Effects of Luminous Environment on Worker Productivity in Building Spaces

This paper is based in part, on the results of a survey undertaken by the writer for an industrial client. The purpose was to collect and systematize information on quantitative relations between the indoor environment and worker productivity. Office workers strongly believe that lighting conditions are an extremely important aspect of their workspace environment. Unfavorable conditions may hamper productivity. Daylighting is of particular importance. It is further shown that lighting conditions have a strong impact on worker performance in industrial facilities. Certain lighting strategies can contribute to an enhancement in worker productivity while cutting down on energy consumption. The influence on worker productivity of different characteristics of illumination are described. These include spectral distribution, color rendition, glare, daylight versus artificial light, and others. The presence or absence of windows on worker comfort and perception is also discussed. It is shown that improving lighting conditions is a highly cost-effective method of increasing worker productivity in office spaces as well as in manufacturing facilities.     

AN EMPIRICAL STUDY ON ANALYZING THE PRODUCTIVITY OF BANK BRANCHES

Productivity analysis and its strategic implications are not only important for manufacturing sector but equally essential for other sectors as well. Branch banking sector is no exception in this sense and banks have to operate more efficiently and effectively in an increasingly competitive environment to sustain or improve their relative positions. This paper discusses the methodology of an empirical study that was employed in analyzing the operating productivities of a set of 44 bank branches of a major commercial bank offering relatively homogeneous products in a multi-market business environment. The methodology was based on the concepts and principles of Data Envelopment Analysis (DEA). The results of the study have indicated that this kind of productivity analysis is not only complementary to traditionally used financial ratios but also is a useful bank management tool in reallocating resources between the branches in order to achieve higher efficiencies.     

Biological treatment of industrial wastes in a photobioreactor.

An algal-bacterial consortium was tested for the treatment from a coke factory. A Chlorella vulgaris strain and a phenol-degrading Alcaligenes sp. were first isolated from the wastewater treatment plant to serve as inocula in the subsequent biodegradation tests. Batch tests were then conducted with samples from the real wastewater or using a synthetic wastewater containing 325 mg phenol/l and 500 mg NH4+/l as target pollutants. Direct biological treatment of the real wastewater was not possible due to the toxicity of organic compounds. Activated carbon adsorption and UV(A-B)-irradiation were efficient in detoxifying the effluent for subsequent biological treatment as inoculation of pretreated samples with the algal-bacterial consortium was followed by complete phenol removal and NH4+ removal of 45%. Complete phenol removal and 33% NH4+ removal were achieved during the fed-batch treatment of artificial wastewater at 6 d hydraulic retention time (HRT). Under continuous feeding at 3.6 d HRT, phenol and NH4+ removal dropped to 58 and 18%, respectively. However, complete phenol removal and 29% NH4+ removal were achieved when 8 g NaHCO3/l was added to the artificial wastewater to enhance algal growth. This study confirms the potential of solar-based industrial wastewater treatment based on solar-based UV pretreatment followed by algal-bacterial biodegradation.     

REFORMULATING QUADRATIC ASSIGNMENT PROBLEMS FOR EFFICIENT OPTIMIZATION

Decision making problems in areas such as R&D project selection, facility layout design, capital budgeting, resource allocation, communication network design, and scheduling are more than often formulated as assignment problems with quadratic objective functions in 0-1 variables. Although quadratic assignment problems are formulated as mathematical optimization problems, the solution algorithms that have been suggested in the literature are usually heuristic. The scarcity of exact solution techniques is attributed to the presence of large numbers of 0-1 variables as well as to the optimization of a nonlinear objective function expressed in 0-1 variables. This paper suggests a reformulation method that linearizes the quadratic objective functions in assignment problems and reduces the number of 0-1 variables one has to deal with in the optimization process. The new reformulation leads to use of commercially available codes to solve the resulting mixed-integer linear programming problem. Computational experience with this new reformulation is also discussed.     

Adsorption of uranium from sulfate leach liquor using rice straw impregnated with chlorophenyl hydrazinyl pyrazoloquinazolinon

The impregnation of rice straw with 2-amino-3-(2-(4-chlorophenyl)hydrazinyl)-8,8-dimethyl-8,9-dihydropyrazolo[1,5-a]quinazolin-6(7H)-one (CPHPQ) has been used for the recovery of uranium from sulfate leach liquor. The uranium adsorption and elution of solvent impregnated mercerized rice straw (SIMRS) were carried out using a batch technique. The uranium adsorption controlling factors include pH, initial uranium concentration, contact time, S/L ratio, and temperature. Thermodynamic characteristics showed that the adsorption process is exothermic with enthalpy change ΔH = ?152.1 kJ/mol. The kinetics data fit well with a pseudo-second-order model. The equilibrium data fit well with the Langmuir isotherm. Uranium cake was obtained from the eluate solution using hydrogen peroxide as UO₄.2H₂O precipitate.     

An evolutionary bargaining‐based approach for incentivized cooperation in opportunistic networks

Opportunistic networking enables users to communicate in an environment where connectivity is intermittent or unstable. However, such networking scheme assumes that mobile nodes voluntary cooperate, which cannot be guaranteed. Some nodes can simply exhibit selfish behavior and thus diminish the effectiveness of the approach. In this paper, a game scenario is formulated in which the nodes try to convince each other to participate in packets forwarding. Each node is considered as a player in this game. When a node comes in the communication range of another, a bargaining game starts between them as part of the message forwarding process. Both players try to have a mutual agreement on a price for message forwarding. We present a new incentive mechanism called evolutionary bargaining‐based incentive scheme (EBIS) to motivate selfish nodes to cooperate in data forwarding. In EBIS, a node negotiates with other nodes to obtain an agreeable amount of credit for its forwarding service. Nodes apply a sequential bargaining game and then adapt their strategies using an evolutionary model to maximize the probability of reaching an agreement. Unlike classical bargaining games, nodes in our model are boundedly rational. In addition, we use the evolutionary stable strategy (ESS) concept to determine the adaptive strategies for the nodes. The comparison of EBIS with a benchmarked model demonstrates that EBIS performs better in terms of packet delivery ratio and average latency.     

SYNC‐NET: distributed time synchronization in clustered sensor networks

Time synchronization is essential for several ad‐hoc network protocols and applications, such as TDMA scheduling and data aggregation. In this paper, we propose a time synchronization framework for clustered, multi‐hop sensor networks. We assume that relative node synchronization is sufficient, that is, consensus on one time value is not required. Our goal is to divide the network into connected synchronization regions (nodes within two‐hops) and perform inter‐regional synchronization in O(LLSync) × N_iter time, where O(LLSync) denotes the complexity of the underlying low‐level synchronization technique (used for single‐hop synchronization), and N_iter denotes the number of iterations where the low‐level synchronization protocol is invoked. Thus, our main objective is rapid convergence. We propose novel fully distributed protocols, SYNC‐IN and SYNC‐NET, for regional and network synchronization, respectively, and prove that N_iter is O(1) for all protocols. Our framework does not require any special node capabilities (e.g., being global positioning systems (GPS)‐enabled), or the presence of reference nodes in the network. Our framework is also independent of the particular clustering, inter‐cluster routing, and low‐level synchronization protocols. We formulate a density model for analyzing inter‐regional synchronization, and evaluate our protocols via extensive simulations. Copyright © 2007 John Wiley & Sons, Ltd.     

An energy-aware distributed clustering protocol in wireless sensor networks using fuzzy logic

Clustering is an effective approach for organizing a network into a connected hierarchy, load balancing, and prolonging the network lifetime. On the other hand, fuzzy logic is capable of wisely blending different parameters. This paper proposes an energy-aware distributed dynamic clustering protocol (ECPF) which applies three techniques: (1) non-probabilistic cluster head (CH) elections, (2) fuzzy logic, and (3) on demand clustering. The remaining energy of the nodes is the primary parameter for electing tentative CHs via a non-probabilistic fashion. A non-probabilistic CH election is implemented by introducing a delay inversely proportional to the residual energy of each node. Therefore, tentative CHs are selected based on their remaining energy. In addition, fuzzy logic is employed to evaluate the fitness (cost) of a node in order to choose a final CH from the set of neighboring tentative CHs. On the other hand, every regular (non CH) node elects to connect to the CH with the least fuzzy cost in its neighborhood. Besides, in ECPF, CH elections are performed sporadically (in contrast to performing it every round). Simulation results demonstrate that our approach performs better than well known protocols (LEACH, HEED, and CHEF) in terms of extending network lifetime and saving energy.     

MAC Protocol for Opportunistic Cognitive Radio Networks with Soft Guarantees

Cognitive radio (CR) is the key enabling technology for an efficient dynamic spectrum access. It aims at exploiting an underutilized licensed spectrum by enabling opportunistic communications for unlicensed users. In this work, we first develop a distributed cognitive radio MAC (COMAC) protocol that enables unlicensed users to dynamically utilize the spectrum while limiting the interference on primary (PR) users. The main novelty in COMAC lies in not assuming a predefined CR-to-PR power mask and not requiring active coordination with PR users. COMAC provides a statistical performance guarantee for PR users by limiting the fraction of the time during which the PR users' reception is negatively affected by CR transmissions. To provide such a guarantee, we develop probabilistic models for the PR-to-PR and the PR-to-CR interference under a Rayleigh fading channel model. From these models, we derive closed-form expressions for the mean and variance of interference. Empirical results show that the distribution of the interference is approximately lognormal. Based on the developed interference models, we derive a closed-form expression for the maximum allowable power for a CR transmission. We extend the min-hop routing to exploit the available channel information for improving the perceived throughput. Our simulation results indicate that COMAC satisfies its target soft guarantees under different traffic loads and arbitrary user deployment scenarios. Results also show that exploiting the available channel information for the routing decisions can improve the end-to-end throughput of the CR network (CRN).