559 research outputs found
Effect of whole language instruction in reading comprehension scores of first grade students
The purpose of this study was to determine whether any significant difference in the reading comprehension scores of first grade students utilizing a whole language method of instruction as opposed to phonics-based method of instruction existed. An experimental and control group of first grade students, with 20 children in each group, were administered the Silver Burdett Ginn Reading Comprehension test. Both groups were pre-tested to ascertain their level of reading comprehension before a treatment was administered. Next, the experimental group received the whole language method of reading instruction. Through repeated readings, students were exposed to reading and phonics at the same time. Beginning with familiar texts, the teacher drew attention to the concepts of print, specific words, letter/sound patterns (phonics), and reading strategies. Reading skills and strategies were taught and also assessed directly. This method employed the use of meaningful stories, poems, and opportunities to engage in varied activities (reading, reciting, writing, performing) to enhance the reading experience. One of its goals was making reading more enjoyable, thus increasing the student\u27s desire to read as opposed to the rote memorization procedures of phonics-based methods. At the end of the study, the experimental and control groups were posttested to determine whether one group scored significantly higher on Silver Burdett Ginn Reading Comprehension test. It was hypothesized the first grade students receiving reading instruction through the whole language method would score significantly higher than the first grade students receiving reading instruction through the phonics-based method. The researcher concluded there was no significant difference in reading comprehension test scores between the experimental and control groups. Under these circumstances, the conclusions drawn support the need for more research in this area
Gas Dynamics in the Barred Seyfert Galaxy NGC4151 - II. High Resolution HI Study
We present sensitive, high angular resolution (6" x 5") 21-cm observations of
the neutral hydrogen in the nearby barred Seyfert galaxy, NGC4151. These HI
observations, obtained using the VLA in B-configuration, are the highest
resolution to date of this galaxy, and reveal hitherto unprecedented detail in
the distribution and kinematics of the HI on sub-kiloparsec scales. A complete
analysis and discussion of the HI data are presented and the global properties
of the galaxy are related to the bar dynamics presented in Paper I.Comment: 13 pages including 9 figures and 3 tables; accepted for publication
in MNRA
The effect of caffeine mouth rinse on self-paced cycling performance
The aim of the study was to determine whether caffeine mouth rinse would improve 30 min self-paced cycling trial. Twelve healthy active males (age 20.5±0.7 years, mass 87.4±18.3 kg) volunteered for the study. They attended the laboratory on 3 separate occasions performing a 30 min self-paced cycling trial. On one occasion water was given as a mouth rinse for 5 s (PLA), on another occasion a 6.4% maltodextrin (CHO) solution was given for 5 s and finally a caffeine solution (containing 32 mg of caffeine dissolved in 125 ml water; CAF) was given for 5 s. Distance cycled, heart rate, ratings of perceived exertion, cadence, speed and power output were recorded throughout all trials. Distance cycled during the CAF mouth rinse trial (16.2±2.8 km) was significantly greater compared to PLA trial (14.9±2.6 km). There was no difference between CHO and CAF trials (P=0.89). Cadence, power and velocity were significantly greater during the CAF trial compared to both PLA and CHO (P0.05). Caffeine mouth rinse improves 30 min cycling performance by allowing the participant to increase cadence, power and velocity without a concurrent increase in perceived exertion and heart rate
Statistical analysis driven optimized deep learning system for intrusion detection
Attackers have developed ever more sophisticated and intelligent ways to hack
information and communication technology systems. The extent of damage an
individual hacker can carry out upon infiltrating a system is well understood.
A potentially catastrophic scenario can be envisaged where a nation-state
intercepting encrypted financial data gets hacked. Thus, intelligent
cybersecurity systems have become inevitably important for improved protection
against malicious threats. However, as malware attacks continue to dramatically
increase in volume and complexity, it has become ever more challenging for
traditional analytic tools to detect and mitigate threat. Furthermore, a huge
amount of data produced by large networks has made the recognition task even
more complicated and challenging. In this work, we propose an innovative
statistical analysis driven optimized deep learning system for intrusion
detection. The proposed intrusion detection system (IDS) extracts optimized and
more correlated features using big data visualization and statistical analysis
methods (human-in-the-loop), followed by a deep autoencoder for potential
threat detection. Specifically, a pre-processing module eliminates the outliers
and converts categorical variables into one-hot-encoded vectors. The feature
extraction module discard features with null values and selects the most
significant features as input to the deep autoencoder model (trained in a
greedy-wise manner). The NSL-KDD dataset from the Canadian Institute for
Cybersecurity is used as a benchmark to evaluate the feasibility and
effectiveness of the proposed architecture. Simulation results demonstrate the
potential of our proposed system and its outperformance as compared to existing
state-of-the-art methods and recently published novel approaches. Ongoing work
includes further optimization and real-time evaluation of our proposed IDS.Comment: To appear in the 9th International Conference on Brain Inspired
Cognitive Systems (BICS 2018
Dinosaur tracks in Triassic Molteno sediments: the earliest evidence of dinosaurs in South Africa?
A fossil tracksite containing well-preserved tridactyl footprints of bipedal theropod dinosaurs is reported from fluvial overbank deposits of Molteno age (Stormberg Group: Triassic) in the northeastern Cape Province, South Africa. They occur stratigraphically below the mudrocks of the Elliot Formation, in which dinosaur remains are comparatively common, and are taken to represent the earliest evidence for dinosaurs in South Africa. They also represent the earliest unequivocal evidence of tetrapods in Molteno deposits.Foundation for Research Development; Trustees of the Port Elizabeth Museu
The Open Access Advantage Revisited
This paper is a revision of one that appeared in 2008, incorporating the many developments and changes that have happened since then.published_or_final_versio
Coping with emotional labour in tennis coaching
A tennis coach works in a social environment, employed in a service
based economy with the outcome of client-customer interactions
significantly impacting on the consumer experience. Research
conducted outside of sport has shown that positive affective
displays during interactions, which in a tennis situation may
include providing support through displays of warmth, empathy,
positivity and compassion as the client attempts to master a
new technique, have shown positive associations with customer
satisfaction. Hochschild (1983) coined the term ‘emotional labour’
to describe the process of, and demands resulting from adjusting
one’s demeanour, language and tone during social encounters
in a planned and strategic manner in order to facilitate a positive
outcome. Hochschild proposed that individuals in jobs which
require a high degree of face-to-face interaction with the public are
particularly at risk of experiencing potentially deleterious effects
that result from dealing with emotional labour demands on a daily
basis. It would appear that tennis coaches work in environments
that make them susceptible to experiencing emotional labour and
as such the intention of this article is to first introduce the concept
and then to provide suggestions for how a coach may cope with
these demands
A Case Study on the Advantages of 3D Walkthroughs over Photo Stitching Techniques
Virtual tours and interactive walkthroughs enable a more in-depth platform for communicating information. Many current techniques employ the use of Photo Stitching to accomplish this. However, over the last decade advancements in computing power and the accessibility of game engines, meant that developing rich 3D content for virtual tours is more possible than ever before. As such, the purpose of this paper is to present a study into the advantages of developing an interactive 3D virtual tour of student facilities, using the Unreal Development 4 Game Engine, for educational establishments. The project aims to demonstrate a comparison between the use of Photo Stitching and 3D Modelled interactive walkthrough for developing rich visual environments. The research reveals that the approach in this paper can improve educational facilities prominence within universities, and contains many advantages over Photo Stitching techniques
Rail Internet of Things: An Architectural Platform and Assured Requirements Model
Given the plethora of individual preferences and requirements of public transport passengers for travel, seating, catering, etc., it becomes very challenging to tailor generic services to individuals’ requirements using the existing service platforms. As tens of thousands of sensors have been already deployed along roadsides and rail tracks, and on buses and trains in many countries, it is expected that the introduction of IP networking will revolutionise the functionality of public transport in general and rail services in particular. In this paper, we propose a new communication paradigm to improve rail services and address the requirement of rail service users: the Rail Internet of Things (RIoT). To the best of our knowledge, it is the first work to define the RIoT and design an architectural platform that includes its components and the data communication channels. Moreover, we develop an assured requirements model using the situation calculus modelling to represent the fundamental requirements for adjustable, decentralised feedback control mechanisms necessary for the RIoT-ready software systems. The developed formal model is applied to demonstrate the design of passenger assistance software that interacts with the RIoT ecosystem and provides passengers with real-time information that is tailored to their requirements with runtime adaptability.
Keywords—Assistance; Assured model; Inclusive; IoT; Rail
Internet of Things (RIoT); Situation Calculu
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