Abstract: Surface Mount Technology (SMT) is widely used in the area of the electronic assembly in which the electronic components are mounted to the surface of the printed circuit board (PCB). Most of the defects in the SMT process are mainly related to the quality of solder paste printing. These defects lead to considerable manufacturing costs in the electronics assembly industry. Therefore, the solder paste inspection (SPI) machine for controlling and monitoring the amount of solder paste printing has become an important part of the production process. So far, the setting of the SPI threshold is based on statistical analysis and experts’ experiences to determine the appropriate threshold settings. Because the production data are not normal distribution and there are various variations in the production processes, defects related to solder paste printing still occur. In order to solve this problem, this paper proposes an online machine learning algorithm, called the automatic threshold adjustment (ATA) algorithm, and closed-loop architecture in the SMT process to determine the best threshold settings. Simulation experiments prove that our proposed threshold settings improve the accuracy from 99.85% to 100%.
Abstract: Introduction: Medical malpractice can be defined as health workers neglecting the expected standard or intentionally not implementing it, doing it wrong and/or incomplete, not being able to implement the accurate practice due to personal or systemic reasons despite desiring to do it correctly and the condition that causes permanent or temporary damage to the patient as a result. If the training periods in which health workers improve their knowledge and skills are passed efficiently, they are expected to have a low rate of error in their professional lives. Aim: Aim of the study is to determine the medical malpractice tendencies of students studying in nursing department. Material and Methods: This descriptive research has been performed with 454 students who study in 3rd and 4th years in the Nursing Department of the Faculty of Health Sciences in a state university in normal and evening education and go out for clinical practice during the 2017-2018 academic year. The sample consisted of 454 students who agreed to participate in the study. Ethics committee approval, the permission of the institution and the verbal consent of the participants were obtained. In collection of data, ‘Personal Information Form’ developed by the researchers and the Malpractice Tendency Scale (SMT) were used. The data were analyzed using SPSS 20 package program. 0.05 was used as the level of significance. Results: The Cronbach’s alpha internal consistency coefficient of the scale was 0.94 and the total mean value of the scale was 211.69 ± 22.14. The mean age of the participants was 22,08 ± 1,852 years; 165 (36,4%) were male and 288 (63,6%) were female. Their mean General Point Average (GPA) was 2.65 ± 0.454 (min 1.03 - max 3.90). Students' average duration of self study per week was 2.89 ± 3.81 (min 0 - max 30) hours. The mean score (80.73) of the 4th year students in the sub-dimension of Drug and Transfusion Applications was significantly higher than the mean score (79.20) of 3rd year students (p < 0.05). The mean score (81.01) of the Drug and Transfusion Applications sub-dimension of those who willingly chose the profession was higher than the mean score (78.88) of those who chose the profession unwillingly. The mean average score (21.48) of Fallings sub-dimension of students who cared for 3 to 4 patients per day was lower than the mean score (22.41) of those who cared for 5 patients and over daily on average (p < 0.05). Conclusion: As a result of this study, it was concluded that malpractice tendency of nursing students was low, and an inverse relationship was found between the duration of education and malpractice tendency.
Abstract: This study investigated the relation between processing information and fitness level of active (fit) and sedentary (unfit) children drawn from rural and urban areas in Botswana. It was hypothesized that fit children would display faster simple reaction time (SRT), choice reaction times (CRT) and movement times (SMT). 60, third grade children (7.0 – 9.0 years) were initially selected and based upon fitness testing, 45 participated in the study (15 each of fit urban, unfit urban, fit rural). All children completed anthropometric measures, skinfold testing and submaximal cycle ergometer testing. The cognitive testing included SRT, CRT, SMT and Choice Movement Time (CMT) and memory sequence length. Results indicated that the rural fit group exhibited faster SMT than the urban fit and unfit groups. For CRT, both fit groups were faster than the unfit group. Collectively, the study shows that the relationship that exists between physical fitness and cognitive function amongst the elderly can tentatively be extended to the pediatric population. Physical fitness could be a factor in the speed at which we process information, including decision making, even in children.
Abstract: Software development for complex systems requires
efficient and automatic tools that can be used to verify the
satisfiability of some critical properties such as security ones. With
the emergence of Aspect-Oriented Programming (AOP), considerable
work has been done in order to better modularize the separation of
concerns in the software design and implementation. The goal is to
prevent the cross-cutting concerns to be scattered across the multiple
modules of the program and tangled with other modules. One of the
key challenges in the aspect-oriented programs is to be sure that all
the pieces put together at the weaving time ensure the satisfiability
of the overall system requirements. Our paper focuses on this problem and proposes a formal property
verification approach for a given property from the woven program.
The approach is based on the control flow graph (CFG) of the
woven program, and the use of a satisfiability modulo theories (SMT)
solver to check whether each property (represented par one aspect)
is satisfied or not once the weaving is done.
Abstract: Social Media (SM) is websites increasingly popular
and built to allow people to express themselves and to interact
socially with others. Most SMT are dominated by youth particularly
College students. The proliferation of popular social media tools,
which can accessed from any communication devices has become
pervasive in the lives of today’s student life. Connecting traditional
education to social media tools are a relatively new era and any
collaborative tool could be used for learning activities. This study
focuses (i) how the social media tools are useful for the learning
activities of the students of faculty of medicine in King Khalid
University (ii) whether the social media affects the collaborative
learning with interaction among students, among course instructor,
their engagement, perceived ease of use and perceived ease of
usefulness (TAM) (iii) overall, the students satisfy with this
collaborative learning through Social media.
Abstract: This paper proposes an application of probabilistic technique, namely Gaussian process regression, for estimating an optimal sequence of the single machine with total weighted tardiness (SMTWT) scheduling problem. In this work, the Gaussian process regression (GPR) model is utilized to predict an optimal sequence of the SMTWT problem, and its solution is improved by using an iterated local search based on simulated annealing scheme, called GPRISA algorithm. The results show that the proposed GPRISA method achieves a very good performance and a reasonable trade-off between solution quality and time consumption. Moreover, in the comparison of deviation from the best-known solution, the proposed mechanism noticeably outperforms the recently existing approaches.
Abstract: This paper presents a designed algorithm involves improvement of transferring data over Simple Object Access Protocol (SOAP). The aim of this work is to establish whether using SOAP in exchanging XML messages has any added advantages or not. The results showed that XML messages without SOAP take longer time and consume more memory, especially with binary data.
Abstract: This paper discusses E-government, in particular the challenges that face its development and widespread adoption in Saudi Arabia. E-government can be defined based on an existing set of requirements. E-government has been implemented for a considerable time in developed countries. However, E-government services still face many challenges in their implementation and general adoption in Saudi Arabia. In addition, the literature review and the discussion identify the influential factors, such as quality of service, diffusion of innovation, computer and information literacy, culture, lack of awareness, technical infrastructure, website design, and security, that affect the citizens’ intention to adopt E-government services in Saudi Arabia. Consequently, these factors have been integrated in a new model that would influence citizen to adopt E- government services. Therefore, this research presents an integrated model for ascertaining the intention to adopt E-government services and thereby aiding governments in accessing what is required to increase adoption.
Abstract: A Simultaneous Multithreading (SMT) Processor is
capable of executing instructions from multiple threads in the same
cycle. SMT in fact was introduced as a powerful architecture to
superscalar to increase the throughput of the processor.
Simultaneous Multithreading is a technique that permits multiple
instructions from multiple independent applications or threads to
compete limited resources each cycle. While the fetch unit has been
identified as one of the major bottlenecks of SMT architecture, several
fetch schemes were proposed by prior works to enhance the fetching
efficiency and overall performance.
In this paper, we propose a novel fetch policy called queue situation
identifier (QSI) which counts some kind of long latency instructions of
each thread each cycle then properly selects which threads to fetch
next cycle. Simulation results show that in best case our fetch policy
can achieve 30% on speedup and also can reduce the data cache level 1
miss rate.
Abstract: The problem of spam has been seriously troubling the Internet community during the last few years and currently reached an alarming scale. Observations made at CERN (European Organization for Nuclear Research located in Geneva, Switzerland) show that spam mails can constitute up to 75% of daily SMTP traffic. A naïve Bayesian classifier based on a Bag Of Words representation of an email is widely used to stop this unwanted flood as it combines good performance with simplicity of the training and classification processes. However, facing the constantly changing patterns of spam, it is necessary to assure online adaptability of the classifier. This work proposes combining such a classifier with another NBC (naïve Bayesian classifier) based on pairs of adjacent words. Only the latter will be retrained with examples of spam reported by users. Tests are performed on considerable sets of mails both from public spam archives and CERN mailboxes. They suggest that this architecture can increase spam recall without affecting the classifier precision as it happens when only the NBC based on single words is retrained.
Abstract: In this paper, we propose the pre-processor based on
the Evidence Supporting Measure of Similarity (ESMS) filter and also
propose the unified fusion approach (UFA) based on the general
fusion machine coupled with ESMS filter, which improve the
correctness and precision of information fusion in any fields of
application. Here we mainly apply the new approach to Simultaneous
Localization And Mapping (SLAM) of Pioneer II mobile robots. A
simulation experiment was performed, where an autonomous virtual
mobile robot with sonar sensors evolves in a virtual world map with
obstacles. By comparing the result of building map according to the
general fusion machine (here DSmT-based fusing machine and
PCR5-based conflict redistributor considereded) coupling with ESMS
filter and without ESMS filter, it shows the benefit of the selection of
the sources as a prerequisite for improvement of the information
fusion, and also testifies the superiority of the UFA in dealing with
SLAM.
Abstract: In this paper, a new method of information fusion – DSmT (Dezert and Smarandache Theory) is introduced to apply to managing and dealing with the uncertain information from robot map building. Here we build grid map form sonar sensors and laser range finder (LRF). The uncertainty mainly comes from sonar sensors and LRF. Aiming to the uncertainty in static environment, we propose Classic DSm (DSmC) model for sonar sensors and laser range finder, and construct the general basic belief assignment function (gbbaf) respectively. Generally speaking, the evidence sources are unreliable in physical system, so we must consider the discounting theory before we apply DSmT. At last, Pioneer II mobile robot serves as a simulation experimental platform. We build 3D grid map of belief layout, then mainly compare the effect of building map using DSmT and DST. Through this simulation experiment, it proves that DSmT is very successful and valid, especially in dealing with highly conflicting information. In short, this study not only finds a new method for building map under static environment, but also supplies with a theory foundation for us to further apply Hybrid DSmT (DSmH) to dynamic unknown environment and multi-robots- building map together.