Search results for: content independent features

Authors: Sara Khamseh, Kambiz Javanruee, Hamid Khorsand

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Plenty of metallic materials are used for biomedical applications like hip joints and screws. Besides, it is reported that metal platforms such as stainless steel show significant deterioration because of wear and friction. The surface of metal substrates has been coated with a variety of multicomponent coatings to prevail these problems. The carbon-based multicomponent coatings such as metal-added amorphous carbon and diamond coatings are crucially important because of their remarkable tribological performance and chemical stability. In the current study, H-D contained Nb: (a-C) multicomponent coatings (H-D: hexagonal diamond, a-C: amorphous carbon) coated on A 304 steel substrates using an unbalanced magnetron (UBM) sputtering system. The effects of Nb and H-D content and ID/IG ratio on microstructure, mechanical and tribological characteristics of (Nb: H-D: a-C) composite coatings were investigated. The results of Raman spectroscopy represented that a-C phase with a Graphite-like structure (GLC with high value of sp2 carbon bonding) is formed, and its domain size increased with increasing Nb content of the coatings. Moreover, the Nb played a catalyst for the formation of the H-D phase. The nanoindentation hardness value of the coatings ranged between ~17 to ~35 GPa and (Nb: H-D: a-C) composite coatings with more H-D content represented higher hardness and plasticity index. It seems that the existence of extra-hard H-D particles straightly increased hardness. The tribological performance of the coatings was evaluated using the pin-on-disc method under the wet environment of SBF (Simulated Body Fluid). The COF value of the (Nb: H-D: a-C) coatings decreased with an increasing ID/IG ratio. The lower coefficient of friction is a result of the lamelliform array of graphitic domains. Also, the wear rate of the coatings decreased with increasing H-D content of the coatings. Based on the literature, a-C coatings with high hardness and H3/E2 ratio represent lower wear rates and better tribological performance. According to the nanoindentation analysis, hardness and H3/E2 ratio of (Nb: H-D: a-C) multicomponent coatings increased with increasing H-D content, which in turn decreased the wear rate of the coatings. The mechanical and tribological potency of (Nb: H-D: a-C) composite coatings on A 304 steel substrates paved the way for the development of innovative advanced coatings to ameliorate the performance of A 304 steel for biomedical applications.

Keywords: COF, mechanical properties, (Nb: H-D: a-C) coatings, wear rate

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Authors: Davide Fuscà, Kanan Rahimli, Roberto Leuzzi

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Preventing abuse and illegal activities in a given area of the sea is a very difficult and expensive task. Artificial intelligence offers the possibility to implement new methods to identify the vessel class type from the kinematic features of the vessel itself. The task strictly depends on the quality of the data. This paper explores the application of a deep, long short-term memory model by using AIS flow only with a relatively low quality. The proposed model reaches high accuracy on detecting nine vessel classes representing the most common vessel types in the Ionian-Adriatic Sea. The model has been applied during the Adriatic-Ionian trial period of the international EU ANDROMEDA H2020 project to identify vessels performing behaviors far from the expected one depending on the declared type.

Keywords: maritime surveillance, artificial intelligence, behavior analysis, LSTM

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Authors: Kamal, J. P. Narayan

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In the present wok the effects of basin-shape-ratio on the frequency content and spectral amplitudes of the basin-generated surface waves and the associated spatial variation of ground motion amplification and differential ground motion in a 3D semi-spherical basin has been studied. A recently developed 3D fourth-order spatial accurate time-domain finite-difference (FD) algorithm based on the parsimonious staggered-grid approximation of the 3D viscoelastic wave equations was used to estimate seismic responses. The simulated results demonstrated the increase of both the frequency content and the spectral amplitudes of the basin-generated surface waves and the duration of ground motion in the basin with the increase of shape-ratio of semi-spherical basin. An increase of the average spectral amplification (ASA), differential ground motion (DGM) and the average aggravation factor (AAF) towards the centre of the semi-spherical basin was obtained.

Keywords: 3D viscoelastic simulation, basin-generated surface waves, basin-shape-ratio effects, average spectral amplification, aggravation factors and differential ground motion

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Authors: Sagarjyoti Roy

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Dengue is an arboviral infection, belonging to family flaviviridae, comprising of four serotypes; DENV1, DENV2, DENV3 and DENV4. All four serotypes are capable of causing full-spectrum of clinical features, ranging from self-limiting fever to severe dengue hemorrhagic fever (DHF) and dengue shock syndrome (DSS). Complications may affect any organ system, including those involving gastrointestinal system and serositis. We report a case, of a 28 years, non-alcoholic male, presenting with a 7 day history of fever and malaise followed by abdominal pain and distension, from 4th day of fever. He was admitted in medicine department of RG KAR medical college hospital. Dengue fever was confirmed by NS1 and dengue IgM positivity. Platelet count was 30,000/cc (1.5- 4 lac/cc) and haematocrit was 52% (38- 50% for men). Clinicoradiological findings revealed bilateral pleural effusion, ascites and splenomegaly. Ascitic fluid was hemorrhagic in nature, with a high protein and RBC content. Liver function tests revealed mild transaminitis with normal coagulation profile. Patient was managed conservatively. A diagnosis of dengue fever complicated by serositis and spontaneous haemoperitoneum was made. The symptoms subsided after a hospital stay of 10 days. The case highlights haemorrhage into peritoneal cavity as a possible complication of dengue fever. Although a definite explanation requires more detailed studies, platelet or endothelial cell dysfunction might be contributory.

Keywords: ascites, dengue, haemoperitoneum, serositis

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Authors: Laicheng Cao, Xiangqian Su, Youxiao Wu

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Feature selection is one of the important problems in network security, pattern recognition, data mining and other fields. In order to remove redundant features, effectively improve the detection speed of intrusion detection system, proposes a new feature selection method, which is based on the invasive weed optimization (IWO) algorithm and tabu search algorithm(TS). Use IWO as a global search, tabu search algorithm for local search, to improve the results of IWO algorithm. The experimental results show that the feature selection method can effectively remove the redundant features of network data information in feature selection, reduction time, and to guarantee accurate detection rate, effectively improve the speed of detection system.

Keywords: intrusion detection, feature selection, iwo, tabu search

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Authors: Doaa H. Elgohary, Dina M. Hamoda, S. Yahia

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Technical textiles refer to textile materials that are engineered and designed to have specific functionalities and performance characteristics beyond their traditional use as apparel or upholstery fabrics. These textiles are usually developed for their unique properties such as strength, durability, flame retardancy, chemical resistance, waterproofing, insulation and other special properties. The development and use of technical textiles are constantly evolving, driven by advances in materials science, manufacturing technologies and the demand for innovative solutions in various industries. Kevlar 29 is a type of aramid fiber developed by DuPont. It is a high-performance material known for its exceptional strength and resistance to impact, abrasion, and heat. Kevlar 29 belongs to the Kevlar family, which includes different types of aramid fibers. Kevlar 29 is primarily used in applications that require strength and durability, such as ballistic protection, body armor, and body armor for military and law enforcement personnel. It is also used in the aerospace and automotive industries to reinforce composite materials, as well as in various industrial applications. Two different Kevlar samples were used coated with cooper lithium silicate (CLS); ten different mechanical and physical properties (weight, thickness, tensile strength, elongation, stiffness, air permeability, puncture resistance, thermal conductivity, stiffness, and spray test) were conducted to approve its functional performance efficiency. The influence of different mechanical properties was statistically analyzed using an independent t-test with a significant difference at P-value = 0.05. The radar plot was calculated and evaluated to determine the best-performing samples. The results of the independent t-test observed that all variables were significantly affected by yarn counts except water permeability, which has no significant effect. All properties were evaluated for samples 1 and 2, a radar chart was used to determine the best attitude for samples. The radar chart area was calculated, which shows that sample 1 recorded the best performance, followed by sample 2. The surface morphology of all samples and the coating materials was determined using a scanning electron microscope (SEM), also Fourier Transform Infrared Spectroscopy Measurement for the two samples.

Keywords: cooper lithium silicate, independent t-test, kevlar, technical textiles.

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Authors: Marwa Abida, Florian Gehring, Jamel Mars, Alexandre Vivet, Fakhreddine Dammak, Mohamed Haddar

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The demand for bio-based materials in semi-structural and structural applications is constantly growing to conform to new environmental policies. Among them, Plant Fiber Reinforced Composites (PFRC) are attractive for the scientific community as well as the industrial world. Due to their relatively low densities and low environmental impact, vegetal fibers appear to be suitable as reinforcing materials for polymers. However, the major issue of plant fibers and PFRC in general is their hydrophilic behavior (high affinity to water molecules). Indeed, when absorbed, water causes fiber swelling and a loss of mechanical properties. Thus, the environmental loadings (moisture, temperature, UV) can strongly affect their mechanical properties and therefore play a critical role in the service life of PFRC. In order to analyze the influence of conditioning at relative humidity on the behavior of flax fiber reinforced composites, a preliminary study on flax fabrics has been conducted. The conditioning of the fabrics in different humid atmospheres made it possible to study the influence of the water content on the hygro-mechanical behavior of flax reinforcement through mechanical tensile tests. This work shows that increasing the relative humidity of the atmosphere induces an increase of the water content in the samples. It also brings up the significant influence of water content on the stiffness and elongation at break of the fabric, while no significant change of the breaking load is detected. Non-linear decrease of flax fabric rigidity and increase of its elongation at maximal force with the increase of water content are observed. It is concluded that water molecules act as a softening agent on flax fabrics. Two kinds of typical tensile curves are identified. Most of the tensile curves of samples show one unique linear region where the behavior appears to be linear prior to the first yarn failure. For some samples in which water content is between 2.7 % and 3.7 % (regardless the conditioning atmosphere), the emergence of a two-linear region behavior is pointed out. This phenomenon could be explained by local heterogeneities of water content which could induce premature local plasticity in some regions of the flax fabric sample behavior.

Keywords: hygro-mechanical behavior, hygroscopy, flax fabric, relative humidity, mechanical properties

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Authors: Morteza Elsa, Amirhossein Moghanian

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The major aim of this study was to evaluate the effect of CaO content on in vitro hydroxyapatite formation, MC3T3 cells cytotoxicity and proliferation as well as antibacterial efficiency of sol-gel derived SiO₂–CaO–P₂O₅ ternary system. For this purpose, first two grades of bioactive glass (BG); BG-58s (mol%: 60%SiO₂–36%CaO–4%P₂O₅) and BG-68s (mol%: 70%SiO₂–26%CaO–4%P₂O₅)) were synthesized by sol-gel method. Second, the effect of CaO content in their composition on in vitro bioactivity was investigated by soaking the BG-58s and BG-68s powders in simulated body fluid (SBF) for time periods up to 14 days and followed by characterization inductively coupled plasma atomic emission spectrometry (ICP-AES), Fourier transform infrared spectroscopy (FTIR), X-ray diffraction (XRD), and scanning electron microscopy (SEM) techniques. Additionally, live/dead staining, 3-(4,5dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT), and alkaline phosphatase (ALP) activity assays were conducted respectively, as qualitatively and quantitatively assess for cell viability, proliferation and differentiations of MC3T3 cells in presence of 58s and 68s BGs. Results showed that BG-58s with higher CaO content showed higher in vitro bioactivity with respect to BG-68s. Moreover, the dissolution rate was inversely proportional to oxygen density of the BG. Live/dead assay revealed that both 58s and 68s increased the mean number live cells which were in good accordance with MTT assay. Furthermore, BG-58s showed more potential antibacterial activity against methicillin-resistant Staphylococcus aureus (MRSA) bacteria. Taken together, BG-58s with enhanced MC3T3 cells proliferation and ALP activity, acceptable bioactivity and significant high antibacterial effect against MRSA bacteria is suggested as a suitable candidate in order to further functionalizing for delivery of therapeutic ions and growth factors in bone tissue engineering.

Keywords: antibacterial, bioactive glass, hydroxyapatite, proliferation, sol-gel processes

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Authors: Yoshinori Wakatake

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Many defects after the release of software packages are caused due to omissions of sufficient test items in test specifications. Poor test specifications are detected by manual review, which imposes a high human load. The prevention of omissions depends on the end-user awareness of test specification writers. If test specifications were written while envisioning the behavior of end-users, the number of omissions in test items would be greatly reduced. The paper pays attention to the point that writers who can achieve it differ from those who cannot in not only the description richness but also their gaze information. It proposes a method to estimate the degree of user-awareness of writers through the analysis of their gaze information when writing test specifications. We conduct an experiment to obtain the gaze information of a writer of the test specifications. Test specifications are automatically classified using gaze information. In this method, a Random Forest model is constructed for the classification. The classification is highly accurate. By looking at the explanatory variables which turn out to be important variables, we know behavioral features to distinguish test specifications of high quality from others. It is confirmed they are pupil diameter size and the number and the duration of blinks. The paper also investigates test specifications automatically classified with gaze information to discuss features in their writing ways in each quality level. The proposed method enables us to automatically classify test specifications. It also prevents test item omissions, because it reveals writing features that test specifications of high quality should satisfy.

Keywords: blink, eye tracking, gaze information, pupil diameter, quality improvement, specification document, user-awareness

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Authors: D. S. Fardhyanti, M. Megawati, H. Prasetiawan, U. Mediaty

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Currently, fossil fuel is supplying most of world’s energy resources. However, fossil fuel resources are depleted rapidly and require an alternative energy to overcome the increasing of energy demands. Bio-oil is one of a promising alternative renewable energy resources which is converted from biomass through pyrolysis or fast pyrolysis process. Bio-oil is a dark liquid fuel, has a smelling smoke and usually obtained from sugar cane, wood, coconut shell and any other biomass. Sugar cane content analysis showed that the content of oligosaccharide, hemicellulose, cellulose and lignin was 16.69%, 25.66%, 51.27% and 6.38% respectively. Sugar cane is a potential sources for bio-oil production shown by its high content of cellulose. In this study, production of bio-oil from sugar cane bagasse was investigated via fast pyrolysis reactor. Fast pyrolysis was carried out at 500 °C with a heating rate of 10 °C and 1 hour holding time at pyrolysis temperature. Physical properties and chemical composition of bio-oil were analyzed. The viscosity, density, calorific value and molecular weight of produced bio-oil was 3.12 cp, 2.78 g/cm3, 11,048.44 cals/g, and 222.67 respectively. The Bio-oil chemical composition was investigated using GC-MS. Percentage value of furfural, phenol, 3-methyl 1,2-cyclopentanedione, 5-methyl-3-methylene 5-hexen-2-one, 4-methyl phenol, 4-ethyl phenol, 1,2-benzenediol, and 2,6-dimethoxy phenol was 20.76%, 16.42%, 10.86%, 7.54%, 7.05%, 7.72%, 5.27% and 6.79% respectively.

Keywords: bio-oil, pyrolysis, bagasse, sugar cane, gas chromatography-mass spectroscopy

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Authors: Anusha Jain, Santosh Vishwanathan, Praveen K. Gupta, Shwetha S., Kavitha S. N.

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Agriculture has a major impact on the Indian economy, with the highest employment ratio than any sector of the country. Currently, most of the traditional agricultural practices and farming methods are manual, which results in farmers not realizing their maximum productivity often due to increasing in labour cost, inefficient use of water sources leading to wastage of water, inadequate soil moisture content, subsequently leading to food insecurity of the country. This research paper aims to solve this problem by developing a full-fledged web application-based platform that has the capacity to associate itself with a Microcontroller-based Automated Irrigation System which schedules the irrigation of crops based on real-time soil moisture content employing soil moisture sensors centric to the crop’s requirements using WSN (Wireless Sensor Networks) and M2M (Machine To Machine Communication) concepts, thus optimizing the use of the available limited water resource, thereby maximizing the crop yield. This robust automated irrigation system provides end-to-end automation of Irrigation of crops at any circumstances such as droughts, irregular rainfall patterns, extreme weather conditions, etc. This platform will also be capable of achieving a nationwide united farming community and ensuring the welfare of farmers. This platform is designed to equip farmers with prerequisite knowledge on tech and the latest farming practices in general. In order to achieve this, the MailChimp mailing service is used through which interested farmers/individuals' email id will be recorded and curated articles on innovations in the world of agriculture will be provided to the farmers via e-mail. In this proposed system, service is enabled on the platform where nearby crop vendors will be able to enter their pickup locations, accepted prices and other relevant information. This will enable farmers to choose their vendors wisely. Along with this, we have created a blogging service that will enable farmers and agricultural enthusiasts to share experiences, helpful knowledge, hardships, etc., with the entire farming community. These are some of the many features that the platform has to offer.

Keywords: WSN (wireless sensor networks), M2M (M/C to M/C communication), automation, irrigation system, sustainability, SAAS (software as a service), soil moisture sensor

Procedia PDF Downloads 129

Authors: Mohd Iz'aan Paiz Bin Zamri, Anis Salwa Mohd Khairuddin, Norrima Mokhtar, Rubiyah Yusof

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Effective statistical feature extraction and classification are important in image-based automatic inspection and analysis. An automatic wood species recognition system is designed to perform wood inspection at custom checkpoints to avoid mislabeling of timber which will results to loss of income to the timber industry. The system focuses on analyzing the statistical pores properties of the wood images. This paper proposed a fuzzy-based feature extractor which mimics the experts’ knowledge on wood texture to extract the properties of pores distribution from the wood surface texture. The proposed feature extractor consists of two steps namely pores extraction and fuzzy pores management. The total number of statistical features extracted from each wood image is 38 features. Then, a backpropagation neural network is used to classify the wood species based on the statistical features. A comprehensive set of experiments on a database composed of 5200 macroscopic images from 52 tropical wood species was used to evaluate the performance of the proposed feature extractor. The advantage of the proposed feature extraction technique is that it mimics the experts’ interpretation on wood texture which allows human involvement when analyzing the wood texture. Experimental results show the efficiency of the proposed method.

Keywords: classification, feature extraction, fuzzy, inspection system, image analysis, macroscopic images

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Authors: Serges Djoyou Kamga, Gerard Emmanuel Kamdem Kamga

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Any serious constitutionalism entails a system of government characterised by the separation of powers between the executive, the legislature, and the judiciary. The latter is generally in charge of upholding the rule of law and the respect for human rights which are vital for the functioning of any democracy. Therefore, for the judiciary to play its role as a watchdog, it should be independent from other branches of government. The aim of this paper is to examine the independence of the judiciary in South Africa after 20 of democracy. Defining judicial independence as the courts’ ability ‘to decide cases on the basis of established law and the merits of the case, without interference from other political or governmental agents’, the paper examines the extent to which the South African judiciary is independent after twenty years of democracy. As part of assessing the independence of the judiciary, the paper begins by looking at the situation during apartheid, then proceeds with an examination of the post-apartheid legal order. It also examines the institutional independence of the judiciary by looking into its day to day activities which revolve around its self-governance, or administrative and financial independence. In addition, the paper assesses the judges’ individual independence by examining whether judicial appointment, security of tenure, judges’ remuneration and disciplinary actions and the removal of judges from office do not contain loopholes that can hinder judicial independence. Ultimately, the chapter argues that although the South African model of judicial independence is yet to be perfect, it is a good practice that can be emulated by other African countries.

Keywords: judical independence, South Africa, democracy, separation of powers

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Authors: Mustafa Kucukoduk, Evren Yildiztugay, A. Hediye Sekmen, Ismail Turkan, Yavuz Bagci

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In this study, physiological and biochemical responses of Centaurea tuzgoluensis, a Turkish endemic halophyte, to salinity were studied. Therefore, the changes in shoot growth, leaf relative water content (RWC), ion concentrations, lipid peroxidation, hydroxyl (OH.) radical scavenging activity, proline (Pro) content, and antioxidant system [superoxide dismutase (SOD), catalase (CAT), ascorbate peroxidase (APX) and glutathione reductase (GR)] were investigated. The 60 days (d) old C. tuzgoluensis seedlings were subjected to 0, 150 and 300 mM NaCl for 7 d and 14 d. The relative shoot growth was generally did not change in the 150 mM NaCl, but reduced with 300 mM NaCl stress at 7 d and 14 d. RWC was higher in 150 mM NaCl-treated leaves than that of 300 mM NaCl. Salinity decreased K+/Na+ ratio, but increased Na+, Cl, Ca+2 and Na+/Cl ratio in the leaves. On the other hand, it did not change or increase the K+ content at 150 and 300 mM NaCl, respectively. MDA content in the 150 and 300 mM NaCl-treated leaves remained close to control at 7 d. This was related to enhanced activities of SOD, CAT, APX and GR enzymes, and their isoenzymes especially Fe-SOD in the leaves. On the other hand, the higher sensitivity to 300 mM NaCl at 14 d was associated with inadequate increase in antioxidant enzymes and the decreased OH radical scavenging activity. All these results suggest that C. tuzgoluensis has different antioxidant metabolisms between short- (7 d) and long-term (14 d) salt treatments and salinity tolerance of C. tuzgoluensis might be closely related to increased capacity of antioxidative system to scavenge reactive oxygen species (ROS) and accumulation of osmoprotectant proline under salinity conditions.

Keywords: antioxidant enzymes, endemic halophyte, ion exchange, lipid peroxidation, antioxidant, enzymes, endemic halophyte, ion exchange, lipid peroxidation, proline, Centaurea tuzgoluensis

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Authors: Mark Harmon, Abdolghani Ebrahimi, Patrick Lucey, Diego Klabjan

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In this paper, we predict the likelihood of a player making a shot in basketball from multiagent trajectories. Previous approaches to similar problems center on hand-crafting features to capture domain-specific knowledge. Although intuitive, recent work in deep learning has shown, this approach is prone to missing important predictive features. To circumvent this issue, we present a convolutional neural network (CNN) approach where we initially represent the multiagent behavior as an image. To encode the adversarial nature of basketball, we use a multichannel image which we then feed into a CNN. Additionally, to capture the temporal aspect of the trajectories, we use “fading.” We find that this approach is superior to a traditional FFN model. By using gradient ascent, we were able to discover what the CNN filters look for during training. Last, we find that a combined FFN+CNN is the best performing network with an error rate of 39%.

Keywords: basketball, computer vision, image processing, convolutional neural network

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Authors: Mohammed Alhawiti

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Assessment of Learning Management Systems has been of less importance than its due share. This paper investigates the evaluation of learning management systems (LMS) within educational setting as both an online learning system as well as a helpful tool for multidisciplinary learning environment. This study suggests a theoretical e-learning evaluation model, studying a multi-dimensional methods for evaluation through LMS system, service and content quality, learner`s perspective and attitudes of the instructor. A survey was conducted among 105 e-learners. The sample consisted of students at both undergraduate and master’s levels. Content validity, reliability were tested through the instrument, Findings suggested the suitability of the proposed model in evaluation for the satisfaction of learners through LMS. The results of this study would be valuable for both instructors and users of e-learning systems.

Keywords: e-learning, LMS, higher education, management systems

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Authors: Elena Krelja Kurelović, Jasminka Tomljanović, Vlatka Davidović

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The development of web technologies and mobile devices makes creating, accessing, using and sharing information or communicating with each other simpler every day. However, while the amount of information constantly increasing it is becoming harder to effectively organize and find quality information despite the availability of web search engines, filtering and indexing tools. Although digital technologies have overall positive impact on students’ lives, frequent use of these technologies and digital media enriched with dynamic hypertext and hypermedia content, as well as multitasking, distractions caused by notifications, calls or messages; can decrease the attention span, make thinking, memorizing and learning more difficult, which can lead to stress and mental exhaustion. This is referred to as “information overload”, “information glut” or “information anxiety”. Objective of this study is to determine whether students show signs of information overload and to identify the possible predictors. Research was conducted using a questionnaire developed for the purpose of this study. The results show that students frequently use technology (computers, gadgets and digital media), while they show moderate level of information literacy. They have sometimes experienced symptoms of information overload. According to the statistical analysis, higher frequency of technology use and lower level of information literacy are correlated with larger information overload. The multiple regression analysis has confirmed that the combination of these two independent variables has statistically significant predictive capacity for information overload. Therefore, the information science teachers should pay attention to improving the level of students’ information literacy and educate them about the risks of excessive technology use.

Keywords: information overload, computers, mobile devices, digital media, information literacy, students

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Authors: Alireza Mirrashid, Mohammad Khoshbin, Ali Atghaei, Hassan Shahbazi

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In various industries, smoke and fire are two of the most important threats in the workplace. One of the common methods for detecting smoke and fire is the use of infrared thermal and smoke sensors, which cannot be used in outdoor applications. Therefore, the use of vision-based methods seems necessary. The problem of smoke and fire detection is spatiotemporal and requires spatiotemporal solutions. This paper presents a method that uses spatial features along with temporal-based features to detect smoke and fire in the scene. It consists of three main parts; the task of each part is to reduce the error of the previous part so that the final model has a robust performance. This method also uses transformer modules to increase the accuracy of the model. The results of our model show the proper performance of the proposed approach in solving the problem of smoke and fire detection and can be used to increase workplace safety.

Keywords: attention, fire detection, smoke detection, spatio-temporal

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Authors: Inderpreet Kaur, Sukhjit Kaur, Balwinder Singh Sohi

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The design proposed in this paper mainly focuses on implementation of a single feed compact rectangular microstrip patch antenna (MSA) for single band application. The antenna presented here also works in dual band but its best performance has been obtained when optimised to work in single band mode. In this paper, a new feeding structure is applied in the patch antenna design to overcome undesirable features of the earlier multilayer feeding structures while maintaining their interesting features.To make the proposed antenna more efficient the optimization of the antenna design parameters have been done using HFSS’s optometric. For the proposed antenna one resonant frequency has been obtained at 6.03GHz, with Bandwidth of 167MHz and return loss of -33.82db. The characteristics of the designed structure are investigated by using FEM based electromagnetic solver.

Keywords: bandwidth, retun loss, parasitic lines, microstrip antenna

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Authors: Mohd Moiz Khan, S. M. Mahajani, G. N. Jadhav

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Waste foundry sand (total clay content 15%) contains toxic heavy metals and particulate matter which make dumping of waste sand an environmental and health hazard. Disposal of waste foundry sand (WFS) remains one of the substantial challenges faced by Indian foundries nowadays. To cope up with this issue, the chemical method was used to reclaim WFS. A stirrer tank reactor was used for chemical reclamation. Experiments were performed to reduce the total clay content from 15% to as low as 0.9% in chemical reclamation. This method, although found to be effective for WFS reclamation, it may face a challenge due to the possibly high operating cost. Reclaimed sand was found to be satisfactory in terms of sand qualities such as total clay (0.9%), active clay (0.3%), acid demand value (ADV) (2.6%), loss on igniting (LOI) (3 %), grain fineness number (GFN) (56), and compressive strength (60 kPa). The experimental data generated on chemical reactor under different conditions is further used to optimize the design and operating parameters (rotation speed, sand to acidic solution ratio, acid concentration, temperature and time) for the best performance. The use of reclaimed sand within the foundry would improve the economics and efficiency of the process and reduce environmental concerns.

Keywords: chemical reclamation, clay content, environmental concerns, recycle, waste foundry sand

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Authors: Bubai Maji, Monorama Swain

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Speech is considered an essential and most natural medium for the interaction between machines and humans. However, extracting effective features for speech emotion recognition (SER) is remains challenging. The present studies show that the temporal information captured but high-level temporal-feature learning is yet to be investigated. In this paper, we present an efficient novel method using the Self-attention (SA) mechanism in a combination of Convolutional Neural Network (CNN) and Bi-directional Gated Recurrent Unit (Bi-GRU) network to learn high-level temporal-feature. In order to further enhance the representation of the high-level temporal-feature, we integrate a Bi-GRU output with learnable weights features by SA, and improve the performance. We evaluate our proposed method on our created SITB-OSED and IEMOCAP databases. We report that the experimental results of our proposed method achieve state-of-the-art performance on both databases.

Keywords: Bi-GRU, 1D-CNNs, self-attention, speech emotion recognition

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Authors: Faseluka Olamide Tope

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Giving quality education to students with special needs requires that all necessary resources should be harnessed and digital devices has become important part of resources used as instructional materials in educating students with special needs. Teachers who will make use of these technologies are considered as a part of the most important elements in any educational programme and the effective usage of these technologies largely depends on them. Out of numerous determinants of the effective use of these digital devices, this study examines teachers’ attitude and knowledge as predictors of effective use of digital technology for education of special needs student in Oyo state, Nigeria. The descriptive survey research design of the expo-facto type was adopted for the study, using simple random sampling technique. The study was carried out among sixty (60) participants. Two research questions and two research hypotheses were formulated and used. The data collected through the research instruments for the study were analysedusing frequency, percentage, mean and standard deviation, Pearson, Product, Moment Correlation (PPMC) and Multiple Regression Analysis. The study revealed a significant relationship between teachers attitude (50, < 0.05) and effective use of digital technologies for special needs students. Furthermore, there was a significant contribution F (F=4.289; R=0.876 and R2 =0.758) in the joint contribution of the independent variable  (teacher’s attitude and teacher’s knowledge) and dependent variable (effective use of digital technologies) while teachers knowledge have the highest contribution(b=7.926, t=4.376), the study therefore revealed that teachers attitude and knowledge are potent factors that predicts the effective usage of digital technologies for the education of special needs student. The study recommended that due to the ever-changing nature of technology which comes with new features, teachers should be equipped with appropriate knowledge in order to effectively make use of them and teachers should also develop right attitude toward the use of digital technologies

Keywords: teachers’ knowledge, teachers’ attitude, digital devices, special needs students

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Authors: Ben Soltane Cheima, Ittansa Yonas Kelbesa

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Speaker Identification (SI) is the task of establishing identity of an individual based on his/her voice characteristics. The SI task is typically achieved by two-stage signal processing: training and testing. The training process calculates speaker specific feature parameters from the speech and generates speaker models accordingly. In the testing phase, speech samples from unknown speakers are compared with the models and classified. Even though performance of speaker identification systems has improved due to recent advances in speech processing techniques, there is still need of improvement. In this paper, a Closed-Set Tex-Independent Speaker Identification System (CISI) based on a Multiple Classifier System (MCS) is proposed, using Mel Frequency Cepstrum Coefficient (MFCC) as feature extraction and suitable combination of vector quantization (VQ) and Gaussian Mixture Model (GMM) together with Expectation Maximization algorithm (EM) for speaker modeling. The use of Voice Activity Detector (VAD) with a hybrid approach based on Short Time Energy (STE) and Statistical Modeling of Background Noise in the pre-processing step of the feature extraction yields a better and more robust automatic speaker identification system. Also investigation of Linde-Buzo-Gray (LBG) clustering algorithm for initialization of GMM, for estimating the underlying parameters, in the EM step improved the convergence rate and systems performance. It also uses relative index as confidence measures in case of contradiction in identification process by GMM and VQ as well. Simulation results carried out on voxforge.org speech database using MATLAB highlight the efficacy of the proposed method compared to earlier work.

Keywords: feature extraction, speaker modeling, feature matching, Mel frequency cepstrum coefficient (MFCC), Gaussian mixture model (GMM), vector quantization (VQ), Linde-Buzo-Gray (LBG), expectation maximization (EM), pre-processing, voice activity detection (VAD), short time energy (STE), background noise statistical modeling, closed-set tex-independent speaker identification system (CISI)

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Authors: Aslihan Cetinbas Genc, Meral Unal

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This study presents the structural and cytochemical alterations of stigma at the stages of pre-anthesis, anthesis and post-anthesis in Vibirnum tinus. Capitate stigma continues with a closed style. The receptive surface of stigma is composed of unicellular papillae which are short and flattened at pre-anthesis stage. The papillae in this stage have dense cytoplasm with small vacuoles and a centrally located nucleus. With the start of anthesis, the stigma widens, papillae lengthen and become cylindrical. At anthesis stage, vacuoles enlarge, and nucleus moves to the base of the cell. At post-anthesis stage, the boundaries of the papillae become less noticeable. As proved by Periodic Acid Schiff procedure, the cytoplasm of papillae is rich in insoluble polysaccharides at all stages of development but it becomes remarkable at post-anthesis, particularly at the sub-papillar area. Although there is no significant difference in the content of protein in all stages of the development, it is more abundant at post-anthesis stage, as in Coomassie Brillant Blue stained sections. The surface of papillae is covered by a cuticle which becomes thicker at post-anthesis, and it gives positive reaction with Sudan Black B and Auramine O. The cuticle is covered by a pellicle stained by Coomassie Brillant Blue, indicating dry type of stigma.

Keywords: develeopmental features, histochemistry, stigma, Vibirnum tinus

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Authors: Jameela Ali, Hamid A. Jalab, Loay E. George, Abdul Rahim Ahmad, Azizah Suliman, Karim Al-Jashamy

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Red blood cells (RBC) are the most common types of blood cells and are the most intensively studied in cell biology. The lack of RBCs is a condition in which the amount of hemoglobin level is lower than normal and is referred to as “anemia”. Abnormalities in RBCs will affect the exchange of oxygen. This paper presents a comparative study for various techniques for classifyig the red blood cells as normal, or abnormal (anemic) using WEKA. WEKA is an open source consists of different machine learning algorithms for data mining applications. The algorithm tested are Radial Basis Function neural network, Support vector machine, and K-Nearest Neighbors algorithm. Two sets of combined features were utilized for classification of blood cells images. The first set, exclusively consist of geometrical features, was used to identify whether the tested blood cell has a spherical shape or non-spherical cells. While the second set, consist mainly of textural features was used to recognize the types of the spherical cells. We have provided an evaluation based on applying these classification methods to our RBCs image dataset which were obtained from Serdang Hospital-Malaysia, and measuring the accuracy of test results. The best achieved classification rates are 97%, 98%, and 79% for Support vector machines, Radial Basis Function neural network, and K-Nearest Neighbors algorithm respectively

Keywords: red blood cells, classification, radial basis function neural networks, suport vector machine, k-nearest neighbors algorithm

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Authors: Nynke de Jong, Inge G. P. Duimel-Peeters

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The flipped classroom as an instructional strategy and a type of blended learning that reverses the traditional learning environment by delivering instructional content, off- and online, in- and outside the classroom, has been implemented in a 4-weeks module focusing on ageing in Europe at the Maastricht University. The main aim regarding the organization of this module was implementing flipped classroom-principles in order to create meaningful learning opportunities, while educational technologies are used to deliver content outside of the classroom. Technologies used in this module were an online interactive real time lecture from England, two interactive face-to-face lectures with visual supports, one group session including role plays and team-based learning meetings. The cohort of 2015-2016, using educational technologies, was compared with the cohort of 2014-2015 on module evaluation such as organization and instructiveness of the module, who studied the same content, although conforming the problem-based educational strategy, i.e. educational base of the Maastricht University. The cohort of 2015-2016 with its specific organization, was also more profound evaluated on outcomes as (1) experienced duration of the lecture by students, (2) experienced content of the lecture, (3) experienced the extent of the interaction and (4) format of lecturing. It was important to know how students reflected on duration and content taken into account their background knowledge so far, in order to distinguish between sufficient enough regarding prior knowledge and therefore challenging or not fitting into the course. For the evaluation, a structured online questionnaire was used, whereby above mentioned topics were asked for to evaluate by scoring them on a 4-point Likert scale. At the end, there was room for narrative feedback so that interviewees could express more in detail, if they wanted, what they experienced as good or not regarding the content of the module and its organization parts. Eventually, the response rate of the evaluation was lower than expected (54%), however, due to written feedback and exam scores, we dare to state that it gives a good and reliable overview that encourages to work further on it. Probably, the response rate may be explained by the fact that resit students were included as well, and that there maybe is too much evaluation as some time points in the program. However, overall students were excited about the organization and content of the module, but the level of self-directed behavior, necessary for this kind of educational strategy, was too low. They need to be more trained in self-directness, therefore the module will be simplified in 2016-2017 with more clear and fewer topics and extra guidance (step by step procedure). More specific information regarding the used technologies will be explained at the congress, as well as the outcomes (min and max rankings, mean and standard deviation).

Keywords: blended learning, flipped classroom, public health, self-directness

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Authors: Mohammad Zavid Parvez, Manoranjan Paul

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Epilepsy is a common neurological disorders characterized by sudden recurrent seizures. Electroencephalogram (EEG) is widely used to diagnose possible epileptic seizure. Many research works have been devoted to predict epileptic seizure by analyzing EEG signal. Seizure prediction by analyzing EEG signals are challenging task due to variations of brain signals of different patients. In this paper, we propose a new approach for feature extraction based on phase correlation in EEG signals. In phase correlation, we calculate relative change between two consecutive segments of an EEG signal and then combine the changes with neighboring signals to extract features. These features are then used to classify preictal/ictal and interictal EEG signals for seizure prediction. Experiment results show that the proposed method carries good prediction rate with greater consistence for the benchmark data set in different brain locations compared to the existing state-of-the-art methods.

Keywords: EEG, epilepsy, phase correlation, seizure

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Authors: Adrià Arbués-Sangüesa, Coloma Ballester, Gloria Haro

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Tracking sports players is a widely challenging scenario, specially in single-feed videos recorded in tight courts, where cluttering and occlusions cannot be avoided. This paper presents an analysis of several geometric and semantic visual features to detect and track basketball players. An ablation study is carried out and then used to remark that a robust tracker can be built with Deep Learning features, without the need of extracting contextual ones, such as proximity or color similarity, nor applying camera stabilization techniques. The presented tracker consists of: (1) a detection step, which uses a pretrained deep learning model to estimate the players pose, followed by (2) a tracking step, which leverages pose and semantic information from the output of a convolutional layer in a VGG network. Its performance is analyzed in terms of MOTA over a basketball dataset with more than 10k instances.

Keywords: basketball, deep learning, feature extraction, single-camera, tracking

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Authors: Ritu Chaturvedi, Manoj Paul

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A pot experiment was conducted to investigate the effect of Arbuscular mycorrhizal fungus (AMF) on metal(loid) uptake and accumulation efficiency of Pisum sativum along with physiological and biochemical response. Plants were grown in soil spiked with 50 and 100 mg kg-1 Pb, 25 and 50 mg kg-1 Cd, 50 and 100 mg kg-1 As and a combination of all three metal(loid)s. A parallel set was maintained and inoculated with arbuscular mycorrhizal fungus for comparison. After 60 days, plants were harvested and analysed for metal(loid) content. A steady increase in metal(loid) accumulation was observed on increment of metal(loid) dose and also on AMF inoculation. Plant height, biomass, chlorophyll, carotenoid and carbohydrate content reduced upon metal(loid) exposure. Increase in enzymatic (CAT, SOD and APX) and nonenzymatic (Proline) defence proteins was observed on metal(loid) exposure. AMF inoculation leads to an increase in plant height, biomass, chlorophyll, carotenoids, carbohydrate and enzymatic defence proteins (p≤0.001) under study; whereas proline content was reduced. Considering the accumulation efficiency and adaptive response of plants and alleviation of stress by AMF, this symbiosis can be applied for on-site remediation of Pb and Cd contaminated soil.

Keywords: heavy metal, mycorrhiza, pea, phyroremediation

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Authors: Divi Sharma

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The emergence of positive behaviour support (PBS) is directly linked to applied behaviour analysis that incorporates evidence-based approaches to addressing ethical challenges and improving autonomy, participation, and the overall quality of life of people living and learning in complex social environments. Its features include lifestyle improvement, collaboration with general caregivers, tracking progress with sound steps, comprehensive performance-based interventions, striving for contextual equality, and ensuring entry and implementation. This document aims to summarize its features with the support of case examples such as involving caregivers to play an active role in behavioural interventions, creating effective interventions within natural practices. Additionally, dealing with lifestyle changes, as well as a wide variety of behavioural changes, develop strong strategies which reduce professional dependence.

Keywords: positive behaviour support, quality of life, performance-based interventions, behavioural changes, participation

Procedia PDF Downloads 170