Search results for: human machine interface

Authors: Hassan Kian

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The future of millions of people and consequently, the future of societies and humanity is threatened by a great threat which is called wasted human resources. Perhaps Pasteur, Beethoven and Avicenna, Lavoisier and Einstein and millions of genius individuals and thinkers may have never been discovered and could not found a chance of being known due to various reasons such as poverty or social status, and other problems. So without being able to serve humanity, their talents are fully wasted. While, if a global mechanism exists to discover their talents in different countries and provide to them the right direction, during less than a generation, human society will face to a profound transformation and sustainable social justice will be formed as the basis of sustainable development of human resources. Therefore, the situation of the institution which organizes the affair of discovering and guiding talents was vacant at the level of the international community and its necessity has been felt. So in this plan, the establishment and development of such an organization have been suggested in the international context.

Keywords: talent identification, comparative advantage, sustainable justice, sustainable development

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Authors: Zakeia Benmoussa

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Pressure on freshwater systems comes from removing too much water to grow crops; contamination from economic activities, land use practices, and human waste. The paper will be focusing on how water management can influence the design, implementation, and impacts of the ecological principles of biomimicry as sustainable methods in recycling wastewater. At Texas State, United States of America, in particular the lower area of the Trinity River refuge, there is a true example of the diversity to be found in that area, whether when exploring the lands or the waterways. However, as the Trinity River supplies water to the state’s residents, the lower part of the river at Liberty County presents several problem of wastewater discharge in the river. Therefore, conservation efforts are particularly important in the Trinity River basin. Clearly, alternative ways must be considered in order to conserve water to meet future demands. As a result, there should be another system provided rather than the conventional water treatment. Mimicking ecosystem's technologies out of context is not enough, but if we incorporate plants into building architecture, in addition to their beauty, they can filter waste, absorb excess water, and purify air. By providing an architectural proposal center, a living system can be explored through several methods that influence natural resources on the micro-scale in order to impact sustainability on the macro-scale. The center consists of an ecological program of Plant and Water Biomimicry study which becomes a living organism that purifies the river water in a natural way through architecture. Consequently, a rich beautiful nature could be used as an educational destination, observation and adventure, as well as providing unpolluted fresh water to the major cities of Texas. As a result, these facts raise a couple of questions: Why is conservation so rarely practiced by those who must extract a living from the land? Are we sufficiently enlightened to realize that we must now challenge that dogma? Do architects respond to the environment and reflect on it in the correct way through their public projects? The method adopted in this paper consists of general research into careful study of the system of the living machine, in how to integrate it at architectural level, and finally, the consolidation of the all the conclusions formed into design proposal. To summarise, this paper attempts to provide a sustainable alternative perspective in bridging physical and mental interaction with biodiversity to enhance nature by using architecture.

Keywords: Biodiversity, Design with Nature, Sustainable architecture, Waste water treatment.

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Authors: Edemealem Desalegn Kingawa, Kafte Tasew Timkete, Mekashaw Girmaw Abebe, Terefe Feyisa, Abiyot Bitew Mihretie, Senait Teklemarkos Haile

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Currently, hate speech is a growing challenge for society, individuals, policymakers, and researchers, as social media platforms make it easy to anonymously create and grow online friends and followers and provide an online forum for debate about specific issues of community life, culture, politics, and others. Despite this, research on identifying and detecting hate speech is not satisfactory performance, and this is why future research on this issue is constantly called for. This paper provides a systematic review of the literature in this field, with a focus on approaches like word embedding techniques, machine learning, deep learning technologies, hate speech terminology, and other state-of-the-art technologies with challenges. In this paper, we have made a systematic review of the last six years of literature from Research Gate and Google Scholar. Furthermore, limitations, along with algorithm selection and use challenges, data collection, and cleaning challenges, and future research directions, are discussed in detail.

Keywords: Amharic hate speech, deep learning approach, hate speech detection review, Afaan Oromo hate speech detection

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Authors: Lai-Fen Yang

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In this increasingly visual world, how can we best decipher and understand the many ways that our everyday lives are organized around looking practices and the many images we encounter each day? Indeed, how we interact with and interpret visual images is a basic component of human life. Today, however, we are living in one of the most artificial visual and image-saturated cultures in human history, which makes understanding the complex construction and multiple social functions of visual imagery more important than ever before. Themes regarding our experience of a visually pervasive mediated culture, here, termed visual spectacle.

Keywords: visual culture, contemporary, images, literacy

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Authors: Jinan Fiaidhi, Sabah Mohammed

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Diagnosing cataract severity is an important factor in deciding to undertake surgery. It is usually conducted by an ophthalmologist or through taking a variety of fundus photography that needs to be examined by the ophthalmologist. This paper carries out an investigation using a Siamese neural net that can be trained with small anchor samples to score cataract severity. The model used in this paper is based on a triplet loss function that takes the ophthalmologist best experience in rating positive and negative anchors to a specific cataract scaling system. This approach that takes the heuristics of the ophthalmologist is generally called the thick data approach, which is a kind of machine learning approach that learn from a few shots. Clinical Relevance: The lens of the eye is mostly made up of water and proteins. A cataract occurs when these proteins at the eye lens start to clump together and block lights causing impair vision. This research aims at employing thick data machine learning techniques to rate the severity of the cataract using Siamese neural network.

Keywords: thick data analytics, siamese neural network, triplet-loss model, few shot learning

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Authors: Ayesha Obaid, Abdur Rehman Cheema

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This study is about understanding the role of the gender division of work that has been assigned to men and women in different societies and cultures and its impact on labour force participation through economic development. Development in Gilgit Baltistan has been challenging due to its geographical conditions and the human development indicators are lower than the rest of the Pakistan. Various socioeconomic factors are identified that play an important role in determining the choices and roles men and women undertake for contributing towards the labour force. Our research highlights the areas lagging behind in gender equality in the labour market. The availability and access of gender over these socioeconomic resources determine gender mainstreaming in the labour market. It is a need of time that gender gaps should be addressed at the grass root level by the policy makers to enhance the growth and improve human development indicators.

Keywords: gender division of work, human development, indicators of socioeconomic factors, labour force

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Authors: Nuchjaree Kidjawan, Orapan Thosingha, Pawinee Vaipatama, Prakrankiat Youngkong, Sirinapha Malangputhong, Kitti Thamrongaphichartkul, Phatcharaporn Phetcharat

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NPI uses technology sensorization of things and processed by AI system. The main features are an individual interface pressure sensor system in contact with the mattress and a position management system where the sensor detects the determined pressure with automatic pressure reduction and distribution. The role of NPI is to monitor, identify the risk and manage the interface pressure automatically when the determined pressure is detected. This study aims to evaluate the effects of “Never Pressure Injury (NPI),” an innovative mattress, on the incidence of pressure injuries in critically ill patients. An observational case-control study was employed to compare the incidence of pressure injury between the case and the control group. The control group comprised 80 critically ill patients admitted to a critical care unit of Phyathai3 Hospital, receiving standard care with the use of memory foam according to intensive care unit guidelines. The case group comprised 80 critically ill patients receiving standard care and with the use of the Never Pressure Injury (NPI) innovation mattress. The patients who were over 20 years old and showed scores of less than 18 on the Risk Assessment Pressure Ulcer Scale – ICU and stayed in ICU for more than 24 hours were selected for the study. The patients’ skin was assessed for the occurrence of pressure injury once a day for five consecutive days or until the patients were discharged from ICU. The sample comprised 160 patients with ages ranging from 30-102 (mean = 70.1 years), and the Body Mass Index ranged from 13.69- 49.01 (mean = 24.63). The case and the control group were not different in their sex, age, Body Mass Index, Pressure Ulcer Risk Scores, and length of ICU stay. Twenty-two patients (27.5%) in the control group had pressure injuries, while no pressure injury was found in the case group.

Keywords: pressure injury, never pressure injury, innovation mattress, critically ill patients, prevent pressure injury

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Authors: Mohsen Yaghmoor, Sima Radmanesh

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Rapid environmental changes have been threaten the life of many organizations .Enabling and productivity of human resource should be considered as the most important issue in order to increase performance and ensure survival of the organizations. In this research, the effectiveness of management factory in productivity & inability of human resource have been identified and reviewed at glance. Afterward there were two questions they are “what are the factors effecting productivity and enabling of human resource” . And ”what are the priority order based on effective management of human resource in Fars Poultry Complex". A specified questionnaire has been designed in order to priorities and effectiveness of the identified factors. Six factors specify to consist of: Individual characteristics, teaching, motivation, partnership management, authority or power submission and job development that have most effect on organization. Then specify a questionnaire for priority and effect measurement of specified factor that reach after collect information and using statistical tests of keronchbakh alpha coefficient r=0.792 that we can say the questionnaire has sufficient reliability. After information analysis of specified six factors by Friedman test categorize their effect. Measurement on organization respectively consists of individual characteristics, job development or enrichment, authority submission, partnership management, teaching and motivation. At last it has been indicated to approaches to increase making power full and productivity of manpower.

Keywords: productivity, empowerment, enrichment, authority submission, partnership management, teaching, motivation

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Authors: Saleh Alshehri

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Human skin detection is a vital step in many applications. Some of the applications are critical especially those related to security. This leverages the importance of a high-performance detection algorithm. To validate the accuracy of the algorithm, image databases are usually used. However, the suitability of these image databases is still questionable. It is suggested that the suitability can be measured mainly by the span the database covers of the color space. This research investigates the validity of three famous image databases.

Keywords: image databases, image processing, pattern recognition, neural networks

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Authors: R. S. Sheu, H. Usman, M. S. Lawal

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Takagi-Sugeno (T-S) fuzzy model based control of a load frequency deviation in a single machine with limit nonlinearity on power coefficient is presented in the paper. Two T-S fuzzy rules with only rotor angle variable as input in the premise part, and linear state space models in the consequent part involving characteristic matrices determined from limits set on the power coefficient constant are formulated, state feedback control gains for closed loop control was determined from the formulated Linear Matrix Inequality (LMI) with eigenvalue optimization scheme for asymptotic and exponential stability (speed of esponse). Numerical evaluation of the closed loop object was carried out in Matlab. Simulation results generated of both the open and closed loop system showed the effectiveness of the control scheme in maintaining load frequency stability.

Keywords: T-S fuzzy model, state feedback control, linear matrix inequality (LMI), frequency deviation control

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Authors: Da Tao, Tieyan Wang, Mingfu Qin

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While social robots have been increasingly developed and rapidly applied in our daily life, how robots should interact with humans is still an urgent problem to be explored. Appropriate use of interactive behavior is likely to create a good user experience in human-robot interaction situations, which in turn can improve people’s acceptance of robots. This paper aimed to systematically and quantitatively examine the effects of several important situational factors (i.e., interaction distance, interaction posture, and feedback style) on user experience during human-robot interaction. A three-factor mixed designed experiment was adopted in this study, where subjects were asked to interact with a social robot in different interaction situations by combinations of varied interaction distance, interaction posture, and feedback style. A set of data on users’ behavioral performance, subjective perceptions, and eye movement measures were tracked and collected, and analyzed by repeated measures analysis of variance. The results showed that the three situational factors showed no effects on behavioral performance in tasks during human-robot interaction. Interaction distance and feedback style yielded significant main effects and interaction effects on the proportion of fixation times. The proportion of fixation times on the robot is higher for negative feedback compared with positive feedback style. While the proportion of fixation times on the robot generally decreased with the increase of the interaction distance, it decreased more under the positive feedback style than under the negative feedback style. In addition, there were significant interaction effects on pupil diameter between interaction distance and posture. As interaction distance increased, mean pupil diameter became smaller in side interaction, while it became larger in frontal interaction. Moreover, the three situation factors had significant interaction effects on user acceptance of the interaction mode. The findings are helpful in the underlying mechanism of user experience in human-robot interaction situations and provide important implications for the design of robot behavioral expression and for optimal strategies to improve user experience during human-robot interaction.

Keywords: social robots, human-robot interaction, interaction posture, interaction distance, feedback style, user experience

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Authors: Aditi Acharya

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Environmental pollution is threatening the environmental and human health in the most drastic way. This paper provides insight about the affects of environmental pollution in the perspective of water pollution. Sewage in drinking water, the increasing contamination of water bodies and water resources and the human beings are the major contributors, increasing the harsh activities of pollution. The research presents information about the sources of pollution, its impacts and control activities to be undertaken to make our environment free from water pollution.

Keywords: environmental pollution, water pollution, nanotechnology, nanomaterials

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Authors: Chusak Thanawattano, Roongroj Bhidayasiri

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This paper proposes a novel feature set utilized for classifying the Parkinson tremor and essential tremor. Ten ET and ten PD subjects are asked to perform kinetic, postural and resting tests. The empirical mode decomposition (EMD) is used to decompose collected tremor signal to a set of intrinsic mode functions (IMF). The IMFs are used for reconstructing representative signals. The feature set is composed of peak frequencies of IMFs and reconstructed signals. Hypothesize that the dominant frequency components of subjects with PD and ET change in different directions for different tests, difference of peak frequencies of IMFs and reconstructed signals of pairwise based tests (kinetic-resting, kinetic-postural and postural-resting) are considered as potential features. Sets of features are used to train and test by classifier including the quadratic discriminant classifier (QLC) and the support vector machine (SVM). The best accuracy, the best sensitivity and the best specificity are 90%, 87.5%, and 92.86%, respectively.

Keywords: tremor, Parkinson, essential tremor, empirical mode decomposition, quadratic discriminant, support vector machine, peak frequency, auto-regressive, spectrum estimation

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Authors: Blanka Havlickova

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In the last ten years, there are growing numbers of troops with machine guns serving on streets of European cities. We can see them around government buildings, major transport hubs, synagogues, galleries and main tourist landmarks. As the main purpose of armed soldier’s presence in European cities authorities declare the prevention of terrorist attacks and psychological support for tourists and domestic population. The main objective of the following study is to find out whether the deployment of armed soldiers in European cities has a calming and reassuring effect on Czech citizens (if the presence at armed soldiers make the Czech population feel more secure) or rather becomes a stress factor (the presence of soldiers standing guard in full military fatigues recalls serious criminality and terrorist attacks which are reflected in the fears and insecurity of Czech population). The initial hypothesis of this study is connected with the priming theory, the idea that when we are exposed to an image (armed soldier), it makes us unconsciously focus on a topic connected with this image (terrorism). This paper is based on a quantitative public survey, which was carried out in the form of electronic questioning among the citizens of the Czech Republic. Respondents answered 14 questions about two European cities – London and Paris. Besides general questions investigating the respondents' awareness of these cities, some of the questions focused on the fear that the respondents had when picturing themselves leaving next Monday for the given city (London or Paris). The questions asking about respondent´s travel fears and concerns were accompanied by different photos. When answering the question about fear some respondents have been presented with a photo of Westminster Palace and the Eiffel with ordinary citizens while other respondents have been presented with a picture of the Westminster Palace, the and Eiffel's tower not only with ordinary citizens, but also with one soldier holding a machine gun. The main goal of this paper is to analyse and compare data about concerns for these two groups of respondents (presented with different pictures) and find out if and how an armed soldier with a machine gun in front of the Westminster Palace or the Eiffel Tower affects the public's concerns about visiting the site. In other words, the aim of this paper is to confirm or rebut the hypothesis that the look at a soldier with a machine gun in front of the Eiffel Tower or the Westminster Palace automatically triggers the association with a terrorist attack leading to an increase in fear and insecurity among Czech population.

Keywords: terrorism, security measures, priming, risk perception

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Authors: Odeh Linus

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The pace of globalization is increasing continuously in terms of markets for goods and services, investment opportunities across borders amongst others. Enterprises face competition from all fronts. Human resource management is not left out in this transformation crusade as it has obligation to move along with the changing demands of the globalization process. One of the objectives of this paper is to show that effective managers should constantly be aware of the changes taking place in domestic (home country) environment, as well as around the globe (international and foreign environments) on HR issues and developments. By so doing, they can scan their environment on an ongoing basis, and when they detect opportunities and/or threats, they can transform their organization to seize the opportunities and/or combat or neutralize the threats as the case may be. In this presentation, problems, issues and trends in HRM practice in Nigeria in the current period were reviewed. The factors affecting HRM and its practice in a global context and what should be the direction of the profession and its practice in Nigeria constitute the main focus of this paper.

Keywords: human resource, globalization, management, developing countries

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Authors: Ummi Sholihah Pertiwi Abidin, Khusnul Hajar Nuansari

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Human resource is one of the most important components that can not be separated from communication fields, either in a large community like a mass or narrow ones such as an institution, office, group and even family. Human resource is an asset which is often used as a tool to achieve certain goals. Therefore, development of human resources is essential for improving skills and character of a person especially at the time that has entered globalization era. People are required to be able to compete both in the local and international arena, no matter what. This paper raised topic related to human resource development solution by a unique educational leadership and communication skill improvement through a linguistic approach. Here the authors want to go by form of public speaking method applied in Modern Islamic Boarding School Darussalam Gontor as the extracurricular activity that is using three languages, they are: Indonesian as the mother language or the nation language of the students, Arabic and English as the second language and Gontor’s mean to supply its students to be able to conquer the globalization needs. This implementation produced the establishment of great leaders through confidence growing to speak in public by adjusting the listener context. In linguistic term, it will help enhancing verbal and nonverbal communication skills and so forth in owning a lot of vocabulary.

Keywords: public speaking, Gontor, language, leadership

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Authors: Kumlachew Zelalem Walle, Chun-Chen Yang

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Solid-state lithium metal batteries (SSLMBs) are considered promising candidates for next-generation energy storage devices due to their superior energy density and excellent safety. However, recent findings have shown that the formation of lithium (Li) dendrites in SSLMBs still exhibits a terrible growth ability, which makes the development of SSLMBs have to face the challenges posed by the Li dendrite problem. In this work, an inorganic/organic mixture coating material (g-C3N4/ZIF-8/PVDF) was used to modify the surface of lithium metal anode (LMA). Then the modified LMA (denoted as g-C₃N₄@Li) was assembled with lithium nafion (LiNf) coated commercial NCM811 (LiNf@NCM811) using a bilayer hybrid solid electrolyte (Bi-HSE) that incorporated 20 wt.% (vs. polymer) LiNf coated Li6.05Ga0.25La3Zr2O11.8F0.2 ([email protected]) filler faced to the positive electrode and the other layer with 80 wt.% (vs. polymer) filler content faced to the g-C₃N₄@Li. The garnet-type Li6.05Ga0.25La3Zr2O11.8F0.2 (LG0.25LZOF) solid electrolyte was prepared via co-precipitation reaction process from Taylor flow reactor and modified using lithium nafion (LiNf), a Li-ion conducting polymer. The Bi-HSE exhibited high ionic conductivity of 6.8  10–4 S cm–1 at room temperature, and a wide electrochemical window (0–5.0 V vs. Li/Li+). The coin cell was charged between 2.8 to 4.5 V at 0.2C and delivered an initial specific discharge capacity of 194.3 mAh g–1 and after 100 cycles it maintained 81.8% of its initial capacity at room temperature. The presence of a nano-sheet g-C3N4/ZIF-8/PVDF as a composite coating material on the LMA surface suppress the dendrite growth and enhance the compatibility as well as the interfacial contact between anode/electrolyte membrane. The g-C3N4@Li symmetrical cells incorporating this hybrid electrolyte possessed excellent interfacial stability over 1000 h at 0.1 mA cm–2 and a high critical current density (1 mA cm–2). Moreover, the in-situ formation of Li3N on the solid electrolyte interface (SEI) layer as depicted from the XPS result also improves the ionic conductivity and interface contact during the charge/discharge process. Therefore, these novel multi-layered fabrication strategies of hybrid/composite solid electrolyte membranes and modification of the LMA surface using mixed coating materials have potential applications in the preparation of highly safe high-voltage cathodes for SSLMBs.

Keywords: high-voltage cathodes, hybrid solid electrolytes, garnet, graphitic-carbon nitride (g-C3N4), ZIF-8 MOF

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Authors: Mohsin Ali Shaikh, Song Weiguo, Muhammad Kashan Surahio, Usman Shahid, Rehmat Karim

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When the area of a structure that is threatened by a disaster affects personal safety, the effectiveness of disaster prevention, evacuation, and rescue operations can be summarized by three assessment indicators: personal safety, property preservation, and attribution of responsibility. These indicators are applicable regardless of the disaster that affects the building. People need to get out of the hazardous area and to a safe place as soon as possible because there's no other way to respond. The results of the tragedy are thus closely related to how quickly people are advised to evacuate and how quickly they are rescued. This study considers present fire prevention systems to address catastrophes and improve building safety. It proposes the methods of Prevention Level for Deployment in Advance and Spatial Transformation by Human-Machine Collaboration. We present and prototype a real-time fire protection system architecture for building disaster prevention, evacuation, and rescue operations. The design encourages the use of simulations to check the efficacy of evacuation, rescue, and disaster prevention procedures throughout the planning and design phase of the structure.

Keywords: prevention level, building information modeling, quality management system, simulated reality

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Authors: Erick C. Valverde, Wansu Lim

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Facial emotion recognition (FER) system has been recently developed for more advanced computer vision applications. The ability to identify human emotions would enable smart healthcare facility to diagnose mental health illnesses (e.g., depression and stress) as well as better human social interactions with smart technologies. The FER system involves two steps: 1) face detection task and 2) facial emotion recognition task. It classifies the human expression in various categories such as angry, disgust, fear, happy, sad, surprise, and neutral. This system requires intensive research to address issues with human diversity, various unique human expressions, and variety of human facial features due to age differences. These issues generally affect the ability of the FER system to detect human emotions with high accuracy. Early stage of FER systems used simple supervised classification task algorithms like K-nearest neighbors (KNN) and artificial neural networks (ANN). These conventional FER systems have issues with low accuracy due to its inefficiency to extract significant features of several human emotions. To increase the accuracy of FER systems, deep learning (DL)-based methods, like convolutional neural networks (CNN), are proposed. These methods can find more complex features in the human face by means of the deeper connections within its architectures. However, the inference speed and computational costs of a DL-based FER system is often disregarded in exchange for higher accuracy results. To cope with this drawback, an optimized DL-based FER system is proposed in this study.An extreme version of Inception V3, known as Xception model, is leveraged by applying different network optimization methods. Specifically, network pruning and quantization are used to enable lower computational costs and reduce memory usage, respectively. To support low resource requirements, a 68-landmark face detector from Dlib is used in the early step of the FER system.Furthermore, a DL compiler is utilized to incorporate advanced optimization techniques to the Xception model to improve the inference speed of the FER system. In comparison to VGG-Net and ResNet50, the proposed optimized DL-based FER system experimentally demonstrates the objectives of the network optimization methods used. As a result, the proposed approach can be used to create an efficient and real-time FER system.

Keywords: deep learning, face detection, facial emotion recognition, network optimization methods

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Authors: Adriana M. Duquette, Derek P. Bornath

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Reaction Time (RT) and Movement Time (MT) are important components of everyday life that have an effect on the way in which we move about our environment. These measures become even more crucial when an event can be caused (or avoided) in a fraction of a second, such as the RT and MT required while driving. The purpose of this study was to develop a more simple method of testing RT and MT during simulated driving with or without text messaging, in a university-aged population (n = 170). In the control condition, a randomly-delayed red light stimulus flashed on a computer interface after the participant began pressing the ‘gas’ pedal on a foot switch mat. Simple RT was defined as the time between the presentation of the light stimulus and the initiation of lifting the foot from the switch mat ‘gas’ pedal; while MT was defined as the time after the initiation of lifting the foot, to the initiation of depressing the switch mat ‘brake’ pedal. In the texting condition, upon pressing the ‘gas’ pedal, a ‘text message’ appeared on the computer interface in a dialog box that the participant typed on their cell phone while waiting for the light stimulus to turn red. In both conditions, the sequence was repeated 10 times, and an average RT (seconds) and average MT (seconds) were recorded. Condition significantly (p = .000) impacted overall RTs, as the texting condition (0.47 s) took longer than the no-texting (control) condition (0.34 s). Longer MTs were also recorded during the texting condition (0.28 s) than in the control condition (0.23 s), p = .001. Overall increases in Response Time (RT + MT) of 189 ms during the texting condition would equate to an additional 4.2 meters (to react to the stimulus and begin braking) if the participant had been driving an automobile at 80 km per hour. In conclusion, increasing task complexity due to the dual-task demand of text messaging during simulated driving caused significant increases in RT (41%), MT (23%) and Response Time (34%), thus further strengthening the mounting evidence against text messaging while driving.

Keywords: simulated driving, text messaging, reaction time, movement time

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Authors: Prabir Mukhopadhyay, Atul Kohale

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Going to school for Indian kids is a panic situation. Many of them are unable to adjust themselves to the confinement of the school building and this problem is compounded by other factors like unknown people in the vicinity, absence of either parents etc. This project aims at addressing these issues by exposing the kids at home to the learning environment. The purpose is to design a physical model with interfaces at each surface. The model would be like a cube with interactive surfaces where the child would be able to draw, paint, complete a picture and do such fun activities.

Keywords: interface, kids, play, computer systems engineering

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Authors: Ricky Leung

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Artificial intelligence (AI) and machine learning (ML) have revolutionized the way health organizations approach social media. The sheer volume of data generated through social media can be overwhelming, but AI and ML can help organizations effectively manage this information to improve the health and well-being of individuals and communities. One way AI can be used to enhance social media in health organizations is through sentiment analysis. This involves analyzing the emotions expressed in social media posts to better understand public opinion and respond accordingly. This can help organizations gauge the impact of their campaigns, track the spread of misinformation, and improve communication with the public. While social media is a useful tool, researchers and practitioners have expressed fear that it will be used for the spread of misinformation, which can have serious consequences for public health. Health organizations must work to ensure that AI systems are transparent, trustworthy, and unbiased so they can help minimize the spread of misinformation. In conclusion, AI and ML have the potential to greatly enhance the use of social media in health organizations. These technologies can help organizations effectively manage large amounts of data and understand stakeholders' sentiments. However, it is important to carefully consider the potential consequences and ensure that these systems are carefully designed to minimize the spread of misinformation.

Keywords: AI, ML, social media, health organizations

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Authors: Lydia Novozhilova, Vladimir Urazhdin

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An optimization problem for reinforced thin-walled vessels under uniform external pressure is considered. The conventional approaches to optimization generally start with pre-defined geometric parameters of the vessels, and then employ analytic or numeric calculations and/or experimental testing to verify functionality, such as stability under the projected conditions. The proposed approach consists of two steps. First, the feasibility domain will be identified in the multidimensional parameter space. Every point in the feasibility domain defines a design satisfying both geometric and functional constraints. Second, an objective function defined in this domain is formulated and optimized. The broader applicability of the suggested methodology is maximized by implementing the Support Vector Machines (SVM) classification algorithm of machine learning for identification of the feasible design region. Training data for SVM classifier is obtained using the Simulation package of SOLIDWORKS®. Based on the data, the SVM algorithm produces a curvilinear boundary separating admissible and not admissible sets of design parameters with maximal margins. Then optimization of the vessel parameters in the feasibility domain is performed using the standard algorithms for the constrained optimization. As an example, optimization of a ring-stiffened closed cylindrical thin-walled vessel with semi-spherical caps under high external pressure is implemented. As a functional constraint, von Mises stress criterion is used but any other stability constraint admitting mathematical formulation can be incorporated into the proposed approach. Suggested methodology has a good potential for reducing design time for finding optimal parameters of thin-walled vessels under uniform external pressure.

Keywords: design parameters, feasibility domain, von Mises stress criterion, Support Vector Machine (SVM) classifier

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Authors: Chandu Rathnayake, Isuri Anuradha

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Early detection and accurate diagnosis of lung diseases play a crucial role in improving patient prognosis. However, conventional diagnostic methods heavily rely on subjective symptom assessments and medical imaging, often causing delays in diagnosis and treatment. To overcome this challenge, we propose a novel lung disease prediction system that integrates patient symptoms and X-ray images to provide a comprehensive and reliable diagnosis.In this project, develop a mobile application specifically designed for detecting lung diseases. Our application leverages both patient symptoms and X-ray images to facilitate diagnosis. By combining these two sources of information, our application delivers a more accurate and comprehensive assessment of the patient's condition, minimizing the risk of misdiagnosis. Our primary aim is to create a user-friendly and accessible tool, particularly important given the current circumstances where many patients face limitations in visiting healthcare facilities. To achieve this, we employ several state-of-the-art algorithms. Firstly, the Decision Tree algorithm is utilized for efficient symptom-based classification. It analyzes patient symptoms and creates a tree-like model to predict the presence of specific lung diseases. Secondly, we employ the Random Forest algorithm, which enhances predictive power by aggregating multiple decision trees. This ensemble technique improves the accuracy and robustness of the diagnosis. Furthermore, we incorporate a deep learning model using Convolutional Neural Network (CNN) with the RestNet50 pre-trained model. CNNs are well-suited for image analysis and feature extraction. By training CNN on a large dataset of X-ray images, it learns to identify patterns and features indicative of lung diseases. The RestNet50 architecture, known for its excellent performance in image recognition tasks, enhances the efficiency and accuracy of our deep learning model. By combining the outputs of the decision tree-based algorithms and the deep learning model, our mobile application generates a comprehensive lung disease prediction. The application provides users with an intuitive interface to input their symptoms and upload X-ray images for analysis. The prediction generated by the system offers valuable insights into the likelihood of various lung diseases, enabling individuals to take appropriate actions and seek timely medical attention. Our proposed mobile application has significant potential to address the rising prevalence of lung diseases, particularly among young individuals with smoking addictions. By providing a quick and user-friendly approach to assessing lung health, our application empowers individuals to monitor their well-being conveniently. This solution also offers immense value in the context of limited access to healthcare facilities, enabling timely detection and intervention. In conclusion, our research presents a comprehensive lung disease prediction system that combines patient symptoms and X-ray images using advanced algorithms. By developing a mobile application, we provide an accessible tool for individuals to assess their lung health conveniently. This solution has the potential to make a significant impact on the early detection and management of lung diseases, benefiting both patients and healthcare providers.

Keywords: CNN, random forest, decision tree, machine learning, deep learning

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Authors: Valery Yakubovich, Shuping wu

Abstract:

Organization theorists have long claimed that organizational innovations are nontechnological, in part because they are unpatentable. The claim rests on the assumption that organizational innovations are abstract ideas embodied in persons and contexts rather than in context-free practical tools. However, over the last three decades, organizational knowledge has been increasingly embodied in digital tools which, in principle, can be patented. To provide the first empirical evidence regarding the patentability of organizational innovations, we trained two machine learning algorithms to identify a population of 205,434 patent applications for organizational technologies (OrgTech) and, among them, 141,285 applications that use organizational innovations accumulated over the 20th century. Our event history analysis of the probability of patenting an OrgTech invention shows that ideas from organizational innovations decrease the probability of patent allowance unless they describe a practical tool. We conclude that the present-day digital transformation places organizational innovations in the realm of high tech and turns the debate about organizational technologies into the challenge of designing practical organizational tools that embody big ideas about organizing. We outline an agenda for patent-based research on OrgTech as an emerging phenomenon.

Keywords: organizational innovation, organizational technology, high tech, patents, machine learning

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Authors: Tasawar Nawaz

Abstract:

Migration has once again become a lively topic in Europe and UK, in particular. A burgeoning concern in the public debate, however, is driven by the fear that migrants are fiscal burden because they drain public resources by drawing on the generous social transfers introduced in Europe to prevent social exclusion. This study challenges these beliefs by gathering empirical evidence through a qualitative research approach on the subject matter. The analysis suggests that UK provides a rich social and economic environment for intellectual profiles especially, human intellectual capital of migrants to flourish and add value to the exchequer. Contrary to the beliefs held by politicians and general public, the empirical evidence suggests that migrants add higher fiscal contribution by working longer hours, paying consistent taxes, and bringing skills which UK may lack thus, are not fiscal burdens on the UK exchequer.

Keywords: austerity, European union, human intellectual capital, migrants, social welfare, United Kingdom

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Authors: Neha Singh, Ananya Arora

Abstract:

Facial expression measurement plays a crucial role in the identification of emotion. Facial expression plays a key role in psychophysiology, neural bases, and emotional disorder, to name a few. The Facial Action Coding System (FACS) has proven to be the most efficient and widely used of the various systems used to describe facial expressions. Coders can manually code facial expressions with FACS and, by viewing video-recorded facial behaviour at a specified frame rate and slow motion, can decompose into action units (AUs). Action units are the most minor visually discriminable facial movements. FACS explicitly differentiates between facial actions and inferences about what the actions mean. Action units are the fundamental unit of FACS methodology. It is regarded as the standard measure for facial behaviour and finds its application in various fields of study beyond emotion science. These include facial neuromuscular disorders, neuroscience, computer vision, computer graphics and animation, and face encoding for digital processing. This paper discusses the conceptual basis for FACS, a numerical listing of discrete facial movements identified by the system, the system's psychometric evaluation, and the software's recommended training requirements.

Keywords: facial action, action units, coding, machine learning

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Authors: Michiko Miyamoto

Abstract:

This paper empirically investigates whether information technology (IT) strategies, business strategies, and divisions are aligned to meet overall business goals for Korean Small and medium-sized enterprises (SMEs), based on structure based Strategic Alignment Model, and make comparison with those of Japanese SMEs. Using 2,869 valid responses of Korean Human Capital Corporate Panel survey, a result of this study suggests that Korean human resources (HR) departments have a major influence over IT strategy, which is the same as Japanese SMEs, even though their management styles are quite different. As for IT strategy, it is not related to other departments at all for Korean SMEs. The Korean management seems to possess a great power over each division, such as Sales/Service, Research and Development/Technical Experts, HR, and Production.

Keywords: IT-business alignment, structured based strategic alignment model, structural equation model, human resources department

Procedia PDF Downloads 257

Authors: Gassem Alfaleh

Abstract:

In Strict liability, a person can be held liable for any harm resulting from certain actions or activities without any mistake. The liability is strict because a person can be liable when he or she commits any harm with or without his intention. The duty owed is the duty to avoid causing the plaintiff any harm. However, “strict liability is imposed at the International level by two types of treaties, namely those limited to giving internal effect to treaty provisions and those that impose responsibilities on states. The basic principle of strict liability is that there is a liability on the operator or the state (when the act concerned is attributable to the state) for damage inflicted without there being a need to prove unlawful behavior”. In international human rights law, strict liability can exist when a defendant is in legal jeopardy by virtue of an internationally wrongful act, without any accompanying intent or mental state. When the defendant engages in an abnormally dangerous activity against the environment, he will be held liable for any harm it causes, even if he was not at fault. The paper will focus on these activities under international human rights law. First, the paper will define important terms in the first section of the paper. Second, it will focus on state and non-state actors in terms of strict liability. Then, the paper will cover three major areas in which states should be liable for hazardous activities: (1) nuclear energy, (2) maritime pollution, (3) Space Law, and (4) other hazardous activities which damage the environment.

Keywords: human rights, law, legal, absolute

Procedia PDF Downloads 139

Authors: Mazo Kone, Rachida Salah, Harir Noria

Abstract:

Background and objectives: c-Cbl and Cbl-b are two members of the Cbl family proteins, with a crucial role of downregulation of tyrosine kinase receptors. They act as E3 ubiquitin ligases and are multivalent adaptor proteins, making them important in maintaining homeostasis in the body. This study investigated the expression level in thymus and testis in normal conditions. Methods: The expression level was assessed by immunochemistry of tissue microarrays of normal thymus and testis biopsies. Results: Cbl-b and c-Cbl proteins were found to be highly expressed in normal testis and thymus, indicated as yellowish brown granules in the cytomembrane and cytoplasm compared to controls. The c-Cbl appears to be more highly expressed than the Cbl-b in the thymus, while c-Cbl appears slightly stronger than Cbl-b in the testis. The thymus was found with a higher grade compared to the testis. Conclusion: In this work we concluded, that in normal condition, thymus tissue expresses more Cbl family proteins(c-Cbl and Cbl-b) than the testis tissue in humans.

Keywords: Human C-Cbl proteins, Human Cbl-b protein, Testis, Thymus

Procedia PDF Downloads 216