Miracle-dz/UniFAR-FTUs huggingface dataset:
Distributed Push-Sum Algorithm for Multi-Agent optimization Via One-Point Gradient Estimator

This paper studies the distributed optimization problem over a multi-agent network that consists of multiple nodes, where the objective function of the problem is the sum of the local objective functions of nodes. The goal of the network is to minimize the collective objective function through local interactions among nodes. We propose an efficient distributed optimization algorithm that is based on push-sum algorithm and one-point gradient estimator, which removes the needs for doubly stochastic weight matrix and the information of subgradients of the objective functions. The convergence of the algorithm is established by deriving an O(1/$T^{1/6}$) (with T being the number of iterations) rate of convergence for the proposed algorithm.
Pakistan: Response validity in a KAP Survey.

This study conducted in Pakistan in 1969 examined the rate of underreporting in the knowledge and practice questions relating to family planning program since 1965. Over 1/3 of known contraceptors indicated that they had never used contraception and less than 10% said they had no knowledge of family planning. Women who used contraceptives for a longer time period were less likely to give false response. There were no significant differences between social class or number of children as to the degree of false response. Family type is insignificant with regard to false response when contraceptive use has been short but when used longer periods women in single families give less false responses than those in joint families. The relationship between age and duration of marriage and false responses is similarly a combination of factors.
Self-Assembly of Shape Memory Polymer Printed by Fused Deposition Modeling

We demonstrated the method for self-assembly of a polyurethane-based shape memory polymer (SMP) printed by a fused deposition modeling (FDM) 3D printer. SMP transfers between a rubber state and a glass state by the change of temperature, and this characteristic is usually used for memorizing a 3D shape. In this study, we used this characteristic not for shape memory but for self-assembly. When a SMP filament is printed in a rubber state by FDM, some internal stress is introduced to the printed SMP structure. Above the glass transition temperature $(T_{g})$, the SMP structure transfers to a rubber state and releases internal stress and shrinks. Utilizing bi-layer structure with different shrink rate, we demonstrated that 2D SMP structures can transform into 3D structures. We achieved to control the rate and direction of shrinking by varying printing temperatures and patterns, which then allowed defining bending directions to form 3D structures.
A novel shape detection method for continuum soft manipulator based on cable encoders

In this paper, a novel shape detecting method is proposed for continuum soft manipulator to detect the shape in real time, so as to achieve high-precision position and attitude control. The method uses three cable encoders to measure the length of the manipulator per section, and they are distributed at 120 degrees apart from the endplate of the manipulator. Based on the theoretical hypothesis that the soft manipulator has infinite degrees of freedom (DOF), the kinematic model for the single-section manipulator is developed by the piecewise constant curvature method. Further, the kinematic model is extended to the multi-section manipulator via improved D-H method, which achieves the mapping from the length information to the pose of the manipulator. Finally, the three-dimensional shape of the soft manipulator is simulated in real time by MATLAB, which verified the effectiveness of the proposed shape detection method.
Wide Band Stripline Circulator at Ku Band For Space Applications

Wide band 3 port Stripline coaxial circulator at Ku band is introduced. The proposed design covers all different sub-band of Ku band frequencies which are being utilized in satellite transponders. The design utilizes Y –Junction ferrite operating at below resonance.25% Wide bandwidth in proposed circulators is achieved using a quarter-wave transformer coupling at all the ports. Excellent insertion-loss variation < 0.2dB, insertion loss<0.5dB, Return Loss>20dB & Isolation>20dB over 10.5 GHz – 13.5 GHz have been demonstrated to meet stringent specifications of satellite communication systems. Stable performance of circulator over temperature range -10 °C to +60 °C is achieved. The circulator also survived qualification level Sine & Random vibration test for Satellite application.
Quality Requirements: Analysis of Utilization in the Systems of a Financial Institution

This article aims at expanding the understanding of the use of quality requirements in line with the classification elements contained in ISO/IEC 25010 sub-characteristics. An analysis was made of 26 systems in a large-size public financial institution, including systems used outside and inside the organization. We used content analysis and the NVivo software to categorize and analyze 942 quality requirements. Considering that the quality requirements chosen were different in their levels of abstraction, detail, and completeness, criteria were defined to allow the classification. Based on the result obtained, it was found that a large part of the previously defined requirements follows the line of classification of the standard, in spite of their having different terms. The analysis also identified requirements that follow a common standard. It was also possible to identify the following high interest characteristics: Usability (31%), Performance Efficiency (20%), and Maintainability (15%). The Functional suitability and Compatibility characteristics had a smaller percentage of attention, each one with less than 3% of requirements identified.
Automated Detection of Human Blastocyst Quality Using Convolutional Neural Network and Edge Detector

IVF (in vitro fertilization) is one type of assisted reproduction technology (ART) that can be a hope for couples with fertility problems (infertility) to get progeny. In supporting the success of IVF, there are several factors that can be an important role the one of which is in determining the quality of the embryo to be implantation. There are several numbers of previous researchers who had conducted research on determining the quality of the embryo but were still assisted by an embryologist and not automatically can detect the grade of embryo quality. In this paper, we propose a Convolutional Neural Network (CNN) model using image processing for detection quality of blastocyst grade with automatically and improve the accuracy. Keras is used for the implementation of CNN. We have tested our model and have been able to achieve a detection accuracy of 64.29% without image pre-processing and 84.62% using image pre-processing with Canny edge detector.
Vehicle detection in aerial images based on lightweight deep convolutional network

Vehicle detection in aerial images is an interesting and challenging task. Traditional meth-ods are based on sliding-window search and handcrafted features, which limits the representation power and has heavy computational costs. Recent research have shown that deep-learning algorithms are widely used in the ﬁeld of object detection. However, the deep-learning algorithms still face many difﬁculties and challenges in the object detection under the aerial scene. Meanwhile, the high computational cost of detection algorithms lead to low-detection efﬁciency. In this study, we build a fast and accurate lightweight detection framework for vehicle detection in aerial scenes. The proposed detection method improves the expressive ability of detection network and signiﬁcantly reduces the amount of calculations in the model. Meanwhile, setting suitable anchor boxes according to the size of the object vehicles have been introduced in our model, which also effectively improves the performance of the detection. In addition, we have published a new aerial vehicle image dataset and veriﬁed the effectiveness of our method. In the Munich dataset and our dataset, our method achieves 85.8% and 91.2% of the mean average precision (mAP), and its detection time is 1.78 and 0.048 s on Nvidia Titan XP. Our results show that the proposed framework achieves signiﬁcant improvement over several alternatives and state-of-the-art schemes with higher accuracy and less detection time.
Why Do I Study the Nursing Career? The Importance of the Motivation and the Vocation

Analyze the predictive relationship between motivation, vocational interests and habits of studies in students of nursing of a private university in Lima, Peru is the objectives of this research. The study involved 125 nursing students (53 of the first grades/72 of past grades) selected by an intentional sampling. The results showed, controlled motivation predicts the study's habits significantly, the time's distribution and concentration habit's, in both groups of students; also controlled motivation predicts work's habits in students of past grades. And autonomous motivation predicts vocational interests, specifically in the personal attitudes toward the career in the first grades students. On the other hand, in students of past grades, vocational interests predict study habits and reading techniques. And finally, in the last grades students' personal attitudes toward career predict habits for work and reading techniques.
Matching-Based Resource Allocation for Multi-User URLLC in Unlicensed Frequency Bands : (Invited Paper)

One of the key services of the upcoming fifth generation (5G) of wireless communications systems and beyond is considered to be ultra-reliable low latency communications (URLLC). However, enabling URLLC is challenging due to the strict requirements in terms of latency and reliability. Focusing on the demands of wireless factory automation, the scope of this work is to discuss conflicting priorities of resource allocation for URLLC networks such as matching stability, fairness between multiple users, and maximum throughput. Since wireless factory automation requires also cost-efficiency and global applicability, the unlicensed 5 GHz ISM band is modelled as an interference-limited multi-connectivity system. In the context of stable matching the influence of the parameter quota is studied, characterizing the maximum number of channels for any user. In order to link stable matching with minimum rate requirements, a new resource allocation algorithm is proposed. Selected approaches are applied to an exemplary scenario and their performance is comparatively evaluated to analyze the trade-offs between achieved maximum sum rates and fairness, i.e., minimum per user rate.
Low-Complexity Sequential Information and Energy Reception

This contribution evaluates and optimizes the performance of simultaneous wireless information and power transfer (SWIPT) with an integrated energy and information receiver, which is characterized by low complexity and energy cost. To this end, a tractable expression for the achievable rate is derived, which is subsequently used to quantify the achievable harvested energy−rate region for the considered time-switching (TS) protocol. Sequential reception of energy and information can be implemented with the aid of TS, which also reduces complexity whilst it is useful in applications that the receiver does not have to be continuously active. In this context, the joint harvested energy−rate outage probability is also defined and minimized for a point-to-point and multicasting system, determining the optimal TS factor. Finally, respective computer simulations corroborate the effectiveness of the proposed framework, whilst interesting insights are developed which are expected to be useful in the design and effective operation of TS wireless power systems.
A 5800- $\mu$ m2 Resistor-Based Temperature Sensor With a One-Point Trimmed Inaccuracy of ±1.2 °C ( $3\sigma$ ) From −50 °C to 105 °C in 65-nm CMOS

This letter describes a compact resistor-based temperature sensor intended for the thermal monitoring of microprocessors and DRAMs. It consists of an <inline-formula> <tex-math notation="LaTeX">$RC$ </tex-math></inline-formula> poly phase filter (PPF) that is read out by a frequency-locked loop (FLL) based on a dual zero-crossing (ZC) detection scheme. The sensor, fabricated in 65-nm CMOS, occupies 5800 <inline-formula> <tex-math notation="LaTeX">${\boldsymbol{\mu }}\text{m}^{2}$ </tex-math></inline-formula> and achieves moderate accuracy [±1.2 °C (<inline-formula> <tex-math notation="LaTeX">$3{\boldsymbol{\sigma }}$ </tex-math></inline-formula>)] over a wide temperature range (−50 °C to 105 °C) after a one-point trim. This is <inline-formula> <tex-math notation="LaTeX">$2\times $ </tex-math></inline-formula> better than the previous compact resistor-based sensors. Operating from 0.85 to 1.3-V supplies, it consumes 32.5-<inline-formula> <tex-math notation="LaTeX">${\boldsymbol{\mu }}\text{A}$ </tex-math></inline-formula> and achieves 2.8-mK resolution in a 1-ms conversion time, which corresponds to a resolution FoM of 0.26 pJ<inline-formula> <tex-math notation="LaTeX">$\cdot \text{K}^{2}$ </tex-math></inline-formula>.
An Object-Oriented Semantic SLAM System towards Dynamic Environments for Mobile Manipulation

For practical applications of mobile manipulation, the robot should have the ability to model the environment geometrically and analyze the object of interest. If there are people or other robots working around, then the robot also needs to have good adaptability to the dynamic environment. In this paper, we propose a SLAM system which can perform object-oriented semantic mapping of a dynamic environment adaptively. The SLAM system consists of six threads, which can eliminate the effects of dynamic objects, analyze models of previously unseen object instances and create a global three-dimensional map of the environment simultaneously. The proposed SLAM system is verified on the TUM RGB-D dataset. Furthermore, the system is applied in a mobile manipulator for object grasping applications and achieves satisfactory results.
A Reconfigurable Screen in the Antenna Nearfield for Media-Based Modulation Scheme

A novel application for reconfigurable screen of unit cell array in the nearfield of an antenna is proposed for media-based modulation (MBM) technique. In MBM, a single tone is transmitted by an antenna and the channel fading coefficients at the receivers are the alphabets. The proposed screen structure is inspired by a frequency selective surface, where transmission through a unit cell is varied to achieve different channel fading coefficients. A 4×4 array of unit cells is used to generate different alphabets for MBM at an operating frequency of 5 GHz. The measured results validate simulations and the corresponding scatterplot or alphabet is calculated from the measured data, that demonstrates the feasibility for MBM.
Neural Network Based Successive Cancellation Decoding Algorithm for Polar Codes in URLLC

Polar codes are considered as a competitive candidate for 5G ultra-reliable and low-latency communication (URLLC) channel codes, but its strict latency and reliability requirements pose signicant challenges to the existing decoding schemes, especially in terms of decoding latency. In this paper, we propose a neural network based successive cancellation (NN-SC) decoding algorithm. In the proposed algorithm, neural networks are used to replace the local decoders for rate-R constituent codes because of their one-shot decoding capacity, which greatly reduce the decoding latency and algorithmic complexity. The simulation results indicate that the NN-SC decoding algorithm can achieve comparable reliability performance against the successive cancellation (SC) decoding for a polar code of length 128 and rate 1/6, while reducing the decoding latency by 65.2% when compared with the simplified SC decoding. In addition, for two conventional decoding algorithms: SC and belief propagation (BP) decoding, the proposed algorithm can further reduce the decoding latency by 22.8% and 13.8%, respectively.
Optical-to-THz Frequency Down-Conversion Utilizing Two-Dimensional Plasmons

We theoretically study the carrier frequency down-conversion from optical signals to terahertz signals utilizing two-dimensional plasmons in an InGaAs-channel high-electron-mobility transistor (InGaAs-HEMT). We demonstrate that the down-conversion can be implemented by the so-called photonic double-mixing functionality in the HEMT utilizing the plasmonic hydrodynamic nonlinearities and that the double-mixing conversion gain can be enhanced by orders of magnitude with the help of the plasmon-resonance effect.
Wrinkled Microelectrode Interface Based on Oil-Pretreated Hyperelastic Substrate

This paper reports a unique fabrication method to obtain wrinkled microelectrodes with different surface morphologies based on different hyperelastic substrates for the first time. The wrinkle microstructures are enhanced by mixture silicone oil in the uncured poly (dimethyl siloxane) (PDMS) or Ecoflex polymer followed by oil-extraction in chloroform and depositing $5\ \mu \mathrm{m}$ Parylene-C film. The wrinkle amplitude of the oil-pretreated PDMS and Ecoflex with Parylene-C top layer show 5-fold and 125-fold increase than the unpretreated ones, respectively. Besides, the wrinkled 3D microelectrode surface distinctly exhibits greater electrochemical properties than the flat 2D one, with impedance decreases of 29.2% and 38.9% for the oil-pretreated PDMS and Ecoflex elastomer.
Investigating How Business Process Ambidexterity Facilitates Business-IT Alignment in Public Sector Organizations.

In today’s world of digital transformation and global hyper-competition the need for organizations to manage and innovate their Business Processes in both incremental and disruptive ways is greater than ever, both for private and public organizations. The nascent concept of Business Process Ambidexterity (balancing process exploitation and exploration) has been receiving a growing interest in the academia, and my research aims to address three research gaps: (1) the conceptualization of Business Process Ambidexterity and guidance on its implementation; (2) its impact on business-IT alignment, and (3) the specific contingency factors of Business Process Ambidexterity in the public sector. I will address these gaps through a research plan, covering a large-scale survey, extreme case research, Delphi study and design science research. At this stage I have completed a Systematic Literature Review of Business Process Ambidexterity, and I am preparing the next steps of my research.
Model-free in-hand manipulation based on commanded virtual contact points

This paper presents a simple strategy to allow the rotation of unknown objects using a robotic hand equipped with tactile sensors. The tactile and kinematic information, obtained while that the object is manipulated, is used to determine the hand configurations that change the object position. The approach was successfully tested using an anthropomorphic robotic hand (Allegro Hand), with the fingertips modified to include tactile sensors (WTS-FT). Using three fingers of the hand, every-day objects were successfully rotated without using their model for the determination of the hand movements.
Features Extraction Applied to the Analysis of the Sounds Emitted by Honey Bees in a Beehive

Last years increase in bee mortality has underlined the necessity of an intensive bee hive monitoring in order to better understand the problems which are seriously affecting the honey bee health. Sound emitted inside a beehive is one of the key parameters for a non-invasive monitoring of their health condition. In this context, the proposed work aims at analyzing the bees' sound introducing features extraction useful for sound classification techniques and for determine dangerous situations. Several experiments on a real scenario have been performed focusing on orphaned colony case and highlighting the potentiality of the proposed approach.
Precise Comb-Based Fourier Transform Spectroscopy for Line Parameter Retrieval

Accurate parameters of molecular transitions are needed for data analysis in many applications, ranging from atmospheric research to astrophysics and determination of fundamental constants. Optical frequency comb Fourier transform spectroscopy (OFC-FTS) is particularly well-suited for high-precision measurements of broadband molecular spectra. From these spectra, the parameters of individual transitions — all measured simultaneously under the same experimental conditions — can be determined. We use a mechanical OFC-FTS spectrometer with sub-nominal resolution [1, 2] to perform precise broadband measurements of entire molecular bands of CO2 using either direct absorption spectroscopy or cavity-enhanced complex refractive index spectroscopy (CE-CRIS) [3] and we extract line parameters for line shapes beyond the Voigt profile.
A Grid Connection Mechanism of Large-scale Distributed Energy Resources based on Blockchain

Distributed energy resource (DER) will become the main primary energy in the future Smart Grid. However, it is impossible for DERs to connect to the grid freely and reliably through traditional technology such as micro grid or virtual power plant. As a new distributed computing paradigm, blockchain has the characteristics of security, transparency and decentralization. Consider these characteristics, this paper proposed a blockchain based virtual power plant model for DER’s grid connection. The coordinated control method of virtual power plant and the independent grid connected behavior of DERs are organically linked by the incentive mechanism of blockchain, realizing the distributed dispatching calculation of virtual power plant. Results of case study showed that the proposed model could not only effectively reduce calculation costs of VPP, but also make grid connection more freely for DERs.
On the Use of Spatial Diversity under Highly Challenging Channels for Ultra Reliable Communications

The Industry 4.0 concept is the result of latest technical advances that have completely changed the existing industrial vision, not only from the mechanical point of view, but also from the Machine-to-Machine (M2M) communication perspective. This revolution encompasses wireless communication technologies that are expected to be the replacement for traditional wired and fixed communication systems. However, industrial propagation channels are still a challenge for wireless industrial network deployments. This paper addresses this problem by proposing spatial diversity based retransmissions. Two general retransmission schemes have been tested: default and smart. Moreover, specific time scheduling choices have been proposed. The impact of the number of transmitters in relation to communication reliability has been analyzed. Results show that the use of spatial diversity based retransmissions makes restrictive reliability values feasible under realistic conditions. In fact, in the case of smart retransmissions, adding a second transmitter the reliability increases around 8 dB. Moreover, whereas the channel coherence time is a critical parameter for time based retransmissions, in the case of spatial diversity, the reliability performance has no dependency on the channel coherence time.
Terahertz Deep Learning Computed Tomography

We present a supervised terahertz deep learning computed tomography (THz DL-CT) system, which offers superior image quality compared with conventional THz CT method evaluated by 3D printed objects. To the best of our knowledge, this is the first demonstration of a THz DL-CT system capable of visualizing hidden objects with multi-material systems.