Passenger segmentation using smart card data

Transit passenger market segmentation enables transit operators to target different classes of transit users for targeted surveys and various operational and strategic planning improvements. However, the existing market segmentation studies in the literature have been generally done using passenger surveys, which have various limitations. The smart card (SC) data from an automated fare collection system facilitate the understanding of the multiday travel pattern of transit passengers and can be used to segment them into identifiable types of similar behaviors and needs. This paper proposes a comprehensive methodology for passenger segmentation solely using SC data. After reconstructing the travel itineraries from SC transactions, this paper adopts the density-based spatial clustering of application with noise (DBSCAN) algorithm to mine the travel pattern of each SC user. An a priori market segmentation approach then segments transit passengers into four identifiable types. The methodology proposed in this paper assists transit operators to understand their passengers and provides them oriented information and services.

The culture of young women's drinking: Implications for developing effective policing strategies. Report to National Drug Strategy Law Enforcement Committee

Alcohol-related mortality and morbidity represents a substantial financial burden on communities across the world. Adolescence and young adulthood is a peak period for heavy episodic alcohol consumption, with over a third of all people aged 14-19 years having been at risk of acute alcoholrelated harm at least once in the previous 12 months (Australian Institute of Health and Welfare [AIHW], 2011). Excessive alcohol consumption has long been seen as a male problem; however, a gradual shift towards a social acceptance of female drunkenness has narrowed the gap in drinking quantity and style between men and women (Grucza, Bucholz, Rice, & Bierut, 2008). The presented data point to the vulnerability of women to the consequences of acute alcohol intoxication and indicate that alcohol-related offending by women is on the rise. Taken together, these findings reveal that alcohol-related harms and aggression for young women are becoming more prevalent and problematic. This report addressed these issues from a policing perspective...

Differential segmentation responses to an alcohol social marketing program

Objective This study seeks establish whether meaningful subgroups exist within a 14-16 year old adolescent population and if these segments respond differently to the Game On: Know Alcohol (GOKA) intervention, a school-based alcohol social marketing program. Methodology This study is part of a larger cluster randomized controlled evaluation of the Game On: Know Alcohol (GOKA) program implemented in 14 schools in 2013/2014. TwoStep cluster analysis was conducted to segment 2114 high school adolescents (14-16 years old) on the basis of 22 demographic, behavioral and psychographic variables. Program effects on knowledge, attitudes, behavioral intentions, social norms, expectancies and refusal self-efficacy of identified segments was subsequently examined. Results Three segments were identified: (1) Abstainers (2) Bingers (3) Moderate Drinkers. Program effects varied significantly across segments. The strongest positive change effects post participation were observed for the Bingers, while mixed effects were evident for Moderate Drinkers and Abstainers. Conclusions These findings provide preliminary empirical evidence supporting application of social marketing segmentation in alcohol education programs. Development of targeted programs that meet the unique needs of each of the three identified segments is indicated to extend the social marketing footprint in alcohol education.

Algorithm of medication review in frail older people: Focus on minimizing the use of high-risk medications

Aim Frail older people typically suffer several chronic diseases, receive multiple medications and are more likely to be institutionalized in residential aged care facilities. In such patients, optimizing prescribing and avoiding use of high-risk medications might prevent adverse events. The present study aimed to develop a pragmatic, easily applied algorithm for medication review to help clinicians identify and discontinue potentially inappropriate high-risk medications. Methods The literature was searched for robust evidence of the association of adverse effects related to potentially inappropriate medications in older patients to identify high-risk medications. Prior research into the cessation of potentially inappropriate medications in older patients in different settings was synthesized into a four-step algorithm for incorporation into clinical assessment protocols for patients, particularly those in residential aged care facilities. Results The algorithm comprises several steps leading to individualized prescribing recommendations: (i) identify a high-risk medication; (ii) ascertain the current indications for the medication and assess their validity; (iii) assess if the drug is providing ongoing symptomatic benefit; and (iv) consider withdrawing, altering or continuing medications. Decision support resources were developed to complement the algorithm in ensuring a systematic and patient-centered approach to medication discontinuation. These include a comprehensive list of high-risk medications and the reasons for inappropriateness, lists of alternative treatments, and suggested medication withdrawal protocols. Conclusions The algorithm captures a range of different clinical scenarios in relation to potentially inappropriate medications, and offers an evidence-based approach to identifying and, if appropriate, discontinuing such medications. Studies are required to evaluate algorithm effects on prescribing decisions and patient outcomes.

Parents as co-researchers at home: Using an observational method to document young children’s use of technology

This paper discusses the use of observational video recordings to document young children’s use of technology in their homes. Although observational research practices have been used for decades, often with video-based techniques, the participant group in this study (i.e., very young children) and the setting (i.e., private homes), provide a rich space for exploring the benefits and limitations of qualitative observation. The data gathered in this study point to a number of key decisions and issues that researchers must face in designing observational research, particularly where non-researchers (in this case, parents) act as surrogates for the researcher at the data collection stage. The involvement of parents and children as research videographers in the home resulted in very rich and detailed data about children’s use of technology in their daily lives. However, limitations noted in the dataset (e.g., image quality) provide important guidance for researchers developing projects using similar methods in future. The paper provides recommendations for future observational designs in similar settings and/or with similar participant groups.

Virus-Specific Cytolytic Antibodies to Nonstructural Protein 1 of Japanese Encephalitis Virus Effect Reduction of Virus Output from Infected Cells

We demonstrate the presence of nonstructural protein 1 (NS1)-specific antibodies in a significant proportion of convalescent-phase human serum samples obtained from a cohort in an area where Japanese encephalitis virus (JEV) is endemic. Sera containing antibodies to NS1 but not those with antibodies to other JEV proteins, such as envelope, brought about complement-mediated lysis of JEV-infected BHK-21 cells. Target cells infected with a recombinant poxvirus expressing JEV NS1 on the cell surface confirmed the NS1 specificity of cytolytic antibodies. Mouse anti-NS1 cytolytic sera caused a complement-dependent reduction in virus output from infected human cells, demonstrating their important role in viral control. Antibodies elicited by JEV NS1 did not cross lyse West Nile virus- or dengue virus-infected cells despite immunoprecipitating the NS1 proteins of these related flaviviruses. Additionally, JEV NS1 failed to bind complement factor H, in contrast to NS1 of West Nile virus, suggesting that the NS1 proteins of different flaviviruses have distinctly different mechanisms for interacting with the host. Our results also point to an important role for JEV NS1-specific human immune responses in protection against JE and provide a strong case for inclusion of the NS1 protein in next generation of JEV vaccines.

Tumour islet Foxp3+ T-cell infiltration predicts poor outcome in nonsmall cell lung cancer

The impact of host immunity on outcome in nonsmall cell lung cancer (NSCLC) is controversial. We examined the relationship between lymphoid infiltration patterns in NSCLC and prognosis. Tumour- and stroma-infiltrating CD3+, CD8+ and forkhead box P3 (Foxp3)+ T-lymphocytes were identified using immunohistochemistry and a novel image analysis algorithm to assess total, cytotoxic and regulatory T-lymphocyte counts, respectively, in 196 NSCLC cases. The median cell count was selected as a cut-point to define patient subgroups and the ratio of the corresponding tumour islet:stroma (TI/S) counts was determined. There was a positive association between overall survival and increased CD8+ TI/S ratio (hazard ratio (HR) for death 0.44, p<0.001) but an inverse relationship between Foxp3+ TI/S ratio and overall survival (HR 4.86, p<0.001). Patients with high CD8+ islet (HR 0.48, p<0.001) and Foxp3+ stromal (HR 0.23, p<0.001) counts had better survival, whereas high CD3+ and CD8+ stromal counts and high Foxp3+ islet infiltration conferred a worse survival (HR 1.55, 2.19 and 3.14, respectively). By multivariate analysis, a high CD8+ TI/S ratio conferred an improved survival (HR 0.48, p=0.002) but a high Foxp3+ TI/S ratio was associated with worse survival (HR 3.91, p<0.001). Microlocalisation of infiltrating T-lymphocytes is a powerful predictor of outcome in resected NSCLC.

Points-to Analysis as a System of Linear Equations

We propose a novel formulation of the points-to analysis as a system of linear equations. With this, the efficiency of the points-to analysis can be significantly improved by leveraging the advances in solution procedures for solving the systems of linear equations. However, such a formulation is non-trivial and becomes challenging due to various facts, namely, multiple pointer indirections, address-of operators and multiple assignments to the same variable. Further, the problem is exacerbated by the need to keep the transformed equations linear. Despite this, we successfully model all the pointer operations. We propose a novel inclusion-based context-sensitive points-to analysis algorithm based on prime factorization, which can model all the pointer operations. Experimental evaluation on SPEC 2000 benchmarks and two large open source programs reveals that our approach is competitive to the state-of-the-art algorithms. With an average memory requirement of mere 21MB, our context-sensitive points-to analysis algorithm analyzes each benchmark in 55 seconds on an average.

The role of the interface in foam-bearing glass-epoxy composites subjected to impact loading

foam, either stacked together as three layers (MC) or inserted at three different positions (3L) while arranging the stacking sequence during the fabrication of glass fiber-epoxy composites, form the subject of investigation. This stacking variation resulted in a different interfacial area between these foam materials and the glass-epoxy regions in the laminates. This area in designed to be maximum for the 3L variety. The energy of impact being high enough to cause development of the crack in the samples, how the change in interfacial area affects the traverse of the crack front and the failure feature of the laminated composite are reported in the form of photomacrographs in this work. The results point to significant changes for the impact data, like for instance the peak load attained by the different samples, through thickness crack propagation and tensile fracture features on the non-impacted end for the plain variety, separation about the mid-zone for the MC laminates and two or more layer separations for the 3L variety. The separation for the foam-bearing systems occur invariably at the interface and here again one of the (two identical) interfaces only is chosen for the separation.

Studies on the variations in compression strengths of graphite powders bearing glass-epoxy composites exposed to humid conditions

The moisture absorption and changes in compression strengths in glass-epoxy (G-E composites without and with discrete quantities of graphite powders introduced into the resin mix prior to its spreading on specific glass fabric (layers) during the lay-up (stacking) sequence forms the subject matter of this report. The results point to higher moisture absorption for graphite bearing specimens. The strengths of graphite-free coupons show a continuous decrease, while the filler bearing ones show an initial rise followed by a drop for larger exposure times. Scanning Fractographic features were examined for an understanding of the process. The observations were explained invoking the effect of matrix plasticizing and the role of interfacial regions.

A token-based distributed algorithm for total order atomic broadcast

In this paper, we propose a new token-based distributed algorithm for total order atomic broadcast. We have shown that the proposed algorithm requires lesser number of messages compared to the algorithm where broadcast servers use unicasting to send messages to other broadcast servers. The traditional method of broadcasting requires 3(N - 1) messages to broadcast an application message, where N is the number of broadcast servers present in the system. In this algorithm, the maximum number of token messages required to broadcast an application message is 2N. For a heavily loaded system, the average number of token messages required to broadcast an application message reduces to 2, which is a substantial improvement over the traditional broadcasting approach.

Ascent Phase Trajectory Optimization of a Generic Launch Vehicle

Trajectory optimization of a generic launch vehicle is considered in this paper. The trajectory from launch point to terminal injection point is divided in to two segments. The first segment deals with launcher clearance and vertical raise of the vehicle. During this phase, a nonlinear feedback guidance loop is incorporated to assure vertical raise in presence of thrust misalignment, centre of gravity offset, wind disturbance etc. and possibly to clear obstacles as well. The second segment deals with the trajectory optimization, where the objective is to ensure desired terminal conditions as well as minimum control effort and minimum structural loading in the high dynamic pressure region. The usefulness of this dynamic optimization problem formulation is demonstrated by solving it using the classical Gradient method. Numerical results for both the segments are presented, which clearly brings out the potential advantages of the proposed approach.

A Randomized Algorithm for Large Scale Support Vector Learning

We propose a randomized algorithm for large scale SVM learning which solves the problem by iterating over random subsets of the data. Crucial to the algorithm for scalability is the size of the subsets chosen. In the context of text classification we show that, by using ideas from random projections, a sample size of O(log n) can be used to obtain a solution which is close to the optimal with a high probability. Experiments done on synthetic and real life data sets demonstrate that the algorithm scales up SVM learners, without loss in accuracy. 1

Online Handwritten Kannada Word Recognizer with Unrestricted Vocabulary

In this paper, we propose a novel heuristic approach to segment recognizable symbols from online Kannada word data and perform recognition of the entire word. Two different estimates of first derivative are extracted from the preprocessed stroke groups and used as features for classification. Estimate 2 proved better resulting in 88% accuracy, which is 3% more than that achieved with estimate 1. Classification is performed by statistical dynamic space warping (SDSW) classifier which uses X, Y co-ordinates and their first derivatives as features. Classifier is trained with data from 40 writers. 295 classes are handled covering Kannada aksharas, with Kannada numerals, Indo-Arabic numerals, punctuations and other special symbols like $ and #. Classification accuracies obtained are 88% at the akshara level and 80% at the word level, which shows the scope for further improvement in segmentation algorithm

Cascaded walks in protein sequence space: use of artificial sequences in remote homology detection between natural proteins

Over the past two decades, many ingenious efforts have been made in protein remote homology detection. Because homologous proteins often diversify extensively in sequence, it is challenging to demonstrate such relatedness through entirely sequence-driven searches. Here, we describe a computational method for the generation of `protein-like' sequences that serves to bridge gaps in protein sequence space. Sequence profile information, as embodied in a position-specific scoring matrix of multiply aligned sequences of bona fide family members, serves as the starting point in this algorithm. The observed amino acid propensity and the selection of a random number dictate the selection of a residue for each position in the sequence. In a systematic manner, and by applying a `roulette-wheel' selection approach at each position, we generate parent family-like sequences and thus facilitate an enlargement of sequence space around the family. When generated for a large number of families, we demonstrate that they expand the utility of natural intermediately related sequences in linking distant proteins. In 91% of the assessed examples, inclusion of designed sequences improved fold coverage by 5-10% over searches made in their absence. Furthermore, with several examples from proteins adopting folds such as TIM, globin, lipocalin and others, we demonstrate that the success of including designed sequences in a database positively sensitized methods such as PSI-BLAST and Cascade PSI-BLAST and is a promising opportunity for enormously improved remote homology recognition using sequence information alone.