Miracle-dz/UniFAR-FTUs huggingface dataset:
A real-time obstacle avoidance method for multi-AUV cluster based on artificial potential field

[Objectives]This paper proposes a real-time obstacle avoidance method based on artificial potential field,in order to cope with the many potential obstacles in complex underwater environment which affects the movement plan for multi-autonomous underwater vehicle(AUV) cluster. [Methods]Firstly,a formation method based on dynamic network topology is adopted,and the AUV is regarded as a node in the network. The potential field function is set to meet the formation requirements. Then,based on the artificial potential field method,the potential field function is established for the region where both targets and obstacles exist simultaneously. Afterwards,the potential field function is upgraded to an exponential function,such that the AUVs can be planned online for real-time accomplishment of the mission of obstacle avoidance for multi-AUV cluster. Finally,10 AUVs and 6 obstacles are simulated with Matlab software. [Results] The simulation results show that with this method,each AUV can successfully avoid obstacles and reach the safe area at the target point. [Conclusions]The artificial potential field function method may enable the multi-AUV to accurately avoid obstacle in real time. The advancement of this technology has important and positive significance for improving military operational capability.
Pt/CNT Micro-Nanorobots Driven by Glucose Catalytic Decomposition

Swimming micro-nanorobots have attracted researchers' interest in potential medical applications on target therapy, biosensor, drug carrier, and others. At present, the experimental setting of the swimming micro-nanorobots was mainly studied in pure water or H2O2 solution. This paper presents a micro-nanorobot that applied glucose in human body fluid as driving fuel. Based on the catalytic properties of the anode and cathode materials of the glucose fuel cell, platinum (Pt) and carbon nanotube (CNT) were selected as the anode and cathode materials, respectively, for the micro-nanorobot. The innovative design adopted the method of template electrochemical and chemical vapor deposition to manufacture the Pt/CNT micro-nanorobot structure. Both the scanning electron microscope (SEM) and transmission electron microscope (TEM) were employed to observe the morphology of the sample, and its elements were analyzed by energy-dispersive X-ray spectroscopy (EDX). Through a large number of experiments in a glucose solution and according to Stoker's law of viscous force and Newton's second law, we calculated the driving force of the fabricated micro-nanorobot. It was concluded that the structure of the Pt/CNT micro-nanorobot satisfied the required characteristics of both biocompatibility and motion.
On Multi-controller Placement Optimization in Software Defined Networking - based WANs

— Software Defined Networking (SDN) is a recent networking technology that promises important advantages in IP networking, related to flexibility at network and application level, together with powerful management and control. However, the SDN specific centralization creates scalability problems in large network environments. Multi-controller implementation of the SDN control plane for large networks can solve the scalability and reliability issues introduced by the SDN centralized logical control principle. There are still open research issues related to controllers placement, static or dynamic assignment of the network forwarding nodes to controllers, especially when network nodes/links and/or controllers failures appear or some constraints are imposed. This paper contains an analysis of some solutions proposed in the literature followed by a work in progress, on multi-criteria optimization methods applicable to the controller placement problem.
Lost in Time: Re-description and Ecological Re-assessment of two Indian Endemic Elattoneura Cowley, 1935 (Playcnemidiae) Damselflies

The Indian Elattoneura are a difficult group to identify due to their extreme morphological similarity and sparse information in identification keys and on geographical distribution. The ambiguity is prominent among two Peninsular Indian Elattoneura species, E. nigerrima (Laidlaw, 1917) and E. tetrica (Laidlaw, 1917), described a hundred years ago. Both species were described based on male specimens with scant information on their females. The species are IUCN Red-listed, E. nigerrima (Data Deficient) and E. tetrica (Least Concern). Hitherto it was thought that E. nigerrima was smaller than E. tetrica and both have non-overlapping geographical distribution. Here, we re-described both sexes of E. nigerrima; E. tetrica along with morphometric data and geospatial analysis. We found that E. nigerrima is significantly larger than E. tetrica. The species are largely allopatric in distribution, with the former having a much wider spatial distribution than previously thought. Based on our geospatial analysis, we provide occurrence data useful for the future IUCN assessments of E. nigerrima and E. tetrica. We highlight the importance of updating taxonomic status information and data on spatiotemporal distribution to proceed with the conservation of endemic insects such as Elattoneura damselflies. Our study indicates reassessments of Indian Odonata species are urgently needed.
Stock Market Trend Prediction using Supervised Machine Learning Algorithms

- Stock trend prediction is the difficult problems, due to stochastic nature which is disturbing both researchers and analysts over half a century. And also for those who are eager to invest in stock market but due to the risk of fluctuation in stock they are not much confidence to invest in stock market, so to overcome this problem our research work focuses to observe fluctuations in stock prices. In this research work four prediction algorithms are proposing using historical data to predict the stock market movements. The proposed supervised algorithms are K-Nearest Neighbor (KNN), Random Forest, Support Vector Machine (SVM) and Linear Regression. The historical data will be collected from Yahoo finance, Kaggle, Towards Data Science, NSE India. The results obtained from the different supervised algorithms for all four algorithms. We have obtained the result from different company dataset and analyzed, and overall performance and we got the random forest algorithm is the best for prediction we got highest 95.8% as a result
A Geographic Theorization of Zongos in Urban Ghana: A Complex Systems Approach

While Zongos have become a permanent abode for many people, especially migrants in urban Ghana, the dynamics of these communities are quite poorly understood. This paper provides a geographic analysis of the formation of Zongos, drawing heavily on a complex systems approach to explore how various variables, including space, ethnicity, class, citizenship, migration and environmental processes intersect to form and sustain Zongos in Ghana. Essentially, the paper throws more light on the key factors that contribute to the spatial concentration of the urban poor in Zongos and concludes with the consequences of having the urban poor living in highly segregated and economically depressed neighbourhoods in Ghanaian cities. The paper argues that the formation of Zongos is not solely attributable to the fondness of migrants from northern Ghana to live among people of like background while in southern cities, but also because of the exclusionary machinations of the majority and their housing gatekeepers.
Cost efficient internet of things based smart farm system for rural farmers: Leveraging design thinking approach

Farmers are faced with challenges of producing enough food and the use of traditional methods seems not to keep pace with the ever-growing demand of the populace thus creating increased concern in food scarcity. Although it has been identified that smart tools will enhance the production pace needed in the Agricultural sector, unfortunately, most of these tools are designed for farmers without their inputs, thus creating tools that are not meeting demands. This study focused on a farmer-centered design, development, and deployment approach to improving farm productivity. The design thinking approach was used to identify the specific need of the farmers in selected areas, ideas were created using brainstorming sessions involving experts in the field, and prototypes were developed and deployed to evaluate the impact performance. The result shows that the proposed system improved the cost-benefit ratio of crop farming from 2.14 to 2.26. This is a 12% productivity increase.
Validation Research on the Application of Depth-wise Separable Convolutional AI Facial Expression Recognition in Non-pharmacological Treatment of BPSD

One of the most obvious clinical reasons of dementia or The Behavioral and Psychological Symptoms of Dementia (BPSD) are the lack of emotional expression, the increased frequency of negative emotions, and the impermanence of emotions. Observing the reduction of BPSD in dementia through emotions can be considered effective and widely used in the field of non-pharmacological therapy. At present, this article will verify whether the image recognition artificial intelligence (AI) system can correctly reflect the emotional performance of the elderly with dementia through a questionnaire survey of three professional elderly nursing staff. The ANOVA (sig.=0.50) is used to determine that the judgment given by the nursing staff has no obvious deviation, and then Kendall’s test (0.722**) and spearman’s test (0.863**) are used to verify the judgment severity of the emotion recognition system and the nursing staff unanimously. This implies the usability of the tool. Additionally, it can be expected to be further applied in the research related to BPSD elderly emotion detection.
Development and Proximate Evaluation of Spirulina Enriched Food for Elderly Population

Spirulina is a multicellular cyanobacterium that has achieved a considerable popularity in the health sectors due to high protein content, antioxidant and macro and micro nutrients. The consumption of food containing spirulina can forget the complications/diseases related with protein and iron deficiencies especially elderly population. This regard, a study to require to development of spirulina enriched food for elderly population. In the present study, spirulina enriched food bar (SEFB) was developed. SEFB accept overall acceptability by panelist such as color and appearance, aroma/odour, flavor and taste, body and texture. SEFB showed good amount of protein (11.86%), and iron (30.24%) as compared to control. Afterward, the developed SEFB exhibited good amount of antioxidants content (42.86%) and moisture conent (12.86%), respectively. SEFB can be most attractive and nutritious food for elderly people due to rich source of protein and iron. This novel food can solve diseases/problems related with protein and iron deficiency.
How Many People Live in Politically Partisan Online News Echo Chambers in Different Countries?

Concern over online news echo chambers has been a consistent theme in recent debates on how people get news and information. Yet, we lack a basic descriptive understanding of how many people occupy bounded online news spaces in different countries. Using online survey data from seven countries we find that (i) politically partisan left-right online news echo chambers are real, but only a minority of approximately 5% of internet news users inhabit them, (ii) in every country covered, more people consume no online news at all than occupy partisan online echo chambers, and (iii) except for the US, decisions over the inclusion or exclusion of particular news outlets make little difference to echo chamber estimates. Differences within and between media systems mean we should be very cautious about direct comparisons between different echo chambers, but underlying patterns of audience overlap, and the continued popularity of mainstream outlets, often preclude the formation of large partisan echo chambers.
MARITIME BIG DATA ANALYSIS WITH ARLAS

Abstract. The maritime industry has become a major part of globalization. Political and economic actors are meeting challenges regarding shipping and people transport. The Automatic Identification System (AIS) records and broadcasts the location of numerous vessels and delivers a huge amount of information that can be used to analyze fluxes and behaviors. However, the exploitation of these numerous messages requires tools based on Big Data principles.Acknowledgement of origin, destination, travel duration and distance of each vessel can help transporters to manage their fleet and ports to analyze fluxes and focus their investigations on some containers based on their previous locations. Thanks to the historical AIS messages provided by the Danish Maritime Authority and ARLAS PROC/ML, an open source and scalable processing platform based on Apache SPARK, we are able to apply our pipeline of processes and extract this information from millions of AIS messages. We use a Hidden Markov Model (HMM) to identify when a vessel is still or moving and we create “courses”, embodying the travel of the vessel. Then we derive the travel indicators. The visualization of results is made possible by ARLAS Exploration, an open source and scalable tool to explore geolocated data. This carto-centered application allows users to navigate into the huge amount of enriched data and helps to take benefits of these new origin and destination indicators. This tool can also be used to help in the creation of Machine Learning algorithms in order to deal with many maritime transportation challenges.
On Stochastic Mirror Descent: Convergence Analysis and Adaptive Variants

We investigate the convergence of stochastic mirror descent in both relatively smooth and smooth convex optimization. In relatively smooth convex optimization we provide new convergence guarantees for stochastic mirror descent (SMD) with a constant stepsize. For smooth convex optimization we propose a new adaptive stepsize scheme – the mirror stochastic Polyak stepsize (mSPS). Notably, our convergence results in both settings do not make bounded gradient assumptions or bounded variance assumptions, and we show convergence to a neighborhood that van-ishes under interpolation. We complement our results with experiments across various supervised learning tasks and different instances of SMD, demonstrating the effectiveness of mSPS. Code is available at https://github.com/ IssamLaradji/mirror-sps .
The Effectiveness of STEAM-Based Augmented Reality Media in Improving the Quality of Natural Science Learning in Elementary School

This study describes the effectiveness of STEAM-based augmented reality (AR) learning media in natural science learning in elementary schools. This research used an experimental method. Six schools were involved as the subjects of this research, which was consisted of 3 elementary schools for experimental classes (60 students) and three elementary schools for control classes (60 students). The teachers involved were the 6th grader teachers. The data collection technique used 30 multiple choices questions for the students.The study results concluded that STEAM-based augmented reality effectively improved the quality of natural science learning in elementary schools. The t-test calculation results utilizing SPSS obtained t-count of 2.874 t-table of 1.980 (df-2= 122-2= 120). The normalized gain results showed a significant increase before and after using STEAM-based augmented reality media in natural science learning in elementary schools, which was 0.72 included in the high category.This research implies that research helps teachers optimize the use of media and teaching approaches. One of them is the use of STEAM with augmented reality media.
New Manufacturing Method of Glass Foam by Cold Expansion of Glass Waste

Abstract An innovation cold manufacturing method of glass foams is presented in the paper. Traditional foaming agents used in conventional expansion processes of glass waste at high temperature were substituted with aluminium powder in aqueous solution of calcium hydroxide, which releases hydrogen forming gas bubbles in the viscous sludge and then, by solidification, a porous structure typical for the glass foam. The manufactured foam is adequate for using as a thermal insulation material for inner wall of buildings, having the apparent density of 0.31 g·cm-3, the thermal conductivity of 0.070 W/m·K and the compressive strength of 1.32 MPa. The process originality is the use of recycled aluminum waste, melted by an own microwave heating technique and sprayed with nitrogen jets. The process effectiveness is remarkable in economical and energy terms.
AuditoryStimuli.jl: A Julia package for generating real-time auditory stimuli

The AuditoryStimuli.jl software package provides researchers with a framework to generate real-time audio signals in the Julia programming language. The package is designed for use in auditory research programs, neurofeedback applications, and audio signal processing development. The package is developed on top of the SampledSignals library (Russell, 2016) to provide auditory specific functionality and encourage best practices in real-time audio generation. As such, modules are provided to generate auditory signals, modify these signals, and output the resulting waveforms. The package can be used to generate offline audio signals, but when used as a real-time audio system, it provides safe guards for common mistakes which can cause signal distortions and undesired auditory percepts.
Exploration of foot-based interaction for menu control and virtual reality applications

Although hand-based interaction is dominant in the field of human-computer interaction, the hands can be occupied during various daily activities, such as driving, and may be unavailable for those with motor impairments. To support or replace some functions of a hand-based interface, this thesis explores the alternative of foot-based interaction. As a preliminary matter relevant to the design of foot-based interfaces, we investigated elementary characteristics including the comfortable range of motion, increments to control, and interaction metaphors. Next, we carried out a systematic comparison of performance and user experience of two interaction techniques, isometric and isotonic control, in the context of foot-based menu selection and parameter control for a musical performance user interface. We then investigated the effect of auditory or vibrotactile feedback as an alternative to visual feedback in particular for tasks where the user’s visual attention is heavily occupied, such as in medical scenarios. Our experiments demonstrated that parameter manipulation by foot interaction is viable even in a non-visual feedback situation. Furthermore, to explore foot-based multimodal immersive experiences, we presented approaches to simulating the surface of a frozen pond, including ice cracking under increased foot pressure. We believe that the lessons learned through this research can provide helpful insights to future designers of interfaces employing interaction by foot.
The efficacy of Rhodiola Rosea based on DTI image Segmentation Algorithm for patients with delayed Encephalopathy caused by CO poisoning

Objectives: By using DTI image segmentation algorithm investigate the effect of large plants Rhodiola injection on myocardial injury in patients with acute severe CO poisoning (ACOP), and to explore the clinical and CT delayed encephalopathy after ACOP. Methods: Seventy-two ACOP patients were randomly divided into control and observation group, 36 cases in each group from December 2015 – December 2017. The control group received hyperbaric oxygen, mannitol, dexamethasone, citicoline injection, gangliosides, dracone; observation group were large strain Rhodiola injection treatment group based on the once daily for two weeks of continuous treatment. The head CT, head MRI results were analyzed retrospectively. Results: (1) hsCRP and ET-1 in the observation group were significantly lower than those in the control group, and VEGF was significantly higher than that in the control group (P<0.01). No, NOS, and iNOS were significantly lower than those of the control group (P<0.01); (2) CT images of 16 cases showed bilateral symmetrical fusion lesions with blurred edges, low density, and oval center around the ventricle; (3) MRI showed that the lesion was located in the cerebral cortex, white matter lateral ventricle and/or basal ganglia in 12 cases. Conclusion: Rhodiola can reduce myocardial vascular endothelial cell injury, improve cardiac function, and protect the damaged myocardium. Meanwhile, after acute CO poisoning delayed encephalopathy early for CT and MRI examination facilitate analysis and prognosis of the disease.
Internet of Robotic Things: A Review

The Internet of Things (IoT) gives a strong structure for connecting things to the internet to facilitate Machine to Machine (M2M) communication and data transmission through basic network protocols such as TCP/IP. IoT is growing at a fast pace, and billions of devices are now associated, with the amount expected to reach trillions in the coming years. Many fields, including the army, farming, manufacturing, healthcare, robotics, and biotechnology, are adopting IoT for advanced solutions as technology advances. This paper offers a detailed view of the current IoT paradigm, specifically proposed for robots, namely the Internet of Robotic Things (IoRT). IoRT is a collection of various developments such as Cloud Computing, Artificial Intelligence (AI), Machine Learning, and the (IoT). This paper also goes over architecture, which would be essential in the design of Multi-Role Robotic Systems for IoRT. Furthermore, includes systems underlying IoRT, as well as IoRT implementations. The paper provides the foundation for researchers to imagine the idea of IoRT and to look beyond the frame while designing and implementing IoRT-based robotic systems in real-world implementations.
THE PERFORMANCE MEASUREMENT OF CONSULTING SERVICE COMPANY IN INDONESIA; CASE STUDY

Performance evaluation is the first step of a company in reaching its competitive advantage in the midst of globalization and free market enactment. The result of performance evaluation can be used as strategic formulation and decision making in fixing performance indicator which is considered as poor. From the facts, this research uses the evaluation adopted from PwC, which used to evaluate the performance of a consulting service company in Indonesia named XYZ Ltd. The reason for choosing PwC business model is because it covers all aspects that affect company’s ability to achieve competitive advantage. Moreover, this research uses 5 of 7 aspects of performance measurement offered by PwC business model. Measurement indicators and characteristics based on library research and company’s internal managerial party interviews are made, so that the evaluation process can be interpreted into the formulation of strategic improvement and decisions making. The result of performance measurement is expected to be able to give a new perspective in overall performance evaluations of consulting companies and evaluate company’s ability to win over its competitors, as well as to prove the ability of PwC’s measurement model in evaluating the performance of consulting companies in Indonesia model of performance.