To address this problem, we propose embeddings of character strings, in addition to words. Experiments show that our models outperform existing systems in Chinese word segmentation and POS tagging, and perform preferable accuracies in dependency parsing. We also explore bi-LSTM models with fewer features.

A 12.77-MHz 31 ppm/°C On-Chip RC Relaxation Oscillator With Digital Compensation Technique <=SEP=> The design of a 12.77-MHz on-chip RC relaxation oscillator with digital compensation technique is presented. To maintain the frequency stability versus temperature and supply voltage variations, loop delay tuning by a digital feedback loop is developed in this system. In order to generate an on-chip reference for digital calibration, a replica comparator is added. The on-chip relaxation oscillator is fabricated in 0.18-μm CMOS process. The measured output frequency variation is 31 ppm/°C across -30 to 120 °C temperature range after compensation. The frequency variation over the supply voltage from 0.6 V to 1.1 V is ±0.5%/V. The measured total power consumption is 56.2 μW at 0.9-V supply voltage when the digital compensation blocks are enabled. After digital compensation, the compensation blocks can be shutdown for power saving, and the main oscillator consumes only 12.8 μW.

A bias for posterior α-band power suppression versus enhancement during shifting versus maintenance of spatial attention <=SEP=> Voluntarily directing visual attention to a cued position in space leads to improved processing of forthcoming visual stimuli at the attended position, and attenuated processing of competing stimuli elsewhere, due to anticipatory tuning of visual cortex activity. In EEG, recent evidence points to a determining role of modulations of posterior alpha-band activity (8-14 Hz) in such anticipatory facilitation (alpha-power decreases) versus inhibition (alpha-power increases). Yet, while such alpha-modulations are a common finding, the direction of modulation varies to a great extent across studies implying dependence on task demands. Here, we reveal opposite modulation of posterior alpha-power with early/initiation versus later/sustained processes of anticipatory attention orienting. Marked alpha-decreases were observed during shifting of attention (initial 700 ms) over occipito-parietal areas processing to-be-attended visual space, while alpha-increases dominated in the subsequent maintenance phase (>700 ms) over occipito-parietal cortex tuned to unattended positions. Notably, the presence of alpha-modulation strongly depended on individual resting alpha-power. Overall, this provides further support to an active facilitative versus inhibitory role of alpha-power decreases and increases and suggests that these attention-related changes are differentially deployed during anticipatory attention orienting to prepare versus maintain the cortex for optimal target processing.

A review of facial nerve anatomy. <=SEP=> An intimate knowledge of facial nerve anatomy is critical to avoid its inadvertent injury during rhytidectomy, parotidectomy, maxillofacial fracture reduction, and almost any surgery of the head and neck. Injury to the frontal and marginal mandibular branches of the facial nerve in particular can lead to obvious clinical deficits, and areas where these nerves are particularly susceptible to injury have been designated danger zones by previous authors. Assessment of facial nerve function is not limited to its extratemporal anatomy, however, as many clinical deficits originate within its intratemporal and intracranial components. Similarly, the facial nerve cannot be considered an exclusively motor nerve given its contributions to taste, auricular sensation, sympathetic input to the middle meningeal artery, and parasympathetic innervation to the lacrimal, submandibular, and sublingual glands. The constellation of deficits resulting from facial nerve injury is correlated with its complex anatomy to help establish the level of injury, predict recovery, and guide surgical management.

A Novel Method for Accurate and Efficient Barcode Detection with Morphological Operations <=SEP=> Barcode technology is the pillar of automatic identification, that is used in a wide range of real-time applications with various types of codes. The different types of codes and applications impose special problems, so there is a continuous need for solutions with improved effectiveness. There are several methods for barcode localization, that are well characterized by accuracy and speed. Particularly, high-speed processing places need automatic barcode localization, e.g. conveyor belts, automated production, where missed detections cause loss of profit. In this paper, we mainly deal with segmentation of images with 1D barcode, but also analyze the operation of different methods for 2D barcode images as well. Our goal is to detect automatically, rapidly and accurately the barcode location by the help of extracted features. We compare some published method from the literature, which basically rely on the contrast between the background and the shape that represent the code. We also propose a novel algorithm, that outperforms the others in both accuracy and efficiency in detecting 1D codes.

Statistics: a brief overview. <=SEP=> The Accreditation Council for Graduate Medical Education sets forth a number of required educational topics that must be addressed in residency and fellowship programs. We sought to provide a primer on some of the important basic statistical concepts to consider when examining the medical literature. It is not essential to understand the exact workings and methodology of every statistical test encountered, but it is necessary to understand selected concepts such as parametric and nonparametric tests, correlation, and numerical versus categorical data. This working knowledge will allow you to spot obvious irregularities in statistical analyses that you encounter.

USER ACCEPTANCE OF COMPUTER TECHNOLOGY : A COMPARISON OF TWO THEORETICAL MODELS * <=SEP=> Computer systems cannot improve organizational performance if they aren't used. Unfortunately, resistance to end-user systems by managers and professionals is a widespread problem. To better predict, explain, and increase user acceptance, we need to better understand why people accept or reject computers. This research addresses the ability to predict peoples' computer acceptance from a measure oftheir intentions, and the ability to explain their intentions in terms oftheir attitudes, subjective norms, perceived usefulness, perceived ease of use, and related variables. In a longitudinal study of 107 users, intentions to use a specific system, measured after a onehour introduction to the system, were correlated 0.35 with system use 14 weeks later. The intentionusage correlation was 0.63 at the end of this time period. Perceived usefulness strongly influenced peoples' intentions, explaining more than half of the variance in intentions at the end of 14 weeks. Perceived ease of use had a small but significant effect on intentions as well, although this effect subsided over time. Attitudes only partially mediated the effects of these beliefs on intentions. Subjective norms had no effect on intentions. These results suggest the possibility of simple but powerful models ofthe determinants of user acceptance, with practical value for evaluating systems and guiding managerial interventions aimed at reducing the problem of underutilized computer technology. (INFORMATION TECHNOLOGY; USER ACCEPTANCE; INTENTION MODELS)

A Two-Layered Permission-Based Android Malware Detection Scheme <=SEP=> Android platform has become the main target of the malware developers in the past few years. One of Android's main defense mechanisms against malicious apps is a permission-based access control mechanism. It is a feasible approach to detect a potential malicious application based on the permissions it requested. In this paper, we proposed a two-layered permission based detection scheme for detecting malicious Android applications. Comparing with previous researches, we consider the apps requested permission pairs as the additional condition, and we also consider used permissions to improve detection accuracy. The result of an evaluation, performed using 28548 benign apps and 1536 malicious apps, indicates that a two-layered permission-based detector has high detection rate of malware.