Search results for: local stakeholders network
Commenced in January 2007
Frequency: Monthly
Edition: International
Paper Count: 11063

Search results for: local stakeholders network

8723 Cultural Collisions, Ethics and HIV: On Local Values in a Globalized Medical World

Authors: Norbert W. Paul

Abstract:

In 1988, parts of the scientific community still heralded findings to support that AIDS was likely to remain largely a ‘gay disease’. The value-ladden terminology of some of the articles suggested that rectum and fragile urethra are not sufficiently robust to provide a barrier against infectious fluids, especially body fluids contaminated with HIV while the female vagina, would provide natural protection against injuries and trauma facilitating HIV-infection. Anal sexual intercourse was constituted not only as dangerous but also as unnatural practice, while penile-vaginal intercourse would follow natural design and thus be relatively safe practice minimizing the risk of HIV. Statements like the latter were not uncommon in the early times of HIV/AIDS and contributed to captious certainties and an underestimation of heterosexual risks. Pseudo-scientific discourses on the origin of HIV were linked to local and global health politics in the 1980ies. The pathways of infection were related to normative concepts like deviant, subcultural behavior, cultural otherness, and guilt used to target, tag and separate specific groups at risk from the ‘normal’ population. Controlling populations at risk became the top item on the agenda rather than controlling modes of transmission and the virus. Hence, the Thai strategy to cope with HIV/AIDS by acknowledging social and sexual practices as they were – not as they were imagined – has become a role model for successful prevention in the highly scandalized realm of sexually transmitted disease. By accepting the globalized character of local HIV-risk and projecting the risk onto populations which are neither particularly vocal groups nor vested with the means to strive for health and justice Thailand managed to culturally implement knowledge-based tools of prevention. This paper argues, that pertinent cultural collisions regarding our strategies to cope with HIV/AIDS are deeply rooted in misconceptions, misreadings and scandalizations brought about in the early history of HIV in the 1980ties. The Thai strategy is used to demonstrate how local values can be balanced against globalized health risk and used to effectuated prevention by which knowledge and norms are translated into local practices. Issues of global health and injustice will be addressed in the final part of the paper dealing with the achievability of health as a human right.

Keywords: bioethics, HIV, global health, justice

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8722 Human Identification Using Local Roughness Patterns in Heartbeat Signal

Authors: Md. Khayrul Bashar, Md. Saiful Islam, Kimiko Yamashita, Yano Midori

Abstract:

Despite having some progress in human authentication, conventional biometrics (e.g., facial features, fingerprints, retinal scans, gait, voice patterns) are not robust against falsification because they are neither confidential nor secret to an individual. As a non-invasive tool, electrocardiogram (ECG) has recently shown a great potential in human recognition due to its unique rhythms characterizing the variability of human heart structures (chest geometry, sizes, and positions). Moreover, ECG has a real-time vitality characteristic that signifies the live signs, which ensure legitimate individual to be identified. However, the detection accuracy of the current ECG-based methods is not sufficient due to a high variability of the individual’s heartbeats at a different instance of time. These variations may occur due to muscle flexure, the change of mental or emotional states, and the change of sensor positions or long-term baseline shift during the recording of ECG signal. In this study, a new method is proposed for human identification, which is based on the extraction of the local roughness of ECG heartbeat signals. First ECG signal is preprocessed using a second order band-pass Butterworth filter having cut-off frequencies of 0.00025 and 0.04. A number of local binary patterns are then extracted by applying a moving neighborhood window along the ECG signal. At each instant of the ECG signal, the pattern is formed by comparing the ECG intensities at neighboring time points with the central intensity in the moving window. Then, binary weights are multiplied with the pattern to come up with the local roughness description of the signal. Finally, histograms are constructed that describe the heartbeat signals of individual subjects in the database. One advantage of the proposed feature is that it does not depend on the accuracy of detecting QRS complex, unlike the conventional methods. Supervised recognition methods are then designed using minimum distance to mean and Bayesian classifiers to identify authentic human subjects. An experiment with sixty (60) ECG signals from sixty adult subjects from National Metrology Institute of Germany (NMIG) - PTB database, showed that the proposed new method is promising compared to a conventional interval and amplitude feature-based method.

Keywords: human identification, ECG biometrics, local roughness patterns, supervised classification

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8721 Energy Efficient Heterogeneous System for Wireless Sensor Networks (WSN)

Authors: José Anderson Rodrigues de Souza, Teles de Sales Bezerra, Saulo Aislan da Silva Eleuterio, Jeronimo Silva Rocha

Abstract:

Mobile devices are increasingly occupying sectors of society and one of its most important features is mobility. However, the use of mobile devices is subject to the lifetime of the batteries. Thus, the use of energy batteries has become an important issue in the study of wireless network technologies. In this context, new solutions that enable aggregate energy efficiency not only through energy saving, and principally they are evaluated from a more realistic model of energy discharge, if easy adaptation to existing protocols. This paper presents a study on the energy needed and the lifetime for Wireless Sensor Networks (WSN) using a heterogeneous network and applying the LEACH protocol.

Keywords: wireless sensor networks, energy efficiency, heterogeneous, LEACH protocol

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8720 Potentials, Challenges And Prospects Of Halal Tourism Development In Ethiopia

Authors: Mohammed Jemal Ahmed

Abstract:

Some anti-Islam attributes, such as alcoholism and voyeurism, have become de facto manifestations of the tourism sector. This eventually causes a paradoxical relationship between tourism and Islam. Hence, on the one hand, Islam inherently encourages Muslims to engage in tourism, the interest of Muslims to engage in tourism is steadily increasing. On the other hand, haram activities and products that are not allowed to Muslims as per the Islamic law and doctrine have surrounded tourism. Therefore, halal tourism has emerged as the best mediator to reconcile the conflicts between secular interests and religious values. Recent studies have confirmed that halal tourism is an emerging cultural phenomenon and secular rather than religious. The central aim of halal tourism is to have delighted customers irrespective of their religious and cultural backgrounds while promoting environmental conservation and social coexistence. This study appraises halal tourism development in Ethiopia from commercial, socio-cultural and diplomatic perspectives. Employing qualitative methodologies, the study, firstly, tried to clarify the existing terminological ambiguities between halal tourism and Islamic tourism and redefine both concepts. Then, it assessed perceptions of local communities and stakeholders towards halal tourism and identified halal tourism resources of Ethiopia. Accordingly, five clusters of halal visitor attractions and five potential halal tourism routes were identified and proposed. Furthermore, the comparative advantages of Ethiopia in terms of halal tourism development and potential barriers to halal tourism development in the country were rigorously appraised. The findings of this study reveal that halal tourism could inject hard currency into the national economy and create job opportunities for the locals. It could also support the mainstream tourism industry through product diversification and curving seasonality. Moreover, socially, halal tourism reinforces interreligious cohesion, relationship and coextensive in multi-religious, multicultural and multiethnic Ethiopia. Politically, it strengthens Ethiopia's foreign diplomatic relationship with the Islamic world and its near and distant neighbor Muslim Countries.

Keywords: halal-conscious travelers, halal tourism, Islamic tourism, tourism resources

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8719 Application of ANN for Estimation of Power Demand of Villages in Sulaymaniyah Governorate

Authors: A. Majeed, P. Ali

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Before designing an electrical system, the estimation of load is necessary for unit sizing and demand-generation balancing. The system could be a stand-alone system for a village or grid connected or integrated renewable energy to grid connection, especially as there are non–electrified villages in developing countries. In the classical model, the energy demand was found by estimating the household appliances multiplied with the amount of their rating and the duration of their operation, but in this paper, information exists for electrified villages could be used to predict the demand, as villages almost have the same life style. This paper describes a method used to predict the average energy consumed in each two months for every consumer living in a village by Artificial Neural Network (ANN). The input data are collected using a regional survey for samples of consumers representing typical types of different living, household appliances and energy consumption by a list of information, and the output data are collected from administration office of Piramagrun for each corresponding consumer. The result of this study shows that the average demand for different consumers from four villages in different months throughout the year is approximately 12 kWh/day, this model estimates the average demand/day for every consumer with a mean absolute percent error of 11.8%, and MathWorks software package MATLAB version 7.6.0 that contains and facilitate Neural Network Toolbox was used.

Keywords: artificial neural network, load estimation, regional survey, rural electrification

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8718 Nine-Level Shunt Active Power Filter Associated with a Photovoltaic Array Coupled to the Electrical Distribution Network

Authors: Zahzouh Zoubir, Bouzaouit Azzeddine, Gahgah Mounir

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The use of more and more electronic power switches with a nonlinear behavior generates non-sinusoidal currents in distribution networks, which causes damage to domestic and industrial equipment. The multi-level shunt power active filter is subsequently shown to be an adequate solution to the problem raised. Nevertheless, the difficulty of adjusting the active filter DC supply voltage requires another technology to ensure it. In this article, a photovoltaic generator is associated with the DC bus power terminals of the active filter. The proposed system consists of a field of solar panels, three multi-level voltage inverters connected to the power grid and a non-linear load consisting of a six-diode rectifier bridge supplying a resistive-inductive load. Current control techniques of active and reactive power are used to compensate for both harmonic currents and reactive power as well as to inject active solar power into the distribution network. An algorithm of the search method of the maximum power point of type Perturb and observe is applied. Simulation results of the system proposed under the MATLAB/Simulink environment shows that the performance of control commands that reassure the solar power injection in the network, harmonic current compensation and power factor correction.

Keywords: Actif power filter, MPPT, pertub&observe algorithm, PV array, PWM-control

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8717 Application of Artificial Intelligence to Schedule Operability of Waterfront Facilities in Macro Tide Dominated Wide Estuarine Harbour

Authors: A. Basu, A. A. Purohit, M. M. Vaidya, M. D. Kudale

Abstract:

Mumbai, being traditionally the epicenter of India's trade and commerce, the existing major ports such as Mumbai and Jawaharlal Nehru Ports (JN) situated in Thane estuary are also developing its waterfront facilities. Various developments over the passage of decades in this region have changed the tidal flux entering/leaving the estuary. The intake at Pir-Pau is facing the problem of shortage of water in view of advancement of shoreline, while jetty near Ulwe faces the problem of ship scheduling due to existence of shallower depths between JN Port and Ulwe Bunder. In order to solve these problems, it is inevitable to have information about tide levels over a long duration by field measurements. However, field measurement is a tedious and costly affair; application of artificial intelligence was used to predict water levels by training the network for the measured tide data for one lunar tidal cycle. The application of two layered feed forward Artificial Neural Network (ANN) with back-propagation training algorithms such as Gradient Descent (GD) and Levenberg-Marquardt (LM) was used to predict the yearly tide levels at waterfront structures namely at Ulwe Bunder and Pir-Pau. The tide data collected at Apollo Bunder, Ulwe, and Vashi for a period of lunar tidal cycle (2013) was used to train, validate and test the neural networks. These trained networks having high co-relation coefficients (R= 0.998) were used to predict the tide at Ulwe, and Vashi for its verification with the measured tide for the year 2000 & 2013. The results indicate that the predicted tide levels by ANN give reasonably accurate estimation of tide. Hence, the trained network is used to predict the yearly tide data (2015) for Ulwe. Subsequently, the yearly tide data (2015) at Pir-Pau was predicted by using the neural network which was trained with the help of measured tide data (2000) of Apollo and Pir-Pau. The analysis of measured data and study reveals that: The measured tidal data at Pir-Pau, Vashi and Ulwe indicate that there is maximum amplification of tide by about 10-20 cm with a phase lag of 10-20 minutes with reference to the tide at Apollo Bunder (Mumbai). LM training algorithm is faster than GD and with increase in number of neurons in hidden layer and the performance of the network increases. The predicted tide levels by ANN at Pir-Pau and Ulwe provides valuable information about the occurrence of high and low water levels to plan the operation of pumping at Pir-Pau and improve ship schedule at Ulwe.

Keywords: artificial neural network, back-propagation, tide data, training algorithm

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8716 A Long Range Wide Area Network-Based Smart Pest Monitoring System

Authors: Yun-Chung Yu, Yan-Wen Wang, Min-Sheng Liao, Joe-Air Jiang, Yuen-Chung Lee

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This paper proposes to use a Long Range Wide Area Network (LoRaWAN) for a smart pest monitoring system which aims at the oriental fruit fly (Bactrocera dorsalis) to improve the communication efficiency of the system. The oriental fruit fly is one of the main pests in Southeast Asia and the Pacific Rim. Different smart pest monitoring systems based on the Internet of Things (IoT) architecture have been developed to solve problems of employing manual measurement. These systems often use Octopus II, a communication module following the 2.4GHz IEEE 802.15.4 ZigBee specification, as sensor nodes. The Octopus II is commonly used in low-power and short-distance communication. However, the energy consumption increase as the logical topology becomes more complicate to have enough coverage in the large area. By comparison, LoRaWAN follows the Low Power Wide Area Network (LPWAN) specification, which targets the key requirements of the IoT technology, such as secure bi-directional communication, mobility, and localization services. The LoRaWAN network has advantages of long range communication, high stability, and low energy consumption. The 433MHz LoRaWAN model has two superiorities over the 2.4GHz ZigBee model: greater diffraction and less interference. In this paper, The Octopus II module is replaced by a LoRa model to increase the coverage of the monitoring system, improve the communication performance, and prolong the network lifetime. The performance of the LoRa-based system is compared with a ZigBee-based system using three indexes: the packet receiving rate, delay time, and energy consumption, and the experiments are done in different settings (e.g. distances and environmental conditions). In the distance experiment, a pest monitoring system using the two communication specifications is deployed in an area with various obstacles, such as buildings and living creatures, and the performance of employing the two communication specifications is examined. The experiment results show that the packet receiving the rate of the LoRa-based system is 96% , which is much higher than that of the ZigBee system when the distance between any two modules is about 500m. These results indicate the capability of a LoRaWAN-based monitoring system in long range transmission and ensure the stability of the system.

Keywords: LoRaWan, oriental fruit fly, IoT, Octopus II

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8715 Voice over IP Quality of Service Evaluation for Mobile Ad Hoc Network in an Indoor Environment for Different Voice Codecs

Authors: Lina Abou Haibeh, Nadir Hakem, Ousama Abu Safia

Abstract:

In this paper, the performance and quality of Voice over IP (VoIP) calls carried over a Mobile Ad Hoc Network (MANET) which has a number of SIP nodes registered on a SIP Proxy are analyzed. The testing campaigns are carried out in an indoor corridor structure having a well-defined channel’s characteristics and model for the different voice codecs, G.711, G.727 and G.723.1. These voice codecs are commonly used in VoIP technology. The calls’ quality are evaluated using four Quality of Service (QoS) metrics, namely, mean opinion score (MOS), jitter, delay, and packet loss. The relationship between the wireless channel’s parameters and the optimum codec is well-established. According to the experimental results, the voice codec G.711 has the best performance for the proposed MANET topology

Keywords: wireless channel modelling, Voip, MANET, session initiation protocol (SIP), QoS

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8714 Robust Numerical Solution for Flow Problems

Authors: Gregor Kosec

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Simple and robust numerical approach for solving flow problems is presented, where involved physical fields are represented through the local approximation functions, i.e., the considered field is approximated over a local support domain. The approximation functions are then used to evaluate the partial differential operators. The type of approximation, the size of support domain, and the type and number of basis function can be general. The solution procedure is formulated completely through local computational operations. Besides local numerical method also the pressure velocity is performed locally with retaining the correct temporal transient. The complete locality of the introduced numerical scheme has several beneficial effects. One of the most attractive is the simplicity since it could be understood as a generalized Finite Differences Method, however, much more powerful. Presented methodology offers many possibilities for treating challenging cases, e.g. nodal adaptivity to address regions with sharp discontinuities or p-adaptivity to treat obscure anomalies in physical field. The stability versus computation complexity and accuracy can be regulated by changing number of support nodes, etc. All these features can be controlled on the fly during the simulation. The presented methodology is relatively simple to understand and implement, which makes it potentially powerful tool for engineering simulations. Besides simplicity and straightforward implementation, there are many opportunities to fully exploit modern computer architectures through different parallel computing strategies. The performance of the method is presented on the lid driven cavity problem, backward facing step problem, de Vahl Davis natural convection test, extended also to low Prandtl fluid and Darcy porous flow. Results are presented in terms of velocity profiles, convergence plots, and stability analyses. Results of all cases are also compared against published data.

Keywords: fluid flow, meshless, low Pr problem, natural convection

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8713 Random Subspace Ensemble of CMAC Classifiers

Authors: Somaiyeh Dehghan, Mohammad Reza Kheirkhahan Haghighi

Abstract:

The rapid growth of domains that have data with a large number of features, while the number of samples is limited has caused difficulty in constructing strong classifiers. To reduce the dimensionality of the feature space becomes an essential step in classification task. Random subspace method (or attribute bagging) is an ensemble classifier that consists of several classifiers that each base learner in ensemble has subset of features. In the present paper, we introduce Random Subspace Ensemble of CMAC neural network (RSE-CMAC), each of which has training with subset of features. Then we use this model for classification task. For evaluation performance of our model, we compare it with bagging algorithm on 36 UCI datasets. The results reveal that the new model has better performance.

Keywords: classification, random subspace, ensemble, CMAC neural network

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8712 Caged in Concrete Jungles: Reasserting Cultural Identity and Environmental Sustainability through Material Choice and Design Expression in Architecture

Authors: Ikenna Michael Onuorah

Abstract:

The relentless march of globalization in architecture has led to a homogenization of built environments, often characterized by an overreliance on imported, resource-intensive materials and a disregard for local cultural contexts. This research posits that such practices pose significant environmental and cultural perils, trapping communities in "caged concrete jungles" devoid of both ecological sustainability and a meaningful connection to their heritage. Through a mixed-method approach encompassing quantitative and qualitative data analysis, the study investigated the impacts of neglecting local materials and cultural expression in architectural design. The research is anticipated to yield significant insights into the multifaceted consequences of neglecting locally available materials and cultural expression in architecture. It creates a compelling case for reasserting local materials and cultural expression in architectural design. Based on the anticipated research findings, the study proposed series of actionable recommendations for architects, policymakers, and communities to promote sustainable and culturally sensitive built environments. This will serve as a wake-up call, urging architects, policymakers, and communities to break free from the confines of "caged concrete jungles" and embrace a more sustainable and culturally sensitive approach to design.

Keywords: sustainability, cultural identity, building materials, sustainable dsigns

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8711 Projective Lag Synchronization in Drive-Response Dynamical Networks via Hybrid Feedback Control

Authors: Mohd Salmi Md Noorani, Ghada Al-Mahbashi, Sakhinah Abu Bakar

Abstract:

This paper investigates projective lag synchronization (PLS) behavior in drive response dynamical networks (DRDNs) model with identical nodes. A hybrid feedback control method is designed to achieve the PLS with mismatch and without mismatch terms. The stability of the error dynamics is proven theoretically using the Lyapunov stability theory. Finally, analytical results show that the states of the dynamical network with non-delayed coupling can be asymptotically synchronized onto a desired scaling factor under the designed controller. Moreover, the numerical simulations results demonstrate the validity of the proposed method.

Keywords: drive-response dynamical network, projective lag synchronization, hybrid feedback control, stability theory

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8710 Water End-Use Classification with Contemporaneous Water-Energy Data and Deep Learning Network

Authors: Khoi A. Nguyen, Rodney A. Stewart, Hong Zhang

Abstract:

‘Water-related energy’ is energy use which is directly or indirectly influenced by changes to water use. Informatics applying a range of mathematical, statistical and rule-based approaches can be used to reveal important information on demand from the available data provided at second, minute or hourly intervals. This study aims to combine these two concepts to improve the current water end use disaggregation problem through applying a wide range of most advanced pattern recognition techniques to analyse the concurrent high-resolution water-energy consumption data. The obtained results have shown that recognition accuracies of all end-uses have significantly increased, especially for mechanised categories, including clothes washer, dishwasher and evaporative air cooler where over 95% of events were correctly classified.

Keywords: deep learning network, smart metering, water end use, water-energy data

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8709 Recurrent Neural Networks for Classifying Outliers in Electronic Health Record Clinical Text

Authors: Duncan Wallace, M-Tahar Kechadi

Abstract:

In recent years, Machine Learning (ML) approaches have been successfully applied to an analysis of patient symptom data in the context of disease diagnosis, at least where such data is well codified. However, much of the data present in Electronic Health Records (EHR) are unlikely to prove suitable for classic ML approaches. Furthermore, as scores of data are widely spread across both hospitals and individuals, a decentralized, computationally scalable methodology is a priority. The focus of this paper is to develop a method to predict outliers in an out-of-hours healthcare provision center (OOHC). In particular, our research is based upon the early identification of patients who have underlying conditions which will cause them to repeatedly require medical attention. OOHC act as an ad-hoc delivery of triage and treatment, where interactions occur without recourse to a full medical history of the patient in question. Medical histories, relating to patients contacting an OOHC, may reside in several distinct EHR systems in multiple hospitals or surgeries, which are unavailable to the OOHC in question. As such, although a local solution is optimal for this problem, it follows that the data under investigation is incomplete, heterogeneous, and comprised mostly of noisy textual notes compiled during routine OOHC activities. Through the use of Deep Learning methodologies, the aim of this paper is to provide the means to identify patient cases, upon initial contact, which are likely to relate to such outliers. To this end, we compare the performance of Long Short-Term Memory, Gated Recurrent Units, and combinations of both with Convolutional Neural Networks. A further aim of this paper is to elucidate the discovery of such outliers by examining the exact terms which provide a strong indication of positive and negative case entries. While free-text is the principal data extracted from EHRs for classification, EHRs also contain normalized features. Although the specific demographical features treated within our corpus are relatively limited in scope, we examine whether it is beneficial to include such features among the inputs to our neural network, or whether these features are more successfully exploited in conjunction with a different form of a classifier. In this section, we compare the performance of randomly generated regression trees and support vector machines and determine the extent to which our classification program can be improved upon by using either of these machine learning approaches in conjunction with the output of our Recurrent Neural Network application. The output of our neural network is also used to help determine the most significant lexemes present within the corpus for determining high-risk patients. By combining the confidence of our classification program in relation to lexemes within true positive and true negative cases, with an inverse document frequency of the lexemes related to these cases, we can determine what features act as the primary indicators of frequent-attender and non-frequent-attender cases, providing a human interpretable appreciation of how our program classifies cases.

Keywords: artificial neural networks, data-mining, machine learning, medical informatics

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8708 Neural Network Motion Control of VTAV by NARMA-L2 Controller for Enhanced Situational Awareness

Authors: Igor Astrov, Natalya Berezovski

Abstract:

This paper focuses on a critical component of the situational awareness (SA), the control of autonomous vertical flight for vectored thrust aerial vehicle (VTAV). With the SA strategy, we proposed a neural network motion control procedure to address the dynamics variation and performance requirement difference of flight trajectory for a VTAV. This control strategy with using of NARMA-L2 neurocontroller for chosen model of VTAV has been verified by simulation of take-off and forward maneuvers using software package Simulink and demonstrated good performance for fast stabilization of motors, consequently, fast SA with economy in energy can be asserted during search-and-rescue operations.

Keywords: NARMA-L2 neurocontroller, situational awareness, vectored thrust aerial vehicle, aviation

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8707 Farmers’ Perception and Response to Climate Change Across Agro-ecological Zones in Conflict-Ridden Communities in Cameroon

Authors: Lotsmart Fonjong

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The livelihood of rural communities in the West African state of Cameroon, which is largely dictated by natural forces (rainfall, temperatures, and soil), is today threatened by climate change and armed conflict. This paper investigates the extent to which rural communities are aware of climate change, how their perceptions of changes across different agro-ecological zones have impacted farming practices, output, and lifestyles, on the one hand, and the extent to which local armed conflicts are confounding their efforts and adaptation abilities. The paper is based on a survey conducted among small farmers in selected localities within the forest and savanna ecological zones of the conflict-ridden Northwest and Southwest Cameroon. Attention is paid to farmers’ gender, scale, and type of farming. Farmers’ perception of/and response to climate change are analysed alongside local rainfall and temperature data and mobilization for climate justice. Findings highlight the fact that farmers’ perception generally corroborates local climatic data. Climatic instability has negatively affected farmers’ output, food prices, standards of living, and food security. However, the vulnerability of the population varies across ecological zones, gender, and crop types. While these factors also account for differences in local response and adaptation to climate change, ongoing armed conflicts in these regions have further complicated opportunities for climate-driven agricultural innovations, inputs, and exchange of information among farmers. This situation underlines how poor communities, as victims, are forced into many complex problems outsider their making. It is therefore important to mainstream farmers’ perceptions and differences into policy strategies that consider both climate change and Anglophone conflict as national security concerns foe sustainable development in Cameroon.

Keywords: adaptation policies, climate change, conflict, small farmers, cameroon

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8706 Designing a Pregnancy Interactive Information Design for a Mobile Application

Authors: Thomas Adi Purnomo Sidhi

Abstract:

The importance of designing a pregnancy interactive information design for a mobile application is felt in order to assist pregnant women to get an easy access of highly credible pregnancy-related information on which often fail to be fulfilled, while it has been a very critical one. Thus, an observation of needs assessment for designing a pregnancy interactive information system design for a mobile application at iOS becomes current objective study. A comparative study of the top five pregnancy interactive information design available at the Apple Store conducted in order to fulfill it. Whilst, an observation of user experiences included for deeper analyzes. Moreover, a literature study conducted to support the arguments that being provided in the current study. The findings, surprisingly, also reveal the advantages of local wisdom in pregnancy that never been attached to those top five applications before.

Keywords: information system design, interactive design, local wisdom, pregnancy

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8705 The Research on Human Resource Management Problem of Turkish Fast Food Company

Authors: Mai Maitiaili Tuerdi

Abstract:

Turkey is one of the countries in which fast food service is growing increasingly in the world. The emergence of KFC and McDonald's to Turkish market is affecting every aspects of local fast-food services. The Turkey's famous catering companies named "Simit Sarayi" and "Güllüoğlu" are famous for accepting the Western fast food management service and skills in order to increase their market share. Also, they have created their unique management skills in this field. In this paper, through empirical and comparative study method we will analyze the famous Turkish local fast-food companies and western human resource management. We will argue how to create and adapt the human resource management while the company is economically and socially growing.

Keywords: human resources management, Turkey, fast food, management

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8704 A Saudi Herbal Database: An Approach for Organizing the Rich Herbal Resource of the Kingdom of Saudi Arabia

Authors: Syed Asif Hassan, Tabrej Khan

Abstract:

The use of traditional medicines for the treatment of various diseases as well as maintaining a healthy lifestyle has gained a significant acceptance across the globe. The increasing popularity of Herbal Medicine can be owed to the fact that is relatively inexpensive and has lesser side effects as compared to general medicines. The Kingdom of Saudi Arabia has a rich heritage of herbal medicine for overages. However, the information about essential traditional herbs of Arabian origin and their implication in the treatment of various diseases are not well documented in an organized manner. Therefore, the requirement of a local platform (database system) for herbal medicines of Arab origin is the need of the day. In this context, various questionnaire and surveys were conducted over a period of 6 months. The surveys were targeted to identify a range of herbal remedies used by the communities of Saudi Arabia e.g., pharmacists and local people. The survey leads us to identify many of the mysterious local medicinal herbs used for the treatment of various ailments and thus reveals a unique insight into the natural herbal resource of Saudi Arabia. The information of the herbal medicines will be further used to develop a Saudi herbal database system using the principles of waterfall method. An interactive dynamic electronic web portal of the herbal database system will be built using MySQL and PHP for accessing the information available in the Saudi herbal database system. The web portal will be a step forward in creating awareness among the Arab nationals of their rich herbal heritage.

Keywords: Saudi herbal medicine, community survey, database system and design, MySQL, PHP

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8703 We Have Never Seen a Dermatologist. Prisons Telederma Project Reaching the Unreachable Through Teledermatology

Authors: Innocent Atuhe, Babra Nalwadda, Grace Mulyowa, Annabella Habinka Ejiri

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Background: Atopic Dermatitis (AD) is one of the most prevalent and growing chronic inflammatory skin diseases in African prisons. AD care is limited in African due to a lack of information about the disease amongst primary care workers, limited access to dermatologists, lack of proper training of healthcare workers, and shortage of appropriate treatments. We designed and implemented the Prisons Telederma project based on the recommendations of the International Society of Atopic Dermatitis. We aimed at; i) increase awareness and understanding of teledermatology among prison health workers and ii) improve treatment outcomes of prisoners with atopic dermatitis through increased access to and utilization of consultant dermatologists through teledermatology in Uganda prisons. Approach: We used Store-and-forward Teledermatology (SAF-TD) to increase access to dermatologist-led care for prisoners and prison staff with AD. We conducted five days of training for prison health workers using an adapted WHO training guide on recognizing neglected tropical diseases through changes on the skin together with an adapted American Academy of Dermatology (AAD) Childhood AD Basic Dermatology Curriculum designed to help trainees develop a clinical approach to the evaluation and initial management of patients with AD. This training was followed by blended e-learning, webinars facilitated by consultant Dermatologists with local knowledge of medication and local practices, apps adjusted for pigmented skin, WhatsApp group discussions, and sharing pigmented skin AD pictures and treatment via zoom meetings. We hired a team of Ugandan Senior Consultant dermatologists to draft an iconographic atlas of the main dermatoses in pigmented African skin and shared this atlas with prison health staff for use as a job aid. We had planned to use MySkinSelfie mobile phone application to take and share skin pictures of prisoners with AD with Consultant Dermatologists, who would review the pictures and prescribe appropriate treatment. Unfortunately, the National Health Service withdrew the app from the market due to technical issues. We monitored and evaluated treatment outcomes using the Patient-Oriented Eczema Measure (POEM) tool. We held four advocacy meetings to persuade relevant stakeholders to increase supplies and availability of first-line AD treatments such as emollients in prison health facilities. Results: We have the very first iconographic atlas of the main dermatoses in pigmented African skin. We increased; i) the proportion of prison health staff with adequate knowledge of AD and teledermatology from 20% to 80%; ii) the proportion of prisoners with AD reporting improvement in disease severity (POEM scores) from 25% to 35% in one year; iii) increased proportion of prisoners with AD seen by consultant dermatologist through teledermatology from 0% to 20% in one year and iv)Increased the availability of AD recommended treatments in prisons health facilities from 5% to 10% in one year. Our study contributes to the use, evaluation, and verification of the use of teledermatology to increase access to specialist dermatology services to the most hard to reach areas and vulnerable populations such as that of prisoners.

Keywords: teledermatology, prisoners, reaching, un-reachable

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8702 Multiple Fault Detection and Classification in a Coupled Motor with Rotor Using Artificial Neural Network

Authors: Mehrdad Nouri Khajavi, Gollamhassan Payganeh, Mohsen Fallah Tafti

Abstract:

Fault diagnosis is an important aspect of maintaining rotating machinery health and increasing productivity. Many researches has been done in this regards. Many faults such as unbalance, misalignment, looseness, bearing faults, etc. have been considered and diagnosed with different techniques. Most of the researches in fault diagnosis of rotating machinery deal with single fault. Where as in reality faults usually occur simultaneously and it is, therefore, necessary to recognize them at the same time. In this research, two of the most common faults namely unbalance and misalignment have been considered simultaneously with different intensity and then identified and classified with the use of Multi-Layer Perception Neural Network (MLPNN). Processed Vibration signals are used as the input to the MLPNN, and the class of mixed unbalancy, and misalignment is the output of the NN.

Keywords: unbalance, parallel misalignment, combined faults, vibration signals

Procedia PDF Downloads 346
8701 Mobility Management via Software Defined Networks (SDN) in Vehicular Ad Hoc Networks (VANETs)

Authors: Bilal Haider, Farhan Aadil

Abstract:

A Vehicular Ad hoc Network (VANET) provides various services to end-users traveling on the road at high speeds. However, this high-speed mobility of mobile nodes can cause frequent service disruptions. Various mobility management protocols exist for managing node mobility, but due to their centralized nature, they tend to suffer in the VANET environment. In this research, we proposed a distributed mobility management protocol using software-defined networks (SDN) for VANETs. Instead of relying on a centralized mobility anchor, the mobility functionality is distributed at multiple infrastructural nodes. The protocol is based on the classical Proxy Mobile IP version 6 (PMIPv6). It is evident from simulation results that this work has improved the network performance with respect to nodes throughput, delay, and packet loss.

Keywords: SDN, VANET, mobility management, optimization

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8700 Predicting Survival in Cancer: How Cox Regression Model Compares to Artifial Neural Networks?

Authors: Dalia Rimawi, Walid Salameh, Amal Al-Omari, Hadeel AbdelKhaleq

Abstract:

Predication of Survival time of patients with cancer, is a core factor that influences oncologist decisions in different aspects; such as offered treatment plans, patients’ quality of life and medications development. For a long time proportional hazards Cox regression (ph. Cox) was and still the most well-known statistical method to predict survival outcome. But due to the revolution of data sciences; new predication models were employed and proved to be more flexible and provided higher accuracy in that type of studies. Artificial neural network is one of those models that is suitable to handle time to event predication. In this study we aim to compare ph Cox regression with artificial neural network method according to data handling and Accuracy of each model.

Keywords: Cox regression, neural networks, survival, cancer.

Procedia PDF Downloads 190
8699 Lidocaine-Bupivacaine Block Improve Analgesia in Cats Undergoing Orchiectomy

Authors: T. C. Ng, R. Radzi, T. K. Ng, H. C. Chen

Abstract:

The analgesic effects of lidocaine-bupivacaine block in cats undergoing routine orchiectomy were determined in this controlled, randomized, and blinded study. Twelve cats were randomly assigned to two groups. Cats in local block group received subcutaneous infiltration of 1 mg/kg of 2% lidocaine and 1 mg/kg of 0.5% bupivacaine into the scrotal sac. Cats in control group received equivolume of saline. Both groups were induced with mixture of ketamine (15 mg/kg) and acepromazine (0.1 mg/kg) intramuscularly and maintained on sevoflurane via facemask. Non-invasive blood pressures (BP), heart (HR), and respiratory rate (RR) were measured intra-operatively at specific events. Post-operatively, all cats received meloxicam, 0.2 mg/kg subcutaneously. Pain scores were determined at 4, 8, and 24 hours postoperatively. Mechanical pressure thresholds (MPT) at the perineum and metatarsus were determined at 2, 4, 8, and 24 hours postoperatively. Intra-operatively, the BP and HR tended to be higher in the control group. The increment in HR peaked during traction and autoligation of the spermatic cord in the control group. There was no treatment difference in RR. Post-operatively, pain scores in the group given local blocks were lower than the control group at 4 hour post-operation. There was no treatment difference in the post-operative HR, RR, BP and MPT values. In conclusion, subcutaneous infiltration of lidocaine-bupivacaine into the scrotal sac before orchiectomy improved intra-operative hemodynamic stability and provided better analgesia up to 4 hours post-surgery.

Keywords: analgesia, bupivacaine, cat, lidocaine, local block, orchiectomy

Procedia PDF Downloads 133
8698 Community Observatory for Territorial Information Control and Management

Authors: A. Olivi, P. Reyes Cabrera

Abstract:

Ageing and urbanization are two of the main trends that characterize the twenty-first century. Its trending is especially accelerated in the emerging countries of Asia and Latin America. Chile is one of the countries in the Latin American region, where the demographic transition to ageing is becoming increasingly visible. The challenges that the new demographic scenario poses to urban administrators call for searching innovative solutions to maximize the functional and psycho-social benefits derived from the relationship between older people and the environment in which they live. Although mobility is central to people's everyday practices and social relationships, it is not distributed equitably. On the contrary, it can be considered another factor of inequality in our cities. Older people are a particularly sensitive and vulnerable group to mobility. In this context, based on the ageing in place strategy and following the social innovation approach within a spatial context, the "Community Observatory of Territorial Information Control and Management" project aims at the collective search and validation of solutions for the satisfaction of mobility and accessibility specific needs of urban aged people. Specifically, the Observatory intends to: i) promote the direct participation of the aged population in order to generate relevant information on the territorial situation and the satisfaction of the mobility needs of this group; ii) co-create dynamic and efficient mechanisms for the reporting and updating of territorial information; iii) increase the capacity of the local administration to plan and manage solutions to environmental problems at the neighborhood scale. Based on a participatory mapping methodology and on the application of digital technology, the Observatory designed and developed, together with aged people, a crowdsourcing platform for smartphones, called DIMEapp, for reporting environmental problems affecting mobility and accessibility. DIMEapp has been tested at a prototype level in two neighborhoods of the city of Valparaiso. The results achieved in the testing phase have shown high potential in order to i) contribute to establishing coordination mechanisms with the local government and the local community; ii) improve a local governance system that guides and regulates the allocation of goods and services destined to solve those problems.

Keywords: accessibility, ageing, city, digital technology, local governance

Procedia PDF Downloads 122
8697 Multi-Path Signal Synchronization Model with Phase Length Constraints

Authors: Tzu-Jung Huang, Hsun-Jung Cho, Chien-Chia Liäm Huang

Abstract:

To improve the level of service (LoS) of urban arterial systems containing a series of signalized intersections, a proper design of offsets for all intersections associated is of great importance. The MAXBAND model has been the most common approach for this purpose. In this paper, we propose a MAXBAND model with phase constraints so that the lengths of the phases in a cycle are variable. In other words, the length of a cycle is also variable in our setting. We conduct experiments on a real-world traffic network, having several major paths, in Taiwan for numerical evaluations. Actual traffic data were collected through on-site experiments. Numerical evidences suggest that the improvements are around 32%, on average, in terms of total delay of the entire network.

Keywords: arterial progression, MAXBAND, signal control, offset

Procedia PDF Downloads 347
8696 The Impact of the Number of Neurons in the Hidden Layer on the Performance of MLP Neural Network: Application to the Fast Identification of Toxics Gases

Authors: Slimane Ouhmad, Abdellah Halimi

Abstract:

In this work, we have applied neural networks method MLP type to a database from an array of six sensors for the detection of three toxic gases. As the choice of the number of hidden layers and the weight values has a great influence on the convergence of the learning algorithm, we proposed, in this article, a mathematical formulation to determine the optimal number of hidden layers and good weight values based on the method of back propagation of errors. The results of this modeling have improved discrimination of these gases on the one hand, and optimize the computation time on the other hand, the comparison to other results achieved in this case.

Keywords: MLP Neural Network, back-propagation, number of neurons in the hidden layer, identification, computing time

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8695 Cost of Outpatient Procedures for Ostomized Patients Treated in the Public Health Network in Brazil and Its Impact on the Budget of the Unified Health System

Authors: Karina Guimaraes, Lilian Santos

Abstract:

This study has the purpose of planning and instituting monitoring actions as a way of knowing the scenario of assistance to the patient with stoma, treated in the public health network in Brazil, from January to November of the year 2016, from the elaboration of a technical document containing the survey of the number of procedures offered and the value of the ostomy services, accredited in the Unified Health System-SUS. The purpose of this document is to improve the quality of these services in the efficient management of available financial resources, making it indispensable for the creation of strategies for the implementation and implementation of care services for people with stomata as a strategic tool in the promotion, prevention, qualification and efficiency in health care.

Keywords: health economic, management, ostomy, unified health system

Procedia PDF Downloads 307
8694 Optimized Cluster Head Selection Algorithm Based on LEACH Protocol for Wireless Sensor Networks

Authors: Wided Abidi, Tahar Ezzedine

Abstract:

Low-Energy Adaptive Clustering Hierarchy (LEACH) has been considered as one of the effective hierarchical routing algorithms that optimize energy and prolong the lifetime of network. Since the selection of Cluster Head (CH) in LEACH is carried out randomly, in this paper, we propose an approach of electing CH based on LEACH protocol. In other words, we present a formula for calculating the threshold responsible for CH election. In fact, we adopt three principle criteria: the remaining energy of node, the number of neighbors within cluster range and the distance between node and CH. Simulation results show that our proposed approach beats LEACH protocol in regards of prolonging the lifetime of network and saving residual energy.

Keywords: wireless sensors networks, LEACH protocol, cluster head election, energy efficiency

Procedia PDF Downloads 326