nils-herrmann/clean_scirepeval huggingface dataset:
Optimizing the Bit Transmission Power for Link Layer Energy Efficiency Under Imperfect CSI

In this paper, we study the issue of selecting the transmission power (energy per symbol) to minimize the expected energy required to successfully deliver a link-layer packet to the destination node in a wireless link performing the automatic repeat request. We consider the system that has a slow-fading channel and employs a minimum mean square error-based channel estimation scheme for a pilot symbol-assisted modulation. We derive a closed-form expression for the packet error probability (PkEP) in the presence of channel estimation error, and we use this expression for minimizing the PkEP in allocating the transmission energy among the pilot and data symbols. We also derive the expected energy required to successfully deliver a link-layer packet as a function of the transmission power and present an optimization method based on the properties of this function.
EMI improvement study on advanced package design

At the present time, the package design faces demands, including the high-speed switching, low-voltage bias and minimization. The high-speed signals may induce not only signal integrity and power integrity issues, but also cause radiation and electromagnetic interference (EMI) problems. To evaluate a package design, near-field scan is a useful technique to investigate the radiation behavior. Our study is based on this near-field approach to estimate the radiation of a package by using a simulation tool. Several factors were investigated in this study. From the near-field results, we could conclude some useful concepts for package layout design.
Back-End Deposited Silicon Photonics for Monolithic Integration on CMOS

We present the vision of back-end deposited silicon photonics (BDSP) and review works that have been done in this field. Individual aspects of BDSP platform including excimer-laser-annealed polycrystalline silicon, low-loss plasma-enhanced chemical vapor deposition silicon nitride waveguide, modulator, detector, electrical interface, back-end CMOS compatibility, and benefits of the platform are discussed in detail.
A novel constitutive parameter extraction technique using a single short circuit waveguide measurement

In this paper, a method was presented for accurately determining the complex CP of a material sample using a single SCL waveguide measurement. An analytic expression for the complex reflection coefficient at the reference plane of the waveguide serves as the forward problem in the novel MPSQP algorithm. The MPSQP is a very robust optimization technique which exploits the speed and accuracy of SQP while avoiding local minima trapping. This technique proves beneficial for several application areas including high temperature material characterization. At high temperatures, a considerable amount of time is devoted to changing terminations, and this process usually requires some amount of cooling and reheating of the sample. During this time, the sample may shift inside the waveguide which, in turn, may introduce errors into the measured data
Field test results of a modified flickermeter Block 5 processing algorithm

IEC TC77/SC77A/WG2 is poised to consider maintenance and revisions to IEC Standard 61000-4-15. Based on the results of multiple CIGRE Working Groups and literature publications, it appears that discrepancies between measured short-term flicker severity values and user complaints can be reduced by making modifications to the so-called Block 5 processing algorithm. For such modifications to be fairly considered in the revision of any standard, it is necessary to establish both theoretical and practical/application bases. Prior work has established theoretical bases for changes in Block 5; in this paper are reported the results obtained from modified algorithms used at multiple sites for extended periods of time. Particular attention has been paid to quantify the extent of the differences obtained from the practical perspective of flicker limit compliance.
Curved surface characterization in 3-D range images

A computational scheme is presented for obtaining a characteristic description of a free-form curved surface from 3-D range images whose natural modes are in the form of level (equidistance) contours. The novelty in this scheme is that dense surface contours are used to directly estimate the surface curvatures in a systematic fashion without having to explicitly or implicitly compute any partial derivatives. The principle of the scheme is described, and the framework of computational paradigm is outlined for a shape description (shape from level contours) of the free-form curved object from its local surface properties. The objective is to obtain an invariant viewpoint and stable representation that is useful in 3-D object reconstruction and recognition. Although the scheme is based on analysis of level contours, the computation model for shape representation is general and applicable to any dense range image.<<ETX>>
On the Performance of Imperfect Channel Estimation for Vehicular Ad-Hoc Networks

In this paper, we investigate the effect of imperfect channel estimation on the performance of inter-vehicular communication systems. In particular, we derive the bit error rate (BER) expression in the presence of channel estimation errors for a space-time block coded (STBC) inter-vehicular communication system based on cascaded Rayleigh fading. Our diversity analysis reveals that the underlying scheme is able to extract the full spatial diversity. Based on the derived BER expression, we formulate a power-allocation problem to optimally allocate power to both training and data transmission phases.
Optimization of call admission control for a statistical multiplexer allocating link bandwidth

For a bufferless statistical multiplexer allocating link bandwidth to a single class of connections with generally distributed call holding times, we study model-based call admission control (CAC) policies that map the number of calls in progress (state variable) to the admission decision (control variable). By formulating the CAC problem as a linear programming, establishing a convexity result, and applying the complementary slackness condition, we analytically prove that a randomized threshold CAC policy minimizes the call blocking probability subject to a packet loss quality-of-service requirement.
Worst average queueing delay of multiple leaky-bucket-regulated streams and jumping-window regulated stream

This paper presents deterministic, worst-case analysis of a queueing system whose multiple homogeneous input streams are regulated by the associated leaky buckets and the queueing system that has a single stream regulated by the jumping-window. Queueing delay averaged over all items is used for performance measure, and the worst-case input traffic and the worst-case performance are identified for both queueing systems. For the former queueing system, the analysis explores different phase relations among leaky-bucket token generations. This paper observes how the phase differences among the leaky buckets affect the worst-case queueing performance. Then, this paper relates the worst-case performance of the former queueing system with that of the latter (the single stream case, as in the aggregate streams from many users, whose item arrivals are regulated by one jumping-window). It is shown that the worst-case performance of the latter is identical to that of the former in which all leaky buckets have the same phase and have particular leaky bucket parameters.
A Programmable Laboratory Testbed in Support of Evaluation of Functional Brain Activation and Connectivity

An important determinant of the value of quantitative neuroimaging studies is the reliability of the derived information, which is a function of the data collection conditions. Near infrared spectroscopy (NIRS) and electroencelphalography are independent sensing domains that are well suited to explore principal elements of the brain's response to neuroactivation, and whose integration supports development of compact, even wearable, systems suitable for use in open environments. In an effort to maximize the translatability and utility of such resources, we have established an experimental laboratory testbed that supports measures and analysis of simulated macroscopic bioelectric and hemodynamic responses of the brain. Principal elements of the testbed include 1) a programmable anthropomorphic head phantom containing a multisignal source array embedded within a matrix that approximates the background optical and bioelectric properties of the brain, 2) integrated translatable headgear that support multimodal studies, and 3) an integrated data analysis environment that supports anatomically based mapping of experiment-derived measures that are directly and not directly observable. Here, we present a description of system components and fabrication, an overview of the analysis environment, and findings from a representative study that document the ability to experimentally validate effective connectivity models based on NIRS tomography.
An application of parametric speaker technology to bus-pedestrian collision warning

The purpose of this research is to address the problem of frequent bus-pedestrian accidents in dense urban areas through the creation of an intelligent pedestrian warning system. Our proposed system uses visual detection and parametric speaker technologies to provide a concise, focused beam of sound that reaches only the detected target while minimizing the amount of disruption and disturbance to neighboring areas. We believe that this solution will provide a minimally invasive, cost-effective method for avoiding bus-pedestrian collisions and substantially reducing the loss of life and property. In this paper, we first present a review and analysis of the relevant technologies and current implementations. Then, we provide a detailed overview of the system that we have developed, and discuss our tests and data collected. Finally, we conclude with a brief discussion of future engineering and cost considerations for implementation of this system in a practical setting.
JPEG 2000: Retrospective and New Developments

JPEG 2000 is a new image coding system that delivers superior compression performance and provides many advanced features in scalability, flexibility, and system functionalities that outperform all previous standards. It brings exciting possibilities to many imaging applications such as the Internet, wireless, security, and digital cinema. This paper gives an overview of this triumph in innovations and teamwork. It gives brief introductions to the four new parts that are under development by the JPEG committee. It attempts to summarize the lessons learned from the JPEG 2000 development experience and draw some conclusions on the success factors of this important standard.
Interior point-based optimization for joint admission control and routing in IP networks

For MPLS-like IP networks, we propose a novel and practically implementable optimal joint admission control and routing (JACR) mechanism for incoming trunk traffic classes with distinct QoS requirements. The proposed mechanism is based on interior point-based optimization techniques to solve the admission control/routing problem in large service provider networks. The significant contributions of our proposed mechanism are a) an efficient resource allocation mechanism that i) simultaneously satisfies both user QoS requirements and network provider's capacity and routing constraints and ii) engineers the usage of network resources efficiently by load-balancing and preventing hotspots from developing in the network, b) computationally efficient to make decisions within real-time call (flow) setup durations, c) scalability to network size and complexity and d) lends itself to a distributed implementation. The proposed mechanism runs in two distinct phases - phase-1 is the admission control and feasible route determination step and phase-2 is the optimal routing step. This structure provides flexibility to the service provider to implement this mechanism in its complete form or even implement it solely as an admission control/feasible route determination algorithm (i.e. use phase-1 only). Experimental results on large-size service provider network with 56 nodes, 117 links and 14 LSPs between an ingress-egress pair demonstrate that, for incoming traffic with diverse QoS requirements, the proposed mechanism is very efficient in determining admission and allocating network resources by optimal routing, all within real-time call setup times.
Symbol rate adaptation and blind rate detection using FOSSIL (forest for OVSF-sequence-set-inducing lineages)

We introduce a forest whose nodes represent orthogonal variable spreading factor (OVSF) code sequences of different lengths used for multi-rate CDMA. These code sequences have properties that facilitate symbol rate adaptation and blind rate detection, which can be used in a fast time-varying environment such as mobile communication systems. The properties of these codes also makes flexible the assignment of code sequences of different lengths to different users who communicates at different constant symbol rates. In particular, certain lineages in the forest have a property that the set of code sequences represented by such a lineage are cyclic orthogonal to each other with unit length being that of the shortest sequence in the set. We present the forest-structured generation of the code sequences and their properties. Then, we present a symbol rate adaptation protocol and a blind rate detection algorithm that use the code properties.
Entire domain basis functions on 2-D NURBS geometries

In a typical MoM solution, the scatterer is discretized into small elements, usually triangular patches. The MoM computes the interaction of equivalent surface currents existing on the patches, and as a result, produces a dense matrix. It is a well-known fact that the matrix fill is an extremely computationally intense task, consuming a large amount of memory and CPU time. Often, especially for problems of interest to the military, the computational requirements in both time and memory for the matrix fill are prohibitive. When this occurs, the user must turn to so-called fast methods such as Fast Multipole Method (FMM) , adaptive basis functions , and others.
Generalized CORDIC for digital signal processing

Many fast signal processing algorithms are based on a geometric framework and efficient implementations of these algorithms often require the computation of elementary functions involving such operations as vector rotations and exponentials. The CORDIC (COordinate Rotation Digital Computer) algorithms are the natural candidates for these elementary operations and they lead to novel realizations in many promising algorithms such as the square-root normalized ladder algorithms. FFT and several well-known matrix algorithms for signal processing. The development of algorithms involving nonstationary processes and the limiting constraints of VLSI motivate the extension of the CORDIC concept in other directions. It can be applied not only to one-parameter groups but to other Lie groups as well, i.e., higher dimensional manifolds, leading to generalized CORDIC algorithms. The computation of special functions is some of the potential benefits. Several such generalizations will be discussed.
Contextual IT Business Value and Barriers: An E-Government and E-Business Perspective

Recently public sector organizations embarked on their journey to create and realize business value through their e-government initiatives. Although the business value of IT has been studied extensively in the private sector environment, I believe e-business value templates that oftentimes rely on economical justifications should not be applied indiscriminately to the public sector. This paper submits that contextual nuances in the public sector such as criticality of political value propositions (i.e. unique IT success factor) and a distinct set of risk factors warrant an investigation into how e-government and e-business initiatives are each characterized by unique business value drivers and barriers. Preliminary meta-analysis on the recent business value of IT studies reveals that e-government initiatives have a distinct set of business value sources different from those of e-business projects. Implications and applications of the findings are briefly discussed.
Why Employees Do Non-Work-Related Computing: An Exploratory Investigation through Multiple Theoretical Perspectives

This study investigates why employees spend time on computing activities that are not related to their work. Drawing from multiple theories, a model for employees' non-work-related computing (NWRC) was developed. The model suggests a blend of rational decision-making and unconscious behavioral factors. The model was tested through an online survey. For the rational factor model, results revealed that behavioral intention and IS environmental factor were significant predictors of NWRC behavior. Perceived usefulness was significant predictor of behavioral intention. However, when unconscious factors, such as habit and affect, were included in the model, behavioral intention became insignificant, and habit became a strong predictor of NWRC behavior, doubling the explanatory power of the model. Our results provide a theory-based explanation on why employees engage in NWRC and practical implications on how organizations can develop strategies to manage this phenomenon.
Complex Constitutive Parameter Extraction for Multilayered Samples using S-Parameter Waveguide Measurements

In this paper, a method was presented for accurately determining the complex CP from individual layers within a multilayer sample using S-parameter waveguide measurements. MPSQP, a modification of SQP, provided a simple mechanism to avoid local minima trapping while still obtaining the global minimum in a short amount of time. Comparison of the extracted CP to those of the SCL method showed that the MPSQP algorithm was successful in accurately estimating the CP for three single layer materials (one nonmagnetic and two radar absorbing). Results were also shown for a three layer material. Based on RMS error comparisons, the CP were found to be accurate to within the tolerance of the available measurements
Online self-supervised monocular visual odometry for ground vehicles

This paper presents an online self-supervised approach to monocular visual odometry and ground classification applied to ground vehicles. We solve the motion and structure problem based on a constrained kinematic model. The true scale of the monocular scene is recovered by estimating the ground surface. We consider a general parametric ground surface model and use the Random Sample Consensus (RANSAC) algorithm for robust fitting of the parameters. The estimated ground surface provides training samples to learn a probabilistic appearance-based ground classifier in an online and self-supervised manner. The appearance-based classifier is then used to bias the RANSAC sampling to generate better hypotheses for parameter estimation of the ground surface model. Thus, without relying on any prior information, we combine geometric estimates with appearance-based classification to achieve an online self-learning scheme from monocular vision. Experimental results demonstrate that online learning improves the computational efficiency and accuracy compared to standard sampling in RANSAC. Evaluations on the KITTI benchmark dataset demonstrate the stability and accuracy of our overall methods in comparison to previous approaches.
7.1 A 1/4-inch 8Mpixel CMOS image sensor with 3D backside-illuminated 1.12μm pixel with front-side deep-trench isolation and vertical transfer gate

According to the trend towards high-resolution CMOS image sensors, pixel sizes are continuously shrinking, towards and below 1.0μm, and sizes are now reaching a technological limit to meet required SNR performance [1-2]. SNR at low-light conditions, which is a key performance metric, is determined by the sensitivity and crosstalk in pixels. To improve sensitivity, pixel technology has migrated from frontside illumination (FSI) to backside illumiation (BSI) as pixel size shrinks down. In BSI technology, it is very difficult to further increase the sensitivity in a pixel of near-1.0μm size because there are no structural obstacles for incident light from micro-lens to photodiode. Therefore the only way to improve low-light SNR is to reduce crosstalk, which makes the non-diagonal elements of the color-correction matrix (CCM) close to zero and thus reduces color noise . The best way to improve crosstalk is to introduce a complete physical isolation between neighboring pixels, e.g., using deep-trench isolation (DTI). So far, a few attempts using DTI have been made to suppress silicon crosstalk. A backside DTI in as small as 1.12μm-pixel, which is formed in the BSI process, is reported in , but it is just an intermediate step in the DTI-related technology because it cannot completely prevent silicon crosstalk, especially for long wavelengths of light. On the other hand, front-side DTIs for FSI pixels  and BSI pixels [6] are reported. In , however, DTI is present not only along the periphery of each pixel, but also invades into the pixel so that it is inefficient in terms of gathering incident light and providing sufficient amount of photodiode area. In , the pixel size is as large as 2.0μm and it is hard to scale down with this technology for near 1.0μm pitch because DTI width imposes a critical limit on the sufficient amount of photodiode area for full-well capacity. Thus, a new technological advance is necessary to realize the ideal front DTI in a small size pixel near 1.0μm.
The synchronized holonomic model: A framework for efficient generation of motion

We present a simple and efficient mathematical framework suitable for generating motion in the context of a variety of robotic motion tasks ranging from low-level motor control up to high-level locomotion planning. Our concept is based on a one-dimensional second-order model that allows analytic computation of its inverse dynamics while respecting physical constraints. This makes it a particularly useful tool for tasks that are expressed only as a start and goal state, such as animation key frames or way points in path planning. By means of time synchronization, the model extends easily to an arbitrary number of dimensions in a way that the target is reached in all dimensions at the same time. The framework excels in terms of execution time, which lies in the microsecond range even for high-dimensional trajectory generation tasks. We demonstrate our method in two different settings — full-body trajectory generation and path planning — and show its benefits in comparison with current state-of-the-art algorithms.
Algorithms to implement snap-shot-based effective-bandwidth routing that best utilizes its excess bandwidth for best effort traffic

Computationally efficient algorithms are developed to implement admission control and explicit routing of label switched paths (LSPs) for individually arriving quality of service (QoS) connection requests in a multiprotocol label switching (MPLS) network domain. A greedy admissions control policy, based on the snap-shot state of the network, is applied to arriving QoS connection requests, i.e., a connection request is admitted whenever there is an available path with sufficient residual capacities along its links to support the connection without re-routing existing LSPs. Although in our novel scenario best effort (BE) traffic flows follow their usual destination-based shortest path routes, in routing QoS connections, our algorithms give consideration to the resultant BE traffic delays. Excess effective bandwidth, the margin by which a QoS connection's effective bandwidth exceeds its average consumed bandwidth, is employed to support BE traffic.