Contribution to Improve Database Classification Algorithms for Multi-Database Mining

Salim Miloudi,Sid Ahmed Rahal,Salim Khiat 한국정보처리학회 2018 Journal of information processing systems Vol.14 No.3

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact,when a multi-branch company needs to explore its distributed data for decision making, it is imperative toclassify these multiple databases into similar clusters before analyzing the data. To search for the bestclassification of a set of n databases, existing algorithms generate from 1 to (n2–n)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification aresubsets of clusters in the next classification), existing algorithms generate each classification independently,that is, without taking into account the use of clusters from the previous classification. Consequently, existingalgorithms are time consuming, especially when the number of candidate classifications increases. Toovercome the latter problem, we propose in this paper an efficient approach that represents the problem ofclassifying the multiple databases as a problem of identifying the connected components of an undirectedweighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of ouralgorithm against existing works and that it overcomes the problem of increase in the execution time.

Athletic Training for Korean EFL Learners’ Anxiety Resistance, Pragmatic Awareness, and Motivation for English Learning

"Salim Bullen", "Young Woo Cho" 培材大學校 人文科學硏究所 2015 人文論叢 Vol.32 No.-

This study investigated whether athletic training, in the form of soccer, may improve Korean college-level EFL learners’ anxiety resistance, pragmatic awareness, and motivation. Fifty-six Korean college students divided into two groups (control and treatment) completed a questionnaire on their self-evaluations of anxiety, pragmatic ability, and motivation. The treatment group (n=28) participated in a soccer training program for two months led by the researcher, who was a native speaker of English, and a bilingual Korean/English speaking assistant. The control group (n=28) received no athletic training during the same period, but practiced English in their regular English courses. At the completion of the program, both groups completed the same questionnaire. Results from ANCOVA analyses showed significant improvements in the two areas: anxiety resistance and pragmatic awareness for the treatment group. However, no significant improvement was found in motivation. These results suggest that athletic training may be used as part of regular EFL instruction to help L2 learners lower anxiety and raise pragmatic awareness. However, motivation is a more complex issue that needs to be addressed from a broader perspective. 운동훈련은 제2언어학습과 커뮤니케이션을 보조할 수 있는 독특한 언어학습 도구이다. 운동훈련을 통하여 제2언어학습자들은 교실 밖 환경에서 실시간으로 의사소통을 하는데 필요한 의사소통 기술을 발달시킬 수 있으며 이를 통하여 영어를 통한 의사소통이 더 의미 있게 된다. 그러나 운동과 제2언어학습 및 의사소통을 통합했을 때 얻을 수 있는 유익을 반영하는 기존연구는 없었다. 따라서 본 연구는 운동의 한 형태로서 축구를 사용하여 제2언어학습자들의 불안에 대한 저항력과, 학습동기, 화용적 인식을 강화할 수 있는 가능성을 탐색하는 것을 목적으로 하였다. 대학 영어강좌를 수강하는 56명의 한국 성인 영어학습자들이 본 연구에 참여하였다. 학습자들은 처치집단과 통제집단 두 집단으로 나뉘어 연구가 시작되기 전 학습불안과, 화용능력, 학습동기에 관한 스스로의 인식에 관한 설문지를 작성하였다. 처치집단(n=28)은 원어민인 연구자와 한국어/영어 이중언어를 구사하는 연구보조원이 이끄는 축구훈련 프로그램에 두 달 동안 참여하였다. 통제집단(n=28)은 같은 기간 어떤 종류의 운동훈련도 받지 않았으며 정규영어강좌에서 학습하였다. 프로그램 종료 후 두 집단은 처음과 동일한 설문지를 작성하였다. 두 집단의 응답을 비교했을 때 처치집단이 학습불안에 대한 저항력과 화용적 인식에서 통제집단보다 더 높은 수준의 유의미한 향상이 있음이 나타났다. 그러나 학습동기에서는 유의미한 향상에 관한 차이점이 발견되지 않았다. 이 결과들은 운동을 통하여 제2언어학습자들이 영어사용자들과 의사소통할 때 느끼는 불안감을 완화시킬 수 있고 화용적 인식을 증대시킬 수 있지만 운동과 제2언어학습동기와의 관계를 더 잘 이해하기 위해서는 추가적인 연구가 필요함을 시사한다.

A review of vibration-based MEMS hybrid energy harvesters

Mohammed Salim,Hakim S. Sultan Aljibori,Dhia Salim,M. Haris M. Khir,A. Sh. Kherbeet 대한기계학회 2015 JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY Vol.29 No.11

Energy harvesters based on Micro-electromechanical systems (MEMS) are well known nowadays due to their small features, abilityfor monolithic integration with the integrated circuit in a single platform, robust, and easily fabricated in bulk. The piezoelectric (PZT)and the electromagnetic (EM) generators are examples of such energy harvesters. To further increase their effectiveness in harvestingambient energy, researchers started to venture into hybrid energy harvesters. Few literature reviews may be found on MEMS harvestingdevices, but not on hybrid harvesters in specific. This paper intended to further elaborate on the hybrid energy harvesters, reported Literatureon such harvesters for recent years with different architectures, models, and results are presented. Table of power comparison betweenthe reported harvesters is presented and discussed.

Contribution to Improve Database Classification Algorithms for Multi-Database Mining

Miloudi, Salim,Rahal, Sid Ahmed,Khiat, Salim Korea Information Processing Society 2018 Journal of information processing systems Vol.14 No.3

Database classification is an important preprocessing step for the multi-database mining (MDM). In fact, when a multi-branch company needs to explore its distributed data for decision making, it is imperative to classify these multiple databases into similar clusters before analyzing the data. To search for the best classification of a set of n databases, existing algorithms generate from 1 to ($n^2-n$)/2 candidate classifications. Although each candidate classification is included in the next one (i.e., clusters in the current classification are subsets of clusters in the next classification), existing algorithms generate each classification independently, that is, without taking into account the use of clusters from the previous classification. Consequently, existing algorithms are time consuming, especially when the number of candidate classifications increases. To overcome the latter problem, we propose in this paper an efficient approach that represents the problem of classifying the multiple databases as a problem of identifying the connected components of an undirected weighted graph. Theoretical analysis and experiments on public databases confirm the efficiency of our algorithm against existing works and that it overcomes the problem of increase in the execution time.

Supplementation of graded levels of organic zinc in the diets of female broilers: effects on performance and carcase quality.

Salim, H M,Lee, H R,Jo, C,Lee, S K,Lee, B D Longman 2011 British poultry science Vol.52 No.5

<P>Zinc is an essential trace element. The objective of this research was to investigate the effects of various levels of organic zinc (OZ) supplementation on growth performance and carcase quality of female broiler chickens. A total of 3200 1-d-old female broiler chicks were randomly allotted to 16 floor pens with 200 birds per pen. A maize-wheat-soyabean meal basal diet (Control) was formulated and 20 mg/kg OZ (20 OZ), 40 mg/kg OZ (40 OZ), and 80 mg/kg OZ (80 OZ) were added to the basal diet to form 4 dietary treatments with 4 replicates per treatment. The OZ source was zinc proteinate which contained 15% zinc. Results showed no significant difference between the treatments in growth performance. A significant increase in thigh skin epidermis and dermis thickness was shown in the OZ supplementation groups; however, no effect was found on the thickness of back skin epidermis and dermis. Collagen contents in breast and thigh meats were not influenced by OZ supplementation but a significant increase in collagen content was found in the back and thigh skin. This increase in collagen content was significantly greater in the back and thigh skin of OZ 80 than with OZ 20. Shear force value and zinc concentration in skins and meat were not significantly influenced by supplementation with OZ. It is concluded that dietary OZ does not improve growth performance of broilers; however, it could increase skin thickness by increasing collagen content in skin, thereby improving carcase quality.</P>

Performance of machine learning methods in diagnosing Parkinson’s disease based on dysphonia measures

Salim Lahmiri,Debra Ann Dawson,Amir Shmuel 대한의용생체공학회 2018 Biomedical Engineering Letters (BMEL) Vol.8 No.1

Parkinson’s disease (PD) is a widespreaddegenerative syndrome that affects the nervous system. Itsearly appearing symptoms include tremor, rigidity, andvocal impairment (dysphonia). Consequently, speechindicators are important in the identification of PD basedon dysphonic signs. In this regard, computer-aided-diagnosissystems based on machine learning can be useful inassisting clinicians in identifying PD patients. In this work,we evaluate the performance of machine learning basedtechniques for PD diagnosis based on dysphonia symptoms. Several machine learning techniques were consideredand trained with a set of twenty-two voice disordermeasurements to classify healthy and PD patients. Thesemachine learning methods included linear discriminantanalysis (LDA), k nearest-neighbors (k-NN), naı¨ve Bayes(NB), regression trees (RT), radial basis function neuralnetworks (RBFNN), support vector machine (SVM), andMahalanobis distance classifier. We evaluated the performanceof these methods by means of a tenfold cross validationprotocol. Experimental results show that the SVMclassifier achieved higher average performance than allother classifiers in terms of overall accuracy, G-mean, andarea under the curve of the receiver operating characteristicplot. The SVM classifier achieved higher performancemeasures than the majority of the other classifiers also interms of sensitivity, specificity, and F-measure statistics. The LDA, k-NN and RT achieved the highest averageprecision. The RBFNN method yielded the highestF-measure.; however, it performed poorly in terms of otherperformance metrics. Finally, t tests were performed toevaluate statistical significance of the results, confirmingthat the SVM outperformed most of the other classifiers onthe majority of performance measures. SVM is a promisingmethod for identifying PD patients based on classificationof dysphonia measurements.

UV Star Formation Rates in the Local Universe

Salim, Samir,Rich, R. Michael,Charlot, Stephane,Brinchmann, Jarle,Johnson, Benjamin D.,Schiminovich, David,Seibert, Mark,Mallery, Ryan,Heckman, Timothy M.,Forster, Karl,Friedman, Peter G.,Martin, D. C IOP Publishing 2007 The Astrophysical journal, Supplement series Vol.173 No.2

Production system influences color stability and lipid oxidation in gluteus medius muscle

Salim Ana Paula Amaral de Alcântara,Ferreira Micheli da Silva,Monteiro Maria Lucia Guerra,Lima Loíse Caroline Santos de,Magalhães Isabelle Trezze Marins,Conte-Júnior Carlos Adam,Mano Sérgio Borges 아세아·태평양축산학회 2023 Animal Bioscience Vol.36 No.5

Objective: We aimed to evaluate the color and oxidative stability of beef gluteus medius (GM) from cattle raised in organic and non-organic production systems. Methods: The GM samples (n = 10) were obtained from organic (ORG; n = 5) or nonorganic (NORG; n = 5) beef samples, sliced into 2.54-cm steaks, packaged in aerobic conditions, and stored for nine days at 4°C. ORG and NORG steaks were compared regarding myoglobin concentration, pH, instrumental color, delta E (ΔE), metmyoglobin reducing activity (MRA), and lipid oxidation on days 0, 5, and 9. Results: Feeding system did not influence (p>0.05) the myoglobin concentration. ORG steaks exhibited greater (p<0.05) meat pH, yellowness, and MRA, whereas NORG steaks exhibited greater (p<0.05) redness, chroma, R630/580, delta E, and lipid oxidation. ORG and NORG steaks exhibited similar (p>0.05) lightness and hue angle. During storage, ORG and NORG exhibited an increase in muscle pH, hue angle, and lipid oxidation; and a decrease (p<0.05) in redness, yellowness, chroma, and color stability (R630/580). Both samples exhibited a stable (p>0.05) pattern for lightness and MRA. Conclusion: Therefore, the production system can affect beef color and lipid stability during storage.

Economic Strategy: Correlation between Macro and Microeconomics on Income Inequality in Indonesia

SALIM, Agus,RUSTAM, Andi,HAERUDDIN, Haeruddin,ASRIATI, Asriati,PUTRA, Aditya Halim Perdana Kusuma Korea Distribution Science Association 2020 The Journal of Asian Finance, Economics and Busine Vol.7 No.8

This study sees a critical gap in the previous body of research, which it seeks to fill; the disclosure of the unemployment ratio correlation has only been measured by the level of economic growth. This study is to add investment variables and government expenditure variables that objectively aim to measure the level of effectiveness in handling the unemployment ratio, which is then a measurement of the effectiveness of unemployment. Economic growth is measured by its impact on income inequality through empirical, conceptual relationships as a critical review and economic strategy for the future. The research uses secondary data on Indonesian macro and microeconomics since 2003-2018, then testing uses a quantitative approach to correlation, regression, and scatterplot. The results of this study show correlations between variables, and volatiles on the graphs show a similar trend. In other words, variables are bound together and support each other. The strategy of prioritizing the scale of government expenditure and investment to reach the target is the primary concern, so that the economic cycle can be optimal and equipped to face the possibility of an economic recession in the future. Many factors cause complex income inequality, though investment does not show a correlation to income inequality.

Concept of Operations of Procurement Engineering Management Support System

Salim, Shelly,Kim, Jin Il,Yeom, Choong Sub,Park, Jong Sun The Korean Society of Systems Engineering 2018 시스템엔지니어링학술지 Vol.14 No.1

A software support system, called procurement engineering management support system (PeMSS), is currently under development through a joint research project. The procurement-related scenarios considered in this research is as follow: an EPC (Engineering, Procurement and Construction) company receives an EPC project contract and starts the project to deliver the agreed system to the acquirer. In order to acquire the required equipments that the EPC company does not produce by itself, it eventually interacts with subcontractors, also called vendors. The EPC company responsibilities during the procurement activities are twofold. First, the EPC company has to guarantee that it has ordered the equipment, through issuing Purchase Order (PO), based on the requirements stated in the contract. Second, the EPC company has to verify that the received equipment designs, called Vendor Print (VP), meet the specifications in the PO, before finally acquiring the equipments. During our survey study, we discovered that EPC company takes a lot of time and effort to create PO and verify VP, mainly because these activities are performed manually by the responsible engineers. Therefore, we intent to support the above activities by developing a support system to the legacy procurement system that can trace the requirements from the contract to the PO and VP, among other functionalities. At the time of the writing of this paper, PeMMS is still under-development, thus, in this paper we focus on presenting the development steps of PeMMS using systems engineering theory and introducing the PO creation function. Wholly, PeMSS attempts to reduce the time and effort of engineers on the procurements activities while also increasing the quality of the procurement outcomes.