• Title/Summary/Keyword: Low Inventory Detection

Search Result 7, Processing Time 0.024 seconds

The Smart Medicine Delivery Using UAV for Elderly Center

  • Li, Jie;Weiwei, Goh;N.Z., Jhanjhi;David, Asirvatham
    • International Journal of Computer Science & Network Security
    • /
    • v.23 no.1
    • /
    • pp.78-88
    • /
    • 2023
  • Medication safety and medicine delivery challenge the well-being of the elderly and the management of the elderly center. With the outbreak of COVID-19, the elderly in the care center were challenged by the inconvenience of the medication restocking. The purpose of this paper accentuates the importance of the design and development of an UAV-based Smart Medicine Case (UAV-SMC) to improve the performance of medication management and medicine delivery in the elderly center. The researchers came up with the design of UAV-SMC in the light of the UAV and IoT technology to improve the performance of both Medication Practice Management (MPM) and Low Inventory Detection and Delivery (LIDD). Based on the result, with UAV-SMC, the performance of both MPM and LIDD was significantly improved. The UAV-SMC improves the efficacy of medication management in the elderly center by 26.97 to 149.83 seconds for each medication practice and 9.03 mins for each time of medicine delivery in Subang Jaya Malaysia. This paper only investigates the adoption of UAV-SMC in the content of elderly center rather than other industries. The authors consider integrating the UAV-SMC with the e-pharmacy system in the future. In conclusion, the UAV-SMC has significantly improved the medication management and guard the safety of elderly and caretaker in the elderly in the post-pandemic times.

Reliability and Validity of Korean Geriatric Anxiety Inventory(K-GAI) (한국판 노인불안도구(K-GAI)의 신뢰도와 타당도)

  • Kim, Jiyun;Park, Myung Sook;Oh, Doo Nam
    • Journal of muscle and joint health
    • /
    • v.21 no.1
    • /
    • pp.75-84
    • /
    • 2014
  • Purpose: The purpose of this study was to test the validity and reliability of the Korean version of the Geriatric Anxiety Inventory (K-GAI). Methods: Two hundreds and thirty six elderly were participated to test K-GAI. Goldberg's short screening scale for anxiety was tested for criterion validity. Receiver operating characteristics (ROC) analysis was used for measuring sensitivity and specificity. Results: The obtained internal consistency was 0.88. There were significant associations between test and retest results. K-GAI scores was significantly associated with Goldberg's short screening scale for anxiety (r=.694, p<.001). We found that a score of seven and greater was optimal for a criterion of anxiety among elderly Koreans. At this cut point, sensitivity was 78.9% and specificity was 73.1%. Conclusion: The K-GAI displayed good psychometric properties. This tool would be useful for early detection of anxiety among elderly Koreans with various situations including cognitive disorder, low education, or physical disability.

An Approach to the Spectral Signature Analysis and Supervised Classification for Forest Damages - An Assessment of Low Altitued Airborne MSS Data -

  • Kim, Choen
    • Korean Journal of Remote Sensing
    • /
    • v.7 no.2
    • /
    • pp.149-163
    • /
    • 1991
  • This paper discusses the capabilities of airborne remotely sensed data to detect and classify forest damades. In this work the AMS (Aircraft Multiband Scanner) was used to obtain digital imagery at 300m altitude for forest damage inventory in the Black Forest of Germany. MSS(Multispectral Scanner) digital numbers were converted to spectral emittance and radiance values in 8 spectral bands from the visible to the thermal infrared and submitted to a maximum-likelihood classification for : (1) tree species ; and. (2) damage classes. As expected, the resulted, the results of MSS data with high spatial resolution 0.75m$\times$0.75m enabled the detection and identification of single trees with different damages and were nearly equivalent to the truth information of ground checked data.

Examination on Autonomous Recovery Algorithm of Piping System (배관 체계 자율 복구 알고리즘 비교, 분석 및 고찰)

  • Yang, Dae Won;Lee, Jeung-hoon;Shin, Yun-Ho
    • Journal of the Korean Society of Safety
    • /
    • v.36 no.4
    • /
    • pp.1-11
    • /
    • 2021
  • Piping systems comprising pumps and valves are essential in the power plant, oil, and defense industry. Their purpose includes a stable supply of the working fluid or ensuring the target system's safe operation. However, piping system accidents due to leakage of toxic substances, explosions, and natural disasters are prevalent In addition, with the limited maintenance personnel, it becomes difficult to detect, isolate, and reconfigure the damage of the piping system and recover the unaffected area. An autonomous recovery piping system can play a vital role under such circumstances. The autonomous recovery algorithms for the piping system can be divided into low-pressure control algorithms, hydraulic resistance control algorithms, and flow inventory control algorithms. All three methods include autonomous opening/closing logic to isolate damaged areas and recovery the unaffected area of piping systems. However, because each algorithm has its strength and weakness, appropriate application considering the overall design, vital components, and operating conditions is crucial. In this regard, preliminary research on algorithm's working principle, its design procedures, and expected damage scenarios should be accomplished. This study examines the characteristics of algorithms, the design procedure, and working logic. Advantages and disadvantages are also analyzed through simulation results for a simplified piping system.

Characteristics of Pain Threshold and Pain Experience in Elderly Patients with Dementia (노인 치매 환자의 통증 역치 및 통증 경험의 특성)

  • Bang, Hyeon-Cheol;Park, Ki-Chang;Kim, Min-Hyuk;Lee, Yeong-Bok;Roh, Hyun-Jean
    • Korean Journal of Psychosomatic Medicine
    • /
    • v.21 no.2
    • /
    • pp.140-146
    • /
    • 2013
  • Objectives: We compared the characteristics of the pain threshold and pain experience between demented group and non-demented group. Methods: This study was part of Gangwon projects for early detection of dementia in 2010. We recruited 8302 local resident ages over 65 years old. Of theses, 1259 people who scored low MMSE were selected and 365 of them completed CERAD-K(Consortium to Establish a Registry for Alzheimer's disease). Finally, 90 in non-demented group and 57 in demented group(mild to moderate Alzheimer's disease) were analyzed. Pain threshold was experimentally measured by pressure algometer and we investigated the pain experience, by Brief pain inventory (BPI), a self-report test. Results: In the demographic characteristics, there are more female, higher ages, lower education in the demented group. There was no significant difference between the two groups in the pain threshold. On the BPI results, 'shoulder pain', 'the number of pain' and 'interference of working' were significantly more prevalent in non-demented group. However, there are no significant differences between the groups in the 'pain severity', 'prevalence of pain' and 'pain treatment'. Conclusions: Demented group report less pain experience but, still perceived pain. It support previous studies that patient with dementia have increased pain tolerance but preserved pain threshold. Thus, active pain assessment and treatment for patients with dementia is needed.

  • PDF

Development of a Detection Model for the Companies Designated as Administrative Issue in KOSDAQ Market (KOSDAQ 시장의 관리종목 지정 탐지 모형 개발)

  • Shin, Dong-In;Kwahk, Kee-Young
    • Journal of Intelligence and Information Systems
    • /
    • v.24 no.3
    • /
    • pp.157-176
    • /
    • 2018
  • The purpose of this research is to develop a detection model for companies designated as administrative issue in KOSDAQ market using financial data. Administration issue designates the companies with high potential for delisting, which gives them time to overcome the reasons for the delisting under certain restrictions of the Korean stock market. It acts as an alarm to inform investors and market participants of which companies are likely to be delisted and warns them to make safe investments. Despite this importance, there are relatively few studies on administration issues prediction model in comparison with the lots of studies on bankruptcy prediction model. Therefore, this study develops and verifies the detection model of the companies designated as administrative issue using financial data of KOSDAQ companies. In this study, logistic regression and decision tree are proposed as the data mining models for detecting administrative issues. According to the results of the analysis, the logistic regression model predicted the companies designated as administrative issue using three variables - ROE(Earnings before tax), Cash flows/Shareholder's equity, and Asset turnover ratio, and its overall accuracy was 86% for the validation dataset. The decision tree (Classification and Regression Trees, CART) model applied the classification rules using Cash flows/Total assets and ROA(Net income), and the overall accuracy reached 87%. Implications of the financial indictors selected in our logistic regression and decision tree models are as follows. First, ROE(Earnings before tax) in the logistic detection model shows the profit and loss of the business segment that will continue without including the revenue and expenses of the discontinued business. Therefore, the weakening of the variable means that the competitiveness of the core business is weakened. If a large part of the profits is generated from one-off profit, it is very likely that the deterioration of business management is further intensified. As the ROE of a KOSDAQ company decreases significantly, it is highly likely that the company can be delisted. Second, cash flows to shareholder's equity represents that the firm's ability to generate cash flow under the condition that the financial condition of the subsidiary company is excluded. In other words, the weakening of the management capacity of the parent company, excluding the subsidiary's competence, can be a main reason for the increase of the possibility of administrative issue designation. Third, low asset turnover ratio means that current assets and non-current assets are ineffectively used by corporation, or that asset investment by corporation is excessive. If the asset turnover ratio of a KOSDAQ-listed company decreases, it is necessary to examine in detail corporate activities from various perspectives such as weakening sales or increasing or decreasing inventories of company. Cash flow / total assets, a variable selected by the decision tree detection model, is a key indicator of the company's cash condition and its ability to generate cash from operating activities. Cash flow indicates whether a firm can perform its main activities(maintaining its operating ability, repaying debts, paying dividends and making new investments) without relying on external financial resources. Therefore, if the index of the variable is negative(-), it indicates the possibility that a company has serious problems in business activities. If the cash flow from operating activities of a specific company is smaller than the net profit, it means that the net profit has not been cashed, indicating that there is a serious problem in managing the trade receivables and inventory assets of the company. Therefore, it can be understood that as the cash flows / total assets decrease, the probability of administrative issue designation and the probability of delisting are increased. In summary, the logistic regression-based detection model in this study was found to be affected by the company's financial activities including ROE(Earnings before tax). However, decision tree-based detection model predicts the designation based on the cash flows of the company.

Detection of Site Environment and Estimation of Stand Yield in Mixed Forests Using National Forest Inventory (국가산림자원조사를 이용한 혼효림의 입지환경 탐색 및 임분수확량 추정)

  • Seongyeop Jeong;Jongsu Yim;Sunjung Lee;Jungeun Song;Hyokeun Park;JungBin Lee;Kyujin Yeom;Yeongmo Son
    • Journal of Korean Society of Forest Science
    • /
    • v.112 no.1
    • /
    • pp.83-92
    • /
    • 2023
  • This study was established to investigate the site environment of mixed forests in Korea and to estimate the growth and yield of stands using national forest resources inventory data. The growth of mixed forests was derived by applying the Chapman-Richards model with diameter at breast height (DBH), height, and cross-sectional area at breast height (BA), and the yield of mixed forests was derived by applying stepwise regression analysis with factors such as cross-sectional area at breast height, site index (SI), age, and standing tree density per ha. Mixed forests were found to be growing in various locations. By climate zone, more than half of them were distributed in the temperate central region. By altitude, about 62% were distributed at 101-400 m. The fitness indexes (FI) for the growth model of mixed forests, which is the independent variable of stand age, were 0.32 for the DBH estimation, 0.22 for the height estimation, and 0.18 for the basal area at breast height estimation, which were somewhat low. However, considering the graph and residual between the estimated and measured values of the estimation equation, the use of this estimation model is not expected to cause any particular problems. The yield prediction model of mixed forests was derived as follows: Stand volume =-162.6859+6.3434 ∙ BA+9.9214 ∙ SI+0.7271 ∙ Age, which is a step- by-step input of basal area at breast height (BA), site index (SI), and age among several growth factors, and the determination coefficient (R2) of the equation was about 96%. Using our optimal growth and yield prediction model, a makeshift stand yield table was created. This table of mixed forests was also used to derive the rotation of the highest production in volume.