5,268 research outputs found
The Separate Valuation Relevance of Earnings, Book Value and their Components in Profit and Loss Making Firms: UK Evidence
This study examines the separate value relevance of earnings, book value and their components in profit and loss-making firms. The investigation take place in a context that both profit and loss-making firms have different features that might affect conclusions concerning the value relevance of earnings and book value partitions. Thus, we are establishing relationships between disaggregated accounting data and the market value of firms in the profit and loss-making firms in cross-sectional valuation models. These results suggest that for loss-making firms, earnings and book value partitions are not generally valuation relevant. However, for profit-making firms, the earnings partition into working capital from operations and non-current accruals is valuation relevant in almost all cross-sections. Book value partitions have also some valuation relevance for profit-making firms, in the presence of earnings partitions.earnings, book value, loss making firms, value relevance
THE EFFECT OF USING MATHEMATICAL SOFTWARE IN UNDERSTANDING MATERIAL IN STATISTICS COURSES
This research was conducted at the Sembilanbelas November Kolaka University. This study aims to show the effect of the use of software in learning on the understanding of statistical material. The material discussed is the data normality test. To achieve that goal the researcher measures the understanding of student material before and after use of the software. Next, data analysis is done by comparing the results of the pre-test and post-test that have been obtained. The final result of the study shows that use mathematical software has a very significant effect of statistical material understanding, especially in data normality testing
AM-DisCNT: Angular Multi-hop DIStance based Circular Network Transmission Protocol for WSNs
The nodes in wireless sensor networks (WSNs) contain limited energy
resources, which are needed to transmit data to base station (BS). Routing
protocols are designed to reduce the energy consumption. Clustering algorithms
are best in this aspect. Such clustering algorithms increase the stability and
lifetime of the network. However, every routing protocol is not suitable for
heterogeneous environments. AM-DisCNT is proposed and evaluated as a new energy
efficient protocol for wireless sensor networks. AM-DisCNT uses circular
deployment for even consumption of energy in entire wireless sensor network.
Cluster-head selection is on the basis of energy. Highest energy node becomes
CH for that round. Energy is again compared in the next round to check the
highest energy node of that round. The simulation results show that AM-DisCNT
performs better than the existing heterogeneous protocols on the basis of
network lifetime, throughput and stability of the system.Comment: IEEE 8th International Conference on Broadband and Wireless
Computing, Communication and Applications (BWCCA'13), Compiegne, Franc
Automatic Speech Recognition for Indonesian using Linear Predictive Coding (LPC) and Hidden Markov Model (HMM)
Speech recognition is influential signal processing in communication technology. Speech recognition has allowed software to recognize the spoken word. Automatic speech recognition could be a solution to recognize the spoken word. This application was developed using Linear Predictive Coding (LPC) for feature extraction of speech signal and Hidden Markov Model (HMM) for generating the model of each the spoken word. The data of speech used for training and testing was produced by 10 speaker (5 men and 5 women) whose each speakers spoke 10 words and each of words spoken for 10 times. This research is tested using 10-fold cross validation for each pair LPC order and HMM states. System performance is measured based on the average accuracy testing from men and women speakers. According to the test results that the amount of HMM states affect the accuracy of system and the best accuracy is 94, 20% using LPC order =13 and HMM state=16
Thermodynamic Interpretation of Field Equations at Horizon of BTZ Black Hole
A spacetime horizon comprising with a black hole singularity acts like a
boundary of a thermal system associated with the notions of temperature and
entropy. In case of static metric of BTZ black hole, the field equations near
horizon boundary can be expressed as a thermal identity ,
where is the mass of BTZ black hole, is the change in the area of
the black hole horizon when the horizon is displaced infinitesimally small,
is the radial pressure provided by the source of Einstein equations,
is the entropy and is the Hawking temperature
associated with the horizon. This approach is studied further to generalize it
for non-static BTZ black hole and show that it is also possible to interpret
the field equation near horizon as a thermodynamic identity , where is the angular velocity and is the
angular momentum of BTZ black hole. These results indicate that the field
equations for BTZ black hole possess intrinsic thermodynamic properties near
horizon.Comment: 8 page
Model Triprakoro Dalam Pembelajaran Nilai Dan Karakter Kepatuhan Untuk Sekolah Dasar
: Triprakoro Model for Character Education of Obedience at Elementary Schools. This study aims at developing a theoretically as well as empirically effective model of character education at elementary schools, focusing on obedience character. This multi-year research and development study encomÂpasses the stages of problem identification, model development, expert validation, small-scale try-out involving two elementary schools, and large-scale try-out involving six elementary schools. The results show that the Tripakoro Model has a very high level of validity, feasibility, and effectiveness to be implemented in elemenÂtary schools to develop the targeted competences in the character education
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