Predicting company merger and acquisition with the help of artificial neural networks

Değişen pazar yapısı ve rekabet koşulları şirketleri, yeni çözümler geliştirme zorunluluğu ile karşı karşıya bırakmıştır. Birleşmeler, şirketlerin yeni çözüm arayışları sonucu gündeme gelmiş buluşlardan bir tanesidir. Faaliyetlerin daha etkin yürütülmesi, faaliyet sinerjisi ve finansal sinerji elde edilmesi, yönetim etkinliğinde artış, piyasa payı, ürün geliştirme ve dağıtım sistemindeki ilerlemeler, marka, patent birleşmelerin başlıca nedenlerini oluşturur. Birleşmelerin doğru bir strateji olabilmesi için, birleşilecek veya satın alınacak şirket seçiminin, çok iyi analiz edilmesi gerektiği, bu makalede önemle vurgulanmıştır. Birleşmeler sağlıklı yapılması durumunda anlamlı olacaktır. Bu da birleşme sürecinde doğru tekniklerin kullanılması anlamını taşır. Makale kapsamında, şirketleri birleşmeye iten nedenler ve birleşen firmalarda performans artışının gerçekleştiği, stratejik planlamanın şirket birleşmeleri ile olan ilintisi anlatılmış, birleşme süreci yapay sinir ağları ile analiz edilmiş, karar vericiye sunulmak üzere, birleşme için bir yapay sinir ağı modeli oluşturulmuş, modelin oluşturulmasında MATLAB yazılımı kullanılmıştır. Neden sinir ağları sorusunun cevabı ise, onun teori gereksinimi esnektir, araştırma yaklaşımı kuralcı değildir ve bilinmeyeni sunuş şekli bulanık küme tabanlıdır ve en önemli özelliği gerçek dünya problemlerine uygulanabilir olmasıdır. Türkiye’de şirket birleşmeleri henüz gelişme aşamasındadır ve tam anlaşılamamıştır. Yöntemleri konusunda yatırımcılar yeterli bilgiye sahip değildir. Makalenin amacı birleşmenin şirketlerin büyümesi için bir yöntem olduğu, bu sürecin çok iyi analiz edilmesi gerektigi ve en doğru şirketi bulmak için sinir ağları modeli kullanılmasi önerilmiş, Türkiye’nin bir eksikliğine katkı sağlanması amaçlanmıştır.Anahtar Kelimeler: Şirket birleşme ve satınalmaları, yapay sinir ağları, karar verme.Today companies have been engaged in a new pursuit for adapting themselves to the changing market and competition conditions. Mergers are among the trends which have gained wider interest, especially in recent years. In order for the mergers to be a true strategy, the choice of company which will be merged or acquired has to be perfectly analyzed. This process was analyzed via artificial neural networks. Predictor variables selection is important factor about quality of the prediction model to get success. Predictor variables that used as inputs on the neural network model are specified on the basis of six hypotheses being frequently suggested in academic and popular financial literature. These are inefficient management hypothesis, growth resource mismatch hypothesis, industry disturbance hypothesis, size hypothesis, market-to-book hypothesis, price-earning hypothesis. 12 predictor variables that support these hypothesis are average excess return (AER), return on equity (ROE), average turnover (AVTURNOV), average growth (AVGROWTH), average liquidity (AVLIQUID), average leverage (AVLEV), GRDUMMY to see AVGROWTH, AVLIQUID, AVLEV combination, IDUMMY to see sector impact on merger and acquisition, total net book value of asset (SIZE), market-to-book (MTB), price and earnings (PE), average payout (AVPAYOUT). Based on inefficient management hypothesis, inefficiently managed firms are often acquired. AER, ROE, AVTURNOVER are chosen predictor variables to measure firm's management's performance. Growth-research mismatch hypothesis, firms with high growth and low resources or with low growth and high resources are likely to be acquired. The combination of AVGROWTH, AVLIQUID and AVLEV is to form GRDUMMY variable that shows growth-research mismatch impact. IDUMMY variable will be selected based on industry hypothesis to cluster industry impact on merger and acquisition. Based on size hypothesis, smaller firms are more likely to be acquired than larger firms. Size will be selected as a variable as well. Market-to-book hypothesis, the companies have got low market-to-book ratios are likely to be targets and same logic deals with price-earnings hypothesis. For these 12 variables, the data were obtained from COMPUSTAT. Most of the data items for variables were averaged over three to four years prior to observation year. Merger and acquisition process has been analyzed by the artificial neural network. To train the multilayer network to predict the company merger and acquisition, back propagation algorithm has been used. The advantages of back propagation algorithm is provided with a set of examples of proper network behavior where an input to the network and corresponding target output. Working approach of algorithm is to adjust the network parameters in order to minimize the mean square error. The first part of the article deals with the stimulators of the merger, the performance increase in merged companies, and the connection of strategic planning with company mergers. In the second part, artificial neural networks, the method used in the merger and acquisition process, is investigated in scope and structure. The reason for handling the artificial neural networks is that their requirement for a theory is flexible, their research approach is not prescriptive, their presentation of the unknown is fuzzy based, and most importantly, its adaptability to the real world problems. It is a considerably difficult process to determine the layer number and number of nodes on these layers that are optimum for acquiring the best neural network model. Several combinations of hidden layers and nodes are tried before reaching the satisfactory model. This process takes a long time and the optimal network is produced after many trials. The activation acquiring process cannot be realized without the computer support. In this process MATLAB 6.5 is utilized which is explained in the third part. In Turkey company mergers have not reached their maturity and they can not be completely understood. Investors do not have sufficient information on its methods. This article aims to support the view that a merger is a way for a company to grow, and to contribute to a better understanding in Turkey by making use of neural network models for identifying the best company to acquire. Keywords: Merger and acquisiton, artificial neural network, decision making

Evaluation of patients with fibrotic interstitial lung disease: Preliminary results from the Turk-UIP study

OBJECTIVE: Differential diagnosis of idiopathic pulmonary fibrosis (IPF) is important among fibrotic interstitial lung diseases (ILD). This study aimed to evaluate the rate of IPF in patients with fibrotic ILD and to determine the clinical-laboratory features of patients with and without IPF that would provide the differential diagnosis of IPF. MATERIAL AND METHODS: The study included the patients with the usual interstitial pneumonia (UIP) pattern or possible UIP pattern on thorax high-resolution computed tomography, and/or UIP pattern, probable UIP or possible UIP pattern at lung biopsy according to the 2011 ATS/ERSARS/ALAT guidelines. Demographics and clinical and radiological data of the patients were recorded. All data recorded by researchers was evaluated by radiology and the clinical decision board. RESULTS: A total of 336 patients (253 men, 83 women, age 65.8 +/- 9.0 years) were evaluated. Of the patients with sufficient data for diag-nosis (n=300), the diagnosis was IPF in 121 (40.3%), unclassified idiopathic interstitial pneumonia in 50 (16.7%), combined pulmonary fibrosis and emphysema (CPFE) in 40 (13.3%), and lung involvement of connective tissue disease (CTD) in 16 (5.3%). When 29 patients with definite IPF features were added to the patients with CPFE, the total number of IPF patients reached 150 (50%). Rate of male sex (p<0.001), smoking history (p<0.001), and the presence of clubbing (p=0.001) were significantly high in patients with IPE None of the women <50 years and none of the men <50 years of age without a smoking history were diagnosed with IPE Presence of at least 1 of the symptoms suggestive of CTD, erythrocyte sedimentation rate (ESR), and antinuclear antibody (FANA) positivity rates were significantly higher in the non-IPF group (p<0.001, p=0.029, p=0.009, respectively). CONCLUSION: The rate of IPF among patients with fibrotic ILD was 50%. In the differential diagnosis of IPF, sex, smoking habits, and the presence of clubbing are important. The presence of symptoms related to CTD, ESR elevation, and EANA positivity reduce the likelihood of IPF

Nazolabial Kist: Manyetik Rezonans Görüntüleme ve Ultrasonografi Bulguları ile Değerlendirilen Bir Vaka Raporu

Öz Nazolabial kist, nazal alar bölgede yer alan, nadir görülen, odontojenik kaynaklı olmayan, iyi huylu ve yavaş büyüyen gelişimsel bir yumuşak doku kistidir. Nazolabial kist; kadınlarda ve yaşamın dördüncü-beşinci dekatlarında daha sık görülür, patogenezi belirsizdir. Bu çalışmanın amacı bir nazolabial kist olgusunu bildirerek, manyetik rezonans ve ultrasonografik görüntüleme özelliklerini tanımlamaktır. 34 yaşında kadın hastanın sağ nazolabial bölgesinde ağrısız şişlik öyküsü vardı. Hasta ilk olarak kulak burun boğaz uzmanı tarafından değerlendirilerek manyetik rezonans görüntüsü(MRG) alınmıştı. Klinik değerlendirmede palpasyonla fluktuan ve düzgün bir kitle saptandı. Ultrasonografik görüntülemede kistik hipoekoik lezyon saptandı. Kistik lezyon cerrahi olarak çıkarıldı. Patoloji raporuna göre sonuç nazolabial kistti. Ultrasonografi(USG), maksillofasiyal bölgede yumuşak doku lezyonlarının değerlendirilmesinde güvenle kullanılan bir yöntemdir. MRG tekniği ise, iyonlaştırıcı radyasyon olmadan mükemmel bir yumuşak doku kontrast çözünürlüğü sağlamaktadır. Anahtar Kelimeler: Kist, Nazal kavite, Nazolabial, Ultrason

Epidural kateter çekilmesi sonrası spinal hematom

A 78-year old female patient with a diagnosis of gonarthrosis, was scheduled for total knee arthroplasty to the left knee under combined spinal and epidural anesthesia. in the lateral decubitus position an 18G Tuohy epidural needle was inserted through L4-5 interspace at the frst attempt without any hemorrhagic complication and combined spinal and epidural anesthesia was applied. Since his routine laboratory test results were non-pathologic, his epidural catheter was withdrawn at the 48th postoperative hour. A second dose of low molecular weight heparin was given 1.5 hours after the removal of the catheter. Three hours after the removal of the catheter, severe lumbar and hip pain and paresthesia increasing with movements developed. Cardiovascular surgery was consulted because of development of edema in the operated leg. Doppler US, increase in the dosage of low molecular weight heparin, and 100 mg acetylsalicylic acid for a putative acute deep venous thromboembolism were recommended. Magnetic resonance ımaging obtained after intensifcation of postoperative lumbar and hip pains revealed an epidural hematoma at T12-L2 level. the patient had to be taken to the operation room on the postoperative 90th hour when foot drop was developed, and drainage of the hematoma and laminectomy were performed. the patient was discharged from the hospital on the 15. postoperative day without any neurologic defect. in conclusion, subsequent to epidural catheter withdrawal noncompliant with ASRA (Association of Regional Anaesthesia) criteria and earlier anticoagulation, spinal hematoma developed Increase in the dosage of anticoagulation in consideration of deep vein thrombosis without proper consideration of differential diagnosis led to spinal hematoma with neurological fndings.Gonartroz tanılı 78 yaşında kadın olguya, kombine epidural spinal anestezi altında sağ diz protezi ameliyatı planlandı. Lateral dekubit pozisyonunda L4-5 aralıktan18G Tuohy epidural iğne ile tek, kansız girişimle kombine epidural spinal anestezi uygulandı. Postoperatif 48 saati ağrısız geçiren olgunun rutin biyokimya değerleri normal olduğu için epidural kateteri çekildi. Epidural kateter sorunsuz olarak çekildikten bir buçuk saat sonra hastaya düşük molekül ağırlıklı heparin yapıldı. Kateter çekildikten üç saat sonra bel ve kalçada hareketle artan şiddetli ağrı ve parestezi gelişti. Opere bacakta ödem gelişmesi nedeniyle kalp damar cerrahisi konsültasyonu istendi. Derin ven trombozu tanısı ile Doppler Ultrasonograf, düşük moleküler ağırlıklı heparin dozunun artırılması ve 100 mg asetilsalisilik asit tedavisi önerildi. Postoperatif bel ve kalçadaki ağrıların artması üzerine çekilen lomber manyetik rezonans görüntülemede T12-L2 düzeyinde epidural hematom saptandı. Postoperatif 90. saatte düşük ayak gelişmesi üzerine ortopedi ameliyathanesinde operasyona alınarak laminektomi uygulandı ve hematom boşaltıldı. Laminektomi ve hematom boşaltılmasını izleyen on beşinci günde hasta nörolojik sekelsiz taburcu edildi. Rejyonal Anestezi Birliği kriterlerine uygun olmayan kateter çekilmesi ve erken antikoagülan kullanılması sonrası spinal hematom gelişmiştir. Ayırıcı tanısı da iyi yapılmadan derin ven trombozu düşünülerek antikoagülasyonun artırılması, artan nörolojik bulgularla seyreden bir spinal hematoma neden olmuştur