Miracle-dz/UniFAR-FTUs huggingface dataset:
Empirical Analysis of Bi-directional Wi-Fi Network Performance on Mobile Robots in Indoor Environments

This paper proposes a framework to measure the important metrics (throughput, delay, packet retransmits, signal strength, etc.) to determine Wi-Fi network performance of mobile robots supported by the Robot Operating Systems (ROS) middleware. We analyze the bidirectional network performance of mobile robots through an experimental setup in an indoor environment, where a mobile robot is communicating vital sensor data such as video streaming from the camera(s) and LiDAR scan values to a command station while it navigates an indoor environment through teleoperated velocity commands received from the command station. The experiments evaluate the performance under 2.4 GHz and 5 GHz channels with different placement of Access Points (AP) with up to two network devices on each side. The framework is generalizable to vehicular network evaluation and the discussions and insights from this study apply to the field robotics community, where the wireless network plays a key role in enabling the success of robotic missions in real-world environments.
A Personal Perspective on Operations Research*

In this presentation, I will try to sketch the present status of Operations Research and Management Science which I have gleaned from my own experience. It is said in Japan that OR/MS was an excellent tool for managers up to the early 70's, but that in recent years it has not been utilized so widely. In addition, there seems to be a big gap between academics and business circles regarding the use of 0 R/MS and the gap is becoming bigger. Many people see this gap as a crisis for OR/MS. Firstly, I will explain several causes of this gap, emphasizing the importance of tight cooperation between models, algorithms and applications which, I think, constitute a kind of troika in OR/MS. Then I will briefly survey models, algorithms and applications of OR/MS. Finally, after emphasizing the role of optimization, I will talk about my personal view on the future development of OR/MS.
Non-linear Recovery of Neuronal Excitability in the Inter-pulse-intervals of High-frequency Stimulation-A Modeling Study

High-frequency stimulation (HFS) of pulses has been used in deep brain stimulation (DBS) to treat neurological diseases. The inter-pulse-interval (IPI) of HFS is one of the critical parameters to dominate the stimulation efficacy, not only because IPIs determine pulse rates but also because the IPIs are commonly too short to allow neuronal state to recover completely during sustained HFS. Therefore, varying IPI can generate various neuronal reactions. However, the recovery of neuronal excitability along with the time of IPI is not clear. In this study, we investigated the recovery progress by utilizing a computational model of a myelinated neuron. The results show a non-linear recovery of the neuron to obtain re-firing ability during sustained HFS, which is dominated by the non-linear dynamics of sodium channels in the axonal membrane.
A STUDY ON VARIOUS FACTORS AFFECTING DISCHARGE HEADWAY AT SIGNALIZED INTERSECTION UNDER HETEROGENEOUS TRAFFIC CONDITIONS

Discharge headway is the headway between successive vehicles negotiating an intersection during the green time of signal operation. It is an important parameter in signal operations and analysis since estimation of parameters such as saturation flow and capacity of an intersection depend on it. Although there have been several studies on discharge headway in homogeneous traffic conditions, there are only a few studies on discharge headways in heterogeneous traffic. This study examines the factors affecting discharge headway under heterogeneous traffic conditions which is characterized by mixed vehicle composition and lack of lane discipline. A new method to measure headways in such cases is proposed here. To get individual vehicle headways, each lane is divided into multiple strips. The width of a strip is approximately equal to the width occupied by a motorcycle. The headways of vehicles in each strip are measured separately and used for analysis. Data collection for the study was carried out at signalized intersections in Sirnagar (Jammu and Kashmir), India. Data was collected for one approach at all intersections. From the data collected, headways of individual vehicles were measured. Linear mixed effect regression was used to model discharge headway. The effect of vehicle length, engine capacity of vehicle, lateral position on roadway, and green time on discharge headway were modeled. From the regression analysis, it was found that all these factors had significant impact on discharge headway. The discharge headway model proposed in this study could be used for obtaining saturation flow rates and capacity at signalized intersections under heterogeneous traffic
The Relationship Between Alexithymia, Cognitive Failures, and General Health in Secondary High School Student With Attention- Deficit/Hyperactivity Disorder

Author Address 1. Department of Psychology, Kish International Branch, Islamic Azad University, Kish Island, Iran; 2. Assistant Professor, Department of Clinical Psychology, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran; 3. Associate Professor, Department of Clinical Psychology, Faculty of Psychology and Education, Kharazmi University, Tehran, Iran. *Corresponding author’s email: M_borjali501@yahoo.com
Relationship between profitability: A case study of food and beverage

This study examined the relationship between assets utilization and corporat of food and beverage industry on the scale, management mechanism and management level should have their own assets structure because without assets production cannot take place. The relationship between assets utilization and corporate efficiency. In addition, six other objectives are to be achieved by the study. The population of the study is made up of all the firms in food and beverage industry quoted on the Nigerian stock Exchange. Stratified sample selected. Out of 21companies two adopted ex-post facto research design method. Secondary data collected from the financial statement of the sampled companies from 2007 used to determine the magnitude using this model ROA=α+β1(DRTO)+ β6(PLANTASSET)+ε. The result of hypotheses showed that only hypothesis one which says that there is no significant relationship between return on asset and
A statistical approach and analysis computing based on autoregressive integrated moving averages models to predict COVID-19 outbreak in Iraq

A time series has been adopted for the numbers of people infected with the Covid-19 pandemic in Iraq for a whole year, starting from the first infection recorded on February 18, 2020 until the end of February 2021, which was collected in the form of weekly observations and at a size of 53 observations. The study found the quality and suitability of the autoregressive moving average model from order (1,3) among a group of autoregressive moving average models. This model was built according to the diagnostic criteria. These criteria are the Akaike information criterion, Bayesian Information Criterion, and Hannan & Quinn Criterion models. The study concluded that this model from order (1,3) is good and appropriate, and its predictions can be adopted in making decisions.
Test Protocol for Room-to-Room Distribution of Outside Air by Residential Ventilation Systems

This test and analysis protocol has been developed as a practical approach for measuring outside air distribution in homes. It has been used successfully in field tests and has led to significant insights on ventilation design issues. Performance advantages of more sophisticated ventilation systems over simpler, less-costly designs have been verified, and specific problems, such as airflow short-circuiting, have been identified.
REGRESSION ANALYSIS OF THE RELATIONSHIP BETWEEN SELECTED VARIABLES OF ECONOMIC GROWTH AND SUSTAINABLE DEVELOPMENT

Environmental threats of anthropological origin, such as global warming, rising water levels, air pollution, excessive waste generation, or the seas and oceans quality decline, are threats that directly affect us. Thus, the main goal of this paper is to evaluate the impact of current economic development in the intentions of planetary limits through regression analysis using cross-sectional and panel data evaluating the dependence of ecological footprint per person, gross domestic product per person and Sustainable Development Index. The analysis shows that economic development in line with the current market rules contributes to expand the ecological footprint. We argue that both green measures into international and national policies as an effective monitoring of the achievement of sustainable goals of all market actors are necessary.
Cost-Efﬁcient Resource Allocation Method for Heterogeneous Cloud Environments

—In this paper we present a novel on-line NFV (Network Function Virtualization) orchestration algorithm for edge computing infrastructure providers that operate in a heterogeneous cloud environment. The goal of our algorithm is to minimize the usage of computing resources which are offered by a public cloud provider (e.g., Amazon Web Services), while fulﬁlling the required networking related constraints (latency, bandwidth) of the services to be deployed. We propose a reference network architecture which acts as a test environment for the evaluation of our algorithm. During the measurements, we compare our results to the optimal solution provided by an ILP-based solver.
Practical Wisdom Through Deliberative Pedagogy: A Constructive Rhetorical Analysis

Deliberative pedagogy holds promise for improving democratic society by cultivating practical wisdom in students as a means to tackle the problems of democracy, such as polarization. This study embraced an opportunity to consider civic education in the 21st century through deliberative pedagogy by considering practical wisdom in a synchronous, virtual deliberation among university stakeholders and local political candidates concerning our role in 21st-century politics. This civic site enabled an analysis of practical wisdom across three student roles: facilitators enrolled in a deliberation course; students from the wider university; and student alumni of the university’s deliberation center, who had been exposed to deliberation in curricular and cocurricular practice. Using a constructive rhetorical analysis to understand practical wisdom within deliberative pedagogy discourse, we contend that students in these three different roles demonstrated three key aspects of practical wisdom through their discursive responses to rhetorical exigences that arose during deliberative engagement. This analysis offers insights beyond outcomes and informs deeper thinking about curricula and better pedagogical practices. Additionally, such studies, focused on the discourse itself, contribute to understandings concerning the connection between rhetoric and deliberative pedagogy.
Unimodular random one-ended planar graphs are sofic

We prove that if a unimodular random graph is almost surely planar and has finite expected degree, then it has a combinatorial embedding into the plane which is also unimodular. This implies the claim in the title immediately by a theorem of Angel, Hutchcroft, Nachmias and Ray [2]. Our unimodular embedding also implies that all the dichotomy results of [2] about unimodular maps extend in the one-ended case to unimodular random planar graphs.
Workplace Friendship and Teacher Citizenship Behaviour, The Moderating Role of Workplace Jealousy: An Empirical Analysis of Senior High Schools in Ghana

The present study examines the effect of workplace friendship on teacher citizenship behavior, moderated by workplace jealousy among senior high schools in Ghana. The study employs a quantitative research approach, whereby 384 respondents were sampled from among 22 public-owned institutions in the Kumasi metropolis, using a simple random sampling technique. Employing Multiple Linear Regression Analysis, the surveyed data was analyzed using SPSS version 23.0. All three hypotheses in this study were supported. In particular, the study found that workplace friendship has a significant and positive effect on teacher citizenship behavior; workplace jealousy has a significant and positive effect on teacher citizenship behavior, and workplace friendship interacting with workplace jealousy has a significant but very weak effect on teacher citizenship behavior. The perception of workplace jealousy from the Ghanaian context is perceived positively and quite different from that of other countries due to historical and cultural backgrounds. Higher education institutions may derive enormous benefits from the findings of this study. Several implications to theory and practice were discussed.
Biochemical and molecular characterization of bacterial Endosymbionts associated with Hishimonus phycitis (Hemiptera: Cicadellidae), the insect vector of sesamum phyllody phytoplasma

The present study, were carried out at GKVK, Bengaluru on diversity of culturable bacterial endosymbionts associated with Hishimonus phycitis. The leafhoppers (H. phycitis) were collected from sesamum crop at ZARS filed unit. The isolated seven endosymbiotic bacteria (Designated as EBHP-1 to 7). The study revealed that, all endosymbionts showed negative reaction to Indole and Voges-Proskauer test (EBHP-1 to 7). In citrate test, six endosymbionts showed positive reaction (EBHP-1, EBHP-2, EBHP-3, EBHP-4, EBHP-6 and EBHP-7) and EBHP-5, showed negative reaction. Further, in the methyl red test EBHP-2, EBHP-5, EBHP-6 and EBHP-7 showed positive and remaining three showed negative (EBHP-1, EBHP-3 and EBHP-4). Isolated DNA from the seven isolates of endosymbionts from their pure culture and subjected to PCR for amplification of gene encoding 16S rRNA using Fp1/Rp2 primers. DNA isolated from all samples yield the expected amplicon of 1.4 kb PCR product, which were sequenced. The phylogenetic analysis of the 16S rRNA gene and nucleotide identity indicated that EBHP-1, EBHP-3, EBHP-6 and EBHP-7 were closely clustered with Pseudomonas sp. and shared sequence similarity of 83-93(%). Similarly, EBHP 4 and EBHP 2 clustered with Exiguobacterium sp. and shared 64-93(%) sequence identity and EBHP-5 with Achromobacter sp. and 89-91(%) sequence similarity. These results suggest that, diverse endosymbiotic bacteria associated with the Hishimonus phycitis, which may have possible role in the transmission of sesamum phyllody.
Renewable Quantum Learning Technology as an Effort to Increase Confidence and Learning Outcomes in Elementary School

The provision of facilities for learning is very necessary for the continuity of education. Through the latest technology in learning, especially quantum learning can increase students' confidence and learning outcomes. This study aims to describe the process of increasing self-confidence and learning outcomes through the implementation of quantum learning. Furthermore, knowing the increase in self-confidence and student learning outcomes through quantum learning. This research was conducted through 2 cycles, including planning, implementation, evaluation, and reflection. Data collection was done through interviews, observations, and tests. A total of 20 elementary school students who became the subject of the study. 2 types of data analysis techniques, namely quantitative data analysis and qualitative data analysis. The results showed an increase in self-confidence and student learning outcomes through the application of quantum learning. The stages of quantum learning include: grow, experience, name, describe, repeat, and celebrate. The application of quantum learning can increase student's self-confidence from 51% to 70% in cycle 1, and increased to 95% in cycle 2. While the average value of learning outcomes in the initial condition is 78.05, increasing to 83.5 in cycle 1, and increased to 90.5 in cycle 2.
Detecting Low Surface Brightness Galaxies with Mask R-CNN

Low surface brightness galaxies (LSBGs), galaxies that are fainter than the dark night sky, are famously difﬁcult to detect. Nonetheless, studies of these galaxies are essential to improve our understanding of the formation and evolution of low-mass galaxies. In this work, we train a deep learning model using the Mask R-CNN framework on a set of simulated LSBGs inserted into images from the Dark Energy Survey (DES) Data Release 2 (DR2). This deep learning model is combined with several conventional image pre-processing steps to develop a pipeline for the detection of LSBGs. We apply this pipeline to the full DES DR2 coadd image dataset, and preliminary results show the detection of 22 large, high-quality LSBG candidates that went undetected by conventional algorithms. Furthermore, we ﬁnd that the performance of our algorithm is greatly improved by including examples of false positives as an additional class during training
Bacterial and Viral Pathogens Associated with The White Garden Snail Theba

The present study was performed during a periodical interval of nine months in (2014) at Alexandria Governorate, Egypt. Whereas, a laboratory trial was carried out to inspect the field collected dead adult land snails ofThebapisana (693 individuals). The inspection revealed that 19.0 % of these collected snails were infected with three pathogenic; bacteria; Bacillus theuringiensis (B.t.) (2.7%), B. cereus (0.1 %), and Brevibacterium sp. (10.1%) in addition to a polyhedrosis virus (2.7 %). Moreover, the made laboratory evaluation showed that the assessed daily cumulative mortality of snails as well as LC50 (Concentration of active ingredient responsible for killing 50% of the examined number animals) value of B.t post 13 days of snail treatment was (7.3x108 Visible spore (VS)/ml), while these determined values for Brevibacteriumsp. and polyhedrosis virus(P.V) were (7.6 x 108VSs/ml) and (3.3 x 106 Polyhedral Inclusion Bodies (P.I.Bs) /ml) after four and 16 days, respectively. The LT50 (Time in days, needed to kill 50% of the exposed pest) for Brevibacterium sp. ranged from 9.8 to 16.3 days for the different tested concentrations. The LT50 of lower concentration of polyhedrosis virus was much prolonged up to (10.6 days) compared to that of the highest concentration (1.5-day). Also, the LT50 values of B.t ranged from 10.2 to 17.5 day for the lowest and highest tested concentrations . The ease and simplicity of the followed bioassay procedures, and the reliability of the method described, as shown by the statistical evaluation of the obtained data, justify the use of the adopted method in the present study.
ON THE STRUCTURAL DETERMINANTS OF GROWTH-AT-RISK

We examine structural differences in growth vulnerabilities across countries resulting from time-varying financial risk. Considering differences in trade openness, financial sector size, the public spending ratio and government effectiveness, our findings suggest the existence of both a structural gap as well as a risk sensitivity gap when estimating growth-at-risk (GaR) across countries. Hence, structural factors do not only drive level-differences in GaR, but also give rise to differences in the responsiveness of GaR to varying levels of risk. Furthermore, we show that structural factors affect the term structure of GaR, with the impact of structural characteristics varying over the forecasting horizon. A proper understanding of structural factors in the context of the GaR framework is particularly important to facilitate the use of the concept in macroprudential policy. JEL classification: E27, E32, E44, F43, G01, G20, G28
Bacterial communities of big-headed ants ( Pheidole rugaticeps ) and American cockroaches ( Periplaneta americana ) revealed pathogens of public health importance

Aims: Several cockroach and ant species have been revealed to infest households with inadequate insect control and food storage practices. These household insects harbor countless bacteria species of public health, agricultural and industrial importance. Many studies have reported disease-causing bacteria from both cockroaches and ant’s species collected from hospitals and residential areas. The aim of this study was to characterize the culturable bacterial communities of two common household insects, big headed ants (Pheidole rugaticeps) and American cockroaches (Periplaneta americana) using 16S rRNA genes sequencing. Methodology and results: A total of 64 bacterial sequences were obtained from P. rugaticeps (48.44%) and P. americana (51.56%) and Firmicutes was the most dominant phylum from both insect species. Bacillus was the most dominant bacterial genus from both cockroach and ant samples. Other important genera isolated were Pseudomonas and Stenotrophomonas which have previously been suggested to have members that are of biotechnological importance. Food poisoning bacterial species, B. cereus and other bacterial strains such as B. subtilis, A. baumannii, B. cepacian, P. aeruginosa, S. epidermidis, Burkholderia cepacian, Serratia marcescens, Staphylococcus epidermidis and S. pseudintermedius with the history of human infections were isolated from some of the insect’s specimens. Conclusion, significance and impact of study: Thus, these household insect pests harbor bacterial species known to cause diseases of serious public health importance that needs serious attentions. Similarly, the insects harbor other bacteria species that may provide opportunities for biotechnological exploration.
Classifying Tourists’ Photos and Exploring Tourism Destination Image Using a Deep Learning Model

ABSTRACT As social network service usage is rapidly surging in our daily life, social network service data plays a crucial role in identifying region of attractions and analyzing tourism destination image. In recent years, the computer vision technology is just beginning to be applied in the tourism field through the transfer learning of a deep learning model. However, the pre-trained models have limitations of properly classifying the photos with the unique landscape or specific elements of the tourism destination. With the purpose of going beyond these limitations, we generated a tourists’ photo classification reflecting regional characteristics and developed a deep learning model to classify photos according to this classification. Through the analysis of 168,216 Flickr photos, we analyzed the tourism destination image of Seoul. Key findings are that (1) tourists prefer to enjoy local food, to visit authentic traditional palaces, and to see inherent cityscape which can be uniquely enjoyed in Seoul, (2) tourist attractive factors differ by region of attractions, (3) tourist preferences differ by continent. This study has novelty in that it develops a tourist’s photo classification suitable for regional characteristics and analyzes tourism destination image by classifying photos using an artificial intelligence technology.
, S., & Flach, P. (2017). Computational support for academic peer review: a perspective from artificial intelligence. Communications of the ACM , 60 (3), 70-79. https:

State-of-the-art tools from machine learning and artiﬁcial intelligence are making inroads to automate parts of the peer review process; however, many opportunities for further improvement remain. Proﬁling, matching and open-world expert ﬁnding are key tasks that can be addressed using feature-based representations commonly used in machine learning. Such streamlining tools also offer perspectives on how the peer review process might be improved: in particular, the idea of proﬁling naturally leads to a view of peer review being aimed at ﬁnding the best publication venue (if any) for a submitted paper. Creating a more global embedding for the peer review process which transcends individual conferences or conference series by means of persistent reviewer and author proﬁles is key, in our opinion, to a more robust and less arbitrary peer review process.