Supply chain financing with advance selling under disruption

We study a financing problem in a supply chain (SC) consisting of one supplier and one buyer under supply disruption. The supplier could face a disruption at its end which could effectively reduce its yield in case of disruption, thereby resulting in supply yield uncertainty. The retailer can finance the supplier using advance selling that can help mitigate the impact of disruption. We model this problem as a Stackelberg game, where the supplier as the leader announces the wholesale price and the retailer responds by deciding its optimal order quantity given stochastic demand and an exogenous fixed retail price. The supplier then commences production and a disruption can happen with a known probability. We assume that under disruption the quantity delivered is a fraction of the initial quantity ordered by the retailer. The retailer loses any unmet demand. We analyze three different scenarios of the Stackelberg game, namely no advance selling with disruption, advance selling without disruption, and advance selling with disruption. Our results indicate that advance selling can be used to mitigate the impact of supply disruption and at the same time could lead to an increase in the overall SC profit.     

A Context Sensitive Multilevel Thresholding Using Swarm Based Algorithms

In this paper, a comprehensive energy function is used to formulate the three most popular objective functions: Kapur's, Otsu and Tsalli's functions for performing effective multilevel color image thresholding. These new energy based objective criterions are further combined with the proficient search capability of swarm based algorithms to improve the efficiency and robustness. The proposed multilevel thresholding approach accurately determines the optimal threshold values by using generated energy curve, and acutely distinguishes different objects within the multi-channel complex images. The performance evaluation indices and experiments on different test images illustrate that Kapur's entropy aided with differential evolution and bacterial foraging optimization algorithm generates the most accurate and visually pleasing segmented images.      

Novel Canonic Current Mode DDCC Based SRCO Synthesized Using a Genetic Algorithm

A survey of the technical literature reveals that synthesis of Current Mode (CM) oscillators using single active building block (ABB) requires an additional identical or complementary current terminal to sense and take out the current output. The topologies of these oscillators are essentially based on the current mode approach. They use a Voltage Controlled Voltage Source (VCVS) and two current terminals to implement the CM oscillator. In the present paper, a novel DDCC (Differential Difference Current Conveyor, introduced in Chiu et al. (IEE Proc., Circuits, Devices, Syst., vol. 143, no. 2, pp. 91–96, 1996)) based canonic CM Single-Resistor Controlled Oscillator (SRCO) is presented, which uses a VCVS and a single current terminal to take out the output. Earlier, authors used DDCCC (Differential Difference Complementary Current conveyor), DVCCC (Differential Voltage Complementary Current Conveyor) to implement CM oscillators and hypothesized the requirement of an additional current terminal for the output. The synthesis of present topology indicates that DDCC is a versatile building block to implement canonic CM SRCOs and doesn't need any additional current terminal. This topology was synthesized using an innovative genetic algorithm. Spice simulations have been included and they verify theoretical results.     

Synthesis and characterization of sulfonated liquid crystalline polyesters

Liquid crystalline polyesters based on hexanediol, dimethyl 4,4′‐biphenyldicarboxylate, and various levels of dimethyl 5‐sodiosulfoisophthalate (0–20 mol%) were prepared using a conventional melt polymerization process. The presence and quantification of the ionic functionality was surveyed using ¹H NMR spectroscopy. Solution viscosities and corresponding molecular weights decreased when the ionic monomer concentration exceeded a critical value (higher than 3 mol%). Differential scanning calorimetry indicated a maximum in the isotropic transition temperature versus ionic modification at approximately 10 mol%. Dynamic mechanical analysis indicated that the glass transition temperature was suppressed due to ionic association at high concentrations (greater than 3 mol%) of ionic functionality. Polarized light microscopy and wide‐angle X‐ray diffraction were used to identify the smectic liquid crystalline and crystalline phases. © 2002 Society of Chemical Industry     

Efficient Beamforming by SLNR Maximization for Dual-Hop Relay Assisted MIMO Network

Relay beamforming is a key signal processing technique to mitigate interference in single and multiuser multiple input and multiple output (MIMO) wireless communication networks. In MIMO relay networks interference cancellation is an essential task of the study to get optimal network capacity. In this paper, the problem of interference resulted from leakage signal from desired signal for intended antenna, which causing interference to other antennas of the same user with multiple antennas is tackled. The criterion of signal to leakage plus noise ratio (SLNR) maximization is considered to design a vector by vector relay downlink precoding based on Fukunaga Koontz transform. This can control the interference among multiple antennas and maximize SLNR. However, matched filter beamforming is utilized at the relay receiving side that can increase output signal to noise ratio at the relay node. The channel state information of both the channel between source to relay and relay to destination is assumed at the relay node. The effectiveness of the proposed technique is studied and compared with conventional relay precoding techniques. Simulation is carried out in MATLAB environment using ideal channel conditions. This study demonstrates that, the proposed scheme for relay assisted MIMO networks can improve overall system performance in terms of ergodic capacity.     

Geographic disparities in arteriovenous fistula placement in patients approaching hemodialysis in the United States

Arteriovenous fistula (AVF) is the preferred vascular access for hemodialysis (HD). Several factors associated with AVF placement have been identified (e.g., age, sex, race, comorbidities). We hypothesized that geographic location of patient residence might be associated with the probability of AVF placement as the initial access. We used the data from the United States Renal Data System (USRDS) database (2005–2008) linked to Medicare claims (2003–2008). Logistic regression was used to estimate specific characteristics of population associated with the AVF as first access placed or attempted for HD initiation. Our primary variable of interest was the geographic location, and the multivariate model was adjusted for age, sex, race, body mass index, primary cause of end‐stage renal disease (ESRD), duration of pre‐ESRD nephrology care, comorbidities, employment status, substance abuse, and income. Geographic location was determined using the data collected by the RUCA project and divided population into metropolitan, micropolitan, and rural categories. Patients (n = 111,953) identified from the USRDS database with linked Medicare claims were examined. Rates of fistula placement in the metropolitan, micropolitan, and rural population were 18.5%, 22.4%, and 21.6%, respectively. In comparison, patients who received catheter as the first access were 81.5%, 77.6% and 78.4%, respectively. The odds ratio of AVF placement as a first HD access in the rural and metropolitan population compared with the micropolitan population were 0.96 (0.90–1.03; P = 0.26) and 0.80 (0.76–0.84; P < 0.001), respectively. Our results indicate the presence of geographic disparities in AVF placement with decreased rates of AVF as the first access created in the metropolitan (but not rural) populations compared with the micropolitan communities.     

A taxonomy of political processes in systems development

Significant resources invested in information system development (ISD) are wasted due to political manoeuvres. Prior research on ISD politics has contributed mainly through theoretical development and case studies. This has enhanced understanding of relevant concepts, political tactics and conditions facilitating politics. However, there is limited understanding of the different processes through which politics unfold. This paper uses 89 ISD projects to develop a taxonomy of political processes in ISD. The taxonomy includes three distinct processes: Tug of War, wherein multiple parties strive to gain project control; Obstacle Race, which involves efforts to resist and pursue the project; and Empire Building, wherein the project is used as an instrument to enhance political or resource bases. The taxonomy is explained using the non‐proponents' view of the project and the balance of power between system's proponents and non‐proponents. We also discuss the emergent taxonomy's implications for how politics can be managed and studied.     

Carbon capture and storage at scale: Lessons from the growth of analogous energy technologies

At present carbon capture and storage (CCS) is very expensive and its performance is highly uncertain at the scale of commercial power plants. Such challenges to deployment, though, are not new to students of technological change. Several successful technologies, including energy technologies, have faced similar challenges as CCS faces now. To draw lessons for the CCS industry from the history of other energy technologies that, as with CCS today, were risky and expensive early in their commercial development, we have analyzed the development of the US nuclear-power industry, the US SO₂-scrubber industry, and the global liquefied natural gas (LNG) industry. Through analyzing the development of the analogous industries we arrive at three principal observations. First, government played a decisive role in the development of all of these analogous technologies. Second, diffusion of these technologies beyond the early demonstration and niche projects hinged on the credibility of incentives for industry to invest in commercial-scale projects. Third, the conventional wisdom that experience with technologies inevitably reduces costs does not necessarily hold. Risky and capital-intensive technologies may be particularly vulnerable to diffusion without accompanying reductions in cost.     

Stochastic techniques used for optimization in solar systems: A review

Nowadays, optimization of solar systems is used to reduce system total cost, increased life cycle savings and improving thermal efficiency. It is very demanding for optimal utilization of solar resources to meet the energy demands. Various optimization techniques either deterministic or stochastic are implemented to achieve this objective. The stochastic techniques generate better results as compared to deterministic in large search space in low computation time. The optimal set of design and operating parameters are means to produce maximum system performance. This study includes review of various stochastic optimization techniques implemented in solar energy systems for performance enhancement. Based on the results given by various investigators, an attempt has been made to compare the stochastic optimization techniques in terms of providing maximum system performance of different solar systems.