Miracle-dz/UniFAR-FTUs huggingface dataset:
VARIASI MORFOLOGI ANDALIMAN (ZANTHOXYLUM ACANTHOPODIUM) DI SUMATRA UTARA

Romaita Newanti Lumban Raja & Alex Hartana. 2017. Morphologycal Variation of Andaliman (Zanthoxylum acanthopodium) in North Sumatra. Floribunda 5(7): 258–266. — Andaliman plants (Zantoxylum acanthopodium DC.) found in North Sumatra, Indonesia, and known as seasoning plants or 'merica Batak’ in Batak dishes. This study was conducted to explore the diversity of andaliman plants in North Sumatra. 27 andaliman plants collected and analyzed based on their 24 morphological characters of stems, leaves, flowers, fruits, and seeds using unweighted pair group method with arithmatic average (UPGMA) and clustered based on similarity for qualitative data (SIMQUAL) and coefficient simple matching, using NTSYS pc. 2.02 version. The phenetic analysis showed dendrograme of 27 andaliman plants in North Sumatra were clustered into 4 groups. The main characters differentiate each group are the color of young branches, thorns on leaf midrib, the color of calyx, and the color of fruit. The group I and II in dendrograme refer to local cultivar names ‘Simanuk’ and ‘Sihorbo’, while the group III and IV refer to ‘Silokot’ and ‘Sikoreng’ cultivars. An identification key for the four andaliman cultivars is presented. Keywords: Andaliman, Character, Clustering, North Sumatra, Morphology, Zantoxylum acanthopodium. Romaita Newanti Lumban Raja & Alex Hartana. 2017. Variasi Morfologi Andaliman (Zanthoxylum acanthopodium) di Sumatra Utara. Floribunda 5(7): 258–266. — Andaliman (Zantoxylum acanthopodium DC.) di Indonesia banyak terdapat di Sumatra Utara dan digunakan sebagai bumbu masakan khas suku Batak. Eksplorasi keberagaman andaliman telah dilakukan dan diperoleh 27 nomer sampel. Analis fenetik berdasarkan 26 karakter morfologi terhadap 27 sampel telah dilakukan dengan metode UPGMA melalui program NTSys versi 2.02. Dendrogram yang dihasilkan menunjukan ada 4 kelompok andaliman yang terpisah berdasarkan karakter utama yang membedakan setiap kelompok yaitu warna dahan muda, rambut pada dahan, onak pada ibu tulang daun, warna kelopak bunga, dan warna buah. Berdasarkan klasifikasi masyarakat, kelompok I dan II merujuk pada kultivar ‘Simanuk’ dan ‘Sihorbo’. Sedangkan kelompok III dan IV merujuk pada kultivar ‘Silokot’ dan ‘Sikoreng’. Hasil pengelompokan kemudian digunakan untuk pembuatan kunci identifikasi. Kata kunci: Andaliman, karakter, pengelompokan, Sumatra Utara, morfologi, Zantoxylum acanthopodium.
Galactic and extragalactic contributions to the astrophysical muon neutrino signal

Spectral and anisotropy properties of IceCube astrophysical neutrino signal reveal an evidence for a significant Galactic contribution to the neutrino flux in Southern hemisphere. We check if the Galactic contribution is detectable in the astrophysical muon neutrino flux observed from a low positive declinations region of the Northern sky. Estimating the Galactic neutrino flux in this part of the sky from gamma-ray and Southern sky neutrino data, we find that the Northern sky astrophysical muon neutrino signal shows an excess over the Galactic flux. This points to the presence of an additional hard spectrum (extragalactic or large scale Galactic halo) component of astrophysical neutrino flux. We show that the Galactic flux component should still be detectable in the muon neutrino data in a decade long IceCube exposure.
Data Mining Software

With increasing amounts of data being generated by businesses and researchers, there is a need for fast, accurate, and robust algorithms for data analysis. Improvements in databases technology, computing performance, and artificial intelligence have contributed to the development of intelligent data analysis. The primary aim of data mining is to discover patterns in the data that lead to better understanding of the data generating process and to make useful predictions (Hand, Mannila, & Smyth, 2001). Most companies now collect and refine massive quantities of data in data warehouses. These companies realize that to succeed in a fast paced world, business users need to be able to get information on demand. Many organizations now view information as one of their most valuable assets, and data mining software allows a company to make full use of these information assets. Data mining software analyzes relationships and patterns in stored transaction data based on open-ended user queries. Several types of analytical software are available: statistical, machine learning and neural networks, decision trees, naive-Bayes, K-nearest neighbor, rule induction, clustering, rules based, linear and logistical regression time sequence, and so forth (Wang, 2005). There is never enough time to think of all the important questions; that is why the computer should do this itself. It can provide the winning edge in business by exploring the database and it brings back invaluable information.
Oxygen isotope composition of the final chamber of planktic foraminifera provides evidence of vertical migration and depth-integrated growth

Abstract. The translation of the original seawater signal (i.e. ambient temperature and δ18Osw) into distinct chambers of a single shell of a foraminifer during calcification can influence our interpretation of surface ocean conditions of the past, when based upon oxygen and carbon stable isotope geochemistry. In this study three different hypotheses were tested to gain more insight into biological and ecological processes that influence the resultant composition of stable isotopes of oxygen (δ18O) in the shells of planktonic foraminifera. These hypotheses were related to the shell size; the differences in isotopic composition between the final chamber and the remaining shell; and the differences between different species. Shells of Trilobatus sacculifer, Globigerinoides ruber white and Neogloboquadrina dutertrei were picked from the top of multi-core GS07-150-24, of modern age, offshore of north-eastern Brazil (3∘46.474′ S, 37∘03.849′ W) and analysed for single-shell and single-chamber stable isotope analysis. We show that the mean value of δ18O of the final chambers (δ18OF) is 0.2 ‰ ± 0.4 ‰ (1σ) higher than the mean value δ18O of the test minus the final chamber (δ18O<F) of T. sacculifer. The formation of the final chamber happens at temperatures that are approximately 1 ∘C cooler than the chambers formed prior, suggesting both ontogenetic depth migration to deeper water and a potential offset from the surface signal. Furthermore, we show that there is no statistical difference in the δ18Osacculifer values of shells of three different size classes of T. sacculifer, although the pattern between the different size classes indicates depth migration during the life and growth of T. sacculifer. Comparison of vital effect corrected δ18Oshell between T. sacculifer, G. ruber white and N. dutertrei suggests that G. ruber has a slightly shallower depth habitat (∼90–120 m) compared to the other two species (∼100–130 m). Disentangling depth vs. seasonal habitat is complicated given the commonality between isotope values from similar depths but different seasons; for instance, the same average isotope value will have a shallower depth habitat in May than September. Calculation of seasonal-depth habitat was therefore tested. Our results highlight the complicated nature of interpreting oxygen isotopes even for the modern record.
Characterization and dewatering of borax clayey tailings by mono- and dual-flocculants systems

Bu calisma, Kirka Borax Konsantrator atiginin tekli- ve ikili-fl okulant sistemini kullanan fl okulasyon yontemi ile susuzlandirilmasini icerir. Zenginlestirme atiginin tekli- ve ikili – fl okulant sistemi ile fl okulasyonunda polyacrilamid (PAM) turu 4 adet anyonik polimer ile poli dialil-dimetil amonyum klorur (polyDADMAC) turu bir katyonik polimer fl okulant olarak kullanilmistir. Deneylerde kullanilan pulp halindeki zenginlestirme atigi numunesi Kirka Borax Konsantratorunun atik desarj noktasindan alinmistir. Flokulasyon testlerinden once fi ziksel, kimyasal ve mineralojik analizler ile atigin karakterizasyonu gerceklestirilmistir. Sonuclar, zenginlestirme atigi katisinin baslica dolomit, montmorillonit ve ince tane boyunda bir miktar bor minerali kacagi ile cok az miktarda kalsit ve kuvarstan olustugunu, zenginlestirme atigi sivi kisminin ise temel karakteristiginin pH degeri (9,4) ve oldukca yuksek cozunmus karbonat ve boraks icerigi oldugunu gostermistir. Flokulasyon testleri 1 litrelik dereceli mezurde ve zenginlestirme atigi numunesinin kendi pH degerinde gerceklestirilmistir. Kullanilan farkli fl okulantlarin fl okulasyon performansini degerlendirmek icin cokelme hizi ve ust akim bulanikligi onemli parametreler olarak olculmustur. Zenginlestirme atik numunesi, kil icerigi ve ince tane boyundaki kati oraninin yuksek olmasi nedeniyle oldukca yavas bir cokelme davranimi gostermistir. Zenginlestirme atiginin anyonik fl okulant ile fl okulasyonu katinin cokelme hizini artirirken berrak bir ust akim saglayamamistir. Ancak, anyonik ve katyonik polimerik fl okulantlarin birlikte kullanildigi ikili- fl okulant sisteminde nispeten yuksek cokelme hizlarinda temiz ust akim saglanabilmistir.
Structural parameters and above-ground biomass of mangrove tree species around the Kakum river estuary of Ghana.

Analysis of forest structure and standing biomass are established methods used to evaluate the maturity of a forest ecosystem. This research aimed at evaluating the structural dimensions and biomass of the mangrove forest around the Kakum estuary of Ghana. A 1 hectare area was sampled. Data was collected with a 10 m2 quadrat at five random sampling points along five transects laid perpendicular to the shoreline. The results showed that R. mangle is the principal species with Importance Value (IV) of 126.53 and Height (H) and Basal Area (BA) of 5.19±2.72 m and 8.55±6.86 cm2 respectively, then A. germinans (IV of 103.02; H of 3.05±1.05 m and BA of 7.90±7.41 cm2). L. racemosa had the least structural parameters (IV of 70.45; H of 2.42±0.99 m and BA of 5.36±4.65 cm2). R. mangle had the highest standing biomass, followed by A. germinans and L. racemosa amounting to 134.08 t/ha, 35.02 t/ha and 22.08 t/ha respectively. The most significant conclusion from this study is that even though R. mangle was found to be the principal species and significantly larger in terms of mean height, basal area and standing biomass, they are of generally low structural development, as applied to the other species as well. We strongly suggest that because these mangroves are being threatened by human development, efforts that allow for maximum structural development of the mangroves must be seriously pursued if the ecosystem is expected to continue to provide an increasingly sustainable source of the required ecological goods and functional services.
The geo-spatial analysis and environmental factors of narcotics hot spots

A mixed methodological approach with two different analytic procedures and multiple data sources was used to examine narcotics hot spots. The first phase compares two methods of hot spots identification; the prediction model and the actual crime. The second phase involves an intensive study to better understand the phenomenon of drug hot spots areas consistently shown to be repeat hotspots. The findings themselves were not statistically significant in reference to the individual indicators of narcotics crime, the prediction model, nor the repeat versus single call incidents. However, the model itself generated interesting ideas that can assist police agencies in better preventing or controlling narcotics activity.
An Improved Anomaly Detection Model for IDS

The application of machine learning technique to anomaly detection acts as one of the important directions of research on IDS. This paper introduces an user behavior anomaly detection model based on machine learning originated mainly by Terran Lane. Then it presents an improved anomaly detection model. It uses shell command sequences of variable lengths to represent user behavior patterns and construct more than one libraries of command sequences to represent normal user behavior profiles. While performing detection, the model mines behavior patterns in the stream of shell command sequences generated by the current user, and evaluates the similarity for each shell command according to the length of the sequence, i.e. the behavior pattern which it belongs to. The similarities of the commands are then filtered and act as the measure to determine whether the behavior of the current user is noamal or not. The performance of the model is tested by computer simulation with UNIX users' shell command data. The results show it has higher detection accuracy than Terran Lane's model.
Semantic Analysis of Facial Gestures from Video Using a Bayesian Framework

The continuous growth of video technology has resulted in increased research into the semantic analysis of video. The multimodal property of the video has made this task very complex. The objective of this thesis was to research, implement and examine the underlying methods and concepts of semantic analysis of videos and improve upon the state of the art in automated emotion recognition by using semantic knowledge in the form of Bayesian inference. The main domain of analysis is facial emotion recognition from video, including both visual and vocal aspects of facial gestures. The goal is to determine if an expression on a person's face in a sequence of video frames is happy, sad, angry, fearful or disgusted. A Bayesian network classification algorithm was designed and used to identify and understand facial expressions in video. The Bayesian network is an attractive choice because it provides a probabilistic environment and gives information about uncertainty from knowledge about the domain. This research contributes to current knowledge in two ways: by providing a novel algorithm that uses edge differences to extract keyframes in video and facial features from the keyframe, and by testing the hypothesis that combining two modalities (vision with speech) yields a better classification result (low false positive rate and high true positive rate) than either modality used alone.
The High Spatial Resolution RS Image Classification Based on SVM Method with the Multi-Source Data

The RS image shows a very promising perspective for urban land-cover and land-use classification,particularly with very high resolution(1—4m) satellite images,while the traditional extraction methods of the high spatial resolution image has the shortcomings of the low accuracy and classification efficiency.This paper deals with the high spatial resolution image(IKONOS) classification based on the SVM method integrating the information of spectral,texture and structure.And comparing to the results based on Maximum Likelihood and SVM method with single-source data,this shows that the high spatial resolution RS image classification based on SVM Method with multi-source data can solve the image classification fragmentation which is based on the single-source data,spectrum,and has the good generalization ability with the high dimension vector.It has more accuration than the maximum likelihood method and SVM based on the single source data,adapts to the high spatial resolution RS Image classification.
The karst and its neighbors: Digital map of geomorphic environments in Quintana Roo

The Yucatan peninsula is a large, carbonate platform with several geomorphic environments, the largest of which is the karst. The other geomorphic environments have not drawn much scholarly attention. The objective of this work is to spatially identify the geomorphic environments found in Quintana Roo, Mexico. These environments were characterized and defined through their geomorphic and environmental conditions, such as climate and vegetation. The soil types associated with them using cluster statistical analysis, principal components and classification analysis, processed through a GIS system. Seven geomorphic environments were defined for Quintana Roo based on their geomorphological characteristics and types of coverage: littoral, paludal, pseudopaludal, tecto-karstic, karstic, gypsum karst and mixed karst, with 12 subtypes. The karstic and tecto-karstic geomorphic environments occupy the largest surface. The digital map (1:50,000) of geomorphic environments that resulted from this investigation has an accuracy level of more than 80%, which makes it an important tool for developing plans and strategies for the use and management of land in Quintana Roo.
GRAVITATIONAL INFALL ONTO MOLECULAR FILAMENTS. II. EXTERNALLY PRESSURIZED CYLINDERS

Two aspects of the evolution of externally pressurized, hydrostatic filaments are discussed. (1) The free-fall accretion of gas onto such a filament will lead to filament parameters (specifically, FWHM–column-density relations) inconsistent with the observations of Arzoumanian et al., except for two cases: for low-mass, isothermal filaments, agreement is found as in the analysis by Fischera & Martin. Magnetized cases, for which the field scales weakly with the density as B∝n1/2, also reproduce observed parameters. (2) Realistically, the filaments will be embedded not only in gas of non-zero pressure, but also of non-zero density. Thus, the appearance of sheet-embedded filaments is explored. Generating a grid of filament models and comparing the resulting column density ratios and profile shapes with observations suggests that the three-dimensional filament profiles are intrinsically flatter than isothermal, beyond projection and evolution effects.
Online and statistical learning in networks

ONLINE AND STATISTICAL LEARNING IN NETWORKS Shahin Shahrampour Ali Jadbabaie Alexander Rakhlin Learning, prediction and identification has been a main topic of interest in science and engineering for many years. Common in all these problems is an agent that receives the data to perform prediction and identification procedures. The agent might process the data individually, or might interact in a network of agents. The goal of this thesis is to address problems that lie at the interface of statistical processing of data, online learning and network science with a focus on developing distributed algorithms. These problems have wide-spread applications in several domains of systems engineering and computer science. Whether in individual or group, the main task of the agent is to understand how to treat data to infer the unknown parameters of the problem. To this end, the first part of this thesis addresses statistical processing of data. We start with the problem of distributed detection in multi-agent networks. In contrast to the existing literature which focuses on asymptotic learning, we provide a finite-time analysis using a notion of Kullback-Leibler cost. We derive bounds on the cost in terms of network size, spectral gap and relative entropy of data distribution. Next, we turn to focus on an inverse-type problem where the network structure is unknown, and the outputs of a dynamics (e.g. consensus dynamics) are given. We propose several network reconstruction algorithms by measuring the network response to the inputs. Our algorithm reconstructs the Boolean structure (i.e., existence and directions of links) of a directed network from a series of dynamical responses. The second part of the thesis centers around online learning where data is received in a sequential fashion. As an example of collaborative learning, we consider the v stochastic multi-armed bandit problem in a multi-player network. Players explore a pool of arms with payoffs generated from player-dependent distributions. Pulling an arm, each player only observes a noisy payoff of the chosen arm. The goal is to maximize a global welfare or to find the best global arm. Hence, players exchange information locally to benefit from side observations. We develop a distributed online algorithm with a logarithmic regret with respect to the best global arm, and generalize our results to the case that availability of arms varies over time. We then return to individual online learning where one learner plays against an adversary. We develop a fully adaptive algorithm that takes advantage of a regularity of the sequence of observations, retains worst-case performance guarantees, and performs well against complex benchmarks. Our method competes with dynamic benchmarks in which regret guarantee scales with regularity of the sequence of cost functions and comparators. Notably, the regret bound adapts to the smaller complexity measure in the problem environment.
Effect of Fillet Thickness on Quality and Shelf Life of Gravlax Salmon

There is an increasing demand for fish and fish products around the world [5]. Seafoods have traditionally been popular in many countries as an alternative source of animal protein [6]. Nowadays, more people are returning to seafood as a healthy alternative to red meat. The low fat content in many fish species (white fleshed, demersal) has positive impacts on coronary heart disease due to the n-3 polyunsaturated fatty acids. This is particularly important for health of conscious people especially in affluent countries, where heart disease mortality is high [6].
One Unwanted Feature of Many Web Vulnerability Scanners

Security experts, web developers, hackers sometimes use Web Vulnerability Scanners (WVSs) for identifying vulnerabilities in web applications. There are commercial and free/open source WVSs, and nowadays, many companies offer WVSs as services. In this paper, we test and evaluate 3 free/open source WVSs and 4 free, trial or regular editions of commercial WVSs using two versions of our one created trading web application. One version has SQL injection and XSS vulnerabilities as critical, and the other version is free from these vulnerabilities. Results are showing that most of the scanners pollute the backend database with many garbage records using user input fields for obtaining user’s opinion, comments, rating, etc., independently of the presence or absence of given critical vulnerabilities. In our experiment, garbage records were injected as comments for ads, and the magnitude of pollution goes more than 50 times the number of ads in the database in the worst case. Also, some scanners manage to find the implemented vulnerabilities without producing garbage records.
Approches formelles dans l'assistance au développement de logiciels

The B-method, as well as its offspring Event-B, are both tool-supported formal methods used for the development of computer systems whose correctness is formally proven. However, the more complex the specification becomes, the more proof obligations need to be discharged. While many proof obligations can be discharged automatically by recent tools such as the RODIN platform, a considerable number still have to be proven interactively. This can be either because the required proof is too complicated or because the B model is erroneous. In this paper we describe a disprover plugin for RODIN that utilizes the ProB animator and model checker to automatically find counterexamples for a given problematic proof obligation. In case the disprover finds a counterexample, the user can directly investigate the source of the problem (as pinpointed by the counterexample) and should not attempt to prove the proof obligation. We also discuss under which circumstances our plug-in can be used as a prover, i.e., when the absence of a counterexample actually is a proof of the proof obligation.