Reviewerly/exHarmony huggingface dataset:
Recognition of Human Face Emotions Detection Using Computer Vision Based Smart Images

Humans share a collection of basic and essential emotions that are expressed by facial expressions that seem to be consistent. The automated identification of humanemotion in imageswill be possible due to an algorithm that detects, extracts, and evaluates these facial expressions.The Face detector and recognizer application is a desktop application used to recognize human face emotions by using a computer vision based smart images. It consists of human face detection picture boxes and considers an image as an original image. It climaxes a face skin color, finds high impact area and identifies different emotions of the face from an image. The results of the image are depending upon the separation of Eyes &amp; Lips movement of person. This is done by comparingface embedding vectors. It finds the smart photos focused on computer vision for successful identification of facial emotions in terms of various modes of speech such as smiling, shocking and weeping.
COGNITIVE NATURAL LANGUAGE PROCESSING ASSISTANT FOR POST-OPERATIVE CARE

The vast intricacies that hover over post-operative care often lead to higher risk and inherent damage, when ignored. Postoperative care has several complications, ranging from decreased quality of care due to enormous patient to doctor gap ratio to unavailability of remote healthcare. To ensure that these issues are eradicated, the Cognitive NLP assistant using Dialogflow is proposed. This assistant will hold a regular conversation similar to what a medical professional would, but at the feasibility of the user’s home. It will monitor and track symptoms. The assistant will suggest prompts, based on prior charts and care suggested for the respective surgery. The proposed methodology is achieved by using the Rule-Based Grammar algorithm and the ML matching algorithm. The assistant’s services will extend to connecting with the medical professional if any abnormalities arise and cover communication gaps, by providing the details it has gathered. This assistant has reduced the burden of the physician while providing care to the user and eliminating the need to travel distances to seek treatment for non-emergent issues along with reducing the stress to schedule an appointment. It will function as a whole care provider by being available around the clock to tend to the user.
Abstract 4214: A microfluidic platform to capture and detect cancer cells in Leukemia patients

Abstract Introduction : BioFluidica has developed a platform, The Liquid Scan™ to analyze circulating cancer cells in whole blood. The Liquid Scan is unique in its performance metrics compared to existing platforms by employing fully automated instrumentation in conjunction with a highly sensitive and a specific cell detection microfluidic chip. This technology can be applied to a broad variety of tumors, including liquid tumors such as leukemias and lymphomas. The unique design of the microfluidic chip permits the capture and analysis of live circulating leukemic cells (CLCs) from whole blood, even when these cells appear undetectable by other methods. The Liquid Scan has been applied to capture CLCs from patients suffering from acute myeloid, as well as acute lymphoblastic leukemia (AML and ALL, respectively). These leukemias are acute diseases of the blood and bone marrow, with mutational changes and clonal expansion of abnormal myeloid and lymphoblastic precursors, respectively claiming a great number of lives every year. Bone marrow biopsies/aspirations have been the standard methods for reliably diagnosis and monitoring these diseases. These procedures are extremely painful for patients, necessitate specialized centers, and trained personnel, which increases the overall cost of treatment. Methods: We have applied the Liquid Scan™ to capture CLCs and characterization, using specific antibodies to capture known clones of leukemic blasts. As a model, we use Kasumi-1, KG-1 and HL-60 cells for AML, and SupB15 cells for ALL, spiked in healthy whole blood. Results: We characterized the ability of the The Liquid Scan™ to capture and release circulating leukemic cells from whole blood, by using cell line models spiked-in whole healthy donor blood and applied to the microfluidic chip. Our results are directly applicable to patient in different stages of the disease, both as an initial diagnostic tool, and as a way to monitor recovery and diagnose relapse. Conclusions: Precision medicine (PM) is significantly changing the treatment of cancer and is bringing new hope for patients. Diagnostic testing for circulating tumor and leukemic cells are promising prognostic and predictive tools for selecting optimal therapies based on the patient’s genetic content. Highly sensitive, and selective BioFluidica’s system is highly sensitive and selective with the capability of rapidly delivering purified and concentrated circulating cancer cells compatible with downstream molecular diagnostics. Citation Format: Rolf Muller, Rachel Toughiri, Alena Bartakova, Paul Diaz, Craig Carson, Paul Armistead, George Fedoriw, Mathew Foster, Maryam Zomorrodi, Jennifer Barber-Singh, Veronica Cheung, Emily Mirkin, Roksolana Melnychuk, Elizabeth Fabio, Sangeetha Purushotham, Judy Muller-Cohn. A microfluidic platform to capture and detect cancer cells in Leukemia patients [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2019; 2019 Mar 29-Apr 3; Atlanta, GA. Philadelphia (PA): AACR; Cancer Res 2019;79(13 Suppl):Abstract nr 4214.
MRCC-Measuring Reusability Based on Coupling and Cohesion Methodology

The component based reusability framework is a procedure of reusing pre-manufactured programming segments to assemble new programming and upgrading the exactness of the techniques for deciding them. The software reuse is principally used to diminish time and spares assets in programming improvement. The product segments are shared and help to lessen the expense of advancement. In existing framework a drawback is the product segment dependent on their nonfunctional reasonableness has been dismissed to an incredible territory. This paper proposes another arrangement of measurements of Fusing and Stability (CC) to determine code scalability frameworks. Coupling and cohesion measures are utilized in different exercises, for example, sway investigation, evaluating the issue inclination of classes, issue forecast, re-modularization, distinguishing of programming part, structure designs, surveying programming quality and so on. It is achievable to infer a productive and hearty reusability forecast model utilizing programming measurements. The product measurement is utilized to improve the nature of programming during the advancement procedure. There are three parts of programming measurements are built up they measure how much substances are coupled one another, it assesses coupling and attachment relationship and lessens the multifaceted nature of classes and techniques. The java is utilized as an assessment instrument for estimating programming measurements and approving the measurements. The experimental results demonstrate the new measurements are reliably prevalent at estimating and positioning the application part of reusability.
Design and Development of Ejection Seat Mechanism in Aircraft

This research manages the discharge framework that can be actualized in a common air ship. It is significant for a flying machine to have a launch situate in the event that the plane meets a mishap in a fight or during experimental drill and the pilot needs to rescue to spare their life. The component includes lifting of the pilot to a protected good ways from the air ship and after that sending the parachute. As there is increment in air traffic, this discharge framework gives extra security measures to the life of travelers. By this strategy alongside the pilot, the group individuals and the travelers can be spared. This discharge framework comprises of an exceptionally made ejector cushion, track framework and parachute. The launch framework is administered by a planning sensor which guarantees that the development of the traveler seat occur in equivalent interim of time to maintain a strategic distance from impact between two continuous seats.
Stimulating the Search Activity of Primary Schoolchildren in the Process of Solving Educational Problems

The article raises the problem of the formation of the search activity of younger schoolchildren and the formation of their subjective position in learning. The essence of the concept of “educational task” is revealed as a component of educational activity. The structure of the lesson is described, in the process of which the skills of younger schoolchildren to solve educational problems that are aimed at mastering generalized methods of objective actions are formed. This provides the opportunity for students to master the system of scientific concepts that allows selfdevelopment and self-learning. A concrete example of solving the educational problem in the lesson of the Russian language in the second grade is given.
Integrate Words Internal Information to Improve Word Embeddings

we propose a method of improving word embeddings by fusing the hidden information within words, which is different from the traditional method of directly using morphological information on the surface of words to train word embeddings.Based on the average principle and two attention mechanisms, we propose to use the hidden information inside words, which is called the implied meanings of morphemes of words in this paper, and propose six implied meaning embedding models.The comparative experiments are carried out on two basic Natural Language Processing tasks, which prove that our models have more advantages than the classical models represented by CBOW, Skip-Gram and GloVe in mining semantic information.In addition, exploring the relationship between the importance of synthetic implied meanings and the word itself.
Technology Law

Can law keep up with runaway technology? In an era of runaway corporate surveillance, artificial intelligence, deep fakes, election hacking, social media disinformation, do-it-yourself biology, genetic modification, automation, and three-dimensional printed medical implants, law has seemed to take a back seat to rampant technological change. To listen to Silicon Valley barons, there is nothing any of us can do about it.CAN LAW KEEP UP? calls their bluff. The book provides a fresh look at law, at what it actually is, how it works, and how we can create the kind of laws that help humans survive and thrive in the face of technological change. It shows that law can keep up with technology because law is a kind of technology – social technology built by humans out of cooperative fictions like firms, nations, or money. To survive the challenges of the future, we need a new kind of law, and a new way of understanding how humans use language to cooperate, to build an ever-growing and ever-changing system of understandings about how we can secure the benefits of changing technology to all.
Analysis of Neural Network Based Language Modeling

The fundamental and core process of the natural language processing is the language modelling usually referred as the statistical language modelling. The language modelling is also considered to be vital in the processing the natural languages as the other chores such as the completion of sentences, recognition of speech automatically, translations of the statistical machines, and generation of text and so on. The success of the viable natural language processing totally relies on the quality of the modelling of the language. In the previous spans the research field such as the linguistics, psychology, speech recognition, data compression, neuroscience, machine translation etc. As the neural network are the very good choices for having a quality language modelling the paper presents the analysis of neural networks in the modelling of the language. Utilizing some of the dataset such as the Penn Tree bank, Billion Word Benchmark and the Wiki Test the neural network models are evaluated on the basis of the word error rate, perplexity and the bilingual evaluation under study scores to identify the optimal model.
Supplementary material to &amp;quot;Sources and processes of iron aerosols in a megacity of Eastern China&amp;quot;

represents a significant difference between the two groups at the 0.05 level (2-tailed).** represents a significant difference between the two groups at the 0.01 level (2-tailed).
Design and Hardware Implementation of Portable Generator using TEG

Electrical energy has become a part of all human beings, the claim for electricity has been very high in the current days and hence electricity generated by usual means is not plenty. Nowadays solar, wind and thermal power station are mostly used to generate electricity. But by using this more amount of space can be occupied, fuel cost is increasing day by day, and also power consumption rate is very high in commercial sectors. So avoid these problems by using Thermo Electric power Generator (TEG). It is in the form of peltier coolers and TE generators. TE generator produces electrical energy from waste heat. It works based on principle of SEEBECK effect. It is named after the Baltic German physicist Thomas Johann seebeck. This paper proposed an idea of Design and Hardware implementation of Portable Generator using TEG. Hardware model was implemented and tested.
Research on the Security Situation Awareness Method of Ubiquitous Power Internet of Things Network Based on Artificial Intelligence

In order to accurately determine the security situation awareness of the power system IoT network, this paper proposes an artificial intelligence-based security situation awareness <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</sup> method, which abstracts the perception problem so that it can be applied to actual scenarios. Input the records of the actual field monitoring equipment as the data source to the classifier to obtain the perceptual results, and then use the processed results as the training input of the RBF neural network <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[2]</sup> to find out the mapping relationship with the network situation value, thereby quantifying the system’s performance Security posture. Finally, the KDD Cup99 data set <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</sup> can be compared with the attack data of the power information network to verify the reliability of the proposed method in the network security situation analysis.
Electronic Eye for Blind People with Object Detection and Audio Output Using Image Processing

One of the major issues faced by Blind people is detecting and recognizing an object. The objective of this project is to help the blind people because mobility of blind people is always a great problem. The mobility of blind people in unknown environment seems impossible without external help, because they don’t have any proper idea about their surroundings. So, we are developing a electronic eye which helps them to know about their surroundings and also guide them during travelling. Developing a system based on image processing using DNN algorithm which is able to labeling objects with the help of OpenCV and Tensor flow libraries and converting the labeled text in to speech and producing output in the form of audio to make the blind person aware of the object in front of him or her. The scope of this system is also measuring the distance of the object from the person and reporting the same Object detection using image processing and Machine Learning. It searches the object. We want to innovate our system the possibility of using the hearing sense to understand real time objects. For the security purpose track blind people in real time environment.
Hand Gesture Method to Speech Conversion using Image Segmentation and Feature Extraction Algorithm

Hand gestures are used by the speech impaired persons to easily communicate with others. Hand gesture is a visual language, different from spoken language but serves as the same purpose of spoken language. Image segmentation and feature extraction algorithms are used to recognize the hand gestures of the deaf people .In this paper the proposed system will not only recognize the hand gestures but it will translate into suitable messages by using skin color segmentation. With the help of speakers speech playback is possible in the MATLAB.
Dynamics

Networks are everywhere: networks of friends, transportation networks and the Web. Neurons in our brains and proteins within our bodies form networks that determine our intelligence and survival. This modern, accessible textbook introduces the basics of network science for a wide range of job sectors from management to marketing, from biology to engineering, and from neuroscience to the social sciences. Students will develop important, practical skills and learn to write code for using networks in their areas of interest - even as they are just learning to program with Python. Extensive sets of tutorials and homework problems provide plenty of hands-on practice and longer programming tutorials online further enhance students' programming skills. This intuitive and direct approach makes the book ideal for a first course, aimed at a wide audience without a strong background in mathematics or computing but with a desire to learn the fundamentals and applications of network science.
A Case Study of Artificial Intelligence is being used to Reshape Business

AI Publications is an open access peer review international journal to publish the article in the field of Agriculture, Horticulture, Food science, Rural Development, Environment and Health Research, Chemistry, Mathematics,Physics.
Target Detection of Sar Image using Modified Markov Random Fields Ayed Model Segmentation Along With Google Net Classification

In the modern world the mechanism of target detection in the SAR images have huge assistance for humans to deal with complex visual signals of satellite images effectively. However, the ultimate aim of the paper was to segment the region of interest precisely from despeckling SAR images. This paper proposes a novel modified Markov random fields ayed model segmentation along with Google NET classification target detection. In the initial stage, the image gets despeckled for removing the unwanted noise. The boundaries of the images were calculated for checking the discontinuity using the canny edge detector. Then in the data reduction step by grouping the similar data items. Then the target region was segmented using the modified Markov random fields ayed model methods then the segmented output can undergo the classification process by using the Google NET CNN architecture. The proposed technique was capable of getting better results under risky conditions . Thus, the results validate the target detection of detection rate in different complexity over the existing methodology
Alexander Reutlinger and Juha Saatsi, eds. Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations

Journal Article Alexander Reutlinger and Juha Saatsi, eds. Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations Get access Alexander Reutlinger and Juha Saatsi, eds. Explanation Beyond Causation: Philosophical Perspectives on Non-Causal Explanations. Oxford University Press, 2018. ISBN 978-0-19-877794-6 (hbk); 978-0-19-108380-8 (e-book). Pp. xii + 269. Online doi: 10.1093/oso/9780198777946.001.0001. Philosophia Mathematica, Volume 28, Issue 1, February 2020, Page 136, https://doi.org/10.1093/philmat/nkaa004 Published: 29 February 2020
Preliminary Examination of the Accuracy of a Fall-Detection Device Embedded into Hearing Instruments

Background: Accidental falls are a significant health risk to older adults and patients seen in audiologyclinics. Personal emergency response systems are effective in preventing long lies (defined as remainingon the floor or ground for greater than one hour after a fall), but some individuals would prefer to wear less conspicuousdevices than a traditional neck-worn pendant. No previous investigation has compared theaccuracy of head-worn fall detection devices with those worn on other parts of the body. In this study, wecompared the accuracy of one commonly used fall detection pendant with two variants of a new hearinginstrument–based fall detection system.&lt;br /&gt; Purpose: The purpose of the study was to evaluate the accuracy of detecting falls by using inertial sensorsembedded in hearing instruments.&lt;br /&gt; Research Design: A study with repeated measures for one group.&lt;br /&gt; Study Sample: Ten young adults served as participants. All participants had normal or corrected-to normalvision during testing. Individuals were excluded if they had self-reported cardiac disorders, recentconcussions, or musculoskeletal conditions.&lt;br /&gt; Data Collection and Analysis: Data were collected from inertial measurement unit (IMU) sensors, embeddedinto a binaural set of hearing instruments, during laboratory-based simulations of falls, near-falls,and activities of daily living (ADLs). The detection state of a fall detection pendant was simultaneouslyrecorded during performance of each trial and compared with the outputs of offline hearing instrumentfirmware emulators.&lt;br /&gt; Results: One hearing instrument–based fall detection system was more accurate than the fall detectionpendant. A second hearing instrument–based fall detection system performed similar to the fall detectionpendant. Each of the three fall detection systems investigated were robust against false-positive detectionsduring ADLs.&lt;br /&gt; Conclusions: Preliminary findings demonstrate that hearing instruments embedded with a fall detectiondevice (FDD) may be a suitable alternative to more traditional forms of FDDs (e.g., pendant, wrist-worndevice, etc.) for detecting falls and potentially preventing long lies.&lt;br /&gt;
Privacy-preserving voice-based search over mHealth data

Voice-enabled devices have a potential to significantly improve the healthcare systems as smart personal assistants. They usually come with a hands-free feature to add an extra level of usability and convenience to elderly, disabled people and patients. In this paper, we propose a privacy-preserving voice-based search scheme to enhance the privacy of in-home healthcare applications. We consider an application scenario where patients use the devices to communicate with their caregivers by recording and uploading their voices to the servers, where the caregivers can search the interested voices of their patients based on the voice content, mood, tone and background sounds. Our scheme preserves the richness and privacy of voice data and enables accurate and efficient voice-based search, while in current systems that use speech recognition, the richness and privacy of voice data are compromised. Specifically, our scheme achieves the privacy by employing a privacy-preserving voice feature matching technique and a novel category-based encryption; only encrypted voice data is uploaded to the server who is unable to access the original voice data. In addition, our scheme enables the server to selectively and accurately respond to caregivers' queries on the voice data based on voice similarities. We evaluate our scheme through real experiments and show that our scheme even with privacy preservation can successfully match similar voice data at an average accuracy of 80.8%.