bluuebunny/crossref_metadata_2025 huggingface dataset:
Multilingual twitter sentiment analysis using machine learning
Authors: Arun K. , Srinagesh A.
Published: September 2020

Twitter sentiment analysis is one of the leading research fields. Most of the researchers were contributed to twitter sentiment analysis in English tweets, but few researchers focus on the multilingual twitter sentiment analysis. Some challenges are hoping for the research solutions in multilingual twitter sentiment analysis. This study presents the implementation of sentiment analysis in multilingual twitter data and improves the data classification up to the adequate level of accuracy. Twitter is the sixth leading social networking site in the world. Active users for twitter in a month are 330 million. People can tweet or re-tweet in their languages and allow users to use emoji’s, abbreviations, contraction words, miss spellings, and shortcut words. The best platform for sentiment analysis is twitter. Multilingual tweets and data sparsity are the two main challenges. In this paper, the MLTSA algorithm gives the solution for these two challenges. MLTSA algorithm divides into two parts. One is detecting and translating non-English tweets into English using natural language processing (NLP). And the second one is an appropriate pre-processing method with NLP support can reduce the data sparsity. The result of the MLTSA with SVM achieves good accuracy by up to 95%.
An approach for a multi-stage under-frequency based load shedding scheme for a power system network
Authors: Siyanda Mnguni Mkhululi Elvis , Mfoumboulou Yohan Darcy
Published: September 2020

The integration of load shedding schemes with mainstream protection in power system networks is vital. The traditional power system network incorporates different protection schemes to protect its components. Once the power network reaches its maximum limits, and the load demand continue to increase the whole system will experience power system instability. The system frequency usually drops due to the loss of substantial generation creating imbalance. The best method to recover the system from instability is by introducing an under-frequency load shedding (UFLS) scheme in parallel with the protection schemes. This paper proposed a new UFLS scheme used in power systems and industry to maintain stability. Three case studies were implemented in this paper. Multi-stage decision-making algorithms load shedding in the environment of the DIgSILENT power factory platform is developed. The proposed algorithm speeds-up the operation of the UFLS scheme. The load shedding algorithm of the proposed scheme is implemented as a systematic process to achieve stability of the power network which is exposed to different operating conditions. The flexibility of the proposed scheme is validated with the modified IEEE 39-bus New England model. The application of the proposed novel UFLS schemes will contribute further to the development of new types of engineers.
Feasibility and optimal design of a hybrid power system for rural electrification for a small village
Authors: Adebanji Bankole , Adepoju Gafari Abiola , Olulope Paul , Fasina Taiwo , Adetan Oluwumi
Published: September 2020

A hybrid renewable energy system is at present accepted globally, as the best option for rural electrification particularly in areas where grid extension is infeasible. However, the need for hybrid design to be optimal in terms of operation and component selection serves as a challenge in obtaining reliable electricity at a minimum cost. In this work, the feasibility of installing a small hydropower into an existing water supply dam and the development of an optimal sizing optimization model for a small village-Itapaji, Nigeria were carried out. The developed hybrid power system (HPS) model consists of solar photovoltaic, small hydropower, battery and diesel generator. The optimal sizing of the system’s components for optimum configuration was carried out using Genetic Algorithm. The hybrid model’s results were compared with hybrid optimization model for electric renewable (HOMER) using correlation coefficient (r) and root mean square error (RMSE) to verify its validity. The results of the simulation obtained from the developed model showed better correlation coefficient (r) of 0.88 and root mean square error (RMSE) of 0.001 when compared to that of HOMER. This will serve as a guide for the power system engineers in the feasibility assessment and optimal design of HPS for rural electrification.
Tool delivery robot using convolutional neural network
Authors: Pinzon-Arenas Javier , Jimenez-Moreno Robinson
Published: September 2020

In the following article, it is presented a human-robot interaction system where algorithms were developed to control the movement of a manipulator in order to allow it to search and deliver, in the hand of the user, a desired tool with a certain orientation. A Convolutional Neural Network (CNN) was used to detect and recognize the user's hand, geometric analysis for the adjustment of the delivery status of the tool from any position of the robot and any orientation of the gripper, and a trajectory planning algorithm for the movement of the manipulator. It was possible to use the activations of a CNN developed in previous works for the detection of the position and orientation of the hand in the workspace and thus track it in real time, both in a simulated environment and in a real environment.
Analysis of threats and security issues evaluation in mobile P2P networks
Authors: Mohammed Ali Abdulwahhab , Kadhim Dheyaa Jasim
Published: September 2020

Technically, mobile P2P network system architecture can consider as a distributed architecture system (like a community), where the nodes or users can share all or some of their own software and hardware resources such as (applications store, processing time, storage, network bandwidth) with the other nodes (users) through Internet, and these resources can be accessible directly by the nodes in that system without the need of a central coordination node. The main structure of our proposed network architecture is that all the nodes are symmetric in their functions. In this work,

the security issues of mobile P2P network system architecture such as (web threats, attacks and encryption) will be discussed deeply and then we propose different approaches and we analysis and evaluation of these mobile P2P network security issues and submit some proposal solutions to resolve the related problems with threats and other different attacks since these threats and attacks will be serious issue as networks are growing up especially with mobility attribute in current P2P networks.
Spectrum sharing in cognitive radio networks
Authors: Martinez Julian , Hernandez Cesar , Pedraza Luis
Published: September 2020

Cognitive radio networks are the next step to tackle scarcity in wireless networks given the increasing demand of radioelectric spectrum where the proposed solution is to share said resource to improve this situation. In the present article, a review of the current state of spectrum sharing in cognitive radio networks. To achieve this purpose, the articles published over the last 4 years on the matter were reviewed including topics such as mobile networks and TV. Some studies and simulations proposed to share the spectrum is shown. The current state of the studies reveals that there has been significant progress in this research area yet it is necessary to continue similar studies and set in motion different schemes.
Numerical algorithm for solving second order nonlinear fuzzy initial value problems
Authors: Jameel A. F. , Anakira N. R. , Shather A. H. , Saaban Azizan , Alomari A. K.
Published: September 2020

The purpose of this analysis would be to provide a computational technique for the numerical solution of second-order nonlinear fuzzy initial value (FIVPs). The idea is based on the reformulation of the fifth order Runge Kutta with six stages (RK56) from crisp domain to the fuzzy domain by using the definitions and properties of fuzzy set theory to be suitable to solve second order nonlinear FIVP numerically. It is shown that the second order nonlinear FIVP can be solved by RK56 by reducing the original nonlinear equation intoa system of couple first order nonlinear FIVP. The findings indicate that the technique is very efficient and simple to implement and satisfy the Fuzzy solution properties. The method’s potential is demonstrated by solving nonlinear second-order FIVP.
Ontology-based context-sensitive software security knowledge management modeling
Authors: Alenezi Mamdouh
Published: September 2020

The disconcerting increase in the number of security attacks on software calls for an imminent need for including secure development practices within the software development life cycle. The software security management system has received considerable attention lately and various efforts have been made in this direction. However, security is usually only considered in the early stages of the development of software. Thus, this leads to stating other vulnerabilities from a security perspective. Moreover, despite the abundance of security knowledge available online and in books, the systems that are being developed are seldom sufficiently secure. In this paper, we have highlighted the need for including application context sensitive modeling within a case-based software security management system. Furthermore, we have taken the context-driven and ontology-based frameworks and prioritized their attributes according to their weights which were achieved by using the Fuzzy AHP methodology.
Multi-objective Pareto front and particle swarm optimization algorithms for power dissipation reduction in microprocessors
Authors: Sulaiman Diary R.
Published: September 2020

The progress of microelectronics making possible higher integration densities, and a considerable development of on-board systems are currently undergoing, this growth comes up against a limiting factor of power dissipation. Higher power dissipation will cause an immediate spread of generated heat which causes thermal problems. Consequently, the system's total consumed energy will increase as the system temperature increase.

High temperatures in microprocessors and large thermal energy of computer systems produce huge problems of system confidence, performance, and cooling expenses. Power consumed by processors are mainly due to the increase in number of cores and the clock frequency, which is dissipated in the form of heat and causes thermal challenges for chip designers. As the microprocessor’s performance has increased remarkably in

Nano-meter technology, power dissipation is becoming non-negligible. To solve this problem, this article addresses power dissipation reduction issues for high performance processors using multi-objective Pareto front (PF), and particle swarm optimization (PSO) algorithms to achieve power dissipation as a prior computation that reduces the real delay of a target microprocessor unit. Simulation is verified the conceptual fundamentals and optimization of joint body and supply voltages (Vth-VDD) which showing satisfactory findings.
Authentication and password storing improvement using SXR algorithm with a hash function
Authors: Polpong Jakkapong , Wuttidittachotti Pongpisit
Published: September 2020

Secure password storing is essential in systems working based on password authentication. In this paper, SXR algorithm (Split, Exclusive OR, and Replace) was proposed to improve secure password storing and could also be applied to current authentication systems. SXR algorithm consisted of four steps. First, the received password from users was hashed through a general hash function. Second, the ratio and the number of iterations from the secret key (username and password) were calculated. Third, the hashed password and ratio were computed, and the hashed password was divided based on the ratio (Split) into two values. Both the values were applied to XOR equation according to the number of iterations, resulting in two new values. Last, the obtained values were concatenated and stored in the database (Replace). On evaluating, complexity analyses and comparisons has shown that SXR algorithm could provide attack resistance with a stronger hashed password against the aforementioned attacks. Consequently, even if the hackers hacked the hashed password, it would be challenging and would consume more time to decrypt the actual one, because the pattern of the stored password is the same as the one that has been hashed through the general hash function.
A mathematical model of movement in virtual reality through thoughts
Authors: Trenchev Ivan , Mavrevski Radoslav , Traykov Metodi , Zajmi–Rugova Ilire
Published: September 2020

In this article, we'll introduce ways to build virtual worlds through different computer programs. We will show the method of rectangles for analyzing data obtained from the electroencephalogram. We will demonstrate basic mathematical models for movement prediction in a system of virtual reality. Using this data, the main transformations are possible-change of position and rotation (change of orientation).
Impact of rail impedance intrinsic variability on railway system operation, EMC and safety
Authors: Mariscotti Andrea
Published: September 2020

Running rails in electrified transportation systems are the interface element for several phenomena related to system performance, electromagnetic compatibility and safety: useful voltage at rolling stock, short circuit current, induced voltage, stray current, and track circuit operation. This work presents the physical and mathematical groundings of rail electrical parameters (dc and ac resistance, ac internal and external inductance) and experimental results available in the literature, discussing variability and reliability for each interface. The results consist thus of the identification of the relevant rails longitudinal electrical parameters, the presentation of a set of reliable experimental values, and the discussion of the best approach to manage their variability and uncertainty.
Simulation of a microgrid for a non-interconnected zone that integrates renewable energies
Authors: Reina German , Mauledoux Mauricio , Aviles Oscar A.
Published: September 2020

This paper develops a simulation of a small electrical network (Microgid) that integrates renewable energies, the model of the micro network is made up of a solar energy source, a wind energy source, an energy storage element, a non-renewable source such as a diesel generator. The model of the microgrid represent a non-interconnected area from the electrical network in Colombia. The non-interconnected areas sometimes depend on unreliable connections to the grid integration of renewable energies could be the best option to guarantee energy in these sectors and allow generating projects with social impact. A possible solution to this deficit of energy is to supplement the production of energy with renewable energy plants from resources as sun or wind. The simulated model allowed to study the effects of the network in island mode and in interconnected mode, showing the imbalances that can be obtained by integrating renewable energies and storage systems. It is verified that with an inclusion of more than 30% of power in renewable energies there is the possibility of having load imbalances, which affect the frequency and cause instability in the network. It also verifies how a control system can regulate the load balance but must interact with the other energy sources.
Position and speed optimization of servo motor control through FPGA
Authors: Ajel Ahmed R. , Abdul Abbas Huda M. , Mnati Mohannad Jabbar
Published: September 2020

We have put our model in this paper in which we will be controlling the speed and direction of the servomotor through FPGA. So, as to guarantee the precision from the check control procedure, we have made a project in which the document provides the control plane associated with servo motor depending on Altera DE1 board gentle primary processor as program controller. The system utilizes FPGA since the primary gadget, as well as within Quartus II 10.0 program atmosphere. The associated control components aremade to type a good executable control program in which speed and direction will be controlled the servo motor performance. The particular handle signs from your handle method are usually separated and amplified which results in the push to appreciate the particular handle with the servo motor. Based on the features associated with Altera, it is expounded through 2 facets of equipment’s hardware as well as a software program that supplies an answer for that style associated with the servo control system. This particular document utilizes the actual PID control formula to manage the actual common screening device to attain versatile as well as precise control reasons. The actual equipment execution from the PID control formula is put in place through FPGA; precise as well as effective control program is built to enhance the speed and performance of the servomotor through FPGA.
Planning multi-terminal direct current grids based graphs theory
Authors: Rios Mario A. , Acero Fredy A.
Published: September 2020

Transmission expansion planning in AC power systems is well known and employs a variety of optimization techniques and methodologies that have been used in recent years. By contrast, the planning of HVDC systems is a new matter for the interconnection of large power systems, and the interconnection of renewable sources in power systems. Although the HVDC systems has evolved, the first implementations were made considering only the needs of transmission of large quantities of power to be connected to the bulk AC power system. However, for the future development of HVDC systems, meshed or not, each AC system must be flexible to allow the expansion of these for future conditions. Hence, a first step for planning HVDC grids is the planning and development of multi-terminal direct current (MTDC) systems which will be later transformed in a meshed system. This paper presented a methodology that use graph theory for planning MTDC grids and for the selection of connection buses of the MTDC to an existing HVAC transmission system. The proposed methodology was applied to the Colombian case, where the obtained results permit to migrate the system from a single HVDC line to a MTDC grid.
Straggler handling approaches in mapreduce framework: a comparative study
Authors: Katrawi Anwar H. , Abdullah Rosni , Anbar Mohammed , AlShourbaji Ibrahim , Abasi Ammar Kamal
Published: September 2020

The proliferation of information technology produces a huge amount of data called big data that cannot be processed by traditional database systems. These Various types of data come from different sources. However, stragglers are a major bottleneck in big data processing, and hence the early detection and accurate identification of stragglers can have important impacts on the performance of big data processing. This work aims to assess five stragglers identification methods: Hadoop native scheduler, LATE Scheduler, Mantri, MonTool, and Dolly. The performance of these techniques was evaluated based on three benchmarked methods: Sort, Grep and WordCount. The results show that the LATE Scheduler performs the best and it would be efficient to obtain better results for stragglers identification.
Commercial wind turbines modeling using single and composite cumulative probability density functions
Authors: Omar Othman A. M. , Ahmed Hamdy M. , Elbarkouky Reda A.
Published: September 2020

As wind turbines more widely used with newer manufactured types and larger electrical power scales, a brief mathematical modelling for these wind turbines operating power curves is needed for optimal site matching selections. In this paper, 24 commercial wind turbines with different ratings and different manufactures are modelled using single cumulative probability density functions modelling equations. A new mean of a composite cumulative probability density function is used for better modelling accuracy. Invasive weed optimization algorithm is used to estimate different models designing parameters. The best cumulative density function model for each wind turbine is reached through comparing the RMSE of each model. Results showed that Weibull-Gamma composite is the best modelling technique for 37.5% of the reached results.
A nested square-shape dielectric resonator for microwave band antenna applications
Authors: Ullah Ubaid , Mabrouk Ismail Ben , Al-Hasan Muath , Nedil Mourad , Ain Mohd Fadzil
Published: September 2020

In this paper, a nested square-shape dielectric resonator (NSDR) has been designed and investigated for antenna applications in the microwave band. A solid square dielectric resonator (SSDR) was modified systematically by introducing air-gap in the azimuth (ϕ-direction). By retaining the square shape of the dielectric resonator (DR), the well-known analysis tools can be applied to evaluate the performance of the NSDR. To validate the performance of the proposed NSDR in antenna applications, theoretical, simulation, and experimental analysis of the subject has been performed. A simple microstrip-line feeding source printed on the top of Rogers RO4003 grounded substrate was utilized without any external matching network. Unlike solid square DR, the proposed NSDR considerably improves the impedance bandwidth. The proposed antenna has been prototyped and experimentally validated. The antenna operates in the range of 12.34GHz to 21.7GHz which corresponds to 56% percentage bandwidth with peak realized gain 6.5dB. The antenna has stable radiation characteristics in the broadside direction. A close agreement between simulation and experimental results confirms the improved performance of NSDR in antenna applications.
Wireless sensor network’s localization based on multiple signal classification algorithm
Authors: Lafta Nabeel Aad , Hreshee Saad S.
Published: September 2020

Wireless sensor networks (WSNs) are a number of sensitive nodes senses a physical phenomenon at the position of their deployment then sends information to the base station to take appropriate operation. (WSNs) are used in many applications such track military targets, discover fires, study natural phenomena such as earthquakes, humidity, heat, etc. The nodes are spread in large areas and it is difficult to locate them manually because they are published randomly by planes or any other method and since the information received from sensitive nodes is useless without knowing their location in this case a problem resulted in the positioning of the nodes. So it unacceptable to equip each sensor node with global position system (GPS) due to various problems such as raises cost and energy consumption. In this paper explained a non-GPS technique to self-positioning of nodes in (WSNs) by using the multiple signal classification (MUSIC) algorithm to determine the position of the active sensor through estimated the direction of arrival (DOA) of the node signal. Then modified MUSIC algorithm (M-MUSIC) to solve the problem of coherent signal. MATLAB program successfully used to simulate the proposed algorithm.
A framework for IoT-enabled environment aware traffic management
Authors: Mohamed Firdhous Mohamed Fazil , Sudantha B. H. , Hussien Naseer Ali
Published: September 2020

Vehicular traffic has increased across all over the world especially in urban areas due to many reasons including the reduction in the cost of vehicles, degradation of the quality of public transport services and increased wealth of people. The traffic congestion created by these vehicles causes many problems. Increased environment pollution is one of the most serious negative effects of traffic congestion. Noxious gases and fine particles emitted by vehicles affect people in different ways depending on their age and present health conditions. Professionals and policy makers have devised schemes for better managing traffic in congested areas. These schemes suffer from many shortcomings including the inability to adapt to dynamic changes of traffic patterns. With the development of technology, new applications like Google maps help drivers to select less congested routes. But, the identification of the best route takes only the present traffic condition on different road segments presently. In this paper the authors propose a system that helps drivers select routes based on the present and expected environment pollution levels at critical points in a given area.
Maximum power point tracking techniques for photovoltaic systems: a comparative study
Authors: Abo-Sennah M. A. , El-Dabah M. A. , Mansour Ahmed El-Biomey
Published: September 2020

Photovoltaic systems (PV) are one of the most important renewable energy resources (RER). It has limited energy efficiency leading to increasing the number of PV units required for certain input power i.e. to higher initial cost. To overcome this problem, maximum power point tracking (MPPT) controllers are used. This work introduces a comparative study of seven MPPT classical, artificial intelligence (AI), and bio-inspired (BI) techniques: perturb and observe (P&O), modified perturb and observe (M-P&O), incremental conductance (INC), fuzzy logic controller (FLC), artificial neural network (ANN), adaptive neuro-fuzzy inference system (ANFIS), and cuckoo search (CS). Under the same climatic conditions, a comparison between these techniques in view of some criteria’s: efficiencies, tracking response, implementation cost, and others, will be performed. Simulation results, obtained using MATLAB/SIMULINK program, show that the MPPT techniques improve the lowest efficiency resulted without control. ANFIS is the highest efficiency, but it requires more sensors. CS and ANN produce the best performance, but CS provided significant advantages over others in view of low implementation cost, and fast computing time. P&O has the highest oscillation, but this drawback is eliminated using M-P&O. FLC has the longest computing time due to software complexity, but INC has the longest tracking time.
A powerful comparison of deep learning frameworks for Arabic sentiment analysis
Authors: Zahidi Youssra , Younoussi Yacine El , Al-Amrani Yassine
Published: September 2020

Deep learning (DL) is a machine learning (ML) subdomain that involves algorithms taken from the brain function named artificial neural networks (ANNs). Recently, DL approaches have gained major accomplishments across various Arabic natural language processing (ANLP) tasks, especially in the domain of Arabic sentiment analysis (ASA). For working on Arabic SA, researchers can use various DL libraries in their projects, but without justifying their choice or they choose a group of libraries relying on their particular programming language familiarity. We are basing in this work on Java and Python programming languages because they have a large set of deep learning libraries that are very useful in the ASA domain. This paper focuses on a comparative analysis of different valuable Python and Java libraries to conclude the most relevant and robust DL libraries for ASA. Throw this comparative analysis, and we find that: TensorFlow, Theano, and Keras Python frameworks are very popular and very used in this research domain.
Similarity-preserving hash for content-based audio retrieval using unsupervised deep neural networks
Authors: Panyapanuwat Petcharat , Kamonsantiroj Suwatchai , Pipanmaekaporn Luepol
Published: September 2020

Due to its efficiency in storage and search speed, binary hashing has become an attractive approach for a large audio database search. However, most existing hashing-based methods focus on data-independent scheme where random linear projections or some arithmetic expression are used to construct hash functions. Hence, the binary codes do not preserve the similarity and may degrade the search performance. In this paper, an unsupervised similarity-preserving hashing method for content-based audio retrieval is proposed. Different from data-independent hashing methods, we develop a deep network to learn compact binary codes from multiple hierarchical layers of nonlinear and linear transformations such that the similarity between samples is preserved. The independence and balance properties are included and optimized in the objective function to improve the codes. Experimental results on the Extended Ballroom dataset with 8 genres of 3,000 musical excerpts show that our proposed method significantly outperforms state-of-the-art data-independent method in both effectiveness and efficiency.
Use of a Novel Septal Occluder Device for Left Atrial Appendage Closure in Patients With Postsurgical and Postlariat Leaks or Anatomies Unsuitable for Conventional Percutaneous Occlusion
Authors: Della Rocca Domenico G. , Horton Rodney P. , Tarantino Nicola , Van Niekerk Christoffel Johannes , Trivedi Chintan , Chen Qiong , Mohanty Sanghamitra , Anannab Alisara , Murtaza Ghulam , Akella Krishna , Gianni Carola , Bassiouny Mohamed , Ahmadian-Tehrani Ashkan , Al-Ahmad Amin , Burkhardt J. David , Natale Veronica N. , Price Matthew , Gallinghouse G. Joseph , Gibson Douglas N. , Lakkireddy Dhanunjaya , Di Biase Luigi , Natale Andrea
Published: September 2020

Background:

Interventional therapies aiming at excluding the left atrial appendage (LAA) from systemic circulation have been established as a valid alternative to oral anticoagulation in patients at high thromboembolic risk. However, their efficacy on stroke prophylaxis may be compromised owing to incomplete LAA closure. Additionally, the need for an alternative thromboembolic prevention may remain unmet in patients with contraindications to oral anticoagulation whose appendage anatomy is unsuitable for some conventional devices commercially available. We aimed at evaluating the feasibility of LAA closure with the novel Gore Cardioform Septal Occluder in patients with incomplete appendage ligation or anatomic features which do not meet the manufacturer’s requirements for Watchman deployment.

Methods:

Twenty-one consecutive patients (mean age: 72±6 years; 85.7% males; CHA
2
DS
2
-VASc: 4.5±1.4; HAS-BLED: 3.6±1.0) were included. Transesophageal echocardiography was performed within 2 months to assess for residual LAA patency.

Results:

Fourteen patients had incomplete LAA closure following surgical (n=6) or Lariat ligation (n=8). In 7 patients with an appendage anatomy unsuitable for Watchman deployment, the mean maximal landing zone size and LAA depth were 14.4±1.3 and 18.6±2.8 mm. Successful Cardioform Septal Occluder deployment was achieved in all patients. No peri-procedural complications were documented. Procedure and fluoroscopy times were 46±13 and 14±5 minutes. Follow-up transesophageal echocardiography after 58±9 days revealed complete LAA closure in all patients.

Conclusions:

Transcatheter LAA closure via a Cardioform Septal Occluder device might be a valid alternative in patients with residual leaks following failed appendage ligation or whose LAA anatomy does not meet the minimal anatomic criteria to accommodate a Watchman device.

Graphic Abstract:

A
graphic abstract
is available for this article.
TRaNsMOGRiFiER: Fictional Narratives as Catalyst for Experimental Instrument-Building and Musical/Artistic Collaboration
Authors: Ferguson John R. , Bussigel Peter
Published: September 2020

The authors report on their artistic research project TRaNsMOGRiFiER and highlight musician-specific approaches to creating with technology that privilege the sharing of tools and practical knowledge. The use of fictional narratives as a catalyst for instrument-building and art-making is at the foreground of the discussion. By rethinking DIY/maker culture with an emphasis on collaboration and collective creativity, the authors highlight the tension between the production of fixed media output and practices that resist encapsulation. TRaNsMOGRiFiER underscores the benefits of hands-on learning and presents a collaborative artistic platform with a focus on open-ended processes and ongoing change.
Closed-Loop Deep Learning: Generating Forward Models With Backpropagation
Authors: Daryanavard Sama , Porr Bernd
Published: September 2020

A reflex is a simple closed-loop control approach that tries to minimize an error but fails to do so because it will always react too late. An adaptive algorithm can use this error to learn a forward model with the help of predictive cues. For example, a driver learns to improve steering by looking ahead to avoid steering in the last minute. In order to process complex cues such as the road ahead, deep learning is a natural choice. However, this is usually achieved only indirectly by employing deep reinforcement learning having a discrete state space. Here, we show how this can be directly achieved by embedding deep learning into a closed-loop system and preserving its continuous processing. We show in z-space specifically how error backpropagation can be achieved and in general how gradient-based approaches can be analyzed in such closed-loop scenarios. The performance of this learning paradigm is demonstrated using a line follower in simulation and on a real robot that shows very fast and continuous learning.
Repetitive Control for Multi-Joint Arm Movements Based on Virtual Trajectories
Authors: Uno Yoji , Suzuki Takehiro , Kagawa Takahiro
Published: September 2020

According to the neuromuscular model of virtual trajectory control, the postures and movements of limbs are performed by shifting the equilibrium positions determined by agonist and antagonist muscle activities. In this study, we develop virtual trajectory control for the reaching movements of a multi-joint arm, introducing a proportional-derivative feedback control scheme. In virtual trajectory control, it is crucial to design a suitable virtual trajectory such that the desired trajectory can be realized. To this end, we propose an algorithm for updating virtual trajectories in repetitive control, which can be regarded as a Newton-like method in a function space. In our repetitive control, the virtual trajectory is corrected without explicit calculation of the arm dynamics, and the actual trajectory converges to the desired trajectory. Using computer simulations, we assessed the proposed repetitive control for the trajectory tracking of a two-link arm. Our results confirmed that when the feedback gains were reasonably high and the sampling time was sufficiently small, the virtual trajectory was adequately updated, and the desired trajectory was almost achieved within approximately 10 iterative trials. We also propose a method for modifying the virtual trajectory to ensure that the formation of the actual trajectory is identical even when the feedback gains are changed. This modification method makes it possible to execute flexible control, in which the feedback gains are effectively altered according to motion tasks.
Review of the Scorpaena papillosa species complex (Teleostei: Scorpaenidae) with description of a new species from southwestern Australia
Authors: WIBOWO KUNTO , MOTOMURA HIROYUKI
Published: September 2020

A taxonomic review of the Scorpaena papillosa species complex, defined here as having 10 dorsal-fin soft rays, coronal spines, and two upwardly directed spines on the lacrimal bone, resulted in the recognition of two species and two subspecies, Scorpaena papillosa (Schneider & Forster, 1801) including two subspecies, i.e., S. papillosa papillosa (New Zealand) and S. papillosa ergastulorum Richardson, 1842a (southeastern Australia), and S. vesperalis n. sp. (southwestern Australia). Scorpaena p. papillosa and S. p. ergastulorum, are redescribed, with designation of a neotype for S. p. papillosa. Scorpaena vesperalis n. sp., described from coastal waters off southwestern Western Australia on the basis of 57 specimens, is characterized as follows: pectoral-fin rays 14–16; longitudinal scale rows 37–41; body depth 32.3–39.5 % of SL; upper-jaw length 19.6–22.5 % of SL; maxilla depth 5.7–7.3 % of SL; postorbital length 18.2–21.3 % of SL; least distance between interorbital ridges 1.4–2.7 % of SL; 1st anal-fin spine length 7.2–10.0 % of SL; anterior lacrimal spine simple, without additional small spinous points on its posterior margin; a single united pore behind the lower jaw symphysial knob; relatively large supraocular tentacle; all fins of preserved specimens usually uniformly whitish to translucent; and small body size (maximum recorded length 67.6 mm SL). The new species is likely endemic to southwestern Australia. Morphological ontogenetic changes in the relative lengths of some body proportions in the three taxa are also discussed.
On the identity of the centipede Sogona cyclareata Attems, 1947 (Geophilomorpha, Geophilidae)
Authors: FONSECA RÉGIA MAYANE PACHECO , AKKARI NESRINE , CHAGAS-JR AMAZONAS
Published: September 2020

The type material of Sogona cyclareata Attems, 1947 is revised. The syntype shares characters with representatives of the family Schendylidae and not the Geophilidae to which it is currently assigned. The species has the claw of the second maxillae pectinate and the labrum not divided into median and lateral portions. Sogona cyclareata presents also characters of the genus Schendylops Cook, 1899 such as the presence of two pores in each coxopleuron, ultimate legs without claws, and the arrangement of the sternal pores-fields. No Schendylops species known to date has the characters of S. cyclareata, so we propose the new combination Schendylops cyclareatus.
Provisioning of Virtual Machines in the Context of an Auto-Scaling Cloud Computing Environment
Authors: Rajput R. S. , Goyal Dinesh , Hussain Rashid , Singh Pratham
Published: September 2020

The cloud computing environment is accomplishing cloud workload by distributing between several nodes or shift to the higher resource so that no computing resource will be overloaded. However, several techniques are used for the management of computing workload in the cloud environment,
but still, it is an exciting domain of investigation and research. Control of the workload and scaling of cloud resources are some essential aspects of the cloud computing environment. A well-organized load balancing plan ensures adequate resource utilization. The auto-scaling is a technique
to include or terminate additional computing resources based on the scaling policies without involving humans efforts. In the present paper, we developed a method for optimal use of cloud resources by the implementation of a modified auto-scaling feature. We also incorporated an auto-scaling
controller for the optimal use of cloud resources.
Energy Efficient Synchronous Media Access Control for Wireless Sensor Networks
Authors: Guleria Kalpna , Kumar Sushil , Verma Anil Kumar
Published: September 2020

The technological advancements have brought a revolution in the field of communication, especially in the area of wireless communication. It has made the deployment of WSNs possible which comprise of a large number of low-power and low-cost sensor nodes to perform the task of sensing, processing, and communication. WSNs set stringent requirements for network lifetime, resource constraint, application specific behavior and they are highly dynamic in nature. The one factor which affects the most is the network lifetime and it requires the energy efficient operation to be performed. This article aims at providing researchers a clear understanding and deep insight into the selection MAC protocols which is one of the major design factor while establishing WSNs or developing an energy efficient routing protocol for WSNs. The article presents a systematic review of various low duty cycle syncronous MAC protocols along with an in-depth analytical comparison and discussion based on various performance metrics.
Innovative Economic Sector Development as a Key Economic Growth Factor
Authors: Sergeevna Budovich Lidia
Published: September 2020

The issue of the innovative economic sector development and innovation management is discussed in this article. In order to ensure the competent management of the implementation of the innovation model of the Russian economy development, first of all it is necessary to understand the
essence and content of the concepts that characterize this process. To date, as the analysis of scientific publications shows, scientists and practitioners are far from always having the same understanding of the content of such concepts. This explains the author’s attempt to define
the terms that describe the process of innovative economic development and their impact on the economic processes. The official documents and scientific papers present various interpretations of the concepts of ‘innovative development,’ ‘innovative economic sector,’
‘innovation processes.’
Food Supply Chain Traceability by Using Blockchain Technology
Authors: Sharma Anupam , Jhamb Deepika , Mittal Amit
Published: September 2020

In the digitized world, everything and products are being designed and used with the help of advanced technologies. The Agriculture industry is not an exception; Walmart has started tackling food safety by using blockchain technology in the supply chain. As agriculture is one of the most influential sectors for the world economy and has also a great impact on the livelihood of the people. As the agriculture industry is growing globally, it is difficult to keep an eye on the information of the whole food supply chain management. So be able to increase the transparency, food safety and customer satisfaction digitalization of food is the need of the hour. In context to Indian economy very little research has been done in the area of addressing farmer’s problem by using blockchain technology. This research will help in addressing the major issues of traceability, transparency and quality and trust in food supply chain management and the hybridisation of agriculture field by using blockchain technology. This new technology has led to new products and new methods to organise the supply chain in an efficient way and analyze the blockchain framework for the traceability of products. This study aims to find out the challenges and issues faced by the farmers in the food supply chain and to propose the relevant efficient and transparent solutions that will benefit farmers as well as customers in the long run.
Hemodynamic Changes with 1:1000 Epinephrine on Wrung-Out Pledgets Before and During Sinus Surgery
Authors: Peleman John R. , Tarwade Pritee , Han Xiaoxia , Penning Donald H. , Craig John R.
Published: September 2020

Background:

Intranasal topical 1:1000 epinephrine has been used safely and effectively for hemostasis during endoscopic sinus surgery (ESS). Prior studies assessing hemodynamic changes after intranasal topical epinephrine application have only used soaking wet cottonoid pledgets, and have only assessed for hemodynamic changes before any surgery being performed.

Objective:

The purposes of this study were to determine whether intranasal application of topical 1:1000 epinephrine with wrung-out cottonoid pledgets caused significant hemodynamic changes both before and during ESS, and whether it allowed for adequate hemostasis.

Methods:

A prospective evaluation of 30 patients with eosinophilic chronic rhinosinusitis with nasal polyps (CRSwNP) undergoing complete bilateral ESS was conducted. Heart rate, blood pressure (systolic, diastolic, and mean arterial pressure), and electrocardiography changes were recorded at 0, 1, 2, and 5-minute intervals after placing wrung-out epinephrine-saturated pledgets, both before and at the end of ESS. No submucosal epinephrine injections were performed. Estimated blood loss (EBL) and major intraoperative complications were recorded for all cases.

Results:

There were no significant hemodynamic changes or electrocardiographic abnormalities after placement of wrung-out epinephrine-soaked pledgets both before and after ESS. After bilateral ESS, there were actually mean decreases in heart rate and blood pressure parameters. Mean EBL was 75.8 ± 32.2 mL, and no major intraoperative complications occurred.

Conclusion:

Intranasal application of topical 1:1000 epinephrine via wrung-out cottonoid pledgets was effective for intraoperative hemostasis, and did not cause clinically significant alterations in hemodynamic parameters or cardiovascular events, either before or during ESS in patients with CRSwNP. Level of Evidence: 4
An Improbable Journey: The Career and Influence of Puncky P. Heppner
Authors: Neville Helen A. , Wang Yu-Wei
Published: September 2020

Puncky Paul Heppner is one of the most productive counseling psychologists; he is also a social justice advocate, loving partner, and artist. Dr. Heppner has influenced counseling psychology in immeasurable ways. He is internationally recognized for his research on applied problem-solving and research methods, widely acknowledged for his visionary and collaborative leadership style, and highly respected for his culturally informed mentoring. In this life narrative, we contextualize his numerous accomplishments. We first discuss the influence of his early life experiences, following his life journey through his undergraduate years and doctoral studies, to his 36-year career at the University of Missouri. We highlight the numerous ways in which Dr. Heppner has influenced (counseling) psychology, including increasing the racial, ethnic, and international representation in the field through his leadership and advocacy as president of the Society of Counseling Psychology and editor of The Counseling Psychologist.
Tooth Loss and Dementia: A Critical Examination
Authors: Thomson W.M. , Barak Y.
Published: September 2020

Dementia is a major contributor to dependence and disability in older people, with aging societies characterized by growing numbers of people living with the condition. Dementia rates are highest in those with low education early in life, midlife hypertension, midlife hearing loss, depression, obesity, loneliness, a sedentary lifestyle, or sustained exposure to smoking or diabetes. Tooth loss is a putative risk factor for dementia which has received increasing research attention, but systematic review findings are mixed. Three main mechanisms have been proposed, involving 1) tooth loss leading to compromised nutrition and then leading to poorer central nervous system (CNS) function; 2) tooth loss resulting in fewer interocclusal contacts and so less somatosensory feedback to the CNS, leading to impaired cognition; and (3) chronic periodontitis resulting in tooth loss, but not before the inflammation has affected the CNS, impairing cognition. None of these is supported by compelling empirical evidence. Here, we use the life course approach to propose a plausible, empirically supported explanation for the associations between missing teeth and poorer cognitive function in older people. Evidence from longstanding cohort studies demonstrates that the putative association arises from cognitive function much earlier in life, in childhood. People with better childhood cognitive function have better oral health and access to routine dental care as they go through life, losing fewer teeth along the life course. They are also much more likely to have better cognitive function in old age. Their less cognitively able childhood counterparts will experience higher disease rates and poorer access to care, resulting in greater incremental tooth loss. Comparison of the 2 groups at any age from the mid-20s on will show greater numbers of missing teeth in the group who were less cognitively able in childhood. Those differences will be most pronounced in old age.