Miracle-dz/UniFAR-FTUs huggingface dataset:
Reference Values and Water quality Assessment Based on the Regional Environmental Characteristics

For the development of reference values and evaluation of water quality in various environmental conditions, we divided the coastal region around Korean peninsular into 5 distinctive ecological regions based on the influence of surface current, depth, tidal range, turbidity, and climate condition. We used national marine environment monitoring data collected by National Fisheries Research & Development Institute(NFRDI) from 2000-2009. For the reference values, we used maximum seasonal mean from 2000 to 2007 for DIN, DIP, and chlorophyll-a and minimum seasonal mean for secchi depth measured at stations without the influence of river runoff in each ecological regions. For the reference value of bottom dissolved oxygen saturation, we used minimum mean value of 90% calculated from minimal riverine influence stations of whole regions. We calculated enrichment score for each assessment criteria. The enrichment score of DIN, DIP, and Chlorophyll-a was 1 (
The in-depth cognitive levels of imagination of artisans and designers

This paper investigated the in-depth cognitive levels of artisans (craft artisans) and designers (design trainers) as they observed design problems (in the early stage of idea generation) during design training. A concept network method based on the associative concept dictionary was employed to extract the verbalised thoughts of four artisans and four designers. We then identified semantic relationships based on a factor analysis. We discovered that, in contrast to designers, artisans tended to activate lower in-depth cognitive levels. Our study demonstrated that artisans placed greater focus on product appearance and technical aspects, such as operation (replace, reduce, etc.) and shape (waist, body, etc.). In contrast, designers paid greater attention to the presence of issues related to surroundings, such as scene (silverware, norm, etc.) and appeal (fresh, dish, etc.). These results demonstrate that closely or remotely associated concepts correlate with shallow or in-depth cognitive levels based on creative solutions.
An empirical assessment of the use of different communication modes for requirement elicitation and negotiation using students as a subject

Requirements engineering is considered the most communication-intensive activity among all other software engineering activities. Requirements' elicitation and negotiation are communication-rich stages that require intensive contact between different stakeholders (i.e., clients and engineers). For this reason, the need to identify the appropriate task/technology fits, to support the communication between different stakeholders, plays a key role in an efficient software products' development. This work reports an empirical study that assesses the use of three different communication modes, namely: Text-Based Communication, Face-to-Face, and Rich Media, in order to support the different tasks of requirements elicitation and negotiation, by using students as the study subjects. We conducted an experimental study of six groups of students, who were developing a requirements document, over a period of eight weeks. Each communication mode was used by two different groups. We evaluated the three communication modes in terms of the participants' satisfaction with performance, comfort with the communication mode, and the perceived engagement level, using post questionnaires. The main finding of this study is that the face-to-face communication mode was the most preferred method during both the elicitation and negotiation stages, in comparison to the text-based and rich media modes.
A Hierarchical Bayesian Model for Text Corpora

We propose a new generative probabilistic Dirich- let Author-Topic (DAT) Model for extracting information about authors and topics from large text collections. DAT is a three-level hierarchical Bayesian model. The model builds on the Author Topic (AT) model, adding the key attribute that distribution over author is conditioned on a Dirichlet prior. The probability distribution over topics in a multi-author document is a mixture of the distributions associated with the authors. The three level distributions including document-author, author-topic and topic-word are learned from data in an unsupervised manner using a Gibbs sampling algorithm. We give results on a large corpus which contains 1740 papers from the Neural Information Processing Systems Conference (NIPS). Experiments based on perplexity scores for test documents are used to illustrate systematic differences between the proposed model and a number of alternatives.
Comparing NN paradigms in hybrid NN/HMM speech recognition using tied posteriors

Hybrid NN/HMM acoustic modeling is nowadays an established alternative approach in automatic speech recognition technology. A comparison of feedforward and recurrent neural network topologies integrated in the tied posteriors framework is presented. We give some insights in the training process of the networks estimating class posterior probabilities and show how the net's quality can be determined by introducing a new measurement prior to evaluating the complete ASR system. Finally, we demonstrate the flexibility of the tied posteriors framework by showing results for different context independent and context dependent acoustic models all based on the same system structure.
INTERDEPENDENCE, INFORMATION PROCESSING AND ORGANIZATION DESIGN: AN EPISTEMIC PERSPECTIVE

We develop a novel analytical framework to study epistemic interdependence - a situation in which agents need predictive knowledge about each other - as a basis for understanding information processing requirements in organizations, and the resulting implications for organization design. The framework we develop helps to describe and compare the nature of the underlying coordination problems generated by different patterns of interdependence, and the resulting knowledge requirements for the design and implementation of appropriate organizational structures. The framework offers a formal language that may prove useful for parsimoniously integrating what we know, as well as for building new theory.
A practical approach to enterprise IT security

As the Internet has matured, so have the threats to its safe use, and so must the security measures that enable its business use. Traditional piecemeal, single-layer, single-dimensional security approaches are no longer adequate. These approaches can create a false sense of security and create as many problems as they attempt to address. We propose a multifaceted framework to prevent, detect, and respond to ever more sophisticated threats to enterprise IT information and assets. We outline a practical implementation approach to building enterprise IT security mechanisms in an incremental and continuous fashion. We believe that enterprises should adopt a similar multifaceted framework, following a practical but disciplined implementation approach. Enterprises must treat IT security as a required business enabler rather than just a costly item with low priority.
Development of a portable bicycle/pedestrian monitoring system for safety enhancement

Pedestrians involved in roadway accidents account for nearly 12 percent of all traffic fatalities and 59,000 injuries each year. Most injuries occur when pedestrians attempt to cross roads, and there have been noted differences in accident rates midblock vs. at intersections. Collecting data on pedestrian behavior is a time consuming manual process that is prone to error. This leads to a lack of quality information to guide the proper design of lane markings and traffic signals to enhance pedestrian safety. Researchers at the Georgia Tech Research Institute are developing and testing an automated system that can be rapidly deployed for data collection to support the analysis of pedestrian behavior at intersections and midblock crossings with and without traffic signals. This system will analyze the collected video data to automatically identify and characterize the number of pedestrians and their behavior. It consists of a mobile trailer with four high definition pan-tilt cameras for data collection. The software is custom designed and uses state of the art commercial pedestrian detection algorithms. We will be presenting the system hardware and software design, challenges, and results from the preliminary system testing. Preliminary results indicate the ability to provide representative quantitative data on pedestrian motion data more efficiently than current techniques.
Compiling for the multiscalar architecture

High-performance, general-purpose microprocessors serve as compute engines for computers ranging from personal computers to supercomputers. Sequential programs constitute a major portion of real-world software that run on the computers. State-of-the-art microprocessors exploit instruction level parallelism (ILP) to achieve high performance on such applications by searching for independent instructions in a dynamic window of instructions and executing them on a wide-issue pipeline. Increasing the window size and the issue width to extract more ILP may hinder achieving high clock speeds, limiting overall performance. The Multiscalar architecture employs multiple small windows and many narrow-issue processing units to exploit ILP at high clock speeds. Sequential programs are partitioned into code fragments called tasks, which are speculatively executed in parallel. Inter-task register dependences are honored via communication and synchronization and inter-task control flow and memory dependences are handled by speculation and verification in hardware. Since this thesis is the first attempt at investigating the problem of compiling for the Multiscalar architecture, I identify the fundamental interactions between applications and the Multiscalar architecture from the standpoint of performance and explore a few compiler optimization opportunities instead of proposing the best technique for a specific problem. Control flow speculation, register communication, memory dependence speculation, load imbalance, and task overheads are key performance issues. To extract high degrees of ILP, compiler heuristics partition programs into large tasks, which comprise multiple basic blocks. To maintain high prediction accuracy and avoid delays due to inter-task register communication, the heuristics control the number of successors of tasks while including register dependences within tasks. Inter-task register communication is generated and scheduled to overlap computation and inter-task register communication. For the SPEC95 benchmarks, the heuristics increase task sizes significantly while improving control flow speculation accuracy with respect to basic blocks, enabling large window spans from which to extract parallelism. Including register dependences within tasks improves performance considerably. Sophisticated register communication generation and scheduling are effective in boosting performance. Dead register analysis reduces register communication traffic considerably. All the optimizations grow in importance for larger number of PUs.
Challenges in Collection Development for Entrepreneurship

Entrepreneurship is a high-risk high-reward endeavor that relies on the effective use of information. An entrepreneur’s success is often based on a mixture of luck, a good idea, acquiring the right pieces of information, and then acting on it to make a competitive decision. At Purdue we are investigating ways of providing greater access to relevant entrepreneurial information. Specifically, the Management & Economics Library is collaborating with Purdue Extension to provide resources to dedicated workstations at the off-campus Extension Office sites. The Extension Offices’ role has been changing over time as technology has affected the agriculture industry. They see themselves as a source for small business support and regional economic development. The Management & Economics Library at Purdue is attempting to leverage its resources with technology support through the Purdue Extension Offices. Purdue University, as a land-grant institution, has a strategic initiative to support the greater community and state. The articles in this section all have at their core a focus on the effective utilization of resources for entrepreneurial success. Carissa M. Holler Phillips leads off with an analysis of research conducted by students for a business plan project. Sylvia James presents an introduction to the effective use of information when identifying potential sources of private equity. At the University of Toledo, Julia A. Martin provides insight into a collaboration and resource/collection development initiative with a local economic development center. Karen Resch McKeown, from ProQuest, presents details on the research they conducted to design and develop their ProQuest Entrepreneurship database. The mix of articles presents a variety of perspectives on the development, use, and study of information resources relating to entrepreneurship. Perhaps some insight can be gained to help develop your own entrepreneurial collection or information intensive project.
Probabilistic programming for assessment of capability and capacity

Answering the questions "What can the adversary do? " and "What will the adversary do? " are critical functions of intelligence analysis. These questions require processing many sources of information, which is currently performed manually by analysts, leading to missed opportunities and potential mistakes. We have developed a system for Assessment of Capability and Capacity via Intelligence Analysis (ACACIA) to help analysts assess the capability, capacity, and intention of a nation state or non-state actor. ACACIA constructs a Bayesian network (BN) to model the objectives and means of an actor in a situation. However, a straightforward BN implementation is insufficient, since objectives and means are different in every situation. Additionally, we wish to apply knowledge about an element gained from one situation to another situation containing the same element. Furthermore, different elements of the same kind usually share the same model structure with different parameters. We use the probabilistic programming language Figaro, which allows models to be constructed using the power of programming languages, to address these issues, generating BNs for diverse situations while maximizing sharing. We learn the parameters of a program from training instances. Experiments show ACACIA is capable of making accurate inferences and that learning effectively improves ACACIA's performance.
Study of hsCRP, adiponectin, NF-κB in low bodyweight, standard bodyweight and obese subjects with type 2 diabetes mellitus in India

Introduction: Low bodyweight type 2 DM is a distinct clinical entity having many inherent peculiarities seen in India and developing countries, constituting 11% to 25% of type 2 diabetic subjects. Our study aimed at assessing the prevalence of inflammatory markers like hsCRP, adiponectin and NF-κB expression in peripheral blood mononuclear cells in subjects with type 2 DM in relation to BMI. Materials and Methods: 57 consecutive type 2 diabetics were recruited for study, classified as Low Bodyweight (A = BMI < 18.5), Standard weight (B = BMI 18.5 - 24.99) and Obese (C = BMI ≥ 25). Group D comprised 14 healthy controls. They were evaluated for clinical parameters, FBG, 2hrPPBG, HbA1c, lipid profile and above mentioned inflammatory markers. Results: Serum hsCRP was significantly higher in all group of diabetics as compared to Group D but was lowest in Group A. Adiponectin levels were highest in Group D, similar in Groups B and C but lowest in Group A. NF-κB expression, though higher in diabetic subjects than controls (OD = 0.041 ± 0.006), was least in Group A (OD = 0.045 ± 0.005). Discussion and Conclusion: Our study revealed that Indians with type 2DM are in a pro-inflamematory state. Low bodyweight type 2 diabetics had the least pro-inflammatory load. This further supported the earlier observation of lesser macrovascular disease load and testifying that Low Bodyweight type2DM constitutes a distinct entity.
Assuring the Correctness of Large-Scale Adaptive Systems

The next generation of software systems includes systems composed of a large number of distributed, decentralized, autonomous, interacting, cooperating, organically grown, heterogeneous, and continually evolving subsystems, which we call IT Ecosystems. Clearly, we need novel models and approaches to design and develop such systems which can tackle the long-term evolution and complexity problems. In this paper, our framework to model IT-Ecosystems is a combination of top-down (centralized control) and bottom-up (self-organizing) approach. We use a flexible formal model, hierarchical PobSAM, that supports both behavioral and structural adaptation/evolution. We use a detailed, close to real-life, case study of a smart airport to show how we can use hierarchical PobSAM in modeling, analyzing and developing an IT Ecosystem. We provide an executable formal specification of the model in Maude, and use LTL model checking and bounded state space search provided by Maude to analyze the model. We develop a prototype of our case study designed by hierarchical PobSAM using Java and Ponder2. Due to the complexity of model, we can not check all properties at design time using Maude. We propose a new approach for run-time verification of our case study, and check different types of properties which we could not verify using model checking. As our model uses dynamic policies to control the behavior of system which can be modified at runtime, it provides us a suitable capability to react to the property violation by modification of policies.
Understanding language change: Frontmatter

Preface and acknowledgements 1. Introduction 2. Three views of sound change 3. Sound change 2 - the implementation problem 4. Morphological change 5. Syntactic change 1 - the Transparency Principle 6. Word order change and grammaticalisation: language change and general laws 7. Semantic and lexical change 8. Language contact 9. Linguistic variation 10. Pidgins and creoles 11. Language death 12. Linguistic evolution? Bibliography Index.
The Nutritional Revolution

disease two months before my seeing him, and presented the typical signs of the disease: insomnia, anorexia, wasting, photophobia, profuse sweating, blue and swollen extremities, etc. The mother brought him on account of cough with vomiting, and I suspected pertussis. I prescribed chloromycetin, 50 mg. in capsules four-hourly, to be given in syrup, and this was kept up for the 14 days he remained in my care. During this time he commenced to take regular feeds. His photophobia disappeared. He slept well, gained weight, and in fact ceased to be the miserable child he was when first seen. I thought perhaps this was due in part to change of air and environment, and did not feel inclined to give the medical aspect the whole credit for the improvement. Since then, however, I have had another almost exactly similar case. The child, a girl aged I year, was diagnosed in hospital as pink disease two months previously. She developed pertussis, and again I gave the same dosage as in the previous case, 50 mg. four-hourly. I can say quite definitely that the child was much better when examined a week or two later, and apart from slight insomnia all the earlier severe symptoms had disappeared. She is now quite well. This case was particularly interesting because an older brother who was breast-fed developed acrodynia at five months. My present patient was bottle-fed and her symptoms occurred after an acute influenzal bronchitis at the seventh month.
Exploring the Reference Management in Parallel De-Duplication

As the explosion of digital information in network, data de-duplication has been widely used in most backup systems to improve space efficiency. When only unique data segments are stored and shared by backup files, the reference information between the files and their data segments is becoming more and more important to track the data usage and reclaim of freed space. However, as the usage of multi-core and many-core, genereal Group Mark-and-Sweep method has some poor performance in concurrent reference updates due to the synchronization overhead. To alleviate this challenge, a Parallel Mark-and-Sweep mechanism has been exploied based on the research of DHT and similrity method. In our experiments with real-world datasets, it has shown a better performance comparing to the sequential method.
Tree structured filter bank for time-frequency decomposition of EEG signals

A simple tree structured multirate filter bank geometry specifically tailored for EEG time-frequency analysis is presented. The whole structure is based on only one IIR allpass filter. It is computationally efficient and can be easily adaptable to different sampling rates. Octave band subband decomposition of EEG signals is obtained with final subbands in the filter bank tree closely approximating domains of characteristic EEG rhythms. The proposed structure is useful for EEG compression through subband coding and EEG rhythm identification in real time based on energy distribution in subbands.
Geographic Decomposition of the Shortest Path Problem, with an Application to the Traffic Assignment Problem

An algorithm, which can be applied to loosely connected networks, is given for geographically decomposing the shortest path problem. The algorithm is applicable to the traffic assignment problem when it is solved as a series of shortest path problems by the Frank-Wolfe algorithm. Numerical results for a large 1287 node, 3752 arc traffic assignment problem for Washington, D.C., indicate that using geographical decomposition can reduce computer memory storage requirements or program run time.
Efficient Laser Cooling of 85Rb Atoms to the Recoil Temperature Limit

We demonstrate laser cooling of 85Rb atoms in a two-dimensional optical lattice. We follow the two-step degenerate Raman sideband cooling scheme, Kerman el al., Phys. Rev. Lett. 84, 439 (2000), where a fast cooling of atoms to an auxiliary state followed by a slow cooling to a dark state. This method has the advantage of independent control of the heating rate and cooling rate from the optical pumping beam. We operate the lattice at Lamb-Dicke parameter eta=0.45 and show the cooling of spin-polarized 85Rb atoms to the recoil temperature in both dimension within 2.4 ms with 90% of initial atom numbers.
Surface-Enhanced Raman Spectra of Aflatoxin B1 Adsorbed on Silver Clusters

: The structures, surface-enhanced Raman scattering (SERS), and pre-resonance Raman spectra (SERRS) of Aflatoxin B 1 (AFB 1 )-Ag n ( n =2, 4, 6) complexes were calculated using density functional theory (DFT) with the B3LYP/6-311G( d , p ) (C, H, O)/LanL2DZ (Ag) basis set. The results show that the SERS enhancement factors were about 10 2 -10 3 for the AFB 1 -Ag n ( n =2, 4, 6) complexes, respectively. This is due to the C ＝ O stretch of the pyran ring and the larger static polarizability of the three complexes. The SERS spectra were consistent with the experimental results. The SERRS spectra of the three complexes were obtained by excitation at 407.5, 446.2, and 411.2 nm, which were close to the electronic excitation energy of absorption spectra as determined by time-dependent density functional theory (TDDFT). The SERRS enhancement factors caused by the charge-transfer excitation resonance were about 10 4 , which corresponds to the Ag ― O stretching.
The Fast Convolution Neural Networks Applied to License Plate Recognition

In this paper, we propose a fast convolution neural network architecture to solve image document recognition problem, and this is a difficult problem because of ambient lighting conditions, and the images are usually noisy, broken or incomplete. We applied to license plate recognition and also analyzed the results of this mapping process and the number of different features.