nils-herrmann/clean_scirepeval huggingface dataset:
IT Governance Mechanisms in Higher Education

Information technology (IT) has become essential in supporting the growth and sustainability of all types of organizations. Higher education institutions are a special type of organization where technological infrastructure consists of a variety of applications, different platforms, academic systems, cloud applications and heterogeneous technologies. All these technologies for supporting the research, teaching and administrative processes require an effective IT governance framework. The framework of IT governance is composed of structures, processes and relational mechanisms. Each one of these mechanisms has a function and when implemented, should affect the organization positively. The process of identifying the right mechanisms to a specific context is a complex endeavor. This paper looks at the IT governance mechanism that higher education institutions have implemented. We did an extensive literature review making use of databases such as Web of Science, IEEE, SCOPUS, or AIS eLibrary for selecting case studies. We discuss these practices in the context of higher education. To continue this research and improve the IT governance body of knowledge for higher education institutions, future works are pointed out.
Users Profiling Using Clickstream Data Analysis and Classification
Venue: 2016 Cybersecurity and Cyberforensics Conference (CCC)

The nature of today's online communication and the emergence of online social networks have introduced a great challenge related to the identification and the verification of users in web environments. The assumption that every user interact uniquely with a web site provides a baseline for studying user identification based on historical records of user's interactions with specific web site. In this paper, we proposed an approach for using clickstream data to identify users based on their navigational behavior. The study investigates using server side clickstream data collected from previous users' interaction to create a behavioral profile per user. User's profile can be used to identify possible future interactions, which can be associated with distinguishing authenticated user from malicious user. To accomplish this identification, the ability to gather a historical record for user's navigation in a specific web site, is investigated. The goal of the collected data is to use it for training a model that is able to identify if a future interaction can be associated with a certain user.
Synthesis of molecularly imprinted photocatalysts containing low TiO2 loading: Evaluation for the degradation of pharmaceuticals.
Venue: Journal of hazardous materials

A molecularly imprinted (MI) photocatalyst containing a low TiO2 loading (7.00 16.60mgL( 1) of TiO2) was prepared via an acid catalyzed sol gel route using different classes of pharmaceutical compounds (i.e. Atorvastatin, Diclofenac, Ibuprofen, Tioconazole, Valsartan, Ketoconazole and Gentamicine) as the template. Herein, our main goal was to test the hypothesis that photocatalysts based on molecular imprinting may improve the degradation performance of pharmaceutical compounds compared to that of a commercial sample (Degussa P25) due to presence of specific cavities in the silica domain. To elucidate certain trends between the performance of photocatalysts and their structural and textural properties, as well the effect of the structure of the drugs on molecular imprinting, the data were analyzed in terms of pore diameter, pore volume, surface area, zeta potential and six membered ring percentage of silica. In comparison to the commercial sample (P25) we have shown that adsorption and degradation were enhanced from 48 to 752% and from 5 to 427% respectively. A comparison with the control system (non imprinted) indicates that the increased performance of the MI systems was due to the presence of specific cavities on the silica domain, and the textural and structural aspects also support this conclusion. The MI photocatalyst was reusable for seven cycles of reuse in which approximately 60% of its photocatalytic efficiency was preserved for the system containing Diclofenac as the template.
Mental health issues amongst medical students in Asia: a systematic review [2000 2015]
Venue: Annals of translational medicine

Studies have shown that the stress experienced by medical students is far greater than that experienced by other university students. In this study, we aim to understand the consequent mental health issues that are experienced by medical students, particularly in Asia, via a systematic review of the current literature.  Initial searches on MEDLINE, Embase and SpringerLink came up with a total of 1,033 unique articles. Studies not focusing on medical students alone, not mentioning mental health issues or not containing prevalence values were excluded.  We included 14 articles in our analysis. ADs had a prevalence of 7.04% (100/1,420) Depression was prevalent in 11.0% (1,115/10,147) of students. A total of 12.9% (54/420) and 12.9% (41/319) of male and female medical students respectively were screened for depression. Preclinical students were also 1.63 times more likely to be depressed compared to clinical students, with 98.0% (48/49) pre clinical students having screened for depression, compared to 60% (27/45) clinical students. Home staying medical students are 1.33 times more likely to be depressed compared to hostel stayers, with 12.1% (29/239) of home stayers being depressed compared to 9.2% (37/402) of hostel stayers.  We found that mental health issues affect a significant proportion of medical students and they are more prevalent in certain subpopulations of medical students. Our data revealed that preclinical and home staying students can be more susceptible to depression. More research should be done regarding this issue. With such information, it is hoped that appropriate interventions can be designed to improve the mental health of medical students.
Beliefs and perception about mental health issues: a meta synthesis
Venue: Neuropsychiatric disease and treatment

Mental health literacy is the beliefs and knowledge about mental health issues and their remedies. Attitudes and beliefs of lay individuals about mental illness are shaped by personal knowledge about mental illness, knowing and interacting with someone living with mental illness, and cultural stereotypes. Mental health issues are increasing and are alarming in almost every part of the world, and hence compiling this review provides an opportunity to understand the different views regarding mental disorders and problems as well as to fill the gap in the published literature by focusing only on the belief system and perception of mental health problems among general population.  The methodology involved a systematic review and the meta synthesis method, which includes synthesizing published qualitative studies on mental health perception and beliefs. Sample Fifteen relevant published qualitative and mixed method studies, regarding the concept of mental health, were identified for meta synthesis.  All the themes of the selected studies were further analyzed to give a broader picture of mental health problems and their perceived causes and management. Only qualitative studies, not older than 2010, focusing on beliefs about, attitudes toward, and perceptions of mental health problems, causes, and treatments were included in this review.  The findings are divided into four major categories, namely, 1) symptoms of mental health issues, 2) description of mental health issues, 3) perceived causes, and 4) preferred treatment and help seeking behavior. Each category contains themes and subthemes based on published studies.  The findings reveal multiple causes of, descriptions of, and treatment options for mental health problems, thereby providing insight into different help seeking behaviors. Clarity is offered by highlighting cultural differences and similarities in mental health beliefs and perceptions about the causes of mental health problems. The implications of the studies and recommendations based on current findings are also discussed.
'Break a Leg It's all in the mind' Police Officers' Attitudes towards Colleagues with Mental Health Issues

Much has been written about police officer attitudes and interactions with members of the public experiencing mental health issues. However, little has been written or researched regarding police officers attitudes to colleagues with mental health issues. Within policing there is a culture that makes it difficult to discuss psychological injury and mental health with colleagues and managers. To do so is often seen as career destroying. The inherent cynicism associated with policing, lack of empathy, and macho culture further impedes discussion and ultimately access to support services. Austerity has reduced police training. Inadequate training results in officers not understanding mental health issues. There is an argument that personnel policies and systems victimizes officers and fails to understand their needs.
ECONOMIC GROWTH AND PUBLIC DEBT: ADDRESSING UNOBSERVED HETEROGENEITY

The article addresses the non linear and heterogeneous relationship between public debt and economic growth considering the recent combination of increasing public expenditures and debt with continuing low economic growth observed in many countries, controlling the results by an institutional quality multidimensional indicator. Economic theory generally supports a negative relationship between debt and growth in the long run, whereas in the short run fiscal stimulus may induce positive effects. Empirical literature provides some evidence for both, showing that the negative relationship might become more important after reaching a certain threshold, but the results are not absolutely conclusive. Problems of unobserved heterogeneity might be a major reason for that. To tackle the problem of unobserved heterogeneity we suggest a two stage procedure applied to a large sample of 154 countries. We first use cluster analysis to group the countries by their governance quality using the Worldwide Governance Indicators (WGI) database. In a second step the relationship between public debt and growth is investigated using simple and threshold multiple panel regression models (TMR) The results confirm the coefficients to be negative in the long run and to vary across country groups (clusters) depending on institutional quality.
Public Debt and Economic Growth Economic Systems Matter

Most studies on the relationship between public debt and economic growth implicity assume homegenous debt effects across their samples. We in accordance with recent literature challenge this view and state that there likely is a great deal of cross country heterogeneity in that relationship. However, other than scholars assuming that all countries are different, we expect that clusters of countries differ. We identify three country clusters with distinct economic systems: Liberal (Anglo Saxon) Continental (Core EU members) and Nordic (Scandinacian) We argue that different degrees of fiscal uncertainty at comparable levels of public debt between those economic systems constitute a major source of hetergeneity in the debt growth relationship. Our empirical evidence supports this assumption. Continental countries face more growth reducing public debt effects than especially Liberal countries. There, public debt apparently exerts neutral or even positive growth effects, whil for Nordic countries a non linear relationship is discovered, with negative debt effects kicking in at public debt values of around 60% of GDP.
Juvenile Delinquency and Disability

Although the juvenile justice system has made considerable progress over the past century in understanding the developmental differences and implications of juvenile delinquency versus adult criminal behavior, society and the legal system have been slower to acknowledge and respond to potential issues related to juvenile offenders with educational, developmental, mental health, or other disabilities. Over the past few decades, there has been an increase in policy and laws that have worked to better protect the rights of both juvenile and adult offenders with disability. However, learning, understanding, and implementing changes that address issues related to the implications these disabilities may have on how a delinquent functions within the juvenile justice system have lagged. This chapter provides an introduction to issues related to the discussion of juvenile delinquency and disability. General information is provided regarding the prevalence and incidence of various disabilities found among the juvenile delinquency population, as well as theories as to why there is such a high incidence of disabilities in youth in the juvenile justice system.
Multi objective non linear programming problem in intuitionistic fuzzy environment: Optimistic and pessimistic view point
Venue: Expert Syst. Appl.

Multi objective optimization problem under intuitionistic fuzzy environment has been considered.Degree of attainability and non attainability is represented by non linear functions.Optimistic and pessimistic aspect of the problem has been considered.The validity of the problem has been discussed.multiobjective problems arising in the transportation and manufacturing systems have been taken for demonstration. The objective of this manuscript is to present an algorithm for solving multi objective optimization problem under the optimistic and pessimistic view point. The conflicting natures of the different objective have been handled by defining the membership functions corresponding to it in parabolic intuitionistic fuzzy set environment and thus the problem becomes parabolic multi objective non linear optimization programming problem (PMONLOPP) A linear and non linear membership functions corresponding to each objective has been taken in account. An illustrative examples from transportation as well as in manufacturing systems are reported and compared with the typical approaches exist in the literature. As shown, the solutions obtained by the proposed approach are superior to those of existing best solutions reported in the literature. Further more, experimental results indicate that the proposed approach may yield better solutions to these types of problems than those obtained by using current algorithms.
Video Recording Mobile Phone Camera of Micro Teaching Subject in Teaching Skills of Students Teacher The Case of Students Teacher Education in Islamic Kalimantan University MAB Banjarmasin

Teacher training and education programme has activities that are in the form of lecture intended to train students to have experience with factual and technical readiness about the learning process, and basic skills learning which can then be used in preparation to develop themselves as prospective educators before plunging into school. The research design is qualitative research. This study investigated the perceptions of student teachers to video recording mobile phone camera as the media in teaching micro teaching. The data were collected through in depth semi structured interviews with 18 student teachers in English Department Programme of Faculty of Teacher Training Education of Islamic Kalimantan University MAB Banjarmasin. Participatns indicated that they used video recording handphone camera in learning/exploring theory of teaching practice of hands on experience. The research has also shown that by using video recording handphone camera the students had more to do teaching practice, as they need the application skills of teaching. Based on the findings in this study, it is recommended that the teacher education training programme in Islamic Kalimantan University recomended increase the amount of time for teaching practice for student teachers by using video recording handphone camera.
High Performance and Dynamically Updatable Packet Classification Engine on FPGA
Venue: IEEE Transactions on Parallel and Distributed Systems

High performance and dynamically updatable hardware architectures for multi field packet classification have regained much interest in the research community. For example, software defined networking requires 15 fields of the packets to be checked against a predefined rule set. Many algorithmic solutions for packet classification have been studied over the past decade. FPGA based packet classification engines can achieve very high throughput; however, supporting dynamic updates is yet challenging. In this paper, we present a two dimensional pipelined architecture for packet classification on FPGA; this architecture achieves high throughput while supporting dynamic updates. In this architecture, modular Processing Elements (PEs) are arranged in a two dimensional array. Each PE accesses its designated memory locally, and supports prefix match and exact match efficiently. The entire array is both horizontally and vertically pipelined. We exploit striding, clustering, dual port memory, and power gating techniques to further improve the performance of our architecture. The total memory is proportional to the rule set size. Our architecture sustains high clock rate even if we scale up (1) the length of each packet header, or/and (2) the number of rules in the rule set. The performance of the entire architecture does not depend on rule set features such as the number of unique values in each field. The PEs are also self reconfigurable; they support dynamic updates of the rule set during run time with very little throughput degradation. Experimental results show that, for a 1 K 15 tuple rule set, a state of the art FPGA can sustain a throughput of 650 Million Packets Per Second (MPPS) with 1 million updates/second. Compared to TCAM, our architecture demonstrates at least four fold energy efficiency while achieving two fold throughput.
Multilayer Packet Classification With Graphics Processing Units
Venue: IEEE/ACM Transactions on Networking

The rapid growth of server virtualization has ignited a wide adoption of software based virtual switches, with significant interest in speeding up their performance. In a similar trend, software defined networking (SDN) with its strong reliance on rule based flow classification, has also created renewed interest in multi dimensional packet classification. However, despite these recent advances, the performance of current software based packet classifiers is still limited, mostly by the low parallelism of general purpose CPUs. In this paper, we explore how to accelerate packet classification using the high parallelism and latency hiding capabilities of graphic processing units (GPUs) We implement GPU accelerated versions for both linear and tuple search, currently deployed in virtual switches, and also introduce a novel algorithm called Bloom search. These algorithms are integrated with high speed packet I/O to build GSwitch, a GPU accelerated software switch, and also to extend Open vSwitch. Our experimental evaluation indicates that, under realistic rule sets, GSwitch is at least 7 x faster than an equally priced CPU classifier. We also show that our GPU accelerated Open vSwitch outperforms the classic Open vSwitch implementation by a factor of 10, on average.
Bilateral symmetry in vision and influence of ocular surgical procedures on binocular vision: A topical review
Venue: Journal of optometry

We analyze the role of bilateral symmetry in enhancing binocular visual ability in human eyes, and further explore how efficiently bilateral symmetry is preserved in different ocular surgical procedures. The inclusion criterion for this review was strict relevance to the clinical questions under research. Enantiomorphism has been reported in lower order aberrations, higher order aberrations and cone directionality. When contrast differs in the two eyes, binocular acuity is better than monocular acuity of the eye that receives higher contrast. Anisometropia has an uncommon occurrence in large populations. Anisometropia seen in infancy and childhood is transitory and of little consequence for the visual acuity. Binocular summation of contrast signals declines with age, independent of inter ocular differences. The symmetric associations between the right and left eye could be explained by the symmetry in pupil offset and visual axis which is always nasal in both eyes. Binocular summation mitigates poor visual performance under low luminance conditions and strong inter ocular disparity detrimentally affects binocular summation. Considerable symmetry of response exists in fellow eyes of patients undergoing myopic PRK and LASIK, however the method to determine whether or not symmetry is maintained consist of comparing individual terms in a variety of ad hoc ways both before and after the refractive surgery, ignoring the fact that retinal image quality for any individual is based on the sum of all terms. The analysis of bilateral symmetry should be related to the patients' binocular vision status. The role of aberrations in monocular and binocular vision needs further investigation.
Automating Feature Engineering

Engineering is the task of transforming the feature space in a given learning problem to improve the performance of a trained model. It is a crucial but timeintensive and skillful process, involving a data scientist or a domain expert. It is often the key determinant of the time and cost required to build an effective learner. In this paper, we discuss our system for performing feature engineering in an automated manner using a combination of exploratory and learning techniques. We also mention our larger charter of an automated data science pipeline.
Cognito: Automated Feature Engineering for Supervised Learning
Venue: 2016 IEEE 16th International Conference on Data Mining Workshops (ICDMW)

Feature engineering involves constructing novel features from given data with the goal of improving predictive learning performance. Feature engineering is predominantly a human intensive and time consuming step that is central to the data science workflow. In this paper, we present a novel system called "Cognito" that performs automatic feature engineering on a given dataset for supervised learning. The system explores various feature construction choices in a hierarchical and non exhaustive manner, while progressively maximizing the accuracy of the model through a greedy exploration strategy. Additionally, the system allows users to specify domain or data specific choices to prioritize the exploration. Cognito is capable of handling large datasets through sampling and built in parallelism, and integrates well with a state of the art model selection strategy. We present the design and operation of Cognito, along with experimental results on eight real datasets to demonstrate its efficacy.
Automated feature discovery via sentence selection and source code summarization
Venue: J. Softw. Evol. Process.

Programs are, in essence, a collection of implemented features. Feature discovery in software engineering is the task of identifying key functionalities that a program implements. Manual feature discovery can be time consuming and expensive, leading to automatic feature discovery tools being developed. However, these approaches typically only describe features using lists of keywords, which can be difficult for readers who are not already familiar with the source code. An alternative to keyword lists is sentence selection, in which one sentence is chosen from among the sentences in a text document to describe that document. Sentence selection has been widely studied in the context of natural language summarization but is only beginning to be explored as a solution to feature discovery. In this paper, we compare four sentence selection strategies for the purpose of feature discovery. Two are off the shelf approaches, while two are adaptations we propose. We present our findings as guidelines and recommendations to designers of feature discovery tools.