Abstract: Introduction: Student nurses must develop skills in observation, communication and reflection as well as public health knowledge from their first year of training. This paper will explain a method developed for students to collect their own findings about public health in urban areas. These areas are both rich in the history of old public health that informs the content of many traditional public health walks, but are also locations where new public health concerns about chronic disease are concentrated. The learning method explained in this paper enables students to collect their own data and write original work as first year students. Examples of their findings will be given. Methodology: In small groups, health care students are instructed to walk in neighbourhoods near to the hospitals they will soon attend as apprentice nurses. On their walks, they wander slowly, engage in conversations, and enter places open to the public. As they drift, they observe with all five senses in the real three dimensional world to collect data for their reflective accounts of old and new public health. They are encouraged to stop for refreshments and taste, as well as look, hear, smell, and touch while on their walk. They reflect as a group and later develop an individual reflective account in which they write up their deep reflections about what they observed on their walk. In preparation for their walk, they are encouraged to look at studies of quality of Life and other neighbourhood statistics as well as undertaking a risk assessment for their walk. Findings: Reflecting on their walks, students apply theoretical concepts around social determinants of health and health inequalities to develop their understanding of communities in the neighbourhoods visited. They write about the treasured historical architecture made of stone, bronze and marble which have outlived those who built them; but also how the streets are used now. The students develop their observations into thematic analyses such as: what we drink as illustrated by the empty coke can tossed into a now disused drinking fountain; the shift in home-life balance illustrated by streets where families once lived over the shop which are now walked by commuters weaving around each other as they talk on their mobile phones; and security on the street, with CCTV cameras placed at regular intervals, signs warning trespasses and barbed wire; but little evidence of local people watching the street. Conclusion: In evaluations of their first year, students have reported the health walk as one of their best experiences. The innovative approach was commended by the UK governing body of nurse education and it received a quality award from the nurse education funding body. This approach to education allows students to develop skills in the real world and write original work.
Abstract: Cancer affects people globally with breast cancer being a leading killer. Breast cancer is due to the uncontrollable multiplication of cells resulting in a tumour or neoplasm. Tumours are called ‘benign’ when cancerous cells do not ravage other body tissues and ‘malignant’ if they do so. As mammography is an effective breast cancer detection tool at an early stage which is the most treatable stage it is the primary imaging modality for screening and diagnosis of this cancer type. This paper presents an automatic mammogram classification technique using wavelet and Gabor filter. Correlation feature selection is used to reduce the feature set and selected features are classified using different decision trees.
Abstract: Accurate software reliability prediction not only enables developers to improve the quality of software but also provides useful information to help them for planning valuable resources. This paper examines the performance of three well-known data mining techniques (CART, TreeNet and Random Forest) for predicting software reliability. We evaluate and compare the performance of proposed models with Cascade Correlation Neural Network (CCNN) using sixteen empirical databases from the Data and Analysis Center for Software. The goal of our study is to help project managers to concentrate their testing efforts to minimize the software failures in order to improve the reliability of the software systems. Two performance measures, Normalized Root Mean Squared Error (NRMSE) and Mean Absolute Errors (MAE), illustrate that CART model is accurate than the models predicted using Random Forest, TreeNet and CCNN in all datasets used in our study. Finally, we conclude that such methods can help in reliability prediction using real-life failure datasets.
Abstract: Polymers from renewable resources have attracted an increasing amount of attention over the last two decades, predominantly due to two major reasons: firstly environmental concerns, and secondly the realization that our petroleum resources are finite. Finding new uses for agricultural commodities is also an important area of research. Therefore, it is crucial to get new sources of natural materials that can be used in different applications. Ramon tree (Brosimum alicastrum) is a tropical plant that grows freely in Yucatan countryside. This paper focuses on the seeds recollection, processing and starch extraction and characterization in order to find out about its suitability as biomaterial. Results demonstrated that it has a high content of qualities to be used not only as comestible but also as an important component in polymeric blends.
Abstract: We assume an IoT-based smart-home environment where the on-off status of each of the electrical appliances including the room lights can be recognized in a real time by monitoring and analyzing the smart meter data. At any moment in such an environment, we can recognize what the household or the user is doing by referring to the status data of the appliances. In this paper, we focus on a smart-home service that is to activate a robot vacuum cleaner at right time by recognizing the user situation, which requires a situation-aware model that can distinguish the situations that allow vacuum cleaning (Yes) from those that do not (No). We learn as our candidate models a few classifiers such as naïve Bayes, decision tree, and logistic regression that can map the appliance-status data into Yes and No situations. Our training and test data are obtained from simulations of user behaviors, in which a sequence of user situations such as cooking, eating, dish washing, and so on is generated with the status of the relevant appliances changed in accordance with the situation changes. During the simulation, both the situation transition and the resulting appliance status are determined stochastically. To compare the performances of the aforementioned classifiers we obtain their learning curves for different types of users through simulations. The result of our empirical study reveals that naïve Bayes achieves a slightly better classification accuracy than the other compared classifiers.
Abstract: Texture is an important characteristic in real and
synthetic scenes. Texture analysis plays a critical role in inspecting
surfaces and provides important techniques in a variety of
applications. Although several descriptors have been presented to
extract texture features, the development of object recognition is still a
difficult task due to the complex aspects of texture. Recently, many
robust and scaling-invariant image features such as SIFT, SURF and
ORB have been successfully used in image retrieval and object
recognition. In this paper, we have tried to compare the performance
for texture classification using these feature descriptors with k-means
clustering. Different classifiers including K-NN, Naive Bayes, Back
Propagation Neural Network , Decision Tree and Kstar were applied in
three texture image sets － UIUCTex, KTH-TIPS and Brodatz,
respectively. Experimental results reveal SIFTS as the best average
accuracy rate holder in UIUCTex, KTH-TIPS and SURF is
advantaged in Brodatz texture set. BP neuro network works best in the
test set classification among all used classifiers.
Abstract: The effectiveness of microchannels in enhancing heat
transfer has been demonstrated in the semiconductor industry. In
order to tap the microscale heat transfer effects into macro
geometries, overcoming the cost and technological constraints,
microscale passages were created in macro geometries machined
using conventional fabrication methods. A cylindrical insert was
placed within a pipe, and geometrical profiles were created on the
outer surface of the insert to enhance heat transfer under steady-state
single-phase liquid flow conditions. However, while heat transfer
coefficient values of above 10 kW/m2·K were achieved, the heat
transfer enhancement was accompanied by undesirable pressure drop
increment. Therefore, this study aims to address the high pressure
drop issue using Constructal theory, a universal design law for both
animate and inanimate systems. Two designs based on Constructal theory were developed to study
the effectiveness of Constructal features in reducing the pressure drop
increment as compared to parallel channels, which are commonly
found in microchannel fabrication. The hydrodynamic and heat
transfer performance for the Tree insert and Constructal fin (Cfin)
insert were studied using experimental methods, and the underlying
mechanisms were substantiated by numerical results. In technical
terms, the objective is to achieve at least comparable increment in
both heat transfer coefficient and pressure drop, if not higher
increment in the former parameter. Results show that the Tree insert improved the heat transfer
performance by more than 16 percent at low flow rates, as compared
to the Tree-parallel insert. However, the heat transfer enhancement
reduced to less than 5 percent at high Reynolds numbers. On the
other hand, the pressure drop increment stayed almost constant at 20
percent. This suggests that the Tree insert has better heat transfer
performance in the low Reynolds number region. More importantly,
the Cfin insert displayed improved heat transfer performance along
with favourable hydrodynamic performance, as compared to Cfinparallel
insert, at all flow rates in this study. At 2 L/min, the
enhancement of heat transfer was more than 30 percent, with 20
percent pressure drop increment, as compared to Cfin-parallel insert.
Furthermore, comparable increment in both heat transfer coefficient
and pressure drop was observed at 8 L/min. In other words, the Cfin
insert successfully achieved the objective of this study. Analysis of the results suggests that bifurcation of flows is
effective in reducing the increment in pressure drop relative to heat
transfer enhancement. Optimising the geometries of the Constructal
fins is therefore the potential future study in achieving a bigger stride
in energy efficiency at much lower costs.
Abstract: Recent progress in the next generation of automobile
technology is geared towards incorporating information technology
into cars. Collectively called smart cars are bringing intelligence to
cars that provides comfort, convenience and safety. A branch of smart
cars is connected-car system. The key concept in connected-cars is the
sharing of driving information among cars through decentralized
manner enabling collective intelligence. This paper proposes a
foundation of the information model that is necessary to define the
driving information for smart-cars. Road conditions are modeled
through a unique data structure that unambiguously represent the time
variant traffics in the streets. Additionally, the modeled data structure
is exemplified in a navigational scenario and usage using UML.
Optimal driving route searching is also discussed using the proposed
data structure in a dynamically changing road conditions.
Abstract: Patient-specific models are instance-based learning
algorithms that take advantage of the particular features of the patient
case at hand to predict an outcome. We introduce two patient-specific
algorithms based on decision tree paradigm that use AUC as a
metric to select an attribute. We apply the patient specific algorithms
to predict outcomes in several datasets, including medical datasets.
Compared to the patient-specific decision path (PSDP) entropy-based
and CART methods, the AUC-based patient-specific decision path
models performed equivalently on area under the ROC curve (AUC).
Our results provide support for patient-specific methods being a
promising approach for making clinical predictions.
Abstract: Fractal based digital image compression is a specific
technique in the field of color image. The method is best suited for
irregular shape of image like snow bobs, clouds, flame of fire; tree
leaves images, depending on the fact that parts of an image often
resemble with other parts of the same image. This technique has
drawn much attention in recent years because of very high
compression ratio that can be achieved. Hybrid scheme incorporating
fractal compression and speedup techniques have achieved high
compression ratio compared to pure fractal compression. Fractal
image compression is a lossy compression method in which selfsimilarity
nature of an image is used. This technique provides high
compression ratio, less encoding time and fart decoding process. In
this paper, fractal compression with quad tree and DCT is proposed
to compress the color image. The proposed hybrid schemes require
four phases to compress the color image. First: the image is
segmented and Discrete Cosine Transform is applied to each block of
the segmented image. Second: the block values are scanned in a
zigzag manner to prevent zero co-efficient. Third: the resulting image
is partitioned as fractals by quadtree approach. Fourth: the image is
compressed using Run length encoding technique.
Abstract: The study assessed the effectiveness of Pawpaw
(Carica papaya) wood in reducing the concentrations of heavy
metals in wastewater acting as a bio-sorbent. The following heavy
metals were considered; Zinc, Cadmium, Lead, Copper, Iron,
Selenium, Nickel and Manganese. The physiochemical properties of
Carica papaya stem were studied. The experimental sample was
sourced from the trunk of a felled matured pawpaw tree. Wastewater
for experimental use was prepared by dissolving soil samples
collected from a dump site at Owerri, Imo state of Nigeria in water.
The concentration of each metal remaining in solution as residual
metal after bio-sorption was determined using Atomic absorption
Spectrometer. The effects of pH and initial heavy metal concentration
were studied in a batch reactor. The results of Spectrometer test
showed that there were different functional groups detected in the
Carica papaya stem biomass. There was increase in metal removal as
the pH increased for all the metals considered except for Nickel and
Manganese. Optimum bio-sorption occurred at pH 5.9 with 5g/100ml
solution of bio-sorbent. The results of the study showed that the
treated wastewater is fit for irrigation purpose based on Canada
wastewater quality guideline for the protection of Agricultural
standard. This approach thus provides a cost effective and
environmentally friendly option for treating wastewater.
Abstract: In wireless sensor network, sensor node transmits the
sensed data to the sink node in multi-hop communication
periodically. This high traffic induces congestion at the node which is
present one-hop distance to the sink node. The packet transmission
and reception rate of these nodes should be very high, when
compared to other sensor nodes in the network. Therefore, the energy
consumption of that node is very high and this effect is known as the
“funneling effect”. The tree based-data aggregation technique
(TBDA) is used to reduce the energy consumption of the node. The
throughput of the overall performance shows a considerable decrease
in the number of packet transmissions to the sink node. The proposed
scheme, TBDA, avoids the funneling effect and extends the lifetime
of the wireless sensor network. The average case time complexity for
inserting the node in the tree is O(n log n) and for the worst case time
complexity is O(n2).
Abstract: A sign pattern is a matrix whose entries belong to the set
{+,−, 0}. An n-by-n sign pattern A is said to allow an eventually
positive matrix if there exist some real matrices A with the same
sign pattern as A and a positive integer k0 such that Ak > 0 for all
k ≥ k0. It is well known that identifying and classifying the n-by-n
sign patterns that allow an eventually positive matrix are posed as two
open problems. In this article, the tree sign patterns of small order
that allow an eventually positive matrix are classified completely.
Abstract: The 1:1 cocrystal of 2-amino-4-chloro-6-
methylpyrimidine (2A4C6MP) with 4-methylbenzoic acid (4MBA)
(I) has been prepared by slow evaporation method in methanol,
which was crystallized in monoclinic C2/c space group, Z = 8, and a
= 28.431 (2) Å, b = 7.3098 (5) Å, c = 14.2622 (10) Å and β =
109.618 (3)°. The presence of unionized –COOH functional group in
cocrystal I was identified both by spectral methods (1H and 13C
NMR, FTIR) and X-ray diffraction structural analysis. The
2A4C6MP molecule interact with the carboxylic group of the
respective 4MBA molecule through N—H⋯O and O—H⋯N
hydrogen bonds, forming a cyclic hydrogen–bonded motif R2
2(8).
The crystal structure was stabilized by Npyrimidine—H⋯O=C and
C=O—H⋯Npyrimidine types hydrogen bonding interactions.
Theoretical investigations have been computed by HF and density
function (B3LYP) method with 6–311+G (d,p)basis set. The
vibrational frequencies together with 1H and 13C NMR chemical
shifts have been calculated on the fully optimized geometry of
cocrystal I. Theoretical calculations are in good agreement with the
experimental results. Solvent–free formation of this cocrystal I is
confirmed by powder X-ray diffraction analysis.
Abstract: As computing technology advances, smartphone
applications can assist student learning in a pervasive way. For
example, the idea of using mobile apps for the PA Common Trees,
Pests, Pathogens, in the field as a reference tool allows middle school
students to learn about trees and associated pests/pathogens without
bringing a textbook. While working on the development of three heterogeneous mobile
apps, we ran into numerous challenges. Both the traditional waterfall
model and the more modern agile methodologies failed in practice.
The waterfall model emphasizes the planning of the duration for each
phase. When the duration of each phase is not consistent with the
availability of developers, the waterfall model cannot be employed.
When applying Agile Methodologies, we cannot maintain the high
frequency of the iterative development review process, known as
‘sprints’. In this paper, we discuss the challenges and solutions. We
propose a hybrid model known as the Relay Race Methodology to
reflect the concept of racing and relaying during the process of
software development in practice. Based on the development project,
we observe that the modeling of the relay race transition between any
two phases is manifested naturally. Thus, we claim that the RRM
model can provide a de fecto rather than a de jure basis for the core
concept in the software development model. In this paper, the background of the project is introduced first.
Then, the challenges are pointed out followed by our solutions.
Finally, the experiences learned and the future works are presented.
Abstract: Dead wood and habitat tree such as fallen logs, snags,
stumps and cracks and loos bark etc. are regarded as an important
ecological component of forests on which many forest dwelling
species depend on presence of them within forest ecosystems.
Meanwhile its relation to management history in Caspian forest has
gone unreported. The aim of research was to compare the amounts of
dead wood and habitat trees in the forests with historically different
intensities of management, including: forests with the long term
implication of management (PS), the short term implication of
management (NS) which were compared with semi virgin forest
(GS). The number of 405 individual dead and habitat trees were
recorded and measured at 109 sampling locations. ANOVA revealed
volume of dead tree in the form and decay classes significantly differ
within sites and dead volume in the semi virgin forest significantly
higher than managed sites. Comparing the amount of dead and
habitat tree in three sites showed that, dead tree volume related with
management history and significantly differ in three study sites.
Meanwhile, frequency of habitat trees was significantly different
within sites. The highest amount of habitat trees including cavities,
cracks and loose bark and fork split trees was recorded in virgin site
and lowest recorded in the sites with the long term implication of
management. It can be concluded that forest management cause
reduction of the amount of dead and habitat tree specially in a large
size, thus managing this forest according to ecological sustainable
principles require a commitment to maintaining stand structure that
allow, continued generation of dead trees in a full range of size.
Abstract: Biomass treatment through densification is very suitable and helpful technology before its effective energy recovery. Densification process of biomass is significantly influenced by various technological and material variables, which are ultimately reflected on the final solid biofuels quality. The paper deals with the experimental research of the relationship between technological and material variables during densification of fast-growing trees, roundly fast-growing willows. The main goal of presented experimental research is to determine the relationship between compression pressure and raw material particle size from a final briquettes density point of view. Experimental research was realized by single-axis densification. The impact of particle size with interaction of compression pressure and stabilization time on the quality properties of briquettes was determined. These variables interaction affects the final solid biofuels (briquettes) quality. From briquettes production point of view and from densification machines constructions point of view is very important to know about mutual interaction of these variables on final briquettes quality. The experimental findings presented here are showing the importance of mentioned variables during the densification process.
Abstract: One of the major problems being faced by human society is that the global temperature is believed to be rising due to human activity that releases carbon IV Oxide (CO2) to the atmosphere. Carbon IV Oxide is the most important greenhouse gas influencing global warming and possible climate change. With climate change becoming alarming, reducing CO2 in our atmosphere has become a primary goal of international efforts. Forest lands are major sink and could absorb large quantities of carbon if the trees are judiciously managed. The study aims at estimating the carbon sequestration capacity of Pinus caribaea (pine) and Tectona grandis (Teak) under the prevailing environmental conditions and exploring tree growth variables that influences the carbon sequestration capacity in Omo Forest Reserve, Ogun State, Nigeria. Improving forest management by manipulating growth characteristics that influences carbon sequestration could be an adaptive strategy of forestry to climate change. Random sampling was used to select Temporary Sample Plots (TSPs) in the study area from where complete enumeration of growth variables was carried out within the plots. The data collected were subjected to descriptive and correlational analyses. The results showed that average carbon stored by Pine and Teak are 994.4±188.3 Kg and 1350.7±180.6 Kg respectively. The difference in carbon stored in the species is significant enough to consider choice of species relevant in climate change adaptation strategy. Tree growth variables influence the capacity of the tree to sequester carbon. Height, diameter, volume, wood density and age are positively correlated to carbon sequestration. These tree growth variables could be manipulated by the forest manager as an adaptive strategy for climate change while plantations of high wood density species could be relevant for management strategy to increase carbon storage.
Abstract: The Gezi Park protests of 2013 have significantly changed the Turkish agenda and its effects have been felt historically. The protests, which rapidly spread throughout the country, were triggered by the proposal to recreate the Ottoman Army Barracks to function as a shopping mall on Gezi Park located in Istanbul’s Taksim neighbourhood despite the oppositions of several NGOs and when trees were cut in the park for this purpose. Once the news that the construction vehicles entered the park on May 27 spread on social media, activists moved into the park to stop the demolition, against whom the police used disproportioned force. With this police intervention and the then prime-minister Tayyip Erdoğan's insistent statements about the construction plans, the protests turned into anti- government demonstrations, which then spread to the rest of the country, mainly in big cities like Ankara and Izmir. According to the Ministry of Internal Affairs’ June 23rd reports, 2.5 million people joined the demonstrations in 79 provinces, that is all of them, except for the provinces of Bayburt and Bingöl, while even more people shared their opinions via social networks. As a result of these events, 8 civilians and 2 security personnel lost their lives, namely police chief Mustafa Sarı, police officer Ahmet Küçükdağ, citizens Mehmet Ayvalıtaş, Abdullah Cömert, Ethem Sarısülük, Ali İsmail Korkmaz, Ahmet Atakan, Berkin Elvan, Burak Can Karamanoğlu, Mehmet İstif, and Elif Çermik, and 8163 more were injured. Besides being a turning point in Turkish history, the Gezi Park protests also had broad repercussions in both in Turkish and in global media, which focused on Turkey throughout the events. Our study conducts content analysis of three Turkish reporting newspapers with varying ideological standpoints, Hürriyet, Cumhuriyet ve Yeni Şafak, in order to reveal their basic approach to news casting in context of the Gezi Park protests. Headlines, news segments, and news content relating to the Gezi protests were treated and analysed for this purpose. The aim of this study is to understand the social effects of the Gezi Park protests through media samples with varying political attitudes towards news casting.
Abstract: This study was undertaken at four different sites
(north polluted, south polluted, south healthy and north healthy) in
Tehran, in order to examine whether there was a relationship between
publicly available air quality data and the public’s perception of air
quality and to suggest some guidelines for reducing air pollution. A
total of 200 people were accidentally filled out the research
questionnaires at mentioned sites and air quality data were obtained
simultaneously from the Air Quality Control Department. Data was
analyzed in Excel and SPSS software’s. Clean air and job security
were of great importance to people comparing to other pleasant
aspect of life. Also air pollution and serious diseases were the most
important of people concerns. Street monitors and news paper
services on air quality were little used by the public as a means of
obtaining information on air pollution. Using public transportation
and avoiding inevitable journeys are the most important ways for
reducing air pollution. The results reveal that the public’s perception
of air quality is not a reliable indicator of the actual levels of air
pollution.