Narrow Results

The computational power requirements of real-world optimization problems begin to exceed the general performance of the Central Processing Unit (CPU). The modeling of such problems is in constant evolution and requires more computational power. Solving them is expensive in computation time and even metaheuristics, well known for their eficiency, begin to be unsuitable for the increasing amount of data. Recently, thanks to the advent of languages such as CUDA, the development of parallel metaheuristics on Graphic Processing Unit (GPU) platform to solve combinatorial problems such as the Quadratic Assignment Problem (QAP) has received a growing interest. It is one of the most studied NP-hard problems and it is known for its high computational cost. In this paper, we survey several of the most important metaheuristics approaches for the QAP and we focus our survey on parallel metaheuristics using the GPU.

Acupuncture has been a popular alternative medicine in the United States for several decades. Its therapeutic effects on pain have been validated by both basic and clinical researches, and it is currently emerging as a unique non-pharmaceutical choice for pain against opioid crisis. However, the full spectrum of acupuncture indications remains unexplored. In this study, we conducted a cross-sectional survey among 419 acupuncturists nation-wide to investigate the top 10 and top 99 acupuncture indications in private clinics in the United States. We found the top 10 indications to be: lower back pain, depression, anxiety, headache, arthritis, allergies, general pain, female infertility, insomnia, neck pain and frozen shoulder. Among the top 99 indications, pain represents the largest category; and mental health management, especially for mood disorders, is in greatest demand. The following popular groups are: immune system dysfunctions, gastrointestinal diseases, gynecology and neurology. In addition, specialty index, commonality index, and the potential to become medical specialties were estimated for each indication. Demographic analysis suggests that China trained acupuncturists tend to have broader indication spectrums, but the top conditions treated are primarily decided by local needs. Also, gender, resident states, age and clinical experience all affect indication distributions. Our data for the first time outlines the profile of acupuncture treatable conditions in the US and is valuable for strategic planning in acupuncture training, healthcare administration and public education.

The relationship between budget deficits and macroeconomic variables (such as growth, interest rates, trade deficit, exchange rate, among others) represents one of the most widely debated topics among economists and policy makers in both developed and developing countries. However, the purpose of this paper is to review the extensive literature to such a relationship, concentrating on theoretical debates and empirical studies, in order to derive substantive conclusions, which can be beneficial in the macroeconomics area; policy analysis; or in terms of constructing or developing a macroeconomic model for analyzing the impact of budget deficits on macroeconomic variables. The majority of these studies regress a macroeconomic variable on the deficit variable. These studies are cross-country and utilize time series data. In general the key outcomes from the studies presented in this paper indicated that both the method of financing and the components of government expenditures could have different effects. Therefore, it is crucial for the government to distinguish between consumption and investment expenditures especially when the government is in the process of evaluating the impact of fiscal policy on private investment and output growth or in the process of cutting expenditures to reduce the fiscal imbalances in the country. Even though the overall results from the empirical literature with respect to the impact of public investment on private investment and growth are ambiguous, the bulk of the empirical studies find a significantly negative effect of public consumption expenditure on growth, while the effects of public investment expenditure (such as on education, healthcare) are found to be positive although less robust. The key findings from these studies is important in particular for developing countries to be aware of the importance of government investment expenditures in the area of education, healthcare, infrastructure to long-term economic growth and the benefits from which are an important contributor to welfare and well-being. The key outcome from all of the studies presented in this paper while investigating the relationship between the budget deficit and current account deficit showed strong evidence in both developed and developing countries towards supporting the Keynesian proposition (conventional view) which suggests that an increase in the budget deficit would induce domestic absorption and, hence import expansion, causing a current account deficit. The key findings from the empirical studies investigating the relationship between the budget deficit and interest rates indicated strong evidence towards supporting the Keynesian model of a significant and positive relationship between budget deficits and interest rates. The major outcomes from the empirical studies examining the relationship between budget deficits and inflation showed strong evidence that the budget deficit financed through monetization and a rising money supply could lead to inflation.

This study examines the financial rights and responsibilities of China’s local villages and townships based on a field survey conducted in Xingguo County. This field study focussed on local revenues and expenditures from 2012 to 2014. Upon analyzing data from the survey, we noted numerous difficulties of local financial management due to a lack of well-configured financial authority and power among central and local governments. In addition, revenues and expenditures are unbalanced at the local government level in China. Rural financial management systems need to be improved, and the rural finance function should be strengthened.

The vehicle routing problem (VRP) and its variants are a class of network problems that have attracted the attention of many researchers in recent years, owing to their pragmatic approach to solving issues in logistics management. Most surveys/reviews of the extant literature often focus on specific variants or aspects of the VRP. However, a few reviews of the overall VRP literature are available. The focus of these papers is to identify which VRP literature characteristics are the most popular in recent studies. To this end, we analyze 229 articles published between 2015 and 2017. We provide a systematic literature review evaluating the Scenario Characteristics and Problem Physical Characteristics that are most frequently addressed by VRP researchers, the Type of Study and Data Characteristics that they address, the most cited works that constitute the theoretical pillars of the field, and details of three specific problem variants that have been studied extensively in recent years and their opportunities for future research.

Utilizing the gauge framework, software under development at Baylor University, we explicitly construct all layer 1 weakly coupled free fermionic heterotic string (WCFFHS) gauge models up to order 32 in four to ten large spacetime dimensions. These gauge models are well suited to large scale systematic surveys and, while they offer little phenomenologically, are useful for understanding the structure of the WCFFHS region of the string landscape. Herein, we present the gauge groups statistics for this swath of the landscape for both supersymmetric and non-supersymmetric models.

An appropriate parking supply in cities should not only satisfy car travel demands but also restrict the number of car trips to reduce congestion and carbon emissions on road networks. This paper analyzes when car owners will abandon car driving based on a survey of the parking experiences of people in Changsha, China. The results indicate that car owners are most likely to abandon driving when the total time expenditure (including the search time and walking time) exceeds 20 min or the walking distance between a car park and a destination exceeds 400 m. In addition, car owners’ decisions regarding different trip purposes (commuting, business, hospital trips, shopping and entertainment activities) are compared. Multinomial logistic regression models and correspondence analysis methods are applied to identify the factors influencing car owners’ decisions. The results show that public transport and the parking pricing level near work places have a substantial impact on people’s decisions: people will more readily abandon driving when the travel time of public transit decreases; age, occupation and annual household income have a significant influence on people’s parking condition preferences for business trips and trips to hospitals; and the factor that primarily influences the mode choice for shopping and entertainment trips is annual household income. The outcome of this study can provide a basis for determining the optimal parking supply level and facilitate the realization of sustainable transportation.

The study presented in this paper highlights an important issue that was subject for discussions and research about a decade ago and now have gained new interest with the current advances of grid computing and desktop grids. New techniques are being invented on how to utilize desktop computers for computational tasks but no other study, to our knowledge, has explored the availability of the said resources. The general assumption has been that there are resources and that they are available. The study is based on a survey on the availability of resources in an ordinary office environment. The aim of the study was to determine if there are truly usable under-utilized networked desktop computers available for non-desktop tasks during the off-hours. We found that in more than 96% of the cases the computers in the current investigation was available for the formation of part-time (night and weekend) computer clusters. Finally we compare the performance of a full time and a metamorphosic cluster, based on one hypothetical linear scalable application and a real world welding simulation.

This paper reviews recent state-of-the-art H.264 sub-pixel motion estimation (SME) algorithms and architectures. First, H.264 SME is analyzed and the impact of its functionalities on coding performance is investigated. Then, design space of SME algorithms is explored representing design problems, approaches, and recent advanced algorithms. Besides, design challenges and strategies of SME hardware architectures are discussed and promising architectures are surveyed. Further perspectives and future prospects are also presented to highlight emerging trends and outlook of SME designs.

Software maintainability is a very important quality attribute. Its prediction for relational database-driven software applications can help organizations improve the maintainability of these applications. The research presented herein adopts a survey-based approach where a survey was conducted with 40 software professionals aimed at identifying and ranking the important maintainability predictors for relational database-driven software applications. The survey results were analyzed using frequency analysis. The results suggest that maintainability prediction for relational database-driven applications is not the same as that of traditional software applications in terms of the importance of the predictors used for this purpose. The results also provide a baseline for creating maintainability prediction models for relational database-driven software applications.

Runtime adaptive systems are able to dynamically transform their internal structure, and hence their behavior, in response to internal or external changes. Such transformations provide the basis for new functionalities or improvements of the non-functional properties that match operational requirements and standards. Software Product Line Engineering (SPLE) has introduced several models and mechanisms for variability modeling and management. Dynamic software product lines (DSPL) engineering exploits the knowledge acquired in SPLE to develop systems that can be context-aware, post-deployment reconfigurable, or runtime adaptive. This paper focuses on DSPL engineering approaches for developing runtime adaptive systems and proposes a framework for classifying and comparing these approaches from two distinct perspectives: adaptation properties and adaptation realization. These two perspectives are linked together by a series of guidelines that help to select a suitable adaptation realization approach based on desired adaptation types.

Technical debt (TD) expresses the lack of internal quality directly affecting software evolution. Therefore, it has gained the attention of software researchers and practitioners recently. Software researchers have performed empirical studies to observe the perspective of TD in different software cultures and organizations. However, it is important to replicate such studies in more places and with more practitioners to strengthen the perception of TD. In this paper, we present the results of a set of new research questions from an evolved survey design of a survey replication in the Uruguayan software industry to characterize how the software industry professionals understand, perceive, and adopt TD management (TDM) activities. The results allow us to observe that different participant contexts (startups, government, job roles) show different levels of awareness and perception of TD. Details in the form of the adoption of each TDM activity were presented. We could observe some difficulties in conducting some TDM activities that the practitioners consider very important, especially in TDM and monitoring. Differences in specific organizational contexts like startups and government could indicate the need for research efforts in other software engineering communities that meet their specific TD challenges and needs.

We present a survey of the hidden surface removal literature, focusing on object-space algorithms. We give a brief definition and history of the problem, followed by a discussion of problems and algorithms associated with the priority ordering of faces. We go on to examine object-space algorithms in order of increasing object complexity: xy-parallel rectangles, ordered triangles, c-oriented faces, c-oriented polyhedra, polyhedral terrains, and general polyhedra. We also review recent work on merging visibility maps and moving viewpoints. Finally, we present a list of open problems.

The development of vision-based human activity recognition and analysis systems has been a matter of great interest to both the research community and practitioners during the last 20 years. Traditional methods that require a human operator watching raw video streams are nowadays deemed as at least ineffective and expensive. New, smart solutions in automatic surveillance and monitoring have emerged, propelled by significant technological advances in the fields of image processing, artificial intelligence, electronics and optics, embedded computing and networking, molding the future of several applications that can benefit from them, like security and healthcare. The main motivation behind it is to exploit the highly informative visual data captured by cameras and perform high-level inference in an automatic, ubiquitous and unobtrusive manner, so as to aid human operators, or even replace them. This survey attempts to comprehensively review the current research and development on vision-based human activity recognition. Synopses from various methodologies are presented in an effort to garner the advantages and shortcomings of the most recent state-of-the-art technologies. Also a first-level self-evaluation of methodologies is also proposed, which incorporates a set of significant features that best describe the most important aspects of each methodology in terms of operation, performance and others and weighted by their importance. The purpose of this study is to serve as a reference for further research and evaluation to raise thoughts and discussions for future improvements of each methodology towards maturity and usefulness.

A person’s preference to select or reject certain meals is influenced by several aspects, including colour. In this paper, we study the relevance of food colour for such preferences. To this end, a set of images of meals is processed by an automatic method that associates mood adjectives that capture such meal preferences. These adjectives are obtained by analyzing the colour palettes in the image, using a method based in Kobayashi’s model of harmonic colour combinations. The paper also validates that the colour palettes calculated for each image are harmonic by developing a rating model to predict how much a user would like the colour palettes obtained. This rating is computed using a regression model based on the COLOURlovers dataset implemented to learn users’ preferences. Finally, the adjectives associated automatically with images of dishes are validated by a survey which was responded by 178 people and demonstrates that the labels are adequate. The results obtained in this paper have applications in tourism marketing, to help in the design of marketing multimedia material, especially for promoting restaurants and gastronomic destinations.

Hybrid entrepreneurs (HEs) represent a considerable share of all entrepreneurial activity. Yet little is known about the phenomenon. In this study we examine the differences between transitory HEs, who expect to make the transition to full-time entrepreneurship, and persistent HEs, who view their part-time status as permanent. With data collected from 848 academic HEs we find that only a small minority considers full self-employment likely in the near future and that self-fulfillment is the most significant motive for entrepreneurial activities. The results suggest that persistent hybrid entrepreneurship should be viewed as a form of entrepreneurship in its own right, and that even partial entrepreneurship has the potential to lengthen careers and improve wellbeing at work. Hybrid entrepreneurship offers the entrepreneurially inclined employees the best of both worlds.

Survey analysis method is widely used in many areas such as social study, marketing research, economics, public health, clinical trials and transportation data analysis. Minimum sample size determination is always needed before a survey is conducted to avoid huge cost. Some statistical methods can be found from the literature for finding the minimum required sample size. This paper proposes a method for finding the minimum total sample size needed for the survey when the population is divided into cells. The proposed method can be used for both the infinite population case and the finite population case. A computer program is needed to realize the sample size calculation. The computer program the authors used is SAS/IML, which is a special integrated matrix language (IML) procedure of the Statistical Analysis System (SAS) software.

The redundancy is a widely spread technology of building computing systems that continue to operate satisfactorily in the presence of faults occurring in hardware and software components. The principle objective of applying redundancy is achieve reliability goals subject to techno-economic constraints. Due to a plenty of applications arising virtually in both industrial and military organizations especially in embedded fault tolerance systems including telecommunication, distributed computer systems, automated manufacturing systems, etc., the reliability and its dependability measures of redundant computer-based systems have become attractive features for the systems designers and production engineers. However, even with the best design of redundant computer-based systems, software and hardware failures may still occur due to many failure mechanisms leading to serious consequences such as huge economic losses, risk to human life, etc. The objective of present survey article is to discuss various key aspects, failure consequences, methodologies of redundant systems along with software and hardware redundancy techniques which have been developed at the reliability engineering level. The methodological aspects which depict the required steps to build a block diagram composed of components in different configurations as well as Markov and non-Markov state transition diagram representing the structural system has been elaborated. Furthermore, we describe the reliability of a specific redundant system and its comparison with a non redundant system to demonstrate the tractability of proposed models and its performance analysis.

Background: This controlled randomized experiment tested the research hypothesis that providing the CTS-6 quantitative diagnostic information to hand surgeons affects the diagnosis of carpal tunnel syndrome.

Methods: Surgeon members of American Association for Hand Surgery participated in an online survey. Demographic and practice pattern information was collected. Few surgeons routinely use diagnostic questionnaires or algorithms. Each member was given four clinical scenarios. The respondents were randomized, The experimental group was given the same scenarios as the control group plus the quantitative results of the CTS-6 diagnostic tool.

Results: There were statistically significant differences between the groups in the diagnostic decisions. Using the CTS-6 quantitative diagnostic tool affected the diagnosis of carpal tunnel syndrome, especially for patients with the lowest number of findings associated with carpal tunnel syndrome.

Conclusions: While accurate diagnostic decisions are dependent on the incorporation of all of the pertinent information gathered during the history and physical exams, the results of the CTS-6 may help the clinician focus their thinking and revise their diagnostic probabilities.

Construction workers are frequently exposed to awkward work postures and physical demands that can lead to work-related musculoskeletal disorders. There has been limited development of assessment and outreach strategies targeting this highly mobile workforce in general and especially among Hispanic construction workers. We report the prevalence of joint pain from a convenience sample of Hispanic construction workers. A workplace musculoskeletal disorder assessment was undertaken coinciding with construction-site lunch truck visits among 54 workers employed at two large South Florida construction sites. A 45-item questionnaire preloaded onto handheld devices was utilized to record field data. Forty-seven percent of Hispanic workers reported joint pain 30 days prior to interview date, of whom 87% indicated these joint problems interfered with work activities. Over 63% reported experiencing low back pain that lasted at least a whole day during the past 3 months. Right and left knees were the most frequently reported painful joints (both 34%). Musculoskeletal disorders as evident by joint pain, appears to be prevalent among Hispanic construction workers. Workplace ergonomic prevention strategies that reduce musculoskeletal disorders using innovative recruitment and engagement methods (such as during lunch truck construction-site visits) may improve opportunities to reduce joint pain and damage.