Negation in Modern Standard Arabic: An LFG approach

Modern Standard Arabic (MSA) uses five different particles to express sentential negation: the invariant particle maa, the particle laa and its tensed counterparts lam (PAST) and lan (FUT), and laysa which is marked only for SUBJ agreement. Partial analyses of these elements are offered in other frameworks, notably Minimalism (Shlonsky, 1997; Benmamoun, 2000), but have not to date received an analysis within LFG. We propose an approach to four of these particles: the fifth one, namely maa, raises a number of additional issues and we leave it to one side for reasons of space. laa, lam, lan show distinctions of TENSE, occur only with imperfective forms of the verb (excluding the perfective) and must immediately precede the verb itself. They are limited to occurrence in verbal sentences. We propose that the adjacency requirement follows from the fact that these negative particles are non-projecting words adjoined to the (imperfective) V. On the other hand, laysa is a fully verbal element, and is thus a negative verb, occurring only with present tense interpretation

A novel approach for predicting the spatial patterns of urban expansion by combining the chi-squared automatic integration detection decision tree, Markov chain and cellular automata models in GIS

Urban development is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. To understand urban expansion, it is important to establish models that can simulate urbanization process and its deriving factors behaviours, monitor deriving forces interactions and predict spatio-temporally probable future urban growth patterns explicitly. In this research, therefore, we presented a hybrid model that integrates the chi-squared automatic integration detection decision tree (CHAID-DT), Markov chain (MC) and cellular automata (CA) models to analyse, simulate and predict future urban expansions in Tripoli, Libya in 2020 and 2025. First, CHAID-DT model was applied to investigate the contributions of urban factors to the expansion process, to explore their interactions and to provide future urban probability map; second, MC model was employed to estimate the future demand of urban land; third, CA model was used to allocate estimated urban land quantity on the probability map to present future projected land use map. Three satellite images of the study area were obtained from the periods of 1984, 2002 and 2010 to extract land use maps and urban expansion data. We validated the model with two methods, namely, receiver operating characteristic and the kappa statistic index of agreement. Results confirmed that the proposed hybrid model could be employed in urban expansion modelling. The applied hybrid model overcame the individual shortcomings of each model and explicitly described urban expansion dynamics, as well as the spatio-temporal patterns involved

Spatio-temporal prediction of urban expansion using bivariate statistical models: assessment of the efficacy of evidential belief functions and frequency ratio models

The urban development process is a continuous and dynamic spatio-temporal phenomenon associated with economic developments and growing populations. Understanding urban expansion processes require models capable of simulating, monitoring, and predicting both urban growth and urban sprawl. In this research, probability-based Evidential Belief Functions (EBF) and Frequency Ratio (FR) models were employed to simulate and to predict the urban expansion probability map of the metropolitan area in Tripoli, Libya. These methods have not been used before in the urban development simulations of cities. By using the geographic information system (GIS), three satellite imageries obtained from 1996, 2002, and 2010 were employed to extract seven urban-deriving factors for the study area. The urban factors are slope, distance to active economic center, distance to central business district (CBD), distance to roads, distance to built-up areas, distance to educational area, and distance to coastal areas. For model calibration, both the EBF and FR models were applied to simulate urban expansion from 1996 to 2002. Data from 2002 to 2010 were used for models validation. Consequently, future suitability maps of urban growth were produced. The validation results indicated 83 % prediction accuracy for the EBF model and 84 % for the FR model. The outcomes established that the models could be employed in the urban expansion modeling of metropolises. The applied models, however, have dynamic and temporal limitations that should be considered in urban growth analysis

Spatio-temporal Analysis of Urban and Population Growths in Tripoli using Remotely Sensed Data and GIS.

The remote sensing data and GIS have been used widely to analyse and study the patterns of urban expansions. The capital of Libya, Tripoli was selected to perform this study and to examine its urban growth. Four satellite imageries and population censuses of the study area for the time period 1984 to 2010 were used in this work. The objectives of this paper are identifying and analysing the urban sprawl of Tripoli as a pattern and as process. Also to understand and assess the interchangeable relationship of urban growth and population growth of study area. Urban area extents in different time periods were extracted by supervised classification method of the satellite imageries. Then, the population data and urban extents data were coupled to perform the analysis. Additionally, Shannon's entropy technique was used for further assessment of urban growth. The study findings demonstrate that Tripoli had sprawled urban growth during the period 1984 to 2010. Moreover, during the above mentioned period, the urban expansion dispersion rate has shown in an ascending mode. Consequently, this uncontrolled dispersed urban development had resulted in high consumption land rate per capita despite of decrement in population growth rate

Role of semicore states in the electronic structure of group-III nitrides: An exact exchange study

The bandstructure of the zinc-blende phase of AlN, GaN, InN is calculated employing the exact-exchange (EXX) Kohn-Sham density-functional theory and a pseudopotential plane-wave approach. The cation semicore d electrons are treated both as valence and as core states. The EXX bandgaps of AlN and GaN (obtained with the Ga 3d electrons included as core states) are in excellent agreement with previous EXX results, GW calculations and experiment. Inclusion of the semicore d electrons as valence states leads to a large reduction in the EXX bandgaps of GaN and InN. Contrary to common belief, the removal of the self-interaction, by the EXX approach, does not account for the large disagreement for the position of the semicore d electrons between the LDA results and experiment.Comment: 10 pages including 3 figures; related publications can be found at http://www.fhi-berlin.mpg.de/th/th.htm

Exact-exchange density-functional calculations for noble-gas solids

The electronic structure of noble-gas solids is calculated within density functional theory's exact-exchange method (EXX) and compared with the results from the local-density approximation (LDA). It is shown that the EXX method does not reproduce the fundamental energy gaps as well as has been reported for semiconductors. However, the EXX-Kohn-Sham energy gaps for these materials reproduce about 80 % of the experimental optical gaps. The structural properties of noble-gas solids are described by the EXX method as poorly as by the LDA one. This is due to missing Van der Waals interactions in both, LDA and EXX functionals.Comment: 4 Fig

Real options modeling and valuation of price adjustment flexibility with an application to the leasing industry

Uncertainty poses not only threats but also opportunities. This study sought to build the scientific foundation for introducing a real options (ROs) methodology for price risk management to the leasing industry. A price risk management that allows for both coping with threats and taking advantage of opportunities. In the leasing industry, fixed rate long-term lease contracts help contract parties stabilize cash flows within volatile markets. The contract\u27s term, however, may be extended long enough that prevent capturing the opportunities of gaining greater profits or reducing expenses. Therefore, the flexibility that enables participants to take advantage of favorable market price is desirable. This discussion is dedicated to the study of three different forms of price adjustments flexibility: 1) single-sided price adjustment flexibility (SSPAF). 2) double-sided price adjustment flexibility (DSPAF) with the preemptive right to exercise. 3) DSPAF with the non-preemptive right to exercise. Each was designed to meet various participants flexibility requirements and budgets. An ROs methodology was developed to model, price, and optimize these flexibility clauses. The proposed approach was then tested in the example of Time Charter (TC) rate contracts from the maritime transport industry. Both the metric and the process for quantifying the benefit of the proposed flexibility clauses are provided. This work provides an alternative approach to the price risk management, which is accessible to all participants in the leasing industry. It is also the starting point in studying the multiple-party, multiple-exercisable price adjustment flexibility. Moreover, both the flexibility designs and the proposed ROs methodology for price risk management are applicable to not only other forms of lease contracts but also to other forms of contract relationships. --Abstract, page iii

Location prediction based on a sector snapshot for location-based services

In location-based services (LBSs), the service is provided based on the users' locations through location determination and mobility realization. Most of the current location prediction research is focused on generalized location models, where the geographic extent is divided into regular-shaped cells. These models are not suitable for certain LBSs where the objectives are to compute and present on-road services. Such techniques are the new Markov-based mobility prediction (NMMP) and prediction location model (PLM) that deal with inner cell structure and different levels of prediction, respectively. The NMMP and PLM techniques suffer from complex computation, accuracy rate regression, and insufficient accuracy. In this paper, a novel cell splitting algorithm is proposed. Also, a new prediction technique is introduced. The cell splitting is universal so it can be applied to all types of cells. Meanwhile, this algorithm is implemented to the Micro cell in parallel with the new prediction technique. The prediction technique, compared with two classic prediction techniques and the experimental results, show the effectiveness and robustness of the new splitting algorithm and prediction technique