Persistence of earnings and prediction of future cash flows: the role of timely recognition of bad news

Timely recognition of losses and expenses compared to revenues and increased values precipitates future expenses to match with current revenues. Thus, timely recognition of losses acts to reduce the persistence of earnings. However, it is expected that a more timely recognition of negative cash flows, as bad news, increase the power of earnings for predicting future cash flows. This study investigates the effects of the timely recognition of bad news (loss) versus the good news on the decrease of the persistence of earnings, and the effect of negative cash flows on forecasting future cash flows. In this study, two pooling type models and a panel type model have been used to estimate the persistence of earnings and cash flows. Seventy eight firms that were listed in the Tehran Stock Exchange during the period 2003–2010 were duly reviewed. The results of this research proved that the timely recognition of loss does not affect the persistence and the power of earnings for the purpose of forecasting future cash flows. The findings imply that conservatism does not distort persistence of earnings

Identification of native fish in Hamedan province (Gamaciyab)

This study was carried out from 2001 to 2002 in Gamasyab River of Hamadan province of Iran in order to identification of indigenous species of this water resource. The main objective of this study was to fish identification for scientific purposes, geographical distribution pattern, preparation atlas of the fishes, introduction of commercial species and awareness on ecological situation of their natural habitats. Also providing necessary information for conservation and sustainable use of these valuable stocks and minimizing environmental impacts of unsecured utilization. Sampling were carried out by selecting 15 sampling stations through the river and fishing by electro fisher and cast net. Identification accomplished by valid identification keys in species level. Photography and slides provides and 10 pieces of each species tagged by unique codes for preservation in national museum. 50 morphometric and meristic characteristics studied for scientific identification.. Indigenous fishes belong to 14 species, 10 genus, 3 family and 2 order. Indeed 2 exotic species belong to Cyprinidae and Salmonidae families recognized. From these indigenous species, 11 belong to Cyprinidae family and only one species belong to Sisoridae family

Ecological studies of Bisheh-palan Wetland (Broojerd)

Bisheh-Dalan wetland is located in southern of Broojerd city near the Tireh River with 914 hectares area.This survey was done in 2002-2003.Water temperature variation between 8 at 23/5 °C, the quantity pH between 6.5-7.4, Ec between 362-443 μm/cm, minimum-dissolved oxygen 5/5 mg/l in Bisheh-Dalan area. The phytoplankton comprised 4 families and 15 genus include (Microcystis Gloeotrehia Gloeocapsa, Merismopedia Ceratium, Glenodinium, Gymnodinium, Peridinium Closterium, Stauratrum, Treubaria, Cymbella, Cyclotella, Nitzchia, Navieula), the zooplanktons had 3 families and 10 genus, consist (Stmocephalus, Shnucephalus, Diaphanasoma, Simocephalus, Daphnia, Eueyclops, Attheylla, Cyclops, Trinema, Aeanthoeyclops) and the benthos have been had 10 orders and 15 families with names (Ecdyonuridae, Caenidae, Baetidae, Chiranomidae, Calicidae, Dytiscidae, Limmaeidae, Planorbiidae, Glossosomatidae , Tubificidae, Erpobdellidae, Planariidae, Gammaridae) in Bisheh-Dalan area. The fishes of Bisheh-Dalan wetland composed 2 family with names Cyprinidae and poeciliidae with 7 genus and 8 species. Maximum number of fishes located to Capoeta with 2 Species

Redundancy Effect on Fault Tolerance in Wireless Sensor Networks

There are several usages for wireless sensor networks in military, supervisory, region considering, physiology, etc. Sensor nodes are usually equipped with some non chargeable batteries having limitations in lifetime while they cannot be replaced with other sensors when they fail. Each sensor has a failure probability which is affected from some factors like electrical energy, hardware failures, communication error, undesired environment situations, etc. Thus, fault tolerant is a very important and critical factor in such networks. Hardware redundancies like having redundant nodes and paths are suitable echniques used for increasing fault tolerant factor. On the other hand, using hardware redundancies leads increasing in overall network consumption because of using more number of sensors. In this paper we estimate the affect of redundancy on the number of correct responses that wireless sensor networks have on the received queries and also show the level of redundancy needed in different network conditions like having different fault probabilities and needed clusters to response the received queries. Keywords: wireless sensor network, fault tolerance, redundancy, reliabilit

Sampling Rate Prediction of Biosensors in Wireless Body Area Networks using Deep-Learning Methods

In this paper, we propose a scheme which aims at determining and forecasting sampling rate of active biosensors in Wireless Body Area Networks (WBANs). In this regard, from the first round until a certain round, the sampling rate of biosensors would be determined. Accordingly, we introduce our modified Fisher test, develop Spline interpolation method, introduce three main parameters namely information of patient's activity, patient's risk and pivot biosensor's value. Then, by employing these parameters plus introduced statistical and mathematical based strategies, the sampling rate of the active biosensors in the next round would be determined at the end of each entire round. After reaching a pre-denoted round the sampling rate of biosensors would be predicted through forecasting methods. In this regard, we develop two machine learning based techniques namely Adaptive Neuro Fuzzy Inference System (ANFIS) and Long Short Term Memory (LSTM) and compare them with four famous similar techniques. In addition to using forecasted sampling frequencies of the biosensors for controlling their energy expenditure, these forecasted values would also be used to forecast patient's status in the future. This is the first work in this domain that uses current information of the patient to determine adaptive sampling frequency and then employs the time series of determined sampling frequencies to forecast the patient's status and biosensors energy expenditure in the future. For estimating our schemes, we simulated them in MATLAB R2018b software and compared the results with a number of similar schemes. Based on the simulation results, the proposed schemes are capable to reduce data traffic by 81, decrease energy consumption of the network by 73 while having the capability of predicting sampling rate of biosensors with 97 accuracy. © 2020 Elsevier B.V

An Energy Efficient Coverage Method for Clustered Wireless Sensor Networks

An important issue in WSN is the regional covering A coverage algorithm should be able to solve this issue by considering the power consumption to improve the network lifetime This requires employing the lowest number of sensors A solution is just to turn on a subset of nodes This subset should be chosen in such a way to cover the entire region This can be achieved by partitioning the network nodes and considering a representative for each part in a time slice to perform the responsibilities of all the partition members for full coverage This will lead to turn on some of the nodes in a time slice rather than all of them This paper presents a novel algorithm that employs grouping and time scheduling sensor nodes to turn some of them on to cover the entire area In this algorithm the sensing range of the nodes depends on their energy The cluster head denotes the sensing range and also turn on time slice of each node by considering node s remained energy and positio

Experimental analysis of the unit cell approach for two-phase flow dynamics in curved flow channels

Flow behavior of gas\u8211liquid mixtures in thin channels has become increasingly important as a result of miniaturization of fluid and thermal systems. The present empirical study investigates the use of the unit cell or periodic boundary approach commonly used in twophase flows. This work examines the flow patterns formed in small tube diameter (<3 mm) and curved geometry flow systems for air\u8211water mixtures at standard conditions. Liquid and gas superficial velocities were varied from 0.1 to 7.0 (approx. \ub10.01) m/s and 0.03 to 14 (approx. \ub10.2) m/s for air and water respectively to determine the flow pattern formed in three geometries and dispersed bubble, plug, slug and annular flow patterns are reported using high-frame rate videography. Flow patterns formed were plotted on the generalized two-phase flow pattern map to interpret the effect of channel size and curvature on the flow regime boundaries. Relative to a straight a channel, it is shown that a \u8216C shaped\u8217 channel that causes a directional change in the flow induces chaotic advection and increases phase interaction to enhance gas bubble or liquid slug break-up thus altering the boundaries between the dispersed bubble and plug/slug flow regimes as well as between the annular and plug/slug flow regimes.NRC publication: Ye