This paper presents a computational framework for providing affective labels to real-life situations, called A-Situ. We first define an affective situation, as a specific arrangement of affective entities relevant to emotion elicitation in a situation. Then, the affective situation is represented as a set of labels in the valence-arousal emotion space. Based on physiological behaviors in response to a situation, the proposed framework quantifies the expected emotion evoked by the interaction with a stimulus event. The accumulated result in a spatiotemporal situation is represented as a polynomial curve called the affective curve, which bridges the semantic gap between cognitive and affective perception in real-world situations. We show the efficacy of the curve for reliable emotion labeling in real-world experiments, respectively concerning 1) a comparison between the results from our system and existing explicit assessments for measuring emotion, 2) physiological distinctiveness in emotional states, and 3) physiological characteristics correlated to continuous labels. The efficiency of affective curves to discriminate emotional states is evaluated through subject-dependent classification performance using bicoherence features to represent discrete affective states in the valence-arousal space. Furthermore, electroencephalography-based statistical analysis revealed the physiological correlates of the affective curves.

--Past research on recognizing human affect has made use of a variety of physiological sensors in many ways. Nonetheless, how affective dynamics are influenced in the context of human daily life has not yet been explored. In this work, we present a wearable affective life-log system (ALIS), that is robust as well as easy to use in daily life to detect emotional changes and determine their cause-and-effect relationship on users' lives. The proposed system records how a user feels in certain situations during long-term activities with physiological sensors. Based on the long-term monitoring, the system analyzes how the contexts of the user's life affect his/her emotion changes. Furthermore, real-world experimental results demonstrate that the proposed wearable life-log system enables us to build causal structures to find effective stress relievers suited to every stressful situation in school life. For instance, today's coffee is not always the same as yesterday's coffee. The cup of coffee we drank today may not be as enjoyable as the cup of coffee we drank yesterday. While drinking coffee generally helps to reduce a person's stress, the stress-relieving effects of coffee may vary from day to day for many reasons. For a person who likes calm and quiet surronding, a cup of coffee drunk today in a crowded coffee shop with distracting background noise is likely to be less enjoyable than a cup of coffee drunk yesterday in the quiet kitchen of one's own home. This instance shows that a person can have different emotional responses to the same life events in different circumstances. Why and how does a person experience various emotions from a single event under different situations? Answering this question could improve human life in a variety of ways, as by improving physical health. People who suffer from depression are more vulnerable to heart disease than people with no history of depression. Therefore, discovering life elements related to depression and offering guidance to avoid such elements can help sufferers to lessen their suffering and lead a meaningful life. In response to this question, recent researches on recognizing human affect has made use of a variety of physiological sensors in many ways. B. Kim and S. Jo are with the School of Computing, KAIST, Republic of Korea. S. Jo is the corresponding author.

Human communication often involves the use of verbal irony or sarcasm, where the speakers usually mean the opposite of what they say. To better understand how verbal irony is expressed by the speaker and interpreted by the hearer we conduct a crowdsourcing task: given an utterance expressing verbal irony, users are asked to verbalize their interpretation of the speaker's ironic message. We propose a typology of linguistic strategies for verbal irony interpretation and link it to various theoretical linguistic frameworks. We design computational models to capture these strategies and present empirical studies aimed to answer three questions: (1) what is the distribution of linguistic strategies used by hearers to interpret ironic messages?; (2) do hearers adopt similar strategies for interpreting the speaker's ironic intent?; and (3) does the type of semantic incongruity in the ironic message (explicit vs. implicit) influence the choice of interpretation strategies by the hearers?

A group of researchers have published results from a shocking experiment that shows how voice controlled smart devices can be operated remotely using targeted laser beams to simulate human speech. The researchers announced Monday that they were able to control a Google Home and command it to remotely open the garage door from a separate building 230 feet away. Also susceptible were Amazon's Echo, Facebook Portal, a range of Android smartphones and tablets, and both iPhones and iPads. The experiments were conducted by a group of scientists from the University of Michigan and The University of Electro-Communications in Tokyo. 'It's possible to make microphones respond to light as if it were sound,' Takeshi Sugarawa, of University of Electro-Communications in Tokyo, told Wired.

The value of machine learning in finance is becoming more apparent by the day. As banks and other financial institutions strive to beef up security, streamline processes, and improve financial analysis, ML is becoming the technology of choice. Unlike so many hyped technologies and overrated buzzwords, machine learning is not going away -- probably ever. The ability of computer programs to learn on their own and improve over time creates new opportunities for industries across the board. While it is true that the naturally conservative financial industry was not at the front of the line for ML adoption, machine learning in fintech is now a common phrase.

As consumers, we experience the benefits of artificial intelligence in our lives as it seamlessly integrates into our daily activities. We are aware of the potential for this technology to transform our organizations in a similar fashion, but still struggle to identify where and how we can use it to generate business value. This has certainly been the trend for some time, but artificial intelligence is now a fundamental requirement for the success of your organization. It is no longer an option. Those that can leverage it will survive and thrive, while those that are unable or unwilling will fall far behind.

If you are reading this on your mobile phone, congratulations – you are a cyborg. Do not worry, we all are. Any tight integration and enhancement of our human cognition with machine-based intelligence are, in a sense, the creation of a cyborg system, scientists argue. And this enhancement is only set to increase, as we continue to augment our brains to be more productive in the future of work. However, although we will all work together with intelligent machines and AI to get the job done in the future, there are degrees to the level in which we will be cyborgs.

Google will not allow its artificial intelligence (AI) software to be used in weapons or unreasonable surveillance efforts under new standards for its business decisions in the nascent field, the Alphabet unit said on Thursday. The restriction could help Google management defuse months of protest by thousands of employees against the company's work with the U.S. military to identify objects in drone video. Google instead will seek government contracts in areas such as cybersecurity, military recruitment and search and rescue, CEO Sundar Pichai said in a blog post. "We want to be clear that while we are not developing AI for use in weapons, we will continue our work with governments and the military in many other areas," he said. Breakthroughs in the cost and performance of advanced computers have carried AI from research labs into industries such as defence and health in the last couple of years.

Plan Jericho has introduced Ai-Search – an artificial intelligence (Ai) prototype – to transform airborne search and rescue. The prototype came about after Air Commodore Darren Goldie challenged Jericho to find a way of using a detector on an aircraft to enhance search and rescue (SAR). Plan Jericho's Ai lead Wing Commander Michael Gan said Jericho saw the opportunity to use Ai to augment and enhance SAR. "The idea was to train a machine-learning algorithm and Ai sensors to complement existing visual search techniques. Our vision was to give any aircraft and other Defence platforms, including unmanned aerial systems, a low-cost, improvised SAR capability," Wing Commander Gan said.

South Korea's Samsung Electronics and US-based tech giant IBM on Tuesday announced a partnership to develop a platform providing business-to-business mobile solutions based on 5G network and artificial intelligence focusing on public safety.Their collaboration which was revealed at a Samsung forum held in San Jose, California, will offer governments and businesses around the globe faster and stronger AI-powered mobile solutions for strengthening safety.They will build a new safety platform based on IBM's AI Watson-based cloud and which will be delivered through Samsung's mobile devices, ranging from the Galaxy smartphones and watches to tablet PCs.The new platform will allow enterprise clients to track people's vital signs, including heart rate and physical activity, to determine if they are in distress and automatically dispatch help. For example, in a 5G network environment, people equipped with Samsung Galaxy smartwatches and phones embedded with biometric sensors will be able to check their vital signs and other important health indicators and share the information with the platform in real time.The platform will alert emergency managers if there are any changes in these data points, which may indicate the responder may be in danger of a heart attack, heat exhaustion, or any other life-threatening event requiring immediate attention. It transmits the data to emergency managers to provide insights for their decision-making.According to the International Labor Organization, nearly 3 million deaths occur each year due to occupational accidents. Governments and enterprises have an increasing need to build systems which track the vital signs of workers in remote or high-stress environments.It is designed to help improve the work environment for police officers, firefighters, soldiers, power plant employees and those working in harsh weather conditions, according to Samsung."Together, IBM and Samsung will use the power of IBM Cloud, 5G, AI and edge computing to enable our clients to leverage these advanced technologies to have a greater impact on the way people work, shop and protect their health and families," said Martin Schroeter, senior vice president of global markets at IBM.