Search results for: human machine collaboration

Authors: André Augusto Ceballos Melo

Abstract:

Design to facilitate the recognition of congruent prosthetic movements, context-to-motion translations guided by image, verbal prompt, users nonverbal communication such as facial expressions, gestures, paralinguistics, scene context, and object recognition contributes to this process though it can also be applied to other tasks, such as walking, Prosthetic limbs as assistive technology through gestures, sound codes, signs, facial, body expressions, and scene context The context-to-motion model is a machine learning approach that is designed to improve the control and dexterity of prosthetic limbs. It works by using sensory input from the prosthetic limb to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. This can help to improve the performance of the prosthetic limb and make it easier for the user to perform a wide range of tasks. There are several key benefits to using the context-to-motion model for prosthetic limb control. First, it can help to improve the naturalness and smoothness of prosthetic limb movements, which can make them more comfortable and easier to use for the user. Second, it can help to improve the accuracy and precision of prosthetic limb movements, which can be particularly useful for tasks that require fine motor control. Finally, the context-to-motion model can be trained using a variety of different sensory inputs, which makes it adaptable to a wide range of prosthetic limb designs and environments. Stable diffusion is a machine learning method that can be used to improve the control and stability of movements in robotic and prosthetic systems. It works by using sensory feedback to learn about the dynamics of the environment and then using this information to generate smooth, stable movements. One key aspect of stable diffusion is that it is designed to be robust to noise and uncertainty in the sensory feedback. This means that it can continue to produce stable, smooth movements even when the sensory data is noisy or unreliable. To implement stable diffusion in a robotic or prosthetic system, it is typically necessary to first collect a dataset of examples of the desired movements. This dataset can then be used to train a machine learning model to predict the appropriate control inputs for a given set of sensory observations. Once the model has been trained, it can be used to control the robotic or prosthetic system in real-time. The model receives sensory input from the system and uses it to generate control signals that drive the motors or actuators responsible for moving the system. Overall, the use of the context-to-motion model has the potential to significantly improve the dexterity and performance of prosthetic limbs, making them more useful and effective for a wide range of users Hand Gesture Body Language Influence Communication to social interaction, offering a possibility for users to maximize their quality of life, social interaction, and gesture communication.

Keywords: stable diffusion, neural interface, smart prosthetic, augmenting

Procedia PDF Downloads 96

Authors: Tarek Saadawi, Rosario Gennaro, Jonathan Akeley

Abstract:

There is rapidly growing demand for professionals to fill positions in Cybersecurity. This is recognized as a national priority both by government agencies and the private sector. Cybersecurity is a very wide technical area which encompasses all measures that can be taken in an electronic system to prevent criminal or unauthorized use of data and resources. This requires defending computers, servers, networks, and their users from any kind of malicious attacks. The need to address this challenge has been recognized globally but is particularly acute in the New York metropolitan area, home to some of the largest financial institutions in the world, which are prime targets of cyberattacks. In New York State alone, there are currently around 57,000 jobs in the Cybersecurity industry, with more than 23,000 unfilled positions. The Cybersecurity Program at City College is a collaboration between the Departments of Computer Science and Electrical Engineering. In Fall 2020, The City College of New York matriculated its first students in theCybersecurity Master of Science program. The program was designed to fill gaps in the previous offerings and evolved out ofan established partnership with Facebook on Cybersecurity Education. City College has designed a program where courses, curricula, syllabi, materials, labs, etc., are developed in cooperation and coordination with industry whenever possible, ensuring that students graduating from the program will have the necessary background to seamlessly segue into industry jobs. The Cybersecurity Program has created multiple pathways for prospective students to obtain the necessary prerequisites to apply in order to build a more diverse student population. The program can also be pursued on a part-time basis which makes it available to working professionals. Since City College’s Cybersecurity M.S. program was established to equip students with the advanced technical skills needed to thrive in a high-demand, rapidly-evolving field, it incorporates a range of pedagogical formats. From its outset, the Cybersecurity program has sought to provide both the theoretical foundations necessary for meaningful work in the field along with labs and applied learning projects aligned with skillsets required by industry. The efforts have involved collaboration with outside organizations and with visiting professors designing new courses on topics such as Adversarial AI, Data Privacy, Secure Cloud Computing, and blockchain. Although the program was initially designed with a single asynchronous course in the curriculum with the rest of the classes designed to be offered in-person, the advent of the COVID-19 pandemic necessitated a move to fullyonline learning. The shift to online learning has provided lessons for future development by providing examples of some inherent advantages to the medium in addition to its drawbacks. This talk will address the structure of the newly-implemented Cybersecurity Master’s Program and discuss the innovations, challenges, and possible future directions.

Keywords: cybersecurity, new york, city college, graduate degree, master of science

Procedia PDF Downloads 140

Authors: Rhea Kapoor

Abstract:

Fractal dimension provides a way to characterize non-geometric shapes like those found in nature. The purpose of this research is to estimate Minkowski fractal dimension of human lung images for early detection of lung cancer. Lung cancer is the leading cause of death among all types of cancer and an early histopathological analysis will help reduce deaths primarily due to late diagnosis. A Python application program, PathoPy2.0, was developed for analyzing medical images in pixelated format and estimating Minkowski fractal dimension using a new box-counting algorithm that allows windowing of images for more accurate calculation in the suspected areas of cancerous growth. Benchmark geometric fractals were used to validate the accuracy of the program and changes in fractal dimension of lung images to indicate the presence of issues in the lung. The accuracy of the program for the benchmark examples was between 93-99% of known values of the fractal dimensions. Fractal dimension values were then calculated for lung images, from National Cancer Institute, taken over time to correctly detect the presence of cancerous growth. For example, as the fractal dimension for a given lung increased from 1.19 to 1.27 due to cancerous growth, it represents a significant change in fractal dimension which lies between 1 and 2 for 2-D images. Based on the results obtained on many lung test cases, it was concluded that fractal dimension of human lungs can be used to diagnose lung cancer early. The ideas behind PathoPy2.0 can also be applied to study patterns in the electrical activity of the human brain and DNA matching.

Keywords: fractals, histopathological analysis, image processing, lung cancer, Minkowski dimension

Procedia PDF Downloads 171

Authors: Rojith K. Balakrishnan

Abstract:

Plasmablastic lymphoma (PBL) is an uncommon, recently described B-cell derived lymphoma that is most commonly seen in patients with Human Immunodeficiency Virus (HIV) infection. Here we report a case of PBL in a 35 year old man with HIV who presented with multiple subcutaneous swellings all over the body and oral mucosal lesions.The biopsy report was suggestive of Diffuse Large B Cell Lymphoma. Immunohistochemistry was done which showed, lymphoma cells, positive for MUM1, CD 138, and VS 38. The proliferation index (MIB) was 95%. Final report was consistent with the diagnosis of Plasmablastic Lymphoma. The lesion completely regressed after treatment with systemic chemotherapy. Up to date, only a few cases of plasmablastic lymphoma have been reported from India. Increased frequency of this lymphoma in HIV patients and rarity of the tumour, along with rapid response of the same to chemotherapy, make this case a unique one. Hence the knowledge about this new entity is important for clinicians who deal with HIV patients.

Keywords: human immunodeficiency virus (HIV), oral cavity lesion, plasmablastic lymphoma, subcutaneous swelling

Procedia PDF Downloads 265

Authors: Scott Andersen

Abstract:

Perhaps simply and rather unadornedly, consciousness is having multiple goals for action and the continuously adjudication of such goals to implement action, referred to as the Maps of Meaning (MoM) Consciousness Theory. The MoM theory triangulates through three parallel corollaries, action (behavior), mechanism (morphology/pathophysiology), and goals (teleology). (1) An organism’s consciousness contains a fluid, nested goals. These goals are not intentionality, but intersectionality, embodiment meeting the world. i.e., Darwinian inclusive fitness or randomization, then survival of the fittest. These goals form via gradual descent under inclusive fitness, the goals being the abstraction of a ‘match’ between the evolutionary environment and organism. Human consciousness implements the brain efficiency hypothesis, genetics, epigenetics, and experience crystallize efficiencies, not necessitating best or objective but fitness, i.e., perceived efficiency based on one’s adaptive environment. These efficiencies are objectively arbitrary, but determine the operation and level of one’s consciousness, termed extreme thrownness. Since inclusive fitness drives efficiencies in physiologic mechanism, morphology and behavior (action) and originates one’s goals, embodiment is necessarily entangled to human consciousness as its the intersection of mechanism or action (both necessitating embodiment) occurring in the world that determines fitness. Perception is the operant process of consciousness and is the consciousness’ de facto goal adjudication process. Goal operationalization is fundamentally efficiency-based via one’s unique neuronal mapping as a byproduct of genetics, epigenetics, and experience. Perception involves information intake and information discrimination, equally underpinned by efficiencies of inclusive fitness via extreme thrownness. Perception isn’t a ‘frame rate,’ but Bayesian priors of efficiency based on one’s extreme thrownness. Consciousness and human consciousness is a modular (i.e., a scalar level of richness, which builds up like building blocks) and dimensionalized (i.e., cognitive abilities become possibilities as emergent phenomena at various modularities, like stratified factors in factor analysis). The meta dimensions of human consciousness seemingly include intelligence quotient, personality (five-factor model), richness of perception intake, and richness of perception discrimination, among other potentialities. Future consciousness research should utilize factor analysis to parse modularities and dimensions of human consciousness and animal models.

Keywords: consciousness, perception, prospection, embodiment

Procedia PDF Downloads 41

Authors: Anthony Nyamekeh-Armah Adjei, Toshiaki Aoki

Abstract:

The unreliable and poor efficiency of electricity distribution leading to frequent power outages and high losses are the major challenge facing the power distribution sector in Ghana. Distribution system routes electricity from the power generating station at a higher voltage through the transmission grid and steps it down through the low voltage lines to end users. Approximately all electricity problems and disturbances that have increased the call for renewable and sustainable energy in recent years have their roots in the distribution system. Therefore, sustaining electricity distribution efficiency can potentially contribute to the reserve of natural energy resources use in power generation, reducing greenhouse gas emission (GHG), decreasing tariffs for consumers and effective human security. Human Security is a people-centered approach where individual human being is the principal object of concern, focuses on protecting the vital core of all human lives in ways for meeting basic needs that enhance the safety and protection of individuals and communities. The vulnerability is the diminished capacity of an individual or group to anticipate, resist and recover from the effect of natural, human-induced disaster. The research objectives are to explore the causes of frequent power outages to consumers, high losses in the distribution network and the effect of poor electricity distribution efficiency on the vulnerable (poor and ordinary) people that mostly depend on electricity for their daily activities or life to survive. The importance of the study is that in a developing country like Ghana where raising a capital for new infrastructure project is difficult, it would be beneficial to enhance the efficiency that will significantly minimize the high energy losses, reduce power outage, to ensure safe and reliable delivery of electric power to consumers to secure the security of people’s livelihood. The methodology used in this study is both interview and questionnaire survey to analyze the response from the respondents on causes of power outages and high losses facing the electricity company of Ghana (ECG) and its effect on the livelihood on the vulnerable people. Among the outcome of both administered questionnaire and the interview survey from the field were; poor maintenance of existing sub-stations, use of aging equipment, use of poor distribution infrastructure and poor metering and billing system. The main observation of this paper is that the poor network efficiency (high losses and power outages) affects the livelihood of the vulnerable people. Therefore, the paper recommends that policymakers should insist on all regulation guiding electricity distribution to improve system efficiency. In conclusion, there should be decentralization of off-grid solar PV technologies to provide a sustainable and cost-effective, which can increase daily productivity and improve the quality of life of the vulnerable people in the rural communities.

Keywords: electricity efficiency, high losses, human security, power outage

Procedia PDF Downloads 279

Authors: Mami Sugiura, Shinichi Arakawa, Masayuki Murata, Satoshi Imai, Toru Katagiri, Motoyoshi Sekiya

Abstract:

API (Application Programming Interface) economy, where many participants join/interact and form the economy, is expected to increase collaboration between information services through API, and thereby, it is expected to increase market value from the service collaborations. In this paper, we introduce API evaluators, which are the activator of API economy by reviewing and/or evaluating APIs, and develop a multi-sided API economy model that formulates interactions among platform provider, API developers, consumers, and API evaluators. By obtaining the equilibrium that maximizes utility of all participants, the impact of API evaluators on the utility of participants in the API economy is revealed. Numerical results show that, with the existence of API evaluators, the number of developers and consumers increase by 1.5% and the utility of platformer increases by 2.3%. We also discuss the strategies of platform provider to maximize its utility under the existence of API evaluators.

Keywords: API economy, multi-sided markets, API evaluator, platform, platform provider

Procedia PDF Downloads 178

Authors: Rajesh Ranjan, Marimuthu Palaniswami, A. A. Hashmi

Abstract:

With the changing lifestyle and environment around us, the prevalence of the critical and incurable disease has proliferated. One such condition is the neurological disorder which is rampant among the old age population and is increasing at an unstoppable rate. Most of the neurological disorder patients suffer from some movement disorder affecting the movement of their body parts. Tremor is the most common movement disorder which is prevalent in such patients that infect the upper or lower limbs or both extremities. The tremor symptoms are commonly visible in Parkinson’s disease patient, and it can also be a pure tremor (essential tremor). The patients suffering from tremor face enormous trouble in performing the daily activity, and they always need a caretaker for assistance. In the clinics, the assessment of tremor is done through a manual clinical rating task such as Unified Parkinson’s disease rating scale which is time taking and cumbersome. Neurologists have also affirmed a challenge in differentiating a Parkinsonian tremor with the pure tremor which is essential in providing an accurate diagnosis. Therefore, there is a need to develop a monitoring and assistive tool for the tremor patient that keep on checking their health condition by coordinating them with the clinicians and caretakers for early diagnosis and assistance in performing the daily activity. In our research, we focus on developing a system for automatic classification of tremor which can accurately differentiate the pure tremor from the Parkinsonian tremor using a wearable accelerometer-based device, so that adequate diagnosis can be provided to the correct patient. In this research, a study was conducted in the neuro-clinic to assess the upper wrist movement of the patient suffering from Pure (Essential) tremor and Parkinsonian tremor using a wearable accelerometer-based device. Four tasks were designed in accordance with Unified Parkinson’s disease motor rating scale which is used to assess the rest, postural, intentional and action tremor in such patient. Various features such as time-frequency domain, wavelet-based and fast-Fourier transform based cross-correlation were extracted from the tri-axial signal which was used as input feature vector space for the different supervised and unsupervised learning tools for quantification of severity of tremor. A minimum covariance maximum correlation energy comparison index was also developed which was used as the input feature for various classification tools for distinguishing the PT and ET tremor types. An automatic system for efficient classification of tremor was developed using feature extraction methods, and superior performance was achieved using K-nearest neighbors and Support Vector Machine classifiers respectively.

Keywords: machine learning approach for neurological disorder assessment, automatic classification of tremor types, feature extraction method for tremor classification, neurological movement disorder, parkinsonian tremor, essential tremor

Procedia PDF Downloads 150

Authors: Asim Cengiz, Dede Basturk, Hakan Ozalp

Abstract:

Practicing recurring resistance workout such as may cause changes in human muscle. These changes may be because combination if several factors determining physical fitness. Thus, it is important to identify these changes. Several studies were reviewed to investigate these changes. As a result, the changes included positive modifications in amplified citrate synthase (CS) maximal activity, increased capacity for pyruvate oxidation, improvement on molecular signaling on human performance, amplified resting muscle glycogen and whole GLUT4 protein content, better health outcomes such as enhancement in cardiorespiratory fitness. Sprint training also have numerous long long-term changes inhuman body such as better enzyme action, changes in muscle fiber and oxidative ability. This is important because SV is the critical factor influencing maximal cardiac output and therefore oxygen delivery and maximal aerobic power.

Keywords: sprint, training, performance, exercise

Procedia PDF Downloads 300

Authors: Xiaoying Guo, Xiangyun Wang, Chunhua Jia

Abstract:

Web page has been one of the most important way of knowing the world. Humans catch a lot of information from it everyday. Thus, understanding where human looks when they surfing the web pages is rather important. In normal scenes, the down-top features and top-down tasks significantly affect humans’ eye movement. In this paper, we investigated if the conventional visual salience algorithm can properly predict humans’ visual attractive region when they viewing the web pages. First, we obtained the eye movement data when the participants viewing the web pages using an eye tracker. By the analysis of eye movement data, we studied the influence of visual saliency and thinking way on eye-movement pattern. The analysis result showed that thinking way affect human’ eye-movement pattern much more than visual saliency. Second, we compared the results of web page visual salience region extracted by Itti model and Spectral Residual (SR) model. The results showed that Spectral Residual (SR) model performs superior than Itti model by comparison with the heat map from eye movements. Considering the influence of mind habit on humans’ visual region of interest, we introduced one of the most important cue in mind habit-fixation position to improved the SR model. The result showed that the improved SR model can better predict the human visual region of interest in web pages.

Keywords: web page salience region, eye-tracker, spectral residual, visual salience

Procedia PDF Downloads 270

Authors: Ngoc Dang Khoa Nguyen, Imran Ali

Abstract:

The cloud customer relationship management (CRM) has emerged as an innovative tool to augment the customer satisfaction and performance of banking systems. Cloud CRM allows to collect, analyze and utilize customer-associated information and update the systems, thereby offer superior customer service. Cloud technologies have invaluable potential to ensure innovative customer experiences, successful collaboration, enhanced speed to marketplace and IT effectiveness. As such, many leading banks have been attracted towards adoption of such innovative and customer-driver solutions to revolutionize their existing business models. Chief Information Officers (CIOs) are already implemented or in the process of implementation of cloud CRM. However, many organizations are still reluctant to take such initiative due to the lack of information on the factors influencing its implementation. This paper, therefore, aims to delve into the strategies, benefits and challenges intertwined in the implementation of Cloud CRM in banking sector and provide reliable solutions.

Keywords: banking sector, cloud computing, cloud CRM, strategy

Procedia PDF Downloads 158

Authors: D. Thawinkarn, S. Wongbutlee

Abstract:

The Social Change Leadership model is strongly aligned with administration’s mission. This research aims to examine the elements of social change leadership, build and develop leadership for social change, and evaluate effectiveness of leadership development model for social change. The research operation has 3 phases: model studies by in-depth interviews and survey research; drafting and creating model which verified by the experts; and trial of model in schools. The results showed that administrators and teachers have the elements of leadership for social change in moderate level. These elements are ranged descending from consciousness of self, common purpose, congruence, collaboration, commitment, citizenship, and controversy with civility. Model of leadership for social change is included the principles, objectives, content, process. Workshop process: Results show that the model of leadership development for social change in administrators and teachers leads to higher score in leadership evaluation prior to administering the operation.

Keywords: leadership, social change model, organization, administrators

Procedia PDF Downloads 410

Authors: Alieu B. Sanneh

Abstract:

In a country where there are minimal economic opportunities, with a declining living condition of the people, do electorates in Africa’s newest democracy reevaluate their support for a candidate based on issues or ethnicity. In the 2016 presidential election in The Gambia, the opposition coalition party had successfully managed to overthrow an authoritarian government, which has ruled the country for 22 years. The results of the election are not only surprising but also presented an interesting theoretical puzzle that raises important this paper is going to address. An important fact is that dictator had organized an election which he lost, and this paper will assess the voting decisions of Gambian electorates to determine whether they were more concerned with issues such as status of the economy, human rights abuses by the Jammeh administration or the ethnicities of the contestants who took part in the election. This study uses field survey data, conducted six months after this historic vote, to evaluate the opinion of the electorates. Contrary to the notion of the prevalence of ethnic voting in African elections, an argument made by many scholars, this study concluded that Gambian voters were more concerned with issues such as the economy and human rights under the Jammeh administration than they were for the ethnicities of the candidates. The election was issue-based, and that Jammeh lost the polls due to the concern the electorate had on human rights abuses by his government.

Keywords: election, issue, ethnicity, regime change

Procedia PDF Downloads 109

Authors: Abdol-Hassan Doulah

Abstract:

In this research, some of the inorganic complexes of uranyl with N- donor ligands were synthesized. Complexes were characteriezed by FT-IR and UV spectra, ¹HNMR, ¹³CNMR and some physical properties. The uranyl unit (UO2) is composed of a center of uranium atom with the charge (+6) and two oxygen atom by forming two U=O double bonds. The structure is linear (O=U=O, 180) and usually stable. So other ligands often coordinate to the U atom in the plane perpendicularly to the O=U=O axis. The antitumor activity of some of ligand and their complexes against a panel of human tumor cell lines (HT29: Haman colon adenocarcinoma cell line T47D: human breast adenocarcinoma cell line) were determined by MTT(3-[4,5-dimethylthiazol-2-yl]-2,5-diphenyl-tetrazolium bromide) assay. These data suggest that some of these compounds provide good models for the further design of potent antitumor compounds.

Keywords: inorganic, uranyl complex-donor ligands, Schiff bases, anticancer activity

Procedia PDF Downloads 450

Authors: C. B. Abhilash, Kavi Mahesh

Abstract:

Human beings are the most advanced species on earth; it's all because of the ability to communicate and share information via human language. In today's world, a huge amount of data is available on the web in text format. This has also resulted in the generation of big data in structured and unstructured formats. In general, the data is in the textual form, which is highly unstructured. To get insights and actionable content from this data, we need to incorporate the concepts of text mining and natural language processing. In our study, we mainly focus on Interesting data through which interesting facts are generated for the knowledge base. The approach is to derive the analytics from the text via the application of natural language processing. Using semantic web Resource framework descriptors (RDF), we generate the triple from the given data and derive the interesting patterns. The methodology also illustrates data integration using the RDF for reliable, interesting patterns.

Keywords: RDF, interestingness, knowledge base, semantic data

Procedia PDF Downloads 155

Authors: Taha SamadSoltani, Peyman Rezaei Hachesu, Marjan GhaziSaeedi, Maryam Zolnoori

Abstract:

Introduction: Data mining defined as a process to find patterns and relationships along data in the database to build predictive models. Application of data mining extended in vast sectors such as the healthcare services. Medical data mining aims to solve real-world problems in the diagnosis and treatment of diseases. This method applies various techniques and algorithms which have different accuracy and precision. The purpose of this study was to apply knowledge discovery and data mining techniques for the diagnosis of asthma based on patient symptoms and history. Method: Data mining includes several steps and decisions should be made by the user which starts by creation of an understanding of the scope and application of previous knowledge in this area and identifying KD process from the point of view of the stakeholders and finished by acting on discovered knowledge using knowledge conducting, integrating knowledge with other systems and knowledge documenting and reporting.in this study a stepwise methodology followed to achieve a logical outcome. Results: Sensitivity, Specifity and Accuracy of KNN, SVM, Naïve bayes, NN, Classification tree and CN2 algorithms and related similar studies was evaluated and ROC curves were plotted to show the performance of the system. Conclusion: The results show that we can accurately diagnose asthma, approximately ninety percent, based on the demographical and clinical data. The study also showed that the methods based on pattern discovery and data mining have a higher sensitivity compared to expert and knowledge-based systems. On the other hand, medical guidelines and evidence-based medicine should be base of diagnostics methods, therefore recommended to machine learning algorithms used in combination with knowledge-based algorithms.

Keywords: asthma, datamining, classification, machine learning

Procedia PDF Downloads 443

Authors: Jam Harley

Abstract:

The COVID-19 epidemic accelerated the speed of change in the workplace. Overnight, several individuals shifted from co-location in an office to hybrid or remote work. The pandemic also expedited and intensified the need to address persistent leadership and management concerns, including digital transformation, remote management, leading through fast change, anxiety, and uncertainty. Nonetheless, many leaders have failed to address the problems left behind by the epidemic. In a fundamental work devoted to comprehending what constitutes a human need, Maslow reiterates similar descriptors in his explanation of belongingness as the human need to be accepted, acknowledged, respected, and appreciated by a community of other individuals. This study aims to investigate the lived experiences of dispersed hybrid team members in order to find leadership best practices that improve team performance and retention through an increased individual’s sense of belonging.

Keywords: organizational change, belonging, diversity, equity

Procedia PDF Downloads 50

Authors: José Antonio Núñez

Abstract:

Sigmund Freud’s Theory of Psychoanalysis was a groundbreaking contribution to the province of the human psyche and behavior. Nowadays, psychoanalytic theory is applied to numerous fields. One of them is literature. Literary criticism has put into practice the basis of Freud’s idea to analyze literary works. This essay is about the analysis of Edgar A. Poe’s short story ‘The Tell-Tale Heart,’ under the lens of Freud’s psychoanalytical perspective. In 1919, it was published ‘Das Unheimliche’ (The Uncanny) by Freud. On this article, the famous Austrian psychoanalyst showed his explanations about what he called ‘the uncanny,’ and its relation to the human unconscious. In this paper, Freud’s famous article has been used to analyze Poe’s short story ‘The Tell-Tale Heart,’ and to find the analogies that exist between Poe’s macabre short story and Freud’s theory of ‘the uncanny.’

Keywords: psychoanalysis, theory of the unconscious, the uncanny, unheimlich

Procedia PDF Downloads 602

Authors: Mark Gavriel, Ariel J. Jaffa, Dan Grisaru, David Elad

Abstract:

The human endometrium-myometrium interface (EMI) is the uterine inner barrier without a separatig layer. It is composed of endometrial epithelial cells (EEC) and endometrial stromal cells (ESC) in the endometrium and myometrial smooth muscle cells (MSMC) in the myometrium. The EMI undergoes structural remodeling during the menstruation cycle which are essential for human reproduction. Recently, we co-cultured a layer-by-layer in vitro model of EEC, ESC and MSMC on a synthetic membrane for mechanobiology experiments. We also treated the model with progesterone and β-estradiol in order to mimic the in vivo receptive uterus In the present study we analyzed the cytokines profile in a single layer of EEC the hormonal treated in vitro model of the EMI. The methodologies of this research include simple tissue-engineering . First, we cultured commercial EEC (RL95-2, ATCC® CRL-1671™) in 24-wellplate. Then, we applied an hormonal stimuli protocol with 17-β-estradiol and progesterone in time dependent concentration according to the human physiology that mimics the menstrual cycle. We collected cell supernatant samples of control, pre-ovulation, ovulation and post-ovulaton periods for analysis of the secreted proteins and cytokines. The cytokine profiling was performed using the Proteome Profiler Human XL Cytokine Array Kit (R&D Systems, Inc., USA) that can detect105 human soluble cytokines. The relative quantification of all the cytokines will be analyzed using xMAP – LUMINEX. We conducted a fishing expedition with the 4 membranes Proteome Profiler. We processed the images, quantified the spots intensity and normalized these values by the negative control and reference spots at the membrane. Analyses of the relative quantities that reflected change higher than 5% of the control points of the kit revealed the The results clearly showed that there are significant changes in the cytokine level for inflammation and angiogenesis pathways. Analysis of tissue-engineered models of the uterine wall will enable deeper investigation of molecular and biomechanical aspects of early reproductive stages (e.g. the window of implantation) or developments of pathologies.

Keywords: tissue-engineering, hormonal stimuli, reproduction, multi-layer uterine model, progesterone, β-estradiol, receptive uterine model, fertility

Procedia PDF Downloads 124

Authors: Mrinal Kanti Bhowmik, Debanjana Debnath Jr., Debotosh Bhattacharjee

Abstract:

A facial expression is undeniably the human manners. It is a significant channel for human communication and can be applied to extract emotional features accurately. People in pain often show variations in facial expressions that are readily observable to others. A core of actions is likely to occur or to increase in intensity when people are in pain. To illustrate the changes in the facial appearance, a system known as Facial Action Coding System (FACS) is pioneered by Ekman and Friesen for human observers. According to Prkachin and Solomon, a set of such actions carries the bulk of information about pain. Thus, the Prkachin and Solomon pain intensity (PSPI) metric is defined. So, it is very important to notice that facial expressions, being a behavioral source in communication media, provide an important opening into the issues of non-verbal communication in pain. People express their pain in many ways, and this pain behavior is the basis on which most inferences about pain are drawn in clinical and research settings. Hence, to understand the roles of different pain behaviors, it is essential to study the properties. For the past several years, the studies are concentrated on the properties of one specific form of pain behavior i.e. facial expression. This paper represents a comprehensive study on pain assessment that can model and estimate the intensity of pain that the patient is suffering. It also reviews the historical background of different pain assessment techniques in the context of painful expressions. Different approaches incorporate FACS from psychological views and a pain intensity score using the PSPI metric in pain estimation. This paper investigates in depth analysis of different approaches used in pain estimation and presents different observations found from each technique. It also offers a brief study on different distinguishing features of real and fake pain. Therefore, the necessity of the study lies in the emerging fields of painful face assessment in clinical settings.

Keywords: facial action coding system (FACS), pain, pain behavior, Prkachin and Solomon pain intensity (PSPI)

Procedia PDF Downloads 339

Authors: Malinee Pongsavee

Abstract:

Sodium formate is the chemical substance used for food additive. Catalase is the important antioxidative enzyme in protecting the cell from oxidative damage by reactive oxygen species (ROS). The resultant level of oxidative stress in sodium formatetreated lymphocytes was investigated. The sodium formate concentrations of 0.05, 0.1, 0.2, 0.4 and 0.6 mg/mL were treated in human lymphocytes for 12 hours. After 12 treated hours, catalase activity change was measured in sodium formate-treated lymphocytes. The results showed that the sodium formate concentrations of 0.4 and 0.6 mg/mL significantly decreased catalase activities in lymphocytes (P < 0.05). The change of catalase activity in sodium formate-treated lymphocytes may be the oxidative damage marker for detect sodium formate exposure in human.

Keywords: sodium formate, catalase activity, oxidative damage marker, toxicity

Procedia PDF Downloads 472

Authors: Tales H. J. Moreira, Thiago M. R. Dias, Gray F. Moita

Abstract:

The adviser-advised relationship, in addition to the evident propagation of knowledge, can provide an increase in the scientific production of the advisors. Specifically, in post-graduate programs, in which the advised submit diverse papers in different means of publication, these end up boosting the production of their advisor, since in general the advisors appear as co-authors, responsible for instructing and assisting in the development of the work. Therefore, to visualize the orientation process and the scientific production resulting from this relation is another important way of analyzing the scientific collaboration in the different areas of knowledge. In this work, are used the data of orientations and postgraduate supervisions from the Lattes curricula, from the main advisors who work in the Engineering area, to obtain an overview of the process of orientation of this group, and even, to produce Academic genealogical trees, where it is possible to verify how knowledge has spread in the diverse areas of engineering.

Keywords: academic genealogy, advice, engineering, lattes platform

Procedia PDF Downloads 318

Authors: Eric Mwenda, Shadrack Ngene

Abstract:

Human-wildlife conflicts (HWCs) are the main threat to conservation in Africa. This is because wildlife needs overlap with those of humans. In Kenya, about 70% of wildlife occurs outside protected areas. As a result, wildlife and human range overlap, causing HWCs. The HWCs in Kenya occur in the drylands adjacent to protected areas. The top five counties with the highest incidences of HWC are Taita Taveta, Narok, Lamu, Kajiado, and Laikipia. The common wildlife species responsible for HWCs are elephants, buffaloes, hyenas, hippos, leopards, baboons, monkeys, snakes, and crocodiles. To ensure individuals affected by the conflicts are compensated, Kenya has developed a model of HWC compensation claims data collection and payment. We collected data on HWC from all eight Kenya Wildlife Service (KWS) Conservation Areas from 2009 to 2019. Additional data was collected from stakeholders' consultative workshops held in the Conservation Areas and a literature review regarding payment of injuries and ongoing insurance schemes being practiced in areas. This was followed by the description of the claims administration process and calculation of the pricing of the compensation claims. We further developed a digital platform for data capture and processing of all reported conflict cases and payments. Our product recognized four categories of HWC (i.e., human death and injury, property damage, crop destruction, and livestock predation). Personal bodily injury and human death were provided based on the Continental Scale of Benefits. We proposed a maximum of Kenya Shillings (KES) 3,000,000 for death. Medical, pharmaceutical, and hospital expenses were capped at a maximum of KES 150,000, as well as funeral costs at KES 50,000. Pain and suffering were proposed to be paid for 12 months at the rate of KES 13,500 per month. Crop damage was to be based on farm input costs at a maximum of KES 150,000 per claim. Livestock predation leading to death was based on Tropical Livestock Unit (TLU), which is equivalent to KES 30,000, whick includes Cattle (1 TLU = KES 30,000), Camel (1.4 TLU = KES 42,000), Goat (0.15 TLU = 4,500), Sheep (0.15 TLU = 4,500), and Donkey (0.5 TLU = KES 15,000). Property destruction (buildings, outside structures and harvested crops) was capped at KES 150,000 per any one claim. We conclude that it is possible to use an administrator to collect data on HWC compensation claims and make payments using technology. The success of the new approach will depend on a piloting program. We recommended that a pilot scheme be initiated for eight months in Taita Taveta, Kajiado, Baringo, Laikipia, Narok, and Meru Counties. This will test the claims administration process as well as harmonize data collection methods. The results of this pilot will be crucial in adjusting the scheme before country-wide roll out.

Keywords: human-wildlife conflicts, compensation, human death and injury, crop destruction, predation, property destruction

Procedia PDF Downloads 50

Authors: Tsu-Wang Shen, Shan-Chun Chang, Chih-Hsien Wang, Te-Chao Fang

Abstract:

For electrocardiogram (ECG) biometrics system, it is a tedious process to pre-install user’s high-intensity heart rate (HR) templates in ECG biometric systems. Based on only resting enrollment templates, it is a challenge to identify human by using ECG with the high-intensity HR caused from exercises and stress. This research provides a heartbeat segment method with slope-oriented neural networks against the ECG morphology changes due to high intensity HRs. The method has overall system accuracy at 97.73% which includes six levels of HR intensities. A cumulative match characteristic curve is also used to compare with other traditional ECG biometric methods.

Keywords: high-intensity heart rate, heart rate resistant, ECG human identification, decision based artificial neural network

Procedia PDF Downloads 423

Authors: Donald Wright

Abstract:

The ultimate goal of this study is to reinvigorate the philosophical underpinnings the study of urbanization with scientific data with the goal of circumventing what seems an inevitable future clash between rural and urban populations. To that end urban infrastructure must be sustainable economically, politically and ecologically over the course of several generations as cities continue to grow with the incorporation of climate refugees. Our research will provide data concerning the projected increase in population over the coming two decades in Morocco, and the population will shift from rural areas to urban centers during that period of time. As a result, urban infrastructure will need to be adapted, developed or built to fit the demand of future internal migrations from rural to urban centers in Morocco. This paper will also examine how past experiences of internally displaced people give insight into the challenges faced by future migrants and, beyond the gathering of data, how people react to internal migration. This study employs four different sets of research tools. First, a large part of this study is archival, which involves compiling the relevant literature on the topic and its complex history. This step also includes gathering data bout migrations in Morocco from public data sources. Once the datasets are collected, the next part of the project involves populating the attribute fields and preprocessing the data to make it understandable and usable by machine learning algorithms. In tandem with the mathematical interpretation of data and projected migrations, this study benefits from a theoretical understanding of the critical apparatus existing around urban development of the 20th and 21st centuries that give us insight into past infrastructure development and the rationale behind it. Once the data is ready to be analyzed, different machine learning algorithms will be experimented (k-clustering, support vector regression, random forest analysis) and the results compared for visualization of the data. The final computational part of this study involves analyzing the data and determining what we can learn from it. This paper helps us to understand future trends of population movements within and between regions of North Africa, which will have an impact on various sectors such as urban development, food distribution and water purification, not to mention the creation of public policy in the countries of this region. One of the strengths of this project is the multi-pronged and cross-disciplinary methodology to the research question, which enables an interchange of knowledge and experiences to facilitate innovative solutions to this complex problem. Multiple and diverse intersecting viewpoints allow an exchange of methodological models that provide fresh and informed interpretations of otherwise objective data.

Keywords: climate change, machine learning, migration, Morocco, urban development

Procedia PDF Downloads 140

Authors: Eliziane Fernanda Navarro, Aparecida Eleonora Sitta

Abstract:

Child of the Dark is the work of the Brazilian author Carolina Maria de Jesus, published at the first time by Ática and Francisco Alves in 1960. It is, mostly, a story of lack of rights. It lacks to men who live in the slums what is essential in order to take advantage of the privilege of rationality to develop themselves as civilized humans. It is, therefore, in the withholding of the basic rights that inequality finds space to build itself to be the main misery on Earth. Antonio Candido, a Brazilian sociologist claims that it is the right to literature has the ability to humanize men, once the aptitude to create fiction and fable is essential to the social balance. Hence, for the forming role that literature holds, it must be thought as the number of rights that assure human dignity, such as housing, education, health, freedom, etc. When talking about her routine, Carolina puts in evidence something that has great influence over the formation of human beings, contributing to the way they live: the slum. Even though it happens in a distinct way and using her own linguistics variation, Carolina writes about something that will only be discussed later on Brazil’s Cities Statute and Erminia Maricato: the right to the city, and how the slums are, although inserted in the city, an attachment, an illegal city, a dismissing room. It interests ourselves, for that matter, in this work, to analyse how the deprivation of the rights to the city and literature, detailed in Carolina’s journal, conditions human beings to a life where the instincts overcome the social values.

Keywords: Child of the Dark, slum, literature, architecture and urbanism, fundamental rights, Brazil

Procedia PDF Downloads 307

Authors: Pekka Makkonen, Georgios Lampropoulos, Kerstin Siakas

Abstract:

This paper examines the impact of social media on knowledge work. It discloses and highlights which specific aspects, areas and tasks of knowledge work can be improved by the use of social media. Moreover, the study includes a survey about higher education students’ viewpoints in regard to the use of social media as a means to enhance knowledge work and knowledge sharing. The analysis has been conducted based both on empirical data and on discussions about the sources dealing with knowledge work and how it can be enhanced by using social media. The results show that social media can improve knowledge work, knowledge building and maintenance tasks in which communication, information sharing and collaboration play a vital role. Additionally, by using social media, personal, collaborative and supplementary work activities can be enhanced. Based on the results of the study, we suggest how knowledge work can be enhanced when using the contemporary information and communications technologies (ICTs) of the 21^st century and recommend future directions towards improving knowledge work.

Keywords: knowledge work, social media, social media services, improving work performance

Procedia PDF Downloads 151

Authors: Yeo Ryeong Jeon, Pyong Kon Cho, Eun Ok Han, Hyon Chul Jang, Yong Min Kim

Abstract:

This study surveyed on recognition related to radiation safety for radiation safety managers and workers those who have been worked in Republic of Korea education and research institution. At present, South Korea has no guideline and manual of radiation safety for education and research institution. Therefore, we tried to find an educational basis for development of radiation safety guideline and manual. To check the level of knowledge, attitude, and behavior about radiation safety, we used the questionnaire that consisted of 29 questions against knowledge, attitude and behavior, 4 questions against self-efficacy and expectation based on four factors (radiation source, human, organizational and physical environment) of the Haddon's matrix. Responses were collected between May 4 and June 30, 2015. We analyzed questionnaire by means of IBM SPSS/WIN 15 which well known as statistical package for social science. The data were compared with mean, standard deviation, Pearson's correlation, ANOVA (analysis of variance) and regression analysis. 180 copies of the questionnaire were returned from 60 workplaces. The overall mean results for behavior level was relatively lower than knowledge and attitude level. In particular, organizational environment factor on the radiation safety management indicated the lowest behavior level. Most of the factors were correlated in Pearson’s correlation analysis, especially between knowledge of human factors and behavior of human factors (Pearson’s correlation coefficient 0.809, P<.01). When analysis performed in line with the main radiation source type, institutions where have been used only opened RI (radioisotope) behavior level was the lowest among all subjects. Finally, knowledge of radiation source factor (β=0.556, P<.001) and human factor(β=0.376, P<.001) had the greatest impact in terms of behavior practice. Radiation safety managers and workers think positively about radiation safety management, but are poorly informed organizational environment of their institution. Thus, each institution need to efforts to settlement of radiation safety culture. Also, pedagogical interventions for improving knowledge on radiation safety needs in terms of safety accident prevention.

Keywords: radiation safety management, factor analysis, SPSS, republic of Korea

Procedia PDF Downloads 361

Authors: Olga Leontjeva

Abstract:

In the age of Artificial Intelligence (AI), some organization management approaches need to be adapted or changed. Human Resource Management (HRM) is a part of organization management that is under the managers' focus nowadays, because AI integration into organization activities brings some HRM-connected challenges. The topic became more significant during the crises of many organizations in the world caused by the coronavirus pandemic (COVID-19). The paper presents an approach, which will be used for the study that is going to be focused on the various case analysis. The author of the future study will analyze the cases of the organizations from Latvia and Spain that are grouped by the size, type of activity and area of business. The information for the cases will be collected through structured interviews and online surveys. The main result presented is the questionnaire developed that will be used for the study as well as the definition and description of sampling. The first round of the survey will be based on convenience sampling that is the main limitation of the study. To conclude, the approach developed will help to collect valid data if the organizations participating in the survey are ready to share their cases in depth, so the researchers could draw the right conclusions and generalize compared organizations’ cases. The questionnaire developed for the survey is applicable for both written online data collection as well as for the interviews. The case analysis will help to identify some HRM challenges that are connected to AI integration into organization activities such as management of different generation employees and their training peculiarities.

Keywords: age of artificial intelligence, case analysis, generation Y and Z employees, human resource management

Procedia PDF Downloads 163

Authors: Marta Kozuń, Krystian Toczewski, Sylwester Gerus, Justyna Wolicka, Kamila Boberek, Jarosław Filipiak, Dariusz Patkowski

Abstract:

Long gap esophageal atresia is a congenital defect and is a challenge for pediatric surgeons all over the world. There are different surgical techniques in use to treat atresia. One of them is esophageal elongation but the optimal suture placement technique to achieve maximum elongation with low-risk complications is still unknown. The aim of the study was to characterize the process of esophageal elongation from the biomechanical point of view. Esophagi of white Pekin Duck was used as a model based on the size of this animal which is similar to a newborn (2.5-4kg). The specimens were divided into two groups: the control group (CG) and the group with sutures (SG). The esophagi of the control group were mounted in the grips of the MTS Tytron 250 testing machine and tensile test until rupture was performed. The loading speed during the test was 10mm/min. Then the SG group was tested. Each esophagus was cut into two equal parts and that were fused together using surgical sutures. The distance between both esophagus parts was 20mm. Ten both ends were mounted on the same testing machine and the tensile test with the same parameters was conducted. For all specimens, force and elongation were recorded. The biomechanical properties, i.e., the maximal force and maximal elongation, were determined on the basis of force-elongation curves. The maximal elongation was determined at the point of maximal force. The force achieved with the suture group was 10.1N±1.9N and 50.3N±11.6N for the control group. The highest elongation was also obtained for the control group: 18mm±3mm vs. 13.5mm ±2.4mm for the suture group. The presented study expands the knowledge of elongation of esophagi. It is worth emphasizing that the duck esophagus differs from the esophagus of a newborn, i.e., its wall lacks striated muscle cells. This is why the parts of animal esophagi used in the research are may characterized by different biomechanical properties in comparison with newborn tissue.

Keywords: long gap atresia treatment, esophageal elongation, biomechanical properties, soft tissue

Procedia PDF Downloads 94