EEG Emotion Recognition Using an Attention Mechanism Based on an Optimized Hybrid Model

Emotions serve various functions.The traditional emotion recognition methods are based primarily on readily accessible facial expressions,gestures,and voice signals.However,it is often challenging to ensure that these non-physical signals are valid and reliable in practical applications.Electroencephalogram(EEG)signals are more successful than other signal recognition methods in recognizing these characteristics in real-time since they are difficult to camouflage.Although EEG signals are commonly used in current emotional recognition research,the accuracy is low when using traditional methods.Therefore,this study presented an optimized hybrid pattern with an attention mechanism(FFT_CLA)for EEG emotional recognition.First,the EEG signal was processed via the fast fourier transform(FFT),after which the convolutional neural network(CNN),long short-term memory(LSTM),and CNN-LSTM-attention(CLA)methods were used to extract and classify the EEG features.Finally,the experiments compared and analyzed the recognition results obtained via three DEAP dataset models,namely FFT_CNN,FFT_LSTM,and FFT_CLA.The final experimental results indicated that the recognition rates of the FFT_CNN,FFT_LSTM,and FFT_CLA models within the DEAP dataset were 87.39%,88.30%,and 92.38%,respectively.The FFT_CLA model improved the accuracy of EEG emotion recognition and used the attention mechanism to address the often-ignored importance of different channels and samples when extracting EEG features.

Emotion Analysis: Bimodal Fusion of Facial Expressions and EEG

With the rapid development of deep learning and artificial intelligence,affective computing,as a branch field,has attracted increasing research attention.Human emotions are diverse and are directly expressed via nonphysiological indicators,such as electroencephalogram(EEG)signals.However,whether emotion-based or EEG-based,these remain single-modes of emotion recognition.Multi-mode fusion emotion recognition can improve accuracy by utilizing feature diversity and correlation.Therefore,three different models have been established:the single-mode-based EEG-long and short-term memory(LSTM)model,the Facial-LSTM model based on facial expressions processing EEG data,and the multi-mode LSTM-convolutional neural network(CNN)model that combines expressions and EEG.Their average classification accuracy was 86.48%,89.42%,and 93.13%,respectively.Compared with the EEG-LSTM model,the Facial-LSTM model improved by about 3%.This indicated that the expression mode helped eliminate EEG signals that contained few or no emotional features,enhancing emotion recognition accuracy.Compared with the Facial-LSTM model,the classification accuracy of the LSTM-CNN model improved by 3.7%,showing that the addition of facial expressions affected the EEG features to a certain extent.Therefore,using various modal features for emotion recognition conforms to human emotional expression.Furthermore,it improves feature diversity to facilitate further emotion recognition research.

小分子干扰性核糖核酸的作用机制及其在人类免疫缺陷病毒中的应用

基因治疗已成为治疗AIDS的可能途径之一。在Ⅰ期临床试验中已有基于RNA的疗法通过安全测试。然而体外实验数据提示，其抗病毒效果不尽相同，且HIV病毒株的多样性削弱其效果。

THREE-ELECTRODE HIGH-TEMPERATURE OXYGEN SENSOR

Using micro-electronic techniques, a high-temperature oxygen sensor with three electrodesis designed. Yttrium-doped stabilized zirconia is used to make the solid electrolyte and thesupporting substrate for the electrodes. A gold resistance thermometer is installed on thesensor to directly monitor the temperature of gas. The platinum film is covered with aporous alumina coating, to reduce the flow effect on the sensor output and prolong thesensor’s life. Tests, conducted at 650-900℃ in the mixture of oxygen and nitrogen withthe spanning 0-32.7% oxygen concentration, indicate that the sensor is of higher sensitivity,better reproducibility and durability, fast response, but relatively large current outputs areachieved simultaneously. The sensor fabricated using photolithographic reduction and thick-film metallization techniques is conductive to substantial miniaturization.

Foreword

This special issue of Regenerative Biomaterials presents 13 manuscriptsprovided by participants of the China–US Forum on GrandChallenges for Biomaterials in the 21st Century. This forum washeld on November 17, 2015, in Chengdu, China and was chaired bythe Editor of Regenerative Biomaterials, Professor Xingdong Zhangand Professor Nicholas Peppas. The participants of this forum wereinternationally recognized experts from the United States ofAmerica and the Peoples Republic of China. It is noteworthy thatthe United States speakers were members of the National Academyof Engineering, Section 2. Bioengineering, and most of the Chinesespeakers were members of the Chinese Academy of Engineering orthe Chinese Academy of Sciences. The overlying theme of this forumand this resultant special issue is the impact that the biological environmentin which biomaterials will be utilized is now recognized asproviding a wide variety of significant and impactful challenges thatmust be overcome if biomaterials are to achieve clinical application.

The World,Seen From Within(Ⅱ)Sorts of Reality--A Semio-Cognitive Ontology and Phenomenology

This short essay discusses the conditions—and the general contours—of a viable ontology assigning a place to meaning in the architecture of the sorts of reality we acknowledge in the framework of a non-reductive realist philosophy(John Searle^1, Barry Smith^2) compatible with both cognitive and semiotic approaches to the human world.

What Is a Game?--A Ludo-Semiotic Approach

In this diminutive essay, I propose a schema that may specify the behavior we associate with playing games, and I emphasize in particular the function of the factor of chance. I also suggest a blending model accounting for the important intentional properties of participating and watching games—the dynamic phenomenology of ludic semiosis.

The World,Seen From Within(Ⅲ)On Mind and Matter,and the Founders of Rationalism

The aim of the following essay is to find a semantic core pattern, characterizing its ontology or metaphysics, in the form of thinking that emerged in the work of Descartes, spread and was modified through Spinoza and Leibniz, and became the panorama of science-oriented philosophies constituting the implicit or explicit underpinnings of contemporary thinking, research, and debate, especially in relation to the study of meaning and mind.

The World,Seen From Within(Ⅰ)On the Enminded Body:Spinoza,Descartes,and the Philosophy of Cognition

Ontologically, Baruch Spinoza and René Descartes take significantly different stands on truth, mind and meaning. In this respect, the latter can be regarded as the founder of modern epistemology, phenomenology, and scientific thinking. Nevertheless, Spinoza's mysticism and certain resounding Spinozist rejections of Cartesian rationalism can be found at the root of modern analytic philosophy and, even more surprisingly, in most basic assumptions of current cognitive science. The main issue of this "metaphysical" debate is the status of mind, consciousness, mental representations, truth, and meaning in general, and therefore the debate concerns the possibility of a cognitive semantics.

The World,Seen From Within-Three Essays on Metaphysics and Meaning

These short essays reflect an exploration of a question that has intrigued me for quite some time,namely why—in modern and contemporary thinking and research—the reference to the founders of modern rationality,especially Descartes,Spinoza,and Leibniz,is still so uncertain,timid,vague,even in scholarly contexts,and why the issue of ontological monism versus dualism keeps coming up in everyday debate involving matter,mind,consciousness,and meaning.Are we at all some sorts of rationalists today,in our quest for knowledge in general and for a general view of how reality works?I do not see any viable alternative to rationalistic views,and therefore find it urgent to better understand what such rationalism(s)may mean and have meant.