Consequences of changing rainfall for fungal pathogen-induced mortality in tropical tree seedlings

Most general circulation models predict that most tropical forests will experience lower and less frequent rainfall in future as a result of climate change, which may reduce the capacity of fungal pathogens to drive density-dependent tree mortality. This is potentially significant because fungal pathogens are thought to play a key role in promoting and structuring plant diversity in tropical forests through the Janzen–Connell mechanism. Therefore, we hypothesize that the drying of tropical forests will negatively impact species coexistence. To test one prediction of this hypothesis, we imposed experimental watering regimes on the seedlings of a tropical tree, Pleradenophora longicuspis, and measured mortality induced by fungal pathogens under shade house conditions. The frequency of watering had a strong impact on survival. Seedlings watered daily experienced significantly higher mortality than those watered every three or every six days, while increasing the volume of water applied also led to increased mortality, although this relationship was less pronounced. These results suggest that the capacity of fungal pathogens to drive density-dependent mortality may be reduced in drier climates and when rainfall is less frequent, with potential implications for the diversity enhancing Janzen–Connell mechanism

STUDIJA DOHVATA SLIKA POMOĆU POJAČANE TRANSFORMACIJE RADONA I PCS I LDA TEHNIKA

Image Retrieval is very one of the biggest task in the recent years. It is widely used in many real time databases to retrieve related images in various fields like medicine, military, online shopping etc. This paper offers with using radon transform followed by PCA and LDA techniques for image retrieval is called as Combined Radon Space Features Set (CRSFS). Caltech 101 database image sets used in this paper. The correct direction is select means the computation time and complexity of operation is less to achieve good retrieval rate.Obrada slika je jedan od najvećih zadataka u posljednjih nekoliko godina. Naširoko se koristi u mnogim bazama podataka kad se u realnom vremenu koriste povezane slike u različitim područjima kao što su medicina, vojska, online trgovina, itd. Ovaj rad nudi pomoć radon pretvorbe i zatim PCA i LDA tehnika za popravljanje slike (CRSFS). Korištena je Caltech 101 baza slika. Ispravan smjer je odabrati način računanja vremena i složenosti rada da bi se postigla manja cijena preuzimanja

ISTRAŽIVANJE O POVEZIVANJU ENTITETA ZA SPECIFIČNE DOMENE S HETEROGENIM INFORMACIJSKIM MREŽAMA

Entity linking is a task of extracting information that links the mentioned entity in a collection of text with their similar knowledge base as well as it is the task of allocating unique identity to various entities such as locations, individuals and companies. Knowledgebase (KB) is used to optimize the information collection, organization and for retrieval of information. Heterogeneous information networks (HIN) comprises multiple-type interlinked objects with various types of relationship which are becoming increasingly most popular named bibliographic networks, social media networks as well including the typical relational database data. In HIN, there are various data objects are interconnected through various relations. The entity linkage determines the corresponding entities from unstructured web text, in the existing HIN. This work is the most important and it is the most challenge because of ambiguity and existing limited knowledge. Some HIN could be considered as a domain-specific KB. The current Entity Linking (EL) systems aimed towards corpora which contain heterogeneous as web information and it performs sub-optimally on the domain-specific corpora. The EL systems used one or more general or specific domains of linking such as DBpedia, Wikipedia, Freebase, IMDB, YAGO, Wordnet and MKB. This paper presents a survey on domain-specific entity linking with HIN. This survey describes with a deep understanding of HIN, which includes datasets,types and examples with related concepts.Povezivanje entiteta je zadatak izvlačenja podataka koji povezuju spomenuti entitet u zbirci teksta sa njihovom sličnom bazom znanja, kao i zadatak dodjeljivanja jedinstvenog identiteta različitim entitetima, kao što su lokacije, pojedinci i tvrtke. Baza znanja (BZ) koristi se za optimizaciju prikupljanja, organizacije i pronalaženja informacija. Heterogene mreže informacija (HMI) obuhvaćaju višestruke međusobno povezane objekte različitih vrsta odnosa koji postaju sve popularniji i nazivaju se bibliografskim mrežama, mrežama društvenih medija, uključujući tipične podatke relacijske baze podataka. U HMI-u postoje razni podaci koji su međusobno povezani kroz različite odnose. Povezanost entiteta određuje odgovarajuće entitete iz nestrukturiranog teksta na webu u postojećem HMI-u. Ovaj je rad najvažniji i najveći izazov zbog nejasnoće i postojećeg ograničenog znanja. Neki se HMI mogu smatrati BZ-om specifičnim za domenu. Trenutni sustav povezivanja entiteta (PE) usmjeren je prema korpusima koji sadrže heterogene informacije kao web informacije i oni djeluju suptimalno na korpusima specifičnim za domenu. PE sustavi koristili su jednu ili više općih ili specifičnih domena povezivanja, kao što su DBpedia, Wikipedia, Freebase, IMDB, YAGO, Wordnet i MKB. U ovom radu predstavljeno je istraživanje o povezivanju entiteta specifičnog za domenu sa HMI-om. Ovo istraživanje opisuje s dubokim razumijevanjem HMI-a, što uključuje skupove podataka, vrste i primjere s povezanim konceptima

SUSTAV ZA OTKRIVANJE I OBRANU KORIŠTENJEM RUDARENJA PODATAKA

Network security helps to prevent the network against the intruders from performing malicious activities. The security can be provided to the networks using firewalls, anti-virus software and scanners, cryptographic systems, Secure Socket Layer (SSL) and Intrusion Detection Systems (IDS).Authentication is the commonly used technique to protect the unauthorized users from the network. But, it is easy to compromise the login passwords using brute force attacks. The IDS and firewalls concentrate on the external attacks, while the internal attacks are not taken into account. In order to solve these issues, this paper proposes an Inner Interruption Discovery and Defense System (IIDDS) at the System Call (SC) level using data mining and forensic techniques. The user’s profiles are maintained and compared with the actual dataset using Hellinger distance. A hash function is applied on the incoming messages and they are summarized in the sketch dataset. The experimental results evaluate the proposed system in terms of accuracy and response time.Mrežna sigurnost pomaže zaštititi mrežu od uljeza u obavljanju zlonamjernih aktivnosti. Sigurnost se može osigurati mrežama koristeći vatrozide, antivirusni softver i skenere, kriptografske sustave, Secure Socket Layer (SSL) i sustave za otkrivanje upada (IDS). Autentifikacija je najčešće korištena tehnika za zaštitu neovlaštenih korisnika na mreži. No, lako je kompromitirati lozinke za prijavu pomoću napada na silu. IDS i vatrozidi koncentriraju se na vanjske napade, dok se interni napadi ne uzimaju u obzir. Da bi se riješili ti problemi, u članku se predlaže unutarnje prekidanje i obrambeni sustav (IIDDS) na razini System Call (SC) razine pomoću rudarenja podataka i forenzičke tehnike. Profili korisnika održavaju se i uspoređuju sa stvarnim skupom podataka pomoću Hellingerove udaljenosti. Na dolazne poruke primjenjuje se hash funkcija i oni su sažeti u skupu skica podataka. Eksperimentalni rezultati procjenjuju predloženi sustav u smislu točnosti i vremena odziva

ROBUSNA AUTOMATSKA VIZUALNA METODA ZA ODREĐIVANJE KUTOVA LICA IZ SLIKA

A analysis of human facial images has become increasingly important due to its numerous applications. In this regards, extracting facial parameter is vital and various studies have been done in this field. Hence in our proposed work, first time up to our knowledge, a robust automatic method is introduced for determining facial angles from profile view images using radon transform. Radon transform is a kind of linear integration along a specific direction and angles play an important role to do this transform. The global features were rather considered by constructing a linear discriminant analysis (LDA) and also local features were rather considered by locality preserving projection (LPP). Our proposed combined algorithm has not only good precision, but also efficient performance and robust with noisy, scale and rotated image environments. In this work, several experiments have been conducted to analyze the robustness of our proposed Radon Combined Global and Local Preserving Features (RCGLPF) algorithm along with other existing conventional algorithms.Analiza ljudskih slika lica postaje sve važnija zbog brojnih primjena. U tom smislu, ekstrakcija parametra lica je od vitalnog značaja i na tom su području učinjene različite studije. Stoga se u našem predloženom radu, prvi put po našem saznanju, uvodi robusna automatska metoda za određivanje kutova lica iz slika profila pomoću radonske transformacije. Transformacija radona je vrsta linearne integracije duž određenog smjera, a kutovi igraju važnu ulogu u toj transformaciji. Globalna obilježja razmotrena su konstrukcijom linearne diskriminacijske analize (LDA), a lokalna obilježja razmatrana su pomoću projekcije očuvanja lokaliteta (LPP). Naš predloženi kombinirani algoritam ima ne samo dobru preciznost, nego i učinkovite performanse i robustnost s bučnim, skaliranim i rotiranim okruženjima slike. U ovom radu provedeno je nekoliko eksperimenata za analizu robustnosti našeg predloženog algoritma globalnog i lokalnog očuvanja radona (RCGLPF) zajedno s drugim postojećim konvencionalnim algoritmima

PROVIDING AN AI-ENABLED NETWORK ASSISTANT FOR COMMAND LINE INTERFACE ENVIRONMENTS

Techniques are presented herein that support a “copilot” for a command-line interface (CLI) in the form of a CLI-driven network assistant that may help a user through the automatic completion of a command; that may provide a one-line summary of the reasons behind a predicted command; and that may recommend expected commands and expected actions for the user, not only for the user’s current request but also considering the specific state of a network. Aspects of the presented techniques may leverage artificial intelligence (AI) technology and large language model (LLM) algorithms

AUTOMATED COMMUNICATION SYSTEM FOR DETECTION OF LUNG CANCER USING CATASTROPHE FEATURES

Jedan od najvećih izazova s kojima se svijet danas suočava je smrtnost od raka. Jedan od četiri svih dijagnosticiranih karcinoma uključuje karcinom pluća, gdje je smrtnost visoka, čak i nakon tolikog tehničkog i medicinskog napretka. Većina slučajeva raka pluća dijagnosticira se u trećem ili četvrtom stadiju, kada se bolest ne može liječiti. Glavni razlog najveće smrtnosti zbog karcinoma pluća je nedostupnost sustava za „preskrining“ koji može detektirati stanice raka u ranim fazama. Stoga je potrebno razviti sustav za predklinički pregled koji pomaže liječnicima da pronađu i otkriju rak pluća u ranim fazama. Od svih vrsta karcinoma pluća, adenokarcinom se povećava alarmantnom brzinom. Razlog se uglavnom pripisuje povećanoj stopi pušenja - i aktivnom i pasivnom. U ovom radu razvijen je sustav za klasifikaciju plućnih žljezdanih stanica za rano otkrivanje raka korištenjem više prostora u boji. Za segmentaciju koriste se razne tehnike klasteriranja na različitim prostorima boja kao što su HSV, CIELAB, CIEXYy i CIELUV. Značajke se izdvajaju i klasificiraju pomoću Support Vector Machine (SVM).One of the biggest challenges the world face today is the mortality due to Cancer. One in four of all diagnosed cancers involve the lung cancer, where the mortality rate is high, even after so much of technical and medical advances. Most lung cancer cases are diagnosed either in the third or fourth stage, when the disease is not treatable. The main reason for the highest mortality, due to lung cancer is because of non availability of prescreening system which can analyze the cancer cells at early stages. So it is necessary to develop a prescreening system which helps doctors to find and detect lung cancer at early stages. Out of all various types of lung cancers, adenocarcinoma is increasing at an alarming rate. The reason is mainly attributed to the increased rate of smoking - both active and passive. In the present work, a system for the classification of lung glandular cells for early detection of Cancer using multiple color spaces is developed. For segmentation, various clustering techniques like K-Means clustering and Fuzzy C-Means clustering on various Color spaces such as HSV, CIELAB, CIEXYy and CIELUV are used. Features are Extracted and classified using Support Vector Machine (SVM)

MODEL KONTROLE PRISTUPA USLUGAMA U OBLAKU NA OSNOVU RAZLIČITIH ULOGA KORISNIKA

The rapid development of computer technology, cloud-based services have become a hot topic. They not only provide users with convenience, but also bring many security issues, such as data sharing and privacy issue. In this paper, we present an access control system with privilege separation based on privacy protection (PS-ACS). In the PS-ACS scheme, we divide users into private domain (PRD) and public domain (PUD) logically. In PRD, to achieve read access permission and write access permission, we adopt the Key-Aggregate Encryption (KAE) and the Improved Attribute-based Signature (IABS) respectively. In PUD, we construct new multi-authority cipher text policy attribute-based encryption (CP-ABE) scheme with efficient decryption to avoid the issues of single point of failure and complicated key distribution, and design an efficient attribute revocation method for it. The analysis and simulation result shows that our scheme is feasible and superior to protect users’ privacy in cloud-based services.Nagli razvoj računalne tehnologije, usluge temeljene na oblaku, postale su aktualna tema. Oni ne samo da korisnicima pružaju praktičnost, nego i donose mnoga sigurnosna pitanja, kao što je dijeljenje podataka i problem privatnosti. U ovom radu predstavljamo sustav kontrole pristupa s razdvajanjem povlastica na temelju zaštite privatnosti (PS-ACS). U PS-ACS shemi, podijelimo korisnike na privatnu domenu (PRD) i javnu domenu (PUD) logično. U PRD-u, da bi se postiglo dopuštenje pristupa za čitanje i dopuštenje za pisanje, usvajamo ključno šifriranje (KAE) i poboljšani potpis na temelju atributa (IABS). U PUD-u konstruiramo novu shemu šifriranja (CP-ABE) koja se temelji na pravilima šifriranog teksta s učinkovitim dešifriranjem kako bismo izbjegli probleme s jednom točkom neuspjeha i komplicirane distribucije ključeva i dizajnirali učinkovitu metodu opoziva atributa za nju. Rezultati analize i simulacije pokazuju da je naša shema izvediva i superiorna za zaštitu privatnosti korisnika u uslugama temeljenim na oblaku

Bumblebees are not deterred by ecologically relevant concentrations of nectar toxins

Bees visit flowers to collect nectar and pollen that contain nutrients and simultaneously facilitate plant sexual reproduction. Paradoxically, nectar produced to attract pollinators often contains deterrent or toxic plant compounds associated with herbivore defence. The functional significance of these nectar toxins is not fully understood, but they may have a negative impact on pollinator behaviour and health, and, ultimately, plant pollination. This study investigates whether a generalist bumblebee, Bombus terrestris, can detect naturally occurring concentrations of nectar toxins. Using paired-choice experiments, we identified deterrence thresholds for five compounds found in the nectar of bee-pollinated plants: quinine, caffeine, nicotine, amygdalin and grayanotoxin. The deterrence threshold was determined when bumblebees significantly preferred a sucrose solution over a sucrose solution containing the compound. Bumblebees had the lowest deterrence threshold for the alkaloid quinine (0.01 mmol l−1); all other compounds had higher deterrence thresholds, above the natural concentration range in floral nectar. Our data, combined with previous work using honeybees, suggest that generalist bee species have poor acuity for the detection of nectar toxins. The fact that bees do not avoid nectar-relevant concentrations of these compounds likely indicates that it is difficult for them to learn to associate floral traits with the presence of toxins, thus maintaining this trait in plant popula