Miracle-dz/UniFAR-FTUs huggingface dataset:
Method and device increasing efficiency of drilling directional wells

The main independent controllable parameters in dr illing oil and gas wells are the weight on bit and the frequency of bit rotation. When drilling deep directional wells with horizontal sections of the wellbore, the weight comes to the bottomhole with a delay due to increased frictional forces during the movement of the drill string to the bottomhole. This complicates the drilling control procedure. There are the methods of autonomous control of the weight on bit using electrical drilling, downhole motor, and the bit feeders. The research has shown that all known methods can generally only supplement the conventional method of creating weight on bit – transmitting the weight of the compressed part of the drilling tool and formation of hydraulic force on the downhole motor shaft. Each of those methods has certain shortcomings and does not solve the problem entirely. This paper presents the method and the device that are most effective for drilling directional wells. It is achieved by generating an additional weight on bit in the device, transferring this weight and the part of the force from the drill string through the upper end of the downhole motor shaft to the bit. Reduction of the frictional forces of the drill string against the borehole wall is carried out by the constant transmission of the bit axial vibrations from the upper end of the shaft of the downhole motor to the drill string and by adjustment of the axial vibrations parameters. Keywords—drilling; directional wells; bit; weight on bit; device; control.
Hierarchical Sub-sentential Alignment with IBM Models for Statistical Phrase-based Machine Translation

In this paper, we describe a novel method for joint word alignment and symmetrization. Based on initial parameters from simple IBM models, we synchronously parse the parallel sentence pair under the framework of bracket transduction grammar constraints. Our 2-phase method can achieve nearly the same run-time as fast align while delivering better alignments on distantly-related language pairs such as English– Japanese. We show how to integrate this method into a standard phrase-based SMT pipeline. Although the alignment quality results are mixed, by forcing all words to be aligned ( 1-to-many/many-to-1 ), our method signiﬁcantly reduces the phrase table size with no diﬀerence in translation quality and even outperforms fast align in some end-to-end translation experiments.
Action recognition in egocentric videos

With an increase in usage and availability of wearable devices like GoPro, Microsoft Hololens, Google Glass, etc, egocentric video analysis has become essential. An interesting application is action recognition in egocentric videos. Research has been performed on action recognition in first person(egocentric) videos. First person action recognition is a hard problem given that first person videos are shaky, have limited hand-object interaction, and have limited publicly available datasets. Most of the existing research uses hand-crafted features to learn actions which works best for a given domain. First person videos have two types of actions. First, where hand-object interactions are present and the other one, where no such interactions are present. Current methods can only be used to recognise any one type of action but not both using a single method. This research proposes a novel action recognition method to recognise two types of actions, one where hand-object interaction is present and other where no such interactions are present. Further, a new dataset named IIITD Plumbing dataset is introduced which provides large number of videos, objects, and actions. The proposed system makes use of spatio-temporal information captured from raw frames. We also introduce a new method to perform activity recognition that learns grammar from learned actions.
Design and Hardware Implementation Considerations of Modified Multilevel Cascaded H-Bridge Inverter for Photovoltaic System

Inverters are an essential part in many applications including photovoltaic generation. With the increasing penetration of renewable energy sources, the drive for efficient inverters is gaining more and more momentum. In this paper, output power quality, power loss, implementation complexity, cost, and relative advantages of the popular cascaded multilevel H-bridge inverter and a modified version of it are explored. An optimal number of levels and the optimal switching frequency for such inverters are investigated, and a five-level architecture is chosen considering the trade-offs. This inverter is driven by level shifted in-phase disposition pulse width modulation technique to reduce harmonics, which is chosen through deliberate testing of other advanced disposition pulse width modulation techniques. To reduce the harmonics further, the application of filters is investigated, and an LC filter is applied which provided appreciable results. This system is tested in MATLAB/Simulink and then implemented in hardware after design and testing in Proteus ISIS. The general cascaded multilevel H-bridge inverter design is also implemented in hardware to demonstrate a novel low-cost MOSFET driver build for this study. The hardware setups use MOSFETs as switching devices and low-cost ATmega microcontrollers for generating the switching pulses via level shifted in-phase disposition pulse width modulation. This implementation substantiated the effectiveness of the proposed design.
Human-Autonomous System Interaction Framework to Support Safety in Astronaut-Robot Team Interactions

The focus of this effort is on protocol development and utilization in autonomous robot teams to promote safety in interactions within the team and with an Astronaut or Astronauts. A module for protocol-awareness is integrated into a robot control framework. While a particular framework must be selected for specificity, this approach is generally applicable to robot control frameworks in which the robot may be considered an „agent‟. Safety –related protocols are defined. Simulation results of a notional Lunar Sampling Mission involving an active, autonomous robot team which utilizes the safety-related protocols and an Astronaut are presented. Preliminary results of the deployment onto robot hardware are given and future plans noted.
Trade-off Between Hit Rate and Hit Latency for Optimizing DRAM Cache

Due to the large storage capacity, high bandwidth and low latency, 3D DRAM is proposed to be the last level cache, referred to as DRAM cache. The hit rate and hit latency are two conflicting optimization goals for DRAM cache. To address this issue, we design a new DRAM organization that trades the lower hit rate for shorter hit latency by way-locator cache and novel cache set layout. We have designed a novel DRAM cache organization to simultaneously achieve a good hit rate and shorter latency, referred to as SODA-cache. The SODA-cache adapts 2-way set associate cache motivated by the observation that 2-way set associative cache provides the most hit rate improvement from the direct-mapped cache to highly associative cache. The proposed way-locator cache and a novel set layout effectively reduce the cache-hit latency. We use SPEC 2006 CPU benchmark to evaluate our design and two stat-of-art DRAM cache designs. Experimental results show that SODA-cache can improve hit rate by 8.1 percent compared with Alloy-cache and reduce average access latency by 23.1, 13.2 and 8.6 percent compared with LH-cache, Alloy-cache and ATCache respectively on average. Accordingly, SODA-cache outperforms over LH-cache, Alloy-cache and ATCache by on average 17, 12.8 and 8.4 percent respectively in term of weighted speedup.
Isolated Cuk Converter with Two Symmetrical Output voltages For SRM Drive

In this paper, a high power factor based isolated dual output Cuk converter fed SRM drive is proposed. The selected converter is featured with two equal output power sources, DC isolation and improved power quality operation over a complete input voltage range and loading conditions. To obtain input current shaping, DCM (Discontinuous Conduction Mode) of operation is selected, which presents the most simple and low cost control as compared to CCM (Continuous Conduction Mode), and CRM (critical conduction mode). It has resulted in the reduced size and cost of magnetic structure considerably. The speed control of proposed drive is based upon DC link voltage control, which is obtained by modulating pulse width of the Cuk converter. Experimental results of a prototype of isolated Cuk converter fed SRM drive is demonstrated here. The obtained input current THD complies with given regulation for harmonics, such as an IEC 61000-3-2.
Relaying the High-Frequency Contents of Tactile Feedback to Robotic Prosthesis Users: Design, Filtering, Implementation, and Validation

It is known that high-frequency tactile information conveys useful cues to discriminate important contact properties for manipulation, such as first contact and roughness. Despite this, no practical system, implementing a modality matching paradigm, has been developed so far to convey this information to users of upper-limb prostheses. The main obstacle to this implementation is the presence of unwanted vibrations generated by the artificial limb mechanics, which are not related to any haptic exploration task. In this letter, we describe the design of a digital system that can record accelerations from the fingers of an artificial hand and reproduce them on the user's skin through voice-coil actuators. Particular attention has been devoted to the design of the filter, needed to cancel all those vibrations measured by the sensors that do not convey information on meaningful contact events. The performance of the newly designed filter is also compared with the state of the art. Exploratory experiments with prosthesis users have identified some applications where this kind of feedback could lead to sensory-motor performance enhancement. Results show that the proposed system improves the perception of object-salient features such as first-contact events, roughness, and shape.
PDMS-Assisted Microfiber M-Z Interferometer With a Knot Resonator for Temperature Sensing

We experimentally demonstrate a compact temperature sensor using a microfiber-based Mach–Zehnder interferometer with a knot micro-ring resonator. The arm with a knot micro-ring resonator is embedded in polydimethylsiloxane (PDMS), which acts as the temperature transducer. The scattering matrix method is employed to establish the numerical model of the device. Owing to the high thermo-optic coefficient of PDMS, the response spectrum of the device will blue-shift when the ambient temperature increases. The device is characterized by changing temperature in two different environments (air and liquid), respectively. For temperature sensing operated in air, the device is tested utilizing a heating platform, which shows a sensitivity of −35.12 pm/°C when the temperature of the heating platform varies at a range of 15.5 °C. After that, a sensitivity boosting up to −41.58 pm/°C is measured when the device is immersed in a salt solution (25 ‰ in concentration) with the temperature changing from 22.2 °C to 32.9 °C.
An efficient method for the physical mapping of transgenes in barley using in situ hybridization

The genetic transformation of crops by particle bombardment and Agrobacterium tumefaciens systems have the potential to complement conventional plant breeding programmes. However, before deployment, transgenic plants need to be characterized in detail, and physical mapping is an integral part of this process. Therefore, it is important to have a highly efficient method for transgene detection by fluorescence in situ hybridization (FISH). This study describes a new approach, which provides efficient control of probe length and labelling, both of which play an important role in in situ hybridization of transgenes. The approach is based on reducing the size of the plasmid prior to labelling by nick translation, rather than using the whole or linearized plasmid, or varying the amounts of DNaseI in the nick translation mixture. This provided much more efficient labelling of the probe, which yielded optimal hybridization, minimal fluorescent background, and accurate physical location of the transgene.Key words:.
Sentiment Analysis on Twitter Data using Apache Spark Framework

Sentiment analysis has become an interesting field for both research and industrial domains. The expression sentiment refers to the feelings or thought of the person across some certain issues. Furthermore, it is also considered a direct application for opinion mining. The huge amount of tweets jotted down daily makes Twitter a rich source of textual data and one of the most essential data volumes; therefore, this data has different aims, such as business, industrial or social aims according to the data requirement and needed processing. Actually, the amount of data, which is massive, grows rapidly per second and this is called big data which requires special processing techniques and high computational power in order to perform the required mining tasks. In this work, we perform a sentiment analysis with the help of Apache Spark framework, which is considered an open source distributed data processing platform which utilizes distributed memory abstraction. The goal of using Apache Spark’s Machine learning library (MLIB) is to handle an extraordinary amount of data effectively. We recommend some Preprocessing and Machine learning text feature extraction steps for getting greater results in Sentiment Analysis classification. The effectiveness of our proposed approach is proved against other approaches achieving better classification results when using Naïve Bayes, Logistic Regression and Decision trees classification algorithms. Finally, our solution estimates the performance of Apache Spark concerning its scalability.
Automatic Mining of Large IoT Sensor Tensor

Given a large collection of multiple time-evolving sensor sequences, how can we capture the transitions of time series patterns? How can we find individual differences between different sequences? In this paper we present CUBEMARKER, an effective method for capturing multi-aspect features of sensor sequences, which provides a compact and powerful representation of sensor behavior. Our second contribution is a novel, scalable, and parameter-free algorithm. CUBEMARKER performs two-way mining for all attributes. Specifically it discovers multi-aspect time series patterns (human motion, smart factory, etc) and groups of patterns simultaneously. Extensive experiments on real datasets show that CUBEMARKER is effective in that it can capture meaningful patterns for various real sensor datasets.
Super Dragon: A 10-m-Long-Coupled Tendon-Driven Articulated Manipulator

The decommissioning of the Fukushima Daiichi Nuclear Power Plants is a national urgent problem in Japan. The distribution and characteristics of the fuel debris inside the nuclear reactor must be investigated to safely retrieve them. This letter describes a 10-m-long articulated manipulator for investigation inside the primary container vessel. We employed a coupled tendon-driven mechanism and a gravity compensation mechanism using synthetic fiber ropes to design a lightweight and slender articulated manipulator. After discussing the basic principle and control algorithm, we focus on the detailed mechanical design of a prototype model. We confirmed its feasibility through basic motion experiments.
The Effects of Service Availability and Recognition Errors on Trust in Voice User Interfaces

This study was conducted to determine the effects of speech recognition accuracy and system availability on customers' perceptions of a speech-enabled Interactive Voice Response (IVR) system. Fifty-six participants searched for bank rate information using a prototype speech recognition banking system in one of four conditions: (1) perfect system performance when obtaining rate information, (2) occasional speech recognition errors, (3) occasional loss of system availability, and (4) a combination of recognition errors and loss of system availability. A “system trust” measure was a better discriminator between conditions than a commonly-used subjective satisfaction measure: participants who experienced periods of unavailable service trusted the system less than those who experienced fully available service, but these groups reported similar subjective satisfaction rates. Participants who encountered speech recognition errors reported no lower levels of trust or satisfaction than those who experienced perfect recognition accuracy. The paper discusses the relationship between system trust and the willingness to use self-service systems, as well as special aspects of speech recognition systems in terms of “persona” and users' perceptions.
Novel Reusable Transosseous Tunnel Based Soft Tissue Repair Techniques about the Shoulder: A Rational, Value Based Approach

Submit Manuscript | http://medcraveonline.com rotator cuff repair, outpatient rotator cuff repair saves cost when compared to inpatient repair, and open cuff repair is more cost effective compared to all arthroscopic [3,4]. There is also evidence that anchor burden may increase cost significantly [5,6]. Adla et al. [7] showed that arthroscopic cuff repair was less cost effective by an average of $1,248.75 per case [7]. Narvy et al. [8] recently defined the direct economic cost of rotator cuff repair in the outpatient setting as $5,904.21 [8]. In their study, implantable anchors were the dominant cost driver, with a mean anchor cost per case of $3,432.67, with double row repairs averaging $4,570.25 anchor cost per case. In a similar vein, Genuario concluded in a decision-analytic model that double row rotator cuff repair was not cost effective for any size tear [5]. While there is evidence that anchors increase cost, there is little evidence that any one implant or method is superior to another in terms of implants or repair techniques [9,10]. Because clinical outcome does not correlate well with structural integrity of the cuff after repair, it is likely that various implants and techniques will be equivalent or noninferior in evidence based analysis [11]. Arthroscopic soft tissue repair about the shoulder offers a prime opportunity to provide high value, time honored repair techniques with updated cost effective arthroscopic approaches for our changing environment.
K-means Algorithm And Its ApplicationFor Clustering Companies Listed InZhejiang Province

There exist many problems in the credit market where we have data that needs to be classified into distinct groups. This paper will introduce a financial K-means algorithm, which based on the historical financial ratios, applies the cluster analysis technology to analyze the listed enterprises in Zhejiang province. We analyze indicators related to financial attributes and choose nine finance indicators. According to better valuation on the companies listed, we apply “trial and error” and choose four as the number of clustering. Testing shows that companies belong to cluster 2 and cluster 3 add up to 71 companies, including 87% in all. They are all companies worthy of making loans, which is inconsistent with the good economic situation of Zhejiang province. Category 4 has nine companies including 11% that are judged as high risk business. So banks should provide these customers for loans with a mortgage or guarantee.
An Intelligent Cooperative Vision Perception System for Connected Vehicles via IPv6

As the complexity of transportation systems increases, driving safety has become a critical issue in these years. Object detection based on Convolution Neural Networks (CNNs) plays an important role for intelligent driving in detecting vehicles, pedestrians and so on. However, the detection models in CNNs ask for huge computation and memory usage, which makes it difficult to work in on-board devices. What’s more, intelligent driving needs high-precision and low-latency requirements in city traffic scenarios for object detection. This paper proposes an intelligent cooperative vision perception system for the connected vehicles. The driving videos are collected from vehicles and transmitted to cloud for vision perception with CNNs in this system. In addition, there are two kinds of visual models which achieve 73.64% and 65.67% mean Average Precision (mAP) respectively for chosen. Considering the bandwidth consumption and transmission latency, a resolution adaptive strategy and a frame-rate control strategy are designed and the IPv6 route is used for transmitting between the vehicle and cloud. This system assists drivers for better and safer decisions by augmenting the perception ability.
Attend2trend: Attention Model for Real-Time Detecting and Forecasting of Trending Topics

Knowing what is increasing in popularity is important to researchers, news organizations, auditors, government entities and more. In particular, knowledge of trending topics provides us with information about what people are attracted to and what they think is noteworthy. Yet detecting trending topics from a set of texts is a difficult task, requiring detectors to learn trending patterns while simultaneously making predictions. In this paper, we propose a deep learning model architecture for the challenging task of trend detection and forecasting. The model architecture aims to learn and attend to the trending values' patterns. Our preliminary results show that our model detects the trending topics with a high accuracy.
A Lumped-Charge Model for High-Power PT-p-i-n Diode With a Buffer Layer

This paper presents a lumped-charge model for the punchthrough p-i-n (PT-p-i-n) diode with a buffer layer. Based on the lumped-charge modeling, this paper analyzes the influence of the buffer layer and carrier lifetime control technology. The PT-p-i-n diode model involves dealing with changes in the diode doping concentration and carrier lifetime in the switching process. The variation of carrier lifetime with the injected charge is discussed and a lumped-charge model of carrier lifetime is proposed. Considering that the characteristics of p-i-n diode are changed with temperatures, the model uses the added temperature function of physical parameters to get the static and transient temperature characteristics. Then the model is implemented into the circuit simulation platform PSPICE. Finally, the antiparallel freewheeling diode in the Infineon 3300 V/1500 A Insulated Gate Bipolar Transisto module is used for verification. The comparisons between the simulated and measured results have a good agreement both in static and in switching operations at different temperatures.
Demo: UAV Assisted Adaptive Aerial Internet

This demonstration presents a unmanned aerial vehicle (UAV) assisted space Internet system. We have developed the intelligent router and embedded the server program into the intelligent router. The server program has the function of instant message (IM), file caching, delay tolerant communication, etc. The multiple UAVs carry the intelligent routers and provide local area network (LAN) for the users on ground within a certain area. The UAV swarm forms a mobile ad hoc network (MANET) to extend the coverage of the LAN. Besides, the delay-tolerant communication can be provided exploiting the mobility of UAVs. This demonstration verifies the basic function of aerial base station (BS), which can provide a guideline for the development of UAV assisted aerial Internet system.
Efficiency of 128-bit Encryption and Decryption Process in Elgamal Method Using Elliptic Curve Cryptography (ECC)

Cryptography is a growing science of data security. The integrity of a data is an important thing to keep the secrets contained in the data. In this research will be visualized the efficient quantities that use elliptic curves and do not use them. The hope is that by using elliptic curves the timing of the encryption and decryption process can run faster and help the Central Processing Unit (CPU) in the computation of ElGamal Method.