Miracle-dz/UniFAR-FTUs huggingface dataset:
Cross Entropy Algorithm for Joint Precoding and Transmit Antenna Selection in Multiuser MIMO Systems with Limited Feedback

This paper considers the joint precoding and transmit antenna selection to reduce the hardware cost such as the radio-frequency (RF) chains associated with antennas in the downlink of multi-user multi-input multi-output (MU-MIMO) systems with limited feedback. The joint precoding and transmit antenna selection algorithm requires an exhaustive search (ES) of all possible combinations and permutations to find the optimum solution at transmitter, thus resulting in extremely high computational complexity. In order to reduce the computational load while still maximizing channel capacity, the cross entropy (CE) method is addressed to determine sub-optimum solution. Compared with the conventional genetic algorithm (GA) and random search method, simulation results show that the CE method provides not only a better performance but also a lower computational complexity.
A Hub Architecture for Service Ecosystems - Towards Business-to-Business Automation with an Ontology-enabled Collaboration Platform

The management and coordination of business process collaboration experiences changes because of globalization, specialization, and innovation. Service-oriented computing (SOC) is a means towards businessprocess automation and recently, many industry standards emerged to become part of the service-oriented architecture (SOA) stack. In a globalized world, organizations face new challenges for setting up and carrying out collaborations in semi-automating ecosystems for business services. A need emerges for service Hubs that not only store service offers and requests together with their issuing organizations and assigned owners, but that also allow an evaluation of trust and reputation in an anonymized electronic service marketplace. In this paper, we explore the features of a semi-automating ecosystem in which business processes are expressed as services and where Hubs are essential for bringing together service offers and requests. The presented Hub architecture is designed so that business managers benefit from an interface that borrows concepts of socialnetworking sites while the complex computing machinery for matching service offers and requests remains hidden from the user. The partial implementation of service-Hub components demonstrate the feasibility of
Challenges of applying DTN routing protocols in realistic disaster scenarios

Delay Tolerant Networks (DTNs) are used to deliver messages in cases of intermittent connectivity. Disaster scenarios with multiple Mobile Ad hoc Networks formed by the communication equipment of first responders are one example for such networks. In this paper, we evaluate different delay tolerant routing schemes based on realistic mobility models and traffic patterns. Both options are crucial as the routing schemes usually exploit the movement of the nodes in order to deliver the messages. Our results show that the choice of a routing protocol has an impact on the experienced delay, but a DTN-based communication system should also provide the necessary contact opportunities. Therefore, we present a solution to integrate additional nodes and efficient routing to address this.
Relying on the Information of Interested—and Potentially Dishonest—Parties

This paper investigates the role of evidence production in the regulation of private behavior via judicial and administrative process. The paper presents a model in which the law makes the agent's fine depend on the presentation of evidence whose production cost, in turn, depends on how the agent has behaved in the regulated activity. The targeted behavior becomes more privately beneficial to the agent to the extent that it reduces the agent's evidence costs and so improves its highest obtainable payoffs (net of costs) at the subsequent hearing. This view of evidence production has several notable implications, including that truth-finding has no direct role in deterrence, that non-falsifiable evidence, even when available, is unlikely to be the best choice for the system, and that "overdeterrence" may well be cost effective.
Identifying Decision Makers from Professional Social Networks

Sales professionals help organizations win clients for products and services. Generating new clients starts with identifying the right decision makers at the target organization. For the past decade, online professional networks have collected tremendous amount of data on people's identity, their network and behavior data of buyers and sellers building relationships with each other for a variety of use-cases. Sales professionals are increasingly relying on these networks to research, identify and reach out to potential prospects, but it is often hard to find the right people effectively and efficiently. In this paper we present LDMS, the LinkedIn Decision Maker Score, to quantify the ability of making a sales decision for each of the 400M+ LinkedIn members. It is the key data-driven technology underlying Sales Navigator, a proprietary LinkedIn product that is designed for sales professionals. We will specifically discuss the modeling challenges of LDMS, and present two graph-based approaches to tackle this problem by leveraging the professional network data at LinkedIn. Both approaches are able to leverage both the graph information and the contextual information on the vertices, deal with small amount of labels on the graph, and handle heterogeneous graphs among different types of vertices. We will show some offline evaluations of LDMS on historical data, and also discuss its online usage in multiple applications in live production systems as well as future use cases within the LinkedIn ecosystem.
Topic-Level Extractive Summarization of Lectures and Meetings Using a Snippet Similarity Graph

In this paper, we present an approach for topic-level video snippet-based extractive summarization, which relies on con tent-based recommendation techniques. We identify topic-level snippets using transcripts of all videos in the dataset and indexed these snippets globally in a word vector space. Generate snippet cosine similarity scores matrix, which are then utilized to compute top snippets to be utilized for summarization. We also compare the snippet similarity globally across all video snippets and locally within a video snippets. This approach has performed well on the AMI meeting corpus, in terms of ROUGE scores compare to state-of-the-art methods. Experiments showed that corpus like AMI meeting has large overlap between global and local snippet similarity of 80% and the ROUGE scores are comparable. Moreover, we applied proposed TopS summarizer in dierent scenarios on Video Lectures, to emphasize the merits of ease in utilizing summarizer with such content-based recommendation technique.
A Modified Differential Evolution Multi-objective Optimization Method

Differential Evolution (DE) is population based, direct search, global optimization new algorithm. DE is simple and efficient, so solving Multi-objective Optimization Problems (MOP) using DE has become a new hot research topic. It was found in the research process that there are deteriorations in the process of solving MOP based on DE. Due to deterioration occurs, thus the convergence can no longer be guaranteed for the algorithm, and the efficiency is reduced for solving. This paper proposed resolve methods correspond to these two deteriorations. Numerical experiments show the effectiveness of the proposed algorithm.
A Systematic Search for Gravitationally Lensed Arcs in the Hubble Space Telescope WFPC2 Archive

We present the results of a systematic search for gravitationally lensed arcs in clusters of galaxies located in the Hubble Space Telescope Wide Field and Planetary Camera 2 data archive. By carefully examining the images of 128 clusters we have located 12 candidate radial arcs and 104 tangential arcs, each of whose length-to-width ratio exceeds 7. In addition, 24 other radial arc candidates were identified with a length-to-width ratio of less than 7. Keck spectroscopy of 17 candidate radial arcs suggests that contamination of the radial arc sample from nonlensed objects is ~30%-50%. With our catalog, we explore the practicality of using the number ratio of radial to tangential arcs as a statistical measure of the slope β of the dark matter distribution in cluster cores (where ρDM ∝ r-β at small radii). Despite the heterogeneous nature of the cluster sample, we demonstrate that this abundance ratio is fairly constant across various cluster subsamples partitioned according to X-ray luminosity and optical survey depth. We develop the necessary formalism to interpret this ratio in the context of two-component mass models for cluster cores. Although the arc statistics in our survey are consistent with a range of density profiles—β ≲ 1.6 depending on various assumptions—we show that one of the prime limiting factors is the distribution of stellar masses for the brightest cluster galaxies. We discuss the prospects for improving the observational constraints and thereby providing a reliable statistical constraint on cluster dark matter profiles on ≲100 kpc scales.
Open Innovation strategy : Exploring challenges and opportunities

Innovation strategy has been playing an important role on innovation development in industrial firms. Extant studies have investigated in particular open innovation strategy. By using a qualitative case study, I have conducted a research in an Indonesian R&D firm that has implemented an open innovation strategy. The purpose of this research is to add more information and confirm existing knowledge by exploring challenges and opportunities during the implementation of an open innovation strategy. I identify many challenges which are found in several aspects of innovation development such as collaboration management, assets protection and accessing external knowledge. Furthermore, the opportunities that I found are related with enhancement of license strategy, nurture of employee’s loyalty and establishment of various collaboration forms. These challenges and opportunities occurred due to the influence of the openness paradigm. The results of this study also confirm previous research result on the adoption of the partly open innovation scheme and the layered collaboration scheme.RQ: what are the firm-level challenges and opportunities with using an open innovation strategy?
Differences of image classification techniques for land use and land cover classification

Land use and land cover classification of remotely sensed data is an important research and commonly used in remote sensing application. In this study, the different types of classification techniques were used by using satellite image of some part of Selangor, Malaysia. For this objective, the land use and land cover was classified with Landsat 8 satellite image and ERDAS Imagine software as the image processing packages. From the classification output, the accuracy assessment and kappa statistic were evaluated to get the most accurate classifier. The optimal performance would be identified by validating the classification results with ground truth data. Of classified image, the Maximum Likelihood technique (overall accuracy 82.5%) is the highest and more applicable for satellite image classification compared with Mahalanobis Distance and Minimum Distance. The accurate classification can produce the correct Land Use and Land Cover map that can be used for many varieties purposes.
A new edge detector based on fractional integration

In computer vision and image processing, the Canny edge detector algorithm is the most widely implemented from performance point of view. In this paper, attempting to reduce the computational time of this algorithm on skipping the smoothing step, a fractional integral mask (FIM) is introduced and investigated. It has been shown that the smoothing operation can be omitted when simply convolving the image with our new FIM instead of using integer gradient masks. The efficiency of our FIM is interpreted in term of the running time, robustness to noise, and the potentiality of detecting week edges. The results of simulation show how the quality of edge detection can be enhanced when the fractional factor could be fine tuned. The FIM is a prominent tool which can take part in multispectral images segmentation in the field of satellite imaging.
Novel NKX2-5 mutations responsible for congenital heart disease

Objective Congenital heart disease (CHD) is the most common birth defect and is the leading cause of infant morbidity and mortality resulted from various birth defects. Increasing evidence demonstrates that genetic variation in the NKX2-5 gene, which encodes a homeobox-containing transcription factor crucial to cardiogenesis, is an important molecular determinant for CHD. Nevertheless, the genetic components underlying CHD in a significant portion of patients remain largely unknown. In this study, we sought to screen NKX2-5 for potential molecular defects in patients with CHD. Methods The entire coding region of NKX2-5 was sequenced initially in a cohort of 268 unrelated patients with CHD. The relatives of the patients carrying identified mutations and 200 unrelated control individuals were subsequently genotyped. Results Three novel heterozygous missense NKX2-5 mutations, p.Q22K, p.R36S, and p.E54K, were identified in 3 families with autosomal dominantly inherited atrial septal defect, ventricular septal defect, and tetralogy of Fallot, respectively. Absent in 200 control individuals, these mutations were highly conserved evolutionarily and co-segregated with CHD in the families with complete penetrance. Conclusion The findings expand the spectrum of mutations in NKX2-5 linked to CHD and provide new insight into the molecular aetiology involved in the pathogenesis of CHD, which signifies potential implications for genetic diagnosis and gene-specific therapy for this common disease in the young.
University of Oklahoma Graduate College Learning Grasp Affordances Learning Grasp Affordances a Thesis Approved for the School of Computer Science Brian Watson for All of Their Help and Support. in Addition, I Would Also like to Thank

When presented with an object to be manipulated, a robot must identify the available forms of interaction. How might an agent acquire this mapping from object representation to action? In this thesis, I describe an approach that learns a mapping from objects to grasps through human demonstration and robot teleoperation. For a given object, the teacher demonstrates a set of feasible grasps. These example grasps are then clustered in terms of the pose of the hand and the configuration of the fingers. Individual clusters in this space are represented using probability density functions, and thus correspond to variations around canonical grasp types. Multiple clusters are captured through a mixture distribution-based representation. Experimental results demonstrate the feasibility of extracting a compact set of canonical grasps from the provided experience. Each of these canonical grasps can then be used to parameterize a reach controller that brings a robot hand into a specific spatial relationship with an object.
A Dialogue Environment for Accessing Public Administration Data: the TAMIC-P System

The purpose of this paper is to show that with a combination of state of art technologies it is possible to realize effective and powerful dialogue systems for Information-Seeking applications. TAMIC-P, a prototype natural language based interface will be described. The system is designed to support Public Administration desk operators during an information session with a citizen. Three aspects work together to determine the system's usability: (i) a strong multimodal approach, allowing full interchangeability between natural language and direct manipulation; (ii) a robust dialogue component, allowing complex sequences of turns; (iii) the adaptive integration of different information sources, such as personal data and related norms.
Designing Soni cation of User Data in A ective Interaction

Different design approaches contributed to what we see today as the prevalent design paradigm for Human Computer Interaction; though they have been mostly applied to the visual aspect of interaction. In this master's thesis it is presented a proposal for sound design strategies that can be used in applications involving affective interaction. The sonification of the Affective Diary, a digital diary with focus on emotions, affects, and bodily experience of the user is proposed for testing this approach. Results from studies in music and emotion were applied to sonic interaction design. This is one of the first attempts introducing different physics-based models for the real-time complete sonification of an interactive user interface in portable devices. Design av användarens data ljudsättning i affektiv interaktion
Blended UI Controls for Situated Analytics

This paper presents a context aware model for situated analytics, supporting a blended user interface. Our approach is a state-based model, allowing seamless transition between the physical space and information space during use. We designed the model to allow common user interface controls to work in tandem with the printed information on a physical object by adapting the operation and presentation based on a semantic matrix. We demonstrate the use of the model with a set of blended controls including; pinch zoom, menus, and details-on-demand. We analyze each control to highlight how the physical and virtual information spaces work in tandem to provide a rich interaction environment in augmented reality.
A NOVEL APPROACH FOR VITALITY CONSTRAINED CONTRAST ENHANCEMENT ALGORITHM USING SD-MSR

In this propose A Novel calculation for imperativeness obliged differentiation upgrade Algorithm utilizing SD-MSR . As a rule, MSR, which is the key segment of the proposed calculation, comprises of force controllable log operation and subbandwise increase control. To start with, we decay an info picture to MSRs of distinctive sub-groups, and figure a fitting addition for every MSR. Second, we apply a coarse-to-fine power control system, which recomputes the MSRs and additions. This step emphasizes until the target force sparing is precisely fulfilled. With feature successions, the differentiation levels of adjoining pictures are resolved reliably utilizing fleeting soundness as a part of request to abstain from glinting antiquities. At long last, we display a few improvement aptitudes for ongoing preparing. Test results demonstrate that the proposed calculation gives preferable visual quality over past techniques, and a steady powersparing degree without glimmering ancient rarities, actually for feature arrangements.
Register file partitioning and recompilation for register file power reduction

Register files in modern embedded processors contribute a substantial budget in the energy consumption due to their large switching capacitance and long working time. For some embedded processors, on average 25% of registers account for 83% of register file accessing time. This motivates us to partition the register file into hot and cold regions, with the most frequently used registers placed in the hot region, and the rarely accessed ones in the cold region. We employ the bit-line splitting and drowsy register cell techniques to reduce the overall register file accessing power. We propose a novel approach to partition the register in a way that can achieve the largest power saving. We formulate the register file partitioning process into a graph partitioning problem, and apply an effective algorithm to obtain the optimal result. We evaluate our algorithm for MiBench and SPEC2000 applications on the SimpleScalar PISA system, and an average saving of 58.3% and 54.4% over the nonpartitioned register file accessing power is achieved. The area overhead is negligible, and the execution time overhead is acceptable (5.5% for MiBench 2.4% for SPEC2000). Further evaluation for MiBench applications is performed on Alpha and X86 system.
Functional Analysis of GmCPDs and Investigation of Their Roles in Flowering

The onset of floral development is a pivotal switch in the life of soybean. Brassinosteroids (BRs), a group of steroidal phytohormones with essential roles in plant growth and development, are associated with flowering induction. Genes involved in BR biosynthesis have been studied to a great extent in Arabidopsis, but the study of these genes has been limited in soybean. In this study, four CPD homologs (GmCPDs) catalyzing BR synthesis were isolated from soybean. Transcripts were mainly confined to cotyledons and leaves and were down-regulated in response to exogenous BR. Bioinformatic analysis showed strong sequence and structure similarity between GmCPDs and AtCPD as well as CPDs of other species. Overexpression of GmCPDs in an Arabidopsis BR-deficient mutant rescued the phenotype by restoring the biosynthesis pathway, revealing the functional roles of each GmCPDs in. Except for the rescue of root development, leaf expansion and plant type architecture, GmCPDs in expression also complemented the late flowering phenotype of Arabidopsis mutants deficient in CPD. Further evidence in soybean plants is that the expression levels of GmCPDs in are under photoperiod control in Zigongdongdou, a photoperiod-sensitive variety, and show a sudden peak upon floral meristem initiation. Together with increased GmCPDs in expression in the leaves and cotyledons of photoperiod-insensitive early-maturity soybean, it is clear that GmCPDs in contribute to flowering development and are essential in the early stages of flowering regulation.
Wool price differences by preparation in the United States.

Price differences for U.S. wools by preparation and type were examined using data collected from warehouses and pool sales across the United States over the period 1993 to 2002. The goal was to determine premium/discounts in wool prices by preparation and type, controlling for season, year, region, average-fiber diameter, and lot size. Unlike previous research efforts, a hedonic model was used in this investigation. The hedonic price model explained about 83 percent of the variation in U.S. wool prices. Seasonality in U.S. clean wool prices was evident. Wool prices received by producers from January to March as well as from October to December were significantly lower from 5.9 percent to 17.4 percent than those prices in September. Wool prices in June were roughly 8 percent higher than those of September. In accord with prior expectations, U.S. clean wool prices were highest in 1995 and 1997. Prices in remaining years from 1993 to 2002 were significantly lower from 11.8 percent to 52.2 percent relative to the base year of 1997. Further, U.S. clean wool prices were discounted by 7.9 percent and 9.8 percent respectively, in the Eastern and Western regions of the United States relative to the Central region. In line with prior research, prices of table-skirted and classed wool were significantly higher than original bag wool by slightly more than 8 percent. Significant differences among wool types also were evident. In particular, U.S. clean prices of TSC and BOU Main Line Wool were higher by 23.5 percent over the OB wool breed. Significant differences were noted as well among wool types from OB. Among wool types, the premiums/discounts relative to OB wool breed type were quite large in magnitude. U.S. clean wool prices were sensitive to change in average diameter. The elasticity of clean price with respect to average fiber diameter was estimated to be roughly -1.42. Lot size, as measured by grease weight, also positively affected U.S. clean prices. The elasticity of clean price with respect to lot size was estimated as 0.16.