Problem Description Clause Samples

Problem Description. Reasons for Request for Regulatory Flexibility 1. Hazardous Waste Determination [40 CFR 262.11] The Universities have found, and their stakeholder group has confirmed, that hazardous waste determination may be made prematurely in the laboratories and may be a barrier to the reuse, recycling and redistribution of laboratory waste throughout the institution. This is attributable to the finding that once researchers and graduate students no longer have use for an individual laboratory waste, they are seldom aware of the reuse and recycling opportunities available in other laboratories. Thus, they are prone to call even reusable materials “hazardous waste.” The result is that a certain quantity of reusable material is unnecessarily disposed of every year. In fact, under the current OSHA/RCRA 1Such performance-based systems applicable to hazardous materials in laboratories have been developed and successfully implemented by the National Institutes of Health for biohazards, the Nuclear Regulatory Commission for nuclear hazards and OSHA for workplace hazards. For example, under OSHA’s performance-based Laboratory Standard, management of hazardous materials in the laboratory is principally regulated by means of a written Chemical Hygiene Plan as required under 29 CFR 1910.1450, which is developed by each organization in accordance with the criteria set forth in the standard. scheme, a 1996 survey revealed that less than 1% of laboratory waste is currently reused by university laboratories.

Problem Description. ‌ In order to better motivate the generalization process that led to the design of protocol presented in this paper, let us introduce a model that we will show to encompass various practical problems, and an example situation for which solutions in literature (to the best of our knowledge) do not give satisfactory results. (i) Let N be a network, where each node i ∈ N has access to a Random Variable X , where X(i) = (X(i), . . . , X(i)), for all c ∈ {1, . . . , m}, where X(i) takes values in a discrete set V , P(i) 1 m c c c is its probability mass function, and X(i) = X(l), for all i, l ∈ N and for all c. Each node i . Σ c c records O(i) = x(i), . . . , x(i) , the observed values given by the random variable. The goal of 1 m our protocol is to allow the nodes in N to reach agreement on a vector of observed values. We make a distinction between two kind of components: ambiguous and unambiguous. A component c is ambiguous if there exist two honest nodes i, l ∈ N who observe two distinct values x(i) =ƒ x(l), otherwise we say that the component is unambiguous.

Problem Description. The problem, described in this thesis, is the case of Statoil. Therefore in this section we will give a short description of Statoil upstream logistics. The objective of this thesis is develop approach that during the main goal of vessel charter costs and fuel consumption costs minimization determines the best speed in order to curb the growth of greenhouse gases worldwide. Our problem illustrated in Figure 1 includes offshore installations that are supplied from single onshore base. Figure 1. Periodic supply vessel planning problem with 5 installations. Red ball represents Mongstad onshore base, while white squares are the real offshore installations. Blue and red lines are hypothetical voyages. The following practical constraints must be taken into account in our problem: 1) Voyage duration limits. 2) The limits of installation visits per voyage. 3) Vessel deck capacity. 4) Weekly demand of each installation. 5) The visit requirement for each installation during the week. 6) The capacity and schedule of onshore base. Restriction on the voyage duration is due to factors that too short voyages are not desirable, too long voyages cause to much uncertainty. Hence, the minimum duration of two days and maximum of three days are introduced. Moreover, each vessel could service only limited number of installations, there is a minimum and maximum number of visits per voyage. Every installation has its own schedule of working hours. Some are opened round the clock and can be supplied at any time, while others are closed from 19:00 till 7:00. In addition, all vessels should start all voyages from onshore base at 16:00. It is also assumed that vessels return to the depot not late than 8 hours before departure time, if next voyage starts on the same day. Concerning day-offs, the onshore base is closed on Sundays. Weekly vessel schedule is decided depending on planned demands of the installations. All of them have to be visited certain number of times during the week. It is also essential that the installation visits are fairly evenly spread throughout the week. Additionally, the total demand of all installations in each vessel voyage may not exceed the vessel deck capacity. Vessel A Vessel B The simple solution example is shown on the figure two. It represents sample with two supply vessels that have to visit five installations. Some of them need to be visited two times a week when others require more often supply. Two platform supply vessels fulfill all required dema...

Problem Description. Currently, more and more travel agencies outsource tour-guides‟ business to service suppliers, that is, travel agencies entrusted tourists‟ service to service suppliers; Tourists prefer to choose the travel agency which brings higher tourism‟s utility for them through good travel experience supported by service suppliers. So the relationship among tourists, travel agencies and service suppliers are dual principal-agent, among which travel agencies are both principals and agents. This paper researches the service outsourcing system consisting of a travel agency, a service supplier and tourists. In the system, the system‟s output is determined by collaborative service of the travel agency and the service supplier, and tourists‟ utilities is determined by efforts level of the travel agency and the service supplier. During the cooperation between the travel agency and the service supplier, the private information of both parties is difficult to be observed by each other. So it is easy to lead to moral hazards in both parties, therefore, affect tourists‟ utility and satisfaction. According to dual principal- agent theory, the best way for the travel agency is to provide the service supplier with a set of effectively incentive contracts, which optimizes tourism experience of tourists, at the same time, maximizes the service supplier‟s utilities after satisfying the travel agency‟s revenue. (1) the travel agency provides service outsourcing contracts with fixed salary and revenue sharing coefficient to the service supplier; (2) The service supplier adapts his service cost according to the contract supplied by the travel agency and decide whether to sign contracts; (3) if the service supplier accepts contracts, the travel agency and the service supplier maximize tourists‟ utilities by their optimal efforts levels at the same time maximizing their expected utilities; (4)after finishing the cooperative production, the travel agency pays fees to the service supplier.

Problem Description. Suppose we want to create a WCF service with code contracts. A straightforward approach to combine both tech- nologies would be as follows: using System.ServiceModel;

Problem Description. Reasons for Request for Regulatory Flexibility 1. Hazardous Waste Determination [40 CFR 262.11] The Universities have found, and their stakeholder group has confirmed, that hazardous waste determination may be made prematurely in the laboratories and may be a barrier to the reuse, recycling and redistribution of laboratory waste throughout the institution. This is attributable to the finding that once researchers and graduate students no longer have use for an individual laboratory waste, they are seldom aware of the reuse and recycling opportunities available in other laboratories. Thus, they are prone to call even reusable materials “hazardous waste.” The result is that a certain quantity of reusable material is unnecessarily disposed of every year. In fact, under the current OSHA/RCRA scheme, a 1996 survey revealed that less than 1% of laboratory waste is currently reused by university laboratories.

Problem Description eduroam IdPs use data storage (directories, databases, etc.) to store their users’ credentials. There are different technical ways to store user passwords in a secure, non-reversibly encrypted way. When using PEAP, the only option to store the credentials in this way is by employing the NT-Hash function to the password, which is a variant of the MD4 hash function. Many IdPs opt not to use NT-Hashes, but different forms of hashes which provide greater cryptographic strength than MD4. Popular choices are SHA1, SHA256 or their salted derivatives. Such hashes have the drawback that they are not compatible with PEAP. IdPs which use such hashes are forced to deploy EAP-TTLS with cleartext transmission of the user password within the TTLS tunnel (usually PAP). The EAP authentication combination EAP-TTLS+PAP is based on the creation of a secure communication channel using a certificate (EAP-TTLS) and sending user name and password in clear text inside the established tunnel from the user device to the IdP. The secure tunnel extends from the user device to the IdP (authentication server). Although the EAP-TTLS-PAP authentication combination is a common solution, Nokia phones that are able to connect to the wireless network use Symbian OS, which does not support EAP-TTLS+PAP. For more information on this topic, see the Nokia forum thread, EAP-TTLS/PAP support [NOKIAFORUM].

Problem Description. The proposed scheduling problem considers the splitting into cycles of the batches of orders allocated to the assembly line of a factory. The situations that this scheduling is required is in order to avoid assembly line stoppages caused by different processing times of the different orders while also in cases where the material flow of components delivery needs to be balanced. The bellow characteristics define the environment at which the problem is defined for: A set of orders/ products have been planned to be assembled in a specific line without the definition of the specific sequence The line is consisted of a set of positions/ steps which need to be performed before the final product is available There is a specific cycle time requirement (in hours) of a batch that need to be respected when sequencing the orders. The sub-assembled product of previous position cannot move to the next position unless the next position is empty The objective is to create batches of orders/ products that fit a specific cycle time requirement in order to balance material delivery flow; maximize the throughput of the line by allocating orders with similar durations in the assembly steps.

Problem Description. The main objective of this thesis is to focus on uncertainties, using real option theory and apply that in decision processes to choose infrastructure solutions in gas pipeline system. It presents a framework of how to make decisions under uncertainties by using different options. Real option analysis helps managers to deal with the concept of a hub system in developing gas infrastructure for a new area. We use Ormen ▇▇▇▇▇ Project at Nyhamna as a case study to see if real options give support to develop Nyhamna as a hub. We focus on cost efficiency to analyze Nyhamna as a hub. We also look into the alternative where the real option can be waited until new capacity will be available in an alternative hub, Åsgard. We will try to quantify the project’s value under different alternatives, using real option analysis. We had interviews with the head leader of ▇▇▇▇▇ ▇▇▇▇▇ Project (▇▇. ▇▇▇ ▇▇▇▇▇ Hollen ) and a representative of Gassco (▇▇. ▇▇▇▇ ▇▇▇▇ ▇▇▇▇). Since they need time to work on this project and decide whether Nyhamna could be developed as a hub, part of this information is confidential and not available for us as students. For some extent, we have found data on relevant projects on the internet. After getting these data, we have tried to construct them as good as possible. Hence, this thesis emphasizes on analyzing the values of different options at Nyhamna based on some assumptions. In addition, we have tried the data to apply the options at Nyhamna in competition with an existing hub at Åsgard.