nils-herrmann/clean_scirepeval huggingface dataset:
Use of Non-conductive Film (NCF) with Nano-Sized Filler Particles for Solder Interconnect: Research and Development on NCF Material and Process Characterization

As three-dimensional Through-Silicon Via (3D-TSV) packaging is emerging in the semiconductor market to integrate multiple functions in a system for further miniaturization, thermal compression bonding (TCB), which stacks multiple bare chips on top of each other with Cu pillar bumps with solder cap, has become an indispensable new packaging technology. The novel non-conductive film (NCF) described in this paper is an epoxy-type thermosetting material in film form, with lower density of Nano-sized silica filler particles (average particle size is 100 Nano meters). Advantages of this NCF material with Nano-sized fillers include: transparency of the NCF material so that the TCB bonder's image recognition system can easily identify fiducial marks on the chip, ability of the Nano-filler to flow out with the NCF resin during thermal compression bonding, to mitigate filler entrapment between solder joints, which is critical to ensure reliable solder connections, compatibility with fine pitch applications with extremely narrow chip-to-chip and chip-to-substrate gaps to form void-free underfill. Instead of the previous processes of die attach, fluxing, traditional oven mass re-flow, flux cleaning, and capillary underfill (CUF), the current process involves the use of NCF & TCB. The NCF is applied on a wafer in a film form by lamination, and then a wafer is diced with the pre-laminated NCF in pieces. Then they are joined by TCB, with typical parameters of 250°C for 10 seconds with 80N (solder cap on 15μm diameter Cu pillar, 40μm pitch, 1000 bumps). NCF heated by TCB is quickly liquidized to lower its viscosity after a few seconds. Other advantages of NCF is that it has a fluxing function included in the material, which eliminates the need for separate flux apply and flux clean steps, which simplifies process and costs. Also, NCF can control extrusion along the package's edge line since NCF is a half-cured B-stage material which has some mechanical rigidity during handling and lamination. Thus NCF Thermal Compression Flip Chip Bonding method is the vital solution to ensure good reliability with mass productivity for next generation's packaging. The characterization of NCF material and the importance of controlling viscosity and elastic modulus during thermal-compression will be analyzed and discussed in this paper. Process and reliability data on test vehicles will be shown.
A Better Comparison Summary of Credit Scoring Classification

The credit scoring aim is to classify the customer credit as defaulter or non-defaulter. The credit risk analysis is more effective with further boosting and smoothing of the parameters of models. The objective of this paper is to explore the credit score classification models with an imputation technique and without imputation technique. However, data availability is low in case of without imputation because of missing values depletion from the large dataset. On the other hand, imputation based dataset classification accuracy with linear method of ANN is better than other models. The comparison of models with boosting and smoothing shows that error rate is better metric than area under curve (AUC) ratio. It is concluded that artificial neural network (ANN) is better alternative than decision tree and logistic regression when data availability is high in dataset. Credit score data mining; classification; artifical neural network; imputation
The self to other model of empathy: Providing a new framework for understanding empathy impairments in psychopathy, autism, and alexithymia

Despite increasing empirical and theoretical work on empathy, particularly on the content of empathic representations, there is a relative lack of consensus regarding the information processing necessary for empathy to occur. Here we attempt to delineate a mechanistic cognitive model of empathy in order to provide a framework within which neuroimaging work on empathy can be located, and which may be used in order to understand various disorders characterised by atypical levels of empathy. To this end data from individuals with psychopathy, autism, and alexithymia inform the model, and the model is used to provide a unifying framework for any empathy impairments seen in these disorders. The model adopts a developmental framework and tries to address the four difficult questions of empathy: How do we know what another is feeling? What is the role of theory of mind in empathy? How does the state of another cause a corresponding state in the self? How do we represent another's emotion once emotional contagion has taken place?
Editing Training Data for kNN Classifiers with Neural Network Ensemble

Since kNN classifiers are sensitive to outliers and noise contained in the training data set, many approaches have been proposed to edit the training data so that the performance of the classifiers can be improved. In this paper, through detaching the two schemes adopted by the Depuration algorithm, two new editing approaches are derived. Moreover, this paper proposes to use neural network ensemble to edit the training data for kNN classifiers. Experiments show that such an approach is better than the approaches derived from Depuration, while these approaches are better than or comparable to Depuration.
An incremental strategy for tractor-trailer vehicle global trajectory optimization in the presence of obstacles

Trajectory planning is a critical aspect in driving an autonomous tractor-trailer vehicle. This study considers trajectory planning as a minimal-time optimal control problem that incorporates the kinematics, mechanical/physical constraints, environmental requirements and an optimization criterion. This formulation benefits in the ability to directly handle time-dependent requirements. A gradient-based numerical solver is adopted to tackle the formulated optimal control problem. An incremental strategy is proposed to enhance the global optimization ability of that solver and to help find satisfactory solutions in challenging cases. Specifically, when an optimal solution is found, we doubt whether that is merely a local optimum and then still expect to make evolution; when optimal solutions are not easy to obtain, we expect at least one feasible solution first, which is taken as a preliminary guess to assist the subsequent optimization process. Both procedures proceed alternatively until no progress can be made any further. Some intricate simulation results are well beyond manual operation ability. Moreover, our overall proposal, as a unified and open framework, can deal with a wide variety of user-specified requirements.
Bystander Responses to a Violent Incident in an Immersive Virtual Environment

Under what conditions will a bystander intervene to try to stop a violent attack by one person on another? It is generally believed that the greater the size of the crowd of bystanders, the less the chance that any of them will intervene. A complementary model is that social identity is critical as an explanatory variable. For example, when the bystander shares common social identity with the victim the probability of intervention is enhanced, other things being equal. However, it is generally not possible to study such hypotheses experimentally for practical and ethical reasons. Here we show that an experiment that depicts a violent incident at life-size in immersive virtual reality lends support to the social identity explanation. 40 male supporters of Arsenal Football Club in England were recruited for a two-factor between-groups experiment: the victim was either an Arsenal supporter or not (in-group/out-group), and looked towards the participant for help or not during the confrontation. The response variables were the numbers of verbal and physical interventions by the participant during the violent argument. The number of physical interventions had a significantly greater mean in the in-group condition compared to the out-group. The more that participants perceived that the Victim was looking to them for help the greater the number of interventions in the in-group but not in the out-group. These results are supported by standard statistical analysis of variance, with more detailed findings obtained by a symbolic regression procedure based on genetic programming. Verbal interventions made during their experience, and analysis of post-experiment interview data suggest that in-group members were more prone to confrontational intervention compared to the out-group who were more prone to make statements to try to diffuse the situation.
SegMap: 3D Segment Mapping using Data-Driven Descriptors

When performing localization and mapping, working at the level of structure can be advantageous in terms of robustness to environmental changes and differences in illumination. This paper presents SegMap: a map representation solution to the localization and mapping problem based on the extraction of segments in 3D point clouds. In addition to facilitating the computationally intensive task of processing 3D point clouds, working at the level of segments addresses the data compression requirements of real-time singleand multi-robot systems. While current methods extract descriptors for the single task of localization, SegMap leverages a data-driven descriptor in order to extract meaningful features that can also be used for reconstructing a dense 3D map of the environment and for extracting semantic information. This is particularly interesting for navigation tasks and for providing visual feedback to endusers such as robot operators, for example in search and rescue scenarios. These capabilities are demonstrated in multiple urban driving and search and rescue experiments. Our method leads to an increase of area under the ROC curve of 28.3% over current state of the art using eigenvalue based features. We also obtain very similar reconstruction capabilities to a model specifically trained for this task. The SegMap implementation is available open-source along with easy to run demonstrations at www.github.com/ethz-asl/segmap.
Radio resource allocation and power control scheme to mitigate interference in device-to-device communications underlaying LTE-A uplink cellular networks

The integration of Device-to-Device (D2D) communication into a cellular network improves system spectral efficiency, increases capacity, reduces power consumption and also reduces traffic to the evolved NodeB (eNB). However, D2D communication generates interference to the conventional cellular network which deteriorates the system performance. In this paper, we propose a radio resource allocation and power control scheme to mitigate the interference using cell sectorization scheme while reusing uplink cellular resources by the D2D pairs. By simulations, we show that our proposed scheme improves the overall system performance compared with the existing methods.
WebVR - - Web Virtual Reality Engine Based on P2P network

WebVR, a multi-user online virtual reality engine, is introduced. The main contributions are mapping the geographical space and virtual space to the P2P overlay network space, and dividing the three spaces by quad-tree method. The geocoding is identified with Hash value, which is used to index the user list, terrain data, and the model object data. Sharing of data through improved Kademlia network model is designed and implemented. In this model, XOR algorithm is used to calculate the distance of the virtual space. The model greatly improves the hit rate of 3D geographic data search under P2P overlay network. Some data preprocessing methods have been adopted to accelerate the data transfer. 3D Global data is used for testing the engine. The test result indicates that, without considering the client bandwidth limit, the more users, the faster
Time Series Forecasting Based on Augmented Long Short-Term Memory

In this paper, we use recurrent autoencoder model to predict the time series in single and multiple steps ahead. Previous prediction methods, such as recurrent neural network (RNN) and deep belief network (DBN) models, cannot learn long term dependencies. And conventional long short-term memory (LSTM) model doesn’t remember recent inputs. Combining LSTM and autoencoder (AE), the proposed model can capture long-term dependencies across data points and uses features extracted from recent observations for augmenting LSTM at the same time. Based on comprehensive experiments, we show that the proposed methods significantly improves the state-of-art performance on chaotic time series benchmark and also has better performance on real-world data. Both single-output and multiple-output predictions are investigated.
A Matlab-based modeling and simulation package for electric and hybrid electric vehicle design

This paper discusses a simulation and modeling package developed at Texas A&M University, V-Elph 2.01. VElph facilitates in-depth studies of electric vehicle (EV) and hybrid EV (HEV) configurations or energy management strategies through visual programming by creating components as hierarchical subsystems that can be used interchangeably as embedded systems. V-Elph is composed of detailed models of four major types of components: electric motors, internal combustion engines, batteries, and support components that can be integrated to model and simulate drive trains having all electric, series hybrid, and parallel hybrid configurations. V-Elph was written in the Matlab/Simulink graphical simulation language and is portable to most computer platforms. This paper also discusses the methodology for designing vehicle drive trains using the V-Elph package. An EV, a series HEV, a parallel HEV, and a conventional internal combustion engine (ICE) driven drive train have been designed using the simulation package. Simulation results such as fuel consumption, vehicle emissions, and complexity are compared and discussed for each vehicle.
Beam-Tilting Antenna With Negative Refractive Index Metamaterial Loading

A beam-tilting antenna with negative refractive index metamaterial (NRIM) loading is proposed for WLAN applications. The proposed antenna is composed of a double-feed dielectric resonator antenna (DRA) and 1 × 4 NRIM array, which are fixed over and in the middle of the DRA. The proposed NRIM unit cell comprises a fractal cross-ring resonator structure and performs a negative refractive index in the band from 5 to 5.5 GHz. When the electromagnetic (EM) waves enter a medium with a negative refractive index, the direction of propagation of the EM wave can be changed. Therefore, beam-tilting can be implemented by using the DRA cooperating with the proposed NRIM array. The simulation and experimental results show that the beam-tilting antenna can steer the main beam by ±38° in the  xoz-plane over 5–5.5-GHz band. The reflection coefficient of the antenna is better than −10 dB in the band from 5 to 5.5 GHz. Furthermore, the measured results have a good agreement with simulated ones.
Optimum beamforming using transmit antenna arrays

Transmit beamforming is a powerful means of increasing capacity in systems in which the transmitter is equipped with an antenna array, especially in systems in which receive beamforming is not available, as is typical in the base-to-mobile \downlink" in a cellular communication system. In this paper, the problem of transmit beamforming is formulated as one of minimizing the power radiated by the base station, subject to satisfying quality of service requirements at the mobiles. For a single cell system, a global minimum is shown to exist, and an iterative algorithm that converges to it is provided. The solution extends to accomodate receive beamforming at the mobiles. It also extends to provide a mechanism for space-time transmit ltering, which exploits the diierences between the temporal as well as the spatial channels between the base station and diierent mobiles. Finally, a system with multiple source-destination pairs (e.g., in an ad hoc network) is considered. An iterative algorithm that outputs a con-vergent sequence of feasible points with monontonically decreasing costs is provided for this case.
10.6 THz figure-of-merit phase-change RF switches with embedded micro-heater

We report on GeTe-based phase-change RF switches with embedded micro-heater for thermal switching. With heater parasitics reduced, GeTe RF switches show onstate resistance of 0.05 ohm*mm and off-state capacitance of 0.3 pF/mm. The RF switch figure-of-merit is estimated to be 10.6 THz, which is about 15 times better than state-of-the-art silicon-on-insulator switches. With on-state resistance of 1 ohm and off-state capacitance of 15 fF, RF insertion loss was measured at <;0.2 dB, and isolation was >25 dB at 20 GHz, respectively. RF power handling was >5.6 W for both onand off-state of GeTe.
Gait support for complete spinal cord injury patient by synchronized leg-swing with HAL

Biped walking improves the circulation of blood as well as bone density of the lower limbs, thereby enhancing the quality of life (QOL). It is significant not only to healthy people but also to physically challenged persons such as complete spinal cord injury (SCI) patients. The purpose of this paper is to propose an estimation algorithm that infers the intention related to the forward leg-swing in order to support the gait for complete SCI patients wearing an exoskeleton system called a Hybrid Assistive Limb (HAL), and to verify the effectiveness of the proposed algorithm through a clinical trial. The proposed algorithm infers the patient's intention in synchronization with the deviation of the center of the ground reaction force (CoGRF) that is observed immediately before a person starts walking. The patient conveys this intention by inducing the deviation of the CoGRF, using crutches or handrails with both of his/her arms. In the clinical trial, we confirmed that the algorithm inferred the patient's intention to swing the leg forward, and achieved a smooth gait in synchronization with it. As a result, the gait speed and cadence of the SCI patient with HAL during the 10-meter walking test increased to 6.67 [m/min] and 20 [steps/min], respectively after several trials.
Error and attack tolerance of complex networks

Communication/transportation systems are often subjected to failures and attacks. Here we represent such systems as networks and we study their ability to resist failures (attacks) simulated as the breakdown of a group of nodes of the network chosen at random (chosen accordingly to degree or load). We consider and compare the results for two di/erent network topologies: the Erd1 os–R2 enyi random graph and the Barab2 asi–Albert scale-free network. We also discuss brie5y a dynamical model recently proposed to take into account the dynamical redistribution of loads after the initial damage of a single node of the network.
Estimation techniques and simulation platforms for 77 GHz FMCW ACC radars

HAL is a multi-disciplinary open access archive for the deposit and dissemination of scientific research documents, whether they are published or not. The documents may come from teaching and research institutions in France or abroad, or from public or private research centers. L’archive ouverte pluridisciplinaire HAL, est destinée au dépôt et à la diffusion de documents scientifiques de niveau recherche, publiés ou non, émanant des établissements d’enseignement et de recherche français ou étrangers, des laboratoires publics ou privés. Estimation techniques and simulation platforms for 77 GHz FMCW ACC radars Ali Bazzi, Camilla Karnfelt, Alain Peden, Thierry Chonavel, Philippe Galaup, Frantz Bodereau
Friction Models and Friction Compensation

Friction occurs in all mechanical systems,e.g. bearings, transmissions, hydraulic and pneumatic cylinders, valves, brakes and wheels. Friction appears at the physical interface between two surfaces in contact. Lubricants such as grease or oil are often used but the there may also be a dry contact between the surfaces. Friction is strongly influenced by contaminations. There is a wide range of physical phenomena that cause friction, this includes elastic and plastic deformations, fluid mechanics and wave phenomena, and material sciences, see [45, 53, 9, 10]. Friction was studied extensively in classical mechanical engineering and there has lately been a strong resurgence. Apart from intellectual curiosity this is driven by strong engineering needs in a wide range of industries from disc drives to cars. The availability of new precise measurement techniques has been a good driving force. Friction is also very important for the control engineer, for example in design of drive systems, high-precision servo mechanisms, robots, pneumatic and hydraulic systems and anti-lock brakes for cars. Friction is highly nonlinear and † Department of Automatic Control, Lund Institute of Technology, Lund University, Box 118, S-221 00 LUND, Sweden ‡ Laboratoire d’Automatique de Grenoble, CNRS-INPG-UJF, ENSIEG-INPG, B.P. 46, 38402 Grenoble, France †† Control Department, EIS, ULA, Mérida 5101, Venezuela
10W ultra-broadband power amplifier

We report the design and performance of an ultra-broadband power amplifier. It achieves 10 Watts output power with 21dB ± 1.5dB gain from 20 MHz to 3000 MHz. At lower frequencies from 20 to 1000 MHz the output power is 15 Watts with 22% efficiency. To achieve this performance, we employ a new design concept to control the device impedance and the power combiner impedance to be naturally 50 Ohms, such that no impedance matching is needed. Also, we developed a broadband microwave balun as a push-pull power combiner, which doubles as an impedance transformer. We believe the combination of output power, bandwidth and efficiency is the best reported to date.
Potential Bacillus probiotics enhance bacterial numbers, water quality and growth during early development of white shrimp (Litopenaeus vannamei).

Epidemics of epizootics and occurrence of multiresistant antibiotics of pathogenic bacteria in aquaculture have put forward a development of effective probiotics for the sustainable culture. This study examined the effectiveness of forms of mixed Bacillus probiotics (probiotic A and probiotic B) and mode of probiotic administration on growth, bacterial numbers and water quality during rearing of white shrimp (Litopenaeus vannamei) in two separated experiments: (1) larval stages and (2) postlarval (PL) stages. Forms of Bacillus probiotics and modes of probiotic administration did not affect growth and survival of larval to PL shrimp. The compositions of Bacillus species in probiotic A and probiotic B did not affect growth and survival of larvae. However, postlarvae treated with probiotic B exhibited higher (P<0.05) growth than probiotic A and controls, indicating Bacillus probiotic composition affects the growth of PL shrimp. Total heterotrophic bacteria and Bacillus numbers in larval and PL shrimp or culture water of the treated groups were higher (P<0.05) than in controls. Levels of pH, ammonia and nitrite of the treated shrimp were significantly decreased, compared to the controls. Microencapsulated Bacillus probiotic was effective for rearing of PL L. vannamei. This investigation showed that administration of mixed Bacillus probiotics significantly improved growth and survival of PL shrimp, increased beneficial bacteria in shrimp and culture water and enhanced water quality for the levels of pH, ammonia and nitrite of culture water.