Search results for: Access algorithm

Authors: Almutasim Billa A. Alanazi, Hal S. Tharp

Abstract:

Artificial Intelligence (AI), specifically Reinforcement Learning (RL), has proven helpful in many control path planning technologies by maximizing and enhancing their performance, such as navigation systems. Since it learns from experience by interacting with the environment to determine the optimal policy, the optimal policy takes the best action in a particular state, accounting for the long-term rewards. Most navigation systems focus primarily on "arriving faster," overlooking safety and efficiency while estimating the optimum path, as safety and efficiency are essential factors when planning for a long-distance journey. This paper represents an RL control model that proposes a control mechanism for improving navigation systems. Also, the model could be applied to other control path planning applications because it is adjustable and can accept different properties and parameters. However, the navigation system application has been taken as a case and evaluation study for the proposed model. The model utilized a Q-learning algorithm for training and updating the policy. It allows the agent to analyze the quality of an action made in the environment to maximize rewards. The model gives the ability to update rewards regularly based on safety and efficiency assessments, allowing the policy to consider the desired safety and efficiency benefits while making decisions, which improves the quality of the decisions taken for path planning compared to the conventional RL approaches.

Keywords: Artificial intelligence, control system, navigation systems, reinforcement learning.

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Authors: Mustafa M. Donma, Sule G. Kacmaz, Ahsen Yilmaz, Savas Guzel, Orkide Donma

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Obesity, as excessive fat accumulation in the body, is a global health problem. The prevalence of obesity and its complications increase due to easy access to high-energy food and decreased physical activity. Cardiovascular diseases (CVDs) constitute a significant part of obesity-related morbidity and mortality. Since the effects of obesity on cardiovascular system may start during childhood without clinical findings, elucidating the mechanisms of cardiovascular changes associated with childhood obesity became more important. In this study, we aimed to investigate some biochemical parameters which may be involved in obesity-related pathologic processes of CVDs. One hundred and seventy-seven children were included in the study, and they were divided into four groups based upon WHO criteria and presence of the metabolic syndrome (MetS): children with normal-BMI, obesity, morbid obesity, and MetS. High-sensitive cardiac troponin T (hs-cTnT), cardiac myosin binding protein C (cMyBP-C), trimethylamine N-oxide (TMAO), soluble tumor necrosis factor-like weak inducer (sTWEAK), chromogranin A (CgA), multimerin-2 levels, and other biochemical parameters were measured in serum samples. Anthropometric measurements and clinical findings of the children were recorded. Statistical analyses were performed. Children with normal-BMI had significantly higher CgA levels than children with obesity, morbid obesity, and MetS (p < 0.05). Cardiac MyBP-C levels of children with MetS were significantly higher than of children with normal-BMI and OB children (p < 0.05). There was no significant difference in hs-cTnT, sTWEAK, TMAO and multimerin-2 between the groups (p>0.05). These results suggested that cMyBP-C and CgA molecules may be involved in the pathogenesis of obesity-related CVDs.

Keywords: biomarker, cardiovascular diseases, children, obesity

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Authors: Tibor Kulcsar, Gabor Sarossy, Gabor Bereznai, Robert Auer, Janos Abonyi

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On-line (near infrared) spectroscopy is widely used to support the operation of complex process systems. Information extracted from spectral database can be used to estimate unmeasured product properties and monitor the operation of the process. These techniques are based on looking for similar spectra by nearest neighborhood algorithms and distance based searching methods. Search for nearest neighbors in the spectral space is an NP-hard problem, the computational complexity increases by the number of points in the discrete spectrum and the number of samples in the database. To reduce the calculation time some kind of indexing could be used. The main idea presented in this paper is to combine indexing and visualization techniques to reduce the computational requirement of estimation algorithms by providing a two dimensional indexing that can also be used to visualize the structure of the spectral database. This 2D visualization of spectral database does not only support application of distance and similarity based techniques but enables the utilization of advanced clustering and prediction algorithms based on the Delaunay tessellation of the mapped spectral space. This means the prediction has not to use the high dimension space but can be based on the mapped space too. The results illustrate that the proposed method is able to segment (cluster) spectral databases and detect outliers that are not suitable for instance based learning algorithms.

Keywords: indexing high dimensional databases, dimensional reduction, clustering, similarity, k-nn algorithm.

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Authors: A. Rezazadeh, N. Omidvar, H. Eini-Zinab

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Food insecurity (FI) influences may result in poor physical and mental health outcomes. Minor ethnic group may experience higher level of FI, and this situation may be related with higher depression prevalence. The aim of this study was to determine the association of depression with food security status in major (Azeri) and minor (Kurdish) ethnicity living in Urmia, West Azerbaijan, north of Iran. In this cross-sectional study, 723 participants (427 women and 296 men) aged 20–64 years old, from two ethnic groups (445 Azeri and 278 Kurdish), were selected through a multi stage cluster systematic sampling. Depression rate was assessed by “Beck” short form questionnaire (validated in Iranians) through interviews. Household FI status (HFIS) was measured using adapted HFI access scale through face-to-face interviews at homes. Multinomial logistic regression was used to estimate odds ratios (OR) of depression across HFIS. Higher percent of Kurds had moderate and severe depression in comparison with Azeri group (73 [17.3%] vs. 86 [27.9%]). There were not any significant differences between the two ethnicities in mild depression. Also, of all the subjects, moderate-to-sever FI was more prevalent in Kurds (28.5%), compared to Azeri group (17.3%) [P < 0.01]. Kurdish ethnic group living in food security or mild FI households had lower chance to have symptom of severe depression in comparison to those with sever FI (OR=0.097; 95% CI: 0.02-0.47). However, there was no significant association between depression and HFI in Azeri group. Findings revealed that the severity of HFI was related with severity depression in minor studied ethnic groups. However, in Azeri ethnicity as a major group, other confounders may have influence on the relation with depression and FI, that were not studied in the present study.

Keywords: Depression, ethnicity, food security status, Iran.

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Authors: David M. Jenkins Jr.

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Scale Time Offset Robust Modulation (STORM) [1]– [3] is a high bandwidth waveform design that adds time-scale to embedded reference modulations using only time-delay [4]. In an environment where each user has a specific delay and scale, identification of the user with the highest signal power and that user-s phase is facilitated by the STORM processor. Both of these parameters are required in an efficient multiuser detection algorithm. In this paper, the STORM modulation approach is evaluated with a direct sequence spread quadrature phase shift keying (DS-QPSK) system. A misconception of the STORM time scale modulation is that a fine temporal resolution is required at the receiver. STORM will be applied to a QPSK code division multiaccess (CDMA) system by modifying the spreading codes. Specifically, the in-phase code will use a typical spreading code, and the quadrature code will use a time-delayed and time-scaled version of the in-phase code. Subsequently, the same temporal resolution in the receiver is required before and after the application of STORM. In this paper, the bit error performance of STORM in a synchronous CDMA system is evaluated and compared to theory, and the bit error performance of STORM incorporated in a single user WCDMA downlink is presented to demonstrate the applicability of STORM in a modern communication system.

Keywords: Pseudonoise coded communication, Cyclic codes, Code division multiaccess

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Authors: Daniel M. Muntean, Viorel Ungureanu

Abstract:

More than half of the urban population in Romania lives today in residential buildings made out of large prefabricated reinforced concrete panels. Since their initial design was made in the 1960’s, these housing units are now being technically and morally outdated, consuming large amounts of energy for heating, cooling, ventilation and lighting, while failing to meet the needs of the contemporary life-style. Due to their widespread use, the design of a system that improves their energy efficiency would have a real impact, not only on the energy consumption of the residential sector, but also on the quality of life that it offers. Furthermore, with the transition of today’s existing power grid to a “smart grid”, buildings could become an active element for future electricity networks by contributing in micro-generation and energy storage. One of the most addressed issues today is to find locally adapted strategies that can be applied considering the 20-20-20 EU policy criteria and to offer sustainable and innovative solutions for the cost-optimal energy performance of buildings adapted on the existing local market. This paper presents a possible adaptive design scenario towards sustainable retrofitting of these housing units. The apartments are transformed in order to meet the current living requirements and additional extensions are placed on top of the building, replacing the unused roof space, acting not only as housing units, but as active solar energy collection systems. An adaptive building envelope is ensured in order to achieve overall air-tightness and an elevator system is introduced to facilitate access to the upper levels.

Keywords: Adaptive building, energy efficiency, retrofitting, residential buildings, smart grid.

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Authors: Marco Antonio Lara De la Calleja, María Catalina Ovando Chico, Eduardo Lopez Ruiz

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Community empowerment has been proved to be a key element in the solution of the food security problem. As a result of a conceptual analysis, it was found that agricultural production, economic development and governance, are the traditional basis of food security models. Although the literature points to social inclusion as an important factor for food security, no model has considered it as the basis of it. The aim of this research is to identify different dimensions that make an integral model for food security, with emphasis on community empowerment. A diagnosis was made in the study community (Tatoxcac, Zacapoaxtla, Puebla), to know the aspects that impact the level of food insecurity. With a statistical sample integrated by 200 families, the Latin American and Caribbean Food Security Scale (ELCSA) was applied, finding that: in households composed by adults and children, have moderated food insecurity, (ELCSA scale has three levels, low, moderated and high); that result is produced mainly by the economic income capacity and the diversity of the diet on its food. With that being said, a model was developed to promote food security through five dimensions: 1. Regional context of the community; 2. Structure and system of local food; 3. Health and nutrition; 4. Information and technology access; and 5. Self-awareness and empowerment. The specific actions on each axis of the model, allowed a systemic approach needed to attend food security in the community, through the empowerment of society. It is concluded that the self-awareness of local communities is an area of extreme importance, which must be taken into account for participatory schemes to improve food security. In the long term, the model requires the integrated participation of different actors, such as government, companies and universities, to solve something such vital as food security.

Keywords: Community empowerment, food security, model, systemic approach.

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Authors: Julius Onyancha, Valentina Plekhanova

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One of the significant issues facing web users is the amount of noise in web data which hinders the process of finding useful information in relation to their dynamic interests. Current research works consider noise as any data that does not form part of the main web page and propose noise web data reduction tools which mainly focus on eliminating noise in relation to the content and layout of web data. This paper argues that not all data that form part of the main web page is of a user interest and not all noise data is actually noise to a given user. Therefore, learning of noise web data allocated to the user requests ensures not only reduction of noisiness level in a web user profile, but also a decrease in the loss of useful information hence improves the quality of a web user profile. Noise Web Data Learning (NWDL) tool/algorithm capable of learning noise web data in web user profile is proposed. The proposed work considers elimination of noise data in relation to dynamic user interest. In order to validate the performance of the proposed work, an experimental design setup is presented. The results obtained are compared with the current algorithms applied in noise web data reduction process. The experimental results show that the proposed work considers the dynamic change of user interest prior to elimination of noise data. The proposed work contributes towards improving the quality of a web user profile by reducing the amount of useful information eliminated as noise.

Keywords: Web log data, web user profile, user interest, noise web data learning, machine learning.

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Authors: Farnaz Amin Salehi, David Edward.Cotton, Mohammad Ali Abdoli, Kambiz Rezapour

Abstract:

The daily increase of organic waste materials resulting from different activities in the country is one of the main factors for the pollution of environment. Today, with regard to the low level of the output of using traditional methods, the high cost of disposal waste materials and environmental pollutions, the use of modern methods such as anaerobic digestion for the production of biogas has been prevailing. The collected biogas from the process of anaerobic digestion, as a renewable energy source similar to natural gas but with a less methane and heating value is usable. Today, with the help of technologies of filtration and proper preparation, access to biogas with features fully similar to natural gas has become possible. At present biogas is one of the main sources of supplying electrical and thermal energy and also an appropriate option to be used in four stroke engine, diesel engine, sterling engine, gas turbine, gas micro turbine and fuel cell to produce electricity. The use of biogas for different reasons which returns to socio-economic and environmental advantages has been noticed in CHP for the production of energy in the world. The production of biogas from the technology of anaerobic digestion and its application in CHP power plants in Iran can not only supply part of the energy demands in the country, but it can materialize moving in line with the sustainable development. In this article, the necessity of the development of CHP plants with biogas fuels in the country will be dealt based on studies performed from the economic, environmental and social aspects. Also to prove the importance of the establishment of these kinds of power plants from the economic point of view, necessary calculations has been done as a case study for a CHP power plant with a biogas fuel.

Keywords: Anaerobic Digestion, Biogas, CHP, Organic Wastes

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Authors: Seyedvahid Najafi, Viliam Makis

Abstract:

In recent years, maintenance optimization has attracted special attention due to the growth of industrial systems complexity. Maintenance costs are high for many systems, and preventive maintenance is effective when it increases operations' reliability and safety at a reduced cost. The novelty of this research is to consider general repair in the modeling of multi-unit series systems and solve the maintenance problem for such systems using the semi-Markov decision process (SMDP) framework. We propose an opportunistic maintenance policy for a series system composed of two main units. Unit 1, which is more expensive than unit 2, is subjected to condition monitoring, and its deterioration is modeled using a gamma process. Unit 1 hazard rate is estimated by the proportional hazards model (PHM), and two hazard rate control limits are considered as the thresholds of maintenance interventions for unit 1. Maintenance is performed on unit 2, considering an age control limit. The objective is to find the optimal control limits and minimize the long-run expected average cost per unit time. The proposed algorithm is applied to a numerical example to compare the effectiveness of the proposed policy (policy Ⅰ) with policy Ⅱ, which is similar to policy Ⅰ, but instead of general repair, replacement is performed. Results show that policy Ⅰ leads to lower average cost compared with policy Ⅱ. 

Keywords: Condition-based maintenance, proportional hazards model, semi-Markov decision process, two-unit series systems.

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Authors: F. Jiménez, R. Jódar, M. Martín, G. Sánchez, G. Sciavicco

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Abstract—Attribute or feature selection is one of the basic strategies to improve the performances of data classification tasks, and, at the same time, to reduce the complexity of classifiers, and it is a particularly fundamental one when the number of attributes is relatively high. Its application to unsupervised classification is restricted to a limited number of experiments in the literature. Evolutionary computation has already proven itself to be a very effective choice to consistently reduce the number of attributes towards a better classification rate and a simpler semantic interpretation of the inferred classifiers. We present a feature selection wrapper model composed by a multi-objective evolutionary algorithm, the clustering method Expectation-Maximization (EM), and the classifier C4.5 for the unsupervised classification of data extracted from a psychological test named BASC-II (Behavior Assessment System for Children - II ed.) with two objectives: Maximizing the likelihood of the clustering model and maximizing the accuracy of the obtained classifier. We present a methodology to integrate feature selection for unsupervised classification, model evaluation, decision making (to choose the most satisfactory model according to a a posteriori process in a multi-objective context), and testing. We compare the performance of the classifier obtained by the multi-objective evolutionary algorithms ENORA and NSGA-II, and the best solution is then validated by the psychologists that collected the data.

Keywords: Feature selection, multi-objective evolutionary computation, unsupervised classification, behavior assessment system for children.

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Authors: Ali Shirazi, Robert A. Taylor, Stephen D. White, Graham L. Morrison

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In this paper, a detailed simulation model of a solar-powered triple-effect LiBr–H₂O absorption chiller is developed to supply both cooling and heating demand of a large-scale building, aiming to reduce the fossil fuel consumption and greenhouse gas emissions in building sector. TRNSYS 17 is used to simulate the performance of the system over a typical year. A combined energetic-economic-environmental analysis is conducted to determine the system annual primary energy consumption and the total cost, which are considered as two conflicting objectives. A multi-objective optimization of the system is performed using a genetic algorithm to minimize these objectives simultaneously. The optimization results show that the final optimal design of the proposed plant has a solar fraction of 72% and leads to an annual primary energy saving of 0.69 GWh and annual CO₂ emissions reduction of ~166 tonnes, as compared to a conventional HVAC system. The economics of this design, however, is not appealing without public funding, which is often the case for many renewable energy systems. The results show that a good funding policy is required in order for these technologies to achieve satisfactory payback periods within the lifetime of the plant.

Keywords: Economic, environmental, multi-objective optimization, solar air-conditioning, triple-effect absorption chiller.

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Authors: Muhammad Mehran Arshad Khan, Chengliang Wang, Zou Minhui, Danyal Badar Soomro

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Security of the smart home in terms of behavior activity pattern recognition is a totally dissimilar and unique issue as compared to the security issues of other scenarios. Sensor devices (low capacity and high capacity) interact and negotiate each other by detecting the daily behavior activity of individuals to execute common tasks. Once a device (e.g., surveillance camera, smart phone and light detection sensor etc.) is compromised, an adversary can then get access to a specific device and can damage daily behavior activity by altering the data and commands. In this scenario, a group of common instruction processes may get involved to generate deadlock. Therefore, an effective suitable security solution is required for smart home architecture. This paper proposes seamless distributed Scheme which fortifies low computational wireless devices for secure communication. Proposed scheme is based on lightweight key-session process to upheld cryptic-link for trajectory by recognizing of individual’s behavior activities pattern. Every device and service provider unit (low capacity sensors (LCS) and high capacity sensors (HCS)) uses an authentication token and originates a secure trajectory connection in network. Analysis of experiments is revealed that proposed scheme strengthens the devices against device seizure attack by recognizing daily behavior activities, minimum utilization memory space of LCS and avoids network from deadlock. Additionally, the results of a comparison with other schemes indicate that scheme manages efficiency in term of computation and communication.

Keywords: Authentication, key-session, security, wireless sensors.

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Authors: Satish Kumar Peddapelli

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This paper presents advances in pulse width modulation techniques which refers to a method of carrying information on train of pulses and the information be encoded in the width of pulses. Pulse Width Modulation is used to control the inverter output voltage. This is done by exercising the control within the inverter itself by adjusting the ON and OFF periods of inverter. By fixing the DC input voltage we get AC output voltage. In variable speed AC motors the AC output voltage from a constant DC voltage is obtained by using inverter. Recent developments in power electronics and semiconductor technology have lead improvements in power electronic systems. Hence, different circuit configurations namely multilevel inverters have became popular and considerable interest by researcher are given on them. A fast space-vector pulse width modulation (SVPWM) method for five-level inverter is also discussed. In this method, the space vector diagram of the five-level inverter is decomposed into six space vector diagrams of three-level inverters. In turn, each of these six space vector diagrams of three-level inverter is decomposed into six space vector diagrams of two-level inverters. After decomposition, all the remaining necessary procedures for the three-level SVPWM are done like conventional two-level inverter. The proposed method reduces the algorithm complexity and the execution time. It can be applied to the multilevel inverters above the five-level also. The experimental setup for three-level diode-clamped inverter is developed using TMS320LF2407 DSP controller and the experimental results are analyzed.

Keywords: Five-level inverter, Space vector pulse wide modulation, diode clamped inverter.

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Authors: Rafael Muñoz, Juan Melchor, Alicia Valera, Laura Peralta, Guillermo Rus

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A torsional piezoelectric ultrasonic transducer design is proposed to measure shear moduli in soft tissue with direct access availability, using shear wave elastography technique. The measurement of shear moduli of tissues is a challenging problem, mainly derived from a) the difficulty of isolating a pure shear wave, given the interference of multiple waves of different types (P, S, even guided) emitted by the transducers and reflected in geometric boundaries, and b) the highly attenuating nature of soft tissular materials. An immediate application, overcoming these drawbacks, is the measurement of changes in cervix stiffness to estimate the gestational age at delivery. The design has been optimized using a finite element model (FEM) and a semi-analytical estimator of the probability of detection (POD) to determine a suitable geometry, materials and generated waves. The technique is based on the time of flight measurement between emitter and receiver, to infer shear wave velocity. Current research is centered in prototype testing and validation. The geometric optimization of the transducer was able to annihilate the compressional wave emission, generating a quite pure shear torsional wave. Currently, mechanical and electromagnetic coupling between emitter and receiver signals are being the research focus. Conclusions: the design overcomes the main described problems. The almost pure shear torsional wave along with the short time of flight avoids the possibility of multiple wave interference. This short propagation distance reduce the effect of attenuation, and allow the emission of very low energies assuring a good biological security for human use.

Keywords: Cervix ripening, preterm birth, shear modulus, shear wave elastography, soft tissue, torsional wave.

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Authors: M. Saravanan, M. Madheswaran

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Wireless Sensor Network (WSN) clustering architecture enables features like network scalability, communication overhead reduction, and fault tolerance. After clustering, aggregated data is transferred to data sink and reducing unnecessary, redundant data transfer. It reduces nodes transmitting, and so saves energy consumption. Also, it allows scalability for many nodes, reduces communication overhead, and allows efficient use of WSN resources. Clustering based routing methods manage network energy consumption efficiently. Building spanning trees for data collection rooted at a sink node is a fundamental data aggregation method in sensor networks. The problem of determining Cluster Head (CH) optimal number is an NP-Hard problem. In this paper, we combine cluster based routing features for cluster formation and CH selection and use Minimum Spanning Tree (MST) for intra-cluster communication. The proposed method is based on optimizing MST using Simulated Annealing (SA). In this work, normalized values of mobility, delay, and remaining energy are considered for finding optimal MST. Simulation results demonstrate the effectiveness of the proposed method in improving the packet delivery ratio and reducing the end to end delay.

Keywords: Wireless sensor network, clustering, minimum spanning tree, genetic algorithm, low energy adaptive clustering hierarchy, simulated annealing.

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Authors: Domenico Chizzoniti, Monica Moscatelli, Letizia Cattani, Piero Favino, Luca Preis

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A settlement strategy is to anticipate and respond the needs of existing and future communities through the provision of primary health care facilities in marginalized areas. Access to a health care network is important to improving healthcare coverage, often lacking, in developing countries. The study explores that a good sanitary system strategy of rural contexts brings advantages to an existing settlement: improving transport, communication, water and social facilities. The objective of this paper is to define a possible methodology to implement primary health care facilities in disadvantaged areas of emerging countries. In this research, we analyze the case study of Lauro de Freitas, a municipality in the Brazilian state of Bahia, part of the Metropolitan Region of Salvador, with an area of 57,662 km² and 194.641 inhabitants. The health localization system in Lauro de Freitas is an integrated process that involves not only geographical aspects, but also a set of factors: population density, epidemiological data, allocation of services, road networks, and more. Data were collected also using semi-structured interviews and questionnaires to the local population. Synthesized data suggest that moving away from the coast where there is the greatest concentration of population and services, a network of primary health care facilities is able to improve the living conditions of small-dispersed communities. Based on the health service needs of populations, we have developed a methodological approach that is particularly useful in rural and remote contexts in emerging countries.

Keywords: Primary health care, developing countries, policy health planning, settlement strategy.

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Authors: R. Geetha, T. Padmavathy

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Security audit is an important aspect or feature to be considered in cloud service customer. It is basically a certification process to audit the controls that deliver the security requirements. Security audits are conducted by trained and qualified staffs that belong to an independent auditing organization. Security audits must be carried as a standard of security controls. Proper check to be made that the cloud user has a proper reporting and logging facilities with the customer's system and hence ensuring appropriate business and operational flow of data through cloud service. We propose a cloud-based secure auditing framework, which enables confided in power to safely store their mystery information on the semi-believed cloud specialist co-ops, and specifically share their mystery information with a wide scope of information recipient, to diminish the key administration intricacy for power proprietors and information collectors. Unique in relation to past cloud-based information framework, data proprietors transfer their mystery information into cloud utilizing static and dynamic evaluating plan. Another propelled determination is, if any information beneficiary needs individual record to download, the information collector will send the solicitation to the expert. The specialist proprietor has the Access Control. At the off probability, the businessman must impart the primary record to the knowledge collector, acknowledge statistics beneficiary solicitation. Once the acknowledgement for the records is over, the recipient downloads the first record and this record shifting time with date and downloading time with date are monitored by the inspector. In addition to deduplication concept, diminished cloud memory area using dynamic document distribution has been proposed.

Keywords: Cloud computing, cloud storage auditing, data integrity, key exposure.

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Authors: Joseph Zernik

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Validity, integrity, and impacts of the IT systems of the US federal courts have been studied as part of the Human Rights Alert-NGO (HRA) submission for the 2015 Universal Periodic Review (UPR) of human rights in the United States by the Human Rights Council (HRC) of the United Nations (UN). The current report includes overview of IT system analysis, data-mining and case studies. System analysis and data-mining show: Development and implementation with no lawful authority, servers of unverified identity, invalidity in implementation of electronic signatures, authentication instruments and procedures, authorities and permissions; discrimination in access against the public and unrepresented (pro se) parties and in favor of attorneys; widespread publication of invalid judicial records and dockets, leading to their false representation and false enforcement. A series of case studies documents the impacts on individuals' human rights, on banking regulation, and on international matters. Significance is discussed in the context of various media and expert reports, which opine unprecedented corruption of the US justice system today, and which question, whether the US Constitution was in fact suspended. Similar findings were previously reported in IT systems of the State of California and the State of Israel, which were incorporated, subject to professional HRC staff review, into the UN UPR reports (2010 and 2013). Solutions are proposed, based on the principles of publicity of the law and the separation of power: Reliance on US IT and legal experts under accountability to the legislative branch, enhancing transparency, ongoing vigilance by human rights and internet activists. IT experts should assume more prominent civic duties in the safeguard of civil society in our era.

Keywords: E-justice, federal courts, United States, human rights, banking regulation.

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Authors: F. Mehran

Abstract:

With the rapid popularization of internet services, it is apparent that the next generation terrestrial communication systems must be capable of supporting various applications like voice, video, and data. This paper presents the performance evaluation of turbo- coded mobile terrestrial communication systems, which are capable of providing high quality services for delay sensitive (voice or video) and delay tolerant (text transmission) multimedia applications in urban and suburban areas. Different types of multimedia information require different service qualities, which are generally expressed in terms of a maximum acceptable bit-error-rate (BER) and maximum tolerable latency. The breakthrough discovery of turbo codes allows us to significantly reduce the probability of bit errors with feasible latency. In a turbo-coded system, a trade-off between latency and BER results from the choice of convolutional component codes, interleaver type and size, decoding algorithm, and the number of decoding iterations. This trade-off can be exploited for multimedia applications by using optimal and suboptimal performance parameter amalgamations to achieve different service qualities. The results are therefore proposing an adaptive framework for turbo-coded wireless multimedia communications which incorporate a set of performance parameters that achieve an appropriate set of service qualities, depending on the application's requirements.

Keywords: Mobile communications, Turbo codes, wireless multimedia communication systems.

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Authors: Sultan Alharby, Nick Harris, Alex Weddell, Jeff Reeve

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The concept of the Internet of Things (IoT) has received much attention over the last five years. It is predicted that the IoT will influence every aspect of our lifestyles in the near future. Wireless Sensor Networks are one of the key enablers of the operation of IoTs, allowing data to be collected from the surrounding environment. However, due to limited resources, nature of deployment and unattended operation, a WSN is vulnerable to various types of attack. Security is paramount for reliable and safe communication between IoT embedded devices, but it does, however, come at a cost to resources. Nodes are usually equipped with small batteries, which makes energy conservation crucial to IoT devices. Nevertheless, security cost in terms of energy consumption has not been studied sufficiently. Previous research has used a security specification of 802.15.4 for IoT applications, but the energy cost of each security level and the impact on quality of services (QoS) parameters remain unknown. This research focuses on the cost of security at the IoT media access control (MAC) layer. It begins by studying the energy consumption of IEEE 802.15.4 security levels, which is followed by an evaluation for the impact of security on data latency and throughput, and then presents the impact of transmission power on security overhead, and finally shows the effects of security on memory footprint. The results show that security overhead in terms of energy consumption with a payload of 24 bytes fluctuates between 31.5% at minimum level over non-secure packets and 60.4% at the top security level of 802.15.4 security specification. Also, it shows that security cost has less impact at longer packet lengths, and more with smaller packet size. In addition, the results depicts a significant impact on data latency and throughput. Overall, maximum authentication length decreases throughput by almost 53%, and encryption and authentication together by almost 62%.

Keywords: Internet of Things, IEEE 802.15.4, security cost evaluation, wireless sensor network, energy consumption.

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Authors: Ashish Saini, A.K. Saxena

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The genetic algorithm (GA) based solution techniques are found suitable for optimization because of their ability of simultaneous multidimensional search. Many GA-variants have been tried in the past to solve optimal power flow (OPF), one of the nonlinear problems of electric power system. The issues like convergence speed and accuracy of the optimal solution obtained after number of generations using GA techniques and handling system constraints in OPF are subjects of discussion. The results obtained for GA-Fuzzy OPF on various power systems have shown faster convergence and lesser generation costs as compared to other approaches. This paper presents an enhanced GA-Fuzzy OPF (EGAOPF) using penalty factors to handle line flow constraints and load bus voltage limits for both normal network and contingency case with congestion. In addition to crossover and mutation rate adaptation scheme that adapts crossover and mutation probabilities for each generation based on fitness values of previous generations, a block swap operator is also incorporated in proposed EGA-OPF. The line flow limits and load bus voltage magnitude limits are handled by incorporating line overflow and load voltage penalty factors respectively in each chromosome fitness function. The effects of different penalty factors settings are also analyzed under contingent state.

Keywords: Contingent operation state, Fuzzy rule base, Genetic Algorithms, Optimal Power Flow.

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Authors: G. Tamanza, A. Bossoni

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84 deaf students (from primary school to college) and their families participated in this inclusion project in cooperation with numerous institutions in northern Italy (Brescia-Lombardy). Participants were either congenitally deaf or their deafness was related to other pathologies. This research promoted the integration of deaf students as they pass from primary school to high school to college. Learning methods and processes were studied that focused on encour­aging individual autonomy and socialization. The research team and its collaborators included school teachers, speech ther­apists, psychologists and home tutors, as well as teaching assistants, child neuropsychiatrists and other external authorities involved with deaf persons social inclusion programs. Deaf children and their families were supported, in terms of inclusion, and were made aware of the research team that focused on the Bisogni Educativi Speciali (BES or Special Educational Needs) (L.170/2010 - DM 5669/2011). This project included a diagnostic and evaluative phase as well as an operational one. Results demonstrated that deaf children were highly satisfied and confident; academic performance improved and collaboration in school increased. Deaf children felt that they had access to high school and college. Empowerment for the families of deaf children in terms of networking among local services that deal with the deaf also improved while family satisfaction also improved. We found that teachers and those who gave support to deaf children increased their professional skills. Achieving autonomy, instrumental, communicative and relational abilities were also found to be crucial. Project success was determined by temporal continuity, clear theoretical methodology, strong alliance for the project direction and a resilient team response.

Keywords: Autonomy, inclusion, skills, well-being.

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Authors: Shih-Bin Wang, Ping Yuan, Syu-Fang Liu, Ming-Jun Kuo

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By the application of an improved back-propagation neural network (BPNN), a model of current densities for a solid oxide fuel cell (SOFC) with 10 layers is established in this study. To build the learning data of BPNN, Taguchi orthogonal array is applied to arrange the conditions of operating parameters, which totally 7 factors act as the inputs of BPNN. Also, the average current densities achieved by numerical method acts as the outputs of BPNN. Comparing with the direct solution, the learning errors for all learning data are smaller than 0.117%, and the predicting errors for 27 forecasting cases are less than 0.231%. The results show that the presented model effectively builds a mathematical algorithm to predict performance of a SOFC stack immediately in real time. Also, the calculating algorithms are applied to proceed with the optimization of the average current density for a SOFC stack. The operating performance window of a SOFC stack is found to be between 41137.11 and 53907.89. Furthermore, an inverse predicting model of operating parameters of a SOFC stack is developed here by the calculating algorithms of the improved BPNN, which is proved to effectively predict operating parameters to achieve a desired performance output of a SOFC stack.

Keywords: a SOFC stack, BPNN, inverse predicting model of operating parameters, optimization of the average current density

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Authors: Lan Wu

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China’s declared transformation towards a ‘new electricity system dominated by renewable energy’ requires a cleaner electricity consumption mix with high shares of renewable energy sourced-electricity (RES-E). Unfortunately, integration of RES-E into Chinese electricity markets remains a problem pending more robust legal support, evidenced by the curtailment of wind and solar power due to integration constraints. The upcoming Energy Law of the PRC (Energy Law) is expected to provide such long-awaiting support and coordinate the existing diverse sector-specific laws to deal with the weak implementation that dampening the delivery of their desired regulatory effects. However, in the shadow of the COVID-19 crisis, it remains uncertain how this new Energy Law brings synergies to RES-E integration, mindful of the significant impacts of the pandemic. Through the theoretical lens of the interplay between China’s electricity market reform and legislative development, this paper investigates whether there is a paradigm shift in Energy Law regarding renewable energy integration compared with the existing sector-specific energy laws. It examines the 2020 Draft for Comments on the Energy Law and analyses its relationship with sector-specific energy laws focusing on RES-E integration. The comparison is drawn upon five critical aspects of the RES-E integration issue, including the status of renewables, marketisation, incentive schemes, consumption mechanisms, access to power grids and dispatching. The analysis shows that it is reasonable to expect a more open and well-organised electricity market, enabling the absorption of high shares of RES-E. The present paper concludes that a period of prosperous development of RES-E in the post-COVID-19 era can be anticipated with the legal support by the upcoming Energy Law. It contributes to understanding the signals China is sending regarding the transition towards a cleaner energy future.

Keywords: energy law, energy transition, electricity market reform, renewable energy integration

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Authors: Syarifah Abd Rahim, Fatinah Ab Rahman, Engku N. E. M. Nasir, Noor A. Ramle

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Co-crystal is believed to improve the solubility and dissolution rates and thus, enhanced the bioavailability of poor water soluble drugs particularly during the oral route of administration. With the existing of poorly soluble drugs in pharmaceutical industry, the screening of co-crystal formation using carbamazepine (CBZ) as a model drug compound with dicarboxylic acids co-crystal formers (CCF) namely fumaric (FA) and succinic (SA) acids in ethanol has been studied. The co-crystal formations were studied by varying the mol ratio values of CCF to CBZ to access the effect of CCF concentration on the formation of the co-crystal. Solvent evaporation, slurry and cooling crystallization which representing the solution based method co-crystal screening were used. Based on the differential scanning calorimetry (DSC) analysis, the melting point of CBZ-SA in different ratio was in the range between 188oC-189oC. For CBZ-FA form A and CBZ-FA form B the melting point in different ratio were in the range of 174oC-175oC and 185oC-186oC respectively. The product crystal from the screening was also characterized using X-ray powder diffraction (XRPD). The XRPD pattern profile analysis has shown that the CBZ co-crystals with FA and SA were successfully formed for all ratios studied. The findings revealed that CBZ-FA co-crystal were formed in two different polymorphs. It was found that CBZ-FA form A and form B were formed from evaporation and slurry crystallization methods respectively. On the other hand, in cooling crystallization method, CBZ-FA form A was formed at lower mol ratio of CCF to CBZ and vice versa. This study disclosed that different methods and mol ratios during the co-crystal screening can affect the outcome of co-crystal produced such as polymorphic forms of co-crystal and thereof. Thus, it was suggested that careful attentions is needed during the screening since the co-crystal formation is currently one of the promising approach to be considered in research and development for pharmaceutical industry to improve the poorly soluble drugs.

Keywords: Carbamazepine, co-crystal, co-crystal former, dicarboxylic acid.

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Authors: Abdelkarim M. Ertiame, D. W. Yu, D. L. Yu, J. B. Gomm

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In this paper, a robust fault detection and isolation (FDI) scheme is developed to monitor a multivariable nonlinear chemical process called the Chylla-Haase polymerization reactor, when it is under the cascade PI control. The scheme employs a radial basis function neural network (RBFNN) in an independent mode to model the process dynamics, and using the weighted sum-squared prediction error as the residual. The Recursive Orthogonal Least Squares algorithm (ROLS) is employed to train the model to overcome the training difficulty of the independent mode of the network. Then, another RBFNN is used as a fault classifier to isolate faults from different features involved in the residual vector. Several actuator and sensor faults are simulated in a nonlinear simulation of the reactor in Simulink. The scheme is used to detect and isolate the faults on-line. The simulation results show the effectiveness of the scheme even the process is subjected to disturbances and uncertainties including significant changes in the monomer feed rate, fouling factor, impurity factor, ambient temperature, and measurement noise. The simulation results are presented to illustrate the effectiveness and robustness of the proposed method.

Keywords: Robust fault detection, cascade control, independent RBF model, RBF neural networks, Chylla-Haase reactor, FDI under closed-loop control.

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Authors: Kai Häussermann, Christoph Hubig, Paul Levi, Frank Leymann, Oliver Siemoneit, Matthias Wieland, Oliver Zweigle

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Using spatial models as a shared common basis of information about the environment for different kinds of contextaware systems has been a heavily researched topic in the last years. Thereby the research focused on how to create, to update, and to merge spatial models so as to enable highly dynamic, consistent and coherent spatial models at large scale. In this paper however, we want to concentrate on how context-aware applications could use this information so as to adapt their behavior according to the situation they are in. The main idea is to provide the spatial model infrastructure with a situation recognition component based on generic situation templates. A situation template is – as part of a much larger situation template library – an abstract, machinereadable description of a certain basic situation type, which could be used by different applications to evaluate their situation. In this paper, different theoretical and practical issues – technical, ethical and philosophical ones – are discussed important for understanding and developing situation dependent systems based on situation templates. A basic system design is presented which allows for the reasoning with uncertain data using an improved version of a learning algorithm for the automatic adaption of situation templates. Finally, for supporting the development of adaptive applications, we present a new situation-aware adaptation concept based on workflows.

Keywords: context-awareness, ethics, facilitation of system use through workflows, situation recognition and learning based on situation templates and situation ontology's, theory of situationaware systems

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Authors: Manop Aorpimai, Ponthep Navakitkanok

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In this paper, the development of the ephemeris generation module used for the Thaichote satellite operations is presented. It is a vital part of the flight dynamics system, which comprises, the orbit determination, orbit propagation, event prediction and station-keeping maneouvre modules. In the generation of the spacecraft ephemeris data, the estimated orbital state vector from the orbit determination module is used as an initial condition. The equations of motion are then integrated forward in time to predict the satellite states. The higher geopotential harmonics, as well as other disturbing forces, are taken into account to resemble the environment in low-earth orbit. Using a highly accurate numerical integrator based on the Burlish-Stoer algorithm the ephemeris data can be generated for long-term predictions, by using a relatively small computation burden and short calculation time. Some events occurring during the prediction course that are related to the mission operations, such as the satellite’s rise/set viewed from the ground station, Earth and Moon eclipses, the drift in groundtrack as well as the drift in the local solar time of the orbital plane are all detected and reported. When combined with other modules to form a flight dynamics system, this application is aimed to be applied for the Thaichote satellite and successive Thailand’s Earth-observation missions. 

Keywords: Flight Dynamics System, Orbit Propagation, Satellite Ephemeris, Thailand’s Earth Observation Satellite.

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Authors: Kasthurirangan Gopalakrishnan, Marshall R. Thompson, Anshu Manik

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This paper describes the use of artificial neural networks (ANN) for predicting non-linear layer moduli of flexible airfield pavements subjected to new generation aircraft (NGA) loading, based on the deflection profiles obtained from Heavy Weight Deflectometer (HWD) test data. The HWD test is one of the most widely used tests for routinely assessing the structural integrity of airport pavements in a non-destructive manner. The elastic moduli of the individual pavement layers backcalculated from the HWD deflection profiles are effective indicators of layer condition and are used for estimating the pavement remaining life. HWD tests were periodically conducted at the Federal Aviation Administration-s (FAA-s) National Airport Pavement Test Facility (NAPTF) to monitor the effect of Boeing 777 (B777) and Beoing 747 (B747) test gear trafficking on the structural condition of flexible pavement sections. In this study, a multi-layer, feed-forward network which uses an error-backpropagation algorithm was trained to approximate the HWD backcalculation function. The synthetic database generated using an advanced non-linear pavement finite-element program was used to train the ANN to overcome the limitations associated with conventional pavement moduli backcalculation. The changes in ANN-based backcalculated pavement moduli with trafficking were used to compare the relative severity effects of the aircraft landing gears on the NAPTF test pavements.

Keywords: Airfield pavements, ANN, backcalculation, newgeneration aircraft

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