Rakenduste kasutajaarvustustest informatsiooni kaevandamine tarkvara arendustegevuste soodustamiseks

Kasutajate vajaduste ja ootuste hindamine on arendajate jaoks oluline oma tarkvararakenduste kvaliteedi parandamiseks. Mobiilirakenduste platvormidele sisestatud arvustused on kasulikuks infoallikaks kasutajate pidevalt muutuvate vajaduste hindamiseks. Igapäevaselt rakenduste platvormidele esitatud arvustuste suur maht nõuab aga automaatseid meetodeid neist kasuliku info leidmiseks. Arvustuste automaatseks liigitamiseks, nt veateatis või uue funktsionaalsuse küsimine, saab kasutada teksti klassifitseerimismudeleid. Rakenduse funktsioonide automaatne kaevandamine arvustustest aitab teha kokkuvõtteid kasutajate meelsusest rakenduse olemasolevate funktsioonide osas. Kõigepealt eksperimenteerime erinevate tekstiklassifitseerimise mudelitega ning võrdleme lihtsaid, leksikaalseid tunnuseid kasutavaid mudeleid keerukamatega, mis kasutavad rikkalikke lingvistilisi tunnuseid või mis põhinevad tehisnärvivõrkudel. Erinevate faktorite mõju uurimiseks funktsioonide kaevandamise meetoditele me teeme kõigepealt kindlaks erinevate meetodite baastaseme täpsuse rakendades neid samades eksperimentaalsetes tingimustes. Seejärel võrdleme neid meetodeid erinevates tingimustes, varieerides treenimiseks kasutatud annoteeritud andmestikke ning hindamismeetodeid. Kuna juhendatud masinõppel baseeruvad kaevandamismeetodid on võrreldes reeglipõhistega tundlikumad (1) andmete märgendamisel kasutatud annoteerimisjuhistele ning (2) märgendatatud andmestiku suurusele, siis uurisime nende faktorite mõju juhendatud masinõppe kontekstis ja pakkusime välja uued annoteerimisjuhised, mis võivad aidata funktsioonide kaevandamise täpsust parandada. Käesoleva doktoritöö projekti tulemusel valmis ka kontseptuaalne tööriist, mis võimaldab konkureerivaid rakendusi omavahel võrrelda. Tööriist kombineerib arvustuse tekstide klassifitseerimise ja rakenduse funktsioonide kaevandamise meetodid. Tööriista hinnanud kümme tarkvaraarendajat leidsid, et sellest võib olla kasu rakenduse kvaliteedi parandamiselFor app developers, it is important to continuously evaluate the needs and expectations of their users to improve app quality. User reviews submitted to app marketplaces are regarded as a useful information source to re-access evolving user needs. The large volume of user reviews received every day requires automatic methods to find such information in user reviews. Text classification models can be used to categorize review information into types such as feature requests and bug reports, while automatic app feature extraction from user reviews can help in summarizing users’ sentiments at the level of app features. For classifying review information, we perform experiments to compare the performance of simple models using only lexical features to models with rich linguistic features and models built on deep learning architectures, i.e., Convolutional Neural Network (CNN). To investigate factors influencing the performance of automatic app feature extraction methods, i.e. rule-based and supervised machine learning, we first establish a baseline in a single experimental setting and then compare the performances in different experimental settings (i.e., varying annotated datasets and evaluation methods). Since the performance of supervised feature extraction methods is more sensitive than rule- based methods to (1) guidelines used to annotate app features in user reviews and (2) the size of the annotated data, we investigate their impact on the performance of supervised feature extraction models and suggest new annotation guidelines that have the potential to improve feature extraction performance. To make the research results of the thesis project also applicable for non-experts, we developed a proof-of-concept tool for comparing competing apps. The tool combines review classification and app feature extraction methods and has been evaluated by ten developers from industry who perceived it useful for improving the app quality.  https://www.ester.ee/record=b529379

BARRIERS IN IMPLEMENTATION OF E-BUSINESS TECHNOLOGIES IN SMALL AND MEDIUM ENTERPRISES (SMEs) IN PAKISTAN

The current research investigates the Barriers in implementation of E-Business Technologies in Small and Medium enterprises (SMEs) in Pakistan. Data were collected from 2000 respondents by using simple random technique. A structural questionnaire was developed for the data collection and reliability and validity of data. It was revealed that most of the SMEs business owners are not familiar in using internet and in many cases they are not computer literate. It was further revealed that Government should provide some basic computer training to the Small and Medium Enterprises so they will able to use computer. The proper implementation of E-Business technologies in SMEs in Pakistan, Government and other related agencies can initiate E-Business in SMEs to achieve competitive edge

Pressure distribution on helicopter fuselage

Modern rotorcrafts are subjected to some of the most complex flow behaviors ever encountered by the rotorcraft aerodynamicist. The objective of this research work is to investigate the pressure distribution on a helicopter fuselage in relation to the helicopter phenomenon. In this experimental work, a standard ellipsoidal helicopter fuselage model was mated to a main-rotor-hub assembly from a remote-control helicopter. The model was equipped with 28 pressure taps where the locations of the taps were predetermined by CFD analysis. The experiments were carried out in the UTM wind tunnel with a test section of 2m (width) x 1.5m (height) x 5.8m (length) with the maximum wind speed of 80 m/s. Data of pressure corresponding to the variations of helicopter’s pylon configurations and advance ratios were recorded using Electronic Pressure Scanning System. The effects of advance ratio and pylon configuration to the pressure distribution on helicopter fuselage were analysed. Findings reveal that the employment of pylon does augmenting the pressure coefficient on the rear part of the fuselage. Results also indicate the pressure distributions on the right and left sides of the fuselage are unsymmetrical indicating a very complex flow phenomenon experienced by the helicopter fuselage

Structural and Ion Dynamics in Fluorine-Free Oligoether Carboxylate Ionic Liquid-Based Electrolytes

Here, we investigate the physicochemical and electrochemical properties of fluorine-free ionic liquid (IL)-based electrolytes with two different cations, tetrabutylphosphonium, (P-4,4,4,(4))(+), and tetrabutylammonium, (N-4,N-4,N-4,N-4)(+), coupled to a new anion, 2-[2-(2-methoxyethoxy)ethoxylacetate anion (MEEA), for both neat and (P-4,P-4,P-4,P-4) (MEEA)(-), also doped with 10-40 mol % of Li(MEEA). We find relatively weaker cation-anion interactions in (P-4,P-4,P-4,P-4)(MEEA) than in (N-4,N-4,N-4,N-4)(MEEA), and for both ILs, the structural flexibility of the oligoether functionality in the anion results in low glass transition temperatures, also for the electrolytes made. The pulsed field gradient nuclear magnetic resonance (PFG NMR) data suggest faster diffusion of the (MEEA)(-) anion than (P-4,P-4,P-4,P-4)(+) cation in the neat IL, but the addition of a Li salt results in slightly lower mobility of the former than the latter and lower ionic conductivity. This agrees with the combined Li-7 NMR and attenuated total reflection-Fourier transform infrared (ATR-FTIR) spectroscopy data, which unambiguously reveal preferential interactions between the lithium cations and the carboxylate groups of the IL anions, which also increased as a function of the lithium salt concentration. In total, these systems provide a stepping stone for further design of fluorine-free and low glass transition temperature IL-based electrolytes and also stress how crucial it is to control the strength of ion-ion interactions

Robotic exoskeleton control for lower limb rehabilitation of knee joint

Wearable devices such as exoskeletons are being opted frequently during rehabilitation processes for the post stroke recovery. Such de-vices are playing important role in the development of assistive rehabilitation robotic systems. In this paper three control strategies MPC and LQR and PID are introduced which were applied to knee joint of lower limb exoskeleton model for passive exercise. The two con-trols MPC and LQR are model based control which empowers them for stable responses. In this paper the analysis of robustness of con-trol is done under the noisy and disturbance conditions. The results showed good performance of the exoskeleton model with the applied controls in the provided condition. In the future work the applied controls will be implemented on hardware

Evaluation of Current Technologies for Training, Web Apps, and New Technologies

This report details the activities conducted to assess the feasibility of using new technology tools for safety training. Utilizing established research studies, risk frameworks, and vendor quotations, we compared the different attributes of training methods such as Traditional Training (classroom/presentations), LMS (Learning Management System) based gamification, Computer Simulation, Virtual Reality (VR), and Augmented Reality (AR). The anticipated benefits include improved training program development, higher interactivity and long-term retention, and the chance to reduce work zone risk. The project was divided in three phases, and the following are our four key takeaways. (1) Quality of Safety Training: Benchmarking training practices provided strong evidence that participative programs, such as role plays, demonstrations of safety devices, and risk mapping are some of the best practices. Additionally, training engineers on work zone design, auditing, and recording safe work zones can influence project attributes, such as the length and duration of work zone. Including all these aspects during the project planning phase has a greater chance of influencing work zone safety. (2) Effectiveness of New Technology Tools: Our vendor outreach project phase allowed us to determine the different attributes in training course development and customer experience using new technology tools. Established research studies provided significant support to our hypothesis that new technology tools are more effective and interactive compared to traditional learning. (3) Risk-Based Approach to Training: Analyzing the risk index for work zone attributes indicate the degree of risk that a worker faces while performing a task characterizing those attributes. We concluded that implementation of new technology tools should be planned based on this risk index and optimization model. This will ensure better worker performance and perception of the course content in alignment with the severity of that work attribute. (4) Optimizing Selection of Training Tools for Tasks: We provide an optimization model to choose the optimal mix of training tools to attain the desired level of risk reduction. The tool is spreadsheet-based and shows the benefit of using a portfolio of modules across training tools, each targeted at attaining the desired risk reduction by attribute for a task. By using the risk reduction due to training tools from the literature, the cost data from vendors and task characteristics, this tool can enable INDOT managers to manage risk cost efficiently

Structural evolution of yig during microwave and conventional sintering at 1000ºc

Microwave heating(MH) has emerged in recent years as a new method for sintering a variety of materials against conventional sintering (CH) procedure. However,the phenomenon of microwave-materials interaction is still under debate. In this work,the effect of microwave heating on YIG phase formation was investigated at 1000ºC under the electromagnetic field(2.4GHz). The phase stability fired samples were qualitative and quantitative analyzed using X-ray diffraction(XRD)techniques. The obtained data were compared with CH to track the phase evolution. XRD revealed MHhas produced, YIG with 94% faster than CS. The calculated activation energy at this temperature via diffusion control model shows that MH(39.20kJ/mol)can effectively promote the phase growth rather than CH(90.96 kJ/mol)

Osmotin-loaded magnetic nanoparticles with electromagnetic guidance for the treatment of Alzheimer's disease

Alzheimer's disease (AD) is the most prevalent age-related neurodegenerative disease, pathologically characterized by the accumulation of aggregated amyloid beta (Aβ) in the brain.</p

Snake Bite in South Asia: A Review

Snake bite is one of the most neglected public health issues in poor rural communities living in the tropics. Because of serious misreporting, the true worldwide burden of snake bite is not known. South Asia is the world's most heavily affected region, due to its high population density, widespread agricultural activities, numerous venomous snake species and lack of functional snake bite control programs. Despite increasing knowledge of snake venoms' composition and mode of action, good understanding of clinical features of envenoming and sufficient production of antivenom by Indian manufacturers, snake bite management remains unsatisfactory in this region. Field diagnostic tests for snake species identification do not exist and treatment mainly relies on the administration of antivenoms that do not cover all of the important venomous snakes of the region. Care-givers need better training and supervision, and national guidelines should be fed by evidence-based data generated by well-designed research studies. Poorly informed rural populations often apply inappropriate first-aid measures and vital time is lost before the victim is transported to a treatment centre, where cost of treatment can constitute an additional hurdle. The deficiency of snake bite management in South Asia is multi-causal and requires joint collaborative efforts from researchers, antivenom manufacturers, policy makers, public health authorities and international funders