Search results for: Human action recognition

Authors: Amit Gil, Helman Stern, Yael Edan

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A cognitive collaborative reinforcement learning algorithm (CCRL) that incorporates an advisor into the learning process is developed to improve supervised learning. An autonomous learner is enabled with a self awareness cognitive skill to decide when to solicit instructions from the advisor. The learner can also assess the value of advice, and accept or reject it. The method is evaluated for robotic motion planning using simulation. Tests are conducted for advisors with skill levels from expert to novice. The CCRL algorithm and a combined method integrating its logic with Clouse-s Introspection Approach, outperformed a base-line fully autonomous learner, and demonstrated robust performance when dealing with various advisor skill levels, learning to accept advice received from an expert, while rejecting that of less skilled collaborators. Although the CCRL algorithm is based on RL, it fits other machine learning methods, since advisor-s actions are only added to the outer layer.

Keywords: Robot learning, human-robot collaboration, motion planning, reinforcement learning.

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Authors: Shiuh-Jer Huang, Su-Shean Chen, Sheam-Chyun Lin

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Two-wheel inverted pendulum robot (TWIPR) is designed with two-hub DC motors for human riding and motion control evaluation. In order to measure the tilt angle and angular velocity of the inverted pendulum robot, accelerometer and gyroscope sensors are chosen. The mobile robot’s moving position and velocity were estimated based on DC motor built in hall sensors. The control kernel of this electric mobile robot is designed with embedded Arduino Nano microprocessor. A handle bar was designed to work as steering mechanism. The intelligent model-free fuzzy sliding mode control (FSMC) was employed as the main control algorithm for this mobile robot motion monitoring with different control purpose adjustment. The intelligent controllers were designed for balance control, and moving speed control purposes of this robot under different operation conditions and the control performance were evaluated based on experimental results.

Keywords: Balance control, speed control, intelligent controller and two wheel inverted pendulum.

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Authors: Kitty Kioskli, Nineta Polemi

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Evaluating the levels of cyber-security risks within an enterprise is most important in protecting its information system, services and all its digital assets against security incidents (e.g. accidents, malicious acts, massive cyber-attacks). The existing risk assessment methodologies (e.g. eBIOS, OCTAVE, CRAMM, NIST-800) adopt a technical approach considering as attack factors only the capability, intention and target of the attacker, and not paying attention to the attacker’s psychological profile and personality traits. In this paper, a socio-technical approach is proposed in cyber risk assessment, in order to achieve more realistic risk estimates by considering the personality traits of the attackers. In particular, based upon principles from investigative psychology and behavioural science, a multi-dimensional, extended, quantifiable model for an attacker’s profile is developed, which becomes an additional factor in the cyber risk level calculation.

Keywords: Attacker, behavioural models, cyber risk assessment, cyber-security, human factors, investigative psychology, ISO27001, ISO27005.

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Authors: T. Santiboon

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This research were investigated, determined, and analyzed of the climate characteristically change in the provincial Udon Thani in the period of 60 surrounding years from 1951 to 2010 A.D. that it-s transferred to effects of climatologically data for determining global warming. Statistically significant were not found for the 60 years- data (R2<0.81). Statistically significant were found after adapted data followed as the Sun Spot cycle in 11 year periods, at the level 0.001 (R2= 1.00). These results indicate the Udon Thani-s weather are affected change; temperatures and evaporation were increased, but rainfall and number days of rainfall, cyclone storm, wind speed, and humidity, forest assessment were decreased. The effects of thermal energy from the sun radiation energy and human activities that they-re followed as the sunspot cycle are able to be predicted from the last to the future of the uniformitarian-s the climate change and global warming effect of the world.

Keywords: Climate Change, Global Warming, Udon Thani Province Weather

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Authors: Jamalizadeh, M.R., Moghaddamnia, A., Piri, J., Arbabi, V., Homayounifar, M., Shahryari, A.

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Dust storms are one of the most costly and destructive events in many desert regions. They can cause massive damages both in natural environments and human lives. This paper is aimed at presenting a preliminary study on dust storms, as a major natural hazard in arid and semi-arid regions. As a case study, dust storm events occurred in Zabol city located in Sistan Region of Iran was analyzed to diagnose and predict dust storms. The identification and prediction of dust storm events could have significant impacts on damages reduction. Present models for this purpose are complicated and not appropriate for many areas with poor-data environments. The present study explores Gamma test for identifying inputs of ANNs model, for dust storm prediction. Results indicate that more attempts must be carried out concerning dust storms identification and segregate between various dust storm types.

Keywords: Dust Storm, Gamma Test, Prediction, ANNs, Zabol.

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Authors: Faten. A. Khorshid, Gehan. A. Raouf, Salem. M. El-Hamidy, Gehan. S. Al-amri, Nourah. A. Alotaibi, Taha A. Kumosani

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Cancer becomes one of the leading cause of death in many countries over the world. Fourier-transform infrared (FTIR) spectra of human lung cancer cells (A549) treated with PMF (natural product extracted from PM 701) for different time intervals were examined. Second derivative and difference method were taken in comparison studies. Cesium (Cs) and Rubidium (Rb) nanoparticles in PMF were detected by Energy Dispersive X-ray attached to Scanning Electron Microscope SEM-EDX. Characteristic changes in protein secondary structure, lipid profile and changes in the intensities of DNA bands were identified in treated A549 cells spectra. A characteristic internucleosomal ladder of DNA fragmentation was also observed after 30 min of treatment. Moreover, the pH values were significantly increases upon treatment due to the presence of Cs and Rb nanoparticles in the PMF fraction. These results support the previous findings that PMF is selective anticancer agent and can produce apoptosis to A549 cells.

Keywords: Apoptosis, FTIR spectroscopy, pH therapy, Scanning Electron Microscope- Energy Dispersive X-ray (SEMEDX).

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Authors: M. Sokhanvar, S. M. Shahidipour

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One of the essential requirements for the human beings is the house for living. This is necessary to make the place of satisfaction for contemporary houses residents by attention to their culture. In this article represented the relevant theoretical literature on cultural symbols by use the architecture semiotic to construct the houses as a better place for living. In fact, make a place for everyday life with changing the house to the home is one of the most challengeable subject for architects all around the world. The target of this article is to find Cypriot houses cultural symbols that assist architect to design and build contemporary houses, to make more satisfaction for its residents according to Cypriot life style and their culture. This paper is based on researching the effect of cultural symbols on housing, would require various types of methods. However, this study focuses on two methods, which are quantitative and qualitative. The purpose of the case-specific study is to finding the symbols that used in contemporary houses by attention to the Cypriot cultural symbols in Famagusta houses.

Keywords: Houses, home, architectural symbols, cultural symbols.

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Authors: Afzel Noore

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A new digital watermarking technique for images that are sensitive to blocking artifacts is presented. Experimental results show that the proposed MDCT based approach produces highly imperceptible watermarked images and is robust to attacks such as compression, noise, filtering and geometric transformations. The proposed MDCT watermarking technique is applied to fingerprints for ensuring security. The face image and demographic text data of an individual are used as multiple watermarks. An AFIS system was used to quantitatively evaluate the matching performance of the MDCT-based watermarked fingerprint. The high fingerprint matching scores show that the MDCT approach is resilient to blocking artifacts. The quality of the extracted face and extracted text images was computed using two human visual system metrics and the results show that the image quality was high.

Keywords: Digital watermarking, data hiding, modified discretecosine transformation (MDCT).

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Authors: P. Visutsak

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The study of the interaction between humans and computers has been emerging during the last few years. This interaction will be more powerful if computers are able to perceive and respond to human nonverbal communication such as emotions. In this study, we present the image-based approach to emotion classification through lower facial expression. We employ a set of feature points in the lower face image according to the particular face model used and consider their motion across each emotive expression of images. The vector of displacements of all feature points input to the Adaptive Support Vector Machines (A-SVMs) classifier that classify it into seven basic emotions scheme, namely neutral, angry, disgust, fear, happy, sad and surprise. The system was tested on the Japanese Female Facial Expression (JAFFE) dataset of frontal view facial expressions [7]. Our experiments on emotion classification through lower facial expressions demonstrate the robustness of Adaptive SVM classifier and verify the high efficiency of our approach.

Keywords: emotion classification, facial expression, adaptive support vector machines, facial expression classifier.

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Authors: C. De Lazzari, E. Del Prete, I. Genuini, F. Fedele

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Cardiovascular human simulator can be a useful tool in understanding complex physiopathological process in cardiocirculatory system. It can also be a useful tool in order to investigate the effects of different drugs on hemodynamic parameters. The aim of this work is to test the potentiality of our cardiovascular numerical simulator CARDIOSIM© in reproducing flow/pressure coronary waveforms in presence of two different drugs: Amlodipine (AMLO) and Adenosine (ADO). In particular a time-varying intramyocardial compression, assumed to be proportional to the left ventricular pressure, was related to the venous coronary compliances in order to study its effects on the coronary blood flow and the flow/pressure loop. Considering that coronary circulation dynamics is strongly interrelated with the mechanics of the left ventricular contraction, relaxation, and filling, the numerical model allowed to analyze the effects induced by the left ventricular pressure on the coronary flow.

Keywords: Cardiovascular system, Coronary blood flow, Hemodynamic, Numerical simulation.

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Authors: Sagir M. Yusuf, Chris Baber

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We describe issues bedeviling the coordination of heterogeneous (different sensors carrying agents) multi-agent missions such as belief conflict, situation reasoning, etc. We applied Bayesian and agents' presumptions inferential reasoning to solve the outlined issues with the heterogeneous multi-agent belief variation and situational-base reasoning. Bayesian Belief Network (BBN) was used in modeling the agents' belief conflict due to sensor variations. Simulation experiments were designed, and cases from agents’ missions were used in training the BBN using gradient descent and expectation-maximization algorithms. The output network is a well-trained BBN for making inferences for both agents and human experts. We claim that the Bayesian learning algorithm prediction capacity improves by the number of training data and argue that it enhances multi-agents robustness and solve agents’ sensor conflicts.

Keywords: Distributed constraint optimization problem, multi-agent system, multi-robot coordination, autonomous system, swarm intelligence.

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Authors: Mohammad S. Laghari, Qurban A. Memon, Gulzar A. Khuwaja

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The paper describes a knowledge based system for analysis of microscopic wear particles. Wear particles contained in lubricating oil carry important information concerning machine condition, in particular the state of wear. Experts (Tribologists) in the field extract this information to monitor the operation of the machine and ensure safety, efficiency, quality, productivity, and economy of operation. This procedure is not always objective and it can also be expensive. The aim is to classify these particles according to their morphological attributes of size, shape, edge detail, thickness ratio, color, and texture, and by using this classification thereby predict wear failure modes in engines and other machinery. The attribute knowledge links human expertise to the devised Knowledge Based Wear Particle Analysis System (KBWPAS). The system provides an automated and systematic approach to wear particle identification which is linked directly to wear processes and modes that occur in machinery. This brings consistency in wear judgment prediction which leads to standardization and also less dependence on Tribologists.

Keywords: Computer vision, knowledge based systems, morphology, wear particles.

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Authors: Ping Du, Masaki Sagehashi, Akihiko Terada, Masaaki Hosomi

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Prediction of benzene transport in soil and volatilization from soil to the atmosphere is important for the preservation of human health and management of contaminated soils. The adequacy of a simple numerical model, assuming two-phase diffusion and equilibrium of liquid/solid adsorption, was investigated by experimental data of benzene concentration in a flux chamber (with headspace) where Andosol and sand were filled. Adsorption experiment for liquid phase was performed to determine an adsorption coefficient. Furthermore, adequacy of vapor phase adsorption was also studied through two runs of experiment using sand with different water content. The results show that the model adequately predicted benzene transport and volatilization from Andosol and sand with water content of 14.0%. In addition, the experiment additionally revealed that vapor phase adsorption should be considered in diffusion model for sand with very low water content.

Keywords: Benzene; Transport Model, Adsorption, Soil Contaminant.

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Authors: Amirhossein Safi

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Internet of things (IOT) is a kind of advanced information technology which has drawn societies’ attention. Sensors and stimulators are usually recognized as smart devices of our environment. Simultaneously, IOT security brings up new issues. Internet connection and possibility of interaction with smart devices cause those devices to involve more in human life. Therefore, safety is a fundamental requirement in designing IOT. IOT has three remarkable features: overall perception, reliable transmission, and intelligent processing. Because of IOT span, security of conveying data is an essential factor for system security. Hybrid encryption technique is a new model that can be used in IOT. This type of encryption generates strong security and low computation. In this paper, we have proposed a hybrid encryption algorithm which has been conducted in order to reduce safety risks and enhancing encryption's speed and less computational complexity. The purpose of this hybrid algorithm is information integrity, confidentiality, non-repudiation in data exchange for IOT. Eventually, the suggested encryption algorithm has been simulated by MATLAB software, and its speed and safety efficiency were evaluated in comparison with conventional encryption algorithm.

Keywords: Internet of things, security, hybrid algorithm, privacy.

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Authors: Lenka Ocenasova, Bartosz Gapinski, Robert Cep, Linda Gregova, Branimir Barisic, Jana Novakova, Lenka Petrkovska

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Today technological process makes possible surface control of producing parts which is needful for product quality guarantee. Geometrical structure of part surface includes form, proportion, accuracy to shape, accuracy to size, alignment and surface topography (roughness, waviness, etc.). All these parameters are dependence at technology, production machine parameters, material properties, but also at human, etc. Every parameters approves at total part accuracy, it is means at accuracy to shape. One of the most important accuracy to shape element is roundness. This paper will be deals by comparison of roughness deviations at coordination measuring machines and at special single purpose machines. Will describing measuring by discreet method (discontinuous) and scanning method (continuous) at coordination measuring machines and confrontation with reference method using at single purpose machines.

Keywords: Coordinating Measuring Machines (CMM), Measuring Strategy, Roughness Deviation, Accuracy.

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: Positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means.

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Authors: F. Allag, S. Bouharati, M. Belmahdi, R. Zegadi

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The rapid expansion of deserts in recent decades as a result of human actions combined with climatic changes has highlighted the necessity to understand biological processes in arid environments. Whereas physical processes and the biology of flora and fauna have been relatively well studied in marginally used arid areas, knowledge of desert soil micro-organisms remains fragmentary. The objective of this study is to conduct a diversity analysis of bacterial communities in unvegetated arid soils. Several biological phenomena in hot deserts related to microbial populations and the potential use of micro-organisms for restoring hot desert environments. Dry land ecosystems have a highly heterogeneous distribution of resources, with greater nutrient concentrations and microbial densities occurring in vegetated than in bare soils. In this work, we found it useful to use techniques of artificial intelligence in their treatment especially artificial neural networks (ANN). The use of the ANN model, demonstrate his capability for addressing the complex problems of uncertainty data.

Keywords: Desert soil, Climatic changes, Bacteria, Vegetation, Artificial neural networks.

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Authors: Pil Woo Heo, In Sub Park

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A polypropylene hollow fiber membrane module is used for separating dissolved gases which contain dissolved oxygen from water. These dissolved gases can be used for underwater breathing. To be used for a human, the minimum amount of oxygen is essential. To increase separation of dissolved gases, much water and high surface area of hollow fibers are requested. For efficient separation system, performance of single membrane module with high surface area needs to be investigated.

In this study, we set up experimental devices for analyzing separation characteristics of dissolved gases including oxygen from water using a polypropylene hollow fiber membrane module. Separation of dissolved gases from water is investigated with variations of water flow rates. Composition of dissolved gases is also measured using GC. These results expect to be used in developing the portable separation system.

Keywords: High surface area, breathing, vacuum, composition.

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Authors: Aryana Collins Jackson, Elisabetta Bevacqua, Pierre De Loor, Ronan Querrec

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This paper presents a taxonomy of non-technical skills, communicative intentions, and behavior for an individual acting as a medical coordinator. In medical emergency situations, a leader among the group is imperative to both patient health and team emotional and mental health. Situational Leadership is used to make clear and easy-to-follow guidelines for behavior depending on circumstantial factors. Low-level leadership behaviors belonging to two different styles, directive and supporting, are identified from literature and are included in the proposed taxonomy. The high-level information in the taxonomy consists of the necessary non-technical skills belonging to a medical coordinator: situation awareness, decision making, task management, and teamwork. Finally, communicative intentions, dimensions, and functions are included. Thus this work brings high-level and low-level information - medical non-technical skills, communication capabilities, and leadership behavior - into a single versatile taxonomy of behavior.

Keywords: Medical, leadership styles, taxonomy, human behavior.

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Authors: Mamta Juneja, Parvinder S. Sandhu, Ekta Walia

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Steganography is the process of hiding one file inside another such that others can neither identify the meaning of the embedded object, nor even recognize its existence. Current trends favor using digital image files as the cover file to hide another digital file that contains the secret message or information. One of the most common methods of implementation is Least Significant Bit Insertion, in which the least significant bit of every byte is altered to form the bit-string representing the embedded file. Altering the LSB will only cause minor changes in color, and thus is usually not noticeable to the human eye. While this technique works well for 24-bit color image files, steganography has not been as successful when using an 8-bit color image file, due to limitations in color variations and the use of a colormap. This paper presents the results of research investigating the combination of image compression and steganography. The technique developed starts with a 24-bit color bitmap file, then compresses the file by organizing and optimizing an 8-bit colormap. After the process of compression, a text message is hidden in the final, compressed image. Results indicate that the final technique has potential of being useful in the steganographic world.

Keywords: Compression, Colormap, Encryption, Steganographyand LSB Insertion.

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Authors: Fereidoun Nowshiravan Rahatabad, Mohammad Ali Nekoui, Mohammad Reza Hashemi Golpaygani, AliFallah, Mehdi Kazemzadeh Narbat

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The people are differed by their capabilities, skills and mental agilities. The evolution of human from childhood when they are completely dependent up to adultness the time they gradually set the dependency free is too complicated, by considering they have all started from almost one point but some become cleverer and some less. The main control command of a cybernetic hand should be posted by remaining healthy organs of disabled Person. These commands can be from several channels, which their recording and detecting are different and need complicated study. In this research, we suppose that, this stage has been done or in the other words, the command has been already sent and detected. So the main goal is to control a long hand, upper elbow hand missing, by an interest angle define by disabled. It means that, the system input is the position desired by disables and the output is the elbow-joint angle variation. Therefore the goal is a suitable control design based on neural network theory in order to meet the given mapping.

Keywords: Control - system design, Upper limb prosthesis, neuralnetwork.

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Authors: Orestis Κ. Efthymiou, Stavros T. Ponis

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In the last decade, a new industrial revolution seems to be emerging, supported -once again- by the rapid advancements of Information Technology in the areas of Machine-to-Machine (M2M) communication permitting large numbers of intelligent devices, e.g. sensors to communicate with each other and take decisions without any or minimum indirect human intervention. The advent of these technologies have triggered the emergence of a new category of hybrid (cyber-physical) manufacturing systems, combining advanced manufacturing techniques with innovative M2M applications based on the Internet of Things (IoT), under the umbrella term Industry 4.0. Even though the topic of Industry 4.0 has attracted much attention during the last few years, the attempts of providing a systematic literature review of the subject are scarce. In this paper, we present the authors’ initial study of the field with a special focus on the use and applications of Industry 4.0 principles in material handling automations and in-house logistics. Research shows that despite the vivid discussion and attractiveness of the subject, there are still many challenges and issues that have to be addressed before Industry 4.0 becomes standardized and widely applicable.

Keywords: Industry 4.0, internet of things, manufacturing systems, material handling, logistics.

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Authors: A. Maria G. Melero, A. M. Senna, J. A. Domingues, M. A. Hausen, E. Aparecida R. Duek, V. R. Botaro

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A hydrogel from cellulose acetate cross linked with ethylenediaminetetraacetic dianhydride (HAC-EDTA) was synthesized by our research group, and submitted to characterization and biological tests. Cytocompatibility analysis was performed by confocal microscopy using human adipocyte derived stem cells (ASCs). The FTIR analysis showed characteristic bands of cellulose acetate and hydroxyl groups and the tensile tests evidence that HAC-EDTA present a Young’s modulus of 643.7 MPa. The confocal analysis revealed that there was cell growth at the surface of HAC-EDTA. After one day of culture the cells presented spherical morphology, which may be caused by stress of the sequestration of Ca²⁺ and Mg²⁺ ions at the cell medium by HAC-EDTA, as demonstrated by ICP-MS. However, after seven days and 14 days of culture, the cells present fibroblastoid morphology, phenotype expected by this cellular type. The results give efforts to indicate this new material as a potential biomaterial for tissue engineering, in the future in vivo approach.

Keywords: Cellulose acetate, hydrogel, biomaterial, cellular growth.

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Authors: Sivapalan, S., Subramaniam, G., Clifford, M.J., Balbir Singh, M.S., Abdullah, A

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Higher education has an important role to play in advocating environmentalism. Given this responsibility, the goal of higher education should therefore be to develop graduates with the knowledge, skills and values related to environmentalism. However, research indicates that there is a lack of consciousness amongst graduates on the need to be more environmentally aware, especially when it comes to applying the appropriate knowledge and skills related to environmentalism. Although institutions of higher learning do include environmental parameters within their undergraduate and postgraduate academic programme structures, the environmental boundaries are usually confined to specific engineering majors within an engineering programme. This makes environmental knowledge, skills and values exclusive to certain quarters of the higher education system. The incorporation of environmental literacy within higher education institutions as a whole is of utmost pertinence if a nation-s human capital is to be nurtured to become change agents for the preservation of environment. This paper discusses approaches that can be adapted by institutions of higher learning to include environmental literacy within the graduate-s higher learning experience.

Keywords: Higher education, engineering education, environmental literacy, Malaysia.

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Authors: Salman Iqbal

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Knowledge management (KM) literature has mainly focused on the antecedents of KM. The purpose of this study is to investigate the effect of specific human resource management (HRM) practices on employee knowledge sharing and its outcome as individual knowledge capability. Based on previous literature, a model is proposed for the study and hypotheses are formulated. The cross-sectional dataset comes from a sample of 19 knowledge intensive firms (KIFs). This study has run an item parceling technique followed by Confirmatory Factor Analysis (CFA) on the latent constructs of the research model. Employees’ collaboration and their interpersonal trust can help to improve their knowledge sharing behaviour and knowledge capability within organisations. This study suggests that in future, by using a larger sample, better statistical insight is possible. The findings of this study are beneficial for scholars, policy makers and practitioners. The empirical results of this study are entirely based on employees’ perceptions and make a significant research contribution, given there is a dearth of empirical research focusing on the subcontinent.

Keywords: Employees’ collaboration, individual knowledge capability, knowledge sharing, monetary rewards, structural equation modelling.

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Authors: M. Baryshev, D.Vainauska, S. Kozireva, A.Karpovs

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Liposomal magnetofection is the most powerful nonviral method for the nucleic acid delivery into the cultured cancer cells and widely used for in vitro applications. Use of the static magnetic field condition may result in non-uniform distribution of aggregate complexes on the surface of cultured cells. To prevent this, we developed the new device which allows to concentrate aggregate complexes under dynamic magnetic field, assisting more contact of these complexes with cellular membrane and, possibly, stimulating endocytosis. Newly developed device for magnetofection under dynamic gradient magnetic field, “DynaFECTOR", was used to compare transfection efficiency of human liver hepatocellular carcinoma cell line HepG2 with that obtained by lipofection and magnetofection. The effect of two parameters on transfection efficiency, incubation time under dynamic magnetic field and rotation frequency of magnet, was estimated. Liposomal magnetofection under dynamic gradient magnetic field showed the highest transfection efficiency for HepG2 cells.

Keywords: Dynamic magnetic field, Lipofection, Magnetofection

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Authors: R. Altamimi, G. Skinner, K. Nesbitt

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Encouraging physical activity amongst children and adolescents is becoming an increasingly relevant issue in modern society. Studies have shown that involving children and adolescents in physical activity is essential for their physical, mental and social development. However, with technology playing an increasingly important role in reducing physical work it is becoming more critical to incorporate adequate physical activities into our lives. One way to overcome this problem is to harness technology so that it promotes physical activities, for example, by motivating children and adolescents to exercise more. This paper describes a promising solution to the question of how to increase levels of physical activity in children and adolescents by combining gaming technologies with exercise tracking goals. This research describes a framework called FITTER (Framework for Integrating activity Tracking Technologies for Electronic Recreation) that combines video game play with more traditional, non-computer physical activities.

Keywords: Exergames, Home-based eHealth, Human-computer Interaction, Natural User Interfaces, Wearable Health Informatics.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

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The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: Prasan Pitiranggon, Nunthika Benjathepanun, Somsri Banditvilai, Veera Boonjing

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Our study proposes an alternative method in building Fuzzy Rule-Based System (FRB) from Support Vector Machine (SVM). The first set of fuzzy IF-THEN rules is obtained through an equivalence of the SVM decision network and the zero-ordered Sugeno FRB type of the Adaptive Network Fuzzy Inference System (ANFIS). The second set of rules is generated by combining the first set based on strength of firing signals of support vectors using Gaussian kernel. The final set of rules is then obtained from the second set through input scatter partitioning. A distinctive advantage of our method is the guarantee that the number of final fuzzy IFTHEN rules is not more than the number of support vectors in the trained SVM. The final FRB system obtained is capable of performing classification with results comparable to its SVM counterpart, but it has an advantage over the black-boxed SVM in that it may reveal human comprehensible patterns.

Keywords: Fuzzy Rule Base, Rule Extraction, Rule Generation, Support Vector Machine.

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Authors: Suraiya Jabin, Kamal K. Bharadwaj

Abstract:

In the recent past Learning Classifier Systems have been successfully used for data mining. Learning Classifier System (LCS) is basically a machine learning technique which combines evolutionary computing, reinforcement learning, supervised or unsupervised learning and heuristics to produce adaptive systems. A LCS learns by interacting with an environment from which it receives feedback in the form of numerical reward. Learning is achieved by trying to maximize the amount of reward received. All LCSs models more or less, comprise four main components; a finite population of condition–action rules, called classifiers; the performance component, which governs the interaction with the environment; the credit assignment component, which distributes the reward received from the environment to the classifiers accountable for the rewards obtained; the discovery component, which is responsible for discovering better rules and improving existing ones through a genetic algorithm. The concatenate of the production rules in the LCS form the genotype, and therefore the GA should operate on a population of classifier systems. This approach is known as the 'Pittsburgh' Classifier Systems. Other LCS that perform their GA at the rule level within a population are known as 'Mitchigan' Classifier Systems. The most predominant representation of the discovered knowledge is the standard production rules (PRs) in the form of IF P THEN D. The PRs, however, are unable to handle exceptions and do not exhibit variable precision. The Censored Production Rules (CPRs), an extension of PRs, were proposed by Michalski and Winston that exhibit variable precision and supports an efficient mechanism for handling exceptions. A CPR is an augmented production rule of the form: IF P THEN D UNLESS C, where Censor C is an exception to the rule. Such rules are employed in situations, in which conditional statement IF P THEN D holds frequently and the assertion C holds rarely. By using a rule of this type we are free to ignore the exception conditions, when the resources needed to establish its presence are tight or there is simply no information available as to whether it holds or not. Thus, the IF P THEN D part of CPR expresses important information, while the UNLESS C part acts only as a switch and changes the polarity of D to ~D. In this paper Pittsburgh style LCSs approach is used for automated discovery of CPRs. An appropriate encoding scheme is suggested to represent a chromosome consisting of fixed size set of CPRs. Suitable genetic operators are designed for the set of CPRs and individual CPRs and also appropriate fitness function is proposed that incorporates basic constraints on CPR. Experimental results are presented to demonstrate the performance of the proposed learning classifier system.

Keywords: Censored Production Rule, Data Mining, GeneticAlgorithm, Learning Classifier System, Machine Learning, PittsburgApproach, , Reinforcement learning.

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