Search results for: Functional Networks (FN)
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 5453

Search results for: Functional Networks (FN)

4823 The Morphogenesis of an Informal Settlement: An Examination of Street Networks through the Informal Development Stages Framework

Authors: Judith Margaret Tymon

Abstract:

As cities struggle to incorporate informal settlements into the fabric of urban areas, the focus has often been on the provision of housing. This study explores the underlying structure of street networks, with the goal of understanding the morphogenesis of informal settlements through the lens of the access network. As the stages of development progress from infill to consolidation and eventually, to a planned in-situ settlement, the access networks retain the form of the core segments; however, a majority of street patterns are adapted to a grid design to support infrastructure in the final upgraded phase. A case study is presented to examine the street network in the informal settlement of Gobabis Namibia as it progresses from its initial stages to a planned, in-situ, and permanently upgraded development. The Informal Development Stages framework of foundation, infill, and consolidation, as developed by Dr. Jota Samper, is utilized to examine the evolution of street networks. Data is gathered from historical Google Earth satellite images for the time period between 2003 and 2022. The results demonstrate that during the foundation through infill stages, incremental changes follow similar patterns, with pathways extended, lengthened, and densified as housing is created and the settlement grows. In the final stage of consolidation, the resulting street layout is transformed to support the installation of infrastructure; however, some elements of the original street patterns remain. The core pathways remain intact to accommodate the installation of infrastructure and the creation of housing plots, defining the shape of the settlement and providing the basis of the urban form. The adaptations, growth, and consolidation of the street network are critical to the eventual formation of the spatial layout of the settlement. This study will include a comparative analysis of findings with those of recent research performed by Kamalipour, Dovey, and others regarding incremental urbanism within informal settlements. Further comparisons will also include studies of street networks of well-established urban centers that have shown links between the morphogenesis of access networks and the eventual spatial layout of the city. The findings of the study can be used to guide and inform strategies for in-situ upgrading and can contribute to the sustainable development of informal settlements.

Keywords: Gobabis Namibia, incremental urbanism, informal development stages, informal settlements, street networks

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4822 Role of Interlayer Coupling for the Power Factor of CuSbS2 and CuSbSe2

Authors: Najebah Alsaleh, Nirpendra Singh, Udo Schwingenschlogl

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The electronic and transport properties of bulk and monolayer CuSbS2 and CuSbSe2 are determined by using density functional theory and semiclassical Boltzmann transport theory, in order to investigate the role of interlayer coupling for the thermoelectric properties. The calculated band gaps of the bulk compounds are in agreement with experiments and significantly higher than those of the monolayers, which thus show lower Seebeck coefficients. Since also the electrical conductivity is lower, the monolayers are characterized by lower power factors. Therefore, interlayer coupling is found to be essential for the excellent thermoelectric response of CuSbS2 and CuSbSe2, even though it is weak.

Keywords: density functional theory, thermoelectric, electronic properties, monolayer

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4821 A Study of Behaviors in Using Social Networks of Corporate Personnel of Suan Sunandha Rajabhat University

Authors: Wipada Chaiwchan

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This research aims to study behaviors in using social networks of Corporate personnel of Suan Sunandha Rajabhat University. The sample used in the study were two groups: 1) Academic Officer 70 persons and 2) Operation Officer 143 persons were used in this study. The tools in this research consisted of questionnaire which the data were analyzed by using percentage, average (X) and Standard deviation (S.D.) and Independent Sample T-Test to test the difference between the mean values obtained from two independent samples, and One-way anova to analysis of variance, and Multiple comparisons to test that the average pair of different methods by Fisher’s Least Significant Different (LSD). The study result found that the most of corporate personnel have purpose in using social network to information awareness aspect was knowledge and online conference with social media. By using the average more than 3 hours per day in everyday. Using time in working in one day and there are computers connected to the Internet at home, by using the communication in the operational processes. Behaviors using social networks in relation to gender, age, job title, department, and type of personnel. Hypothesis testing, and analysis of variance for the effects of this analysis is divided into three aspects: The use of online social networks, the attitude of the users and the security analysis has found that Corporate Personnel of Suan Sunandha Rajabhat University. Overall and specifically at the high level, and considering each item found all at a high level. By sorting of the social network (X=3.22), The attitude of the users (X= 3.06) and the security (X= 3.11). The overall behaviors using of each side (X=3.11).

Keywords: social network, behaviors, social media, computer information systems

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4820 Estimation of Forces Applied to Forearm Using EMG Signal Features to Control of Powered Human Arm Prostheses

Authors: Faruk Ortes, Derya Karabulut, Yunus Ziya Arslan

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Myoelectric features gathering from musculature environment are considered on a preferential basis to perceive muscle activation and control human arm prostheses according to recent experimental researches. EMG (electromyography) signal based human arm prostheses have shown a promising performance in terms of providing basic functional requirements of motions for the amputated people in recent years. However, these assistive devices for neurorehabilitation still have important limitations in enabling amputated people to perform rather sophisticated or functional movements. Surface electromyogram (EMG) is used as the control signal to command such devices. This kind of control consists of activating a motion in prosthetic arm using muscle activation for the same particular motion. Extraction of clear and certain neural information from EMG signals plays a major role especially in fine control of hand prosthesis movements. Many signal processing methods have been utilized for feature extraction from EMG signals. The specific objective of this study was to compare widely used time domain features of EMG signal including integrated EMG(IEMG), root mean square (RMS) and waveform length(WL) for prediction of externally applied forces to human hands. Obtained features were classified using artificial neural networks (ANN) to predict the forces. EMG signals supplied to process were recorded during only type of muscle contraction which is isometric and isotonic one. Experiments were performed by three healthy subjects who are right-handed and in a range of 25-35 year-old aging. EMG signals were collected from muscles of the proximal part of the upper body consisting of: biceps brachii, triceps brachii, pectorialis major and trapezius. The force prediction results obtained from the ANN were statistically analyzed and merits and pitfalls of the extracted features were discussed with detail. The obtained results are anticipated to contribute classification process of EMG signal and motion control of powered human arm prosthetics control.

Keywords: assistive devices for neurorehabilitation, electromyography, feature extraction, force estimation, human arm prosthesis

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4819 Analysis of Arthroscopic Rotator Cuff Repair

Authors: Prakash Karrun, M. Manoj Deepak, Mathivanan, K. Venkatachalam

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Our study aims to evaluate the rates of healing and the efficacy of the arthroscopic repair of the rotator cuff tears. 40 patients who had rotator cuff tears were taken up for the study and arthroscopic repair was done with double row technique.They were evaluated and followed up for a minimum of 2 years minimum.The functional status,range of motion and healing rates were compared post operatively. All the patients were followed up with serial questionnaires and MRI at the end of 2 years. There was significant improvement in the functional status of the patient. The MRI showed better rates of healing in these patients.Thus our study effectively proves the efficacy of our operating technique.

Keywords: rotator cuff tear, arthroscopic repair, double stich, healing

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4818 Swallowing Outcomes in Supraglottic Cancer Patients after Trans-Oral Robotic Surgery (TORS) Provided with Early Dysphagia Management Using Standardized Functional and Objective Measures

Authors: Hitesh Gupta, Surender Dabas

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TORS is increasingly gaining widespread use and has been explored as minimally invasive surgery for the treatment of supraglottic cancer (SGC). Being a central critical role of Supraglottis in deglutition, swallowing outcomes post TORS remain a most important factor. Available published studies show inconsistent swallowing outcomes and are deficient in standardized outcome measures, description of swallowing recovery and rehabilitation. So, the objective of this study is to find out swallowing outcomes in SGC patients after TORS provided with early dysphagia management using standardized measures. Prospectively 16 patients were recruited in the study who underwent TORS for primary tumor of Supraglottis, involving one or more sub-sites or invading to sites other than Supraglottis at the BLK Super Specialty Hospital, New Delhi from March 2019 to June 2020. All patients were evaluated for dysphagia with subsequent swallowing rehabilitation on post operative day 3 in the hospital or at the time of discharge, whichever was earlier. Functional oral intake scale (FOIS) and penetration-aspiration score (PAS) were used as outcome measures to quantify swallowing recovery at one month and six month post operatively. Post TORS, patients achieved functional swallow in less than one month, where resection was limited to Supraglottis, while the recovery was delayed in patients with extended resection to tongue base or hypopharynx. Overall, out of Total 16 cases including all supraglottis sub-catagories, 13 (81%) could remove their NG tube (FOIS ≥5 and PAS=1 ) within 6 months. In which 8 cases(62%) achieved functional swallow in less than one month. Swallowing outcomes post TORS supraglottic laryngectomy are favorable if provided with early dysphagia management (or swallowing rehabilitation).

Keywords: dysphagia, supraglottic cancer, swallowing, TORS

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4817 Movie and Theater Marketing Using the Potentials of Social Networks

Authors: Seyed Reza Naghibulsadat

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The nature of communication includes various forms of media productions, which include film and theater. In the current situation, since social networks have emerged, they have brought their own communication capabilities and have features that show speed, public access, lack of media organization and the production of extensive content, and the development of critical thinking; Also, they contain capabilities to develop access to all kinds of media productions, including movies and theater shows; Of course, this works differently in different conditions and communities. In terms of the scale of exploitation, the film has a more general audience, and the theater has a special audience. The film industry is more developed based on more modern technologies, but the theater, based on the older ways of communication, contains more intimate and emotional aspects. ; But in general, the main focus is the development of access to movies and theater shows, which is emphasized by those involved in this field due to the capabilities of social networks. In this research, we will look at these 2 areas and the relevant components for both areas through social networks and also the common points of both types of media production. The main goal of this research is to know the strengths and weaknesses of using social networks for the marketing of movies and theater shows and, at the same time are, also considered the opportunities and threats of this field. The attractions of these two types of media production, with the emergence of social networks, and the ability to change positions, can provide the opportunity to become a media with greater exploitation and higher profitability; But the main consideration is the opinions about these capabilities and the ability to use them for film and theater marketing. The main question of the research is, what are the marketing components for movies and theaters using social media capabilities? What are its strengths and weaknesses? And what opportunities and threats are facing this market? This research has been done with two methods SWOT and meta-analysis. Non-probability sampling has been used with purposeful technique. The results show that a recent approach is an approach based on eliminating threats and weaknesses and emphasizing strengths, and exploiting opportunities in the direction of developing film and theater marketing based on the capabilities of social networks within the framework of local cultural values and presenting achievements on an international scale or It is universal. This introduction leads to the introduction of authentic Iranian culture and foreign enthusiasts in the framework of movies and theater art. Therefore, for this issue, the model for using the capabilities of social networks for movie or theater marketing, according to the results obtained from Respondents, is a model based on SO strategies and, in other words, offensive strategies so that it can take advantage of the internal strengths and made maximum use of foreign situations and opportunities to develop the use of movies and theater performances.

Keywords: marketing, movies, theatrical show, social network potentials

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4816 Presentation of a Mix Algorithm for Estimating the Battery State of Charge Using Kalman Filter and Neural Networks

Authors: Amin Sedighfar, M. R. Moniri

Abstract:

Determination of state of charge (SOC) in today’s world becomes an increasingly important issue in all the applications that include a battery. In fact, estimation of the SOC is a fundamental need for the battery, which is the most important energy storage in Hybrid Electric Vehicles (HEVs), smart grid systems, drones, UPS and so on. Regarding those applications, the SOC estimation algorithm is expected to be precise and easy to implement. This paper presents an online method for the estimation of the SOC of Valve-Regulated Lead Acid (VRLA) batteries. The proposed method uses the well-known Kalman Filter (KF), and Neural Networks (NNs) and all of the simulations have been done with MATLAB software. The NN is trained offline using the data collected from the battery discharging process. A generic cell model is used, and the underlying dynamic behavior of the model has used two capacitors (bulk and surface) and three resistors (terminal, surface, and end), where the SOC determined from the voltage represents the bulk capacitor. The aim of this work is to compare the performance of conventional integration-based SOC estimation methods with a mixed algorithm. Moreover, by containing the effect of temperature, the final result becomes more accurate. 

Keywords: Kalman filter, neural networks, state-of-charge, VRLA battery

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4815 Yoghurt Kepel Stelechocarpus burahol as an Effort of Functional Food Diversification from Region of Yogyakarta

Authors: Dian Nur Amalia, Rifqi Dhiemas Aji, Tri Septa Wahyuningsih, Endang Wahyuni

Abstract:

Kepel fruit (Stelechocarpus burahol) is a scarce fruit that belongs as a logogram of Daerah Istimewa Yogyakarta. Kepel fruit can be used as substance of beauty treatment product, such as deodorant and good for skin health, and also contains antioxidant compound. Otherwise, this fruit is scarcely cultivated by people because of its image as a palace fruit and also the flesh percentage just a little, so it has low economic value. The flesh of kepel fruit is about 49% of its whole fruit. This little part as supporting point why kepel fruit has to be extracted and processed with the other product. Yoghurt is milk processing product that also have a role as functional food. Economically, the price of yoghurt is higher than whole milk or other milk processing product. Yoghurt is usually added with flavor of dye from plant or from chemical substance. Kepel fruit has a role as flavor in yoghurt, besides as product that good for digestion, yoghurt with kepel also has function as “beauty” food. Writing method that used is literature study by looking for the potential of kepel fruit as a local fruit of Yogyakarta and yoghurt as milk processing product. The process just like making common yoghurt because kepel fruit just have a role as flavor substance, so it does not affect to the other processing of yoghurt. Food diversification can be done as an effort to increase the value of local resources that proper to compete in Asean Economic Community (AEC), one of the way is producing kepel yoghurt.

Keywords: kepel, yoghurt, Daerah Istimewa Yogyakarta, functional food

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4814 Testifying in Court as a Victim of Crime for Persons with Little or No Functional Speech: Vocabulary Implications

Authors: Robyn White, Juan Bornman, Ensa Johnson

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People with disabilities are at a high risk of becoming victims of crime. Individuals with little or no functional speech (LNFS) face an even higher risk. One way of reducing the risk of remaining a victim of crime is to face the alleged perpetrator in court as a witness – therefore it is important for a person with LNFS who has been a victim of crime to have the required vocabulary to testify in court. The aim of this study was to identify and describe the core and fringe legal vocabulary required by illiterate victims of crime, who have little or no functional speech, to testify in court as witnesses. A mixed-method, the exploratory sequential design consisting of two distinct phases was used to address the aim of the research. The first phase was of a qualitative nature and included two different data sources, namely in-depth semi-structured interviews and focus group discussions. The overall aim of this phase was to identify and describe core and fringe legal vocabulary and to develop a measurement instrument based on these results. Results from Phase 1 were used in Phase 2, the quantitative phase, during which the measurement instrument (a custom-designed questionnaire) was socially validated. The results produced six distinct vocabulary categories that represent the legal core vocabulary and 99 words that represent the legal fringe vocabulary. The findings suggested that communication boards should be individualised to the individual and the specific crime. It is believed that the vocabulary lists developed in this study act as a valid and reliable springboard from which communication boards can be developed. Recommendations were therefore made to develop an Alternative and Augmentative Communication Resource Tool Kit to assist the legal justice system.

Keywords: augmentative and alternative communication, person with little or no functional speech, sexual crimes, testifying in court, victim of crime, witness competency

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4813 Using Machine Learning to Classify Different Body Parts and Determine Healthiness

Authors: Zachary Pan

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Our general mission is to solve the problem of classifying images into different body part types and deciding if each of them is healthy or not. However, for now, we will determine healthiness for only one-sixth of the body parts, specifically the chest. We will detect pneumonia in X-ray scans of those chest images. With this type of AI, doctors can use it as a second opinion when they are taking CT or X-ray scans of their patients. Another ad-vantage of using this machine learning classifier is that it has no human weaknesses like fatigue. The overall ap-proach to this problem is to split the problem into two parts: first, classify the image, then determine if it is healthy. In order to classify the image into a specific body part class, the body parts dataset must be split into test and training sets. We can then use many models, like neural networks or logistic regression models, and fit them using the training set. Now, using the test set, we can obtain a realistic accuracy the models will have on images in the real world since these testing images have never been seen by the models before. In order to increase this testing accuracy, we can also apply many complex algorithms to the models, like multiplicative weight update. For the second part of the problem, to determine if the body part is healthy, we can have another dataset consisting of healthy and non-healthy images of the specific body part and once again split that into the test and training sets. We then use another neural network to train on those training set images and use the testing set to figure out its accuracy. We will do this process only for the chest images. A major conclusion reached is that convolutional neural networks are the most reliable and accurate at image classification. In classifying the images, the logistic regression model, the neural network, neural networks with multiplicative weight update, neural networks with the black box algorithm, and the convolutional neural network achieved 96.83 percent accuracy, 97.33 percent accuracy, 97.83 percent accuracy, 96.67 percent accuracy, and 98.83 percent accuracy, respectively. On the other hand, the overall accuracy of the model that de-termines if the images are healthy or not is around 78.37 percent accuracy.

Keywords: body part, healthcare, machine learning, neural networks

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4812 Nutritional and Functional Composition of Prickly Pear Cactus (Opuntia ficus-indica Mill.) Grown in Algeria

Authors: Kamel Cheriet

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In Algeria, Opuntia ficus Indica production is important. This seasonal fruit is a characteristic of arid and semi-arid regions. Taking into account its high content in antioxidants, it has an excellent nutritional value. The aim of this research is the prickly pear morphological and physicochemical characterization study which is widely present in the Arris (Batna, Algeria) area. The results of this experimental study are comparative to those of the same species from other world regions. The whole fruit weight is estimated to reach 63.38 g with a juice ratio of 71.42%, a pH of 5.54, moisture of 89.3% and a brix of 10.4°. The quantitative amount of the phenolic compounds of the fruit revealed contents of 20.65-45.70 mg / 100 g of MF for total polyphenols and 0.519 -0.591 mg / 100 g of MF for the flavonoids.

Keywords: functional composition, nutritionals properties, opuntia ficus indica, phenolic compounds

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4811 Investigation of Different Stimulation Patterns to Reduce Muscle Fatigue during Functional Electrical Stimulation

Authors: R. Ruslee, H. Gollee

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Functional electrical stimulation (FES) is a commonly used technique in rehabilitation and often associated with rapid muscle fatigue which becomes the limiting factor in its applications. The objective of this study is to investigate the effects on the onset of fatigue of conventional synchronous stimulation, as well as asynchronous stimulation that mimic voluntary muscle activation targeting different motor units which are activated sequentially or randomly via multiple pairs of stimulation electrodes. We investigate three different approaches with various electrode configurations, as well as different patterns of stimulation applied to the gastrocnemius muscle: Conventional Synchronous Stimulation (CSS), Asynchronous Sequential Stimulation (ASS) and Asynchronous Random Stimulation (ARS). Stimulation was applied repeatedly for 300 ms followed by 700 ms of no-stimulation with 40 Hz effective frequency for all protocols. Ten able-bodied volunteers (28±3 years old) participated in this study. As fatigue indicators, we focused on the analysis of Normalized Fatigue Index (NFI), Fatigue Time Interval (FTI) and pre-post Twitch-Tetanus Ratio (ΔTTR). The results demonstrated that ASS and ARS give higher NFI and longer FTI confirming less fatigue for asynchronous stimulation. In addition, ASS and ARS resulted in higher ΔTTR than conventional CSS. In this study, we proposed a randomly distributed stimulation method for the application of FES and investigated its suitability for reducing muscle fatigue compared to previously applied methods. The results validated that asynchronous stimulation reduces fatigue, and indicates that random stimulation may improve fatigue resistance in some conditions.

Keywords: asynchronous stimulation, electrode configuration, functional electrical stimulation (FES), muscle fatigue, pattern stimulation, random stimulation, sequential stimulation, synchronous stimulation

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4810 A Feasibility Study of Crowdsourcing Data Collection for Facility Maintenance Management

Authors: Mohamed Bin Alhaj, Hexu Liu, Mohammed Sulaiman, Osama Abudayyeh

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An effective facility maintenance management (FMM) system plays a crucial role in improving the quality of services and maintaining the facility in good condition. Current FMM heavily relies on the quality of the data collection function of the FMM systems, at times resulting in inefficient FMM decision-making. The new technology-based crowdsourcing provides great potential to improve the current FMM practices, especially in terms of timeliness and quality of data. This research aims to investigate the feasibility of using new technology-driven crowdsourcing for FMM and highlight its opportunities and challenges. A survey was carried out to understand the human, data, system, geospatial, and automation characteristics of crowdsourcing for an educational campus FMM via social networks. The survey results were analyzed to reveal the challenges and recommendations for the implementation of crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges and opportunities of using crowdsourcing for facility maintenance and providing a road map for applying crowdsourcing technology in FMM. In future work, a conceptual framework will be proposed to support data-driven FMM using social networks.

Keywords: crowdsourcing, facility maintenance management, social networks

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4809 An Approach to Specify Software Requirements in Semantic Form

Authors: Deepa Vijay, Chellammal Surianarayanan, Gopinath Ganapathy

Abstract:

Requirements of a software project serve as a guideline for the entire project team which enable the team towards producing the right outcome. As requirements are the key in deciding the success of the project, it should be specified in an unambiguous manner. Also, the requirements should be complete and consistent. It should be interpreted in the same way by the entire software project team as the customer interprets. Specifying requirements in textual manner is common in software development. This leads to poor understanding of the requirements which results in more errors and degraded quality. There are some literatures which focus on semantic way of specifying functional requirement which ensure the consistency and completeness of requirements. Alternately in the work, a method is proposed to map the syntactic requirements with corresponding semantics in the form of ontologies. This improves the understanding of requirements, prevents errors and improves quality.

Keywords: functional requirement, ontology, requirements management, semantics

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4808 NANCY: Combining Adversarial Networks with Cycle-Consistency for Robust Multi-Modal Image Registration

Authors: Mirjana Ruppel, Rajendra Persad, Amit Bahl, Sanja Dogramadzi, Chris Melhuish, Lyndon Smith

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Multimodal image registration is a profoundly complex task which is why deep learning has been used widely to address it in recent years. However, two main challenges remain: Firstly, the lack of ground truth data calls for an unsupervised learning approach, which leads to the second challenge of defining a feasible loss function that can compare two images of different modalities to judge their level of alignment. To avoid this issue altogether we implement a generative adversarial network consisting of two registration networks GAB, GBA and two discrimination networks DA, DB connected by spatial transformation layers. GAB learns to generate a deformation field which registers an image of the modality B to an image of the modality A. To do that, it uses the feedback of the discriminator DB which is learning to judge the quality of alignment of the registered image B. GBA and DA learn a mapping from modality A to modality B. Additionally, a cycle-consistency loss is implemented. For this, both registration networks are employed twice, therefore resulting in images ˆA, ˆB which were registered to ˜B, ˜A which were registered to the initial image pair A, B. Thus the resulting and initial images of the same modality can be easily compared. A dataset of liver CT and MRI was used to evaluate the quality of our approach and to compare it against learning and non-learning based registration algorithms. Our approach leads to dice scores of up to 0.80 ± 0.01 and is therefore comparable to and slightly more successful than algorithms like SimpleElastix and VoxelMorph.

Keywords: cycle consistency, deformable multimodal image registration, deep learning, GAN

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4807 Opto-Electronic Properties of Novel Structures: Sila-Fulleranes

Authors: Farah Marsusi, Mohammad Qasemnazhand

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Density-functional theory (DFT) was applied to investigate the geometry and electronic properties H-terminated Si-fullerene (Si-fullerane). Natural bond orbital (NBO) analysis confirms sp3 hybridization nature of Si-Si bonds in Si-fulleranes. Quantum confinement effect (QCE) does not affect band gap (BG) so strongly in the size between 1 to 1.7 nm. In contrast, the geometry and symmetry of the cage have significant influence on BG. In contrast to their carbon analogues, pentagon rings increase the stability of the cages. Functionalized Si-cages are stable and can be chemically very active. The electronic properties are highly sensitive to the surface chemistry via functionalization with different chemical groups. As a result, BGs and chemical activities of these cages can be drastically tuned through the chemistry of the surface.

Keywords: density functional theory, sila-fullerens, NBO analysis, opto-electronic properties

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4806 Integrated Finishing of Textiles

Authors: Geetal Mahajan, R. V. Adivarekar

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In this research, an attempt has been made to develop integrated finish on textile fabrics. The demand for mosquito repellent, flame retardant, and water repellent finished fabric has increased. Integrated finishing was done using commercially available products. These finishing agents were first assessed individually for their functional properties and then used in combination with other agents. Dip-air dry and pad-dry-cure (PDC) were two different methods used for fabric finishing. The finished fabric was assessed using spray test, limiting oxygen index and mosquito repellence test. Integrated finished fabric is in great demand by the customers as it increases the aesthetic as well as the functional properties of the fabric with added benefit of water and energy conservation.

Keywords: flame retardant, integrated finishing, mosquito repellent, textiles, water repellent

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4805 A Study on Using Network Coding for Packet Transmissions in Wireless Sensor Networks

Authors: Rei-Heng Cheng, Wen-Pinn Fang

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A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.

Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks

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4804 “Octopub”: Geographical Sentiment Analysis Using Named Entity Recognition from Social Networks for Geo-Targeted Billboard Advertising

Authors: Oussama Hafferssas, Hiba Benyahia, Amina Madani, Nassima Zeriri

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Although data nowadays has multiple forms; from text to images, and from audio to videos, yet text is still the most used one at a public level. At an academical and research level, and unlike other forms, text can be considered as the easiest form to process. Therefore, a brunch of Data Mining researches has been always under its shadow, called "Text Mining". Its concept is just like data mining’s, finding valuable patterns in data, from large collections and tremendous volumes of data, in this case: Text. Named entity recognition (NER) is one of Text Mining’s disciplines, it aims to extract and classify references such as proper names, locations, expressions of time and dates, organizations and more in a given text. Our approach "Octopub" does not aim to find new ways to improve named entity recognition process, rather than that it’s about finding a new, and yet smart way, to use NER in a way that we can extract sentiments of millions of people using Social Networks as a limitless information source, and Marketing for product promotion as the main domain of application.

Keywords: textmining, named entity recognition(NER), sentiment analysis, social media networks (SN, SMN), business intelligence(BI), marketing

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4803 Prediction of Bodyweight of Cattle by Artificial Neural Networks Using Digital Images

Authors: Yalçın Bozkurt

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Prediction models were developed for accurate prediction of bodyweight (BW) by using Digital Images of beef cattle body dimensions by Artificial Neural Networks (ANN). For this purpose, the animal data were collected at a private slaughter house and the digital images and the weights of each live animal were taken just before they were slaughtered and the body dimensions such as digital wither height (DJWH), digital body length (DJBL), digital body depth (DJBD), digital hip width (DJHW), digital hip height (DJHH) and digital pin bone length (DJPL) were determined from the images, using the data with 1069 observations for each traits. Then, prediction models were developed by ANN. Digital body measurements were analysed by ANN for body prediction and R2 values of DJBL, DJWH, DJHW, DJBD, DJHH and DJPL were approximately 94.32, 91.31, 80.70, 83.61, 89.45 and 70.56 % respectively. It can be concluded that in management situations where BW cannot be measured it can be predicted accurately by measuring DJBL and DJWH alone or both DJBD and even DJHH and different models may be needed to predict BW in different feeding and environmental conditions and breeds

Keywords: artificial neural networks, bodyweight, cattle, digital body measurements

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4802 Efficacy of Hemi-Facetectomy in Treatment of Lumbar Foraminal Stenosis

Authors: Manoj Deepak, N. Mathivanan, K. Venkatachalam

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Nerve root stenosis is one of the main cause for back pain. There are many methods both conservative and surgical to treat this disease. It is pertinent to decompress the spine to a proper extent so as to avoid the recurrence of symptoms. But too much of an aggressive approach also has its disadvantages. We present one of the methods to effectively decompress the nerve with better results. Our study was carried out in 52 patients with foramina stenosis between 2008 to 2011.We carried out the surgical procedure of shaving off the medial part of the facet joint so as to decompress the root. We selected those patients who had symptoms of claudication for more than 2 years. They had no signs of instability and they underwent conservative treatment for a period of 2 months before the procedure. Oswersty scoring was used to record the functional level of the patient before and after the procedure. All patients were followed up for a period of minimum 2.5 years. After evaluation for a minimum of 2.5 years, 34 patients had no evidence of recurrence of symptoms with improvement in the functional level.7 patients complained of minimal pain but their functional quality had improved postop. Six patients had symptoms of lumbar canal disease which reduced with conservative treatment. 5 patients required spinal fusion surgeries in the later period. Conclusion: Thus, we can effectively conclude that our procedure is safe and effective in reducing the symptoms in those patients with neurogenic claudication.

Keywords: facetectoemy, stenosis, decompression, Lumbar Foraminal Stenosis, hemi-facetectomy

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4801 Worst-Case Load Shedding in Electric Power Networks

Authors: Fu Lin

Abstract:

We consider the worst-case load-shedding problem in electric power networks where a number of transmission lines are to be taken out of service. The objective is to identify a prespecified number of line outages that lead to the maximum interruption of power generation and load at the transmission level, subject to the active power-flow model, the load and generation capacity of the buses, and the phase-angle limit across the transmission lines. For this nonlinear model with binary constraints, we show that all decision variables are separable except for the nonlinear power-flow equations. We develop an iterative decomposition algorithm, which converts the worst-case load shedding problem into a sequence of small subproblems. We show that the subproblems are either convex problems that can be solved efficiently or nonconvex problems that have closed-form solutions. Consequently, our approach is scalable for large networks. Furthermore, we prove the convergence of our algorithm to a critical point, and the objective value is guaranteed to decrease throughout the iterations. Numerical experiments with IEEE test cases demonstrate the effectiveness of the developed approach.

Keywords: load shedding, power system, proximal alternating linearization method, vulnerability analysis

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4800 Investigation about Structural and Optical Properties of Bulk and Thin Film of 1H-CaAlSi by Density Functional Method

Authors: M. Babaeipour, M. Vejdanihemmat

Abstract:

Optical properties of bulk and thin film of 1H-CaAlSi for two directions (1,0,0) and (0,0,1) were studied. The calculations are carried out by Density Functional Theory (DFT) method using full potential. GGA approximation was used to calculate exchange-correlation energy. The calculations are performed by WIEN2k package. The results showed that the absorption edge is shifted backward 0.82eV in the thin film than the bulk for both directions. The static values of the real part of dielectric function for four cases were obtained. The static values of the refractive index for four cases are calculated too. The reflectivity graphs have shown an intensive difference between the reflectivity of the thin film and the bulk in the ultraviolet region.

Keywords: 1H-CaAlSi, absorption, bulk, optical, thin film

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4799 Translation Choices of Logical Meaning from Chinese into English: A Systemic Functional Linguistics Perspective

Authors: Xueying Li

Abstract:

Different from English, it is common to observe Chinese clauses logically related in an implicit way without any conjunctions. This typological difference has posed a great challenge for Chinese-English translators, as 1) translators may interpret logical meaning in different ways when there are no conjunctions in Chinese Source Text (ST); 2) translators may have questions whether to make Chinese implicit logical meaning explicit or to remain implicit in Target Text (TT), and whether other dimensions of logical meaning (e.g., type of logical meaning) should be shifted or not. Against this background, this study examines a comprehensive arrange of Chinese-English translation choices of logical meaning to deal with this challenge in a systematic way. It compiles several ST-TT passages from a set of translation textbooks in a corpus, namely Ying Yu Bi Yi Shi Wu (Er Ji)) [Translation Practice between Chinese and English: Intermediate Level] and its supportive training book, analyzes how logical meaning in ST are translated in TT in texts across different text types with Systemic Functional Linguistics (SFL) as the theoretical framework, and finally draws a system network of translation choices of logical meaning from Chinese into English. Since translators may probably think about semantic meaning rather than lexico-grammatical resources in translation, this study goes away from traditional lexico-grammatical choices, but rather describing translation choices from the semantic level. The findings in this study can provide some help and support for translation practitioners so that they can understand that besides explicitation, there are a variety of possible linguistic choices available for making informed decisions when translating Chinese logical meaning into English.

Keywords: Chinese-English translation, logical meaning, systemic functional linguistics, translation choices

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4798 Analysis of Decentralized on Demand Cross Layer in Cognitive Radio Ad Hoc Network

Authors: A. Sri Janani, K. Immanuel Arokia James

Abstract:

Cognitive radio ad hoc networks different unlicensed users may acquire different available channel sets. This non-uniform spectrum availability imposes special design challenges for broadcasting in CR ad hoc networks. Cognitive radio automatically detects available channels in wireless spectrum. This is a form of dynamic spectrum management. Cross-layer optimization is proposed, using this can allow far away secondary users can also involve into channel work. So it can increase the throughput and it will overcome the collision and time delay.

Keywords: cognitive radio, cross layer optimization, CR mesh network, heterogeneous spectrum, mesh topology, random routing optimization technique

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4797 Electricity Price Forecasting: A Comparative Analysis with Shallow-ANN and DNN

Authors: Fazıl Gökgöz, Fahrettin Filiz

Abstract:

Electricity prices have sophisticated features such as high volatility, nonlinearity and high frequency that make forecasting quite difficult. Electricity price has a volatile and non-random character so that, it is possible to identify the patterns based on the historical data. Intelligent decision-making requires accurate price forecasting for market traders, retailers, and generation companies. So far, many shallow-ANN (artificial neural networks) models have been published in the literature and showed adequate forecasting results. During the last years, neural networks with many hidden layers, which are referred to as DNN (deep neural networks) have been using in the machine learning community. The goal of this study is to investigate electricity price forecasting performance of the shallow-ANN and DNN models for the Turkish day-ahead electricity market. The forecasting accuracy of the models has been evaluated with publicly available data from the Turkish day-ahead electricity market. Both shallow-ANN and DNN approach would give successful result in forecasting problems. Historical load, price and weather temperature data are used as the input variables for the models. The data set includes power consumption measurements gathered between January 2016 and December 2017 with one-hour resolution. In this regard, forecasting studies have been carried out comparatively with shallow-ANN and DNN models for Turkish electricity markets in the related time period. The main contribution of this study is the investigation of different shallow-ANN and DNN models in the field of electricity price forecast. All models are compared regarding their MAE (Mean Absolute Error) and MSE (Mean Square) results. DNN models give better forecasting performance compare to shallow-ANN. Best five MAE results for DNN models are 0.346, 0.372, 0.392, 0,402 and 0.409.

Keywords: deep learning, artificial neural networks, energy price forecasting, turkey

Procedia PDF Downloads 276
4796 Biomechanical Evaluation of the Chronic Stroke with 3D-Printed Hand Device

Authors: Chen-Sheng Chen, Tsung-Yi Huang, Pi-Chang Sun

Abstract:

Chronic stroke patients often have complaints about hand dysfunction due to flexor hypertonia and extensor weakness, which makes it difficult to open their affected hand for functional grasp. Hand rehabilitation after stroke is essential for restoring functional independence. Constraint-induced movement therapy has shown to be a successful treatment for patients who have acquired certain level of wrist and finger extension. The goal of this study was to investigate the feasibility of task-oriented approach incorporating 3D-printed dynamic hand device by evaluating hand functional performance. This study manufactured a hand device using 3d printer for chronic stroke. The experimental group engaged task-oriented approach with dynamic hand device, but the control group only received task-oriented approach. Outcome measurements include palmar pinch force (PPF), lateral pinch force (LPF), grip force (GF), and Box and Blocks Test (BBT). The results of study revealed the improvement of PPF in experimental group but not in control group. Meanwhile, improvement in LPF, GF and BBT can be found in both groups. This study demonstrates that the 3D-printed dynamic hand device is an effective therapeutic assistive device to improve pinch force, grasp force, and dexterity and facilitate motivation during home program in individuals with chronic stroke.

Keywords: 3D printing, biomechanics, hand orthosis, stroke

Procedia PDF Downloads 251
4795 Evaluation of the Nutritional Potential of a Developed Spice Formulation for nah poh (An Emulsion-Based Gravy): Physicochemical and Techno-Functional Characterisations

Authors: Djiazet Stève, Mezajoug Kenfack Laurette Blandine, Ravi Pullakhandam, Bethala L. A. Prabhavathi Devi, Tchiegang Clergé, Prathapkumar Halady Shetty

Abstract:

The nutritional potential of a developed spice formulation for nah poh was evaluated. It was found that when spices were used for the formulation for nah poh, the concentration of some nutrients is diluted while that of some of them increases. The proportion of unsaturated fats was estimated to be 76.2% of the total fat content while the chemical score varied between 31 to 39%. The contents of some essential minerals of nutritional interest in mg are as follows for 100g of spice: 2372.474 ± 0.007 for potassium, 16.447 ± 0.010 for iron, 4.772 ± 0.005 for zinc, 0.537 ± 0.001 for cupper, 0.138 ± 0.005 for selenium, and 112.954 ± 0.003 for manganese. This study shows that the consumption of these spices in the form of formulation significantly contributes to meet the mineral requirements of the populations whose food habits regularly require these spices.

Keywords: spice formulation, characterisation, nutritional potential, nah poh, techno functional properties

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4794 Perception-Oriented Model Driven Development for Designing Data Acquisition Process in Wireless Sensor Networks

Authors: K. Indra Gandhi

Abstract:

Wireless Sensor Networks (WSNs) have always been characterized for application-specific sensing, relaying and collection of information for further analysis. However, software development was not considered as a separate entity in this process of data collection which has posed severe limitations on the software development for WSN. Software development for WSN is a complex process since the components involved are data-driven, network-driven and application-driven in nature. This implies that there is a tremendous need for the separation of concern from the software development perspective. A layered approach for developing data acquisition design based on Model Driven Development (MDD) has been proposed as the sensed data collection process itself varies depending upon the application taken into consideration. This work focuses on the layered view of the data acquisition process so as to ease the software point of development. A metamodel has been proposed that enables reusability and realization of the software development as an adaptable component for WSN systems. Further, observing users perception indicates that proposed model helps in improving the programmer's productivity by realizing the collaborative system involved.

Keywords: data acquisition, model-driven development, separation of concern, wireless sensor networks

Procedia PDF Downloads 417