Time-Cost Data in Agency Administration: Efficiency Controls in Family and Children's Service

Social Work ◽  
1970 ◽  
Vol 15 (4) ◽  
pp. 23-31 ◽  
Author(s):  
Norman L. Bonney ◽  
Lawrence H. Streicher
2012 ◽  
Vol 214 ◽  
pp. 792-798
Author(s):  
Fei Liu ◽  
Yan Jia ◽  
Wei Hong Han

In this paper, we proposed a multi-hierarchical diversity algorithm MHD to prevent privacy disclosing in dataset. We proposed some definitions of multi-hierarchical diversity firstly. Sensitive values are partitioned into several classes. We ensured no proportion of class exceeding the threshold. We generalized some values of sensitive attribute to reduce information loss. Clustering method was used to lower data distort. Greed algorithm was used to lower time cost. We compared MHD with classic algorithms, ε-cloning and m-Invariance about Time Cost, Data Distort, Usability and Imbalance. Empirical results showed that our algorithm could protect privacy and publish datasets with high security and lower information loss


2006 ◽  
Vol 26 (3) ◽  
pp. 265-272 ◽  
Author(s):  
Scott B. Cantor ◽  
Lawrence B. Levy ◽  
Marylou Cárdenas-Turanzas ◽  
Karen Basen-Engquist ◽  
Tao Le ◽  
...  

1982 ◽  
Vol 14 (2) ◽  
pp. 109-113 ◽  
Author(s):  
Suleyman Tufekci
Keyword(s):  

2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method


Author(s):  
Ali Hameed Al-Badri

Appendicitis is a common and urgentsurgical illness with protean manifestations,generous overlap with other clinical syndromes,and significant morbidity,whichincreases with diagnostic delay. No single sign,symptom,or diagnostic test accurately confirms the diagnosis ofappendiceal inflammation in all cases. The surgeon's goals are to evaluate a relatively small population of patients referred for suspected appendicitis and to minimize the negative appendectomy rate without increasing the incidence of perforation. The emergency department clinician must evaluate the larger group of patients who present to the ED with abdominal pain of all etiologies with the goal of approaching 100% sensitivity for the diagnosis in a time-,cost-,and consultation-efficient manner.IN 1886Reginald fitz, pathologist 1st described the clinical condition of A.A.Fewyears laterCharles mcBurney describe the clinical finding ofA.A.55% of patients presented with classical symptom of A.A so complication occurbecauseof atypical presentation which due to variation in app. Position, age of patient & degree of inflammation.Migrating pain 80% sensitive and specific Vomiting 50% Nausea60 -90 %Anorexia 75 % Diarrhea18 % 32 % has similar attach 90 % RLQ tenderness Marklesign 74 %Dunphy's sign (sharp pain in the RLQ elicited by a voluntary cough) may be helpful in making the clinical diagnosis of localized peritonitis. Similarly,RLQ pain in response to percussion of a remote quadrant of the abdomen,or to firm percussion of the patient's heel,suggests peritoneal Inflammation


2021 ◽  
Vol 11 (13) ◽  
pp. 6188
Author(s):  
Parinaz Jafari ◽  
Malak Al Hattab ◽  
Emad Mohamed ◽  
Simaan AbouRizk

Due to a lack of suitable methods, extraction of reporting requirements from lengthy construction contracts is often completed manually. Because of this, the time and costs associated with completing reporting requirements are often informally approximated, resulting in underestimations. Without a clear understanding of requirements, contractors are prevented from implementing improvements to reporting workflows prior to project execution. This study developed an automated reporting requirement identification and time–cost prediction framework to overcome this challenge. Reporting requirements are extracted using Natural Language Processing (NLP) and Machine Learning (ML), and stochastic simulations are used to predict overhead costs and durations associated with report preparation. Functionality and validity of the framework were demonstrated using real contracts, and an accuracy of over 95% was observed. This framework provides a tool to rapidly and efficiently retrieve requirements and quantify the time and costs associated with reporting, in turn providing necessary insights to streamline reporting workflows.


2021 ◽  
pp. 1-13
Author(s):  
Sun Jianzhu ◽  
Zhang Qingshan ◽  
Yu Yinyun

Multi-site selection is a hot research issue for equipment manufacturing enterprises. With the development of smart industry, equipment manufacturing enterprises have entered the era of personalized and small batch manufacturing. Enterprises want to better meet customer needs and win competition, they must carry out scientific factory planning and site selection, so as to ensure quick response to the market. Based on this, this paper proposes a two-stage location selection model. Firstly, the method uses fuzzy numbers to express the demand size of demand points. Secondly, the distance factor is used as a criterion to select the candidate manufacturing bases with sufficient available resources. Next, the location model of enterprise manufacturing base is established which the goal of maximizing service efficiency and the constraints of time, cost and demand. Finally, a random numerical example is used to simulate the model, and lingo is used to solve it.


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