Search results for: computer viruses

Authors: Lina S. Calucag

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Integration of research and teaching in higher education can provide valuable ways of enhancing the student learning experience, but establishing such integrative links can be complex and problematic, given different practices and levels of understanding. This study contributes to the pedagogical literature in drawing on findings from students’ survey exploring perceptions of research-informed teaching to examine how links between research and teaching can be suitably strengthened. The study employed a descriptive research design limited to the undergraduate students taking thesis/capstone courses in the tertiary levels private or public colleges and universities across the globe as respondents of the study. The findings noted that the students’ responses from different disciplines: engineering, science, education, business-related, and computer on the nexus between research and teaching is remarkable in fostering student expectations of research-informed teaching approaches. Students’ expectations on research-led, research-oriented, research-based, and research-tutored are enablers in linking research and teaching. It is recommended that experimental studies should be conducted using the four different research-informed teaching approaches in the classroom, namely: research-led, research-oriented, research-based, and research-tutored.

Keywords: research-led, research-informed teaching, research-oriented teaching, research-tutored, research-based

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Authors: Agastya Pratap Singh

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This review paper examines the emerging applications of generative adversarial networks (GANs) in the fields of image recognition and anomaly detection. With the rapid growth of digital image data, the need for efficient and accurate methodologies to identify and classify images has become increasingly critical. GANs, known for their ability to generate realistic data, have gained significant attention for their potential to enhance traditional image recognition systems and improve anomaly detection performance. The paper systematically analyzes various GAN architectures and their modifications tailored for image recognition tasks, highlighting their strengths and limitations. Additionally, it delves into the effectiveness of GANs in detecting anomalies in diverse datasets, including medical imaging, industrial inspection, and surveillance. The review also discusses the challenges faced in training GANs, such as mode collapse and stability issues, and presents recent advancements aimed at overcoming these obstacles.

Keywords: generative adversarial networks, image recognition, anomaly detection, synthetic data generation, deep learning, computer vision, unsupervised learning, pattern recognition, model evaluation, machine learning applications

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Authors: Pawan Kumar Mishra, Ganesh Singh Bisht

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Super-resolution is the technique that is being used in computer vision to construct high-resolution images from a single low-resolution image. It is used to increase the frequency component, recover the lost details and removing the down sampling and noises that caused by camera during image acquisition process. High-resolution images or videos are desired part of all image processing tasks and its analysis in most of digital imaging application. The target behind super-resolution is to combine non-repetition information inside single or multiple low-resolution frames to generate a high-resolution image. Many methods have been proposed where multiple images are used as low-resolution images of same scene with different variation in transformation. This is called multi-image super resolution. And another family of methods is single image super-resolution that tries to learn redundancy that presents in image and reconstruction the lost information from a single low-resolution image. Use of deep learning is one of state of art method at present for solving reconstruction high-resolution image. In this research, we proposed Deep Denoising Super Resolution (DDSR) that is a deep neural network for effectively reconstruct the high-resolution image from low-resolution image.

Keywords: resolution, deep-learning, neural network, de-blurring

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Authors: Javier Barrachina, Piedad Garrido, Manuel Fogue, Julio A. Sanguesa, Francisco J. Martinez

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It is very common to observe, especially in Computer Science studies that students have difficulties to correctly understand how some mechanisms based on Artificial Intelligence work. In addition, the scope and limitations of most of these mechanisms are usually presented by professors only in a theoretical way, which does not help students to understand them adequately. In this work, we focus on the problems found when teaching Evolutionary Algorithms (EAs), which imitate the principles of natural evolution, as a method to solve parameter optimization problems. Although this kind of algorithms can be very powerful to solve relatively complex problems, students often have difficulties to understand how they work, and how to apply them to solve problems in real cases. In this paper, we present two interactive graphical applications which have been specially designed with the aim of making Evolutionary Algorithms easy to be understood by students. Specifically, we present: (i) TSPS, an application able to solve the ”Traveling Salesman Problem”, and (ii) FotEvol, an application able to reconstruct a given image by using Evolution Strategies. The main objective is that students learn how these techniques can be implemented, and the great possibilities they offer.

Keywords: education, evolutionary algorithms, evolution strategies, interactive learning applications

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Authors: Martins Gbenga., Orosun M. M., Olowookere C. J., Bamidele Lateef

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Radiation exposures from diagnostic medical examinations are almost always justified by the benefits of accurate diagnosis of possible disease conditions. The aim is to assess the influence of selected exposure parameters on scattered dose rates. The research was carried out using Gamma Scout software installation on the Computer system (Laptop) to record the radiation counts, pulse rate, and dose rate for 136 patients. Seventy-three patients participated in the male category with 53.7%, while 63 females participated with 46.3%. The mean and standard deviation value for each parameter is recorded, and tube potential is within 69.50±11.75 ranges between 52.00 and 100.00, tube current is within 23.20±17.55 ranges between 4.00 and 100.00, focus skin distance is within 73.195±33.99 and ranges between 52.00 and 100.00. Dose Rate (DRate in µSv/hr) is significant at an interval of 0.582 and 0.587 for tube potential and body thickness (cm). Tube potential is significant at an interval of 0.582 and 0.842 of DRate (µSv/hr) and body thickness (cm). The study was compared with other studies. The exposure parameters selected during each examination contributed to scattered radiation. A quality assurance program (QAP) is advised for the center.

Keywords: x-radiation, exposure rate, dose rate, tube potentials, scattered radiation, diagnostic examination

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Authors: Nasrin Mohammadhasani, Rosa Angela Fabio

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The attention to relevance information is the key element for learning. Otherwise, Attention Deficit Hyperactivity Disorder (ADHD) students have a fuzzy visual pattern that prevents them to attention and remember learning subject. The present study aimed to test the hypothesis that the presence of a pedagogical agent can effectively support ADHD learner's attention and learning outcomes in a multimedia learning environment. The learning environment was integrated with a pedagogical agent, named Koosha as a social peer. This study employed a pretest and posttest experimental design with control group. The statistical population was 30 boys students, age 10-11 with ADHD that randomly assigned to learn with/without an agent in well designed environment for mathematic. The results suggested that experimental and control groups show a significant difference in time when they participated and mathematics achievement. According to this research, using the pedagogical agent can enhance learning of ADHD students by gaining and guiding their attention to relevance information part on display, so it can be considered as asocial cue that provides theme cognitive supports.

Keywords: attention, computer assisted instruction, multimedia learning environment, pedagogical agent

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Authors: A. H. Elkholy, D. M. Almutairi

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The successful and efficient execution of a forging process is dependent upon the correct analysis of loading and metal flow of blanks. This paper investigates the Upper Bound Technique (UBT) and its application in the analysis of open forging process when a possibility of blank bulging exists. The UBT is one of the energy rate minimization methods for the solution of metal forming process based on the upper bound theorem. In this regards, the kinematically admissible velocity field is obtained by minimizing the total forging energy rate. A computer program is developed in this research to implement the UBT. The significant advantages of this method is the speed of execution while maintaining a fairly high degree of accuracy and the wide prediction capability. The information from this analysis is useful for the design of forging processes and dies. Results for the prediction of forging loads and stresses, metal flow and surface profiles with the assured benefits in terms of press selection and blank preform design are outlined in some detail. The obtained predictions are ready for comparison with both laboratory and industrial results.

Keywords: forging, upper bound technique, metal forming, forging energy, forging die/platen

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Authors: Maryam Tajadod

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The treatment of cancer is one of the main challenges of nuclear medicine; while cancer begins in an organ, such as the breast or prostate, it spreads to the bone, resulting in metastatic bone. In the treatment of cancer with radiotherapy, the determination of the involved tissues’ dose is one of the important steps in the treatment protocol. Comparing absorbed doses for Lu-177 and Ra-223 and Ac-225 in the bone marrow and soft tissue of bone phantom with evaluating energetic emitted particles of these radionuclides is the important aim of this research. By the use of MCNPX computer code, a model for bone phantom was designed and the values of absorbed dose for Ra-223 and Ac-225, which are Alpha emitters & Lu-177, which is a beta emitter, were calculated. As a result of research, in comparing gamma radiation for three radionuclides, Lu-177 released the highest dose in the bone marrow and Ra-223 achieved the lowest level. On the other hand, the result showed that although the figures of absorbed dose for Ra and Ac in the bone marrow are near to each other, Ra spread more energy in cortical bone. Moreover, The alpha component of the Ra-223 and Ac-225 have very little effect on bone marrow and soft tissue than a beta component of the lu-177 and it leaves the highest absorbed dose in the bone where the source is located.

Keywords: bone metastases, lutetium-177, radium-223, actinium-225, absorbed dose

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Authors: Bahar Urhan Torun, Havva Nur Tarakcı

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At the present time, online marketing has become the common target of small and full-scale organizations. Today’s humanbeing who has to spend most of their time in front of the computer because of his job, prefers to socialize by internet due to the easy access to technology. So online marketing area expands day by day. All business organizations from the smallest to the biggest are in a race in order to get a cut from the virtual market share in an extreme competitive environment. However these organizations which use the internet to reach more consumers cannot determine their target group accurately, so this is the biggest handicap of online marketing sales nowadays. The aim of this study is to determine some significant elements about need for communicating efficiently with the consumer on the internet on online marketing. The strategies that can be used in order to increase sales and the limitations of virtual environment where cannot be communicated with the consumer face to face are argued in this study’s scope. As a consequence it is thought that to study on this subject because of lacking and also being limited efficiency of researches and outputs. Within this scope suggesting some proposals about how to communicate efficiently with the consumer and also offering the consumers’ demands efficiently is the essential objective of this study.

Keywords: online marketing, competition, consumer, communication

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Authors: Victoria Zenotz

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For Fairclough (1989) critical literacy is a tool to enable readers and writers to build up meaning in discourse. More recently other authors (Leu et al., 2004) have included the new technology context in their definition of literacy. In their view being literate nowadays means to “successfully use and adapt to the rapidly changing information and communication technologies and contexts that continuously emerge in our world and influence all areas of our personal and professional lives.” (Leu et al., 2004: 1570). In this presentation the concept of critical literacy will be related to the creation of digital stories. In the first part of the presentation concepts such as literacy and critical literacy are examined. We consider that real social practices will help learners may improve their literacy level. Accordingly, we show some research, which was conducted at a secondary school in the north of Spain (2013-2014), to illustrate how the “writing” of digital stories may contribute to the development of critical literacy. The use of several instruments allowed the collection of data at the different stages of their creative process including watching and commenting models for digital stories, planning a storyboard, creating and selecting images, adding voices and background sounds, editing and sharing the final product. The results offer some valuable insights into learners’ literacy progress.

Keywords: literacy, computer assisted language learning, esl

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Authors: Mohammad Saleh Vahdatpour, Yanqing Zhang

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Understanding the neural mechanisms underlying motion detection in the human visual system has long been a fascinating challenge in neuroscience and artificial intelligence. This paper presents a spiking neural network model inspired by the processing of motion information in the primate visual system, particularly focusing on the Middle Temporal (MT) area. In our study, we propose a multi-layer spiking neural network model to perform motion detection tasks, leveraging the idea that synaptic delays in neuronal communication are pivotal in motion perception. Synaptic delay, determined by factors like axon length and myelin insulation, affects the temporal order of input spikes, thereby encoding motion direction and speed. Overall, our spiking neural network model demonstrates the feasibility of capturing motion detection principles observed in the primate visual system. The combination of synaptic delays, learning mechanisms, and shared weights and delays in SMD provides a promising framework for motion perception in artificial systems, with potential applications in computer vision and robotics.

Keywords: neural network, motion detection, signature detection, convolutional neural network

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Authors: Ece A. Irmak, Amdulla O. Mekhrabov, M. Vedat Akdeniz

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There is a growing interest in the modeling and simulation of magnetic nanoalloys by various computational methods. Magnetic crystalline/amorphous nanoparticles (NP) are interesting materials from both the applied and fundamental points of view, as their properties differ from those of bulk materials and are essential for advanced applications such as high-performance permanent magnets, high-density magnetic recording media, drug carriers, sensors in biomedical technology, etc. As an important magnetic material, Fe-Ni based nanoalloys have promising applications in the chemical industry (catalysis, battery), aerospace and stealth industry (radar absorbing material, jet engine alloys), magnetic biomedical applications (drug delivery, magnetic resonance imaging, biosensor) and computer hardware industry (data storage). The physical and chemical properties of the nanoalloys depend not only on the particle or crystallite size but also on composition and atomic ordering. Therefore, computer modeling is an essential tool to predict structural, electronic, magnetic and optical behavior at atomistic levels and consequently reduce the time for designing and development of new materials with novel/enhanced properties. Although first-principles quantum mechanical methods provide the most accurate results, they require huge computational effort to solve the Schrodinger equation for only a few tens of atoms. On the other hand, molecular dynamics method with appropriate empirical or semi-empirical inter-atomic potentials can give accurate results for the static and dynamic properties of larger systems in a short span of time. In this study, structural evolutions, magnetic and electronic properties of Fe-Ni based nanoalloys have been studied by using molecular dynamics (MD) method in Large-scale Atomic/Molecular Massively Parallel Simulator (LAMMPS) and Density Functional Theory (DFT) in the Vienna Ab initio Simulation Package (VASP). The effects of particle size (in 2-10 nm particle size range) and temperature (300-1500 K) on stability and structural evolutions of amorphous and crystalline Fe-Ni bulk/nanoalloys have been investigated by combining molecular dynamic (MD) simulation method with Embedded Atom Model (EAM). EAM is applicable for the Fe-Ni based bimetallic systems because it considers both the pairwise interatomic interaction potentials and electron densities. Structural evolution of Fe-Ni bulk and nanoparticles (NPs) have been studied by calculation of radial distribution functions (RDF), interatomic distances, coordination number, core-to-surface concentration profiles as well as Voronoi analysis and surface energy dependences on temperature and particle size. Moreover, spin-polarized DFT calculations were performed by using a plane-wave basis set with generalized gradient approximation (GGA) exchange and correlation effects in the VASP-MedeA package to predict magnetic and electronic properties of the Fe-Ni based alloys in bulk and nanostructured phases. The result of theoretical modeling and simulations for the structural evolutions, magnetic and electronic properties of Fe-Ni based nanostructured alloys were compared with experimental and other theoretical results published in the literature.

Keywords: density functional theory, embedded atom model, Fe-Ni systems, molecular dynamics, nanoalloys

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Authors: Ibrahim Mohammed, Suleiman Taofiq, Muhammad Naziru Yahya

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Geoelectrical measurements using Schlumberger Vertical Electrical Sounding (VES) method were carried out in Waziri Umaru Federal Polytechnic, Birnin Kebbi, Nigeria, with the aim of determining the groundwater potential in the area. Twelve (12) Vertical Electric Sounding (VES) data were collected using Terrameter (ABEM SAS 300c) and analyzed using computer software (IPI2win), which gives an automatic interpretation of the apparent resistivity. The results of the interpretation of VES data were used in the characterization of three to five geo-electric layers from which the aquifer units were delineated. Data analysis indicated that water bearing formation exists in the third and fourth layers having resistivity range of 312 to 767 Ωm and 9.51 to 681 Ωm, respectively. The thickness of the formation ranges from 14.7 to 41.8 m, while the depth is from 8.22 to 53.7 m. Based on the result obtained from the interpretation of the data, five (5) VES stations were recommended as the most viable locations for groundwater exploration in the study area. The VES stations include VES A4, A5, A6, B1, and B2. The VES results of the entire area indicated that the water bearing formation occurs at maximum depth of 53.7 m at the time of this survey.

Keywords: aquifer, depth, groundwater, resistivity, Schlumberger

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Authors: Liu Junzhu

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In contemporary China,city is expanding with an amazing speed. And because of the unexpected events’ interference, spatial structure could change itself in a short time, That will lead to the new urban district livingness and unfortunately, this phenomenon is very common.On the one hand,it fail to achieve the goal of city planning, On the other hand,it is unfavourable to the sustainable development of city. Bill Hillier’stheory Space Syntax shows organzation pattern of each space,it explains the characteristics of urban spatial patterns and its transformation regulation from the point of self-organization in system and also, it gives confirmatory and predictive ways to the building and city. This paper used axial model to summarize Hangzhou City’s special structure and enhanced comprehensive understanding of macroscopic space and environment, space structure,developing trend, ect, by computer analysis of Space Syntax. From that, it helps us to know the operation law in the urban system and to understand Hangzhou City’s spatial pattern and indirect social effect it has mad more clearly, Thus, it could comply with the tendency of cities development in process and planning of policy and plan our cities’ future sustainably.

Keywords: sustainable urban design, space syntax, spatial network, segment angular analysis, social inclusion

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Authors: Jadisha Cornejo, Helio Pedrini

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Recognition of emotions based on facial expressions has received increasing attention from the scientific community over the last years. Several fields of applications can benefit from facial emotion recognition, such as behavior prediction, interpersonal relations, human-computer interactions, recommendation systems. In this work, we develop and analyze an emotion recognition framework based on facial expressions robust to occlusions through the Weber Local Descriptor (WLD). Initially, the occluded facial expressions are reconstructed following an extension approach of Robust Principal Component Analysis (RPCA). Then, WLD features are extracted from the facial expression representation, as well as Local Binary Patterns (LBP) and Histogram of Oriented Gradients (HOG). The feature vector space is reduced using Principal Component Analysis (PCA) and Linear Discriminant Analysis (LDA). Finally, K-Nearest Neighbor (K-NN) and Support Vector Machine (SVM) classifiers are used to recognize the expressions. Experimental results on three public datasets demonstrated that the WLD representation achieved competitive accuracy rates for occluded and non-occluded facial expressions compared to other approaches available in the literature.

Keywords: emotion recognition, facial expression, occlusion, fiducial landmarks

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Authors: Jorge Martinez-Garcia, Ingrid Stelzner, Joerg Stelzner, Damian Gwerder, Philipp Schuetz

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Tree-ring analysis is an important part of the quality assessment and the dating of (archaeological) wood samples. It provides quantitative data about the whole anatomical ring structure, which can be used, for example, to measure the impact of the fluctuating environment on the tree growth, for the dendrochronological analysis of archaeological wooden artefacts and to estimate the wood mechanical properties. Despite advances in computer vision and edge recognition algorithms, detection and counting of annual rings are still limited to 2D datasets and performed in most cases manually, which is a time consuming, tedious task and depends strongly on the operator’s experience. This work presents an image processing approach to detect the whole 3D tree-ring structure directly from X-ray computed tomography imaging data. The approach relies on a modified Canny edge detection algorithm, which captures fully connected tree-ring edges throughout the measured image stack and is validated on X-ray computed tomography data taken from six wood species.

Keywords: ring recognition, edge detection, X-ray computed tomography, dendrochronology

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Authors: Hadj Brahim Mounia, Belhamel Farid, Souici Messoud

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In big cities, construction on sloping land (landslide) is becoming increasingly prevalent due to the unavailability of flat lands. This has created a major challenge for structural engineers with regard to structure design, due to the difficulties encountered during the implementation of projects, both for the structure and the soil. This paper analyses the effect of the number of floors of a building, founded on isolated footing on the stability of the slope using the computer code finite element PLAXIS 2D v. 8.2. The isolated footings of a building in this case were anchored in soil so that the levels of successive isolated footing realize a maximum slope of base of three for two heights, which connects the edges of the nearest footings, according to the Algerian building code DTR-BC 2.331: Shallow foundations. The results show that the embedment of the foundation into the soil reduces the value of the safety factor due to the change of the stress state of the soil by these foundations. The number of floors a building has also influences the safety factor. It has been noticed from this case of study that there is no risk of collapse of slopes for an inclination between 5° and 8°. In the case of slope inclination greater than 10° it has been noticed that the urbanization is prohibited.

Keywords: isolated footings, multi-storeys building, PLAXIS 2D, slope

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Authors: Terada Pinyo

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This study is a survey research designed to evaluate the quality of graduate students and factors influencing their quality. The sample group consists of 240 students. The data are collected from stratified sampling and are analyzed and calculated by instant computer program. Statistics used are percentage, mean, standard deviation, Pearson correlation coefficient, Cramer’s V and logistic regression analysis. It is found that the graduate students’ opinions regarding their characteristics according to the Thai Qualifications Framework for Higher Education (TQF) are at high score range both overall and specific category. The top categories that received the top score are interpersonal skills and responsibility, ethics and morals, knowledge, cognitive skills, numerical analysis with communication and information technology skills, respectively. On the other hand, factors affecting the quality of graduate students are cognitive skills, numerical analysis with communication and information technology, knowledge, interpersonal skills and responsibility, ethics and morals, and career regarding sales/business, respectively.

Keywords: student quality evaluation, Thai qualifications framework for higher education, graduate school, cognitive skills

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Authors: Mehrnaz Mostafavi, Mahtab Shabani, Alireza Azani, Fatemeh Ghafari

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Artificial intelligence (AI) can transform breast cancer diagnosis and therapy by providing sophisticated solutions for screening, imaging interpretation, histopathological analysis, and treatment planning. This literature review digs into the many uses of AI in breast cancer treatment, highlighting the need for collaboration between AI scientists and healthcare practitioners. It emphasizes advances in AI-driven breast imaging interpretation, such as computer-aided detection and diagnosis (CADe/CADx) systems and deep learning algorithms. These have shown significant potential for improving diagnostic accuracy and lowering radiologists' workloads. Furthermore, AI approaches such as deep learning have been used in histopathological research to accurately predict hormone receptor status and categorize tumor-associated stroma from regular H&E stains. These AI-powered approaches simplify diagnostic procedures while providing insights into tumor biology and prognosis. As AI becomes more embedded in breast cancer care, it is crucial to ensure its ethical, efficient, and patient-focused implementation to improve outcomes for breast cancer patients ultimately.

Keywords: breast cancer, artificial intelligence, cancer diagnosis, clinical practice

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Authors: Melissa C. LaDuke

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The overarching purpose of this study was to determine the relationship between the current format of online delivery for Defense Acquisition University (DAU) courses and Air Force Acquisition (AFA) personnel participation. AFA personnel (hereafter named “student”) were particularly of interest, as they have been mandated to take anywhere from 3 to 30 online courses to earn various DAU specialization certifications. Participants in this qualitative case study were AFA personnel who pursued DAU certifications in science and technology management, program/contract management, and other related fields. Air Force personnel were interviewed about their experiences with online courses. The data gathered were analyzed and grouped into 12 major themes. The themes tied into the theoretical framework and spoke to either teacher-centered or student-centered educational practices within Defense Acquisitions University. Based on the results of the data analysis, various factors contributed to student perceptions of DAU courses, including the online course construct and relevance to their job. The analysis also found students want to learn the information presented but would like to be able to apply the information learned in meaningful ways.

Keywords: educational theory, computer-based training, interview, student perceptions, online course design, teacher positionality

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Authors: Naman Solanki, Souraj Mondal

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With the world moving towards online communication, the video datastore has exploded in the past few years. Consequently, it has become crucial to analyse participant’s engagement levels in online communication videos. Engagement prediction of people in videos can be useful in many domains, like education, client meetings, dating, etc. Video-level or frame-level prediction of engagement for a user involves the development of robust models that can capture facial micro-emotions efficiently. For the development of an engagement prediction model, it is necessary to have a widely-accepted standard dataset for engagement analysis. DAiSEE is one of the datasets which consist of in-the-wild data and has a gold standard annotation for engagement prediction. Earlier research done using the DAiSEE dataset involved training and testing standard models like CNN-based models, but the results were not satisfactory according to industry standards. In this paper, a multi-level classification approach has been introduced to create a more robust model for engagement analysis using the DAiSEE dataset. This approach has recorded testing accuracies of 0.638, 0.7728, 0.8195, and 0.866 for predicting boredom level, engagement level, confusion level, and frustration level, respectively.

Keywords: computer vision, engagement prediction, deep learning, multi-level classification

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Authors: Manuela Nayantara Jeyaraj

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Information Technology (IT) is considered to be the prime contributor towards most of the energy releases and hence recursively impacting on the environmental Carbon Footprint on a major scale. The hostile effects brought about due to this massive carbon release such as global warming and ecosystem wipe-outs are currently being realized in Sri Lanka due to the rapid development and merging of computer based technologies. Sri Lanka, being a nature-rich island, has the undying need to preserve its natural environment hence resolving to better ‘Green IT’ practices in all possible spheres. Green IT implies the IT related practices for environmental sustainability. But the industrial divisions in Sri Lanka are still hesitant to fully realize the benefits of applying better “Green IT” principles due to considerations related to costs and other issues. In order to bring about a positive awareness of Green IT, the use of Smart Grids, which is yet a conceptualized principle within the Sri Lankan context, can be considered as a feasible proof in hand. This paper tends to analyze the feasibility of utilizing Smart Grids to ensure minimized cost and effects in preserving the environment hence ensuring Sustainable Green IT practices in an economically and technologically viable manner in Sri Lanka.

Keywords: green IT, industry, smart grid, Sri Lanka, sustainability

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Authors: Rodrigo Lentini, Beatrice Ionascu, Friederike A. Eyssel, Scandar Copti, Mohamad Eid

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The haptic modality has brought a new dimension to human computer interaction by engaging the human sense of touch. However, designing appropriate haptic stimuli, and in particular tactile stimuli, for various applications is still challenging. To tackle this issue, we present an intuitive system that facilitates the authoring of tactile gestures for various applications. The system transforms a hand gesture into a tactile gesture that can be rendering using a home-made haptic jacket. A case study is presented to demonstrate the ability of the system to develop tactile gestures that are recognizable by human subjects. Four tactile gestures are identified and tested to intensify the following four emotional responses: high valence – high arousal, high valence – low arousal, low valence – high arousal, and low valence – low arousal. A usability study with 20 participants demonstrated high correlation between the selected tactile gestures and the intended emotional reaction. Results from this study can be used in a wide spectrum of applications ranging from gaming to interpersonal communication and multimodal simulations.

Keywords: tactile stimulation, tactile gesture, emotion reactions, arousal, valence

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Authors: Sedat Cereci

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This study investigates character of communication, evaluates communication and information need of people, handles relation between communication and contemporary technology, and emphasizes technological lack on communication education in many societies. To get information and communication are of main needs of people and people developed different instruments and technics to learn and to communicate in the past. Because of social need, communication became social matter and governments contributed facilities of communication and set communication places for people to meet and to communicate. Industrial Revolution and technological developments also contributed communication technics and proved numerous technological facilities for communication. Education in the world also use developed technology in any department and communication education especially necessities high technological facilities in schools. Many high schools and universities have communication departments and most of them use contemporary technological facilities, but they are not sufficient. Communication departments in educational organizations in Turkey have computer classrooms, monitors, cameras, microphones, telephones, different softwares, and others. However, despite all this, technological facilities and teaching methods are not sufficient because of contemporary developments. Technology develops rapidly due to hopes of people and technological facilities in education cannot catch developments and people always hope more.

Keywords: information, communication education, technology, technological lack, contemporary conditions, technics

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Authors: O. Rahli, N. Mimouni, R. Bennacer, K. Bouhadef

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This numerical study investigates the travelling wave’s appearance and the behavior of Poiseuille-Rayleigh-Benard (PRB) flow induced in 3D thermosolutale mixed convection (TSMC) in horizontal rectangular channels. The governing equations are discretized by using a control volume method with third order Quick scheme in approximating the advection terms. Simpler algorithm is used to handle coupling between the momentum and continuity equations. To avoid the excessively high computer time, full approximation storage (FAS) with full multigrid (FMG) method is used to solve the problem. For a broad range of dimensionless controlling parameters, the contribution of this work is to analyzing the flow regimes of the steady longitudinal thermoconvective rolls (noted R//) for both thermal and mass transfer (TSMC). The transition from the opposed volume forces to cooperating ones, considerably affects the birth and the development of the longitudinal rolls. The heat and mass transfers distribution are also examined.

Keywords: heat and mass transfer, mixed convection, poiseuille-rayleigh-benard flow, rectangular duct

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Authors: Siyao Zhu, Yifang Xu

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After natural and man-made disasters, robots can bypass the danger, expedite the search, and acquire unprecedented situational awareness to design rescue plans. The hands-free requirement from the first responders excludes the use of tedious manual control and operation. In unknown, unstructured, and obstructed environments, natural-language-based supervision is not amenable for first responders to formulate, and is difficult for robots to understand. Brain-computer interface is a promising option to overcome the limitations. This study aims to test the feasibility of using electroencephalography (EEG) signals to decode human intentions and detect the level of consensus on robot-provided information. EEG signals were classified using machine-learning and deep-learning methods to discriminate search intentions and agreement perceptions. The results show that the average classification accuracy for intention recognition and consensus assessment is 67% and 72%, respectively, proving the potential of incorporating recognizable users’ bioelectrical responses into advanced robot-assisted systems for emergency response.

Keywords: consensus assessment, electroencephalogram, emergency response, human-robot collaboration, intention recognition, search and rescue

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Authors: Rahul Mohite, Lahcen Ouarbya

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This paper focuses on the interplay between humans and computer systems and the ability of these systems to understand and respond to human emotions, including non-verbal communication. Current emotion recognition systems are based solely on either facial or verbal expressions. The limitation of these systems is that it requires large training data sets. The paper proposes a system for recognizing human emotions that combines both speech and emotion recognition. The system utilizes advanced techniques such as deep learning and image recognition to identify facial expressions and comprehend emotions. The results show that the proposed system, based on the combination of facial expression and speech, outperforms existing ones, which are based solely either on facial or verbal expressions. The proposed system detects human emotion with an accuracy of 86%, whereas the existing systems have an accuracy of 70% using verbal expression only and 76% using facial expression only. In this paper, the increasing significance and demand for facial recognition technology in emotion recognition are also discussed.

Keywords: facial reputation, expression reputation, deep gaining knowledge of, photo reputation, facial technology, sign processing, photo type

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Authors: Ritesh Kumar, Gitanjali Chhetri, Mandira Bhatia, Mohit Mishra, Abhijith Bailur, Abhinav

Abstract:

The prevalence of the internet and technology in our day to day lives is creating more security issues than ever. The need for protecting and providing a secure access to private and business data has led to the development of many security systems. One of the potential solutions is to employ the bio-metric authentication technique. In this paper we present an innovative biometric authentication method that utilizes a person’s EEG signal, which is acquired in response to an auditory stimulus,and transferred wirelessly to a computer that has the necessary ANN algorithm-Multi layer perceptrol neural network because of is its ability to differentiate between information which is not linearly separable.In order to determine the weights of the hidden layer we use Gaussian random weight initialization. MLP utilizes a supervised learning technique called Back propagation for training the network. The complex algorithm used for EEG classification reduces the chances of intrusion into the protected public or private data.

Keywords: EEG signal, auditory evoked potential, biometrics, multilayer perceptron neural network, back propagation rule, Gaussian random weight initialization

Procedia PDF Downloads 409

Authors: Prashant Dhiman, Viranshu Kumar, Pradeep Joshi

Abstract:

Lot of research is going on to study the effect of cryogenic treatment on materials. Cryogenic treatment is a heat treatment process which is used widely to enhance the mechanical and metallurgical properties of various materials whether the material is ferrous or non ferrous. In almost all ferrous metals, it is found that retained austenite is converted into martensite. Generally deep cryogenic treatment is done using liquid nitrogen having temperature of -195 ℃. The austenite is unstable at this stage and converts into martensite. In non ferrous materials there presents a microcavity and under the action of stress it becomes crack. When this crack propagates, fracture takes place. As the metal contract under low temperature, by doing cryogenic treatment these microcavities will be filled hence increases the soundness of the material. Properties which are enhanced by cryogenic treatment of both ferrous and non ferrous materials are hardness, tensile strength, wear rate, electrical and thermal conductivity, and others. Also there is decrease in residual stress. A large number of manufacturing process (EDM, CNC etc.) are using cryogenic treatment on different tools or workpiece to reduce their wear. In this Review paper the use of cryogenic heat treatment in different manufacturing has been shown along with their advantages.

Keywords: cyrogenic treatment, EDM (Electrical Discharge Machining), CNC (Computer Numeric Control), Mechanical and Metallurgical Properties

Procedia PDF Downloads 436

Authors: Fawaz S. Al-Anzi, Dia AbuZeina

Abstract:

Speech recognition is of an important contribution in promoting new technologies in human computer interaction. Today, there is a growing need to employ speech technology in daily life and business activities. However, speech recognition is a challenging task that requires different stages before obtaining the desired output. Among automatic speech recognition (ASR) components is the feature extraction process, which parameterizes the speech signal to produce the corresponding feature vectors. Feature extraction process aims at approximating the linguistic content that is conveyed by the input speech signal. In speech processing field, there are several methods to extract speech features, however, Mel Frequency Cepstral Coefficients (MFCC) is the popular technique. It has been long observed that the MFCC is dominantly used in the well-known recognizers such as the Carnegie Mellon University (CMU) Sphinx and the Markov Model Toolkit (HTK). Hence, this paper focuses on the MFCC method as the standard choice to identify the different speech segments in order to obtain the language phonemes for further training and decoding steps. Due to MFCC good performance, the previous studies show that the MFCC dominates the Arabic ASR research. In this paper, we demonstrate MFCC as well as the intermediate steps that are performed to get these coefficients using the HTK toolkit.

Keywords: speech recognition, acoustic features, mel frequency, cepstral coefficients

Procedia PDF Downloads 259