Big Data Processing in the Cloud: a Hydra/Sufia Experience

Presentation at Open Repositories 2014, Helsinki, Finland, June 9-13, 2014

The radio frequency identification technology in the supply chain management: a case of a big logistics company

Nowadays global business trends force the adoption of innovative ICTs into the supply chain management (SCM). Particularly, the RFID technology is on high demand among SCM professionals due to its business advantages such as improving of accuracy and veloc-ity of SCM processes which lead to decrease of operational costs. Nevertheless, a question of the RFID technology impact on the efficiency of warehouse processes in the SCM re-mains open. The goal of the present study is to experiment the possibility of improvement order picking velocity in a warehouse of a big logistics company with the use of the RFID technology. In order to achieve this goal the following objectives have been developed: 1) Defining the scope of the RFID technology applications in the SCM; 2) Justification of the RFID technology impact on the SCM processes; 3) Defining a place of the warehouse order picking process in the SCM; 4) Identification and systematization of existing meth-ods of order picking velocity improvement; 5) Choosing of the study object and gathering of the empirical data about number of orders, number of hours spent per each order line daily during 5 months; 6) Processing and analysis of the empirical data; 7) Conclusion about the impact of the RFID technology on the speed of order picking process. As a result of the research it has been found that the speed of the order picking processes has not been changed as time has gone after the RFID adoption. It has been concluded that in order to achieve a positive effect in the speed of order picking process with the use of the RFID technology it is necessary to simultaneously implement changes in logistics and organizational management in 3PL logistics companies. Practical recommendations have been forwarded to the management of the company for further investigation and procedure.

Molecular characterization of DDX26, a human DEAD-box RNA helicase, located on chromosome 7p12

DEAD-box proteins comprise a family of ATP-dependent RNA helicases involved in several aspects of RNA metabolism. Here we report the characterization of the human DEAD-box RNA helicase DDX26. The gene is composed of 14 exons distributed over an extension of 8,123 bp of genomic sequence and encodes a transcript of 1.8 kb that is expressed in all tissues evaluated. The predicted amino acid sequence shows a high similarity to a yeast DEAD-box RNA helicase (Dbp9b) involved in ribosome biogenesis. The new helicase maps to 7p12, a region of frequent chromosome amplifications in glioblastomas involving the epidermal growth factor receptor (EGFR) gene. Nevertheless, co-amplification of DDX26 with EGFR was not detected in nine tumors analyzed.

Visual analytics for behavioral and niche market segmentation

Companies require information in order to gain an improved understanding of their customers. Data concerning customers, their interests and behavior are collected through different loyalty programs. The amount of data stored in company data bases has increased exponentially over the years and become difficult to handle. This research area is the subject of much current interest, not only in academia but also in practice, as is shown by several magazines and blogs that are covering topics on how to get to know your customers, Big Data, information visualization, and data warehousing. In this Ph.D. thesis, the Self-Organizing Map and two extensions of it – the Weighted Self-Organizing Map (WSOM) and the Self-Organizing Time Map (SOTM) – are used as data mining methods for extracting information from large amounts of customer data. The thesis focuses on how data mining methods can be used to model and analyze customer data in order to gain an overview of the customer base, as well as, for analyzing niche-markets. The thesis uses real world customer data to create models for customer profiling. Evaluation of the built models is performed by CRM experts from the retailing industry. The experts considered the information gained with help of the models to be valuable and useful for decision making and for making strategic planning for the future.

Pienet erikoiskaupat Big datan aikakaudella: Asiakastiedonjohtamisen edellyttämät strategiset orientaatiot.

This master’s thesis has examined how Entrepreneurial, Customer and Knowledge Management Orientations are needed in the use of Big data technology by small retail firms in their Customer Knowledge Management. A vision of the ability of small retailers to move to the Big data era is based on empirical evidence of owner-managers’ attitudes and the firms’ processes. Abductive content analysis was used as a research strategy and the qualitative data was collected through theme interviews of owner-managers of 11 small-size retail firms. The biggest obstacles to the use of Big data by small retail firms are: a lack of information about the new technology; a lack of Knowledge Management Orientation; and, a lack of proactive dimension in Entrepreneurial and Customer Orientations. A strong reactive customer-led orientation, and the ability of the owner-manager to system thinking will support Customer Knowledge Management development. The low stage of technology-use is preventing utilization of customer information. Co-operation between firms or with educational organizations may significantly enhance the use of Big data –technology by small retail firms.

High mobility group box 1 as a mediator of endotoxin administration after hemorrhagic shock-primed lung injury

High mobility group box 1 (HMGB1) was discovered as a novel late-acting cytokine that contributes to acute lung injury (ALI). However, the contribution of HMGB1 to two-hit-induced ALI has not been investigated. To examine the participation of HMGB1 in the pathogenesis of ALI caused by the two-hit hypothesis, endotoxin was injected intratracheally in a hemorrhagic shock-primed ALI mouse model. Concentrations of HMGB1 in the lung of the shock group were markedly increased at 16 h (1.63 ± 0.05, compared to the control group: 1.02 ± 0.03; P < 0.05), with the highest concentration being observed at 24 h. In the sham/lipopolysaccharide group, lung HMGB1 concentrations were found to be markedly increased at 24 h (1.98 ± 0.08, compared to the control group: 1.07 ± 0.03; P < 0.05). Administration of lipopolysaccharide to the hemorrhagic shock group resulted in a notable HMGB1 increase by 4 h, with a further increase by 16 h. Intratracheal lipopolysaccharide injection after hemorrhagic shock resulted in the highest lung leak at 16 h (2.68 ± 0.08, compared to the control group: 1.05 ± 0.04; P < 0.05). Compared to the hemorrhagic shock/lipopolysaccharide mice, blockade of HMGB1 at the same time as lipopolysaccharide injection prevented significantly pulmonary tumor necrosis factor-alpha, interleukin-1beta and myeloperoxidase. Lung leak was also markedly reduced at 16 h; blockade of HMGB1 24 h after lipopolysaccharide injection failed to alter lung leak or myeloperoxidase at 48 h. Our observations suggest that HMGB1 plays a key role as a late mediator when lipopolysaccharide is injected after hemorrhagic shock-primed ALI and the kinetics of its release differs from that of one-hit ALI. The therapeutic window to suppress HMGB1 activity should not be delayed to 24 h after the disease onset.

Role of high mobility group box-1 and protection of growth hormone and somatostatin in severe acute pancreatitis

In this study, we investigated the potential role of high-mobility group box 1 (HMGB1) in severe acute pancreatitis (SAP) and the effects of growth hormone (G) and somatostatin (S) in SAP rats. The rats were randomly divided into 6 groups of 20 each: sham-operated, SAP, SAP+saline, SAP+G, SAP+S and SAP+G+S. Ileum and pancreas tissues of rats in each group were evaluated histologically. HMGB1 mRNA expression was measured by reverse transcription-PCR. Levels of circulating TNF-α, IL-1, IL-6, and endotoxin were also measured. In the SAP group, interstitial congestion and edema, inflammatory cell infiltration, and interstitial hemorrhage occurred in ileum and pancreas tissues. The levels of HMGB1, TNF-α, IL-1, IL-6 and endotoxin were significantly up-regulated in the SAP group compared with those in the sham-operated group, and the 7-day survival rate was 0%. In the SAP+G and SAP+S groups, the inflammatory response of the morphological structures was alleviated, the levels of HMGB1, TNF-α, IL-1, IL-6, and endotoxin were significantly decreased compared with those in the SAP group, and the survival rate was increased. Moreover, in the SAP+G+S group, all histological scores were significantly improved and the survival rate was significantly higher compared with the SAP group. In conclusion, HMGB1 might participate in pancreas and ileum injury in SAP. Growth hormone and somatostatin might play a therapeutic role in the inflammatory response of SAP.

Implementing Green IT approach for transferring Big Data over Parallel Data Link

The whole research of the current Master Thesis project is related to Big Data transfer over Parallel Data Link and my main objective is to assist the Saint-Petersburg National Research University ITMO research team to accomplish this project and apply Green IT methods for the data transfer system. The goal of the team is to transfer Big Data by using parallel data links with SDN Openflow approach. My task as a team member was to compare existing data transfer applications in case to verify which results the highest data transfer speed in which occasions and explain the reasons. In the context of this thesis work a comparison between 5 different utilities was done, which including Fast Data Transfer (FDT), BBCP, BBFTP, GridFTP, and FTS3. A number of scripts where developed which consist of creating random binary data to be incompressible to have fair comparison between utilities, execute the Utilities with specified parameters, create log files, results, system parameters, and plot graphs to compare the results. Transferring such an enormous variety of data can take a long time, and hence, the necessity appears to reduce the energy consumption to make them greener. In the context of Green IT approach, our team used Cloud Computing infrastructure called OpenStack. It’s more efficient to allocated specific amount of hardware resources to test different scenarios rather than using the whole resources from our testbed. Testing our implementation with OpenStack infrastructure results that the virtual channel does not consist of any traffic and we can achieve the highest possible throughput. After receiving the final results we are in place to identify which utilities produce faster data transfer in different scenarios with specific TCP parameters and we can use them in real network data links.

IFRS 9 – standardiuudistus Big Four -tilintarkastusyhteisöjen näkökulmasta – kommenttikirjeiden empiirinen analyysi

Since 2008, One of the International Accounting Standards Board’s (IASB) objective has been to replace the old IAS 39 – Financial Instruments standard. IASB achieved this objective in July 2014 when they published the new IFRS 9 – Financial Instruments after many phases. In this study, the main purpose was to find out how the Big Four – audit entities have welcomed the different reforms which IFRS 9 brings to the treatment of financial instruments in the financial statements. Alongside with this, the study presents a short overview to the common attitude towards the new standard. The study proceeds so that the most siginificant reforms have been divided into three main categories and inside of these more precisely to single reforms. This study is based on the qualitative research method. The empirical data of the study consists of comment letters by the Big Four – entities, which have been sent to the IASB regarding Exposure Drafts (ED) of IFRS 9. In total IASB received 757 comment letters regarding to the specific EDs. In this study the population were restricted to 16 comment letters sent by the Big Four – entities. The data is available at IFRS Foundation’s website. According to the research results Big Four – entities think that the reforms which IFRS 9 brings are mainly welcome. In its entirety Big Four – entities consider IFRS 9 better than its predecessor IAS 39. There were differnces in opinions towards IFRS 9 and specific reforms among the Big Four - entities. According to the findings the best reforms were related to the efficiency demands of hedge accounting and to impairments and the valuation of credit losses. The least popular reforms were the reforms regarding the measurement of financial assets and liabilities; more specifically fair value option and the reforms concerning equity instruments were viewed as most challenging.