snu-aidas/HVMap-dataset huggingface dataset:
Knowledge management strategy and its link to knowledge creation process

Knowledge has become to be considered as valuable strategic assets that can provide proprietary competitive advantages. It is more important for companies to distinguish themselves through knowledge management strategies. Without a constant creation of knowledge, a business is condemned to poor performance. However, it is still unclear how these strategies affect knowledge creation. Knowledge management strategies can be categorized as being either human or system oriented. This paper proposes a model to illustrate the link between the strategies and its creating process. The model is derived on the basis of samples from 58 Korean firms. The model depicts how companies should align the strategies with four knowledge creation modes such as socialization, externalization, combination, and internalization. It is found that human strategy is more likely to be effective for socialization while system strategy is more likely to be effective for combination. Furthermore, the survey result suggests that managers should adjust knowledge management strategies in view of the characteristics of their departments. q 2002 Elsevier Science Ltd. All rights reserved.
An Improved Dijkstra Algorithm for Firefighting

In this paper, briefly the efforts going toward a mathematical calculation to validate a new-Dijkstra algorithm from the original normal Dijkstra algorithm [1] as an improvised Dijkstra. The result of this improvised Dijkstra was used to find the shortest path for firefighting unit to reach the location of the fire exactly. The idea depends on the influence of turns on the path, while there are two equal paths’, the more number of turns take more time to pass through it and the less number turns takes less time to pass through it. To apply this scenario practically we take a small real area in south Khartoum. The result gives strong justification that proves and verifies our methodology with a clear contribution in Improved Dijkstra algorithm for firefighting like Geo-Dijkstra. Furthermore, an evaluation of the above-mentioned algorithms has been done showing very promising and realistic results.
Collaborative matrix factorization mechanism for group recommendation in big data-based library systems

Purpose –Academic groups are designed specifically for researchers. A group recommendation procedure is essential to support scholars’ research-based social activities. However, group recommendation methods are rarely applied in online libraries and they often suffer from scalability problem in big data context. The purpose of this paper is to facilitate academic group activities in big data-based library systems by recommending satisfying articles for academic groups. Design/methodology/approach – The authors propose a collaborative matrix factorization (CoMF) mechanism and implement paralleled CoMF under Hadoop framework. Its rationale is collaboratively decomposing researcher-article interaction matrix and group-article interaction matrix. Furthermore, three extended models of CoMF are proposed. Findings – Empirical studies on CiteULike data set demonstrate that CoMF and three variants outperform baseline algorithms in terms of accuracy and robustness. The scalability evaluation of paralleled CoMF shows its potential value in scholarly big data environment. Research limitations/implications – The proposed methods fill the gap of group-article recommendation in online libraries domain. The proposed methods have enriched the group recommendation methods by considering the interaction effects between groups and members. The proposed methods are the first attempt to implement group recommendation methods in big data contexts. Practical implications – The proposed methods can improve group activity effectiveness and information shareability in academic groups, which are beneficial to membership retention and enhance the service quality of online library systems. Furthermore, the proposed methods are applicable to big data contexts and make library system services more efficient. Social implications – The proposed methods have potential value to improve scientific collaboration and research innovation. Originality/value – The proposed CoMF method is a novel group recommendation method based on the collaboratively decomposition of researcher-article matrix and group-article matrix. The process indirectly reflects the interaction between groups and members, which accords with actual library environments and provides an interpretable recommendation result.
Biomedical question answering: A survey

OBJECTIVES
In this survey, we reviewed the current state of the art in biomedical QA (Question Answering), within a broader framework of semantic knowledge-based QA approaches, and projected directions for the future research development in this critical area of intersection between Artificial Intelligence, Information Retrieval, and Biomedical Informatics.


MATERIALS AND METHODS
We devised a conceptual framework within which to categorize current QA approaches. In particular, we used "semantic knowledge-based QA" as a category under which to subsume QA techniques and approaches, both corpus-based and knowledge base (KB)-based, that utilize semantic knowledge-informed techniques in the QA process, and we further classified those approaches into three subcategories: (1) semantics-based, (2) inference-based, and (3) logic-based. Based on the framework, we first conducted a survey of open-domain or non-biomedical-domain QA approaches that belong to each of the three subcategories. We then conducted an in-depth review of biomedical QA, by first noting the characteristics of, and resources available for, biomedical QA and then reviewing medical QA approaches and biological QA approaches, in turn. The research articles reviewed in this paper were found and selected through online searches.


RESULTS
Our review suggested the following tasks ahead for the future research development in this area: (1) Construction of domain-specific typology and taxonomy of questions (biological QA), (2) Development of more sophisticated techniques for natural language (NL) question analysis and classification, (3) Development of effective methods for answer generation from potentially conflicting evidences, (4) More extensive and integrated utilization of semantic knowledge throughout the QA process, and (5) Incorporation of logic and reasoning mechanisms for answer inference.


CONCLUSION
Corresponding to the growth of biomedical information, there is a growing need for QA systems that can help users better utilize the ever-accumulating information. Continued research toward development of more sophisticated techniques for processing NL text, for utilizing semantic knowledge, and for incorporating logic and reasoning mechanisms, will lead to more useful QA systems.
Memory consolidation and the hippocampus: further evidence from studies of autobiographical memory in semantic dementia and frontal variant frontotemporal dementia

Studies of autobiographical memory in semantic dementia have found relative preservation of memories for recent rather than remote events. As semantic dementia is associated with progressive atrophy to temporal neocortex, with early asymmetric sparing of the hippocampus, this neuropsychological pattern suggests that the hippocampal complex plays a role in the acquisition and retrieval of recent memories, but is not necessary for the recall of older episodic events. In an alternative view of memory consolidation, however, the hippocampus plays a role in the retrieval of all autobiographical memories, regardless of the age of the memory [Curr. Opin. Neurobiol. 7(1997)217]. This 'multiple trace theory' predicts that patients with semantic dementia should show no effects of time in their autobiographical recall. In this article, we ask whether it is possible to reconcile the data from semantic dementia with the multiple trace theory by investigating whether the time-dependent pattern of autobiographical retrieval seen in the disease is due to (i) patients showing this effect being exceptional in their presentation; and/or (ii) patients with semantic dementia exhibiting impaired strategic retrieval from concomitant frontal damage. A series of experiments in patients with semantic dementia, the frontal variant of frontotemporal dementia and Alzheimer's disease clearly demonstrates that neither of these two factors can explain the documented effect of time seen in semantic dementia. Nonetheless, we discuss how damage to semantic knowledge could result in an autobiographical memory deficit and suggest that data from semantic dementia may be consistent with both views of hippocampal involvement in long-term memory.
Sparse Model-based Image Alignment Feature Alignment Pose & Structure Refinement Motion Estimation Thread New Image Last Frame Map Frame Queue Feature Extraction Initialize Depth-Filters

Direct methods for Visual Odometry (VO) have gained popularity due to their capability to exploit information from all intensity gradients in the image. However, low computational speed as well as missing guarantees for optimality and consistency are limiting factors of direct methods, where established feature-based methods instead succeed at. Based on these considerations, we propose a Semi-direct VO (SVO) that uses direct methods to track and triangulate pixels that are characterized by high image gradients but relies on proven feature-based methods for joint optimization of structure and motion. Together with a robust probabilistic depth estimation algorithm, this enables us to efficiently track pixels lying on weak corners and edges in environments with little or high-frequency texture. We further demonstrate that the algorithm can easily be extended to multiple cameras, to track edges, to include motion priors, and to enable the use of very large field of view cameras, such as fisheye and catadioptric ones. Experimental evaluation on benchmark datasets shows that the algorithm is significantly faster than the state of the art while achieving highly competitive accuracy. SUPPLEMENTARY MATERIAL Video of the experiments: https://youtu.be/hR8uq1RTUfA
Resin composite--state of the art.

OBJECTIVES
The objective is to review the current state of the art of dental composite materials.


METHODS
An outline of the most important aspects of dental composites was created, and a subsequent literature search for articles related to their formulation, properties and clinical considerations was conducted using PubMed followed by hand searching citations from relevant articles.


RESULTS
The current state of the art of dental composites includes a wide variety of materials with a broad range of mechanical properties, handling characteristics, and esthetic possibilities. This highly competitive market continues to evolve, with the major emphasis in the past being to produce materials with adequate strength, and high wear resistance and polishability retention. The more recent research and development efforts have addressed the issue of polymerization shrinkage and its accompanying stress, which may have a deleterious effect on the composite/tooth interfacial bond. Current efforts are focused on the delivery of materials with potentially therapeutic benefits and self-adhesive properties, the latter leading to truly simplified placement in the mouth.


SIGNIFICANCE
There is no one ideal material available to the clinician, but the commercial materials that comprise the current armamentarium are of high quality and when used appropriately, have proven to deliver excellent clinical outcomes of adequate longevity.
Parental vaccine safety concerns in 2009.

OBJECTIVE
Vaccine safety concerns can diminish parents' willingness to vaccinate their children. The objective of this study was to characterize the current prevalence of parental vaccine refusal and specific vaccine safety concerns and to determine whether such concerns were more common in specific population groups.


METHODS
In January 2009, as part of a larger study of parents and nonparents, 2521 online surveys were sent to a nationally representative sample of parents of children who were aged </=17 years. The main outcome measures were parental opinions on vaccine safety and whether the parent had ever refused a vaccine that a doctor recommended for his or her child.


RESULTS
The response rate was 62%. Most parents agreed that vaccines protect their child(ren) from diseases; however, more than half of the respondents also expressed concerns regarding serious adverse effects. Overall, 11.5% of the parents had refused at least 1 recommended vaccine. Women were more likely to be concerned about serious adverse effects, to believe that some vaccines cause autism, and to have ever refused a vaccine for their child(ren). Hispanic parents were more likely than white or black parents to report that they generally follow their doctor's recommendations about vaccines for their children and less likely to have ever refused a vaccine. Hispanic parents were also more likely to be concerned about serious adverse effects of vaccines and to believe that some vaccines cause autism.


CONCLUSIONS
Although parents overwhelmingly share the belief that vaccines are a good way to protect their children from disease, these same parents express concerns regarding the potential adverse effects and especially seem to question the safety of newer vaccines. Although information is available to address many vaccine safety concerns, such information is not reaching many parents in an effective or convincing manner.
Measurement of preoperative and postoperative nasal tip projection and rotation.

OBJECTIVE
To measure the effect of columellar struts and cephalic trim on tip projection and tip rotation using digitized photographs.


METHODS
Using photographs of 62 patients who underwent external rhinoplasty, we retrospectively analyzed nasal tip projection (the Goode method) and rotation (nasolabial angle) before and after surgery. A cartilaginous strut was used in 36 patients, whereas 26 patients did not receive a strut. Patients were categorized into 4 subgroups, depending on the placement of a strut (placement, strut+ vs nonplacement, strut-) and the removal of the cephalic margin (removal, cephalic+ vs nonremoval, cephalic-) of the lateral crus: strut-/cephalic-, n = 17; strut+/cephalic-, n = 23; strut-/cephalic+, n = 9; strut+/cephalic+, n = 12.


RESULTS
Nasal tip projection, measured with the Goode method, increased from 0.58 to 0.60 (P = .02) in the strut+ group; in the strut- group, nasal tip projection did not change significantly. Nasolabial angle increased from 93.96 degrees to 100.92 degrees in the strut+/cephalic- group and from 88.30 degrees to 95.06 degrees in the strut+/cephalic+ group. Removal of the cephalic margin alone (strut-/cephalic+) hardly affected tip rotation (P = .05).


CONCLUSIONS
The external rhinoplasty approach did not lead to a decrease in nasal tip projection. A cartilaginous strut slightly increased nasal tip projection and also increased nasal tip rotation. This effect was accentuated by the removal of the cephalic margin of the lateral crus.
Labeled Faces in the Wild: A Survey

In 2007, Labeled Faces in the Wild was released in an effort to spur research in face recognition, specifically for the problem of face verification with unconstrained images. Since that time, more than 50 papers have been published that improve upon this benchmark in some respect. A remarkably wide variety of innovative methods have been developed to overcome the challenges presented in this database. As performance on some aspects of the benchmark approaches 100% accuracy, it seems appropriate to review this progress, derive what general principles we can from these works, and identify key future challenges in face recognition. In this survey, we review the contributions to LFW for which the authors have provided results to the curators (results found on the LFW results web page). We also review the cross cutting topic of alignment and how it is used in various methods. We end with a brief discussion of recent databases designed to challenge the next generation of face recognition algorithms. Erik Learned-Miller University of Massachusetts, Amherst, Massachusetts, e-mail: elm@cs.umass.edu Gary B. Huang Howard Hughes Medical Institute, Janelia Research Campus, e-mail: gbhuang@cs.umass.edu Aruni RoyChowdhury University of Massachusetts, Amherst, Massachusetts, e-mail: aruni@cs.umass.edu Haoxiang Li Stevens Institute of Technology, Hoboken, New Jersey, e-mail: hli18@stevens.edu Gang Hua Stevens Institute of Technology, Hoboken, New Jersey, e-mail: ganghua@gmail.com
The sounds of silence: language, cognition, and anxiety in selective mutism.

OBJECTIVES
To determine whether oral language, working memory, and social anxiety differentiate children with selective mutism (SM), children with anxiety disorders (ANX), and normal controls (NCs) and explore predictors of mutism severity.


METHOD
Children ages 6 to 10 years with SM (n = 44) were compared with children with ANX (n = 28) and NCs (n = 19) of similar age on standardized measures of language, nonverbal working memory, and social anxiety. Variables correlating with mutism severity were entered in stepwise regressions to determine predictors of mute behavior in SM.


RESULTS
Children with SM scored significantly lower on standardized language measures than children with ANX and NCs and showed greater visual memory deficits and social anxiety relative to these two groups. Age and receptive grammar ability predicted less severe mutism, whereas social anxiety predicted more severe mutism. These factors accounted for 38% of the variance in mutism severity.


CONCLUSIONS
Social anxiety and language deficits are evident in SM, may predict mutism severity, and should be evaluated in clinical assessment. Replication is indicated, as are further studies of cognition and of intervention in SM, using large, diverse samples.
Examining strategic ambidexterity as an antecedent of functional and cross-functional ambidexterity
Pornographic image detection utilizing deep convolutional neural networks

Many internet users are potential victims of the pornographic images and a large part of them are underage children. Thus, content-based pornographic images detection is an important task in computer vision and multimedia research. Previous solutions usually rely on hand-engineered visual features that are hard to analyze and select. In this paper, to detect pornographic images in any style accurately and efficiently with a single model, a novel scheme utilizing the deep convolutional neural networks (CNN) is proposed. The training data are obtained from internet followed by an improved sliding window method and some novel data augmentation approaches. Then a highly efficient training algorithm is proposed based on two strategies. The first is the pre-trained midlevel representations non-fixed fine-tuning strategy. The second is adjusting the training data at the appropriate time on the basis of the performance of the proposed network on the validation set. Furthermore, we introduce a fast image scanning method which is also based on the sliding window approach in the test. We further propose a fast forward pass method based on the “fixedpoint algorithm”. So our CNN could detect all scale images so fast by one forward pass. The effectiveness of the proposed method is demonstrated in experiments on the proposed dataset and the comparative results show that our ∗Corresponding author Email address: tenglwy@gmail.com (Teng Li) Preprint submitted to Neurocomputing June 9, 2016 method lead to state-of-the-art detection performance.
The prerepresentational self and its affective core.
Building Simple Annotation Tools

OF THE THESIS Building Simple Annotation Tools
Optical interconnects for extreme scale computing systems

Large-scale high performance computing is permeating nearly every corner of modern applications spanning from scientific research and business operations, to medical diagnostics, and national security. All these communities rely on computer systems to process vast volumes of data quickly and efficiently, yet progress toward increased computing power has experienced a slowdown in the last number of years. The sheer cost and scale, stemming from the need for extreme parallelism, are among the reasons behind this stall. In particular, very large-scale, ultra-high bandwidth interconnects, essential for maintaining computation performance, represent an increasing portion of the total cost budget. Photonic systems are often cited as ways to break through the energy-bandwidth limitations of conventional electrical wires toward drastically improving interconnect performance. This paper presents an overview of the challenges associated with large-scale interconnects, and reviews how photonic technologies can contribute to addressing these challenges. We review some important aspects of photonics that should not be underestimated in order to truly reap the benefits of cost and power reduction. © 2017 Elsevier B.V. All rights reserved.
The economic costs of pain in the United States.

UNLABELLED
In 2008, according to the Medical Expenditure Panel Survey (MEPS), about 100 million adults in the United States were affected by chronic pain, including joint pain or arthritis. Pain is costly to the nation because it requires medical treatment and complicates treatment for other ailments. Also, pain lowers worker productivity. Using the 2008 MEPS, we estimated 1) the portion of total U.S. health care costs attributable to pain; and 2) the annual costs of pain associated with lower worker productivity. We found that the total costs ranged from $560 to $635 billion in 2010 dollars. The additional health care costs due to pain ranged from $261 to $300 billion. This represents an increase in annual per person health care costs ranging from $261 to $300 compared to a base of about $4,250 for persons without pain. The value of lost productivity due to pain ranged from $299 to $335 billion. We found that the annual cost of pain was greater than the annual costs of heart disease ($309 billion), cancer ($243 billion), and diabetes ($188 billion). Our estimates are conservative because they do not include costs associated with pain for nursing home residents, children, military personnel, and persons who are incarcerated.


PERSPECTIVE
This study estimates that the national cost of pain ranges from $560 to $635 billion, larger than the cost of the nation's priority health conditions. Because of its economic toll on society, the nation should invest in research, education, and training to advocate the successful treatment, management, and prevention of pain.