Virtualni i empirijski uvod u modernizaciju zemljišne evidencije

The land record modernisation is vital for nations under developing economy. The modernisation of land records is tedious process. The written part of the cadastre is modified with ease by use of computers. The map portion of the cadastre is critical for modernisation. The land record modernisation with two procedures and their associated enigma is analysed in this paper. The predominant source of error while performing overlay analysis with digitised land records on satellite images is land slope and the limiting land slope of 8° 15\u27 00\u27\u27 is recommended through virtual analysis. The empirical analysis identified the land area suitable for total station or chain survey. The land area less than 900 m2 requires chain survey and land area greater than 900 m2 requires total station survey. The crucial part of land record modernisation is to identify errors and error sources to create reliable land record to cater needs of land under current development zone. The land under future development zone needs to be segregated to identify suitable area for total station or chain surveying.Modernizacija zemljišne evidencije važna je za nacije s gospodarstvom u razvoju. Modernizacija zemljišne evidencije težak je proces. Pisani dio katastra lako se modificira uz pomoć računala. Grafički dio katastra kritičan je u pogledu modernizacije. U ovom radu analizirana je modernizacija zemljišne evidencije kroz dva postupka i s njima povezanu enigmu. Prevladavajući izvor pogrešaka prilikom analize preklapanja s digitaliziranim zemljišnim podacima na satelitskim snimkama je nagib zemljišta te se preporuča ograničavajući nagib zemljišta od 8° 15\u27 00\u27\u27 kroz virtualnu analizu. Empirijskom analizom utvrđuje se površina zemljišta primjerena za izmjeru geodetskom mjernom stanicom ili lancem. Površina zemljišta manja od 900 m2 zahtijeva izmjeru lancem, a površina zemljišta veća od 900 m2 zahtijeva izmjeru geodetskom mjernom stanicom. Ključni dio modernizacije zemljišne evidencije odnosi se na utvrđivanje pogrešaka i izvora pogrešaka kako bi se izradila pouzdana evidencija zemljišta u svrhu zadovoljavanja potreba zemljišta u trenutnoj zoni razvoja. Zemljište u budućoj zoni razvoja treba biti izdvojeno kako bi se utvrdile odgovarajuće površine za izmjeru geodetskom mjernom stanicom ili lancem

Fusing Long Short-Term Memory and Autoencoder Models for Robust Anomaly Detection in Indoor Air Quality Time-Series Data

People spend most of their time indoors by choice or by need. Carbon dioxide (CO2) accumulation can cause various adverse health effects, including vertigo, headache, and fatigue. Therefore, monitoring indoor air quality(IAQ) is necessary for various health reasons. The market is flooded with air quality monitoring devices. However, the ordinary public does not make use of them because they are expensive and difficult to obtain. Several research studies have been carried out to monitor indoor air quality with the help of the Internet of Things(IoT), which has greatly simplified the method for monitoring IAQ. In this research, we offer an improved IoT based IAQ monitoring system with AI-powered recommendations. Our suggested system relies on the Message Queuing Telemetry Transport(MQTT) protocol for communication between IoT devices. In addition, the gathered CO2 occupancy data is used together with the deep learning approach of Long Short-Term Memory and Autoencoder (LSTM-AE) to detect anomalies or outliers in CO2 concentrations.  Due to a close connection between air quality and human health and well-being, the detection of anomalies in the data of  IAQ has emerged as an essential topic of study. Anomalies requiring the observation of correlations spanning numerous data points (i.e., often referred to as long-term dependencies) were not detectable by conventional statistical and basic machine learning (ML) related techniques in the sector of  IAQ.  Hence this research uses the LSTM-AE model to address this issue.  In comparison to previous similar models, our experimental results on a generated CO2 occupancy time series reveal a robust and powerful accuracy of 99.49%

Portfolio Optimization and the Random Magnet Problem

Diversification of an investment into independently fluctuating assets reduces its risk. In reality, movement of assets are are mutually correlated and therefore knowledge of cross--correlations among asset price movements are of great importance. Our results support the possibility that the problem of finding an investment in stocks which exposes invested funds to a minimum level of risk is analogous to the problem of finding the magnetization of a random magnet. The interactions for this ``random magnet problem'' are given by the cross-correlation matrix {\bf \sf C} of stock returns. We find that random matrix theory allows us to make an estimate for {\bf \sf C} which outperforms the standard estimate in terms of constructing an investment which carries a minimum level of risk.Comment: 12 pages, 4 figures, revte

Alternation of different fluctuation regimes in the stock market dynamics

Based on the tick-by-tick stock prices from the German and American stock markets, we study the statistical properties of the distribution of the individual stocks and the index returns in highly collective and noisy intervals of trading, separately. We show that periods characterized by the strong inter-stock couplings can be associated with the distributions of index fluctuations which reveal more pronounced tails than in the case of weaker couplings in the market. During periods of strong correlations in the German market these distributions can even reveal an apparent L\'evy-stable component.Comment: 19 page

The Apparent Madness of Crowds: Irrational collective behavior emerging from interactions among rational agents

Standard economic theory assumes that agents in markets behave rationally. However, the observation of extremely large fluctuations in the price of financial assets that are not correlated to changes in their fundamental value, as well as the extreme instance of financial bubbles and crashes, imply that markets (at least occasionally) do display irrational behavior. In this paper, we briefly outline our recent work demonstrating that a market with interacting agents having bounded rationality can display price fluctuations that are {\em quantitatively} similar to those seen in real markets.Comment: 4 pages, 1 figure, to appear in Proceedings of International Workshop on "Econophysics of Stock Markets and Minority Games" (Econophys-Kolkata II), Feb 14-17, 200

Bioactive potential of actinobacteria isolated from the gut of marine fishes

1280-1285The study was undertaken to explore the gut-associated actinobacteria from two marine fish with special reference to antimicrobial and anti-quorum sensing activity. A total of 40 actinobacterial strains were isolated from fish gut samples using starch casein agar and Kuster’s agar medium. About 14 morphologically different strains recovered from Rastrelliger kanagurta (Indian mackerel) and Panna microdon (Panna croaker) were screened for the antimicrobial activity against Staphylococcus aureus MTCC96, Escherichia coli MTCC739, Salmonella enterica, Candida albicans, and quorum sensing inhibition (QSI) against Chromobacterium violaceum and Serratia marcescens. The actinobacterial strain IM20 from R. kanagurta showed both antimicrobial and QSI activity, whereas the strains PCA1 and PCA4 from P. microdon showed only antimicrobial activity. Strain IM20, which showed wide range of activity, was selected as the potential strain for further studies. Thus, the findings suggested that the fish-associated actinobacteria is a promising source for antimicrobial compounds for developing novel therapeutic drugs

Long-Time Fluctuations in a Dynamical Model of Stock Market Indices

Financial time series typically exhibit strong fluctuations that cannot be described by a Gaussian distribution. In recent empirical studies of stock market indices it was examined whether the distribution P(r) of returns r(tau) after some time tau can be described by a (truncated) Levy-stable distribution L_{alpha}(r) with some index 0 < alpha <= 2. While the Levy distribution cannot be expressed in a closed form, one can identify its parameters by testing the dependence of the central peak height on tau as well as the power-law decay of the tails. In an earlier study [Mantegna and Stanley, Nature 376, 46 (1995)] it was found that the behavior of the central peak of P(r) for the Standard & Poor 500 index is consistent with the Levy distribution with alpha=1.4. In a more recent study [Gopikrishnan et al., Phys. Rev. E 60, 5305 (1999)] it was found that the tails of P(r) exhibit a power-law decay with an exponent alpha ~= 3, thus deviating from the Levy distribution. In this paper we study the distribution of returns in a generic model that describes the dynamics of stock market indices. For the distributions P(r) generated by this model, we observe that the scaling of the central peak is consistent with a Levy distribution while the tails exhibit a power-law distribution with an exponent alpha > 2, namely beyond the range of Levy-stable distributions. Our results are in agreement with both empirical studies and reconcile the apparent disagreement between their results

Scaling of the distribution of price fluctuations of individual companies

We present a phenomenological study of stock price fluctuations of individual companies. We systematically analyze two different databases covering securities from the three major US stock markets: (a) the New York Stock Exchange, (b) the American Stock Exchange, and (c) the National Association of Securities Dealers Automated Quotation stock market. Specifically, we consider (i) the trades and quotes database, for which we analyze 40 million records for 1000 US companies for the 2-year period 1994--95, and (ii) the Center for Research and Security Prices database, for which we analyze 35 million daily records for approximately 16,000 companies in the 35-year period 1962--96. We study the probability distribution of returns over varying time scales $\Delta t$, where $\Delta t$ varies by a factor of $\approx 10^5$---from 5 min up to $\approx$ 4 years. For time scales from 5~min up to approximately 16~days, we find that the tails of the distributions can be well described by a power-law decay, characterized by an exponent $\alpha \approx 3$ ---well outside the stable L\'evy regime $0 < \alpha < 2$. For time scales $\Delta t \gg (\Delta t)_{\times} \approx 16$days, we observe results consistent with a slow convergence to Gaussian behavior. We also analyze the role of cross correlations between the returns of different companies and relate these correlations to the distribution of returns for market indices.Comment: 10pages 2 column format with 11 eps figures. LaTeX file requiring epsf, multicol,revtex. Submitted to PR

Economic Fluctuations and Diffusion

Stock price changes occur through transactions, just as diffusion in physical systems occurs through molecular collisions. We systematically explore this analogy and quantify the relation between trading activity - measured by the number of transactions $N_{\Delta t}$ - and the price change $G_{\Delta t}$, for a given stock, over a time interval $[t, t+\Delta t]$. To this end, we analyze a database documenting every transaction for 1000 US stocks over the two-year period 1994-1995. We find that price movements are equivalent to a complex variant of diffusion, where the diffusion coefficient fluctuates drastically in time. We relate the analog of the diffusion coefficient to two microscopic quantities: (i) the number of transactions $N_{\Delta t}$ in $\Delta t$, which is the analog of the number of collisions and (ii) the local variance $w^2_{\Delta t}$ of the price changes for all transactions in $\Delta t$, which is the analog of the local mean square displacement between collisions. We study the distributions of both $N_{\Delta t}$ and $w_{\Delta t}$, and find that they display power-law tails. Further, we find that $N_{\Delta t}$ displays long-range power-law correlations in time, whereas $w_{\Delta t}$ does not. Our results are consistent with the interpretation that the pronounced tails of the distribution of $G_{\Delta t} are due to$w_{\Delta t}$, and that the long-range correlations previously found for$| G_{\Delta t} |$are due to$N_{\Delta t}$.Comment: RevTex 2 column format. 6 pages, 36 references, 15 eps figure

Components of multifractality in high-frequency stock returns

We analyzed multifractal properties of 5-minute stock returns from a period of over two years for 100 highly capitalized American companies. The two sources: fat-tailed probability distributions and nonlinear temporal correlations, vitally contribute to the observed multifractal dynamics of the returns. For majority of the companies the temporal correlations constitute a much more significant related factor, however.Comment: to appear in Physica