Physical Sciences and Mathematics Commons^™

Web Based Attendance Management System (Project Source Code In Php And Mysql), Dr. Muhammad Zubair Asghar

Dr. Muhammad Zubair Asghar

This source code deals with the development of web based attendance management system using PHP and MYSQL. It is developed by one my BSCS student, namely sahar hassan under my supervision.

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen Cheng

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Robust Distributed Scheduling Via Time Period Aggregation, Shih-Fen Cheng, John Tajan, Hoong Chuin Lau

Shih-Fen CHENG

In this paper, we evaluate whether the robustness of a market mechanism that allocates complementary resources could be improved through the aggregation of time periods in which resources are consumed. In particular, we study a multi-round combinatorial auction that is built on a general equilibrium framework. We adopt the general equilibrium framework and the particular combinatorial auction design from the literature, and we investigate the benefits and the limitation of time-period aggregation when demand-side uncertainties are introduced. By using simulation experiments on a real-life resource allocation problem from a container port, we show that, under stochastic conditions, the performance variation …

Mapping The Organizational Relations Within Physical Security’S Body Of Knowledge: A Management Heuristic Of Sound Theory And Best Practice, Richard Coole, David J. Brooks

David J Brooks Dr.

Security Science education at university levels is still in its infancy, with little agreement towards knowledge, curriculum and competency. Therefore, it is essential that educators draw on relevant literature highlighting means of efficient and effective knowledge transfer for tertiary students within the Security Science domain. Such knowledge transfer will reduce the gap between academic knowledge (explicit) and professional competency (tacit knowledge). This paper presents phase one of a multiphase study. A qualitative “systems based knowledge structure” of security domain categories has been conceptually mapped as a domain heuristic. The heuristic drew on research highlighting that experts have both richer depths …

Mapping The Organizational Relations Within Physical Security’S Body Of Knowledge: A Management Heuristic Of Sound Theory And Best Practice, Richard Coole, David J. Brooks

David J Brooks Dr.

Security Science education at university levels is still in its infancy, with little agreement towards knowledge, curriculum and competency. Therefore, it is essential that educators draw on relevant literature highlighting means of efficient and effective knowledge transfer for tertiary students within the Security Science domain. Such knowledge transfer will reduce the gap between academic knowledge (explicit) and professional competency (tacit knowledge). This paper presents phase one of a multiphase study. A qualitative “systems based knowledge structure” of security domain categories has been conceptually mapped as a domain heuristic. The heuristic drew on research highlighting that experts have both richer depths …

Ramping Down Chinese Commercial Cyber Espionage, Emilio Iasiello

Emilio Iasiello

While detractors believe that commercial cyber espionage hasn’t really stopped, recent Chinese efforts show a government trying to get a handle on its large spying apparatus that could include hired and independent contractors acting autonomously in addition to its other resources. While complete cessation may never occur, significant timely reduction demonstrates Beijing’s willingness to work with the United States as a partner and not a pariah, and provides a foundation from which the two governments can move forward on other cyber security areas where incongruity persists.

Designing For Positive Health Affect: Decoupling Negative Emotion And Health Monitoring Technologies, Tammy R. Toscos, Kay Connelly, Yvonne Rogers

Tammy R Toscos

Through various health-focused technology projects, we discovered that the emotional response to technology was related to uptake and sustained use of health monitoring technologies. In this paper we present a case study of how we synthesized constructs of social cognitive theory, technology as experience, and diabetes management guidelines as a framework for making design recommendations for blood glucose monitoring technology that address the emotional response of users. We suggest applying this theoretical lens for design may help attend to emotional responses of users in an effort to decouple strong negative emotions that are paired to health monitoring technologies that provide …

Is It The Typeset Or The Type Of Statistics? Disfluent Font And Self-Disclosure, Rebecca Balebako, Eyal Peer, Laura Brandimarte, Lorrie Faith Cranor, Alessandro Acquisti

Lorrie F Cranor

Background. The security and privacy communities have become increasingly interested in results from behavioral economics and psychology to help frame decisions so that users can make better privacy and security choices. One such result in the literature suggests that cognitive disfluency (presenting questions in a hard-to-read font) reduces self-disclosure. (A. L. Alter and D. M. Oppenheimer. Suppressing secrecy through metacognitive ease cognitive fluency encourages self-disclosure. Psychological science, 20(11):1414-1420, 2009) Aim. To examine the replicability and reliability of the effect of disfluency on self-disclosure, in order to test whether such approaches might be used to promote safer security and privacy behaviors. …

A Field Trial Of Privacy Nudges For Facebook, Yang Wang, Pedro Giovanni Leon, Alessandro Acquisti, Lorrie Faith Cranor, Alain Forget, Norman Sadeh

Lorrie F Cranor

Anecdotal evidence and scholarly research have shown that Internet users may regret some of their online disclosures. To help individuals avoid such regrets, we designed two modifications to the Facebook web interface that nudge users to consider the content and audience of their online disclosures more carefully. We implemented and evaluated these two nudges in a 6-week field trial with 28 Facebook users. We analyzed participants' interactions with the nudges, the content of their posts, and opinions collected through surveys. We found that reminders about the audience of posts can prevent unintended disclosures without major burden; however, introducing a time …

Guess Again (And Again And Again): Measuring Password Strength By Simulating Password-Cracking Algorithms (Cmu-Cylab-11-008), Patrick Kelley, Saranga Komanduri, Michelle L. Mazurek, Richard Shay, Tim Vidas, Lujo Bauer, Nicolas Christin, Lorrie Faith Cranor, Julio Lopez

Lorrie F Cranor

Text-based passwords remain the dominant authentication method in computer systems, despite significant advancement in attackers’ capabilities to perform password cracking. In response to this threat, password composition policies have grown increasingly complex. However, there is insufficient research defining metrics to characterize password strength and evaluating password-composition policies using these metrics. In this paper, we describe an analysis of 12,000 passwords collected under seven composition policies via an online study. We develop an efficient distributed method for calculating how effectively several heuristic password-guessing algorithms guess passwords. Leveraging this method, we investigate (a) the resistance of passwords created under different conditions to …

From Facebook Regrets To Facebook Privacy Nudges, Yang Wang, Pedro Giovanni Leon, Xiaoxuan Chen, Saranga Komanduri, Gregory Norcie, Alessandro Acquisti, Lorrie Faith Cranor, Norman Sadeh

Lorrie F Cranor

As social networking sites (SNSs) gain in popularity, instances of regrets following online (over)sharing continue to be reported. In June 2010, a pierogi mascot for the Pittsburgh Pirates was fired because he posted disparaging comments about the team on his Facebook page. More recently, a high school teacher was forced to resign because she posted a picture on Facebook in which she was holding a glass of wine and a mug of beer. These incidents illustrate how, in addition to fostering socialization and interaction between friends and strangers, the ease and immediacy of communication that SNSs make possible can sometimes …

A Survey Of The Use Of Adobe Flash Local Shared Objects To Respawn Http Cookies (Cmu-Cylab-11-001), Aleecia M. Mcdonald, Lorrie Faith Cranor

Lorrie F Cranor

Website developers can use Adobe’s Flash Player product to store information locally on users’ disks with Local Shared Objects (LSOs). LSOs can be used to store state information and user identifiers, and thus can be used for similar purposes as HTTP cookies. In a paper by Soltani et al, researchers documented at least four instances of “respawning,” where users deleted their HTTP cookies only to have the HTTP cookies recreated based on LSO data. In addition, the Soltani team found half of the 100 most popular websites used Flash technologies to store information about users. Both respawning and using LSOs …

An Empirical Analysis Of Phishing Blacklists, Steve Sheng, Brad Wardman, Gary Warner, Lorrie Faith Cranor, Jason Hong, Chengshan Zhang

Lorrie F Cranor

In this paper, we study the effectiveness of phishing blacklists. We used 191 fresh phish that were less than 30 minutes old to conduct two tests on eight anti-phishing toolbars. We found that 63% of the phishing campaigns in our dataset lasted less than two hours. Blacklists were ineffective when protecting users initially, as most of them caught less than 20% of phish at hour zero. We also found that blacklists were updated at different speeds, and varied in coverage, as 47% - 83% of phish appeared on blacklists 12 hours from the initial test. We found that two tools …

The Privacy And Security Behaviors Of Smartphone App Developers, Rebecca Balebako, Abigail Marsh, Jialiu Lin, Jason I. Hong, Lorrie Faith Cranor

Lorrie F Cranor

Smartphone app developers have to make many privacy-related decisions about what data to collect about endusers, and how that data is used. We explore how app developers make decisions about privacy and security. Additionally, we examine whether any privacy and security behaviors are related to characteristics of the app development companies. We conduct a series of interviews with 13 app developers to obtain rich qualitative information about privacy and security decision-making. We use an online survey of 228 app developers to quantify behaviors and test our hypotheses about the relationship between privacy and security behaviors and company characteristics. We find …

Disjunctive Answer Set Solvers Via Templates, Remi Brochenin, Yuliya Lierler, Marco Maratea

Yuliya Lierler

Projected Nesterov’S Proximal-Gradient Signal Recovery From Compressive Poisson Measurements, Renliang Gu, Aleksandar Dogandžić

Aleksandar Dogandžić

We develop a projected Nesterov’s proximal-gradient (PNPG) scheme for reconstructing sparse signals from compressive Poisson-distributed measurements with the mean signal intensity that follows an affine model with known intercept. The objective function to be minimized is a sum of convex data fidelity (negative log-likelihood (NLL)) and regularization terms. We apply sparse signal regularization where the signal belongs to a nonempty closed convex set within the domain of the NLL and signal sparsity is imposed using total-variation (TV) penalty. We present analytical upper bounds on the regularization tuning constant. The proposed PNPG method employs projected Nesterov’s acceleration step, function restart, and …

Effect Of Retiring Custom Web Applications On Business And Information Technology Alignment, Shubhashree Thekahally

Shubhashree Thekahally 7340504

Web applications provide the information technology (IT) implementation of business and align IT with business. Retirement of IT applications should ensure stability of business and IT alignment. The current study investigated the alignment gaps created between business and IT resulting from retiring IT software applications. The purpose of this study was to identify IT integration points with business and provide a process-based solution that sustained IT alignment with business after retiring IT applications. The theoretical framework strategic alignment model aided in identifying 3 IT domains as the IT integration points with business: enterprise architecture, configuration management database, and service-level agreement. …

Can You Summarize This? Identifying Correlates Of Input Difficulty For Generic Multi-Document Summarization, Ani Nenkova, Annie Louis

Ani Nenkova

Different summarization requirements could make the writing of a good summarymore difficult, or easier. Summary length and the characteristics of the input are such constraints influencing the quality of a potential summary. In this paper we report the results of a quantitative analysis on data from large-scale evaluations of multi-document summarization, empirically confirming this hypothesis. We further show that features measuring the cohesiveness of the input are highly correlated with eventual summary quality and that it is possible to use these as features to predict the difficulty of new, unseen, summarization inputs.

Discourse Indicators For Content Selection In Summaization, Annie Louis, Aravind K. Joshi, Ani Nenkova

Ani Nenkova

We present analyses aimed at eliciting which specific aspects of discourse provide the strongest indication for text importance. In the context of content selection for single document summarization of news, we examine the benefits of both the graph structure of text provided by discourse relations and the semantic sense of these relations. We find that structure information is the most robust indicator of importance. Semantic sense only provides constraints on content selection but is not indicative of important content by itself. However, sense features complement structure information and lead to improved performance. Further, both types of discourse information prove complementary …

Automatic Sense Prediction For Implicit Discourse Relations In Text, Emily Pitler, Annie Louis, Ani Nenkova

Ani Nenkova

We present a series of experiments on automatically identifying the sense of implicit discourse relations, i.e. relations that are not marked with a discourse connective such as “but” or “because”. We work with a corpus of implicit relations present in newspaper text and report results on a test set that is representative of the naturally occurring distribution of senses. We use several linguistically informed features, including polarity tags, Levin verb classes, length of verb phrases, modality, context, and lexical features. In addition, we revisit past approaches using lexical pairs from unannotated text as features, explain some of their shortcomings and …

Automatic Evaluation Of Linguistic Quality In Multi-Document Summarization, Emily Pitler, Annie Louis, Ani Nenkova

Ani Nenkova

To date, few attempts have been made to develop and validate methods for automatic evaluation of linguistic quality in text summarization. We present the first systematic assessment of several diverse classes of metrics designed to capture various aspects of well-written text. We train and test linguistic quality models on consecutive years of NIST evaluation data in order to show the generality of results. For grammaticality, the best results come from a set of syntactic features. Focus, coherence and referential clarity are best evaluated by a class of features measuring local coherence on the basis of cosine similarity between sentences, coreference …

Structural Features For Predicting The Linguistic Quality Of Text: Applications To Machine Translation, Automatic Summarization And Human-Authored Text, Ani Nenkova, Jieun Chae, Annie Louis, Emily Pitler

Ani Nenkova

Sentence structure is considered to be an important component of the overall linguistic quality of text. Yet few empirical studies have sought to characterize how and to what extent structural features determine fluency and linguistic quality. We report the results of experiments on the predictive power of syntactic phrasing statistics and other structural features for these aspects of text. Manual assessments of sentence fluency for machine translation evaluation and text quality for summarization evaluation are used as gold-standard. We find that many structural features related to phrase length are weakly but significantly correlated with fluency and classifiers based on the …

Measuring Importance And Query Relevance In Toopic-Focused Multi-Document Summarization, Surabhi Gupta, Ani Nenkova, Dan Jurafsky

Ani Nenkova

The increasing complexity of summarization systems makes it difficult to analyze exactly which modules make a difference in performance. We carried out a principled comparison between the two most commonly used schemes for assigning importance to words in the context of query focused multi-document summarization: raw frequency (word probability) and log-likelihood ratio. We demonstrate that the advantages of log-likelihood ratio come from its known distributional properties which allow for the identification of a set of words that in its entirety defines the aboutness of the input. We also find that LLR is more suitable for query-focused summarization since, unlike raw …

Using Entity Features To Classify Implicit Discourse Relations, Annie Louis, Aravind K. Joshi, Rashmi Prasad, Ani Nenkova

Ani Nenkova

We report results on predicting the sense of implicit discourse relations between adjacent sentences in text. Our investigation concentrates on the association between discourse relations and properties of the referring expressions that appear in the related sentences. The properties of interest include coreference information, grammatical role, information status and syntactic form of referring expressions. Predicting the sense of implicit discourse relations based on these features is considerably better than a random baseline and several of the most discriminative features conform with linguistic intuitions. However, these features do not perform as well as lexical features traditionally used for sense prediction.

Creating Local Coherence: An Empirical Assessment, Annie Louis, Ani Nenkova

Ani Nenkova

Two of the mechanisms for creating natural transitions between adjacent sentences in a text, resulting in local coherence, involve discourse relations and switches of focus of attention between discourse entities. These two aspects of local coherence have been traditionally discussed and studied separately. But some empirical studies have given strong evidence for the necessity of understanding how the two types of coherence-creating devices interact. Here we present a joint corpus study of discourse relations and entity coherence exhibited in news texts from the Wall Street Journal and test several hypotheses expressed in earlier work about their interaction.

Automatically Evaluating Content Selection In Summarization Without Human Models, Annie Louis, Ani Nenkova

Ani Nenkova

We present a fully automatic method for content selection evaluation in summarization that does not require the creation of human model summaries. Our work capitalizes on the assumption that the distribution of words in the input and an informative summary of that input should be similar to each other. Results on a large scale evaluation from the Text Analysis Conference show that input-summary comparisons are very effective for the evaluation of content selection. Our automatic methods rank participating systems similarly to manual model-based pyramid evaluation and to manual human judgments of responsiveness. The best feature, Jensen- Shannon divergence, leads to …

Entity-Driven Rewrite For Multi-Document Summarization, Ani Nenkova

Ani Nenkova

In this paper we explore the benefits from and shortcomings of entity-driven noun phrase rewriting for multi-document summarization of news. The approach leads to 20% to 50% different content in the summary in comparison to an extractive summary produced using the same underlying approach, showing the promise the technique has to offer. In addition, summaries produced using entity-driven rewrite have higher linguistic quality than a comparison non-extractive system. Some improvement is also seen in content selection over extractive summarization as measured by pyramid method evaluation.

Detecting Prominence In Conversational Speech: Pitch Accent, Givenness And Focus, Vivek Kumar Rangarajan Sridhar, Ani Nenkova, Shrikanth Narayanan, Dan Jurafsky

Ani Nenkova

The variability and reduction that are characteristic of talking in natural interaction make it very difficult to detect prominence in conversational speech. In this paper, we present analytic studies and automatic detection results for pitch accent, as well as on the realization of information structure phenomena like givenness and focus. For pitch accent, our conditional random field model combining acoustic and textual features has an accuracy of 78%, substantially better than chance performance of 58%. For givenness and focus, our analysis demonstrates that even in conversational speech there are measurable differences in acoustic properties and that an automatic detector for …

Modelling Prominence And Emphasis Improves Unit-Selection Synthesis, Volker Strom, Ani Nenkova, Robert Clark, Yolanda Vazquez-Alvarez, Jason Brenier, Simon King, Dan Jurafsky

Ani Nenkova

We describe the results of large scale perception experiments showing improvements in synthesising two distinct kinds of prominence: standard pitch-accent and strong emphatic accents. Previously prominence assignment has been mainly evaluated by computing accuracy on a prominence-labelled test set. By contrast we integrated an automatic pitch-accent classifier into the unit selection target cost and showed that listeners preferred these synthesised sentences. We also describe an improved recording script for collecting emphatic accents, and show that generating emphatic accents leads to further improvements in the fiction genre over incorporating pitch accent only. Finally, we show differences in the effects of prominence …