Miracle-dz/UniFAR-FTUs huggingface dataset:
Development of Ultra-Wideband Short-Range Impulse Radar System for Vehicular Applications

This paper introduces a state-of-art on an ultra-wideband (UWB) technology in intelligent transport systems (ITS). To examine the detection performance of a UWB short-range radar for vehicular applications, we developed a 26-GHz band short-range UWB radar system with an embedded compact MMIC-based RF module. In this paper, we briefly comment on the current regulatory environment for UWB radar systems by outlining the structure of an international organization involved in examining the regulatory status of these systems. We then describe the principles of detection and system design for impulse radar, the radar system that we developed, and a MMIC-based RF module as well as the performance of these devices. We measured their performance in a series of laboratory experiments and also measured UWB radar cross sections of an automobile. The results of our experiments suggest that our radar system is capable of detecting targets with a range resolution of around 9 cm. key words: impulse radar, ultra wideband, UWB, vehicular, system, laboratory experiment, intelligent transport system, ITS
Source time scale and optimal buffer/bandwidth trade-off for regulated traffic in an ATM node

In this paper we study the problem of resource allocation and control for an ATM node with regulated traffic. Both guaranteed lossless service and statistical service with small loss probability are considered. We investigate the relationship between source characteristics and the buffer/bandwidth trade-off under both services. Our contributions are the following. For guaranteed lossless service, we find that the optimal resource allocation scheme suggests a time scale separation of sources sharing an ATM node with finite bandwidth and buffer space, and the optimal buffer/bandwidth trade-off is determined by the sources' time scale. For statistical service with a small loss probability, we present a new approach for estimating the loss probability in a shared buffer multiplexor with the so called "extremal" on-off periodic sources. Under this approach, the optimal resource allocation for statistical service is achieved by maximizing both the benefits of buffering sharing and bandwidth sharing. The optimal buffer/bandwidth trade-off is again determined by time scale separation.
The Impacts of Software Engineering Organization and CMMI Implementation: A study from an Organizational Culture Perspective

This paper presents two case studies to theorize how project team culture in software engineering organizations affects CMMI implementation from an organizational culture framework. We contend that CMMI implementation success is positively related to project team culture along the eight dimensions of organizational culture, such as orientation to horizon. The results indicate the extent of the impact of project team culture on CMMI implementation. In addition, we develop a cultural construction that shows the dimensions of culture that best facilitate a strong project team culture in CMMI implementation. Possible research questions on which future research can be based are also identified. Managerial relevance statement This paper proposed cultural construction and research model arising from data collected in our two case studies in practice extend theory about the impact upon CMMI implementation. They provide a theoretically grounded basis upon which future research can be built. Findings of this paper suggest that CMMI implementation project teams are influenced, but not necessarily bound by existing organizational culture. Moreover, CMMI is often implemented to support change in the fundamental structure of an organization, it can also require or bring about changes in the underlying organizational culture to support the integration in a software engineering organization. Furthermore, the requirements for the impact do not stop with the implementation. Therefore, rather than forming a sub-culture, the initiatives that CMMI implementation project teams pursue in order to conquer cultural obstacles to the impact on the team during implementation may actually form the framework for changes in the broader organizational culture in a software engineering organization.
Discovery and Genomic Characterization of a Novel Ovine Partetravirus and a New Genotype of Bovine Partetravirus

Partetravirus is a recently described group of animal parvoviruses which include the human partetravirus, bovine partetravirus and porcine partetravirus (previously known as human parvovirus 4, bovine hokovirus and porcine hokovirus respectively). In this report, we describe the discovery and genomic characterization of partetraviruses in bovine and ovine samples from China. These partetraviruses were detected by PCR in 1.8% of bovine liver samples, 66.7% of ovine liver samples and 71.4% of ovine spleen samples. One of the bovine partetraviruses detected in the present samples is phylogenetically distinct from previously reported bovine partetraviruses and likely represents a novel genotype. The ovine partetravirus is a novel partetravirus and phylogenetically most related to the bovine partetraviruses. The genome organization is conserved amongst these viruses, including the presence of a putative transmembrane protein encoded by an overlapping reading frame in ORF2. Results from the present study provide further support to the classification of partetraviruses as a separate genus in Parvovirinae.
A Robot Implementation of a Biologi ally Inspired Method for Novelty Dete tion

This work examines the ability of a biologi ally inspired novelty dete tion model to learn and dete t hanges in the environmentof a mobile robot. The novelty dete tion model used was inspired by re ent neurologi al (cid:12)ndings of novelty neurons in monkeys' perirhinal orti es. Experiments examine the di(cid:11)eren e required between stimuli before the novelty dete tion model re ognises them as novel and the ability of the model to learn its environment on-line. The novelty dete tion model examined in this paper is based on al ulating the energy of a Hop(cid:12)eld network. It appears to be potentially useful for on-line learning on mobile robots as it an reliably learn from a single presentation of a novel stimuli. A qualitative omparison is made to an alternative model that also arries out novelty dete tion on a mobile robot.
Development of Audio Sensing Technology for Ambient Assisted Living: Applications and Challenges

One of the greatest challenges in Ambient Assisted Living is to design health smart homes that anticipate the needs of its inhabitant while maintaining their safety and comfort. It is thus essential to ease the interaction with the smart home through systems that naturally react to voice command using microphones rather than tactile interfaces. However, efficient audio analysis in such noisy environment is a challenging task. In this paper, a real-time audio analysis system, the AuditHIS system, devoted to audio analysis in smart home environment is presented. AuditHIS has been tested thought three experiments carried out in a smart home that are detailed. The results show the difficulty of the task and serve as basis to discuss the stakes and the challenges of this promising technology in the domain of AAL.
Molecular Properties and Functional Divergence of the Dehydroascorbate Reductase Gene Family in Lower and Higher Plants

Dehydroascorbate reductase (DHAR), which reduces oxidized ascorbate, is important for maintaining an appropriate ascorbate redox state in plant cells. To date, genome-wide molecular characterization of DHARs has only been conducted in bryophytes (Physcomitrella patens) and eudicots (e.g. Arabidopsis thaliana). In this study, to gain a general understanding of the molecular properties and functional divergence of the DHARs in land plants, we further conducted a comprehensive analysis of DHARs from the lycophyte Selaginella moellendorffii, gymnosperm Picea abies and monocot Zea mays. DHARs were present as a small gene family in all of the land plants we examined, with gene numbers ranging from two to four. All the plants contained cytosolic and chloroplastic DHARs, indicating dehydroascorbate (DHA) can be directly reduced in the cytoplasm and chloroplast by DHARs in all the plants. A novel vacuolar DHAR was found in Z. mays, indicating DHA may also be reduced in the vacuole by DHARs in Z. mays. The DHARs within each species showed extensive functional divergence in their gene structures, subcellular localizations, and enzymatic characteristics. This study provides new insights into the molecular characteristics and functional divergence of DHARs in land plants.
Assessing Readability of Consumer Health Information: An Exploratory Study

Researchers and practitioners frequently use readability formulas to predict the suitability of health-related texts for consumers (e.g., patient instructions, informed consent documents). However, the appropriateness of using readability formulas originally developed for students and educational texts for lay audiences and health-related texts remains to be validated. In this exploratory study, we compared two methods of assessing the readability of consumer health materials: the Cloze procedure, using actual readers, and readability formulas, using our Readability Analyzer program. A statistically significant inverse correlation (r = -0.581, p = 0.01) was found, suggesting that the Readability Analyzer may provide a reasonable "first approximation" for predicting readability of consumer health texts. We also identified several linguistic factors associated with increased reading ease as candidates for improving the performance of the Readability Analyzer. Our ultimate objective is to develop tools to support the design and evaluation of health information that is comprehensible and accessible to laypersons.
Aging and Decision-Making Competence

Around the world, average life expectancy is increasing. Adults of all ages face important decisions that affect their life outcomes and overall well-being. This paper reviews recent developments in research on age differences in decision-making competence. The measurement of age differences in decision-making competence is grounded in normative theories of decision making, which posit how people should be making decisions, as well as descriptive research, which aims to examine how people actually make decisions. Studies on age differences in decision making have shown mixed patterns of results, perhaps because of having included a wide range of decision-making competence tasks. Each decision task may rely on a different combination of skills, with some showing age-related declines and others showing no change or improvements with age. Here, I discuss the potential skills that may contribute to making good decisions, including cognitive deliberation, experience, emotions, and motivation. Although fluid cognitive abilities that underlie cognitive deliberation are known to decline with age, the others show different developments with age. I also discuss potential interventions that aim to target cognitive deliberation, experience, emotions, and motivation, so as to promote better decisions and associated life outcomes across the life span.
Phenolic Content and Antioxidant Activities of Burr Parsley (Caucalis platycarpos L.)

Since C. platycarpos contains a wide variety of antioxidants, in the present study total flavonoid and phenolic acid content as well as antioxidative activity of various C. platycarpos extracts were investigated. The results obtained show a significant polyphenol content and antioxidant activity of the investigated plant. Moreover, a positive correlation between antioxidant activity and content of flavonoids and phenolic acids was found, indicating the responsibility of these compounds for the antioxidant effectiveness of C. platycarpos extracts and making C. platycarpos a good potential source of natural antioxidants.
A New Queuing Policy for Delay Tolerant Networks

there has been much research activity in the area of Delay Tolerant Networks (DTNs). Routing is one of the key components in the DTN architecture. DTNs operate with the principle of store, carry and forward. According to this principle, a node may store a message in its buffer and carry it along, until it can forward it further. The message transmission occurs only when nodes come into the communication range of each other. Mobility of the nodes shortens the contact duration. It may not be possible for a node to transmit all messages it has during the available period of contact. Therefore decision has to be made on the order of messages to be transmitted. Similarly, in order to cope up with long disconnections, messages are buffered for a long period of time. Once the buffer capacity is reached, nodes must decide on the message to be dropped. Thus a new queuing policy has been proposed in this paper which takes care of both. The proposed policy considers the class of service and the expiration time for making such decisions. The Delay Tolerant Networks with random behavior is considered in this paper. Therefore epidemic routing which is the better choice for such network has been used for evaluation. The simulation results show that the new policy outperforms existing policy in terms of delivery ratio and delivery latency with preferential delivery.
Exploiting a Bootstrapping Approach for Automatic Annotation of Emotions in Texts

The objective of this research is to develop a technique to automatically annotate emotional corpora. The complexity of automatic annotation of emotional corpora still presents numerous challenges and thus there is a need to develop a technique that allow us to tackle the annotation task. The relevance of this research is demonstrated by the fact that people's emotions and the patterns of these emotions provide a great value for business, individuals, society or politics. Hence, the creation of a robust emotion detection system becomes crucial. Due to the subjectivity of the emotions, the main challenge for the creation of emotional resources is the annotation process. Thus, with this staring point in mind, the objective of our paper is to illustrate an innovative and effective bootstrapping process for automatic annotations of emotional corpora. The evaluations carried out confirm the soundness of the proposed approach and allow us to consider the bootstrapping process as an appropriate approach to create resources such as an emotional corpus that can be employed on supervised machine learning towards the improvement of emotion detection systems.
Improved Analysis of List Decoding and Its Application to Convolutional Codes and Turbo Codes

A list decoder generates a list of more than one codeword candidates, and decoding is erroneous if the transmitted codeword is not included in the list. This decoding strategy can be implemented in a system that employs an inner error correcting code and an outer error detecting code that is used to choose the correct codeword from the list. Probability of codeword error analysis for a linear block code with list decoding is typically based on the "worst case" lower bound on the effective weights of codewords for list decoding evaluated from the weight enumerating function of the code. In this paper, the concepts of generalized pairwise error event and effective weight enumerating function are proposed for evaluation of the probability of codeword error of linear block codes with list decoding. Geometrical analysis shows that the effective Euclidean distances are not necessarily as low as those predicted by the lower bound. An approach to evaluate the effective weight enumerating function of a particular code with list decoding is proposed. The effective Euclidean distances for decisions in each pairwise error event are evaluated taking into consideration the actual Hamming distance relationships between codewords, which relaxes the pessimistic assumptions upon which the traditional lower bound analysis is based. Using the effective weight enumerating function, a more accurate approximation is achieved for the probability of codeword error of the code with list decoding. The proposed approach is applied to codes of practical interest, including terminated convolutional codes and turbo codes with the parallel concatenation structure
Decision based Resource Selection in Grid Environment

Grid computing allows users to locate computing resources and data dynamically during the computation. One of the main challenges in Grid computing is efficient selection of resources for the tasks submitted by users. Resource Selection is the most crucial phase in grid scheduling and resource management. The goal of selection is to identify list of authenticated resources that are available in the grid for job submission and to choose the best node. The challenges for the best resource selection involve analysis of several factors such as prediction time to run a job, access restriction to resources, and cost to use resources. In this paper we present a DBRS (Decision based Resource Selection) architecture that combines these influential factors and make the resource selection process more effective. We proposed the decision-making process which includes time utility function, price utility function and resource assessment and based upon these values we calculate multi attribute value. Then according to the multi utility
QoS routing design for adaptive streaming in Software Defined Network

Adaptive streaming over HTTP(DASH) is a popular method to deliver best possible quality media using available network resources. In this paper we propose QoS routing algorithm design for providing high quality and continuous stream of media streaming in SDN(Software Defined Network). To provide seamless DASH service over SDN is a challenge because traditional DASH service manner mismatches with SDN per-flow centralized management architecture. Therefore, it is necessary to have some interactions between communication layers for making routing decision. Firstly, we propose server driven bit rate estimation approach to computes video bit rate and inform the application QoS requirement to the control layer. The media server estimates the resources available and dynamically adapts the video bit rate in order to reduce additional software stacks on end-user devices. We also present a Kalman Filter based rate adaptation mechanism that predicts the next bit rate of the media in a seamless manner. Secondary, we propose a QoS routing design for adaptive stream, it allows SDN controller evaluates all passable paths based on whole network topology by taking the bit rate of the segments in to account. We perform an experiment and presented the server driven bandwidth estimation mechanism to compute the appropriate bit rate and rate switching in smooth manner. We also construct a SDN testbed for QoS routing algorithm for adaptive streaming, it shows additional reroute step to find path that satisfy the bitrate before downgrade the video quality.
Searching and mining the web for personalized and specialized information

With the rapid growth of the Web, users are often faced with the problem of information overload and find it difficult to search for relevant and useful information on the Web. Besides general-purpose search engines, there exist some alternative approaches that can help users perform searches on the Web more effectively and efficiently. Personalized search agents and specialized search engines are two such approaches. The goal of this research is to investigate how machine learning and artificial intelligence techniques can be used to improve these approaches.
The Birth and Death of the Orange Book

This article traces the origins of US government-sponsored computer security research and the path that led from a focus on government-funded research and system development to a focus on the evaluation of commercial products. That path led to the creation of the Trusted Computer System Evaluation Criteria (TCSEC), or Orange Book. The TCSEC placed great emphasis on requirements for mandatory security controls and high assurance, and the resulting TCSEC evaluation process was time-consuming and costly for commercial vendors and emphasized product features not valued by customers. As a result, vendor commitment to evaluations waned. The TCSEC was eventually supplanted by the international Common Criteria, which after almost 15 years, have moved to a model based on more straightforward requirements and a more deterministic evaluation process.
A probabilistic approach to building change detection

Among different remote sensing applications, change detection deserves specific consideration. The importance of this area is its applicability on damage assessment after natural disasters. Fortunately, recent sensors allow researchers to develop advanced change detection methods. Some of these benefit from panchromatic or multispectral remote sensing images, whereas others use 3D data besides the 2D information. In this study, we benefit from both 2D and 3D data to detect changes in buildings. We specifically focused on building change detection, since after a natural disaster damaged building information is one of the most important one. Our building change detection method is based on our previous study based on probabilistic building detection. In this study, we first extract corner points using the Harris corner detector from panchromatic images. These corner points are used on Digital Surface Model (DSM) data to estimate possible building locations. To do so, we represent possible building locations via a kernel based density estimation method. In this study, we use the difference of the bitemporal estimated kernel maps (obtained in two different times) for change detection. Then, we apply a morphology based shape refinement method. As a result, we can detect changes in the scene. We tested our method on WorldView-2 sensor images with 780 buildings. The results are promising.
Striatal dopamine D2 receptor availability predicts the thalamic and medial prefrontal responses to reward in cocaine abusers three years later

Low levels of dopamine (DA) D2 receptor availability at a resting baseline have been previously reported in drug addicted individuals and have been associated with reduced ventral and dorsal prefrontal metabolism. The reduction in DA D2 receptor availability along with the reduced ventral frontal metabolism is thought to underlie compromised sensitivity to nondrug reward, a core characteristic of drug addiction. We therefore hypothesized that variability in DA D2 receptor availability at baseline will covary with dynamic responses to monetary reward in addicted individuals. Striatal DA D2 receptor availability was measured with [11C]raclopride and positron emission tomography and response to monetary reward was measured (an average of three years later) with functional magnetic resonance imaging in seven cocaine‐addicted individuals. Results show that low DA D2 receptor availability in the dorsal striatum was associated with decreased thalamic response to monetary reward; while low availability in ventral striatum was associated with increased medial prefrontal (Brodmann Area 6/8/32) response to monetary reward. These preliminary results, that need to be replicated in larger sample sizes and validated with healthy controls, suggest that resting striatal DA D2 receptor availability predicts variability in functional responses to a nondrug reinforcer (money) in prefrontal cortex, implicated in behavioral monitoring, and in thalamus, implicated in conditioned responses and expectation, in cocaine‐addicted individuals. Synapse 64:397–402, 2010. © 2009 Wiley‐Liss, Inc.