snu-aidas/HVMap-dataset huggingface dataset:
Towards reliable traffic sign recognition

The demand for reliable traffic sign recognition (TSR) increases with the development of safety driven advanced driver assistance systems (ADAS). Emerging technologies like brake-by-wire or steer-by-wire pave the way for collision avoidance and threat identification systems. Obviously, decision making in such critical situations requires high reliability of the information base. Especially for comfort systems, we need to take into account that the user tends to trust the information provided by the ADAS [1]. In this paper, we present a robust system architecture for the reliable recognition of circular traffic signs. Our system employs complementing approaches for the different stages of current TSR systems. This introduces the application of local SIFT features for content-based traffic sign detection along with widely applied shape-based approaches. We further add a technique called contracting curve density (CCD) to refine the localization of the detected traffic sign candidates and therefore increase the performance of the subsequent classification module. Finally, the recognition stage based on SIFT and SURF descriptions of the candidates executed by a neural net provides a robust classification of structured image content like traffic signs. By applying these steps we compensate the weaknesses of the utilized approaches, and thus, improve the system's performance.
Mobile applications for weight management: theory-based content analysis.

BACKGROUND
The use of smartphone applications (apps) to assist with weight management is increasingly prevalent, but the quality of these apps is not well characterized.


PURPOSE
The goal of the study was to evaluate diet/nutrition and anthropometric tracking apps based on incorporation of features consistent with theories of behavior change.


METHODS
A comparative, descriptive assessment was conducted of the top-rated free apps in the Health and Fitness category available in the iTunes App Store. Health and Fitness apps (N=200) were evaluated using predetermined inclusion/exclusion criteria and categorized based on commonality in functionality, features, and developer description. Four researchers then evaluated the two most popular apps in each category using two instruments: one based on traditional behavioral theory (score range: 0-100) and the other on the Fogg Behavioral Model (score range: 0-6). Data collection and analysis occurred in November 2012.


RESULTS
Eligible apps (n=23) were divided into five categories: (1) diet tracking; (2) healthy cooking; (3) weight/anthropometric tracking; (4) grocery decision making; and (5) restaurant decision making. The mean behavioral theory score was 8.1 (SD=4.2); the mean persuasive technology score was 1.9 (SD=1.7). The top-rated app on both scales was Lose It! by Fitnow Inc.


CONCLUSIONS
All apps received low overall scores for inclusion of behavioral theory-based strategies.
Security in Cloud Computing Using Cryptographic Algorithms Miss .

Cloud computing is the concept implemented to decipher the Daily Computing Problems. Cloud computing is basically virtual pool of resources and it provides these resources to users via internet. Cloud computing is the internet based development and used in computer technology. The prevalent problem associated with cloud computing is data privacy, security, anonymity and reliability etc. But the most important between them is security and how cloud provider assures it. To secure the Cloud means secure the treatments (calculations) and storage (databases hosted by the Cloud provider). In this paper we analyses different security issues to cloud and different cryptographic algorithms adoptable to better security for the cloud. Keywords— Cloud Computing, Cryptographic Algorithm, Internet, Security Algorithms, Security Attacks, Security Issue
Maternal depression and early childhood growth in developing countries: systematic review and meta-analysis.

OBJECTIVE
To investigate the relationship between maternal depression and child growth in developing countries through a systematic literature review and meta-analysis.


METHODS
Six databases were searched for studies from developing countries on maternal depression and child growth published up until 2010. Standard meta-analytical methods were followed and pooled odds ratios (ORs) for underweight and stunting in the children of depressed mothers were calculated using random effects models for all studies and for subsets of studies that met strict criteria on study design, exposure to maternal depression and outcome variables. The population attributable risk (PAR) was estimated for selected studies.


FINDINGS
Seventeen studies including a total of 13,923 mother and child pairs from 11 countries met inclusion criteria. The children of mothers with depression or depressive symptoms were more likely to be underweight (OR: 1.5; 95% confidence interval, CI: 1.2-1.8) or stunted (OR: 1.4; 95% CI: 1.2-1.7). Subanalysis of three longitudinal studies showed a stronger effect: the OR for underweight was 2.2 (95% CI: 1.5-3.2) and for stunting, 2.0 (95% CI: 1.0-3.9). The PAR for selected studies indicated that if the infant population were entirely unexposed to maternal depressive symptoms 23% to 29% fewer children would be underweight or stunted.


CONCLUSION
Maternal depression was associated with early childhood underweight and stunting. Rigorous prospective studies are needed to identify mechanisms and causes. Early identification, treatment and prevention of maternal depression may help reduce child stunting and underweight in developing countries.
Methods for Pretreatment of Lignocellulosic Biomass for Efficient Hydrolysis and Biofuel Production

Industrial & Engineering Chemistry Research is published by the American Chemical Society. 1155 Sixteenth Street N.W., Washington, DC 20036 Review Methods for Pretreatment of Lignocellulosic Biomass for Efficient Hydrolysis and Biofuel Production Parveen Kumar, Diane M. Barrett, Michael J. Delwiche, and Pieter Stroeve Ind. Eng. Chem. Res., Article ASAP • DOI: 10.1021/ie801542g • Publication Date (Web): 20 March 2009 Downloaded from http://pubs.acs.org on March 26, 2009
Are men really more ‘ oriented ’ toward short-term mating than women ?

According to Sexual Strategies Theory (D.M. Buss and D.P. Schmitt 1993), both men and women possess psychological adaptations for short-term mating. However, men may possess three adaptations that make it seem as though they are generally more ‘oriented’ toward short-term mating than women: (1) Men possess greater desire for short-term sexual relationships than women; (2) Men prefer larger numbers of sexual partners over time than women; and (3) Men require less time before consenting to sex than women. We review a wide body of psychological theory and evidence that corroborates the presence of these adaptations in men’s short-term sexual psychology. We also correct some recurring misinterpretations of Sexual Strategies Theory, such as the mistaken notion that women are designed solely for long-term mating. Finally, we document how the observed sex differences in short-term mating complement some feminist theories and refute competing evolutionary theories of human sexuality. Psychology, Evolution & Gender 3.3 December 2001 pp. 211–239 Psychology, Evolution & Gender ISSN 1461-6661 print/ISSN 1470-1073 online © 2001 Taylor & Francis Ltd http://www.tandf.co.uk/journals DOI: 10.1080/1461666011011933 1
MOBILE LEARNING FOR EDUCATION : BENEFITS AND CHALLENGES

Education and training is the process by which the wisdom, knowledge and skills of one generation are passed on to the next. Today there are two form s f education and training: conventional education and distance education. Mobile learning, or "M-Lear ning", offers modern ways to support learning process through mobile devices, such as handheld an d tablet computers, MP3 players, smart phones and mobile phones. This document introduces the sub ject of mobile learning for education purposes. It examines what impact mobile devices have had on teaching and learning practices and goes on to look at the opportunities presented by the use of d igital media on mobile devices. The main purpose of this paper is to describe the current state of mobi le learning, benefits, challenges, and it’s barrier s to support teaching and learning. Data for this paper w re collected through bibliographic and internet research from January to March 2013. Four key areas will be addressed in this paper: 1. An analysis of Mobile Learning. 2. Differentiating E-Learning from Mobile Learning 3. Value and Benefits of Mobile Learning 4. Challenges and Barriers of M obile Learning: Study showed that M-Learning as a Distance learning brought great benefits to socie ty include : Training when it is needed, Training a t any time; Training at any place; Learner-centred co ntent; Avoidance of re-entry to work problems; Training for taxpayers, and those fully occupied du ring university lectures and sessions at training centres; and The industrialisation of teaching and learning. And also, notebooks, mobile Tablets, iPod touch, and iPads are very popular devices for mobil e learning because of their cost and availability o f apps. --------------------------------
Improved Algorithm for Intrusion Detection Using Genetic Algorithm and SNORT

Intrusion Detection Systems (IDSs) detects the network attacks by scanning each data packets. There are various approaches were done for making better IDS, though traditional IDS approaches are insufficient in terms of automating detection of attacks as attackers evolved. This research is focused on Genetic Algorithm approach used in Intrusion Detection. This research shows that how the traditional SNORT and Genetic Algorithm combined together so that the number of rules of SNORT is decreased. Experimental results Shows That IDS using Genetic Algorithm and SNORT can decrease the amount of detection time, CPU Utilization and Memory Utilization. Keywords—Genetic Algorithm, SNORT, Fitness Function,
Semantic Spaces: Measuring the Distance between Different Subspaces

Semantic Space models, which provide a numerical representation of words’ meaning extracted from corpus of documents, have been formalized in terms of Hermitian operators over real valued Hilbert spaces by Bruza et al. [1]. The collapse of a word into a particular meaning has been investigated applying the notion of quantum collapse of superpositional states [2]. While the semantic association between words in a Semantic Space can be computed by means of the Minkowski distance [3] or the cosine of the angle between the vector representation of each pair of words, a new procedure is needed in order to establish relations between two or more Semantic Spaces. We address the question: how can the distance between different Semantic Spaces be computed? By representing each Semantic Space as a subspace of a more general Hilbert space, the relationship between Semantic Spaces can be computed by means of the subspace distance. Such distance needs to take into account the difference in the dimensions between subspaces. The availability of a distance for comparing different Semantic Subspaces would enable to achieve a deeper understanding about the geometry of Semantic Spaces which would possibly translate into better effectiveness in Information Retrieval tasks.
Neural Disambiguation of Causal Lexical Markers Based on Context

Causation is a psychological tool of humans to understand the world and it is projected in natural language. Causation relates two events, so in order to understand the causal relation of those events and the causal reasoning of humans, the study of causality classification is required. We claim that the use of linguistic features may restrict the representation of causality, and dense vector spaces can provide a better encoding of the causal meaning of an utterance. Herein, we propose a neural network architecture only fed with word embeddings for the task of causality classification. Our results show that our claim holds, and we outperform the state-of-the-art on the AltLex corpus. The source code of our experiments is publicly available.1
The Description Logic Handbook: Theory, Implementation, and Applications

Like modal logic, temporal logic, or description logic, separation logic has become a Description Logic Handbook: Theory, Implementation and Applications,”. The Description Logic Handbook: Theory, Implementation and Applications (Franz Baader, Diego Calvanese, Deborah. McGuinness, Daniele Nardi, Peter. To formalize knowledge, we employ various logic-based formalisms, such as The Description Logic Handbook: Theory, Implementation and Applications.
The Semantic Web" in Scientific American
Hand Gesture Recognition System

The task of gesture recognition is highly challenging due to complex background, presence of nongesture hand motions, and different illumination environments. In this paper, a new technique is proposed which begins by detecting the hand and determining its canter, tracking the hands trajectory and analyzing the variations in the hand locations, and finally recognizing the gesture. The proposed technique overcomes background complexity and distance from camera which is up to 2.5 meters. Experimental results show that the proposed technique can recognize 12 gestures with rate above 94%. Keywords— Hand gesture recognition, skin detection, Hand tracking.
Prosthetic gingival reconstruction in a fixed partial restoration. Part 1: introduction to artificial gingiva as an alternative therapy.

The Class III defect environment entails a vertical and horizontal deficiency in the edentulous ridge. Often, bone and soft tissue surgical procedures fall short of achieving a natural esthetic result. Alternative surgical and restorative protocols for these types of prosthetic gingival restorations are presented in this three-part series, which highlights the diagnostic and treatment aspects as well as the lab and maintenance challenges. A complete philosophical approach involves both a biologic understanding of the limitations of the hard and soft tissue healing process as well as that of multiple adjacent implants in the esthetic zone. These limitations may often necessitate the use of gingiva-colored "pink" restorative materials and essential preemptive planning via three-dimensional computer-aided design/computer-assisted manufacture to achieve the desired esthetic outcome. The present report outlines a rationale for consideration of artificial gingiva when planning dental prostheses. Prosthetic gingiva can overcome the limitations of grafting and should be a consideration in the initial treatment plan. (Int J Periodontics Restorative Dent 2009;29:471-477.).
Instructional video in e-learning: Assessing the impact of interactive video on learning effectiveness

Interactive video in an e-learning system allows proactive and random access to video content. Our empirical study examined the influence of interactive video on learning outcome and learner satisfaction in e-learning environments. Four different settings were studied: three were e-learning environments—with interactive video, with non-interactive video, and without video. The fourth was the traditional classroom environment. Results of the experiment showed that the value of video for learning effectiveness was contingent upon the provision of interactivity. Students in the e-learning environment that provided interactive video achieved significantly better learning performance and a higher level of learner satisfaction than those in other settings. However, students who used the e-learning environment that provided non-interactive video did not improve either. The findings suggest that it may be important to integrate interactive instructional video into e-learning systems. # 2005 Elsevier B.V. All rights reserved.
Reality mining based on Social Network Analysis

Data Mining is the extraction of hidden predictive information from large databases. The process of discovering interesting, useful, nontrivial patterns from large spatial datasets is called spatial data mining. When time gets associated it becomes spatio temporal data mining. The study of spatio temporal data mining is of great concern for the study of mobile phone sensed data. Reality Mining is defined as the study of human social behavior based on mobile phone sensed data. It is based on the data collected by sensors in mobile phones, security cameras, RFID readers, etc. All allow for the measurement of human physical and social activity. In this paper Netviz, Gephi and Weka tools have been used to convert and analyze the Facebook. Further, analysis of a reality mining dataset is also presented.
Ontology Based SMS Controller for Smart Phones

Text analysis includes lexical analysis of the text and has been widely studied and used in diverse applications. In the last decade, researchers have proposed many efficient solutions to analyze / classify large text dataset, however, analysis / classification of short text is still a challenge because 1) the data is very sparse 2) It contains noise words and 3) It is difficult to understand the syntactical structure of the text. Short Messaging Service (SMS) is a text messaging service for mobile/smart phone and this service is frequently used by all mobile users. Because of the popularity of SMS service, marketing companies nowadays are also using this service for direct marketing also known as SMS marketing.In this paper, we have proposed Ontology based SMS Controller which analyze the text message and classify it using ontology aslegitimate or spam. The proposed system has been tested on different scenarios and experimental results shows that the proposed solution is effective both in terms of efficiency and time. Keywords—Short Text Classification; SMS Spam; Text Analysis; Ontology based SMS Spam; Text Analysis and Ontology
Genetic programming - on the programming of computers by means of natural selection

Page ii Complex Adaptive Systems John H. Holland, Christopher Langton, and Stewart W. Wilson, advisors Adaptation in Natural and Artificial Systems: An Introductory Analysis with Applications to Biology, Control, and Artificial Intelligence, MIT Press edition John H. Holland Toward a Practice of Autonomous Systems: Proceedings of the First European Conference on Artificial Life edited by Francisco J. Varela and Paul Bourgine Genetic Programming: On the Programming of Computers by Means of Natural Selection John R. Koza
Back propagation neural network with adaptive differential evolution algorithm for time series forecasting

The back propagation neural network (BPNN) can easily fall into the local minimum point in time series forecasting. A hybrid approach that combines the adaptive differential evolution (ADE) algorithm with BPNN, called ADE–BPNN, is designed to improve the forecasting accuracy of BPNN. ADE is first applied to search for the global initial connection weights and thresholds of BPNN. Then, BPNN is employed to thoroughly search for the optimal weights and thresholds. Two comparative real-life series data sets are used to verify the feasibility and effectiveness of the hybrid method. The proposed ADE–BPNN can effectively improve forecasting accuracy relative to basic BPNN, autoregressive integrated moving average model (ARIMA), and other hybrid models. 2014 Elsevier Ltd. All rights reserved.
On code reuse from StackOverflow: An exploratory study on Android apps

Context: Source code reuse has been widely accepted as a fundamental activity in software development. Recent studies showed that StackOverflow has emerged as one of the most popular resources for code reuse. Therefore, a plethora of work proposed ways to optimally ask questions, search for answers and find relevant code on StackOverflow. However, little work studies the impact of code reuse from Stack-
BIM: An integrated model for planned and preventive maintenance of architectural heritage

Modern digital technologies give us great possibilities to organize knowledge about constructions, regarding multidisciplinary fields like preservation, conservation and valorization of our architectural heritage, in order to suggest restoration projects and related work, or to suppose a planned preventive maintenance. New procedures to archive, analyze and manage architectural information find a natural support in 3D model, thanks to the development of capacities of new modeling software. Moreover, if the model contains or interfaces with a heterogeneous archive of information, as it is for BIM, this model can be considered as the bases of critical studies, projects of restoration, heritage maintenance, integrated management, protection, and valorization, and evaluation of economic aspects, management and planning, that can flow into a planned preventive maintenance [1]. The aspect that limit the use of BIM technology is the set up parametric object library inside programs: the standardized level of these objects deals difficulty with survey and restoration issues, where each single element has its own historical and architectural characterization [2]. From this foreword, the goal of this research is more evident: the possibilities of using BIM modeling to the existing constructions and cultural heritage, as a support for the construction and management of a Plan for planned preventive maintenance.
Design for reliability of power electronics modules

0026-2714/$ see front matter 2009 Published by doi:10.1016/j.microrel.2009.07.055 * Corresponding author. Tel.: +44 (0)20 8331 8660 E-mail address: c.bailey@gre.ac.uk (C. Bailey). Power electronics uses semiconductor technology to convert and control electrical power. Demands for efficient energy management, conversion and conservation, and the increasing take-up of electronics in transport systems has resulted in tremendous growth in the use of power electronics devices such as Insulated Gate Bipolar Transistors (IGBT’s). The packaging of power electronics devices involves a number of challenges for the design engineer in terms of reliability. For example, IGBT modules will contain a number of semiconductor dies within a small footprint bonded to substrates with aluminum wires and wide area solder joints. To a great extent, the reliability of the package will depend on the thermo-mechanical behavior of these materials. This paper details a physics of failure approach to reliability predictions of IGBT modules. It also illustrates the need for a probabilistic approach to reliability predictions that include the effects of design variations. Also discussed are technologies for predicting the remaining life of the package when subjected to qualification stresses or in service stresses using prognostics methods. 2009 Published by Elsevier Ltd.