Search results for: image subset selection
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5117

Search results for: image subset selection

2987 Genetic Characterization of Barley Genotypes via Inter-Simple Sequence Repeat

Authors: Mustafa Yorgancılar, Emine Atalay, Necdet Akgün, Ali Topal

Abstract:

In this study, polymerase chain reaction based Inter-simple sequence repeat (ISSR) from DNA fingerprinting techniques were used to investigate the genetic relationships among barley crossbreed genotypes in Turkey. It is important that selection based on the genetic base in breeding programs via ISSR, in terms of breeding time. 14 ISSR primers generated a total of 97 bands, of which 81 (83.35%) were polymorphic. The highest total resolution power (RP) value was obtained from the F2 (0.53) and M16 (0.51) primers. According to the ISSR result, the genetic similarity index changed between 0.64–095; Lane 3 with Line 6 genotypes were the closest, while Line 36 were the most distant ones. The ISSR markers were found to be promising for assessing genetic diversity in barley crossbreed genotypes.

Keywords: barley, crossbreed, genetic similarity, ISSR

Procedia PDF Downloads 330
2986 Application of Low-order Modeling Techniques and Neural-Network Based Models for System Identification

Authors: Venkatesh Pulletikurthi, Karthik B. Ariyur, Luciano Castillo

Abstract:

The system identification from the turbulence wakes will lead to the tactical advantage to prepare and also, to predict the trajectory of the opponents’ movements. A low-order modeling technique, POD, is used to predict the object based on the wake pattern and compared with pre-trained image recognition neural network (NN) to classify the wake patterns into objects. It is demonstrated that low-order modeling, POD, is able to predict the objects better compared to pretrained NN by ~30%.

Keywords: the bluff body wakes, low-order modeling, neural network, system identification

Procedia PDF Downloads 164
2985 Proactive Pure Handoff Model with SAW-TOPSIS Selection and Time Series Predict

Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

Abstract:

This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

Procedia PDF Downloads 469
2984 Soil Remediation Technologies towards Green Remediation Strategies

Authors: G. Petruzzelli, F. Pedron, M. Grifoni, M. Barbafieri, I. Rosellini, B. Pezzarossa

Abstract:

As a result of diverse industrial activities, pollution from numerous contaminant affects both groundwater and soils. Many contaminated sites have been discovered in industrialized countries and their remediation is a priority in environmental legislations. The aim of this paper is to provide the evolution of remediation from consolidated invasive technologies to environmental friendly green strategies. Many clean-up technologies have been used. Nowadays the technologies selection is no longer exclusively based on eliminating the source of pollution, but the aim of remediation includes also the recovery of soil quality. “Green remediation”, a strategy based on “soft technologies”, appears the key to tackle the issue of remediation of contaminated sites with the greatest attention to environmental quality, including the preservation of soil functionality.

Keywords: bioremediation, Green Remediation, phytoremediation, remediation technologies, soil

Procedia PDF Downloads 214
2983 Post 2014 Afghanistan and Its Implications on Pakistan

Authors: Naad-E-Ali Sulehria

Abstract:

This paper unfolds the facts and findings of Afghan scenario particularly its implications on Pakistan. At present, the Post 2014 withdrawal of US and ISAF combat forces from Afghan land is one of the up-to-the-minute issues among analysts of international relations. Deliberating from the current situation of Afghanistan towards its future prospects and the elements vibrating Afghanistan's internal dynamics, as well as exploitation of its resources by other states and non-state actors, are discussed accordingly. Moreover, the reasons behind such a paradigm shift in US foreign policy are tried to be contemplated with first hand knowledge. It is investigated that 'what is the current image of Afghanistan in today's world?', 'what will be its future aspects?', and 'what sort of Afghanistan does Pakistan foresees' as the concerned area of discussion.

Keywords: Afghanistan, Pakistan, new great game, taliban

Procedia PDF Downloads 285
2982 Application of EEG Wavelet Power to Prediction of Antidepressant Treatment Response

Authors: Dorota Witkowska, Paweł Gosek, Lukasz Swiecicki, Wojciech Jernajczyk, Bruce J. West, Miroslaw Latka

Abstract:

In clinical practice, the selection of an antidepressant often degrades to lengthy trial-and-error. In this work we employ a normalized wavelet power of alpha waves as a biomarker of antidepressant treatment response. This novel EEG metric takes into account both non-stationarity and intersubject variability of alpha waves. We recorded resting, 19-channel EEG (closed eyes) in 22 inpatients suffering from unipolar (UD, n=10) or bipolar (BD, n=12) depression. The EEG measurement was done at the end of the short washout period which followed previously unsuccessful pharmacotherapy. The normalized alpha wavelet power of 11 responders was markedly different than that of 11 nonresponders at several, mostly temporoparietal sites. Using the prediction of treatment response based on the normalized alpha wavelet power, we achieved 81.8% sensitivity and 81.8% specificity for channel T4.

Keywords: alpha waves, antidepressant, treatment outcome, wavelet

Procedia PDF Downloads 297
2981 Factors Determining Selection of Essential Nutrition Supplements

Authors: Daniel C. S. Lim

Abstract:

There are numerous nutritional supplements, such as multivitamins and nutrition drinks, in the market today. Many of these supplements are expensive and tend to be driven commercially by business decisions and big marketing budgets. Many of the costs are ultimately borne by the end user in the quest for keeping to a healthy lifestyle. This paper proposes a system with a list of ten determinants to gauge how to decide the value of various supplements. It suggests variables such as composition, safety, efficacy and bioavailability, as well as several other considerations. These guidelines can help to tackle many of the issues that people of all ages face in the way that they receive essential nutrients. The system also aims to promote and improve the safety and choice of foods and supplements. In so doing, the system aims to promote the individual’s or population’s control over their own health and reduce the growing health care burden on the society.

Keywords: choice of foods and supplements, essential nutrients, nutritional supplements, system safety

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2980 Clustering the Wheat Seeds Using SOM Artificial Neural Networks

Authors: Salah Ghamari

Abstract:

In this study, the ability of self organizing map artificial (SOM) neural networks in clustering the wheat seeds varieties according to morphological properties of them was considered. The SOM is one type of unsupervised competitive learning. Experimentally, five morphological features of 300 seeds (including three varieties: gaskozhen, Md and sardari) were obtained using image processing technique. The results show that the artificial neural network has a good performance (90.33% accuracy) in classification of the wheat varieties despite of high similarity in them. The highest classification accuracy (100%) was achieved for sardari.

Keywords: artificial neural networks, clustering, self organizing map, wheat variety

Procedia PDF Downloads 630
2979 Use of Artificial Intelligence and Two Object-Oriented Approaches (k-NN and SVM) for the Detection and Characterization of Wetlands in the Centre-Val de Loire Region, France

Authors: Bensaid A., Mostephaoui T., Nedjai R.

Abstract:

Nowadays, wetlands are the subject of contradictory debates opposing scientific, political and administrative meanings. Indeed, given their multiple services (drinking water, irrigation, hydrological regulation, mineral, plant and animal resources...), wetlands concentrate many socio-economic and biodiversity issues. In some regions, they can cover vast areas (>100 thousand ha) of the landscape, such as the Camargue area in the south of France, inside the Rhone delta. The high biological productivity of wetlands, the strong natural selection pressures and the diversity of aquatic environments have produced many species of plants and animals that are found nowhere else. These environments are tremendous carbon sinks and biodiversity reserves depending on their age, composition and surrounding environmental conditions, wetlands play an important role in global climate projections. Covering more than 3% of the earth's surface, wetlands have experienced since the beginning of the 1990s a tremendous revival of interest, which has resulted in the multiplication of inventories, scientific studies and management experiments. The geographical and physical characteristics of the wetlands of the central region conceal a large number of natural habitats that harbour a great biological diversity. These wetlands, one of the natural habitats, are still influenced by human activities, especially agriculture, which affects its layout and functioning. In this perspective, decision-makers need to delimit spatial objects (natural habitats) in a certain way to be able to take action. Thus, wetlands are no exception to this rule even if it seems to be a difficult exercise to delimit a type of environment as whose main characteristic is often to occupy the transition between aquatic and terrestrial environment. However, it is possible to map wetlands with databases, derived from the interpretation of photos and satellite images, such as the European database Corine Land cover, which allows quantifying and characterizing for each place the characteristic wetland types. Scientific studies have shown limitations when using high spatial resolution images (SPOT, Landsat, ASTER) for the identification and characterization of small wetlands (1 hectare). To address this limitation, it is important to note that these wetlands generally represent spatially complex features. Indeed, the use of very high spatial resolution images (>3m) is necessary to map small and large areas. However, with the recent evolution of artificial intelligence (AI) and deep learning methods for satellite image processing have shown a much better performance compared to traditional processing based only on pixel structures. Our research work is also based on spectral and textural analysis on THR images (Spot and IRC orthoimage) using two object-oriented approaches, the nearest neighbour approach (k-NN) and the Super Vector Machine approach (SVM). The k-NN approach gave good results for the delineation of wetlands (wet marshes and moors, ponds, artificial wetlands water body edges, ponds, mountain wetlands, river edges and brackish marshes) with a kappa index higher than 85%.

Keywords: land development, GIS, sand dunes, segmentation, remote sensing

Procedia PDF Downloads 43
2978 Reviving Sustainable Architecture in Non-Wester Culture

Authors: Khaled Asfour

Abstract:

Going for LEED certification is the latest concern in Egyptian practice that only materialized during the last 4 years. Egyptian Consultant Group (ECG) together with Credit Agricole had the vision to design a headquarters (Cairo) that delivers a serious sustainable design. The bank is a strong advocator of “green banking” and supports renewable energy and energy saving projects. Their HQ in Cairo has passed all the hurdles to become the first platinum LEED certificate holder in Egypt. With this design Egyptian practice has finally re-engaged in a serious way with its long-standing traditions in sustainable architecture. Perhaps the closest to our memory is the medieval houses of Cairo. Few centuries later these qualities disappeared with the advent of Modern Movement that focused more on standard modernist image making than real localized quality of living environments. The first person to note this disappearance was Hassan Fathy half a century ago. Despite international applaud for his efforts he had no effect on prevailing local practice that continued senselessly adopting recycled modernist templates. The Egyptian society was not ready to accept any reference to historic architecture. Disciples of Hassan Fathy, few decades later sought, of tackling the lack of interest in green architecture in a different way. Mohamed Awad introduced in his design sustainable ideals inspired from traditional architecture rather than recycling directly historic forms and images. Despite success, this approach did not go far enough to influence the prevailing practice. Since year 2000 Egyptian economy was ebbing and flowing dramatically. This staggering fluctuation coupled by energy crisis has disillusioned architects and clients on the issue of modern image making. No more shining architecture under the sun with high running cost of fossil fuel. They sought of adopting contemporary green measures that offer pleasant living while saving on energy. A revival is on its way but is very slow and timid. The paper will present this problem of reviving sustainable architecture. How this process can be accelerated in order to give stronger impact on current practice will be addressed through the works of Mario Cucinella and Norman Foster.

Keywords: LEED certification, Hasan Fathy, Medieval architecture, Mario Cucinella, Norman Foster

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2977 A Forearm-Wrist Rehabilitation Module for Stroke and Spinal Cord Injuries

Authors: Vahid Mehrabi, Iman Sharifi, H. A. Talebi

Abstract:

The automation of rehabilitation procedure by the implementation of robotic devices can overcome the limitation in conventional physiotherapy methods by increasing training sessions and duration of process. In this paper, the design of a simple rehabilitation robot for forearm-wrist therapy in stroke and spinal cord injuries is presented. Wrist’s biological joint motion is modeled by a gimbal-like mechanism which resembles the human arm anatomy. Presented device is an exoskeleton robot with rotation axes corresponding to human skeleton anatomy. The mechanical structure, actuator and sensor selection, system kinematics and comparison between our device range of motion and required active daily life values is illustrated.

Keywords: rehabilitation, robotic devices, physiotherapy, forearm-wrist

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2976 Multi-Criteria Selection and Improvement of Effective Design for Generating Power from Sea Waves

Authors: Khaled M. Khader, Mamdouh I. Elimy, Omayma A. Nada

Abstract:

Sustainable development is the nominal goal of most countries at present. In general, fossil fuels are the development mainstay of most world countries. Regrettably, the fossil fuel consumption rate is very high, and the world is facing the problem of conventional fuels depletion soon. In addition, there are many problems of environmental pollution resulting from the emission of harmful gases and vapors during fuel burning. Thus, clean, renewable energy became the main concern of most countries for filling the gap between available energy resources and their growing needs. There are many renewable energy sources such as wind, solar and wave energy. Energy can be obtained from the motion of sea waves almost all the time. However, power generation from solar or wind energy is highly restricted to sunny periods or the availability of suitable wind speeds. Moreover, energy produced from sea wave motion is one of the cheapest types of clean energy. In addition, renewable energy usage of sea waves guarantees safe environmental conditions. Cheap electricity can be generated from wave energy using different systems such as oscillating bodies' system, pendulum gate system, ocean wave dragon system and oscillating water column device. In this paper, a multi-criteria model has been developed using Analytic Hierarchy Process (AHP) to support the decision of selecting the most effective system for generating power from sea waves. This paper provides a widespread overview of the different design alternatives for sea wave energy converter systems. The considered design alternatives have been evaluated using the developed AHP model. The multi-criteria assessment reveals that the off-shore Oscillating Water Column (OWC) system is the most appropriate system for generating power from sea waves. The OWC system consists of a suitable hollow chamber at the shore which is completely closed except at its base which has an open area for gathering moving sea waves. Sea wave's motion pushes the air up and down passing through a suitable well turbine for generating power. Improving the power generation capability of the OWC system is one of the main objectives of this research. After investigating the effect of some design modifications, it has been concluded that selecting the appropriate settings of some effective design parameters such as the number of layers of Wells turbine fans and the intermediate distance between the fans can result in significant improvements. Moreover, simple dynamic analysis of the Wells turbine is introduced. Furthermore, this paper strives for comparing the theoretical and experimental results of the built experimental prototype.

Keywords: renewable energy, oscillating water column, multi-criteria selection, Wells turbine

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2975 Implementation of a Method of Crater Detection Using Principal Component Analysis in FPGA

Authors: Izuru Nomura, Tatsuya Takino, Yuji Kageyama, Shin Nagata, Hiroyuki Kamata

Abstract:

We propose a method of crater detection from the image of the lunar surface captured by the small space probe. We use the principal component analysis (PCA) to detect craters. Nevertheless, considering severe environment of the space, it is impossible to use generic computer in practice. Accordingly, we have to implement the method in FPGA. This paper compares FPGA and generic computer by the processing time of a method of crater detection using principal component analysis.

Keywords: crater, PCA, eigenvector, strength value, FPGA, processing time

Procedia PDF Downloads 537
2974 Update on Epithelial Ovarian Cancer (EOC), Types, Origin, Molecular Pathogenesis, and Biomarkers

Authors: Salina Yahya Saddick

Abstract:

Ovarian cancer remains the most lethal gynecological malignancy due to the lack of highly sensitive and specific screening tools for detection of early-stage disease. The OSE provides the progenitor cells for 90% of human ovarian cancers. Recent morphologic, immunohistochemical and molecular genetic studies have led to the development of a new paradigm for the pathogenesis and origin of epithelial ovarian cancer (EOC) based on a ualistic model of carcinogenesis that divides EOC into two broad categories designated Types I and II which are characterized by specific mutations, including KRAS, BRAF, ERBB2, CTNNB1, PTEN PIK3CA, ARID1A, and PPPR1A, which target specific cell signaling pathways. Type 1 tumors rarely harbor TP53. type I tumors are relatively genetically stable and typically display a variety of somatic sequence mutations that include KRAS, BRAF, PTEN, PIK3CA CTNNB1 (the gene encoding beta catenin), ARID1A and PPP2R1A but very rarely TP53 . The cancer stem cell (CSC) hypothesis postulates that the tumorigenic potential of CSCs is confined to a very small subset of tumor cells and is defined by their ability to self-renew and differentiate leading to the formation of a tumor mass. Potential protein biomarker miRNA, are promising biomarkers as they are remarkably stable to allow isolation and analysis from tissues and from blood in which they can be found as free circulating nucleic acids and in mononuclear cells. Recently, genomic anaylsis have identified biomarkers and potential therapeutic targets for ovarian cancer namely, FGF18 which plays an active role in controlling migration, invasion, and tumorigenicity of ovarian cancer cells through NF-κB activation, which increased the production of oncogenic cytokines and chemokines. This review summarizes update information on epithelial ovarian cancers and point out to the most recent ongoing research.

Keywords: epithelial ovarian cancers, somatic sequence mutations, cancer stem cell (CSC), potential protein, biomarker, genomic analysis, FGF18 biomarker

Procedia PDF Downloads 362
2973 Degradation of the Cu-DOM Complex by Bacteria: A Way to Increase Phytoextraction of Copper in a Vineyard Soil

Authors: Justine Garraud, Hervé Capiaux, Cécile Le Guern, Pierre Gaudin, Clémentine Lapie, Samuel Chaffron, Erwan Delage, Thierry Lebeau

Abstract:

The repeated use of Bordeaux mixture (copper sulphate) and other chemical forms of copper (Cu) has led to its accumulation in wine-growing soils for more than a century, to the point of modifying the ecosystem of these soils. Phytoextraction of copper could progressively reduce the Cu load in these soils, and even to recycle copper (e.g. as a micronutrient in animal nutrition) by cultivating the extracting plants in the inter-row of the vineyards. Soil cleaning up usually requires several years because the chemical speciation of Cu in solution is mainly based on forms complexed with dissolved organic matter (DOM) that are not phytoavailable, unlike the "free" forms (Cu2+). Indeed, more than 98% of Cu in the solution is bound to DOM. The selection and inoculation of invineyardsoils in vineyard soils ofbacteria(bioaugmentation) able to degrade Cu-DOM complexes could increase the phytoavailable pool of Cu2+ in the soil solution (in addition to bacteria which first mobilize Cu in solution from the soil bearing phases) in order to increase phytoextraction performance. In this study, sevenCu-accumulating plants potentially usable in inter-row were tested for their Cu phytoextraction capacity in hydroponics (ray-grass, brown mustard, buckwheat, hemp, sunflower, oats, and chicory). Also, a bacterial consortium was tested: Pseudomonas sp. previously studied for its ability to mobilize Cu through the pyoverdine siderophore (complexing agent) and potentially to degrade Cu-DOM complexes, and a second bacterium (to be selected) able to promote the survival of Pseudomonas sp. following its inoculation in soil. Interaction network method was used based on the notions of co-occurrence and, therefore, of bacterial abundance found in the same soils. Bacteria from the EcoVitiSol project (Alsace, France) were targeted. The final step consisted of incoupling the bacterial consortium with the chosen plant in soil pots. The degradation of Cu-DOMcomplexes is measured on the basis of the absorption index at 254nm, which gives insight on the aromaticity of the DOM. The“free” Cu in solution (from the mobilization of Cu and/or the degradation of Cu-MOD complexes) is assessed by measuring pCu. Eventually, Cu accumulation in plants is measured by ICP-AES. The selection of the plant is currently being finalized. The interaction network method targeted the best positive interactions ofFlavobacterium sp. with Pseudomonassp. These bacteria are both PGPR (plant growth promoting rhizobacteria) with the ability to improve the plant growth and to mobilize Cu from the soil bearing phases (siderophores). Also, these bacteria are known to degrade phenolic groups, which are highly present in DOM. They could therefore contribute to the degradation of DOM-Cu. The results of the upcoming bacteria-plant coupling tests in pots will be also presented.

Keywords: complexes Cu-DOM, bioaugmentation, phytoavailability, phytoextraction

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2972 Sensory Ethnography and Interaction Design in Immersive Higher Education

Authors: Anna-Kaisa Sjolund

Abstract:

The doctoral thesis examines interaction design and sensory ethnography as tools to create immersive education environments. In recent years, there has been increasing interest and discussions among researchers and educators on immersive education like augmented reality tools, virtual glasses and the possibilities to utilize them in education at all levels. Using virtual devices as learning environments it is possible to create multisensory learning environments. Sensory ethnography in this study refers to the way of the senses consider the impact on the information dynamics in immersive learning environments. The past decade has seen the rapid development of virtual world research and virtual ethnography. Christine Hine's Virtual Ethnography offers an anthropological explanation of net behavior and communication change. Despite her groundbreaking work, time has changed the users’ communication style and brought new solutions to do ethnographical research. The virtual reality with all its new potential has come to the fore and considering all the senses. Movie and image have played an important role in cultural research for centuries, only the focus has changed in different times and in a different field of research. According to Karin Becker, the role of image in our society is information flow and she found two meanings what the research of visual culture is. The images and pictures are the artifacts of visual culture. Images can be viewed as a symbolic language that allows digital storytelling. Combining the sense of sight, but also the other senses, such as hear, touch, taste, smell, balance, the use of a virtual learning environment offers students a way to more easily absorb large amounts of information. It offers also for teachers’ different ways to produce study material. In this article using sensory ethnography as research tool approaches the core question. Sensory ethnography is used to describe information dynamics in immersive environment through interaction design. Immersive education environment is understood as three-dimensional, interactive learning environment, where the audiovisual aspects are central, but all senses can be taken into consideration. When designing learning environments or any digital service, interaction design is always needed. The question what is interaction design is justified, because there is no simple or consistent idea of what is the interaction design or how it can be used as a research method or whether it is only a description of practical actions. When discussing immersive learning environments or their construction, consideration should be given to interaction design and sensory ethnography.

Keywords: immersive education, sensory ethnography, interaction design, information dynamics

Procedia PDF Downloads 119
2971 Detection and Classification Strabismus Using Convolutional Neural Network and Spatial Image Processing

Authors: Anoop T. R., Otman Basir, Robert F. Hess, Eileen E. Birch, Brooke A. Koritala, Reed M. Jost, Becky Luu, David Stager, Ben Thompson

Abstract:

Strabismus refers to a misalignment of the eyes. Early detection and treatment of strabismus in childhood can prevent the development of permanent vision loss due to abnormal development of visual brain areas. We developed a two-stage method for strabismus detection and classification based on photographs of the face. The first stage detects the presence or absence of strabismus, and the second stage classifies the type of strabismus. The first stage comprises face detection using Haar cascade, facial landmark estimation, face alignment, aligned face landmark detection, segmentation of the eye region, and detection of strabismus using VGG 16 convolution neural networks. Face alignment transforms the face to a canonical pose to ensure consistency in subsequent analysis. Using facial landmarks, the eye region is segmented from the aligned face and fed into a VGG 16 CNN model, which has been trained to classify strabismus. The CNN determines whether strabismus is present and classifies the type of strabismus (exotropia, esotropia, and vertical deviation). If stage 1 detects strabismus, the eye region image is fed into stage 2, which starts with the estimation of pupil center coordinates using mask R-CNN deep neural networks. Then, the distance between the pupil coordinates and eye landmarks is calculated along with the angle that the pupil coordinates make with the horizontal and vertical axis. The distance and angle information is used to characterize the degree and direction of the strabismic eye misalignment. This model was tested on 100 clinically labeled images of children with (n = 50) and without (n = 50) strabismus. The True Positive Rate (TPR) and False Positive Rate (FPR) of the first stage were 94% and 6% respectively. The classification stage has produced a TPR of 94.73%, 94.44%, and 100% for esotropia, exotropia, and vertical deviations, respectively. This method also had an FPR of 5.26%, 5.55%, and 0% for esotropia, exotropia, and vertical deviation, respectively. The addition of one more feature related to the location of corneal light reflections may reduce the FPR, which was primarily due to children with pseudo-strabismus (the appearance of strabismus due to a wide nasal bridge or skin folds on the nasal side of the eyes).

Keywords: strabismus, deep neural networks, face detection, facial landmarks, face alignment, segmentation, VGG 16, mask R-CNN, pupil coordinates, angle deviation, horizontal and vertical deviation

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2970 Evaluating Performance of an Anomaly Detection Module with Artificial Neural Network Implementation

Authors: Edward Guillén, Jhordany Rodriguez, Rafael Páez

Abstract:

Anomaly detection techniques have been focused on two main components: data extraction and selection and the second one is the analysis performed over the obtained data. The goal of this paper is to analyze the influence that each of these components has over the system performance by evaluating detection over network scenarios with different setups. The independent variables are as follows: the number of system inputs, the way the inputs are codified and the complexity of the analysis techniques. For the analysis, some approaches of artificial neural networks are implemented with different number of layers. The obtained results show the influence that each of these variables has in the system performance.

Keywords: network intrusion detection, machine learning, artificial neural network, anomaly detection module

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2969 Digital Immunity System for Healthcare Data Security

Authors: Nihar Bheda

Abstract:

Protecting digital assets such as networks, systems, and data from advanced cyber threats is the aim of Digital Immunity Systems (DIS), which are a subset of cybersecurity. With features like continuous monitoring, coordinated reactions, and long-term adaptation, DIS seeks to mimic biological immunity. This minimizes downtime by automatically identifying and eliminating threats. Traditional security measures, such as firewalls and antivirus software, are insufficient for enterprises, such as healthcare providers, given the rapid evolution of cyber threats. The number of medical record breaches that have occurred in recent years is proof that attackers are finding healthcare data to be an increasingly valuable target. However, obstacles to enhancing security include outdated systems, financial limitations, and a lack of knowledge. DIS is an advancement in cyber defenses designed specifically for healthcare settings. Protection akin to an "immune system" is produced by core capabilities such as anomaly detection, access controls, and policy enforcement. Coordination of responses across IT infrastructure to contain attacks is made possible by automation and orchestration. Massive amounts of data are analyzed by AI and machine learning to find new threats. After an incident, self-healing enables services to resume quickly. The implementation of DIS is consistent with the healthcare industry's urgent requirement for resilient data security in light of evolving risks and strict guidelines. With resilient systems, it can help organizations lower business risk, minimize the effects of breaches, and preserve patient care continuity. DIS will be essential for protecting a variety of environments, including cloud computing and the Internet of medical devices, as healthcare providers quickly adopt new technologies. DIS lowers traditional security overhead for IT departments and offers automated protection, even though it requires an initial investment. In the near future, DIS may prove to be essential for small clinics, blood banks, imaging centers, large hospitals, and other healthcare organizations. Cyber resilience can become attainable for the whole healthcare ecosystem with customized DIS implementations.

Keywords: digital immunity system, cybersecurity, healthcare data, emerging technology

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2968 Relational Attention Shift on Images Using Bu-Td Architecture and Sequential Structure Revealing

Authors: Alona Faktor

Abstract:

In this work, we present a NN-based computational model that can perform attention shifts according to high-level instruction. The instruction specifies the type of attentional shift using explicit geometrical relation. The instruction also can be of cognitive nature, specifying more complex human-human interaction or human-object interaction, or object-object interaction. Applying this approach sequentially allows obtaining a structural description of an image. A novel data-set of interacting humans and objects is constructed using a computer graphics engine. Using this data, we perform systematic research of relational segmentation shifts.

Keywords: cognitive science, attentin, deep learning, generalization

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2967 Expert Supporting System for Diagnosing Lymphoid Neoplasms Using Probabilistic Decision Tree Algorithm and Immunohistochemistry Profile Database

Authors: Yosep Chong, Yejin Kim, Jingyun Choi, Hwanjo Yu, Eun Jung Lee, Chang Suk Kang

Abstract:

For the past decades, immunohistochemistry (IHC) has been playing an important role in the diagnosis of human neoplasms, by helping pathologists to make a clearer decision on differential diagnosis, subtyping, personalized treatment plan, and finally prognosis prediction. However, the IHC performed in various tumors of daily practice often shows conflicting and very challenging results to interpret. Even comprehensive diagnosis synthesizing clinical, histologic and immunohistochemical findings can be helpless in some twisted cases. Another important issue is that the IHC data is increasing exponentially and more and more information have to be taken into account. For this reason, we reached an idea to develop an expert supporting system to help pathologists to make a better decision in diagnosing human neoplasms with IHC results. We gave probabilistic decision tree algorithm and tested the algorithm with real case data of lymphoid neoplasms, in which the IHC profile is more important to make a proper diagnosis than other human neoplasms. We designed probabilistic decision tree based on Bayesian theorem, program computational process using MATLAB (The MathWorks, Inc., USA) and prepared IHC profile database (about 104 disease category and 88 IHC antibodies) based on WHO classification by reviewing the literature. The initial probability of each neoplasm was set with the epidemiologic data of lymphoid neoplasm in Korea. With the IHC results of 131 patients sequentially selected, top three presumptive diagnoses for each case were made and compared with the original diagnoses. After the review of the data, 124 out of 131 were used for final analysis. As a result, the presumptive diagnoses were concordant with the original diagnoses in 118 cases (93.7%). The major reason of discordant cases was that the similarity of the IHC profile between two or three different neoplasms. The expert supporting system algorithm presented in this study is in its elementary stage and need more optimization using more advanced technology such as deep-learning with data of real cases, especially in differentiating T-cell lymphomas. Although it needs more refinement, it may be used to aid pathological decision making in future. A further application to determine IHC antibodies for a certain subset of differential diagnoses might be possible in near future.

Keywords: database, expert supporting system, immunohistochemistry, probabilistic decision tree

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2966 Congenital Sublingual Dermoid Cyst with Cutaneous Fistula

Authors: Rafael Ricieri, Rogerio Barros, Francisco Clovis

Abstract:

Objective– The Objective of this is study is to report a rare case of dermoid cyst, with a sublingual location and cutaneous fistula in a 4 year-old child.Methods: This study is a case report. The main study instrument was the medical record and the radiological and intraoperative image bank. Results: Infants with congenital cervical lesions eventually need tomography for diagnostic elucidation, and health services should be structured to perform sedation and thin tomographic sections in order to reduce morbidity.

Keywords: congenital, sublingual dermoid cyst, fistula, pediatric surgery, head and kneck surgery

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2965 Active Learning: Increase Learning through Engagement

Authors: Jihan Albayati, Kim Abdullah

Abstract:

This poster focuses on the significance of active learning strategies and their usage in the ESL classroom. Active learning is a big shift from traditional lecturing to active student engagement which can enhance and enrich student learning; therefore, engaging students is the core of this approach. Students learn more when they participate in the process of learning such as discussions, debates, analysis, synthesis, or any form of activity that requires student involvement. In order to achieve active learning, teachers can use different instructional strategies that are conducive to learning and the selection of these strategies depends on student learning outcomes. Active learning techniques must be carefully designed and integrated into the classroom to increase critical thinking and student participation. This poster provides a concise definition of active learning and its importance, instructional strategies, active learning techniques and their impact on student engagement. Also, it demonstrates the differences between passive and active learners.

Keywords: active learning, learner engagement, student-centered, teaching strategies

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2964 Femoral Neck Anteversion and Neck-Shaft Angles: Determination and Their Clinical Implications in Fetuses of Different Gestational Ages

Authors: Vrinda Hari Ankolekar, Anne D. Souza, Mamatha Hosapatna

Abstract:

Introduction: Precise anatomical assessment of femoral neck anteversion (FNA) and the neck shaft angles (NSA) would be essential in diagnosing the pathological conditions involving hip joint and its ligaments. FNA of greater than 20 degrees is considered excessive femoral anteversion, whereas a torsion angle of fewer than 10 degrees is considered femoral retroversion. Excessive femoral torsion is not uncommon and has been associated with certain neurologic and orthopedic conditions. The enlargement and maturation of the hip joint increases at the 20th week of gestation and the NSA ranges from 135- 140◦ at birth. Material and methods: 48 femurs were tagged according to the GA and two photographs for each femur were taken using Nikon digital camera. Each femur was kept on a horizontal hard desk and end on an image of the upper end was taken for the estimation of FNA and a photograph in a perpendicular plane was taken to calculate the NSA. The images were transferred to the computer and were stored in TIFF format. Microsoft Paint software was used to mark the points and Image J software was used to calculate the angles digitally. 1. Calculation of FNA: The midpoint of the femoral head and the neck were marked and a line was drawn joining these two points. The angle made by this line with the horizontal plane was measured as FNA. 2. Calculation of NSA: The midpoint of the femoral head and the neck were marked and a line was drawn joining these two points. A vertical line was drawn passing through the tip of the greater trochanter to the inter-condylar notch. The angle formed by these lines was calculated as NSA. Results: The paired t-test for the inter-observer variability showed no significant difference between the values of two observers. (FNA: t=-1.06 and p=0.31; NSA: t=-0.09 and p=0.9). The FNA ranged from 17.08º to 33.97 º on right and 17.32 º to 45.08 º on left. The NSA ranged from 139.33 º to 124.91 º on right and 143.98 º to 123.8 º on left. Unpaired t-test was applied to compare the mean angles between the second and third trimesters which did not show any statistical significance. This shows that the FNA and NSA of femur did not vary significantly during the third trimester. The FNA and NSA were correlated with the GA using Pearson’s correlation. FNA appeared to increase with the GA (r=0.5) but the increase was not statistically significant. A decrease in the NSA was also noted with the GA (r=-0.3) which was also statistically not significant. Conclusion: The present study evaluates the FNA and NSA of the femur in fetuses and correlates their development with the GA during second and third trimesters. The FNA and NSA did not vary significantly during the third trimester.

Keywords: anteversion, coxa antetorsa, femoral torsion, femur neck shaft angle

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2963 In-Flight Radiometric Performances Analysis of an Airborne Optical Payload

Authors: Caixia Gao, Chuanrong Li, Lingli Tang, Lingling Ma, Yaokai Liu, Xinhong Wang, Yongsheng Zhou

Abstract:

Performances analysis of remote sensing sensor is required to pursue a range of scientific research and application objectives. Laboratory analysis of any remote sensing instrument is essential, but not sufficient to establish a valid inflight one. In this study, with the aid of the in situ measurements and corresponding image of three-gray scale permanent artificial target, the in-flight radiometric performances analyses (in-flight radiometric calibration, dynamic range and response linearity, signal-noise-ratio (SNR), radiometric resolution) of self-developed short-wave infrared (SWIR) camera are performed. To acquire the inflight calibration coefficients of the SWIR camera, the at-sensor radiances (Li) for the artificial targets are firstly simulated with in situ measurements (atmosphere parameter and spectral reflectance of the target) and viewing geometries using MODTRAN model. With these radiances and the corresponding digital numbers (DN) in the image, a straight line with a formulation of L = G × DN + B is fitted by a minimization regression method, and the fitted coefficients, G and B, are inflight calibration coefficients. And then the high point (LH) and the low point (LL) of dynamic range can be described as LH= (G × DNH + B) and LL= B, respectively, where DNH is equal to 2n − 1 (n is the quantization number of the payload). Meanwhile, the sensor’s response linearity (δ) is described as the correlation coefficient of the regressed line. The results show that the calibration coefficients (G and B) are 0.0083 W·sr−1m−2µm−1 and −3.5 W·sr−1m−2µm−1; the low point of dynamic range is −3.5 W·sr−1m−2µm−1 and the high point is 30.5 W·sr−1m−2µm−1; the response linearity is approximately 99%. Furthermore, a SNR normalization method is used to assess the sensor’s SNR, and the normalized SNR is about 59.6 when the mean value of radiance is equal to 11.0 W·sr−1m−2µm−1; subsequently, the radiometric resolution is calculated about 0.1845 W•sr-1m-2μm-1. Moreover, in order to validate the result, a comparison of the measured radiance with a radiative-transfer-code-predicted over four portable artificial targets with reflectance of 20%, 30%, 40%, 50% respectively, is performed. It is noted that relative error for the calibration is within 6.6%.

Keywords: calibration and validation site, SWIR camera, in-flight radiometric calibration, dynamic range, response linearity

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2962 Relation between Roots and Tangent Lines of Function in Fractional Dimensions: A Method for Optimization Problems

Authors: Ali Dorostkar

Abstract:

In this paper, a basic schematic of fractional dimensional optimization problem is presented. As will be shown, a method is performed based on a relation between roots and tangent lines of function in fractional dimensions for an arbitrary initial point. It is shown that for each polynomial function with order N at least N tangent lines must be existed in fractional dimensions of 0 < α < N+1 which pass exactly through the all roots of the proposed function. Geometrical analysis of tangent lines in fractional dimensions is also presented to clarify more intuitively the proposed method. Results show that with an appropriate selection of fractional dimensions, we can directly find the roots. Method is presented for giving a different direction of optimization problems by the use of fractional dimensions.

Keywords: tangent line, fractional dimension, root, optimization problem

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2961 Computerized Adaptive Testing for Ipsative Tests with Multidimensional Pairwise-Comparison Items

Authors: Wen-Chung Wang, Xue-Lan Qiu

Abstract:

Ipsative tests have been widely used in vocational and career counseling (e.g., the Jackson Vocational Interest Survey). Pairwise-comparison items are a typical item format of ipsative tests. When the two statements in a pairwise-comparison item measure two different constructs, the item is referred to as a multidimensional pairwise-comparison (MPC) item. A typical MPC item would be: Which activity do you prefer? (A) playing with young children, or (B) working with tools and machines. These two statements aim at the constructs of social interest and investigative interest, respectively. Recently, new item response theory (IRT) models for ipsative tests with MPC items have been developed. Among them, the Rasch ipsative model (RIM) deserves special attention because it has good measurement properties, in which the log-odds of preferring statement A to statement B are defined as a competition between two parts: the sum of a person’s latent trait to which statement A is measuring and statement A’s utility, and the sum of a person’s latent trait to which statement B is measuring and statement B’s utility. The RIM has been extended to polytomous responses, such as preferring statement A strongly, preferring statement A, preferring statement B, and preferring statement B strongly. To promote the new initiatives, in this study we developed computerized adaptive testing algorithms for MFC items and evaluated their performance using simulations and two real tests. Both the RIM and its polytomous extension are multidimensional, which calls for multidimensional computerized adaptive testing (MCAT). A particular issue in MCAT for MPC items is the within-person statement exposure (WPSE); that is, a respondent may keep seeing the same statement (e.g., my life is empty) for many times, which is certainly annoying. In this study, we implemented two methods to control the WPSE rate. In the first control method, items would be frozen when their statements had been administered more than a prespecified times. In the second control method, a random component was added to control the contribution of the information at different stages of MCAT. The second control method was found to outperform the first control method in our simulation studies. In addition, we investigated four item selection methods: (a) random selection (as a baseline), (b) maximum Fisher information method without WPSE control, (c) maximum Fisher information method with the first control method, and (d) maximum Fisher information method with the second control method. These four methods were applied to two real tests: one was a work survey with dichotomous MPC items and the other is a career interests survey with polytomous MPC items. There were three dependent variables: the bias and root mean square error across person measures, and measurement efficiency which was defined as the number of items needed to achieve the same degree of test reliability. Both applications indicated that the proposed MCAT algorithms were successful and there was no loss in measurement proficiency when the control methods were implemented, and among the four methods, the last method performed the best.

Keywords: computerized adaptive testing, ipsative tests, item response theory, pairwise comparison

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2960 Describing Cognitive Decline in Alzheimer's Disease via a Picture Description Writing Task

Authors: Marielle Leijten, Catherine Meulemans, Sven De Maeyer, Luuk Van Waes

Abstract:

For the diagnosis of Alzheimer's disease (AD), a large variety of neuropsychological tests are available. In some of these tests, linguistic processing - both oral and written - is an important factor. Language disturbances might serve as a strong indicator for an underlying neurodegenerative disorder like AD. However, the current diagnostic instruments for language assessment mainly focus on product measures, such as text length or number of errors, ignoring the importance of the process that leads to written or spoken language production. In this study, it is our aim to describe and test differences between cognitive and impaired elderly on the basis of a selection of writing process variables (inter- and intrapersonal characteristics). These process variables are mainly related to pause times, because the number, length, and location of pauses have proven to be an important indicator of the cognitive complexity of a process. Method: Participants that were enrolled in our research were chosen on the basis of a number of basic criteria necessary to collect reliable writing process data. Furthermore, we opted to match the thirteen cognitively impaired patients (8 MCI and 5 AD) with thirteen cognitively healthy elderly. At the start of the experiment, participants were each given a number of tests, such as the Mini-Mental State Examination test (MMSE), the Geriatric Depression Scale (GDS), the forward and backward digit span and the Edinburgh Handedness Inventory (EHI). Also, a questionnaire was used to collect socio-demographic information (age, gender, eduction) of the subjects as well as more details on their level of computer literacy. The tests and questionnaire were followed by two typing tasks and two picture description tasks. For the typing tasks participants had to copy (type) characters, words and sentences from a screen, whereas the picture description tasks each consisted of an image they had to describe in a few sentences. Both the typing and the picture description tasks were logged with Inputlog, a keystroke logging tool that allows us to log and time stamp keystroke activity to reconstruct and describe text production processes. The main rationale behind keystroke logging is that writing fluency and flow reveal traces of the underlying cognitive processes. This explains the analytical focus on pause (length, number, distribution, location, etc.) and revision (number, type, operation, embeddedness, location, etc.) characteristics. As in speech, pause times are seen as indexical of cognitive effort. Results. Preliminary analysis already showed some promising results concerning pause times before, within and after words. For all variables, mixed effects models were used that included participants as a random effect and MMSE scores, GDS scores and word categories (such as determiners and nouns) as a fixed effect. For pause times before and after words cognitively impaired patients paused longer than healthy elderly. These variables did not show an interaction effect between the group participants (cognitively impaired or healthy elderly) belonged to and word categories. However, pause times within words did show an interaction effect, which indicates pause times within certain word categories differ significantly between patients and healthy elderly.

Keywords: Alzheimer's disease, keystroke logging, matching, writing process

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2959 An Overview on the Effectiveness of Brand Mascot and Celebrity Endorsement

Authors: Isari Pairoa, Proud Arunrangsiwed

Abstract:

Celebrity and brand mascot endorsement have been explored for more than three decades. Both endorsers can effectively transfer their reputation to corporate image and can influence the customers to purchase the product. However, there was little known about the mediators between the level of endorsement and its effect on buying behavior. The objective of the current study is to identify the gab of the previous studies and to seek possible mediators. It was found that consumer’s memory and identification are the mediators, of source credibility and endorsement effect. A future study should confirm the model of endorsement, which was established in the current study.

Keywords: product endorsement, memory, identification theory, source credibility, unintentional effect

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2958 Role of Tele-health in Expansion of Medical Care

Authors: Garima Singh, Kunal Malhotra

Abstract:

Objective: The expansion of telehealth has been instrumental in increasing access to medical services, especially for underserved and rural communities. In 2020, 14 million patients received virtual care through telemedicine and the global telemedicine market is expected to reach up to $185 million by 2023. It provides a platform and allows a patient to receive primary care as well as specialized care using technology and the comfort of their homes. Telemedicine was particularly useful during COVID-pandemic and the number of telehealth visits increased by 5000% during that time. It continues to serve as a significant resource for patients seeking care and to bridge the gap between the disease and the treatment. Method: As per APA (American Psychiatric Association), Telemedicine is the process of providing health care from a distance through technology. It is a subset of telemedicine, and can involve providing a range of services, including evaluations, therapy, patient education and medication management. It can involve direct interaction between a physician and the patient. It also encompasses supporting primary care providers with specialist consultation and expertise. It can also involve recording medical information (images, videos, etc.) and sending this to a distant site for later review. Results: In our organization, we are using telepsychiatry and serving 25 counties and approximately 1.4 million people. We provide multiple services, including inpatient, outpatient, crisis intervention, Rehab facility, autism services, case management, community treatment and multiple other modalities. With project ECHO (Extension for Community Healthcare Outcomes) it has been used to advise and assist primary care providers in treating mental health. It empowers primary care providers to treat patients in their own community by sharing knowledge. Conclusion: Telemedicine has shown to be a great medium in meeting patients’ needs and accessible mental health. It has been shown to improve access to care in both urban and rural settings by bringing care to a patient and reducing barriers like transportation, financial stress and resources. Telemedicine is also helping with reducing ER visits, integrating primary care and improving the continuity of care and follow-up. There has been substantial evidence and research about its effectiveness and its usage.

Keywords: telehealth, telemedicine, access to care, medical technology

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