Search results for: human machine interface
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11676

Search results for: human machine interface

8436 A Novel Machine Learning Approach to Aid Agrammatism in Non-fluent Aphasia

Authors: Rohan Bhasin

Abstract:

Agrammatism in non-fluent Aphasia Cases can be defined as a language disorder wherein a patient can only use content words ( nouns, verbs and adjectives ) for communication and their speech is devoid of functional word types like conjunctions and articles, generating speech of with extremely rudimentary grammar . Past approaches involve Speech Therapy of some order with conversation analysis used to analyse pre-therapy speech patterns and qualitative changes in conversational behaviour after therapy. We describe this approach as a novel method to generate functional words (prepositions, articles, ) around content words ( nouns, verbs and adjectives ) using a combination of Natural Language Processing and Deep Learning algorithms. The applications of this approach can be used to assist communication. The approach the paper investigates is : LSTMs or Seq2Seq: A sequence2sequence approach (seq2seq) or LSTM would take in a sequence of inputs and output sequence. This approach needs a significant amount of training data, with each training data containing pairs such as (content words, complete sentence). We generate such data by starting with complete sentences from a text source, removing functional words to get just the content words. However, this approach would require a lot of training data to get a coherent input. The assumptions of this approach is that the content words received in the inputs of both text models are to be preserved, i.e, won't alter after the functional grammar is slotted in. This is a potential limit to cases of severe Agrammatism where such order might not be inherently correct. The applications of this approach can be used to assist communication mild Agrammatism in non-fluent Aphasia Cases. Thus by generating these function words around the content words, we can provide meaningful sentence options to the patient for articulate conversations. Thus our project translates the use case of generating sentences from content-specific words into an assistive technology for non-Fluent Aphasia Patients.

Keywords: aphasia, expressive aphasia, assistive algorithms, neurology, machine learning, natural language processing, language disorder, behaviour disorder, sequence to sequence, LSTM

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8435 Modal FDTD Method for Wave Propagation Modeling Customized for Parallel Computing

Authors: H. Samadiyeh, R. Khajavi

Abstract:

A new FD-based procedure, modal finite difference method (MFDM), is proposed for seismic wave propagation modeling, in which simulation is dealt with in the modal space. The method employs eigenvalues of a characteristic matrix formed by appropriate time-space FD stencils. Since MFD runs for different modes are totally independent of each other, MFDM can easily be parallelized while considerable simplicity in parallel-algorithm is also achieved. There is no requirement to any domain-decomposition procedure and inter-core data exchange. More important is the possibility to skip processing of less-significant modes, which enables one to adjust the procedure up to the level of accuracy needed. Thus, in addition to considerable ease of parallel programming, computation and storage costs are significantly reduced. The method is qualified for its efficiency by some numerical examples.

Keywords: Finite Difference Method, Graphics Processing Unit (GPU), Message Passing Interface (MPI), Modal, Wave propagation

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8434 Determination of Slope of Hilly Terrain by Using Proposed Method of Resolution of Forces

Authors: Reshma Raskar-Phule, Makarand Landge, Saurabh Singh, Vijay Singh, Jash Saparia, Shivam Tripathi

Abstract:

For any construction project, slope calculations are necessary in order to evaluate constructability on the site, such as the slope of parking lots, sidewalks, and ramps, the slope of sanitary sewer lines, slope of roads and highways. When slopes and grades are to be determined, designers are concerned with establishing proper slopes and grades for their projects to assess cut and fill volume calculations and determine inverts of pipes. There are several established instruments commonly used to determine slopes, such as Dumpy level, Abney level or Hand Level, Inclinometer, Tacheometer, Henry method, etc., and surveyors are very familiar with the use of these instruments to calculate slopes. However, they have some other drawbacks which cannot be neglected while major surveying works. Firstly, it requires expert surveyors and skilled staff. The accessibility, visibility, and accommodation to remote hilly terrain with these instruments and surveying teams are difficult. Also, determination of gentle slopes in case of road and sewer drainage constructions in congested urban places with these instruments is not easy. This paper aims to develop a method that requires minimum field work, minimum instruments, no high-end technology or instruments or software, and low cost. It requires basic and handy surveying accessories like a plane table with a fixed weighing machine, standard weights, alidade, tripod, and ranging rods should be able to determine the terrain slope in congested areas as well as in remote hilly terrain. Also, being simple and easy to understand and perform the people of that local rural area can be easily trained for the proposed method. The idea for the proposed method is based on the principle of resolution of weight components. When any object of standard weight ‘W’ is placed on an inclined surface with a weighing machine below it, then its cosine component of weight is presently measured by that weighing machine. The slope can be determined from the relation between the true or actual weight and the apparent weight. A proper procedure is to be followed, which includes site location, centering and sighting work, fixing the whole set at the identified station, and finally taking the readings. A set of experiments for slope determination, mild and moderate slopes, are carried out by the proposed method and by the theodolite instrument in a controlled environment, on the college campus, and uncontrolled environment actual site. The slopes determined by the proposed method were compared with those determined by the established instruments. For example, it was observed that for the same distances for mild slope, the difference in the slope obtained by the proposed method and by the established method ranges from 4’ for a distance of 8m to 2o15’20” for a distance of 16m for an uncontrolled environment. Thus, for mild slopes, the proposed method is suitable for a distance of 8m to 10m. The correlation between the proposed method and the established method shows a good correlation of 0.91 to 0.99 for various combinations, mild and moderate slope, with the controlled and uncontrolled environment.

Keywords: surveying, plane table, weight component, slope determination, hilly terrain, construction

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8433 Issues in Organizational Assessment: The Case of Frustration Tolerance Measurement in Mexico

Authors: David Ruiz, Carlos Nava, Roberto Carbajal

Abstract:

The psychological profile has become one of the most important sources of information when it comes to individual selection and the hiring process in any organization. Psychological instruments are used to collect data about variables that are considered critically important for performance in work. However, because of conceptual chaos in organizational psychology, most of the information provided by psychological testing is not directly useful for Mexican human resources professionals to take hiring decisions. The aims of this paper are 1) to underline the lack of conceptual precision in theoretical testing foundations in Mexico and 2) presenting a reliability and validity analysis of a frustration tolerance instrument created as an alternative to a heuristically conduct individual assessment in organizations. First, a description of assessment conditions in Mexico is made. Second, an instrument and a theoretical framework is presented as an alternative to the assessment practices in the country. A total of 65 Psychology Iztacala Superior Studies Faculty students were assessed. Cronbach´s alpha coefficient was calculated and an exploratory factor analysis was carried out to prove the scale unidimensionality. Reliability analysis revealed good internal consistency of the scale (Cronbach’s α = 0.825). Factor analysis produced 4 factors for the scale. However, factor loadings and explained variation give proof to the scale unidimensionality. It is concluded that the instrument has good psychometric properties that will allow human resources professionals to collect useful data. Different possibilities to conduct psychological assessment are suggested for future development.

Keywords: psychological assessment, frustration tolerance, human resources, organizational psychology

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8432 Toxicological Interactions of Silver Nanoparticles and Non-Essential Metals in Human Hepatocarcinoma Cell Line

Authors: Renata Rank Miranda, Arandi Ginane Bezerra, Ciro Alberto Oliveira Ribeiro, Marco AntôNio Ferreira Randi, Carmen Lúcia Voigt, Lilian Skytte, Kaare Lund Rasmussen, Francisco Filipak Neto, Frank Kjeldsen

Abstract:

Synergetic and antagonistic effects of drugs are well-known concerns in pharmacological assessments of dose and toxicity. Similar approach should be used in assessing cellular uptake and cytotoxicity of nanoparticles. Since nanoparticles are released into the aquatic environment they may interact with existing xenobiotics. Here we used biochemical assays and quantitative proteomics to assess the cytotoxicity of silver nanoparticles (AgNP) when human hepatoma HepG2 cells were co-exposed to 2 nm AgNP together with either Cd2+ or Hg2+ ions. Time-course experiments (2h, 4h, and 24h) were conducted to assess the first response to the exposure studies. The general trend was that a synergetic toxicological response was observed in cells exposed to both AgNP and Cd2+ or Hg2+, with AgNP and Cd2+ being more toxic. This was observed by a significant increase in the ROS and superoxide level of >35% in the case of AgNP+Cd2+ compared to the sum of responses of AgNP and Cd2+, individually. Metabolic activity and viability also dropped more for AgNP+Cd2+ (>10%) than for AgNP and Cd2+ combined. We used inductively coupled plasma mass spectrometry to investigate if AgNP facilitates larger influx of toxic metal ions into HepG2 cells. Only Hg2+ ions was found to be more efficiently engulfed as the concentration of Hg2+ was found 2.8 times larger compared to exposure experiments with only Hg2+. This effect was not observed for Cd2+. We now continue with deep proteomics studies to obtain wider details on the mechanism of the toxicity related to AgNP, Cd2+, and AgNP+Cd2+, respectively.

Keywords: nanotoxicology, silver nanoparticles, proteomics, human cell line

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8431 The Effect of Fly Ash in Dewatering of Marble Processing Wastewaters

Authors: H. A. Taner, V. Önen

Abstract:

In the thermal power plants established to meet the energy need, lignite with low calorie and high ash content is used. Burning of these coals results in wastes such as fly ash, slag and flue gas. This constitutes a significant economic and environmental problems. However, fly ash can find evaluation opportunities in various sectors. In this study, the effectiveness of fly ash on suspended solid removal from marble processing wastewater containing high concentration of suspended solids was examined. Experiments were carried out for two different suspensions, marble and travertine. In the experiments, FeCl3, Al2(SO4)3 and anionic polymer A130 were used also to compare with fly ash. Coagulant/flocculant type/dosage, mixing time/speed and pH were the experimental parameters. The performances in the experimental studies were assessed with the change in the interface height during sedimentation resultant and turbidity values of treated water. The highest sedimentation efficiency was achieved with anionic flocculant. However, it was determined that fly ash can be used instead of FeCl3 and Al2(SO4)3 in the travertine plant as a coagulant.

Keywords: dewatering, flocculant, fly ash, marble plant wastewater

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8430 Prevention and Treatment of Hay Fever Prevalence by Natural Products: A Phytochemistry Study on India and Iran

Authors: Tina Naser Torabi

Abstract:

Prevalence of allergy is affected by different factors according to its base and seasonal weather changes, and it also needs various treatments.Although reasons of allergy existence are not clear but generally, allergens cause reaction between antigen and antibody because of their antigenic traits. In this state, allergens cause immune system to make mistake and identify safe material as threat, therefore function of immune system impaired because of histamine secretion. There are different reasons for allergy, but herbal reasons are on top of the list, although animal causes cannot be ignored. Important point is that allergenic compounds, cause making dedicated antibody, so in general every kind of allergy is different from the other one. Therefore, most of the plants in herbal allergenic category can cause various allergies for human beings, such as respiratory allergies, nutritional allergies, injection allergies, infection allergies, touch allergies, that each of them show different symptoms based on the reason of allergy and also each of them requires different prevention and treatment. Geographical condition is another effective factor in allergy. Seasonal changes, weather condition, herbal coverage variety play important roles in different allergies. It goes without saying that humid climate and herbal coverage variety in different seasons especially spring cause most allergies in human beings in Iran and India that are discussed in this article. These two countries are good choices for allergy prevalence because of their condition, various herbal coverage, human and animal factors. Hay fever is one of the allergies, although the reasons of its prevalence are unknown yet. It is one of the most popular allergies in Iran and India because of geographical, human, animal and herbal factors. Hay fever is on top of the list in these two countries. Significant point about these two countries is that herbal factor is the most important factor in prevalence of hay fever. Variety of herbal coverage especially in spring during herbal pollination is the main reason of hay fever prevalence in these two countries. Based on the research result of Pharmacognosy and Phytochemistry, pollination of some plants in spring is major reason of hay fever prevalence in these countries. If airborne pollens in pollination season enter the human body through air, they will cause allergic reactions in eyes, nasal mucosa, lungs, and respiratory system, and if these particles enter the body of potential person through food, they will cause allergic reactions in mouth, stomach, and other digestive systems. Occasionally, chemical materials produced by human body such as Histamine cause problems like: developing of nasal polyps, nasal blockage, sleep disturbance, risk of asthma developing, blood vasodilation, sneezing, eye tears, itching and swelling of eyes and nasal mucosa, Urticaria, decrease in blood pressure, and rarely trauma, anesthesia, anaphylaxis and finally death. This article is going to study the reasons of hay fever prevalence in Iran and India and presents prevention and treatment Method from Phytochemistry and Pharmocognocy point of view by using local natural products in these two countries.

Keywords: hay fever, India, Iran, natural treatment, phytochemistry

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8429 [Keynote Talk]: Formal Specification and Description Language and Message Sequence Chart to Model and Validate Session Initiation Protocol Services

Authors: Sa’ed Abed, Mohammad H. Al Shayeji, Ovais Ahmed, Sahel Alouneh

Abstract:

Session Initiation Protocol (SIP) is a signaling layer protocol for building, adjusting and ending sessions among participants including Internet conferences, telephone calls and multimedia distribution. SIP facilitates user movement by proxying and forwarding requests to the present location of the user. In this paper, we provide a formal Specification and Description Language (SDL) and Message Sequence Chart (MSC) to model and define the Internet Engineering Task Force (IETF) SIP protocol and its sample services resulted from informal SIP specification. We create an “Abstract User Interface” using case analysis so that can be applied to identify SIP services more explicitly. The issued sample SIP features are then used as case scenarios; they are revised in MSCs format and validated to their corresponding SDL models.

Keywords: modeling, MSC, SDL, SIP, validating

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8428 The Potential of Fly Ash Wastes to Improve Nutrient Levels in Agricultural Soils: A Material Flow Analysis Case Study from Riau District, Indonesia

Authors: Hasan Basri Jumin

Abstract:

Fly ash sewage of pulp and paper industries when processed with suitable process and true management may possibly be used fertilizer agriculture purposes. The objective of works is to evaluate re-cycling possibility of fly ash waste to be applied as a fertilizer for agriculture use. Fly ash sewage was applied to maize with 28 g/plant could be increased significantly the average of dry weigh from dry weigh of seed increase from 6.7 g/plant into 10.3 g/plant, and net assimilation rates could be increased from 14.5 mg.m-2.day-1 into 35.4 mg.m-2 day-1. Therefore, production per hectare was reached 3.2 ton/ha. The chemical analyses of fly ash waste indicated that, there are no exceed threshold content of dangerous metals and biology effects. Mercury, arsenic, cadmium, chromium, cobalt, lead, and molybdenum contents as heavy metal are lower than the threshold of human healthy tolerance. Therefore, it has no syndrome effect to human health. This experiment indicated that fly ash sewage in lower doses until 28 g/plant could be applied as substitution fertilizer for agriculture use and it could be eliminate the environment pollution.

Keywords: fly-ash, fertilizer, maize, sludge-sewage pollutant, waste

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8427 Human Rights and Fundamental Freedoms in Crisis as Viewed during Bangladesh Parliamentary Election-2018 and Afterwards: A Contestant's Perspective on Social Measures

Authors: Mohammad S. Islam

Abstract:

Elections in Bangladesh are always controversial, and sometimes it becomes a violent affair when state power is combined with politics. Despite the commitment of the ruling party- the polling government to ensure free, fair, and credible elections, the participants of opposition parties and the general voters became very disappointed, terribly frustrated, and severely shocked. It happened when numerous claims of serious irregularities of vote rigging and violence came out in broad daylight during the election. This paper addresses the issues of how the ruling party created frightening and a horror situation to make people silent over electoral fraud and violent incidents, including gang rape. It also seeks to demonstrate that election-2018 was simply the deceptive action of the ruling party to legitimate their power, but not to provide a minimum opportunity for voters to exercise their fundamental right to vote. The fundamental freedom and the rule of law seemed to be ignored completely in this election process and afterwards. With the help of state machinery, the government of the ruling party violated human rights, restricted fundamental freedoms, and humiliated social protection & dignity. The contestant’s views as witnessed and relevant literatures are cited first for conceptual understanding. Then, the paper will examine how a new dimension of circumstantial social measures related to sustained protection can reduce all kinds of violence against humanity towards establishing a peaceful democratic society. Finally, this paper interprets the key findings and considers wider implications.

Keywords: electoral fraud, human rights, sustained protection, social measures, vote rigging

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8426 A Simulated Scenario of WikiGIS to Support the Iteration and Traceability Management of the Geodesign Process

Authors: Wided Batita, Stéphane Roche, Claude Caron

Abstract:

Geodesign is an emergent term related to a new and complex process. Hence, it needs to rethink tools, technologies and platforms in order to efficiently achieve its goals. A few tools have emerged since 2010 such as CommunityViz, GeoPlanner, etc. In the era of Web 2.0 and collaboration, WikiGIS has been proposed as a new category of tools. In this paper, we present WikiGIS functionalities dealing mainly with the iteration and traceability management to support the collaboration of the Geodesign process. Actually, WikiGIS is built on GeoWeb 2.0 technologies —and primarily on wiki— and aims at managing the tracking of participants’ editing. This paper focuses on a simplified simulation to illustrate the strength of WikiGIS in the management of traceability and in the access to history in a Geodesign process. Indeed, a cartographic user interface has been implemented, and then a hypothetical use case has been imagined as proof of concept.

Keywords: geodesign, history, traceability, tracking of participants’ editing, WikiGIS

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8425 Early Diagnosis of Myocardial Ischemia Based on Support Vector Machine and Gaussian Mixture Model by Using Features of ECG Recordings

Authors: Merve Begum Terzi, Orhan Arikan, Adnan Abaci, Mustafa Candemir

Abstract:

Acute myocardial infarction is a major cause of death in the world. Therefore, its fast and reliable diagnosis is a major clinical need. ECG is the most important diagnostic methodology which is used to make decisions about the management of the cardiovascular diseases. In patients with acute myocardial ischemia, temporary chest pains together with changes in ST segment and T wave of ECG occur shortly before the start of myocardial infarction. In this study, a technique which detects changes in ST/T sections of ECG is developed for the early diagnosis of acute myocardial ischemia. For this purpose, a database of real ECG recordings that contains a set of records from 75 patients presenting symptoms of chest pain who underwent elective percutaneous coronary intervention (PCI) is constituted. 12-lead ECG’s of the patients were recorded before and during the PCI procedure. Two ECG epochs, which are the pre-inflation ECG which is acquired before any catheter insertion and the occlusion ECG which is acquired during balloon inflation, are analyzed for each patient. By using pre-inflation and occlusion recordings, ECG features that are critical in the detection of acute myocardial ischemia are identified and the most discriminative features for the detection of acute myocardial ischemia are extracted. A classification technique based on support vector machine (SVM) approach operating with linear and radial basis function (RBF) kernels to detect ischemic events by using ST-T derived joint features from non-ischemic and ischemic states of the patients is developed. The dataset is randomly divided into training and testing sets and the training set is used to optimize SVM hyperparameters by using grid-search method and 10fold cross-validation. SVMs are designed specifically for each patient by tuning the kernel parameters in order to obtain the optimal classification performance results. As a result of implementing the developed classification technique to real ECG recordings, it is shown that the proposed technique provides highly reliable detections of the anomalies in ECG signals. Furthermore, to develop a detection technique that can be used in the absence of ECG recording obtained during healthy stage, the detection of acute myocardial ischemia based on ECG recordings of the patients obtained during ischemia is also investigated. For this purpose, a Gaussian mixture model (GMM) is used to represent the joint pdf of the most discriminating ECG features of myocardial ischemia. Then, a Neyman-Pearson type of approach is developed to provide detection of outliers that would correspond to acute myocardial ischemia. Neyman – Pearson decision strategy is used by computing the average log likelihood values of ECG segments and comparing them with a range of different threshold values. For different discrimination threshold values and number of ECG segments, probability of detection and probability of false alarm values are computed, and the corresponding ROC curves are obtained. The results indicate that increasing number of ECG segments provide higher performance for GMM based classification. Moreover, the comparison between the performances of SVM and GMM based classification showed that SVM provides higher classification performance results over ECG recordings of considerable number of patients.

Keywords: ECG classification, Gaussian mixture model, Neyman–Pearson approach, support vector machine

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8424 Strategies for Tackling Climate Change: Review of Sustainability and Air-Conditioning

Authors: Tosin T. Oye, Keng Goh, Naren Gupta, Toyosi K. Oye

Abstract:

One of the most extreme difficulties confronting humankind in the twenty-first century is the consumption of energy. Non-renewable energy sources have been the fundamental energy assets for human culture. The consumption of energy sources emanating from the use of air-conditioning is still causing and has caused harm to the environment and human health. The request for energy could be double or perhaps triple in the future because of the utilization of air-conditioning systems as the worldwide population develops and emerging districts grow their economics. This has recently raised worries in sustainable development over climate change, global warming, ozone layer reduction, health issues, and possible supply problems. As a result of the improvement of way of life, air-conditioning has generally been applied. Nevertheless, environmental pollutions and health issues related with the use of air-conditioning unfolds more as often as possible. In order to diminish their level of undesirable impact on the environment, it is essential to establish suitable strategies for tackling climate change. Therefore, this paper aims to review and analyze studies in sustainability and air- conditioning and subsequently suggest strategies for combatting climate change. Future perspectives for tackling climate change are likewise suggested. The key findings revealed that it is required to establish sustainability measures to reduce the level of energy consumption and carbon emissions in a bid to effectively tackle climate change and its impact on the environment, and then raise public alertness towards the adverse impact of climate change arising from the use of air-conditioning systems. The research outcome offers valuable awareness to the general public, organizations, policymakers, and the government in making future municipal zones sustainable and more climate resilient.

Keywords: air-conditioning, climate change, environment, human health, sustainability

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8423 Inversely Designed Chipless Radio Frequency Identification (RFID) Tags Using Deep Learning

Authors: Madhawa Basnayaka, Jouni Paltakari

Abstract:

Fully passive backscattering chipless RFID tags are an emerging wireless technology with low cost, higher reading distance, and fast automatic identification without human interference, unlike already available technologies like optical barcodes. The design optimization of chipless RFID tags is crucial as it requires replacing integrated chips found in conventional RFID tags with printed geometric designs. These designs enable data encoding and decoding through backscattered electromagnetic (EM) signatures. The applications of chipless RFID tags have been limited due to the constraints of data encoding capacity and the ability to design accurate yet efficient configurations. The traditional approach to accomplishing design parameters for a desired EM response involves iterative adjustment of design parameters and simulating until the desired EM spectrum is achieved. However, traditional numerical simulation methods encounter limitations in optimizing design parameters efficiently due to the speed and resource consumption. In this work, a deep learning neural network (DNN) is utilized to establish a correlation between the EM spectrum and the dimensional parameters of nested centric rings, specifically square and octagonal. The proposed bi-directional DNN has two simultaneously running neural networks, namely spectrum prediction and design parameters prediction. First, spectrum prediction DNN was trained to minimize mean square error (MSE). After the training process was completed, the spectrum prediction DNN was able to accurately predict the EM spectrum according to the input design parameters within a few seconds. Then, the trained spectrum prediction DNN was connected to the design parameters prediction DNN and trained two networks simultaneously. For the first time in chipless tag design, design parameters were predicted accurately after training bi-directional DNN for a desired EM spectrum. The model was evaluated using a randomly generated spectrum and the tag was manufactured using the predicted geometrical parameters. The manufactured tags were successfully tested in the laboratory. The amount of iterative computer simulations has been significantly decreased by this approach. Therefore, highly efficient but ultrafast bi-directional DNN models allow rapid and complicated chipless RFID tag designs.

Keywords: artificial intelligence, chipless RFID, deep learning, machine learning

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8422 In vitro Bioacessibility of Phenolic Compounds from Fruit Spray Dried and Lyophilized Powder

Authors: Carolina Beres, Laurine Da Silva, Danielle Pereira, Ana Ribeiro, Renata Tonon, Caroline Mellinger-Silva, Karina Dos Santos, Flavia Gomes, Lourdes Cabral

Abstract:

The health benefits of bioactive compounds such as phenolics are well known. The main source of these compounds are fruits and derivates. This study had the objective to study the bioacessibility of phenolic compounds from grape pomace and juçara dried extracts. For this purpose both characterized extracts were submitted to a simulated human digestion and the total phenolic content, total anthocyanins and antioxidant scavenging capacity was determinate in digestive fractions (oral, gastric, intestinal and colonic). Juçara had a higher anthocianins bioacessibility (17.16%) when compared to grape pomace (2.08%). The opposite result was found for total phenolic compound, where the higher bioacessibility was for grape (400%). The phenolic compound increase indicates a more accessible compound in the human gut. The lyophilized process had a beneficial impact in the final accessibility of the phenolic compounds being a more promising technique.

Keywords: bioacessibility, phenolic compounds, grape, juçara

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8421 3D Human Face Reconstruction in Unstable Conditions

Authors: Xiaoyuan Suo

Abstract:

3D object reconstruction is a broad research area within the computer vision field involving many stages and still open problems. One of the existing challenges in this field lies with micromotion, such as the facial expressions on the appearance of the human or animal face. Similar literatures in this field focuses on 3D reconstruction in stable conditions such as an existing image or photos taken in a rather static environment, while the purpose of this work is to discuss a flexible scan system using multiple cameras that can correctly reconstruct 3D stable and moving objects -- human face with expression in particular. Further, a mathematical model is proposed at the end of this literature to automate the 3D object reconstruction process. The reconstruction process takes several stages. Firstly, a set of simple 2D lines would be projected onto the object and hence a set of uneven curvy lines can be obtained, which represents the 3D numerical data of the surface. The lines and their shapes will help to identify object’s 3D construction in pixels. With the two-recorded angles and their distance from the camera, a simple mathematical calculation would give the resulting coordinate of each projected line in an absolute 3D space. This proposed research will benefit many practical areas, including but not limited to biometric identification, authentications, cybersecurity, preservation of cultural heritage, drama acting especially those with rapid and complex facial gestures, and many others. Specifically, this will (I) provide a brief survey of comparable techniques existing in this field. (II) discuss a set of specialized methodologies or algorithms for effective reconstruction of 3D objects. (III)implement, and testing the developed methodologies. (IV) verify findings with data collected from experiments. (V) conclude with lessons learned and final thoughts.

Keywords: 3D photogrammetry, 3D object reconstruction, facial expression recognition, facial recognition

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8420 Creating Energy Sustainability in an Enterprise

Authors: John Lamb, Robert Epstein, Vasundhara L. Bhupathi, Sanjeev Kumar Marimekala

Abstract:

As we enter the new era of Artificial Intelligence (AI) and Cloud Computing, we mostly rely on the Machine and Natural Language Processing capabilities of AI, and Energy Efficient Hardware and Software Devices in almost every industry sector. In these industry sectors, much emphasis is on developing new and innovative methods for producing and conserving energy and sustaining the depletion of natural resources. The core pillars of sustainability are economic, environmental, and social, which is also informally referred to as the 3 P's (People, Planet and Profits). The 3 P's play a vital role in creating a core Sustainability Model in the Enterprise. Natural resources are continually being depleted, so there is more focus and growing demand for renewable energy. With this growing demand, there is also a growing concern in many industries on how to reduce carbon emissions and conserve natural resources while adopting sustainability in corporate business models and policies. In our paper, we would like to discuss the driving forces such as Climate changes, Natural Disasters, Pandemic, Disruptive Technologies, Corporate Policies, Scaled Business Models and Emerging social media and AI platforms that influence the 3 main pillars of Sustainability (3P’s). Through this paper, we would like to bring an overall perspective on enterprise strategies and the primary focus on bringing cultural shifts in adapting energy-efficient operational models. Overall, many industries across the globe are incorporating core sustainability principles such as reducing energy costs, reducing greenhouse gas (GHG) emissions, reducing waste and increasing recycling, adopting advanced monitoring and metering infrastructure, reducing server footprint and compute resources (Shared IT services, Cloud computing, and Application Modernization) with the vision for a sustainable environment.

Keywords: climate change, pandemic, disruptive technology, government policies, business model, machine learning and natural language processing, AI, social media platform, cloud computing, advanced monitoring, metering infrastructure

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8419 Development of Web-Based Iceberg Detection Using Deep Learning

Authors: A. Kavya Sri, K. Sai Vineela, R. Vanitha, S. Rohith

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Large pieces of ice that break from the glaciers are known as icebergs. The threat that icebergs pose to navigation, production of offshore oil and gas services, and underwater pipelines makes their detection crucial. In this project, an automated iceberg tracking method using deep learning techniques and satellite images of icebergs is to be developed. With a temporal resolution of 12 days and a spatial resolution of 20 m, Sentinel-1 (SAR) images can be used to track iceberg drift over the Southern Ocean. In contrast to multispectral images, SAR images are used for analysis in meteorological conditions. This project develops a web-based graphical user interface to detect and track icebergs using sentinel-1 images. To track the movement of the icebergs by using temporal images based on their latitude and longitude values and by comparing the center and area of all detected icebergs. Testing the accuracy is done by precision and recall measures.

Keywords: synthetic aperture radar (SAR), icebergs, deep learning, spatial resolution, temporal resolution

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8418 Magnetoelectric Coupling in Hetero-Structured Nano-Composite of BST-BLFM Films

Authors: Navneet Dabra, Jasbir S. HUndal

Abstract:

Hetero-structured nano-composite thin film of Ba0.5Sr0.5TiO3/Bi0.9La0.1Fe0.9Mn0.1O3 (BST/BLFM) has been prepared by chemical solution deposition method with various BST to BLFM thickness ratios. These films have been deposited over on p-type Si (100) substrate. These samples exhibited low leakage current, large grain size and uniform distribution of particles. The maximum remanent polarization (Pr) was achieved in the heterostructures with thickness ratio of 2.65. The dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H), ferromagnetic exchange interaction and magnetoelectric measurements were carried out. Field Emission Scanning Electron Microscopy has been employed to investigate the surface morphology of these heterostructured nano-composite films.

Keywords: magnetoelectric, Schottky emission, interface coupling, dielectric tenability, electric hysteresis (P-E), ME coupling coefficient, magnetic hysteresis (M-H)

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8417 Malaria Vector Situation in Tanjung Subdistrict, West Lombok Regency, West Nusa Tenggara Province, Indonesia

Authors: Subagyo Yotopranoto, Sri Wijayanti Sulistyawati, Sukmawati Basuki, Budi Armika, Yoes Prijatna Dachlan

Abstract:

Malaria is a parasitic infectious disease that still remains a health problem in the world, including Indonesia. There is an outbreak happen at West Nusa Tenggara in 2007. A tourist spot in West Nusa Tenggara called West Lombok is mesoendemic area for malaria. Tanjung is the highest malaria morbidity subdistrict in West Lombok. Thus, the research conducted for the presence of a new species of malaria vectors, that are suspected of one factors which caused high morbidity of malaria in this region. The study was conducted in coastal and highland areas. We collected and identified Anopheles larvae from their breeding places. We also collected and identified Anopheles adult mosquitoes with outdoor cow net, indoor and outdoor human bait. In coastal area (Tembobor village), we found Anopheles vagus larvae from rivers as its breeding places. In highland area (Dasan Tengah village), we found An. subpictus from pool, lagoon, and river as its breeding places. In coastal area, with outdoor human bait, we collected An. vagus and An. subpictus adult mosquitoes. With indoor human bait, we collected An. subpictus adult mosquitoes. Whereas with outdoor cow net, we collected An. subpictus and An. maculatus, the first was more dominant. Furthermore, An subpictus strong suspected as malaria vector in coastal area. Anopheles subpictus was an anthropozoophylic mosquitoes, because it was found at indoor and outdoor places.

Keywords: malaria, vector, Tanjung, West Nusa Tenggara

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8416 Levels of Heavy Metals and Arsenic in Sediment and in Clarias Gariepinus, of Lake Ngami

Authors: Nashaat Mazrui, Oarabile Mogobe, Barbara Ngwenya, Ketlhatlogile Mosepele, Mangaliso Gondwe

Abstract:

Over the last several decades, the world has seen a rapid increase in activities such as deforestation, agriculture, and energy use. Subsequently, trace elements are being deposited into our water bodies, where they can accumulate to toxic levels in aquatic organisms and can be transferred to humans through fish consumption. Thus, though fish is a good source of essential minerals and omega-3 fatty acids, it can also be a source of toxic elements. Monitoring trace elements in fish is important for the proper management of aquatic systems and the protection of human health. The aim of this study was to determine concentrations of trace elements in sediment and muscle tissues of Clarias gariepinus at Lake Ngami, in the Okavango Delta in northern Botswana, during low floods. The fish were bought from local fishermen, and samples of muscle tissue were acid-digested and analyzed for iron, zinc, copper, manganese, molybdenum, nickel, chromium, cadmium, lead, and arsenic using inductively coupled plasma optical emission spectroscopy (ICP-OES). Sediment samples were also collected and analyzed for the elements and for organic matter content. Results show that in all samples, iron was found in the greatest amount while cadmium was below the detection limit. Generally, the concentrations of elements in sediment were higher than in fish except for zinc and arsenic. While the concentration of zinc was similar in the two media, arsenic was almost 3 times higher in fish than sediment. To evaluate the risk to human health from fish consumption, the target hazard quotient (THQ) and cancer risk for an average adult in Botswana, sub-Saharan Africa, and riparian communities in the Okavango Delta was calculated for each element. All elements were found to be well below regulatory limits and do not pose a threat to human health except arsenic. The results suggest that other benthic feeding fish species could potentially have high arsenic levels too. This has serious implications for human health, especially riparian households to whom fish is a key component of food and nutrition security.

Keywords: Arsenic, African sharp tooth cat fish, Okavango delta, trace elements

Procedia PDF Downloads 177
8415 Dependence of the Photoelectric Exponent on the Source Spectrum of the CT

Authors: Rezvan Ravanfar Haghighi, V. C. Vani, Suresh Perumal, Sabyasachi Chatterjee, Pratik Kumar

Abstract:

X-ray attenuation coefficient [µ(E)] of any substance, for energy (E), is a sum of the contributions from the Compton scattering [ μCom(E)] and photoelectric effect [µPh(E)]. In terms of the, electron density (ρe) and the effective atomic number (Zeff) we have µCom(E) is proportional to [(ρe)fKN(E)] while µPh(E) is proportional to [(ρeZeffx)/Ey] with fKN(E) being the Klein-Nishina formula, with x and y being the exponents for photoelectric effect. By taking the sample's HU at two different excitation voltages (V=V1, V2) of the CT machine, we can solve for X=ρe, Y=ρeZeffx from these two independent equations, as is attempted in DECT inversion. Since µCom(E) and µPh(E) are both energy dependent, the coefficients of inversion are also dependent on (a) the source spectrum S(E,V) and (b) the detector efficiency D(E) of the CT machine. In the present paper we tabulate these coefficients of inversion for different practical manifestations of S(E,V) and D(E). The HU(V) values from the CT follow: <µ(V)>=<µw(V)>[1+HU(V)/1000] where the subscript 'w' refers to water and the averaging process <….> accounts for the source spectrum S(E,V) and the detector efficiency D(E). Linearity of μ(E) with respect to X and Y implies that (a) <µ(V)> is a linear combination of X and Y and (b) for inversion, X and Y can be written as linear combinations of two independent observations <µ(V1)>, <µ(V2)> with V1≠V2. These coefficients of inversion would naturally depend upon S(E, V) and D(E). We numerically investigate this dependence for some practical cases, by taking V = 100 , 140 kVp, as are used for cardiological investigations. The S(E,V) are generated by using the Boone-Seibert source spectrum, being superposed on aluminium filters of different thickness lAl with 7mm≤lAl≤12mm and the D(E) is considered to be that of a typical Si[Li] solid state and GdOS scintilator detector. In the values of X and Y, found by using the calculated inversion coefficients, errors are below 2% for data with solutions of glycerol, sucrose and glucose. For low Zeff materials like propionic acid, Zeffx is overestimated by 20% with X being within1%. For high Zeffx materials like KOH the value of Zeffx is underestimated by 22% while the error in X is + 15%. These imply that the source may have additional filtering than the aluminium filter specified by the manufacturer. Also it is found that the difference in the values of the inversion coefficients for the two types of detectors is negligible. The type of the detector does not affect on the DECT inversion algorithm to find the unknown chemical characteristic of the scanned materials. The effect of the source should be considered as an important factor to calculate the coefficients of inversion.

Keywords: attenuation coefficient, computed tomography, photoelectric effect, source spectrum

Procedia PDF Downloads 386
8414 The Role of Artificial Intelligence Algorithms in Decision-Making Policies

Authors: Marisa Almeida AraúJo

Abstract:

Artificial intelligence (AI) tools are being used (including in the criminal justice system) and becomingincreasingly popular. The many questions that these (future) super-beings pose the neuralgic center is rooted in the (old) problematic between rationality and morality. For instance, if we follow a Kantian perspective in which morality derives from AI, rationality will also surpass man in ethical and moral standards, questioning the nature of mind, the conscience of self and others, and moral. The recognition of superior intelligence in a non-human being puts us in the contingency of having to recognize a pair in a form of new coexistence and social relationship. Just think of the humanoid robot Sophia, capable of reasoning and conversation (and who has been recognized for Saudi citizenship; a fact that symbolically demonstrates our empathy with the being). Machines having a more intelligent mind, and even, eventually, with higher ethical standards to which, in the alluded categorical imperative, we would have to subject ourselves under penalty of contradiction with the universal Kantian law. Recognizing the complex ethical and legal issues and the significant impact on human rights and democratic functioning itself is the goal of our work.

Keywords: ethics, artificial intelligence, legal rules, principles, philosophy

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8413 Islam, Tolerance and Anti-Terrorism: A Critical Assessment with Reference to the Royal 'Amman Message'

Authors: Adnan M. Al Assaf

Abstract:

This research project aims to assess the methods of enhancing tolerant thinking and behavior among Muslim societies. This is in addition to spreading the anti-terrorist approach in their communities. The critical assessment for the Islamic major texts in question is the selected way for convincing, as Muslims adopt these sources as the authentic references for their lives and cultures. Moreover, this research devotes a special room to the analysis of the royal ‘Amman Message’ as a contemporary Islamic approach for enhancing tolerance and anti-terrorism from an Islamic perspective. The paper includes the study of the related concepts, texts, practical applications, with some reference to the history of Islam in human interaction, accepting the others, mercy with minorities, protecting human rights. Furthermore, it assesses the methods of enhancing tolerance and minimizing the terrorist thinking and behavior practically, in the view of Amman message, as well.

Keywords: Islam, tolerance, anti-terrorism, coexistence, Amman Message

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8412 A Formal Approach for Instructional Design Integrated with Data Visualization for Learning Analytics

Authors: Douglas A. Menezes, Isabel D. Nunes, Ulrich Schiel

Abstract:

Most Virtual Learning Environments do not provide support mechanisms for the integrated planning, construction and follow-up of Instructional Design supported by Learning Analytic results. The present work aims to present an authoring tool that will be responsible for constructing the structure of an Instructional Design (ID), without the data being altered during the execution of the course. The visual interface aims to present the critical situations present in this ID, serving as a support tool for the course follow-up and possible improvements, which can be made during its execution or in the planning of a new edition of this course. The model for the ID is based on High-Level Petri Nets and the visualization forms are determined by the specific kind of the data generated by an e-course, a population of students generating sequentially dependent data.

Keywords: educational data visualization, high-level petri nets, instructional design, learning analytics

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8411 Rapid Building Detection in Population-Dense Regions with Overfitted Machine Learning Models

Authors: V. Mantey, N. Findlay, I. Maddox

Abstract:

The quality and quantity of global satellite data have been increasing exponentially in recent years as spaceborne systems become more affordable and the sensors themselves become more sophisticated. This is a valuable resource for many applications, including disaster management and relief. However, while more information can be valuable, the volume of data available is impossible to manually examine. Therefore, the question becomes how to extract as much information as possible from the data with limited manpower. Buildings are a key feature of interest in satellite imagery with applications including telecommunications, population models, and disaster relief. Machine learning tools are fast becoming one of the key resources to solve this problem, and models have been developed to detect buildings in optical satellite imagery. However, by and large, most models focus on affluent regions where buildings are generally larger and constructed further apart. This work is focused on the more difficult problem of detection in populated regions. The primary challenge with detecting small buildings in densely populated regions is both the spatial and spectral resolution of the optical sensor. Densely packed buildings with similar construction materials will be difficult to separate due to a similarity in color and because the physical separation between structures is either non-existent or smaller than the spatial resolution. This study finds that training models until they are overfitting the input sample can perform better in these areas than a more robust, generalized model. An overfitted model takes less time to fine-tune from a generalized pre-trained model and requires fewer input data. The model developed for this study has also been fine-tuned using existing, open-source, building vector datasets. This is particularly valuable in the context of disaster relief, where information is required in a very short time span. Leveraging existing datasets means that little to no manpower or time is required to collect data in the region of interest. The training period itself is also shorter for smaller datasets. Requiring less data means that only a few quality areas are necessary, and so any weaknesses or underpopulated regions in the data can be skipped over in favor of areas with higher quality vectors. In this study, a landcover classification model was developed in conjunction with the building detection tool to provide a secondary source to quality check the detected buildings. This has greatly reduced the false positive rate. The proposed methodologies have been implemented and integrated into a configurable production environment and have been employed for a number of large-scale commercial projects, including continent-wide DEM production, where the extracted building footprints are being used to enhance digital elevation models. Overfitted machine learning models are often considered too specific to have any predictive capacity. However, this study demonstrates that, in cases where input data is scarce, overfitted models can be judiciously applied to solve time-sensitive problems.

Keywords: building detection, disaster relief, mask-RCNN, satellite mapping

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8410 User Requirements Study in Order to Improve the Quality of Social Robots for Dementia Patients

Authors: Konrad Rejdak

Abstract:

Introduction: Neurodegenerative diseases are frequently accompanied by loss and unwanted change in functional independence, social relationships, and economic circumstances. Currently, the achievements of social robots to date is being projected to improve multidimensional quality of life among people with cognitive impairment and others. Objectives: Identification of particular human needs in the context of the changes occurring in course of neurodegenerative diseases. Methods: Based on the 110 surveys performed in the Medical University of Lublin from medical staff, patients, and caregivers we made prioritization of the users' needs as high, medium, and low. The issues included in the surveys concerned four aspects: user acceptance, functional requirements, the design of the robotic assistant and preferred types of human-robot interaction. Results: We received completed questionnaires; 50 from medical staff, 30 from caregivers and 30 from potential users. Above 90% of the respondents from each of the three groups, accepted a robotic assistant as a potential caregiver. High priority functional capability of assistive technology was to handle emergencies in a private home-like recognizing life-threatening situations and reminding about medication intake. With reference to the design of the robotic assistant, the majority of the respondent would like to have an anthropomorphic appearance with a positive emotionally expressive face. The most important type of human-robot interaction was a voice-operated system and by touchscreen. Conclusion: The results from our study might contribute to a better understanding of the system and users’ requirements for the development of a service robot intended to support patients with dementia.

Keywords: assistant robot, dementia, long term care, patients

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8409 Dissolution of South African Limestone for Wet Flue Gas Desulphurization

Authors: Lawrence Koech, Ray Everson, Hein Neomagus, Hilary Rutto

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Wet Flue gas desulphurization (FGD) systems are commonly used to remove sulphur dioxide from flue gas by contacting it with limestone in aqueous phase which is obtained by dissolution. Dissolution is important as it affects the overall performance of a wet FGD system. In the present study, effects of pH, stirring speed, solid to liquid ratio and acid concentration on the dissolution of limestone using an organic acid (adipic acid) were investigated. This was investigated using the pH stat apparatus. Calcium ions were analyzed at the end of each experiment using Atomic Absorption (AAS) machine.

Keywords: desulphurization, limestone, dissolution, pH stat apparatus

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8408 The Relationship between the Content of Inner Human Experience and Well-Being: An Experience Sampling Study

Authors: Xinqi Guo, Karen R. Dobkins

Abstract:

Background and Objectives: Humans are probably the only animals whose minds are constantly filled with thoughts, feelings and emotions. Previous studies have investigated human minds from different dimensions, including its proportion of time for not being present, its representative format, its personal relevance, its temporal locus, and affect valence. The current study aims at characterizing human mind by employing Experience Sampling Methods (ESM), a self-report research procedure for studying daily experience. This study emphasis on answering the following questions: 1) How does the contents of the inner experience vary across demographics, 2) Are certain types of inner experiences correlated with level of mindfulness and mental well-being (e.g., are people who spend more time being present happier, and are more mindful people more at-present?), 3) Will being prompted to report one’s inner experience increase mindfulness and mental well-being? Methods: Participants were recruited from the subject pool of UC San Diego or from the social media. They began by filling out two questionnaires: 1) Five Facet Mindfulness Questionnaire-Short Form, and 2) Warwick-Edinburgh Mental Well-being Scale, and demographic information. Then they participated in the ESM part by responding to the prompts which contained questions about their real-time inner experience: if they were 'at-present', 'mind-wandering', or 'zoned-out'. The temporal locus, the clarity, and the affect valence, and the personal importance of the thought they had the moment before the prompt were also assessed. A mobile app 'RealLife Exp' randomly delivered these prompts 3 times/day for 6 days during wake-time. After the 6 days, participants completed questionnaire (1) and (2) again. Their changes of score were compared to a control group who did not participate in the ESM procedure (yet completed (1) and (2) one week apart). Results: Results are currently preliminary as we continue to collect data. So far, there is a trend that participants are present, mind-wandering and zoned-out, about 53%, 23% and 24% during wake-time, respectively. The thoughts of participants are ranked to be clearer and more neutral if they are present vs. mind-wandering. Mind-wandering thoughts are 66% about the past, consisting 80% of inner speech. Discussion and Conclusion: This study investigated the subjective account of human mind by a tool with high ecological validity. And it broadens the understanding of the relationship between contents of mind and well-being.

Keywords: experience sampling method, meta-memory, mindfulness, mind-wandering

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8407 DQN for Navigation in Gazebo Simulator

Authors: Xabier Olaz Moratinos

Abstract:

Drone navigation is critical, particularly during the initial phases, such as the initial ascension, where pilots may fail due to strong external interferences that could potentially lead to a crash. In this ongoing work, a drone has been successfully trained to perform an ascent of up to 6 meters at speeds with external disturbances pushing it up to 24 mph, with the DQN algorithm managing external forces affecting the system. It has been demonstrated that the system can control its height, position, and stability in all three axes (roll, pitch, and yaw) throughout the process. The learning process is carried out in the Gazebo simulator, which emulates interferences, while ROS is used to communicate with the agent.

Keywords: machine learning, DQN, gazebo, navigation

Procedia PDF Downloads 89