Indoor geolocation in the absence of direct path

Severe multipath in indoor areas causes undetected direct path (UDP) conditions, which pose a serious challenge to the design of robust precision indoor geolocation systems. Based on a scenario on the third floor of the Atwater Kent Laboratory at the Worcester Polytechnic Institute, we explain the reason for frequent absence of direct path, and introduce and analyze the effectiveness of two novel approaches to mitigating the large ranging errors caused by UDP conditions. The first technique exploits nondirect paths for ranging, while the second approach relies on cooperative localization for wireless sensor and ad hoc networks     

Software‐defined networking to improve handover in mobile edge networks

Mobility management and handover for a seamless connection are among all‐time challenges of wireless networks. Software‐defined networking (SDN) has opened new horizons toward research by adding intelligence in edge networks while decoupling the control and data planes. The flexibility and centralized nature of SDN further improve the handover decision algorithms. In this paper, we have improved the network performance with respect to the number of handovers and the handover delay by applying an LTE‐SDN architecture and a novel handover decision algorithm based on predicting the future locations of a moving vehicle. The proposed algorithm decouples the handover procedure into two phases of preparation and execution. In the preparation phase, which occurs in the control plane, the handover decision and resource allocation take place, and in the execution phase, handover gets executed similar to the LTE architecture. The results of our research indicate that our proposed LTE‐SDN performance is improved with respect to the number of handovers, handover delay, and signaling overhead by 24%, 16%, and 20%, respectively. On the other hand, average Reference Signal Received Quality (RSRQ) value is decreased by 4% as a tradeoff for the improvements gained.     

Optimum design of three-dimensional steel frames with prismatic and non-prismatic elements

Engineering with Computers - In the present article, optimal seismic design of three-dimensional steel frames is carried out. The frames are subjected to gravity and earthquake loadings and are...     

Understanding of RF Cloud Interference Measurement and Modeling

International Journal of Wireless Information Networks - Importance of spectrum regulation and management was first revealed on May of 1985 after the release of unlicensed ISM bands resulting in...     

Effect of management strategies on reducing negative impacts of climate change on water resources of the Isfahan–Borkhar aquifer using MODFLOW

Recently, many studies have investigated the effect of climate change on groundwater resources in semiarid and arid areas and have shown adverse effects on groundwater recharge and water level. However, only a few studies have shown suitable strategies for reducing these adverse effects. In this study, climate conditions were predicted for the future period of 2020–2044, under the emission scenarios of RCP2.6, RCP4.5, and RCP8.5, for Isfahan–Borkhar aquifer, Isfahan, Iran, using MODFLOW‐2000 (MODFLOW is United States Geological Survey product). Results showed that the average groundwater level of the aquifer would decrease to 13, 15, and 16 m in 2012 to 2044 approximately under RCP2.6, RCP4.5, and RCP8.5 scenarios, respectively. Then, three groundwater sustainability management scenarios were defined that included 10%, 30%, and 50% reduction in groundwater extraction. These strategies simulated the reduced negative effects of climate change on the aquifer. The results showed that decreases in water withdrawal rates of 10%, 30%, and 50% under RCP8.5 scenario (critical scenario) could decrease the mean groundwater level by 14, 11, and 7 m, respectively. The main result of the study showed that 50% reduction in groundwater withdrawal may increase the groundwater levels significantly in order to restore the aquifer sustainability in the study area. In this study, with assuming that the current harvest of wells in the future period is constant, so the results of studies showed that for the aquifer's sustainability management, the water abstraction from the aquifer should reduce up to 50% of the existing wells. Changing the irrigation method from surface to subdroplet irrigation plays an important role in reducing the withdrawal from the aquifer. The results of a study in Iran have shown that the change in the irrigation method from surface to subdroplet irrigation causes a 40% reduction in water use for agriculture.     

Precision of RSS-Based Localization in the IoT

International Journal of Wireless Information Networks - Currently, the most popular indoor geolocation technique used in smart device is the RSS-based Wi-Fi localization. The general accuracy of...     

Low-cost optical approach for noncontact predicting moisture content of apple slices during hot air drying

Absorption and scattering properties of product change as moisture content is reduced, but it has not been investigated how these changes are correlated. This study was aimed to measure and test the feasibility of using optical properties in predicting the moisture content of sliced apple samples during hot air drying. In this investigation, the noninvasive backscattering laser imaging technique at three wavelengths (650, 780, and 880?nm) and Farrell’s diffusion theory were used to determine absorption and reduced scattering coefficients. Artificial neural network model was applied to correlate the optical coefficients and moisture content of samples. The highest correlation between above-mentioned parameters was found at 780?nm. The best moisture content prediction result was obtained when absorption and reduced scattering coefficients were combined at three wavelengths with R_p?=?0.984. The results suggested that this method can be effectively used to predict the moisture content and control the drying process.     

Long short-term memory for predicting daily suspended sediment concentration

Frequent and accurate estimation of suspended sediment concentration (SSC) in surface waters and hydraulic schemes is of prime importance for proper design, operation and management of many hydraulic projects. in the present study, a long short-term memory (LSTM) was considered for predicting daily suspended sediment concentration in a river. The LSTM extends recurrent neural network with memory cells, instead of recurrent units, to store and output information, easing the learning of temporal relationships on long time scales. To build the model, daily observed time series of river discharge (Q) and SSC in the Schuylkill River in the United States were used. The results of the proposed model were evaluated and compared with the feedforward neural network and the adaptive neuro fuzzy inference system models which were trained using three different learning algorithms and widely used in the literature for prediction of daily SSC. The comparison of prediction accuracy of the models demonstrated that the LSTM model could satisfactory predict SSC time series, and adequately estimate cumulative suspended sediment load (SSL).

     

The formation and properties of single nuclei

The formation and growth of single metallic nuclei of silver, mercury and copper have been studied at microscopically small electrodes of platinum and carbon. Once formed, metallic nuclei act as point sinks, growing under hemispherical mass-transfer control. The rate of growth at low overpotential is a function of the mean surface concentration as determined by the Nernst relation.The rate of formation of isolated nuclei has been determined as the inverse of the delay time attending their birth as indicated by the onset of the growth current. A distribution of delay times is observed in keeping with the statistical nature of the nucleation process.The nuclei or crystallites formed are spherical droplets in the case of mercury or microscopic single crystals in the case of solid metals, their size being accessible from the current—time integral of their growth. They are stable on open circuit and exhibit the residual overpotential of their excess surface free energy, ie their Gibbs—Kelvin potential. This potential is a linear function of their inverse equivalent spherical radius. The surface tensions calculated from the simplest application of the Gibbs—Kelvin equations appear to be higher than the known or estimated bulk values.The microscopic metallic crystallites have been used as reactive electrodes. The high mass-transfer flux to their surface enabled the exchange current to be determined by a simple, steady state small amplitude dc procedure.These studies confirm the considerable promise of microscopically small electrodes in electrochemistry.     

A hybrid fuzzy multiple criteria group decision making approach for sustainable project selection

In this paper, a new hybrid fuzzy multiple criteria group decision making (FMCGDM) approach has been proposed for sustainable project selection. First, a comprehensive framework, including economic, social, and environmental effects of an investment, strategic alliance, organizational readiness, and risk of investment has been proposed for sustainable project selection. As the relative importance of the criteria of the proposed framework are hard to find through several conflictive preferences of a group of Decision Makers (DMs) so, a goal programming (GP) has been supplied to this aim considering multiplicative and fuzzy preference relation. Then, a fuzzy TOPSIS method has been developed to assess the fitness of investment chances. It is based on Preference Ratio (PR), which is known as an efficient ranking method for fuzzy numbers, and a fuzzy distance measurement. The properties of proposed hybrid approach make it robust for modeling real case of uncertain group decision making problems. The FMCGDM has been developed through a linkage between Lingo 11.0, MS-Excel 12.0, and Visual Basic 6.0. The proposed hybrid approach has been applied in a real case study called Iranian financial and credit institute for sustainable project selection.