Miracle-dz/UniFAR-FTUs huggingface dataset:
A MATLAB based Facial Recognition using Image Processing

—Automatic recognition of people is a challenging problem which has received much attention during recent years due to its many applications in different fields. Face recognition is one of those challenging problems and up to date, there is no technique that provides a robust solution to all situations. This paper presents a new technique for human face recognition. This technique uses an image-based approach towards artificial intelligence by removing redundant data from face images through image compression using the two-dimensional discrete cosine transform (2D-DCT). The DCT extracts features from face images based on skin color. Feature-vectors are constructed by computing DCT coefficients. A self-organizing map (SOM) using an unsupervised learning technique is used to classify DCT-based feature vectors into groups to identify if the subject in the input image is “present” or “not present” in the image database. Face recognition with SOM is carried out by classifying intensity values of grayscale pixels into different groups. Evaluation was performed in MATLAB using an image database of 25 face images, containing five subjects and each subject having 5 images with different facial expressions. After training for approximately 850 epochs the system achieved a recognition rate of 81.36% for 10 consecutive trials. The main advantage of this technique is its high-speed processing capability and low computational requirements, in terms of both speed and memory utilization.
Impact of Multi-partition Systems on Goal-oriented Parallel Computer Job Scheduling Policies

This work is focusing on applying goal-oriented parallel computer job scheduling policies on multi-partition parallel computer systems since several existing systems partition their system resources. Goal-oriented parallel computer job scheduling policies utilizes a combinatorial search technique to find the best schedule within a time limit. Two implementation ideas of multi-partition goal-oriented parallel computer job scheduling policies are proposed and evaluated using an event-driven simulator. The first implementation idea includes the partition selection question into the search space while the second idea selects a partition according to some heuristics resulting in a smaller search space. The experimental results show that the second idea with a best-fit partition selection heuristic performs well under both equal-size and non-equal-size two-partition systems. Furthermore, the proposed policy also outperforms the two basic priority backfill policies.
Service robot teaching assistant in school classroom

— The Covid-19 pandemic found us unprepared in multiple levels of our everyday lives. After the first lockdown period we are facing the challenge to create a new normality by combining our habits and social norms with precautions against the virus. The educational field is one of the top priority fields with the double role, to educate and keep the students safe. In the current paper, we propose the use of service robots as teaching assistants for students aged 13-17. In a real school classroom environment, we conducted a set of experiments with a course conducted by a teacher and a service robot in the role of his/her assistant. Students’ responses in the given questionnaires before and after the course shown that after the interaction with the robot, they statistically significantly believe that the use of robots can make difficult courses more interesting, easier understandable and motivate them to follow a relevant career in the future. Additionally, apart from the educational benefits we propose that it will eliminate the spread of the virus in the class since the teacher will minimize his/her physical contact with the students and the students will have the chance to collaborate through their robot agent.
DISCRIMINATING BETWEEN REJECTORS , PREMATURE TERMINATORS , SHORT-TERM SUCCESSES , AND LONG-TERM CONTINUERS USING 16 PF SCORES 1

A multiple discriminant function analysis was performed to determine what, if any, personality differences can be identified for clients who refuse counseling, terminate prematurely, attain their goals in short-term counseling, ~r continue for long-term counseling. The 16 PF was administered to 282 adult clients in a community mental health center and used to predict their response to counseling. Two significant canonical discriminant functions were obtained. A hit rate of 51 % was obtained which is considerably better than the -33% rate than would be expected on the basis of random assignment.
Optimized Design, Analysis of High Gear Ratio Magnetic Gear for High Speed and High power

In this paper, we proposed a non-contact magnetic gear model with a halbach array of 81kW and 60krpm for high speed and high power applications. The optimization model was proposed using orthogonal array and the response surface methodology, and was selected considering torque, torque ripple and power density. The feature of this paper is the division of axial permanent magnet to reduce eddy current loss. Also, the characteristics of the optimization model are analyzed through 2-D and 3-D finite element analysis. When each permanent magnet was divided into 8 segment, the eddy current loss was reduced by about 76%. The structural deformation and stress of the pole piece component were confirmed by the forced vibration analysis considering the electric force mapping on each pole piece.
Analysis of Handgrip Strength and Anthropometric Measurements of Manufacturing Workers in the Philippines

In industrial applications, it is essential to know and estimate the Handgrip Strength (HGS) of workers to accordingly designate them to appropriate job specifications. Most of the manufacturing companies have a manual or semiautomatic product processing unit; thus, it will require an ample amount of dexterity that constitutes to the exertion of grip force. This study aims to assess the relationship between the Anthropometric and Handgrip Strength of the manufacturing workers that can be used both the industrial sector and government implementing agencies. Nine hand dimensions and thirteen body measurements in standing position with the HGS considering both genders were tested among sixty participants. The HGS of both hands were used in developing regression models for Anthropometric Measurements and Demographic Profile. The results show that the gender, age group, tenure, five hand dimensions and nine body measurements in standing position significantly affects the HGS. The findings will provide companies and government labour and safety agencies comprehensive information on the Anthropometric and Handgrip Strength measurements of the manufacturing workers. The results therefore can provide relevant perspectives in terms of the proper designation of workers and improves the ergonomics and safety of the workers employed both in domestic and international workplaces.
A survey concept on Deep Learning

Artifical intelligence is an area of computer science that emphasize the creation of Intelligence machines that work and react like human . ie, machine can learn and think . The team machine learning , deep learning and AI are interconnected with each other. Deep Learning is a subset of machine learning and machine learning is a subset of AI, which is an umbrella term for any computer program that does something smart. Machine learning is set of algorithms that parse data, learn have learning to make intelligent decision.
Learning Manipulation Tasks from Vision-based Teleoperation

Learning from demonstration is an approach to directly teach robots new tasks without explicit programming. Prior methods typically collect demonstration data through kinesthetic teaching or teleoperation. This is challenging because the human must physically interact with the robot or use specialized hardware. This paper presents a teleoperation system based on tracking the human hand to alleviate the requirement of speciﬁc tools for robot control. The data recorded during the demonstration is used to train a deep imitation learning model that enables the robot to imitate the task. We conduct experiments with a KUKA LWR IV+ robotic arm for the task of pushing an object from a random start location to a goal location. Results show the successful completion of the task by the robot after only 100 collected demonstrations. In comparison to the baseline model, the introduction of regularization and data augmentation leads to a higher success rate.
Avalanche Prediction from Meteorological Data of Mountains through AI Techniques

---Avalanches, tends to cause, amongst the most critical problems to the people and the infrastructure, in the mountain area of India. The processes that leads to avalanche releases are predetermined however the place and time of avalanche releases are notoriously challenging to prognosticate. Statistical approaches provides a substitute for deterministic predictions, by means of data released from meteorological departments, for predicting the likelihood of avalanche release that is natural. We took help from classification trees for predicting times or days with as well as without the avalanche in various part of Indian mountains area, which was grounded on parameters from meteorological data. A data-archive of nearly 10 years with avalanche surveillance was temporally and conceptually linked with wind’s grids, temperatures and precipitation data. Grids were utilised owing to the fact that they dispensed additional temporally reliable datasets than were offered by measurements of local weather stations through Artificial intelligence technology.
Low-Dose CT Restoration with Deep Neural Network

—To reduce the potential radiation risk, low-dose CT has attracted much attention. However, simply lowering the radiation dose will lead to significant deterioration of the image quality. In this paper, we propose a noise reduction method for low-dose CT via deep neural network without accessing original projection data. A deep convolutional neural network is trained to transform low-dose CT images towards normal-dose CT images, patch by patch. Visual and quantitative evaluation demonstrates a competing performance of the proposed method.
IJPL-06-2020-0047_proof 108..117

Purpose – This paper discusses the role of public leadership and the strategic response of local governments to the external shock caused by the COVID-19 pandemic. The authors examine the typical Czech response with regard to how the leadership of municipalities in the Czech Republic responded to this extremely negative external stimulus. Design/methodology/approach – The authors use qualitative research methods for this investigation. They have chosen the case study method (see Yin, 2009; Stake, 1995; Klonoski, 2013). The general case is the Czech Republic. Mini-cases consist of municipalities from the Znojmo region, municipalities of the Central Bohemian region and the municipal districts in the capital city of Prague. Furthermore, the method of participant observation was used. Findings – The authors’ analysis of the problem of local government responses to the pandemic crisis shows that municipal leaders responded with a variety of (non-)adaptation strategies. It appears that certain framework factors influenced the various local governments’ behavior. Originality/value – The article examines the strategic behavior of Czech municipal leaders regarding the pandemic crisis based on the observation of the reactions of local governments in the Czech Republic to the pandemic crisis and strives to define their basic strategies.
Review Classification by using Neural Network & TF-IDF

: Review plays an important role for consumer as well as for manufacturer, seller so this reviews are needed to be analyzed in such a manner so that it can give better results for effective usage the reviews data is huge so to analyze this data there are various types of techniques to be analyzed this review data. This paper studies various approaches & techniques to analyze the data & word embedding is also studied . A system is proposed to use Neural network, word embedding for review classification.
Design of W-band PIN Diode SPDT Switch with Low Loss

A W-band PIN diode single pole double throw (SPDT) switch with low insertion loss (IL) was successfully developed using a hybrid integration circuit (HIC) of microstrip and coplanar waveguide (CPW) in this paper. In order to achieve low loss of the SPDT switch, the beam-lead PIN diode 3D simulation model was accurately established in Ansys High Frequency Structure Simulator (HFSS) and the W-band H-plane waveguide-microstrip transition was realized based on the principle of the magnetic field coupling. The key of the proposed method is to design the H-plane waveguide-microstrip transition, it not only realizes the low IL of the SPDT switch, but also the direct current (DC) bias of the PIN diode can be better grounded. In order to validate the proposed design method, a W-band PIN diode SPDT switch is fabricated and measured. The measurement results show that the IL of the SPDT switch is less than 2 dB in the frequency range of 85 to 95 GHz, while the isolation of the SPDT switch is greater than 15 dB in the frequency range of 89.5 to 94 GHz. In the frequency range of 92 to 93 GHz, the IL of the SPDT switch is less than 1.65 dB, and its isolation is higher than 22 dB. Switch rise time and switch fall time of the SPDT switch are smaller than 29ns and 19ns, respectively. Good agreement between the simulations and measurements validates the design method.
Cost-effectiveness of Microsoft Academic Graph with machine learning for automated study identification in a living map of coronavirus disease 2019 (COVID-19) research

Background: Conventionally, searching for eligible articles to include in systematic reviews and maps of research has relied primarily on information specialists conducting Boolean searches of multiple databases and manually processing the results, including deduplication between these multiple sources. Searching one, comprehensive source, rather than multiple databases, could save time and resources. Microsoft Academic Graph (MAG) is potentially such a source, containing a network graph structure which provides metadata that can be exploited in machine learning processes. Research is needed to establish the relative advantage of using MAG as a single source, compared with conventional searches of multiple databases. This study sought to establish whether: (a) MAG is sufficiently comprehensive to maintain our living map of coronavirus disease 2019 (COVID-19) research; and (b) eligible records can be identified with an acceptably high level of specificity. Methods: We conducted a pragmatic, eight-arm cost-effectiveness analysis (simulation study) to assess the costs, recall and precision of our semi-automated MAG-enabled workflow versus conventional searches of MEDLINE and Embase (with and without machine learning classifiers, active learning and/or fixed screening targets) for maintaining a living map of COVID-19 research. Resource use data (time use) were collected from information specialists and other researchers involved in map production. Results: MAG-enabled workflows dominated MEDLINE-Embase workflows in both the base case and sensitivity analyses. At one month (base case analysis) our MAG-enabled workflow with machine learning, active learning and fixed screening targets identified n=469 more new, eligible articles for inclusion in our living map – and cost £3,179 GBP ($5,691 AUD) less – than conventional MEDLINE-Embase searches without any automation or fixed screening targets. Conclusions: MAG-enabled continuous surveillance workflows have potential to revolutionise study identification methods for living maps, specialised registers, databases of research studies and/or collections of systematic reviews, by increasing their recall and coverage, whilst reducing production costs.
Physical environments of water containers and Aedes sp larvae in dengue-endemic areas of Tanjungpinang Riau

Purpose: This study aimed to determine the relationship of the container environment's type and condition to the existence of Aedes sp larvae in Tanjungpinang Timur District. Methods: An observational study with a cross-sectional approach involved 401 houses with containers in Tanjungpinang Timur District, Tanjungpinang City. Data on the existence of larvae was performed using the single larvae method. Data on container type and container environmental conditions (water pH, water temperature, air temperature, air humidity) and larvae's presence were collected by observing and measuring. Results: 863 containers were observed, 138 of them (15.99%) were found larvae of Aedes sp, containers inside the house (65.57%), and not closed (88.53%). The types of containers were controllable sites (95.13%), disposable sites (3.36%), and under controllable sites (1.51%). The measurement of water pH (76.13%) and water temperature (82.73%) of the containers were categorized as good. Container temperature 98.38% showed results with a range of unfavorable conditions (<200C &> 300C) and air humidity of 99.07% with a range (<81.5% &> 89.5%). Type, location, condition of container closure, water pH, water temperature, and air temperature of containers were related to larvae in Tanjungpinang Timur District (p-value <0.05), while the variable humidity was not related to the existence of larvae. Conclusion: Physical environmental factors strongly support the reproduction of DHF vectors in the East Tanjungpinang District. It is necessary to increase public knowledge and routine home eradication of mosquito nests (PSN), especially controllable site containers widely used as water reservoirs.
A 25,000 year record of climate and vegetation change from the southwestern Cape coast, South Africa

Abstract The southwestern Cape of South Africa is a particularly dynamic region in terms of long-term climate change. We analysed fossil pollen from a 25,000 year sediment core taken from a near-coastal wetland at Pearly Beach that revealed that distinct changes in vegetation composition occurred along the southwestern Cape coast. From these changes, considerable variability in temperature and moisture availability are inferred. Consistent with indications from elsewhere in southwestern Africa, variability in Atlantic Meridional Overturning Circulation (AMOC) was identified as a strong determinant of regional climate change. At Pearly Beach, this resulted in phases of relatively drier conditions (~24–22.5 cal ka BP and ~22–18 cal ka BP) demarcated by brief phases of increased humidity from ~24.5–24 cal ka BP and 22.5–22 cal ka BP. During glacial Termination I (~19–11.7 ka), a marked increase in coastal thicket pollen from ~18.5 to 15.0 cal ka BP indicates a substantial increase in moisture availability, coincident, and likely associated with, a slowing AMOC and a buildup of heat in the southern Atlantic. With clear links to glacial and deglacial Earth system dynamics and perturbations, the Pearly Beach record represents an important new contribution to a growing body of data, providing insights into the patterns and mechanisms of southwestern African climate change.
Toward Conversational Query Reformulation

In traditional web search interfaces, information seekers reformulate their queries by editing the terms in the search box in order to guide the retrieval process. Such kind of editing is at odds with the natural language interaction paradigm in conversational interfaces, and for purely voice-based interfaces it is impossible. Conversational search studies reveal that participants instead describe their changes to a query; however, the principles of such “editing conversations” have not been analyzed in depth. The paper in hand formalizes the problem of conversational query reformulation. We cast reformulations as meta-queries that imply operations on the original query and categorize the operations following the standard CRUD terminology (create, read, update, delete). Based on this formalization we crowdsource a dataset with 2694 human refor-mulations across four search domains. Our analysis of the meta-queries reveals a large variety in word usage and indicates ambiguous reformulations as an important research topic of its own.
Mandibular effects of temporary anchorage devices in Class II patients treated with Forsus Fatigue Resistant Devices: A systematic review

Abstract Objective: To determine whether temporary anchorage devices (TADs) could enhance the mandibular effects of Forsus Fatigue Resistant Devices (FFRD) in growing patients presenting with a Class II malocclusion. Materials and methods: Without language restriction, electronic and manual searches were conducted through databases and relevant journals until the 20th February, 2020. Studies comparing the therapeutic effects in Class II patients treated with TA-anchored FFRD and patients receiving conventional FFRD were considered eligible. Two reviewers independently conducted the study inclusion, data extraction and risk of bias assessment following Cochrane guidelines. The outcomes were qualitatively synthesised and the level of evidence was evaluated using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) tool. Results: Six studies meeting the selection criteria were identified. All except one reported that a greater reduction in the proclination of the mandibular incisors was achieved in TAD-anchored groups compared with the conventionally-treated groups. Controversial results were found in the skeletal and soft tissue descriptions of positional change. The evidence quality varied from very low to moderate. Conclusion: Moderate-quality evidence suggests that TADs are beneficial in reducing the proclination of the mandibular incisors caused by FFRD in Class II patients. Controversies related to the effects on mandibular growth and soft tissue positional change remain. There is a trend that miniplates may enhance the mandibular skeletal effects of FFRD better than miniscrews but further investigation is indicated.
The 8 International Scientific Conference “DEFENSE RESOURCES MANAGEMENT IN THE 21st CENTURY” Braşov, November 14 2013 EMOTIONAL, SITUATIONAL AND MULTICULTURAL AWARENESS-AN ESSENTIAL CONDITION OF MILITARY TEAM LEADERSHIP EFFICIENCY

This study aims to investigate the way in which emotional, situational and multicultural awareness influences the efficiency of activities related to military team leadership in the dynamic conditions specific to complex military missions. The present study inserts emotional, situational and multicultural awareness into the larger scope of emotional intelligence which has been widely studied by us in our own research in 2008 when we identified factorial solutions of emotional intelligence in navy students and officers’ personality.
Wojciech RZEŹNIK

„Journal of Research and Applications in Agricultural Engineering” 2015, Vol. 60(2) 72 Wojciech RZEŹNIK Institute of Technology and Life Sciences Poznan Branch, Department of Environmental Management in Livestock Buildings and Air Protection ul. Biskupińska 67, 60-463 Poznań, Poland e-mail: w.rzeznik@itep.edu. pl Ilona RZEŹNIK Poznan University of Technology Institute of Environmental Engineering ul. Piotrowo 3a, 61-138 Poznań, Poland
The effects of host species and substratum factors on the abundance and growth of epiphytic orchids

It has been observed that epiphytic orchids are less abundant on trees of the genus Quercus (Fagaceae) than on other Neotropical hosts. This study investigates this claim and attempts to link that pattern to substrate inhospitability. The results of orchid abundance counts on Quercus and non-Quercus hosts yielded statistically non-significant results, although the data appear to support this apparent distribution. Specklinia aristata were placed in six experimental treatments in order to examine the effects of pH, fissure depth, and water-holding capacity of the substrate on orchid growth. The results of these experiments also yielded no statistically significant differences between orchid growth on conditions mimicking oak and non-oak bark. However, average new leaf data implicates pH as the most inhibitory factor of orchid growth.