Remote sensing image simulation is a very effective method to verify the feasibility of sensor devices for ground observation. The key to remote sensing image application is that simultaneous interpreting of remote sensing images can make use of the different characteristics of different data, eliminate the redundancy and contradiction between different sensors, and improve the timeliness and reliability of remote sensing information extraction. The hotspots and difficulties in this direction are based on remote sensing image simulation (...) of 3D scenes on the ground. Therefore, constructing the 3D scene model on the ground rapidly and accurately is the focus of current research. Because different scenes have different radiation characteristics, therefore, when using MATLAB to write a program generated by 3D scenes, 3D scenes must be saved as different text files according to different scene types, and then extension program of the scene is written to solve the defect that the calculation efficiency is not ideal due to the huge amount of data. This paper uses POV ray photon reverse tracking software to simulate the imaging process of remote sensing sensors, coordinate transformation is used to convert a triangle text file to POV ray readable information and input the RGB value of the base color based on the colorimetry principle, and the final 3D scene is visualized. This paper analyzes the thermal radiation characteristics of the scene and proves the rationality of the scene simulation. The experimental results show that introducing the chroma in the visualization of the scene model makes the whole scene have not only fidelity, but also radiation characteristics in shape and color. This is indispensable in existing 3D modeling and visualization studies. Compared with the complex radiation transmission method, using the multiple angle two-dimensional image generated by POV rays to analyze the radiation characteristics of the scene, the result is intuitive and easy to understand. (shrink)

Functional imaging techniques, such as positron emission tomography and functional magnetic resonance imaging, present a unique opportunity to examine, in humans, the cerebral representation of space in vivo. Space is ubiquitous and not a unitary phenomenon, and the brain uses visual, vestibular and proprioceptive inputs to produce multiple representations of space subserving spatial cognition, ranging from gaze control to remembering multiple complex large-scale environments. Functional imaging studies have shown the importance of the parietal cortex in perceptual, motor, attention and working (...) memory aspects of body-centred human spatial cognition. Functional imaging has also revealed pathways in humans homologous to those found in monkeys for the separate processing of spatial location and object identity. There are further suggestions of similar differentiation in working memory. The importance of the medial temporal region in the recall of spatial location has been confirmed also and novel virtual reality paradigms are now providing insights into the cerebral representation of spatially-extended large-scale environments. We still have much to learn about the cerebral representation of space in the human brain and functional brain imaging, in concert with patient studies and animal models, will allow us to continue investigating. (shrink)

This essay provides an introduction to the terminology, concepts, methods, and challenges of image‐based modeling in biology. Image‐based modeling and simulation aims at using systematic, quantitative image data to build predictive models of biological systems that can be simulated with a computer. This allows one to disentangle molecular mechanisms from effects of shape and geometry. Questions like “what is the functional role of shape” or “how are biological shapes generated and regulated” can be addressed in the (...) framework of image‐based systems biology. The combination of image quantification, model building, and computer simulation is illustrated here using the example of diffusion in the endoplasmic reticulum. (shrink)

Alcohol use disorder is a burden to society creating social and health problems. Detection of AUD and its effects on the brain are difficult to assess. This problem is enhanced by the comorbid use of other substances such as nicotine that has been present in previous studies. Recent machine learning algorithms have raised the attention of researchers as a useful tool in studying and detecting AUD. This work uses AUD and controls samples free of any other substance use to assess (...) the performance of a set of commonly used machine learning classifiers detecting AUD from resting state functional network connectivity derived from independent component analysis. The cohort used included 51 alcohol dependent subjects and 51 control subjects. Despite alcohol, none of the 102 subjects reported use of nicotine, cannabis or any other dependence or habit formation substance. Classification features consisted of whole brain rsFNC estimates undergoing a feature selection process using a random forest approach. Features were then fed to 10 different machine learning classifiers to be evaluated based on their classification performance. A neural network classifier showed the highest performance with an area under the curve of 0.79. Other good performers with similar AUC scores were logistic regression, nearest neighbor, and support vector machine classifiers. The worst results were obtained with Gaussian process and quadratic discriminant analysis. The feature selection outcome pointed to functional connections between visual, sensorimotor, executive control, reward, and salience networks as the most relevant for classification. We conclude that AUD can be identified using machine learning classifiers in the absence of nicotine comorbidity. (shrink)

In response to calls to forget and unthink photography this article considers the computational environment and its consequences for the image making. What is there to know about images that are networked and generated with data processing techniques rather than with light and chemistry? How to analyse images and read what they are and what they represent, beyond what is visible in the picture? The article argues that glitches while aesthetically capturing errors in the machine point to broader (...) conditions of image making revealing systemic errors and not only its momentary technical failures. To explore digital images as affective phenomena to be sensed, the article looks at how glitch and its operations have been used by artists to generate digital images, and most importantly how they reveal computational systems as technical objects and affective infrastructures where discrimination is not an error but part of the system. (shrink)

Due to advancements in technology such as data science and artificial intelligence, healthcare research has gained momentum and is generating new findings and predictions on abnormalities leading to the diagnosis of diseases or disorders in human beings. On one hand, the extensive application of data science to healthcare research is progressing faster, while on the other hand, the ethical concerns and adjoining risks and legal hurdles those data scientists may face in the future slow down the progression (...) of healthcare research. Simply put, the application of data science to ethically guided healthcare research appears to be a dream come true. Hence, in this paper, we discuss the current practices, challenges, and limitations of the data collection process during medical image analysis (MIA) conducted as part of healthcare research and propose an ethical data collection framework to guide data scientists to address the possible ethical concerns before commencing data analytics over a medical dataset. (shrink)

Big data has brought about opportunities for landscape architecture, changing the design thinking of layout optimization simulation, expanding the platform for public participation in layout optimization simulation design, reflecting social and humanistic care, and promoting the integration of discipline cooperation and data. At the same time, it also brings about challenges. The proposal of data theory, the acquisition and analysis of data, and the protection of privacy are all issues that we need to face and solve. (...) First, build a layout optimization simulation program under the background of big data. Follow the procedures of conventional layout optimization simulation, add big data analysis technology to the preliminary analysis, layout optimization simulation design, and later evaluation management, introduce new data processing methods, and build a theoretical framework of landscape optimization simulation methods that integrate new and traditional data. Second, studying the evolution of the landscape image layout of the three-dimensional pastoral complex is different: the overall landscape image layout of the three-dimensional pastoral complex shows a trend of fragmentation and heterogeneity. Among them, the arable land is gradually fragmented, the wetland and water area are simplified in form, the woodland and grassland patches are gradually distributed, the fragmentation is reduced by 76.19%, and the connectivity index is gradually increased. From a spatial perspective, the edge area outside the Fourth Ring Road becomes the most obvious area of fragmentation tendency. Finally, by introducing big data into the landscape layout optimization simulation, a layout optimization simulation method based on big data is constructed and used in the layout optimization simulation of the landscape image layout of the three-dimensional pastoral complex to guide the participatory layout optimization simulation. (shrink)

Image data serves as a valuable resource for investigating relationships between colors and emotions. This study conducts an image-based visual corpus analysis on the color associations of 100 Chinese emotion words, aiming to uncover the pivotal roles of colors in understanding emotional concepts. The study addresses two primary objectives: (i) examining the interrelations among four affective properties (valence, arousal, prototypicality, and emotionality) and four image-based color attributes (Jz: a dimension depicting black–white color distinction, Az: a dimension (...) for green-red, Bz: a dimension for blue–yellow, and color variability) associated with these emotion words; and (ii) assessing the efficacy of image-based color information in profiling affective (dis)similarities among different emotion words. The empirical results reveal (i) significant positive correlations between color variability and arousal, Jz and valence, Az and arousal, Bz and valence, as well as a negative correlation between Jz and prototypicality; (ii) the effectiveness of image-based color information in depicting the valence-dominated affective (dis)similarities among the 100 Chinese emotion words. This study contributes image-based empirical support to complement existing research on color-emotion mappings. Moreover, it advances methodological approaches by advocating for the utilisation of image data to address theoretical inquiries in cognitive science. (shrink)

Video data has now become the most common form of data for educational researchers studying classroom interaction and school culture. Software protocols for analysing vast archives of video data are deployed regularly, allowing researchers to annotate, code and sort images. These protocols are often applied by researchers without reflection or reference to the extensive philosophical work in film and media studies. Without exception, this research treats the video image as movement-image or picture, a recording of (...) ‘raw data’, indexical of a given time-space relationship. In this article I situate this kind of research within the history of scientific cinema, drawing on Deleuze's books on cinema, as well as his ideas on colour and figure from The Logic of Sensation, to propose an alternative way of analysing video data. One of the central claims of Deleuze in Cinema 2 is that the time-image reconfigures bodies as expressions of force – the body becomes a ‘shock of forces’. I argue that such an approach allows us to study the student body as less a phenomenological organism with built-in ‘I can’ cognitive and motor capacities, and more an indeterminate crystalline contraction and expansion of intensity. I present an example of how to study classroom video data as time-image, and explore the implications of such work for education research. (shrink)

Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...) they are presumptuous. After elaborating this moral concern, I explore the possibility that carefully procuring the training data for image recognition systems could ensure that the systems avoid the problem. The lesson of this paper extends beyond just the particular case of image recognition systems and the challenge of responsibly identifying a person’s intentions. Reflection on this particular case demonstrates the importance (as well as the difficulty) of evaluating machine learning systems and their training data from the standpoint of moral considerations that are not encompassed by ordinary assessments of predictive accuracy. (shrink)

Data hiding and watermarking are considered one of the most important topics in cyber security. This article proposes an optimized method for embedding a watermark image in a cover medium (color image). First, the color of the image is separated into three components (RGB). Consequently, the discrete wavelet transform is applied to each component to obtain four bands (high–high, high–low, low–high, and low–low), resulting in 12 bands in total. By omitting the low–low band from each component, (...) a new square matrix is formed from the rest bands to be used for the hiding process after adding keys to it. These keys are generated using a hybrid approach, combining two chaotic functions, namely Gaussian and exponential maps. The embedding matrix is divided into square blocks with a specific length, each of which is converted using Hessenberg transform into two matrices, P and H. For each block, a certain location within the H-matrix is used for embedding a secret value; the updated blocks are assembled, and the reverse process is performed. An optimization method is applied, through the application of the firework algorithm, on the set of the initial values that generate keys. Using an optimization procedure to obtain keys requires performing lowest possible change rate in an image and maintain the quality of the image. To analyze and test the efficiency of the proposed method, mean-square error (MSE) and peak signal-to-noise ratio (PSNR) measurements are calculated. Furthermore, the robustness of the watermark is computed by applying several attacks. The experimental results show that the value of the MSE is reduced by about 0.01 while the value of the PSNR is increased by about 1.25 on average. Moreover, the proposed method achieved a high-retrieval rate in comparison with the non-optimization approach. (shrink)

Ontology is one strategy for promoting interoperability of heterogeneous data through consistent tagging. An ontology is a controlled structured vocabulary consisting of general terms (such as “cell” or “image” or “tissue” or “microscope”) that form the basis for such tagging. These terms are designed to represent the types of entities in the domain of reality that the ontology has been devised to capture; the terms are provided with logical defi nitions thereby also supporting reasoning over the tagged (...) class='Hi'>data. Aim: This paper provides a survey of the biomedical imaging ontologies that have been developed thus far. It outlines the challenges, particularly faced by ontologies in the fields of histopathological imaging and image analysis, and suggests a strategy for addressing these challenges in the example domain of quantitative histopathology imaging. The ultimate goal is to support the multiscale understanding of disease that comes from using interoperable ontologies to integrate imaging data with clinical and genomics data. (shrink)

Visual content captures attention, is easy to understand, and is more likely to be remembered. However, it is not limited to conveying informative content; it can also be used to propagate hate. While existing research has predominantly focused on textual hate speech, this study aims to address a research gap by analyzing the characteristics of visual hate, including its channels, intensity, sources, and targets, through a standardized manual content analysis. The hate images were collected through the citizen science approach of (...) data donation. Findings highlight that transgender individuals and migrants are the primary targets of visual hate. It reveals a presence of hate images not only on communication platforms but also in various intermediaries and journalistic media. Half of these images use factual or humorous methods to discriminate against individuals or groups, while an equal number adopt a highly aggressive tone. The study suggests governance measures to combat this issue effectively. (shrink)

The use of super‐resolution imaging techniques in cell biology has yielded a wealth of information regarding cellular elements and processes that were invisible to conventional imaging. Focusing on images obtained by stimulated emission depletion (STED) microscopy, we discuss how the new high‐resolution data influence the ways in which we use and interpret images in cell biology. Super‐resolution images have lent support to some of our current hypotheses. But, more significantly, they have revealed unexpectedly complex processes that cannot be accounted (...) for by the simpler models based on diffraction‐limited imaging. The super‐resolution imaging data challenge cell biologists to change their theoretical framework, by including, for instance, interpretations that describe multiple functions, functional errors or lack of function for cellular elements. In this context, we argue that descriptive research using super‐resolution microscopy is now as necessary as hypothesis‐driven research. (shrink)

Image data play important role in various real-time online and offline applications. Biomedical field has adopted the imaging system to detect, diagnose, and prevent several types of diseases and abnormalities. The biomedical imaging data contain huge information which requires huge storage space. Moreover, currently telemedicine and IoT based remote health monitoring systems are widely developed where data is transmitted from one place to another. Transmission of this type of huge data consumes more bandwidth. Along with (...) this, during this transmission, the attackers can attack the communication channel and obtain the important and secret information. Hence, biomedical image compression and encryption are considered the solution to deal with these issues. Several techniques have been presented but achieving desired performance for combined module is a challenging task. Hence, in this work, a novel combined approach for image compression and encryption is developed. First, image compression scheme using wavelet transform is presented and later a cryptography scheme is presented using confusion and diffusion schemes. The outcome of the proposed approach is compared with various existing techniques. The experimental analysis shows that the proposed approach achieves better performance in terms of autocorrelation, histogram, information entropy, PSNR, MSE, and SSIM. (shrink)

Additional arguments for sense‐data begin by defending the claim that perceptual sensations are psychological individuals, examples being phosphenes, after‐images, and the ‘ringings’ of ‘tinnitus’. Five arguments for sense‐data follow. First, that since corresponding to every veridical visual field is a possible non‐veridical visual field of sensations, the latter merely needs a different and regular outer cause to be deemed veridical. Second, since bodily sensation experience is extremely strong evidence for the existence of a matching sensation cause, the experience (...) of ‘ringing’ must be strong evidence that a ‘ringing’ sensation is its cause, and this holds in the veridical hearing of a ringing sound. Third, that it is inconceivable that one has a truly visual experience of a red visual field, and absolutely nothing red‐looking be there before one had noticed. Fourth, that the experience of sound might have had a different developmental history, in which first there was merely experience of auditory sensation, and then over millennia such experience gradually found itself caused by regular outer phenomena, thereby constituting the hearing of sound. And a fifth argument that resembles the first argument. (shrink)

There is currently a gap in our understanding of how figures produced by mechanical imaging techniques play evidential roles: several studies based on close examination of scientific practice show that imaging techniques do not yield data whose significance can simply be read off the image. If image-making technology is not a simple matter of nature re-presenting itself to us in a legible way, just how do the images produced provide support for scientific claims? In this article I (...) will first show that there is a distinct question about the semiotics of mechanically produced images that has not yet been answered. I show that my account of visual representations can do so, and I argue that the role of convention involved in my account is compatible with the view that visual representations produced through mechanized imaging techniques can play genuine evidential roles in scientific reasoning. (shrink)

Anatomical studies propose that the primate auditory cortex contains more fields than have actually been functionally confirmed or described. Spatially resolved functional magnetic resonance imaging (fMRI) with carefully designed acoustical stimulation could be ideally suited to extend our understanding of the processing within these fields. However, after numerous experiments in humans, many auditory fields remain poorly characterized. Imaging the macaque monkey is of particular interest as these species have a richer set of anatomical and neurophysiological data to clarify the (...) source of the imaged activity. We functionally mapped the auditory cortex of behaving and of anesthetized macaque monkeys with high resolution fMRI. By optimizing our imaging and stimulation procedures, we obtained robust activity throughout auditory cortex using tonal and band-passed noise sounds. Then, by varying the frequency content of the sounds, spatially specific activity patterns were observed over this region. As a result, the activity patterns could be assigned to many auditory cortical fields, including those whose functional properties were previously undescribed. The results provide an extensive functional tessellation of the macaque auditory cortex and suggest that 11 fields contain neurons tuned for the frequency of sounds. This study provides functional support for a model where three fields in primary auditory cortex are surrounded by eight neighboring ‘‘belt’’ fields in non-primary auditory cortex. The findings can now guide neurophysiological recordings in the monkey to expand our understanding of the processing within these fields. Additionally, this work will improve fMRI investigations of the human auditory cortex. (shrink)

Rapid technological advances have produced a variety of novel techniques that allow a comprehensive assessment of brain function to be combined with detailed information about brain structure and connectivity. Any assessment that is based on exhibited behavior after brain injury will be prone to error for a number of reasons. These questions are explored in the context of recent studies in both healthy populations and brain injured patients that have sought to investigate covert awareness through the use of functional neuroimaging. (...) Those circumstances in which functional magnetic resonance imaging data can be used to infer awareness in the absence of a behavioral response are contrasted with those circumstances in which it cannot. This distinction is fundamental for understanding and interpreting patterns of brain activity following acute brain injury and has implications for clinical care, diagnosis, prognosis, and medicolegal decision-making after serious brain injury. (shrink)

Given that visualisations via medical imaging have tremendously increased over the last decades, the overall presence of colour-coded brain slices generated on the basis of functional imaging, i.e. neuroimaging techniques, have led to the assumption of so-called kinds of brains or cognitive profiles that might be especially related to non-healthy humans affected by neurological, neuropsychological or psychiatric syndromes or disorders. In clinical contexts especially, one must consider that visualisations through medical imaging are suggestive in a twofold way. Imaging data (...) not only visually render pathological entities, but also tend to represent objective and concrete evidence for these psychophysical states in question. This article aims to identify key issues in visually rendering psychiatric disorders via functional approaches of imaging within the neurosciences from an epistemological point of view. (shrink)

Given that many imaging technologies in biology and medicine are non-optical and generate data that is essentially numerical, it is a striking feature of these technologies that the data generated using them are most frequently displayed in the form of semi-naturalistic, photograph-like images. In this paper, I claim that three factors underlie this: (1) historical preferences, (2) the rhetorical power of images, and (3) the cognitive accessibility of data presented in the form of images. The third of (...) these can be argued to provide an epistemic advantage to images, but I will further argue that this is often misleading and that images can in many cases be less informative than the corresponding mathematical data. (shrink)

Interoperability across data sets is a key challenge for quantitative histopathological imaging. There is a need for an ontology that can support effective merging of pathological image data with associated clinical and demographic data. To foster organized, cross-disciplinary, information-driven collaborations in the pathological imaging field, we propose to develop an ontology to represent imaging data and methods used in pathological imaging and analysis, and call it Quantitative Histopathological Imaging Ontology – QHIO. We apply QHIO to (...) breast cancer hot-spot detection with the goal of enhancing reliability of detection by promoting the sharing of data between image analysts. (shrink)

Big data-analysis is linked to the expectation to provide a general image of socially relevant topics and processes. Similar to this, the idea of the public sphere involves being representative of all citizens and of important topics and problems. This contribution, on one side, aims to explain how a normative concept of the public sphere could be infiltrated by big data. On the other, it will discuss how participative processes and common wealth can profit from a thorough (...) use of big data analysis. As important parts of the argument, two concepts will be introduced: the numerical public and total politicisation. (shrink)

Here, a streamlined, scalable, laboratory approach is discussed that enables medium‐to‐large dataset analysis. The presented approach combines data management, artificial intelligence, containerization, cluster orchestration, and quality control in a unified analytic pipeline. The unique combination of these individual building blocks creates a new and powerful analysis approach that can readily be applied to medium‐to‐large datasets by researchers to accelerate the pace of research. The proposed framework is applied to a project that counts the number of plasmonic nanoparticles bound to (...) peripheral blood mononuclear cells in dark‐field microscopy images. By using the techniques presented in this article, the images are automatically processed overnight, without user interaction, streamlining the path from experiment to conclusions. (shrink)

This article addresses the question of the relevance of brain imaging to legal criteria that are behavioral, that is, that require evaluation of a defendant's actions or mental states. It begins with the legal standard for the admissibility of scientific and technical evidence. Then it considers the relevance of imaging to behavioral legal criteria. The problem is translating mechanistic neuroscience data into the law's folk psychological standards. It uses examples from the criminal law, but the analysis generalizes to behavioral (...) criteria in the civil law. The central question is, “How, precisely, does the proffered scan or data based on scanning answer the specific legal question it supposedly helps answer?” I conclude that, at present, brain imaging has little relevance to behavioral legal criteria. The final section takes note of a rampant disorder, brain overclaim syndrome, and offers a remedy, cognitive jurotherapy. (shrink)

Most research on image schema examined the meaning configuration of words connotation. However, previous studies of adjectives are meaningful in cognitive linguistics because they provide insight into how those adjectives are involved with psychological movement. In this sense, from the perspective of cognitive linguistics, one’s conceptualization and cognition are closely associated with their bodily experience and surroundings; adjectives are no exception. The varieties of transformations of image schemas lay the foundation for the conception and perception. Accordingly, this study (...) is an investigation into the perception of adjectives and psychological activities associated with image schema. Data in this study come from adjectives in the novel The Great Gatsby, which were tagged and calculated with the help of software Python and the NLTK package. The results demonstrate that a significant amount of adjectives were used in the novel. Moreover, Nick’s psychological activities changed significantly from the SOURCE to the DESTINATION schematic stage, which is uncovered by his expression of adjectives. Finally, the results further suggest that transformations of image schema as BALANCE, CONTAINER, and PATH work together to motivate one’s linguistic expression of adjectives. The present findings have several implications for research on lexicons and literacy interpretation from cognitive linguistics. (shrink)

Previous research suggested a role of gaze in preference formation, not merely as an expression of preference, but also as a causal influence. According to the gaze cascade hypothesis, the longer subjects look at an item, the more likely they are to develop a preference for it. However, to date the connection between viewing and liking has been investigated predominately with self-paced viewing conditions in which the subjects were required to select certain items from simultaneously presented stimuli on the basis (...) of perceived visual attractiveness. Such conditions might promote a default, but non-mandatory connection between viewing and liking. To explore whether the connection is separable, we examined the evaluative processing of single naturalistic food images in a 2 x 2 design, conducted completely within subjects, in which we varied both the type of exposure (self-paced versus time-controlled) and the type of evaluation (non-exclusive versus exclusive). In the self-paced exclusive evaluation, longer viewing was associated with a higher likelihood of a positive evaluation. However, in the self-paced non-exclusive evaluation, the trend reversed such that longer viewing durations were associated with lesser ratings. Furthermore, in the time-controlled tasks, both with non-exclusive and exclusive evaluation, there was no significant relationship between the viewing duration and the evaluation. The overall pattern of results was consistent for viewing times measured in terms of exposure duration (i.e., the duration of stimulus presentation on the screen) and in terms of actual gaze duration (i.e., the amount of time the subject effectively gazed at the stimulus on the screen). The data indicated that viewing does not intrinsically lead to a higher evaluation when evaluating single food images; instead, the relationship between viewing duration and evaluation depends on the type of task. We suggest that self-determination of exposure duration may be a prerequisite for any influence from viewing time on evaluative processing, regardless of whether the influence is facilitative. Moreover, the purported facilitative link between viewing and liking appears to be limited to exclusive evaluation, when only a restricted number of items can be included in a chosen set. (shrink)

fMRI promises to uncover the functional structure of the brain. I argue, however, that pictures of ‘brain activity' associated with fMRI experiments are poor evidence for functional claims. These neuroimages present the results of null hypothesis significance tests performed on fMRI data. Significance tests alone cannot provide evidence about the functional structure of causally dense systems, including the brain. Instead, neuroimages should be seen as indicating regions where further data analysis is warranted. This additional analysis rarely involves simple (...) significance testing, and so justified skepticism about neuroimages does not provide reason for skepticism about fMRI more generally. (shrink)

In this article, I provide an account of the development of the "translate" concept from the verbs used in Old English through the Middle English period, including the establishment of the Latin-based translate. The development and current pattern of polysemy are described through the elaboration of a Lakoffian cognitive model structured by image schemas and various types of action on those schemas--more specifically combination, dissolution, and metaphoric projection. Concordance and corpus data illustrate the development at various stages.

Slagging-off is an important preprocessing operation of steel-making to improve the purity of iron. Current manual-operated slag removal schemes are inefficient and labor-intensive. Automatic slagging-off is desirable but challenging as the reliable recognition of iron and slag is difficult. This work focuses on realizing an efficient and accurate recognition algorithm of iron and slag, which is conducive to realize automatic slagging-off operation. Motivated by the recent success of deep learning techniques in smart manufacturing, we introduce deep learning methods to this (...) field for the first time. The monotonous gray value of industry images, poor image quality, and nonrigid feature of iron and slag challenge the existing fully convolutional networks. To this end, we propose a novel spatial and feature graph convolutional network module. SFGCN module can be easily inserted in FCNs to improve the reasoning ability of global contextual information, which is helpful to enhance the segmentation accuracy of small objects and isolated areas. To verify the validity of the SFGCN module, we create an industrial dataset and conduct extensive experiments. Finally, the results show that our SFGCN module brings a consistent performance boost for a wide range of FCNs. Moreover, by adopting a lightweight network as backbone, our method achieves real-time iron and slag segmentation. In the future work, we will dedicate our efforts to the weakly supervised learning for quick annotation of big data stream to improve the generalization ability of current models. (shrink)

The purpose of this research is to describe the brand image and consumer satisfaction of X Cafe. In addition, this research also describes the difference brand image perceived by satisfied customers and unsatisfied customers. Subject of this research contained 100 persons which included male and female. The data was analyzed using multivariate method with support from SPSS. The result of this research shows that the average score of X Cafe customer satisfaction is under satisfied score due to (...) some unfulfilled hopes toward X Cafe. The brand images perceived by X Café customers who feel satisfied are quiet ambience, good quality drinks, and relaxing place. On the contrary, the brand images perceived by unsatisfied customers are crowded ambience, expensive, and place for reading free newspaper and magazine. (shrink)

From a twenty-first century partnership between bioethics and neuroscience, the modern field of neuroethics is emerging, and technologies enabling functional neuroimaging with unprecedented sensitivity have brought new ethical, social and legal issues to the forefront. Some issues, akin to those surrounding modern genetics, raise critical questions regarding prediction of disease, privacy and identity. However, with new and still-evolving insights into our neurobiology and previously unquantifiable features of profoundly personal behaviors such as social attitude, value and moral agency, the difficulty of (...) carefully and properly interpreting the relationship between brain findings and our own self-concept is unprecedented. Therefore, while the ethics of genetics provides a legitimate starting point - even a backbone - for tackling ethical issues in neuroimaging, they do not suffice. Drawing on recent neuroimaging findings and their plausible real-world applications, we argue that interpretation of neuroimaging data is a key epistemological and ethical challenge. This challenge is two-fold. First, at the scientific level, the sheer complexity of neuroscience research poses challenges for integration of knowledge and meaningful interpretation of data. Second, at the social and cultural level, we find that interpretations of imaging studies are bound by cultural and anthropological frameworks. In particular, the introduction of concepts of self and personhood in neuroimaging illustrates the interaction of interpretation levels and is a major reason why ethical reflection on genetics will only partially help settle neuroethical issues. Indeed, ethical interpretation of such findings will necessitate not only traditional bioethical input but also a wider perspective on the construction of scientific knowledge. (shrink)

Sense data are the alleged mind-dependent objects that we are directly aware of in perception, and that have exactly the properties they appear to have. For instance, sense data theorists say that, upon viewing a tomato in normal conditions, one forms an image of the tomato in one's mind. This image is red and round. The mental image is an example of a “sense datum.” Many philosophers have rejected the notion of sense data, either (...) because they believe that perception gives us direct awareness of physical phenomena, rather than mere mental images, or because they believe that the mental phenomena involved in perception do not have the properties that appear to us (for instance, I might have a visual experience representing a red, round tomato, but my experience is not itself red or round). Defenders of sense data have argued, among other things, that sense data are required to explain such phenomena as perspectival variation, illusion, and hallucination. Critics of sense data have objected to the theory's commitment to mind-body dualism, the problems it raises for our knowledge of the external world, its difficulty in locating sense data in physical space, and its apparent commitment to the existence of objects with indeterminate properties. (shrink)

Images are an important source of data and information in the agricultural sciences. The use of image-processing techniques has outstanding implications for the analysis of agricultural operations. Fruit and vegetable classification is one of the major applications that can be utilized in supermarkets to automatically detect the kinds of fruits or vegetables purchased by customers and to determine the appropriate price for the produce. Training on-site is the underlying prerequisite for this type of arrangement, which is generally caused (...) by the users having little or no expert knowledge. We explored various methods used in addressing fruit and vegetable classification and in recognizing fruit disease problems. We surveyed image-processing approaches used for fruit disease detection, segmentation and classification. We also compared the performance of state-of-the-art methods under two scenarios, i.e., fruit and vegetable classification and fruit disease classification. The methods surveyed in this paper are able to distinguish among different kinds of fruits and their diseases that are very alike in color and texture. (shrink)

The way in which one understands information and concepts, and the way a student works to develop this, is an individual aspect of learning that cannot be universally defined as (at least manifested) the same for everyone. ‘Understanding’ is a broad term, and the way one achieves understanding is dependent on the way that material is presented. In this article, we argue that the philosophy of science can be important to nursing education—in particular, by showing that the way we imbue (...) understanding might depend on the meaning of ‘understanding’. Diagrams and concept maps are meant to guide newly formed knowledge and connections to develop proper thinking (e.g., the order in which nursing students must prioritize data) that a student requires in the field. We argue that whether or not an image/diagram/concept map confers understanding will depend on both what the object is and what we mean by ‘understanding’. (shrink)

The article aims to concretize the phenomenological account concerning the problem of an auditory image. The author considers auditory imagery as a scientific object and compares different treatments of the problem to fix the potential and advantages of its phenomenological interpretation. In the first stage of the study, the author distinguishes the key characteristics of the image by means the lexical analysis. This is the perceptual (predominantly visual) nature of an image, integrality, and essentiality (image as (...) an idea). In the second stage, the understandings of the mental and auditory imagery in physiology, experimental psychology, music psychology, musicology, and interdisciplinary studies are described. In the third stage, the peculiar phenomenological ways of the comprehension of an auditory image are revealed. The phenomenological interest is to pick out consciousness which perceiving of an image equally from the process of perceiving and from entailing in an image. The specific phenomenological stance is placing an auditory image on the bound of transcendent (the process of perceiving) and immanent (an image that is already perceived). The auditory image is conceived as the unity of Modi of its givenness. Most fecks of this Modi are original, they cannot be transferred into other science scopes: they are the interconnection of all moments of the temporal unfolding, self-organization in the time, self-referentiality, non-semanticity, periodicity/randomness, eventuality, quasi-embodiment (physicality). Solely phenomenological problems are problems of the constitution of an auditory image, its life-horizon, intersubjectivity, and regional matching. The author infers that phenomenology does not conceive auditory image as sustained auditory representation, associated with acoustic memory. Its perceptual nature does not play a key role here. Moreover, the perceptual-semantic duality of the image is not fixed by the phenomenological description. The phenomenological approach is unique because it researches auditory data exhaustively but does not use semantic and referential analysis of them. The main feature of phenomenological description is the focus on the unity of auditory image: All the elements of auditory data are interpreted in their synthesis as the different levels of the unity of hearing image. Thus, the phenomenological approach as a whole is the most promising for comprehending such a dominant quality of the auditory image as integrality. (shrink)

With more than 120 color photographs, Images of Kansas City provides an exquisite view of one of the country's most desirable places to live. This outstanding collection showcases the many landmarks and scenes associated with Kansas City: Country Club Plaza, with its beautiful fountains and statues; two great sports teams, the Kansas City Chiefs and Royals; buildings such as the Power & Light Building, the H. Roe Bartle Exhibition Hall, and the Nelson-Atkins Museum of Art; events at the American Royal (...) arena; and, of course, views of Kansas City's magnificent skyline. The images in this book were chosen from hundreds of photos submitted to William Mills by both professional and amateur photographers from Kansas City and the surrounding area. Because the contest had few restrictions about subject matter, the photos included demonstrate a wide sampling of photographic approaches and techniques, rendering an excellent portrayal of this vital city. In his introduction, William Mills provides important historical data on the background and development of Kansas City, touching briefly on the special people and features that have made Kansas City the thriving city that it is today. (shrink)

The rapid growth of covert activities via communications network brought about an increasing need to provide an efficient method for data hiding to protect secret information from malicious attacks. One of the options is to combine two approaches, namely steganography and compression. However, its performance heavily relies on three major factors, payload, imperceptibility, and robustness, which are always in trade-offs. Thus, this study aims to hide a large amount of secret message inside a grayscale host image without sacrificing (...) its quality and robustness. To realize the goal, a new two-tier data hiding technique is proposed that integrates an improved exploiting modification direction method and Huffman coding. First, a secret message of an arbitrary plain text of characters is compressed and transformed into streams of bits; each character is compressed into a maximum of 5 bits per stream. The stream is then divided into two parts of different sizes of 3 and 2 bits. Subsequently, each part is transformed into its decimal value, which serves as a secret code. Second, a cover image is partitioned into groups of 5 pixels based on the original EMD method. Then, an enhancement is introduced by dividing the group into two parts, namely k1 and k2, which consist of 3 and 2 pixels, respectively. Furthermore, several groups are randomly selected for embedding purposes to increase the security. Then, for each selected group, each part is embedded with its corresponding secret code by modifying one grayscale value at most to hide the code in a -ary notational system. The process is repeated until a stego-image is eventually produced. Finally, the χ2 test, which is considered one of the most severe attacks, is applied against the stego-image to evaluate the performance of the proposed method in terms of its robustness. The test revealed that the proposed method is more robust than both least significant bit embedding and the original EMD. Additionally, in terms of imperceptibility and capacity, the experimental results have also shown that the proposed method outperformed both the well-known methods, namely original EMD and optimized EMD, with a peak signal-to-noise ratio of 55.92 dB and payload of 52,428 bytes. (shrink)

Generation Z people are a significant force driving the modern world. They lead educated lifestyles, enjoy expressing themselves creatively, and prefer to seek out new ideas or approaches to achieve the finest results. The research study aims to examine the tourism motivation and the image that affects the cultural tourism decisions of tourists of Generation Z. The study employed quantitative research techniques to gather data from 385 Thai Generation Z tourists. The research findings revealed that status and prestige (...) significantly influenced cultural tourism decisions, followed by cultural, emotional, affective, physical, and interpersonal motivation. Moreover, the pre-conceptualized image of the tourist destinations has the most significant influence on cultural tourism decisions, followed by tourists' perceptions and the tourists' feelings. This has practical implications for economic development at both the national and regional levels. At the same time, it reflects much about Generation Z's needs and expectations, calling for the urgency to preserve the cultural heritage of the locality and the country as a whole. This is expected to maintain the value of cultural tourism, generating a balance of development in the future. (shrink)