Instruction Length Research Articles

Modeling and Execution of Floating Point Parallel Processing Operation for RISC Processor

The development of processors with sundry suggestions have been made regarding a exactitude definition of RISC, but the prosaic concept is that such a computer has a small set of simple and prosaic instructions, instead of an outsized set of intricate and specialized instructions. This project proposes the planning of a high speed 64 bit RISC processor. The miens of this processor consume less power and it contrives on high speed. The processor comprises of sections namely Instruction Fetch section, Instruction Decode section, and Execution section. The ALU within the execution section comprises a double-precision floating-point multiplier designed during a corollary architecture thus improving the speed and veracity of the execution. All the sections are designed using Verilog coding. Monotonous instruction format, cognate prosaic-purpose registers, and pellucid addressing modes were the other miens. RISC exemplified as Reduced Instruction Set Computer. For designing high-performance processors, RISC is considered to be the footing. The RISC processor has a diminished number of Instructions, fixed instruction length, more prosaic-purpose register which are catalogued into the register file, load-store architecture and facilitate addressing modes which make diacritic instruction execute faster and achieve a net gain in performance. Thus the cardinal intent of this paper is to consummate the veridicality by devouring less power, area and with merest delay and it would be done by reinstating the floating-point ALU with single precision section by floating- point double precision section. Video processing, telecommunications and image processing were the high end applications used by architecture.

An In-Service Primary Teacher’s Responses to Unexpected Moments in the Mathematics Classroom

The purpose of this case study is to investigate the triggers of unexpected (contingent) moments during one in-service primary teacher’s teaching of the measurement of length and perimeter, to identify this teacher’s responses to these moments, and to examine how these responses change the flow of the measurement of length and perimeter instruction. Ten lessons were recorded: the triggers of the contingent moments during these lessons were analyzed according to Rowland, Thwaites and Jared’s (2015) framework and the teacher’s responses were analyzed according to Stockero and Van Zoest’s (Journal of Mathematics Teacher Education, 16(2), 125–147, 2013) response types. The findings of this study showed that the contingent moments in these lessons resulted from the students’ incorrect answers, questions, and ideas, and the availability of materials. Moreover, the analysis of the teacher’s responses indicated that there were differences in the teacher’s spontaneous responses during the lessons, both in terms of the different types and the depth of the given responses. In addition, the teacher’s way of responding affected the flow of the measurement of length and perimeter instruction.

The effect of linguistic comprehension instruction on generalized language and reading comprehension skills: A systematic review.

The effect of linguistic comprehension instruction on generalized language and reading comprehension skills: A systematic review.

A meta-analysis of the effects of instruction and corrective feedback on L2 pragmatics and the role of moderator variables

AbstractThis paper reports the results of a meta-analysis of 39 published studies conducted during the last decade (from 2006 to 2016) on the effects of instruction and corrective feedback on learning second language (L2) pragmatics. The study meta-analyzed the effects of instruction in terms of several moderator variables including mode of instruction, type of instruction, outcome measures, length of instruction, language proficiency, and durability of the instructional effects. It was found that (a) computer-assisted instruction generated larger effects than face-to-face instruction, (b) instruction was generally more effective for L2 pragmatic comprehension than production, (c) instruction produced larger effects when tested by selected response outcome measures although different patterns were observed across explicit-implicit categories, (d) longer treatments generated a larger effect size than shorter treatments, (e) studies conducted with intermediate level learners produced larger effect sizes than beginner or advanced level learners, and (f) the observed effects of instruction were maintained.

The Impact of Instruction and Out‐of‐School Exposure to Foreign Language Input on Learners’ Vocabulary Knowledge in Two Languages

This cross‐sectional study investigated the impact of length of instruction, out‐of‐school exposure to foreign language input, and gender on learners’ receptive vocabulary knowledge in two foreign languages: French (first foreign language) and English (second foreign language). The findings suggest that, although length of instruction correlated positively with vocabulary knowledge in English and French, the gains remained modest when out‐of‐school exposure to the foreign language input was limited. Despite fewer years of English instruction, participants’ vocabulary knowledge in English was considerably larger than their French vocabulary knowledge, which can be explained by their large amounts of out‐of‐school exposure to English language input. Participants’ online activities in particular had a positive effect on their vocabulary knowledge in English. Although gender influenced participants’ engagement with online activities in English, gender did not have a direct effect on their vocabulary knowledge, as the structural equation modeling analysis showed.Open PracticesThis article has been awarded an Open Materials badge. The test materials are publicly accessible via the IRIS database at https://www.iris-database.org: The English VocabLab test (https://www.iris-database.org/iris/app/home/detail?id=york%3a933919) and The French VocabLab test (https://www.iris-database.Org/iris/app/home/detail?id=york%3a933777). Learn more about the Open Practices badges from the Center for Open Science: https://osf.io/tvyxz/wiki.

TrABin: Trustworthy analyses of binaries

Verification of microkernels, device drivers, and crypto routines requires analyses at the binary level. In order to automate these analyses, in the last years several binary analysis platforms have been introduced. These platforms share a common design: the adoption of hardware-independent intermediate representations, a mechanism to translate architecture dependent code to this representation, and a set of architecture independent analyses that process the intermediate representation. The usage of these platforms to verify software introduces the need for trusting both the correctness of the translation from binary code to intermediate language (called transpilation) and the correctness of the analyses. Achieving a high degree of trust is challenging since the transpilation must handle (i) all the side effects of the instructions, (ii) multiple instruction encodings (e.g. ARM Thumb), and (iii) variable instruction length (e.g. Intel). Similarly, analyses can use complex transformations (e.g. loop unrolling) and simplifications (e.g. partial evaluation) of the artifacts, whose bugs can jeopardize correctness of the results. We overcome these problems by developing a binary analysis platform on top of the interactive theorem prover HOL4. First, we formally model a binary intermediate language and we prove correctness of several supporting tools (i.e. a type checker). Then, we implement two proof-producing transpilers, which respectively translate ARMv8 and CortexM0 programs to the intermediate language and generate a certificate. This certificate is a HOL4 proof demonstrating correctness of the translation. As demonstrating analysis, we implement a proof-producing weakest precondition generator, which can be used to verify that a given loop-free program fragment satisfies a contract. Finally, we use an AES encryption implementation to benchmark our platform.

Dynamic Scalable Elliptic Curve Cryptographic Scheme and Its Application to In-Vehicle Security

The design of unified, efficient, and lightweight cryptographic platform for resource-constrained on-board devices such as sensors, microcontrollers, and actuators in the context of Internet of Vehicles remains an open and challenging problem, for both academic and industry. Elliptic curve cryptography (ECC) is considered as a promising encryption algorithm for the next generation communications, as it could provide the same strong security level using relatively smaller key size when compared to the currently used Rivest–Shamir–Adleman algorithm. However, traditional ECCs have the disadvantage of using a fixed curve, making it very easy to be intensively analyzed while being hard to construct a united platform for on-board devices with processors of different instruction lengths. To mitigate the above problem, this paper suggests a dynamic scalable elliptic curve cryptosystem. To synchronize the curve in use, a curve list of different security levels is generated and preserved on both parties. Since both parties randomly choose the curve and the prime number, a extra security level could be provided, so that the security level can still remain the same even using smaller key sizes, while the computation efficiency will be enhanced and the power consumption will be reduced, which is especially suitable for the application in on-board embedded devices. Detailed experimental results illustrate that the presented scheme improves the efficiency by 30% in average when compared with traditional ECC implementations on a similar security level. Therefore, the proposed scalable ECC scheme as a unified cryptographic platform is more economic for these on-board devices in vehicles.

Incorrect use of inhalation devices among patients with bronchial asthma. A hospital-based cross-sectional study in Rio de Janeiro, Brazil.

Treatment of asthma implies inhalation of specific drugs to reach high concentrations in the respiratory tree and ensure low drug bioavailability and few adverse effects. This study aimed to evaluate the effectiveness of the inhalation technique among outpatients with asthma. Tertiary-care hospital-based cross-sectional study in Rio de Janeiro. We evaluated inhalation practices in a convenience sample. A questionnaire was used to investigate sociodemographic data and assess disease control level, duration of use of the inhalation device, length of treatment and previous instructions provided by the prescribing physician. Patients demonstrated their inhalation technique using empty devices, and their technique was considered correct when all steps were appropriately performed or when errors did not interfere with the treatment outcome. Among the 71 participants, 53 (74.7%) had been using the same inhaler device for at least two years and 41 (57.8%) had been under treatment for two years or more. Twelve (17.1%) said that they had been taught once and 57 (81.4%) at least twice, while one (1.4%) reported not having received any guidance regarding use of inhaler devices. Eighteen patients (25.3%) presented controlled asthma and 28 (39.5%) performed the inhalation technique correctly. Incorrect technique was associated with fewer evaluations of the inhalation technique (P =0.04) and uncontrolled asthma (P = 0.01). Less than half of the sample performed the inhalation technique correctly. Incorrect inhalation technique was related to lower number of evaluations of the use of the inhalation device and uncontrolled asthma.

The Effects of Extensive Reading on English Vocabulary Learning: A Meta-analysis

Extensive reading has been continuously studied as a promising instructional method for improving students’ language proficiency, including reading proficiency, vocabulary acquisition, and grammar awareness. The present study is a meta–analysis, which synthesized the data of 21 empirical studies (N = 1268). It was designed to explore whether extensive reading instruction was effective in improving students’ vocabulary acquisition, and if so, how the effectiveness varied in terms of the instruction length and teaching methods. Stata 14.0 was utilized to calculate the collected data. The results revealed that: (1) extensive reading has a significant effect on English vocabulary learning; (2) one semester (less than three months) is the most appropriate length of extensive reading instruction for vocabulary learning; (3) Graded Readers, comprehension questions and vocabulary exercise play significant roles as reading materials and education methods in promoting the vocabulary learning of EFL learners.

The effect of out-of-class exposure to English language media on learners’ vocabulary knowledge

Abstract The aim of this study is to investigate (1) how often Flemish English-as-a-foreign language learners are exposed to English language media outside of the classroom, (2) whether current out-of-class exposure to English language media is related to learners’ vocabulary knowledge, and (3) whether length of instruction (three or six years), gender, and out-of-class exposure to English language media affect Flemish learners’ vocabulary. Data were collected with 79 English-as-a-foreign language learners. They were administered a frequency-based vocabulary test and a questionnaire. The findings of this study show that Flemish English-as-a-foreign language learners are frequently exposed to English language media. The results also indicate a positive relationship between learners’ vocabulary knowledge and exposure to non-subtitled TV programs and movies, the Internet, and written print (books, magazines). Finally, both length of instruction and current out-of-class exposure to English language media had an effect on learners’ vocabulary knowledge, but out-of-class exposure had a larger effect than length of instruction.

Variable Length Instruction Compression on Transport Triggered Architectures

The memories used for embedded microprocessor devices consume a large portion of the system’s power. The power dissipation of the instruction memory can be reduced by using code compression methods, which may require the use of variable length instruction formats in the processor. The power-efficient design of variable length instruction fetch and decode is challenging for static multiple-issue processors, which aim for low power consumption on embedded platforms. The memory-side power savings using compression are easily lost on inefficient fetch unit design. We propose an implementation for instruction template-based compression and two instruction fetch alternatives for variable length instruction encoding on transport triggered architecture, a static multiple-issue exposed data path architecture. With applications from the CHStone benchmark suite, the compression approach reaches an average compression ratio of 44% at best. We show that the variable length fetch designs reduce the number of memory accesses and often allow the use of a smaller memory component. The proposed compression scheme reduced the energy consumption of synthesized benchmark processors by 15% and area by 33% on average.

The paradoxical effect of long instructions on negative affect and performance: When, for whom and why do they backfire?

For reasons of bureaucracy and safety, astronauts on the International Space Station are provided with excruciatingly detailed instructions and a lack of decision-making power, even for simple routine tasks. Besides being time-consuming, many astronauts report feelings of demotivation, irritation, and even defiance when confronted with this working method. Anecdotic evidence suggests that this method leads to situations where astronauts read instructions diagonally or avoid checking in with mission support, thereby ironically increasing the risk of error making. There is a need to consider under which circumstances, for whom, and why the provision of long instructions could be detrimental for well-being and performance. An experimental study with LEGO assembly tasks examined whether length of instructions (i.e. short versus long) and task complexity (simple vs. complex) impact negative affect, motivational experiences and performance of participants (N = 113, Mage = 18.75 ± 2.46 years). Long instructions for simple tasks provoked greater feelings of irritation, diminished the perceived value of instructions, and negatively influenced productivity and accuracy. The negative effect of long instructions on irritation was explained via decreased perceived value. Additionally, the effect of length of instructions on irritation differed for participants high versus those low in need for achievement.

The platform shapes the message: How website design affects abstraction and valence of online consumer reviews

Online consumer reviews provide relevant information about products and services for consumers. In today's networked age, the online consumer review platform market is hyper-competitive. These platforms can easily change different design characteristics to get more reviewers and to nudge reviewers to deliver higher quality reviews. This study explored the relation between online consumer review platforms' design characteristics and the reviewers' construal level. A psycholinguistic coding scheme was used to assess which social and physical design characteristics impact the language abstraction in accompanying online consumer reviews. To this end, we content analyzed reviews of services and products posted on eight different online consumer review platforms (N=400). This resulted in a number of key design characteristics (e.g., reviewer identification, reviewer status, order of instructions and length instructions) that led to a decrease in language abstraction used in online consumer reviews. Moreover, results showed that language abstraction mediated the relationship between the four design characteristics and valence. The findings and their broader theoretical, methodological and practical implications are discussed. Online consumer review platforms could capitalize on our findings in adaptive design choices.

AN ENHANCED TASK ALLOCATION STRATEGY IN CLOUD ENVIRONMENT

Cloud computing is a vigorous technology by which a user can get software, application, operating system and hardware as a service without actually possessing it and paying only according to the usage. Cloud Computing is a hot topic of research for the researchers these days. With the rapid growth of Interne technology cloud computing have become main source of computing for small as well big IT companies. In the cloud computing milieu the cloud data centers and the users of the cloud-computing are globally situated, therefore it is a big challenge for cloud data centers to efficiently handle the requests which are coming from millions of users and service them in an efficient manner. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.

Floating accumulator architecture

Although technology advancement can pack more and more physical registers in processors, the numbers of architectural registers defined by the instruction set architectures (ISAs) remain relatively small on most modern processors. Exposing more architectural registers to compilers and programmers can improve the effectiveness of compiler optimization and the quality of code. However, increasing the number of architectural registers by simply adding extra bits to the register fields of instructions will expand the code size. Therefore, a better way of exposing more ISA registers without significantly expanding the code size is needed. This paper presents a new ISA called Floating Accumulator Architecture (FAA) that can expand the number of ISA registers without increasing the instruction length. Unlike the accumulator architecture whose accumulator is a fixed, special register, FAA dynamically chooses a register from the general-purpose register file as the accumulator. In other words, the accumulator in FAA is an alias to some register in the register file at any instruction, and the alias relation can be dynamically updated by FAA at any program points. Since the accumulator implicitly stores the result, the destination register field can be omitted from FAA instructions, resulting in a saving of 3 to 5 bits for each instruction. This new free instruction bit space can be utilized in two possible ways: doubling the number of ISA registers of modern 32-bit RISC processors or maintaining the number of ISA registers for 16-bit instructions on embedded processors. This paper presents the result of utilizing the free bit space to double the number of ISA registers from 16 to 32 on ARM processors, and experimental results show that performance can be improved by 7.6% on average for MediaBench benchmarks.

On Static Binary Translation of ARM/Thumb Mixed ISA Binaries

Code discovery has been a main challenge for static binary translation, especially when the source instruction set architecture has variable-length instructions, such as the x86 architectures. Due to embedded data such as PC (program counter)-relative data, jump tables, or paddings in the code section, a binary translator may be misled to translate data as instructions. For variable-length instructions, once a piece of data is mis-translated as instructions, decoding subsequent bytes could also go wrong. We are concerned with static binary translation for the very popular Advanced RISC Machine (ARM) architectures. Although ARM is considered a reduced instruction set computer architecture, it does allow the mix of 32-bit (ARM) instructions and 16-bit (Thumb) instructions in the same executables. In addition to different instruction lengths, the ARM and Thumb instructions are located at 4-byte or 2-byte aligned addresses, respectively. Furthermore, because ARM and Thumb instructions share the same encoding space, a 4-byte word could sometimes be decoded as one ARM instruction or two Thumb instructions. The correct decoding of this 4-byte word is actually determined at runtime by the least-significant bit of the program counter. For unstripped binaries, the mapping symbols can be used to identify ARM code regions and Thumb code regions. However, for stripped binaries, such mapping symbols are unavailable. We propose a novel solution to statically translate stripped ARM/Thumb mixed executables. Our solution is implemented in a static binary translator. The binary translator further generates multiple versions of translated code for the code regions whose types cannot be determined with our solution. One of the code versions is selected during runtime. The binary translator also includes a series of analyses that enable the removal of most useless code versions. Based on the experimental results on stripped ARM/Thumb mixed binaries in the SPEC2006 and Embedded Microprocessor Benchmark Consortium (EEMBC) benchmark suites, our static binary translator achieves impressive performance when migrating them to run on x86 machines and the space overhead is no more than 10%.

Study on Anti-collision Algorithm in Underground Mine Personnel Positioning System

In order to avoid signal collision occurs when more than one electronic tag send the recognition information to the reader in underground mine personnel positioning system, an improved binary searching algorithm is proposed in this paper. The improved algorithm can reduce redundant information and searching times by using dynamic and variable querying instruction length and regressive strategy. The simulation results show that this algorithm is superior to other algorithms in searching times, searching time and throughput. It can effectively solve the anticollision problem of multi-object identification.

A NOVEL APPROACH OF OPTIMIZING PERFORMANCE USING K-MEANS CLUSTERING IN CLOUD COMPUTING

Cloud computing is distributed computing, storing, sharing and accessing data over the Internet. It provides a pool of shared resources to the users available on the basis of pay as you go service that means users pay only for those services which are used by him according to their access times. Load balancing ensures that no single node will be overloaded and used to distribute workload among multiple nodes. It helps to improve system performance and proper utilization of resources. We propose an improved load balancing algorithm for job scheduling in the cloud environment using K-Means clustering of cloudlets and virtual machines in the cloud environment. All the cloudlets given by the user are divided into 3 clusters depending upon client’s priority, cost and instruction length of the cloudlet. The virtual machines inside the datacenter hosts are also grouped into multiple clusters depending upon virtual machine capacity in terms of processor, memory, and bandwidth. Sorting is applied at both the ends to reduce the latency. Multiple number of experiments have been conducted by taking different configurations of cloudlets and virtual machine. Various parameters like waiting time, execution time, turnaround time and the usage cost have been computed inside the cloudsim environment to demonstrate the results. Compared with the other job scheduling algorithms, the improved load balancing algorithm can outperform them according to the experimental results.Â

POWER SAVING LOAD BALANCING STRATEGY USING DVFS IN CLOUD ENVIRONMENT

Cloud Computing is a technology that provides a platform for the sharing of resources such as software, infrastructure, application and other information. Cloud Computing is being used widely all over the world by many IT companies as it provides benefits to the users like cost saving and ease of use. However with the growing demands of users for computing services, cloud providers are encouraged to deploy large datacenters which consume very high amount of energy resulting in carbon dioxide emissions. Power consumption is a key concern in data centers. That type of critical issues not only reduces the profit margin, but also has effect on high carbon production which is harmful for environment and living organisms. Reducing power consumption has been an important requirement for cloud resource providers not only to reduce operating costs, but also to improve system reliability. In research work, we have arranged the virtual machines in ascending order of the load. Cloudlets would be assigned to that virtual machine that has lesser load. Cloudlets are divided into three categories like high, medium and low on the basis of their instruction length. Dvfs approach which has been implemented in the paper would scale the power according to the length of the cloudlets. Three modes of Dvfs have been implemented in the research work. Various parameters like processing time, processing cost and total power consumed by all the cloudlets at the data center have been computed and analyzed. Cloudsim a toolkit for modeling and simulation of cloud computing environment has been used to implement and demonstrate the experimental results.

Elementary English education in Indonesia: Policy developments, current practices, and future prospects

With a current figure reaching more than 26 million (Kementrian, 2015), Indonesia is second after China in terms of the number of children learning English as a foreign language in elementary schools. This paper examines the development of elementary English education in Indonesia, and shows that it has been undergoing a great transformation in recent years. The paper begins by providing an overview of policy developments relating to elementary English education in the country. It then discusses current practices in elementary English education in relevant areas, focusing in particular on classroom size and length of instruction, the role and status of teachers, and pedagogical concerns. Finally, the paper analyzes the prospects for elementary English education in the foreseeable future.