Abstract: This study examines the ways in which cancer patient narratives are portrayed and framed on the websites of three leading U.S. cancer care centers – The University of Texas MD Anderson Cancer Center in Houston, Memorial Sloan Kettering Cancer Center in New York, and Seattle Cancer Care Alliance. Thirty patient stories, 10 from each cancer center website blog, were analyzed using qualitative and quantitative textual analysis of unstructured data, documenting common themes and other elements of story structure and content. Patient narratives were coded using grounded theory as the basis for conducting emergent qualitative research. As part of a systematic, inductive approach to collecting and analyzing data, recurrent and unique themes were examined and compared in terms of positive and negative framing, patient agency, and institutional praise. All three of these cancer care centers are teaching hospitals, with university affiliations, that emphasize an evidence-based scientific approach to treatment that utilizes the latest research and cutting-edge techniques and technology. The featured cancer stories suggest positive outcomes based on anecdotal narratives as opposed to the science-based treatment models employed by the cancer centers. An analysis of 30 sample stories found skewed representation of the “cancer experience” that emphasizes positive outcomes while minimizing or excluding more negative realities of cancer diagnosis and treatment. The stories also deemphasize patient agency, instead focusing on deference and gratitude toward the cancer care centers, which are cast in the role of savior.
Abstract: In this paper, we present a Platform-as-a-Service (PaaS) model for controlling the privacy enforcement mechanisms applied on user data when stored and processed in Cloud data centers. The proposed architecture consists of establishing user configurable ‘sticky’ policies on the Graphical User Interface (GUI) data-bound components during the application development phase to specify the details of privacy enforcement on the contents of these components. Various privacy classification classes on the data components are formally defined to give the user full control on the degree and scope of privacy enforcement including the type of execution containers to process the data in the Cloud. This not only enhances the privacy-awareness of the developed Cloud services, but also results in major savings in performance and energy efficiency due to the fact that the privacy mechanisms are solely applied on sensitive data units and not on all the user content. The proposed design is implemented in a real PaaS cloud computing environment on the Microsoft Azure platform.
Abstract: Shenzhen is a modern city of China's reform and opening-up policy, the development of urban morphology has been established on the administration of the Chinese government. This city`s planning paradigm is primarily affected by the spatial structure and human behavior. The subjective urban agglomeration center is divided into several groups and centers. In comparisons of this effect, the city development law has better to be neglected. With the continuous development of the internet, extensive data technology has been introduced in China. Data mining and data analysis has become important tools in municipal research. Data mining has been utilized to improve data cleaning such as receiving business data, traffic data and population data. Prior to data mining, government data were collected by traditional means, then were analyzed using city-relationship research, delaying the timeliness of urban development, especially for the contemporary city. Data update speed is very fast and based on the Internet. The city's point of interest (POI) in the excavation serves as data source affecting the city design, while satellite remote sensing is used as a reference object, city analysis is conducted in both directions, the administrative paradigm of government is broken and urban research is restored. Therefore, the use of data mining in urban analysis is very important. The satellite remote sensing data of the Shenzhen city in July 2018 were measured by the satellite Modis sensor and can be utilized to perform land surface temperature inversion, and analyze city heat island distribution of Shenzhen. This article acquired and classified the data from Shenzhen by using Data crawler technology. Data of Shenzhen heat island and interest points were simulated and analyzed in the GIS platform to discover the main features of functional equivalent distribution influence. Shenzhen is located in the east-west area of China. The city’s main streets are also determined according to the direction of city development. Therefore, it is determined that the functional area of the city is also distributed in the east-west direction. The urban heat island can express the heat map according to the functional urban area. Regional POI has correspondence. The research result clearly explains that the distribution of the urban heat island and the distribution of urban POIs are one-to-one correspondence. Urban heat island is primarily influenced by the properties of the underlying surface, avoiding the impact of urban climate. Using urban POIs as analysis object, the distribution of municipal POIs and population aggregation are closely connected, so that the distribution of the population corresponded with the distribution of the urban heat island.
Abstract: Pet population in India is increasing phenomenally owing to the changes in urban lifestyle with increasing number of single professionals, single parents, delayed parenthood etc. The animal companionship as a means of reducing stress levels, deriving emotional support, and unconditional love provided by dogs are a few reasons attributed for increasing pet ownership. The consequence is the booming of the pet care products and dog care centers catering to the different requirements of rearing the pets. Dog care centers quite popular in tier 1 metros of India cater to the requirement of the dog owners providing space for the dogs in absence of the owner. However, it is often reported that the absence of the owner leads to destructive and exploratory behavior issues; the main being the anxiety disorders. In the above context, it becomes imperative for a designer to design dog boarding centers that help in reducing the separation anxiety in dogs keeping in mind the different interior design parameters. An exploratory research with focus group discussion is employed involving a group of dog owners, behaviorists, proprietors of day care as well as boarding centers, and veterinarians to understand their perception on the significance of different interior parameters of color, texture, ventilation, aroma therapy and acoustics as a means of reducing the stress levels in dogs sent to the boarding centers. The data collected is organized as thematic networks thus enabling the listing of the interior design parameters that needs to be considered in designing dog boarding centers.
Abstract: Clothing recycling bin is a traditional way to collect textile waste in many areas. In the clothing recycling business, the transportation cost normally takes over 50% of total costs. This case gives a good way to reduce transportation cost by reverse logistics system. In this reverse logistics system, there are offline strategic alliance partners, such as transport firms, convenience stores, laundries, and post office which are integrated onto the mobile APP. Offline strategic alliance partners provide the service of textile waste collection, and transportation by their vacant vehicles return journey from convenience stores, laundries and post offices to sorting centers. The results of the case study provide the strategic alliance with a valuable and light - asset business model by using the logistics of offline memberships. The company in this case just focuses on textile waste sorting, reuse, recycling etc. The research method of this paper is a case study of a clothing recycling company in Chengdu by field research and interview; the analysis is based on the theory of the reverse logistics system.
Abstract: Cloud computing can be defined as one of the prominent technologies that lets a user change, configure and access the services online. it can be said that this is a prototype of computing that helps in saving cost and time of a user practically the use of cloud computing can be found in various fields like education, health, banking etc. Cloud computing is an internet dependent technology thus it is the major responsibility of Cloud Service Providers(CSPs) to care of data stored by user at data centers. Scheduling in cloud computing environment plays a vital role as to achieve maximum utilization and user satisfaction cloud providers need to schedule resources effectively. Job scheduling for cloud computing is analyzed in the following work. To complete, recreate the task calculation, and conveyed scheduling methods CloudSim3.0.3 is utilized. This research work discusses the job scheduling for circulated processing condition also by exploring on this issue we find it works with minimum time and less cost. In this work two load balancing techniques have been employed: ‘Throttled stack adjustment policy’ and ‘Active VM load balancing policy’ with two brokerage services ‘Advanced Response Time’ and ‘Reconfigure Dynamically’ to evaluate the VM_Cost, DC_Cost, Response Time, and Data Processing Time. The proposed techniques are compared with Round Robin scheduling policy.
Abstract: Data mining technique used in the field of clustering is a subject of active research and assists in biological pattern recognition and extraction of new knowledge from raw data. Clustering means the act of partitioning an unlabeled dataset into groups of similar objects. Each group, called a cluster, consists of objects that are similar between themselves and dissimilar to objects of other groups. Several clustering methods are based on partitional clustering. This category attempts to directly decompose the dataset into a set of disjoint clusters leading to an integer number of clusters that optimizes a given criterion function. The criterion function may emphasize a local or a global structure of the data, and its optimization is an iterative relocation procedure. The K-Means algorithm is one of the most widely used partitional clustering techniques. Since K-Means is extremely sensitive to the initial choice of centers and a poor choice of centers may lead to a local optimum that is quite inferior to the global optimum, we propose a strategy to initiate K-Means centers. The improved K-Means algorithm is compared with the original K-Means, and the results prove how the efficiency has been significantly improved.
Abstract: The Numerical weather prediction (NWP) models are
considered powerful tools for guiding quantitative rainfall prediction.
A couple of NWP models exist and are used at many operational
weather prediction centers. This study considers two models namely
the Consortium for Small–scale Modeling (COSMO) model and the
Weather Research and Forecasting (WRF) model. It compares the
models’ ability to predict rainfall over Uganda for the period 21st
April 2013 to 10th May 2013 using the root mean square (RMSE)
and the mean error (ME). In comparing the performance of the
models, this study assesses their ability to predict light rainfall events
and extreme rainfall events. All the experiments used the default
parameterization configurations and with same horizontal resolution
(7 Km). The results show that COSMO model had a tendency of
largely predicting no rain which explained its under–prediction. The
COSMO model (RMSE: 14.16; ME: -5.91) presented a significantly
(p = 0.014) higher magnitude of error compared to the WRF
model (RMSE: 11.86; ME: -1.09). However the COSMO model
(RMSE: 3.85; ME: 1.39) performed significantly (p = 0.003) better
than the WRF model (RMSE: 8.14; ME: 5.30) in simulating light
rainfall events. All the models under–predicted extreme rainfall events
with the COSMO model (RMSE: 43.63; ME: -39.58) presenting
significantly higher error magnitudes than the WRF model (RMSE:
35.14; ME: -26.95). This study recommends additional diagnosis of
the models’ treatment of deep convection over the tropics.
Abstract: Traveling salesman problem (TSP) is a combinatorial integer optimization problem that asks "What is the optimal route for a vehicle to traverse in order to deliver requests to a given set of customers?”. It is widely used by the package carrier companies’ distribution centers. The main goal of applying the TSP in courier organizations is to minimize the time that it takes for the courier in each trip to deliver or pick up the shipments during a day. In this article, an optimization model is constructed to create a new TSP variant to optimize the routing in a courier organization with a consideration of congestion in Amman, the capital of Jordan. Real data were collected by different methods and analyzed. Then, concert technology - CPLEX was used to solve the proposed model for some random generated data instances and for the real collected data. At the end, results have shown a great improvement in time compared with the current trip times, and an economic study was conducted afterwards to figure out the impact of using such models.
Abstract: An essential component of a finite volume method (FVM) is the advection scheme that estimates values on the cell faces based on the calculated values on the nodes or cell centers. The most widely used advection schemes are upwind schemes. These schemes have been developed in FVM on different kinds of structured and unstructured grids. In this research, the physical influence scheme (PIS) is developed for a cell-centered FVM that uses an implicit coupled solver. Results are compared with the exponential differencing scheme (EDS) and the skew upwind differencing scheme (SUDS). Accuracy of these schemes is evaluated for a lid-driven cavity flow at Re = 1000, 3200, and 5000 and a backward-facing step flow at Re = 800. Simulations show considerable differences between the results of EDS scheme with benchmarks, especially for the lid-driven cavity flow at high Reynolds numbers. These differences occur due to false diffusion. Comparing SUDS and PIS schemes shows relatively close results for the backward-facing step flow and different results in lid-driven cavity flow. The poor results of SUDS in the lid-driven cavity flow can be related to its lack of sensitivity to the pressure difference between cell face and upwind points, which is critical for the prediction of such vortex dominant flows.
Abstract: The purpose of this study is to investigate Alahsa Governorate status and its vulnerability to generate urban heat islands. Alahsa Governorate is a famous oasis in the Arabic Peninsula including several oil centers. Extensive literature review was done to collect previous relative data on the urban heat island of Alahsa Governorate. Data used for the purpose of this research were collected from authorized bodies who control weather station networks over Alahsa Governorate, Eastern Province, Saudi Arabia. Although, the number of weather station networks within the region is very limited and the analysis using GIS software and its techniques is difficult and limited, the data analyzed confirm an increase in temperature for more than 2 °C from 2004 to 2014. Such increase is considerable whenever human health and comfort are the concern. The increase of temperature within one decade confirms the availability of urban heat islands. The study concludes that, Alahsa Governorate is vulnerable to create urban heat islands and more attention should be drawn to strategic planning of the governorate that is developing with a high pace and considerable increasing levels of urbanization.
Abstract: The traditional k-means algorithm has been widely used as a simple and efficient clustering method. However, the algorithm often converges to local minima for the reason that it is sensitive to the initial cluster centers. In this paper, an algorithm for selecting initial cluster centers on the basis of minimum spanning tree (MST) is presented. The set of vertices in MST with same degree are regarded as a whole which is used to find the skeleton data points. Furthermore, a distance measure between the skeleton data points with consideration of degree and Euclidean distance is presented. Finally, MST-based initialization method for the k-means algorithm is presented, and the corresponding time complexity is analyzed as well. The presented algorithm is tested on five data sets from the UCI Machine Learning Repository. The experimental results illustrate the effectiveness of the presented algorithm compared to three existing initialization methods.
Abstract: This paper presents modern solutions of distributed generation in rural communities aiming at the improvement of energy and environmental security, as well as power supply reliability to important customers (e.g. health care, sensitive consumer required continuity). Distributed sources are mainly gas and biogas cogeneration units, as well as wind and photovoltaic sources. Some examples of their applications in a selected Silesian community are given.
Abstract: Lean philosophy has evolved over time and has been implemented both in manufacturing and services, more recently lean has been integrated in the companies of the health sector. Currently it is important to understand the successful way to implement this philosophy and try to identify barriers and enablers to the sustainability of lean healthcare. The main purpose of this research is to identify the barriers and enablers in the implementation of Lean Healthcare based on case studies of Colombian healthcare centers. In order to do so, we conducted semi-structured interviews based on a maturity model. The main results indicate that the success of Lean implementation depends on its adaptation to contextual factors. In addition, in the Colombian context were identified new factors such as organizational culture, management models, integration of the care and administrative departments and triple helix relationship.
Abstract: In a language the inventory of greetings is dynamic with frequent input and output, although this is hardly noticed by the speakers. In this register, there are a number of constant, conservative elements that survive different language models (among them, the classic formulae: bună ziua! (good afternoon!), bună seara! (good evening!), noapte bună! (good night!), la revedere! (goodbye!) and a number of items that fail to pass the test of time, according to language use at a time (ciao!, pa!, bai!). The source of innovation depends both of internal factors (contraction, conversion, combination of classic formulae of greetings), and of external ones (borrowings and calques). Their use imposes their frequencies at once, namely the elimination of the use of others. This paper presents a sociolinguistic approach of contemporary Romanian greetings, based on prosodic surveys in two research projects: AMPRom, and SoRoEs. Romanian language presents a rich inventory of questions (especially partial interrogatives questions/WH-Q) which are used as greetings, alone or, more commonly accompanying a proper greeting. The representative of the typical formulae is Ce mai faci? (How are you?), which, unlike its English counterpart How do you do?, has not become a stereotype, but retains an obvious emotional impact, while serving as a mark of sociolinguistic group. The analyzed corpus consists of structures containing greetings recorded in the main Romanian cultural (urban) centers. From the methodological point of view, the acoustic analysis of the recorded data is performed using software tools (GoldWave, Praat), identifying intonation patterns related to three sociolinguistics variables: age, sex and level of education. The intonation patterns of the analyzed statements are at the interface between partial questions and typical greetings.
Abstract: Logistics centers represent areas that all national and international logistics and activities related to logistics can be implemented by the various businesses. Logistics centers have a key importance in joining the transport stream and the transport system operations. Therefore, it is important where these centers are positioned to be effective and efficient and to show the expected performance of the centers. In this study, the location selection problem to position the logistics center is discussed. Alternative centers are evaluated according certain criteria. The most appropriate center is identified using the axiomatic design method.
Abstract: In this paper, monitoring and control of tap changer
mechanism of a transformer implementation in an Intelligent
Electronic Device (IED) is discussed. It has been a custom for
decades to provide a separate panel for on load tap changer control
for monitoring the tap position. However, this facility cannot either
record or transfer the information to remote control centers. As there
is a technology shift towards the smart grid protection and control
standards, the need for implementing remote control and monitoring
has necessitated the implementation of this feature in numerical
relays. This paper deals with the programming, settings and logic
implementation which is applicable to both IEC 61850 compatible
and non-compatible IEDs thereby eliminating the need for separate
tap changer control equipment. The monitoring mechanism has been
implemented in a 28MVA, 110 /6.9kV transformer with 16 tap
position with GE make T60 IED at Ultratech cement limited
Gulbarga, Karnataka and is in successful service.
Abstract: This paper proposes the application of the Smart
Security Concept in the East Mediterranean. Smart Security aims to
secure critical infrastructure, such as hydrocarbon platforms, against
asymmetrical threats. The concept is based on Anti Asymmetrical
Area Denial (A3D) which necessitates limiting freedom of action of
maritime terrorists and piracy by founding safe and secure maritime
areas through sea lines of communication using short range
capabilities.
Abstract: Contemporary city is a subject to rapid economic and
social changes. Therefore, it requires an active policy designed to
meet the diverse needs of their residents, build competitive position
and capacity to compete with other cities. Competitiveness of cities
depends largely on their resources but also to a large extent, on the
policies and performance of local authorities. Cooperation with social
sector also plays an important role, as it affects the use of resources
and builds an advantage over other cities.
The subject of this article is city's contemporary problems of
development with particular emphasis on central areas. This issue is a
starting point for reflection on the process of urban regeneration in
medium size cities in Poland, as well as cooperation between various
actors and their roles in the revitalization processes of Polish cities'
centers.
Abstract: Distributed Generation (DG) can help in reducing the
cost of electricity to the costumer, relieve network congestion and
provide environmentally friendly energy close to load centers. Its
capacity is also scalable and it provides voltage support at distribution
level. Hence, DG placement and penetration level is an important
problem for both the utility and DG owner. DG allocation and capacity
determination is a nonlinear optimization problem. The objective
function of this problem is the minimization of the total loss of the
distribution system. Also high levels of penetration of DG are a new
challenge for traditional electric power systems. This paper presents a
new methodology for the optimal placement of DG and penetration
level of DG in distribution system based on General Algebraic
Modeling System (GAMS) and Genetic Algorithm (GA).