Towards a Task-based Guidance in Exploratory Visual Analytics

Exploring large datasets and identifying meaningful information is still an active topic in many application fields. Dealing with large datasets is currently not only a matter of simply collecting and structuring data for retrieval, but sometimes it also requires the provision of adequate means for guiding the user through the exploration process. Visualizations have shown to be an effective method in this context, the reason being that since they are grounded on visual cognition, people understand them and can naturally perform visual operations such as clustering, filtering and comparing quantities. However, systems which help us to create visualizations often require specific knowledge in data analysis, which ordinary users typically do not possess. To address this gap, we propose a system that guides the user in the data analysis process. To achieve this, the system observes current user behavior, tries to infer the task of the user and recommends the next analysis steps to help her to carry out the task

Decision support for multi-component systems: visualizing interdependencies for predictive maintenance

Taking dependencies between components seriously and considering the multi-component perspective instead of the single-system perspective could help to improve the results of predictive maintenance (PdM). However, modeling and identifying the interdependencies in complex industrial systems is challenging. A way to tackle this challenge and to identify interdependencies is using visualization. To the best of our knowledge, existing research on visualizing interdependencies is not applied to multi-component systems (MCS) so far. Further, it is not clear how visualization approaches can provide suitable decision support to identify interdependencies in PdM tasks. We evaluate three key visualization approaches to represent interdependencies in the context of PdM for MCS using a crowd-sourced design study in a questionnaire survey involving 530 participants. Based on our study, we were able to rank these approaches based on performance and usability for our given PdM task. The multi-line approach outperformed other approaches with respect to performance

The Recommendation Dashboard: A System to Visualise and Organise Recommendations

Abstract Recommender systems are becoming common tools supporting automatic, context-based retrieval of resources. When the number of retrieved resources grows large visual tools are required that leverage the capacity of human vision to analyse large amounts of information. We introduce a Web-based visual tool for exploring and organising recommendations retrieved from multiple sources along dimensions relevant to cultural heritage and educational context. Our tool provides several views supporting filtering in the result set and integrates a bookmarking system for organising relevant resources into topic collections. Building upon these features we envision a system which derives user's interests from performed actions and uses this information to support the recommendation process. We also report on results of the performed usability evaluation and derive directions for further development

Türkiye'de eğitimin gelire etkisinin ekonometrik analizi

Eğitim ile gelir ilişkisi iktisadi literatürde birçok araştırmaya konu olmuş, yapılan çalışmalarda eğitimin bireysel bazda geliri, ulusal çapta ise büyümeyi etkileyen en önemli faktörlerden biri olduğu kanıtlanmıştır. Bu çalışmada, beşeri sermayenin gelir üzerindeki etkisinin incelendiği ekonometrik analizlerde yaygın olarak kullanılan Mincer Kazanç Denklemi’nden yola çıkılarak, Türkiye’de eğitimin gelire etkisinin ölçümlenmesinde en uygun model ve yönteme ulaşılması amaçlanmıştır. Bu kapsamda Mincer Kazanç Denklemi farklı şekillerde kurgulanarak En Küçük Kareler (EKK), Araç Değişkenler ve İki Aşamalı EKK yöntemleri ile analiz edilmiştir. Bununla birlikte eğitim değişkeni için ölçme hatasının varlığı Hausmann’ın İçsellik Testi ile sorgulanmıştır. Bu kapsamda içsellik problemi tespit edilen eğitim değişkeni için “meslek”, “sağlık durumu” ve “maddi yoksunluk” göstergeleri araç değişken olarak seçilmiştir. Uygulamada zayıf araç değişken probleminin varolabileceği de göz önüne alınarak kısmi korelasyon katsayısı ile seçilen araçların gücü test edilmiştir. Uygulama sonuçları, seçilen araç değişkenlerin zayıf olduğunu ortaya koymuş, bu durumda başvurulan İki Aşamalı EKK Yöntemi ile sapmalı tahmincilerden uzaklaşıldığı bulgusuna ulaşılmıştır. İktisadi açıdan ise eğitimin 2016 yılınde gelirin belirleyicileri arasında olduğu, eğitim görülen her bir ek yılın kişinin gelirini yüzde 0,78 artırdığı sonucuna varılmıştır. -------------------- The relationship between education and income has been subjected to many research. This researches show that the education is among the factors that effect the income personally, and also the growth at the country level. This study aims to find out the optimal model and method that measures the effects of education on income in Turkey by using Mincer Earnings Function, which is widely used in econometric analysis, measuring the outcomes of human capital on income. In this framework, Mincer Earnings Function analyzed by using the Least Squares Method, Instrumental Variables (IV) Estimation and Two-Dimensional Least Squares Method, Also, this study considers the problem of making inference on a structural parameter in instrumental variables regression when the instruments are only weakly correlated with the endogenous explanatory variables. Having weak instrumental variable problem examined by coefficient of part correlation and “occupation”, “health condition” and “financial deficiency” have been chosen as the instrumental variable for education which is determined endogeneity problem. The results of the empirical study have shown that instrumental variables were weak and for this reason applied two-dimensiona

A Causality-Inspired Approach for Anomaly Detection in a Water Treatment Testbed

Critical infrastructure, such as water treatment facilities, largely relies on the effective functioning of industrial control systems (ICSs). Due to the wide adoption of high-speed network and digital infrastructure technologies, these systems are now highly interconnected not only to corporate networks but also to the public Internet, mostly for remote control and monitoring purposes. Sophisticated cyber-attacks may take advantage the increased interconnectedness or other security gaps of an ICS and infiltrate the system with devastating consequences to the economy, national security, and even human life. Due to the paramount importance of detecting and isolating these attacks, we propose an unsupervised anomaly detection approach that employs causal inference to construct a robust anomaly score in two phases. First, minimal domain knowledge via causal models helps identify critical interdependencies in the system, while univariate models contribute to individually learn the normal behavior of the system’s components. In the final phase, we employ the extreme studentized deviate (ESD) on the computed score to detect attacks and to exclude any irrelevant sensor signals. Our approach is validated on the widely used Secure Water Treatment (SWaT) benchmark, and it exhibits the highest F1 score with zero false alarms, which is extremely important for real-world deployment

Epilepsy in the elderly

WOS: 000372007900004Amaç: Epilepsi yaşlılarda sık görülen bir hastalıktır, ancak etiyolojisi, klinik sunumu, eşlik eden hastalıkları ve prognozu genç hastalardan farklıdır. Bu çalışmada epilepsi nedenleri, yaşlılarda nöbet tipleri, elektroensefalografi (EEG) bulguları araştırıldı. Gereç ve Yöntem: İlk epileptik nöbetini geçiren ve altmış beş yaş üzerinde 95 hasta retrospektif olarak değerlendirildi. Yaş, epilepsi tipi, EEG bulguları, manyetik rezonans görüntüleme ve/veya kranial tomografi bulguları, etiyoloji, eşlik eden hastalıklar ve verilen antiepileptik tedaviler değerlendirildi. Bulgular: Hastalarımızın yaş ortalaması 75 idi ve 50 (%56) hasta erkekti. Doksan beş hastanın 55’inde (%58) parsiyel tipte nöbet, 36’sında (%38) jeneralize tonik klonik nöbet ve 4’ünde (%4) jeneralize status epileptikus vardı. İnteriktal EEG’de fokal epileptiform aktivite sıklığı %32,6 idi. Nöbetler hastaların %85’inde (81 hasta) monoterapi ile %15’inde (14 hasta) politerapiyle kontrol altında idi. Çalışmamız serebrovasküler hastalıkların, en sık (%63) etyolojik neden olduğunu gösterdi. Yaş ve nöbet sıklığı ve EEG anormallikleri arasında anlamlı bir ilişki saptanmadı. Ancak yaş ve eşlik eden hastalıklar arasında anlamlı bir ilişki saptandı. Sonuç: Sonuçlarımız fokal nöbetlerin yaşlı epilepsinin en sık belirtisi olduğunu desteklemektedir. Serebrovasküler hastalıklar yaşlılarda epilepsinin en fazla rastlanan etiyolojik nedenidir. Monoterapi hastaların çoğunluğunda yeterlidir. Yaşlı nüfusun devamlı büyümesi, doğru tanı ve etkili tedavi gereksinimini arttırmaktadır.Objective: Epilepsy is frequently seen in the elderly, but its etiology, clinical presentation, comorbidities, and prognoses are different than younger patients. In this study, we investigated types of seizures, electroencephalography (EEG) findings and the cause of epilepsy in the elderly. Materials and Methods: We retrospectively analyzed 95 patients who were 65 years old or older, and who had an epileptic seizure for the first time. Type of epilepsy, age, EEG findings, magnetic resonance imaging and/or cranial tomography findings, etiology, comorbidities and antiepileptic medication were evaluated. Results: The average age of our patients was 75, and 50 (56%) patients were male. Among 95 patients, 55 (58%) had focal seizures, 36 (38%) had generalized tonic-clonic seizures and 4 (4%) had convulsive status epilepticus. The frequency of focal interictal epileptiform activity was 32.6% patients. Seizures were responsive to treatment administered as monotherapy in 81 (85%) patients and as politherapy in 14 (15%) patients. Our study showed that cerebrovascular disease was the most common (63%) etiological cause identified. There was no significant relationship between age and frequency of seizures and EEG abnormalities. However, a significant correlation was found between age and comorbidities. Conclusion: Our results supported the focal seizure is the most common manifestation of epilepsy in the elderly. Cerebrovascular disease is the most common etiological cause of epilepsy in the elderly. Monotherapy is sufficient in the majority of patients. Continuous growth of the elderly population is increasing the need for accurate diagnosis and effective treatment

Epileptic Seizure as First Presenting Symptom of Multiple Sclerosis: A Case Report

While epileptic seizures are seen in the course of multiple sclerosis, they are rarely the first symptom. The first epileptic seizure of a 26-yearold woman with multiple sclerosis is described in the present report. The patient presented to the emergency department with generalized tonic-clonic seizure. Neurologic examination was normal except for right-sided hemiparesis and hyperactive deep tendon reflexes. Cranial MRI revealed periventricular, multiple millimetric lesions and a 45x27-mm, semi-ring-enhanced, cortical, T2/FLAIR, hyperintense lesion in the centrum semiovale. IgG index was high, and oligoclonal band was positive in cerebrospinal fluid examination. Electroencephalography showed prominent fronto-temporal activity on the left side and sharp wave paroxysms. Multiple sclerosis was diagnosed, and pulse corticosteroid therapy was initiated. Due to recurrent seizures, antiepileptic drug was added to treatment; seizures were controlled with monotherapy. It is known that patients with multiple sclerosis experience seizures. Multiple sclerosis should be considered in the differential diagnosis of young patients presenting with seizures

Visual Data Analysis of Production Quality Data for Aluminum Casting

Today’s manufacturing industry is shaped by the Industry 4.0 vision, which is to increase the number of individual goods produced while minimizing the production costs and time. To increase the production outcome and quality, users need to continuously monitor and adjust the entire process. While the recent advances in sensor technology can help users to collect, produce and exchange data, human beings are often overwhelmed by the amount of data being collected. Still, the human visual system is a powerful tool that can be used to decode and process large datasets. To make intelligent use of this ability, we have developed an interactive visual data analysis tool called ADAM that can support production data exploration in the aluminum industry. Furthermore, we demonstrate the effectiveness of our tool using real production data and present insights which could be gained from use of our tool by domain experts