Miracle-dz/UniFAR-FTUs huggingface dataset:
ROAD SURFACE DETECTION FROM MOBILE LIDAR DATA

Abstract. The accurate three-dimensional road surface information is highly useful for health assessment and maintenance of roads. It is basic information for further analysis in several applications including road surface settlement, pavement condition assessment and slope collapse. Mobile LiDAR system (MLS) is frequently used now a days to collect detail road surface and its surrounding information in terms three-dimensional (3D) point cloud. Extraction of road surface from volumetric point cloud data is still in infancy stage because of heavy data processing requirement and the complexity in the road environment. The extraction of roads especially rural road, where road-curb is not present is very tedious job especially in Indian roadway settings. Only a few studies are available, and none for Indian roads, in the literature for rural road detection. The limitations of existing studies are in terms of their lower accuracy, very slow speed of data processing and detection of other objects having similar characteristics as the road surface. A fast and accurate method is proposed for LiDAR data points of road surface detection, keeping in mind the essence of road surface extraction especially for Indian rural roads. The Mobile LiDAR data in XYZI format is used as input in the proposed method. First square gridding is performed and ground points are roughly extracted. Then planar surface detection using mathematical framework of principal component analysis (PCA) is performed and further road surface points are detected using similarity in intensity and height difference of road surface pointe in their neighbourhood.A case study was performed on the MLS data points captured along wide-street (two-lane road without curb) of 156 m length along rural roadway site in the outskirt of Bengaluru city (South-West of India). The proposed algorithm was implemented on the MLS data of test site and its performance was evaluated it terms of recall, precision and overall accuracy that were 95.27%, 98.85% and 94.23%, respectively. The algorithm was found computationally time efficient. A 7.6 million MLS data points of size 27.1 MB from test site were processed in 24 minutes using the available computational resources. The proposed method is found to work even for worst case scenarios, i.e., complex road environments and rural roads, where road boundary is not clear and generally merged with road-side features.
Review on the research development of beaks in Cephalopoda

With the decline of traditional world economic fisheries resources,the exploitation and utilization of cephalopod resources have been recognized generally in the world and many researches on cephalopod resources and biology were made.Beak with the features of steady structure,erosion-resistant and better information storing,is one of hard and main predation organs of cephalopods,and it not only plays an important role in taxonomy but also as a good material to study cephalopod biology and taxonomy.Based on the studies conducted by the authors at home and abroad,the paper described the morphological characteristics of beak and the studies of beaks were reviewed,which were applied in cephalopod biology,taxonomy,stock estimation and feeding habits of predators.The results show that the fixed term "beak" has been formed in the morphology,and has played an important role in cephalopod taxonomy.A new approach on analyzing food composition and diet change was also provided by the analysis of pigmentation in the beak,and analyzing pigmentation has become one of the key problems in studying age and growth of cephalopod.The results show that some problems still exist in age identifying and stock estimating,which should be solved in the future,although certain progress has been made.
Deep Learning in Encoding and Decoding of Polar Codes

In this paper, we apply neural networks to the encoding and decoding of polar codes. Polar codes in 5G communication which meets the simple and ultra-low latency can also be improved. This paper aims to improve the polar codes to achieve simplicity and hardware friendliness. After trained by the neural network, we get a simple math formula to estimate the reliability of the encoding in the polar codes, which can achieve the same effect as GA (Gaussian Algorithm). In terms of decoding, by using NND (Neural Network Decoding) to decode polar codes, we achieve almost the same effect as the conventional SC (Successive Cancellation) algorithm. In order to achieve further improvements, we use the neural network to optimize BP (Belief Propagation) algorithm. Thanks to it, a small number of iterations can be enough to decode the polar codes, even with an iteration of one. The simulation shows that though the early stage of training is full of difficulties, the result can be used to achieve one-step and fool-type decoding.
Concerted action of lactate oxidase and pyruvate oxidase in aerobic growth of Streptococcus pneumoniae : role of lactate as an energy source

Streptococcus pneumoniae was shown to possess lactate oxidase in addition to well-documented pyruvate oxidase. The activities of both H 2 O 2 -forming oxidases in wild-type cultures were detectable even in the early exponential phase of growth and attained the highest levels in the early stationary phase. For each of these oxidases, a defective mutant was constructed and compared to the parent regarding the dynamics of pyruvate and lactate in aerobic cultures. The results obtained indicated that the energy-yielding metabolism in the wild type could be best described by the following scheme. (i) As long as glucose is available, approximately one-fourth of the pyruvate formed is converted to acetate by the sequential action of pyruvate oxidase and acetate kinase with acquisition of additional ATP; (ii) the rest of the pyruvate is reduced by lactate dehydro- genase to form lactate, with partial achievement of redox balance; (iii) the lactate is oxidized by lactate oxidase back to pyruvate, which is converted to acetate as reaction mixture received 1 ml each of 4 M hydroxylamine (pH 6.4) and 0.1 M acetate buffer (pH 5.4), and was kept standing for 10 min at room temperature. Then, 1 ml each of 36% HCl, 12% (wt/vol) trichloroacetic acid, and 5% (wt/vol) ferric chloride in 0.1 N HCl were added to the mixture, which was kept standing at room temperature for 20 min before being centrifuged at 16,000 (cid:2) g for 5 min. The absorbance of the supernatant was measured at 540 nm. Lactate oxidase activity was assessed by assaying the H 2 O 2 produced by a modiﬁcation of the method previously described (29). The reaction mixture consisted of 1 ml of the permeabilized cell suspension and 3 ml of 0.1 M sodium phosphate buffer (pH 7.0) containing 2.2 mM sodium L -lactate (Sigma). The reaction was initiated by the addition of enzyme and incubated at 37°C with shaking. At 5-min intervals, 0.5-ml samples were withdrawn and immediately mixed with 60 (cid:5) l of concen-trated HCl in glass tubes chilled in an ice-water bath. The mixtures were cen- trifuged for 5 min at 16,000 (cid:2) g , and a 50- (cid:5) l portion of each supernatant was for O oxidase was each
A Mobility Model and Dynamic Scatternet Formation for Wireless Personal Area Networks with Portable Bluetooth Devices

: Bluetooth is a mature technology for a variety of personal computing devices, which are interconnected to form a wireless personal area networks (WPANs). The topology of the WPAN is known as scatternet, which consists of the portable Bluetooth devices. This paper presents a proposed mobility model for the portable Bluetooth devices. Based on the mobility model a dynamic scatternet formation is developed for WPANs that interconnects portable Bluetooth devices. The proposed approach constructs a scatternet within three phases: scatternet backbone formation, device movement detection, and scatternet reformation. Finally, the paper demonstrates the approach with a practical case and then discusses the topics for further study.
TCP Syn Protection: An Evaluation

The drop of initial TCP control packets can dramatically penalize flow performance. More the flow is small, more the penalty is important. This paper studies an Active Queue Management (AQM) aiming to protect TCP SYN and SYNACK from losses, and evaluates the improvements for short TCP flows and the impacts on long-lived TCP flows. This AQM is an extension based on Random Early Detection (RED). Evaluations are performed in the ns-2 simulator. Results demonstrate the effectiveness of the idea supported in a decrease in the transfer delay of short flows and indiscernible effects on large flows.
Lossy Images Compression Based on Multiresolution

A hybrid lossy compression system was presented in this paper. It was based on combining the multiresolution coding together with a polynomial approximation of linear base to decompose grey images followed by an efficient coding. The test results showed promising performance where the compression ratio improved about three times or more compared with the results of the traditional linear predicting coding system.
Evaluating the Usefulness of the Adapted Thematic Analysis in the Process of Design

A number of HCI studies reported thematic analysis method as a useful tool for evaluating existing technologies and informing design of new technologies. Whilst these studies reported on the resulting designs, they lacked detailed account about the use of the method itself or how the output of the method was linked to proposed designs. To explore this ‘knowledge gap’, thematic analysis method was applied to a data set resulting from semi-structured interviews conducted with five families. The adaptation of the thematic analysis approach led to a new ‘output’ in which findings were structured into a Design Map consisting of Categories, Themes and Codes. The usefulness of this Design Map in the process of design was evaluated in a study conducted with participants studying design at an undergraduate level. This paper describes the rationale for using Lean UX approach to refine the aims of the study and reports results from the Exit Questionnaires aiming to elicit participants’ opinions about the use of a Design Map in the process of design.
Segmenting, Summarizing and Predicting Data Sequences

academic) Temporal data is ubiquitous nowadays and can be easily found in many applications. Consider the extensively studied social media website Twitter. All the information can be associated with time stamps, and thus form different types of data sequences: a sequence of feature values of users who retweet a message, a sequence of tweets from a user, or a sequence of the evolving friendship networks. Mining these sequences is an important task, which reveals patterns in the sequences, and it is a very challenging task as it usually requires different techniques for different sequences. The problem becomes even more complicated when the sequences are correlated. In this dissertation, we study the following two types of data sequences. We show how to carefully exploit within-sequence and across-sequence correlations to develop more effective and scalable algorithms. 1. Multi-dimensional value sequences: We study sequences of multi-dimensional values, where each value is associated with a time stamp. Such sequences arise in many domains such as epidemiology (medical records), social media (keyword trends), and Critical Infrastructure (power outage data). Our goals are: for individual sequences, to find a segmentation of the sequence to capture where the pattern changes; for multiple correlated sequences, to use the correlations between sequences to further improve our segmentation; and to automatically find explanations of the segmentation results. 2. Social media post sequences: Driven by applications from popular social media websites such as Twitter and Weibo, we study the modeling of social media post sequences. Our goal is to understand how the posts (like tweets) are generated and how we can gain understanding of the users behind these posts. For individual social media post sequences, we study a prediction problem to find the users’ latent state changes over the sequence. For dependent post sequences, we analyze the social influence among users, and how it affects users in generating posts and links. Our models and algorithms lead to useful discoveries and solve real problems in Epidemiology, Social Media and Critical Infrastructure Systems. Further, most algorithms and frameworks we propose can be extended to solve sequence mining problems in other domains as well. Segmenting, Summarizing and Predicting Data Sequences
Psycholinguistic studies of word morphology and their implications for models of the mental lexicon and lexical processing

We sample from behavioral studies of visually presented inflected and derived words in the lexical decision task to describe how we understand morphologically complex word forms. We discuss how these results inform theories of the mental lexicon and lexical processing and offer some implications for how these findings might inform teaching practices for beginning readers about morphology. We focus on experimental findings pertaining to morphological regularity, whole word and morpheme frequency (including family size, entropy measures, affix frequency, and position), along with semantic transparency and morpho-orthographic parsing of words composed of several morphemes. Models of how we understand and produce morphologically complex words epitomize issues about how to capture knowledge about word patterns and the extent to which that knowledge is better characterized as general statistical patterning based on graded similarity of form and meaning as contrasted with rules that apply to linguistically defined morphemic units.
Efficient Solving Methods for POMDP-based Threat Defense Environments on Bayesian Attack Graphs

In this work, we show how to formulate a threat defense environment as a Partially Observable Markov Decision Process (POMDP) that allows for fast approximate defense algorithms against multiple attackers. It is done through an action extension, coined the Inspect action, which allows the agent to reveal the true state of the environment, thereby reducing the problem into a traditional Markov Decision Process (MDP) for the current time-step. The work is an extension of previous definitions of the same problem. Furthermore, based on the new definition we define and show the optimal policy, as well as two new solving algorithms, n-Myopic and n-Lookahead. To evaluate their performance, we show and compare the results of these new algorithms to more standard solving algorithms, such as Q-learning and Policy Gradients. The experimental results show that the new algorithms perform better than previous attempts and allows for larger scale threat environments thanks to the approximate MDP reduction. Additionally, to facilitate future research, two OpenAI Gym environments were developed and are publicly available for new research to build upon. We encourage new research with similar problem description to use this software library, opening up to standardized performance results.
Group and strain-specific neutralization sites of infectious bursal disease virus defined with monoclonal antibodies.

SUMMARY. Two somatic cell hybridizations were performed utilizing splenocytes from mice immunized with one or more strains of infectious bursal disease virus (IBDV). Supernatants from hybridoma cell lines were initially screened by the enzyme-linked immunosorbent assay (ELISA) against multiple strains of IBDV. Cell lines that secreted antibodies with ELISA reactivity patterns of interest were cloned, and their monoclonal antibodies (MCAs) were subsequently tested in cross-virus-neutralization tests. Two of the nine MCAs selected exhibited strong neutralizing activity and precipitated IBDV antigens in agar gel precipitin tests as well. MCA B69 significantly neutralized only the cloned D78 strain of IBDV, whereas MCA R63 neutralized all IBDV strains (representing both serotype I and II viruses) against which it was tested. Results of competitive ELISAs that used the R63 and B69 MCAs showed that the two neutralization sites on the D78 strain were not overlapping.
Preparation of hydroxypropyl-β-cyclodextrin inclusion with Levonorgestrel and Quinestrol (EP-1) and its influence on the reproductive organs Brandt's voles (Lasiopodomys brandtii)

EP series rodent contraception is mainly composed of levonorgestrel and quinestrol.However,neither component do not readily dissolves in water,which limits the precision of research and application.In the present study,solubilization was measured in hydroxypropyl-β-cyclodextrin(HPCD) inclusion complexes of levonorgestrel and quinestrol,respectively.Afterwards,the effects of treatment times(after 2 and 4 weeks) and doses(0,1,2,4 mg/kg) of EP-1 inclusion complexes on reproductive organs were investigated using a gastric gavage method.The results showed that the solubility of levonorgestrel and quinestrol reached 4 mg/mL and 0.5 mg/mL in 20% aqueous HPCD solution,respectively.For females,there were no significant differences after 2 or 4 weeks between the control and treatment groups that received gavage.For males,the average weight of reproductive organs of the group that received gavage for 2 weeks of 2 mg/kg group was less than that of the control group.Our results indicate that the solubility of EP-1 was significantly enhanced by forming inclusion complexes with HPCD;the suppressive effects on reproduction in male Brandt's voles is more obvious than those in females.Moreover,inclusion did not affect the anti-fertility effect of EP-1.
Conversion Rate of Soil Carbon and Nitrogen in Natural Pinus tabulaeformis Forest on the Taiyue Mountains, China

The effects of soil water content, soil temperature and fine root biomass on gross nitrification, denitrification and respiration rates in natural Pinus tabulaeformis forest soil in the Taiyue Mountains, China, and the changes in the rates with different depths of soil were investigated using the barometric process separation (BaPS) technique. The results indicated that the gross nitrification and respiration rates showed a decreasing trend as the soil depth increased, but the denitrification rate fluctuated strongly. The soil water content, soil temperature and fine root biomass had significant positive effects on the gross nitrification and respiration rates (P0.05), but had no positive effect on the denitrification rate. Fig 4, Tab 2, Ref 28
Control Systems of Bionic Limbs of the New Generation and Control Systems with EMG Signals of VR and Games and Toys

The LLC Bionic Natali company is a startup and has been engaging in creation of bionic artificial limbs of hands for more than 2 years, and the LLC Bi-oN EMG was created one year ago on base of LLC Bionic Natali. From the first steps, projects had been directed on the solution of a problem of development of the domestic bionic functional artificial limb of the hand based on neural network and others algorithms. In projects, it had been created the functional system of management, system of tactile feedback which has increased controllability of a functional artificial limb is already realized and integrated, and also the functional bionic artificial limb of the hand. Based on this work it had been done the general representations and practical application of machine training, neural network and others algorithms. The technology of recognition of gestures of electromyographic activity based on neural network or an analog of network is the cornerstone. The bracelet is put on a hand (in case of disabled people, a stump), further noninvasive electrodes remove potential difference of neuromuscular activity; by means of an electric circuit there is data handling and their transmission to the processor where by means of a neural network there is a recognition of a gripper, further data are transferred for control of a bionic hand. This technology has also found so far mostly theoretical management, but undergoes testing practical, for control of the knee module of a bionic artificial limb of the lower limb. The technology of bracelet became the product of LLC Bi-oN EMG for virtual reality, games and rehabilitation. On the basis of this researches the important conclusion has been drawn: after carrying out operations within rehabilitation and the subsequent requirement of rehabilitation of disabled people before use of bionic artificial limbs of hands, use of an electromyographic bracelet of LLC Bi-oN EMG is offered as option.
STUDIES ON PURE CULTURE OF THE ECTOMYCORRHIZAL FUNGI ASSOCIATED WITH PINUS YUNNANENSIS

Several surveys were carried out under Pinus yunnanensis Franch forest in Central Yunnan; the total collections are over 130. 33 species, belonging to 19 genera, 13 families were selected to supply a diversity of pure cultures. 4 types of media were selected for the pure culture study of ectomycorrhizal fungi. As a result, pure cultures of 25 species, 17 genera, and 11 families were obtained. The total isolation success rate reached 75.8%; the success rate of 4 media (No.1, No2, No.3, No.4) was 36.4%, 63.6%, 33.3% and 57.6% respectively. Modified PDA medium (No.2) and pine needles medium (No.4) are more suitable for the isolation, purification and maintenance of ectomycorrhizal fungi associated with P. yunnanensis.
Validation of Hybridized Particle Swarm Optimization (PSO) Algorithm with the Pheromone Mechanism of Ant Colony Optimization (ACO) using Standard Benchmark Function

Swarm intelligence (SI) is the communal behavior of devolved, self-organized structures, natural or artificial. SI systems consist typically of a population of simple agents interacting locally with one another and with their environment. The inspiration often comes from nature, especially biological systems. The agents follow very simple rules, and although there is no centralized control structure dictating how individual agents should behave, local, and to a certain degree random, interactions between such agents lead to the emergence of "intelligent" global behavior, unknown to the individual agents This research work aims at hybridizing the conventional Particle Swarm Optimization (PSO) algorithm with the pheromone mechanism of Ant Colony Optimization (ACO) to attain faster convergence on a feasible standard PSO solution space then benchmarked against standard optimization test functions using Python Programming language to prove the correctness and convergence of the Hybridized PSO optimization mode for minimization. The result shows that hybridizing swarm intelligence performs better in solving difficult continuous optimization problems. General Terms Algorithm, Optimization, Algorithmic Pseudo-code, Swarm Intelligence,
ANALISIS SISTEM ANTRIAN PELANGGAN BANK RAKYATINDONESIA (BRI) CABANG BANDAR LAMPUNG MENGGUNAKANMODEL ANTRIAN MULTI CHANNEL-SINGLE PHASE

Antrian merupakan masalah yang selalu dihadapi oleh nasabah pada suatu bank. Antrian terjadi disebabkan karena kebutuhan akan layanan melebihi kapasitas pelayanan, sehingga nasabah yang datang tidak dapat segera dilayani disebabkan kesibukan layana pada bagian teller. Penelitian dilakukan pada Bank Rakyat Indonesia (BRI) Cabang Bandar Lampung, selama satu minggu pengamatan, setiap harinya pada pukul 09.00-11.00 WIB. Setelah pengambilan data, maka dilakukan pengukuran keseimbangan atau steady state dan pengujian hipotesis. Parameter sistem antrian yang diukur adalah ekspektasi pola kedatangan, ekspektasi pola pelayanan, peluang masa sibuk, ekspektasi panjang antrian, ekspektasi dalam sistem, ekspektasi menunggu dalam sistem, ekspektasi menunggu dalam antrian dan ekspektasi waktu pelayanan. Penelitian ini menghasilkan model antrian (M/G/4) : (FIFO/ , pola kedatangan berdistribusi Poisson dan pola pelayanan tidak berdistribusi Eksponensial, melainkan berdistribusi Normal. Disiplin antrian yaitu first in first out (FIFO), dengan struktur antrian multi channel-single phase. Kata Kunci: First in first out, multi channel-single phase, teori antrian