10811607
Capacity Management for Contract Manufacturing
Contract manufacturers sell capacity under different terms to different buyers. In a common practice, the supplier offers a market standard price and lead-time combination for products listed in its catalog. At the same time, it strikes contracts with some high-volume customers who require recurring delivery of a custom product at a short notice, usually timed to meet the buyer's production schedule. Whereas the manufacturer is obligated to satisfy demand from these customers, it can dynamically choose which transactional orders to accept. In this paper, we analyze two scenarios. In the first scenario, the manufacturer produces contractual orders on a make-to-order basis, and in the second, it maintains finished goods inventory for such orders. At each decision epoch, the manufacturer decides which transactional orders to accept to maximize its long-run expected profit. When contractual items are made to stock, the manufacturer also chooses how much extra capacity to allocate to contractual items, over and above what is needed to meet realized demand. We establish the structure of the optimal policies and propose scalable heuristics when optimal policies are hard to compute/implement. Our models are then used to study the effect of demand variability on the optimal profit. We also show how the amount of capacity available, relative to demand, changes the desirability of serving either transactional-only or both markets.
5303171
Revenue Management for a Primary-Care Clinic in the Presence of Patient Choice
In addition to having uncertain patient arrivals, primary-care clinics also face uncertainty arising from patient choices. Patients have different perceptions of the acuity of their need, different time-of-day preferences, as well as different degrees of loyalty toward their designated primary-care provider (PCP). Advanced access systems are designed to reduce wait and increase satisfaction by allowing patients to choose either a same-day or a scheduled future appointment. However, the clinic must carefully manage patients' access to physicians' slots to balance the needs of those who book in advance and those who require a same-day appointment. On the one hand, scheduling too many appointments in advance can lead to capacity shortages when same-day requests arrive. On the other hand, scheduling too few appointments increases patients' wait time, patient-PCP mismatch, and the possibility of clinic slots going unused. 
 
The capacity management problem facing the clinic is to decide which appointment requests to accept to maximize revenue. We develop a Markov decision process model for the appointment-booking problem in which the patients' choice behavior is modeled explicitly. When the clinic is served by a single physician, we prove that the optimal policy is a threshold-type policy as long as the choice probabilities satisfy a weak condition. For a multiple-doctor clinic, we partially characterize the structure of the optimal policy. We propose several heuristics and an upper bound. Numerical tests show that the two heuristics based on the partial characterization of the optimal policy are quite accurate. We also study the effect on the clinic's optimal profit of patients' loyalty to their PCPs, total clinic load, and load imbalance among physicians.
17681650
Cross-Layer Optimized Data Gathering in Wireless Multimedia Sensor Networks
Using multimedia sensor nodes can enhance the capability of wireless sensor networks (WSNs) for event description. In some scenarios, e.g., an erupting volcano, the WSNs are not deployed to work for long time. Instead, the WSNs aim to deliver continuous and reliable multimedia data as much as possible within an expected lifetime. In this paper, we focus on the efficient multimedia data gathering in WSNs within an expected lifetime. A distributed transmission Radius and data generation Rate Adjustment (RRA) scheme is proposed based on a cross-layer design, considering the interaction among physical, network and transport layers. Simulation results show that the proposed RRA strategy can effectively enhance the data gathering performance in wireless multimedia sensor networks (WMSNs) by dynamically adjusting the transmission radius of sensor nodes and the data generation rate of source nodes.
27763383
Security of MD5 Challenge and Response: Extension of APOP Password Recovery Attack
In this paper, we propose an extension of the APOP attack that recovers the first 31 characters of APOP password in practical time, and theoretically recovers 61 characters. We have implemented our attack, and have confirmed that 31 characters can be successfully recovered. Therefore, the security of APOP is completely broken. The core of our new technique is finding collisions for MD5 which are more suitable for the recovery of APOP passwords. These collisions are constructed by employing the collision attack of den Boer and Bosselares and by developing a new technique named "IV Bridge" which is an important step to satisfy the basic requirements of the collision finding phase. We show that the construction of this "IV Bridge" can be done efficiently as well.
31093950
Extended Password Recovery Attacks against APOP, SIP, and Digest Authentication
In this paper, we propose password recovery attacks against challenge-response authentication protocols. Our attacks use a message difference for a MD5 collision attack proposed in IEICE 2008. First, we show how to efficiently find a message pair that collides with the above message difference. Second, we show that a password used in authenticated post office protocol (APOP) can be recovered practically. We also show that the password recovery attack can be applied to a session initiation protocol (SIP) and digest authentication. Our attack can recover up to the first 31 password characters in a short time and up to the first 60 characters faster than the naive search method. We have implemented our attack and confirmed that 31 characters can be successfully recovered.
14686364
Software Design Methodology for Set-Top Box
Digital TV industry is developing rapidly recent years in China, which brings up generous commercial value and opens a great software market. However, this field is divided into more than 300 parts, where services are different from one to another. As a result, it’s difficult to design software of the Set-Top Box for developers, and usually they have to change from one platform to another, in order to meet the network operator’s needs. To resolve this problem, we propose a brand new software stack in this paper, which is well-layered and extendable, to make the software design easy and effective, and to make the applications reusable on different platforms. We have implemented this software stack to 3 different platforms, which performed pretty well and made the project ahead of schedule.
8366599
Achieving both high precision and high recall in near-duplicate detection
To find near-duplicate documents, fingerprint-based paradigms such as Broder's shingling and Charikar's simhash algorithms have been recognized as effective approaches and are considered the state-of-the-art. Nevertheless, we see two aspects of these approaches which may be improved. First, high score under these algorithms' similarity measurement implies high probability of similarity between documents, which is different from high similarity of the documents. But how similar two documents are is what we really need to know. Second, there has to be a tradeoff between hash-code length and hash-code multiplicity in fingerprint paradigms, which makes it hard to maintain a satisfactory recall level while improving precision.
 In this paper our contributions are two-folded. First, we propose a framework for implementing the longest common subsequence (LCS) as a similarity measurement in reasonable computing time, which leads to both high precision and recall. Second, we present an algorithm to get a trustable partition from the LCS to reduce the negative impact from templates used in web page design. A comprehensive experiment was conducted to evaluate our method in terms of its effectiveness, efficiency, and quality of result. More specifically, the method has been successfully used to partition a set of 430 million web pages into 68 million subsets of similar pages, which demonstrates its effectiveness. For quality, we compared our method with simhash and a Cosine-based method through a sampling process (Cosine is compared to LCS as an alternative similarity measurement). The result showed that our algorithm reached an overall precision of 0.95 while simhash was 0.71 and Cosine was 0.82. At the same time our method obtains 1.86 times as much recall as simhash and 1.56 times as much recall as Cosine. Comparison experiment was also done for documents in the same web sites. For that, our algorithm, simhash and Cosine find almost the same number of true-positives at a precision of 0.91, 0.50 and 0.63 respectively. In terms of efficiency, our algorithm takes 118 hours to process the whole archive of 430 million topic-type pages on a cluster of six Linux boxes, at the same time the processing time of simhash and Cosine is 94 hours and 68 hours respectively. When considering the need of word segmentation for languages such as Chinese, the processing time of Cosine should be multiplied and in our experiment it is 602 hours.