East Asia's dynamic development model and the Republic of Korea's experiences

No region has been more dynamic in recent years than East Asia. Despite its successful economic development, evaluations of the East Asian development model have often been capricious, shifting from"miracle"to"cronyism."How can we explain East Asia's ups and downs consistently? To respond to this challenge, it is necessary to study the progress of East Asian development and to trace the influence of Asian cultural values. This study mainly focuses on cultural aspects of economic progress and analyzes East Asia's philosophical and historical backgrounds to explain the dynamic process. East Asians believe that balance between opposite but complementary forces, Yin and Yang, will ensure social stability and progress. Through repeated rebalancing to maintain harmony, the society comes to maturity. In traditional East Asian societies, a balance was maintained between Confucianism (Yang) and Taoism, Buddhism, and other philosophies (Yin). In modern societies, the challenge is to balance traditional systems (Yang) and Western style capitalism (Yin). This East Asian development model explains the Republic of Korea's rise, fall, and recovery. Korea was a poor country until the early 1960s, during the time when spiritualism (Yang) dominated. From the 1960s through the 1980s, Korea achieved rapid growth by finding a new balance and moving toward materialism (Yin) from spiritualism (Yang). But the failure to maintain a harmonious balance between cooperative systems and collectivism (Yang) and individualism (Yin) led to major weaknesses in labor and financial markets that contributed significantly to the financial crisis in 1997. As Korea arrived at a new balance by instituting reform programs, the venture-oriented information and communication technology (ICT) industry blossomed and led to a rapid economic recovery. Since 2000, domestic financial scandals and political corruption have emerged as new social issues. Korea's next challenge is to find a new harmonization between morality (Yang) and legal frameworks (Yin).Environmental Economics&Policies,Public Health Promotion,Ethics&Belief Systems,Earth Sciences&GIS,Decentralization,Earth Sciences&GIS,Ethics&Belief Systems,Economic Theory&Research,Environmental Economics&Policies,Health Economics&Finance

Leader Member Exchange: An Interactive Framework to Uncover a Deceptive Insider as Revealed by Human Sensors

This study intends to provide a theoretical ground that conceptualizes the prospect of detecting insider threats based on leader-member exchange. This framework specifically corresponds to two propositions raised by Ho, Kaarst-Brown et al. [42]. Team members that are geographically co-located or dispersed are analogized as human sensors in social networks with the ability to collectively “react” to deception, even when the act of deception itself is not obvious to any one member. Close interactive relationships are the key to afford a network of human sensors an opportunity to formulate baseline knowledge of a deceptive insider. The research hypothesizes that groups unknowingly impacted by a deceptive leader are likely to use certain language-action cues when interacting with each other after a leader violates group trust

Trustworthiness in Virtual Organizations

This study examines perceptions of human trustworthiness as a key component in countering insider threats. The term insider threat refers to situations where a critical member of an organization behaves against the interests of the organization, in an illegal and/or unethical manner. Identifying how an individual’s behavior varies over time - and how anomalous behavior can be detected - are important elements in the preventive control of insider threat behaviors in securing cyber infrastructure. Using online team-based game-playing, this study seeks to re-create realistic insider threat situations in which human “sensors” can observe changes in a target’s behavior. The intellectual merit of this socio-technical study lies in its capability to tackle complex insider threat problems by adopting a social psychological theory on predicting human trustworthiness in a virtual collaborative environment. The study contributes to a theoretical framework of trustworthiness attribution, and gameplaying methodology to predict the occurrence of malfeasance

Addressing Health Disparities in Middle School Students’ Nutrition and Exercise

Those with low income, especially women of African American and Hispanic heritage have the greatest risk of inactivity and obesity. A 4-session (Internet and video) intervention with healthy snack and gym labs was tested in 2 (gym lab in 1) urban low–middle-income middle schools to improve low fat diet and moderate and vigorous physical activity.1 The gym lab was particularly beneficial (p = .002). Fat in diet decreased with each Internet session in which students participated. Percentage of fat in food was reduced significantly p = .018 for Black, White, and Black/Native American girls in the intervention group. Interventions delivered through Internet and video may enable reduction of health disparities in students by encouraging those most at risk to consume 30% or less calories from fat and to engage in moderate and vigorous physical activity

Cyber Forensics on Internet of Things: Slicing and Dicing Raspberry Pi

Any device can now connect to the Internet, and Raspberry Pi is one of the more popular applications, enabling single-board computers to make robotics, devices, and appliances part of the Internet of Things (IoT). The low cost and customizability of Raspberry Pi makes it easily adopted and widespread. Unfortunately, the unprotected Raspberry Pi device—when connected to the Internet—also paves the way for cyber-attacks. Our ability to investigate, collect, and validate digital forensic evidence with confidence using Raspberry Pi has become important. This article discusses and presents techniques and methodologies for the investigation of timestamp variations between different Raspberry Pi ext4 filesystems (Raspbian vs. UbuntuMATE), comparing forensic evidence with that of other ext4 filesystems (i.e., Ubuntu), based on interactions within a private cloud, as well as a public cloud. Sixteen observational principles of file operations were documented to assist in our understanding of Raspberry Pi’s behavior in the cloud environments. This study contributes to IoT forensics for law enforcement in cybercrime investigations

Computer-Mediated Deception: Collective Language-action Cues as Stigmergic Signals for Computational Intelligence

Collective intelligence is easily observable in group-based or interpersonal pairwise interaction, and is enabled by environment-mediated stigmertic signals. Based on innate ability, human sensors not only sense and coordinate, but also tend to solve problems through these signals. This paper argues the efficacy of computational intelligence for adopting the collective language-action cues of human intelligence as stigmertic signals to differentiate deception. A study was conducted in synchronous computer-mediated communication environment with a dataset collected from 2014 to 2015. An online game was developed to examine the accuracy of certain language-action cues (signs), deceptive actors (agents) during pairwise interaction (environment). The result of a logistic regression analysis demonstrates the computational efficacy of collective language-action cues in differentiating and sensing deception in spontaneous communication. This study contributes to the computational modeling in adapting human intelligence as a base to attribute computer-mediated deception

Multiple Alarms and Driving Situational Awareness

There is increasing interest in actively mitigating safety in vehicles beyond that of improving crash worthiness. According to the National Highway Transportation Safety Administration (NHTSA), there are more than 40,000 deaths on highways each year. This number may be decreasing with increasing active public concern and awareness for the use of safety restraints, but the numbers are still in excess of 40,000 deaths annually. Focusing on crash-worthiness as a measure of safety in vehicles will eventually reach a point of diminishing return, thus there is a need for automotive manufacturers to shift their safety focus to crash avoidance safety systems (Runge, 2002). In the public domain, significant progress and advancements have been made under the Intelligent Vehicles Initiative (IVI) set up by U.S. Department of Transportation to prevent motor vehicle crashes by assisting drivers in avoiding hazardous mistakes (U.S DOT, 1998). One IVI focus area is facilitating the rapid deployment of Collision Avoidance Systems (CAS) in vehicles. Collision Avoidance Systems are a subset of Advanced Vehicle Control Safety Systems (AVCSS) which come under the umbrella of Intelligent Transportation Systems (ITS). These Collision Avoidance Systems warn drivers of imminent collisions and can potentially help to save lives. Primary directions of research in CAS are determining implementation strategies and technologies in vehicles and roadway infrastructure, as well as optimizing the driving performance of different populations of drivers when using CAS. In CAS implementation, vehicles will communicate with other vehicles as well as with the roadway infrastructure via sensors and telecommunication networks. The data obtained can then be used in Collision Avoidance Systems. Vehicle-to-vehicle CAS include warnings that trigger when a vehicle is about to collide with another vehicle. Examples include Frontal Warning, Rear Warning and Blind Spot Detection Warnings. Vehicle-to-infrastructure CAS include warnings that trigger when a vehicle is about to have a collision with the roadway infrastructure. Examples include Intersection Warnings, Lane Departure Warnings, Curve Speed Warnings and Road-condition Warnings. Driving in a dynamic environment has become increasingly complex, such that drivers must visually track objects, monitor a constantly changing system, manage system information, to include the explosion of telematics, and make decisions in this dynamic and potentially high mental workload environment. Introducing Collision Avoidance Systems into vehicles could add to the complexity of this dynamic environment as different drivers will respond differently to Collision Avoidance Systems and there are many critical human factors issues that require investigation.Prepared for Ford Motor Co

Resilience of Society to Recognize Disinformation: Human and/or Machine Intelligence

The paper conceptualizes the societal impacts of disinformation in hopes of developing a computational approach that can identify disinformation in order to strengthen social resilience. An innovative approach that considers the sociotechnical interaction phenomena of social media is utilized to address and combat disinformation campaigns. Based on theoretical inquiries, this study proposes conducting experiments that capture subjective and objective measures and datasets while adopting machine learning to model how disinformation can be identified computationally. The study particularly will focus on understanding communicative social actions as human intelligence when developing machine intelligence to learn about disinformation that is deliberately misleading, as well as the ways people judge the credibility and truthfulness of information. Previous experiments support the viability of a sociotechnical approach, i.e., connecting subtle language-action cues and linguistic features from human communication with hidden intentions, thus leading to deception detection in online communication. The study intends to derive a baseline dataset and a predictive model and by that to create an information system artefact with the capability to differentiate disinformation