Internet Monitoring Research Articles

Big data for bipolar disorder.

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

E-learning in a Philippine University Tourism and Hospitality Program: Perceptions of Students and Faculty

This study examines the perceptions of students and faculty on the use of an e-learning module in a tourism and hospitality program offered in a non-sectarian autonomous university with four campuses. A self-paced course by a third party was offered to selected tourism and hospitality students. Instructional materials are in the form of presentation slides with audio, video, and flip books. Evaluation of the course was solicited through an online survey conducted for students and faculty, and interviews with administrators. Results indicate positive reception among students, faculty and administrators and recommendations on internet infrastructure and monitoring procedures for the succeeding classes.

Digital cleansing? A look into state-sponsored policing of Ethiopian networked communities

ABSTRACTIn June 2015, the National Election Board of Ethiopia announced that the incumbent Ethiopian People's Revolutionary Democratic Front (EPRDF) and its affiliates had won 100 per cent of the House of People's Representatives seats. The results have extended Ethiopia's anocratic one-party rule since the EPRDF ousted the former military dictatorship through armed struggle in 1991. Despite earlier promises of democratic reform, the EPRDF has increasingly become a self-proclaimed vanguard party at the expense of political inclusivity, continuing its attempts to validate its longevity through a ‘developmentalism’ rhetoric, which frames alternative speech as heresy, and at times a crime. One notable consequence of this hegemonic thinking is an alarming invisibility of plurality in the traditional Ethiopian media landscape. Drawing from hegemonic notions of development statism, this article looks at the extent to which digital platforms have become viable alternatives to traditional electronic and print media in Ethiopia. I argue that, despite its potential to promote freedom of speech, the Ethiopian online sphere is systematically policed through state-sanctioned legal frameworks. Through analysis of an online survey, I also demonstrate how perceptions of users about online experiences show skepticism toward the role of the Ethiopian state in Internet monitoring.

Big data are coming to psychiatry: a general introduction.

Big data are coming to the study of bipolar disorder and all of psychiatry. Data are coming from providers and payers (including EMR, imaging, insurance claims and pharmacy data), from omics (genomic, proteomic, and metabolomic data), and from patients and non-providers (data from smart phone and Internet activities, sensors and monitoring tools). Analysis of the big data will provide unprecedented opportunities for exploration, descriptive observation, hypothesis generation, and prediction, and the results of big data studies will be incorporated into clinical practice. Technical challenges remain in the quality, analysis and management of big data. This paper discusses some of the fundamental opportunities and challenges of big data for psychiatry.

Flexible benchmarking: a new reference model

Purpose – The purpose of this paper is to describe and propose a new way to do benchmarking. It describes an explanatory case study whereby data are collected through an internet benchmarking system with multi-criteria performance. Design/methodology/approach – The research methodology was to conduct a literature review on international journals about evolution, typology and trends of benchmarking. Through a third year case study of Internet Benchmarking and Monitoring System of Productive Arrangements System the authors describe and propose a flexible benchmarking model. Findings – The paper provides empirical insights about a new model of flexible benchmarking taking into account different demands, whereby partners’ data are collected and processed according to their needs. Research limitations/implications – For monitoring and trending analysis more data and time is needed. These three-year applications show that it takes a long time to build a database that can be meaningful for benchmarking and monitoring purposes management. It also requires management maturity, performance system and finally procedures to invite companies to collect and input online data. Practical implications – The paper describes a flexible benchmarking, detailing its features in the form of a case study. The gap analysis shows the individual and collective gaps and requirements. Examples of practical use and reports generated “online” are presented. Originality/value – The paper presents a new potential for the use of benchmarking tools. It is expected to contribute to the academic area, describing ways to achieve greater potential in the use of benchmarking tools, proposing a new way to do benchmarking.

Psyclones: a roller coaster of life? Hidden synthetic cannabinoids and stimulants in apparently harmless products.

The urge to gain information on a new drug marketed online as 'Psyclone' has emerged after the death of a 38-year-old man in Bolton (UK). The fatality appeared to be a consequence of smoking this psychoactive product. From October to December 2013, qualitative searches of the Web have been carried out in English and Italian, using the keywords 'Psyclone', 'Psyclone legal high', 'Psyclone incense' and 'Psyclone research chemical' on the Google search engine and on the database provided by the Global Public Health Intelligence Network. Our research highlighted the existence of two psychoactive products labelled as Psyclone but with different contents and packaging: a herbal blend containing two synthetic cannabinoids (AKB-48 and 5f-PB-22) and a research chemical containing 50% ethylphenidate, 30% caffeine and 20% lidocaine. Desired and side effects of both compounds are explored in the paper. Being sold as a legal product, Psyclone may appeal to recreational users, who remain unaware of its real content. This is a serious public health threat, which may lead to acute intoxications and fatalities. Further studies in the field, including Internet monitoring, are therefore required.

Accounting and Finance Teaching Enjoyment & Pedagogy for Quality Enhancements, Establishments and Empowerments

Teachers are the facilitators for the accounting and finance students. To facilitate, they should share the practical and theoretical knowledge, what they acquired during their education and experiences. Students must enjoy the teaching. Learn to Teach and Teach to Learn should be the moto of accounting and finance teachers. Accounting and Finance Education must be focused to the subjects for which the pedagogy must be adopted using chalk & talk, audio, videos, games, assignments, surprise quizzes, case studies, research projects, group discussions, seminar presentations, guest lectures, workshops, written exams on computer, evaluations through the software, industrial visits, good communication skills, infrastructures of the classroom, digital libraries, laptops with internet connection, monitoring and scrutinizing, transparency, 360 degree evaluation and eagle eyes are very important to promote the stream which help to improve and sustain the subjects also to the real economy development with proper discipline system in Ethiopia.

An Experimental Study of Influential Elements on Cyberloafing from General Deterrence Theory Perspective Case Study: Tehran Subway Organization

Cyber-loafing is a virtually new phenomenon from the old problem of loafing at work places. The internet has alone made remarkable changes in today’s organizations, although has brought many concerns and pitfalls for efficiency and effectiveness in working hours. This study, by the means of General Deterrence Theory and rational choice theory, examined the role of rules and regulations against cyber-slacking and the effect of detection and past enforcement of punishments in Tehran subway organization. The results of this study revealed that severe regulations against cyber-loafers will decrease the intention to cyber-loaf. Moreover, the existence of appropriate detection mechanisms like internet monitoring systems, the awareness of past enforcement of strict retributions among employees, and abusiveness perception of a particular internet activity will substantially lower the chance of being involved in internet abuse in work places.

Methods and resources to monitor internet censorship

Purpose – The purpose of this paper is to raise awareness of the importance for library and information services (LIS) to take the responsibility to find a manageable way to regularly monitor internet censorship in their countries, and to suggest a framework for such monitoring and to encourage manageable on-going small scale research projects. Design/methodology/approach – The paper follows on contract research for the IFLA Committee on Freedom of Access to Information and Freedom of Expression on country specific trends in internet censorship. Based on an extensive literature survey (not fully reflected here) and data mining, a framework is suggested for regular monitoring of country specific negative and positive trends in internet censorship. The framework addresses search strategies and information resources; setting up alerting services; noting resources for data mining; a detailed break-down and systematic monitoring of negative and positive trends; the need for reflection on implications, assessment of need(s) for concern (or not) and generation of suggestions for actions; sharing findings with the LIS community and wider society; and raising sensitivity for internet censorship as well as advocacy and lobbying against internet censorship. Apart from monitoring internet censorship, the framework is intended to encourage manageable on-going small scale research. Findings – A framework of internet censorship monitoring can support the regular, systematic and comprehensive monitoring of known as well as emerging negative and positive trends in a country, and can promote timely expressions of concerns and appropriate actions by LIS. It can support sensitivity to the dangers of internet censorship and raise LIS’ levels of self-efficacy in dealing with internet censorship and doing manageable, small scale research in this regard. Originality/value – Although a number of publications have appeared on internet censorship these do not offer a framework for monitoring internet censorship and encouraging manageable on-going small scale research in this regard.

Social Media and Online Reputation Management as Practice

Intensive consumer participation on social media has raised new challenges in terms of reputation management and CRM. This paper tackles the issue of online reputation management in the era of social media (SM). It explores the practices of SM managers using a qualitative research methodology based mainly on online observation and in-depth interviews with practitioners. It is not simply a case of stating what SM and online reputation management could or should be but of identifying what it is from within, from the field analysis of the discourse and practices of professionals. The analysis of the results reveals that online reputation management is organised around five main activities and SM managers have to play five roles relating to various issues and competences. It is also evident that online reputation management is at the interface of Internet monitoring, online communication and social CRM. Finally, companies are not considering social CRM as much as customers would like.

Using Opinion Mining Techniques for Early Crisis Detection

The goal of our research is to investigate the use of internet monitoring in crisis management using linguistic processing and text mining techniques. We present a system that detects and classifies events on topics and, using an altered opinion mining workflow, detects geographical entities related to these events and the sentiments expressed towards them. The results are displayed in customized GoogleMaps views, indicating areas with a potential risk, such as natural disasters, unfavorable weather or threatening protests. All the processing is done in real time and, depending on the monitored sources, our work could be of used as a population warning system, but it could also be useful for regional or local authorities in managing intervention time and resources by prioritizing the situations for which they have to act.

High-Throughput Content-Based Video Analysis Technologies

Under the environment of Big Data, how to analyze the content of high concurrent video data is a scientific problem which requires urgent solution. In this paper, we introduce the technologies about highthroughput content-based video analysis for content-based monitoring of web images and videos. We give an intensive survey on the state of the developments and trends in four key technologies: efficient video decoding and feature extraction with mass-core processors, and high-dimensional indexing and semantic recognition on distributed systems. Furthermore, we introduce our latest research works on these technologies: parallel deblocking filter on mass-core processor, extraction and mining of highly robust and parallel local features, high-dimensional distributed indexing, ensemble learning for large scale data, so as to take full advantages of high performances of multi-grain parallel computing platforms for the purpose of providing key technologies for the important applications such as Internet video monitoring and search, etc.

To monitor or not to monitor: Effectiveness of a cyberloafing countermeasure

The goal of this study is to explore and analyze the effectiveness of a possible countermeasure to the so-called “cyberloafing” problem involving a technical solution of Internet filtering and monitoring. Through a multi-theoretical lens, we utilize operant conditioning and individuals’ psychological morals of procedural justice and social norms to study the effectiveness of this countermeasure in addressing the associated agency problem and in promoting compliance with an organization's Internet usage policies. We find that in addition to the blocking module, confirmation and quota modules of an Internet filtering and monitoring system can prevent shirking and promote better compliance through employee empowerment and attention resource replenishment.

Research on the Monitoring of Internet with Public Opinions Based on Micro-Blog in Universities

It is so important to monitor Internet public opinions based on micro-blog in universities that universities are able to grasp public opinion trends comprehensively and to make correct guidance of public opinion timely. In this paper, we propose a monitoring platform of micro-blog public opinions via combining artificial participation with computer technologies. The technologies of search engine and date mining are applied to this platform including topic detection and tracking, hotspot detection and emotional tendency analysis to mine and monitor micro-blog public opinion automatically. This platform is able to make full use of the advantages of the professional group of micro-blog public opinion monitoring to increase the effectiveness and efficiency of monitoring and guidance work of micro-blog Internet public opinions in universities.

Implementation of Lightweight BHO Hijack Technology for Online Behavior Monitoring

With the increasingly wide range of Internet applications, Internet behavior monitoring aroused widespread concern. With BHO hijacking techniques to build an efficient monitoring system, not only can achieve real-time monitoring online behavior, but also has a lightweight characteristics, not only that, but also be able to effectively shield the site or filtered, to avoid unauthorized users from bad web , but also effectively prevent the illegal intrusion of the Web page. In the system design process, the application, the application of advanced signal report have both modular design strategy, so that the system has relatively broad applicability and can be private users, the user unit may be, in addition, the system In the communication efficiency is relatively good. In short, the Internet behavior of the monitoring system has won the people's widespread recognition.

Winning Public Opinion Online: China's Internet Content Control

The Chinese authorities have demonstrated great capability in putting online activities under strict surveillance. A comprehensive and complex system of internet monitoring and censorship has been established, consisting of the Great Firewall, online content control and targeted suppression, as well as an army of online commentators. Since Xi assumed leadership in late 2012, Beijing has shown considerable determination to win “public opinion” in the cyber world.

A permanent Raman lidar station in the Amazon: description, characterization, and first results

Abstract. A permanent UV Raman lidar station, designed to perform continuous measurements of aerosols and water vapor and aiming to study and monitor the atmosphere from weather to climatic time scales, became operational in the central Amazon in July 2011. The automated data acquisition and internet monitoring enabled extended hours of daily measurements when compared to a manually operated instrument. This paper gives a technical description of the system, presents its experimental characterization and the algorithms used for obtaining the aerosol optical properties and identifying the cloud layers. Data from one week of measurements during the dry season of 2011 were analyzed as a mean to assess the overall system capability and performance. Both Klett and Raman inversions were successfully applied. A comparison of the aerosol optical depth from the lidar and from a co-located Aerosol Robotic Network (AERONET) sun photometer showed a correlation coefficient of 0.86. By combining nighttime measurements of the aerosol lidar ratio (50–65 sr), back-trajectory calculations and fire spots observed from satellites, we showed that observed particles originated from biomass burning. Cirrus clouds were observed in 60% of our measurements. Most of the time they were distributed into three layers between 11.5 and 13.4 km a.g.l. The systematic and long-term measurements being made by this new scientific facility have the potential to significantly improve our understanding of the climatic implications of the anthropogenic changes in aerosol concentrations over the pristine Amazonia.

A Model of Ecological Monitoring and Response System for Internet Public Opinion

With the popularization and application of the internet, traditional pattern of public opinion has changed basically, and internet public opinion is cause for more and more concern. Among it, the monitoring and response to internet public opinion has become a new important task around the world. Based on the theory of internet public opinion ecology system’s constitutes, this paper built up an internet ecological monitoring and response system model, including public opinion monitoring information collection, analysis, and response modules, and discussed how to monitor and respond to internet public opinion, how to transform passive response to active research management, and make rational decisions, not emotional decisions. This has certain significance for the establishment of specific systems, and the study internet public opinion scientific, systematic.

Applied-Information Technology in Research of Security Processing Based on IOT Data

Internet of things (IOT) has become an important trend in the development of information technology. How to deal with huge amounts of internet data is becoming more and more important. In this paper, we have a further research in the technology of applied-information about mass content of network data security processing model. This model is mainly composed of massive internet of data acquisition, data storage, based on the rules of mass data processing and data security management, etc. The model can be applied to all kinds of massive internet data monitoring system based on rules, such as: the lake water quality monitoring system based on Internet of things, PM2.5 monitoring system, and so on.

Google Searches for Suicide and Risk of Suicide

Routine surveillance of the incidence of disease comprises a core function of federal and regional public health programs (1). Surveillance systems for mental disorders, however, remain underdeveloped despite strong temporal variation in their incidence. Recently Google, the most commonly used search engine in the world, launched “Google Trends.” This website allows the public to gather statistics on queries to the Google.com search engine. To the extent that depression—a key risk factor for suicide—and suicidal ideation presage an increased risk of suicide completion, surveillance of Google Trends queries may assist with focused bursts of suicide prevention efforts. We tested whether suicide-related Google searches predict the monthly incidence of completed suicides. We examined England and Wales given their publicly available suicide database and their high societal cost of premature death due to suicide (i.e., $9.2 billion in 2009 alone) (2). We retrieved the incidence of suicide in England and Wales for January 2004 to December 2010, the longest series that overlaps with internet-based suicide queries. We defined suicide using conventional ICD-10 classification schemes. We used as independent variables the monthly internet-based queries on a series of search terms within England and Wales, drawn from previous literature, that relate to suicide ideation (3,4). We examined three distinct sets of terms: suicide methodology (“suicide”, “suicide” and “methods”), depressive symptoms (terms: “suicide” and “depression”, “depression”, “depression” and “help”), and suicide help (terms: “suicide” and “help”). To statistically control for temporal patterns in suicide (e.g., seasonality, trend), we applied rigorous time-series routines (see Appendix) (5). We further controlled for the unemployment rate and Google searches in the news, which often peak following suspected suicides of popular personalities (e.g., Amy Winehouse) but may not signal increased help-seeking or depression. In the three searches that included the term “depression,” we find a positive relation with search volume and suicide in that same month (see Appendix). The strongest positive relation occurs between the “depression and help” Google Trends query and suicide incidence in the same month (coef. at lag 0 months = .0045, standard error [SE] = .0014, p=.002). We estimate that Google searches statistically account for a seven percent increase in suicides during months in which search volume for “depression” increased. However, none of the internet searches predict the incidence of suicide in the following month. We, moreover, find no relation between “suicide” or “suicide and methods” searches and suicide incidence We caution the reader against inferring an individual’s internet search behavior, depressive symptoms and their risk of suicide from our population-level tests. Temporal fluctuations in Google searches, rather, gauge a population-level interest which cannot shed light on individual differences in suicide risk. In addition, our findings of a positive relation between internet search volume for “suicide and depression” and completed suicide in the same month cannot definitively establish that suicide-related searches precede suicide completion. Nevertheless, our findings in England and Wales indicate that current surveillance efforts for suicide may benefit from the real-time use of Google-based internet searches for depression.