Search results for: e-content producing algorithm

Authors: Nurulnadwan Aziz, Ariffin Abdul Mutalib, Siti Mahfuzah Sarif

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This paper reports an ongoing project regarding the development of Conceptual Design Model of Assistive Courseware for Low Vision (AC4LV) learners. Having developed the intended model, it has to be validated prior to producing it as guidance for the developers to develop an AC4LV. This study requires two phases of validation process which are through expert review and prototyping method. This paper presents a part of the validation process which is findings from experts review on Conceptual Design Model of AC4LV which has been carried out through a questionnaire. Results from 12 international and local experts from various respectable fields in Human-Computer Interaction (HCI) were discussed and justified. In a nutshell, reviewed Conceptual Design Model of AC4LV was formed. Future works of this study are to validate the reviewed model through prototyping method prior to testing it to the targeted users.

Keywords: assistive courseware, conceptual design model, expert review, low vision learners

Procedia PDF Downloads 548

Authors: Regan Harper, Song Yang, Douglas Adams

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During the historically unprecedent time of Covid-19 pandemic, we survey college students with social issue generators to measure their core discussion groups. For the total 191 students, we elicit 847 conversation partners (alters) with our five social issue generators such as school closing, facemasks, collegiate sports, race and policing, and social inequality, producing an average of 4.43 alters per respondent. The core discussion groups of our sample are very gender balanced, with female alters slightly outnumbering male alters. However, the core discussion groups are racially homogenous, consisting of mostly white students (around or above 80 percent). Explanatory analyses reveal that gender and race of respondents significantly impact the size, gender composition, and racial composition of their core discussion networks. We discuss those major findings and implications of future studies in our conclusion section.

Keywords: core discussion groups, social issue generators, ego-centric network, Covid-19 pandemic

Procedia PDF Downloads 92

Authors: Mahmoud Almasri, Xavier Marjou, Fanny Parzysz

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The demand for services provided by Unmanned Aerial Vehicles (UAVs) is increasing pervasively across several sectors including potential public safety, economic, and delivery services. As the number of applications using UAVs grows rapidly, more and more powerful, quality of service, and power efficient computing units are necessary. Recently, cellular technology draws more attention to connectivity that can ensure reliable and flexible communications services for UAVs. In cellular technology, flying with a high speed and altitude is subject to several key challenges, such as frequent handovers (HOs), high interference levels, connectivity coverage holes, etc. Additional HOs may lead to “ping-pong” between the UAVs and the serving cells resulting in a decrease of the quality of service and energy consumption. In order to optimize the number of HOs, we develop in this paper a Q-learning-based algorithm. While existing works focus on adjusting the number of HOs in a static network topology, we take into account the impact of cells deployment for three different simulation scenarios (Rural, Semi-rural and Urban areas). We also consider the impact of the decision distance, where the drone has the choice to make a switching decision on the number of HOs. Our results show that a Q-learning-based algorithm allows to significantly reduce the average number of HOs compared to a baseline case where the drone always selects the cell with the highest received signal. Moreover, we also propose which hyper-parameters have the largest impact on the number of HOs in the three tested environments, i.e. Rural, Semi-rural, or Urban.

Keywords: drones connectivity, reinforcement learning, handovers optimization, decision distance

Procedia PDF Downloads 110

Authors: Saadan Man, Razidah Othmanjaludin, Madiha Baharuddin

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Nowadays, the pharmaceutical products are produced through the mixing of active and complex ingredient, naturally or synthetically; and involve extensive use of prohibited animal products. This article studies the challenges faced from fiqh perspective in the production of halal pharmaceutical products which frequently contain impure elements or prohibited animal derivatives according to Islamic law. This study is qualitative which adopts library research as well as field research by conducting series of interviews with the several related parties. The gathered data is analyzed from Sharia perspective by using some instruments especially the principle of Maqasid of Sharia. This study shows that the halal status of pharmaceutical products depends on the three basic elements: the sources of the basic ingredient; the processes involved in three phases of production, i.e., before, during and after; and the possible effects of the products. Various fiqh challenges need to be traversed in producing halal pharmaceutical products including the sources of the ingredients, the logistic process, the tools used, and the procedures of productions. Thus, the whole supply chain of production of pharmaceutical products must be well managed in accordance to the halal standard.

Keywords: fiqh, halal pharmaceutical, pharmaceutical products, Malaysia

Procedia PDF Downloads 196

Authors: Keshav Raj Dhakal, Jit Bahadur Rokaya Chhetri

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The Micro Hydro (MH) is one of the successful technology in Rural Nepal. Out of 75 district, 59 districts have installed 1287 MH projects with a total capacity of 24 Mega Watt (MW). Now, the challenge is how to sustain them. Dolakha is a prominent district for sustainable endues of power to sustain the MH projects. A total of 37 MH projects have been constructed with producing 886 Kilo Watt (KW) of energy in the district. This study traces out the impact of earthquake in MH sector in Dolakha district. It shows that 59 % of projects have been affected by devastating earthquake in April and May, 2015 where 29 % are completely damaged. Most of the damages are in civil structures like Penstock, forebay, power house, Canal, Intake. Transmission and distribution line have been partially damaged. This paper analysis failure of the civil structural component of MH projects and its financial consequence to the community. This study recommends that a disaster impact assessment is essential before construction of MH projects.

Keywords: micro hydro, earthquake, structural failure, financial consequence

Procedia PDF Downloads 206

Authors: Pavlo Selyshchev, Samuel Akintunde

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A theoretical approach to consider formation of chemical compound layer at the interface between initial substances A and B due to the interfacial interaction and diffusion is developed. It is considered situation when speed of interfacial interaction is large enough and diffusion of A-atoms through AB-layer is much more then diffusion of B-atoms. Atoms from A-layer diffuse toward B-atoms and form AB-atoms on the surface of B-layer. B-atoms are assumed to be immobile. The growth kinetics of the AB-layer is described by two differential equations with non-linear coupling, producing a good fit to the experimental data. It is shown that growth of the thickness of the AB-layer determines by dependence of chemical reaction rate on reactants concentration. In special case the thickness of the AB-layer can grow linearly or parabolically depending on that which of processes (interaction or the diffusion) controls the growth. The thickness of AB-layer as function of time is obtained. The moment of time (transition point) at which the linear growth are changed by parabolic is found.

Keywords: phase formation, binary systems, interfacial reaction, diffusion, compound layers, growth kinetics

Procedia PDF Downloads 572

Authors: Varun Agarwal

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Introduction: With the advent of personalized medicine, histopathological review of whole slide images (WSIs) for cancer diagnosis presents an exceedingly time-consuming, complex task. Specifically, detecting metastatic regions in WSIs of sentinel lymph node biopsies necessitates a full-scanned, holistic evaluation of the image. Thus, digital pathology, low-level image manipulation algorithms, and machine learning provide significant advancements in improving the efficiency and accuracy of WSI analysis. Using Camelyon16 data, this paper proposes a deep learning pipeline to automate and ameliorate breast cancer metastasis localization and WSI classification. Methodology: The model broadly follows five stages -region of interest detection, WSI partitioning into image tiles, convolutional neural network (CNN) image-segment classifications, probabilistic mapping of tumor localizations, and further processing for whole WSI classification. Transfer learning is applied to the task, with the implementation of Inception-ResNetV2 - an effective CNN classifier that uses residual connections to enhance feature representation, adding convolved outputs in the inception unit to the proceeding input data. Moreover, in order to augment the performance of the transfer learning CNN, a stack of convolutional denoising autoencoders (CDAE) is applied to produce embeddings that enrich image representation. Through a saliency-detection algorithm, visual training segments are generated, which are then processed through a denoising autoencoder -primarily consisting of convolutional, leaky rectified linear unit, and batch normalization layers- and subsequently a contrast-normalization function. A spatial pyramid pooling algorithm extracts the key features from the processed image, creating a viable feature map for the CNN that minimizes spatial resolution and noise. Results and Conclusion: The simplified and effective architecture of the fine-tuned transfer learning Inception-ResNetV2 network enhanced with the CDAE stack yields state of the art performance in WSI classification and tumor localization, achieving AUC scores of 0.947 and 0.753, respectively. The convolutional feature retention and compilation with the residual connections to inception units synergized with the input denoising algorithm enable the pipeline to serve as an effective, efficient tool in the histopathological review of WSIs.

Keywords: breast cancer, convolutional neural networks, metastasis mapping, whole slide images

Procedia PDF Downloads 132

Authors: Syed Qasim Gilani, Muhammad Umair, Muhammad Noman, Syed Bilawal Shah, Aqib Abbasi, Muhammad Waheed

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Cardiovascular Diseases(CVD's) are the major cause of death in the world. The main reason for these deaths is the unavailability of first aid for heart failure. In many cases, patients die before reaching the hospital. We in this paper are presenting innovative online health service for Cardiac Patients. The proposed online health system has two ends. Users through device developed by us can communicate with their doctor through a mobile application. This interface provides them with first aid.Also by using this service, they have an easy interface with their doctors for attaining medical advice. According to the proposed system, we developed a device called Cardiac Care. Cardiac Care is a portable device which a patient can use at their home for monitoring heart condition. When a patient checks his/her heart condition, Electrocardiogram (ECG), Blood Pressure(BP), Temperature are sent to the central database. The severity of patients condition is checked using Artificial Intelligence Algorithm at the database. If the patient is suffering from the minor problem, our algorithm will suggest a prescription for patients. But if patient's condition is severe, patients record is sent to doctor through the mobile Android application. Doctor after reviewing patients condition suggests next step. If a doctor identifies the patient condition as critical, then the message is sent to the central database for sending an ambulance for the patient. Ambulance starts moving towards patient for bringing him/her to hospital. We have implemented this model at prototype level. This model will be life-saving for millions of people around the globe. According to this proposed model patients will be in contact with their doctors all the time.

Keywords: cardiovascular disease, classification, electrocardiogram, blood pressure

Procedia PDF Downloads 185

Authors: Priyanka Bhatnagar, Malkeshkumar Patel, Joondong Kim, Joonpyo Hong

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Artificial skin and sensory memory platforms are produced using a flexible, transparent photovoltaic (TPV) device. The TPV device is composed of a metal oxide heterojunction (nZnO/p-NiO) and transmits visible light (> 50%) while producing substantial electric power (0.5 V and 200 μA cm-2 ). This TPV device is a transparent energy interface that can be used to detect signals and propagate information without an external energy supply. The TPV artificial skin offers a temperature detection range (0 C75 C) that is wider than that of natural skin (5 C48 °C) due to the temperature-sensitive pyrocurrent from the ZnO layer. Moreover, the TPV thermoreceptor offers sensory memory of extreme thermal stimuli. Much like natural skin, artificial skin uses the nociceptor mechanism to protect tissue from harmful damage via signal amplification (hyperalgesia) and early adaption (allodynia). This demonstrates the many features of TPV artificial skin, which can sense and transmit signals and memorize information under self-operation mode. This transparent photovoltaic skin can provide sustainable energy for use in human electronics.

Keywords: transparent, photovoltaics, thermal memory, artificial skin, thermoreceptor

Procedia PDF Downloads 113

Authors: Khaled Ahmed Kadouh, Kamal Ali Albashiri

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This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.

Keywords: JAX-WS, SMTP, SOAP, web service, XML

Procedia PDF Downloads 496

Authors: Amir Abbas Fatemi, Zahra Tabrizian, Kabir Sadeghi

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To find the location and severity of damage that occurs in a structure, characteristics changes in dynamic and static can be used. The non-destructive techniques are more common, economic, and reliable to detect the global or local damages in structures. This paper presents a non-destructive method in structural damage detection and assessment using GA and static data. Thus, a set of static forces is applied to some of degrees of freedom and the static responses (displacements) are measured at another set of DOFs. An analytical model of the truss structure is developed based on the available specification and the properties derived from static data. The damages in structure produce changes to its stiffness so this method used to determine damage based on change in the structural stiffness parameter. Changes in the static response which structural damage caused choose to produce some simultaneous equations. Genetic Algorithms are powerful tools for solving large optimization problems. Optimization is considered to minimize objective function involve difference between the static load vector of damaged and healthy structure. Several scenarios defined for damage detection (single scenario and multiple scenarios). The static damage identification methods have many advantages, but some difficulties still exist. So it is important to achieve the best damage identification and if the best result is obtained it means that the method is Reliable. This strategy is applied to a plane truss. This method is used for a plane truss. Numerical results demonstrate the ability of this method in detecting damage in given structures. Also figures show damage detections in multiple damage scenarios have really efficient answer. Even existence of noise in the measurements doesn’t reduce the accuracy of damage detections method in these structures.

Keywords: damage detection, finite element method, static data, non-destructive, genetic algorithm

Procedia PDF Downloads 239

Authors: Gauravi Agarkar, Mahendra Rai

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Endophytic fungi from medicinal plants are important source of numerous pharmacologically important compounds. In the present investigation, the endophytic fungi were isolated from three medicinal plants; Andrographis paniculata, Rauwolfia serpentina and Tridax procumbens. Endophytic Colletotrichum sp. were identified on the basis of cultural and morphological characteristics as well as internal transcribed spacer (ITS) sequence analysis. Antibacterial and antifungal activity of the ethyl acetate and methanol extract of endophytic Colletotrichum sp. was evaluated against seven different human pathogenic bacteria and six Candida sp. The extracts were effective and showed significant activity against all the test pathogens. In case of yeast Candida, the combined effect of extracts and standard antibiotic was enhanced greatly showing synergistic activity. Further, the extracts were assayed for Minimum Inhibitory Concentration (MIC) and Minimum Bactericidal/Fungicidal Concentration (MBC/MFC) where, MIC values were in the range of 100-250 μg/ml. These results suggest that the endophytic Colletotrichum sp. isolated from the medicinal plants are capable of producing promising antimicrobial metabolites.

Keywords: antimicrobial, colletotrichum, endophytic fungi, medicinal plants

Procedia PDF Downloads 563

Authors: Aedah Abd Rahman, Nurdatillah Hasim

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Software quality issues require special attention especially in view of the demands of quality software product to meet customer satisfaction. Software development projects in most organisations need proper defect management process in order to produce high quality software product and reduce the number of defects. The research question of this study is how to produce high quality software and reducing the number of defects. Therefore, the objective of this paper is to provide a framework for managing software defects by following defined life cycle processes. The methodology starts by reviewing defects, defect models, best practices and standards. A framework for defect management life cycle is proposed. The major contribution of this study is to define a defect management road map in software development. The adoption of an effective defect management process helps to achieve the ultimate goal of producing high quality software products and contributes towards continuous software process improvement.

Keywords: defects, defect management, life cycle process, software quality

Procedia PDF Downloads 306

Authors: Prasad Kalagura, B. Veeresh kumar

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We constructed an interface system that would allow a similarly paralyzed user to interact with a computer with almost full functional capability. A real-time tracking algorithm is implemented based on adaptive skin detection and motion analysis. The clicking of the mouse is activated by the user's eye blinking through a sensor. The keyboard function is implemented by voice recognition kit.

Keywords: embedded ARM7 processor, mouse pointer control, voice recognition

Procedia PDF Downloads 579

Authors: Pitsanu Tongkhow, Pichet Jiraprasertwong

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This research investigates risk factors for defective products in autoparts factories. Under a Bayesian framework, a generalized linear mixed model (GLMM) in which the dependent variable, the number of defective products, has a Poisson distribution is adopted. Its performance is compared with the Poisson GLM under a Bayesian framework. The factors considered are production process, machines, and workers. The products coded RT50 are observed. The study found that the Poisson GLMM is more appropriate than the Poisson GLM. For the production Process factor, the highest risk of producing defective products is Process 1, for the Machine factor, the highest risk is Machine 5, and for the Worker factor, the highest risk is Worker 6.

Keywords: defective autoparts products, Bayesian framework, generalized linear mixed model (GLMM), risk factors

Procedia PDF Downloads 570

Authors: O. B. Iskender, K. V. Ling, V. Dubanchet, L. Simonini

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This paper presents a Guidance and Control (G&C) strategy to address spacecraft maneuvering problem for future Rendezvous and Docking (RVD) missions. The proposed strategy allows safe and propellant efficient trajectories for space servicing missions including tasks such as approaching, inspecting and capturing. This work provides the validation test results of the G&C laws using a Hardware-In-the-Loop (HIL) setup with two robotic mockups representing the chaser and the target spacecraft. Through this paper, the challenges of the relative motion control in space are first summarized, and in particular, the constraints imposed by the mission, spacecraft and, onboard processing capabilities. Second, the proposed algorithm is introduced by presenting the formulation of constrained Model Predictive Control (MPC) to optimize the fuel consumption and explicitly handle the physical and geometric constraints in the system, e.g. thruster or Line-Of-Sight (LOS) constraints. Additionally, the coupling between translational motion and rotational motion is addressed via dual quaternion based kinematic description and accordingly explained. The resulting convex optimization problem allows real-time implementation capability based on a detailed discussion on the computational time requirements and the obtained results with respect to the onboard computer and future trends of space processors capabilities. Finally, the performance of the algorithm is presented in the scope of a potential future mission and of the available equipment. The results also cover a comparison between the proposed algorithms with Linear–quadratic regulator (LQR) based control law to highlight the clear advantages of the MPC formulation.

Keywords: autonomous vehicles, embedded optimization, real-time experiment, rendezvous and docking, space robotics

Procedia PDF Downloads 125

Authors: Jayson Vicente

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The young men and women of Philippine Military Academy Cadet Corps Armed Forces of the Philippines (PMA CCAFP) are bred to be front liners and last line of defense during war and times of peace; as such, they must be equipped with the most practical and most effective combat-ready Martial Arts and Combative skills to effectively fulfill their duty, as well as to protect and safeguard themselves to continue serving the people and their country. This study shall assess the current Martial Arts and Combative Program of the PMA CCAFP using descriptive methodology by interviews and floating questionnaires. The current Martial Arts and Combative Program of the PMA CCAFP with all of the subjects involved are more sports inclined rather than combat-equipped. Picking the best from each subject used in the program, this study seeks to recommend improvements or create a better Martial Arts and Combative Program that will satisfy the objective of producing Martial Arts combatant graduates. A good Martial Arts and Combative Program for PMA is essential to prepare them for what lies ahead, which is unforgiving and no rules to pacify threat.

Keywords: combative, martial arts, military, program

Procedia PDF Downloads 151

Authors: T. Büyüksırıt, H. Kuleaşan

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Natural antimicrobials are used to preserve foods that can be found in plants, animals, and microorganisms. Antimicrobial substances are natural or artificial agents that produced by microorganisms or obtained semi/total chemical synthesis are used at low concentrations to inhibit the growth of other microorganisms. Food borne pathogens and spoilage microorganisms are inactivated by the use of antagonistic microorganisms and their metabolites. Yeasts can produce toxic proteins or glycoproteins (toxins) that cause inhibition of sensitive bacteria and yeast species. Antimicrobial substance producing phenotypes belonging different yeast genus were isolated from different sources. Toxins secreted by many yeast strains inhibiting the growth of other yeast strains. These strains show antimicrobial activity, inhibiting the growth of mold and bacteria. The effect of antimicrobial agents produced by yeasts can be extremely fast, and therefore may be used in various treatment procedures. Rapid inhibition of microorganisms is possibly caused by microbial cell membrane lipopolysaccharide binding and in activation (neutralization) effect. Antimicrobial agents inhibit the target cells via different mechanisms of action.

Keywords: antimicrobial agents, yeast, toxic protein, glycoprotein

Procedia PDF Downloads 368

Authors: Ali Mohagheghzadeh, Samad Vaez Badiegard, Bita Shomali

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Nowadays, with the increase in population, the need for protein sources is increasing. Different bacteria can cause food poisoning while most of the symptoms of food poisoning are similar to those of gastrointestinal infections. As a result, the diagnosis of bacteria and viruses causing food poisoning would not be possible without a stool culture. Cases of food poisoning are often accompanied by gastrointestinal disorders such as diarrhea, vomit, and gastrointestinal stomach cramps. Thus, providing enough food, taking into account health issues has always been a concern of authorities. Since E. coli bacterium is one of the important indicators of food hygiene and quality, producing food without being contaminated by this bacterium is desired in the food industry. This study aimed at assessing the E. coli contamination of poultry meat produced in slaughterhouses. Samples were taken from critical areas of slaughterhouses, namely the feather picking area, viscera and carcass evacuation area the area after cooling chillers. The results showed that 60% of contamination occurs in feather picking area. Among antiseptic and detergent materials, the highest reduction belongs to Epimax.

Keywords: slaughterhouse, E. coli, Epimax, contamination

Procedia PDF Downloads 710

Authors: Goksen Arik, Mihriban Korukluoglu

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Lactic acid bacteria (LAB) has been used commonly in the food industry. They can be used as natural preservatives because acidifying carried out in the medium can protect the last product against microbial spoilage. Besides, other metabolites produced by LAB during fermentation period have also an antimicrobial effect on pathogen and spoilage microorganisms in the food industry. LAB are responsible for the desirable and distinctive aroma and flavour which are observed in fermented food products such as pickle, kefir, yogurt, and cheese. Various LAB strains are able to produce B-group vitamins such as folate (B11), riboflavin (B2) and cobalamin (B12). Especially wild-type strains of LAB can produce B-group vitamins in high concentrations. These cultures may be used in food industry as a starter culture and also the microbial strains can be used in encapsulation technology for new and functional food product development. This review is based on the current applications of B-group vitamin producing LAB. Furthermore, the new technologies and innovative researches about B vitamin production in LAB have been demonstrated and discussed for determining their usage availability in various area in the food industry.

Keywords: B vitamin, food industry, lactic acid bacteria, starter culture, technology

Procedia PDF Downloads 390

Authors: F. Ghazalnaz Sharifonnasabi, Iman Makhdoom

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Breast cancer is a serious health concern that affects many people around the world. According to a study published in the Breast journal, the global burden of breast cancer is expected to increase significantly over the next few decades. The number of deaths from breast cancer has been increasing over the years, but the age-standardized mortality rate has decreased in some countries. It’s important to be aware of the risk factors for breast cancer and to get regular check- ups to catch it early if it does occur. Machin learning techniques have been used to aid in the early detection and diagnosis of breast cancer. These techniques, that have been shown to be effective in predicting and diagnosing the disease, have become a research hotspot. In this study, we consider two deep learning approaches including: Multi-Layer Perceptron (MLP), and Convolutional Neural Network (CNN). We also considered the five-machine learning algorithm titled: Decision Tree (C4.5), Naïve Bayesian (NB), Support Vector Machine (SVM), K-Nearest Neighbors (KNN) Algorithm and XGBoost (eXtreme Gradient Boosting) on the Breast Cancer Wisconsin Diagnostic dataset. We have carried out the process of evaluating and comparing classifiers involving selecting appropriate metrics to evaluate classifier performance and selecting an appropriate tool to quantify this performance. The main purpose of the study is predicting and diagnosis breast cancer, applying the mentioned algorithms and also discovering of the most effective with respect to confusion matrix, accuracy and precision. It is realized that CNN outperformed all other classifiers and achieved the highest accuracy (0.982456). The work is implemented in the Anaconda environment based on Python programing language.

Keywords: breast cancer, multi-layer perceptron, Naïve Bayesian, SVM, decision tree, convolutional neural network, XGBoost, KNN

Procedia PDF Downloads 79

Authors: Rashidah Ghazali, Herlina Abdul Rahim, Mashitah Shikh Maidin, Shafishuhaza Sahlan, Noramli Abdul Razak

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Sound exposure effects have been investigated by broadcasting a group of broilers with sound of Quran verses (Group B) whereas the other group is the control broilers (Group C). The growth rate comparisons in terms of weight and raw meat texture measured by shear force have been investigated. Twenty-seven broilers were randomly selected from each group on Day 24 and weight measurement was carried out every week till the harvest day (Day 39). Group B showed a higher mean weight on Day 24 (1.441±0.013 kg) than Group C. Significant difference in the weight on Day 39 existed for Group B compared to Group C (p< 0.05). However, there was no significant (p> 0.05) difference of shear force in the same muscles (breast and drumstick raw meat) of both groups but the shear force of the breast meat for Group B and C broilers was lower (p < 0.05) than that of their drumstick meat. Thus, broadcasting the sound of Quran verses in the coop can be applied to improve the growth rate of broilers for producing better quality poultry.

Keywords: broilers, sound, shear force, weight

Procedia PDF Downloads 420

Authors: Keivan Saeb, Azade Kakouei, Razieh Jafari Hajati, Khalil Pourshamsian, Babak Babakhani

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Urtica Diocia L. from the Urticaceae family is a plant of herbal value and of a noticeable distribution in the north of Iran. The growth of different plants in various natural environments and ecosystems seems to be affected by factors such as the height (from sea surface).To investigate the effect of height on Urtica Diocia L. medicine compounds in its natural environment, three areas with the height of zero, 800 and 1800m were selected.The samples were randomly gathered three times and were dried; also, their compounds was extracted using the Clivenger with the water-distilling method. To determine the medicine compounds, the GC-MS as well as the GC machines were used. The analysis of variance was done in the form of the random-full-block design. The results indicated that there was a significant difference between the percent of EOs in the selected heights; however, such difference was not significant within each height. From among the eight flavors of the study, the phytol compound was more in terms of percentage. By increasing the height the percent of EOs would decrease. lower heights could be considered most appropriate for producing the studied effective materials despite of the moistened climate and soil there.

Keywords: Urtica diocia L., height, EOs, medicine

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Authors: Seyedamir Makinejadsanij

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One of the most important factors in the production of quality steel is to know the exact weight of steel in the steelmaking area. In this study, a calculation method is presented to estimate the exact weight of the melt as well as the objects transported by the overhead crane. Iran Alloy Steel Company's steelmaking area has three 90-ton cranes, which are responsible for transferring the ladles and ladle caps between 34 areas in the melt shop. Each crane is equipped with a Disomat Tersus weighing system that calculates and displays real-time weight. The moving object has a variable weight due to swinging, and the weighing system has an error of about +-5%. This means that when the object is moving by a crane, which weighs about 80 tons, the device (Disomat Tersus system) calculates about 4 tons more or 4 tons less, and this is the biggest problem in calculating a real weight. The k-means algorithm is an unsupervised clustering method that was used here. The best result was obtained by considering 3 centers. Compared to the normal average(one) or two, four, five, and six centers, the best answer is with 3 centers, which is logically due to the elimination of noise above and below the real weight. Every day, the standard weight is moved with working cranes to test and calibrate cranes. The results are shown that the accuracy is about 40 kilos per 60 tons (standard weight). As a result, with this method, the accuracy of moving weight is calculated as 99.95%. K-means is used to calculate the exact mean of objects. The stopping criterion of the algorithm is also the number of 1000 repetitions or not moving the points between the clusters. As a result of the implementation of this system, the crane operator does not stop while moving objects and continues his activity regardless of weight calculations. Also, production speed increased, and human error decreased.

Keywords: k-means, overhead crane, melt weight, weight estimation, swing problem

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Authors: Carlos Gonzalez, Ernesto Linan

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We propose a methodology to conciliate two apparently contradictory processes in the development of secure obfuscated software and good software engineered software. Our methodology consists first in the system designers defining the type of security level required for the software. There are four types of attackers: casual attackers, hackers, institution attack, and government attack. Depending on the level of threat, the methodology we propose uses five or six teams to accomplish this task. One Software Engineer Team and one or two software Obfuscation Teams, and Compiler Team, these four teams will develop and compile the secure obfuscated software, a Code Breakers Team will test the results of the previous teams to see if the software is not broken at the required security level, and an Intrusion Analysis Team will analyze the results of the Code Breakers Team and propose solutions to the development teams to prevent the detected intrusions. We also present an analytical model to prove that our methodology is no only easier to use, but generates an economical way of producing secure obfuscated software.

Keywords: development methodology, obfuscated software, secure software development, software engineering

Procedia PDF Downloads 253

Authors: Supriyono, Sumardiyono, Rendy J. Pramono

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Biodiesel is one of the alternative fuels promising for substituting petrodiesel as energy source which has an advantage as it is sustainable and eco-friendly. Due to the raw material that tends to decompose during storage, biodiesel also has the same characteristic that tends to decompose during storage. Biodiesel decomposition will form higher acid value as the result of oxidation to double bond on a fatty acid compound on biodiesel. Thus, free fatty acid value could be used to evaluate degradation of biodiesel due to the oxidation process. High free fatty acid on biodiesel could impact on the engine performance. Decomposition of biodiesel due to oxidation reaction could prevent by introducing a small amount of antioxidant. The origin of raw materials and the process for producing biodiesel will determine the effectiveness of antioxidant. Biodiesel made from high free fatty acid (FFA) crude palm oil (CPO) by using two steps esterification is vulnerable to oxidation process which is resulted in increasing on the FFA value. Tocopherol also known as vitamin E is one of the antioxidant that could improve the stability of biodiesel due to decomposition by the oxidation process. Tocopherol 0.5% concentration on palm oil biodiesel could reduce 13% of increasing FFA under temperature 80 °C and exposing time 180 minute.

Keywords: antioxidant, palm oil biodiesel, decomposition, oxidation, tocopherol

Procedia PDF Downloads 357

Authors: Xiaohong Yang, Haitao Fu, Xizhong An, Aibing Yu

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Silver@titanium dioxide (Ag@TiO2) core-shell nanostructures and Ag surface doped TiO2 particles (TiO2@Ag) have been designed and synthesized by sol-gel and hydrothermal methods under mild conditions. These two types of Ag/TiO2 nanocomposites were characterized in terms of their properties by various techniques such as transmission electron microscope (TEM), X-ray diffraction (XRD), Brunauer Emmett Teller (BET) and ultra violet-visible absorption spectroscopy (UV-Vis). Specifically, the photocatalystic performance and antibacterial behavior of such nanocomposites have been investigated and compared. It was found that The Ag@TiO2 core-shell nanostructures exhibit superior photocatalytic property to the Ag surface doped TiO2 particles under the reported conditions. While with UV pre-irradiation, the Ag@TiO2 core-shell composites exhibit better bactericidal performance. This is probably because the Ag cores tend to facilitate charge separation for TiO2, producing greater hydroxyl radicals on the surface of the TiO2 particles. These findings would be useful for the design and synthesis of Ag/TiO2 nanocomposites with desirable photocatalystic and antimicrobial activity for environmental applications.

Keywords: Ag@TiO2 core-shell nanoparticles, Ag surface doped TiO2 nanoparticles, photocatalysis, antibacterial

Procedia PDF Downloads 486

Authors: Fatemeh Babaeian, Nemai Chandra Karmakar

Abstract:

Chipless RFID system is a wireless system for tracking and identification which use passive tags for encoding data. The advantage of using chipless RFID tag is having a planar tag which is printable on different low-cost materials like paper and plastic. The printed tag can be attached to different items in the labelling level. Since the price of chipless RFID tag can be as low as a fraction of a cent, this technology has the potential to compete with the conventional optical barcode labels. However, due to the passive structure of the tag, data processing of the reflection signal is a crucial challenge. The captured reflected signal from a tag attached to an item consists of different components which are the reflection from the reader antenna, the reflection from the item, the tag structural mode RCS component and the antenna mode RCS of the tag. All these components are summed up in both time and frequency domains. The effect of reflection from the item and the structural mode RCS component can distort/saturate the frequency domain signal and cause difficulties in extracting the desired component which is the antenna mode RCS. Therefore, it is required to study the reflection of the tag in both time and frequency domains to have a better understanding of the nature of the captured chipless RFID signal. The other benefits of this study can be to find an optimised encoding technique in tag design level and to find the best processing algorithm the chipless RFID signal in decoding level. In this paper, the reflection from a typical backscattered chipless RFID tag with six resonances is analysed, and different components of the signal are separated in both time and frequency domains. Moreover, the time domain signal corresponding to each resonator of the tag is studied. The data for this processing was captured from simulation in CST Microwave Studio 2017. The outcome of this study is understanding different components of a measured signal in a chipless RFID system and a discovering a research gap which is a need to find an optimum detection algorithm for tag ID extraction.

Keywords: antenna mode RCS, chipless RFID tag, resonance, structural mode RCS

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Authors: Natascha C. D'Amico, Enzo Grossi, Giovanni Valbusa, Ala Malasevschi, Gianpiero Cardone, Sergio Papa

Abstract:

Purpose: To characterize, through a radiomic approach, the nature of areas classified PI-RADS (Prostate Imaging Reporting and Data System) 3/5, recognized in multiparametric prostate magnetic resonance with T2-weighted (T2w), diffusion and perfusion sequences with paramagnetic contrast. Methods and Materials: 24 cases undergoing multiparametric prostate MR and biopsy were admitted to this pilot study. Clinical outcome of the PI-RADS 3/5 was found through biopsy, finding 8 malignant tumours. The analysed images were acquired with a Philips achieva 1.5T machine with a CE- T2-weighted sequence in the axial plane. Semi-automatic tumour segmentation was carried out on MR images using 3DSlicer image analysis software. 45 shape-based, intensity-based and texture-based features were extracted and represented the input for preprocessing. An evolutionary algorithm (a TWIST system based on KNN algorithm) was used to subdivide the dataset into training and testing set and select features yielding the maximal amount of information. After this pre-processing 20 input variables were selected and different machine learning systems were used to develop a predictive model based on a training testing crossover procedure. Results: The best machine learning system (three-layers feed-forward neural network) obtained a global accuracy of 90% ( 80 % sensitivity and 100% specificity ) with a ROC of 0.82. Conclusion: Machine learning systems coupled with radiomics show a promising potential in distinguishing benign from malign tumours in PI-RADS 3/5 areas.

Keywords: machine learning, MR prostate, PI-Rads 3, radiomics

Procedia PDF Downloads 189

Authors: Dnyanesh P. Mathur, Gregory L. Slater

Abstract:

Gravitation and the expansion of the universe at a large scale are generally regarded as two completely distinct phenomena. Yet, in general, relativity theory, they both manifest as 'curvature' of spacetime. We propose a hypothesis which treats these two 'curvature-producing' phenomena as aspects of an underlying process. This process treats spacetime itself as composed of discrete units (Plancktons) and is 'dynamic' in the sense that these elements of spacetime are continually being both created and annihilated. It is these two complementary processes of Planckton creation and Planckton annihilation which manifest themselves as - 'cosmic expansion' on the one hand and as 'gravitational attraction’ on the other. The Planckton hypothesis treats spacetime as a perfect fluid in the same manner as the co-moving frame of reference of Friedman equations and the Gullstrand-Painleve metric; i.e.Planckton hypothesis replaces 'curvature' of spacetime by the 'flow' of Plancktons (spacetime). Here we discuss how this perspective may allow a unified description of both cosmological and gravitational acceleration as well as providing a mechanism for inducing an irreducible action at every point associated with the creation and annihilation of Plancktons, which could be identified as the zero point energy.

Keywords: discrete spacetime, spacetime flow, zero point energy, planktons

Procedia PDF Downloads 115