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Topic Review
Diaspora
Diaspora is a free personal web server that implements a distributed social networking service. Installations of the software form nodes (termed "pods") which make up the distributed Diaspora social network. The project was founded by Dan Grippi, Maxwell Salzberg, Raphael Sofaer and Ilya Zhitomirskiy, students at New York University's Courant Institute of Mathematical Sciences. The group received crowdfunding in excess of $200,000 via Kickstarter. A consumer alpha version was released on 23 November 2010. Konrad Lawson, blogging for the Chronicle of Higher Education, suggested Diaspora in July 2011 as an alternative to corporately produced software.
  • 723
  • 09 Nov 2022
Topic Review
Reminiscence Therapy in Depression Treatment in the Elderly
Reminiscence therapy is a mechanism to help someone remember events from their life. It is often used as a therapy tool for reducing depression, calming behavioral and psychological symptoms of dementia, or affecting mood of the elderly. Although its most common use is for the elderly and people affected with dementia or depression, it has also been used with people of all ages, including children. The reminiscing process can take place in a group or individually or by using technological devices such as mobile devices or robots. It is marked by remembering notable events from the past.
  • 723
  • 03 Mar 2022
Topic Review
Lithium Technologies
Lithium Technologies is a San Francisco-based provider of software that allows businesses to connect with their customers on social media and digital channels. Lithium was founded in 2001 as a spin-out from GX Media, which created technologies for professional rankings and tournaments and now hosts a number of popular gaming sites. The company's founders include Dennis Fong, Lyle Fong, Michel Thouati, Kirk Yokomizo, John Joh, Nader Alizadeh, Michael Yang, and Matt Ayres. The Lithium platform comprises a set of products for digital marketing and social customer support, including Lithium Communities, which act as the hub for a brand's digital conversations; Lithium Response, a social customer care tool; and Lithium Reach a social media management tool. Klout data powers the Lithium platform with its proprietary algorithms and volume of data with over 750M scored profiles." Lithium's SaaS platform combines online customer community applications such as forums, blogs, innovation management, product reviews, and tribal knowledge bases with the broader social web and traditional CRM business processes, resulting in a wide range of online customer interaction methods. Stemming from its gaming roots, the platform incorporates elaborate rating systems for contributors, with ranks, badges, and "kudos counts". Lithium hosts an annual user conference, LiNC (Lithium Networking Conference) designed to give digital strategists a deeper understanding of trends in social customer engagement. Since its inception in 2008, the event has grown 1,100% to 900+ attendees in 2016. In 2017, the company held a series of localized LiNC events in cities like London, San Francisco, and Sydney.
  • 722
  • 18 Nov 2022
Topic Review
Speaker Recognition Systems
Along with the prevalence and increasing influence of the speaker recognition technology, its security has drawn broad attention. Though speaker recognition systems (SRSs) have reached a high recognition accuracy, their security remains a big concern since a minor perturbation on the audio input may result in reduced recognition accuracy.
  • 721
  • 28 Jul 2022
Topic Review
Machine Learning in Smart Farming
Machine learning applications are having a great impact on the global economy by transforming the data processing method and decision making. Agriculture is one of the fields where the impact is significant, considering the global crisis for food supply. 
  • 721
  • 01 Sep 2023
Topic Review
Information System for Security Auditing
Information security and cybersecurity management play a key role in modern enterprises. There is a plethora of standards, frameworks, and tools, ISO 27000 and the NIST Cybersecurity Framework being two relevant families of international Information Security Management Standards (ISMSs). Globally, these standards are implemented by dedicated tools to collect and further analyze the information security auditing that is carried out in an enterprise. The overall goal of the auditing is to evaluate and mitigate the information security risk. The risk assessment is grounded by auditing processes, which examine and assess a list of predefined controls in a wide variety of subjects regarding cybersecurity and information security. For each control, a checklist of actions is applied and a set of corrective measures is proposed, in order to mitigate the flaws and to increase the level of compliance with the standard being used. The auditing process can apply different ISMSs in the same time frame. However, as these processes are time-consuming, involve on-site interventions, and imply specialized consulting teams, the methodology usually adopted by enterprises consists of applying a single ISMS and its existing tools and frameworks. This strategy brings overall less flexibility and diversity to the auditing process and, consequently, to the assessment results of the audited enterprise.
  • 721
  • 05 May 2022
Topic Review
Adversarial Machine Learning Attacks against Intrusion Detection Systems
Concerns about cybersecurity and attack methods have risen in the information age. Many techniques are used to detect or deter attacks, such as intrusion detection systems (IDSs), that help achieve security goals, such as detecting malicious attacks before they enter the system and classifying them as malicious activities. However, the IDS approaches have shortcomings in misclassifying novel attacks or adapting to emerging environments, affecting their accuracy and increasing false alarms. To solve this problem, researchers have recommended using machine learning approaches as engines for IDSs to increase their efficacy. Machine-learning techniques are supposed to automatically detect the main distinctions between normal and malicious data, even novel attacks, with high accuracy. However, carefully designed adversarial input perturbations during the training or testing phases can significantly affect their predictions and classifications. Adversarial machine learning (AML) poses many cybersecurity threats in numerous sectors that use machine-learning-based classification systems, such as deceiving IDS to misclassify network packets.
  • 720
  • 09 Mar 2023
Topic Review
PET/CT Radiomics in Lung Cancer
Quantitative extraction of imaging features from medical scans (‘radiomics’) has become a major research topic in recent years. Numerous studies have emphasized the potential use of radiomics for computer-assisted diagnosis, as well as for predicting survival and response to treatment in patients with lung cancer. Furthermore, radiomics is appealing in that it enables full-field analysis of the lesion, provides nearly real-time results, and is non-invasive.
  • 719
  • 17 Feb 2021
Topic Review
Analytica
Analytica is a visual software developed by Lumina Decision Systems for creating, analyzing and communicating quantitative decision models. It combines hierarchical influence diagrams for visual creation and view of models, intelligent arrays for working with multidimensional data, Monte Carlo simulation for analyzing risk and uncertainty, and optimization, including linear and nonlinear programming. Its design, especially its influence diagrams and treatment of uncertainty, is based on ideas from the field of decision analysis. As a computer language, it combines a declarative (non-procedural) structure for referential transparency, array abstraction, and automatic dependency maintenance for efficient sequencing of computation.
  • 719
  • 25 Oct 2022
Topic Review
Central Bank Digital Currency
Due to the growth of the internet and communication technologies, electronic financial systems are becoming popular. Physical cash is losing its preeminence, and digital numbers on computers represent money. However, electronic financial systems, mostly operated by private entities, have defects to be compensated for, such as high charges for using the system, security issues, and the problem of exclusion. As a solution, many countries around the world are considering central bank digital currency. For central bank digital currency to be utilized as a national legal tender, it must be universal and accessible regardless of time and place, similar to physical cash. Therefore, offline payment functions that extend the accessibility of central bank digital currency are becoming attractive.
  • 719
  • 26 May 2022
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