Search results for: automatic flight planning

Authors: Yasmine Abu Adla, Racha Soubra, Milana Kasab, Mohamad O. Diab, Aly Chkeir

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Over the past several years, researchers have shown a great interest in assessing the mobility of elderly people to measure their functional status. Usually, such an assessment is done by conducting tests that require the subject to walk a certain distance, turn around, and finally sit back down. Consequently, this study aims to provide an at home monitoring system to assess the patient’s status continuously. Thus, we proposed a technique to automatically detect when a subject sits down while walking at home. In this study, we utilized a Doppler radar system to capture the motion of the subjects. More than 20 features were extracted from the radar signals, out of which 11 were chosen based on their intraclass correlation coefficient (ICC > 0.75). Accordingly, the sequential floating forward selection wrapper was applied to further narrow down the final feature vector. Finally, 5 features were introduced to the linear discriminant analysis classifier, and an accuracy of 93.75% was achieved as well as a precision and recall of 95% and 90%, respectively.

Keywords: Doppler radar system, stand-to-sit phase, TUG test, machine learning, classification

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Authors: Namhun Lee, Seong Jin Kim

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The construction industry represents one of the largest industries in the United States, yet it continues to face several occupational health and safety challenges. Many workers on construction sites are suffering from extended exposure to stressful situations such as poor and hazardous work environments and task complexity. Stress can be commonly defined as a feeling of emotional or physical tension, which can easily impact construction safety and result in a higher rate of job-related injuries in the construction industry. Physiological signals transmitted from wearable biosensors can be used to detect excessive stress. Therefore, workers’ stress should be detected and mitigated to prevent any type of serious incident or accident proactively. By doing this, construction productivity, as well as job satisfaction, would also be improved in the construction industry. To establish a foundation in this field of research, a conceptual framework for using wearable technology for construction safety has been developed for continuous and automatic monitoring of worker’s stress. The conceptual framework will serve as a foothold in future studies on the application of wearable technology for construction safety.

Keywords: construction safety, occupational stress, stress monitoring, wearable biosensors

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Authors: Arsalan Jabbar, Wajiha Javed, Nelofer Mehboob, Zahid Memon

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Introduction: There are multiple social, individual and cultural factors that influence an individual’s decision to adopt family planning methods especially among non-users in patriarchal societies like Pakistan.Non-users, if targeted efficiently, can contribute significantly to country’s CPR. A research study showed that non-users if convinced to adopt lactational amenorrhea method can shift to long-term methods in future. Research shows that if non-users are targeted efficiently a 59% reduction in unintended pregnancies in Saharan Africa and South-Central and South-East Asia is anticipated. Methods: We did secondary data analysis on Pakistan Demographic Heath Survey (2012-13) dataset. Use of contraception (never-use/ever-use) was the outcome variable. At univariate level Chi-square/Fisher Exact test was used to assess relationship of baseline covariates with contraception use. Then variables to be incorporated in the model were checked for multi-collinearity, confounding, and interaction. Then binary logistic regression (with an urban-rural stratification) was done to find the relationship between contraception use and baseline demographic and social variables. Results: The multivariate analyses of the study showed that younger women (≤ 29 years) were more prone to be never users as compared to those who were > 30 years and this trend was seen in urban areas (AOR 1.92, CI 1.453-2.536) as well as rural areas (AOR 1.809, CI 1.421-2.303). While looking at regional variation, women from urban Sindh (AOR 1.548, CI 1.142-2.099) and urban Balochistan (AOR 2.403, CI 1.504-3.839) had more never users as compared to other urban regions. Women in the rich wealth quintile were more never users and this was seen both in urban and rural localities (urban (AOR 1.106 CI .753-1.624); rural areas (AOR 1.162, CI .887-1.524)) even though these were not statistically significant. Women idealizing more children(> 4) are more never users as compared to those idealizing less children in both urban (AOR 1.854, CI 1.275-2.697) and rural areas (AOR 2.101, CI 1.514-2.916). Women who never lost a pregnancy were more inclined to be non-users in rural areas (AOR 1.394, CI 1.127-1.723) .Women familiar with only traditional or no method had more never users in rural areas (AOR 1.717, CI 1.127-1.723) but in urban areas it wasn’t significant. Women unaware of Lady Health Worker’s presence in their area were more never users especially in rural areas (AOR 1.276, CI 1.014-1.607). Women who did not visit any care provider were more never users (urban (AOR 11.738, CI 9.112-15.121) rural areas (AOR 7.832, CI 6.243-9.826)). Discussion/Conclusion: This study concluded that government, policy makers and private sector family planning programs should focus on the untapped pool of never users (younger women from underserved provinces, in higher wealth quintiles, who desire more children.). We need to make sure to cover catchment areas where there are less LHWs and less providers as ignorance to modern methods and never been visited by an LHW are important determinants of never use. This all is in sync with previous literate from similar developing countries.

Keywords: contraception, demographic and health survey, family planning, never users

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Authors: Joy Ghosh, Debasmita Biswas

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The road network of any area is the most important indicator of regional planning. For proper utilization of urban road networks, the structural parameters such as connectivity and accessibility should be analyzed and evaluated. This paper aims to explain the application of GIS on urban road network connectivity and accessibility analysis with a case study of Chandannagar City. This paper has been made to analyze the road network connectivity through various connectivity measurements like the total number of nodes and links, Cyclomatic Number, Alpha Index, Beta Index, Gamma index, Eta index, Pi index, Theta Index, and Aggregated Transport Score, Road Density based on existing road network in Chandannagar city in India. Accessibility is measured through the shortest Path Matrix, associate Number, and Shimbel Index. Various urban services, such as schools, banks, Hospitals, petrol pumps, ATMs, police stations, theatres, parks, etc., are considered for the accessibility analysis for each ward. This paper also highlights the relationship between urban land use/ land cover (LULC) and urban road network and population density using various spatial and statistical measurements. The datasets were collected through a field survey of 33 wards of the Chandannagar Municipal Corporation area, and the secondary data were collected through an open street map and satellite image of LANDSAT8 OLI & TIRS from USGS. Chandannagar was actually once a French colony, and at that time, various sort of planning was applied, but now Chandannagar city continues to grow haphazardly because that city is facing some problems; the knowledge gained from this paper helps to create a more efficient and accessible road network. Therefore, it would be suggested that some wards need to improve their connectivity and accessibility for the future growth and development of Chandannagar.

Keywords: accessibility, connectivity, transport, road network

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Authors: Francine Morales Tavares, Jose Alberto Rio Fernandes

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The expanding concept of Heritage and the increased relevance of how heritage places relate to their surroundings is associated with an important shift in public heritage policies and how they consider the development of cities and communities, with an increasingly relevant role of management. Within the current discussions, management plans, mandatory since the year 2005 in areas classified by UNESCO as World Heritage, it is a tool for the reconciliation of cultural heritage demands with the needs of multiple users of a certain area, being especially critical in the case of urban areas with intense touristic pressure. Considering the transformations of the heritage policy management model, this paper discusses the practices on the integration of cultural heritage in urban policies through indicators which were selected from resource manual 'Managing Cultural World Heritage (2013)' and analyzed two case studies: The Management Plan of the Historic Centre of Porto (Portugal) and The Management Plan for the Historic Site of Olinda (Brazil). The empirical evidence concluded that for the historic centre of Porto the increase of tourism is the main aim driver in the management plan, with positive and negative aspects on the heritage management point of view, unlike Olinda, where the plan for the development of local urban policies was identified as essential. Plans also differ in form, content and process but coincide on being unaligned with committed local political leaders’ agendas, with the consequent misunderstandings between theory and practice, planning and management, and critically missing in the field integration of urban policies. Therefore, more debate about management plans, more efficient tools and also, appropriate methodologies to correlate cultural heritage and urban public policy are still lacking.

Keywords: world heritage, management plan, planning, urban policies

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Authors: Kausik Halder, Nabendu Chaki, Ranjan Dasgupta

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We present a modelling framework that supports the engineering of early requirements specifications for design of learner centric dynamic Learning Management System. The framework is based on i* modelling tool and Means End Analysis, that adopts primitive concepts for modelling early requirements (such as actor, goal, and strategic dependency). We show how pedagogical and computational requirements for designing a learner centric Learning Management system can be adapted for the automatic early requirement engineering specifications. Finally, we presented a model on a Learner Quanta based adaptive Courseware. Our early requirement analysis shows that how means end analysis reveals gaps and inconsistencies in early requirements specifications that are by no means trivial to discover without the help of formal analysis tool.

Keywords: adaptive courseware, early requirement engineering, means end analysis, organizational modelling, requirement modelling

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Authors: Çiğdem Bakır, Mecit Yüzkat

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With the increasing emphasis on water quality worldwide, the search for and expanding the market for new and intelligent monitoring systems has increased. The current method is the laboratory process, where samples are taken from bodies of water, and tests are carried out in laboratories. This method is time-consuming, a waste of manpower, and uneconomical. To solve this problem, we used machine learning methods to detect water pollution in our study. We created decision trees with the Orange3 software we used in our study and tried to determine all the factors that cause water pollution. An automatic prediction model based on water quality was developed by taking many model inputs such as water temperature, pH, transparency, conductivity, dissolved oxygen, and ammonia nitrogen with machine learning methods. The proposed approach consists of three stages: preprocessing of the data used, feature detection, and classification. We tried to determine the success of our study with different accuracy metrics and the results. We presented it comparatively. In addition, we achieved approximately 98% success with the decision tree.

Keywords: decision tree, water quality, water pollution, machine learning

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Authors: Matthias Haerri, Tobias Huettche, Clemens Kustner

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This article discusses the impact of digitization on business valuation. In order to become and remain ‘digital’, investments are necessary whose return on investment (ROI) often remains vague. This uncertainty is contradictory for a valuation, that rely on predictable cash flows, fixed capital structures and the steady state. However digitisation does not make a company valuation impossible, but traditional approaches must be reconsidered. The authors identify four areas that are to be changing: (1) Tools instead of intuition - In the future, company valuation will neither be art nor science, but craft. This does not require intuition, but experience and good tools. Digital evaluation tools beyond Excel will therefore gain in importance. (2) Real-time instead of deadline - At present, company valuations are always carried out on a case-by-case basis and on a specific key date. This will change with the digitalization and the introduction of web-based valuation tools. Company valuations can thus not only be carried out faster and more efficiently, but can also be offered more frequently. Instead of calculating the value for a previous key date, current and real-time valuations can be carried out. (3) Predictive planning instead of analysis of the past - Past data will also be needed in the future, but its use will not be limited to monovalent time series or key figure analyses. With pictures of ‘black swans’ and the ‘turkey illusion’ it was made clear to us that we build forecasts on too few data points of the past and underestimate the power of chance. Predictive planning can help here. (4) Convergence instead of residual value - Digital transformation shortens the lifespan of viable business models. If companies want to live forever, they have to change forever. For the company valuation, this means that the business model valid on the valuation date only has a limited service life.

Keywords: business valuation, corporate finance, digitisation, disruption

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Authors: Alaa Alateeqi, Sara Aldhulaiee, Sara Alibraheem, Noura Alsaleh

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For the past few decades or so, Kuwait's local food industry has grown remarkably due to increase in demand for processed or semi processed food products in the market. It is important that the ever increasing food manufacturing/processing units maintain the required quality standards as per regional and to some extent international quality requirements. It has been realized that all Kuwait food manufacturing units should understand and follow the international standard practices, and moreover a set of guidelines must be set for quality assurance such that any new business in this area is aware of the minimum requirements. The current study has been undertaken to identify the gaps in Kuwait food industries in following the Good Manufacturing Practices (GMP) in terms of quality planning, control and quality assurance. GMP refers to Good Manufacturing Practices, which are a set of rules, laws or regulations that certify producing products within quality standards and ensuring that it is safe, pure and effective. The present study therefore reports about a ‘case study’ in a reputed food manufacturing unit in Kuwait; starting from assessment of the current practices followed by diagnosis, report of the diagnosis and road map and corrective measures for GMP implementation in the unit. The case study has also been able to identify the best practices and establish a benchmarking data for other companies to follow, through measuring the selected company's quality, policies, products and strategies and compare it with the established benchmarking data. A set of questionnaires and assessment mechanism has been established for companies to identify their ‘benchmarking score’ in relation to the number of non-conformities and conformities with the GMP standard requirements.

Keywords: good manufacturing practices, GMP, benchmarking, Kuwait Food Industries, food quality

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Authors: Sidney A. Lima, Hermann J. H. Kux, Elcio H. Shiguemori

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The Unmanned Aircraft Systems (UAS) usually navigate through the Global Navigation Satellite System (GNSS) associated with an Inertial Navigation System (INS). However, GNSS can have its accuracy degraded at any time or even turn off the signal of GNSS. In addition, there is the possibility of malicious interferences, known as jamming. Therefore, the image navigation system can solve the autonomy problem, because if the GNSS is disabled or degraded, the image navigation system would continue to provide coordinate information for the INS, allowing the autonomy of the system. This work aims to evaluate the accuracy of the positioning though photogrammetry concepts. The methodology uses orthophotos and Digital Surface Models (DSM) as a reference to represent the object space and photograph obtained during the flight to represent the image space. For the calculation of the coordinates of the perspective center and camera attitudes, it is necessary to know the coordinates of homologous points in the object space (orthophoto coordinates and DSM altitude) and image space (column and line of the photograph). So if it is possible to automatically identify in real time the homologous points the coordinates and attitudes can be calculated whit their respective accuracies. With the methodology applied in this work, it is possible to verify maximum errors in the order of 0.5 m in the positioning and 0.6º in the attitude of the camera, so the navigation through the image can reach values equal to or higher than the GNSS receivers without differential correction. Therefore, navigating through the image is a good alternative to enable autonomous navigation.

Keywords: autonomy, navigation, security, photogrammetry, remote sensing, spatial resection, UAS

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Authors: Libin Ouyang

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China has experienced a very fast urbanization process in the past two decades. Due to the uncoordinated characteristics of regional development in China, a large number of people from rural areas or small towns have flooded into regional central cities, which are building new cities around them due to the shortage of construction land or the need for urban development. However, the construction of some new cities has not achieved the expected effect, the absorption capacity of industry and population is limited, and the phenomenon of capital and land waste is obvious. This paper takes the Xixian New Area in Shaanxi Province, an inland region in Northwest China, as an example, and tries to analyse the reasons for the lack of vitality in the current situation of the Xixian New Area from the perspective of site layout and urban design, analyses the practical experience of the construction of new city cores in developed countries and regions, and studies how to optimise at the level of site layout planning and urban design to improve the vitality and attractiveness of the new city, decongest the population of large cities, effectively solve the problems of large cities, and promote The study will also examine how to optimise land use planning and urban design to enhance the vitality and attractiveness of new cities, relieve the population of large cities, effectively solve the problems of large cities and promote sustainable development of new cities. The study can serve as a reference for urban planners and policy makers, provide theoretical assistance for new city construction in other less developed regions of China, and provide some case references for urban construction in other developing countries undergoing rapid urbanisation.

Keywords: new city, land use layout, urban design, attraction

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Authors: Victor Radich, Tania Basso, Regina Moraes

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Lead qualification is one of the main procedures in Customer Relationship Management (CRM) projects. Its main goal is to identify potential consumers who have the ideal characteristics to establish a profitable and long-term relationship with a certain organization. Social networks can be an important source of data for identifying and qualifying leads since interest in specific products or services can be identified from the users’ expressed feelings of (dis)satisfaction. In this context, this work proposes the use of machine learning techniques and sentiment analysis as an extra step in the lead qualification process in order to improve it. In addition to machine learning models, sentiment analysis or opinion mining can be used to understand the evaluation that the user makes of a particular service, product, or brand. The results obtained so far have shown that it is possible to extract data from social networks and combine the techniques for a more complete classification.

Keywords: lead qualification, sentiment analysis, opinion mining, machine learning, CRM, lead scoring

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Authors: Yun-Xuan Tang, Pei-Yuan Liu, Kun-Mu Lu, Min-Tsung Tseng, Liang-Kuang Chen, Yuh-Feng Tsai, Ching-Wen Lee, Jay Wu

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Breast cancer is predominant of malignant tumors in females. The increase in the glandular density increases the risk of breast cancer. BI-RADS is a frequently used density indicator in mammography; however, it significantly overestimates the glandularity. Therefore, it is very important to accurately and quantitatively assess the glandularity by mammography. In this study, 20%, 30% and 50% glandularity phantoms were exposed using a mammography machine at 28, 30 and 31 kVp, and 30, 55, 80 and 105 mAs, respectively. The regions of interest (ROIs) were drawn to assess the gray level. The relationship between the glandularity and gray level under various compression thicknesses, kVp, and mAs was established by the multivariable linear regression. A phantom verification was performed with automatic exposure control (AEC). The regression equation was obtained with an R-square value of 0.928. The average gray levels of the verification phantom were 8708, 8660 and 8434 for 0.952, 0.963 and 0.985 g/cm3, respectively. The percent differences of glandularity to the regression equation were 3.24%, 2.75% and 13.7%. We concluded that the proposed method could be clinically applied in mammography to improve the glandularity estimation and further increase the importance of breast cancer screening.

Keywords: mammography, glandularity, gray value, BI-RADS

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Authors: Fezzani Boubaker

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The modified activated sludge model (ASM1 or Mantis) is a generic structured model and a common platform for dynamic simulation of varieties of aerobic processes for optimization and upgrading of existing plants and for new facilities design. In this study, the modified ASM1 included in the GPS-X software was used to simulate the wastewater treatment plant (WWTP) of Beja treating domestic sewage mixed with baker‘s yeast factory effluent. The results of daily measurements and operating records were used to calibrate the model. A sensitivity and an automatic optimization analysis were conducted to determine the most sensitive and optimal parameters. The results indicated that the ASM1 model could simulate with good accuracy: the COD concentration of effluents from the WWTP of Beja for all months of the year 2012. In addition, it prevents the disruption observed at the output of the plant by injecting the baker‘s yeast factory effluent at high concentrations varied between 20 and 80 g/l.

Keywords: ASM1, activated sludge, baker’s yeast effluent, modelling, simulation, GPS-X 5.1 software

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Authors: Lin Wenli, Fu Linchun, Zhang Yi, Wu Ming

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To meet the demands of long-life and high-intelligence for satellites, the electrical power system should be provided with self-health condition evaluation capability. Any over-stress events in operations should be recorded. Based on Linear stresses accumulation damage theory, accumulative damage analysis was performed on thermal-mechanical-electrical united stresses for three components including the solar array, the batteries and the power conditioning unit. Then an overall health percentage evaluation model for satellite electrical power system was built. To obtain the accurate quantity for system health percentage, an automatic feedback closed-loop correction method for all coefficients in the evaluation model was present. The evaluation outputs could be referred as taking earlier fault-forecast and interventions for Ground Control Center or Satellites self.

Keywords: satellite electrical power system, health percentage, linear stresses accumulation damage, evaluation model

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Authors: Fuad Noman, Sh-Hussain Salleh, Chee-Ming Ting, Hadri Hussain, Syed Rasul

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In this paper, a data-driven dictionary approach is proposed for the automatic detection and classification of cardiovascular abnormalities. Electrocardiography (ECG) signal is represented by the trained complete dictionaries that contain prototypes or atoms to avoid the limitations of pre-defined dictionaries. The data-driven trained dictionaries simply take the ECG signal as input rather than extracting features to study the set of parameters that yield the most descriptive dictionary. The approach inherently learns the complicated morphological changes in ECG waveform, which is then used to improve the classification. The classification performance was evaluated with ECG data under two different preprocessing environments. In the first category, QT-database is baseline drift corrected with notch filter and it filters the 60 Hz power line noise. In the second category, the data are further filtered using fast moving average smoother. The experimental results on QT database confirm that our proposed algorithm shows a classification accuracy of 92%.

Keywords: electrocardiogram, dictionary learning, sparse coding, classification

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Authors: Andressa dos Santos Nicolau, João P. da S.C Algusto, Claudio Márcio do N. A. Pereira, Roberto Schirru

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In case of abnormal situations, the nuclear power plant (NPP) operators must follow written procedures to check the condition of the plant and to classify the type of emergency. In this paper, we proposed a Real Time Expert System in order to improve operator’s performance in case of transient or accident with reactor shutdown. The expert system’s knowledge is based on the sequence of events (SoE) of known accident and two emergency procedures of the Brazilian Pressurized Water Reactor (PWR) NPP and uses two kinds of knowledge representation: rule and logic trees. The results show that the system was able to classify the response of the automatic protection systems, as well as to evaluate the conditions of the plant, diagnosing the type of occurrence, recovery procedure to be followed, indicating the shutdown root cause, and classifying the emergency level.

Keywords: emergence procedure, expert system, operator support, PWR nuclear power plant

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Authors: Oliveira M., Gonçalves L., Francisco I., Caramelo F., Vale F., Sanz D., Domingues M., Lopes M., Moreia D., Lopes T., Santos T., Cardoso H.

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The ARTHUR project consists of a platform that allows the virtual performance of maxillofacial surgeries, offering, in a photorealistic concept, the possibility for the patient to have an idea of the surgical changes before they are performed on their face. For this, the system brings together several image formats, dicoms and objs that, after loading, will generate the bone volume, soft tissues and hard tissues. The system also incorporates the patient's stereophotogrammetry, in addition to their data and clinical history. After loading and inserting data, the clinician can virtually perform the surgical operation and present the final result to the patient, generating a new facial surface that contemplates the changes made in the bone and tissues of the maxillary area. This tool acts in different situations that require facial reconstruction, however this project focuses specifically on two types of use cases: bone congenital disfigurement and acquired disfiguration such as oral cancer with bone attainment. Being developed a cloud based solution, with mobile support, the tool aims to reduce the decision time window of patient. Because the current simulations are not realistic or, if realistic, need time due to the need of building plaster models, patient rates on decision, rely on a long time window (1,2 months), because they don’t identify themselves with the presented surgical outcome. On the other hand, this planning was performed time based on average estimated values of the position of the maxilla and mandible. The team was based on averages of the facial measurements of the population, without specifying racial variability, so the proposed solution was not adjusted to the real individual physiognomic needs.

Keywords: 3D computing, image processing, image registry, image reconstruction

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Authors: Evans Belly, Imdad Rizvi, M. M. Kadam

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Satellite imagery is one of the emerging technologies which are extensively utilized in various applications such as detection/extraction of man-made structures, monitoring of sensitive areas, creating graphic maps etc. The main approach here is the automated detection of buildings from very high resolution (VHR) optical satellite images. Initially, the shadow, the building and the non-building regions (roads, vegetation etc.) are investigated wherein building extraction is mainly focused. Once all the landscape is collected a trimming process is done so as to eliminate the landscapes that may occur due to non-building objects. Finally the label method is used to extract the building regions. The label method may be altered for efficient building extraction. The images used for the analysis are the ones which are extracted from the sensors having resolution less than 1 meter (VHR). This method provides an efficient way to produce good results. The additional overhead of mid processing is eliminated without compromising the quality of the output to ease the processing steps required and time consumed.

Keywords: building detection, shadow detection, landscape generation, label, partitioning, very high resolution (VHR) satellite imagery

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Authors: Lee Myung-Won, Kwak Keun-Chang

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This paper is concerned with knowledge representation and extraction of fuzzy if-then rules using Interval Type-2 Context-based Fuzzy C-Means clustering (IT2-CFCM) with the aid of fuzzy granulation. This proposed clustering algorithm is based on information granulation in the form of IT2 based Fuzzy C-Means (IT2-FCM) clustering and estimates the cluster centers by preserving the homogeneity between the clustered patterns from the IT2 contexts produced in the output space. Furthermore, we can obtain the automatic knowledge representation in the design of Radial Basis Function Networks (RBFN), Linguistic Model (LM), and Adaptive Neuro-Fuzzy Networks (ANFN) from the numerical input-output data pairs. We shall focus on a design of ANFN in this paper. The experimental results on an estimation problem of energy performance reveal that the proposed method showed a good knowledge representation and performance in comparison with the previous works.

Keywords: IT2-FCM, IT2-CFCM, context-based fuzzy clustering, adaptive neuro-fuzzy network, knowledge representation

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Authors: Zakir H. Shaik, Punam L. Vartak

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Management By Objectives (MBO) is a management technique in which objectives of an organisation are conveyed to the employees to establish the individual goals. These objectives and goals are then monitored and assessed jointly by management and the employee time to time. This tool can be used for planning, monitoring as well as for performance appraisal. The success of an organisation is largely dependent on its’s Vision. Thus, it is of paramount importance to achieve the realm of vision through a mission which is well crafted within the organisation to address the objectives. The success of the mission depends upon how realistic and action oriented philosophical approach, an organisation caters to; and how the individual goals are set to track and meet the objectives. Thus, focused and passionate efforts of the team, assigned for the mission, are an absolute obligation for achieving the vision of any organisation. Any construction site is generally a controlled disorder having huge investments, resources and logistics involved. The Construction progression is time-consuming with many isolated as well as interconnected activities. Traditional MBO approach can be unsuccessful if planning and control is non-realistic and inflexible. Moreover, the Construction Industry is far behind understanding these concepts. It is important to address the employee engagement in defining and creating awareness to achieve the targets. Besides, current economic environment and competitive world demands refined management tools to achieve profit, growth and survival of the business. Therefore, the necessity of rational MBO becomes vital part towards the success of an organisation. This paper details about the philosophical assumptions to develop the grounded theory in lieu of achieving objectives through RATIONAL MBO approach in Construction Contracting Organisations. The goals and objectives of the Construction Contracting Organisations can be achieved efficiently by adopting this RATIONAL MBO approach, as those are based on realistic, logical and balanced assumptions.

Keywords: growth, leadership, management by objectives, Management By Objectives (MBO), profit, rational

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Authors: Vahid Anari, Mina Bakhshi

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Visual search and identification of immunohistochemically stained tissue of meningioma was performed manually in pathologic laboratories to detect and diagnose the cancers type of meningioma. This task is very tedious and time-consuming. Moreover, because of cell's complex nature, it still remains a challenging task to segment cells from its background and analyze them automatically. In this paper, we develop and test a computerized scheme that can automatically identify cells in microscopic images of meningioma and classify them into positive (proliferative) and negative (normal) cells. Dataset including 150 images are used to test the scheme. The scheme uses Fuzzy C-means algorithm as a color clustering method based on perceptually uniform hue, saturation, value (HSV) color space. Since the cells are distinguishable by the human eye, the accuracy and stability of the algorithm are quantitatively compared through application to a wide variety of real images.

Keywords: positive cell, color segmentation, HSV color space, immunohistochemistry, meningioma, thresholding, fuzzy c-means

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Authors: A. Biran, P. Sobhe Bidari, K. Raahemifar

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Diabetic Retinopathy (DR) is an eye disease that leads to blindness. The earliest signs of DR are the appearance of red and yellow lesions on the retina called hemorrhages and exudates. Early diagnosis of DR prevents from blindness; hence, many automated algorithms have been proposed to extract hemorrhages and exudates. In this paper, an automated algorithm is presented to extract hemorrhages and exudates separately from retinal fundus images using different image processing techniques including Circular Hough Transform (CHT), Contrast Limited Adaptive Histogram Equalization (CLAHE), Gabor filter and thresholding. Since Optic Disc is the same color as the exudates, it is first localized and detected. The presented method has been tested on fundus images from Structured Analysis of the Retina (STARE) and Digital Retinal Images for Vessel Extraction (DRIVE) databases by using MATLAB codes. The results show that this method is perfectly capable of detecting hard exudates and the highly probable soft exudates. It is also capable of detecting the hemorrhages and distinguishing them from blood vessels.

Keywords: diabetic retinopathy, fundus, CHT, exudates, hemorrhages

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Authors: Jie Ji, Jing Xu, Yuehong Zhuang, Xiangqing Kang, Ying Qian, Ping Zhou, Di Xue

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Background: In 2014, there were 28,341 health professionals in Pudong new area of Shanghai and the number per 1000 population was 5.199, 55.55% higher than that in 2006. But it was always less than the average number of health professionals per 1000 population in Shanghai from 2006 to 2014. Therefore, allocation planning for the health professionals in Pudong new area has become a high priority task in order to meet the future demands of health care. In this study, we constructed an objective-based system dynamics model to forecast the number of health professionals in Pudong new area of Shanghai in 2020. Methods: We collected the data from health statistics reports and previous survey of human resources in Pudong new area of Shanghai. Nine experts, who were from health administrative departments, public hospitals and community health service centers, were consulted to estimate the current and future status of nine variables used in the system dynamics model. Based on the objective of the number of health professionals per 1000 population (8.0) in Shanghai for 2020, the system dynamics model for health professionals in Pudong new area of Shanghai was constructed to forecast the number of health professionals needed in Pudong new area in 2020. Results: The system dynamics model for health professionals in Pudong new area of Shanghai was constructed. The model forecasted that there will be 37,330 health professionals (6.433 per 1000 population) in 2020. If the success rate of health professional recruitment changed from 20% to 70%, the number of health professionals per 1000 population would be changed from 5.269 to 6.919. If this rate changed from 20% to 70% and the success rate of building new beds changed from 5% to 30% at the same time, the number of health professionals per 1000 population would be changed from 5.269 to 6.923. Conclusions: The system dynamics model could be used to simulate and forecast the health professionals. But, if there were no significant changes in health policies and management system, the number of health professionals per 1000 population would not reach the objectives in Pudong new area in 2020.

Keywords: allocation planning, forecast, health professional, system dynamics

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Authors: P. S. Jagadeesh Kumar, Tracy Lin Huan, S. Meenakshi Sundaram

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Alzheimer’s disease is one of the prevalent kind of ailment, expected for impudent reconciliation or an effectual therapy is to be accredited hitherto. Probable detonation of patients in the upcoming years, and consequently an enormous deal of apprehension in early discovery of the disorder, this will conceivably chaperon to enhanced healing outcomes. Complex impetuosity of the brain is an observant symbolic of the disease and a unique recognition of genetic sign of the disease. Machine learning alongside deep learning and decision tree reinforces the aptitude to absorb characteristics from multi-dimensional data’s and thus simplifies automatic classification of Alzheimer’s disease. Susceptible testing was prophesied and realized in training the prospect of Alzheimer’s disease classification built on machine learning advances. It was shrewd that the decision trees trained with deep neural network fashioned the excellent results parallel to related pattern classification.

Keywords: Alzheimer's diagnosis, decision trees, deep neural network, machine learning, pattern classification

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Authors: Parker Townes, Aisouda Savadlou, Shoshana Weiss, Marina Jarenova, Suzzane Ferris, Dan Devoe, Russel Schachar, Scott Patten, Tomas Lange, Marlena Colasanto, Holly McGinn, Paul Arnold

Abstract:

Some research suggests obsessive-compulsive disorder (OCD) is associated with impaired executive functioning: higher-level mental processes involved in carrying out tasks and solving problems. Relevant literature was identified systematically through online databases. Meta-analyses were conducted for task performance metrics reported by at least two articles. Results were synthesized by the executive functioning domain measured through each performance metric. Heterogeneous literature was identified, typically involving few studies using consistent measures. From 29 included studies, analyses were conducted on 33 performance metrics from 12 tasks. Results suggest moderate associations of working memory (two out of five tasks presented significant findings), planning (one out of two tasks presented significant findings), and visuospatial abilities (one out of two tasks presented significant findings) with OCD in youth. There was inadequate literature or contradictory findings for other executive functioning domains. These findings suggest working memory, planning, and visuospatial abilities are impaired in pediatric OCD, with mixed results. More work is needed to identify the effect of age and sex on these results. Acknowledgment: This work was supported by the Alberta Innovates Translational Health Chair in Child and Youth Mental Health. The funders had no role in the design, conducting, writing, or decision to submit this article for publication.

Keywords: obsessive-compulsive disorder, neurocognition, executive functioning, adolescents, children

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Authors: Navid Mohammadzadeh, Huy Truong-Ba, Michael Cholette

Abstract:

The solar tower (ST) plant is a promising technology to exploit large-scale solar irradiation. With thermal energy storage, ST plant has the potential to shift generation to high electricity price periods. However, the size of storage limits the dispatchability of the plant, particularly when it should compete with uncertainty in forecasts of solar irradiation and electricity prices. The purpose of this study is to explore the size of storage when Rolling Horizon Control (RHC) is employed for dispatch scheduling. To this end, RHC is benchmarked against perfect knowledge (PK) forecast and two day-ahead dispatching policies. With optimisation of dispatch planning using PK policy, the optimal achievable profit for a specific size of the storage is determined. A sensitivity analysis using Monte-Carlo simulation is conducted, and the size of storage for RHC and day-ahead policies is determined with the objective of reaching the profit obtained from the PK policy. A case study is conducted for a hypothetical ST plant with thermal storage located in South Australia and intends to dispatch under two market scenarios: 1) fixed price and 2) wholesale spot price. The impact of each individual source of uncertainty on storage size is examined for January and August. The exploration of results shows that dispatching with RH controller reaches optimal achievable profit with ~15% smaller storage compared to that in day-ahead policies. The results of this study may be applied to the CSP plant design procedure.

Keywords: solar tower plant, spot market, thermal storage system, optimized dispatch planning, sensitivity analysis, Monte Carlo simulation

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Authors: Selena Ferrian, Erin Mccaffrey, Toshie Saito, Aiqin Cao, Noah Greenwald, Mark Robert Nicolls, Trevor Bruce, Roham T. Zamanian, Patricia Del Rosario, Marlene Rabinovitch, Michael Angelo

Abstract:

Recent experimental and clinical observations are advancing immunotherapies to clinical trials in pulmonary arterial hypertension (PAH). However, comprehensive mapping of the immune landscape in pulmonary arteries (PAs) is necessary to understand how immune cell subsets interact to induce pulmonary vascular pathology. We used multiplexed ion beam imaging by time-of-flight (MIBI-TOF) to interrogate the immune landscape in PAs from idiopathic (IPAH) and hereditary (HPAH) PAH patients. Massive immune infiltration in I/HPAH was observed with intramural infiltration linked to PA occlusive changes. The spatial context of CD11c+DCs expressing SAMHD1, TIM-3 and IDO-1 within immune-enriched microenvironments and neutrophils were associated with greater immune activation in HPAH. Furthermore, CD11c-DC3s (mo-DC-like cells) within a smooth muscle cell (SMC) enriched microenvironment were linked to vessel score, proliferating SMCs, and inflamed endothelial cells. Experimental data in cultured cells reinforced a causal relationship between neutrophils and mo-DCs in mediating pulmonary arterial SMC proliferation. These findings merit consideration in developing effective immunotherapies for PAH.

Keywords: pulmonary arterial hypertension, vascular remodeling, indoleamine 2-3-dioxygenase 1 (IDO-1), neutrophils, monocyte-derived dendritic cells, BMPR2 mutation, interferon gamma (IFN-γ)

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Authors: Mahdiyeh Zafaranchi, Ethan S. Cantor, William T. Riddell, Jess W. Everett

Abstract:

The New Jersey Department of Military and Veteran’s Affairs (NJ DMAVA) operates over 50 facilities throughout the state of New Jersey, U.S. NJDMAVA is under a mandate to move toward decarbonization, which will eventually include eliminating the use of natural gas and other fossil fuels for heating. At the same time, the organization requires increased resiliency regarding electric grid disruption. These competing goals necessitate adopting the use of on-site renewables such as photovoltaic and geothermal power, as well as implementing power control strategies through microgrids. Planning for these changes requires a detailed understanding of current and future electricity use on yearly, monthly, and shorter time scales, as well as a breakdown of consumption by heating, ventilation, and air conditioning (HVAC) equipment. This paper discusses case studies of two buildings that were simulated using the QUick Energy Simulation Tool (eQUEST). Both buildings use electricity from the grid and photovoltaics. One building also uses natural gas. While electricity use data are available in hourly intervals and natural gas data are available in monthly intervals, the simulations were developed using monthly and yearly totals. This approach was chosen to reflect the information available for most NJ DMAVA facilities. Once completed, simulation results are compared to metrics recommended by several organizations to validate energy use simulations. In addition to yearly and monthly totals, the simulated peak demands are compared to actual monthly peak demand values. The simulations resulted in monthly peak demand values that were within 30% of the measured values. These benchmarks will help to assess future energy planning efforts for NJ DMAVA.

Keywords: building energy modeling, eQUEST, peak demand, smart meters

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Authors: Kristen Erekson, Sarah Spendlove Caswell

Abstract:

Nurse educators have the challenge of training future nurses that will provide compassionate care to an increasingly diverse population of patients in a culturally sensitive way. One approach to this challenge is an immersive public and global health experience as part of the nursing program curriculum. Undergraduate nursing students at our institution are required to participate in a Public and Global Health course. They participate in a didactic preparatory course followed by a 3-to-4-week program in one of the following locations: The Czech Republic, Ecuador, Finland/Poland, Ghana, India, Spain, Taiwan, Tonga, an Honor Flight to Washington D.C. with Veterans, or in local (Utah) communities working with marginalized populations (including incarcerated individuals, refugees, etc.). The students are required to complete 84 clinical hours and 84 culture hours (which involve exposure to local history, art, architecture, customs, etc.). As Faculty, we feel strongly that these public and global health experiences help cultivate cultural awareness in our students and prepare nurses who are better prepared to serve a diverse population of patients throughout their careers. This presentation will highlight our experiences and provide ideas for other nurse educators who have an interest in developing similar programs in their schools but do not know where to start. Suggestions about how to start building relationships that can lead to these opportunities, along with logistics for continuing the programs, will be highlighted.

Keywords: global health nursing, nursing education, clinical education, public health nursing

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